Miracle-dz/UniFAR-FTUs huggingface dataset:
Vitamin D

Vitamin D has received a lot of attention recently as a result of a meteoric rise in the number of publications showing that vitamin D plays a crucial role in a plethora of physiological functions and associating vitamin D deficiency with many acute and chronic illnesses including disorders of calcium metabolism, autoimmune diseases, some cancers, type 2 diabetes mellitus, infectious diseases and cardiovascular disease. The recent data on vitamin D from experimental, ecological, case-control, retrospective and prospective observational studies, as well as smaller intervention studies, are significant and confirm the sunshine vitamin’s essential role in a variety of physiological and preventative functions. The results of these studies justify the recommendation to improve the general vitamin D status in children and adults by means of a healthy approach to sunlight exposure, consumption of foods containing vitamin D and supplementation with vitamin D preparations. In general, closer attention should therefore be paid to vitamin D deficiency in medical and pharmaceutical practice than has been the case hitherto.
Friend Recommendation for Location-Based Mobile Social Networks

Along with the rapid growth of Internet, many social websites are founded, and gradually begin to influence the people's life. Such as Facebook, the social network site provides the personalized recommendation system with friends-of-friends method to recommend new friends to users. The intuition is derived from the idea that it is more probable a person will know a friend of their friends rather than a random person. However, this approach does not consider any insights into human cognitive components such as social interactions. Thus, we propose a brand-new friend recommendation approach. The main concept is to recommend friends who have the similar interests or another thing with self to users. Besides utilizing the information on social networks, such as interests, the concept of real-life location and dwell time is further added in our approach. In this paper, we develop two comparison methods to provide quality friend recommendation. First method combines the existing landmark and user's dwell time at certain landmark to make the Voronoi diagram, and analyzes location similarity between users. Second methods is to analyze the interest lists from each social network accounts by using pattern matching and finding longest common subsequence. Through this two comparison methods, we assess the acceptable degree between two, and successfully implement the friend recommendation system.
Molecular MRI of Atherosclerosis

Despite advances in prevention, risk assessment and treatment, coronary artery disease (CAD) remains the leading cause of morbidity and mortality in Western countries. The lion’s share is due to acute coronary syndromes (ACS), which are predominantly triggered by plaque rupture or erosion and subsequent coronary thrombosis. As the majority of vulnerable plaques does not cause a significant stenosis, due to expansive remodeling, and are rather defined by their composition and biological activity, detection of vulnerable plaques with x-ray angiography has shown little success. Non-invasive vulnerable plaque detection by identifying biological features that have been associated with plaque progression, destabilization and rupture may therefore be more appropriate and may allow earlier detection, more aggressive treatment and monitoring of treatment response. MR molecular imaging with target specific molecular probes has shown great promise for the noninvasive in vivo visualization of biological processes at the molecular and cellular level in animals and humans. Compared to other imaging modalities; MRI can provide excellent spatial resolution; high soft tissue contrast and has the ability to simultaneously image anatomy; function as well as biological tissue composition and activity.
Bayesian model selection in complex linear systems, as illustrated in genetic association studies

Motivated by examples from genetic association studies, this article considers the model selection problem in a general complex linear model system and in a Bayesian framework. We discuss formulating model selection problems and incorporating context‐dependent a priori information through different levels of prior specifications. We also derive analytic Bayes factors and their approximations to facilitate model selection and discuss their theoretical and computational properties. We demonstrate our Bayesian approach based on an implemented Markov Chain Monte Carlo (MCMC) algorithm in simulations and a real data application of mapping tissue‐specific eQTLs. Our novel results on Bayes factors provide a general framework to perform efficient model comparisons in complex linear model systems.
Impacto de modelos alternativos de uso de rebocadores portuários no aumento da capacidade de navios

A presente dissertacao tem por finalidade apresentar uma metodologia alternativa e inovadora de utilizacao de rebocadores portuarios em assistencia na manobra de navios, com a finalidade precipua de reduzir a velocidade de trânsito de navios no canal de acesso aos portos e terminais. Esta reducao de velocidade apresenta, por consequencia, um efeito de reducao no afundamento da embarcacao pela acao de ondas e devido ao efeito Squat, aumentando-se o parâmetro de navegacao denominado folga abaixo da quilha. Finalmente, o proposito final do trabalho e converter este incremento de folga abaixo da quilha em aumento de calado, proporcionando ao armador do navio um aumento de carga a ser transportada e, em alguns casos, aumento de receita, dependendo do valor de frete pactuado (dentro de um contrato de afretamento) entre armador e afretador, e valores de afretamento dos rebocadores. O metodo proposto podera ser utilizado como instrumento de apoio a tomada de decisao por diretores e gestores da area comercial de uma empresa de navegacao ou, uma empresa administradora de um porto ou terminal, que pretendam eliminar limitacoes portuarias utilizando-se de rebocadores portuarios.
Enhanced Accuracy of Force Application for AFM Nanomanipulation Using Nonlinear Calibration of Optical Levers

