Miracle-dz/UniFAR-FTUs huggingface dataset:
Specific regions within the embryonic midbrain and cerebellum require different levels of FGF signaling during development

Prospective midbrain and cerebellum formation are coordinated by FGF ligands produced by the isthmic organizer. Previous studies have suggested that midbrain and cerebellum development require different levels of FGF signaling. However, little is known about the extent to which specific regions within these two parts of the brain differ in their requirement for FGF signaling during embryogenesis. Here, we have explored the effects of inhibiting FGF signaling within the embryonic mouse midbrain (mesencephalon) and cerebellum (rhombomere 1) by misexpressing sprouty2 (Spry2) from an early stage. We show that such Spry2 misexpression moderately reduces FGF signaling, and that this reduction causes cell death in the anterior mesencephalon, the region furthest from the source of FGF ligands. Interestingly, the remaining mesencephalon cells develop into anterior midbrain, indicating that a low level of FGF signaling is sufficient to promote only anterior midbrain development. Spry2 misexpression also affects development of the vermis, the part of the cerebellum that spans the midline. We found that, whereas misexpression of Spry2 alone caused loss of the anterior vermis, reducing FGF signaling further, by decreasing Fgf8 gene dose, resulted in loss of the entire vermis. Our data suggest that cell death is not responsible for vermis loss, but rather that it fails to develop because reducing FGF signaling perturbs the balance between vermis and roof plate development in rhombomere 1. We suggest a molecular explanation for this phenomenon by providing evidence that FGF signaling functions to inhibit the BMP signaling that promotes roof plate development.
Alteration of the Migratory Behavior of UV-Induced Regulatory T Cells by Tissue-Specific Dendritic Cells1

UV radiation-induced regulatory T cells (UV-Treg) inhibit the sensitization but not the elicitation of contact hypersensitivity when injected i.v. Because UV-Treg express the lymph node homing receptor CD62 ligand, upon i.v. injection they migrate into the lymph nodes but not into the periphery and therefore inhibit sensitization but not elicitation. We tried to modify the migratory behavior of UV-Treg with the aim to get them into the periphery and thereby to suppress the effector phase of immune reactions. Because the tissue selective homing of T effector cells is determined by tissue-specific dendritic cells (DC), we attempted to reprogram the migratory behavior of UV-Treg by DC. 2,4-Dinitrofluorobencene (DNFB)-specific UV-Treg coincubated with epidermal Langerhans cells (LC) blocked the elicitation upon i.v. injection into DNFB-sensitized mice. In contrast, i.v. injection of UV-Treg not incubated with LC did not inhibit the ear challenge. The same negative effect was observed for UV-Treg coincubated with DC from bone marrow, spleen, or lymph nodes. This effect was not due to different maturation stages as checked by MHC class II expression of the different DC types. Incubation with LC but not with bone marrow-derived DC down-regulated the expression of CD62 ligand on UV-Treg. Accordingly, CFDA-SE labeled UV-Treg coincubated with LC were found in the ears but not in the lymph nodes upon i.v. injection. This finding shows that the migratory behavior can be reprogrammed by tissue-specific DC and may have input on strategies trying to use Treg not only for the prevention but also for the treatment of immune-mediated diseases.
Sub-microliter microwave dielectric spectroscopy for identification and quantification of carbohydrates in aqueous solution

This paper presents the technique and associated miniature RF biosensor dedicated to the microwave dielectric spectroscopy of carbohydrates in aqueous solution. Small amounts of liquid in the range of microliter are required. This sensor includes an area for electromagnetic field analysis that operates in the near field, while a microfluidic channel allows precisely bringing and locating the liquid solution to be studied on the sensing zone. Different carbohydrates were measured from 40 MHz to 40 GHz with relevant concentrations for biologists and chemists. Derived from the extracted complex relative permittivity of the examined liquids, this paper shows that each biomolecules type exhibits a specific dielectric signature, which allows their identification and quantification.
Educational Data Mining with Focus on Dropout Rates

