Real Analysis vs Advanced Calculus vs Numerical Analysis [education]

Hi all,

I’m a rising junior double majoring in mathematical economics and data science. For my degree, I’m supposed to take one of these course sequences: real analysis 1 and 2, advanced calculus 1 and 2, and numerical analysis 1 and 2. I’m not sure if I want to do a PhD in the future or not, but I do know that I would like to go into the statistics field (I love causal inference/econometrics). I’ll be starting statistics research this fall, so that should help me decide I think, but I have to decide on a course sequence before then. Based on that, would you be able to recommend which course sequence I should take. Here are the course descriptions:

  1. real analysis 1: Real and complex number systems, completeness. Sequences and series and their limits. Continuity of real and complex functions. Derivative. Analytic functions. Power series.

Real analysis 2: The Riemann-Stiltjes integral. Cauchy integral theorem. Cauchy integral formula and its consequences. The calculus of residues.

  1. Advanced calculus 1: This is a first semester course in real analysis. Topics include the real number system and the completeness property, sequences and their limits, limits of real-valued functions and continuity and point-set topology of Euclidean spaces.

Advanced calculus 2: This is a second semester course in real analysis. Topics include the derivative and differentiable functions, the Riemann integral, infinite series and convergence tests, power and Taylor series and operations with them, and topics from calculus of several variables.

  1. numerical analysis 1: Computer arithmetic, pitfalls of computation, iterative methods for the solution of a single nonlinear equation, interpolation, least squares, numerical differentiation, numerical integration, and solutions of linear systems by direct and iterative methods.

Numerical analysis 2: Solution of systems of nonlinear equations, solution of initial value problems, matrix norms and the analysis of iterative solutions, numerical solution of boundary value problems and partial differential equations, and introduction to the finite element method.

Thank you!

👍︎ 6
📰︎ r/statistics
💬︎
👤︎ u/sk81k
📅︎ Aug 21 2020
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ANOVA ERROR MESSAGE: Warning messages: 1: In model.response(mf, "numeric") : using type = "numeric" with a factor response will be ignored 2: In Ops.factor(y, z$residuals) : ‘-’ not meaningful for factor .

I tries conducting an ANOVA analysis of this data using

TAT <- aov(subline~age.days, data = Aphids)

However, I always get this message

Warning messages: 1: In model.response(mf, "numeric") : using type = "numeric" with a factor response will be ignored 2: In Ops.factor(y, z$residuals) : ‘-’ not meaningful for factor .

Could someone tell me whether they get the same and if not where I went wrong?

DATA: https://2018.qmplus.qmul.ac.uk/pluginfile.php/1295985/mod_resource/content/1/Aphid_longevity_A06_405.txt

or

subline age.days

H323 22

none 27

H9 20

H402 26

H30 21

H76 34

HAf6 29

H323 14

H30 25

HAf6 27

H402 27

H9 25

H76 37

none 46

HAf6 26

H30 20

H323 20

H76 32

H9 25

H402 14

none 43

none 11

H402 25

HAf6 32

H323 23

H30 28

H9 26

HAf6 25

H323 24

H402 21

none 38

H9 21

H30 27

H76 36

H76 31

H9 28

HAf6 27

H30 7

none 25

H323 16

H402 25

HAf6 20

H76 12

H402 17

none 34

H9 28

H30 21

H323 12

H402 26

H323 20

H76 33

none 34

HAf6 6

H9 22

H30 26

Thank you in advance.

👍︎ 2
📰︎ r/RStudio
💬︎
👤︎ u/Cydonk
📅︎ Feb 06 2021
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The Definitive Vex Mythoclast Analysis: Examining over a million player records to model VoG drops

Edit: There seems to be some confusion about this post. I’m not complaining about drop rates. I’m actually an amateur player and have no interest in obtaining Vex, I just wanted to contribute to the interesting analysis work that was presented by other users in the community. If anything I think it's cool that Exotic means Exotic. This is presented purely as a just-for-fun project to help keep my data skills sharp.

TL;DR/Disclaimer/FAQ:

  • Q: This is too long - what's the result?
    • A: We predict a Vex drop rate of 4.29%, with a caveat that we are likely under-reporting for two false negative cases:
      • Private player inventories (which return as negatives even if the player owns Vex)
      • Unlootable clears (which are presumably mixed into the total VoG clears data)
    • Therefore we suspect our model tends to shoot low, and that the drop rate is likely 5%.
  • Q: Why did you prediction change from yesterday to today?
    • A: My original post was estimating 4.15%. This was adjusted slightly because I realized destiny-worker-6 (in my Docker cluster) took a lot longer to exit than the rest of my cluster, so I was only using a portion of its output data. Not sure why this happened.
    • This is also why there was a slight data gap in the range of 60 or so clears (which would have been very obvious if I'd been paying attention to the response volume density chart). Remodeling with the missing chunk from destiny-worker-6 resulted in a more inclusive estimation of 4.23%, but we still conclude that it's likely 5%.
  • Q: I can't read your code in Reddit and it looks like there's graphics missing?
  • Q: Did you account for looted clears?
    • A: No, we didn't account for looted clears. This is because I've simply never played a raid and didn't know this was a mechanic. I'll revisit this on the next round as many have proposed methods for identifying whether a clear is 'looted' during the initial raid data scraping.
    • However, it's worth pointing out that our model is weighted by response volume for each # of VoG completions. So while extreme outliers do affect our model's tail-end, they are not as influential near the origin (where we expect our model to be most accurate due to the heteroskedacity of our data coll
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📅︎ Sep 26 2021
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Globally Optimal Solutions for Space Elevator Stage 4 & Maximizing AWESOME Points Production

Fellow pioneers,

did you ever wonder which recipe usage is the best to complete Space Elevator stage 4 as quickly as possible, or to produce as many AWESOME points per minute as possible? Today, you'll have to wonder no longer!

Goal Formulation & Assumptions

Let's call the problem of minimizing time to complete Space Elevator stage 4 SE4, and that of maximizing points per minute PTS. In each problem, we are looking for a recipe allocation (that is, a mapping from every available recipe to the number of buildings simultaneously conducting this recipe at a certain clock speed) which optimizes the respective goal function while satisfying a set of conditions.

Recipes in this sense includes some "pseudo recipes" like sinking a belt's worth of input of each sinkable item type, consuming an item type in a power building, and extracting a resource via a certain building at a certain clock speed. For SE4 it also includes the space elevator stage as a pseudo recipe, which takes the required items at their exact ratios as input and has no output.

The conditions we impose are as follows:

  • the number of resource nodes and wells extracted from of each resource and purity must not exceed the map limit, i.e. the number of such nodes and wells available in the game world.
  • total power consumption must not exceed total power production (vice versa is fine). Production includes average power output of geothermal generators on all geysirs on the map (as of time of this writing: 3 impure, 9 normal, 6 pure).
  • for all types of items, the production rate must exactly match the consumption rate. This implies that no unsinkable items must be produced, and no unproducable items must be consumed.
  • for all unlimited buildings (those not tied to nodes or wells), clock speed is fixed at 100%. Underclocking improves power efficiency - if we allow it, all unlimited buildings will be clocked at the minimum allowed clock speed (e.g. 1%) and one would have to build 100x as many of them. Could be lowered, but let's start with 100% for now, which implies the most compact building realization that doesn't require excessive amounts of power shards.
  • for all limited buildings, clock speeds from 1% to the lower between 250% and the speed that saturates the output belts or pipes are allowed.

If there are ties between feasible recipe allocations with regard to the optimization goal, an allocation that minimizes the amount of buildings to be built is preferred.

Solution Methods

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👤︎ u/MarioVX
📅︎ Nov 26 2021
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A somewhat academic analysis of Enderal's real-life religious references

Hi there,

After 100 hours my Dark Keeper has finished his journey in Enderal. Upon my time spent with this game, numerous quests, dialogues and enviroments have resonated deeply within me. I enjoyed very much the setting's originality, it's very well executed mixture of motifs, myths and stories came together to make one of the best cRPG experiences I ever had. To be frank, there were times where my enthusiasm fired up as if I was playing a fully fledged TES game (if not more).

I heard many rumours before playing Enderal about the way this game critizes and puts into focus "religion" as a concept. But from my point of view, I felt quite an opposite: criticism isn't bad, and it largely leads to some better understandings of what a phenomena is or isn't - either via negation, either via countersignals. While gloomy at times, I think Enderal is one of the best attempts at discussing, representing and challenging religious topics in any games ever, period. It may be bleak and pessimistic, but that doesn't mean it doesn't have juice. Quite the contrary.

Outside of my Dark Keeper activities such as bashing inn doors, tomb raiding and soul-eating, I am an (IRL) academic researcher in Religious History, studying from a philological standpoint various texts and traditions. My specialization is on Coptic (Late Egyptian) sources, thus I am fairly aquianted with Gnosticism, Early Christianity and many strange cults that floated around the year 0.

From this point of view I have composed some scans about various moments and aspects of Enderal and of it's story/setting, so that people interested in "lore-picking" can reflect on the vast body of real-life historical references Enderal makes. As with TES, I believe that the analogy between complex fantasy lore and real-life lore enriches both sides of the story, increasing appreciation and inner learnings.

Reading notes:

A. Please do not take what is here as more than a personal, if somewhat "educated" speculation. The authors and developers of Enderal may have had motifs/intentions other that those reflected here; At times, they may have intentionally referenced some real-life concepts, otherwise not. I am not here to imply, just to reflect upon.

B. It goes without saying that all that is below is FULL OF SPOILERS. In this quest to valorize Enderal, we are going to spoil it a lot, (similar to how [Tealor tried to save the world by assuring it's almost destruction](https://i.kym-cdn.com/photos/

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👍︎ 84
📰︎ r/enderal
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📅︎ Dec 11 2021
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Once Upon A Time, the SEC Held a Securities Lending and Short Sale Roundtable During the Global Financial Crisis, and Here’s What Happened – Full Transcript Included

Preface

So, I went down a pretty big rabbit hole while casually researching the economic collapse of 2008 and who the winners and losers were, and I thought there were some pretty significant things here that reinforce what we’ve been theorizing, researching, and advocating against since January. What’s happening now, as we well know now, is simply a sequel to Part I of the saga in abusive securities lending practices and naked short selling. After the House of Cards collapsed the first time, the SEC held a roundtable discussion – consisting of two panels – on securities lending and short sales with financial industry experts to attempt to put a stop to the colossal fuckery after Lehman Brothers filed for bankruptcy. Let me back up here for a second.

