nils-herrmann/clean_scirepeval huggingface dataset:
Midterm II Answer Key ECON 504 - Microeconomics II

The unique pure strategy subgame perfect equilibrium is (Rr, r). 2. (30pts.) An entrepreneur has a project that she presents to a capitalist. She has her own money that she could invest in the project and is looking for additional funding from the capitalist. The project is either good (denoted g) (with probability p) or it is bad (denoted b) (with probability 1− p) and only the entrepreneur knows the quality of the project. The entrepreneur (E) decides whether to invest her own money (I) or not (N), the capitalist (C) observes whether the entrepreneur has invested or not and then decides whether to invest his money (i) or not (n).  1 represents the game and gives the payoffs, where the first number is the entrepreneur’s payoff and the second number is the capitalist’s. (a) (20pts.) Find the set of pure strategy perfect Bayesian equilibria of this game.
Human-in-the-loop Artificial Intelligence

Little by little, newspapers are revealing the bright future that Artificial Intelligence (AI) is building. Intelligent machines will help everywhere. However, this bright future has a dark side: a dramatic job market contraction before its unpredictable transformation. Hence, in a near future, large numbers of job seekers will need financial support while catching up with these novel unpredictable jobs. This possible job market crisis has an antidote inside. In fact, the rise of AI is sustained by the biggest knowledge theft of the recent years. Learning AI machines are extracting knowledge from unaware skilled or unskilled workers by analyzing their interactions. By passionately doing their jobs, these workers are digging their own graves. In this paper, we propose Human-in-the-loop Artificial Intelligence (HIT-AI) as a fairer paradigm for Artificial Intelligence systems. HIT-AI will reward aware and unaware knowledge producers with a different scheme: decisions of AI systems generating revenues will repay the legitimate owners of the knowledge used for taking those decisions. As modern Robin Hoods, HIT-AI researchers should fight for a fairer Artificial Intelligence that gives back what it steals.
Supply Chain Contract Evolution

This paper draws together theories from organisational and neo-institutional literatures to address the evolution of supply chain contracts. Using a longitudinal case study of the Norwegian State Railways, we examine how firms move through the stages in an inter-organisational process of supply chain contract evolution and how they can cooperate to ensure efficiency and equity in their contractual relationship. The findings suggest that inefficient and inequitable initial contracts can occur in part, because of the cognitive shortcomings in human decision-making processes that reveal themselves early in the arrangement before learning and trust building can accumulate. We then reveal how parties can renegotiate towards a more equitable and efficient supply chain contract.
Ontology-based information extraction of regulatory networks from scientific articles with case studies for Escherichia coli

The amount of scientific papers in the Molecular Biology field has experienced an enormous growth in the last years, prompting the need of developing automatic Information Extraction (IE) systems. This work is a first step towards the ontology-based domain-independent generalization of a system that identifies Escherichia coli regulatory networks. First, a domain ontology based on the RegulonDB database was designed and populated. After that, the steps of the existing IE system were generalized to use the knowledge contained in the ontology, so that it could be potentially applied to other domains. The resulting system has been tested both with abstract and full articles that describe regulatory interactions for E. coli, obtaining satisfactory results.
GPipe: Efficient Training of Giant Neural Networks using Pipeline Parallelism

GPipe is a scalable pipeline parallelism library that enables learning of giant deep neural networks. It partitions network layers across accelerators and pipelines execution to achieve high hardware utilization. It leverages recomputation to minimize activation memory usage. For example, using partitions over 8 accelerators, it is able to train networks that are 25× larger, demonstrating its scalability. It also guarantees that the computed gradients remain consistent regardless of the number of partitions. It achieves an almost linear speedup without any changes in the model parameters: when using 4× more accelerators, training the same model is up to 3.5× faster. We train a 557 million parameters AmoebaNet model and achieve a new state-ofthe-art 84.3% top-1 / 97.0% top-5 accuracy on ImageNet 2012 dataset. Finally, we use this learned model to finetune multiple popular image classification datasets and obtain competitive results, including pushing the CIFAR-10 accuracy to 99% and CIFAR-100 accuracy to 91.3%.
1 Creativity , Intelligence , and Personality

