Miracle-dz/UniFAR-FTUs huggingface dataset:
A preliminary comparison of the hopes of researchers, clinicians, and families for the future ethical use of genetic findings on schizophrenia

A written questionnaire about genetic testing was distributed to all registrants at The 2004 World Congress of Psychiatric Genetics, mailed to clinical psychiatrists obtained from a directory of clinicians practicing in New York City, and mailed to members of families who have multiple affected family members with schizophrenia. A total of 274 individuals responded (162 researchers, 64 clinicians, and 48 family members). This survey shows that the majority of family members who completed the questionnaire (83.3%) would want to be tested if a genetic test were to become available. Over half of the family members (56.2%) would want prenatal testing. Similarly, over half of the clinicians (56.3%) would recommend it, despite only 25% of the researchers reporting that it would be a future useful tool. All of the clinicians surveyed thought adoption agencies should inform families about a family history of schizophrenia, while only half of the researchers thought this should be done (51.9%). These differences in opinions between consumers, their clinicians, and researchers could be based on a lack of understanding of the amount of risk conferred to family members by reported gene variants. Providing public discussions for placing these risks in perspective should be the responsibility of researchers. Open public discussion of the ethical and social uses of the information gained from psychiatric genetic research and its limitations is encouraged. © 2005 Wiley‐Liss, Inc.
Machine learning and learning from machines

Machine learning has been around for decades or, depending on your view, centuries. To consider the tools and underpinnings of machine learning, one would need to go back to the work of Bayes and Laplace, the derivation of least squares, and Markov chains, all of which form the basis and the probability construct used pervasively in machine learning. There has been a flood of progress between 1950 (with Alan Turing's proposal of a learning machine) and early 2000 (with practical applications of deep learning in place and more recent advances such as AlexNet in 2012). Deep learning has demonstrated tremendous success in a variety of application domains in the past few years, and with some new modalities of applications, it continues to open new opportunities. The recent popularity and emergence of machine learning in the oil and gas industry is likely due to the abundance of unused or overlooked data and the economic need to extract additional information from the data currently used. Additionally, there is an unprecedented availability of computing power, easy-to-use coding libraries, and application programming interfaces, as well as recent and significant advances in various flavors of neural networks. In this paper, we will attempt to show how machine learning can assist geoscientists in performing routine tasks in a much shorter time frame. We assert that there is a great opportunity for geoscientists to learn from machines, use these techniques to quality check their work, and gain nuanced insights from their data. Another advantage is that these approaches lead to the optimization of machine learning workflows by providing more accurate training data sets thus driving continuous learning and enhancement of the model.
The relationship between acute otitis media and the anatomic form of the hard palate.

PURPOSE Acute otitis media (AOM) is a serious health concern for millions of children. This study was conducted to determine the relationship between AOM and the shape of the hard palate. METHODS Intraoral examinations were performed on 175 pediatric dental patients ages 4-6. The palatal height was classified as high, medium or low. The accompanying parent completed a survey regarding their child's age, gender, overall health, history of AOM and presence of known risk factors for AOM. RESULTS Eighty five percent of the total sample had a positive history for AOM, with 76% experiencing AOM prior to age 1. High palatal vault was a significant finding in children that experienced AOM before age 1 (odds ratio 3.49). Logistic regression analysis revealed that children with high palatal vaults underwent tube placement more often than the rest of the study population (odds ratio 2.49). CONCLUSIONS Our study revealed a relationship between the presence of high palatal vaults and early, recurrent acute otitis media in young children. Recognition of high palatal vault in children suffering from AOM, in the presence of other known risk factors, may guide health care professionals to identify an otitis media prone patient and aid in prevention of recurrence.
Convergence of Policy Gradient Methods for Finite-Horizon Exploratory Linear-Quadratic Control Problems

We study the global linear convergence of policy gradient (PG) methods for finite-horizon continuous-time exploratory linear-quadratic control (LQC) problems. The setting includes stochastic LQC problems with indefinite costs and allows additional entropy regularisers in the objective. We consider a continuous-time Gaussian policy whose mean is linear in the state variable and whose covariance is state-independent. Contrary to discrete-time problems, the cost is noncoercive in the policy and not all descent directions lead to bounded iterates. We propose geometry-aware gradient descents for the mean and covariance of the policy using the Fisher geometry and the Bures-Wasserstein geometry, respectively. The policy iterates are shown to satisfy an a-priori bound, and converge globally to the optimal policy with a linear rate. We further propose a novel PG method with discrete-time policies. The algorithm leverages the continuous-time analysis, and achieves a robust linear convergence across different action frequencies. A numerical experiment confirms the convergence and robustness of the proposed algorithm.
San Francisco Crime Classification

