who plays mad eye moody in the harry potter movies

Harry Potter and the Goblet of Fire (film)

Michael Gambon as Albus Dumbledore:The headmaster of Hogwarts and one of the greatest wizards of all time. Gambon commented on the state of the character in the film: "Dumbledore is no longer in control and he's frightened." Newell compared Gambon's performance with Richard Harris' iteration in earlier films, showing the character as "fallible and not omnipotent" and "inadequate rather than super-adequate."
Brendan Gleeson as Alastor "Mad-Eye" Moody:A famous ex-Auror appointed by Dumbledore as the new Defence Against the Dark Arts teacher at Hogwarts. Gleeson referred to Moody as "a gunslinger with a wand," whose "great wounds have damaged him greatly." Heyman found Gleeson brought "a great balance of ferociousness and humour" to what he called a "complex, challenging character."
Jason Isaacs as Lucius Malfoy: Draco's father and a former Hogwarts pupil of Slytherin House. He is also a member of the Death Eaters. Isaacs didn't initially expect to be back in the fourth Harry Potter film, but felt nonetheless grateful to be able to "get the wig out of mothballs" while preparing for the next film, where he was slated to have a bigger role.
Gary Oldman as Sirius Black: Harry's godfather, who had escaped from Azkaban after being wrongly imprisoned for twelve years and is now a fugitive.
Alan Rickman as Severus Snape: The Potions teacher at Hogwarts and head of Slytherin.
Maggie Smith as Minerva McGonagall: Deputy Headmistress of Hogwarts, the Transfiguration teacher at Hogwarts and head of Gryffindor.
Timothy Spall as Peter Pettigrew / Wormtail: The Death Eater who betrayed Harry's parents to Voldemort.

Daniel Radcliffe

Daniel Jacob Radcliffe (born 23 July 1989) is an English actor. He rose to fame at age 12 when he began portraying Harry Potter in the film series of the same name. Radcliffe portrayed Potter in all eight films in the series, beginning with Harry Potter and the Philosopher's Stone (2001) and concluding with Harry Potter and the Deathly Hallows – Part 2 (2011).


when does jim propose to pam on the office

Jim Halpert

In "The Job," Jim, Karen, and Michael each interview for the corporate position. During the interview, he notices a caring note from Pam in his briefcase. After the interview he drives back to Scranton, leaving Karen without a ride. Back at the Scranton office, Pam is reflecting on her history with Jim, stating that they “never got the timing right” and were just “too similar”. Jim then suddenly interrupts the session to ask her out to dinner, much to her surprise. Flustered and overjoyed, Pam accepts the invitation.
Seasons 4–6
At the beginning of the season, it is revealed that Jim and Pam are dating, and that Karen had left the Scranton branch shortly after Jim breaks up with her.
In the episodes "Survivor Man" and "Night Out," Jim takes on his role as manager while Michael is out of the office. Both times, however, his attempts at making the office better go awry. Ryan, annoyed by Jim's popularity with his boss David Wallace, gives Jim a performance warning in "Did I Stutter?" citing "goofing off with Dwight" and "spending time at reception" as productivity problems, despite his high sale numbers.
In "Goodbye, Toby," Jim shows his happiness and support for Pam getting into the Pratt Institute, where she will be for the next three months. He plans to propose at Toby's going away party until Andy proposes in front of everybody to Angela, who accepts. Jim puts his ring back in his pocket and postpones the engagement. Instead, he proposes during the season-five premiere, "Weight Loss," during a rainy last-minute lunch date at an Interstate rest stop between Scranton and New York City, where Pam is attending Pratt.

The Thing About Pam

Jeff Ryan Baker as Louis Gumpenberger, a Missouri resident who is shot and killed by Pam.
Dateline journalist Keith Morrison provides the show's narration.
Episodes
Production
Development
On January 10, 2020, NBC announced its plans to shut down the unscripted production unit Peacock Productions. Variety reported that the decision was sparked by the rise of streaming services and a necessity for "higher-quality productions". In a statement, NBC said the company was "shifting its documentary strategy to an entirely new model" that would be "consistent with industry trends". Two weeks later, on January 23, NBC News Studios was launched. Liz Cole, executive producer of Dateline NBC and the then-president of Peacock Productions, announced she would also serve as president of the new company. The studio's intent is to produce content for emerging platforms, documentaries, docu-series, and select scripted programming. At the time of its announcement, NBC News Studios had already attained partnerships with Blumhouse Television and Focus Features, with the former revealing they were in negotiations to develop and produce scripted programs based on stories told on Dateline. In a statement, Cole said "the documentary business is certainly more robust than it ever has been. More and more people are seeking out that content".


Stackoverflow Stackexchange

Q: Website Payment Pro outside US My current online shop use PayPal express checkout (for credit card too) to charge users.
Our surveys (and A/B testing) showed that they are willing to make am order in a fewer step and without going to Paypal website.
We are based in Hong Kong so Website Payment Pro with DirectPayment can't be used.
Do you any other solution that could fit (i.e same level of pricing) our needs.
Small transactions (< 100 USD), need to fully integrate the solution within our shop for credit card (no redirection to another website)?
We will probably keep paypal as a backup solution for customers without credit cards.

A: Since PayPal indeed does not offer WPP in Hong Kong, I see just three options:

*

*Open a business in US/UK/Canada where WPP is available;

*Use a standard credit card payment provider, not PayPal;

*Keep using WPS.

I'm afraid that none of these are the same level of pricing and benefits though. :(

Unix Stackexchange

Q: Linux sort second last column I would like know how to sort the second last column ? It has the word "days=" in front of the number.  I'm able to get the column with awk '{print $(NF-1)}', but sorting is wrong.
    457000      (test2) && (SGD||RMB||HKD||YEN)    days=5000    71
    37622 (this is || test1)&&(SGD||HKD||RMB) days=630 40010
    43944 (this is)&&(SGD||HKD) days=80 102732
    79378 (this is||test2)&&(HKD||RMB)   days=800 205425

The result I'm looking for is
    43944 (this is)&&(SGD||HKD) days=80 102732
    37622 (this is || test1)&&(SGD||HKD||RMB) days=630 40010
    79378 (this is||test2)&&(HKD||RMB) days=800 205425
    457000      (test2) && (SGD||RMB||HKD||YEN)    days=5000    71

A: A bit hacky, but it ought to work:
awk '{print substr($(NF-1), 6), $0}' file | sort -g | cut -d' ' -f2-

It duplicates the second-to-last column at the front (dropping the days=), sorts numerically, and then removes the first column (the duplicated second-to-last one).


Stackoverflow Stackexchange

Q: Cooking Measurements in C# / F# Do any of you know a library for the representation and calculation of cooking units  (Cup, Tablespoon, Gallon...) in C# or F# (especially in regard to culture, metric/imperial)?

A: Units of measure are built into the F# language:
http://msdn.microsoft.com/en-us/library/dd233243.aspx
They can be easily extended with custom units, as long as you know conversion ratios.
Edit: Of course, you might end up with some strange unit types to account between differences in weights and volumes (the ratio of 1 cup of flour to 1 cup of water is not the same as the ratio of 100g of flour to 100g of water...)

Superuser Stackexchange

Q: Measure object in a photo, without a smartphone I see a number of apps for measuring size of objects in photos -- if one has a smart phone. I don't. Are there any online services which can do same? Or program for Windows PC?
No 100mb trial ware or demo's please as I only need it for one job, namely getting the surface dimensions of a table:

A: You can use KLONK Image Measurement for this task.
You first take a picture of table in a perpendicular angle on what you want to measure. On the image you must place an object which you know the size of.
And then you aquire it into the application, calibrate according to the object and the measure what you need to measure.


A paper that achieved human-level performance on the WikiSQL dataset using table-aware word contextualization.

