Miracle-dz/UniFAR-FTUs huggingface dataset:
Effects of photoperiod on lactotrophs and on dopaminergic and 5-hydroxytryptaminergic neurones in bull calves.

This study was conducted to determine whether photoperiod-induced changes in serum concentrations of prolactin in cattle were associated with changes in activity of dopamine or 5-hydroxytryptamine (5-HT) neurones in the infundibulum/pituitary stalk and the secretion rate and number of lactotrophs in the anterior pituitary gland. Sixteen prepubertal bull calves (approximately 8 weeks of age) were divided into two groups. One group of eight was maintained on a photoperiod of 8 h light: 16 h darkness (8L:16D) and the other group was exposed to 16L:8D for 4 weeks. At this time calves were injected with a decarboxylase inhibitor (m-hydroxybenzylhydrazine dihydrochloride, NSD 1015) which blocks the conversion of dihydroxyphenylalanine (DOPA) to dopamine and of 5-hydroxytryptophan (5-HTP) to 5-HT. Calves were killed with pentobarbital 15 min later. Accumulations of DOPA and 5-HTP in selected brain regions were used as indices of activity of dopamine and 5-HT neurones respectively. Secretory rate and number of prolactin-secreting lactotrophs were determined by reverse haemolytic plaque assay. Relative to calves exposed to 8L:16D, exposure to 16L:8D increased serum concentrations of prolactin by eightfold, anterior pituitary gland weight by 23%, release of prolactin from pituitary explants by 57% and the area of the plaque for prolactin-secreting lactotrophs by 70%. There was no difference in the rates of accumulation of DOPA and 5-HTP in the infundibulum/pituitary stalk of animals exposed to 4 weeks of 16L:8D or 8L:16D. (ABSTRACT TRUNCATED AT 250 WORDS)
Compensation of Amplitude Imbalance and Imperfect Quadrature in Resolver Signals for PMSM Drives

This paper proposes a compensation algorithm for reducing the position errors that are due to two nonideal output signals of a resolver in the vector control of a permanent magnet synchronous motor. Practically, a resolver generates periodic position errors because of the amplitude imbalance and imperfect quadrature between the two output signals of the resolver. As a result, the dq-axis currents of the synchronous reference frame have ripple components that are twice the stator fundamental frequency. In this paper, the effects of the position errors are analyzed on the basis of the synchronous dq-axis current equations, including the position errors. The d-axis current is directly used as the input signal of the proposed compensator to estimate the position errors by using a simple integral operation according to the rotor position, because the d-axis current is typically constant or zero. The proposed algorithm additionally considers the bandwidth effect of the closed current control loop to estimate the exact error signals according to the variation of the rotor speed. Therefore, the proposed algorithm does not need any additional hardware and much computation time. Furthermore, this algorithm can be applied to both the steady and transient states. The experimental results verify the effectiveness of the proposed algorithm.
Human Brain Regions Involved in Visual Categorization

Categorization of dot patterns is a frequently used paradigm in the behavioral study of natural categorization. To determine the human brain regions involved in categorization, we used Positron Emission Tomography to compare regional Cerebral Blood Flow patterns in two tasks employing patterns that consisted of nine dots. In the categorization task, subjects categorized novel exemplars of two categories, generated by distorting two prototypes, and other random dot patterns. In the control task, subjects judged the position of similarly distorted patterns. Each task was presented at two matched levels of difficulty. Fixation of the fixation target served as baseline condition. The categorization task differentially activated the orbitofrontal cortex and two dorsolateral prefrontal regions. These three prefrontal regions were equally weakly active in the position discrimination task and the baseline condition. The intraparietal sulcus was activated in both tasks, albeit significantly less in the position discrimination than in the categorization task. A similar activation pattern was present in the neostriatum. Task difficulty had no effect. These functional imaging results show that the dot-pattern categorization task strongly engages prefrontal and parietal cortical areas. The activation of prefrontal cortex during visual categorization in humans agrees with the recent finding of category-related responses in macaque prefrontal neurons.
Oger: modular learning architectures for large-scale sequential processing

Oger (OrGanic Environment for Reservoir computing) is a Python toolbox for building, training and evaluating modular learning architectures on large data sets. It builds on MDP for its modularity, and adds processing of sequential data sets, gradient descent training, several crossvalidation schemes and parallel parameter optimization methods. Additionally, several learning algorithms are implemented, such as different reservoir implementations (both sigmoid and spiking), ridge regression, conditional restricted Boltzmann machine (CRBM) and others, including GPU accelerated versions. Oger is released under the GNU LGPL, and is available from http: //organic.elis. ugent.be/oger.
Detecting image points of general imbalance