On September 15, 2008, Lehman Brothers Holdings Inc. filed for chapter 11 protection in New York. This constituted the largest bankruptcy filing in U.S. history, with Lehman holding nearly $700 billion in assets. At the time of the bankruptcy filings, Lehman was the fourth-largest investment bank in the U.S. They were faced with unprecedented losses in 2008 due to the subprime-mortgage crisis, and it was at that time Timothy F. Geithner, the president of the Federal Reserve Bank of New York, called a meeting on September 12, 2008, to discuss Lehman's future, including the possibility of an emergency liquidation.

On the day that Lehman filed for bankruptcy, sometimes referred to as "Ugly Monday," the Dow Jones Industrial Average closed down just over 500 points, resulting in the SEC's “prohibition” of naked short selling and a three-week temporary ban on all short selling of financial stocks.

But how did the SEC get to that point? On Wednesday, September 30, 2009, the SEC held a roundtable on securities lending and short sales at their headquarters in Washington, D.C. Two panel discussions were held during a morning session and an afternoon session. Below, I’ve abbreviated sections of the full transcript of the first panel session for easier reading. Feel free to check out the full transcript if you’re curious, but for the sake of character limits, I’ve only included the most salac

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📰︎ r/Superstonk
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📅︎ Aug 04 2021
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Move over Bloomberg Terminal, here comes Gamestonk Terminal

https://github.com/DidierRLopes/GamestonkTerminal

Hey all,

2 months ago I made a terminal that I had been working on my spare time, to help me on my stock research, open-source. See https://dro-lopes.medium.com/gamestonk-terminal-the-next-best-thing-after-bloomberg-terminal-a263c001a61f

**The motto:**Gamestonk Terminal provides a modern Python-based integrated environment for investment research, that allows the average joe retail trader to leverage state-of-the-art Data Science and Machine Learning technologies. As a modern Python-based environment, Gamestonk Terminal opens access to numerous Python data libraries in Data Science (Pandas, Numpy, Scipy, Jupyter), Machine Learning (Pytorch, Tensorflow, Sklearn, Flair), and Data Acquisition (Beautiful Soup, and numerous third-party APIs).

As of today, and thanks to all your help and the traction created around it, the terminal is looking better than ever. Now it's no longer only me taking care of the repo, but also 2 other experienced devs (thanks u/hbar340), who are adding features on a daily basis and increasing the robustness of the codebase. Feel free to wander through the FEATURES page to see what you would get out of this tool!

If some of you thought it was amazing 2 months ago, you won't believe what it looks like now. You can check out the ROADMAP for all the features that have been added since, but let me list some of them:

  • New Screener for stocks, which allows users to save their presets and share them
  • New Options menu
  • New Comparison Analysis to compare several tickers in their historical price, sentiment, or fundamental analysis
  • New Portfolio Optimisation that assigns stocks weights based on risk level specified by the user
  • New Exploratory Data Analysis menu that looks at historical data from a statistic point of view
  • New Residual Analysis after using a statistical model for prediction
  • New menu to provide access to your portfolio (supports Robinhood, Ally invest, Alpaca, and Degiro)
  • New Cryptocurrency, Forex, and FRED menus
  • Prediction with backtesting
  • Technical analysis that includes a score and a summary
  • Due Diligence menu with data from Dark Pools, and also Failure to Deliver
  • Sentiment analysis from news provided from collaboration with a company that provides this feature pa
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📰︎ r/Superstonk
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👤︎ u/SexyYear
📅︎ Apr 23 2021
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Peggy Carr, 41-years-old. Florida woman falls victim to a mysterious illness after drinking from a bottle of soda. Soon, her children are sick and dying as well. The investigation reveals an "evil genius" who sought to terrorize his neighbors and murder an entire family by means of poison.

Part 1: Chemical Warfare

In 1988, a 41-year-old woman named Peggy Carr was working her job as a waitress at a restaurant when suddenly she felt a strange pain. It was like nothing she’d ever felt before in her entire life. She thought she was having a heart attack. She told her manager that she had to leave early, she was feeling a weird pain in her chest. "My hands feel so numb," she said. "And my legs are just hurting so bad."

Peggy’s daughter, Cissy, worked with her at the same restaurant, and she drove her mother home. By the time she got home, the pain was excruciating; Peggy felt like her entire body was on fire. Her husband, Pye Carr, told her that her legs probably just hurt from standing up all day.

But Peggy knew that wasn't it. She'd worked long hours at the restaurant on plenty of other days, and she'd definitely come home with sore legs before, but this was something completely different. She felt like she was going to explode. Her children, of which she had several, could tell that something was terribly wrong and urged Pye to help her. Eventually, Pye gave in and drove Peggy to the nearest hospital.

Peggy Carr, with her children: Allen, Cissy and Duane

The doctors in the emergency room were baffled. This was like nothing they’d ever seen before. They decided that her symptoms were psychosomatic, since they didn’t seem to correspond with any known disease or ailment. It was all in her head, she was just stressed out and needed some rest, that's all. Peggy balked at this explanation; she was in more pain than she’d ever been in her entire life. “I know it’s not in my head,” Peggy said, “this is real.”

But a few days' rest did seem to solve the problem, at least at first. After 3 days at the hospital Peggy’s condition improved enough that she was able to go home. Maybe it had just been stress after all.

Most of the family believed that Peggy had just gotten some sort of weird stomach virus, and so they were giving her bottles of Coca Cola to help settle her stomach. These were old-style bottles, with crimped caps instead of a screw-on lid. Peggy drank the bottles without any thought. Only later would anyone recognize how odd it was that there was an 8-pack of Coke bottles in the Carr house; the family usually drank Pepsi.

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👍︎ 1k
📰︎ r/TrueCrime
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📅︎ Jun 29 2021
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Judges

I might have been influenced by a particular pair of movies that may share a similar title ;)

Hope you enjoy.

~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

Judges

“I’m tired of this shit Fred. Yeah we’re a violent species, I get that. Our history hasn’t once had a period where conflict didn’t exist. But come on. We’ve progressed beyond that shit now. Hell man, we’ve become the main peacekeepers of our arm of the galaxy. You’d think the looks and whispered insults would stop.” I barely held back the disappointment in my voice as I talked to my brother back home on Earth.

“Well you are Judges, and no one likes the law on a good day, let alone any day. Just hang in there little bro. You have another year or so left on your contract before you can call it quits and come back here to relax. Keep it together and when you get back, I’ll make sure the only thing on your mind is booze, tits, and good times.”

Leave it to family to make you feel somewhat better, even if it’s just joking. “I’ll try bro, I’ll try.” I hear a loud knocking on the door behind me. “Well shit, time’s up. I’ll call you again when I get a chance. Tell everyone I love them and I’ll be home before they know it.”

“Will do, Dick. Be safe.” he ends the call with a smile. He knows I hate that nickname, but apparently it comes with being named Richard. Either way I get up and open the door to my sergeant looking quite distressed.

“We got an issue on OD-336. Seems that some diplomats have had a...disagreement of sorts in the past and wanted to reconcile on neutral grounds. We’ve been called in to make sure their reconciliation is fair and according to law..”

“Think they won’t do it peacefully?”

“Most likely. Luckily they separated the ones who instigated the fight and agreed to meet again when heads cooled down. Apparently 6 months wasn’t long enough as they nearly went at it as soon as they saw each other.”

“Fuck me.” I kept up with the sergeant’s pace while others around us quickly cleared the passageway to let us through. Two Judges walking with purpose is never a good image. “What can we expect if they act up again?”

“Laser or plasma. Maybe some kinetic weapons, possibly small explosives. Best to get suited up with a personal shield, energy-rated combat suit, and melee weapons. Non-lethal preferably, even if they are politicians.”

Yeah, he still hates anything political. “It’s been two years sarge.” I say dejectedly. “You found yourself an hone

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👍︎ 208
📰︎ r/HFY
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📅︎ Sep 07 2021
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The ultimate blueprint to getting a job in data science

EDIT: I’m on discord to answer your questions: https://discord.gg/raQ5NjHy

It’s pretty late in the UK (11.30pm, but I’ll stay up as long as you guys want me to)

Organisation is Key

I’ve interviewed at Google (and DeepMind), Uber, Facebook, Amazon for roles that lie under the “Data Scientist” umbrella and this is the typical interview construction theme I’ve observed:

Software Engineering Applied Statistics Machine Learning Data Wrangling, Manipulation and Visualisation

Now nobody is expecting some super graduate level competency in all of these topics, but you need to know enough to convince your interviewer that you’re capable of delivering if they offered you the job. How much you need to know depends on the job spec, but in this increasingly competitive market, no knowledge is lost.

I recommend using Notion to organise your job prep. It’s extremely versatile, and enables you to utilise the Spaced Repetition and Active Recall principles to nail down learning and deploying key topics that come up time and time again in a Data Scientist interview. Ali Abdaal has a great tutorial on note taking with Notion to maximise your learning potential during the interview process.

I used to run through my Notion notes over and over, but in particular, right before my interview. This ensured that key topics and definitions were loaded into my working memory and I didn’t waste precious time “ummmmmm”ing when hit with some question.

  1. Software Engineering Not all Data Scientist roles will grill you on the time complexity of an algorithm, but all of these roles will expect you to write code. Data Science isn’t one job, but a collection of jobs that attracts talent from a variety of industries, including the software engineering world. As such you’re competing with guys that know the ins and outs of writing efficient code and I would recommend spending at least 1–2 hours a day in the lead-up to your interview practicing the following concepts:

Arrays Hash Tables Linked Lists Two-Pointer based algorithms String algorithms (interviewers LOVE these) Binary Search Divide and Conquer Algorithms Sorting Algorithms Dynamic Programming Recursion

DO NOT LEARN THE ALGORITHMS OFF BY HEART. This approach is useless, because the interviewer can question you on any variation of the algorithm and you will be lost. Instead learn the strategy behind how each algorithm works. Learn what computational and spatial complexity are, and learn why they are so fundamental to building

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📅︎ Feb 02 2021
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A GME Saga: The Battle at Helm's Deep

First, I'm not a financial advisor and all of this is a combination of opinion research articles and a great deal of research by others.

​

Helm's Deep: The Derivatives Market

​

So, one may be wondering especially since the recent quarterly losses were released how does a hedge fund remain Liquid this long and continue to have the leverage required to short the stock? (Spoofing is also happening).

