Miracle-dz/UniFAR-FTUs huggingface dataset:
On The Geometry and Shape of Brain Sub-Manifolds

This paper develops mathematical representations for neuro-anatomically significant substructures of the brain and their variability in a population. The focus of the paper is on the neuro-anatomical variation of the geometry and the "shape" of two-dimensional surfaces in the brain. As examples, we focus on the cortical and hippocampal surfaces in an ensemble of Macaque monkeys and human MRI brains. The "shapes" of the substructures are quantified via the construction of templates; the variations are represented by defining probabilistic deformations of the template. Methods for empirically estimating probability measures on these deformations are developed by representing the deformations as Gaussian random vector fields on the embedded sub-manifolds. The Gaussian random vector fields are constructed as quadratic mean limits using complete orthonormal bases on the sub-manifolds. The complete orthonormal bases are generated using modes of vibrations of the geometries of the brain sub-manifolds. The covari.
Edge-based Facial Feature Extraction Using Gabor Wavelet and Convolution Filters

Feature extraction is a crucial step for many systems of face detection and facial expression recognition. In this paper, we present edge-based feature extraction for recognizing six different expressions, which are angry, fear, happy, neutral, sadness and surprise. Edge detection is performed by using Gabor wavelet and convolution filters. In this paper we propose two convolution kernels that are specific for the edge detection of facial components in two orientations. In this study, Principal Component Analysis (PCA) is used to reduce the features dimension. To validate the performance of our proposed feature extraction, the generated features are classified using Support Vector Machine. The experimental results demonstrated that the proposed feature extraction method could generate significant facial features and these features are able to be classified into each expression.
Effects of Progesterone Synthesized De Novo in the Developing Purkinje Cell on Its Dendritic Growth and Synaptogenesis

De novo steroidogenesis from cholesterol is a conserved property of vertebrate brains, and such steroids synthesizedde novo in the brain are called neurosteroids. The identification of neurosteroidogenic cells is essential to the understanding of the physiological role of neurosteroids in the brain. We have demonstrated recently that neuronal neurosteroidogenesis occurs in the brain and indicated that the Purkinje cell actively synthesizes several neurosteroids de novo from cholesterol in vertebrates. Interestingly, in the rat, this neuron actively synthesizes progesterone de novo from cholesterol only during neonatal life, when cerebellar cortical formation occurs most markedly. Therefore, in this study, the possible organizing actions of progesterone during cerebellar development have been examined. In vitro studies using cerebellar slice cultures from newborn rats showed that progesterone promotes dose-dependent dendritic outgrowth of Purkinje cells but dose not affect their somata. This effect was blocked by the anti-progestin RU 486 [mifepristone; 17β-hydroxy-11β-(4-methylaminophenyl)-17α-(1-propynyl) estra-4,9-dien-3 one-6–7]. In vivoadministration of progesterone to pups further revealed an increase in the density of Purkinje spine synapses electron microscopically. In contrast to progesterone, there was no significant effect of 3α,5α-tetrahydroprogesterone, a progesterone metabolite, on Purkinje cell development. Reverse transcription-PCR–Southern and immunocytochemical analyses showed that intranuclear progesterone receptors were expressed in Purkinje cells. These results suggest that progesterone promotes both dendritic outgrowth and synaptogenesis in Purkinje cells through intranuclear receptor-mediated mechanisms during cerebellar development. Such organizing actions may contribute to the formation of the cerebellar neuronal circuit.
Content Based Image Retrieval by using Multi Layer Centroid Contour Distance

In this paper we present a new approach to measuring similarity between two shape of object. In conventional method, centroid contour distance (CCD) is formed by measuring distance between centroid (center) and boundary of object, but this method cannot capture if an object have multiple boundary in the same angle. We develop a novel approach feature shape by measuring distance between centroid (center) and boundary of object that can capture multiple boundaries in the same angle or multi-layer centroid contour distance (MLCCD). The experiment result on simulation dataset and plankton dataset show that the proposed method (MLCCD) better than the conventional method (CCD).
Decoding Encoded Yorùbá Nomenclature: An Exercise of Linguistic Competence and Performance

The study investigated word formation experience in Yorùbá names. At the deployment of ellipsis, as the instrument of analysis, one observed the effectiveness of terminologies of competence and performance, being operational in the clipping of statements to nominal lexemes, illustrated with names of ten towns in South West Nigeria. The study exhibited flexibility in the development of Yorùbá, which depended largely on users’ needs. Historical facts of business, religion, hunting, war and conquest supported the formations, without seemingly consistent linguistic principles. Eliminations of linguistic components occurred to the statements and sometimes with twists in pronunciations, displaying new lexemes and meanings. Although, individuals might attempt to regulate ways that people employ language to formulate words, the study suggested that language communicators should be allowed to deploy language as pleased. As language analyses seem descriptive, utilizing language as delighted might yield novel items to enhance language development in unique forms.
Voltron: A Hybrid System For Answer Validation Based On Lexical And Distance Features

