Miracle-dz/UniFAR-FTUs huggingface dataset:
THE LAYERED STRUCTURE OF COMPOSITE MATERIALS BASED ON NIOBIUM ALLOY OBTAINED BY THE SOLID-PHASE TECHNOLOGY

The methods of diffusion welding and pack rolling in two cycles experimental samples were made of composite materials, differing in functional properties: the superconducting multilayer tape based alloy Nb-50Ti, stabilized with copper and refractory material with a layered structure. From the X-ray spectral analysis concluded that interdiffusion between the layers in multilayer composites with the formation of expected alloys and chemical compounds occurred mainly due to the diffusion of niobium and carbon. Due to the high mobility of atomic carbon was able to penetrate all the structural components of the composite and to form the reinforcing phase in the form of carbide precipitates and layers of silicon-carbon chemical compound.
ANESTHESIA IN OYSTERS OF THE GENUS Crassostrea CULTURED IN BRAZIL*

This study evaluated: 1) the time required for anaesthesia induction and recovery of oysters Crassostrea rhizophorae, Crassostrea gasar and Crassostrea gigas using magnesium chloride (MgCl2); 2) the survival after anaesthesia and gonad sampling; and 3) the D-larvae generation after anaesthesia. For each species, three groups of 10 animals were kept in 50 g L-1 MgCl2, salinity of 36 and temperature of 22 oC. One control group was kept in solution without MgCl2. Every 1 h anaesthetised oysters were recorded, sampled to determine sex and placed in clean seawater to assess recovering every 30 min. Gonad samplings were made beside the posterior adductor muscle, using 1 mL syringes and needles (0.60 x 25 mm). Factorial crosses were generated within and between anaesthetised and non-anaesthetised oyster groups to produce D-larvae in C. gigas. The survival after 10 days of anaesthesia was 100% for the three studied species. For C. rhizophorae and C. gigas, 100% of the animals were anaesthetised after 360 min and were recovered after 240 and 150 min, respectively. For C. gasar, 87% were anesthetised after 720 min and recovered after >240 min. There were no significant differences in D-larvae numbers between factorial crosses. The salt MgCl2 served as an efficient relaxant and caused no deleterious effect on the survival of the three studied species, or on the D-larvae generation in C. gigas.
Antinociceptive activities of the ethanolic extracts of ocimum kilimandscharicum baker ex gürke and ocimum kenyense ayob. ex a.j. paton leaves

Ocimum kilimandscharicum and Ocimum kenyense are two closely related species endemic to Kenya. They find wide application in a diverse array of medicinal applications, including pain relief. The present investigation was carried out to study their antinociceptive activity using the radiant tail-flick test in mice. At 100, 200, 400 and 800 (mg/kg Bwt) dosages, the ethanolic leaf extracts of both O. kilimandscharicum and kenyense exhibited statistically significant antinociceptive activities (p < 0.01), in a dose dependent manner. The experimental results obtained in this study therefore validate the traditional uses of these plant species as analgesics. Further, this study provides a springboard into future phytochemical and pharmacological studies of these plant species.
The Knot Spectrum of Confined Random Equilateral Polygons

Abstract It is well known that genomic materials (long DNA chains) of living organisms are often packed compactly under extreme confining conditions using macromolecular self-assembly processes but the general DNA packing mechanism remains an unsolved problem. It has been proposed that the topology of the packed DNA may be used to study the DNA packing mechanism. For example, in the case of (mutant) bacteriophage P4, DNA molecules packed inside the bacteriophage head are considered to be circular since the two sticky ends of the DNA are close to each other. The DNAs extracted from the capsid without separating the two ends can thus preserve the topology of the (circular) DNAs. It turns out that the circular DNAs extracted from bacteriophage P4 are non-trivially knotted with very high probability and with a bias toward chiral knots. In order to study this problem using a systematic approach based on mathematical modeling, one needs to introduce a DNA packing model under extreme volume confinement condition and test whether such a model can produce the kind of knot spectrum observed in the experiments. In this paper we introduce and study a model of equilateral random polygons con_ned in a sphere. This model is not meant to generate polygons that model DNA packed in a virus head directly. Instead, the average topological characteristics of this model may serve as benchmark data for totally randomly packed circular DNAs. The difference between the biologically observed topological characteristics and our benchmark data might reveal the bias of DNA packed in the viral capsids and possibly lead to a better understanding of the DNA packing mechanism, at least for the bacteriophage DNA. The purpose of this paper is to provide information about the knot spectrum of equilateral random polygons under such a spherical confinement with length and confinement ratios in a range comparable to circular DNAs packed inside bacteriophage heads.
Training Deep Neural Networks with 8-bit Floating Point Numbers