Title: A Comprehensive Exploration on WikiSQL with Table-Aware Word Contextualization

Abstract: We present SQLova, the first Natural-language-to-SQL (NL2SQL) model to achieve human performance in WikiSQL dataset. We revisit and discuss diverse popular methods in NL2SQL literature, take a full advantage of BERT {Devlin et al., 2018) through an effective table contextualization method, and coherently combine them, outperforming the previous state of the art by 8.2% and 2.5% in logical form and execution accuracy, respectively. We particularly note that BERT with a seq2seq decoder leads to a poor performance in the task, indicating the importance of a careful design when using such large pretrained models. We also provide a comprehensive analysis on the dataset and our model, which can be helpful for designing future NL2SQL datsets and models. We especially show that our model's performance is near the upper bound in WikiSQL, where we observe that a large portion of the evaluation errors are due to wrong annotations, and our model is already exceeding human performance by 1.3% in execution accuracy.


Title: Pay Attention: a Call to Regulate the Attention Market and Prevent Algorithmic Emotional Governance

Abstract: Over the last 70 years, we, humans, have created an economic market where attention is being captured and turned into money thanks to advertising. During the last two decades, leveraging research in psychology, sociology, neuroscience and other domains, Web platforms have brought the process of capturing attention to an unprecedented scale. With the initial commonplace goal of making targeted advertising more effective, the generalization of attention-capturing techniques and their use of cognitive biases and emotions have multiple detrimental side effects such as polarizing opinions, spreading false information and threatening public health, economies and democracies. This is clearly a case where the Web is not used for the common good and where, in fact, all its users become a vulnerable population. This paper brings together contributions from a wide range of disciplines to analyze current practices and consequences thereof. Through a set of propositions and principles that could be used do drive further works, it calls for actions against these practices competing to capture our attention on the Web, as it would be unsustainable for a civilization to allow attention to be wasted with impunity on a world-wide scale.

Title: Phenotypical Behavior and Evolutionary Slavery

Abstract: A new evolutionary solution to Prisoner Dilemma situations is proposed in this paper. A specific genetic code may have different phenotypes, meaning different strategies for different individuals carrying that gene. This means that, under the right parameters, it is a good evolutionary solution to create two types of phenotypes with different strategies, here called as leaders and servants. In this solution, servants always cooperate with the leaders and leaders never do with the servants. Inside the same class, the usual strategies apply. Possible applications of this solution are discussed.


Title: A study on speech enhancement using exponent-only floating point quantized neural network (EOFP-QNN)

Abstract: Numerous studies have investigated the effectiveness of neural network quantization on pattern classification tasks. The present study, for the first time, investigated the performance of speech enhancement (a regression task in speech processing) using a novel exponent-only floating-point quantized neural network (EOFP-QNN). The proposed EOFP-QNN consists of two stages: mantissa-quantization and exponent-quantization. In the mantissa-quantization stage, EOFP-QNN learns how to quantize the mantissa bits of the model parameters while preserving the regression accuracy using the least mantissa precision. In the exponent-quantization stage, the exponent part of the parameters is further quantized without causing any additional performance degradation. We evaluated the proposed EOFP quantization technique on two types of neural networks, namely, bidirectional long short-term memory (BLSTM) and fully convolutional neural network (FCN), on a speech enhancement task. Experimental results showed that the model sizes can be significantly reduced (the model sizes of the quantized BLSTM and FCN models were only 18.75% and 21.89%, respectively, compared to those of the original models) while maintaining satisfactory speech-enhancement performance.

Title: Simple and Efficient Quantization Techniques for Neural Speech Coding

Abstract: Neural audio coding has emerged as a vivid research direction by promising good audio quality at very low bitrates unachievable by classical coding techniques. Here, end-to-end trainable autoencoder-like models represent the state of the art, where a discrete representation in the bottleneck of the autoencoder has to be learned that allows for efficient transmission of the input audio signal. This discrete representation is typically generated by applying a quantizer to the output of the neural encoder. In almost all state-of-the-art neural audio coding approaches, this quantizer is realized as a Vector Quantizer (VQ) and a lot of effort has been spent to alleviate drawbacks of this quantization technique when used together with a neural audio coder. In this paper, we propose simple alternatives to VQ, which are based on projected Scalar Quantization (SQ). These quantization techniques do not need any additional losses, scheduling parameters or codebook storage thereby simplifying the training of neural audio codecs. Furthermore, we propose a new causal network architecture for neural speech coding that shows good performance at very low computational complexity.


Nostalgia for the Soviet Union

Many of the ex-Soviet republics suffered economic collapse upon the dissolution, resulting in lowered living standards, increased mortality rates, devaluation of national currencies, and rising income inequality. Chaotic neoliberal market reforms, privatization, and austerity measures urged by Western economic advisers, including Lawrence Summers, and the International Monetary Fund (IMF) were often blamed by the populace of the former Soviet states for exacerbating the problem. Between 1991 and 1994, a third of Russia's population was plunged into poverty, and between 1994 and 1998 this figure increased to over half the population. Most of the Soviet state enterprises were acquired and liquidated by Russian business oligarchs as part of the privatization campaign, which rendered large segments of the ex-Soviet workforce unemployed and impoverished. Capital gains made in post-Soviet Russia during the 1990s were mostly concentrated in the hands of oligarchs who benefited from the acquisition of state assets, while the majority of the population suffered severe economic hardship.
According to Kristen Ghodsee, a researcher on post-communist Eastern Europe:
Among the working poor, Soviet nostalgia is often directly linked to the guarantee of state employment and regular salaries. The collapse of Soviet state enterprises and contraction of the public sector after the dissolution resulted in widespread unemployment. With the disappearance of the Soviet industrial complex, as much as half the working class of the former USSR lost their jobs during the 1990s. One study of rural Georgians in the early 2000s found that the vast majority yearned for a return to the security of their public sector jobs, even those that did not favor a return to the centrally planned economy. They attributed their poverty to the demise of the Soviet state, which in turn resulted in the widespread association of stability with the Soviet era and lack of confidence in the post-Soviet governments. A related study of working class Kyrgyz women in the same time frame found that most remembered the Soviet era primarily for its low levels of unemployment.

Dissolution of the Soviet Union

In a similar poll held in February 2005, 50% of respondents in Ukraine stated they regretted the disintegration of the Soviet Union. In 2013, according to Gallup, 56% of Ukrainians said that the dissolution of the Soviet Union did more harm than good, with only 23% saying it did more good than harm. However, a similar poll conducted in 2016 by a Ukrainian group showed only 35% Ukrainians regretting the Soviet collapse and 50% not regretting it.
The breakdown of economic ties that followed the Soviet collapse led to a severe economic crisis and catastrophic fall in the standard of living in post-Soviet states and the former Eastern Bloc, which was even worse than the Great Depression. An estimated seven million premature deaths took place in the former USSR after it collapsed, with around four million in Russia alone. Poverty and economic inequality surged between 1988 and 1989 and between 1993 and 1995, with the Gini ratio increasing by an average of 9 points for all former socialist countries. Even before the 1998 Russian financial crisis, the Russian GDP was half of what it had been in the early 1990s. By 1999, around 191 million people in post-Soviet states and former Eastern Bloc countries were living on less than $5.50 a day.


how to connect two monitors to one thunderbolt?

Apple Stackexchange

Q: does thunderbolt support connecting multiple computers to a monitor I'm planning to get a new Mac mini server plus a mac book pro.
I would like information about Thunderbolt support for connecting two computers to a single display, i.e. in my case the Mac mini to the Thunderbolt display port and simultaneously the Mac Book pro with the Thunderbolt cable.

A: Do you mean multiple inputs (like a TV)? In that case, no. The Thunderbolt display supports one input but allows you to chain additional displays or drives using the Thunderbolt port on the back of the display.

