Miracle-dz/UniFAR-FTUs huggingface dataset:
Modeling User Preferences Using Relative Feedback for Personalized Recommendations

Recommender systems are widely developed to learn user preferences from their past history and make predictions on the unseen items a user may like. User preferences in the form of absolute preferences, such as user ratings or clicks are commonly used to model a user’s interest and generate recommendations. However, rating items is not the most nat-ural mechanism that users use for making decisions in daily life. For instance, we do not rate t-shirts when we want to buy one. It is more likely that we will compare them one to one, and purchase the preferred one. In this work, we focus on relative feedback, which generates pairwise preferences as an alternative way to model user preferences and compute recommendations. In our scenario, each user is shown a set of item pairs and asked to compare them to indicate which item in the pair is more preferred. We propose a recommendation algorithm to predict a user’s relative preference for a given pairs of items and compute a personalised ranking of items. We demonstrate the effectiveness of our proposed algorithm in comparison with state-of-the-art relative feedback based recommendation approaches. Our experimental results reveal that the proposed algorithm is able to outperform the baseline algorithms on popular ranking-oriented evaluation metrics.
Reintroduction of rare and endangered plants: common factors, questions and approaches

The science of reintroduction for conservation purposes is young, and there is still much to learn about the practice. As a means to achieving biological goals of successfully establishing new populations to enhance a species survival prospects, and project goals, such as learning how to go about establishing new populations, reintroduction projects are best done as well designed scientific experiments that test explicit hypotheses. Focusing on a range of factors common to any reintroduction, we review several empirical reintroduction projects with respect to hypotheses tested, experimental materials and methods employed, and evaluate their success in both biological and project terms.
In-memory k Nearest Neighbor GPU-based Query Processing

The k Nearest Neighbor (k-NN) algorithm is widely used for classification in several application domains (medicine, economy, entertainment, etc.). Let a group of query points, for each of which we need to compute the k-NNs within a reference dataset to derive the dominating feature class. When the reference points volume is extremely big, it can be proved challenging to deliver low latency results. Furthermore, when the query points are originating from streams, the need for new methods arises to address the computational overhead. We propose and implement two in-memory GPU-based algorithms for the k-NN query, using the CUDA API and the Thrust library. The first one is based on a Brute Force approach and the second one is using heuristics to minimize the reference points near a query point. We also present an extensive experimental comparison against existing algorithms, using synthetic and real datasets. The results show that both of our algorithms outperform these algorithms, in terms of execution time as well as total volume of in-memory reference points that can be handled.
Optically stimulated luminescence dating reveals rate of beach ridge and sand spit depositions from the upper Gulf of Thailand

This study aimed to increase the understanding of the history of late Quaternary coastal evolution. An analysis was carried out on the optically stimulated luminescence (OSL) dates of 12 quartz-rich samples collected from the Chanthaburi paleosand spit and 37 samples from beach ridges at Sam Roi Yot National Park in the upper Gulf of Thailand. The single-aliquot regenerative technique was employed after OSL sample treatment. As a result, both equivalent dose and annual dose provided OSL signals that were internally consistent. The derived OSL ages were in good agreement with the stratigraphic evolution of the spit and beach-ridge progradation. OSL dating of the paleo-sand spit revealed that the age ranged from 17,210 to 1,370 years. The average lateral migration rate of the sand spit varied from 0.2 to 1.8 m/year. The OSL age of the beach ridge plain from Sam Roi Yot National Park started from 10,200 to 880 years. The beach ridge plain had an average eastward progradation of 0.4-22 m/year.
Evaluation of Learning Motivation within an Adaptive e-Learning Platform for Engineering Science

Learning motivation represents an important determinant for a successful learning process. Especially in the context of self-regulated learning with e-learning systems learning blocks or learning breaks occur increasingly when motivation is dropping. Creating appropriate learning experiences that respond to learners’ needs is important to maintain learning motivation. This supports continuous usage of e-learning systems at universities. Adaptive e-learning systems are a possibility to react profoundly to individual needs of the learners before or during the learning process. Therefore, an e-learning platform for microand nanotechnologies was transformed into an adaptive learning system to foster learning motivation at the Technische Universität Ilmenau within a multi-level development process. Results showed that the e-learning platform was well accepted but a significant benefit of the adaptive version compared to the non-adaptive version could
SAS vs. NSAS: Analysis and Comparison of Self-Adaptive Systems and Non-Self-Adaptive Systems based on Smells and Patterns