The task of crime prevention is constrained by police resources. For the safety of a city, if the police is aware of what kinds of crimes are mainly going on, and what their distribution is over the city, they can identify where to target police resources and help alleviate crimes. In this paper, given time and location, we predicted the category of crimes that occurred from 2003 to 2015 in San Francisco’s neighborhoods based on a dataset derived from SFPD Crime Incident Reporting System. We investigated classification models including Näıve Bayes, k -NN, Gradient Tree Boosting and analyze their pros and cons on this prediction task. Since this is a competition currently held by Kaggle, we also submitted our results to Kaggle and compared them with the public leaderboard, ranking nearly top 10% on our best performance in the end.
State-Dependent Computation Using Coupled Recurrent Networks

Although conditional branching between possible behavioral states is a hallmark of intelligent behavior, very little is known about the neuronal mechanisms that support this processing. In a step toward solving this problem, we demonstrate by theoretical analysis and simulation how networks of richly interconnected neurons, such as those observed in the superficial layers of the neocortex, can embed reliable, robust finite state machines. We show how a multistable neuronal network containing a number of states can be created very simply by coupling two recurrent networks whose synaptic weights have been configured for soft winner-take-all (sWTA) performance. These two sWTAs have simple, homogeneous, locally recurrent connectivity except for a small fraction of recurrent cross-connections between them, which are used to embed the required states. This coupling between the maps allows the network to continue to express the current state even after the input that elicited that state is withdrawn. In addition, a small number of transition neurons implement the necessary input-driven transitions between the embedded states. We provide simple rules to systematically design and construct neuronal state machines of this kind. The significance of our finding is that it offers a method whereby the cortex could construct networks supporting a broad range of sophisticated processing by applying only small specializations to the same generic neuronal circuit.
Performance Evaluation of Conservative Algorithms in Parallel Simulation Languages

Parallel discrete event simulation with conservative synchronization algorithms has been used as a high performance alternative to sequential simulation. In this paper, we examine the performance of a set of parallel conservative algorithms that have been implemented in the Maisie parallel simulation language. The algorithms include the asynchronous null message algorithm, the synchronous conditional event algorithm, and a new hybrid algorithm called Accelerated Null Message that combines features from the preceding algorithms. The performance of the algorithms is compared using the Ideal Simulation Protocol. This protocol provides a tight lower bound on the execution time of a simulation model on a given architecture and serves as a useful base to compare the synchronization overheads of the different algorithms. The performance of the algorithms is compared as a function of various model characteristics that include model connectivity, computation granularity, load balance, and lookahead.
Supporting Online Material Materials and Methods Som Text Figs. S1 to S4 Tables S1 and S2 References a Virus in a Fungus in a Plant: Three-way Symbiosis Required for Thermal Tolerance

A mutualistic association between a fungal endophyte and a tropical panic grass allows both organisms to grow at high soil temperatures. We characterized a virus from this fungus that is involved in the mutualistic interaction. Fungal isolates cured of the virus are unable to confer heat tolerance, but heat tolerance is restored after the virus is reintroduced. The virus-infected fungus confers heat tolerance not only to its native monocot host but also to a eudicot host, which suggests that the underlying mechanism involves pathways conserved between these two groups of plants. E ndophytic fungi commonly grow within plant tissues and can be mutualistic in some cases, as they allow plant adaptation to extreme environments (1). A plant-fungal symbiosis between a tropical panic grass from geothermal soils, Dichanthelium lanuginosum, and the fungus Curvularia protuberata allows both organisms to grow at high soil temperatures in Yellowstone National Park (YNP) (2). Field and laboratory experiments have shown that when root zones are heated up to 65°C, non-symbiotic plants either become shriveled and chlorotic or simply die, whereas symbiotic plants tolerate and survive the heat regime. When grown separately, neither the fungus nor the plant alone is able to grow at temperatures above 38°C, but symbiotically, they are able to tolerate elevated temperatures. In the absence of heat stress, symbiotic plants have enhanced growth rate compared with nonsymbiotic plants and also show significant drought tolerance (3). Fungal viruses or mycoviruses can modulate plant-fungal symbioses. The best known example of this is the hypovirus that attenuates the virulence (hypovirulence) of the chestnut blight fungus, Cryphonectria parasitica (4). Virus regulation of hypovirulence has been demonstrated experimentally in several other pathogenic fungi (5–8). However, the effect of mycoviruses on mutualistic fungal endophytes is unknown. There is only one report of a mycovirus from the well-known mutualistic endophyte, Epichloë festucae, but no phenotype has been associated with this virus (9). Fungal virus genomes are commonly composed of double-stranded RNA (dsRNA) (10). Large molecules of dsRNA do not normally occur in fungal cells and, therefore, their presence is a sign of a viral infection (9). Using a protocol for nucleic acid extraction with enrichment for dsRNA (11), we detected the presence of a virus in C. protuberata. The dsRNA banding pattern consists of two segments of about 2.2 and 1.8 kb. A smaller segment, less than 1 kb in length, was variable in presence and size in the isolates …
Representing Cognitive Activity in Complex Tasks