Summary High dropout rates in higher education may be motivated by social, economic or personal factors and it is a reality in the Mathematics Major at Universidade Estadual do Oeste do Parana - Cascavel. Thus, the aim of this study was to identify the factors that may have been influencing this reality through Data Mining (Classification). The study investigated the academic background and socioeconomic factors. Higher dropout rates were identified in the first year of this Major in which the course 'Differential and Integral Calculus I' was the one that most contributed for that. As for the socioeconomic factor, full-time working necessity was the one that was the most responsible for dropouts. Although trivial, the rules found endorse what by socializing with academics involved in the research was expected. It is hoped that this work may contribute to the elaboration of policies aimed at meeting the needs of the students, therefore ensuring their permanency at the University.
Optical Flow with Semantic Segmentation and Localized Layers

Existing optical flow methods make generic, spatially homogeneous, assumptions about the spatial structure of the flow. In reality, optical flow varies across an image depending on object class. Simply put, different objects move differently. Here we exploit recent advances in static semantic scene segmentation to segment the image into objects of different types. We define different models of image motion in these regions depending on the type of object. For example, we model the motion on roads with homographies, vegetation with spatially smooth flow, and independently moving objects like cars and planes with affine motion plus deviations. We then pose the flow estimation problem using a novel formulation of localized layers, which addresses limitations of traditional layered models for dealing with complex scene motion. Our semantic flow method achieves the lowest error of any published monocular method in the KITTI-2015 flow benchmark and produces qualitatively better flow and segmentation than recent top methods on a wide range of natural videos.
Distributed-feedback grating used as an array-mode selector in resonant antiguided diode laser arrays: effects of the mirror facet position with respect to the grating

In resonant and nearly resonant antiguided arrays (ROW arrays), if the grating is located below the active region, a distributed-feedback (DFB) grating can function as a selector for the in-phase array mode in addition to its role as a frequency discriminator. Threshold current densities are calculated for competing (lateral) spatial modes in AR/HR coated 10- and 20-element arrays incorporating lower gratings (ROW-LDFB arrays). Calculations include the effects of random facet locations relative to the grating phase. The threshold current density, J/sub th/, of the in-phase mode and its discrimination, /spl Delta/J/sub th/, against other (array) spatial modes vary with facet location. For 20 (10) elements, J/sub th//spl ap/350-525 (400-550) A/cm/sup 2/ and /spl Delta/J/sub th/ reaches a maximum of 55 (58) A/cm/sup 2/ for 0.01/0.95 AR/HR-coated 350 /spl mu/m-long devices. For 10-element arrays, the probability of in-phase operation is approximately 50%; for 20-element arrays, the probability is 100%. Preliminary experimental results from 20-element nonresonant devices with uncoated facets are near diffraction-limited beams and nearly single-frequency operation to 250 mW.
Fast, Easy, and Cheap: Construction of Statistical Machine Translation Models with MapReduce

In recent years, the quantity of parallel training data available for statistical machine translation has increased far more rapidly than the performance of individual computers, resulting in a potentially serious impediment to progress. Parallelization of the model-building algorithms that process this data on computer clusters is fraught with challenges such as synchronization, data exchange, and fault tolerance. However, the MapReduce programming paradigm has recently emerged as one solution to these issues: a powerful functional abstraction hides system-level details from the researcher, allowing programs to be transparently distributed across potentially very large clusters of commodity hardware. We describe MapReduce implementations of two algorithms used to estimate the parameters for two word alignment models and one phrase-based translation model, all of which rely on maximum likelihood probability estimates. On a 20-machine cluster, experimental results show that our solutions exhibit good scaling characteristics compared to a hypothetical, optimally-parallelized version of current state-of-the-art single-core tools.
A Theory of Self-Esteem

Self-esteem has been conceptualized as an outcome, motive, and buffer, but there is no overall theory of self-esteem. In this article it is suggested that identity theory can provide a theoretical framework for the integration of the various conceptualizations of self-esteem. We suggest that self-esteem is an outcome of, and necessary ingredient in, the self-verification process that occurs within groups, maintaining both the individual and the group. Verification of role identities increases an individual's worth-based and efficacy-based self-esteem. The self-esteem built up by self-verification buffers the negative emotions that occur when self-verification is problematic, thus allowing continued interaction and continuity in structural arrangements during periods of disruption and change. Last, a desire for self-esteem, produced in part through self-verification, stabilizes the group because it motivates individuals to form and maintain relationships that verify identities.
Sipuleucel-T immunotherapy for castration-resistant prostate cancer.