Imbalance oriented selection scheme was recently proposed to detect stable image points in weakly or sparsely textured images. The scheme chooses image points whose one-pixel-wide directional intensity variations can be clustered into two imbalanced classes as candidates. In this paper, we propose general imbalance decided by multi-pixel-wide directional intensity variations. We present a case study of general imbalanced points in road sign images, which demonstrates the good potential of general imbalanced points.
MOOC visual analytics: Empowering students, teachers, researchers, and platform developers of massively open online courses

Along with significant opportunities, Massively Open Online Courses (MOOCs) provide major challenges to students (keeping track of course materials and effectively interacting with teachers and fellow students), teachers (managing thousands of students and supporting their learning progress), researchers (understanding how students interact with materials and each other), and MOOC platform developers (supporting effective course design and delivery in a scalable way). This article demonstrates the use of data analysis and visualization as a means to empower students, teachers, researchers, and platform developers by making large volumes of data easy to understand. First, we introduce the insight needs of different stakeholder groups. Second, we compare the wide variety of data provided by major MOOC platforms. Third, we present a novel framework that distinguishes visualizations by the type of questions they answer. We then review the state of the art MOOC visual analytics using a tabulation of stakeholder needs versus visual analytics workflow types. Finally, we present new data analysis and visualization workflows for statistical, geospatial, and topical insights. The workflows have been optimized and validated in the Information Visualization MOOC (IVMOOC) annually taught at Indiana University since 2013. All workflows, sample data, and visualizations are provided at http://cns.iu. edu/2016-MOOCVis.html.
Image Gathering using Both Color and Texture Features

This paper has a further exploration and study of visual feature extraction. According to the HSV (Hue, Saturation, Value) color space, the work of color feature extraction is finished, the process is as follows: quantifying the color space in non-equal intervals, constructing one dimension feature vector and representing the color feature by cumulative histogram. Similarly, the work of texture feature extraction is obtained by using gray-level co-occurrence matrix (GLCM) or color co-occurrence matrix (CCM). Through the quantification of HSV color space, we combine color features and GLCM as well as CCM separately. Depending on the former, image retrieval based on multi-feature fusion is achieved by using normalized Euclidean distance classifier. Through the image retrieval experiment, indicate that the use of color features and texture based on CCM has obvious advantage. I. Introduction The need for efficient content-based image retrieval has increased tremendously in many application areas such as biomedicine, military, commerce, education, and web image classification and searching. Currently, rapid and effective searching for desired images from large-scale image database becomes an important and challenging research topic [1,2]. Content-based Image Retrieval (CBIR) technology overcomes the defects of traditional text-based image retrieval technology, such as heavy workload and strong subjectivity. It makes full use of image content features (colour, texture, shape, etc.), which are analysed and extracted automatically by computer to achieve the effective retrieval [3,4]. Using a single feature for image retrieval can not be a good solution for the accuracy and efficiency. High-dimensional feature will reduce the query efficiency; low-dimensional feature will reduce query accuracy, so it may be a better way using multi features for image retrieval. Colour and texture are the most important visual features. Firstly, we discuss the colour and texture features separately. On this basis, a new method using integrated features is provided, and experiment is done on the real images, satisfactory result is achieved, verify the superiority of integrated feature than the single feature.
Leadership for Literacy: A Framework for Policy and Practice

This article provides a framework for practitioners and policy actors that links leadership and literacy. The focus is on the specification of research-anchored scaffolding that can assist school administrators and policy players in their quest to strengthen student performance in reading. The framework itself isbuilt frommaterial culled from4 lines ofempirical investigation: quality instruction, effective reading programs, school effects, and educational leadership. The analysis represents an important dimension of what we refer to as second-generation work on instructional leadership.
Linearized and Single-Pass Belief Propagation

How can we tell when accounts are fake or real in a social network? And how can we tell which accounts belong to liberal, conservative or centrist users? Often, we can answer such questions and label nodes in a network based on the labels of their neighbors and appropriate assumptions of homophily ("birds of a feather flock together") or heterophily ("opposites attract"). One of the most widely used methods for this kind of inference is Belief Propagation (BP) which iteratively propagates the information from a few nodes with explicit labels throughout a network until convergence. A well-known problem with BP, however, is that there are no known exact guarantees of convergence in graphs with loops. This paper introduces Linearized Belief Propagation (LinBP), a linearization of BP that allows a closed-form solution via intuitive matrix equations and, thus, comes with exact convergence guarantees. It handles homophily, heterophily, and more general cases that arise in multi-class settings. Plus, it allows a compact implementation in SQL. The paper also introduces Single-pass Belief Propagation (SBP), a localized (or "myopic") version of LinBP that propagates information across every edge at most once and for which the final class assignments depend only on the nearest labeled neighbors. In addition, SBP allows fast incremental updates in dynamic networks. Our runtime experiments show that LinBP and SBP are orders of magnitude faster than standard BP, while leading to almost identical node labels.
Significance of white matter high intensity lesions as a predictor of stroke from arteriolosclerosis

