Miracle-dz/UniFAR-FTUs huggingface dataset:
Learning Simulation Control in General Game-Playing Agents

The aim of General Game Playing (GGP) is to create intelligent agents that can automatically learn how to play many different games at an expert level without any human intervention. One of the main challenges such agents face is to automatically learn knowledge-based heuristics in real-time, whether for evaluating game positions or for search guidance. In recent years, GGP agents that use Monte-Carlo simulations to reason about their actions have become increasingly more popular. For competitive play such an approach requires an effective search-control mechanism for guiding the simulation playouts. In here we introduce several schemes for automatically learning search guidance based on both statistical and reinforcement learning techniques. We compare the different schemes empirically on a variety of games and show that they improve significantly upon the current state-of-the-art in simulation-control in GGP. For example, in the chess-like game Skirmish, which has proved a particularly challenging game for simulation-based GGP agents, an agent employing one of the proposed schemes achieves 97% winning rate against an unmodified agent.
EFFECTS OF SOCIAL NETWORK ON STUDENTS’ PERFORMANCE: A WEB-BASED FORUM STUDY IN TAIWAN

This research investigates the effects of social networks on students’ performance in online education which uses networking as an adjunct mode for enhancing traditional face-to-face education or distance education. Using data from a 40-student course on Advanced Management Information Systems (AMIS), we empirically tested how social networks (friendly, advising, and adversarial) related to students’ performance. First, advising network variables are positively related to student performance both in the class and on the forum. Adversarial variables are negatively correlated with almost all students’performance. Second, advising and adversarial network variables are good determinants for overall academic performance; however, adversarial network variables are not influential on students’ performance on the forum. Friendship network variables are not determinants of students’ performance. Implications for the results are also discussed.
Reducing Clinical Trial Costs by Detecting and Measuring the Placebo Effect and Treatment Effect Using Brain Imaging

Although the placebo effect is known to have a strong impact on the outcomes of clinical trials, methods for measuring it are limited to physiological observations. We propose a method of localizing, identifying and measuring placebo and treatment-induced networks in the brain using functional neuroimaging. Measuring the relative activation of these "placebo" brain networks serves as a proxy for the placebo effect contained within the variable of interest (depression rating, blood pressure, etc). Analogous to the difference between a paired and unpaired t-test, this allows for a sharp gain in power and reduction in the sample sizes needed in clinical trials, potentially leading to a drastically smaller sample sizes for establishing efficacy, a shorter time-to-market for a drug, and a drastic reduction in the cost of bringing new drugs into the market.
PRODUCTIVITY GROWTH AT FORD IN THE COMING OF MASS PRODUCTION: A PRELIMINARY ANALYSIS

carefully document and analyze aspects of the changes in the organization of production at the Ford Motor Company in the years in which mass production methods for automobile manufacturing were first being developed and iraplemented. Yet these books, even Lewchuk's, provide only a sketchy quantitative account of the productivity consequences of the changes. Only sketchy quantitative evidence was available to the authors at the free they wrote. This is a frustrating state of affairs. Recent developments in the theory of the firm and of both theoretical and empirical study of economic growth give great salience to firm-level actions and their consequences. Yet we have no wellgrounded answer to the question of how big these consequences might be even for epochal actions, and no real firm-level standards exist for comparison to the computafons on industry-level, sectoral, and economy-wide data well-known to economists and other students of economic growth and development. The Ford Motor Company in the years before World War I represents a paradigm case of such firm-level epochal actions. The paucity of relevant Ford data has recently become somewhat less extreme. This paper utilizes information that has come to light since the books cited above were published to expand, at least incrementally, what we know. 2 The data used in this paper are annual. Given the macro literature, this is a reasonable place to start. But given the history of technology literature, it is not a reasonable place to stop. In subsequent work I expect to extend this sort of analysis to much higher frequency data in order to relate it to a finer-grained timeline of change in the organization of production. I also expect to explore inter-firm comparisons.
Using two-stage conditional word frequency models to model word burstiness and motivating TF-IDF

