Miracle-dz/UniFAR-FTUs huggingface dataset:
Training Excitatory-Inhibitory Recurrent Neural Networks for Cognitive Tasks: A Simple and Flexible Framework

The ability to simultaneously record from large numbers of neurons in behaving animals has ushered in a new era for the study of the neural circuit mechanisms underlying cognitive functions. One promising approach to uncovering the dynamical and computational principles governing population responses is to analyze model recurrent neural networks (RNNs) that have been optimized to perform the same tasks as behaving animals. Because the optimization of network parameters specifies the desired output but not the manner in which to achieve this output, “trained” networks serve as a source of mechanistic hypotheses and a testing ground for data analyses that link neural computation to behavior. Complete access to the activity and connectivity of the circuit, and the ability to manipulate them arbitrarily, make trained networks a convenient proxy for biological circuits and a valuable platform for theoretical investigation. However, existing RNNs lack basic biological features such as the distinction between excitatory and inhibitory units (Dale’s principle), which are essential if RNNs are to provide insights into the operation of biological circuits. Moreover, trained networks can achieve the same behavioral performance but differ substantially in their structure and dynamics, highlighting the need for a simple and flexible framework for the exploratory training of RNNs. Here, we describe a framework for gradient descent-based training of excitatory-inhibitory RNNs that can incorporate a variety of biological knowledge. We provide an implementation based on the machine learning library Theano, whose automatic differentiation capabilities facilitate modifications and extensions. We validate this framework by applying it to well-known experimental paradigms such as perceptual decision-making, context-dependent integration, multisensory integration, parametric working memory, and motor sequence generation. Our results demonstrate the wide range of neural activity patterns and behavior that can be modeled, and suggest a unified setting in which diverse cognitive computations and mechanisms can be studied.
Novel hydroxyl naphthoquinones with potent Cdc25 antagonizing and growth inhibitory properties

Cdc25 phosphatases are important in cell cycle control and activate cyclin-dependent kinases (Cdk). Efforts are currently under way to synthesize specific small-molecule Cdc25 inhibitors that might have anticancer properties. NSC 95397, a protein tyrosine phosphatase antagonist from the National Cancer Institute library, was reported to be a potent Cdc25 inhibitor. We have synthesized two hydroxyl derivatives of NSC 95397, monohydroxyl-NSC 95397 and dihydroxyl-NSC 95397, which both have enhanced activity for inhibiting Cdc25s. The new analogues, especially dihydroxyl-NSC 95397, potently inhibited the growth of human hepatoma and breast cancer cells in vitro. They influenced two signaling pathways. The dual phosphorylation of extracellular signal-regulated kinase 1/2 (ERK1/2) was induced, likely due to inhibition of the ERK phosphatase activity in Hep 3B cell lysate but not the dual specificity ERK phosphatase MKP-1. They also inhibited Cdc25 enzymatic activities and induced tyrosine phosphorylation of the Cdc25 target Cdks. Addition of hydroxyl groups to the naphthoquinone ring thus enhanced the potency of NSC 95397. These two new compounds may be useful probes for the biological functions of Cdc25s and have the potential for disrupting the cell cycle of growing tumor cells.
The intelligent voice-interactive interface

“Put That There” is a voice and gesture interactive system implemented at the Architecture Machine Group at MIT. It allows a user to build and modify a graphical database on a large format video display. The goal of the research is a simple, conversational interface to sophisticated computer interaction. Natural language and gestures are used, while speech output allows the system to query the user on ambiguous input. This project starts from the assumption that speech recognition hardware will never be 100% accurate, and explores other techniques to increase the usefulness (i.e., the “effective accuracy”) of such a system. These include: redundant input channels, syntactic and semantic analysis, and context-sensitive interpretation. In addition, we argue that recognition errors will be more tolerable if they are evident sooner through feedback and easily corrected by voice.
Javascript to Scheme Compilation

This paper presents Jsigloo, a Bigloo frontend compiling Ja vascript to Scheme. Javascript and Scheme share many features: both a re dynamically typed, they feature closures and allow for func tions as first class citizens. Despite their similarities it is not always easy to map Javascript constructs to efficient Scheme code, a n in this paper we discuss the non-obvious transformations that needed special attention. Even though optimizations were supposed to be done by Bigloo the chosen Javascript-Scheme mapping made several analyse s ineffective and some optimizations are hence implemented in Jsi gloo. We illustrate the opportunities Bigloo missed and show how t he additional optimizations improve the situation.
Experimental evaluation of capacitance value; to self-excite the induction motor operating as generator in wind energy conversion

