Miracle-dz/UniFAR-FTUs huggingface dataset:
Atherogenic Indices and Polymorphism of the FXR Gene in Obese Individuals , Overweight and Normal Weight Individuals

Obesity is the result of interplay between genetic and environmental factors. Polymorphisms in various genes controlling appetite and metabolism predispose to obesity when sufficient calories are present. It is not known whether polymorphisms in FXR gene are associated with high lipid level among obese individuals. This study was designed to investigate and compare the lipid profile and polymorphism of the FXR gene in obese individuals, overweight and normal weight individuals. We investigated 35 obese subjects, 35 overweight subjects and 35 normal weight subjects. Plasma triglyceride, plasma cholesterol, plasma high density lipoprotein (HDL), plasma low density lipoprotein (LDL) and fasting blood glucose were determined in these subjects. These subjects were also genotyped for farnesoid receptor. Abnormal allele of FXR gene occurred more frequently in the obese category than those in overweight and normal weight category. Plasma triglyceride was significantly lower in FXR homozygous (FXR +/+ ) individual than FXR heterozygous (FXR +/) individual (p<0.05). Plasma HDL was significantly higher in heterozygous subjects than homozygous subjects for FXR. Plasma cholesterol and LDL was significantly lower in FXR +/+ as compared to FXR +/(p<0.05). Genetic changes affecting FXR function have the potential to be proatherogenic and early management strategy should be encouraged to protect these group of individual from atherogenic complications.
Effect of ventricle motion on the dynamic behaviour of chorded mitral valves

An Immersed Boundary (IB) model is employed to investigate the dynamic behaviour of a novel chorded mitral prosthesis, which is in the early stages of its development, under physiological flow conditions. In vivo magnetic resonance images (MRIs) of the left ventricle are analysed to determine the relative motion of the mitral annulus and the papillary muscle regions of the ventricle. The dynamic boundary conditions are incorporated into IB simulations to test the valve in a more realistic dynamic geometric environment. The IB model has successfully identified the effect of the dynamic boundary conditions on the mechanical behaviour of the valve and revealed the strengths and weaknesses of the current mitral design. The mechanical performance of the prosthesis is compared with recent studies of native porcine valves; differences in mechanical behaviour are observed. Potential improvements for the design of the prosthesis are proposed. r 2007 Elsevier Ltd. All rights reserved.
The Mixadapt Scale: A Measure of Marketing Mix Adaptation to the Foreign Market

This study presents a four-dimensional multi-item scale for assessing the degree of marketing mix adaptation to the foreign market (the MIXADAPT scale). The scale shows evidence of reliability as well as convergent, discriminant and nomological validity in samples of Portuguese and British exporters. Additionally, the scale reveals factorial similarity and factorial equivalence across the two samples. The findings are used to generate managerial and theoretical implications as well as directions for future research.
Constrained Autoencoders for Data Representation and Dictionary Learning

Without proper choice of constraints, autoencoders are capable of learning identity mapping or overcomplete representations. The features learned by this architecture may be local, isolated or primitive. The extraction of features, however, can be controlled by judiciously enforcing some desired attributes, in form of constraints on its parameters. This paper gives an overview of autoencoders and such constraints for data representation. It also puts the autoencoder learning in a broader context of dictionary learning.
Characterization of the 3D microstructure of Ibuprofen tablets by means of synchrotron tomography

A new methodology to segment the three‐dimensional (3D) internal structure of Ibuprofen tablets from synchrotron tomography is presented, introducing a physically coherent trinarization for greyscale images of Ibuprofen tablets consisting of three phases: microcrystalline cellulose, Ibuprofen and pores. For this purpose, a hybrid approach is developed combining a trinarization by means of statistical learning with a trinarization based on a watershed algorithm. This hybrid approach allows us to compute microstructure characteristics of tablets using methods of statistical image analysis. A comparison with experimental results shows that there is a significant amount of pores which is below the resolution limit. At the same time, results from image analysis let us conjecture that these pores constitute the great majority of the surface between pores and solid. Furthermore, we compute microstructure characteristics, which are experimentally not accessible such as local percolation probabilities and chord length distribution functions. Both characteristics are meaningful in order to quantify the influence of tablet compaction on its microstructure. The presented approach can be used to get better insight into the relationship between production parameters and microstructure characteristics based on 3D image data of Ibuprofen tablets manufactured under different conditions and elucidate key effects on the strength and solubility kinetics of the final formulation.
Towards many-class classification of materials based on their spectral fingerprints

