Miracle-dz/UniFAR-FTUs huggingface dataset:
Regional brain variations of tryptophan, monoamines, monoamine oxidase activity, plasma free and total tryptophan during the estrous cycle of the rat.

Normal 4-day cyclic rats were sacrificed at 10 a.m. and 3 p.m. on proestrus or estrus and at 10 a.m. on metestrus. Noradrenaline (NA), dopamine (DA) and tryptophan (T) concentrations varied only slightly. Serotonin (5-HT) concentrations showed characteristic changing patterns in many hypothalamic, limbic and midbrain structures with a decrease during proestrus and an increase during estrus being observed. Monoamine oxidase (MAO) activity changes were often parallel to the 5-HT changes, but were not as great. The marked changes in 5-HT early in proestrus are a further indication of its inhibitory effect on gonadotropin release mechanisms before the 'critical period'.
Exercise training modifies walking kinematics and energy cost in obese adolescents: A pilot controlled trial

Abstract The aim of this study was to investigate the effects of a weight loss intervention based on physical exercise on the relationship between energy cost and stride frequency during walking in obese teenagers. Participants aged 13–16 years old were assigned to a training (n = 14) and control (n = 10) groups. During eight weeks, the training group performed three 60-min weekly sessions of high-intensity intermittent activities coupled with aerobic training. Body composition, gait parameters and energy cost during 4-min walking bouts at participants’ most comfortable speed and preferred stride frequency (PSF), PSF-10%, PSF + 10%, PSF-20% and PSF + 20% were measured before and after intervention. The effects of training and stride frequencies on the energy cost of walking were analysed by an ANOVA with repeated measures. The main results showed that the exercise intervention induced a significant increase in walking speed (+23.2%), and significant decreases in body mass (−1.4%), body fat percentage (−2.1%) and energy cost of walking at various frequencies (decreases ranging from −10.5% to −20.4%, p < .05). In addition, significantly greater decreases were shown at high frequencies (p < .05). No significant differences were shown in the control group (p > .05). These results suggest that this type of training is beneficial to reduce walking energy cost of obese teenagers, in particular at high frequencies. This should improve their well-being during daily activities.
Weirdness Coefficient as a Feature Selection Method for Arabic Special Domain Text Classification

Given the importance of organizing and managing the rapid growth in knowledge of Arabic electronic content, this study introduces the Weirdness Coefficient (W) as a new feature selection method for Arabic special domain text classification. The proposed method was used to classify a dataset comprising five Islamic topics using Naive base (NB) and K-nearest neighbor (K-NN) classifiers, and three representation schemas. The results were also compared with a well-known feature selection method, Chi-squared. In addition to its simplicity in computation, the Weirdness Coefficient showed promising classification accuracy.
Real Time Vehicle License Plate Recognition Based on 2D Haar Discrete Wavelet Transform

This thesis is to present a new approach for license-plate recognition using 2D Haar Discrete Wavelet Transform (HDWT) and Artificial neural Network. This thesis consists of three main parts. The first part is to locate and extract the license-plate in an image. The second part is to train of the license-plate. The third part is to real time scan recognize of the license-plate. Traditional license plate recognition system design complexity. The paper present is a vehicle license plate after 2D Haar Discrete Wavelet Transform three transforms, select only after the third conversion coefficients of low-frequency part of the image pixels, image pixels into one-sixty fourth, thus reducing the number of scanning image pixels, increasing rapid implementation of recognition work and the memory usage. This article is to directly scan for license plate recognition, without recognition of the individual characters. This new approach is a real time recognition, experimental results of license plate recognition rates can be as high as 95.33%.
Flexible prediction analysis of microarrays

In this paper, we study the widely used nearest shrunken centroid classifier (NSC, also known as PAM) for microarray data from the supervised dimension reduction perspective. A simple modification is proposed and through application to public microarray data, we illustrate the favorable performance of the proposed method. Supplementary information can be found at http://www.biostat. umn. edu/~baolin/research/fpam.html.
Temporomandibular Disorders: The Habitual Chewing Side Syndrome

