Miracle-dz/UniFAR-FTUs huggingface dataset:
Binge Drinking among Residential Program Youth in Israel: Toward an Understanding of Predictors for Policy and Prevention

Alcohol use is attributed to about 25% of the total deaths among youth and young adults. Harmful alcohol use among youth has been overshadowed by the preoccupation with widespread use of other substances including cannabis and prescription drugs. A crosssectional cohort of 1,327 residential program and high school youth were compared regarding binge drinking habits and risk factors. Data was collected from 2004 to 2016. Residential program youth binge drinking predictors were substance abuse within the last month, alcohol availability, causing harm to others (e.g., fighting, stealing and possessing a weapon), unstructured day activity, and being a passenger in a car where the driver had been drinking. Binge drinking predictors among high school were smoking within the last month and alcohol availability. Effective risk behavior prevention involves a wide range of factors including the need to control alcohol access among those under the legal drinking age. An eco-systems approach involving youth and people they are in contact with is a viable prevention approach. However, conflicting personal and economic factors regarding alcohol use, among others, are a daunting barrier to overcome.
Dispersion compensation using transmission-based nonuniform grating

In this paper, we analyze and propose a non-uniform transmission based ramp chirp grating which can give maximum negative dispersion profile over broadband wavelength range. Coupled mode theory is used for obtaining quantitative information about the delay spectral dependence of the grating structure. A matrix method is used for analyzing the grating characteristics. For a grating length of 25 m, the grating can give negative dispersion of 266 ps/nm. When the grating is inserted after 16.07 km in line with the existing fiber optic link, the maximum average compensated dispersion lies within +/- 1.0 ps/nm-km over 1530-nm - 1560-nm wavelength range.
Self-initiated expatriates: an alternative to company-assigned expatriates?

Purpose - – The purpose of this paper is to examine scholars’ proposal that self-initiated expatriates (SIEs) can provide an alternative to company-assigned expatriates (CAEs) for filling key positions in foreign subsidiaries at a lower cost. Design/methodology/approach - – Underpinned by findings from empirical studies, this conceptual paper compares SIEs with CAEs and their traditional alternative, multinational corporation (MNC) local employees, to examine the suitability of SIEs as a replacement for CAEs. Findings - – SIEs are likely not a suitable alternative to CAEs for purposes of control, transfer, running the foreign operation and management development (purposes requiring firm-specific competencies), but are likely suitable for filling technical and lower and middle management positions (requiring more generic, specialist competencies) and purposes of managing within the subsidiary and responding to the local environment (purposes requiring cross-cultural and host location-specific competencies). Practical implications - – Guidance is provided for the recruitment of SIEs as an alternative to CAEs. Originality/value - – The paper adds new insight in assessing whether SIEs provide an alternative to CAEs by proposing a framework that integrates: the identification of SIEs’ competencies relative to those of CAEs and MNC local employees, based on career capital theory; with the assessment of their value, based on human capital allocation theory, against the purposes for which CAEs are deployed.
Noise control in three-dimensional propagation

This paper presents an investigation into the process of noise cancellation in a three-dimensional non-dispersive (linear) propagation medium using a multiple-source system configuration. The process of field cancellation is considered from a frequency-domain viewpoint. The degree of cancellation is analysed in relation to source-related and geometry-related parameters of the system leading to a three-dimensional description of the pattern of cancellation and reinforcement in the medium and merits of the system design. Moreover, the effect of implementation errors on the physical extent of cancellation and the extent of error tolerances, for consideration in the process of design of the system, are analysed and discussed.
A Glue-like Semantics for Mandarin Chinese: Annotation and Formalism

The FrameNet project is to design a lexical database of English based on a linguistic theory called Frame Semantics. The meaning of most words can best be understood on the basis of a semantic frame, and the basic assumption on which the frames are built is that each word evokes a particular situation with particular participants (Fillmore, 1968). For example, the concept of cooking usually involves a person doing the cooking (Cook), the food that is to be cooked (Food), something to hold the food while cooking (Container) and a source of heat (Heating instrument). In FrameNet, this event is represented as a frame called Apply heat, while the Cook, Food, Heating instrument and Container are all frame elements (FEs), and predicates evoking frames are called lexical unites (LUs). FrameNet provides a description of more than 1,200 semantic frames underlying the meaning of the words described, and valence representation (semantic and syntactic) of several thousand words and phrases, each accompanied by a representative collection of more than 200,000 manually annotated sentences (Baker et al., 1998). However, FrameNet fails to provide precise syntax-semantics interface as the annotation for frames and FEs is directly based on running sentences without the interaction with syntactic entities. Many of the FrameNet frames, including the constructions, apply equally well to other languages, as evidences by the various efforts to develop FrameNets in other languages such as French (Candito et al., 2014), Chinese (Liu, 2011), German (Burchardt et al., 2009) and so on. Among the previous work, the Chinese FrameNet (CFN) is most relevant to our work. However, the CFN is still under construction, and like many other FrameNet project, they take Berkeley’s FrameNet Project as the reference and annotate the frame semantics on running sentences, which would be really time-consuming and laborintensive. And similar to English FrameNet, they are dependent from syntactic structure, while other semantic representations, like the Proposition Bank (PropBank), provide information about basic semantic propositions and predicate-argument relations based on syntactic trees.
Decision-Support Tool for Assessing the Environmental Effects of Constructing Commercial Buildings

