Miracle-dz/UniFAR-FTUs huggingface dataset:
Psychotic experiences and future school performance in childhood: a population‐based cohort study

Background Psychotic experiences are common in childhood and an important risk indicator of adverse mental health outcomes. However, little is known about the association of psychotic experiences with functional outcomes in childhood, particularly regarding school performance. The aim of the present study was to examine whether psychotic experiences were prospectively related to school performance in childhood. Methods This study was embedded in the population‐based Generation R Study (N = 2,362). Psychotic experiences were assessed using self‐reports on hallucinations at age 10 years. School performance was assessed using a standardized national school performance test at age 12 years. We considered the total school performance score, as well as language and mathematics subscales. Analyses were adjusted for sociodemographic characteristics, maternal nonverbal IQ, nonverbal IQ at age 6 years and co‐occurring psychopathology at age 10 years. Results Psychotic experiences were prospectively associated with poorer school performance scores (B = −0.61, 95% CI [−0.98;−0.25], p = .001), as well as poorer language (B percentile rank score = −2.00, 95% CI [−3.20;−0.79], p = .001) and mathematical ability (B percentile rank score = −1.75, 95% CI [−2.99;−0.51], p = .006). These associations remained after additional adjustment for nonverbal IQ at age 6 years (B = −0.51, 95% CI [−0.86;−0.16], p = .005), and co‐occurring internalizing (B = −0.40, 95% CI [−0.77;−0.03], p = .036) and externalizing problems (B = −0.40, 95% CI [−0.75;−0.04], p = .029), but not attention problems (B = −0.10, 95% CI [−0.47;0.26], p = .57). Conclusions Children with psychotic experiences had lower school performance scores than their nonaffected peers. The finding was independent of sociodemographic characteristics, intelligence and co‐occurring internalizing and externalizing problems, but not attention problems. This study suggests that psychotic experiences are associated with childhood functional impairments, although the relatively small effects and the role of attention problems warrant further exploration.
Quantifying Changes in British Columbia Dungeness Crab (Cancer magister) Landings Using Intervention Analysis

Natural or man-induced interventions may cause temporary or permanent changes in the behaviour of biological systems. To determine the impact of future management decisions, it is first necessary to quantify the effects of past interventions on the system. Only then can rational decisions be made so as to ensure that the desired response is achieved. However, time series data are often autocorrelated and this precludes the use of standard statistical tests. The linear stochastic intervention model outlined in this paper takes this autocorrelation into account and provides a procedure for quantifying the impacts of particular interventions. This model is employed to determine if there has been a significant abrupt decrease in Dungeness crab (Cancer magister) landings in British Columbia.
Integrated screening and treatment services for HIV, hypertension and diabetes in Kenya: assessing the epidemiological impact and cost‐effectiveness from a national and regional perspective

As people with HIV age, prevention and management of other communicable and non‐communicable diseases (NCDs) will become increasingly important. Integration of screening and treatment for HIV and NCDs is a promising approach for addressing the dual burden of these diseases. The aim of this study was to assess the epidemiological impact and cost‐effectiveness of a community‐wide integrated programme for screening and treatment of HIV, hypertension and diabetes in Kenya.
The in vivo and in vitro effect of a fructooligosaccharide prebiotic combined with alfalfa molt diets on egg production and salmonella in laying hens

