Miracle-dz/UniFAR-FTUs huggingface dataset:
First Year Challenge: The Role of Self-Regulated Learning to Prevent Internet Addiction among First-Year University Students

University students are categorized as digital natives group who use internet frequently in their daily life. Several studies mentioned that internet affects the way university students learn and socialize with peers. Referring to the university context, first year of university is a crucial periode where students learn to adjust with academic and social aspects after transforming from highschool period. Thus, first-year students are assumed to be more vulnerable to internet addiction due to academic and social adjustment issues. First-year students will look for support and escape from uncomfortable adjustment situation by accessing the internet. Regarding this situation, self-regulated learning (SRL) is a potential factor than can prevent students from internet addiction. This present study aims to explore the relationship between self-regulated learning (SRL) and internet addiction among first year university students. Participants are first-year students (N = 76), consisting of 14 males and 62 females. Data were collected by using Young’s internet addiction test (IAT), self-regulated learning scale (SRLS) adapted from SRSS scale by Kadioglu, Uzuntiryaki & Aydin (2011) and questionaire. Results showed that significant correlation is found between selfregulated learning and internet addiction (p < .05). Moreover, there is no significant correlation between GPA and internet addiction as well as SRL also does not correlate with GPA of the participants. SRL indicators of effort regulation and attention-focusing correlate with internet addiction. Further research should consider the improvement of measurement tools to identify internet access behavior and internet addiction among first-year students.
Yet Another Look at the Modernisation Hypothesis: Evidence from Latin America

We investigate in this paper whether the exogenous version of the modernisation hypothesis holds in South America, or whether democracy needs development for its own consolidation. We use a sample of all nine countries that re-democratised in the last thirty years or so and the data sets cover two distinct periods, 1970-2007, and 1945-1969. The results, based on dynamic panel time-series data analysis (we use the Fixed Effects, Common Correlated Effects and Fixed Effects with Instrumental Variables estimators), suggest that the modernisation hypothesis holds in the region during the period 1970-2007, or that income, or development in general, plays a positive role in "sustaining" democracy. Moreover, the exogenous version of the modernisation hypothesis does survive scrutiny for the period 1945-1969 as well, a period in which the continent was relatively poorer and democracy a rather elusive concept in the region. We also test for the critical junctures hypothesis, or whether particular historical structural changes play any role in contemporaneous democratisation in the region, however we are not able to provide any concrete evidence in favour of it. Essentially, we suggest that a certain level of development is an important condition for democracy to survive and mature, which - in times of a new democratisation wave taking place in societies with diÂ¤erent developmental paths - is a suggestive observation.
A CONNECTIONIST PARADIGM IN THE COORDINATION AND CONTROL OF MULTIPLE SELF-INTERESTED AGENTS

Complex design and planning cases involve distributed knowledge conducted by selfinterested agents. The multiplicity of interdependencies among goals, plans and activities emerged in design and planning, directs the necessity for coordination and consensus. We can distinguish two conditions where the importance for co-ordination among the parties involved, takes different forms. These are multi-agent collaborative planning and distributed problem solving. We introduce a connectionist approach to “co-ordination via control” and we discuss the formalization of a meta-model for knowledge representation that captures interdependencies among objects emerged in complex design and planning cases. We finally discuss the development of a Web-based tool for agent control and coordination.
BeepShuttle Junior: Software for the Administration of the 20m Shuttle Run Test in Children and Adolescents

The 20m shuttle run test (20mSRT) is applied for assessing cardiorespiratory fitness, and is included in many fitness test batteries, such as Eurofit, Alpha-fit, FitnessGram, etc. The aim of this study was to validate software, specially designed by us (BeepShuttle Junior), which administers the 20mSRT, calculates the maximal oxygen uptake (VO2max) in children and adolescents from 6 to 17 years of age, and classifies them in accordance with comprehensive genderand age-specific international norms. This software supports the administration of the 20mSRT with an appropriate animation and audio signals. The most recent VO2max reference standards were combined in order to assess cardiorespiratory fitness. The results can be exported in an Excel compatible CSV file for additional analyses. A total of 63 children (31 girls and 32 boys) from London, aged from 6 to 9, were tested with the BeepShuttle Junior software, which calculated VO2max and percentile scores for each child. The boys performed significantly better than girls in cardiorespiratory fitness (47.7 ± 3.1 vs 45.9 ± 2.2 ml/kg/min respectively, p < 0.05), but the mean percentile scores for boys and girls were similar (53.2 ± 23.6 and 53.9 ± 22.1 respectively). This software computes the percentile score for the exact age (years, months) and the exact VO2max of each participant by linear interpolation. The individual results and assessments completely matched the interpolated normative data tables.
Intronic Sequences for the Discrimination of Silkworm Strains in Silkworm Powder

