Miracle-dz/UniFAR-FTUs huggingface dataset:
Neurotransmitters regulating acid secretion in the proventriculus of the Houbara bustard (Chlamydotis undulata): A morphological viewpoint

Endocrine cells containing somatostatin (Som), gastrin‐releasing peptide (GRP), and neuronal nitric oxide synthase (nNOS) and nerve fibers containing choline acetyl transferase (ChAT), tyrosine hydroxylase (TH), galanin (Gal), substance P (SP), and vasoactive intestinal polypeptide (VIP) were immunolocalized in the proventriculus of the Houbara bustard, Chlamydotis undulata. While GRP‐immunoreactive (GRP‐IR) cells occur in the inner zone, somatostatin (Som‐IR) and polyclonal nNOS (nNOS‐IR) immunoreactive cells were localized mainly in the peripheral zone of submucosal glands. GRP‐IR, Som‐IR, and nNOS‐IR cells were occasionally observed in the walls of the gastric glands. Endocrine cells are of the closed variety and usually possess apical processes extending along the basal surfaces of adjacent nonreactive cells. Ultrastructural features of these cells are typical. ChAT, Gal, SP, VIP, and TH were immunolocalized in nerve fibers and terminals in the walls of arterioles and capillaries at the periphery of submucosal glands. Immunoreactivity to monoclonal nNOS occurred mainly in neuronal cell bodies in ganglia located around the submucosal glands. ChAT and TH immunoreactive cell bodies were also occasionally seen around the submucosal glands in the peripheral region. Immunoreactivity to Gal, SP, and VIP, but not ChAT or TH, was discernible around the walls of gastric glands. It was concluded that the distribution of neurotransmitters in neuronal structures is similar, but that of the endocrine cells varies from that of some avian species. The roles of these neurotransmitters in the regulation of acid secretion are discussed. J. Morphol. 248:175–184, 2001. © 2001 Wiley‐Liss, Inc.
On the use of mass scaling for stable and efficient simulated tempering with molecular dynamics

Simulated tempering (ST) is a generalized‐ensemble algorithm that employs trajectories exploring a range of temperatures to effectively sample rugged energy landscapes. When implemented using the molecular dynamics method, ST can require the use of short time steps for ensuring the stability of trajectories at high temperatures. To address this shortcoming, a mass‐scaling ST (MSST) method is presented in which the particle mass is scaled in proportion to the temperature. Mass scaling in the MSST method leads to velocity distributions that are independent of temperature and eliminates the need for velocity scaling after the accepted temperature updates that are required in conventional ST simulations. The homogeneity in time scales with changing temperature improves the stability of simulations and allows for the use of longer time steps at high temperatures. As a result, the MSST is found to be more efficient than the standard ST method, particularly for cases in which a large temperature range is employed. © 2016 Wiley Periodicals, Inc.
Neural Structural Correspondence Learning for Domain Adaptation

We introduce a neural network model that marries together ideas from two prominent strands of research on domain adaptation through representation learning: structural correspondence learning (SCL, (Blitzer et al., 2006)) and autoencoder neural networks (NNs). Our model is a three-layer NN that learns to encode the non-pivot features of an input example into a low dimensional representation, so that the existence of pivot features (features that are prominent in both domains and convey useful information for the NLP task) in the example can be decoded from that representation. The low-dimensional representation is then employed in a learning algorithm for the task. Moreover, we show how to inject pre-trained word embeddings into our model in order to improve generalization across examples with similar pivot features. We experiment with the task of cross-domain sentiment classification on 16 domain pairs and show substantial improvements over strong baselines.
Participation in Active Singing Leads to Cognitive Improvements in Individuals with Dementia

Conflict of Interest: The editor in chief has reviewed the conflict of interest checklist provided by the authors and has determined that the authors have no financial or any other kind of personal conflicts with this paper. Author Contributions: Wu, Lu: study concept and design, acquisition of subjects and data, data analysis. Wu, Lu, Cheng, Kawachi: interpretation of findings, critical review of manuscript. Sponsor’s Role: None.
MEDIA PEMBELAJARAN INTERAKTIF PERANGKAT LUNAK PENGOLAH ANGKA UNTUK KELAS XI SMA NEGERI 2 WATES