​

Liquidity in Select Futures Markets (cftc.gov)

​

Recent diminishing liquidity

Thus far, we have seen an obvious need to additional liquidity for hedge funds, typically in the form of cash. But where would one get this cash and who would be give it to these hedgies. Well, it is the large commercial banks of course! The banks foresee the future and are playing the long game, they know Inflation is coming... Meanwhile the Fed has backed Treasury bonds! So, what the hedgies have done is actually outright buy treasury bonds and exchange them in a Swap through the Repo Market to gain additional liquidity. Of course banks get interest on that!. Hedge funds have been Re-hypothicating these treasury bills between one another and exchanging them for liquidity in a never ending loop to banks. At some point this strategy will run dry.

​

Visual Explanation of Repo Market

​

​

​

Chart courtesy of u/jsmar18

Amazing DD about Michael Burry's last post

​

​

​

Second, another strategy that's being used is the OTM options strategy or Doom Options as revealed by Dookie Dimez (Twitch). The credit risk is of significant importance in the current financial market. For instance, unlike most financial institutions whose long-run performance is affected by the tail-risk induced extreme negative retu

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👍︎ 3k
📰︎ r/Superstonk
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👤︎ u/Turdfurg23
📅︎ Apr 10 2021
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99.9% of the Universe Chapter 56

Next

The Preserver and Sam walked in their protective suits on the outer shell of Twain. Several thousand peoples inside were watching on monitors, body displays, and from the atrium. Orbit watched via the multitude of box spiders already distributed in the area.

The two slowly walked up to the twisting structure rising out from the alloyed hull. Sam put his hand out and touched the hexagonal checkered wall. He rubbed its surface, and a light dust flicked off, only to be drawn back into place. "That's weird. How's it doing that?"

The Preserver focused on him. "Unknown. Capture a sample for analysis. You have bottles on you."

Sam breathed slowly out his nose into his helmet. "Yes, good idea Mr. Preserver. I will take a sample."

Sam brushed of more of the dust and caught it in the bottle before it could be drawn back into place. The dust tried to climb out of the bottle until he put on the lid, and then it went still. "That's some weird shit."

The Preserver refocused all three eyes on the Star Angels' nest. There were several large openings, and he started toward the nearest one. Sam followed his lead.

They slowly and deliberately walked forward, each step planned so as to not accidently fling themselves out into the void. They neared the slip shaped opening, and the Preserver paused, putting up two of his hands to stop Sam.

Sam stopped, looking at the opening. A glowing tendril extended out, followed by the glowing outer sheath of an Angel. Sam watched as it flowed out from the hole, and into space. "You get all that Orbit?"

"Yes sir. Did you see the central core of the creature?"

"Yes. A big lump of something, and some organs. I don't know. It looked like light pulses were coming out of it."

"Exactly sir. The energy recordings I have taken show they are generating huge sums of power, and use it quite efficiently."

"They are power plants then?" Sam asked.

"Some sort of fusion is happening inside of them. Yes sir."

Sam looked at the Preserver. "How is that possible without them detonating? They're animals right or are they some sort of machine AI things?"

The Preserver focused one eye on Sam, the other two at the opening. "We will be inside in a moment. We both have bottles, we will get samples and find out Sam."

"Sir, they speak to one another on sheath frequencies. It is all crude, basic communications. Feel

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👤︎ u/TheCJK
📅︎ Jun 19 2021
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Setting the X axis in numerical order when plotting residuals for a multiple regression[Excel 2007]

I am performing some analysis on a linear multiple regression. I have been tasked with the following:

"Using the residuals or unexplained portions of the reading scores (dependent variable) from this regression equation (7.53 + .416 Socioeconomic Status + .236 Teacher Education + .311 Teacher Experience + 1.58 Verbal Score + .033 library services), plot the residual against the reading score for each school. Do you observe any pattern?"

My instinct has been to do the following:

Data-> Data Analysis -> Regression -> fill in the proper inputs ->line fit plots

This gives me charts depicting residuals for each independent variable. My questions are:

  1. Am I going about answering this question sensibly?
  2. Is there a way that I can reorganize these residual charts so that the X axis appears in numerical order? Right now it's plotting them in the order in which they appeared originally in the data, but it is very difficult to observe whether there are any patterns without the X axis being in numerical order. Note that I cannot set the original data to be in numerical order, as there are several independent variables.

Thank you!

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📰︎ r/excel
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📅︎ Mar 27 2015
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I want to study some subjects I'm gonna have in the next semester in advance. Could you recommend some good resources I could use (books, video playlists, etc)?

Those are the subjects I'm going to have (with their syllabuses to give you a better idea on what we're going to have):

#Real and Complex Analysis

> 1. algebra and σ-algebra of sets. Measurable spaces. Measure, spaces with measure. Borel measure. Complete and regular measures. > 2. External measure. The problem of measure expansion. Caratheodory's condition. Constructions of Lebesgue measure. Characterization of measurable sets in the Lebesgue sense. > 3. Measurable functions. The space of simple functions. Theorem on approximation of measurable function by simple functions. > 4. Lebesgue integral and its properties. Relation of the Lebesgue integral to the Riemann integral. A theorem of convergence. Fatou's lemma. Lebesgue's convergence theorems. > 5. Productive measures. Tonelli's and Fubini's theorems. > 6. Functions with bounded variation. Absolutely continuous functions. Lebesgue's theorem of differentiability almost everywhere. > 7. Geometry and topology of the complex plane, Riemann sphere. Composite functions, continuity, elementary functions. > 8. Differentiation in the complex domain. Rules of differentiation. Cauchy-Riemann equations. Geometric interpretation of the complex derivative. > 9. Analytic functions (regular, holomorphic). Regularity of elementary functions. Conformal representation. > 10. Integration of complex functions. Curvilinear integrals of complex functions. > 11. Cauchy's integral theorem. Existence of a prime function. Cauchy's integral formula. Generalized Cauchy's formula. > 12. Expandability of an analytic function into a power series. Taylor and Laurant series. Zero points of an analytic function. Uniqueness theorem of analytic function. > 13. Cauchy's inequality. Integer functions. Liouville's theorem. Schwarz's lemma. > 14. Singular points. Residuum of a function. Determination of residues. Theorem on residues.

#Calculus of variations

> 1. Review of extremal problems of elementary analysis and basic concepts of functional analysis related to variational calculus. > 2. The simplest problem of variational calculus. Differential of a function. Necessary conditions for the existence of an extremum. Euler's equation. The case of many variables. Variational derivative. Invariability of Euler's equations. > 3. Generalizations of the simplest problem of variational calculus to the case of Banach and Hilbert spaces. > 4. parametric problems. Variational problems in param

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Trazyn The Infinite Best Moments

Just wanted to post some Trazyn moments (trolls). Apologies if it's lengthy. Most of these are from the book The Infinite and the Divine.

Some context:

Long after fighting off an Ork invasion of the Imperial world of Serenade, Trazyn the Infinite and Orikan the Diviner return to the world in pursuit of a centuries-long quest ( A key to the tomb of the last remaining original Necrontyr body without the genetic sun cancer still in existence in the Universe). When they arrive they enter an Imperial cathedral and discover that the citizens of the imperial world Serenade remember the Ork invasion a little bit differently.

  • From The Infinite and the Divine:

Trazyn reached the door of the great cathedral. ‘After you, colleague.’ ‘This is the part where I turn my back and you stab it, surely?’ ‘Have it your way,’ Trazyn shrugged, and passed through the door. ‘But this is our fastest entryway to the Eternity Gate.’ Shadows seeped down the walls of the cathedral’s interior, collecting in pools on the floor. Candles, ranked like men battling in a confused melee, burned before the images of saints, residue from smoke and dissolved wax blackening their golden feet. A pilgrim, head shaved in a monk’s tonsure and clad in the light blue robes of his order, walked a labyrinth in the floor. He stopped to ring a bell and mutter a prayer every time he pivoted in the twisting path. Each whispered invocation echoed, paper-dry in the empty space. ‘You see the windows?’ Trazyn pointed at the stained glass, radiating in the bright morning sun. ‘Each panel charts the history of Serenade.’ ‘Fascinating,’ said Orikan, clearly unimpressed with this parochialism. ‘Why are we here? I was given to understand that it was time to start our great task.’ ‘It is. This is part of it. See the first? The God-Emperor shaping the mountains and islands of Serenade with His very hands. The first settlement ship exiting the empyrean, the angelic Saint Madrigal showing the way to Serenade with her blessed lyre – she is usually depicted with a sword, so this is a regional variation–’ ‘Trazyn,’ warned Orikan, ‘immortality aside, my time is valuable.’ ‘Oh, very well. Moving to the interesting part. Here we have the Greenskin War, as they call it. And who, my dear rival, is that in the next panel?’ Orikan looked up, dismissing the overlaid data-scroll he’d secretly been reading. ‘No.’ *‘Oh yes.’ Storming through the square, meeting the greenski

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How Residues of Chinese Imperial Worldview Still Impact Modern China Strategic Toolkit

In the previous post titled Jaw-Jaw: China’s Great Power Disease (Edward Luttwak) I went through Edward Luttwak's his book, which in the post dealt mainly with who Luttwak's perceived was the Chinese world view and cognitive biases impact their perception of the strategic reality. The problem with Luttwak while he has a decent understanding of basic principles behind China's Imperial worldview, but not sufficient enough to explain different approaches throughout China's history, even during the same dynasty. . Secondly, he doesn't realize the Chinese, including ethnic Han and conquest dynasties (Yuan and Qing) used non-Chinese concepts when ruling non-Han subjects and nations if they felt it was advantageous,

In this post, I will first examine some of the basic principles behind China's worldview in the Imperial past This section will cover concepts such as Tianxia-Guojia, Concept of Hua-Yi,, Mandate of Heaven. Lastly, I will examine five areas of statecraft - observing an opponent, alliances, building "walls", use of commercial tools and treaties within the context of the first section.

A. TIANXIA, HUA-YI CONCEPT AND MANDATE OF HEAVEN

A1. TIANXIA (天下) **AND GUOJIA (**國家)

A2. HUA-YI DISTINCTION

A3. MANDATE OF HEAVEN

B. BARBARIAN HANDLING AND ENCOUNTERS WITH DONALD J TRUMP

C. RISE OF CONFUCIANISM, HEQIN MARRIAGES AND ALLIANCES

C1, HEQIN MARRIAGES

C2. ALLIANCES

D. THE GREAT WALL AND THE ART OF BUILDING WALLS

E. POLITICAL OVER THE COMMERCIAL

E1, CHINESE THE MATERIALIST

E2. DOMINANCE OF COMMERCE

G. CHANGING EQUILIBRIUM AND TREATIES

H. CONCLUSION

Post 1949 leaders, like their Imperial counterparts, used a varied toolkit to guide and justify their actions. Chinese leaders take concepts and themes from Imperial China, experience of the Soviet Union, Imperial Japan and the West. Different leaders use different time periods and interpretations of history to frame an issue.