Background Temporomandibular disorders are the most common cause of chronic orofacial pain, but, except where they occur subsequent to trauma, their cause remains unknown. This cross-sectional study assessed chewing function (habitual chewing side) and the differences of the chewing side and condylar path and lateral anterior guidance angles in participants with chronic unilateral temporomandibular disorder. This is the preliminary report of a randomized trial that aimed to test the effect of a new occlusal adjustment therapy. Methods The masticatory function of 21 randomly selected completely dentate participants with chronic temporomandibular disorders (all but one with unilateral symptoms) was assessed by observing them eat almonds, inspecting the lateral horizontal movement of the jaw, with kinesiography, and by means of interview. The condylar path in the sagittal plane and the lateral anterior guidance angles with respect to the Frankfort horizontal plane in the frontal plane were measured on both sides in each individual. Results Sixteen of 20 participants with unilateral symptoms chewed on the affected side; the concordance (Fisher’s exact test, P = .003) and the concordance-symmetry level (Kappa coefficient κ = 0.689; 95% confidence interval [CI], 0.38 to 0.99; P = .002) were significant. The mean condylar path angle was steeper (53.47(10.88) degrees versus 46.16(7.25) degrees; P = . 001), and the mean lateral anterior guidance angle was flatter (41.63(13.35) degrees versus 48.32(9.53) degrees P = . 036) on the symptomatic side. Discussion The results of this study support the use of a new term based on etiology, “habitual chewing side syndrome”, instead of the nonspecific symptom-based “temporomandibular joint disorders”; this denomination is characterized in adults by a steeper condylar path, flatter lateral anterior guidance, and habitual chewing on the symptomatic side.
Cell Walls of Developing Wheat Starchy Endosperm: Comparison of Composition and RNA-Seq Transcriptome1[C][W][OA]

The transcriptome of the developing starchy endosperm of hexaploid wheat (Triticum aestivum) was determined using RNA-Seq isolated at five stages during grain fill. This resource represents an excellent way to identify candidate genes responsible for the starchy endosperm cell wall, which is dominated by arabinoxylan (AX), accounting for 70% of the cell wall polysaccharides, with 20% (1,3;1,4)-β-d-glucan, 7% glucomannan, and 4% cellulose. A complete inventory of transcripts of 124 glycosyltransferase (GT) and 72 glycosylhydrolase (GH) genes associated with cell walls is presented. The most highly expressed GT transcript (excluding those known to be involved in starch synthesis) was a GT47 family transcript similar to Arabidopsis (Arabidopsis thaliana) IRX10 involved in xylan extension, and the second most abundant was a GT61. Profiles for GT43 IRX9 and IRX14 putative orthologs were consistent with roles in AX synthesis. Low abundances were found for transcripts from genes in the acyl-coA transferase BAHD family, for which a role in AX feruloylation has been postulated. The relative expression of these was much greater in whole grain compared with starchy endosperm, correlating with the levels of bound ferulate. Transcripts associated with callose (GSL), cellulose (CESA), pectin (GAUT), and glucomannan (CSLA) synthesis were also abundant in starchy endosperm, while the corresponding cell wall polysaccharides were confirmed as low abundance (glucomannan and callose) or undetectable (pectin) in these samples. Abundant transcripts from GH families associated with the hydrolysis of these polysaccharides were also present, suggesting that they may be rapidly turned over. Abundant transcripts in the GT31 family may be responsible for the addition of Gal residues to arabinogalactan peptide.
Fetal and Neonatal Programming : Epigenetic Modification of Phenotype Influence of abnormally high leptin levels during pregnancy on metabolic phenotypes in progeny mice