The in vivo and in vitro Effect of a Fructooligosaccharide Prebiotic Combined with Alfalfa Molt Diets on Egg Production and Salmonella in Laying Hens. (May 2005) Lisa Michelle Donalson, B.S., Sam Houston State University Chair of Advisory Committee: Dr. Steven Ricke Salmonellosis affects an estimated 1.4 million people a year with a great majority of cases never being reported. Salmonella Enteritidis (SE) can be found in a variety of foods including poultry meat and eggs. Susceptibility of SE colonization is increased by molting. Induced molting is used in the poultry industry to rejuvenate the hen’s reproductive tract and increase post molt egg quality and production. The most common molting method is complete feed withdrawal. Recent animal welfare pressures have encouraged the industry to seek alternatives to feed withdrawal with one alternative being feeding a high fiber diet like alfalfa. Alfalfa is high in protein, but low in energy which is desirable for a molt diet. Alfalfa’s fermentation properties have been thought to be an inhibitor in pathogen colonization during molting. Including a prebiotic such as fructooligosaccharide (FOS) in the molt diet is thought to further decrease colonization while benefiting the indigenous microflora. Laying hens were molted using alfalfa combined with different ratios of layer ration in an in vivo experiment. The hens responded comparably to the alfalfa molt diets
Anuran HaemoprotozoaFound in the Vicinity of Nagasaki City 2. Dactylosoma ranarum (Kruse, 1890)

During a period of July to August, 1974, blood examinations of frogs and tad- poles collected from Mogi, near Nagasaki City, were carried out. Trypanosoma rotatorium (Mayer, 1843) was detected from the blood smears as reported in a previous paper (Miyata, 1976). From the smears at the same time, Dactylosoma ranarum (Kruse, 1890) was also found, and the following observations were obtained: 1) D. ranarum was found only from adult of Rana rugosa (larger than 4cm in body size), and 8 out of 21 frogs had this parasite in their blood. 2) From all smears in which D. ranarum was detected, T. rotatorium was found except one case. 3) Two types of schizogony were recognized. In type A, 3~10 nuclei
Significant life events and social connectedness in Australian women's gambling experiences

Aim The aim is to examine significant life events and social connections that encourage some women to gamble. Specifically, how do these events and connections described as important for women who develop gambling-related problems differ for women who remain recreational gamblers? Design 20 women who were electronic gaming machine (EGMs, poker machines, slots) players were interviewed using a brief interview guide. They also completed the nine question Problem Gambling Severity Index (PGSI) from the Canadian Problem Gambling Index CPGI). 11 women self-identified as recreational gamblers (RG) while 9 had sought and received help for their gambling problems (PG). Using a feminist, qualitative design and an adaptive grounded theory method to analyze their histories, a number of themes emerged indicating a progression to problem gambling for some and the ability to recognise when control over gambling was needed by others. Results Although both groups (RG and PG) reported common gambling motivations differences appeared in the strength of their social support networks and ways of coping with stress, especially stress associated with a significant life event. Conclusions The human need for social connectedness and personal bonds with others emphasised the usefulness of using social capital theories in gambling research with women.
Parental Divorce in Childhood and Loneliness in Young Adults

The effects of childhood parental separation and divorce on adult loneliness were studied. Eighty-seven volunteer male and female participants completed the UCLA Revised Loneliness Scale and the Reported Mourning Behavior Checklist. Data were analyzed using stepwise multiple regression, and results were acceptable at the . 05 level of significance. Analysis of the data revealed that there were significant relationships between reported mourning behaviors, as well as the respondents' ages at the time of parent separation, and loneliness.
A model for generating intravalues of time series

This paper presents a model for generating intravalues of time-series. The model uses a mean reverting stochastic process (MRSP). The deterministic or mean part of the process is forecasted by an autoregressive of order n, AR(n), model. The unobservable AR(n) coefficients are calculated by a Kalman Filter using n time series observations. The stochastic part of the process is a Brownian motion multiplied by a volatility term. Measures of the Kalman filter covariance matrix along with the process itself are used to capture the volatility dynamics for the intravalues of the time-series. The MRSP model also provides for the evolution of the intravalues of the time series. Experimental results are presented demonstrating the applicability of the model using daily data from the Dow Jones Industrial Average (DJIA) time series. Key-Words: -Mean reverting process, Autoregressive model, Kalman filter, time-series intravalues
Extending the Behavioral Theory of the Firm to Entrepreneurial Firms