Construction of commercial buildings consumes significant amounts of energy and produces lots of emissions and waste. Where should environmental improvement efforts be focused during design and construction? The Construction Environmental Decision-Support Tool allows designers and industry practitioners to quantify energy use, emissions, and waste generation rates due to the construction phase of commercial buildings. A case study of the Bren School at the University of California, Santa Barbara, and several relevant construction scenarios are analyzed. When considering the complete building over its entire life cycle, the construction phase comprised 2% of energy consumption, 1% of C O2 emissions, 7% of CO emissions, 8% of N Ox emissions, 8% of P M10 emissions, and 1% of S O2 emissions. This is due to the dominance of the long-term use phase (50 years) compared to a relatively short construction phase (2 years) . Scaling up to the national level, however, construction impacts of projects are significant.
Power cables' thermal protection by interval simulation of imprecise dynamical systems

The embedding of advanced simulation techniques in power cables enables improved thermal protection because of higher accuracy, adaptiveness and flexibility. In particular, they make possible (i) the accurate solution of differential equations describing the cables thermal dynamics and (ii) the adoption of the resulting solution in the accomplishment of dedicated protective functions. However, the use of model-based protective systems is exposed to the uncertainty affecting some model components (e.g. weather along the line route, thermophysical properties of the soil, cable parameters). When uncertainty can be described in terms of probability distribution, well-known techniques, such as Monte Carlo, are used to simulate the system behaviour. On the other hand, when the description of uncertainty in probabilistic terms is unfeasible or problematic, nonprobabilistic alternatives should be taken into consideration. This paper will discuss and compare three interval-based techniques as alternatives to probabilistic methods in the simulation of power cable dynamics. The experimental session will assess the interval-based approaches by simulating the thermal behaviour of medium voltage power cables.
AN ANALYSIS ON PERCEIVED SERVICE QUALITY AND STUDENTS’ SATISFACTION OF E-LEARNING DURING COVID-19 IN HIGHER EDUCATION INSTITUTION

The outbreak of Corona Virus Disease 2019 (COVID-19) in various countries at the end of 2019 has transferred traditional classroom teaching to e-learning platforms, which unswervingly affects the educational quality. The whole education system from school to higher education level has been distorted due to COVID-19 in India and all over the globe and forced to accept online mode. However, even with this paradigm shift, little research has been done to extend traditional service management concepts to online educational settings during the pandemic in developing countries. This research attempts to bridge this gap by applying the SERVQUAL scale, a well-validated and widely used service operations construct, to the online classroom environment, this paper uses a questionnaire survey and Google forms to collect experience data of 354 students. The findings show that the SERVQUAL scale exhibits both reliability and convergent and divergent validity; in fact, in these regards, it outperforms traditional student assessment scales. Four factors empathy, responsiveness, reliability and website content and privacy have significant effect on student satisfaction of perceived e-learning quality. The findings of this paper can be used for making approaches for online education across the globe to accelerate the online education level during pandemic, to promote the reform of information-based education. The paper provides the whole picture of current online teaching-learning during Covid-19, which makes it rare and gives a holistic view of the environment. This novel technique to assessing the quality of e-learning services demonstrates that students may be considered as customers and has far-reaching consequences for all parties involved in higher education delivery.
Design of a Nine-Transistor/Two-Magnetic-Tunnel-Junction-Cell-Based Low-Energy Nonvolatile Ternary Content-Addressable Memory

Towards a low search-energy nonvolatile ternary content-addressable memory (TCAM), we propose a novel nine-transistor/two-magnetic-tunnel-junction (9T–2MTJ) nonvolatile TCAM cell circuit with a high-speed accessibility. Since critical path for switching in the TCAM cell circuit is only a single metal-oxide-semiconductor (MOS) transistor, switching delay of the TCAM word circuit is minimized. As a result, the worst-case switching delay of 0.22 ns is achieved in a 144-bit word circuit under a 90 nm complementary MOS (CMOS)/MTJ technology, which is about 2.6 times faster than that of a conventional CMOS-based TCAM. In order to minimize the active power dissipation in the proposed TCAM, a multi-level segmented match-line scheme that maximally brings inessential cells to standby state is also applied to the 9T–2MTJ-cell-based word circuit. Finally, low search-energy of 0.73 fJ/bit/search is achieved in a 144-bit × 256-word nonvolatile TCAM together with eliminating standby power using nonvolatility.
MOVIE SUCCESS PREDICTION USING MACHINE LEARNING