Several authors have recently studied the problem of creating exchangeable models for natural languages that exhibit word burstiness. Word burstiness means that a word that has appeared once in a text should be more likely to appear again than it was to appear in the first place. In this article the different existing methods are compared theoretically through a unifying framework. New models that do not satisfy the exchangeability assumption but whose probability revisions only depend on the word counts of what has previously appeared, are introduced within this framework. We will refer to these models as two-stage conditional presence/abundance models since they, just like some recently introduced models for the abundance of rare species in ecology, seperate the issue of presence from the issue of abundance when present. We will see that the widely used TF-IDF heuristic for information retrieval follows naturally from these models by calculating a crossentropy. We will also discuss a connection between TF-IDF and file formats that seperate presence from abundance given presence.
Cardiac myocytes' dynamic contractile behavior differs depending on heart segment

Cardiac myocytes originating from different parts of the heart exhibit varying morphology and ultrastructure. However, the difference in their dynamic behavior is unclear. We examined the contraction of cardiac myocytes originating from the apex, ventricle, and atrium, and found that their dynamic behavior, such as amplitude and frequency of contraction, differs depending on the heart segment of origin. Using video microscopy and high‐precision image correlation, we found that: (1) apex myocytes exhibited the highest contraction rate (∼17 beats/min); (2) ventricular myocytes exhibited the highest contraction amplitude (∼5.2 micron); and (3) as myocyte contraction synchronized, their frequency did not change significantly, but the amplitude of contraction increased in apex and ventricular myocytes. In addition, as myocyte cultures mature they formed contractile filaments, further emphasizing the difference in myocyte dynamics is persistent. These results suggest that the dynamic behavior (in addition to static properties) of myocytes is dependent on their segment of origin. Biotechnol. Bioeng. 2013; 110: 628–636. © 2012 Wiley Periodicals, Inc.
Bats-inspired frequency hopping for mitigation of interference between automotive radars

It was reported for specific bats, that they use a certain scheme to shift the frequencies of their echo location calls to counteract interferences with conspecifics. As in road traffic, an increasing number of cars is equipped with radar sensors, there is also the problem of mutual interference. The available frequency bands are limited, so a randomized frequency hopping will not be the best solution. In this paper, we adapt the frequency hopping behavior of the bats reported in [1] to a radar system. We discuss the algorithm and show measurements of its performance in an anechoic chamber.
The Effect of Measles on Health-Related Quality of Life: A Patient-Based Survey

Background Measles is a highly contagious and potentially fatal illness preventable through vaccination. Outbreaks in the UK and many other European countries have been increasing over recent years, with over 3,207 laboratory-confirmed cases reported by Public Health England from January 2012 to the end of June 2013. To aid rational decision making regarding measles control versus other use of healthcare resources, it is important to measure the severity of measles in units that are comparable to other diseases. The standard metric for this in the UK is the quality-adjust life year (QALY). To our knowledge, the impact of measles on health-related quality of life (HRQoL) in terms of QALYs has not been quantified. Methods and Findings Individuals with confirmed measles were sent questionnaires requesting information on the short-term impact of the illness on their HRQoL using the EuroQol EQ-5D-3L questionnaire. HRQoL was reported for the day the questionnaire was received, the worst day of infection and at follow-up three weeks later. 507 questionnaires were sent to individuals with confirmed measles with 203 returned (40%). The majority of respondents were not vaccinated. The mean time off work or school was 9.6 days. The mean duration of perceived illness was 13.8 days. The mean number of QALYs lost was 0.019 (equivalent to 6.9 days). The overall burden of disease in terms of QALYs lost in England based on the total number of confirmed cases in the twelve month period from 1st June 2012 was estimated to be 44.2 QALYs. Conclusion The short-term impact of measles infection on HRQoL is substantial, both at the level of the individual patient and in terms of the overall disease burden. This is the first attempt to quantify QALY-loss due to measles at a population level, and provides important parameters to guide future intervention and control measures.
Colorectal Cancer : Screening Double-Contrast Barium Enema Examination in Average-Risk Adults Older Than 50 Years 1