This paper explains a method to calculate the capacitance value of a 3-Ø cage induction motor working as a generator in the self-excited mode of operation. The synchronous impedance test method has been reviewed. The capacitance value is determined from the manufacturer data. The effect of voltage variation with different capacitances has been evaluated at constant speed. Performance of self-excited asynchronous generator (SEASG) with the capacitance (calculated value) is evaluated experimentally. Simulation study of the SEASG is done using power system tool box in Mat Lab/Simulink.
Limits of Calcium Clearance by Plasma Membrane Calcium ATPase in Olfactory Cilia

Background In any fine sensory organelle, a small influx of Ca2+ can quickly elevate cytoplasmic Ca2+. Mechanisms must exist to clear the ciliary Ca2+ before it reaches toxic levels. One such organelle has been well studied: the vertebrate olfactory cilium. Recent studies have suggested that clearance from the olfactory cilium is mediated in part by plasma membrane Ca2+-ATPase (PMCA). Principal Findings In the present study, electrophysiological assays were devised to monitor cytoplasmic free Ca2+ in single frog olfactory cilia. Ca2+ was allowed to enter isolated cilia, either through the detached end or through membrane channels. Intraciliary Ca2+ was monitored via the activity of ciliary Ca2+-gated Cl− channels, which are sensitive to free Ca2+ from about 2 to 10 µM. No significant effect of MgATP on intraciliary free Ca2+ could be found. Carboxyeosin, which has been used to inhibit PMCA, was found to substantially increase a ciliary transduction current activated by cyclic AMP. This increase was ATP-independent. Conclusions Alternative explanations are suggested for two previous experiments taken to support a role for PMCA in ciliary Ca2+ clearance. It is concluded that PMCA in the cilium plays a very limited role in clearing the micromolar levels of intraciliary Ca2+ produced during the odor response.
A Dynamic Stochastic Heuristical Algorithm for Flexible Workload Management *

An increasing number of real-time applications, related to multimedia, adaptive control and videoconference, require greater flexible scheduling than classical real-time systems permit. This paper proposes a novel approach that generates dynamically the upper bounds and the lower bounds of tasks to manage overload in a real-time system. And then we design a very simple stochastic heuristical algorithm to maximize the weighted reward of task set, and analyze the performance of this algorithm. The proposed scheme provides a very simple and efficient mechanism to handle overload in linear time complexity in the presence of rate constraints
How to Sample and Reconstruct Curves With Unusual Features

This work generalizes the ideas in the NearestNeighbor-Crust algorithm by Dey and Kumar. It allows to reconstruct smooth closed curves from "samples with " � 0.48 which is a big improvement compared to the original bound. Further generalization leads to a new algorithm which reconstructs arbitrary curves (open, closed, smooth, with corners, with intersections) in any dimension. The algorithm works well in practice but lacks a nice sampling condition comparable to the well-known "-sampling condition. This shortcoming is posed as an open problem.
An SVM based classification method for EEG signals

In this paper, a brain/computer interface is proposed. The aim of this work is the recognition of the will of a human being, without the need of detecting the movement of any muscle. Disabled people could take, of course, most important advantages from this kind of sensor system, but it could also be useful in many other situations where arms and legs could not be used or a brain-computer interface is required to give commands. In order to achieve the above results, a prerequisite has been that of developing a system capable of recognizing and classifying four kind of tasks: thinking to move the right hand, thinking to move the left hand, performing a simple mathematical operation, and thinking to a carol. The data set exploited in the training and test phase of the system has been acquired by means of 61 electrodes and it is formed by time series subsequently transformed to the frequency domain, in order to obtain the power spectrum. For every electrode we have 128 frequency channels. The classification algorithm that we used is the Support Vector Machine (SVM).
The Positive Influence of Attachment to Power-symbol Product

When consumers are attached to a certain brand, positive assets like self-efficacy and life satisfaction are formed. As these positive assets may have a positive influence on brand supportive behavior, forming such assets is an important task. Therefore, the purpose of the study is to examine how power-symbol products form positive assets like self-efficacy and life satisfaction and the influence of these positive assets on brand supportive behavior when the consumer feels economic powerlessness. The study measured the variables like attachment to the power-symbol product, economic powerlessness, self-efficacy, life satisfaction, and brand supportive behavior, and proved the relationship between these variables through the structural equation model. in the states of powerlessness. The analysis showed that the to the power-symbol product positive on self-efficacy and the of life. Here, self-efficacy and satisfaction of life were having a positive influence on brand supportive behavior. The study was able to confirm that hypotheses 1~4 were being supported through these findings.
2 Wavelets and wavelet thresholding 2 . 1 Wavelets