Apple Stackexchange

Q: is it possible to connect two external monitors with mini displayport + thunderbolt to displayport or hdmi? I've heard that thunderbolt can be used as a displayport. That make me wonder if I can use two external monitors with mini displayport and thunderbolt to displayport or hdmi.
Is it possible??

A: The thunderbolt port and display port are the same port.  So it's not two separate ports.
That said, due to the high bandwidth nature of thunderbolt, I suspect we will be able to daisy chain monitors in the future, as well as having thunderbolt "hubs" where multiple devices can be plugged in.
But for now, it's one port.  So only one external monitor.


Breakfast

Breakfast is the first meal of the day usually eaten in the morning. The word in English refers to breaking the fasting period of the previous night. Various "typical" or "traditional" breakfast menus exist, with food choices varying by regions and traditions worldwide.
History
In Old English, a regular morning meal was called , and the word dinner, which originated from Gallo-Romance desjunare ("to break one's fast"), referred to a meal after fasting. Around mid-13 century, that meaning of dinner faded away, and around 15th century "breakfast" came into use in written English to describe a morning meal.
Ancient breakfast
Ancient Egypt
In Ancient Egypt, peasants ate a daily meal, most likely in the morning, consisting of soup, beer, bread, and onions before they left for work in the fields or work commanded by the pharaohs.

Meal

Breakfast Breakfast is the first meal of a day, most often eaten in the early morning before undertaking the day's work. Some believe it to be the most important meal of the day. The word breakfast literally refers to breaking the fasting period of the prior night.
Breakfast foods vary widely from place to place, but often include carbohydrates such as grains or cereals, fruit, vegetables, protein foods like eggs, meat or fish, and beverages such as tea, coffee, milk, or fruit juice, juices often taken first of all. Coffee, milk, tea, juice, breakfast cereals, pancakes, waffles, sausages, French toast, bacon, sweetened breads, fresh fruits, vegetables, eggs, baked beans, muffins, crumpets and toast with butter, margarine, jam or marmalade are common examples of Western breakfast foods, though a large range of preparations and ingredients are associated with breakfast globally.
Variations of breakfast
Full breakfast
A full breakfast is a breakfast meal, usually including bacon, sausages, eggs, and a variety of other cooked foods, with hot beverages such as coffee or tea, or cold beverages such as juice or milk. It is especially popular in the UK and Ireland, to the extent that many cafés and pubs offer the meal at any time of day as an "all-day breakfast". It is also popular in other English-speaking countries.


Theorbo

The theorbo is a plucked string instrument of the lute family, with an extended neck that houses the second pegbox. Like a lute, a theorbo has a curved-back sound box with a flat top, typically with one or three sound holes decorated with rosettes. As with the lute, the player plucks or strums the strings with the right hand while "fretting" (pressing down) the strings with the left hand.
The theorbo is related to the liuto attiorbato, the French , the archlute, the German baroque lute, and the angélique (or angelica). A theorbo differs from a regular lute in its so-called re-entrant tuning in which the first two strings are tuned an octave lower. The theorbo was used during the Baroque music era (1600–1750) to play basso continuo accompaniment parts (as part of the basso continuo group, which often included harpsichord, pipe organ and bass instruments), and also as a solo instrument. It has a range similar to that of cello.

Modulor

History Le Corbusier developed the Modulor in the long tradition of Vitruvius, Leonardo da Vinci's Vitruvian Man, the work of Leon Battista Alberti, and other attempts to discover mathematical proportions in the human body and then to use that knowledge to improve both the appearance and function of architecture. The system is inspired by but does not exactly correspond to human measurements, and it also draws inspiration from the double unit, the Fibonacci numbers, and the golden ratio. Le Corbusier described it as a "range of harmonious measurements to suit the human scale, universally applicable to architecture and to mechanical things".
With the Modulor, Le Corbusier sought to introduce a scale of visual measures that would unite two virtually incompatible systems: the Anglo-Saxon foot and inch and the international metric system. Whilst he was intrigued by ancient civilisations who used measuring systems linked to the human body: elbow (cubit), finger (digit), thumb (inch) etc., he was troubled by the metre as a measure that was a forty-millionth part of the meridian of the earth.
In 1943, in response to the French National Organisation for Standardisation's (AFNOR) requirement for standardising all the objects involved in the construction process, Le Corbusier asked an apprentice to consider a scale based upon a man with his arm raised to 2.20 m in height. The result, in August 1943 was the first graphical representation of the derivation of the scale. This was refined after a visit to the Dean of the Faculty of Sciences in Sorbonne on 7 February 1945 which resulted in the inclusion of a golden section into the representation.


Bee

The thorax has three segments, each with a pair of robust legs, and a pair of membranous wings on the hind two segments. The front legs of corbiculate bees bear combs for cleaning the antennae, and in many species the hind legs bear pollen baskets, flattened sections with incurving hairs to secure the collected pollen. The wings are synchronised in flight, and the somewhat smaller hind wings connect to the forewings by a row of hooks along their margin which connect to a groove in the forewing.
The abdomen has nine segments, the hindermost three being modified into the sting.
The largest species of bee is thought to be Wallace's giant bee Megachile pluto, whose females can attain a length of . The smallest species may be dwarf stingless bees in the tribe Meliponini whose workers are less than  in length.
Sociality
Haplodiploid breeding system
According to inclusive fitness theory, organisms can gain fitness not just through increasing their own reproductive output, but also that of close relatives. In evolutionary terms, individuals should help relatives when Cost < Relatedness * Benefit. The requirements for eusociality are more easily fulfilled by haplodiploid species such as bees because of their unusual relatedness structure.

Bee hummingbird

The bee hummingbird, zunzuncito or Helena hummingbird (Mellisuga helenae) is a species of hummingbird, native to the island of Cuba in the Caribbean. It is the smallest known bird. The bee hummingbird feeds on nectar of flowers and bugs found in Cuba.
Description
The bee hummingbird is the smallest living bird. Females weigh  and are  long, and are slightly larger than males, which have an average weight of  and length of . Like all hummingbirds, it is a swift, strong flier.


What's the purpose of `if __name__ == '__main__'`?

Stackoverflow Stackexchange

Q: What does `if name == "__main__"` mean in Python?
Possible Duplicate:
What does <if name==“main”:> do?

I have wrote scripts in Python for quite a while now and I study more of Python as I need it. When reading other people's code I meet if name == "__main__": construct quite often.
What is it good for?

A: Basically,
There's a distinction between the "main" script file and external files which were imported or referenced in another way. If the script is the "main" script then the special variable __name__ will equal "__main__".
You can use this to protect the "execution" code from the classes and variables the script has. This enables you to import a script and use classes and variables without actually running that script's main code if it has any.
See also: What does if name == “main”: do?

Stackoverflow Stackexchange

Q: Why does it do this ? if - __name__ == '__main__'
Duplicate of:
What does if __name__== "__main__" do?

Consider this code:
if __name__ == '__main__':
    import pdb
    pdb.run("interact()\n")

What does the following line mean?
if(__name__=='__main__')

I fainted.

A: That is a check to see if you are directly running the script or if it is included in a library.
When you run a python script like this:
python myScript.py

It sends a parameter, telling you to run the programs first method, which is widely called "main", so when __name__ is __main__ you know that the program was executed from a command line or double clicked.


Which test was devised to determine whether robots can think?

Chinese room

Searle does not disagree that AI research can create machines that are capable of highly intelligent behavior. The Chinese room argument leaves open the possibility that a digital machine could be built that acts more intelligently than a person, but does not have a mind or intentionality in the same way that brains do.
Searle's "strong AI hypothesis" should not be confused with "strong AI" as defined by Ray Kurzweil and other futurists, who use the term to describe machine intelligence that rivals or exceeds human intelligence -- that is, artificial general intelligence, human level AI or superintelligence. Kurzweil is referring primarily to the amount of intelligence displayed by the machine, whereas Searle's argument sets no limit on this. Searle argues that a superintelligent machine would not necessarily have a mind and consciousness.
Turing test
The Chinese room implements a version of the Turing test. Alan Turing introduced the test in 1950 to help answer the question "can machines think?" In the standard version, a human judge engages in a natural language conversation with a human and a machine designed to generate performance indistinguishable from that of a human being. All participants are separated from one another. If the judge cannot reliably tell the machine from the human, the machine is said to have passed the test.

