Miracle-dz/UniFAR-FTUs huggingface dataset:
Biologically inspired model simulating visual pathways and cerebellum function in human - Achieving visuomotor coordination and high precision movement with learning ability

In recent years, the interdisciplinary research between information science and neuroscience has been a hotspot. In this paper, based on recent biological findings, we proposed a new model to mimic visual information processing, motor planning and control in central and peripheral nervous systems of human. Main steps of the model are as follows: 1) Simulating "where" pathway in human: the Selective Search method is applied to simulate the function of human dorsal visual pathway to localize object candidates; 2) Simulating "what" pathway in human: a Convolutional Deep Belief Network is applied to simulate the hierarchical structure and function of human ventral visual pathway for object recognition; 3) Simulating motor planning process in human: habitual motion planning process in human is simulated, and motor commands are generated from the combination of control signals from past experiences; 4) Simulating precise movement control in human: calibrated control signals, which mimic the adjustment for movement from cerebellum in human, are generated and updated from calibration of movement errors in past experiences, and sent to the movement model to achieve high precision. The proposed framework mimics structures and functions of human recognition, visuomotor coordination and precise motor control. Experiments on object localization, recognition and movement control demonstrate that the new proposed model can not only accomplish visuomotor coordination tasks, but also achieve high precision movement with learning ability. Meanwhile, the results also prove the validity of the introduced mechanisms. Furthermore, the proposed model could be generalized and applied to other systems, such as mechanical and electrical systems in robotics, to achieve fast response, high precision movement with learning ability.
Basolateral proteinase‐activated receptor (PAR‐2) induces chloride secretion in M‐1 mouse renal cortical collecting duct cells

1 Using RT‐PCR, Northern blot analysis, and immunocytochemistry, we confirmed renal expression of proteinase‐activated receptor (PAR‐2) and demonstrated its presence in native renal epithelial and in cultured M‐1 mouse cortical collecting duct (CCD) cells. 2 We investigated the effects of a PAR‐2 activating peptide (AP), corresponding to the tethered ligand that is exposed upon trypsin cleavage, and of trypsin on M‐1 cells using patch‐clamp, intracellular calcium (fura‐2) and transepithelial short‐circuit current (ISC) measurements. 3 In single M‐1 cells, addition of AP elicited a concentration‐dependent transient increase in the whole‐cell conductance. Removal of extracellular Na+ had no effect while removal of Cl− prevented the stimulation of outward currents. The intracellular calcium concentration increased significantly upon application of AP while a Ca2+‐free pipette solution completely abolished the electrical response to AP. 4 In confluent monolayers of M‐1 cells, apical application of AP had no effect on ISC whereas subsequent basolateral application elicited a transient increase in ISC. This increase was not due to a stimulation of electrogenic Na+ absorption since the response was preserved in the presence of amiloride. 5 The ISC response to AP was reduced in the presence of the Cl− channel blocker diphenylamine‐2‐carboxylic acid on the apical side and abolished in the absence of extracellular Cl−. 6 Trypsin elicited similar responses to those to AP while application of a peptide (RP) with the reverse amino acid sequence of AP had no effect on whole‐cell currents or ISC. 7 In conclusion, our data suggest that AP or trypsin stimulates Cl− secretion by Ca2+‐activated Cl− channels in M‐1 CCD cells by activating basolateral PAR‐2.
Fast speaker adaptation using eigenspace-based maximum likelihood linear regression

This paper presents an eigenspace-based fast speaker adaptation approach which can improve the modeling accuracy of the conventional maximum likelihood linear regression (MLLR) techniques when only very limited adaptation data is available. The proposed eigenspace-based MLLR approach was developed by introducing a priori knowledge analysis on the training speakers via PCA, so as to construct an eigenspace for MLLR full regression matrices as well as to derive a set of bases called eigen-matrices. The full regression matrices for each outside speaker are then constrained to be located in the space spanned by the first K eigen-matrices. The proposed eigenspace-based regression matrices, serving as an initial estimate of the speaker-specific MLLR transformation, effectively reduces the number of free parameters, while precise modeling for the inter-dimensional correlation among the model parameters by full matrices was maintained. Experimental results showed that for supervised adaptation using adaptation data with a length of approximately 10 seconds, the proposed approach significantly outperformed the conventional MLLR approaches.
3-Nitropropionic Acid as a Tool to Study the Mechanisms Involved in Huntington’s Disease: Past, Present and Future

