Miracle-dz/UniFAR-FTUs huggingface dataset:
Allelic heterogeneity and more detailed analyses of known loci explain additional phenotypic variation and reveal complex patterns of association

The identification of multiple signals at individual loci could explain additional phenotypic variance (‘missing heritability’) of common traits, and help identify causal genes. We examined gene expression levels as a model trait because of the large number of strong genetic effects acting in cis. Using expression profiles from 613 individuals, we performed genome-wide single nucleotide polymorphism (SNP) analyses to identify cis-expression quantitative trait loci (eQTLs), and conditional analysis to identify second signals. We examined patterns of association when accounting for multiple SNPs at a locus and when including additional SNPs from the 1000 Genomes Project. We identified 1298 cis-eQTLs at an approximate false discovery rate 0.01, of which 118 (9%) showed evidence of a second independent signal. For this subset of 118 traits, accounting for two signals resulted in an average 31% increase in phenotypic variance explained (Wilcoxon P< 0.0001). The association of SNPs with cis gene expression could increase, stay similar or decrease in significance when accounting for linkage disequilibrium with second signals at the same locus. Pairs of SNPs increasing in significance tended to have gene expression increasing alleles on opposite haplotypes, whereas pairs of SNPs decreasing in significance tended to have gene expression increasing alleles on the same haplotypes. Adding data from the 1000 Genomes Project showed that apparently independent signals could be potentially explained by a single association signal. Our results show that accounting for multiple variants at a locus will increase the variance explained in a substantial fraction of loci, but that allelic heterogeneity will be difficult to define without resequencing loci and functional work.
Horizontal sedimentation differences in a eutrophic Swiss lake

Settling fluxes measured by means of sediment traps were 887 g dry wt m-2 yr- I, 113 g POC m-2 yr-I, and 2.6 g PP m-2 yr-I in 1982-1983 at a central station in eutrophic Lake Hallwil, Switzerland. Nearshore settling rates were higher by a factor of 1.4-3.4. Since particulate organic carbon (POC), particulate phosphorus (PP), and biomass concentration in the lake water showed vertical rather than horizontal differences, this result was attributed to permanent bottom sediment resuspension and redeposition in the littoral zone. Horizontal sediment transport (sediment focusing) and sediment resuspension in the profundal zone in winter, when wind and turbulence are increased, accounted for only about 20% of the sedimentation rates. Because 70-80% of the total sedimentation for the year occurred during summer, such processes are of minor importance in Lake Hallwil, although a “nepheloid” layer with increased POC and PP concentrations 5-8 m above the bottom was present. It is stressed that the mechanisms of sediment transport must be known to permit interpretation of trap results and to understand lake metabolism.
Monoclonal antibody Zt/g4 targeting RON receptor tyrosine kinase enhances chemosensitivity of bladder cancer cells to Epirubicin by promoting G1/S arrest and apoptosis

Epirubicin (EPI) is one of the most used intravesical chemotherapy agents after transurethral resection to non-muscle invasive bladder tumors (NMIBC) to prevent cancer recurrence and progression. However, even after resection of bladder tumors and intravesical chemotherapy, half of them will recur and progress. RON is a membrane tyrosine kinase receptor usually overexpressed in bladder cancer cells and associated with poor pathological features. This study aims to investigate the effects of anti-RON monoclonal antibody Zt/g4 on the chemosensitivity of bladder cells to EPI. After Zt/g4 treatment, cell cytotoxicity was significantly increased and cell invasion was markedly suppressed in EPI-treated bladder cancer cells. Further investigation indicated that combing Zt/g4 with EPI promoted cell G1/S-phase arrest and apoptosis, which are the potential mechanisms that RON signaling inhibition enhances chemosensitivity of EPI. Thus, combing antibody-based RON targeted therapy enhances the therapeutic effects of intravesical chemotherapy, which provides new strategy for further improvement of NMIBC patient outcomes.
Modular and Highly Configurable Computation Mobility Framework for Internet of Things