The purpose of this paper is to describe our submission to the SemEval-2015 Task 3 on Answer Selection in Community Question Answering. We participated in subtask A, where the systems had to classify community answers for a given question as definitely relevant, potentially useful, or irrelevant. For every question-answer pair in the training data we extract a vector with a variety of features. These vectors are then fed to a MaxEnt classifier for training. Given a question and an answer the trained classifier outputs class probabilities for each of the three desired categories. The one with the highest probability is chosen. Our system scores better than the average score in subtask A of Task 3.
E-DEEC- Enhanced Distributed Energy Efficient Clustering scheme for heterogeneous WSN

Many routing protocols on clustering structure have been proposed in recent years. In recent advances, achieving the energy efficiency, lifetime, deployment of nodes, fault tolerance, latency, in short high reliability and robustness have become the main research goals of wireless sensor network. Many routing protocols on clustering structure have been proposed in recent years based on heterogeneity. We propose EDEEC for three types of nodes in prolonging the lifetime and stability of the network. Hence, it increases the heterogeneity and energy level of the network. Simulation results show that EDEEC performs better than SEP with more stability and effective messages.
Quantitative Assessment of Oral Orbicular Muscle Deformation After Cleft Lip Reconstruction: An Ultrasound Elastography Study

Reconstruction of a cleft lip leads inevitably to scar tissue formation. Scar tissue within the restored oral orbicular muscle might be assessed by quantification of the local contractility of this muscle. Furthermore, information about the contraction capability of the oral orbicular muscle is crucial for planning the revision surgery of an individual patient. We used ultrasound elastography to determine the local deformation (strain) of the upper lip and to differentiate contracting muscle from passive scar tissue. Raw ultrasound data (radio-frequency format; rf-) were acquired, while the lips were brought from normal state into a pout condition and back in normal state, in three patients and three normal individuals. During this movement, the oral orbicular muscle contracts and, consequently, thickens in contrast to scar tissue that will not contract, or even expand. An iterative coarse-to-fine strain estimation method was used to calculate the local tissue strain. Analysis of the raw ultrasound data allows estimation of tissue strain with a high precision. The minimum strain that can be assessed reproducibly is 0.1%. In normal individuals, strain of the orbicular oral muscle was in the order of 20%. Also, a uniform strain distribution in the oral orbicular muscle was found. However, in patients deviating values were found in the region of the reconstruction and the muscle tissue surrounding that. In two patients with a successful reconstruction, strain was reduced by 6% in the reconstructed region with respect to the normal parts of the muscle (from 22% to 16% and from 25% to 19%). In a patient with severe esthetical and functional disability, strain decreased from 30% in the normal region to 5% in the reconstructed region. With ultrasound elastography, the strain of the oral orbicular muscle can be quantified. In healthy subjects, the strain profiles and maximum strain values in all parts of the muscle were similar. The maximum strain of the muscle during pout was 20% plusmn 1%. In surgically repaired cleft lips, decreased deformation was observed.
Internet Diffusion & Internet Domains: Looking for a new Metric. The Case of Registrations by Italian Individuals

ABSTRACT This paper reports about the analysis of the Internet diffusion among families and business basing on daily observations on registrations of second level domain names underneath the “. it” ccTLD 1 . In particular, domains registered by individuals are analysed. The penetration rate over the relevant population of potential adopters is computed at highly disaggregated geographical level (province). A concentration analysis is carried out to investigate whether the geographical distribution of Internet is less concentrated than population and income suggesting a diffusive effect. Regression analysis is carried out using demographic, social, economic and infrastructure indicators. Finally we briefly describe the further developments of our research. At the present we are building a database containing domains registered by firms in addition to domains registered by individuals. The ide a is to use the database in order to check for the existence of power laws both in the number of domains registered in each province and in the number of domains registered by each firm.
Unintended effects of ethnically targeted advertising

Although, advertising has been a major area of study in marketing, limited research investigating the unintended effects of targeted advertising beyond social and moral issues has been limited. This thesis contributes to the current body of knowledge by examining the unintended effects of ethnically targeted advertising on ethnic groups that are not targeted, but who are still likely to see the advertising. The thesis also develops a holistic model for measuring the effects of targeted advertising using four variables; emotions, attitude to the advertisement, attitude to the company and behavioural intentions. The conceptual basis of the model is accommodation theory, which allows for different levels of targeting based on the language mix used in advertisements (e.g. ranging from advertisements that are solely in the targeted group language to advertisements with a mixture of languages to advertisements that are solely in the non-targeted group's language). The model was tested on three different ethnic groups in Malaysia.
Ascent‐based Monte Carlo expectation– maximization