The state-of-the-art hardware platforms for training deep neural networks are moving from traditional single precision (32-bit) computations towards 16 bits of precision - in large part due to the high energy efficiency and smaller bit storage associated with using reduced-precision representations. However, unlike inference, training with numbers represented with less than 16 bits has been challenging due to the need to maintain fidelity of the gradient computations during back-propagation. Here we demonstrate, for the first time, the successful training of deep neural networks using 8-bit floating point numbers while fully maintaining the accuracy on a spectrum of deep learning models and datasets. In addition to reducing the data and computation precision to 8 bits, we also successfully reduce the arithmetic precision for additions (used in partial product accumulation and weight updates) from 32 bits to 16 bits through the introduction of a number of key ideas including chunk-based accumulation and floating point stochastic rounding. The use of these novel techniques lays the foundation for a new generation of hardware training platforms with the potential for 2-4 times improved throughput over today's systems.
New Insight into Hybrid Stochastic Gradient Descent: Beyond With-Replacement Sampling and Convexity

As an incremental-gradient algorithm, the hybrid stochastic gradient descent (HSGD) enjoys merits of both stochastic and full gradient methods for finite-sum minimization problem. However, the existing rate-of-convergence analysis for HSGD is made under with-replacement sampling (WRS) and is restricted to convex problems. It is not clear whether HSGD still carries these advantages under the common practice of without-replacement sampling (WoRS) for non-convex problems. In this paper, we affirmatively answer this open question by showing that under WoRS and for both convex and non-convex problems, it is still possible for HSGD (with constant step-size) to match full gradient descent in rate of convergence, while maintaining comparable sample-size-independent incremental first-order oracle complexity to stochastic gradient descent. For a special class of finite-sum problems with linear prediction models, our convergence results can be further improved in some cases. Extensive numerical results confirm our theoretical affirmation and demonstrate the favorable efficiency of WoRS-based HSGD.
THE IMPACT OF EARTHQUAKE ON CHILD TEST SCORE

Natural disasters always affect different aspects of individual life. They affect almost every part of life, such as the emotional, economic, physical, social, and environmental aspects. Children are believed to be very vulnerable to disasters. The increasing frequency of disasters and the intensity of their destruction motivate an analysis of the impacts of disasters, especially on education, for children. This paper uses a micro level survey data set from the Indonesian Family Life Survey (IFLS) which covers approximately 83% of the Indonesian population within the survey area. The main objective of this paper is to examine the effects of earthquakes on students’ performance, measured by their child test scores. This type of disaster was chosen because of its intensity, as measured by the percentage of people killed, and the percentage of people evacuated. Moreover, we also investigate the children who took the test immediately after the earthquake and compare their scores with those whose tests were a year after the earthquake. Arguably an earthquake is an exogenous event, so we use the exogenous variation of earthquake as a natural experiment design to estimate the effect of earthquakes on child test scores. A Difference in Difference model (DiD) can be used for estimating if a certain group is exposed to the causal variable of interest, such as an earthquake, and other groups are not. The results confirm that child test scores are significantly affected by earthquakes.
The Influence of Home Movies on the Dressing Pattern of Students: A Study in a Nigerian Public University

This research work examines the influence of home movies on the dressing pattern of students of tertiary institutions. The researcher employed simple random sampling to select 152 students from Taraba State University, Jalingo which formed the sample size. Questionnaire and interview were used as the instruments for data collection. Data gathered were presented using tables while frequency counts and simple percentages were used for analysis and interpretation. The research work among many things reveals that virtually all the respondents’ watches television and they do so very often. The study also revealed that youths imitate the hip hop/hippies and makeup/hairstyles projected in home movies than any other form of dressing and the major reasons for that are for fashion and imitating a role model as the study postulates such act makes them look indecent on campus. Reversing this issue, the study recommends that media and film regulatory bodies must continue to be vigilant in screening contents of home movies so as to ensure the preservation of Nigerian/ African cultural values both in the content and costume of these home movies.
WHY CUSTOMERS DO NOT COMPLETE ONLINE TRANSACTIONS: THE MISSING LINK

The purpose of this study is to investigate the stages of online business that motivate customers to complete online transactions. By using the Technology Acceptance theory, the online businesstransaction model is proposed and tested. The results of our survey of Canadian firms validate the four-stage causal model—Perception, Interpretation, Value Assessment, and Transaction stages. Given the international scope of online business, identification of the stages is important for both scholars and managers, because relatively few customers who visit websites complete transactions, suggesting that at some stage the customer abandons the website. By assessing the stages of their online businesses, managers can determine which stage is most worthy of attention in order to encourage customers to complete online transactions. Managers who understand the stages can attract new customers and serve existing customers more effectively.
'Single-sided' autofocusing of sound in layered materials

