Miracle-dz/UniFAR-FTUs huggingface dataset:
Signature of dynamical heterogeneity in spatial correlations of particle displacement and its temporal evolution in supercooled liquids

The existence of heterogeneity in the dynamics of supercooled liquids is believed to be one of the hallmarks of the glass transition. Intense research has been carried out in the past to understand the origin of this heterogeneity in dynamics and a possible length scale associated with it. We have done extensive molecular dynamics simulations of few model glass-forming liquids in three dimensions to understand the temporal evolution of the dynamic heterogeneity and the heterogeneity length scale. We find that although the strength of the dynamic heterogeneity is maximum at a timescale close to characteristic $\alpha$-relaxation time of the system, dynamic heterogeneity itself is well-developed at timescale as short as $\beta$-relaxation time and survives up to a timescale as long as few tens of $\alpha$-relaxation time. Moreover, we discovered that temperature dependence of heterogeneity length remains the same in the whole time window although its absolute value changes over time in a non-monotonic manner.
Alternative strategies for estimation of country sire variance in international evaluations of dairy bulls

The MACE program is the most accurate method currently available for international genetic comparisons. The multiple-country model allows each country to have different genetic parameters, different units of measurement and genetic correlations between countries that are less than one. The implementation and further evaluation of MACE has however revealed some practical limitations, such as its sensitivity to variance component estimates.
Consecutive Course Modules Developed with Simple Materials to Facilitate the Learning of Basic Concepts in Astronomy.

From the perspective of teaching, the huge natural laboratory that astronomy provides constitutes the most prominent connection between astronomy and other branches of science. The purpose of this research was to provide educators with activities of observation using simple materials that were developed to facilitate the teaching of basic concepts of astronomy, presenting these in the form of course modules that they could use in the classroom. Six modules were developed for teaching basic astronomy. The modules "What is Astronomy? ", "The Solar System and Observing the Sun", "Astronomy Topics in the Elementary School Curriculum and Experimental Activities" and "Space Research and Life in Outer Space" were implemented in the day classes while the modules "The History of Astronomy and Sky Observation" and "Sky Observation with a Telescope" were implemented during evening classes. The modules developed are unique in that their content treats the basic concepts of astronomy with an integrated and consecutive approach to make the activities easier for teachers to implement in the classroom. The effectiveness of the activities that were designed was investigated by testing the modules on Pre-service Science Teachers (N=88), after which observation notes were recorded.
Anticoagulant Activity of Some Ficus carica Varieties Extracts Grown in Algeria

Abstract The hemostatic system is a complex balanced system that triggers clot formation to prevent blood loss after trauma. To block abnormal bleeding and maintain intravascular blood in a liquid state, in this study we investigated the possible anticoagulant effect of leaves and fruits extracts from some fig varieties grown in Algeria by determining the quick time (QT). The blood samples of the healthy individuals were used. For in vitro coagulation assays, the clotting times obtained in the presence of polyphenols in different extracts of F.carica samples indicate that they exert a high anticoagulant activity on the exogenous pathway of coagulation. Moreover, the polyphenolic extract of ‘Roudane’ variety presented a substantial increase in coagulation. Based on these preliminary results, it can be suggested that the fig polyphenolic extracts (FPE) of this varieties have anticoagulant activity that could be useful in preventing blood clots.
SRTTU Design and Simulation of a Highly Efficient InGaN / Si Double-Junction Solar Cell

ARTICLE HISTORY: Received 22 November 2017 Revised 20 December 2017 Accepted 01 January 2017 A solar cell is an electronic device which not only harvests photovoltaic effect but also transforms light energy into electricity. In photovoltaic phenomenon, a P-N junction is created to form an empty region. The presented paper aims at proposing a new highly efficient InGaN/Si double-junction solar cell structure. This cell is designed to be used in a real environmental situation, so only structural parameters are optimized. In the present structure, a thin layer of Cd-S is used as the antireflector window layer. The cell is simulated using ATLAS-SILVACO software and its maximum efficiency is computed to be 37.23%. Considering the supposed structure, the findings show that the efficiency of this solar cell, which is 37.32%, is so far the highest reported efficiency amongst all solar cells.
Leveraging the Ubiquitous Web as a Secure Context-aware Platform for Adaptive Applications

The availability as well as diversity of connected devices has turned the Internet into a ubiquitous concept. In addition to desktop and laptop PCs, the Internet also connects numerous mobile devices, home entertainment systems, and even in-car units. Various new types software applications arise, trying to make optimal use of this trend. However, as the fragmentation of devices and platforms grows, application developers are increasingly facing the need to cover a wider variety of target devices. Maintaining a viable balance between development costs and market coverage has turned out to be a challenging issue when developing applications for such a ubiquitous ecosystem. In this paper, we present the Webinos approach, a distributed web runtime that adaptively leverages the device-independent characteristics of the Web. By introducing the concept of context-aware Personal Zones, the Webinos platform aims to facilitate the development of self-adaptive and immersive applications, optimized for ubiquitous computing environments. Keywords-ubiquitous web; context-aware platform; distributed runtime; adaptive applications; webinos
On the fluid permeability of heat treated paulownia wood