Summary. The expectation–maximization (EM) algorithm is a popular tool for maximizing likelihood functions in the presence of missing data. Unfortunately, EM often requires the evaluation of analytically intractable and high dimensional integrals. The Monte Carlo EM (MCEM) algorithm is the natural extension of EM that employs Monte Carlo methods to estimate the relevant integrals. Typically, a very large Monte Carlo sample size is required to estimate these integrals within an acceptable tolerance when the algorithm is near convergence. Even if this sample size were known at the onset of implementation of MCEM, its use throughout all iterations is wasteful, especially when accurate starting values are not available. We propose a data‐driven strategy for controlling Monte Carlo resources in MCEM. The algorithm proposed improves on similar existing methods by recovering EM's ascent (i.e. likelihood increasing) property with high probability, being more robust to the effect of user‐defined inputs and handling classical Monte Carlo and Markov chain Monte Carlo methods within a common framework. Because of the first of these properties we refer to the algorithm as ‘ascent‐based MCEM’. We apply ascent‐based MCEM to a variety of examples, including one where it is used to accelerate the convergence of deterministic EM dramatically.
A Multiscale Code for Flexible Hybrid Simulations Using ASE Framework

Multiscale computer simulations combine the computationally efficient classical algorithms with more expensive--and more accurate--ab initio quantum mechanical algorithms. Here, the authors describe one implementation of multiscale computations using the Atomistic Simulation Environment (ASE). This implementation can mix classical codes including the large-scale atomic/molecular massively parallel simulator (LAMMPS) and the density functional theory-based projector-augmented wave (PAW) implementation designed to work with ASE. Any combination of codes linked via the ASE interface can be mixed. The authors introduce a framework to easily add classical force-fields calculators for ASE using LAMMPS, which also allows harnessing the full performance of classical-only molecular dynamics. Their work makes it possible to combine different simulation codes (quantum mechanical or classical) with great ease and minimal coding effort.
3D forward modelling of time domain electromagnetic data

Summary We develop a forward modelling algorithm for computing time domain electromagnetic responses for conductive, permeable bodies in the low frequency regime. Both physical properties can be highly discontinuous. The parameter regimes considered give rise to highly stiff problems in the time domain and an implicit method, backward Euler, is used for time-stepping. At each time step the electromagnetic equations are solved in a stable manner by using a Helmholtz decomposition of the electric field to convert to potentials, and then discretizing in space by using a finite volume formulation. The final system is solved using a biconjugate gradient solver with preconditioning. Numerical comparisons are made against a 1d semi-analytic solution for a conductive permeable half-space, and a 3d integral equation solution for a block in a halfspace. The Forward Problem
Acyclic modeling of combinational loops

This paper presents a method to convert gate-level combinational loop into an acyclic circuit, if the combinational loop is not oscillatory. Combinational loops breach design methodologies, because they can involve undesirable circuit behavior and can possibly lead to oscillations based on the external stimuli to the loops. However, for designs compiled using automated synthesis-compiler, these loops are very likely to appear in the generated gate-level designs. We present a modeling of combinational loops as state holding elements and break non oscillatory loops using a level sensitive latch. Apart from modeling combinational loops consisting of gates, the algorithm also converts the loops through design latches. The increase in design area, due to the loop conversion, has an upper bound of twice the size of the original feedback path. However, in case of multiply nested feedback paths, each path is treated separately. Unlike previous work that converts cyclic combinational logic where the feedback is not exercised, this paper presents an algorithm to identify the stateful "latch" behavior in a class of feedback logic (non-oscillatory, monotonic). A conversion algorithm replaces such feedback logic by an equivalent circuit comprising explicit latches and acyclic combinational logic. The replacement circuit has an identical behavior as the original stateful feedback logic.
ENHANCING NETWORK INTRUSION CLASSIFICATION THROUGH THE KOLMOGOROV-SMIRNOV SPLITTING CRITERION

Our investigation aims at detecting network intrusions using decision tree algorithms. Large differences in prior class probabilities of intrusion data have been reported to hinder the performance of decision trees. We propose to replace the Shannon entropy used in tree induction algorithms with a Kolmogorov Smirnov splitting criterion which locates a Bayes optimal cutpoint of attributes. The Kolmogorov-Smirnov distance based on the cumulative distributions is not degraded by class imbalance. Numerical test results on the KDDCup99 dataset showed that our proposals are attractive to network intrusion detection tasks. The single decision tree gives best results for minority classes, cost metric and global accuracy compared with the bagged boosting of trees of the KDDCup’99 winner and classical decision tree algorithms using the Shannon entropy. In contrast to the complex model of KDDCup winner, our decision tree represents inductive rules (IF-THEN) that facilitate human interpretation.
Intensity of activation and timing of deactivation modulate elastic energy storage and release in a pennate muscle and account for gait-specific initiation of limb protraction in the horse