After a serial study on the therapeutic efficacy of the powdery silkworm for diabetics was positively resulted in, many powdery silkworm products were on the market in Korea. Up to now, however, no causal method is available to discriminate the strain of silkworms that is a major ingredient for manufacturing powdery silkworm, even though the quality of the powdery silkworm differs greatly by source and origin of strains. We previously were successful in identifying 25 silkworm strains kept in Korea using nine intronic sequences. In this study, we tested the utility of the nine intronic sequences to distinguish the most widely reared silkworm strains originated from Korea and China. Two intron regions, PTTH Intron3 and PTTH Intron3, showed a substantial sequence divergence (mean sequence divergence of 3.13% in PTTH Intron3 and 4.99% in PTTH Intron3). These two intronic sequences provided no identical sequences among the seven strains tested. Thus, these sequences each along can be used to discriminate the seven strains tested in this study. Furthermore, other intron regions, except for VDP Intron4 allowed us to discriminate strains by strain-specific unique insertion/deletion or substitution.
Antioxidant Evaluation in Malaysian Medicinal Plant : Persicaria minor ( Huds . )

Persicaria minor (Huds.) from the family Polygonaceae is a common medicinal plant found in South East Asia. In Malaysia the plant is locally know as kesum. The kesum leaves are often consumed as ulam (raw medicinal plants consumed with daily meals) for preventive health care. In the Malaysian Traditional Medicine System, the decoction of kesum leave is recommended for digestive disorders and stomach pain. In a previous study (Vimala et al. 1999), preliminary screening of various Malaysian medicinal plants showed that kesum leaf possessed high antioxidant activity (>90%). Thus kesum is a potential and interesting plant for antioxidant evaluation. In this study, to obtain the antioxidant profile of kesum, the leaf aqueous extract was subjected to 3 antioxidant pathways representing Lipid Peroxidation Inhibition, Superoxide Scavenging and DPPH Free Radical Scavenging. The leaf extract was also subjected to Total Phenolic Content (TPC) and HPLC evaluation. The kesum leaf aqueous extract was further subjected to cytotoxicity evaluation using WRL-68 human liver and Vero monkey kidney cell lines. The extract was also subjected to microbial load count and heavy metal analysis. The results of the present study showed that kesum leaf aqueous extract possessed high antioxidant activity which was exhibited as >70% inhibitory activity in all 3 antioxidant assays. Kesum leaf also showed high Total Phenolic Content (2800.6 mg/100g GAE). The HPLC analysis showed the presence of flavanoids, phenolics and oxalic acid in kesum leaf. The leaf extract was found to be free from cytotoxicity (IC50 >300 μg/ml) in WRL-68 human liver and Vero monkey kidney cells. Microbial contamination and heavy metals were not detected. Thus kesum is a potential antioxidant plant for cultivation and exploitation as food additive. Oxalic acid is a powerful oxidizing agent that binds calcium to aid the digestive system. The scientific findings of this study support the traditional claims of kesum leaf as a medicinal plant for preventive health care and digestive disorders. Thus the kesum leaf is recommended as an antioxidant food additive for preventive health care.
A fuzzy sets approach to new product portfolio management

The evaluation of R&D projects in a high technology firm is very important. A lot of them quite often do not lead to new products as management did not take into consideration indexes such as probability of commercial success, technological success, strategic fit, etc which cannot be expressed in a quantitative form. An efficient and reliable approach for evaluating R&D projects capable of handling simultaneously the quantitative and qualitative criteria involved based on the theory of fuzzy logic is presented and a software model of the approach has been developed and tested in a real environment. It is a multiple criteria decision-making method where all projects are rated according to a number of quantitative and qualitative criteria capturing possibilities of technical and commercial success and the consistency of the projects with business strategy. We report on the criteria used for the evaluation of the projects and on the operation of the software model.
History PCA: A New Algorithm for Streaming PCA

In this paper we propose a new algorithm for streaming principal component analysis. With limited memory, small devices cannot store all the samples in the high-dimensional regime. Streaming principal component analysis aims to find the $k$-dimensional subspace which can explain the most variation of the $d$-dimensional data points that come into memory sequentially. In order to deal with large $d$ and large $N$ (number of samples), most streaming PCA algorithms update the current model using only the incoming sample and then dump the information right away to save memory. However the information contained in previously streamed data could be useful. Motivated by this idea, we develop a new streaming PCA algorithm called History PCA that achieves this goal. By using $O(Bd)$ memory with $B\approx 10$ being the block size, our algorithm converges much faster than existing streaming PCA algorithms. By changing the number of inner iterations, the memory usage can be further reduced to $O(d)$ while maintaining a comparable convergence speed. We provide theoretical guarantees for the convergence of our algorithm along with the rate of convergence. We also demonstrate on synthetic and real world data sets that our algorithm compares favorably with other state-of-the-art streaming PCA methods in terms of the convergence speed and performance.
Query-by-Example Spoken Document Retrieval : The Star Challenge 2008