Makarova EN, Chepeleva EV, Panchenko PE, Bazhan NM. Influence of abnormally high leptin levels during pregnancy on metabolic phenotypes in progeny mice. Am J Physiol Regul Integr Comp Physiol 305: R1268–R1280, 2013. First published October 2, 2013; doi:10.1152/ajpregu.00162. 2013. —Maternal obesity increases the risk of obesity in offspring, and obesity is accompanied by an increase in blood leptin levels. The “yellow” mutation at the mouse agouti locus (A) increases blood leptin levels in C57BL preobese pregnant mice without affecting other metabolic characteristics. We investigated the influence of the A mutation or leptin injection at the end of pregnancy in C57BL mice on metabolic phenotypes and the susceptibility to diet-induced obesity (DIO) in offspring. In both C57BL-A and leptin-treated mice, the maternal effect was more pronounced in male offspring. Compared with males born to control mothers, males born to A mothers displayed equal food intake (FI) but decreased body weight (BW) gain after weaning, equal glucose tolerance, and enhanced FI-to-BW ratios on the standard diet but the same FI and BW on the high-fat diet. Males born to A mothers were less responsive to the anorectic effect of exogenous leptin and less resistant to fasting (were not hyperphagic and gained less weight during refeeding after food deprivation) compared with males born to control mothers. However, all progeny displayed equal hypothalamic expression of Agouti gene-related protein (AgRP), neuropeptide Y (NPY), and proopiomelanocortin (POMC) and equal plasma leptin and glucose levels after food deprivation. Leptin injections in C57BL mice on day 17 of pregnancy decreased BW in both male and female offspring but inhibited FI and DIO only in male offspring. Our results show that hyperleptinemia during pregnancy has sex-specific long-term effects on energy balance regulation in progeny and does not predispose offspring to developing obesity.
A Low-Latency Low-Power QR-Decomposition ASIC Implementation in 0.13 $\mu{\rm m}$  CMOS

This paper presents a hybrid QR decomposition (QRD) design that reduces the number of computations and increases their execution parallelism by using a unique combination of Multi-dimensional Givens rotations, Householder transformations and conventional 2-D Givens rotations. A semi-pipelined semi-iterative architecture is presented for the QRD core, that uses innovative design ideas to develop 2-D, Householder 3-D and 4-D/2-D configurable CORDIC processors, such that they can perform the maximum possible number of vectoring and rotation operations within the given number of cycles, while minimizing gate count and maximizing the resource utilization. Test results for the 0.3 mm2 QRD chip, fabricated in 0.13 μm 1P8M CMOS technology, demonstrate that the proposed design for 4×4 complex matrices attains the lowest reported processing latency of 40 clock cycles (144 ns) at 278 MHz and dissipates 48.2 mW at 1.3 V supply and 25°C. It outperforms all of the previously published QRD designs by offering the highest QR processing efficiency.
Selectivity Estimation on Streaming Spatio-Textual Data Using Local Correlations

In this paper, we investigate the selectivity estimation problem for streaming spatio-textual data, which arises in many social network and geo-location applications. Specifically, given a set of continuously and rapidly arriving spatio-textual objects, each of which is described by a geo-location and a short text, we aim to accurately estimate the cardinality of a spatial keyword query on objects seen so far, where a spatial keyword query consists of a search region and a set of query keywords. To the best of our knowledge, this is the first work to address this important problem. We first extend two existing techniques to solve this problem, and show their limitations. Inspired by two key observations on the "locality" of the correlations among query keywords, we propose a local correlation based method by utilizing an augmented adaptive space partition tree (A2SP-tree for short) to approximately learn a local Bayesian network on-the-fly for a given query and estimate its selectivity. A novel local boosting approach is presented to further enhance the learning accuracy of local Bayesian networks. Our comprehensive experiments on real-life datasets demonstrate the superior performance of the local correlation based algorithm in terms of estimation accuracy compared to other competitors.
MPIS: maximal-profit item selection with cross-selling considerations