SUMMARY The equine biceps brachii (biceps) initiates rapid limb protraction through a catapult mechanism. Elastic strain energy is slowly stored in an internal tendon and is then rapidly released to protract the forelimb. The muscle fibres are short, have little scope for length change and can therefore only shorten slowly compared with the speed at which the whole muscle must shorten, which makes them poor candidates for driving rapid limb protraction. We suggest that the muscle fibres in the biceps act to modulate the elastic energy output of the muscle–tendon unit (MTU) to meet the demands of locomotion under different conditions. We hypothesise that more elastic strain energy is stored and released from the biceps MTU during higher speed locomotion to accommodate the increase in energy required to protract the limb and that this can be achieved by varying the length change and activation conditions of the muscle. We examined the work performed by the biceps during trot and canter using an inverse dynamics analysis (IDA). We then used excised biceps muscles to determine how much work could be performed by the muscle in active and passive stretch–shorten cycles. A muscle model was developed to investigate the influence of changes in activation parameters on energy storage and energy return from the biceps MTU. Increased biceps MTU length change and increased work performed by the biceps MTU were found at canter compared with at trot. More work was performed by the ex vivo biceps MTU following activation of the muscle and by increasing muscle length change. However, the ratio of active to passive work diminished with increasing length change. The muscle model demonstrated that duration and timing of activation during stretch–shorten cycles could modulate the elastic energy storage and return from the biceps. We conclude that the equine biceps MTU acts as a tuneable spring and the contractile component functions to modulate the energy required for rapid forelimb protraction at different speeds.
Reward Associations Magnify Memory-based Biases on Perception

Long-term spatial contextual memories are a rich source of predictions about the likely locations of relevant objects in the environment and should enable tuning of neural processing of unfolding events to optimize perception and action. Of particular importance is whether and how the reward outcome of past events can impact perception. We combined behavioral measures with recordings of brain activity with high temporal resolution to test whether the previous reward outcome associated with a memory could modulate the impact of memory-based biases on perception, and if so, the level(s) at which visual neural processing is biased by reward-associated memory-guided attention. Data showed that past rewards potentiate the effects of spatial memories upon the discrimination of target objects embedded within complex scenes starting from early perceptual stages. We show that a single reward outcome of learning impacts on how we perceive events in our complex environments.
The Orphan G Protein-coupled Receptors GPR41 and GPR43 Are Activated by Propionate and Other Short Chain Carboxylic Acids*

GPR41 and GPR43 are related members of a homologous family of orphan G protein-coupled receptors that are tandemly encoded at a single chromosomal locus in both humans and mice. We identified the acetate anion as an agonist of human GPR43 during routine ligand bank screening in yeast. This activity was confirmed after transient transfection of GPR43 into mammalian cells using Ca2+ mobilization and [35S]guanosine 5′-O-(3-thiotriphosphate) binding assays and by coexpression with GIRK G protein-regulated potassium channels in Xenopus laevis oocytes. Other short chain carboxylic acid anions such as formate, propionate, butyrate, and pentanoate also had agonist activity. GPR41 is related to GPR43 (52% similarity; 43% identity) and was activated by similar ligands but with differing specificity for carbon chain length, with pentanoate being the most potent agonist. A third family member,GPR42, is most likely a recent gene duplication ofGPR41 and may be a pseudogene. GPR41 was expressed primarily in adipose tissue, whereas the highest levels of GPR43 were found in immune cells. The identity of the cognate physiological ligands for these receptors is not clear, although propionate is known to occur in vivo at high concentrations under certain pathophysiological conditions.
Design of Integral Controller for SSSC and TCPS based AGC of hydrothermal System under Deregulated Environment

*(EEE Department, Yogananda Institute of technology and Science, Tirupathi, India) ** (Research Scholar, S.V University, Tirupathi, India ** (Department of Electrical Engineering, S.V.University, Tirupathi ABSTRACT This paper presents the design of integral controller for Automatic Generation Control (AGC) of hydrothermal system under deregulated environment employing simulated annealing (SA). Static Synchronous Series Compensator (SSSC) has also been proposed to further increase the dynamic performance of the system in terms of peak time, overshoot and settling time. The concept of soft computing techniques greatly helps in overcoming the disadvantages posed by the conventional controllers. Open transmission access and the evolving of more socialized companies for generation, transmission and distribution affects the formulation of AGC problem. So the traditional AGC system is modified to take into account the effect of bilateral contracts on the dynamics. Simulation results show that the simulated annealing based system employing Static Synchronous Series Compensator has better dynamic performance over the system without SSSC.