Fibre direction cylindrical specimens from the sapwood and heartwood areas of Paulownia wood were heat treated at 180, 190, and 200°C split in eight groups of ten specimens each. Air and water permeability were measured, thereafter. Results demonstrated that heat treatment had a positive effect on air permeability both in sapwood and heartwood specimens. That increase might be attributed to the development of cell wall micro-checks caused by thermal degradation and fracture of the vessel tyloses. Liquid permeability was significantly decreased as a result of heat treatment.
FlowGraph: Distributed temporal pattern detection over dynamically evolving graphs

Temporally evolving graphs are an indispensable requisite of modern-day big data processing pipelines. Existing graph processing systems mostly focus on static graphs and lack the essential support for pattern detection and event processing in graph-shaped data. On the other hand, stream processing systems support event and pattern detection, but they are inadequate for graph processing. This work lies at the intersection of the graph and stream processing domains with the following objectives: (i) It introduces the syntax of a language for the detection of temporal patterns in large-scale graphs. (ii) It presents a novel data structure called distributed label store (DLS) to efficiently store graph computation results and discover temporal patterns within them. The proposed system, called FlowGraph, unifies graph-shaped data with stream processing by observing graph changes as a stream flowing into the system. It provides an API to handle temporal patterns that predicate on the results of graph computations with traditional graph computations.
Shifting and broadening in the fundamental band of CO highly diluted in He and Ar: A comparison with theory

We present measurements of the shifts and widths of the rovibrational lines of the fundamental band of CO highly diluted in He and Ar at 296 K. The shifts are decomposed into parts odd and even in the line number, m. These are then compared with close coupled calculations carried out with the best known interaction potentials. There is general agreement between the calculated and measured values of the broadening and shifting. Furthermore, the results illustrate that the decomposition of the shifts into parts, odd and even in m, is a powerful tool for separating out the relative contributions of the isotropic and anisotropic part of the interaction to the shifts and which part needs to be corrected if there is a discrepancy. Thus, shift measurements can be added to the list of experiments that may be used to determine reliable interaction potentials. The results also show, given a potential, that close coupled calculations are accurate and could be used to confirm or establish empirical models of the temperature dependence of the broadening or shifting, etc. Such modeling is important at atmospheric physics.
Path tracing using lower level of detail for secondary rays

Path tracing is a computationally expensive method of three dimensional rendering that aims to accurately simulate the propagation of light. A large amount of time is typically spent calculating intersections between rays and the scene, which is composed of triangular meshes stored in some form of bounding volume. This time can be reduced by lowering the overall number of triangles in the scene. Path tracing works by casting rays from the camera into the scene, reflecting until they hit a light source. Secondary rays, or rays which occur after the first intersection, usually contribute less to the overall image, yet require much more time to calculate than primary rays. This thesis found that significant performance gains can be made by using lower level of detail (LOD) triangular meshes for secondary rays. While the lower LOD models are less accurate, they still provide a good approximation of the mesh for secondary rays. Scenes with 1.4 million faces could be rendered up to 10% faster using a 1/32 ratio level of detail for secondary rays. A study with 14 subjects who ranked images based on image quality showed they were unable to differentiate between low LOD and full LOD images.
Evaluating building integrated photovoltaic performance models

Predictive performance tools could accelerate the implementation of building integrated photovoltaics (BIPV). The National Institute of Standards and Technology (NIST) seeks to improve and validate previously developed computer simulation tools with experimental data collected in a building integrated photovoltaic "test bed. " Twelve months of performance data has been collected for BIPV panels using four different cell technologies: crystalline, polycrystalline, silicon film, and triple-junction amorphous. Two panels using each cell technology were present, one without any insulation attached to its rear surface and one with insulation attached to its rear surface. Two predictive performance tools were investigated: IV Curve Tracer, a photovoltaic model developed by Sandia National Laboratories (SNL), and PHANTASM, a BIPV predictive tool developed by the Solar Energy Laboratory at the University of Wisconsin. The performance data associated with the eight panels in the BIPV "test bed", along with meteorological data, was compared to the predictions of the SNL and PHANTASM models.
Application of hybrid of Fuzzy Set, Trust and Genetic Algorithm in query log mining for effective Information Retrieval