Tujuan penelitian ini adalah merancang media pembelajaran interaktif perangkat lunak pengolah angka serta mengetahui besar persentase kelayakan media pembelajaran interaktif tersebut. Metode yang digunakan pada penelitian ini adalah penelitian pengembangan (Research and Development). Penelitian ini dilakukan di SMA Negeri 2 Wates. Subyek penelitian adalah siswa kelas XI IPA 1 dan XI IPS 2 SMA Negeri 2 Wates. Obyek penelitian adalah media pembelajaran perangkat lunak pengolah angka yang dirancang menggunakan software Macromedia Flash Profesional 8. Metode yang digunakan dalam pengumpulan data yaitu dengan observasi dan angket, dan metode analisis data adalah dengan teknik analisis deskriptif kuantitatif. Hasil pengujian Alpha testing yang dilakukan oleh ahli media, memperoleh persentase kelayakan 91,67 %. Penilaian ahli materi mendapat persentase kelayakan sebesar 81,82 %. Pengujian Betha testing yang dilakukan oleh pengguna memperoleh persentase kelayakan sebesar 81,67 %, jadi media pembelajaran yang dikembangkan memiliki kriteria penilaian sangat baik.
Reconstructing spatio-temporal activities of neural sources using an MEG vector beamformer technique

The authors have developed a method suitable for reconstructing spatio-temporal activities of neural sources by using magnetoencephalogram (MEG) data. The method extends the adaptive beamformer technique originally proposed by Borgiotti and Kaplan (1979) to incorporate the vector beamformer formulation in which a set of three weight vectors are used to detect the source activity in three orthogonal directions. The weight vectors of the vector-extended version of the Borgiotti-Kaplan beamformer are then projected onto the signal subspace of the measurement covariance matrix to obtain the final form of the proposed beamformer's weight vectors. The authors' numerical experiments show that both spatial resolution and output signal-to-noise ratio of the proposed beamformer are significantly higher than those of the minimum-variance-based vector beamformer used in previous investigations. The authors also applied the proposed beam former to two sets of auditory-evoked MEG data, and the results clearly demonstrated the method's capability of reconstructing spatio-temporal activities of neural sources.
EDEN-BP-dependent post-transcriptional regulation of gene expression in Xenopus somitic segmentation

EDEN-BP is a Xenopus RNA-binding protein that triggers deadenylation [poly(A) tail shortening], and thereby translational repression and degradation, of a subset of maternal mRNAs soon after fertilization. We show here that this factor is expressed in the presomitic mesoderm of older embryos, the site where somitic segmentation takes place. Inhibiting EDEN-BP function using either antisense morpholino oligonucleotides or neutralizing antibodies leads to severe defects in somitic segmentation, but not myotomal differentiation. This is associated with defects in the expression of segmentation markers belonging to the Notch signalling pathway in the presomitic mesoderm. We show by a combination of approaches that the mRNA encoding XSu(H), a protein that plays a central role in Notch signalling, is regulated by the EDEN-BP pathway. Accordingly, XSu(H) is overexpressed in EDEN-BP knock-down embryos, and overexpressing XSu(H) causes segmentation defects. We finally give data indicating that, in addition to XSu(H), other segmentation RNAs are a target for EDEN-BP. These results show that EDEN-BP-dependent post-transcriptional regulation of gene expression is required for the process of somitic segmentation.
ECAT: Event Capture Annotation Tool

This paper introduces the Event Capture Annotation Tool (ECAT), a user-friendly, open-source interface tool for annotating events and their participants in video, capable of extracting the 3D positions and orientations of objects in video captured by Microsoft's Kinect(R) hardware. The modeling language VoxML (Pustejovsky and Krishnaswamy, 2016) underlies ECAT's object, program, and attribute representations, although ECAT uses its own spec for explicit labeling of motion instances. The demonstration will show the tool's workflow and the options available for capturing event-participant relations and browsing visual data. Mapping ECAT's output to VoxML will also be addressed.
A General Factor of Personality.