Hyperspectral sensors are becoming cheaper and more available to the public. It is reasonable to assume that in the near future they will become more and more ubiquitous. This gives rise to many interesting applications, for example identification of pharmaceutical products and classification of food stuffs. Such applications require a precise models of the underlying classes, but hand-crafting these models is not feasible. In this paper, we propose to instead learn the model from the data using machine learning techniques. We investigate the use of two popular methods: support vector machines and random forest classifiers. In contrast to similar approaches, we restrict ourselves to linear support vector machines. Furthermore, we train the classifiers by solving the primal, instead of dual optimization problem. Our experiments on a large dataset show that the support vector machine approach is superior to random forest in classification accuracy as well as training time.
Tail asymptotics of the Brownian signature

The signature of a path \gamma is a sequence whose n-th term is the order-n iterated integrals of \gamma. It arises from solving multidimensional linear differential equations driven by \gamma. We are interested in relating the path properties of \gamma with its signature. If \gamma is C^{1}, then an elegant formula of Hambly and Lyons relates the length of \gamma to the tail asymptotics of the signature. We show an analogous formula for the multidimensional Brownian motion, with the quadratic variation playing a similar role to the length. In the proof, we study the hyperbolic development of Brownian motion and also obtain a new subadditive estimate for the asymptotic of signature, which may be of independent interest. As a corollary, we strengthen the existing uniqueness results for the signatures of Brownian motion.
Factors Influencing Supplementary Extension Service Provision by Agricultural Cooperatives in Kazungula District , Zambia

This study examined the factors influencing supplementary extension service provision by agricultural cooperatives in Kazungula District of Zambia. Six out of sixteen cooperatives were purposively selected and 142 respondents were proportionately random sampled from the selected cooperatives. Data was collected through a semi-structured questionnaire. Data was analysed using descriptive statistics and inferential statistics. The study found that public extension was still the major extension service source in the study area followed by agricultural cooperatives and non-governmental organisation. Study revealed that 57.7 percent of the respondents indicated that local agricultural cooperatives supplemented extension services. The study found that more than half of the respondents had negative attitudes toward agricultural cooperative services and at least half of the respondents showed low participation in agricultural cooperative activities. The binary logistic regression analysis shows that credit, share capital, cooperative office distance, maize area planted and maize yield were significantly influencing supplementary extension service provision by agricultural cooperatives in the study area. Therefore, as a recommendation, different support institutions should consider favourable financing options and capacity building of active and viable agricultural cooperatives.
Validating rule-based systems: a complete methodology

This paper describes a complete methodology for the validation of rule-based expert systems. The methodology is presented as a 5-step process that has three central themes: creation of a minimal set of test inputs that adequately cover the domain represented in the knowledge base; a Turing test-like methodology that evaluates the system's responses to the test inputs and compares them to the responses of human experts; and use of the validation results for system improvement. The development of a minimal set of test inputs takes into consideration various criteria, both user-defined and domain-specific. These criteria are used to reduce the potentially very large exhaustive set of test inputs to one that is practical. The Turing test-like evaluation methodology makes use of a panel of experts to both evaluate each set of test cases and compare the results with those of the expert system, as well as with those of the other experts in the validation panel. The hypothesis being presented is that much can be learned about the experts themselves by having them evaluate each other's responses to the same test inputs anonymously. Thus, by carefully scrutinizing the results of each expert in relation to the other experts, we are better able to judge an evaluator's expertise, and consequently, better determine the validity of an expert system.
Curvature-Adaptive Remeshing with Feature Preservation of Manifold Triangle Meshes with Boundary

In computer graphics meshes are a common representation of surfaces. These meshes are often irregular and contain more vertices than necessary to approximate a surface sufficiently. With remeshing a better mesh can be created for the underlying surface with respect to some quality criteria. In this project, manifold triangle meshes with boundaries and feature edges are considered; they are represented by a half-edge data structure for fast access of neighbouring elements of vertices, edges and triangles. The remeshing approach used is based on local mesh operations (edge-split, edge-flip, edge-collapse and vertex relocation) to adjust the density of elements and to improve their connectivity for a more regular mesh. An optional back-projection of vertices to the original surface can be used to keep the shape of the new mesh close to the reference mesh. With a sizing field based on an approximation of the curvature of the surface it is possible to adjust the sampling density to represent the final mesh with fewer triangles in areas of low curvature. The result of this approach is curvature-adaptive isotropic remeshing of good quality with feature preservation. The whole remeshing process is implemented in an interactive application that allows modifications of parameters. CR Categories: I.3. 5 [Computer Graphics]: Computational Geometry and Object Modeling
Learning Approach and Learning: Exploring a New Technological Learning System