Huntington’s disease (HD) is an inheritable autosomal-dominant disorder whose causal mechanisms remain unknown. Experimental models have begun to uncover these pathways, thus helping to understand the mechanisms implicated and allowing for the characterization of potential targets for new therapeutic strategies. 3-Nitropropionic acid is known to produce in animals behavioural, biochemical and morphologic changes similar to those occurring in HD. For this reason, this phenotypic model is gaining attention as a valuable tool to mimick this disorder and further developing new therapies. In this review, we will focus on the past and present research of this molecule, to finally bring a perspective on what will be next in this promising field of study.
[2-(sec-Butyliminomethyl)quinoline]chlorido(η6-1-isopropyl-4-methylbenzene)ruthenium(II) hexafluoridophosphate

In the title compound, [RuCl(C10H14)(C14H16N2)]PF6, the aromatic ring of the isopropylmethylbenzene fragment shows an η6-arene coordination to the ruthenium atom. Its coordination sphere is completed by a chloride ligand and 2-(sec-butyliminomethyl)quinoline. The dihedral angle between the η6-arene ring and the quinoline Schiff base is 45.64 (9)°. The sec-butyl substituent and the PF6 − anion are disordered over two positions with ratios of 0.595 (11):0.405 (11) and 0.752 (8):0.248 (8), respectively.
Neonatal Leptin Exposure Specifies Innervation of Presympathetic Hypothalamic Neurons and Improves the Metabolic Status of Leptin-Deficient Mice

The paraventricular nucleus of the hypothalamus (PVH) consists of distinct functional compartments regulating neuroendocrine, behavioral, and autonomic activities that are involved in the homeostatic control of energy balance. These compartments receive synaptic inputs from neurons of the arcuate nucleus of the hypothalamus (ARH) that contains orexigenic agouti-related peptide (AgRP) and anorexigenic pro-opiomelanocortin (POMC) neuropeptides. The axon outgrowth from the ARH to PVH occurs during a critical postnatal period and is influenced by the adipocyte-derived hormone leptin, which promotes its development. However, little is known about leptin's role in specifying patterns of cellular connectivity in the different compartments of the PVH. To address this question, we used retrograde and immunohistochemical labeling to evaluate neuronal inputs onto sympathetic preautonomic and neuroendocrine neurons in PVH of leptin-deficient mice (Lepob/Lepob) exposed to a postnatal leptin treatment. In adult Lepob/Lepob mice, densities of AgRP- and α-melanocortin stimulating hormone (αMSH)-immunoreactive fibers were significantly reduced in neuroendocrine compartments of the PVH, but only AgRP were reduced in all regions containing preautonomic neurons. Moreover, postnatal leptin treatment significantly increased the density of AgRP-containing fibers and peptidergic inputs onto identified preautonomic, but not onto neuroendocrine cells. Neonatal leptin treatment neither rescued αMSH inputs onto neuroendocrine neurons, nor altered cellular ratios of inhibitory and excitatory inputs. These effects were associated with attenuated body weight gain, food intake and improved physiological response to sympathetic stimuli. Together, these results provide evidence that leptin directs cell type-specific patterns of ARH peptidergic inputs onto preautonomic neurons in the PVH, which contribute to normal energy balance regulation.
Antibacterial and anti-adherence effects of a plant extract mixture (PEM) and its individual constituent extracts (Psidium sp., Mangifera sp., and Mentha sp.) on single- and dual-species biofilms