Secondly, Imperial Chinese rulers were pragmatist, and placed realpolitik above Confucianism. They had no problem dealing with non-Confucian polity like the steppe nomads as equals even on paper when ti was necessary, [Notions of Confucian benevolence given a dominate role on foreign policy would have amused Imperial Chinese rulers.](https:/

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Achieving dietary micronutrient adequacy in a finite world - Ty Beal -- animal-source foods provide key micronutrients vital to healthy diets. Planetary boundaries and local contexts must be considered to facilitate regenerative and sustainable livestock production.

Achieving dietary micronutrient adequacy in a finite world

Ty Beal

https://www.sciencedirect.com/science/article/pii/S2590332221004772?dgcid=author Free for 50 days

Free for forever below.

https://twitter.com/TyRBeal/status/1438874951973588994

https://preview.redd.it/j2qta31au2o71.png?width=680&format=png&auto=webp&s=6e74fa52b466500a3f3f81502e0f76ca622d00eb

Modern food systems have contributed to extensive environmental degradation, resulting in calls for a planetary health diet that dramatically reduces the consumption of animal-source foods. However, animal-source foods provide key micronutrients vital to healthy diets. Planetary boundaries and local contexts must be considered to facilitate regenerative and sustainable livestock production.

Main text

No species has transformed the planet like humans. Much of this transformation has come from the processes involved in producing food for human consumption. Modern food systems—which include the people, places, and practices involved in food production, capture, harvest, processing, transport, retail, consumption, and disposal—are responsible for extensive loss of natural resources and the destruction of ecosystems and biodiversity. But food systems are also essential for human survival. Much of the destructive nature of our food systems has been attributed to our domestication of livestock and the resources this requires. The animal-source foods (ASFs) derived from these livestock also happen to provide us with many of the nutrients we need (Figure 1), access to which varies dramatically around the world. How we provide a growing global population with these essential nutrients while staying within environmental limits is one of our greatest and most pressing challenges.

Figure 1. Priority micronutrient densities of select foods

Adapted from Beal et al.1 For canned fish with bones, bivalves, crustaceans, and whole grains, median values were calculated from common foods in USDA FoodData Central.[2](https://www.sciencedirect.com/science/

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Converting Nitrogen into Protein—Beyond 6.25 and Jones' Factors (2008)

Full-text: https://sci-hub.se/10.1080/10408390701279749

After a brief few keyword search on PubMed and Google Scholar, this is all I found for "6.25 Jones' Factors." Yet "protein chemistry" resulted in over 200k results on PubMed (too broad). Along the way, I found this one: My 65 years in protein chemistry (2015).

INTRODUCTION

6.25, the Flawed Viewpoint

> The protein content in a foodstuff is estimated by multiplying the nitrogen content by a nitrogen-to-protein conversion factor, usually set at 6.25. This historical factor (dating back to the 19th century) assumes the nitrogen content of proteins to be 16%. Although widely accepted, this practical rule is little resistant to closer scrutiny.
>
>First, it has long been acknowledged that pure proteins differ in terms of their nitrogen contents (Jones, 1941). This results from differences in their amino acid composition, because the nitrogen content of amino acids can vary considerably, being high in arginyl, histidyl, glycyl, and asparagyl residues and low in phenylalanyl and tyrosyl residues. Jones (1941) reported that avocado protein contains 13.4% nitrogen and amandin (an almond protein) 19.3%. In such cases, using a 6.25 conversion factor can lead to a 15–20% error in the protein content. Different values have been reported by other authors for other proteins, and even for different protein fractions within the same protein source. For example, the nitrogen content of collagen is 18%. Consequently, the nitrogen-to-protein ratio in meat products will vary as a function of the collagen level (Benedict, 1987).
>
> Second, nitrogenous compounds in foodstuffs do not only comprise protein or amino acid, they also include numerous substances such as nucleic acids, amines, urea, ammonia, nitrates, nitrites, phospholipids, nitrogenous glycosides, etc. (Fig. 1). The fraction of non-alpha-amino nitrogen is highly variable for a given protein source, depending on the production process and the degree of purification of the protein source.
>
> Therefore, in many cases, multiplying the nitrogen content of a protein source by 6.25 cannot provide a sound estimate of the protein content (Fig. 1). N × 6.25 is referred as the “crude protein” content, a term that is now less and less employed in human nutrition.

[ Figu

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First look at Alexion’s Factor D drugs relative to Biocryst’s

In a few days to weeks, Biocryst ($BCRX) is going to release a significant amount of new information about its Factor D drug BCX9930 and the responses of patients with the disorder PNH to it. Investors will be poring over the new data, which we have been told will not be a single press release but a big release, perhaps a conference or some other type of presentation. We will receive an update on the ongoing Phase II PNH trial, as well as discover new data about dose-ranging and non-naïve C5 inhibitor resistant patients. In combination with these, we will likely hear about new clinical trials, the company saying that they will be renal, and may hear about the start of a Phase III trial. So a lot to hear about and digest for the investor community, which is hopeful but most definitely does not seem to be counting Factor D as a given—at least not by the stock price given to the company—see my other posts about what a fair valuation of Factor D would make Biocryst worth.

Here I’m going to discuss a little background on Alexion before I discuss primarily ALXN2040/Danicopan. Alexion sells the drugs Soliris (eculizumab) and Ultomiris (ravulizumab), C5 inhibitors that have been the go-to drugs for PNH for several years. It has been switching patients from Soliris to Ultomiris over the past couple years due to a patent dispute on Soliris that threatens future revenue. These drugs have limited efficacy, a lot of side effects, and are injected. It is likely for this reason that it bought Achillion—mainly for Achillion’s two oral Factor D drugs, now referred to as ALXN2040/Danicopan and ALXN2050, that are currently in clinical trials. Factor D is gradually being recognized to be a superior target for many diseases relative to C5, and so it was a natural direction for the company to go. Note that according to the company, ALXN2050 is more potent. It was likely these two Factor D drugs that resulted in Alexion being bought by Astra-Zeneca for $39 billion, a deal which is on its way to closing.

I’m now going to focus on some of my observations from the second paper that Alexion published on ALXN2040/Danicopan (Risitan et al, Haematologica, 2020; https://pubmed.ncbi.nlm.nih.gov/33121236/). They studied 10 patients giving them a dose of 100-200 mg three times per day for up to 84 days, evaluating them at 4 and 12 weeks. 8 of the patients finished the treatment, two of them dropping out, one because of a breakthrough event ca

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A Long, In-Depth Analysis on Diluc (The Op character that has great skills & a great story)

An In-Depth Analysis on Diluc

Well, it seems it’s high time I write some analyses on pre-existing characters. Personally, I wouldn’t consider Diluc my pick for best husbando (I hope it’s okay I use that term since we are all degenerates here) but I do find him to be one of the best written characters. Too bad he was NERFED so hard in Genshin. . . just look how his hair and face was done so dirty ( /・・ ) ノ

As always, though I’m sure this doesn’t need to be said, this is not a math analysis. I’m sure, by now, we all know Diluc goes brrrrrrrrrrrrrr.

So. . . I hope you enjoy the analysis ʕ·ᴥ· ʔ

Let me note, I do not know every piece of lore in the game so I’m sorry for anything incorrect. There will be spoilers for the Webcomic and, if you have not read it yet, you should go read it. Lastly, if I say anything incorrect, I feign my innocence.

TLDR:

  • Diluc was once a talented knight of Ordo Favonius. It was both his and his father’s, Crepus’s, wish for Diluc to become a great knight. Crepus, unlike his son, was never graced by the Gods.
  • In the past, Diluc was perceived well by both the citizens and the knights. He also had a close relationship with both his father and Kaeya.
  • 3 major events occured on Diluc’s 18th birthday: Crepus’s death due to Evil Eye backfiring on him, Eroch wishing to conceal the truth of Crepus’s death, and Kaeya revealing his true character to Diluc.
  • Fueled by both anger and bitterness, Diluc pursued finding the truth of Crepus’s death. He began to attack Fatui strongholds until he had a run-in with the Harbingers. An unknown person from the north, part of a secret organization, rescued him.
  • Diluc joined the secret organization, using the Delusion Evil Eye. He returned to Mondstadt, dealing with the Black Fire incident. After the incident was resolved, Evil Eye was sent to Dottore smashed and Kaeya returned Diluc’s vision in a vase.
  • Diluc, now as the Darknight Hero, protects Mondstadt alone. He refuses to work with the Knight of Favonius due to his past.
  • Since returning to Mondstadt, Diluc has gotten rid of various items that were possessions of his late father. Yet he has kept others. Ultimately Diluc is torn between his feelings of wishing to return to the past, and his lone duties.

Word Count: 3712 (+ 1023 Summary)

- - - - - - - - - - - - - - -

Diluc Analysis

Bread and Butter:

“As the wealthiest gentleman in Mondstadt, the ever-dapper Diluc always presents himself as the

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That's a pretty unique approach! youtube.com/watch?v=CIRGU…
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📅︎ Aug 03 2018
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The "rostrum" of the new multi-purpose offshore patrol vessels [Italian PPA class]

This is an article published on the January 2021 issue of the Rivista Marittima, the official monthly magazine of the Marina Militare, the Italian Navy. It has been written by Captain Gabriele Catapano and Commander Mario De Biase.

I translated the article from Italian to English and, because the original is a little verbose and repetitive, I tried to adjust it for a more pleasant reading experience. No information was cut.


Launch of the Paolo Thaon di Revel PPA

The multi-purpose offshore patrol vessel [pattugliatore polivalente d'altura] (PPA), developed together with the LSS [logistical support ship] and LHD as part of the program for the safeguard of the maritime capability of the Defence, is an extremely complex and sophisticated ship able to conduct different types of missions, expressing first order operative capabilities. It is a vessel belonging to a new concept, created to guard and control the maritime spaces of national interest, to monitor maritime and economic activities, to contribute to the preservation of the maritime environment, to support rescue operations for the population in case of natural calamities and to take part in escorts for naval groups, major ships and merchant ships. All of this is to be undertaken by a single platform, for which three configurations of the combat system have been envisioned, respectively Light, Light+ and Full.
The necessity to integrate these numerous and complex capabilities on the same platform required the development of some innovative design features, like hull shapes and appendages that could satisfy the requirement for the fastest possible speed. As it is easily understood, significantly high speeds require, all other factors being equal (like hull dimensions, displacement, etc.), similarly high propulsive capacities.