Computation offloading or cyber foraging is a key capability required to achieve effective resource utilization in mobile cloud computing. It enables the dynamic offloading of computations to either neighboring mobile nodes or remote cloudbased servers, retrieve results from the offloaded computations, and thereafter continue execution of the mobile business logic. A number of computational mobility solutions have emerged recently for mobile cloud computing involving smart phones and tablets. However, these solutions incur limitations in the context of Internet of Things (IoT) due to the significant heterogeneity illustrated by the range of objects involved in IoT and the fact that existing solutions tend to be tightly coupled to their underlying frameworks, which makes it hard to seamlessly adapt these solutions to the IoT scenarios. To address these concerns, this paper makes three contributions. First, it presents a novel modular and highly configurable framework for providing seamless computational mobility in the IoT realm. Second, it provides implementation details for key capabilities of this framework. Third, it provides qualitative evaluation of the framework’s capabilities. Keywords—Mobile cloud computing, IoT, software engineering, modular and configurable framework.
Genetic algorithm for feature selection of MR brain images using wavelet co-occurence

The selection of features has a considerable impact on the success or failure of classification process. Feature selection refers to the procedure of selecting a subset of informative attributes to build models describing data. The main purpose of feature selection is to reduce the number of features used in classification while maintaining high classification accuracy. A large number of algorithms have been proposed for feature subset selection. Here we compare classical sequential methods with the genetic approach in terms of the number of features, classification accuracy and reduction rate. Genetic Algorithm (GA) achieves an acceptable classification accuracy with only five of the available 44 features. The optimal feature such as mean of contrast, mean of homogeneity, mean of sum average, mean of sum variance and range of autocorrelation provide best classification performance. Similar classification performance is obtained with SFFS and SFBS but with larger feature set.
Bone marrow stromal cells enhance differentiation of cocultured neurosphere cells and promote regeneration of injured spinal cord

Transplantation of bone marrow stromal cells (MSCs) has been regarded as a potential approach for promoting nerve regeneration. In the present study, we investigated the influence of MSCs on spinal cord neurosphere cells in vitro and on the regeneration of injured spinal cord in vivo by grafting. MSCs from adult rats were cocultured with fetal spinal cord‐derived neurosphere cells by either cell mixing or making monolayered‐feeder cultures. In the mixed cell cultures, neuroshpere cells were stimulated to develop extensive processes. In the monolayered‐feeder cultures, numerous processes from neurosphere cells appeared to be attracted to MSCs. In an in vivo experiment, grafted MSCs promoted the regeneration of injured spinal cord by enhancing tissue repair of the lesion, leaving apparently smaller cavities than in controls. Although the number of grafted MSCs gradually decreased, some treated animals showed remarkable functional recovery. These results suggest that MSCs might have profound effects on the differentiation of neurosphere cells and be able to promote regeneration of the spinal cord by means of grafting. © 2003 Wiley‐Liss, Inc.
MOBILIDADE ACADÊMICA INTERNACIONAL NO ENSINO TÉCNICO: A PERSPECTIVA DE DOCENTES E GESTORES DE INSTITUIÇÕES PÚBLICAS

Esta pesquisa aborda o processo de mobilidade academica internacional no ensino tecnico, analisando as perspectivas de professores e gestores das instituicoes publicas pesquisadas. Esta estruturada a partir de um estudo documental e pesquisa de campo, com objetivo exploratorio e abordagem qualitativa, realizado em duas instituicoes publicas de ensino tecnico na Regiao Metropolitana do Vale do Paraiba e Litoral Norte, nas cidades de Lorena e Cachoeira Paulista. Foram realizadas entrevistas com os docentes e gestores. A amostra compoe-se de 10 participantes, sendo sete professores e tres gestores. Os dados foram analisados por meio de tecnicas qualitativas do metodo de analise de conteudo, com o auxilio do software IRaMuTeQ (Interface de R pour les Analyses Multimensionnelles de Textes et de Questionnaries). Docentes e gestores veem o intercâmbio como uma forma de enriquecimento cultural e aumento da visao de mundo do aluno, alem de acreditarem que ele gera uma imagem institucional positiva, destacando a importância do programa como auxiliar no controle da evasao escolar. Pode-se concluir que a experiencia de intercâmbio proporcionada pelas instituicoes deve ser aprimorada, pois a mobilidade estudantil contribui para o desenvolvimento global do aluno e, consequentemente, para o desenvolvimento regional, a medida que colabora para a construcao de uma sociedade mais critica e participante de decisoes em seu entorno.
Studying the Effects of SNS Users ’ Alternative Privacy Strategies With an Activity Tracking Tool