Background Plant extracts mixture (PEM) and its individual constituent plant extracts(Psidium sp., Mangifera sp., Mentha sp.) are known to have an anti-adhering effect towards oral bacteria in the single-species biofilm. To date, the adhering ability of the early and late plaque colonisers (Streptococcus sanguinis and Streptococcus mutans) to PEM-treated experimental pellicle have not been investigated in dual-species biofilms. Methods Fresh leaves of these plants were used in the preparation of the respective aqueous extract decoctions. The minimum inhibitory concentration (MIC) of the extracts towards S. sanguinis ATCC BAA-1455 and S. mutans ATCC 25175 was determined using a two-fold serial microdilution method. The sum of fractional inhibitory concentration (ΣFIC) index of PEM and its constituent plant extracts was calculated using the MIC values of the plants. The minimum bactericidal concentration (MBC) of the plant extracts was also determined. The anti-adherence effect of the plant extracts (individually and mixed) was carried out by developing simulated S. sanguinis and S. mutans respectively in single- and dual-species of biofilms in the Nordini’s Artificial Mouth (NAM) model system in which the experimental pellicle was pretreated with the plant extract before bacterial inoculation. The bacterial population in the respective biofilms was quantified using ten-fold serial dilutions method and expressed as colony forming unit per ml (CFU/ml). The bacterial population was also viewed using Scanning Electron Microscope (SEM). All experiments were done in triplicate. Results The PEM compared with its respective constituent plants showed the lowest MIC towards S. sanguinis (3.81 mg/ml) and S. mutans (1.91 mg/ml) and exhibited a synergistic effect. The Psidium sp. (15.24 mg/ml) and, PEM and Psidium sp. (30.48 mg/ml) showed the lowest MBC towards S. sanguinis and S. mutans respectively. The anti-adherence effect of the PEM and its respective constituent plants (except Psidium sp.) was different for the two bacteria in the single-species biofilm. In the dual-species biofilms, PEM demonstrated similar anti-adherence effect towards S. sanguinis and S. mutans. The proportions of the bacterial population viewed under SEM appeared to be in agreement with the quantified population. Discussion The combination of the active constituents of the individual plant extracts in PEM may contribute to its low MIC giving rise to the synergistic effect. The different anti-adherence effect towards S. sanguinis and S. mutans in both single- and dual-species biofilms could be due to the different proportion of the active constituents of the extracts and the interaction between different bacteria. The better adhering ability of S. sanguinis towards the PEM-treated pellicle when present together with S. mutans in the dual-species biofilms may suggest the potential of PEM in controlling the balance between the early and late colonisers in biofilms.
XEvolve: an XML schema evolution framework

This paper presents XEvolve, a framework that unifies streaming validation of XML documents, and efficient testing of equivalence and inclusion of specifications for various XML schema languages. For these purposes, this framework relies on Visibly Pushdown Automata (VPA) as a unifying model for the various schema languages. Schemas are first translated into VPA; standard algorithms for VPA can be then used to validate documents as well as to test equivalence or inclusion of schemas. In general, inclusion and equivalence are tested in exponential-time. However, when the given specifications are provided as DTD or XSD, these tests have a polynomial-time complexity with respect to the automaton size. Moreover, in this case the memory foot-print of the validation does not depend on the size of the input document but only on its depth.
A cooperative multiscale phase-based disparity algorithm

In this paper, we propose a phase-based disparity estimation algorithm embedded in two different cooperative multiscale schemes. The first disparity integration scheme selects the best disparity as the one having the highest magnitude of the Gabor coefficient through the scales, while the second scheme assumes that the best disparity is the one for which the local spatial frequency is the nearest, in relative distance, from the peak tuning frequency of the filter. We show that both these schemes are efficient and roughly equivalent since they give the same results.
Characterizing the Business Cycles of Emerging Economies

Using the dating algorithm by Harding and Pagan (2002) on a quarterly database for 23 emerging market economies (EMEs) and 12 developed countries over the period 1980.Q1 - 2006.Q2, the authors proceed to characterize and compare the business cycle features of these two groups. They first find that recessions are deeper and more frequent among EMEs (especially, among LAC countries) and that expansions are more sizable and longer (especially, among East Asian countries). After this characterization, this paper explores the linkages between the cost of recessions (as measured by the average annual rate of output loss in the peak-to-trough phase of the cycle) and several country-specific factors. The main findings are: (a) adverse terms of trade shocks raises the cost of recessions in countries with a more open trade regime, deeper financial markets and, surprisingly, a more diversified output structure. (b) U.S. interest rate shocks seem to have a significant impact on the cost of recessions in East Asian countries. (c) Recessions tend to be deeper if they coincide with a sudden stop, but the effect tends to be mitigated in countries with deeper domestic credit markets. (d) Countries with stronger institutions tend to have less costly recessions.
On Optimizing the Arithmetic Precision of MCMC Algorithms