In theory, the fundamental laws of hydrodynamics indicate that to limit the resistance to motion of a given hull and therefore to limit installed propulsion, the displacement being equal, it is necessary to increase the waterline length. It is in fact known that the resistance to motion R for a partly submerged body is essentially the sum of two main components: the friction resistance R^F connected to viscous phenomena (1) and the residual resistance R^R (which includes the so-called wave-making resistance) (2), connected to gravitational phenomena; this latter component, which is prevalent in the total amount of the resistance to motion

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📅︎ May 17 2021
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An Analysis of the Metaphysical Mechanisms behind the Imperial Gellar Field and Gellar Field Applications used during the Dark Age of Technology (Part 1)

Hey guys, it's been a while since I last posted something to this subreddit. Since then, I've been working on what amounts to a 36 page essay that attempts to clarify the otherwise contradictory pieces of information regarding the Gellar Field. I’m really excited to share this with you guys, because this has taken me a long time to make. And even if you don’t agree with what I have to say, I hope the assembled lore excerpts can help you better conceptualize how Gellar Fields, and the Warp, works. Since this essay is very long, I'll be posting it incrementally across a few posts so that the word count limit wouldn't be an issue.

Before I begin this discussion, one thing needs to be made clear: It does not matter whether or not you consider canon how a Gellar field requires comatose psykers to generate. Since it has been confirmed by GW and multiple Black Library authors that this is canon, this aforementioned discussion will consider it canon, and will build upon this idea to reveal insights about why a Gellar Field would need this.

-----------------------------------------------------------------------------------------------------------------------------------------------------

Introduction

In the 40th Millenium, Warp travel forms the lifeline of the Imperium. Yet its highly distinguished catalogue of warp expeditions could not be possible without the utility of Gellar Fields. As defined in numerous sources, a Gellar Field generates a protective bubble of realspace that protects the ship and its passengers from both daemonic entities and the ambient energies of the Warp. In contrast with expectations, recent lore has indicated that the Gellar field is instead generated by the sacrifice of a comatose psyker, whose dreams are then used to generate the aforementioned bubble of realspace. While the reception of which remained mixed, this new piece of information clashes with established canon which states that the first Warp Drive was invented roughly alongside the first Gellar Field during the 18th millennium. Should Gellar Field generation also require comatose psykers during that bygone millennia, then humanity ought to have had a consistent supply of psykers to fuel extrasolar explorations for 7 millennia, up to the height of the Dark Age of Technology (DaOT). However, this contradicts established lore which states that humanity's first psykers sacrificed themselves in order to create the Emperor, and the second wave of humanity's psykers only ap

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Marx, Marxism and the cooperative movement

https://www.researchgate.net/publication/5208466_Marx_Marxism_and_the_cooperative_movement

This paper has a dual aim: first, to draw attention to a number of passages in which Marx explicitly extolled the cooperative movement and thereby confute the wrong but widely held assumption that Marx was inimical to the market and rejected cooperation as a production mode even for the transition period;second, to argue that the continuing neglect of Marxists both of the co-operative movement and of the passages from Marx (and Engels) that present a system of producer cooperatives as a new production mode can be traced back in part to the late emergence of an economic theory of producer cooperatives.

On several occasions Marx declared himself strongly in favour of cooperative firms, maintaining that their generalised introduction would result in a new production mode. At different times in his life, he even seems to have been confident that cooperatives would eventually supplant capitalistic firms altogether. Lenin also endorsed the cooperative movement and, in a 1923 work (entirely devoted to this subject), he went so far as to equate cooperation with socialism at large. More precisely, besides describing cooperation as an important organisational step in the transition to socialism, he explicitly argued that ‘cooperation is socialism’ (Lenin,1923). All the same, ever since the time of the Paris Commune the cooperative movement has received little attention from Marxists.

One argument we intend to put forward in our analysis is that this scant attention for the cooperative movement is due at least in part to the kind of cooperative—a firm in which workers are ‘their own capitalists’ (Marx, 1894, p. 571)—that has asserted itself in history, because this tends to endorse the view that a system of producer cooperatives is not a genuine form of socialism.

However, modern economic theory has shown that the pure cooperative is Vanek’s LMF (see Vanek, 1971A, 1971B), which does not self-finance itself and whose workers can consequently not be correctly described as ‘their own capitalists’. And this consideration disproves the arguments of those Marxists who maintain that cooperatives are, by their very nature, an intermediate form in between capitalism and socialism. But what are the implications of the above reflections? Once we have made it clear that Marx looked upon cooperation as a new production mode superseding capital-ism, Marxists fall into at least two distinct grou

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📅︎ Apr 03 2021
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A Beginners Guide to CBD

Wanted to put this out there for anyone just starting out. There’s a lot of info but should give a nice overview to CBD.

There are 6 main sections and all the info comes from a slightly more in-depth version that is published on our website: https://www.fortheageless.com/pages/cbd-oil-uk-guide

We have been retailing CBD products since 2016 and amassed a lot of info about the industry, products and the people who purchase it. The info is always changing and I will of course update this as we receive it.

1. What is CBD?

2. Facts about CBD

3. How does CBD work?

4. Are there any side effects?

5. Choosing your product

6. How to take CBD

1. What is CBD?

Cannabidiol (CBD) is one of the best known of over one hundred cannabinoids found in the cannabis plant. Unlike THC (tetrahydrocannabinol), CBD is non-intoxicating and is used in numerous food supplements and skincare products.

After reviewing the latest research, the World Health Organization announced that they consider it as safe for use as a food supplement. They also stated that it’s “generally well tolerated with a good safety profile”.

2. Facts about CBD

CBD is legal in the UK - Most CBD products are legal to purchase in the UK. However, to be sold in the UK it must not be promoted as a medicine or having medicinal benefits. For a CBD product to be sold containing THC (full-spectrum), there must be no more than 1mg of THC or CBN in the final preparation.

Note: 0.2% THC only applies the amount permitted in hemp plants that can be grown under licence in the UK and not products that can be sold.

Whilst most CBD products are available for sale legally, hemp flower is not legal in the UK because it is currently covered by the same law as cannabis flower in the MDR 2001.

CBD won’t get you high - [CBD does not make you feel high](https://www.fortheageless.com/blo

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[R] Latest developments in Graph Neural Networks: A list of recent conference talks

Graph Neural Networks (GNNs) has seen rapid development lately with a good number of research papers published at recent conferences. I am putting together a short intro of GNN and a summary of the latest research talks. Hope it is helpful for anyone who are getting into the field or trying to catch up the updates.

--------------------------------------

What is a Graph Neural Network?

A graph is a datatype containing nodes (vertices) that connect to each other through edges, which can be directed or undirected. Each node has a set of features (which could represent properties of nodes or could be one-hot-encoded information), and the edges define relations between nodes.

In a typical GNN, Message Passing is performed between nearby nodes through the edges. Intuitively, the message is a neural encoding of the information that is passed from one node to its connected neighbors. At any layer, the representation of a node is computed by aggregating the messages from all its neighbors to the current node. After multiple rounds of message passing, one can obtain a vector representation for each node, which can be interpreted as an embedding representation describing not only the node feature information but also the neighborhood graph structure around this node. (This article is very helpful to learn basics and math behind GNNs.)

A graph can be used to depict numerous data from social networks and images to chemical structures, neurons in the human brain and even a regular, fully connected neural network. That’s what makes GNNs so useful.

--------------------------------------

Below is a quick summary of a few interesting talks on GNNs with links to their videos. Paper links can be found under the video or in the description. There is a time-stamped note section on the side to jot down your thoughts or share them publicly as you watch the video.

A digest of a few recent papers on GNNs

XGNN: Towards Model-Level Explanations of Graph Neural Networks

One of the major problems with using neural networks is that they are used as black boxes. They are unlikely to be used for critical situations due to the lack of reasons behind a decision. Current methods use gradients, perturbations, and activation

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📅︎ Oct 07 2020
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I Read It So You Don't Have To: Love Italian Style (by Melissa Gorga)

As much as I've been enjoying our literary exploration of RHONY's trailblazing cosmopolites, I think it's time to mix things up and travel approximately thirty miles down the road to get a taste of the suburban paradise that is the non-Jersey-Shore part of New Jersey. And since I'm sure we could all use a little bit of extra help keeping that spark alive -- especially in these trying times -- what better place to start than Melissa Gorga's 2013 relationship advice book, Love Italian Style: The Secrets of My Hot and Happy Marriage.

If you were in any doubt as to our author's expertise on the particular issue at hand, never fear! You have only to flip the book over to its back cover to be thoroughly rid of any residual skepticism. What is love, if not those nuzzling noses, that slender hand thrown into contrast against a patch of coarse, hoary facial hair? However, I have to admit that my personal definition of love would probably have included a little help from my friendly neighborhood tooth-whitening app. Between an unfortunately positioned shadow and the striking contrast of Melissa's hyper-peroxided chompers, poor Joe looks like he got pulled into this photo shoot midway through eating a particularly unwieldy Tootsie Roll.

In the introduction ("Blueprint for a Better Marriage"), Melissa primes us on her motivations for writing this book.

>Since I entered the world of reality TV, the number one message I get from fans is, "I want your marriage!"

She continues,

>The number two message I get from fans: "How do you do it?"

I think a far more interesting question would be, Why do you do it, but that's neither here nor there. Melissa goes to empower the reader with the knowledge that, no matter the state of their marriage, there's always a way to turn things around.

>If other women want a close-to-perfect marriage, they can have it, too. It's their choice. Even if they don’t think they are, they are in control. Women steer the ship. What they say and how they act towards their partner will directly correlate with his response.

I am breathless with relief, and immediately begin making plans to send a copy of this book to every domestic violence hotline in the nation. How silly of me -- the solution was there the whole time! How disappointing that all of those other women couldn't have just tried a little harder.

With that selfless act of charity over

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How to perform IT Risk Assessment

Cybersecurity is all about understanding, managing, controlling and mitigating risk to your organization’s critical assets. Whether you like it or not, if you work in security, you are in the risk management business.

To get started with IT security risk assessment, you need to answer three important questions:

  1. What are your organization’s critical information technology assets — that is, the data whose exposure would have a major impact on your business operations?
  2. What are the top five business processes that utilize or require this information?
  3. What threats could affect the ability of those business functions to operate?