ivergent thinking; creativity in women; hemispheric specialization opposing right brain to left as the source of intuition, metaphor, and imagery; the contribution of altered states of consciousness to creative thinking; an organismic interpretation of the relationship of creativity to personality and intelligence; new methods of analysis of biographical material and a new emphasis on psychohistory; the relationship of thought disorder to originality; the inheritance of intellectual and personal traits important to creativity; the enhancement of creativity by training; these have been the main themes emerging in research on creativity since the last major reviews of the field (Stein 1968; Dellas & Gaier 1970; Freeman, Butcher & Christie 1971; Gilchrist 1972). Much indeed has happened in the field of creativity research since 1950, when J. P. Guilford in his parting address as president of the American Psychological Association pointed out that up to that time only 186 out of 121,000 entries in Psychological Abstracts dealt with creative imagination. By 1956, when the first national research conference on creativity was organized by C. W. Taylor at the University of Utah (under the sponsorship of the National Science Foundation), this number had doubled. By 1962, when Scientific Creativity (compiled by C. W. Taylor and F. Barron) went to press with a summary of the
Occupational Therapy for Children with Attention Deficit Hyperactivity Disorder ( ADHD ) , Part 2 : a Multicentre Evaluation of an Assessment and Treatment Package

In part 1 of this article, an occupational therapy model of practice for children with attention deficit hyperactivity disorder (ADHD) was described (Chu and Reynolds 2007). It addressed some specific areas of human functioning related to children with ADHD in order to guide the practice of occupational therapy. The model provides an approach to identifying and communicating occupational performance difficulties in relation to the interaction between the child, the environment and the demands of the task. A family-centred occupational therapy assessment and treatment package based on the model was outlined. The delivery of the package was underpinned by the principles of the family-centred care approach. Part 2 of this two-part article reports on a multicentre study, which was designed to evaluate the effectiveness and acceptability of the proposed assessment and treatment package and thereby to offer some validation of the delineation model. It is important to note that no treatment has yet been proved to ‘cure’ the condition of ADHD or to produce any enduring effects in affected children once the treatment is withdrawn. So far, the only empirically validated treatments for children with ADHD with substantial research evidence are psychostimulant medication, behavioural and educational management, and combined medication and behavioural management (DuPaul and Barkley 1993, A family-centred occupational therapy assessment and treatment package for children with attention deficit hyperactivity disorder (ADHD) was evaluated. The package involves a multidimensional evaluation and a multifaceted intervention, which are aimed at achieving a goodness-of-fit between the child, the task demands and the environment in which the child carries out the task. The package lasts for 3 months, with 12 weekly contacts with the child, parents and teacher. A multicentre study was carried out, with 20 occupational therapists participating. Following a 3-day training course, they implemented the package and supplied the data that they had collected from 20 children. The outcomes were assessed using the ADHD Rating Scales, pre-intervention and post-intervention. The results showed behavioural improvement in the majority of the children. The Measure of Processes of Care – 20-item version (MPOC-20) provided data on the parents’ perceptions of the family-centredness of the package and also showed positive ratings. The results offer some support for the package and the guiding model of practice, but caution should be exercised in generalising the results because of the small sample size, lack of randomisation, absence of a control group and potential experimenter effects from the research therapists. A larger-scale randomised controlled trial should be carried out to evaluate the efficacy of an improved package.
Combating Fake News with Interpretable News Feed Algorithm

Nowadays, artificial intelligence algorithms are used for targeted and personalized content distribution in the large scale as part of the intense competition for attention in the digital media environment. Unfortunately, targeted information dissemination may result in intellectual isolation and discrimination. Further, as demonstrated in recent political events in the US and EU, malicious bots and social media users can create and propagate targeted “fake news” content in different forms for political gains. From the other direction, fake news detection algorithms attempt to combat such problems by identifying misinformation and fraudulent user profiles. This paper reviews common news feed algorithms as well as methods for fake news detection, and we discuss how news feed algorithms could be misused to promote falsified content, affect news diversity, or impact credibility. We review how news feed algorithms and recommender engines can enable confirmation bias to isolate users to certain news sources and affecting the perception of reality. As a potential solution for increasing user awareness of how content is selected or sorted, we argue for the use of interpretable and explainable news feed algorithms. We discuss how improved user awareness and system transparency could mitigate unwanted outcomes of echo chambers and bubble filters in social media.
Detecting Semantically Equivalent Questions in Online User Forums

Two questions asking the same thing could be too different in terms of vocabulary and syntactic structure, which makes identifying their semantic equivalence challenging. This study aims to detect semantically equivalent questions in online user forums. We perform an extensive number of experiments using data from two different Stack Exchange forums. We compare standard machine learning methods such as Support Vector Machines (SVM) with a convolutional neural network (CNN). The proposed CNN generates distributed vector representations for pairs of questions and scores them using a similarity metric. We evaluate in-domain word embeddings versus the ones trained with Wikipedia, estimate the impact of the training set size, and evaluate some aspects of domain adaptation. Our experimental results show that the convolutional neural network with in-domain word embeddings achieves high performance even with limited training data.
Touching a Stranger : Designing for Engaging Experience in Embodied Interaction