Film Industry is not only a industry or a center of entertainment, rather it is now a center of global business. All over the world is now excited about a movie’s box office success, popularity etc. A huge data is available online about these movies’ success or popularity. The film industry is very important sector in the global market. Therefore, it is very necessary maximize the profit by predicting the movie success before its release. The number of movies released in the world is growing at an tremendous rate and success rate of movie is of very importance since million of dollars are invested in the making of each of these movies. In such a cases, prior knowledge about the success or failure of a movie and what factor affect a movie success will benefit the production houses since these predictions will give them a good idea of how to go about with the advertising , which itself is an expensive affair altogether. So, the prediction of the success of the movie is very necessary to the film industry. We proposed to develop a model for predicting the success of the movie being a Flop or Hit, long before a movie is actually released using machine learning techniques and algorithms.
Genotyping, Antibiotic Resistance and Biofilm Formation Ability of Clostridium perfringens Isolated from Raw Milk, Dairy Products and Human Consumers

| Clostridium perfringens is one of the most common causes of food poisoning in the world. In this study, C. perfringens isolated from raw milk, milk products and human consumers were investigated for their antibiotic resistance and biofilm formation ability. A total of 460 samples (buffalo milk, cow milk, camel milk, yoghurt, Kareish cheese and soft (processed) cheese, 60 of each and 100 diarrheic stool sample of human consumers) were collected from Zagazig city, Sharkia Governorate, Egypt, and examined for the presence of C. perfringens strains. Twenty-four C. perfringens strains were isolated and all were of type A and 3 (12.5%) of camel milk origin and 4 (16.7%) from human diarrheic stool were positive for the enterotoxin associated (cpe) gene. Antibiotic sensitivity revealed that 87.5% of the isolates were resistant to oxytetracycline followed by amoxicillin (83.4%), ampicillin and erythromycin (75%, each). C. perfringens isolates from different sources were able to form biofilm at various temperatures (4°C, 25°C and 35°C). In conclusions, the collected samples from the study area are considered potential sources for human infection with C. perfringens. Therefore, milk and dairy products should be inspected periodically to control contamination with foodborne pathogens.
In ) security of video surveillance systems in building automation systems

Over the past decades, surveillance has evolved from purely human supervision to Closed Circuit Television to, in recent years, interconnected Video Surveillance Systems (VSS). Currently, VSSs are often connected to the internet and integrated in existing networked systems. The most common system integration is with the building automation systems of modern smart buildings. The subsystems comprising a building automation system include critical systems such as access control, heating, air condition, and now video surveillance. These systems were originally isolated, but are now being connected to the internet and each other. This transition brings new security risks, as the legacy systems often relied on the isolation for their security. The new systems have improved connectivity and internet connection for remote control. This increases not only the attack surface but also the impact of a cyberattack. Intrusion Detection Systems (IDS) have become one of the most effective tools for detecting threats to networked systems. Whereas several IDS for industrial control systems are commercially available, there is no comprehensive solution for VSSs. In this thesis, we provide a definition of threats against VSSs and develop a novel tool for detecting them by using passive network traffic analysis. The proposed solution is built on top of SilentDefense, a world-leading IDS for industrial control systems. We implement several techniques to classify hosts belonging to VSSs as well as potential threats related to HTTP and RTSP, the two most widely used network protocols in VSSs. The results of the performed tests to validate the effectiveness of the proposed solution show a perfect classification rate for datasets containing RTSP traffic and a threat detection rate of over 98% for known vulnerabilities in the considered datasets.
Sinusoidal phase modulating interferometer base on integration method

We describe a sinusoidal phase modulating interferometer in which a CCD image sensor measure phase values, the method uses four frames obtained by integration of the time-varying intensity in an interference pattern during the four quarters of the modulation period. The optimum amplitude and phase of the sinusoidal phase modulation were determined by considering the measurement error that is resulted in the additive noise; the effect caused by the deviation from the optimum phase modulation is analyzed. Theoretical analyses and experimental verifications have shown that the distance-measurement accuracy is 2.7 nm with these techniques.
LightOCT: Exploring the depth for Retinal disease detection