Objectives: To determine whether the extent of white matter high intensity lesions (WML) on magnetic resonance imaging (MRI) is an independent predictor of risk for stroke from arteriolosclerosis, and whether serial evaluation of WML can be used to identify patients who are at risk of strokes. Methods: Prospective follow up with serial MRI scans was done in 89 patients who were either diagnosed as having symptomatic lacunar infarcts or were stroke-free, neurologically normal individuals with headache or dizziness. None had significant stenosis of major cerebral arteries or atrial fibrillation. Multivariable analysis with the Cox proportional hazards model was used to test the predictive value for subsequent stroke of risk factor status at entry and during follow up, lacunar infarction, and the extent of WML (scored from 0 to 16) on the baseline scans. Results: During follow up (mean (SD), 51 (19) months), seven strokes occurred (five lacunar infarcts and two haemorrhages): four in nine patients with severe WML (score 9–16), and three in 40 patients with mild WML (score 1–8) (log-rank test; p < 0.005). None of 40 patients without WML experienced stroke. The extent of WML was an independent predictor of subsequent stroke (relative risk for a 1 point score increase, 1.60; 95% confidence interval, 1.02 to 2.54; p < 0.05). In three strokes among 80 patients without severe WML, two occurred in four patients with an increase in WML score during follow up, and one occurred in the other 76 patients without an increased score (p < 0.0001). Conclusions: Severe WML at baseline is an independent predictor of risk for stroke from arteriolosclerosis, while progression of WML during follow up may be associated with subsequent stroke in patients with initially mild WML.
Human friendship estimation model for communication robots

Abstract Based on the analysis of non-verbal inter-human interaction, this paper proposes a model for estimating human friendships in the presence of a humanoid robot. Our previous study in an elementary school provided rich video data of two months of inter-human interaction in the presence of a humanoid robot. Such data are particularly useful for developing a robot’s social ability: a friendship estimation capability. We analyzed the video based on an observation method to analyze the interaction among children and the robot. From their non-verbal interactions, several important factors for friendship estimation were retrieved, including touch, gaze, co-presence, and distance. Gender was also considered a factor in the model, since gender differences were observed in non-verbal interactions. The model discriminated between friendly and non-friendly relationships among the children with 74.5% accuracy for boys and 83.8% for girls.
Ethno-religious Background as a Determinant of Educational and Occupational Attainment in Britain

This article seeks to contribute to a newly growing literature on religious differences in education and the labour market, and seeks to answer two main questions: To what extent does education have similar impacts on occupational attainment across ethnic and faith groups? To what extent are these ethnic differences due to religious affiliation and/or skin colour? The data used in this study have been obtained from the 2001 UK Census.The data suggest that ethnicity per se is not an important factor but operates as a proxy, and, as this article shows, skin colour and culture (religion) are to a greater extent arguably the main mechanisms that operate to reinforce disadvantage among some groups or to facilitate social mobility amongst others. The direction and strength of their influence appears to be dependent on whether the specific culture is seen as compatible or `alien' in relation to the hegemonic culture.
Photography

In this article paper, the author presents her own experience of working as a photographer, using photography (or, more broadly, a photographic session) as an action that facilitates coping with the experience of loss. The article describes two types of bereavement sessions: the Memoir project and the Trauer project. In the first of the projects, the author took photographs and helped to conduct the session. In the latter case, she was both a performer and photographer. Both sessions had the intended effect and fit into the theoretical framework to which the author refers in the paper.
Discovering service dependencies in mobile ad hoc networks

The combination of service-oriented applications, with their run-time service binding, and mobile ad hoc networks, with their transient communication topologies, brings a new level of complex dynamism to the structure and behavior of software systems. This complexity challenges our ability to understand the dependence relationships among system components when performing analyses such as fault localization and impact analysis. Current methods of dynamic dependence discovery, developed for use in fixed networks, assume that dependencies change slowly. Moreover, they require relatively long monitoring periods as well as substantial memory and communication resources, which are impractical in the mobile ad hoc network environment. We describe a new method, designed specifically for this environment, that allows the engineer to trade accuracy against cost, yielding dynamic snapshots of dependence relationships. We evaluate our method in terms of the accuracy of the discovered dependencies.
Optimization method for obtaining nearest-neighbour DNA entropies and enthalpies directly from melting temperatures

