Miracle-dz/UniFAR-FTUs huggingface dataset:
Teratogenicity of low doses of all-trans retinoic acid in presomite mouse embryos.

This study was designed to examine the developmental dose response for all-trans retinoic acid (TRA) administered at presomite stages in mouse embryos. Previous studies using hamsters [Shenefelt (1972) Teratology 5:103-118] have shown that developmental stages corresponding to those present early on gestational day (GD) 7 in mice are most sensitive to retinoid-induced teratogenesis. Our preliminary studies showed that at this treatment time, gavage dosages of 7.5 mg/kg maternal body weight administered to C57B1/6N mice, an inbred strain, resulted in severe craniofacial malformations representing the holoprosencephaly, aprosencephaly spectrum. Additionally, in an outbred mouse strain, CD-1, exencephaly was induced by dosages of 2.5 mg/kg TRA and above. Readily detectable abnormalities of the eyes, including anophthalmia and severe microphthalmia and iridial colobomata, were induced by even lower doses cf TRA in the C57B1/6N strain. Incidences of micro/anophthalamia were 6.7%, 8.1%, 12.9%, and 32.4% at 0, 0.313, 0.625, and 1.25 mg/kg, respectively. The dosages required to induce significant incidences of exencephaly (2.5 mg/kg) and severe ocular abnormalities (1.25 mg/kg) on GD 7 in mice are approximately 50-100-fold less than those that are commonly used to examine the teratogenicity of this compound at later developmental stages in this species. The trend toward an increase in the incidence of severe ocular malformations at the lowest dose examined and the fact that subtle ocular malformations were not taken into account for this study suggest that even lower dosages may be effective. (ABSTRACT TRUNCATED AT 250 WORDS)
Recognition of group activities using dynamic probabilistic networks

Dynamic Probabilistic Networks (DPNs) are exploited for modeling the temporal relationships among a set of different object temporal events in the scene for a coherent and robust scene-level behaviour interpretation. In particular, we develop a Dynamically Multi-Linked Hidden Markov Model (DML-HMM) to interpret group activities involving multiple objects captured in an outdoor scene. The model is based on the discovery of salient dynamic interlinks among multiple temporal events using DPNs. Object temporal events are detected and labeled using Gaussian Mixture Models with automatic model order selection. A DML-HMM is built using Schwarz's Bayesian Information Criterion based factorisation resulting in its topology being intrinsically determined by the underlying causality and temporal order among different object events. Our experiments demonstrate that its performance on modelling group activities in a noisy outdoor scene is superior compared to that of a Multi-Observation Hidden Markov Model (MOHMM), a Parallel Hidden Markov Model (PaHMM) and a Coupled Hidden Markov Model (CHMM).
An accessibility index for the Metropolitan Region of São Paulo

The objective of this paper was to elaborate an index to measure accessibility to jobs in the Metropolitan Region of São Paulo. The index followed a gravitational formulation as proposed by HANSEN (1959), weighting the opportunities according to the impedance to achieve them. We defined ‘opportunities’ as the number of jobs in each zone, and ‘impedance’ as an inverse exponential function of travel time between each pair of zones, which was calculated by an Engineering Company. Two indices were calculated, one for trips made by private vehicles and a second one for public transportation. We observed that: a) accessibility is usually higher as nearer the zone is to city center; b) the spatial distribution of accessibility is different between the two modes, being shaped as concentric rings for the case of private vehicle and being somehow attached to the railway network for the case of public transportation; c) there is a significant spatial correlation between income and accessibility.
Computation on the Optimal Control of Networked Control Systems with Multiple Switching Modes Over High Speed Local Area Networks