Once you know what you need to protect, you can begin developing strategies. However, before you spend a dollar of your budget or an hour of your time implementing a solution to reduce risk, you should be able to answer the following questions:

  1. What is the risk you are reducing?

  2. Is it the highest priority security risk?

  3. Are you reducing it in the most cost-effective way?

These questions get to the heart of the problem — that it is all about risk.

What is Risk?

Risk is a business concept — is the likelihood of financial loss for the organization high, medium, low or zero? Three factors play into risk determination: what the threat is, how vulnerable the system is, and the importance of the asset that could be damaged or made unavailable. Thus, risk can be defined as follows:

Risk = Threat x Vulnerability x Asset

Although risk is represented here as a mathematical formula, it is not about numbers; it is a logical construct. For example, suppose you want to assess the risk associated with the threat of hackers compromising a particular system. If your network is very vulnerable (perhaps because you have no firewall and no antivirus solution), and the asset is critical, your risk is high. However, if you have good perimeter defenses and your vulnerability is low, and even though the asset is still critical, your risk will be medium.

There are two special cases to keep in mind:

  • Anything times zero is zero. If any of the factors is zero, even if the other factors are high or critical, your risk is zero.
  • Risk implies uncertainty. If something is guaranteed to happen, it is not a risk.

Here are some common ways you can suffer financial damage:

  • Data loss. Theft of trade secrets could cause you to lose business to your competitors. Theft of customer information could result in loss of trust and
... keep reading on reddit ➡

👍︎ 415
📰︎ r/sysadmin
💬︎
📅︎ Jan 18 2018
🚨︎ report
Move over Bloomberg Terminal, here comes Gamestonk Terminal

Hey all,

2 months ago I made a terminal that I had been working on my spare time, to help me on my stock research, open-source. See https://dro-lopes.medium.com/gamestonk-terminal-the-next-best-thing-after-bloomberg-terminal-a263c001a61f

The motto:
Gamestonk Terminal provides a modern Python-based integrated environment for investment research, that allows the average joe retail trader to leverage state-of-the-art Data Science and Machine Learning technologies. As a modern Python-based environment, Gamestonk Terminal opens access to numerous Python data libraries in Data Science (Pandas, Numpy, Scipy, Jupyter), Machine Learning (Pytorch, Tensorflow, Sklearn, Flair), and Data Acquisition (Beautiful Soup, and numerous third-party APIs).

As of today, and thanks to all your help and the traction created around it, the terminal is looking better than ever. Now it's no longer only me taking care of the repo, but also 2 other experienced devs (thanks u/hbar340), who are adding features on a daily basis and increasing the robustness of the codebase. Feel free to wander through the FEATURES page to see what you would get out of this tool!

If some of you thought it was amazing 2 months ago, you won't believe what it looks like now. You can check out the ROADMAP for all the features that have been added since, but let me list some of them:

  • New Screener for stocks, which allows users to save their presets and share them
  • New Options menu
  • New Comparison Analysis to compare several tickers in their historical price, sentiment, or fundamental analysis
  • New Portfolio Optimisation that assigns stocks weights based on risk level specified by the user
  • New Exploratory Data Analysis menu that looks at historical data from a statistic point of view
  • New Residual Analysis after using a statistical model for prediction
  • New menu to provide access to your portfolio (supports Robinhood, Ally invest, Alpaca, and Degiro)
  • New Cryptocurrency, Forex, and FRED menus
  • Prediction with backtesting
  • Technical analysis that includes a score and a summary
  • Due Diligence menu with data from Dark Pools, and also Failure to Deliver
  • Sentiment analysis from news provided from collaboration with a company that provides this feature paid. Free for us!

As always feedback is appreciated, and contributions even more so!

Let’s try to reduce the gap between the amount of information that the Hedge Funds have access to in comparison with the u

... keep reading on reddit ➡

👍︎ 2k
💬︎
👤︎ u/SexyYear
📅︎ Apr 23 2021
🚨︎ report
Move over Bloomberg Terminal, here comes Gamestonk Terminal

https://github.com/DidierRLopes/GamestonkTerminal

Hey all,

2 months ago I made a terminal that I had been working on my spare time, to help me on my stock research, open-source. See https://dro-lopes.medium.com/gamestonk-terminal-the-next-best-thing-after-bloomberg-terminal-a263c001a61f

The motto:
Gamestonk Terminal provides a modern Python-based integrated environment for investment research, that allows the average joe retail trader to leverage state-of-the-art Data Science and Machine Learning technologies. As a modern Python-based environment, Gamestonk Terminal opens access to numerous Python data libraries in Data Science (Pandas, Numpy, Scipy, Jupyter), Machine Learning (Pytorch, Tensorflow, Sklearn, Flair), and Data Acquisition (Beautiful Soup, and numerous third-party APIs).

As of today, and thanks to all your help and the traction created around it, the terminal is looking better than ever. Now it's no longer only me taking care of the repo, but also 2 other experienced devs (thanks u/hbar340), who are adding features on a daily basis and increasing the robustness of the codebase. Feel free to wander through the FEATURES page to see what you would get out of this tool!

If some of you thought it was amazing 2 months ago, you won't believe what it looks like now. You can check out the ROADMAP for all the features that have been added since, but let me list some of them:

  • New Screener for stocks, which allows users to save their presets and share them
  • New Options menu
  • New Comparison Analysis to compare several tickers in their historical price, sentiment, or fundamental analysis
  • New Portfolio Optimisation that assigns stocks weights based on risk level specified by the user
  • New Exploratory Data Analysis menu that looks at historical data from a statistic point of view
  • New Residual Analysis after using a statistical model for prediction
  • New menu to provide access to your portfolio (supports Robinhood, Ally invest, Alpaca, and Degiro)
  • New Cryptocurrency, Forex, and FRED menus
  • Prediction with backtesting
  • Technical analysis that includes a score and a summary
  • Due Diligence menu with data from Dark Pools, and also Failure to Deliver
  • Sentiment analysis from news provided from collaboration with a company that provides this feature
... keep reading on reddit ➡

👍︎ 631
📰︎ r/DDintoGME
💬︎
👤︎ u/SexyYear
📅︎ Apr 24 2021
🚨︎ report
The ultimate blueprint to getting a job in data science

EDIT: I’m on discord to answer your questions: https://discord.gg/raQ5NjHy

It’s pretty late in the UK (11.30pm, but I’ll stay up as long as you guys want me to)

Organisation is Key

I’ve interviewed at Google (and DeepMind), Uber, Facebook, Amazon for roles that lie under the “Data Scientist” umbrella and this is the typical interview construction theme I’ve observed:

Software Engineering Applied Statistics Machine Learning Data Wrangling, Manipulation and Visualisation

Now nobody is expecting some super graduate level competency in all of these topics, but you need to know enough to convince your interviewer that you’re capable of delivering if they offered you the job. How much you need to know depends on the job spec, but in this increasingly competitive market, no knowledge is lost.

I recommend using Notion to organise your job prep. It’s extremely versatile, and enables you to utilise the Spaced Repetition and Active Recall principles to nail down learning and deploying key topics that come up time and time again in a Data Scientist interview. Ali Abdaal has a great tutorial on note taking with Notion to maximise your learning potential during the interview process.

I used to run through my Notion notes over and over, but in particular, right before my interview. This ensured that key topics and definitions were loaded into my working memory and I didn’t waste precious time “ummmmmm”ing when hit with some question.

  1. Software Engineering Not all Data Scientist roles will grill you on the time complexity of an algorithm, but all of these roles will expect you to write code. Data Science isn’t one job, but a collection of jobs that attracts talent from a variety of industries, including the software engineering world. As such you’re competing with guys that know the ins and outs of writing efficient code and I would recommend spending at least 1–2 hours a day in the lead-up to your interview practicing the following concepts:

Arrays Hash Tables Linked Lists Two-Pointer based algorithms String algorithms (interviewers LOVE these) Binary Search Divide and Conquer Algorithms Sorting Algorithms Dynamic Programming Recursion

DO NOT LEARN THE ALGORITHMS OFF BY HEART. This approach is useless, because the interviewer can question you on any variation of the algorithm and you will be lost. Instead learn the strategy behind how each algorithm works. Learn what computational and spatial complexity are, and learn why they are so fundamental to building

... keep reading on reddit ➡

👍︎ 540
💬︎
📅︎ Feb 03 2021
🚨︎ report
Move over Bloomberg Terminal, here comes Gamestonk Terminal

https://github.com/DidierRLopes/GamestonkTerminal

Hey all,

2 months ago I made a terminal that I had been working on my spare time, to help me on my stock research, open-source. See https://dro-lopes.medium.com/gamestonk-terminal-the-next-best-thing-after-bloomberg-terminal-a263c001a61f

The motto:
Gamestonk Terminal provides a modern Python-based integrated environment for investment research, that allows the average joe retail trader to leverage state-of-the-art Data Science and Machine Learning technologies. As a modern Python-based environment, Gamestonk Terminal opens access to numerous Python data libraries in Data Science (Pandas, Numpy, Scipy, Jupyter), Machine Learning (Pytorch, Tensorflow, Sklearn, Flair), and Data Acquisition (Beautiful Soup, and numerous third-party APIs).

As of today, and thanks to all your help and the traction created around it, the terminal is looking better than ever. Now it's no longer only me taking care of the repo, but also 2 other experienced devs (thanks u/hbar340), who are adding features on a daily basis and increasing the robustness of the codebase. Feel free to wander through the FEATURES page to see what you would get out of this tool!

If some of you thought it was amazing 2 months ago, you won't believe what it looks like now. You can check out the ROADMAP for all the features that have been added since, but let me list some of them:

  • New Screener for stocks, which allows users to save their presets and share them
  • New Options menu
  • New Comparison Analysis to compare several tickers in their historical price, sentiment, or fundamental analysis
  • New Portfolio Optimisation that assigns stocks weights based on risk level specified by the user
  • New Exploratory Data Analysis menu that looks at historical data from a statistic point of view
  • New Residual Analysis after using a statistical model for prediction
  • New menu to provide access to your portfolio (supports Robinhood, Ally invest, Alpaca, and Degiro)
  • New Cryptocurrency, Forex, and FRED menus
  • Prediction with backtesting
  • Technical analysis that includes a score and a summary
  • Due Diligence menu with data from Dark Pools, and also Failure to Deliver
  • Sentiment analysis from news provided from collaboration with a company that provides this featur
... keep reading on reddit ➡

👍︎ 384
💬︎
👤︎ u/SexyYear
📅︎ Apr 24 2021
🚨︎ report
A GME Saga: The Two Towers

First, I'm not a financial advisor and all of this is a combination of opinion research articles and a great deal of research by others.