BACKGROUND Sipuleucel-T, an autologous active cellular immunotherapy, has shown evidence of efficacy in reducing the risk of death among men with metastatic castration-resistant prostate cancer. METHODS In this double-blind, placebo-controlled, multicenter phase 3 trial, we randomly assigned 512 patients in a 2:1 ratio to receive either sipuleucel-T (341 patients) or placebo (171 patients) administered intravenously every 2 weeks, for a total of three infusions. The primary end point was overall survival, analyzed by means of a stratified Cox regression model adjusted for baseline levels of serum prostate-specific antigen (PSA) and lactate dehydrogenase. RESULTS In the sipuleucel-T group, there was a relative reduction of 22% in the risk of death as compared with the placebo group (hazard ratio, 0.78; 95% confidence interval [CI], 0.61 to 0.98; P=0.03). This reduction represented a 4.1-month improvement in median survival (25.8 months in the sipuleucel-T group vs. 21.7 months in the placebo group). The 36-month survival probability was 31.7% in the sipuleucel-T group versus 23.0% in the placebo group. The treatment effect was also observed with the use of an unadjusted Cox model and a log-rank test (hazard ratio, 0.77; 95% CI, 0.61 to 0.97; P=0.02) and after adjustment for use of docetaxel after the study therapy (hazard ratio, 0.78; 95% CI, 0.62 to 0.98; P=0.03). The time to objective disease progression was similar in the two study groups. Immune responses to the immunizing antigen were observed in patients who received sipuleucel-T. Adverse events that were more frequently reported in the sipuleucel-T group than in the placebo group included chills, fever, and headache. CONCLUSIONS The use of sipuleucel-T prolonged overall survival among men with metastatic castration-resistant prostate cancer. No effect on the time to disease progression was observed. (Funded by Dendreon; ClinicalTrials.gov number, NCT00065442.)
Stronger Lower Bounds on Quantum OBDD for the Hidden Subgroup Problem

We consider the Hidden Subgroup in the context of quantum Ordered Binary Decision Diagrams. We show several lower bounds for this function. In this paper we also consider a slightly more general definition of the hidden subgroup problem (in contrast to that in [KH10]). It turns out that in this case the problem is intractable for the quantum OBDD. We prove exponential lower bounds for this function.
Serum biomarker analysis in patients with recurrent spontaneous abortion

Recurrent spontaneous abortion (RSA) occurs in 1–5% of parturients. The sustained therapy and research for RSA is expensive, which is a serious issue faced by both patients and doctors. The aim of the present study was to detect protein expression profiles in the serum of RSA patients and healthy controls, and to identify potential biomarkers for this disease. A 1,000-protein microarray consisting of a combination of Human L-507 and L-493 was used. The microarray data revealed that eight serum protein expression levels were significantly upregulated and 143 proteins were downregulated in RSA patients compared with the healthy controls. ELISA individually validated 5 of these 151 proteins in a larger cohort of patients and control samples, demonstrating a significant decrease in insulin-like growth factor-binding protein-related protein 1 (IFGBP-rp1)/IGFBP-7, Dickkopf-related protein 3 (Dkk3), receptor for advanced glycation end products (RAGE) and angiopoietin-2 levels in patients with RSA. Sensitivity and specificity analyses were calculated by a receiver operating characteristics curve, and were revealed to be 0.881, 0.823, 0.79 and 0.814, with diagnostic cut-off points of 95.44 ng/ml for IFGBP-rp1, 32.84 ng/ml for Dkk3, 147.27 ng/ml for RAGE and 441.40 ng/ml for angiopoietin-2. The present study indicated that these four proteins were downregulated in RSA samples and may be useful as biomarkers for the prediction and diagnosis of RSA. Subsequent studies in larger-scale cohorts are required to further validate the diagnostic value of these markers.
Neuroplasticity and Functional Recovery: Training Models and Compensatory Strategies in Music Therapy