A recent hypothesis is that a general factor of personality (GFP) occupies the apex of the hierarchy of personality as well as the apex of the personality disorders in the same way in which g , the general factor of mental ability, occupies the apex in the organization of cognitive abilities (Rushton, Bons, & Hur, 2008 ). High scores on the GFP indicate what is meant by someone having a “ good ” personality; low scores indicate what is meant by a “ diffi cult ” personality, in other words someone who is hard to get along with. Individuals high on the GFP are altruistic, agreeable, relaxed, conscientious, sociable, and open, with high levels of well being and self esteem. Because the GFP defi nes clear positive and negative poles, it provides potential for understanding the socially “ advantaged ” (those with high levels of emotional intelligence) as well as the socially “ challenged ” (those more likely to suffer a personality disorder). The GFP can be viewed as a dimension of social effectiveness. The explanation we favor for the GFP is that it arose through evolutionary selection for socially desirable traits that facilitate performance across a wide range of contexts (Rushton et al., 2008 ). This follows a proposal by Darwin (1871) that natural selection acted directionally, to endow people with more cooperative and less contentious personalities than their archaic ancestors or nearest living relatives, the chimpanzees. Rushton et al. (2008) conjectured that individuals high on the GFP left more progeny, since people prefer as mates, fellow workers, and leaders those who are altruistic, conscientious, and emotionally stable. People able to cooperate in groups were also more likely to win competitions and wars. The alternative to the GFP being substantive is that it results from artifacts of scale construction and from evaluative bias such as responding in a socially desirable manner. The main empirical impetus for identifying a GFP comes from the observation that the Big Five factors typically intercorrelate, despite claims that they are
Academy of Sciences of the Czech Republic Transformations enabling to construct limited-memory Broyden class methods

The Broyden class of quasi-Newton updates for inverse Hessian approximation are transformed to the formal BFGS update, which makes possible to generalize the well-known Nocedal method based on the Strang recurrences to the scaled limited-memory Broyden family, using the same number of stored vectors as for the limited-memory BFGS method. Two variants are given, the simpler of them does not require any additional matrix by vector multiplications. Numerical results indicate that this approach can save computational time.
Human-Centered Robot Navigation—Towards a Harmoniously Human–Robot Coexisting Environment

This paper proposes a navigation algorithm that considers the states of humans and robots in order to achieve harmonious coexistence between them. A robot navigation in the presence of humans and other robots is rarely considered in the field of robotics. When navigating through a space filled with humans and robots with different functions, a robot should not only pay attention to obstacle avoidance and goal seeking, it should also take into account whether it interferes with other people or robots. To deal with this problem, we propose several harmonious rules, which guarantee a safe and smooth navigation in a human-robot environment. Based on these rules, a practical navigation method-human-centered sensitive navigation (HCSN)-is proposed. HCSN considers the fact that both humans and robots have sensitive zones, depending on their security regions or on a human's psychological state. We model these zones as various sensitive fields with priorities, whereby robots tend to yield socially acceptable movements.
Clinical significance of imaging and histological characteristics of filum terminale in tethered cord syndrome.

OBJECT The pathophysiology of tethered cord syndrome (TCS) is uncertain; however, it has been suggested that fibrous and fatty elements within the filum terminale (FT) play a role. The objective of this study was to describe the radiological and histological features of the FT in TCS and determine if there are associations between those features and clinical outcomes, complications, and urodynamics. METHODS In this retrospective study, histological, MRI, and clinical data obtained in 293 patients with TCS who underwent FT transection were reviewed and analyzed in a multivariate analysis. RESULTS The median patient age was 4.9 years (range 0.3-64.3 years). On MRI, a fatty filum was present in 65% of patients and a thickened filum (> 2 mm) was seen in 45%. Histologically, the FT contained prominent fibrous tissue in 95%, nerve twigs in 79%, adipose tissue in 59%, and vascular tissue in 36%. Histological features associated with a thickened filum on MR images were adipose tissue (OR 3.5, p < 0.001), nerve twigs (OR 2.2, p = 0.028), and vascular tissue (OR 0.5, p = 0.025). Adipose tissue was associated with a conus level below the L2-3 disc space (OR 2.3, p = 0.031) and with a fatty filum on imaging (OR 9.8, p < 0.001). Nerve twigs were associated with abnormal urodynamics (OR 10.9, p = 0.049). The only variable predictive of clinical improvement was conus level; patients with conus levels caudal to L-2 were less likely to improve postoperatively (OR 0.3, p = 0.042). CONCLUSIONS Fibrous tissue was ubiquitous and may be important in the pathophysiology of TCS. Nerve twigs and adipose tissue were associated with abnormal urodynamics and low-lying coni, respectively. Although the majority of patients clinically improved, patients with normal conus levels had significantly better outcomes.
Subspace-based estimation of time delays and Doppler shifts