Two Towers: Blackrock & Vanguard

This Saga is one of a liquidity issue: It comes in the form of collateral, swaps, derivatives and cash.

A Short Selling Example 

It is natural to wonder how there can be a higher short interest than the total number of shares outstanding. The answer is that the same shares can be lent over and over again. Here is an example: Short sellers need to borrow shares in order to deliver them to buyers. Suppose that Shareholder #1 owns 100 shares. Shareholder #1 is more than happy to take some money from the short sellers by renting out the shares to Short Seller A. Short Seller A sells the borrowed shares to Shareholder #2. Likewise, Shareholder #2 is happy to take money from short sellers by renting the shares to Short Seller B. Short Seller B sells the shares to Shareholder #3. Shareholder #3 does not lend out the shares. Notice that in this example there are 300 shares of long positions (Shareholders 1,2, and 3) and 200 shares of short positions (Short sellers A and B), but only 100 actual shares outstanding. This does not break any current US rules. However, just because the current practice does not violate present rules, the question remains whether extreme levels of short interest jeopardize the operation of a fair and orderly market. In particular, that an inevitable short squeeze develops that would result in dislocation in prices. For example, suppose that Shareholder #1 decides to stop lending out shares and demands the stock back. In that case the short seller would typically attempt to borrow the shares from someone else. However, if the short seller cannot find another stock loan to replace the original loan, the short seller must purchase the shares. If the short seller buys the shares from Shareholder #2, then Shareholder #2 will recall the shares, forcing Short Seller B to purchase the shares.

Collateral

This forced purchasing can cause prices to skyrocket in what is known as a short squeeze. Note that short selling creates the equivalent of a derivative market in the shares. This example is essentially similar to a situation where there is one shareholder (#3) who owns 100 shares with voting rights. In addition, there are two other long investors (#1 and #2) without voting rights who are engaged in contract similar to an indefinite

... keep reading on reddit ➡

👍︎ 598
📰︎ r/GME
💬︎
👤︎ u/Turdfurg23
📅︎ Apr 06 2021
🚨︎ report
I want to study some subjects I'm gonna have in the next semester in advance. Could you recommend some good resources I could use (books, video playlists, etc)?

Those are the subjects I'm going to have (with their syllabuses to give you a better idea on what we're going to have):

#Real and Complex Analysis

> 1. algebra and σ-algebra of sets. Measurable spaces. Measure, spaces with measure. Borel measure. Complete and regular measures. > 2. External measure. The problem of measure expansion. Caratheodory's condition. Constructions of Lebesgue measure. Characterization of measurable sets in the Lebesgue sense. > 3. Measurable functions. The space of simple functions. Theorem on approximation of measurable function by simple functions. > 4. Lebesgue integral and its properties. Relation of the Lebesgue integral to the Riemann integral. A theorem of convergence. Fatou's lemma. Lebesgue's convergence theorems. > 5. Productive measures. Tonelli's and Fubini's theorems. > 6. Functions with bounded variation. Absolutely continuous functions. Lebesgue's theorem of differentiability almost everywhere. > 7. Geometry and topology of the complex plane, Riemann sphere. Composite functions, continuity, elementary functions. > 8. Differentiation in the complex domain. Rules of differentiation. Cauchy-Riemann equations. Geometric interpretation of the complex derivative. > 9. Analytic functions (regular, holomorphic). Regularity of elementary functions. Conformal representation. > 10. Integration of complex functions. Curvilinear integrals of complex functions. > 11. Cauchy's integral theorem. Existence of a prime function. Cauchy's integral formula. Generalized Cauchy's formula. > 12. Expandability of an analytic function into a power series. Taylor and Laurant series. Zero points of an analytic function. Uniqueness theorem of analytic function. > 13. Cauchy's inequality. Integer functions. Liouville's theorem. Schwarz's lemma. > 14. Singular points. Residuum of a function. Determination of residues. Theorem on residues.

#Calculus of variations

> 1. Review of extremal problems of elementary analysis and basic concepts of functional analysis related to variational calculus. > 2. The simplest problem of variational calculus. Differential of a function. Necessary conditions for the existence of an extremum. Euler's equation. The case of many variables. Variational derivative. Invariability of Euler's equations. > 3. Generalizations of the simplest problem of variational calculus to the case of Banach and Hilbert spaces. > 4. parametric problems. Variational problems in param

... keep reading on reddit ➡

👍︎ 2
📰︎ r/maths
💬︎
📅︎ Jul 21 2021
🚨︎ report
A GME Saga: The Two Towers

First, I'm not a financial advisor and all of this is a combination of opinion research articles and a great deal of research by others.

Two Towers: Blackrock & Vanguard

This Saga is one of a liquidity issue: It comes in the form of collateral, swaps, derivatives and cash.

A Short Selling Example

It is natural to wonder how there can be a higher short interest than the total number of shares outstanding. The answer is that the same shares can be lent over and over again. Here is an example: Short sellers need to borrow shares in order to deliver them to buyers. Suppose that Shareholder #1 owns 100 shares. Shareholder #1 is more than happy to take some money from the short sellers by renting out the shares to Short Seller A. Short Seller A sells the borrowed shares to Shareholder #2. Likewise, Shareholder #2 is happy to take money from short sellers by renting the shares to Short Seller B. Short Seller B sells the shares to Shareholder #3. Shareholder #3 does not lend out the shares. Notice that in this example there are 300 shares of long positions (Shareholders 1,2, and 3) and 200 shares of short positions (Short sellers A and B), but only 100 actual shares outstanding. This does not break any current US rules. However, just because the current practice does not violate present rules, the question remains whether extreme levels of short interest jeopardize the operation of a fair and orderly market. In particular, that an inevitable short squeeze develops that would result in dislocation in prices. For example, suppose that Shareholder #1 decides to stop lending out shares and demands the stock back. In that case the short seller would typically attempt to borrow the shares from someone else. However, if the short seller cannot find another stock loan to replace the original loan, the short seller must purchase the shares. If the short seller buys the shares from Shareholder #2, then Shareholder #2 will recall the shares, forcing Short Seller B to purchase the shares.

Collateral

This forced purchasing can cause prices to skyrocket in what is known as a short squeeze. Note that short selling creates the equivalent of a derivative market in the shares. This example is essentially similar to a situation where there is one shareholder (#3) who owns 100 shares with voting rights. In addition, there are two other long investors (#1 and #2) without voting rights who are engaged in contract similar to an indefinitely-

... keep reading on reddit ➡

👍︎ 351
📰︎ r/Superstonk
💬︎
👤︎ u/Turdfurg23
📅︎ Apr 06 2021
🚨︎ report
A GME Saga: The Two Towers

First, I'm not a financial advisor and all of this is a combination of opinion research articles and a great deal of research by others.

Two Towers: Blackrock & Vanguard

This Saga is one of a liquidity issue: It comes in the form of collateral, swaps, derivatives and cash.

 A Short Selling Example 

It is natural to wonder how there can be a higher short interest than the total number of shares outstanding. The answer is that the same shares can be lent over and over again. Here is an example: Short sellers need to borrow shares in order to deliver them to buyers. Suppose that Shareholder #1 owns 100 shares. Shareholder #1 is more than happy to take some money from the short sellers by renting out the shares to Short Seller A. Short Seller A sells the borrowed shares to Shareholder #2. Likewise, Shareholder #2 is happy to take money from short sellers by renting the shares to Short Seller B. Short Seller B sells the shares to Shareholder #3. Shareholder #3 does not lend out the shares. Notice that in this example there are 300 shares of long positions (Shareholders 1,2, and 3) and 200 shares of short positions (Short sellers A and B), but only 100 actual shares outstanding. This does not break any current US rules. However, just because the current practice does not violate present rules, the question remains whether extreme levels of short interest jeopardize the operation of a fair and orderly market. In particular, that an inevitable short squeeze develops that would result in dislocation in prices. For example, suppose that Shareholder #1 decides to stop lending out shares and demands the stock back. In that case the short seller would typically attempt to borrow the shares from someone else. However, if the short seller cannot find another stock loan to replace the original loan, the short seller must purchase the shares. If the short seller buys the shares from Shareholder #2, then Shareholder #2 will recall the shares, forcing Short Seller B to purchase the shares.

 Collateral  

This forced purchasing can cause prices to skyrocket in what is known as a short squeeze. Note that short selling creates the equivalent of a derivative market in the shares. This example is essentially similar to a situation where there is one shareholder (#3) who owns 100 shares with voting rights. In addition, there are two other long investors (#1 and #2) without voting rights who are engaged in contract similar to an

... keep reading on reddit ➡

👍︎ 166
📰︎ r/Superstonk
💬︎
👤︎ u/Turdfurg23
📅︎ Apr 06 2021
🚨︎ report
Move over Bloomberg Terminal, here comes Gamestonk Terminal

https://github.com/DidierRLopes/GamestonkTerminal

Hey all,

2 months ago I made a terminal that I had been working on my spare time, to help me on my stock research, open-source. See https://dro-lopes.medium.com/gamestonk-terminal-the-next-best-thing-after-bloomberg-terminal-a263c001a61f

The motto:
Gamestonk Terminal provides a modern Python-based integrated environment for investment research, that allows the average joe retail trader to leverage state-of-the-art Data Science and Machine Learning technologies. As a modern Python-based environment, Gamestonk Terminal opens access to numerous Python data libraries in Data Science (Pandas, Numpy, Scipy, Jupyter), Machine Learning (Pytorch, Tensorflow, Sklearn, Flair), and Data Acquisition (Beautiful Soup, and numerous third-party APIs).

As of today, and thanks to all your help and the traction created around it, the terminal is looking better than ever. Now it's no longer only me taking care of the repo, but also 2 other experienced devs (thanks u/hbar340), who are adding features on a daily basis and increasing the robustness of the codebase. Feel free to wander through the FEATURES page to see what you would get out of this tool!

