People are better at learning and decision-making when trying to avoid harm to others, according to new research published in JNeurosci. Humans are often motivated by self-interest. Participants in one study, for example, learned a game faster when they earned money for themselves as opposed to another person. However, this pattern changes when physical harm enters the equation. Lengersdorff et al. While in an fMRI scanner, participants played an electric shock game. They chose between two abstract symbols: one had a high chance of delivering a non-painful electrical shock while the other had a low chance of delivering a painful shock.
International Business Cycle Dates
Learn on-demand, earn credit, find products and solutions. All of this is a testament to the volatile environment caused by the coronavirus, and, while hospitals have shown some signs of incremental financial recovery in recent months, there’s no guarantee that these trends will continue. There’s still a long road ahead for those trying to recover from the steep losses incurred during the early months of the pandemic. July volumes continued to fall year-over-year, but showed some signs of potential recovery month-over-month.
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LaTeX mathematics works. Search interesting materials. Wednesday, September 07, Dating the Indian business cycle. Most macroeconomics is about business cycle fluctuations. The ultimate dream of macroeconomic policy is to use monetary policy and fiscal policy to reduce the amplitude of business cycle fluctuations, without contaminating the process of trend GDP growth. From an Indian policy perspective, this agenda is sketched in Shah and Patnaik The starting point of all these glamorous things, however, is measurement.
The major barrier to doing Indian macroeconomics is the lack of the foundations of business cycle measurement.
A college kid’s fake, AI-generated blog fooled tens of thousands. This is how he made it.
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The program has been uniquely designed to calculate which phase the Moon is passing through on any particular day. The cycle of Golden Numbers is the period after which moon phases repeat approximately on the same calendar dates. The illuminated fraction of the moon can be calculated with moonAngle in the oce package, as illustrated graphically and in R code below.
Some moon phases present better opportunities than others, with four significant moon events happening every day. At this phase, the lunar disk is not visible to the unaided eye, except when silhouetted during a solar eclipse. Implementing ELP consists of adding up a long series several thousand in the full model of sine and cosine terms. Algorithm This website is made possible and remain free by displaying online advertisements to our users. The date can vary as much as two days from that of the actual full moon, although the two intersect more often than not.
Gcal uses a very simple algorithm for detecting the Moon phase, which computes approximate values only. When the moon moves degrees it is known as paurnami or full moon and when the moon moves degrees it is known as amavaasai. Vincent liked Moon Phase Algorithm Questions Create the flowchart and algorithm for a module that will prompt the user to enter the amount of cash they have in their pocket.
Hospital operating margins are down 96% through July
Such a committee would not only strengthen the economy’s information base, it would bring greater clarity on the impact of employment during and after a growth recession. A recent slowdown in GDP has triggered talk of whether the Indian economy faces a possible growth recession. The conventional definition of a recession, which economists use, is two or more quarters of declining real GDP. But have you wondered how a macroeconomist identifies the trough or peaks in a business cycle or obtains the period of recession or expansion in an economy?
computer codes for the Bry-Boschan algorithm procedure in Mat Lab. The Levy Two other alternative algorithms used in the literature on business cycles to determine a. “A Comparison of Two Business Cycle Dating Methods.”.
For few months, a recurrent economic issue is the possible U. But there are also some similar questions in the euro area about potentially upcoming recessions, especially in Germany, an open economy that heavily depends on the global business cycle. In this post, I propose to assess the German business cycle based on standard tools often used in the business cycle literature. Predicting recessions is one of the biggest challenge for economists and even trying to identify recessions in real-time is not an easy job.
A first step is to be able to date historical business cycles, defined as the sequence of expansion and recession phases. A rule of thumb is to say that a country is in recession when it experiences two consecutive quarters of negative GDP growth. But in fact identifying a recession is a much more complicated task and needs to refer to the original NBER definition. A simple tool that proved to work quite well in the literature to date turning points is the Bry and Boschan algorithm that identifies peaks and trough in macro series by using simple rules, especially imposing minimum durations of phases 2 quarters and cycles 5 quarters, from peak to peak of trough to trough.
Very often an additional filter is applied to the resulting chronology in order to ensure that the recession is severe enough, severity being measured by 0. By using this Bry-Boschan algorithm on German GDP from q1 to q2, we get 7 recession periods; the dates from Peak P to Trough T being: qq1, qq4, qq4, qq1, qq1, qq1, qq1. Estimated historical recession periods for German GDP are presented in figure below shaded areas :.