This study furthers the understanding of the connections between learning approaches and learning. The research population embraced 44 males from the Jewish ultraorthodox community, who abide by distinct methods of study. One group follows the very didactic, linear and structured approach of a methodical and gradual order, while the second group follows the multi-directional approach that emphasizes global, abstract thought. The participants, who for ideological reasons hardly use computer technology, were exposed to a new technological learning system. The study employed the qualitative research method, with the research tools including textual analysis, observations and guided in-depth interviews. The findings show that those following the multi-directional method handled the device better from the didactic perspective. The question of how learning and teaching paradigms influence individual study is discussed.
Environmental Uncertainty, Comprehensive Performance Measurement Systems, Performance-Based Compensation, and Organizational Performance

This study explores firms' use of comprehensive performance measures and performance-based compensation in response to the increasingly uncertain competitive environment. Data from a sample of 84 Taiwanese high-tech manufacturing firms revealed an increased use of such systems among firms facing higher perceived environmental uncertainty. We also found performance-based pay to fully mediate the relationship between comprehensive performance measures and employee effort. Finally, employee effort is significantly and positively associated with organizational performance and fully explains the effect of performance-based compensation in increasing organizational performance.
Intrusion Detection Technique using DataMining Approach: Survey

Intrusion detection is an essential and important technique in research field. We propose many intrusion detection methods and systems in the literature. In this paper, we give a structured overview of various aspects of intrusion detection. Due to which a researcher can become quickly familiar with every aspect of intrusion detection. We give attacks normally identified by intrusion detection systems. We differentiate existing intrusion detection methods and systems based on the underlying computational methods used. We briefly describe and compare a large number of intrusion detection methods, techniques and systems. In addition, we also discuss tools which are used by network defenders and datasets.
Distributed representation of melodic contours

We introduce a new computational model for melodic contours—melody embeddings. It is based on the approach of distributional semantics where embeddings represent units as continuous vectors in a multi-dimensional space based on hypothesis that units with similar meaning are used in similar contexts. This paradigm is applied to melodic contours and their segments. Melodic contours are represented by vectors of the same dimensionality independent on their length and shape. We successfully evaluated the ability of the proposed model to measure the distance between melodic contours. The results of applying the model for a task of prominent words detection have not showed the improvement over traditional prosodic features. Nevertheless we assume the model to be very promising. The possible applications for the proposed unsupervised prosodic model include processing of speech of under-resourced languages, modelling prosodic variability for text-to-speech synthesis, recognition and classiﬁcation of prosodic events by means of deep-learning algorithms.
Engineering of Mature Human Induced Pluripotent Stem Cell‐Derived Cardiomyocytes Using Substrates with Multiscale Topography

Producing mature and functional cardiomyocytes (CMs) by in vitro differentiation of induced pluripotent stem cells (iPSCs) using only biochemical cues is challenging. To mimic the biophysical and biomechanical complexity of the native in vivo environment during the differentiation and maturation process, polydimethylsiloxane substrates with 3D topography at the micrometer and sub‐micrometer levels are developed and used as cell‐culture substrates. The results show that while cylindrical patterns on the substrates resembling mature CMs enhance the maturation of iPSC‐derived CMs, sub‐micrometer‐level topographical features derived by imprinting primary human CMs further accelerate both the differentiation and maturation processes. The resulting CMs exhibit a more‐mature phenotype than control groups—as confirmed by quantitative polymerase chain reaction, flow cytometry, and the magnitude of beating signals—and possess the shape and orientation of mature CMs in human myocardium—as revealed by fluorescence microscopy, Ca2+ flow direction, and mitochondrial distribution. The experiments, combined with a virtual cell model, show that the physico‐mechanical cues generated by these 3D‐patterned substrates improve the phenotype of the CMs via the reorganization of the cytoskeletal network and the regulation of chromatin conformation.
Effect of arbuscular mycorrhizal fungi on tomato yield and nutrient uptake under different fertilization levels

NEDOROST, L. , POKLUDA, R. : Eff ect of arbuscular mycorrhizal fungi on tomato yield and nutrient uptake under diff erent fertilization levels. Acta univ. agric. et silvic. Mendel. Brun. , 2012, LX, No. 8, pp. 181–186 Eff ect of the arbuscular mycorrhiza on tomato plants (Lycopersicon lycopersicum) in the pot experiment was studied. Three diff erent fertilization regimes (optimum – H1, stress a – H2, stress b - H3) and three diff erent mycorrhizal treatments (control – Ctrl, Glomus mossae – Gm, Glomus intraradices – Gi) were used. Economical parameter (yield), nutritional characteristic (vitamin C content, phosphates and minerals content, total antioxidant capacity), and level of root colonization were studied. The yield of the tomatoes was infl uenced by the basic dose of the fertilization, especially in the H2 and H3 treatment. The highest yield was in the H2 treatment in Gm (938 g per plant). The positive eff ect of the inoculation resulted in the increased content of the vitamin C. The highest signifi cant infl uence was observed in the H2 treatment (plants inoculated with Gi) with the average content of the vitamin C 289 mg.kg −1 . The average rate of the colonization was in the range from 39 % to 65 %.
1 Mapping Informal Settlements in the Middle East 2 Environment using an Object-Based Machine-3 Learning Approach 4