Turing test

The Turing test, originally called the imitation game by Alan Turing in 1950, is a test of a machine's ability to exhibit intelligent behaviour equivalent to, or indistinguishable from, that of a human. Turing proposed that a human evaluator would judge natural language conversations between a human and a machine designed to generate human-like responses. The evaluator would be aware that one of the two partners in conversation was a machine, and all participants would be separated from one another. The conversation would be limited to a text-only channel, such as a computer keyboard and screen, so the result would not depend on the machine's ability to render words as speech. If the evaluator could not reliably tell the machine from the human, the machine would be said to have passed the test. The test results would not depend on the machine's ability to give correct answers to questions, only on how closely its answers resembled those a human would give. Since the Turing test is a test of indistinguishability in performance capacity, the verbal version generalizes naturally to all of human performance capacity, verbal as well as nonverbal (robotic).


Find me a planet near α 23h 06m 29.368s and δ −05° 02′ 29.04″ that could be habitable.

Eyeball planet

An eyeball planet is a hypothetical type of tidally locked planet, for which tidal locking induces spatial features (for example in the geography or composition of the planet) resembling an eyeball. They are terrestrial planets where liquids may be present, in which tidal locking will induce a spatially dependent temperature gradient (the planet will be hotter on the side facing the star and colder on the other side). This temperature gradient may therefore limit the places in which liquid may exist on the surface of the planet to ring-or disk-shaped areas.
Such planets are further divided into "hot" and "cold" eyeball planets, depending on which side of the planet the liquid is present. A "hot" eyeball planet is usually closer to its host star, and the centre of the "eye", facing the star (day side), is made of rock while liquid is present on the opposite side (night side). A "cold" eyeball planet, usually farther from the star, will have liquid on the side facing the host star while the rest of its surface is made of ice and rocks.
Because most planetary bodies have a natural tendency toward becoming tidally locked to their host body on a long enough timeline, eyeball planets may be common and could host life, particularly in planetary systems orbiting red and brown dwarf stars which have lifespans much longer than other main sequence stars.
Potential candidates
Kepler-1652b is potentially an eyeball planet. The TRAPPIST-1 system may contain several such planets.

Alpha Centauri

In 2009, computer simulations showed that a planet might have been able to form near the inner edge of Alpha Centauri B's habitable zone, which extends from  from the star. Certain special assumptions, such as considering that the Alpha Centauri pair may have initially formed with a wider separation and later moved closer to each other (as might be possible if they formed in a dense star cluster), would permit an accretion-friendly environment farther from the star. Bodies around Alpha Centauri A would be able to orbit at slightly farther distances due to its stronger gravity. In addition, the lack of any brown dwarfs or gas giants in close orbits around Alpha Centauri make the likelihood of terrestrial planets greater than otherwise. A theoretical study indicates that a radial velocity analysis might detect a hypothetical planet of  in Alpha Centauri B's habitable zone.
Radial velocity measurements of Alpha Centauri B made with the High Accuracy Radial Velocity Planet Searcher spectrograph were sufficiently sensitive to detect a  planet within the habitable zone of the star (i.e. with an orbital period P = 200 days), but no planets were detected.
Current estimates place the probability of finding an Earth-like planet around Alpha Centauri at roughly 75%. The observational thresholds for planet detection in the habitable zones by the radial velocity method are currently (2017) estimated to be about  for Alpha Centauri A,  for Alpha Centauri B, and  for Proxima Centauri.
Early computer-generated models of planetary formation predicted the existence of terrestrial planets around both Alpha Centauri A and B, but most recent numerical investigations have shown that the gravitational pull of the companion star renders the accretion of planets difficult. Despite these difficulties, given the similarities to the Sun in spectral types, star type, age and probable stability of the orbits, it has been suggested that this stellar system could hold one of the best possibilities for harbouring extraterrestrial life on a potential planet.


History of robots

It features a female humanoid automaton standing by a basin filled with water.When the user pulls the lever, the water drains and the female automaton refills the basin. Furthermore, he created a robotic musical band. According to Mark Rosheim, unlike Greek designs Arab automata worked with dramatic illusion and manipulated the human perception for practical application. The segmental gears described in The Book of Knowledge of Ingenious Mechanical Devices, published by Al-Jazari shortly before his death in 1206, appeared 100 years later in the most advanced European clocks. Al-Jazari also published instructions on the construction of humanoid automata. The first water clocks modeled on Arabic designs were constructed in Europe about 1000 CE, possibly on the basis of the information that was transmitted during Muslim-Christian contact in Sicily and Spain. Among the first recorded European water clocks is that of Gerbert of Aurillac, built in 985 CE. Hero's works on automata were translated into Latin amid the 12th century Renaissance. The early 13th-century artist-engineer Villard de Honnecourt sketched plans for several automata.

Turing test

The test was introduced by Turing in his 1950 paper "Computing Machinery and Intelligence" while working at the University of Manchester. It opens with the words: "I propose to consider the question, 'Can machines think? Because "thinking" is difficult to define, Turing chooses to "replace the question by another, which is closely related to it and is expressed in relatively unambiguous words." Turing describes the new form of the problem in terms of a three-person game called the "imitation game", in which an interrogator asks questions of a man and a woman in another room in order to determine the correct sex of the two players. Turing's new question is: "Are there imaginable digital computers which would do well in the imitation game?" This question, Turing believed, was one that could actually be answered. In the remainder of the paper, he argued against all the major objections to the proposition that "machines can think".
Since Turing introduced his test, it has been both highly influential and widely criticized, and has become an important concept in the philosophy of artificial intelligence. Philosopher John Searle would comment on the Turing test in his Chinese room argument, a thought experiment that stipulates that a machine cannot have a "mind", "understanding", or "consciousness", regardless of how intelligently or human-like the program may make the computer behave. Searle criticizes Turing's test and claims it is insufficient to detect the presence of consciousness.
History


A comprehensive study on introducing backdoors to pre-trained NLP models affecting multiple downstream tasks.

Title: BadPre: Task-agnostic Backdoor Attacks to Pre-trained NLP Foundation Models

Abstract: Pre-trained Natural Language Processing (NLP) models can be easily adapted to a variety of downstream language tasks. This significantly accelerates the development of language models. However, NLP models have been shown to be vulnerable to backdoor attacks, where a pre-defined trigger word in the input text causes model misprediction. Previous NLP backdoor attacks mainly focus on some specific tasks. This makes those attacks less general and applicable to other kinds of NLP models and tasks. In this work, we propose \Name, the first task-agnostic backdoor attack against the pre-trained NLP models. The key feature of our attack is that the adversary does not need prior information about the downstream tasks when implanting the backdoor to the pre-trained model. When this malicious model is released, any downstream models transferred from it will also inherit the backdoor, even after the extensive transfer learning process. We further design a simple yet effective strategy to bypass a state-of-the-art defense. Experimental results indicate that our approach can compromise a wide range of downstream NLP tasks in an effective and stealthy way.

