Miracle-dz/UniFAR-FTUs huggingface dataset:
A validation of wrist actigraphy against polysomnography in patients with schizophrenia or bipolar disorder

Purpose Sleep disturbances are frequent in patients with schizophrenia or bipolar disorder. Actigraphy has been established as a generally reliable method to examine these disturbances across varying time spans, but the validity against polysomnography (PSG) is not well investigated for this population. We validated wrist-worn actigraphy against PSG in a population of chronic, medicated patients with schizophrenia or bipolar disorder. Patients and methods From a clinical trial, we derived data from 37 patients with schizophrenia and five patients with bipolar disorder who were examined with one-night PSG and concomitant actigraphy. The following sleep variables were compared between the two methods: total sleep time, sleep efficiency, sleep latency, number of awakenings, and time awake after sleep onset. The degree of consistency between the two methods was evaluated using the intra-class correlation coefficient and Bland–Altman plots. Subgroup analyses included splitting the analyses according to sex, diagnosis, and duration of wakefulness after sleep onset. PSG was considered the gold standard. Results The intraclass correlation coefficient was high for total sleep time, moderate for the number of awakenings, and low or zero for the other examined sleep variables. These findings were reproduced in the subgroup analyses that compared men and women, as well as patients with bipolar versus schizophrenia spectrum disorders. When excluding patients with extensive periods of wakefulness after the initial sleep period (wake after sleep onset > 100 minutes), the reliability of the actigraphy-derived sleep variables markedly improved. Conclusion Actigraphy reliably measures the total sleep time in this specific patient population. For patients without extensive periods of wakefulness after sleep onset, actigraphy might provide a useful measure of sleep efficiency, sleep latency, and number of awakenings.
Automatic Bridge Bidding Using Deep Reinforcement Learning

Bridge is among the zero-sum games for which artificial intelligence has not yet outperformed expert human players. The main difficulty lies in the bidding phase of bridge, which requires cooperative decision making with partial information. Existing artificial intelligence systems for bridge bidding rely on, and are thus restricted by, human-designed bidding systems or features. In this work, we propose a flexible and pioneering bridge-bidding system, which can learn either with or without the aid of human domain knowledge. The system is based on a novel deep reinforcement learning model, which extracts sophisticated features and learns to bid automatically based on raw card data. The model includes an upper-confidence-bound algorithm and additional techniques to achieve a balance between exploration and exploitation. We further study how different pieces of human knowledge can be exploited to assist the model. Our experiments demonstrate the promising performance of our proposed model. In particular, the model can advance from having no knowledge on bidding to achieving a superior performance compared with a champion-winning computer bridge program that implements a human-designed bidding system. In addition, further synergies can be extracted by incorporating expert knowledge into the proposed model.
In vitro inhibitory effects of plant-derived by-products against Cryptosporidium parvum

Disposal of organic plant wastes and by-products from the food or pharmaceutical industries usually involves high costs. In the present study, 42 samples derived from such by-products were screened in vitro against Cryptosporidium parvum, a protozoan parasite that may contaminate drinking water and cause diarrhoea. The novel bioassay was previously established in the microtitre plate format. Human ileocaecal adenocarcinoma (HCT-8) cell cultures were seeded with C. parvum oocysts and parasite development was monitored by an indirect fluorescent antibody technique (IFAT) and microscopic assessment for clusters of secondary infection (CSI). Minimum inhibitory concentrations (MICs) and potential detrimental effects on the host cells were determined. An ethanolic extract from olive (Olea europaea) pomace, after oil pressing and phenol recovery, reproducibly inhibited C. parvum development (MIC = 250–500 μg mL−1, IC50 = 361 (279–438) μg mL−1, IC90 = 467 (398–615) μg mL−1). Accordingly, tyrosol, hydroxytyrosol, trans-coniferyl alcohol and oleuropein were selected as reference test compounds, but their contributions to the observed activity of the olive pomace extract were insignificant. The established test system proved to be a fast and efficient assay for identifying anti-cryptosporidial activities in biological waste material and comparison with selected reference compounds.
Bayesian Forecasting

Bayesian forecasting is a natural product of a Bayesian approach to inference. The Bayesian approach in general requires explicit formulation of a model, and conditioning on known quantities, in order to draw inferences about unknown ones. In Bayesian forecasting, one simply takes a subset of the unknown quantities to be future values of some variables of interest. This paper presents the principles of Bayesian forecasting, and describes recent advances in compuational capabilities for applying them that have dramatically expanded the scope of applicability of the Bayesian approach. It describes historical developments and the analytic compromises that were necessary prior to recent developments, the application of the new procedures in a variety of examples, and reports on two long-term Bayesian forecasting exercises. in terms of forecasting ability, . a good Bayesian will beat a non-Bayesian, who will do better than a bad Bayesian. (C.W.J. Granger, 1986, p. 16)
Security Vulnerabilities of Emerging Nonvolatile Main Memories and Countermeasures