Markov Chain Monte Carlo (MCMC) is an ubiquitous stochastic method, used to draw random samples from arbitrary probability distributions, such as the ones encountered in Bayesian inference. MCMC often requires forbiddingly long runtimes to give a representative sample in problems with high dimensions and large-scale data. Field-Programmable Gate Arrays (FPGAs) have proven to be a suitable platform for MCMC acceleration due to their ability to support massive parallelism. This paper introduces an automated method, which minimizes the floating point precision of the most computationally intensive part of an FPGA-mapped MCMC sampler, while keeping the precision-related bias in the output within a user-specified tolerance. The method is based on an efficient bias estimator, proposed here, which is able to estimate the bias in the output with only few random samples. The optimization process involves FPGA pre-runs, which estimate the bias and choose the optimized precision. This precision is then used to reconfigure the FPGA for the final, long MCMC run, allowing for higher sampling throughputs. The process requires no user intervention. The method is tested on two Bayesian inference case studies: Mixture models and neural network regression. The achieved speedups over double-precision FPGA designs were 3.5x-5x (including the optimization overhead). Comparisons with a sequential CPU and a GPGPU showed speedups of 223x-446x and 16x-18x respectively.
Leadership in Decision-Making

We studied the relationship between transformational leadership, decision-making styles, and certain outcome using a sample of 98 officers of a large manufacturing organization in India. Results show that transformational leadership is related positively to rational style of decision-making and negatively to avoidant style, and that dependent style moderates the relationship between rational style and transformational leadership. Findings also reveal that perceived effectiveness of leader and follower's extra effort and satisfaction are related positively to rational style and negatively to avoidant style. Follower's intention to quit the job is positively related to intuitive and avoidant styles. Transformational leadership fully mediates the relationship between rational and avoidant styles and extra effort. Controlling for transformational leadership also results in a positive relationship between dependent style and intention to quit. Burns (1978) identified two types of leadership—transactional and transformational. Transactional leadership occurs when one person takes the initiative in making contact with others for the purpose of an exchange of something valued; that is, "leaders approach followers with an eye toward exchanging" (Burns, 1978: 4). Transformational leadership is based on more than the compliance of followers. It involves shifts in the beliefs, needs, and values of followers. According to Burns, "the result of transforming leadership is a relationship of mutual stimulation and elevation that converts followers into leaders and may convert leaders into moral agents" (Burns, 1978: 4). Transformational leadership occurs when leaders and followers raise one another to higher levels of motivation. Transformational leaders motivate followers to work for transcendental goals and self-actualising needs instead of working through a simple exchange relationship. Characteristics such as charisma, inspiration, intellectual stimulation, and individualized consideration distinguish transformational leadership from the other types of leadership (Bass, 1998; Bass, Avolio & Goodheim, 1987). Researchers also speak of charismatic leadership as being different from transformational leadership and referring mainly to leadership based on personal identification of followers with the leader. However, the distinction between these two concepts has not been clearly specified. Although some researchers have suggested that charismatic leadership is a component of transformational leadership (Bass, 1985), others have noted that the distinction between transformational and charismatic leadership is unclear. This lack of clear distinction is reflected in the flexible use of these terms by researchers.
Dynamic Minimization of Sentential Decision Diagrams