The atomic force microscope (AFM) has been widely used as a nano-effector with a function of force sensing to detect interaction forces between an AFM tip and a sample, thereby controlling the process of the nanomanipulation. However, both the extent and accuracy of force application are significantly limited by the nonlinearity of the commonly used optical lever with a nonlinear position-sensitive detector (PSD). In order to compensate the nonlinearity of the optical lever, a nonlinear calibration method is presented. This method applies the nonlinear curve fit to a full-range position-voltage response of the photodiode, obtaining a continuous function of its voltage-related sensitivity. Thus, interaction forces can be defined as integrals of this sensitivity function between any two responses of photodiode voltage outputs, instead of rough transformation with a single conversion factor. The lateral position-voltage response of the photodiode, a universally acknowledged puzzle, was directly characterized by an accurately calibrated force sensor composed of a tippless piezoresistive microcantilever and corresponding electronics, regardless of any knowledge of the cantilevers and laser measuring system. Experiments using a rectangular cantilever (normal spring constant 0.24 N/m) demonstrated that the proposed nonlinear calibration method restrained the sensitivity error of normal position-voltage responses to 3.6% and extended the force application range.
Information modeling for intrusion report aggregation

The paper describes the SCYLLARUS approach to fusing reports from multiple intrusion detection systems (ID-Ses) to provide an overall approach to intrusion situation awareness. The overall view provided by SCYLLARUS centers around the site's security goals, aggregating large numbers of individual IDS reports based on their impact. The overall view reduces information overload by aggregating multiple IDS reports in a rep-down view; and by reducing false positives by weighing evidence provided by multiple ID-Ses and other information sources. Unlike previous efforts in this area, SCYLLARUS is centered around its intrusion reference model (IRM). The SCYLLARUS IRM contains both dynamic and static (configuration) information. A network entity/relationship database (NERD), providing information about the site's hardware and software; a security goal database, describing the site's objectives and security policy; and an event dictionary, describing important events, both intrusions and benign; comprise the static portion of the IRM. The set of IDS reports; the events SCYLLARUS hypothesizes to explain them; and the resulting judgment of the state of site security goals comprise the dynamic part of the IRM.
A robust and reliable non-invasive test for stress responsivity in mice

Stress and an altered stress response have been associated with many multifactorial diseases, such as psychiatric disorders or neurodegenerative diseases. As currently mouse mutants for each single gene are generated and phenotyped in a large-scale manner, it seems advisable also to test these mutants for alterations in their stress responses. Here we present the determinants of a robust and reliable non-invasive test for stress-responsivity in mice. Stress is applied through restraining the mice in tubes and recording behavior in the Open Field 20 min after cessation of the stress. Two hours, but not 15 or 50 min of restraint lead to a robust and reproducible increase in distance traveled and number of rearings during the first 5 min in the Open Field in C57BL/6 mice. This behavioral response is blocked by the corticosterone synthesis inhibitor metyrapone, but not by RU486 treatment, indicating that it depends on corticosteroid secretion, but is not mediated via the glucocorticoid receptor type II. We assumed that with a stress duration of 15 min one could detect hyper-responsivity, and with a stress duration of 2 h hypo-responsivity in mutant mouse lines. This was validated with two mutant lines known to show opposing effects on corticosterone secretion after stress exposure, corticotropin-releasing hormone (CRH) over-expressing mice and CRH receptor 1 knockout (KO) mice. Both lines showed the expected phenotype, i.e., increased stress responsivity in the CRH over-expressing mouse line (after 15 min restraint stress) and decreased stress responsivity in the CRHR1-KO mouse line (after 2 h of restraint stress). It is possible to repeat the acute stress test several times without the stressed animal adapting to it, and the behavioral response can be robustly evoked at different ages, in both sexes and in different mouse strains. Thus, locomotor and rearing behavior in the Open Field after an acute stress challenge can be used as reliable, non-invasive indicators of stress responsivity and corticosterone secretion in mice.
Journal of Digital Information Management