The optimal control problem for the networked control system with multiple switching modes over high speed local area networks is addressed, where an initial state is a parametric vector. Because in the general case, the time delay is much less than the sampling period and the possibility of the packets collision is much lower, it can be assumed that the influence of the time delay and the packets loss on the optimal controller design can be ignored. On the basis of the assumption, the networked control systems with multiple switching modes are modeled as a hybrid system. Moreover, based on the Bellman type inequality for the hybrid systems, a dynamic program to solve the optimal control with a parameter vector is proposed, in every step of the technique, the feasible region is divided into evenly distributed grid points, and then, the optimal control law is transformed into maximizing the lower bound of the cost to go function in grid points. Finally, an experiment setup of the networked control system with multiple switching modes is constructed and a simulation example is given to illustrate the optimal control computation results.
An Effective Multilevel Thresholding Approach Using Conditional Probability Entropy and Genetic Algorithm

Entropy-based image thresholding are used widely in image processing. Conventional methods are efficient in the case of bi-level thresholding. But they are very computationally time consuming when extended to multilevel thresholding since they exhaustively search the optimal thresholds to optimize the objective functions. In this paper, we propose a conditional probability entropy (CPE) based on Bayesian theory and employ Genetic Algorithm (GA) to maximize the CPE for the multithresholds. The experimental results show that CPE is a good criterion of image thresholding and GA is a applicable fast algorithm for multi-level thresholding compared to the exhaustive searching method.
Drug Normalization for Cancer Therapeutic and Druggable Genome Target Discovery

Heterogeneous drug data representation among different druggable genome knowledge resources and datasets delays effective cancer therapeutic target discovery within the broad scientific community. The objective of the present paper is to describe the challenges and lessons learned from our efforts in developing and evaluating a standards-based drug normalization framework targeting cancer druggable genome datasets. Our findings suggested that mechanisms need to be established to deal with spelling errors and irregularities in normalizing clinical drug data in The Cancer Genome Atlas (TCGA), whereas the annotations from NCI Thesaurus (NCIt) and PubChem are two layers of normalization that potentially bridge between the clinical phenotypes and the druggable genome knowledge for effective cancer therapeutic target discovery.
PAPI 5: Measuring power, energy, and the cloud

The PAPI library [1] was originally developed to provide portable access to the hardware performance counters found on a diverse collection of modern microprocessors. Rather than learning and writing to a new performance infrastructure each time code is moved to a new machine, measurement code can be written to the PAPI API which abstracts away the underlying interface. Over time, other system components besides the processor have gained performance interfaces (for example, GPUs and network interfaces). PAPI was redesigned to have a component architecture to allow modular access to these new sources of performance data [2]. In addition to incremental changes in processor support, the recent PAPI 5 release adds support for two emerging concerns in the high-performance landscape: energy consumption and cloud computing. As processor densities climb, the thermal properties and energy usage of high performance systems are becoming increasingly important. We have extended the PAPI interface to simultaneously monitor processor metrics, thermal sensors, and power meters to provide clues for correlating algorithmic activity with thermal response and energy consumption. We have also extended PAPI to provide support for running inside of Virtual Machines (VMs). This ongoing work will enable developers to use PAPI to engage in performance analysis in a virtualized cloud environment.
Strain limiting for soft finger contact simulation

The command of haptic devices for rendering direct interaction with the hand requires thorough knowledge of the forces and deformations caused by contact interactions on the fingers. In this paper, we propose an algorithm to simulate nonlinear elasticity under frictional contact, with the goal of establishing a model-based strategy to command haptic devices and to render direct hand interaction. The key novelty in our algorithm is an approach to model the extremely nonlinear elasticity of finger skin and flesh using strain-limiting constraints, which are seamlessly combined with frictional contact constraints in a standard constrained dynamics solver. We show that our approach enables haptic rendering of rich and compelling deformations of the fingertip.
Activity of Scorpion Venom-Derived Antifungal Peptides against Planktonic Cells of Candida spp. and Cryptococcus neoformans and Candida albicans Biofilms