Title: Backdoor Learning for NLP: Recent Advances, Challenges, and Future Research Directions

Abstract: Although backdoor learning is an active research topic in the NLP domain, the literature lacks studies that systematically categorize and summarize backdoor attacks and defenses. To bridge the gap, we present a comprehensive and unifying study of backdoor learning for NLP by summarizing the literature in a systematic manner. We first present and motivate the importance of backdoor learning for building robust NLP systems. Next, we provide a thorough account of backdoor attack techniques, their applications, defenses against backdoor attacks, and various mitigation techniques to remove backdoor attacks. We then provide a detailed review and analysis of evaluation metrics, benchmark datasets, threat models, and challenges related to backdoor learning in NLP. Ultimately, our work aims to crystallize and contextualize the landscape of existing literature in backdoor learning for the text domain and motivate further research in the field. To this end, we identify troubling gaps in the literature and offer insights and ideas into open challenges and future research directions. Finally, we provide a GitHub repository with a list of backdoor learning papers that will be continuously updated at https://github.com/marwanomar1/Backdoor-Learning-for-NLP.


who has won the most united states championships

List of players who have won the most NFL championships

Seven championships Tom Brady (quarterback) won Super Bowls XXXVI, XXXVIII, XXXIX, XLIX, LI, and LIII with the New England Patriots after the 2001, 2003, 2004, 2014, 2016, and 2018 seasons, respectively. He won Super Bowl LV with the Tampa Bay Buccaneers after the 2020 season.
Six championships
Three players have won six championships counting the pre-Super Bowl era. To avoid double counting from 1966 to 1969, only the NFL championships from 1920–1965 and the Super Bowls from 1966 onward are counted.
Fuzzy Thurston (offensive lineman) won the NFL championships with the Baltimore Colts in 1958, with the Green Bay Packers in 1961, 1962 and 1965, and won Super Bowls I and II with the Packers after the 1966 and 1967 seasons, respectively.
Forrest Gregg (offensive lineman) won the NFL championships with the Green Bay Packers in 1961, 1962 and 1965, Super Bowls I and II with the Packers after the 1966 and 1967 seasons, respectively, and Super Bowl VI with the Dallas Cowboys after the 1971 season.
Herb Adderley (defensive back) won the NFL championships with the Green Bay Packers in 1961, 1962 and 1965, Super Bowls I and II with the Packers after the 1966 and 1967 seasons, respectively, and Super Bowl VI with the Dallas Cowboys after the 1971 season.
Five championships
13 players have won 5 championships counting the pre-Super Bowl era; with the exception of Charles Haley, all were from the 1960s Packers.

WWE United States Championship

Reigns The inaugural champion was Harley Race. There have been 102 different champions, with Ric Flair having the most reigns at six. The longest-reigning champion is Lex Luger, who held the title for 523 days from May 22, 1989, to October 27, 1990. "Stunning" Steve Austin's second reign was the shortest, lasting approximately five minutes. Dean Ambrose is the longest-reigning champion under the WWE banner at 351 days, lasting from May 19, 2013, to May 5, 2014. Booker T and Seth Rollins are the only two men to have held both the United States Championship and a world championship simultaneously; in Booker T's case, the world title was the WCW World Heavyweight Championship, while Rollins held the WWE World Heavyweight Championship (both Lex Luger and Goldberg were the United States Champion when they won their first world championship, but unlike Booker T and Rollins, they vacated the United States Championship after winning their world championships). Terry Funk is the oldest champion in the title's history, winning the title at the age of 56 on September 22, 2000, while David Flair is the youngest at the age of 20 on July 5, 1999. Between NWA/WCW and WWE, the title has been vacated 21 times.
Logan Paul is the current champion in his first reign. He defeated Rey Mysterio at Crown Jewel on November 4, 2023, in Riyadh, Saudi Arabia.


how did the sword of gryffindor get back to hogwarts?

Scifi Stackexchange

Q: Why didn't Voldemort create a Horcrux with a Gryffindor heirloom? Voldemort was said to be very interested in the four founders of Hogwarts. He created a Horcrux from the Ravenclaw diadem, the Hufflepuff cup, and the Slytherin locket. Did he try to find a Gryffindor relic to complete the set, or did he not bother?
I can't see him giving up on such a task, but maybe there was insufficient time.
Gryffindor's sword was hiding 'inside' the Sorting Hat, but a famous family usually has some other heirlooms too.
If there are no canon answers I'd be interested in your own speculation!

A: Even though he probably didn't realize it, he did have a Horcrux in each house.

*

*The Locket/Slytherin.

*The Cup/Hufflepuff.

*The Diadem/Ravenclaw.

*Harry Potter/Gryffindor.

Scifi Stackexchange

Q: How does Neville Longbottom get the Sword of Gryffindor? I recently read the final book of the series. At one point was the vault heist, where the goblin Griphook runs off with the Sword of Gryffindor. Yet near the end of the book, Neville Longbottom suddenly has the sword and uses it to defeat the snake Nagini.
How could this be possible? Griphook wanted the sword because it was goblin-made, so I doubt he would given it over to any non-goblin. How does Neville suddenly get the sword?

A: In the movie the sword materialises (from the hat??), which backs up the "it shows up just as a true Gryffindor needs it" idea. In Pottermore [SPOILER] JKR writes about the Sorting Hat being very adamant about placing Neville in Gryffindor (despite his hesitations), which adds some credence to "true Gryffindor".


who took over the dutch colony in north america

Dutch colonial empire

On the north-east coast of North America, the West India Company took over a settlement that had been established by the Company of New Netherland (1614–1618) at Fort Orange at Albany on the Hudson River, relocated from Fort Nassau which had been founded in 1614. The Dutch had been sending ships annually to the Hudson River to trade fur since Henry Hudson's voyage of 1609. To protect its precarious position at Albany from the nearby English and French, the Company founded the fortified town of New Amsterdam in 1625, at the mouth of the Hudson, encouraging settlement of the surrounding areas of Long Island and New Jersey. The fur trade ultimately proved impossible for the company to monopolize due to the massive illegal private trade in furs, and the settlement of New Netherland was unprofitable. In 1655, the nearby colony of New Sweden on the Delaware River was forcibly absorbed into New Netherland after ships and soldiers were sent to capture it by the Dutch governor, Pieter Stuyvesant.
Since its inception, the Dutch East India Company had been in competition with its counterpart, the English East India Company, founded two years earlier but with a capital base eight times smaller, for the same goods and markets in the East. In 1619, the rivalry resulted in the Amboyna massacre, when several English Company men were executed by agents of the Dutch. The event remained a source of English resentment for several decades, and indeed was used as a cause célèbre as late as the Second Anglo-Dutch War in the 1660s; nevertheless, in the late 1620s the English Company shifted its focus from Indonesia to India.

European colonization of the Americas

Dutch The Netherlands had been part of the Spanish Empire, due to the inheritance of Charles V of Spain. Many Dutch people converted to Protestantism and sought their political independence from Spain. They were a seafaring nation and built a global empire in regions where the Portuguese had originally explored. In the Dutch Golden Age, it sought colonies. In the Americas, the Dutch conquered the northeast of Brazil in 1630, where the Portuguese had built sugar cane plantations worked by black slave labor from Africa. Prince Johan Maurits van Nassau-Siegen became the administrator of the colony (1637–43), building a capital city and royal palace, fully expecting the Dutch to retain control of this rich area. As the Dutch had in Europe, it tolerated the presence of Jews and other religious groups in the colony. After Maurits departed in 1643, the Dutch West India Company took over the colony, until it was lost to the Portuguese in 1654. The Dutch retained some territory in Dutch Guiana, now Suriname. The Dutch also seized islands in the Caribbean that Spain had originally claimed but had largely abandoned, including Sint Maarten in 1618, Bonaire in 1634, Curaçao in 1634, Sint Eustatius in 1636, Aruba in 1637, some of which remain in Dutch hands and retain Dutch cultural traditions.