Emerging nonvolatile memory devices such as phase change memories and memristors are replacing SRAM and DRAM. However, nonvolatile main memories (NVMM) are susceptible to probing attacks even when powered down. This way, they may compromise sensitive data such as passwords and keys that reside in the NVMM. To eliminate this vulnerability, we propose sneak-path encryption (SPE), a hardware intrinsic encryption technique for memristor-based NVMMs. SPE is instruction set architecture independent and has minimal impact on performance. SPE exploits the physical parameters, such as sneak-paths in crossbar memories, to encrypt the data stored in a memristor-based NVMM. SPE is resilient to a number of attacks that may be performed on NVMMs. We use a cycle accurate simulator to evaluate the performance impact of SPE-based NVMM and compare against other security techniques. SPE can secure an NVMM with a ~1.3% performance overhead.
A Laboratory Study of Duopoly Price Competition with Patient Buyers

This article reports a duopoly experiment in which sellers compete to sell to a potentially patient buyer. Each period sellers simultaneously post prices and the buyer costlessly observes either one or both prices. The buyer can then either accept an observed price or reject all offers. Following a rejection, sellers may have an opportunity to post prices again in another round. We study how the duopolists' pricing behavior responds to changes in the likelihood of the buyer observing multiple prices, γ, and the probability of continuing to another round, δ. The unique stationary equilibrium features mixed strategies. Consistent with the equilibrium, observed prices are decreasing in γ and δ. Contrary to the equilibrium, however, buyers sometimes reject profitable price offers, and average prices are lower than predicted when only one round of offers is possible and higher than predicted in the multiple‐round game.
The 2016 Pennsylvania Presidential and U.S. Senate Elections: Breaking Pennsylvania’s Electoral Habits

This article uses pre-election survey data, post-election survey data, and voter registration and election data to interpret the outcomes of the 2016 presidential and U.S. Senate races in Pennsylvania. This analysis shows how changes in voter registration and voter turnout in specific areas of the Commonwealth, driven in large part by less-educated voters, those dissatisfied with the current direction of the country, and the performance of the incumbent president, explain the 2016 election results.
An improved design of Piezo-Composite Actuator used as the artificial muscle for bio-inspired robots

During the past decade, lots of diverse researches have been conducted on application of smart materials to build small-scale robots. Several small, powerful, and reliable piezoelectric actuators using piezoelectric ceramic materials have been invented. Among them, LIPCA was introduced as the best unimorph actuator suitable for bio-inspired robots. The actuator plays the role as an artificial muscle which can produce up-and-down bending motion as voltage is applied. This paper presents an improved design of LIPCA (lightweight piezo-composite actuator) by using the direct piezoelectric effect along the poling direction (d33 mode) with interdigitated electrodes patterned on the two surfaces of PZT wafer that could help the new LIPCA enhancing the actuation performance considerably. An analytical model is used to give a comparison on the performance between the new design and the traditional LIPCA. Numerical optimization analysis on the design variables as electrode width, gap between electrodes and applied voltage for poling process is also performed.
Effects of hyaluronic acid on bleeding following third molar extraction

Abstract Objective To explore the effects of hyaluronic acid (HA) on bleeding and associated outcomes after third molar extraction. Methods Forty patients who had undergone molar extraction were randomly divided into two groups; 0.8% (w/v) HA was applied to the HA group (n=20) whereas a control group (n=20) was not treated. Salivary and gingival tissue factor (TF) levels, bleeding time, maximum interincisal opening (MIO), pain scored on a visual analog scale (VAS), and the swelling extent were compared between the two groups. Results HA did not significantly affect gingival TF levels. Salivary TF levels increased significantly 1 week after HA application but not in the control group. Neither the VAS pain level nor MIO differed significantly between the two groups. The swelling extent on day 3 and the bleeding time were greater in the HA group than in the control group. Conclusions Local injection of HA at 0.8% prolonged the bleeding time, and increased hemorrhage and swelling in the early postoperative period after third molar extractions.
Pengembangan Model Bimbingan Kelompok Berbasis Islami Untuk Meningkatkan Kecerdasan Sosial Siswa Smk Swasta Di Kota Semarang