If some of you thought it was amazing 2 months ago, you won't believe what it looks like now. You can check out the ROADMAP for all the features that have been added since, but let me list some of them:

  • New Screener for stocks, which allows users to save their presets and share them
  • New Options menu
  • New Comparison Analysis to compare several tickers in their historical price, sentiment, or fundamental analysis
  • New Portfolio Optimisation that assigns stocks weights based on risk level specified by the user
  • New Exploratory Data Analysis menu that looks at historical data from a statistic point of view
  • New Residual Analysis after using a statistical model for prediction
  • New menu to provide access to your portfolio (supports Robinhood, Ally invest, Alpaca, and Degiro)
  • New Cryptocurrency, Forex, and FRED menus
  • Prediction with backtesting
  • Technical analysis that includes a score and a summary
  • Due Diligence menu with data from Dark Pools, and also Failure to Deliver
  • Sentiment analysis from news provided from collaboration with a company that provides this feat
... keep reading on reddit ➡

👍︎ 29
📰︎ r/Python
💬︎
👤︎ u/SexyYear
📅︎ Apr 23 2021
🚨︎ report
A GME Saga: The Battle at Helm's Deep

First, I'm not a financial advisor and all of this is a combination of opinion research articles and a great deal of research by others.

Helm's Deep: The Repo Market

So, one may be wondering especially since the recent quarterly losses were released how does a hedge fund remain Liquid this long and continue to have the leverage required to short the stock? (Spoofing is also happening).

Liquidity in Select Futures Markets (cftc.gov)

Thus far, we have seen an obvious need to additional liquidity for hedge funds, typically in the form of cash. But where would one get this cash and who would be give it to these hedgies. Well, it is the large commercial banks of course! The banks foresee the future and are playing the long game, they know Inflation is coming... Meanwhile the Fed has backed Treasury bonds! So, what the hedgies have done is actually outright buy treasury bonds and exchange them in a Swap through the Repo Market to gain additional liquidity. Of course banks get interest on that!. Hedge funds have been Re-hypothicating these treasury bills between one another and exchanging them for liquidity in a never ending loop to banks. At some point this strategy will run dry.

Visual Explanation of Repo Market

Chart by u/jsmar18

Amazing DD on Michael Burry's last post

In the recent release by the Fed they explore alternative options to buying treasury bills as well there was such a problem with them in terms of their yields. So, it will be important to follow what the Fed does next as far as how they continue to prop up this economy. In a recent video Steven theorizes that the Fed is going to transition into long bonds market, which may not be good to the liquidity of said hedge funds as they seem almost entirely reliant on the Repo market to gain access to additional liquidity.

Steve explains Fed transition

Second, another strategy that's being used is the OTM options strategy or Doom Options as revealed by Do

... keep reading on reddit ➡

👍︎ 87
📰︎ r/GME
💬︎
👤︎ u/Turdfurg23
📅︎ Apr 10 2021
🚨︎ report
A GME Saga: The Two Towers

First, I'm not a financial advisor and all of this is a combination of opinion research articles and a great deal of research by others.

**Two Towers: Blackrock & Vanguard**

This Saga is one of a **liquidity** issue: It comes in the form of collateral, swaps, derivatives and cash.

It is natural to wonder how there can be a higher short interest than the total number of shares outstanding. The answer is that the same shares can be lent over and over again. Here is an example: Short sellers need to borrow shares in order to deliver them to buyers. Suppose that Shareholder #1 owns 100 shares. Shareholder #1 is more than happy to take some money from the short sellers by renting out the shares to Short Seller A. Short Seller A sells the borrowed shares to Shareholder #2. Likewise, Shareholder #2 is happy to take money from short sellers by renting the shares to Short Seller B. Short Seller B sells the shares to Shareholder #3. Shareholder #3 does not lend out the shares. Notice that in this example there are 300 shares of long positions (Shareholders 1,2, and 3) and 200 shares of short positions (Short sellers A and B), but only 100 actual shares outstanding. This does not break any current US rules. However, just because the current practice does not violate present rules, the question remains whether extreme levels of short interest jeopardize the operation of a fair and orderly market. In particular, that an inevitable short squeeze develops that would result in dislocation in prices. For example, suppose that Shareholder #1 decides to stop lending out shares and demands the stock back. In that case the short seller would typically attempt to borrow the shares from someone else. However, if the short seller cannot find another stock loan to replace the original loan, the short seller must purchase the shares. If the short seller buys the shares from Shareholder #2, then Shareholder #2 will recall the shares, forcing Short Seller B to purchase the shares.

This forced purchasing can cause prices to **skyrocket** in what is known as a **short squeeze**. Note that short selling creates the equivalent of a **derivative market** in the shares. This example is essentially similar to a situation where there is one shareholder (#3) who owns 100 shares with voting rights. In addition, there are two other long investors (#1 and #2) without voting rights who are engaged in contract similar to an indefinitely-lived contract for differ

... keep reading on reddit ➡

👍︎ 41
💬︎
👤︎ u/Turdfurg23
📅︎ Apr 06 2021
🚨︎ report
Move over Bloomberg Terminal, here comes Gamestonk Terminal

https://github.com/DidierRLopes/GamestonkTerminal

Hey all,

2 months ago I made a terminal that I had been working on my spare time, to help me on my stock research, open-source. See https://dro-lopes.medium.com/gamestonk-terminal-the-next-best-thing-after-bloomberg-terminal-a263c001a61f

The motto:
Gamestonk Terminal provides a modern Python-based integrated environment for investment research, that allows the average joe retail trader to leverage state-of-the-art Data Science and Machine Learning technologies. As a modern Python-based environment, Gamestonk Terminal opens access to numerous Python data libraries in Data Science (Pandas, Numpy, Scipy, Jupyter), Machine Learning (Pytorch, Tensorflow, Sklearn, Flair), and Data Acquisition (Beautiful Soup, and numerous third-party APIs).

As of today, and thanks to all your help and the traction created around it, the terminal is looking better than ever. Now it's no longer only me taking care of the repo, but also 2 other experienced devs (thanks u/hbar340), who are adding features on a daily basis and increasing the robustness of the codebase. Feel free to wander through the FEATURES page to see what you would get out of this tool!

If some of you thought it was amazing 2 months ago, you won't believe what it looks like now. You can check out the ROADMAP for all the features that have been added since, but let me list some of them:

  • New Screener for stocks, which allows users to save their presets and share them
  • New Options menu
  • New Comparison Analysis to compare several tickers in their historical price, sentiment, or fundamental analysis
  • New Portfolio Optimisation that assigns stocks weights based on risk level specified by the user
  • New Exploratory Data Analysis menu that looks at historical data from a statistic point of view
  • New Residual Analysis after using a statistical model for prediction
  • New menu to provide access to your portfolio (supports Robinhood, Ally invest, Alpaca, and Degiro)
  • New Cryptocurrency, Forex, and FRED menus
  • Prediction with backtesting
  • Technical analysis that includes a score and a summary
  • Due Diligence menu with data from Dark Pools, and also Failure to Deliver
  • Sentiment analysis from news provided from collaboration with a company that provides this feat
... keep reading on reddit ➡

👍︎ 22
📰︎ r/GME
💬︎
👤︎ u/SexyYear
📅︎ Apr 23 2021
🚨︎ report
A GME Saga: The Battle at Helm's Deep

First, I'm not a financial advisor and all of this is a combination of opinion research articles and a great deal of research by others.

Helm's Deep: The Repo Market

So, one may be wondering especially since the recent quarterly losses were released how does a hedge fund remain Liquid this long and continue to have the leverage required to short the stock? (Spoofing is also happening).

Liquidity in Select Futures Markets (cftc.gov)

Thus far, we have seen an obvious need to additional liquidity for hedge funds, typically in the form of cash. But where would one get this cash and who would be give it to these hedgies. Well, it is the large commercial banks of course! The banks foresee the future and are playing the long game, they know Inflation is coming... Meanwhile the Fed has backed Treasury bonds! So, what the hedgies have done is actually outright buy treasury bonds and exchange them in a Swap through the Repo Market to gain additional liquidity. Of course banks get interest on that!. Hedge funds have been Re-hypothicating these treasury bills between one another and exchanging them for liquidity in a never ending loop to banks. At some point this strategy will run dry.

Visual Explanation of Repo Market

Chart courtesy of u/cyrus106

In the recent release by the Fed they explore alternative options to buying treasury bills as well there was such a problem with them in terms of their yields. So, it will be important to follow what the Fed does next as far as how they continue to prop up this economy. In a recent video Steven theorizes that the Fed is going to transition into long bonds market, which may not be good to the liquidity of said hedge funds as they seem almost entirely reliant on the Repo market to gain access to additional liquidity.

Steve explains Fed transition

Second, another strategy that's being used is the OTM options strategy or Doom Options as revealed by Dookie Dimez (Twitch). The credit risk is of significant importance in the current financial market. For instance, unlike most fina

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The "rostrum" of the new multi-purpose offshore patrol vessels [Italian PPA class]

This is an article published on the January 2021 issue of the Rivista Marittima, the official monthly magazine of the Marina Militare, the Italian Navy. It has been written by Captain Gabriele Catapano and Commander Mario De Biase.

I translated the article from Italian to English and, because the original is a little verbose and repetitive, I tried to adjust it for a more pleasant reading experience. No information was cut.


Launch of the Paolo Thaon di Revel PPA

The multi-purpose offshore patrol vessel [pattugliatore polivalente d'altura] (PPA), developed together with the LSS [logistical support ship] and LHD as part of the program for the safeguard of the maritime capability of the Defence, is an extremely complex and sophisticated ship able to conduct different types of missions, expressing first order operative capabilities. It is a vessel belonging to a new concept, created to guard and control the maritime spaces of national interest, to monitor maritime and economic activities, to contribute to the preservation of the maritime environment, to support rescue operations for the population in case of natural calamities and to take part in escorts for naval groups, major ships and merchant ships. All of this is to be undertaken by a single platform, for which three configurations of the combat system have been envisioned, respectively Light, Light+ and Full.
The necessity to integrate these numerous and complex capabilities on the same platform required the development of some innovative design features, like hull shapes and appendages that could satisfy the requirement for the fastest possible speed. As it is easily understood, significantly high speeds require, all other factors being equal (like hull dimensions, displacement, etc.), similarly high propulsive capacities.

In theory, the fundamental laws of hydrodynamics indicate that to limit the resistance to motion of a given hull and therefore to limit installed propulsion, the displacement being equal, it is necessary to increase the waterline length. It is in fact known that the resistance to motion R for a partly submerged body is essentially the sum of two main components: the friction resistance R^F connected to viscous phenomena (1) and the residual resistance R^R (which includes the so-called wave-making resistance) (2), connected to gravitational phenomena; this latter component, which is prevalent in the total amount of the resistance to motion

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