Within interaction design, several forces have coincided in the last few years to fuel the emergence of a new field of inquiry, which we summarize under the label of embodied interaction. The term was introduced to the HCI community by Dourish (2001) as a way to combine the then-distinct perspectives of tangible interaction (Ullmer & Ishii, 2001) and social computing. Briefly, his point was that computing must be approached as twice embodied: in the physical/material sense and in the sense of social fabrics and practices. Dourish’s work has been highly influential in the academic interaction design field and has to be considered a seminal contribution at the conceptual level. Still, we find that more needs to be done to create a body of contemporary designoriented knowledge on embodied interaction. Several recent developments within academia combine to inform and advance the emerging field of embodied interaction. For example, the field of wearable computing (see Mann, 1997, for an introduction to early and influential work), which can be considered a close cousin of tangible interaction, puts particular emphasis on physical bodiness and full-body interaction. The established discipline of human-computer interaction (HCI) has increasingly turned towards considering the whole body in interaction, often drawing on recent advances in cognitive science (e.g., Johnson, 2007) and philosophy (e.g., Shusterman, 2008). Some characteristic examples are the work of Twenebowa Larssen et al. (2007) on conceptualization of haptic and kinaesthetic sensations in tangible interaction and Schiphorst’s (2009) design work on the somaesthetics of interaction. Höök (2009) provides an interesting view of the “bodily turn” in HCI through the progression of four successive design cases. In more technical terms, the growing acceptance of the Internet of Things vision (which according to Dodson [2003] traces its origins to MIT around 1999) serves as a driver and enabler for realizations of embodied interaction. Finally, it should be mentioned that analytical perspectives on interaction in media studies are increasingly moving from interactivity to performativity, a concept of long standing in, for example, performance studies which turns out to have strong implications also for how interaction is seen as socially embodied (see Bardzell, Bolter, & Löwgren, 2010, for an example). The picture that emerges is one of a large and somewhat fuzzy design space, that has been predicted for quite a few years within academia but is only now becoming increasingly amenable ORIGINAL ARTICLE
Unsupervised Neural Categorization for Scientific Publications

Most conventional document categorization methods require a large number of documents with labeled categories for training. These methods are hard to be applied in scenarios, such as scientific publications, where training data is expensive to obtain and categories could change over years and across domains. In this work, we propose UNEC, an unsupervised representation learning model that directly categories documents without the need of labeled training data. Specifically, we develop a novel cascade embedding approach. We first embed concepts, i.e., significant phrases mined from scientific publications, into continuous vectors, which capture concept semantics. Based on the concept similarity graph built from the concept embedding, we further embed concepts into a hidden category space, where the category information of concepts becomes explicit. Finally we categorize documents by jointly considering the category attribution of their concepts. Our experimental results show that UNEC significantly outperforms several strong baselines on a number of real scientific corpora, under both automatic and manual evaluation.
Barriers and Facilitators to Inclusive Education

To examine how inclusive our schools are after 25 years of educational reform, students with disabilities and their parents were asked to identify current barriers and provide suggestions for removing those barriers. Based on a series of focus group meetings, 15 students with mobility limitations (9-15 years) and 12 parents identified four categories of barriers at their schools: (a) the physical environment (e.g., narrow doorways, ramps); (b) intentional attitudinal barriers (e.g., isolation, bullying); (c) unintentional attitudinal barriers (e.g., lack of knowledge, understanding, or awareness); and (d) physical limitations (e.g., difficulty with manual dexterity). Recommendations for promoting accessibility and full participation are provided and discussed in relation to inclusive education efforts.
A Brief Introduction into Machine Learning

The Machine Learning field evolved from the broad field of Artificial Intelligence, which aims to mimic intelligent abilities of humans by machines. In the field of Machine Learningone considers the important question of how to make machines able to “learn”. Learning in this context is understood as inductive inference , where one observesexamplesthat represent incomplete information about some “statistical phenomenon”. Inunsupervisedlearning one typically tries to uncover hidden regularities (e.g. clusters) or to detect anomalies in the data (for instance some unusual machine function or a network intrusion). Insupervised learning , there is alabel associated with each example. It is supposed to be the answer to a question about the example. If the label is discrete, then the task is called classification problem– otherwise, for realvalued labels we speak of a regression problem. Based on these examples (including the labels), one is particularly interested to predict the answer for other cases before they are explicitly observed. Hence, learning is not only a question of remembering but also ofgeneralization to unseen cases .
Combining Top-N Recommenders with Metasearch Algorithms