Materials and Methods: The Institutional Review Board at the affiliated Veterans Affairs Medical Center approved this HIPAA-compliant study protocol and did not require informed consent from patients. Computerized databases revealed 276 doublecontrast barium enema examinations performed for colorectal cancer screening in average-risk adults older than 50 years. Radiographic and pathologic reports were reviewed to determine the number of patients who had polypoid lesions 1 cm or larger, polyps smaller than 1 cm, or advanced neoplastic lesions of any size. Forty-five (16.3%) of the 276 patients underwent follow-up sigmoidoscopy or colonoscopy. Medical, endoscopic, and pathologic records were reviewed and compared with radiographic findings.
NPCryptBench: a cryptographic benchmark suite for network processors

Network processors (NPs), a type of multicore, multithread system that exploits system-on-chip techniques, usually adopt a distributed, shared memory hierarchy to scale up network processing. Network applications running on NP often display distinct characteristics on memory subsystem compared with traditional processors with multilevel cache. As security, especially cryptography, has become indispensable in today's networks, we present a benchmark suite called NPCryptBench. It is the first benchmark specially designed to evaluate cryptographic performance on NPs, particularly that of processor and memory subsystem. By running NPCryptBench on Intel IXP network processors, we provide quantitative evidence that performance bottlenecks under such a highly parallel environment reside in memory hierarchy and prolonged access latency, instead of limited computing resources described in recent literature. To alleviate this memory-wall effect, we suggest several software optimizations, which averagely boost the benchmark throughput by 145% on Intel IXP2800. Our analysis and optimizations are also suitable for other NPs with similar architectures.
Engaging students with self-directed development of academic skills through a flipped classroom approach

The generic skills of critical analysis, academic writing and referencing are essential for successful student progression in Higher Education. Extra-curricular programmes of academic skills seminars can offer limited opportunity to evaluate the extent to which students have understood and are able to apply the key concepts to their academic work. To provide a more student-focused active learning environment a ‘flipped-classroom’ approach was introduced for ‘Introduction to Referencing’ seminars. Two short screencasts with follow up questions were used as pre-seminar preparatory resources to deliver the essential principles of referencing. The seminar time was then utilised for a series of student-centred activities. These were developed to evaluate students understanding of the essential aspects of referencing, foster student engagement with the learning process and promote peer-support. Despite limited engagement of some students with the pre-sessional materials, all students attending the seminars actively participated in the activities provided. These generated a greater degree of discussion and there was evidence of deeper learning with students applying generic concepts to specific contexts of their academic work. Overall, observations form the seminars and the positive reactions of the students suggests that the ‘flipped classroom’ provides the opportunity for more effective student- focused support and development of independent learning strategies.
A simulation and data analysis system for large‐scale, data‐driven oil reservoir simulation studies

The main goal of oil reservoir management is to provide more efficient, cost‐effective and environmentally safer production of oil from reservoirs. Numerical simulations can aid in the design and implementation of optimal production strategies. However, traditional simulation‐based approaches to optimizing reservoir management are rapidly overwhelmed by data volume when large numbers of realizations are sought using detailed geologic descriptions. In this paper, we describe a software architecture to facilitate large‐scale simulation studies, involving ensembles of long‐running simulations and analysis of vast volumes of output data. Copyright © 2005 John Wiley & Sons, Ltd.
' September 1989 LIDS-P-1911 RECURSIVE AND ITERATIVE ESTIMATION ALGORITHMS FOR MULTI-RESOLUTION STOCHASTIC PROCESSES