MOTIVATION Free energy nearest-neighbour (NN) thermodynamics is widely used in DNA biochemistry, ranging from the calculation of melting temperatures to the prediction of secondary structures. Methods to calculate NN parameters require the knowledge of total sequence entropies and enthalpies, which are not always available. RESULTS Here, we implement and test a new melting temperature optimization method where we obtain the NN parameters directly from the temperatures. In this way, we bypass the constraints imposed by total sequence entropies and enthalpies. This enabled us to calculate the missing NN entropies and enthalpies for some published datasets, including salt-dependent parameters. Also this allowed us to combine 281 sequences from different types of melting temperature data for which we derived a new set of NN parameters, which have a smaller uncertainty and an improved predictive power. AVAILABILITY AND IMPLEMENTATION C++ source code and compiled binaries for several Linux distributions are available from https://sites.google. com/site/geraldweberufmg/vargibbs and from OpenSuse build service at https://build.opensuse. org/package/show/home:drgweber/VarGibbs. The software package contains scripts and data files to reproduce all results presented here.
Nanodiamonds as novel nanomaterials for biomedical applications: drug delivery and imaging systems

Detonation nanodiamonds (NDs) are emerging as delivery vehicles for small chemical drugs and macromolecular biotechnology products due to their primary particle size of 4 to 5 nm, stable inert core, reactive surface, and ability to form hydrogels. Nanoprobe technology capitalizes on the intrinsic fluorescence, high refractive index, and unique Raman signal of the NDs, rendering them attractive for in vitro and in vivo imaging applications. This review provides a brief introduction of the various types of NDs and describes the development of procedures that have led to stable single-digit-sized ND dispersions, a crucial feature for drug delivery systems and nanoprobes. Various approaches used for functionalizing the surface of NDs are highlighted, along with a discussion of their biocompatibility status. The utilization of NDs to provide sustained release and improve the dispersion of hydrophobic molecules, of which chemotherapeutic drugs are the most investigated, is described. The prospects of improving the intracellular delivery of nucleic acids by using NDs as a platform are exemplified. The photoluminescent and optical scattering properties of NDs, together with their applications in cellular labeling, are also reviewed. Considering the progress that has been made in understanding the properties of NDs, they can be envisioned as highly efficient drug delivery and imaging biomaterials for use in animals and humans.
The distribution of the permanent paralysis in the lower limb in poliomyelitis; a clinical and pathological study.

1. The distribution of the permanent paresis and paralysis in the muscles of 203 lower limbs affected by poliomyelitis is analysed and related to the destruction of motor nerve cells in the grey matter of the lumbo-sacral cord. 2. The tibialis anterior and tibialis posterior and the long muscles of the toes are more often paralysed than paretic; these muscles are innervated by short motor cell columns. Muscles such as the hip flexors and hip adductors that are more often paretic than paralysed are innervated by long cell columns. 3. Muscles innervated by the upper lumbar spinal segments are more frequently affected than those innervated by the sarcal segments. This agrees with the segmental incidence of motor cell destruction found in poliomyelitic spinal cords. 4. Each muscle or muscle group is associated in paralysis with other specific muscles. For instance, the long toe extensors with the peronei and the calf muscles (triceps surae) with the biceps femoris. Associated muscles are innervated by adjacent motor cell columns. The probability of recovery in a paralysed muscle can be determined by reference to the degree of involvement in its associated muscles. 5. The distribution of the paralysis in an individual lower limb is determined by the site and size of foci of motor cell destruction. The cell loss in certain common patterns of paralysis is described. 6. The practical application of these findings is discussed.
holE, the gene coding for the theta subunit of DNA polymerase III of Escherichia coli: characterization of a holE mutant and comparison with a dnaQ (epsilon-subunit) mutant

DNA polymerase III holoenzyme is a multiprotein complex responsible for the bulk of chromosomal replication in Escherichia coli and Salmonella typhimurium. The catalytic core of the holoenzyme is an alpha epsilon theta heterotrimer that incorporates both a polymerase subunit (alpha; dnaE) and a proofreading subunit (epsilon; dnaQ). The role of theta is unknown. Here, we describe a null mutation of holE, the gene for theta. A strain carrying this mutation was fully viable and displayed no mutant phenotype. In contrast, a dnaQ null mutant exhibited poor growth, chronic SOS induction, and an elevated spontaneous mutation rate, like dnaQ null mutants of S. typhimurium described previously. The poor growth was suppressible by a mutation affecting alpha which was identical to a suppressor mutation identified in S. typhimurium. A double mutant null for both holE and dnaQ was indistinguishable from the dnaQ single mutant. These results show that the theta subunit is dispensable in both dnaQ+ and mutant dnaQ backgrounds, and that the phenotype of epsilon mutants cannot be explained on the basis of interference with theta function.