We demonstrate how our methodological approach helps to understand social network sites (hereinafter SNS) users‘ alternative privacy strategies. To this end, we refer to one of our recent empirical studies and describe the effects of users’ avoidance of provided privacy controls. Many studies document that users rarely use Facebook’s friendlist feature because they consider creating, maintaining and applying lists as too burdensome and, thus, prefer to employ alternative strategies, such as withholding information. Based on our empirical results, we suggest to focus on the improvement of tools which do not require much a priori rule setting and could be easily adjusted at the moment of sharing.
Activation of Glycine and Extrasynaptic GABAA Receptors by Taurine on the Substantia Gelatinosa Neurons of the Trigeminal Subnucleus Caudalis

The substantia gelatinosa (SG) of the trigeminal subnucleus caudalis (Vc) has been known for the processing and transmission of orofacial nociceptive information. Taurine, one of the most plentiful free amino-acids in humans, has proved to be involved in pain modulation. In this study, using whole-cell patch clamp technique, we investigated the direct membrane effects of taurine and the action mechanism behind taurine-mediated responses on the SG neurons of the Vc. Taurine showed non-desensitizing and repeatable membrane depolarizations and inward currents which remained in the presence of amino-acid receptors blocking cocktail (AARBC) with tetrodotoxin, indicating that taurine acts directly on the postsynaptic SG neurons. Further, application of taurine at different doses (10 μM to 3 mM) showed a concentration dependent depolarizations and inward currents with the EC50 of 84.3 μM and 723 μM, respectively. Taurine-mediated responses were partially blocked by picrotoxin (50 μM) and almost completely blocked by strychnine (2 μM), suggesting that taurine-mediated responses are via glycine receptor (GlyR) activation. In addition, taurine (1 mM) activated extrasynaptic GABAA receptor (GABAAR)-mediated currents. Taken together, our results indicate that taurine can be a target molecule for orofacial pain modulation through the activation of GlyRs and/or extrasynaptic GABAARs on the SG neurons.
Improving the Odds in Discriminating "Drug-like" from "Non Drug-like" Compounds

We have used a feed-forward neural network technique to classify chemical compounds into potentially "drug-like" and "non drug-like" candidates. The neural network was trained to distinguish between a set of "drug-like" and "non drug-like" chemical compounds taken from the MACCS-II Drug Data Report (MDDR) and the Available Chemicals Directory (ACD). The 2D atom types (of the full atomic representation) were assigned and applied as descriptors to encode numerically each compound. There are four main conclusions: First the method performs well, correctly assigning 88% of the compounds in both MDDR and ACD. Improved discrimination was achieved by a more critical selection of training sets. Second, the method gives much better prediction performance than the widely used "Rule of Five", which accepts as many as 74% of the ACD compounds but only 66% of those in MDDR, resulting in a correlation coefficient which is effectively zero, compared to a value of 0.63 for the neural network prediction. Third, based on a standard Tanimoto similarity search the selection of drug-like compounds in the evaluation set is not biased toward compounds similar to those in the training set. Fourth, the trained neural network was applied to evaluate the drug-likeness of 136 GABA uptake inhibitors with impressive results. The implications of applying a neural network to characterize chemical compounds are discussed.
Diffusion of O2 and N2 through thin and thick SWNT networks

We report the electrical responses of thin and thick single-walled carbon nanotube (SWNT) networks to N2 and O2 adsorption. In the surface desorbed state exposure to N2 and O2 provide an increase in conductance of thin and thick SWNT networks. The increase in conductance of both thin and thick networks is of a greater magnitude during O2 exposure rather than N2 exposure. Thin networks exhibit a greater response to both O2 and N2 rather than thick networks. This is likely a result of the increased semiconducting nature of thin SWNT networks.
Validation of questionnaire and bronchial hyperresponsiveness against respiratory physician assessment in the diagnosis of asthma.