We use cumulants to derive Bayesian credible intervals for wavelet regression estimates. The first four cumulants of the posterior distribution of the estimates are expressed in terms of the observed data and integer powers of the mother wavelet functions. These powers are closely approximated by linear combinations of wavelet scaling functions at an appropriate finer scale. Hence, a suitable modification of the discrete wavelet transform allows the posterior cumulants to be found efficiently for any given data set. Johnson transformations then yield the credible intervals themselves. Simulations show that these intervals have good coverage rates, even when the underlying function is inhomogeneous, where standard methods fail. In the case where the curve is smooth, the performance of our intervals remains competitive with established nonparametric regression methods.
Migrating Information Retrieval from the Graduate to the Undergraduate Curriculum

As reliance on the web in general and web search engines in particular expands, student interest in the domain of information retrieval is increasing. In response to this increased interest, at the Illinois Institute of Technology, we recently extended our computer science undergraduate curriculum to include an introductory course in information retrieval. Instead of simply understanding how to build applications using information retrieval tools, our students build these tools and learn the relevant algorithms implemented in these tools. Our syllabus includes a hands-on lab setting where students use the tools they build to perform experiments that could ultimately extend the field. Also as part of our course, we administered preand post-questionnaires to assess how much knowledge (of the topics included in the course) the students thought they had prior to the start of the course, their expectations for the course, and how well these expectations were met. We present results that indicate a statistically significant improvement in the students' selfreported knowledge in information retrieval. Student final exam scores substantiate these results.
INSULIN GENE VARIABLE NUMBER OF TANDEM REPEAT GENOTYPE, EARLY GROWTH AND GLUCOSE METABOLISM IN ADULT LIFE

he predisposition to type 2 diabetes is programmed early in life and genotypes promoting survival during nutritional adversity could increase the risk of type 2 diabetes. The insulin gene and variation in the insulin gene variable number of tandem repeats (VNTR) polymorphism has been suggested to modify birth size and diabetes susceptibility. Materials and Methods: We assessed the association between the insulin gene VNTR genotypes, early growth and glucose and insulin metabolism in adult life in 488 subjects participating in the Helsinki Birth Cohort Study. Results: Body size at birth did not differ significantly between the INS VNTR genotypes. One additional type III allele was associated with a 13 g decrease (95% CI -55 to 81 g; p=0.7) in birth weight. Fasting glucose concentration was highest in the carriers of the III/III genotype. The cumulative incidence of type 2 diabetes did not differ between the genotypes. Interactions between birth size and insulin VNTR genotype in relation to fasting glucose (p for interaction = 0.08 for birth weight, p=0.05 for birth length) and 2-hour insulin (p for interaction =0.04) were observed. Conclusions: These interactions between body size at birth and genotype reflect interactions between the insulin VNTR gene and the intrauterine environment. Our findings are consistent with the hypothesis of developmental plasticity, where one genotype can give rise to different phenotypes dependent on the early environment.
An Automatic System for the Analysis and Classification of Human Atrial Fibrillation Patterns from Intracardiac Electrograms

This paper presents an automatic system for the analysis and classification of atrial fibrillation (AF) patterns from bipolar intracardiac signals. The system is made up of: 1) a feature- extraction module that defines and extracts a set of measures potentially useful for characterizing AF types on the basis of their degree of organization; 2) a feature-selection module (based on the Jeffries-Matusita distance and a branch and bound search algorithm) identifying the best subset of features for discriminating different AF types; and 3) a support vector machine technique-based classification module that automatically discriminates the AF types according to the Wells' criteria. The automatic system was applied on 100 intracardiac AF signal strips and on a selection of 11 representative features, demonstrating: a) the possibility to properly identify the most significant features for the discrimination of AF types; b) higher accuracy (97.7% using the seven most informative features) than the traditional maximum likelihood classifier; and c) effectiveness in AF classification also with few training samples (accuracy = 88.3% with only five training signals). Finally, the system identifies a combination of indices characterizing changes of morphology of atrial activation waves and perturbation of the isoelectric line as the most effective in separating the AF types.
Molecular Simulation Study of the Vapor–Liquid Interfacial Behavior of a Dimer-forming Associating Fluid

Grand-canonical transition-matrix Monte Carlo simulation is applied to analyze the effect of molecular association on the vapor–liquid coexistence and interfacial behavior of square-well based dimerizing fluids. Finite-size scaling techniques are implemented in conjunction with histogram reweighting to determine the infinite-system surface tension from a series of finite-size simulations. The effect of strength of association and size of association site on coexistence densities, pressure, surface tension, and monomer fraction is presented. Some qualitative features of the dependence of monomer fraction and surface tension on association strength are found to disagree with behavior expected from previous studies using the statistical associating fluid theory (SAFT). Comparison with experimental data shows that molecular models must incorporate an explicit association interaction in order to describe the surface-tension behavior of a real dimerizing fluid (acetic acid).
Production and Quality Evaluation of Ogi Produced from Fermented Maize and Horse Eye Bean (Mucuna urens)