This paper considers the problem of estimating the time delays and Doppler shifts of a known waveform received via several distinct paths by an array of antennas. The general maximum likelihood estimator is presented, and is shown to require a 2d-dimensional nonlinear minimization, where d is the number of received signal reflections. Two alternative solutions based on signal and noise subspace fitting are proposed, requiring only a d-dimensional minimization. In particular, we show how to decouple the required search into a two-step procedure, where the delays are estimated and the Dopplers solved for explicitly. Initial conditions for the time delay search can be obtained by applying generalizations of the MUSIC and ESPRIT algorithms, which are also outlined in the paper. Simulation examples are included to illustrate the algorithms' performance relative to the Cramer-Rao bound.
Molecular and clinical profile of VWD in a large cohort of Chinese population: application of next generation sequencing and CNVplex® technique

Summary Von Willebrand disease (VWD), the most common inherited bleeding disorder, is characterised by a variable bleeding tendency, heterogeneous laboratory phenotype and race specific distribution of mutations. The present study aimed to determine the correlation of genotype and phenotype in 200 Chinese individuals from 90 unrelated families with VWD. Next generation sequencing (NGS) of the whole coding VWF, copy number analysis of VWF by CNVplex® technique as well as a comprehensive phenotypic assessment were carried out in all index patients (IPs). We identified putative mutations in all IPs except five mild type 1 (85/90, 94.4%). In total, 98 different mutations were detected, 62 (63.3% of which were reported for the first time (23 missense mutations, 1 regulatory mutation, 12 splice site mutations and 26 null mutations). Mutations p.Ser1506Leu and p.Arg1374His/Cys/ Ser were the most frequent mutations in 2A (33% of cases) and 2M VWD (67% of cases), respectively. In addition, mutation p.Arg816Trp was detected repeatedly in type 2N patients, while mutation p.Arg854Gln, extremely common in Caucasians, was not found in our cohort. Thirty-three patients had two or more putative mutations. Unlike most cases of type 1 and type 2 VWD, which were transmitted dominantly, we presented seven severe type 1, two type 2A and one type 2M with autosomal recessive inheritance. Here the phenotypic data of patients with novel mutations will certainly contribute to the better understanding of the molecular genetics of VWF-related phenotypes. Supplementary Material to this article is available online at www.thrombosis-online.com.
Missing-data imputation for solar irradiance forecasting in Thailand

This paper considers a solar irradiance forecasting using seasonal autoregressive integrated moving average models (SARIMA) which finds an application in solar power prediction for energy management. A time series prediction typically requires a complete set of historical data while the global horizontal irradiance (GHI) data in Thailand are frequently missing for consecutive days. This paper proposes a data-missing imputation technique using the mean value of GHI averaged over the data corresponding to the same weather type. The required weather classification consists of two steps: a seasonal segmentation based on detecting changes of monotonic properties of temperature and humidity time series, and a nonlinear support vector machine (SVM) that uses weather labels from the previous seasonal segmentation. Experimental results on the GHI data in Bangkok, Thailand shows that the proposed method significantly provides decreased imputation errors and leads to a better solar forecasting performance compared to other imputation techniques.
Structures and Functions of Selective Attention.