The incidence of fungal infections has been increasing in the last decades, while the number of available antifungal classes remains the same. The natural and acquired resistance of some fungal species to available therapies, associated with the high toxicity of these drugs on the present scenario and makes an imperative of the search for new, more efficient and less toxic therapeutic choices. Antimicrobial peptides (AMPs) are a potential class of antimicrobial drugs consisting of evolutionarily conserved multifunctional molecules with both microbicidal and immunomodulatory properties being part of the innate immune response of diverse organisms. In this study, we evaluated 11 scorpion-venom derived non-disulfide-bridged peptides against Cryptococcus neoformans and Candida spp. , which are important human pathogens. Seven of them, including two novel molecules, showed activity against both genera with minimum inhibitory concentration values ranging from 3.12 to 200 μM and an analogous activity against Candida albicans biofilms. Most of the peptides presented low hemolytic and cytotoxic activity against mammalian cells. Modifications in the primary peptide sequence, as revealed by in silico and circular dichroism analyses of the most promising peptides, underscored the importance of cationicity for their antimicrobial activity as well as the amphipathicity of these molecules and their tendency to form alpha helices. This is the first report of scorpion-derived AMPs against C. neoformans and our results underline the potential of scorpion venom as a source of antimicrobials. Further characterization of their mechanism of action, followed by molecular optimization to decrease their cytotoxicity and increase antimicrobial activity, is needed to fully clarify their real potential as antifungals.
A Bayesian adaptive design with biomarkers for targeted therapies

Background Targeted therapies are becoming increasingly important for the treatment of various diseases. Biomarkers are a critical component of a targeted therapy as they can be used to identify patients who are more likely to benefit from a treatment. Targeted therapies, however, have created major challenges in the design, conduct, and analysis of clinical trials. In traditional clinical trials, treatment effects for various biomarkers are typically evaluated in an exploratory fashion and only limited information about the predictive values of biomarkers obtained. Purpose New study designs are required, which effectively evaluate both the diagnostic and the therapeutic implication of biomarkers. Methods The Bayesian approach provides a useful framework for optimizing the clinical trial design by directly integrating information about biomarkers and clinical outcomes as they become available. We propose a Bayesian covariate-adjusted response-adaptive randomization design, which utilizes individual biomarker profiles and patient’s clinical outcomes as they become available during the course of the trial, to assign the most efficacious treatment to individual patients. Predictive biomarker subgroups are determined adaptively using a partial least squares regression approach. Results A series of simulation studies were conducted to examine the operating characteristics of the proposed study design. The simulation studies show that the proposed design efficiently identifies patients who benefit most from a targeted therapy and that there are substantial savings in the sample size requirements when compared to alternative designs. Limitations The design does not control for the type I error in the traditional sense and a positive result should be confirmed by conducting an independent phase III study focusing on the selected biomarker profile groups. Conclusions We conclude that the proposed design may serve a useful role in the early efficacy phase of targeted therapy development. Clinical Trials 2010; 7: 546—556. http://ctj.sagepub. com
Implementation of a Nonlinear Planar Magnetics Model

A nonlinear lumped element model for planar magnetics is presented. This technique develops an equivalent circuit model for multilayer planar magnetic components using 1-D analysis of Maxwell's equations. Conducting layers are represented as impedance networks, while the insulating regions are modeled as air-cored inductors. The equivalent circuit model is extended by representing the nonlinear magnetic core material as a nonlinear impedance whose magnetization characteristic is based on the Jiles-Atherton hysteresis model as well as modeling skin and proximity effects in the conductors and current distribution across windings, the improved model also integrates hysteresis loss of the magnetic core and saturation effects. The technique can be implemented in circuit simulation software. A prototype planar transformer, using printed circuit boards to mount windings, was characterized to validate the performance of the model. It is demonstrated that the developed nonlinear model more accurately represents the characteristics of the experimental transformer compared to the existing linear lumped element model. This includes the effect of core saturation on the input current and output-voltage waveforms. The technique is generalized and can be applied to many topologies and geometries.
Brain mitochondrial defects amplify intracellular [Ca2+] rise and neurodegeneration but not Ca2+ entry during NMDA receptor activation