2 MULTISCALE REPRESENTATIONS AND STOCHASTIC PROCESSES ON TREES A current topic of great interest is the multi-resolution analysis of signals and the development of multi-scale algorithms. 2.1 Multiscale Wavelets and Tees In this paper we describe part of a research effort aimed at As developed in [7], the multi-scale representation of a developing a corresponding theory for stochastic processes continuous-time signal x(t) consists of a sequence of approx-described at multiple scales and for their efficient estimation imations specified in terms of a single function +(t), where or reconstruction given partial and/or noisy measurements the approximation at the mth scale is given by which may also be at several scales. The theories of multi-scale signal representations and wavelet transforms lead nat-+oo urally to models of signals(in one or several dimensions) on zm(t) = E z(m, n)q(2 m t-n) (2.1) trees and lattices. In this paper we focus on one particu-n=-oo lar class of processes defined on dyadic trees. The central The function 4 is far from arbitrary. In particular +(t) results of the paper are three algorithms for optimal esti-must be orthogonal to its integer translates 0(t-n), and, in mation/reconstruction for such processes: one reminiscent of order for the (m + 1)st approximation to be a refinement of the Laplacian pyramid and the efficient use of Haar trans-the mth, we require that forms, a second that is iterative in nature and can be viewed as a multigrid relaxation algorithm, and a third that repre-+(t) = Z h(n)0(2t-n) (2.2) sents an extension of the Rauch-Tung-Striebel algorithm to n processes on dyadic trees and involves a new discrete Riccati equation, which in this case has three steps: predict, merge, conditions for the desired properties of (t) to hold and for conditions for the desired properties of +(t) to hold and for and measurement update. Related work and extensions are also briefly discussed. also briefly discussed. of such a X, h pair is the Haar approximation in which +(t) = 1 INTRODUCTION 1 for t e [0,1) and 0 otherwise, corresponding to h(n) = 6(n) + 6(n-1), where 6(n) is the usual discrete impulse. As The investigation of multi-scale representations of signals shown in [7] there is a family of FIR h(n)'s and corresponding and the development of multi-scale algorithms has been and compactly supported 4(t)'s, where the smoothness of +(t) remains a topic of much interest in many applications. increases with the length …
Estimating importance of implicit factors in e-commerce recommender systems

In this paper, we discuss the importance of different types of implicit user feedback for creating useful recommendations on an e-commerce website. Each website user may provide us with many different types of implicit feedback and it is difficult to decide which one to use for recommendations. If our recommendation algorithm support using more implicit factors, we should also consider importance and "added value" of each factor. We have identified several widely used implicit factors and conducted real user online testing in order to compare their usefulness for recommending algorithms. We have also proposed some combinations of implicit factors and a test, to see if they improve recommendation performance in comparison with the single factor ones.
The fault detection problem in nonlinear systems

In this work, high gain nonlinear observers are used as residual generators to study the fault detection problem in a differential algebraic framework. We analyze the stability of the residual generator when a fault occurs. We consider two faults types: constant and constant sign time-varying. It is shown that under some soft conditions over the aforementioned faults the residual is different from zero.
Effect of soybean on fertility of male and female albino rats

This study aimed to investigate whether consumption of soybean is useful or harmful on reproductive hormones; ovary; uterus; mammary gland; testis and subsequent fertility. In the former experiment, male and female Wister albino rats were used in the present study. Each sex was randomly divided into 4 groups, control group fed on the basal diet (AIN93 G), three treated groups given 30, 60 and 90 gm cooked soybeans/70 kg human body weight (b.w.) for three months. Female rats showed that soybean significantly decreased free estradiol hormone (E2); progesterone hormone; follicle stimulating hormone (FSH); luteinizing hormone (LH); ovary weight and number of ovarian follicles. On the other hand soybean significantly increased total E2; sex hormone binding proteins (SHBP); uterus weight and caused uterus proliferation and cystic hyperplasia. The mammary gland showed gradual hyperplasia and mammary ducts showed proliferation. In male rats soybean significantly decreased free testosterone hormone; LH and FSH, meanwhile total testosterone hormone, SHBP, testes weight and testes diameter were significantly increased accompanied with spermatogenesis arrest. [Serag El Din, O.S. ; Batta, H. , Abd El Azim; Abd El Fattah, N. Effect of soybean on fertility of male and female albino rats. Journal of American Science 2011;7(6):872-883]. (ISSN: 1545-1003). http://www.americanscience. org.
Using multiple genetic variants as instrumental variables for modifiable risk factors