The research is aimed to 1) know the implementation of group counseling in private vocational school in Semarang. 2) know the social intelligence condition in SMK Roudiotus Saidiyyah Semarang. 3) Produce Islamic teaching based group counseling model to increase social intelligence of students in Roudiotus Saidiyyah Semarang. 4) ehther or not the implementation of the islamic teaching based group counseling model effectiveness in increasing social intelligence of the students in Roudiotus Saidiyyah Semarang. The research method used is Research and Development (R & D) method. The data analysis technique used are both qualitative and quantitative. The findings were the Islamic teaching based group counseling model consists of rasional, vision and misson, objectives, the model content, the stages in Islamic teaching based group counseling model, role and function of the group leader, group member qualification, evaluation and follow up.
Properties, Dimensions, and Heritability of Obsessive-Compulsive Symptoms in a Community Sample of Children and Adolescents

Obsessive-compulsive disorder (OCD) is a debilitating neuropsychiatric disorder commonly seen in children and adolescents. The etiology of OCD remains elusive mostly due to its complex, heterogeneous phenotype and genotype. Increasing evidence support a multidimensional model of OCD and a continuous nature of obsessive-compulsive (OC) symptoms in the general population. However, there is limited understanding of OC symptoms in pediatric populations. Using a novel questionnaire, the Toronto Obsessive Compulsive Scale, we investigated properties, dimensions, and heritability of OC symptoms in a community sample of 16,380 children and adolescents, and a sub-sample of 220 twin pairs, respectively. We identified six distinct OC symptom dimensions in our study that parallel those identified in previous studies: (1) Superstition, (2) Cleaning/Contamination, (3) Hoarding, (4) Symmetry/Ordering, (5) Checking/Counting, (6) Rumination. Phenotypic and heritability characteristics of overall and dimensions of OC symptoms are reviewed in detail. Research and clinical implications of the current study are also discussed.
The Density of Fan-Planar Graphs

A topological drawing of a graph is fan-planar if for each edge $e$ the edges crossing $e$ form a star and no endpoint of $e$ is enclosed by $e$ and its crossing edges. A fan-planar graph is a graph admitting such a drawing. Equivalently, this can be formulated by three forbidden patterns, one of which is the configuration where $e$ is crossed by two independent edges and the other two where $e$ is crossed by two incident edges in a way that encloses some endpoint of $e$. A topological drawing is simple if any two edges have at most one point in common. Fan-planar graphs are a new member in the ever-growing list of topological graphs defined by forbidden intersection patterns, such as planar graphs and their generalizations, Turán-graphs and Conway's thrackle conjecture. Hence fan-planar graphs fall into an important field in combinatorial geometry with applications in various areas of discrete mathematics. As every $1$-planar graph is fan-planar and every fan-planar graph is $3$-quasiplanar, they also fit perfectly in a recent series of works on nearly-planar graphs from the areas of graph drawing and combinatorial embeddings. In this paper we show that every fan-planar graph on $n$ vertices has at most $5n-10$ edges, even though a fan-planar drawing may have a quadratic number of crossings. Our bound, which is tight for every $n \geq 20$, indicates how nicely fan-planar graphs fit in the row with planar graphs ($3n-6$ edges) and $1$-planar graphs ($4n-8$ edges). With this, fan-planar graphs form an inclusion-wise largest non-trivial class of topological graphs defined by forbidden patterns, for which the maximum number of edges on $n$ vertices is known exactly. We demonstrate that maximum fan-planar graphs carry a rich structure, which makes this class attractive for many algorithms commonly used in graph drawing. Finally, we discuss possible extensions and generalizations of these new concepts.
The Impact of Early Adversity and Trauma on Adolescent's Epistemic Trust and Learning

This volume is comprised of three parts. Part 1 is a systematic literature review, which summarises the impact of trauma in the parent-child relationship on children’s learning. It critically appraises 32 studies examining the domains of cognitive development, academic performance and functional ability, and social information processing. Despite mixed findings, it concludes that there is a vulnerability of impairments across a range of domains, with the exception of executive functioning. Nine studies identified moderators that may account for some of the variability in findings. Further research is indicated for all domains, and underlines the need for larger sample sizes and the identification of further factors that may be associated with trauma and learning. Part 2 is an empirical paper that examines in an adolescent sample the role of ostensive cues on Epistemic Trust (ET), learning and generalisation. It also explores whether trauma moderates these relationships, and whether trauma negatively impacts ET. The results show that ostensive cues impact ET but not learning and generalisation. Trauma did not moderate the use of ostensive cues, but was associated with ET. Possible reasons for the findings are suggested, as well as their implications for further research. The study was conducted as part of a joint project with Reches (2017) and Draper (2017). Part 3 is a critical appraisal providing reflections on the process of completing the empirical research. It considers the original aims of the study, the recruitment challenges, measurement considerations and my role as a trainee clinical psychologist while undertaking the research.
The Good, the Not So Bad, and the Ugly of Competitive Human Resource Practices: A Multidisciplinary Conceptual Framework