According to the “indirect” excitotoxicity hypothesis, mitochondrial defects increase Ca2+ entry into neurons by rendering NMDA‐R hypersensitive to glutamate. We tested this hypothesis by investigating in the rat striatum and cultured striatal cells how partial mitochondrial complex II inhibition produced by 3‐nitropropionic acid (3NP) modifies the toxicity of the NMDA‐R agonist quinolinate (QA). We showed that nontoxic 3NP treatment, leading to partial inhibition of complex II activity, greatly exacerbated striatal degeneration produced by slightly toxic QA treatment through an “all‐or‐nothing” process. The potentiation of QA‐induced cell death by 3NP was associated with increased calpain activity and massive calpain‐mediated cleavage of several postsynaptic proteins, suggesting major neuronal Ca2+ deregulation in the striatum. However, Ca2+ anomalies probably do not result from NMDA‐R hypersensitivity. Indeed, brain imaging experiments using [18F]fluorodeoxyglucose indirectly showed that 3NP did not increase QA‐induced ionic perturbations at the striatal glutamatergic synapses in vivo. Consistent with this, the exacerbation of QA toxicity by 3NP was not related to an increase in the QA‐induced entry of 45Ca2+ into striatal neurons. The present results demonstrate that the potentiation of NMDA‐R‐mediated excitotoxicity by mitochondrial defects involves primarily intracellular Ca2+ deregulation, in the absence of NMDA‐R hypersensitivity. —Jacquard, C. , Trioulier, Y. , Cosker, F. , Escartin, C. , Bizat, N. , Hantraye, P., Cancela*, J. M. , Bonvento, G. , Brouillet, E. Brain mitochondrial defects amplify intracellular [Ca2+] rise and neurodegeneration but not Ca2+ entry during NMDA receptor activation. FASEB J. 20, E245–E259 (2006)
HTM: A Topic Model for Hypertexts

Previously topic models such as PLSI (Probabilistic Latent Semantic Indexing) and LDA (Latent Dirichlet Allocation) were developed for modeling the contents of plain texts. Recently, topic models for processing hypertexts such as web pages were also proposed. The proposed hypertext models are generative models giving rise to both words and hyperlinks. This paper points out that to better represent the contents of hypertexts it is more essential to assume that the hyperlinks are fixed and to define the topic model as that of generating words only. The paper then proposes a new topic model for hypertext processing, referred to as Hypertext Topic Model (HTM). HTM defines the distribution of words in a document (i.e., the content of the document) as a mixture over latent topics in the document itself and latent topics in the documents which the document cites. The topics are further characterized as distributions of words, as in the conventional topic models. This paper further proposes a method for learning the HTM model. Experimental results show that HTM outperforms the baselines on topic discovery and document classification in three datasets.
Modeling Gross Primary Production for Sunlit and Shaded Canopies Across an Evergreen and a Deciduous Site in Canada

Light use efficiency (LUE) models offer an effective way for regional gross primary productivity (GPP) estimation. However, LUE is not easily determined at the landscape level due to its complexity and dependence on various environmental factors. One possible strategy to avoid the requirement for assessing environmental stressors is using the photochemical reflectance index (PRI) to determine LUE via the epoxidation state of the xanthophyll cycle. Integration of such measurements into GPP models could lead to more realistic GPP estimates of landscape level. Conventional, “one-leaf” LUE models, however, seem less suitable for integration of such remote sensing observations, as optically derived estimates are dependent on the shadow fraction viewed at a given time. Here, we utilize the two-leaf LUE (TL-LUE) model to parameterize LUE from multiangle PRI observations and compare it with MOD17 approach. Significant relationships were found between LUE (LUE, LUEsun, and LUEshaded) and PRI (PRI, PRIsun, and PRIshaded) over 8- and 16-day time steps. Similarly, $R^{2}$ values for the relationships between modeled GPP and observed GPP (EC derived measurements of GPP) were 0.87 (TL-LUE) and 0.81 (MOD17) at deciduous forest and 0.54 (TL-LUE) and 0.46 (MOD17) at evergreen forest for eight-day periods, as well as 0.84 (TL-LUE) and 0.74 (MOD17) at deciduous forest and 0.49 (TL-LUE) and 0.46 (MOD17) at evergreen forest for 16-day periods. Our results are relevant when planning potential future satellite missions to help constrain existing GPP models using remotely sensed data, as such observations will likely be affected by canopy shading effects at the time of observation.
Integrated Control of Peridomestic Larval Habitats of Aedes and Culex Mosquitoes (Diptera: Culicidae) in Atoll Villages of French Polynesia