New research developments in the recovery of function following neurological trauma as well as basic and applied research relevant to music perception and production, seem to point to the suggestion that specific music therapy interventions that directly address the restoration of function as opposed to developing compensatory mechanisms, in certain circumstances, may now be a more appropriate treatment approach. We will address the issue of appropriate timing for the introduction of each strategy and discuss potential outcomes of each approach. As one might imagine, much of this research is published in the neurological journals, which music therapists may not regularly consult. It seems challenging enough just to keep abreast of new music therapy literature. Further, there is so much neurological research that the music therapy clinician often finds it difficult to know where to begin. This text provides an overview of a growing concept related to recovery known as neuroplasticity, and how specific training models in music therapy utilize this relatively recently identified phenomenon. Also, a framework will be provided to help guide the practicing clinician when attempting to build a lineage of systematic thought relevant to the use of music in neurorehabilitation, as well as discuss the frequently employed concept of behavioural compensation. Some music therapy literature that relates to these different concepts is outlined. Discussions surrounding the decision to use either of these two approaches are presented in relation to stages of recovery and the clinical presentation of the client.
Video fade detection by discrete line identification

The video segmentation problem can be regarded as a problem of detecting the fundamental video units (shots). Due to different ways of linking two consecutive shots this task turns out to be difficult. In this work, we propose a method to detect a type of gradual transition, the fade, by image segmentation tools instead of using dissimilarity measures or mathematical models. Firstly, the video is transformed into a 2D image considering the histogram information, called visual rhythm by histogram. Afterwards, we apply image processing tools to detect specified patterns in this image.
Online Detection of Start Time and Location for Hypocenter in North America Power Grid

The power grid dynamics in North America is online detected by the North American power grid frequency monitoring network, and the measured frequency signals by frequency disturbance recorders (FDRs) contain the white noise and spikes that affect the analysis to those signals. In this paper, an interference model is built to depict the FDR frequency signals. Since those contaminated and complicated FDR frequency signals cannot be denoised satisfactorily by a conventional median filter with fixed window size, it is necessary that an adaptive median filter is designed and employed to eliminate noise and spikes. Furthermore, the accurate event start time (EST) is very important to analyze the dynamic process of a power grid and to locate the hypocenter of both the load trip event and the generation trip event, and hence a simple and useful algorithm also is presented to estimate the EST. Two event cases from North American power grids are employed to validate our idea.
Solvability-unconcerned inverse kinematics based on Levenberg-Marquardt method with robust damping

A robust numerical solution to the inverse kinematics is presented based on Levenberg-Marquardt method. The equation solvability in addition to the singularity doesn't concern the method; even in cases where the problem doesn't have solutions or has countless solutions, it converges to the optimum solution in the sense that it minimizes the residual from the target points with the smallest joint deviations. The squared norm of the residual with a small bias is used for the damping factor, while its numerical stability, convergence performance and computation speed are remarkable. It is suitable to large-scale structure-varying kinematic chains, in which the relationship between the number of constraints and the degree-of-freedom frequently changes. It frees robot operators from being careful about the assignment of the target points of effectors. As an application of the proposed method, a stretched-knee walking motion of a humanoid robot is designed.
ADAPT - adaptive automated robotic task practice system for stroke rehabilitation