With the advancement in technology and computation capabilities, identifying retinal damage through state-of-the-art CNNs architectures has led to the speedy and precise diagnosis, thus inhibiting further disease development. In this study, we focus on the classification of retinal damage caused by detecting choroidal neovascularization (CNV), diabetic macular edema (DME), DRUSEN, and NORMAL in optical coherence tomography (OCT) images. The emphasis of our experiment is to investigate the component of depth in the neural network architecture. We introduce a shallow convolution neural network - LightOCT, outperforming the other deep model configurations, with the lowest value of LVCEL and highest accuracy (+98% in each class). Next, we experimented to find the best fit optimizer for LightOCT. The results proved that the combination of LightOCT and Adam gave the most optimal results. Finally, we compare our approach with transfer learning models, and LightOCT outperforms the state-of-the-art models in terms of computational cost, least training time and gives comparable results in the criteria of accuracy. We would direct our future work to improve the accuracy metrics with shallow models such that the trade-off between training time and accuracy is reduced.
Modelling and simulation of an electrohydraulic steering system

The development of an electrohydraulic (E/H) steering system model for an off-road vehicle and the simulation results are presented. This model consists of the main subsystems of an E/H steering system, including a PWM driver, a proportional E/H directional control valve, two steering actuating cylinders, a steering linkage, and wheel-ground interactions. The model is linearised based on the assumptions of incompressible fluid, critical lapped valve, and frictionless spool motion. The linearised model is simulated using MATLAB Simulink and validated on field steering tests using a full-scale vehicle. The results indicate that a linearised model of third-order, with compensation for the system deadband, saturation, and time delay, is capable of satisfactorily representing the dynamic responses of the E/H steering system within steering angle range of -10° and 10°. This validated linear model is capable of estimating the dynamic behaviour of the E/H steering system, and providing critical information for designing high performance steering controllers for off-road vehicles.
Rumen degradation properties of tropical legumes feed under in sacco studies

Degradation properties of protein feed sources such as tropical legumes is very important to match with microbial protein synthesis and by pass protein requirements in dairy cattle ration formulation. However, the information is still limited. This study aims to determine the degradability of dry matter (DMD) and organic matter (OMD) from several legumes in Indonesia using in sacco method. There are 11 types of tropical legumes that are commonly used in dairy cattle ration have been studied, namely acacia, alfalfa, pterocarpus, gliricidia, indigofera, calliandra, butterfly leaf, leucaena, albizia, tamarind, and sesbania. The dried forage mesh samples were put into nylon bags and incubated in the rumen of two fistulated Friesian Holstein bulls for 0, 3, 6, 9, 12, 15, 24, 48, and 72 hours. Parameter observed were degradability of dry matter (DMD), and organic matter (OMD), kinetic parameters, and effective degradation. The data were analysed using descriptive statistic and regression from SAS University software. The result that sesbania and indigofera grouped into highly degradable forage (degradability > 80%), while acacia, albizia, calliandra grouped into low degradable forage (degradability < 50%). From this study it can be concluded that each type of legume has different degradability characteristics using in sacco method.
Flexibility in building use: the technical feasibility of converting redundant offices into flats

The potential for converting empty offices into housing depends upon demands for converted space, the ability to finance conversions and attitudes of owners of empty buildings, together with flexibility in planning and ability to overcome technical constraints. This article explains the reasons for the large stock of redundant office buildings in the UK and questions whether some of these can be converted to provide much needed affordable housing. Technical constraints on their own are rarely insurmountable but the cost of making necessary changes may often be higher than other options of demolition and new building. Case studies of converted buildings show that it is necessary for project managers to deal with a range of issues from planning, location and finance to the accurate assessment of technical criteria in order for successful outcomes. It has often been difficult to find sites where all the necessary variables coincide in a positive manner and for this reason, the conversion of offices into flat.
Time-Domain Electrical Impedance Tomography by Numerical Analysis of the Step Response

This work describes the theoretical basis of an electrical impedance tomography imaging system based on numerical analysis of the step response. Its novelty relies on the use of time domain for rendering the tomographic images. Following the injection of a Heaviside-step current through two electrodes, the voltage-response is measured on all couple of electrodes according to the neighbouring strategy; this process is repeated on every pair of consecutive electrodes. Based on the measurements, a tomographic image is reconstructed using the Gauss-Newton-Raphson algorithm. We tested the technique by simulating two representative circuits: one symmetrical pseudo-isotropic and one pseudo-anisotropic in AC, while both pseudo-isotropic at DC. The time-domain reconstructed images show the second network’s pseudo-anisotropy while allowing the system to show its tendency to pseudo-isotropy when the time elapses towards DC-steady-state. This novel technique for reconstructing electrical impedance tomographic images may shed new light on sensing slight differences in tissues while being fast and low-cost.