While cognitive theory has been recognised as essential for the analysis of Human-Computer Interaction, the representations that have been developed have been directed more towards theoretical purposes than practical application. To bridge the gap between theory and application, representations need to satisfy requirements for broad scope, a unified theoretical basis, and abstraction. Interacting Cognitive Subsystems (ICS) is proposed as a unified cognitive theory that can be used as the basis for such representations, and two approaches based upon the theory are described. One entails the description of Cognitive Task Models, which are a relatively complete representation of the cognitive activity required of a user in the course of an interaction. The other entails the production of less complete diagrammatic notations that are intended to provide support in small scale problem identification and resolution, and which can be applied across tasks, visual interface and sound interface issues, and can handle static and dynamic situations. While the former can be implemented in a production-rule expert system (ICSpert) and so does not require detailed modelling knowledge on the part of the analyst, the latter is a pencil and paper technique that does require theoretical knowledge, but which is intended to facilitate the acquisition of such knowledge in the interest of educating its users about the human aspects of HCI. The representations differ in the knowledge required for their use, in the support that they offer, and in the situations for which they are appropriate. They have been used to represent problems from experimental situations, core HCI scenarios, and ‘real world’ design projects. They share breadth of scope and abstraction, and their parent theory supports transfer of knowledge across domains of application and from older to newer technologies, and supports feedback between the domain of application and the domain of theory. Philip Barnard is a psychologist with an interest in theories of mental architecture and their application to complex tasks, emotion and a range of psychopathologies; he is on the scientific staff of the Medical Research Council's Cognition and Brain Sciences Unit. Jon May is a psychologist with an interest in the application of unified models of cognition to perception, particularly with regard to the effects of task and context; he is a Lecturer in the Department of Psychology at the University of Sheffield. Acknowledgements . We thank our partners in both Amodeus projects for their constant requirement that we explain ourselves more clearly, and in particular Anker Jørgensen and his students at Copenhagen University for supporting the development of the Diagrammatic Representations. Notes: Authors are in alphabetical order. Support . This work was carried out as part of the Amodeus-2 project, ESPRIT Basic Research Action 7040 funded by the Commission of the European Communities. Technical reports from the Amodeus project are available via the World Wide Web at http://www.mrc-cbu.cam. ac.uk/amodeus/ Representing Cognitive Activity
Advances in Aurora kinase inhibitor patents

Background: Aurora-A, Aurora-B and Aurora-C, members of serine/threonine kinase family, play an important role in mitosis. They are essential for spindle assembly, centrosome maturation, chromosomal segregation and cytokinesis during mitosis. Abnormalities in the mitotic process as a result of overexpression/amplification of Aurora kinase have been linked to genomic instability leading to tumorigenesis. Hence, the use of Aurora kinase small-molecule inhibitors as a potential molecular-targeted therapeutic intervention for cancer is being pursued. Objective: A number of reviews focus on the biology of Aurora kinase; a few focus on the medicinal chemistry aspect of Aurora kinase inhibitor development. Here, we review the medicinal chemistry aspect of Aurora kinase inhibitors, with a particular emphasis on the patent literature. Method: The Scifinder® and Delphion® databases were used to search the literature for Aurora kinase inhibitors. Approximately 150 patents and 700 journal references are available, most of them published in the last 5 years. Conclusion/results: Analysis of the literature reveals three common strategies utilized by different groups in developing Aurora kinase inhibitors. These are discussed in detail and could be of use to medicinal chemists in laying out new strategies for developing novel Aurora kinase inhibitors.
The Three Types of Factor Models: A Comparison of Their Explanatory Power

Multifactor models of security market returns can be divided into three types: macroeconomic, fundamental, and statistical factor models. Macroeconomic factor models use observable economic time series, such as inflation and interest rates, as measures of the pervasive shocks to security returns. Fundamental factor models use the returns to portfolios associated with observed security attributes such as dividend yield, the book-to-market ratio, and industry identifiers. Statistical factor models derive their pervasive factors from factor analysis of the panel data set of security returns. This paper compares the explanatory power of these three approaches for U.S. equity returns.
Investigation of stresses in a Kevlar (491PR-286) material disc by the Chebyshev pseudospectral method