A new technique—'single-sided' autofocusing—is proposed and its possible use for inspecting layered materials is surveyed. Based on linear acoustics and the recently developed mathematical theory of focusing, single-sided autofocusing answers the question, 'Given single-sided access, how does one focus sound to a point inside a one-dimensional layered medium at a specified time—given that the velocity profile is unknown? '
Connected Vehicle Remote Diagnostic System

The article proposes a Connected Vehicle Remote Diagnostic System, designed for operational monitoring of the technical parameters of the vehicles systems in real time, from anywhere with a connection. This function is achieved by the fact that the data collection and transmission equipment is equipped with an adapter for monitoring the technical and operational parameters of vehicles and transmitting these parameters to the terminal device for subsequent sending to the telematic server, the adapter is connected to the CAN buses through the diagnostic connector in the vehicle and is coordinated with them on the software and hardware level. The system is designed to remotely communicate with owners and maintenance personnel to vehicle and provide vehicle warnings and information, including location, performance and service data, to make decisions about where and how the vehicle is used. The system provides critical system readings of temperature and pressure for specific vehicle functions, including hydraulic, transmission and cooling systems.
Causal Relation Identification Using Convolutional Neural Networks and Knowledge Based Features

Causal relation identification is a crucial task in information extraction and knowledge discovery. In this work, we present two approaches to causal relation identification. The first is a classification model trained on a set of knowledge-based features. The second is a deep learning based approach training a model using convolutional neural networks to classify causal relations. We experiment with several different convolutional neural networks (CNN) models based on previous work on relation extraction as well as our own research. Our models are able to identify both explicit and implicit causal relations as well as the direction of the causal relation. The results of our experiments show a higher accuracy than previously achieved for causal relation identification tasks.
Multiple bands near fronts in VHF wind‐profiling radar and radiosonde data

Fronts passing over the Mesosphere–Stratosphere–Troposphere radar near Aberystwyth, Wales, UK, possessed multiple bands in returned power and vertical shear of the horizontal wind. Warm fronts tended to have more bands than cold fronts. Of 82 bands in power with an associated band in the radiosonde data, 45% were associated with a decrease in specific humidity and an increase in stability (drying stable bands) and 21% were associated with an increase in humidity and a decrease in stability (moistening unstable bands). The radar detects airstream boundaries near fronts, some of which are not part of the front.
Identifiability of large nonlinear biochemical networks

This work was funded by the Galician government (Xunta de Galiza) through the I2C postdoctoral program (fellowship ED481B2014/133-0), and by the Spanish Ministry of Economy and Competitiveness (grant DPI2013-47100-C2-2-P).
A PCA-based approach for subtracting thermal background emission in high-contrast imaging data

Ground-based observations at thermal infrared wavelengths suffer from large background radiation due to the sky, telescope and warm surfaces in the instrument. This significantly limits the sensitivity of ground-based observations at wavelengths longer than 3 microns. We analyzed this background emission in infrared high contrast imaging data, show how it can be modelled and subtracted and demonstrate that it can improve the detection of faint sources, such as exoplanets. We applied principal component analysis to model and subtract the thermal background emission in three archival high contrast angular differential imaging datasets in the M and L filter. We describe how the algorithm works and explain how it can be applied. The results of the background subtraction are compared to the results from a conventional mean background subtraction scheme. Finally, both methods for background subtraction are also compared by performing complete data reductions. We analyze the results from the M dataset of HD100546 qualitatively. For the M band dataset of beta Pic and the L band dataset of HD169142, which was obtained with an annular groove phase mask vortex vector coronagraph, we also calculate and analyze the achieved signal to noise (S/N). We show that applying PCA is an effective way to remove spatially and temporarily varying thermal background emission down to close to the background limit. The procedure also proves to be very successful at reconstructing the background that is hidden behind the PSF. In the complete data reductions, we find at least qualitative improvements for HD100546 and HD169142, however, we fail to find a significant increase in S/N of beta Pic b. We discuss these findings and argue that in particular datasets with strongly varying observing conditions or infrequently sampled sky background will benefit from the new approach.
Relationships between teacher-reported ADHD symptom profiles and academic achievement domains in a nonreferred convenience sample of first- to fourth-grade students