Abstract : A principle problem of neuropsychology is to relate the neural structures damaged in traumatic brain injury with their functions in the cognitive tasks of daily life. This lecture reviews evidence that elementary operations of cognition as defined by cognitive studies are the level at which the brain localizes its computations. Orienting of visual attention is used as a model task. The component facilitations and inhibitions in visual orienting are related to neural systems through the study of focal neurological lesions. Visual orienting is a part of a more general selective attention system that also involves orienting to language. Our ability to be aware of and to act upon target events depends upon the connections of posterior orienting these pathways in studies of focal changes in cerebral blood flow during performance of language tasks. Although we do not have a general analysis of the mental operations performed by these anterior systems, there is some evidence relating the dorsolateral prefrontal and areas of the medial surface to aspects of focal selection. One way to study the generality of the attentional system developed in this lecture is to examine putative deficits of attention in disorders such as schizophrenia, depression and closed head injury where the organic basis for the deficit is largely unknown. Our preliminary studies of schizophrenia are used to support the utility of the joint functional and structural analysis proposed here.
Bayesian methods for multiaspect target tracking in image sequences

In this paper, we introduce new algorithms for automatic tracking of multiaspect targets in cluttered image sequences. We depart from the conventional correlation filter/Kalman filter association approach to target tracking and propose instead a nonlinear Bayesian methodology that enables direct tracking from the image sequence incorporating the statistical models for the background clutter, target motion, and target aspect change. Proposed algorithms include 1) a batch hidden Markov model (HMM) smoother and a sequential HMM filter for joint multiframe target detection and tracking and 2) two mixed-state sequential importance sampling trackers based on the sampling/importance resampling (SIR) and the auxiliary particle filtering (APF) techniques. Performance studies show that the proposed algorithms outperform the association of a bank of template correlators and a Kalman filter in adverse scenarios of low target-to-clutter ratio and uncertainty in the true target aspect.
Reflections on the Relation Between Sex-Typed Behavior in Childhood and Sexual Orientation in Adulthood

SUMMARY This article reviews the empirical retrospective and prospective literature on the relation between sex-typed behavior in childhood and sexual orientation in adulthood, including a summary of the retrospective meta-analytic study by Bailey and Zucker (1995). Criticisms of the retrospective literature are addressed, followed by suggestions for additional research. Explanations for the linkage are summarized, followed by a discussion of clinical implications.
Multiple Importance Sampling

We introduce a technique called multiple importance sampling that can greatly increase the reliability and efficiency of Monte Carlo integration. It is based on the idea of using more than one sampling technique to evaluate a given integral, and combining the sample values in a provably good way. Our motivation is that most numerical integration problems in computer graphics are " difficult " , i.e. the integrands are discontinuous, high-dimensional, and/or singular. Given a problem of this type, we would like to design a sampling strategy that gives a low-variance estimate of the integral. This is complicated by the fact that the integrand usually depends on parameters whose values are not known at the time an integration strategy is designed (e.g. material properties, the scene geometry, etc.) It is difficult to design a sampling strategy that works reliably in this situation, since the integrand can take on a wide variety of different shapes as these parameters vary. In this chapter, we explore the general problem of constructing low-variance estimators by combining samples from several different sampling techniques. We do not construct new sampling techniques — we assume that these are given to us. Instead, we look for better ways to combine the samples, by computing weighted combinations of the sample values. We show that there is a large class of unbiased estimators of this type, which can be pa-rameterized by a set of weighting functions. Our goal is to find an estimator with minimum variance, by choosing these weighting functions appropriately. A good solution to this problem turns out to be surprisingly simple. We show how to 251
Haplotyping Populations by Pure Parsimony: Complexity of Exact and Approximation Algorithms

In this paper we address the pure parsimony haplotyping problem: Find a minimum number of haplotypes that explains a given set of genotypes. We prove that the problem is APX-hard and present a 2k- 1-approximation algorithm for the case in which each genotype has at most k ambiguous positions. We further give a new integer-programming formulation that has (for the first time) a polynomial number variables and constraints. Finally, we give approximation algorithms, not based on linear programming, whose running times are almost linear in the input size.