2 R) Agency for Science, Technology and Research (A*STAR), Singapore. {hli,kcsim,svivek,lyekm}@i2r.a-star.edu. sg Abstract - In this paper, we give an update of recent research activities in HLT department of I 2 R in query-by- example spoken document retrieval (SDR) and report an evaluation campaign, the Star Challenge 2008, which was organized by A*STAR, Singapore. It is suggested that low- level feature-based approach, which does not rely on error- prone speech transcripts, is a promising solution to query-by- example multilingual spoken document retrieval.
Hg Substitution Effect on Superconductivity and Crystal Structure of MgB 2

Polycrystalline Mg1-xHgxB B 2 samples with x=0, 1%, 2.5%, 5%, 7.5%, and 10% have been synthe- sized by solid-state reaction. Different from the substitu- tion effect of Al, C, Li, etc. on crystal structure of MgB2 B , Hg substitution for Mg results in an increase of the lattice constant in both a and c directions. The super- conductivity of MgB2 is also suppressed by Hg substi- tution. The observed suppression of super- conductivity by Hg substitution is discussed in terms of the interband impurity scattering effect in two-band superconductors.
The Kicktionary – A Multilingual Lexical Resource of Football Language

This paper presents the Kicktionary, an electronic multilingual (English, German, French) lexical resource of the language of football.1 The Kick­ tionary was constructed predominantly on the basis of frame semantic principles, and is therefore perhaps best described as a multilingual, domain-specific FrameNet.2 However, the objectives of the Kicktionary project are in many ways more restricted than those of the Berkeley FrameNet project. My primary goal was (and remains) to produce a lexi­ cal resource usable by humans for purposes of understanding, translating or otherwise paraphrasing texts in the domain of football. In contrast to much work currently being carried out by FrameNet and by related projects, the Kicktionary does thus not claim to make contributions to fields like machine translation, question answering or other sub-areas of natural language processing or artificial intelligence. By restricting the scope of research to computer-assisted lexicography for human users, I want to ofler some answers to the following questions:
COAST report

We describe a model for resolution of belief conflicts by argumentation in agent interactions, based on aspects of dialogic logic, speech act theory and belief systems research. This is part of a long term project on the relations between argumentation and cognitive change in collaborative problem-solving interactions. A set of communicative acts for argumentative interaction is defined, based on viewing them as multifunctional with respect to argumentation and interaction control. We concentrate on defining different intraand inter-personal conflict situations, in terms of agents' mental states, and specify the communicative acts that are relevant within each of them. An illustrative example of an argumentation sequence is presented and discussed in relation to the model. Our main claims are that the dialectical and rhetorical dimensions of argumentation need to be situated within a more general interactional framework, and that resolution of belief conflicts can give rise to increased coherence in agents' epistemic states.
Non-H3 CDR template selection in antibody modeling through machine learning

Antibodies are proteins generated by the adaptive immune system to recognize and counteract a plethora of pathogens through specific binding. This adaptive binding is mediated by structural diversity in the six complementary determining region (CDR) loops (H1, H2, H3, L1, L2 and L3), which also makes accurate structural modeling of CDRs challenging. Both homology and de novo modeling approaches have been used; to date, the former has achieved greater accuracy for the non-H3 loops. The homology modeling of non-H3 CDRs is more accurate because non-H3 CDR loops of the same length and type can be grouped into a few structural clusters. Most antibody-modeling suites utilize homology modeling for the non-H3 CDRs, differing only in the alignment algorithm and how/if they utilize structural clusters. While RosettaAntibody and SAbPred do not explicitly assign query CDR sequences to clusters, two other approaches, PIGS and Kotai Antibody Builder, utilize sequence-based rules to assign CDR sequences to clusters. While the manually curated sequence rules can identify better structural templates, because their curation requires extensive literature search and human effort, they lag behind the deposition of new antibody structures and are infrequently updated. In this study, we propose a machine learning approach (Gradient Boosting Machine [GBM]) to learn the structural clusters of non-H3 CDRs from sequence alone. The GBM method simplifies feature selection and can easily integrate new data, compared to manual sequence rule curation. We compare the classification results using the GBM method to that of RosettaAntibody in a 3-repeat 10-fold cross-validation (CV) scheme on the cluster-annotated antibody database PyIgClassify and we observe an improvement in the classification accuracy of the concerned loops from 84.5% ± 0.24% to 88.16% ± 0.056%. The GBM models reduce the errors in specific cluster membership misclassifications when the involved clusters have relatively abundant data. Based on the factors identified, we suggest methods that can enrich structural classes with sparse data to further improve prediction accuracy in future studies.
Phylogenetic study of Lac Insects of Kerria spp. using intron length polymorphism (EPIC-PCR)