Self-Adaptive Systems are usually built of a managed part, implementing their functionality, and a managing part, implementing their self-adaptation. The complexity of self-adaptive systems results also from the existence of the managing part and the interaction between the managed and the managing parts. The nonself-adaptive systems may be seen as the managed part of self-adaptive systems. The self-adaptive systems are evaluated based on their performances resulted from the self-adaptation. However, self-adaptive systems are software systems, hence, also their software quality is equally important. Our analysis compares the internal quality of self-adaptive and non-self-adaptive systems by considering code smells, architectural smells, and GoF’s design patterns. This comparison provides an insight to the health of the self-adaptive systems with respect to the non-self-adaptive systems (the last being considered as a quality reference).
Isolation of two flavonoids from Bauhinia Monandra (KURZ) leaves and their antioxidative effects

Bauhinia monandra (Kurz), traditionally use in the treatment of diabetes with established significant anti-diabetic activity was investigated for its antioxidant constituents since the activity demonstrated can be linked to the presence of antioxidant compounds. Bioassay directed fractionation of the ethyl acetate soluble leaves extract has led to isolation of two active compounds identified as: Quercetin-3-O-rutinoside (1) and Quercetin (2). The molecular structures elucidations of both compounds were carried out using spectroscopic studies (1H NMR, 13C NMR and MS). These compounds are reported from this species for the first time. A DPPH spectrophotometric assay was used to evaluate the antioxidant potential of the compounds. Compound 2 had higher antioxidant activity while Compound 1 had lower activity than L-ascorbic acid which was used as
QTLs Associated with Resistance to Soybean Cyst Nematode in Soybean: Meta-Analysis of QTL Locations

Soybean cyst nematode (SCN) (Heterodera glycines Ichinohe) is the most important pest of soybean [Glycine max (L.) Merr. ] in the world. A total of 17 quantitative trait locus (QTL) mapping papers and 62 marker–QTL associations have been reported for resistance to soybean cyst nematode in soybean. Conflicting results often occurred. The objectives of this study were to: (i) evaluate evidence for reported marker–QTL associations for resistance to SCN in soybean and (ii) extract relatively reliable and useful information from the reported marker–QTL associations in soybean. A meta-analysis was conducted for QTL locations by comparing the 95% confidence intervals of the reported QTLs. QTLs for different races or different studies were classified into one cluster if their confidence intervals had a region in common. The QTLs of the same cluster may have a shared locus. QTLs for different races or different studies were classified into different clusters if their confidence regions had no region in common and were $ 20 cM away from each other. Different clusters may represent different loci. Reported SCN resistant QTLs were classified into three categories: suggestive, significant, and confirmed. Confirmed QTLs are credible and can be candidates for fine mapping and gene cloning. QTLs on linkage groups (LGs) G, A2, B1, E, and J were classified as confirmed. Two clusters of QTLs were identified on LG G. One of them is rhg1. One cluster of QTLs was identified near the end of LG B1, but one QTL may exist around the middle of LG B1. One cluster of QTLs was identified on LGs A2, E, and J, respectively. QTLs on LGs B2, C1, C2, D1a, D2, L, M, and N were classified into suggestive or significant. Confirmation studies are needed to lend credibility for these QTLs. A relationship between soybean QTLs and SCN races is discussed.
Molecular phylogenetics of the Muscidae (Diptera : Calyptratae): new ideas in a congruence context

Hypotheses about the evolution of Muscidae have long been the subject of continuous re-evaluation and reinterpretation. Current understandings of the relationships among these flies are based mainly on a single set of characters and are therefore questionable. Our understanding of muscid phylogeny thus needs greater support and further corroboration from additional suites of characters. In the current study, we analysed phylogenetic relationships among 24 species of muscid flies (18 genera and six subfamilies) using 2989 characters derived from sequences of mitochondrial (COI and COII) and nuclear genes (CAD and EF-1α). Data from each gene partition were analysed both in combined and separate phylogenetic analyses using maximum parsimony, maximum likelihood, and Bayesian inference. Support was found for the monophyly of the Muscidae in all analyses and for a sister-group relationship between Coenosiini and Phaoniinae. The latter group was placed in a clade with sampled species of Reinwardtiini and Cyrtoneurininae. The genera Ophyra and Hydrotaea were placed in the Muscinae and a sister-group relationship for Musca and Stomoxys was supported. Sampled species of Polietina form a monophyletic lineage, while Morellia was found to be paraphyletic. Combined analysis of gene partitions improved support and resolution for resulting topologies despite significant incongruence between data partitions found through application of the Incongruence Length Difference test.
Service Robots: Emotions of Older Adults in Different Situations

: Against the background of demographic change and an expected shortage of skilled nursing staff, consideration is being given to whether robots will play a greater role to assist older adults in daily life activities and care personnel. Many models of Technology Acceptance do not focus on emotions of older adults triggered by service-type robots that support daily activities or care activities. The present simulated robot study investigated emotions of 142 older adults towards different robots in different situations to contribute to a deeper understanding of the acceptance of robots. The situation in which a robot interacts with a human affected the emotions of the older participants differently: in the service situation, less negative emotions were expressed than in the care situation. These results should be considered when developing service robots for older adults. The results should be validated with existing robots in real life.
Risk Analysis Techniques for ERP Projects based on Seasonal Uncertainty Events