In the literature of data mining, many different algorithms for association rule mining have been proposed. However, there is relatively little study on how association rules can aid in more specific targets. One of the applications for association rules - maximal-profit item selection with cross-selling effect (MPIS) problem - is investigated. The problem is about selecting a subset of items, which can give the maximal profit with the consideration of cross-selling. We prove that a simple version of this problem is NP-hard. We propose a new approach to the problem with the consideration of the loss rule - a kind of association rule to model the cross-selling effect. We show that the problem can be transformed to a quadratic programming problem. In case quadratic programming is not applicable, we also propose a heuristic approach. Experiments are conducted to show that both of the proposed methods are highly effective and efficient.
1H-NMR Analysis of Degree of Substitution in N,O-Carboxymethyl Chitosans from Various Chitosan Sources and Types

N,O-Carboxymethyl chitosans were synthesized by the reaction between shrimp, crab and squid chitosans with monochloroacetic acid under basic conditions at 50°C. The mole ratio of reactants was obtained from various reaction conditions of shrimp chitosan polymer and oligomer types. The mole ratio 1:12:6 of chitosan:sodium hydroxide:monochloroacetic acid was used for preparing carboxymethyl of chitosan polymer types while carboxymethyl of chitosan oligomer types were used the mole ratio 1:6:3 of chitosan:sodium hydroxide:monochloroacetic acid. The chemical structure was analyzed by fourier transformed infrared spectroscopy (FT-IR) and proton nuclear magnatic resonance spectroscopy (1H-NMR). The FT-IR was used for confirm the insertion of carboxymethyl group on chitosan molecules. The 1H-NMR was used for determining the degree of substitution (DS) of carboxymethylation at hydroxyl and amino sites of chitosans. Carboxymethyl chitosan samples had the total DS of carboxymethylation ranging from 1.0-2.2. The highest of DS of carboxymethylation was from shrimp chitosan oligomer type.
Detecting malware with similarity to Android applications

In light of the rapid growth of smartphones, there are unrelenting malicious attacks on smartphones from voice phishing to mobile malwares. Especially, SMiShing malicious application has become a crucial threat on smartphone since it can be easily rampant via URLs embedded in SMS messages and emails. SMiShing attack installs the malicious application, it has been exploited by financial fraud and leak of private information stored on the smartphone. Our solution intercepts and gathers the malicious application and analyzing it instead of smartphone. It can block installing malicious application on smartphone and also analyze fast and accurately. Also, a number of malicious applications targeting Android operation system are similar to known malware and repackaged an existed malicious application. It presents a unique feature that the downloaded applications can be compared with accumulated malwares. In this paper, we propose the detection system for android malicious application using static analysis along with malicious feature similarity.
The Mineralization of Bone and Its Analogies with Other Hard Tissues

Bone is one of the many biological tissues characterized by the still poorly defined process of mineralization, that is, by the deposition of inorganic substance in their organic matrix, and is one that, chiefly due to its important biological functions, but also because of its wide‐ spread presence in primates and its easy availability, has been investigated for hundred of years by thousand of investigators (see reviews by [1-3]). Its study, however, is a demanding task, because of the complexity and variability of the tissue – factors that derive mainly from differences in its histological types, biochemical composition, phases of maturation, and de‐ gree of mineralization (the terms ‘mineralization’, ‘biomineralization’, and ‘calcification’ are treated as equivalents in this paper; see Bonucci [2]). These differences, although recently emphasized [4-5], have not always received due recognition. In this connection, revealing indicative examples include, for instance, the differences between the compact, lamellar bone and spongy, woven bone [4], or between the dense rostrum bone of toothed whales [6] and the medullary bone of birds [7]. These differences may lead to incorrect interpretations of apparently contrasting results, but may also lead to new insights if they are recognized to derive from distinctive traits of tissues belonging to the same broad type, which is what they are. The concepts that follow, which chiefly focus on the local mechanism of matrix calcifica‐ tion, mainly refer to woven bone, which raises fewer technical issues than compact bone, but they are valid for, and can be extended to, all other types of bone and hard tissue.
The Interplay between Alpha-Synuclein Clearance and Spreading