Bioinformatics is as a bridge between life science and computer science: computer algorithms are needed to face complexity of biological processes. Bioinformatics applications manage complex biological data accessing distributed heterogeneous databases, and require large computing power. After introducing bioinformatics requirements, we present the architecture of PROTEUS, a Grid-based Problem Solving Environment that integrates ontology and workflow approaches to enhance composition and execution of bioinformatics application on the Grid. A first distributed implementation of PROTEUS on Globus is also described.
Human arm impedance: Characterization and modeling in 3D space

Humans perform a wide range of skillful and dexterous motion by adjusting the dynamic characteristics of their musculoskeletal system during motion. This capability is based on the non-linear characteristics of the muscles and the motor control architecture that can control motion and exerted force independently. Mechanical impedance (i.e. stiffness, viscosity and inertia) constitutes the most solid characteristic for describing the dynamic behavior of human movements. This paper presents a method for estimating upper limb impedance characteristics in the three-dimensional (3D) space, covering a wide range of the arm workspace. While subjects maintained postures, a seven-degrees-of-freedom (7-DoFs) robot arm was used to produce small displacements of subjects' hands along the three Cartesian axes. The end-point dynamic behavior was modeled using a linear second-order system and the impedance characteristics in the 3D space were identified using the measured forces and motion profiles. Experimental results were confirmed with two subjects.
Metal Oxide Semi-Conductor Gas Sensors in Environmental Monitoring

Metal oxide semiconductor gas sensors are utilised in a variety of different roles and industries. They are relatively inexpensive compared to other sensing technologies, robust, lightweight, long lasting and benefit from high material sensitivity and quick response times. They have been used extensively to measure and monitor trace amounts of environmentally important gases such as carbon monoxide and nitrogen dioxide. In this review the nature of the gas response and how it is fundamentally linked to surface structure is explored. Synthetic routes to metal oxide semiconductor gas sensors are also discussed and related to their affect on surface structure. An overview of important contributions and recent advances are discussed for the use of metal oxide semiconductor sensors for the detection of a variety of gases—CO, NOx, NH3 and the particularly challenging case of CO2. Finally a description of recent advances in work completed at University College London is presented including the use of selective zeolites layers, new perovskite type materials and an innovative chemical vapour deposition approach to film deposition.
International Journal of Advanced Robotic Systems Efficient Topological Localization Using Global and Local Feature Matching Regular Paper

which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. Abstract We present an efficient vision‐based global topological localization approach in which different image features are used in a coarse‐to‐fine matching framework. Orientation Adjacency Coherence Histogram (OACH), a novel image feature, is proposed to improve the coarse localization. The coarse localization results are taken as inputs for the fine localization which is carried out by matching Harris‐ Laplace interest points characterized by the SIFT descriptor. The computation of OACHs and interest points is efficient due to the fact that these features are computed in an integrated process. The matching of local features is improved by using approximate nearest neighbor searching technique. We have implemented and tested the localization system in real environments. The experimental results demonstrate that our approach is efficient and reliable in both indoor and outdoor environments. This work has also been compared with previous works. The comparison results show that our approach has better performance with higher correct ratio and lower computational complexity.
A communication architecture for power routing in the smart grid

One of the main benefits of the smart grid will be the introduction of Distributed Energy Resources (DERs) into the electricity grid at large scale. These DERs will be able to supply areas with electricity when isolated from the main power grid due to failure conditions or system/equipment failures. Although the integration of DER into the power grid makes the energy supply more reliable and reduces its cost, it creates new issues for distributed network operators (DNOs). While in traditional power grid the electricity usually flows from the central power stations to the consumers, in a modern power grid incremented with DER, the electricity follows in two directions as these new sources of energy are introduced at lower voltages. To introduce DER technology, DNOs will be faced with the challenge of making their distribution power networks more flexible and dynamic. Whilst in the past distribution networks were considered as static with no major control operation or reconfiguration requirements, in the smart grid, distribution networks will be in constant change according the direction and amount of power flow. Power routing is an emerging concept that aims at making distribution networks more flexible and dynamic which will help address the technical challenges related to DER. Power routing is predicated on the information availability and coordination which requires a robust and scalable communication. In this paper we propose layered communication architecture that facilitates the implementation of power routing in distribution networks.
A Dictionary Learning Method with Total Generalized Variation for MRI Reconstruction

Reconstructing images from their noisy and incomplete measurements is always a challenge especially for medical MR image with important details and features. This work proposes a novel dictionary learning model that integrates two sparse regularization methods: the total generalized variation (TGV) approach and adaptive dictionary learning (DL). In the proposed method, the TGV selectively regularizes different image regions at different levels to avoid oil painting artifacts largely. At the same time, the dictionary learning adaptively represents the image features sparsely and effectively recovers details of images. The proposed model is solved by variable splitting technique and the alternating direction method of multiplier. Extensive simulation experimental results demonstrate that the proposed method consistently recovers MR images efficiently and outperforms the current state-of-the-art approaches in terms of higher PSNR and lower HFEN values.
Genetics and Neuroscience in Dyslexia: Perspectives for Education and Remediation.