ABSTRACT OBJECTIVES: Previous studies suggested that inattention was related particularly with reading problems among students. However, most of the former studies had clinically referred samples. A majority of the studies conducted with nonreferred samples have evaluated academic achievement with single or a few parent- or teacher-rated items. Almost none of the studies have investigated reading, writing, and mathematics achievements in a single sample. Data from low- and middle-income countries on the subject are exceedingly scarce. Objectives of the present study were to compare actual measurements of reading fluency, reading comprehension, reading and writing errors, mathematics achievement, and teacher ratings of attention deficit hyperactivity disorder (ADHD) symptoms in a single sample. METHODS: Teachers rated ADHD symptoms in a single, nonreferred, population sample (n = 2493) of first- to fourth-grade students with a SNAP-4 rating scale. Actual measurements of reading fluency, reading comprehension, reading and writing errors, and mathematics achievement were also obtained. Fluid IQ was evaluated with Ravens Progressive Matrices. Students were grouped into Predominantly Inattentive (PI), Hyperactive/Impulsive (HI), Combined (C), or control groups. Univariate and multivariate analyses were conducted. Statistical significance was set at p < . 003 after correction for multiple comparisons. RESULTS: We showed that after fluid IQ level and gender were controlled, ADHD-PI and ADHD-C groups (but not ADHD-HI) had significantly lower performance in all academic areas. ADHD-PI increased the risk of being in the lowest performing 10th percentile for reading 3 times, for writing more than 3.9 times, and for mathematics more than 6 times. CONCLUSIONS: We investigated the subtype differences in terms of academic achievement between ADHD-PI, ADHD-HI, and ADHD-C, based on teacher reports. Academic achivement data were not based on teacher or parent reports but on the actual performance of the students using standardized tests. Our results suggested that inattention symptoms must be targeted in primary school students in order to help them have academic achievement similar to their peers.
Practical classification of different moving targets using automotive radar and deep neural networks

In this work, the authors present results for classification of different classes of targets (car, single and multiple people, bicycle) using automotive radar data and different neural networks. A fast implementation of radar algorithms for detection, tracking, and micro-Doppler extraction is proposed in conjunction with the automotive radar transceiver TEF810X and microcontroller unit SR32R274 manufactured by NXP Semiconductors. Three different types of neural networks are considered, namely a classic convolutional network, a residual network, and a combination of convolutional and recurrent network, for different classification problems across the four classes of targets recorded. Considerable accuracy (close to 100% in some cases) and low latency of the radar pre-processing prior to classification (∼0.55 s to produce a 0.5 s long spectrogram) are demonstrated in this study, and possible shortcomings and outstanding issues are discussed.
Duplex nanocrystalline alloys: Entropic nanostructure stabilization and a case study on W–Cr

Grain boundary (GB) segregation can markedly improve the stability of nanostructured alloys, where the fraction of GB sites is inherently large. Here, we explore the concept of entropically supported GB segregation in alloys with a tendency to phase-separate and its role in stabilizing nanostructures therein. These duplex nanocrystalline alloys are notably different, both in a structural and thermodynamic sense, from the previously studied “classical” nanocrystalline alloys, which are solid solutions with GB segregation of solute. Experiments are conducted on the W–Cr system, in which nanoduplex structures are expected. Upon heating ball-milled W–15 at. % Cr up to 950 °C, a nanoscale Cr-rich phase was found along the GBs. These precipitates mostly dissolved into the W-rich grains leaving behind Cr-enriched GBs upon further heating to 1400 °C. The presence of Cr-rich nanoprecipitates and GB segregation of Cr is in line with prediction from our Monte Carlo simulation when GB states are incorporated into the alloy thermodynamics.
Title Distorted mix method for constructing copulas with taildependence

This paper introduces a method for constructing copula functions by combining the ideas of distortion and convex sum, named Distorted Mix Method. The method mixes different copulas with distorted margins to construct new copula functions, and it enables us to model the dependence structure of risks by handling central and tail parts separately. By applying the method we can modify the tail dependence of a given copula to any desired level measured by tail dependence function and tail dependence coefficients of marginal distributions. As an application, a tight bound for asymptotic Value-at-Risk of order statistics is obtained by using the method. An empirical study shows that copulas constructed by this method fit the empirical data of SPX 500 Index and FTSE 100 Index very well in both central and tail parts.
A Novel Rare Missense Variation of the NOD2 Gene: Evidences of Implication in Crohn’s Disease

The NOD2 gene, involved in innate immune responses to bacterial peptidoglycan, has been found to be closely associated with Crohn’s Disease (CD), with an Odds Ratio ranging from 3–36. Families with three or more CD-affected members were related to a high frequency of NOD2 gene variations, such as R702W, G908R, and 1007fs, and were reported in the EPIMAD Registry. However, some rare CD multiplex families were described without identification of common NOD2 linked-to-disease variations. In order to identify new genetic variation(s) closely linked with CD, whole exome sequencing was performed on available subjects, comprising four patients in two generations affected with Crohn’s disease without R702W and G908R variation and three unaffected related subjects. A rare and, not yet, reported missense variation of the NOD2 gene, N1010K, was detected and co-segregated across affected patients. In silico evaluation and modelling highlighted evidence for an adverse effect of the N1010K variation with regard to CD. Moreover, cumulative characterization of N1010K and 1007fs as a compound heterozygous state in two, more severe CD family members strongly suggests that N1010K could well be a new risk factor involved in Crohn’s disease genetic susceptibility.