The Sentential Decision Diagram (SDD) is a recently proposed representation of Boolean functions, containing Ordered Binary Decision Diagrams (OBDDs) as a distinguished subclass. While OBDDs are characterized by total variable orders, SDDs are characterized more generally by vtrees. As both OBDDs and SDDs have canonical representations, searching for OBDDs and SDDs of minimal size simplifies to searching for variable orders and vtrees, respectively. For OBDDs, there are effective heuristics for dynamic reordering, based on locally swapping variables. In this paper, we propose an analogous approach for SDDs which navigates the space of vtrees via two operations: one based on tree rotations and a second based on swapping children in a vtree. We propose a particular heuristic for dynamically searching the space of vtrees, showing that it can find SDDs that are an order-of-magnitude more succinct than OBDDs found by dynamic reordering.
Construct and Criterion-Related Validation of a Measure of Emotional Reasoning Skills: A Two-Study Investigation

In a two-study investigation, the construct and criterion-related validities of the Test of Emotional Intelligence, an ability-based measure of emotional reasoning skills, were examined. In Study 1, as hypothesized, emotional reasoning skills were related to emotion recognition ability (i.e., as measured by Diagnostic Analysis of Nonverbal Accuracy), emotional empathy, and three measures of successful social functioning (i.e., social astuteness, interpersonal influence, and apparent sincerity) assessed by peers, after controlling for personality and occupational environment characteristics. In Study 2, results from a predictive validation study demonstrated that Emotional Intelligence explained additional variance in overall job performance ratings beyond general mental ability and personality traits. Contributions and implications of this research investigation, limitations, and directions for future research are discussed.
An intron in the YRA1 gene is required to control Yra1 protein expression and mRNA export in yeast

Yra1p is an essential and conserved mRNA export factor in yeast. Strikingly, removal of the intron from YRA1 causes a dominant‐negative growth phenotype and a concomitant inhibition of mRNA export. However, both defects are neutralized by replacement of the intron of YRA1 by a different intron. Significantly, Yra1p is overproduced in yeast when expressed from its intronless gene, but Yra1p levels are the same as the wild type when expressed from an intron‐containing YRA1 gene. Thus, an intron in YRA1 controls Yra1p expression and mRNA export.
Glycine, GABA and their transporters in pancreatic islets of Langerhans: evidence for a paracrine transmitter interplay

To elucidate the possible roles of the CNS neurotransmitters glycine and GABA in neuroendocrine paracrine signalling, we investigated their localizations, and those of their transport proteins, by confocal immunofluorescence and quantitative post-embedding immuno-electron microscopy in the pancreatic islets of Langerhans. We show that A-cells contain glycine in synaptic-like microvesicles as well as in secretory granules. A-cells express the macromolecules necessary to: (1) concentrate glycine within both organelle types before release (the vesicular GABA/glycine transporter VGAT=VIAAT); and to (2) take up the transmitter from the extracellular space (the plasma membrane glycine transporter GLYT2). Also B-cells have glycine in their microvesicles and granules, but the microvesicle/cytosol ratio is lower than in A-cells, consistent with the presence of GABA (which competes with glycine for vesicular uptake) in the cytosol at a much higher concentration in B-cells than in A-cells. Both A- and B-cells contain GABA in their microvesicles and secretory granules, and the membranes of the two organelle types contain VGAT in both cell types. A-cells as well as B-cells express a plasma membrane transporter GAT3 that mediates uptake of GABA. The localization of VGAT in the cores of A-cell secretory granules, and in the secretory granule membranes in both cell types, indicates novel aspects of the mechanisms for release of glycine and GABA. The discovery that both A- and B-cells possess the molecular machinery for the evoked release of both glycine and GABA from synaptic-like microvesicles suggests that both of the principal inhibitory transmitters in the brain participate in paracrine signalling in the pancreas.
Data Mining with Independent Component Analysis

Independent component analysis (ICA)/blind source separation (BSS) has received many attentions in neural network and signal processing area recent years. In this paper, we consider the data mining problem with ICA. The data model of under-complete ICA in data mining is given and then gives the most popular ICA algorithm-natural gradient algorithm (NGA). Several applications of data mining with ICA is considered, such as latent variable decompositions, multivariate time series analysis and prediction, text document data analysis, extracting hidden signals in satellite images, weather data mining and so on. All these discussions suggest the huge potential outlook of data mining using ICA. The other contribution of this paper is it contains several literature surveys on various aspects of data mining using ICA