Risk management is fundamental in order to increase Enterprise Resource Planning (ERP) project success rate in order to plan, prevent and react to risks and uncertainties. But based on the literature review, we identified a few studies relating to both seasonal uncertainty events (SUE) and ERP projects. Given this context, this research objective is to analyse the most appropriate risk assessment techniques for ERP projects based on SUE. In order to achieve this goal, we performed and Systematic Review of Literature and we applied the Delphi technique with Project Management Professionals and Enterprise Directors. According to the SLR result, we identified 16 techniques that are more suitable to deal with SUE on ERP projects. After the Delphi panels perspective, six techniques pointed out as the most suitable for these projects. In addition, we identified that not all techniques described by the literature converged with the researched context reality. These findings are very relevant for both the Academia and the Industry to scaffolding SUE on ERP projects.
Performance Analysis of Supervised Machine Learning Algorithms on Medical Dataset

Machine learning (ML) algorithms are designed to perform prediction based on features. With the help of machine learning, system can automatically learn and improve by experience. Machine learning comes under Artificial intelligence. Machine learning is broadly categorized in two types: supervised and unsupervised. Supervised ML performs classification and unsupervised is for clustering. In present scenario, machine learning is used in various areas. It can be used for biometric recognition, hand writing recognition, medical diagnosis etc. In medical field, machine learning plays an important role in identifying diseases based on patient’s features. Presently,doctors use software application based on machine learning algorithm in various disease diagnosis like cancer, cardiac arrest and many more. In this paper we used an ensemble learning method to predict heart problem. Our study described the performance of ML algorithms by comparing various evaluating parameters such as F-measure, Recall, ROC, precision and accuracy. The study done with various combination ML classifiers such as, Decision Tree (DT), Naïve Bayes (NB), Support Vector Machine (SVM), Random Forest (RF) algorithm to predict heart problem. The result showed that by combining two ML algorithm, DT with NB, 81.1% accuracy was achieved. Simultaneously, the models like Support Vector machine (SVM), Decision tree, Naïve Bayes, Random Forest models were also trained and tested individually.
XEL Group Learning - A Socio-technical Framework for Self-regulated Learning

We describe XEL-Group Learning, a socio-technical framework for socially oriented e-learning. The aim of the presented framework is to address the lack of holistic pedagogical solutions that take into account motivational theories, socio–technical factors, and cultural elements in social learning networks. The presented framework provides initiatives for collaboration by providing a dynamic psycho-pedagogical recommendation mechanism with validation properties. In this paper, we begin by highlighting the sociotechnical concept associated with socially-oriented e-learning. Next, we describe XEL-GL’s main mechanisms such as group formation and the semantic matching framework. Moreover, through semantic similarity measurements, we show how cultural elements, such as the learning subject, can enhance the quality of recommendations by allowing for more accurate predictions of friends networks.
Determination of the phytochemical ingredients and antioxidative potential of hydromethanolic extract of Asparagus racemosus Willd

Asparagus racemosus is considered as an important medicinal plant of India. In the present study fifty percent hydromethanolic extract of roots of Asparagus racemosus (ARE) was prepared and analyzed for presence of various phytoconstituents in ARE employing different biochemical qualitative tests and GCMS analysis. It was further explored for its antioxidative potential through hydrogen peroxide scavenging assay. Biochemical tests confirmed presence of various phytochemicals viz., resins, tannins, Saponins, flavonoids, alkaloids, glycosides, etc. GC-MS analysis showed presence of thirty compounds. Major phyto-constituent predicted in Asparagus racemosus is Di-n-octyl phthalate (89.58%) upon comparison with NIST and WELLY library. The present study indicated anti-oxidative property of ARE. The percent H2O2 scavenging activity of ARE was found to be 25.41%. Thus it could be concluded that ARE displayed presence of various phytoconstituents which could be responsible for its antioxidative potential.
The Reproduction and Development of Microsetella Norvegica (Boeck) (Copepoda, Harpacticoida) in Northumberland Coastal Waters