The precision of Information Retrieval (IR) System is low due to imprecise user queries as well as because of information overload on web. The Fuzzy set infers the user’s information need from vague and imprecise queries and web recommender systems are used to overcome information overload problem. The performance of recommender system is still low due to data sparsity. The concept of trust is used to deal with data sparseness problem and improves the performance of recommender system. Optimization techniques like Genetic Algorithm(GA) have been applied in domain of information retrieval for effective web search. In this research hybrid of Fuzzy set, GA and Trust has been used together in query log mining for personalized web search based on using fuzzy queries for recommendation of optimal set of trusted documents. Thus the use of hybrid of Fuzzy set, trust and GA together infer the user’s information need from vague and imprecise user’s queries and optimize the web page ranking of trusted web pages for effective personalized web search. The experimental results were analyzed statistically as well as compared with GA IR, and Fuzzy Trust based IR. Hence based on comparative analysis of results, thus hybrid of Fuzzy Set, Trust and GA shows the improvement in average precision of search results and confirms the effective personalization of web search.
A Weakly Supervised Learning Based Clustering Framework

A weakly supervised learning based clustering framework is proposed in this paper. As the core of this framework, we introduce a novel multiple instance learning task based on a bag level label called unique class count ($ucc$), which is the number of unique classes among all instances inside the bag. In this task, no annotations on individual instances inside the bag are needed during training of the models. We mathematically prove that a perfect $ucc$ classifier, in principle, can be used to perfectly cluster individual instances inside the bags. In other words, perfect clustering of individual instances is possible even when no annotations on individual instances are given during training. We have constructed a neural network based $ucc$ classifier and experimentally shown that the clustering performance of our framework with our $ucc$ classifier is comparable to that of fully supervised learning models. We have also observed that our $ucc$ classifiers can potentially be used for zero-shot learning as they learn better semantic features than fully supervised models for `unseen classes', which have never been input into the models during training.
Relation of Anthropometric Profile and Performance in Competition for Mexican High School Football Players on the Offensive Squad

El objetivo de este trabajo fue determinar la relacion entre los perfiles antropometricos de jugadores juveniles mexicanos de futbol americano y su desempeno en la competicion, tomando en cuenta su posicion ofensiva en el juego. Se estudiaron 41 jugadores de 15 a 18 anos de edad, de nivel bachillerato de dos instituciones educativas. Se registraron medidas antropometricas (peso, estatura, pliegues, diametros y perimetros) para determinar el indice de masa corporal, la composicion corporal y el somatotipo. Nuestros resultados muestran que el perfil antropometrico de los jugadores estuvo relacionado con su desempeno (bueno/muy bueno o malo/deficiente) en su posicion ofensiva en el juego. La estatura fue un factor importante en el caso de los linieros, ya que los clasificados como malos/deficientes para esa posicion, tuvieron una talla significativamente mas baja que los buenos/muy buenos; sin embargo, esta no parece influir como criterio para clasificar a receptores y corredores. Se encontro que los linieros ofensivos fueron los jugadores mas altos y pesados y con mayor porcentaje de grasa, seguidos de los receptores y por ultimo de los corredores. En esta posicion, los malos/deficientes fueron los de menor peso, y los buenos/muy buenos fueron los de mayor porcentaje graso, al igual que en la posicion de corredores. Sin embargo en los receptores la relacion se invierte, ya que los buenos/muy buenos fueron los de menor porcentaje graso. El somatotipo medio por posicion fue mesomorfo-endomorfo para los linieros, mesomorfo-ectomorfo para los receptores y meso-ectomorfo para los corredores.
Heavy Metal Pollution in Mithi River of Mumbai

The present study highlight the toxicity levels of different heavy metals in aquatic environment of one of the most polluted river of Mumbai- the Mithi River. Although the river has attracted tremendous attention after 26/7 flood in Mumbai, the pollution level of the river has remained neglected issue. The present study was performed for two assessment years 2009-10 and 2010-11 at three different sampling stations namely Airport, CST Kalina and BKC Taximen’s Colonyalong the flow of Mithi River. The results of present investigation indicates that the concentration levels of most of the heavy metals like Al, As, Cd, Cr, Hg, Ni, Pb, Sr and Mn obtained during the assessment year 2010-11 was higher than that obtained during 2009-10 by the factor of 1.4 to 5.7 µg/L. The environmental impact of these toxic heavy metals is discussed. The results point out the need of rational planning of pollution control strategies, so as to keep check on release of toxic heavy metals in the river. It is expected that the present study will be useful for rational planning of pollution control strategies and their prioritisation; to evaluate effectiveness of pollution control measures already is existence and to assess the nature and extent of pollution control needed.
Model Bias Characterization in the Design Space under Uncertainty