We propose a new robotic task practice system designed to enhance the recovery of upper extremity functions in patients with stroke. Our system, ADAPT (adaptive and automatic presentation of tasks), which was designed in accordance to current training guidelines for stroke rehabilitation, engages the patient intensively, actively, and adaptively in a variety of realistic functional tasks that require reaching and manipulation. A general-purpose robot simulates the dynamics of the functional tasks. Based on the subject's performance, a task scheduler adaptively selects a task and sets the task difficulty. The tool changer selects the tool corresponding to the selected task, a doorknob for instance. The low-level controller then implements the selected task with the desired difficulty on the robot during the robot-patient interaction. Our preliminary experimental results demonstrate the feasibility of our system.
Recognition of Spoken Arabic Digits Using Neural Predictive Hidden Markov Models

In this study, we propose an algorithm for Arabic isolated digit recognition. The algorithm is based on extracting acoustical features from the speech signal and using them as input to multi-layer perceptrons neural networks. Each word in the vocabulary digits (0 to 9) is associated with a network. The networks are implemented as predictors for the speech samples for a certain duration of time. The back-propagation algorithm is used to train the networks. The hidden markov model (HMM) is implemented to extract temporal features (states) for the speech signal. The input vector to the networks consists of twelve mel frequency cepstral coefficients, log of the energy, and five elements representing the state. Our results show that we are able to reduce the word error rate comparing with an HMM word recognition system.
Quantum dynamics of the parametric oscillator.

We present dynamical calculations for the quantum parametric oscillator using both number-state and coherent-state bases. The coherent-state methods use the positive-P representation, which has a nonclassical phase space an essential requirement in obtaining an exact stochastic representation of this nonlinear problem. This also provides a way to directly simulate quantum tunneling between the two above-threshold stable states of the oscillator. The coherent-state methods provide both analytic results at large photon numbers, and numerical results for any photon number, while our number-state calculations are restricted to numerical results in the low-photon-number regime. The number-state and coherent-state methods give precise agreement within the accuracy of the numerical calculations. We also compare our results with methods based on a truncated Wigner representation equivalent to stochastic electrodynamics, and find that these are unable to correctly predict the tunneling rate given by the other methods. An interesting feature of the results is the much faster tunneling predicted by the exact quantum-theory methods compared with earlier semiclassical calculations using an approximate potential barrier. This is similar to the faster tunneling found when comparing quantum penetration of a barrier to classical thermal activation. The quantum parametric oscillator, which has an exact steady-state solution, therefore provides a useful and accessible system in which nonlinear quantum effects can be studied far from thermal equilibrium.
Ethnicity as a Variable in Leisure Research

The purpose of this study is to examine the usefulness of ethnicity as a construct in leisure research. In particular, we are interested in the degree to which presumed ethnic groups exhibit internal cultural homogeneity. In 2002, the visitors to the Angeles National Forest (ANF) near metropolitan Los Angeles were surveyed. Using purposive sampling at sites known to be heavily used by visitors with diverse ethnic backgrounds, we obtained a sample of 444 Anglos, 312 Hispanics, and 319 Asians (overall n = 1,174). We examined whether the three nominal ethnic groups, Anglos, Hispanics, and Asians, were homogeneous in terms of cultural values as measured by Hofstede's (1980) instrument. We assume that if distinctive ethnic subcultures exist then they should be identifiable by specific measures of languages, religion, family structure, cultural values, and the like. We used cultural consensus analyses to test the homogeneity of the three ethnic groups. The results of cultural consensus analyses showed that none of the three ethnic groups and none of the subgroups we examined within the three ethnic groups were homogeneous in terms of the cultural values. Discussion of the findings and research implications are suggested.
Current Trends in Grief Counseling

Counseling Association by Dr. Garry R. Walz and Dr. Jeanne C. Bleuer of Counseling Outfitters, LLC. Its purpose is to provide a means of capturing the ideas, information and experiences generated by the annual ACA Conference and selected ACA Division Conferences. Papers on a program or practice that has been validated through research or experience may also be submitted. This digital collection of peer-reviewed articles is authored by counselors, for counselors. VISTAS Online contains the full text of over 500 proprietary counseling articles published from 2004 to present.