Vaporwave

Vaporwave was subsumed under a larger "Tumblr aesthetic" that had become fashionable in underground digital music and art scenes of the 2010s. In 2010, Lopatin included several of the tracks from Memory Vague, as well as a few new ones, on his album Chuck Person's Eccojams Vol. 1, released in August under the alias "Chuck Person". With packaging that resembled the 1993 video game Ecco the Dolphin, the album inspired a host of suburban teens and young adults to formulate what would become vaporwave. Seapunk followed in mid-2011 as an aquatic-themed Tumblr subculture and Internet meme that presaged vaporwave in its concern for "spacey" electronic music and Geocities web graphics. Like vaporwave, it was defined by its engagement with the Internet, an approach that is sometimes described as post-Internet.
The musical template for vaporwave came from Eccojams and Ferraro's Far Side Virtual (October 2011). Eccojams featured chopped and screwed variations on popular 1980s pop songs, while Far Side Virtual drew primarily on "the grainy and bombastic beeps" of past media such as Skype and the Nintendo Wii. According to Stereogums Miles Bowe, vaporwave was a fusion between Lopatin's "chopped and screwed plunderphonics" and the "nihilistic easy-listening of James Ferraro's Muzak-hellscapes". A 2013 post on a music blog presented those albums, along with Skeleton's Holograms (November 2010), as "proto vaporwave".

Vaporwave

Vaporwave is a microgenre of electronic music and a subgenre of hauntology, a visual art style, and an Internet meme that emerged in the early 2010s, and became well-known in 2015. It is defined partly by its slowed-down, chopped and screwed samples of smooth jazz, 1970s elevator music, R&B, and lounge music from the 1980s and 1990s. The surrounding subculture is sometimes associated with an ambiguous or satirical take on consumer capitalism and pop culture, and tends to be characterized by a nostalgic or surrealist engagement with the popular entertainment, technology and advertising of previous decades. Visually, it incorporates early Internet imagery, late 1990s web design, glitch art, anime, stylized Greek sculptures, 3D-rendered objects, and cyberpunk tropes in its cover artwork and music videos.
Vaporwave originated as an ironic variant of chillwave, evolving from hypnagogic pop as well as similar retro-revivalist and post-Internet motifs that had become fashionable in underground digital music and art scenes of the era, such as Tumblr's seapunk. The style was pioneered by producers such as James Ferraro, Daniel Lopatin and Ramona Xavier, who each used various pseudonyms. After Xavier's album Floral Shoppe (2011) established a blueprint for the genre, the movement built an audience on sites Last.fm, Reddit and 4chan while a flood of new acts, also operating under online pseudonyms, turned to Bandcamp for distribution.


Title: Toward Stance-based Personas for Opinionated Dialogues

Abstract: In the context of chit-chat dialogues it has been shown that endowing systems with a persona profile is important to produce more coherent and meaningful conversations. Still, the representation of such personas has thus far been limited to a fact-based representation (e.g. "I have two cats."). We argue that these representations remain superficial w.r.t. the complexity of human personality. In this work, we propose to make a step forward and investigate stance-based persona, trying to grasp more profound characteristics, such as opinions, values, and beliefs to drive language generation. To this end, we introduce a novel dataset allowing to explore different stance-based persona representations and their impact on claim generation, showing that they are able to grasp abstract and profound aspects of the author persona.

Title: A Persona-Based Neural Conversation Model

Abstract: We present persona-based models for handling the issue of speaker consistency in neural response generation. A speaker model encodes personas in distributed embeddings that capture individual characteristics such as background information and speaking style. A dyadic speaker-addressee model captures properties of interactions between two interlocutors. Our models yield qualitative performance improvements in both perplexity and BLEU scores over baseline sequence-to-sequence models, with similar gains in speaker consistency as measured by human judges.


Aardvark

Habitat and range Aardvarks are found in sub-Saharan Africa, where suitable habitat (savannas, grasslands, woodlands and bushland) and food (i.e., ants and termites) is available. They spend the daylight hours in dark burrows to avoid the heat of the day. The only major habitat that they are not present in is swamp forest, as the high water table precludes digging to a sufficient depth. They also avoid terrain rocky enough to cause problems with digging. They have been documented as high as  in Ethiopia. They are present throughout sub-Saharan Africa all the way to South Africa with few exceptions including the coastal areas of Namibia, Ivory Coast, and Ghana. They are not found in Madagascar.
Ecology and behaviour
Aardvarks live for up to 23 years in captivity. Its keen hearing warns it of predators: lions, leopards, cheetahs, African wild dogs, hyenas, and pythons. Some humans also hunt aardvarks for meat. Aardvarks can dig fast or run in zigzag fashion to elude enemies, but if all else fails, they will strike with their claws, tail and shoulders, sometimes flipping onto their backs lying motionless except to lash out with all four feet. They are capable of causing substantial damage to unprotected areas of an attacker. They will also dig to escape as they can. Sometimes, when pressed, aardvarks can dig extremely quickly.

Wombat

Wombats are short-legged, muscular quadrupedal marsupials of the family Vombatidae that are native to Australia. Living species are about  in length with small, stubby tails and weigh between . They are adaptable and habitat tolerant, and are found in forested, mountainous, and heathland areas of southern and eastern Australia, including Tasmania, as well as an isolated patch of about  in Epping Forest National Park in central Queensland.


What are some options for recsys architectures?

ReFS

Resilient File System (ReFS), codenamed "Protogon", is a Microsoft proprietary file system introduced with Windows Server 2012 with the intent of becoming the "next generation" file system after NTFS.
ReFS was designed to overcome problems that had become significant over the years since NTFS was conceived, which are related to how data storage requirements have changed. These requirements arose from two major changes in storage systems and usage – the size of storage in use (large or massive arrays of multi-terabyte drives now being fairly common), and the need for continual reliability. As a result, the file system needs to be self-repairing (to prevent disk checking from being impractically slow or disruptive), along with abstraction or  virtualization between physical disks and  logical volumes.
The key design advantages of ReFS include automatic integrity checking and data scrubbing, elimination of the need for running chkdsk, protection against data degradation, built-in handling of hard disk drive failure and redundancy, integration of RAID functionality, a switch to copy/allocate on write for data and metadata updates, handling of very long paths and filenames, and storage virtualization and  pooling, including almost arbitrarily sized logical volumes (unrelated to the physical sizes of the used drives).
Comparison with NTFS

Recommender system

Overview Recommender systems usually make use of either or both collaborative filtering and content-based filtering (also known as the personality-based approach), as well as other systems such as knowledge-based systems. Collaborative filtering approaches build a model from a user's past behavior (items previously purchased or selected and/or numerical ratings given to those items) as well as similar decisions made by other users. This model is then used to predict items (or ratings for items) that the user may have an interest in. Content-based filtering approaches utilize a series of discrete, pre-tagged characteristics of an item in order to recommend additional items with similar properties.
The differences between collaborative and content-based filtering can be demonstrated by comparing two early music recommender systems, Last.fm and Pandora Radio.
Last.fm creates a "station" of recommended songs by observing what bands and individual tracks the user has listened to on a regular basis and comparing those against the listening behavior of other users. Last.fm will play tracks that do not appear in the user's library, but are often played by other users with similar interests. As this approach leverages the behavior of users, it is an example of a collaborative filtering technique.
Pandora uses the properties of a song or artist (a subset of the 400 attributes provided by the Music Genome Project) to seed a "station" that plays music with similar properties. User feedback is used to refine the station's results, deemphasizing certain attributes when a user "dislikes" a particular song and emphasizing other attributes when a user "likes" a song. This is an example of a content-based approach.


Title: LLMs-Healthcare : Current Applications and Challenges of Large Language Models in various Medical Specialties

Abstract: We aim to present a comprehensive overview of the latest advancements in utilizing Large Language Models (LLMs) within the healthcare sector, emphasizing their transformative impact across various medical domains. LLMs have become pivotal in supporting healthcare, including physicians, healthcare providers, and patients. Our review provides insight into the applications of Large Language Models (LLMs) in healthcare, specifically focusing on diagnostic and treatment-related functionalities. We shed light on how LLMs are applied in cancer care, dermatology, dental care, neurodegenerative disorders, and mental health, highlighting their innovative contributions to medical diagnostics and patient care. Throughout our analysis, we explore the challenges and opportunities associated with integrating LLMs in healthcare, recognizing their potential across various medical specialties despite existing limitations. Additionally, we offer an overview of handling diverse data types within the medical field.