Mendelian randomisation analyses use genetic variants as instrumental variables (IVs) to estimate causal effects of modifiable risk factors on disease outcomes. Genetic variants typically explain a small proportion of the variability in risk factors; hence Mendelian randomisation analyses can require large sample sizes. However, an increasing number of genetic variants have been found to be robustly associated with disease-related outcomes in genome-wide association studies. Use of multiple instruments can improve the precision of IV estimates, and also permit examination of underlying IV assumptions. We discuss the use of multiple genetic variants in Mendelian randomisation analyses with continuous outcome variables where all relationships are assumed to be linear. We describe possible violations of IV assumptions, and how multiple instrument analyses can be used to identify them. We present an example using four adiposity-associated genetic variants as IVs for the causal effect of fat mass on bone density, using data on 5509 children enrolled in the ALSPAC birth cohort study. We also use simulation studies to examine the effect of different sets of IVs on precision and bias. When each instrument independently explains variability in the risk factor, use of multiple instruments increases the precision of IV estimates. However, inclusion of weak instruments could increase finite sample bias. Missing data on multiple genetic variants can diminish the available sample size, compared with single instrument analyses. In simulations with additive genotype-risk factor effects, IV estimates using a weighted allele score had similar properties to estimates using multiple instruments. Under the correct conditions, multiple instrument analyses are a promising approach for Mendelian randomisation studies. Further research is required into multiple imputation methods to address missing data issues in IV estimation.
Omega-Conotoxins as Experimental Tools and Therapeutics in Pain Management

Neuropathic pain afflicts a large percentage of the global population. This form of chronic, intractable pain arises when the peripheral or central nervous systems are damaged, either directly by lesion or indirectly through disease. The comorbidity of neuropathic pain with other diseases, including diabetes, cancer, and AIDS, contributes to a complex pathogenesis and symptom profile. Because most patients present with neuropathic pain refractory to current first-line therapeutics, pharmaceuticals with greater efficacy in pain management are highly desired. In this review we discuss the growing application of ω-conotoxins, small peptides isolated from Conus species, in the management of neuropathic pain. These toxins are synthesized by predatory cone snails as a component of paralytic venoms. The potency and selectivity with which ω-conotoxins inhibit their molecular targets, voltage-gated Ca2+ channels, is advantageous in the treatment of neuropathic pain states, in which Ca2+ channel activity is characteristically aberrant. Although ω-conotoxins demonstrate analgesic efficacy in animal models of neuropathic pain and in human clinical trials, there remains a critical need to improve the convenience of peptide drug delivery methods, and reduce the number and severity of adverse effects associated with ω-conotoxin-based therapies.
Physiological Mechanisms Controlling Cerebral Blood Flow

The major conceptions of cerebral blood flow (CBF) control dereloped In the 19th and 20th centuries are listed. The systems of CBF regulation are considered from the viewpoint of automatic control. In the classification of CBF regulation mechanisms, 4 types are identified. The effectors of CBF regulation, i.e. the specific arterial segments through which each type of regulation is accomplished, were found to be mainly the major arteries of the brain and the small pial arteries rather than the intracerebral arterioles. Review of controlling influences on these effectors of regulation, (myogenic, humoral and neurogenic), show that priority should be given to neurogenic mechanisms. Several criteria governing efficiency of CBF regulation are proposed. Review of interactions of different types of CBF regulation shows that there may be both synergistic and antagonistic relationships. Information about the processes is important for medical practice.