In this study, a composite disc with Kevlar (491PR-286) material was modeled. Kevlar consists of very strong fibers of very light carbon origin. That is why they are used quite often in unmanned aerial vehicles and spacecraft. The disc has been subjected to thermal stress under a linearly increasing temperature distribution. The temperature limit conditions were applied as 25 °C, 50 °C, 75 °C, 100 °C, and 150 °C. The obtained findings were determined using a computer program, the psedudospectral Chebyshev method, and analytically in three different ways. The main difference between this study and other studies is that it investigates the thermal stresses occurring in circular discs using different methods. The results obtained are compared fairly among themselves and presented with graphs. It was determined that tangential stresses were higher than radial stresses at the studied temperature values. In the analytical study conducted, the radial stresses on the inner and outer surfaces of the disc were determined to be zero for the boundary conditions. Under the increasing temperature distribution from the inner surface to the outer surface, tangential stresses occurred as tensile stress on the inner part of the disc and compressive stress on the outer part. Under the decreasing temperature distribution from the inner surface to the outer surface, tangential stresses are pressed on the inner part of the disc, resulting in a tensile stress on the outer part. It is observed that with increasing temperature, there is an increase in radial and tangential stress values. At the end of the study, it was concluded that Kevlar (491PR-286) material discs can be used at high temperatures.
The relationship between religiosity of Kazakh women and attitudes toward political, economic, and social factors in modern day Kazakhstan

How does religiosity of a Kazakh woman impact her attitudes toward the political, economic, and social climate of modern day Kazakhstan? There is no reason to presume that Kazakh women have the same opinions as Muslim women from the Islamic countries of the Middle East and Northern Africa if we hold that culture influences social, and therefore religious, life. I argue that Islam in Kazakhstan includes distinct rituals and cultural aspects surrounding religious practice that shape the attitudes of Kazakh women, differentiating them from Muslim women in other Islamic countries. This results from a combination of Islamic rituals and beliefs from Tengrianism, the religion of the Kazakh nomads. I found a weak relationship between religiosity and most political, economic, and social attitudes of Kazakh women. These findings prove that it is vital to treat each Muslim country as a specific case, rather than to generalize the nature of countries with common ethnic groups or religious majorities. As the global prevalence of radical Islamic groups increases, cultivating an understanding of Islam in areas of the world such as Central Asia is vital to comprehending the non-radical realizations of Islam as a belief system.
The Value of Markov Chain Games with Lack of Information on One Side

We consider a two-player zero-sum game, given by a Markov chain over a finite set of states and a family of matrix games indexed by states. The sequence of states follows the Markov chain. At the beginning of each stage, only Player 1 is informed of the current state, then the corresponding matrix game is played, and the actions chosen are observed by both players before proceeding to the next stage. We call such a game a Markov chain game with lack of information on one side. This model generalizes the model of Aumann and Maschler of zero-sum repeated games with lack of information on one side (which corresponds to the case where the transition matrix of the Markov chain is the identity matrix). We generalize the proof of Aumann and Maschler and, from the definition and the study of appropriate nonrevealing auxiliary games with infinitely many stages, show the existence of the uniform value. An important difference with Aumann and Maschler's model is that here the notions for Player 1 of using the information and revealing a relevant information are distinct.
New mexhanical stress transducers based on amorphous alloys

Novel stress transducers of simple construction are described, which can easily be formed into arrays with a great reduction in interconnections relative to discrete strain gauges. Their frequency response extends to DC, and the arrays lend themselves to measuring distribution of pressure or shear at interfaces between contacting surfaces. The principle of operation is based mainly on the properties of acoustic delay lines made of high magnetostriction materials, in particular amorphous alloys. A sensor site is defined by the crossing of a conductor close to a delay line. A pulsed current in the conductor creates an acoustic pulse in the delay line. Mechanical input to the sensor modulates this excitation. This occurs either by displacement of a passive core or by change in its permeability due to stress. Sensors at different sites along the line can be excited simultaneously, producing pulses which are detected serially. Experimental work showing the response of prototype transducers in which Metglas 2605SC alloy is used both as the delay line and as the stress converter is reported. Aspects of performance including the spatial resolution achievable and design factors relating to applications are discussed. >
Human Attention in Visual Question Answering: Do Humans and Deep Networks look at the same regions?

We conduct large-scale studies on `human attention' in Visual Question Answering (VQA) to understand where humans choose to look to answer questions about images. We design and test multiple game-inspired novel attention-annotation interfaces that require the subject to sharpen regions of a blurred image to answer a question. Thus, we introduce the VQA-HAT (Human ATtention) dataset. We evaluate attention maps generated by state-of-the-art VQA models against human attention both qualitatively (via visualizations) and quantitatively (via rank-order correlation). Overall, our experiments show that current attention models in VQA do not seem to be looking at the same regions as humans.