BACKGROUND The Tasmanian Asthma survey (TAS) and the International Study of Asthma and Allergies in Childhood (ISAAC) have used questionnaires to measure the prevalence of asthma in adults and children. We have investigated the validity of these questionnaires by comparing response to questionnaire with a physician assessment of asthma status in the past 12 months. METHODS Ninety-three adults were given the TAS questionnaire to complete and 361 children were given the ISAAC questionnaire. Ninety-one adults and 168 children completed bronchial challenge with hypertonic saline. A consultation with a respiratory physician blinded to the results of the questionnaire and bronchial challenge was given to all subjects. RESULTS In both adults and children, questionnaires showed high agreement with respiratory physician diagnosis with respect to asthma symptoms in the past 12 months. For the TAS questionnaire the positive and negative predictive values (95% confidence limits) for physician diagnosis for adults were 0.89 (0.68-0.98) and 0.94 (0. 86-0.98) respectively. The instrument was also sensitive 0.80 (0. 58-0.93) and highly specific 0.97 (0.90-0.99). For the ISAAC questionnaire the positive and negative predictive vales for physician diagnosis of asthma in children were 0.61 (0.50-0.71) and 0.94 (0.88-0.98) respectively. Sensitivity and specificity were 0.85 (0.73-0.93) and 0.81 (0.76-0.86) respectively. Compared to the physician diagnosis, the sensitivity of bronchial hyperresponsiveness (BHR) for asthma was low for adults 0.39 (0.21-0. 61) and children 0.54 (0.48-0.67) as were the positive predictive values: 0.55 (0.31-0.79) for adults and 0.64 (0.449-0.77) for children. A definition of asthma requiring both a positive questionnaire response and BHR was highly specific but not sensitive for adults 0.37 (0.20-0.59) or children 0.47 (0.35-0.60). CONCLUSIONS Both the TAS and ISAAC questionnaires are valid instruments for the determination of asthma symptoms in the past 12 months.
Joint learning of similarity graph and image classifier from partial labels

Learning of a binary classifier from partial labels is a fundamental and important task in image classification. Leveraging on recent advance in graph signal processing (GSP), a recent work poses classifier learning as a graph-signal restoration problem from partial observations, where the ill-posed problem is regularized using a graph-signal smoothness prior. In this paper, we extend this work by using the same smoothness prior to refine the underlying similarity graph also, so that the same graph-signal projected on the modified graph will be even smoother. Specifically, assuming an edge weight connecting two vertices i and j is computed as the exponential kernel of the weighted sum of feature function differences at the two vertices, we find locally “optimal” feature weights via iterative Newton's method. We show that the conditioning of the Hessian matrix reveals redundancy in the feature functions, which thus can be eliminated for improved computation efficiency. Experimental results show that our joint optimization of the classifier graph-signal and the underlying graph has better classification performance then the previous work and spectral clustering.
Multifractal structure of Bernoulli convolutions

Abstract Let νpλ be the distribution of the random series $\sum_{n=1}^\infty i_n \lam^n$, where in is a sequence of i.i. d. random variables taking the values 0, 1 with probabilities p, 1 − p. These measures are the well-known (biased) Bernoulli convolutions. In this paper we study the multifractal spectrum of νpλ for typical λ. Namely, we investigate the size of the sets \begin{linenomath} \[ \Delta_{\lam, p}(\alpha) = \left\{x\in\R: \lim_{r\searrow 0} \frac{\log \nula^p(B(x, r))}{\log r} =\alpha\right\}\! \]\end{linenomath} Our main results highlight the fact that for almost all, and in some cases all, λ in an appropriate range, Δλ, p(α) is nonempty and, moreover, has positive Hausdorff dimension, for many values of α. This happens even in parameter regions for which νpλ is typically absolutely continuous.
CBUG: A Quadratically Competitive Mobile Robot Navigation Algorithm