Lac insects belonging to Kerria species are the most commonly used species for commercial lac production. They are also harnessed for the production of lac dye and wax. Using five Exon Primed Intron Crossing (EPIC) PCR primers for Kerria spp. , we studied the intra- and interspecific variation among a population of forty eight lac insect lines. The study separated K. chinensis from rest of the lines and also made differentiation between the infrasubspecific forms of K. lacca i.e., kusmi and rangeeni.
Numerical Modeling of the Processes of Coagulation and Dispersion of Drops in Electric Field

Results of the physical and mathematical modeling of the processes of producing and disintegrating water-oil emulsions using the COMSOL Multiphysics software, as well as of electric fields, velocity fields, and pressure fields, under boundary conditions that correspond to the apparatuses under development are presented. Based on the analysis of the data obtained, different versions of the design of electric dispersers and electric dehydrators are proposed. Key words : Electric dispersers; Design; Modernization; Physicochemical characteristics; Emulsion; Model fluids; Drop diameter; Field strength
A Fast Method for Monitoring Driver Fatigue Using Monocular Camera

Driver fatigue is an important factor in a large number of accidents. In this paper, a real time vision-based method is proposed to monitor driver fatigue. Firstly, the face is located by a Haar-like feature based object detection algorithm, Secondly, eye is detected and eyelid distance is computed. By analyzing the changes of the distance of eyelid along with time, we can detect driver’s fatigue and issue a warning. The main advantage of this system is its extreme high speed and very simple equipment. This system runs at about 15 frames per second in video with 640*480resolution.
Modeling time-to-good control of hypertension using Cox proportional hazard and frailty models at Bahir-Dar Felege Hiwot Referral Hospital

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Characterizing the fabric of the urban environment: A case study of Greater Houston, Texas

In this report, the materials and various surface types that comprise a city are referred to as the urban fabric. Urban fabric data are needed in order to estimate the impact of light-colored surfaces (roofs and pavements) and urban vegetation (trees, grass, shrubs) on the meteorology and air quality of a city, and to design effective urban environmental implementation programs. We discuss the results of a semi-automatic Monte-Carlo statistical approach used to develop data on surface-type distribution and city-fabric makeup (percentage of various surface-types) using aerial color orthophotography. The digital aerial photographs for Houston covered a total of about 52 km2 (20 mi2). At 0.30-m resolution, there were approximately 5.8 x 108 pixels of data. Fourmajor land-use types were examined: (1) commercial, (2) industrial, (3) educational, and (4) residential. On average, for the regions studied, vegetation covers about 39 percent of the area, roofs cover about 21 percent, and paved surfaces cover about 29 percent. For the most part, trees shade streets, parking lots, grass, and sidewalks. At ground level, i.e., view from below the vegetation canopies, paved surfaces cover about 32 percent of the study area. GLOBEIS model data from University of Texas and land-use/land-cover (LULC) information from the United States Geological Survey (USGS) were used to extrapolate these results from neighborhood scales to Greater Houston. It was found that in an area of roughly 3,430 km2, defining most of Greater Houston, over 56 percent is residential. The total roof area is about 740 km2, and the total paved surface area (roads, parking areas, sidewalks) covers about 1000 km2. Vegetation covers about 1,320 km2.
Temporal and Spatial Changes of a Seasonal Snowpack Within a Small Sheltered Slope

We studied the seasonal evolution of a natural snowpack and changes thereof within a small sheltered slope, utilizing non-destructive monitoring systems continuously over more than three months. During the winter season 2012, a permanent installation of a 800 MHz upward-looking ground-penetrating radar (upGPR) provided sub-daily to hourly data about variations in total snow depth, liquid-water content and major stratigraphy at a point in the center of the slope. In addition, to observe the spatial representativeness of these point measurements, we performed radar observations along a 22m aerial tramway once a week using a 1GHz GPR system. The transect crossed the upGPR location and thereby allowed us to put the point measurement in the context of the entire slope. Furthermore, conventional snow pits including densities, liquid-water content measurements and depth probings were recorded next to the tramway right before or after the above-snow measurements. An automated weather station, which was located on a ridge line right above the study slope, provided standard meteorological and snow observations. Utilizing upGPR data together with the tramway measurements, we can determine and time strain rates, new-snow amounts and percolation of liquid water in relation to the prevailing weather conditions and observe both spatial and temporal variability in these properties. The scope of this paper is to demonstrate the potential of non-destructive observations in seasonal snowpacks, to provide further information of the formation of changes in stratigraphy and the variability thereof across a slope.