While the Behavioral Theory of the Firm (BTOF) is one of the most popular theories of organizational change in the strategic management literature, the empirical work used to develop the theory used established firms; most empirical tests of the theory do likewise. Over the past decade or so, however, a number of studies have attempted to extend the BTOF to entrepreneurial firms. This paper examines the extent to which the BTOF applies to entrepreneurial firms. We propose that while some constructs and mechanisms specified in the BTOF (such as aspirations, routines, search, and learning) have limited relevance for entrepreneurial firms and need modifications to be relevant, other constructs and mechanisms (such as dominant coalitions and biases) have greater visibility and relevance in entrepreneurial firms than in larger firms. We conclude with a discussion of how we can most fruitfully apply the BTOF to explaining decision making by entrepreneurial firms.
Predicate Optimization for a Visual Analytics Database

Querying the content of images, video, and other non-textual data sources requires expensive content extraction methods. Modern extraction techniques are based on deep convolutional neural networks (CNNs) and can classify objects within images with as-tounding accuracy. Unfortunately, these methods are slow, needing several milliseconds per image using modern GPUs. The cost of content-based queries over a huge video corpus is prohibitive. A promising approach to reduce the runtime cost of queries of visual content is to use a hierarchical model, such as a cascade, where simple cases are handled by an inexpensive classifier. Prior work has sought to design cascades that optimize the computational cost of inference by, for example, using smaller CNNs. However, we observe that there are critical factors besides the inference time that dramatically impact the overall query time. Notably, by treating the input image format and the requisite data handling costs as part of our query optimization, we can enable much more efficient cascades. We find that by jointly optimizing the CNN architecture and input representation, we can provide up to a 40x speedup over the cascades used in the NoScope video query system. We find up to a 156x speedup over ResNet with no accuracy loss and a nearly 300x speedup for users willing to sacrificing some accuracy.
U SING A UTO TVM TO A UTOMATICALLY G ENERATE D EEP L EARNING L IBRARIES FOR M OBILE D EVICES

Providing automated performance portability remains an important challenge for deep learning systems. While popular networks enjoy high performance on popular hardware targets such as server-class GPUs and TPUs, porting even off-the-shelf models with reasonable performance to mobile and embedded systems remains challenging. In this demo, we will demonstrate the AutoTVM system, which provides an automated end-to-end solution for optimizing deep learning operator implementations from computational graph level model specification to specialized operator libraries.
Trypanosomes of some Fennoscandian birds

Linear measurements and derived indices of trypanosomes from species of Fennoscandian birds were compared to those reported form Trypanosoma avium, T. everetti, T. ontarioensis and T. paddae. The trypanosomes encountered in the Fennoscandian birds were identified as T. avium from Tengmalm's owl Aegolius funereus and the pied flycatcher Ficedula hypoleuca, T. everetti from the great tit Parus major and collared flycatcher F. albicollis and T. ontarioensis from the collared flycatcher; T. paddae was not seen.
Is all quadrupedalism the same? Form-function relationships in behaviorally distinct Asian colobines

Gait mechanics in habitual quadrupedal primates has been explored thoroughly. However, little is known about the movements of quadrupedal primates that regularly engage in other, more specialized, forms of locomotion (e.g., suspensory or leaping). It is unclear whether the patterns of quadrupedal locomotion in these anatomically specialized species are compromised in some way compared to other more habitual quadrupeds. This study examined patterns of quadrupedal locomotion in two genera (Pygathrix and Trachypithecus) of Asian colobines. Pygathrix is well-known amongst the old-world monkeys for its unique ability to both walk quadrupedally above branches and to adopt arm-swinging locomotion similar to the gibbons. Trachypithecus are more typical arboreal quadrupeds which rarely exhibit suspensory locomotion. This study takes advantage of the highly diversified locomotor behavior observed within Asian colobines to determine if the use of arm-swinging Pygathrix effects the way species of this genus moves during quadrupedal locomotion compared to the movement of closely related non-suspensory colobines (Trachypithecus). Results of a principal component analysis of locomotor variables demonstrate that quadrupedal locomotion of Pygathrixis different than that of Trachypithecus. These differences arise from variation in stride duration, elbow and knee flexion at touchdown and mid-stance, and hindlimb swing phase. The quadrupedal gaits of Pygathrix are characterized by some traits that increase security, but are also accompanied by a relatively more extended elbow and knee positions that act to increase the tendency for the animal to lose balance. Quadrupedal gaits of Trachypithecus are all similar to each other, representing minimal intrageneric variation.
Resonate-and-Fire Neurons as Frequency Selective Input Encoders for Spiking Neural Networks