Given the diversity of recommendation algorithms, choosing one technique is becoming increasingly difficult. In this paper, we explore methods for combining multiple recommendation approaches. We studied rank aggregation methods that have been proposed for the metasearch task (i.e., fusing the outputs of different search engines) but have never been applied to merge top-N recommender systems. These methods require no training data nor parameter tuning. We analysed two families of methods: voting-based and score-based approaches. These rank aggregation techniques yield significant improvements over state-of-the-art top-N recommenders. In particular, score-based methods yielded good results; however, some voting techniques were also competitive without using score information, which may be unavailable in some recommendation scenarios. The studied methods not only improve the state of the art of recommendation algorithms but they are also simple and efficient.
Comparison of isokinetic hip abduction and adduction peak torques and ratio between sexes.

To evaluate hip abductor and adductor peak torque outputs and compare their ratios between sexes.



A cross-sectional laboratory-controlled study.



Participants visited a laboratory and performed an isokinetic hip abductor and adductor test. All participants performed 2 sets of 5 repetitions of concentric hip abduction and adduction in a standing position at 60 degrees per second. Gravity was determined as a function of joint angle relative to the horizontal plane and was corrected by normalizing the weight of the limb on an individual basis.



A total of 36 collegiate athletes.



Sex (20 females and 16 males).



Bilateral peak hip abductor and adductor torques were measured. The 3 highest peak torque values were averaged for each subject.



Independent t tests were used to compare sex differences in hip abductor and adductor peak torques and the abductor:adductor peak torque ratios. Males demonstrated significantly greater hip abductor peak torque compared with females (males 1.29 ± 0.24 Nm/kg, females 1.13 ± 0.20 Nm/kg; P = 0.03). Neither hip adductor peak torque nor their ratios differed between sexes.



Sex differences in hip abductor strength were observed. The role of weaker hip abductors in females deserves further attention and may be a factor for higher risk of knee pathologies.
The promise of occupational science: a developmental assessment of an emerging academic discipline.

In the late 1980's, occupational science was introduced as a basic discipline that would provide a foundation for occupational therapy. As occupational science grows and develops, some question its relationship to occupational therapy and criticize the direction and extent of its growth and development.



This study was designed to describe and critically analyze the growth and development of occupational science and characterize how this has shaped its current status and relationship to occupational therapy.



Using a mixed methods design, 54 occupational science documents published in the years 1990 and 2000 were critically analyzed to describe changes in the discipline between two points in time. Data describing a range of variables related to authorship, publication source, stated goals for occupational science and type of research were collected.



Descriptive statistics, themes and future directions are presented and discussed.



Through the support of a discipline that is dedicated to the pursuit of a full understanding of occupation, occupational therapy will help to create a new and complex body of knowledge concerning occupation. However, occupational therapy must continue to make decisions about how knowledge produced within occupational science and other disciplines can be best used in practice.
Recent Trends in Banknote Counterfeiting

Currency, defined here as banknotes and coins, plays an important role in the economy as a medium of exchange and a store of value. For Australia’s currency to function efficiently, it is important that the public has confidence in it and is therefore willing to accept banknotes and coins in transactions. Counterfeiting currency is a crime under the Crimes (Currency) Act 1981, and carries penalties of up to 14 years’ jail. People who fall victim to this crime have essentially been robbed. They cannot be reimbursed for their loss as, among other things, doing so would serve as an incentive to counterfeiters to continue their illegal activities. As a result, a high prevalence of counterfeiting can threaten public confidence in currency given that someone who accepts a counterfeit in place of a genuine banknote is left out of pocket and may be reluctant to accept banknotes in the future. Under the Reserve Bank Act 1959, the Reserve Bank issues Australia’s banknotes and has a mandate to contribute to the stability of the Australian currency. To ensure the security of these banknotes, the Reserve Bank works actively to monitor and manage the threat of banknote counterfeiting in Australia. The Reserve Bank works in partnership with key stakeholders to ensure that cash-handling professionals have information on how to detect counterfeits, that machines can authenticate banknotes, and that counterfeiters are apprehended and prosecuted (Evans, Gallagher and Martz 2015). The periodic issuance of new banknote series with upgraded security features, as is currently under way in Australia, is key to ensuring the security of, and thus confidence in, banknotes. Research into potential new security features is ongoing so that the Reserve Bank is well placed to develop and issue new banknote series as required and before counterfeiting levels become problematic. Monitoring of counterfeit activities informs the Bank’s decisions about the timing of such issuance. Recent Trends in Banknote Counterfeiting