Human resource (HR) practices used to inject internal competition into the workplace are the subject of heated debates in business practice; this is however not the case in the field of human resource management (HRM) research. In this article, we first augment previous research in the field to offer an initial conceptualization of competitive HR practices. We then develop a conceptual framework that explains the processes and conditions that drive and determine the impact of competitive HR practices on employees at work. Blending insights from social comparison theory and uncertainty research, we theorize a set of conditions that specify when competitive HR practices unfold their “dark” side, and when the “not so bad” or even “a good side” of competitive HR practices might emerge.
Does Faculty Research Improve Undergraduate Teaching? An Analysis of Existing and Potential Synergies

Academicians have been arguing for decades about whether or not faculty research supports undergraduate instruction. Those who say it does—a group that includes most administrators and faculty members—cite many ways in which research can enrich teaching, while those on the other side cite numerous studies that have consistently failed to show a measurable linkage between the two activities. This article proposes that the two sides are debating different propositions: whether research can support teaching in principle and whether it has been shown to do so in practice. The article reviews the literature on the current state of the research‐teaching nexus and then examines three specific strategies for integrating teaching and scholarship: bringing research into the classroom, involving undergraduates in research projects, and broadening the definition of scholarship beyond frontier disciplinary research. Finally, ways are suggested to better realize the potential synergies between faculty research and undergraduate education.
Mother Vocal Recognition in Antarctic Fur Seal Arctocephalus gazella Pups: A Two-Step Process

In otariids, mother’s recognition by pups is essential to their survival since females nurse exclusively their own young and can be very aggressive towards non-kin. Antarctic fur seal, Arctocephalus gazella, come ashore to breed and form dense colonies. During the 4-month lactation period, females alternate foraging trips at sea with suckling period ashore. On each return to the colony, females and pups first use vocalizations to find each other among several hundred conspecifics and olfaction is used as a final check. Such vocal identification has to be highly efficient. In this present study, we investigated the components of the individual vocal signature used by pups to identify their mothers by performing playback experiments on pups with synthetic signals. We thus tested the efficiency of this individual vocal signature by performing propagation tests and by testing pups at different playback distances. Pups use both amplitude and frequency modulations to identify their mother’s voice, as well as the energy spectrum. Propagation tests showed that frequency modulations propagated reliably up to 64m, whereas amplitude modulations and spectral content greatly were highly degraded for distances over 8m. Playback on pups at different distances suggested that the individual identification is a two-step process: at long range, pups identified first the frequency modulation pattern of their mother’s calls, and other components of the vocal signature at closer range. The individual vocal recognition system developed by Antarctic fur seals is well adapted to face the main constraint of finding kin in a crowd.
COVNET: a cooperative coevolutionary model for evolving artificial neural networks

This paper presents COVNET, a new cooperative coevolutionary model for evolving artificial neural networks. This model is based on the idea of coevolving subnetworks that must cooperate to form a solution for a specific problem, instead of evolving complete networks. The combination of this subnetworks is part of a coevolutionary process. The best combinations of subnetworks must be evolved together with the coevolution of the subnetworks. Several subpopulations of subnetworks coevolve cooperatively and genetically isolated. The individual of every subpopulation are combined to form whole networks. This is a different approach from most current models of evolutionary neural networks which try to develop whole networks. COVNET places as few restrictions as possible over the network structure, allowing the model to reach a wide variety of architectures during the evolution and to be easily extensible to other kind of neural networks. The performance of the model in solving three real problems of classification is compared with a modular network, the adaptive mixture of experts and with the results presented in the bibliography. COVNET has shown better generalization and produced smaller networks than the adaptive mixture of experts and has also achieved results, at least, comparable with the results in the bibliography.
Nested autonomy for unmanned marine vehicles with MOOS‐IvP

This document describes the MOOS‐IvP autonomy software for unmanned marine vehicles and its use in large‐scale ocean sensing systems. MOOS‐IvP is composed of two open‐source software projects funded by the Office of Naval Research. MOOS provides a core autonomy middleware capability, and the MOOS project additionally provides a set of ubiquitous infrastructure utilities. The IvP Helm is the primary component of an additional set of capabilities implemented to form a full marine autonomy suite known as MOOS‐IvP. This software and architecture are platform and mission agnostic and allow for a scalable nesting of unmanned vehicle nodes to form large‐scale, long‐endurance ocean sensing systems composed of heterogeneous platform types with varying degrees of communications connectivity, bandwidth, and latency. © 2010 Wiley Periodicals, Inc.