—More and more embedded applications demand to cope with complex data while still being energy-efﬁcient. Neural networks provide the processing capabilities, but often cannot be utilised because of restricted power goals. Spiking neural networks have been shown to potentially solve this problem due to their hardware friendliness and energy efﬁciency. One remaining problem is the conversion of input data into event-based spikes in order to be processed. In this study, we examine using resonating neuron models to perform spectral transform and temporal spike encoding simultaneously directly on the analogue signal. Additionally, we compare the approach with the fast Fourier transform and demonstrate that both show comparable results while the neuromorphic realisation consumes signiﬁcantly less energy. With the resonating neurons as input stage for large spiking neural networks, it is possible to realise energy efﬁcient networks in neuromorphic hardware without the need of any digital logic. A limitation of the approach is the comparatively large silicon area needed to realise the circuit.
Relaxed Pruning: Memory-Efficient LSTM Inference Engine by Limiting the Synaptic Connection Patterns

This paper presents a memory-efficient LSTM inference engine using a new sparse matrix format with limited synaptic connection patterns. The proposed relaxed pruning uses soft thresholding which removes infrequent connection patterns. The initial experimental results show that memory requirement reduces by 1.52 ∼ 2.05 × over the widely used CSC format depending on the level of sparsity in weight matrices. This improvement comes with negligible accuracy degradation by allowing additional training epochs. Also, the relaxed pruning provides an opportunity to improve inference speed with proper hardware architecture support
Experimental Approach and CFD Simulation of Battery Electric Vehicle Body

Aerodynamic is considered the most significant factor affecting on vehicles fuel consumption and power requirements even at low speed. For this reason, there are much interest and some modifications that decrease drag coefficient and reduce the aerodynamic effectiveness. This study aims to develop an electrical car body (ECB) to decrease the drag coefficient and study the reflection of this parameter in the power consumption rate in different operating speeds. Six different models for car bodies (Bendra, Magenta, Violet, Bluria, Aqua and Vectra) with same wheelbase, height, and track width dimensions are designed. The design of these models has done using Solidworks software by surface tools. Numerical results (frontal area, drag coefficient, drag area and drag force) for the six models are recorded and compared to choose the best designed body. According to results Vectra model is chosen as a best design. The power consumption is calculated for each model at different operating speeds using two different software, Solidworks flow simulation and ANSYS fluent. Experimental results are obtained by testing 3D printing model for the best efficient model with scale 1: 25 at small subsonic open wind tunnel. The experimental results show good agreement with simulation results. Finally, Vectra simulation and experimental results are compared with the real electric and petrol cars to verify the competitive design for Vectra model.
Confidence Measures in Multiclass Speech Emotion Recognition using Ensemble Learning to Catch Blunders

Although Speech Emotion Recognition (SER) systems have continually been improved with regard to outputting decisions on class membership, it is only very recently that Confidence Measures (CM) have been incorporated into such systems. It is easy to presume that classifiers such as k-Nearest Neighbor, Naïve Bayes or Support Vector Machines that can readily output numeric distributions, can therefore easily produce confidence estimates. However these numeric outputs have proven not to be well correlated with classification confidence. With this in mind the contribution of this paper is threefold, 1) providing the first successful demonstration of confidence extraction in the multiclass problem of SER by using metrics from a k-NN meta-classifier within an ensemble architecture . 2) We also demonstrate how this system has shown improvement on a similar approaches discussed later, and 3) finally we note how confidence measures can be useful as a tool for catching blunderous predictions made in SER problems, which can be very useful in real world deployed systems.
MAPPING THE FUNDAMENTAL FREQUENCIES IN THE CITY OF BEIRUT USING AMBIENT NOISE MEASUREMENTS