Our understanding of the causes of a develop- mental disorder like dyslexia has received recent input from both neuroscience and genetics. The discovery of 4 candidate genes for dyslexia and the identifi cation of neuronal networks engaged when children read and spell are the basis for introducing this knowledge into education. However, the input from educational practitioners as well as empirical knowledge from research on learning also contribute signifi - cantly to our understanding of how children acquire the basic skills for learning to read and spell. It is imperative to merge the knowledge acquired from research in the fi elds of neuro- science, genetics, and empirical education, as well as to understand how the learning brain and instruction interact. Doing so can be seen as a major step in attaining an optimal approach for teaching, reading, and spelling and for fi nding the best suited and most effective treatment concepts for dyslexic children and adolescents.
A comparison of randomized and evolutionary approaches for optimizing base station site selection

It is increasingly important to optimally select base stations in the design of cellular networks, as customers demand cheaper and better wireless services. From a set of potential site locations, a subset needs to be selected which optimizes two critical objectives: service coverage and financial cost. As this is an NP-hard optimization problem, heuristic approaches are required for problems of practical size. Our approach consists of two phases which act upon a set of candidate site permutations at each generation. Firstly, a sequential greedy algorithm is designed to commission sites from an ordering of candidate sites, subject to satisfying an alterable constraint. Secondly, an evolutionary optimization technique, which is tested against a randomized approach, is used to search for orderings of candidate sites which optimize multiple objectives. The two-phase strategy is vigorously tested and the results delineated.
3-D Geometry Compression using Multiscale Plane Based Representation and Zerotree Based Coding

In this paper, we present a novel geometry compression scheme for compactly representing 3-D sampled data. The proposed framework is based on the octree structured multiscale geometry representation, where local surface is expressed by multiscale plane descriptions. To reduce planar redundancy between different scale plane approximations in the multiscale pyramid, the multiscale plane pyramid is decomposed and the resulting refinement pyramid is encoded using the zerotree based coding method. The decomposition captures the geometry innovation to refine coarse geometry. Moreover, the zerotree based coding method offers the ordered bitstream according to the contribution for reconstructing the geometry innovation. Therefore, we demonstrate that the proposed algorithm compactly represents the 3-D point samples yielding progressive refinement of the surface geometry.
Ontology-based Competence Management for Healthcare Training Planning: A Case Study

With the increased pressure towards economic efficiency, hospitals and other healthcare institutions need to reengineer their internal organization and processes. This challenges human resources development with increased efficiency of training in general. We have developed a competence management concept for training planning at a big German hospital with a special focus on critically analyzing the suitability of state-of-the-art ontology- based approaches and their operationalization into management processes for the area of nursery. Experiences from the case study show the general feasibility, but also crucial issues summarized in this paper.
Perceção, expressão e valorização das emoções das crianças na educação pré-escolar

A educacao emocional e fundamental para a adaptacao pessoal e social do individuo. Assim sendo, buscou-se por meio desta pesquisa adaptar a prova para avaliar a capacidade de perceber, expressar e valorizar emocoes das criancas portuguesas na educacao pre-escolar. Apos equivalencia semântica, operacional, conceptual e de itens, a prova foi respondida por 374 criancas. Os dados obtidos foram contrastados com criterios externos avaliados pelas representacoes das 26 educadoras de infância. Verificou-se maior numero de acertos em relacao a alegria e a tristeza na subescala percecao e expressao das emocoes basicas com a escola privada a apresentar maior rendimento; que a percecao e valorizacao das emocoes basicas aumenta em funcao da idade; que o genero feminino apresenta maior performance na subescala percecao e valorizacao das emocoes basicas; e relacoes significativas positivas entre as subescalas em analise e os criterios externos - adaptacao, controlo, rendimento e aceitacao, e correlacoes significativas negativas entre as subescalas e a conflitividade. A prova, embora em fase desenvolvimental, contribui para medir a adaptacao pessoal e social das criancas portuguesas na etapa pre-escolar Palavras-chave: Percecao Emocional. Valorizacao Emocional. Avaliacao da Percecao Emocional.