[Chez Microsetella norvegica de la cote de Northumberland, Angleterre, la proportion des mâles aux femelles est de 1.9 a 1. Les œufs evoluent a l'interieur des femelles, dans une chambre incubatrice qui s'etend du premier segment thoracique au dernier segment abdominal. Apres la ponte les œufs sont deposes dans un sac qui contient de 14 a 16 œufs. La morphologie des nauplii et des copepodites est illustree. Les larves sont absentes en hiver mais la reproduction continue pendant le reste de l'annee. Le facteur de croissance est cite pour chaque stade de N3 a l'adulte. , Chez Microsetella norvegica de la cote de Northumberland, Angleterre, la proportion des mâles aux femelles est de 1.9 a 1. Les œufs evoluent a l'interieur des femelles, dans une chambre incubatrice qui s'etend du premier segment thoracique au dernier segment abdominal. Apres la ponte les œufs sont deposes dans un sac qui contient de 14 a 16 œufs. La morphologie des nauplii et des copepodites est illustree. Les larves sont absentes en hiver mais la reproduction continue pendant le reste de l'annee. Le facteur de croissance est cite pour chaque stade de N3 a l'adulte. ]
User-adaptable Natural Language Generation for Regression Testing within the Finance Domain

Reporting duties and regression testing within the financial industry produce huge amounts of data which has to be sighted and analyzed by experts. This time-consuming and expensive process does not fit to modern, agile software developing practices with fast update cycles. In this paper, we present a user-adaptable natural language generation system that supports financial experts from the insurance industry in analysing the results from regression tests for Solvency II risk calculations and evaluate it with a group of experts.
NOVELTIES IN ICE NUCLEATION TERMINOLOGY

A revision of the Nucleation Terminology of 1985 was put forth in Atmospheric Chemistry and Physics (15, 10263, 2015; VDMW15), focussed on ice nucleation. For some of the terms dealt with in VDMW15, in connection with heterogeneous ice nucleation, additional explanations are offered here with a grouping by the degree of novelty involved. The goal is to promote the acceptance of the terms and to motivate discussion about the principles involved.
Evolution of Physics Sub-fields

: We study the evolution and relationships between sub-ﬁelds of Physics using the large data set of articles published in the various physical review journals from 1985-2010. Each article is assigned to some PACS codes by their authors which represent speciﬁc sub-ﬁelds of Physics. We construct a weighted network with nodes as PACS codes and there is a link between two PACS codes if there is an article assigned to both these codes. The weight of a link represents the number of articles in which both PACS codes appears. We study the time evolution of PACS network at various hierarchy levels of PACS codes. We observe that sub-ﬁelds Physics of elementary particles and ﬁelds, Nuclear Physics and Condensed matter physics have stronger connections inside the ﬁeld compared to connections to other sub-ﬁelds. We also observe that both condensed matter physics sub-ﬁelds are strongly related compared to any other pair of sub-ﬁelds.
Standardized procedure for measuring foaming properties of three proteins, a collaborative study

A collaborative study involving nine laboratories was conducted over four years to evaluate a rapid, simple and reliable whipping method for measuring overrun and foam stability. Effectiveness of the method was assessed by measuring the characteristics of foams formed by three protein solutions (5%): sodium caseinate, milk protein isolate, and egg white protein; identifying and systematically eliminating sources of variability. Major sources of variability were protein dispersing technique, the mixer, and the care exercised by the operator during sampling and weighing. The method detected differences in foam stability between egg white, casein and milk protein isolate (pooled SD = 4.5) using different mixers.
A Methodology for Determination of Performance Measures Thresholds for Business Process

Business process performance is vital for organizations which aim to produce a high performance model. In the literature, performance of the business process can be evaluated through formal verifications, simulation, or a set of measures. In this paper, we adopt measures-based assessment to evaluate the performance of business process models, modelled with Business Process Modelling and Notation (BPMN), in terms of the characteristics related to BPMN elements (i.e. time behaviour, cost ) and characteristics related to the actor (ie. availability, suitability and its cost). We propose a methodology based on fuzzy logic which apply performance measures to assess these characteristic’s levels. In addition, it expresses the problem of defining threshold based on a set of BPMN models2s. Furthermore, our methodology evaluates the performance of business process models based on fuzzy logic. The efficiency of the proposed methodology is illustrated through a case study and a tool that fully support the developed system.
Work stress of employees affected by skills shortages in the South African mining industry

Skills shortages in core occupational categories in the South African mining industry have reached crisis proportions. The reason for this is that the demand for qualified individuals exceeds the supply. The result is that available employees are overburdened with duties and responsibilities. To curb the current exodus of qualified employees, such as artisans and engineers, mining companies need to consider the wellbeing of these individuals. This study investigated the work stress of employees affected by skills shortages at selected gold mines in South Africa. A descriptive quantitative research design was employed. Convenience sampling was used, and the final sample consisted of 188 artisans and engineers. The respondents indicated that they do experience work-related stress. Occupational aspects that were statistically significantly related to work stress were the physical work environment, career-related issues, and HR policy, especially pertaining to remuneration and fringe benefits. The findings of the study deepen the understanding of work stress of employees employed in occupational categories where skills shortages exist. The findings suggest that mining companies nationwide need to place increased focus on the wellbeing of their employees, so as to prevent further skills shortages in this industry.