Historically, Beirut the capital of Lebanon has been destroyed several times by earthquakes, the most devastating of which was the 551 A.D. offshore earthquake. Assessing the local seismic hazard and risk is therefore of primary importance for the whole country. The present study is part of a comprehensive set of experimental surveys providing physical insights and quantitative constraints on the site response variability within the city (Brax, 2013). The geology of Beirut constitutes an exception to the geological landscape in the area, in relation with its sub-horizontal platform (Fig.1). Stiff to hard Miocene and Cenomanian units are outcropping on two hills whereas the rest of the platform is covered by alluviums or sandy soils, resulting in highly variable near surface geological conditions throughout the city, which may in turn result in highly variable ground shaking characteristics In order to evaluate the soil effects, 30' long ambient noise measurements were conducted in 615 sites distributed over a region that covers the city of Beirut and parts of its suburbs. The dataset has been processed with the horizontal to vertical spectral ratio technique HVSR according to the SESAME guidelines, resulting in the identification of fundamental frequencies over the study area. Different assessments of the predominant frequencies were made individually by the authors in order to test the robustness of the results. A good correlation between H/V frequencies and the geology of the soil was found. Different zones with large amplitude peaks have also been identified. A detailed map of the fundamental frequencies of the soil was derived for the whole region of study. Despite its limitations, such a map provides a useful information on sub-surface conditions of the city, and highlights several zones where possible amplifications can be expected in future earthquakes, and result in higher risk. It also allows identifying zones, which should be the focus of further investigations. This map could be an important step on the way towards a seismic microzonation of the Greater Beirut area, which is essential for city planning and the optimal design of earthquake resistant structures. 1 Researcher, Conseil National de la Recherche Scientifique CNRS, Beirut, Lebanon, brax@cnrs.edu. lb 2 Researcher, Institut des Sciences de la Terre ISTerre/IRD, Grenoble, France, Cecile.Cornou@ujf-grenoble.fr 3 Researcher, Institut des Sciences de la Terre ISTerre, Grenoble, France, Christophe.Voisin@ujf-grenoble.fr 4 Senior Research Scientist, Institut des Sciences de la Terre ISTerre/IFSTTAR, Grenoble, France, pierreyves.bard@ujf-grenoble.fr
Bacteria con leche: Bacterial populations and antibiotic resistance within conventional, USDA organic, and local milk

Concerns over food production and processing, along with increasing outbreaks of foodborne illnesses and antibiotic resistant infections have led many consumers to seek alternative food sources in the organic and local food markets. This study compared conventional, USDA certified organic, and local “farmer’s market” milk types to determine whether there is any noticeable benefit to purchasing organic or locally harvested milk in terms of their bacterial populations and level of antibiotic resistance. Samples from various milk types were plated on Tryptic Soy Agar and Milk Agar plates to enumerate bacteria, and the cultivated bacteria tested for resistance to the antibiotics penicillin, erythromycin, tetracycline, and gentamicin. Bacterial cultures from the various milk samples were identified using 16S rRNA gene sequencing. Local farmer’s market milk had the most abundant and diverse bacterial composition, containing several potential pathogens, and a high general level of antibiotic resistance. Conventional milk samples also showed considerable bacterial counts and high levels of antibiotic resistance. On the other hand, USDA certified organic milk yielded no culturable bacteria on either TSA or MA plates. This study shows that concerned with food safety should consume USDA organic milk to lessen their exposure to high numbers of antibiotic resistant and potentially pathogenic bacteria.