Abstract An integrated larval mosquito control program was carried out in Tiputa village on Rangiroa atoll of French Polynesia. Mosquito abundance before and after treatment was compared with the abundance in an untreated village. Mosquito larval habitats consisted of large concrete or polyurethane cisterns, wells, and 200-liter drums. Depending on the target species, larval habitat category, its configuration, and purpose (drinking consumption or not), abatement methods consisted of sealing the larval habitats with mosquito gauze, treating them with 1% Temephos, covering the water with a 10-cm thick layer of polystyrene beads or introducing fish (Poecillia reticulata Rosen & Bailey). All premises of the chosen village were treated and a health education program explained basic mosquito ecology and the methods of control. A community health agent was trained to continue the control program at the end of the experiment. Entomological indices from human bait collections and larval surveys indicated that mosquito populations were reduced significantly, compared with concurrent samples from the untreated control village, and that mosquito control remained effective for 6 mo after treatment. Effects of the treatment were noticed by the inhabitants in terms of a reduction in the number of mosquito bites. In the Polynesian context, such control programs may succeed in the long-term only if strong political decisions are taken at the village level, if a community member is designated as being responsible for maintaining the program, and if the inhabitants are motivated sufficiently by the mosquito nuisance to intervene.
University of Texas Medical Branch at Galveston.

Please refer to the General Information Catalog section for Graduate Requirements for Admission available at https://www.utmb. edu/enrollmentservices/catalog.asp The Institute for the Medical Humanities (IMH) advances inquiry that enlarges the scholarly connections among the humanities, health care, health policy, and biomedical research. Rooted in philosophy, literature, religion, history, bioethics and humanistic social science disciplines, our interdisciplinary program is designed to illuminate value questions in health-care settings, elicit meaning from illness by analysis and imagination, and cultivate critical intelligence that probes the making, meaning, and authority of diverse knowledges.
Informalidad y movilidad en el mercado laboral: una aproximación de pseudo-panel

Una de las principales limitaciones del analisis del mercado laboral en los paises en desarrollo es la falta de informacion apropiada de datos de panel. Este documento extiende la metodologia de Dang et al., (2014) para examinar la movilidad en el mercado laboral entre los sectores formal e informal en Bolivia y Colombia, construyendo un pseudo-panel consistente a partir de datos de encuestas de corte transversal repetidas. Despues de poner a prueba la robustez de la metodologia, identificamos los intervalos de confianza de los grupos de movilidad en Bolivia y Colombia (formal a formal, informal a informal, formal a informal e informal a formal). Los resultados proveen evidencia de que en Colombia y Bolivia la movilidad entre los sectores laborales es relativamente baja, lo cual explica la baja variabilidad de la tasa de informalidad en estos paises. Los resultados sugieren que el numero de personas que se mueven al sector informal tiende a ser mas grande que la cantidad de trabajadores que escapan del mercado informal hacia el formal, o por lo menos existe mas variabilidad entre anos para los primeros. Esto implica que las politicas publicas enfocadas en el mercado laboral en America Latina no llevarian a mejoras significativas si los patrones de movilidad no cambian.