Title: Large language models in medicine: the potentials and pitfalls

Abstract: Large language models (LLMs) have been applied to tasks in healthcare, ranging from medical exam questions to responding to patient questions. With increasing institutional partnerships between companies producing LLMs and healthcare systems, real world clinical application is coming closer to reality. As these models gain traction, it is essential for healthcare practitioners to understand what LLMs are, their development, their current and potential applications, and the associated pitfalls when utilized in medicine. This review and accompanying tutorial aim to give an overview of these topics to aid healthcare practitioners in understanding the rapidly changing landscape of LLMs as applied to medicine.


how many seasons are there for the good doctor

The Good Doctor (American TV series)

Development In May 2014, CBS Television Studios began development on an American remake of the hit South Korean medical drama Good Doctor with Daniel Dae Kim as producer. Kim explained the appeal of adapting the series as "something that can fit into a recognizable world with a breadth of characters that can be explored in the long run". The story of an autistic pediatric surgeon was to be set in Boston, and projected to air in August 2015, but CBS did not pick up the project, and it moved to Sony Pictures Television with a put pilot commitment from ABC in October 2016. The series was developed by David Shore who is credited as executive producer alongside Kim, Sebastian Lee and David Kim. ABC officially ordered the series to pilot in January 2017.
On May 11, 2017, ABC ordered to series as a co-production with Sony Pictures Television and ABC Studios, and it was officially picked up for a season of 18 episodes on October 3, 2017. On March 7, 2018, ABC renewed the series for a second season. On February 5, 2019, during the TCA press tour, ABC renewed the series for a third season which premiered on September 23, 2019. On February 10, 2020, ABC renewed the series for a fourth season which premiered on November 2, 2020. On August 6, 2020, it was reported that the fourth season opener is set to focus on the COVID-19 pandemic. On May 3, 2021, ABC renewed the series for a fifth season which premiered on September 27, 2021. On March 30, 2022, ABC renewed the series for a sixth season which premiered on October 3, 2022. On May 13, 2022, executive producer Liz Friedman was promoted to co-showrunner alongside Shore for the sixth season.  On April 19, 2023, ABC renewed the series for a seventh season which premiered on February 20, 2024. On January 11, 2024, it was announced that the seventh season will be its final season.

The Good Doctor (American TV series)

Paige Spara as Lea Dilallo-Murphy (seasons 2–7; recurring, season 1), Shaun's love interest until she left to pursue her dream. Later after she returned, they decide to be platonic close friends and roommates, but they finally became a couple in the season 3 finale. In season 4, she and Shaun were expecting a baby girl together before she has a miscarriage due to a medical problem. In the season 4 finale, Lea gets engaged to Shaun. In the season 5 finale, they get married. In season 6, she and Shaun are expecting a baby boy and she gives birth to Steven in the finale. In a flashforward in the series finale, Shaun and Lea have a daughter together as well. Lea worked as an automotive engineer in the first two seasons before becoming Glassman's assistant in season 3. In season 4, she has become the head of the hospital's IT department.
Jasika Nicole as Dr. Carly Lever (season 3; recurring seasons 1–2), the hospital's head and board certified pathologist introduced in season 1 who becomes Shaun's co-worker in season 2 and girlfriend in season 3. However, Carly breaks up with Shaun near the end of season 3 after realizing that he's in love with Lea.


a paper which evaluates LLMs abilities to roleplay as a character

Title: Virtual signatures of dark sectors in Higgs couplings

Abstract: Where collider searches for resonant invisible particles loose steam, dark sectors might leave their trace as virtual effects in precision observables. Here we explore this option in the framework of Higgs portal models, where a sector of dark fermions interacts with the standard model through a strong renormalizable coupling to the Higgs boson. We show that precise measurements of Higgs-gauge and triple Higgs interactions can probe dark fermions up to the TeV scale through virtual corrections. Observation prospects at the LHC and future lepton colliders are discussed for the so-called singlet-doublet model of Majorana fermions, a generalization of the bino-higgsino scenario in supersymmetry. We advocate a two-fold search strategy for dark sectors through direct and indirect observables.

Title: Character-LLM: A Trainable Agent for Role-Playing

Abstract: Large language models (LLMs) can be used to serve as agents to simulate human behaviors, given the powerful ability to understand human instructions and provide high-quality generated texts. Such ability stimulates us to wonder whether LLMs can simulate a person in a higher form than simple human behaviors. Therefore, we aim to train an agent with the profile, experience, and emotional states of a specific person instead of using limited prompts to instruct ChatGPT API. In this work, we introduce Character-LLM that teach LLMs to act as specific people such as Beethoven, Queen Cleopatra, Julius Caesar, etc. Our method focuses on editing profiles as experiences of a certain character and training models to be personal simulacra with these experiences. To assess the effectiveness of our approach, we build a test playground that interviews trained agents and evaluates whether the agents \textit{memorize} their characters and experiences. Experimental results show interesting observations that help build future simulacra of humankind.


What's the purpose of `if __name__ == '__main__'`?

Stackoverflow Stackexchange

Q: html dangerous tags to avoid while developing a chat application I am developing a chat application using PHP and jQuery... all messages sent by the chat pair are appended to a <div>. While doing this, I found that tags such as <script> can be entered by users. What tags should I avoid while appending the user's message?

A: Avoid tags that will inject content into the page:

*

*applet

*script

*style

*link

*iframe

Other tags may be necessary to remove, as well. Maybe you don't want to embed images. These are things that you will need to determine. At the bare minimum, allow <p> and <br />.

Stackoverflow Stackexchange

Q: What is the purpose of __name__? What does __name__ do? I have only seen it paired with __main__ and nothing else.
I know that the classic if __name__ == __main__: defines the behavior when acting as a package vs running as stand-alone.
However what other usages are there for __name__?

A: __name__ is "__main__" if you're executing the script directly. If you're importing a module, __name__ is the name of the module.
foo.py:
print(__name__)

bar.py
import foo

Run the scripts:
$ python foo.py
__main__
$ python bar.py
foo


Which test was devised to determine whether robots can think?

Turing test

The Turing test, originally called the imitation game by Alan Turing in 1950, is a test of a machine's ability to exhibit intelligent behaviour equivalent to, or indistinguishable from, that of a human. Turing proposed that a human evaluator would judge natural language conversations between a human and a machine designed to generate human-like responses. The evaluator would be aware that one of the two partners in conversation was a machine, and all participants would be separated from one another. The conversation would be limited to a text-only channel, such as a computer keyboard and screen, so the result would not depend on the machine's ability to render words as speech. If the evaluator could not reliably tell the machine from the human, the machine would be said to have passed the test. The test results would not depend on the machine's ability to give correct answers to questions, only on how closely its answers resembled those a human would give. Since the Turing test is a test of indistinguishability in performance capacity, the verbal version generalizes naturally to all of human performance capacity, verbal as well as nonverbal (robotic).

Turing test

The test was introduced by Turing in his 1950 paper "Computing Machinery and Intelligence" while working at the University of Manchester. It opens with the words: "I propose to consider the question, 'Can machines think? Because "thinking" is difficult to define, Turing chooses to "replace the question by another, which is closely related to it and is expressed in relatively unambiguous words." Turing describes the new form of the problem in terms of a three-person game called the "imitation game", in which an interrogator asks questions of a man and a woman in another room in order to determine the correct sex of the two players. Turing's new question is: "Are there imaginable digital computers which would do well in the imitation game?" This question, Turing believed, was one that could actually be answered. In the remainder of the paper, he argued against all the major objections to the proposition that "machines can think".
Since Turing introduced his test, it has been both highly influential and widely criticized, and has become an important concept in the philosophy of artificial intelligence. Philosopher John Searle would comment on the Turing test in his Chinese room argument, a thought experiment that stipulates that a machine cannot have a "mind", "understanding", or "consciousness", regardless of how intelligently or human-like the program may make the computer behave. Searle criticizes Turing's test and claims it is insufficient to detect the presence of consciousness.
History


Research on improving bi-encoder performance using a cross-encoder for generating additional training data.