It is noteworthy that the algorithm does not detect any peak over the recent quarters. Note also that the plain vanilla Bry-Boschan algorithm also provides two additional recessions in and
Brownian Bridge Excel We nd that both models can calculate non-zero short-term CDS spreads and that the second model generates upward sloping term structures over a long time horizon. The aim of this set of notes is to summarize some basic properties of the Brownian motion and Brownian bridge processes. The Black-Scholes model.
The Greeks for vanilla European options B. Simulate 5 paths of the Brownian motion B store them. High costs associated with financial data therefore offer another reason why authors from the same departments.
sbbq — Identify turning points in time series using the BBQ algorithm (Harding () to produce a business cycle dating algorithm based on quarterly data.
The last few months have been nothing short of a national nightmare. We are half a year into a global pandemic that has killed more than , Americans, forced over 55 million people to file for unemployment insurance, and has put millions of small American businesses at risk of permanently closing. At the same time, the nation is grappling with the effects of systemic racism in the wake of the murders of George Floyd, Breonna Taylor, Elijah McClain, and scores of other Black people at the hands of law enforcement.
As we reckon with the legacy of slavery, an ugly side of America that actively upholds racism threatens to undermine our pursuit of racial justice. Monopolies like Google, Facebook, and Amazon are quietly taking advantage of the ongoing chaos to continue amassing power and profit from national distress. Google, for example, wields a tight grip on the search and digital advertising markets that gives the company a financial incentive to promote hateful material.
Elon Musk Hints at New Battery Tech That Could Greatly Boost EV Range
characteristics led to the dating of business cycles and the distinction between from the PAT deviations for CI according to the algorithm developed by Bry and.
From Autoweek. A month ahead of its eagerly-anticipated Battery Day event, Tesla CEO Elon Musk sparked speculation with hints of new battery tech that could drastically improve the energy density of current batteries used in EVs, allowing for much longer ranges with the same general exterior dimensions and perhaps a lighter weight — two of the main limiting factors in today’s EVs.
One clue to what the EV maker could have in store for a September 22 reveal was shown on its own website announcing the event , leading some to speculate about a specific type of technology that Tesla and its research partners could be working on. The image on Tesla’s website displayed a background with a series of vertical filaments, prompting some to suggest Tesla could be researching silicon nanowire battery technology.
Elon Musk invited even more speculation on Monday this week, with a tweet suggesting batteries with far greater energy density were not too far on the horizon. Probably 3 to 4 years,” Musk tweeted. It remains to be seen just what Tesla has in store for Sept. And silicon nanowire filaments are just one of a few promising battery technologies making their way through the pipeline: Toyota promised a preview of solid-state battery tech at this year’s Olympic Games in Tokyo, games that had of course been postponed, ahead of a commercial rollout of long-awaited solid-state battery tech by the middle of the decade.
Solid-state batteries had long been seen as the holy grail of battery composition, replacing the heavy soup of metals and chemicals in current lithium-ion cells with a solid polymer of sorts, ideally yielding a higher energy density and a much lighter battery weight. EV battery technology has not seen a significant breakthrough for quite some time — progress has been incremental — while the biggest “gains” over the past five years have occurred in driving down the speed and cost of production, as well as in internal cooling.
Probably 3 to 4 years. A background image used in the invite represented either a carbon nanotube or silicon nanowire.
The RATS Software Forum
As artificial intelligence technologies are increasingly deployed by government and commercial entitles to generate automated and semi-automated decisions, the right to an explanation for such decisions has become a critical legal issue. This article considers the merits of enacting a statutory right to explanation for automated decisions. To this end, this article begins by considering a theoretical justification for a right to explanation, examines consequentialist and deontological approaches to protection and considers the appropriate ambit of such a right, comparing absolute transparency with partial transparency and counterfactual explanations.
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Key Words: growth cycle, reference date, composite index of business cycle and Boschan () algorithm and 50 point mark in the HDI for detecting turning.
By the end, the college student had used the AI model to produce an entirely fake blog under a fake name. It was meant as a fun experiment. But then one of his posts reached the number-one spot on Hacker News. Few people noticed that his blog was completely AI-generated. While many have speculated about how GPT-3, the most powerful language-generating AI tool to date, could affect content production, this is one of the only known cases to illustrate the potential.
In February of last year, OpenAI made headlines with GPT-2, an earlier version of the algorithm, which it announced it would withhold for fear it would be abused. The decision immediately sparked a backlash, as researchers accused the lab of pulling a stunt.