Parkinson’s Disease (PD) is a complex neurodegenerative disorder classically characterized by movement impairment. Pathologically, the most striking features of PD are the loss of dopaminergic neurons and the presence of intraneuronal protein inclusions primarily composed of alpha-synuclein (α-syn) that are known as Lewy bodies and Lewy neurites in surviving neurons. Though the mechanisms underlying the progression of PD pathology are unclear, accumulating evidence suggests a prion-like spreading of α-syn pathology. The intracellular homeostasis of α-syn requires the proper degradation of the protein by three mechanisms: chaperone-mediated autophagy, macroautophagy and ubiquitin-proteasome. Impairment of these pathways might drive the system towards an alternative clearance mechanism that could involve its release from the cell. This increased release to the extracellular space could be the basis for α-syn propagation to different brain areas and, ultimately, for the spreading of pathology and disease progression. Here, we review the interplay between α-syn degradation pathways and its intercellular spreading. The understanding of this interplay is indispensable for obtaining a better knowledge of the molecular basis of PD and, consequently, for the design of novel avenues for therapeutic intervention.
Neuroscience and Biobehavioral Reviews Identifying Key Features of Early Stressful Experiences That Produce Stress Vulnerability and Resilience in Primates

Keywords: Development Early experiences HPA axis Maternal care Primate models Psychopathology Resilience Risk Stress inoculation Stressor Vulnerability a b s t r a c t This article examines the complex role of early stressful experiences in producing both vulnerability and resilience to later stress-related psychopathology in a variety of primate models of human development . ation in maternal style, and maternal abuse). Based on empirical evidence, it is argued that early life stress exposure does not increase adult vulnerability to stress-related psychopathology as a linear function, as is generally believed, but instead reflects a quadratic function. Features of early stress exposure including the type, duration, frequency, ecological validity, sensory modality, and developmental timing, within and between species, are identified to better understand how early stressful experiences alter neurobi-ological systems to produce such diverse developmental outcomes. This article concludes by identifying gaps in our current knowledge, providing directions for future research, and discussing the translational implications of these primate models for human development and psychopathology.
Clinical Decision Support Systems (cdsss) Have Been Hailed for Their Potential to Reduce Medical Errors Clinical Decision Support Systems for the Practice of Evidence-based Medicine

1 and increase health care quality and efficiency. 2 At the same time, evidence-based medicine has been widely promoted as a means of improving clinical outcomes, where evidence-based medicine refers to the practice of medicine based on the best available scientific evidence. The use of CDSSs to facilitate evidence based medicine therefore promises to substantially improve health care quality. The Evidence and Decision Support track of the 2000 AMIA Spring Symposium examined the challenges in realizing the promise of CDSS-facilitated evidence-based medicine. This paper describes the activities of this track and summarizes discussions in specific A b s t r a c t Background: The use of clinical decision support systems to facilitate the practice of evidence-based medicine promises to substantially improve health care quality. Objective: To describe, on the basis of the proceedings of the Evidence and Decision Support track at the 2000 AMIA Spring Symposium, the research and policy challenges for capturing research and practice-based evidence in machine-interpretable repositories, and to present recommendations for accelerating the development and adoption of clinical decision support systems for evidence-based medicine. Results: The recommendations fall into five broad areas—capture literature-based and practice-based evidence in machine-interpretable knowledge bases; develop maintainable technical and methodological foundations for computer-based decision support; evaluate the clinical effects and costs of clinical decision support systems and the ways clinical decision support systems affect and are affected by professional and organizational practices; identify and disseminate best practices for work flow–sensitive implementations of clinical decision support systems; and establish public policies that provide incentives for implementing clinical decision support systems to improve health care quality. Conclusions: Although the promise of clinical decision support system–facilitated evidence-based medicine is strong, substantial work remains to be done to realize the potential benefits.