Title: Augmented SBERT: Data Augmentation Method for Improving Bi-Encoders for Pairwise Sentence Scoring Tasks

Abstract: There are two approaches for pairwise sentence scoring: Cross-encoders, which perform full-attention over the input pair, and Bi-encoders, which map each input independently to a dense vector space. While cross-encoders often achieve higher performance, they are too slow for many practical use cases. Bi-encoders, on the other hand, require substantial training data and fine-tuning over the target task to achieve competitive performance. We present a simple yet efficient data augmentation strategy called Augmented SBERT, where we use the cross-encoder to label a larger set of input pairs to augment the training data for the bi-encoder. We show that, in this process, selecting the sentence pairs is non-trivial and crucial for the success of the method. We evaluate our approach on multiple tasks (in-domain) as well as on a domain adaptation task. Augmented SBERT achieves an improvement of up to 6 points for in-domain and of up to 37 points for domain adaptation tasks compared to the original bi-encoder performance.

Title: Poly-encoders: Transformer Architectures and Pre-training Strategies for Fast and Accurate Multi-sentence Scoring

Abstract: The use of deep pre-trained bidirectional transformers has led to remarkable progress in a number of applications (Devlin et al., 2018). For tasks that make pairwise comparisons between sequences, matching a given input with a corresponding label, two approaches are common: Cross-encoders performing full self-attention over the pair and Bi-encoders encoding the pair separately. The former often performs better, but is too slow for practical use. In this work, we develop a new transformer architecture, the Poly-encoder, that learns global rather than token level self-attention features. We perform a detailed comparison of all three approaches, including what pre-training and fine-tuning strategies work best. We show our models achieve state-of-the-art results on three existing tasks; that Poly-encoders are faster than Cross-encoders and more accurate than Bi-encoders; and that the best results are obtained by pre-training on large datasets similar to the downstream tasks.


What will I get, if I orde a 'kradser' from a Danish hot dog stand?

Sausage

Greece Loukániko (Greek: λουκάνικο) is the common Greek word for pork sausage.
The name 'loukaniko' is derived from ancient Roman cuisine.
Nordic countries
Nordic sausages (, , , ) are usually made of 60–80% very finely ground pork, very sparsely spiced with pepper, nutmeg, allspice or similar sweet spices (ground mustard seed, onion and sugar may also be added). Water, lard, rind, potato starch flour and soy or milk protein are often added for binding and filling. In southern Norway, grilled and wiener sausages are often wrapped in a lompe, a potato flatbread somewhat similar to a lefse.
Virtually all sausages will be industrially precooked and either fried or warmed in hot water by the consumer or at the hot dog stand. Since hot dog stands are ubiquitous in Denmark (known as Pølsevogn) some people regard pølser as one of the national dishes, perhaps along with medisterpølse, a fried, finely ground pork and bacon sausage. The most noticeable aspect of Danish boiled sausages (never the fried ones) is that the casing often contains a traditional bright-red dye. They are also called wienerpølser and legend has it they originate from Vienna where it was once ordered that day-old sausages be dyed as a means of warning.

Hot dog variations

Germany Even though the type of sausage that led to the creation of the modern hot dog in the United States is undeniably German, German hot dog culture is mainly influenced by Scandinavian—mostly Danish—elements. This does not affect the type of sausage (unlike the Danish rød pølse, German hot dogs usually have frankfurt- or wiener-style sausages) but the condiments—ketchup, mustard or Danish-style remoulade depending on individual preference as well as roasted onions and thinly sliced pickles—are usually marketed as a Danish influence. While sauerkraut is a common, distinctively German, topping in the US, it is not typical in Germany. Grilling the sausage, which is common in America, is largely unknown in Germany where it is steamed like its Scandinavian counterparts.
Iceland
The Iceland Monitor writes that "locals, expatriates and holiday-makers alike must all be familiar with Iceland’s national dish—hot-dogs with all the trimmings (‘pylsa með öllu’ in Icelandic). The hot-dog sausage is served in bread and liberally accompanied with fried onion, raw onion, mustard, ketchup and remoulade (a cold sauce made with mayonnaise and various condiments and herbs). This delicious snack is traditionally washed down with copious amounts of Coca-Cola."
In August 2006, the British newspaper The Guardian selected Iceland's Bæjarins beztu as the best hot dog stand in Europe. Bæjarins beztu pylsur (English: The best hot dog in town) often shortened to simply "Bæjarins beztu," is a popular hot dog stand in central Reykjavík. Hot dogs from this stand are derived from the Danish hot dog. They are often ordered with "the works," i.e., all condiments, or in Icelandic "eina með öllu". Icelandic hot dogs are made from Icelandic lamb, pork and beef and served with a mix of raw white and fried onion, ketchup, sweet brown mustard, and remoulade.


English Stackexchange

Q: "There already is" or "There is already" What is the correct word order of the verb to be and already?

There is already a price tag.

Or:

There already is a price tag.

A: Most speakers would shorten "There is" to "There's" so "There's already a price tag" would be the most common speaking version.


Title: MLLM-as-a-Judge: Assessing Multimodal LLM-as-a-Judge with Vision-Language Benchmark

Abstract: Multimodal Large Language Models (MLLMs) have gained significant attention recently, showing remarkable potential in artificial general intelligence. However, assessing the utility of MLLMs presents considerable challenges, primarily due to the absence of multimodal benchmarks that align with human preferences. Drawing inspiration from the concept of LLM-as-a-Judge within LLMs, this paper introduces a novel benchmark, termed MLLM-as-a-Judge, to assess the ability of MLLMs in assisting judges across diverse modalities, encompassing three distinct tasks: Scoring Evaluation, Pair Comparison, and Batch Ranking. Our study reveals that, while MLLMs demonstrate remarkable human-like discernment in Pair Comparison, there is a significant divergence from human preferences in Scoring Evaluation and Batch Ranking. Furthermore, a closer examination reveals persistent challenges in the judgment capacities of LLMs, including diverse biases, hallucinatory responses, and inconsistencies in judgment, even in advanced models such as GPT-4V. These findings emphasize the pressing need for enhancements and further research efforts to be undertaken before regarding MLLMs as fully reliable evaluators. In light of this, we advocate for additional efforts dedicated to supporting the continuous development within the domain of MLLM functioning as judges. The code and dataset are publicly available at our project homepage: \url{https://mllm-judge.github.io/}.

Title: A Comprehensive Evaluation of Large Language Models on Legal Judgment Prediction

Abstract: Large language models (LLMs) have demonstrated great potential for domain-specific applications, such as the law domain. However, recent disputes over GPT-4's law evaluation raise questions concerning their performance in real-world legal tasks. To systematically investigate their competency in the law, we design practical baseline solutions based on LLMs and test on the task of legal judgment prediction. In our solutions, LLMs can work alone to answer open questions or coordinate with an information retrieval (IR) system to learn from similar cases or solve simplified multi-choice questions. We show that similar cases and multi-choice options, namely label candidates, included in prompts can help LLMs recall domain knowledge that is critical for expertise legal reasoning. We additionally present an intriguing paradox wherein an IR system surpasses the performance of LLM+IR due to limited gains acquired by weaker LLMs from powerful IR systems. In such cases, the role of LLMs becomes redundant. Our evaluation pipeline can be easily extended into other tasks to facilitate evaluations in other domains. Code is available at https://github.com/srhthu/LM-CompEval-Legal