In developing countries, particularly sub-Saharan Africa, infant complementary foods are grossly inadequate, the enrichment of maize with horse eye beans is a veritable approach for combating the effects of protein malnutrition. Yellow maize variety and horse eye bean were processed into flour, mixed in the ratios 95:5, 90:10, 85:15 and 100% maize flour and proximate, functional, pasting, antinutritional and sensory properties were evaluated using standard methods. Results of Proximate analysis, functional analysis, pasting characteristics, anti-nutritional analysis and sensory evaluation showed protein, crude fibre and ash increase with an increase in ratio of horse eye bean flour addition. Proximate analysis performed on the samples showed that sample (85:15) has the highest protein content of (12.37%), fat content, (2.77%) and ash content (0:71%). The control sample (100% maize flour) had a high carbohydrates content of (77.32%) and moisture content rage from 4.18 to 4.61%. The functional properties of all samples had almost the same level of bulk density (0.69%). A significant difference was observed in water absorption capacity of the samples (1.5-3.33%) and likewise swelling capacity. Pasting characteristic (peak viscosity, final viscosity and holding strength) also decreased significantly as proportion of horse eye bean flour increases above 10%. The setback value and breakdown viscosity of maize flour containing zero or 5% horse eye bean flour were significantly lower than those containing 10 and 15% horse eye bean flour. Apart from producing a nutritionally balanced amala meal, 10% fortification was more stable against retrogradation and was assessed to be more acceptable in terms of key quality index (texture and colour). Therefore the result obtained revealed that (he proximate parameters of the samples increases as the horse eye beans added increase, which confirm the reality of the enrichment. However, in terms of overall acceptability the blend ratio of 95:5% horse eye bean was the most the acceptable to the panelist <0.05. Apart from adding value and varieties to Ogi meal due to its textural improvement, fortifying maize flour with horse eye bean flour at 5% level would also reduce the problem of food security especially among children in the sub-Sahara region of Africa where malnutrition due to protein deficiency is common and also the utilization of horse eye bean.
Brain Injury Associated With Chronic Alcoholism

Abstract Alcoholism can result in a number of severe consequences to the central nervous system, including Korsakoff's psychosis, delusions, delirium, Wernicke's encephalopathy, and cerebellar degeneration. Many of these disorders have a substantially higher prevalence than had been previously believed. Neuropathologic and neuroimaging studies have been instrumental in identifying the changes undergone by the alcoholic brain and the factors that may contribute to alcohol-induced brain damage. Biologic differences appear to make women especially susceptible to central nervous system insult from alcohol abuse. The damage caused by alcohol may be associated, in part, with thiamine deficiency, neuronal excitotoxicity, and magnesium wasting.
Design guideline of Wi-Fi fingerprinting in indoor localization using invariant Received Signal Strength

Location-based services application in indoor environment utilizing Wi-Fi Received Signal Strength (RSS) is recently prevalent in pervasive computing applications. It is used as an enabler of various location based personal services with handheld and wearable communication devices. This paper present a design guideline for the benefits of the society who wish to employ invariant RSS-based localization using Wi-Fi fingerprinting in any indoor environment. This useful guideline relates statistically the different levels of the random spatiotemporal disturbances inducing RSS instability to the minimum number of Wi-Fi sources required for achieving a certain class separation degree under the given number of calibration locations to be identified. We developed an algorithm to simulate the invariant reference RSS propagations, spontaneous RSS propagations, identify the effective invariant RSS after applying spatiotemporal disturbances, and compute the class separation degree of the calibrated reference locations. An instance from the result shows that to get a class separation degree of above 90% with 35% random spatiotemporal disturbances when the number of calibrated locations is 20, the optimum number of obtainable Wi-Fi signal sources should be at least 50.
SDLMAS: A Scenario Modeling Framework for Multi-Agent Systems

In this paper we analyze existing methods and languages for modeling agent interactions and propose a SDLMAS Framework for rapid design, development and runtime support of multi-agent systems. The framework provides a simple but expressive declarative language for modeling complex interactions among agents. Proposed language is based on scenarios, sequences of conversation actions directed towards achieving a goal. Scenario descriptions are converted into program code for a chosen target agent platform and system execution is supported by a runtime framework.