This paper presents an approach to validate computational models in the design space under uncertainty. The basic idea is to first characterize the model bias; then correct the original model prediction by adding the characterized model bias in the design space. Particularly, a two-step calibration procedure is proposed and the model bias at each design configuration is approximated using the Maximum Entropy Principle (MEP) method. With the characterized model bias at several design configurations, response surface of the model bias is finally constructed to approximate the model bias at any new design configurations. Two examples including a modified vehicle side impact problem and a thermal problem are used to demonstrate the feasibility of the proposed approach.
The K2 Galactic Caps Project – going beyond the Kepler field and ageing the Galactic disc

Analyses of data from spectroscopic and astrometric surveys have led to conflicting results concerning the vertical characteristics of the Milky Way. Ages are often used to provide clarity, but typical uncertainties of >40 per cent from photometry restrict the validity of the inferences made. Using the Kepler APOKASC sample for context, we explore the global population trends of two K2 campaign fields (3 and 6), which extend further vertically out of the Galactic plane than APOKASC. We analyse the properties of red giant stars utilizing three asteroseismic data analysis methods to cross-check and validate detections. The Bayesian inference tool PARAM is used to determine the stellar masses, radii, and ages. Evidence of a pronounced red giant branch bump and an [α/Fe] dependence on the position of the red clump is observed from the K2 fields radius distribution. Two peaks in the age distribution centred at ∼5 and ∼12 Gyr are found using a sample with σage < 35 per cent. In comparison with Kepler, we find the older peak to be more prominent for K2. This age bimodality is also observed based on a chemical selection of low-[α/Fe] (≤0.1) and high-[α/Fe] (>0.1) stars. As a function of vertical distance from the Galactic mid-plane (|Z|), the age distribution shows a transition from a young to old stellar population with increasing |Z| for the K2 fields. Further coverage of campaign targets with high-resolution spectroscopy is required to increase the yield of precise ages achievable with asteroseismology.
MEDIUM SIZE DUAL-AXIS SOLAR TRACKING SYSTEM WITH SUNLIGHT INTENSITY COMPARISON METHOD AND FUZZY LOGIC IMPLEMENTATION

Nowadays, renewable energy such as solar power has become important for electricity generation, and solar power systems have been installed in homes. Furthermore, solar tracking systems are being continuously improved by researchers around the world, who focus on achieving the best design and thus maximizing the efficiency of the solar power system. In this project, a fuzzy logic controller has been integrated and implemented in a medium-scale solar tracking system to achieve the best real-time orientation of a solar PV panel toward the sun. This project utilized dual-axis solar tracking with a fuzzy logic intelligent method. The hardware system consists of an Arduino UNO microcontroller as the main controller and Light Dependent Resistor (LDR) sensors for sensing the maximum incident intensity of solar irradiance. Initially, two power window motors (one for the horizontal axis and the other for the vertical axis) coordinate and alternately rotate to scan the position of the sun. Since the sun changes its position all the time, the LDR sensors detect its position at five-minute intervals through the level of incident solar irradiance intensity measured by them. The fuzzy logic controller helps the microcontroller to give the best inference concerning the direction to which the solar PV panel should rotate and the position in which it should stay. In conclusion, the solar tracking system delivers high efficiency of output power with a low power intake while it operates.
RELATIONSHIP OF BEHAVIOURAL INTENTIONS WITH ACADEMIC KNOWLEDGE TRANSFER BEHAVIOUR

The current study investigated attitudinal components that potentially impact the Knowledge Transfer Behaviour (KTB) of academics. It focused specifically on the role of behavioural intentions in the academic research process, and the resulting knowledge productivity, utilising a large sample of academics from a Malaysian Public University. The study contributes theoretically and empirically by demonstrating the relationships of the variables comprising the Theory of Planned Behaviour (i.e. attitudes, subjective norms, perceived behavioural control and intentions) on performance outcomes related to Knowledge Transfer Behaviour. The study also has practical significance based on its implications for university faculty members, providing suggestions for better understanding of how they might increase their success at Knowledge Transfer activities. This study adopts a quantitative method, using online questionnaires as the instruments for data collection. The on-line survey was administered by emailing potential respondents a link. Volunteer respondents were academics from Malaysia Public University ( N =985). Path analysis was conducted to test the research hypotheses, using a structural equation modelling (SEM) approach. The results revealed that behavioural intentions significantly predicted KTB, and Attitude and PBC significantly predicted Behavioural Intentions. Unexpectedly, Subjective Norms did not predict behavioural intentions for Knowledge Transfer Behaviour (KTB) of academics. When further modifications were made to the model, Knowledge Transfer behaviour was predominantly uniquely explained by perceived behavioural control. Further recommendations were made for this study by adding other theories such as concept of the Triple Helix by looking upon university, industry and government relationships for expanding further research. Moreover , shedding light on the findings of this study could add valuable information to other researchers and thus contributes theoretically and empirically in Theory of Planned Behaviour literature.