The identification of informal settlements in urban areas is an important step in 10 developing and implementing pro-poor urban policies. Understanding when, where and who 11 lives inside informal settlements is critical to efforts to improve their resilience. This study aims to 12 analyse the capability of machine-learning (ML) methods to map informal areas in Jeddah, Saudi 13 Arabia, using very-high-resolution (VHR) imagery and terrain data. Fourteen indicators of 14 settlement characteristics were derived and mapped using an object-based ML approach and VHR 15 imagery. These indicators were categorised according to three different spatial levels: environ, 16 settlement and object. The most useful indicators for prediction were found to be density and 17 texture measures, (with random forest (RF) relative importance measures of over 25% and 23% 18 respectively). The success of this approach was evaluated using a small, fully independent 19 validation dataset. Informal areas were mapped with an overall accuracy of 91%. Object-based ML 20 as a hybrid approach performed better (8%) than object-based image analysis alone due to its 21 ability to encompass all available geospatial levels. 22
Social influences on risky driving behaviours among young drivers in Oman

Young drivers represent approximately 20% of the Omani population, yet account for over one third of crash injuries and fatalities on Oman's roads. Internationally, research has demonstrated that social influences play an important role within young driver safety, however, there is little research examining this within Arab gulf countries. This study sought to explore young driver behaviour using Akers' social learning theory. A self-report survey was conducted by 1319 (72.9% male and 27.1% female) young drivers aged 17-25 years. A hierarchical regression model was used to investigate the contribution of social learning variables (norms and behaviour of significant others, personal attitudes towards risky behaviour, imitation of significant others, beliefs about the rewards and punishments offered by risky behaviour), socio-demographic characteristics (age and gender), driving experience (initial training, time driving and previous driving without supervision) and sensitivity to rewards and punishments upon the self-reported risky driving behaviours of young drivers. It was found that 39.6% of the young drivers reported that they have been involved in at least one crash since the issuance of their driving licence and they were considered ‘at fault’ in 60.7% of these crashes. The hierarchical multiple regression models revealed that socio-demographic characteristics and driving experience alone explained 14.2% of the variance in risky driving behaviour. By introducing social learning factors into the model a further 37.0% of variance was explained. Finally, 7.9% of the variance in risky behaviour could be explained by including individual sensitivity to rewards and punishments. These findings and the implications are discussed.
The practicability of the integrated probabilistic risk assessment (IPRA) approach for substances in food

Het RIVM heeft de IPRA-methode succesvol toegepast om de gezondheidsrisico's voor de mens van vijf stoffen in voeding te beschrijven. Deze methode is ontwikkeld om de risico's gedetailleerd te kunnen beschrijven als uit klassieke risicobeoordelingen blijkt dat er risico's zijn, of als risico's voor de gezondheid niet uitgesloten kunnen worden. Met de IPRA-methode is het mogelijk om aan te geven welk deel van de bevolking risico loopt nadat zij aan stoffen is blootgesteld en hoe ernstig de effecten op de gezondheid zijn. Op basis van deze informatie kan de overheid vervolgens doelgerichte acties ondernemen om de schadelijke gezondheidseffecten te voorkomen. Verwacht wordt dat de methode ook voor andere stoffen bruikbaar is. Dit blijkt uit onderzoek van het RIVM in samenwerking met Biometris en RIKILT, beide onderdeel van Wageningen Universiteit en Researchcentrum. Het onderzoek is uitgevoerd in opdracht van de Voedsel en Waren Autoriteit (VWA). Voor het onderzoek zijn de risico's beschreven van twee schimmeltoxinen (DON en T-2/HT-2), een zwaar metaal (cadmium), een bestrijdingsmiddelengroep (OPs) en een stof die in verhitte zetmeelproducten voorkomt (acrylamide). Met behulp van de IPRA-methode wordt de hoeveelheid van een stof die een populatie via voedsel binnenkrijgt vergeleken met de maximale dosis die veilig wordt geacht. Verschillen tussen personen en onzekerheden in de berekeningen zijn hierin meegenomen. De blootstellingen van deze vijf stoffen blijven volgens de methode onder de gestelde grenzen, en dus zijn de gezondheidrisico's verwaarloosbaar. Verder kan met de methode inzichtelijk worden gemaakt welke aanvullende gegevens verzameld kunnen worden om de risicobeoordeling te verbeteren. Hierdoor is doelgericht vervolgonderzoek mogelijk.