This paper is concerned with online navigation of a size D mobile robot in an unknown planar environment. A formal means for assessing algorithms for online tasks is competitiveness. For the navigation task, competitiveness measures the algorithm's path length relative to the optimal offline path length. While competitiveness usually means constant relative performance, it is measured in this paper in terms of a quadratic relationship between online performance and optimal offline solution. An online navigation algorithm for a size D robot called CBUG is described. The competitiveness of CBUG is analyzed and shown to be quadratic in the length of the shortest offline path. Moreover, it is shown that, in general, quadratic competitiveness is the best achievable performance over all online navigation algorithms. Thus, up to constants, CBUG achieves optimal competitiveness. The algorithm is improved with some practical speedups, and the usefulness of its competitiveness in terms of path stability is illustrated in office-like environments.
Determining Expert Profiles (With an Application to Expert Finding)

The profile of an individual is a record of the types and areas of skills of that individual ("topical profile") plus a description of her collaboration network ("social profile"). In this paper we define and formalize the task of automatically determining an expert profile of a person from a heterogeneous corpus made up of a large organization's intranet. We propose multiple models for addressing the topical profiling task. Our main methods build on ideas from information retrieval, while refinements bring in filtering (allowing an area into a person's profile only if she is among the top ranking experts in the area). An evaluation based on the W3C-corpus made available by TREC, shows significant improvements of the refined methods over the baseline. We apply our profiling algorithms to significantly enhance the performance of a state-ofthe-art expert finding algorithm and to help users of an operational expert search system find the person they would contact, given a specific problem, topic or information need. Finally, we address the task of determining a social profile for a given person, using graph-based methods.
Design of a dynamic frequency compensation low dropout voltage regulator with buffer impedance attenuation

This paper presents a low-drop (LDO) linear regulator with buffer impedance attenuation (BIA) for frequency compensation. This novel proposed LDO take advantage of the dynamically-biased shunt feedback in the buffer stage, which could lower its output resistance for driving the pass device to achieve fast response. Implemented in 0. 35μm CMOS process, the LDO dissipates 184μA quiescent current and is able to deliver up to 100mA load current. With a 2. 3μF output capacitance, the maximum transient-output variation is 25mV with full-load step change of 100mA. The proposed circuit will find application in the battery-powered portable devices.
Macro-based hardware compilation of Java/sup TM/ bytecodes into a dynamic reconfigurable computing system

This paper presents a new approach to synthesize to reconfigurable hardware (HW) user-specified regions of a program, under the assumption of "virtual HW" support. The automation of this approach is supported by a compiler front-end and by an HW compiler under development. The front-end starts from the Java bytecodes and, therefore, supports any language that can be compiled to the JVM (Java Virtual Machine) model. It extracts from the bytecodes all the dependencies inside and between basic blocks. This information is stored in representation graphs more suitable to efficiently exploit the existent parallelism in the program than those typically used in high-level synthesis. From the intermediate representations the HW compiler exploits the temporal partitions at the behavior level, resolves memory access conflicts, and generates the VHDL descriptions at register-transfer level that will be mapped into the reconfigurable HW devices.
Probability of Dimer Formation on a Honeycomb Lattice

Atoms adsorbed on a honeycomb lattice diffuse and eventually form dimers. Three types of dimers are possible with this lattice’s symmetry: ortho-, metaand para-dimer. We estimate the probability of paraand ortho-dimer formation when atoms jump independently between sites of the underlying lattice. Our analyze is based on a simple model of diffusive motion of a pair of atoms which bind to lattice sites separated by a distance ∆, measured as a number of edges between sites and characterized by a chirality coefficient χ. Because of diffusive motion of atoms, ∆ and χ change in time and we trace a flow over the configurational space. The flow eventually converges to one of possible absorbing states. If the particular adsorbing state is reached it means that a dimer corresponding to this state is formed. We have computed time-dependent probabilities PO and PP for orthoand para-dimer formation, respectively. We have found that 4/15 < PO/PP < 5/14.