Miracle-dz/UniFAR-FTUs huggingface dataset:
Perinatal Asphyxia Reduces Dentate Granule Cells and Exacerbates Methamphetamine-Induced Hyperlocomotion in Adulthood

Background Obstetric complications have been regarded as a risk factor for schizophrenia later in life. One of the mechanisms underlying the association is postulated to be a hypoxic process in the brain in the offspring around the time of birth. Hippocampus is one of the brain regions implicated in the late-onset dopaminergic dysfunction associated with hypoxic obstetric complications. Methodology/Principal Findings We used an animal model of perinatal asphyxia, in which rat pups were exposed to 15 min of intrauterine anoxia during Cesarean section birth. At 6 and 12 weeks after birth, the behavior of the pups was assessed using a methamphetamine-induced locomotion test. In addition, the histopathology of the hippocampus was examined by means of stereology. At 6 weeks, there was no change in the methamphetamine-induced locomotion. However, at 12 weeks of age, we found an elevation in methamphetamine-induced locomotor activity, which was associated with an increase of dopamine release in the nucleus accumbens. At the same age, we also found a reduction of the dentate granule cells of the hippocampus. Conclusions/Significance These results suggest that the dopaminergic dysregulation after perinatal asphyxia is associated with a reduction in hippocampal dentate granule cells, and this may partly contribute to the pathogenesis of schizophrenia.
Assessing Effectiveness of Multicultural Readings in Increasing Ethnocultural Empathy for Undergraduate Students

This study examined how multicultural readings included in the introduction to psychology curriculum were linked to an increase in students’ multicultural interest and sensitivity. Specifically, this study investigated the impact of reading and discussing multicultural articles on students’ ethnocultural empathy, universality-diverse orientation, and openness to diversity. Second purpose of the study was to examine possible individual differences associated with response to the intervention. Participants in the current study were undergraduate students enrolled in five sections of the introduction to psychology class, which were randomly assigned as control and experimental groups. The multicultural readings are four original research articles that examine topics in psychology from a cross-cultural and multicultural perspective. Measures of dependent variables used in the study were: Scale of Ethnocultural Empathy (Wang et al., 2003), Personality Style Inventory for Adolescents (Lounsbury et al., 2003), Experiences in Close Relationships Short Form (Wei, Russell, Mallinckrodt, & Vogel, 2007), Miville–Guzman Universality– Diversity Scale-Short form (Fuertes, Miville, Mohr, Sedlacek,& Gretchen, 2000), Openness to Diversity Scale (Pascarella, Edison, Nora, Hagedon, & Terenzini, 1996), and Balanced Inventory of Desired Responding (Paulhus, 1984). A one-way Multivariate analysis of variance (MANOVA) was used to test the hypothesis that the experimental group, after being exposed to the multicultural readings would show a greater increase in multicultural variables. The study’s main hypothesis was not supported, because the group X time treatment interaction was not significant. Exploratory analyses of personality traits as covariates suggested that only one variable, Attachment
Ameliorative Effect of Gallic Acid on Cyclophosphamide-Induced Oxidative Injury and Hepatic Dysfunction in Rats

Cyclophosphamide (CP), a bifunctional alkylating agent used in chemotherapy has been reported to induce organ toxicity mediated by generation of reactive oxygen species and oxidative stress. Gallic acid (GA), a phenolic substance, is a natural antioxidant with proven free radical scavenging activity and offers protection against oxidative damage. This research study was designed to investigate the ameliorative effect of GA against CP-induced toxicity in rats. Twenty-five male Wistar rats (180–200 g) were randomized into five treatment groups: (A) control, (B) CP, 2 mg/kg body weight (b.w.), (C) pre-treatment with GA (20 mg/kg b.w.) for seven days followed by CP (2 mg/kg b.w.) for seven days, (D) co-treatment with GA (20 mg/kg b.w) and CP (2 mg/kg b.w.) for seven days, and (E) GA (20 mg/kg b.w.) for seven days. CP induced marked renal and hepatic damages as plasma levels of urea, creatinine, bilirubin and activities of AST, ALT, ALP and GGT were significantly elevated (p < 0.05) in the CP-treated group relative to control. In addition, hepatic levels of GSH, vitamin C and activities of SOD, catalase and GST significantly reduced in the CP-treated group when compared with control. This was accompanied with a significant increase in hepatic lipid peroxidation. The restoration of the markers of renal and hepatic damages as well as antioxidant indices and lipid peroxidation by pre- and co-treatment with GA clearly shows that GA offers ameliorative effect by scavenging the reactive oxygen species generated by CP. This protective effect may be attributed to the antioxidant property of gllic acid.
A Novel Fast Framework for Topic Labeling Based on Similarity-preserved Hashing

Recently, topic modeling has been widely applied in data mining due to its powerful ability. A common, major challenge in applying such topic models to other tasks is to accurately interpret the meaning of each topic. Topic labeling, as a major interpreting method, has attracted significant attention recently. However, most of previous works only focus on the effectiveness of topic labeling, and less attention has been paid to quickly creating good topic descriptors; meanwhile, it’s hard to assign labels for new emerging topics by using most of existing methods. To solve the problems above, in this paper, we propose a novel fast topic labeling framework that casts the labeling problem as a k-nearest neighbor (KNN) search problem in a probability vector set. Our experimental results show that the proposed sequential interleaving method based on locality sensitive hashing (LSH) technology is efficient in boosting the comparison speed among probability distributions, and the proposed framework can generate meaningful labels to interpret topics, including new emerging topics.
Segmentation of ascidian notochord cells in DIC timelapse images

We have developed a method to automatically segment notochord cell boundaries from differential interference contrast (DIC) timelapse images of the elongating ascidian tail. The method is based on a specialized parametric active contour, the network snake, which can be initialized as a network of arbitrary but fixed topology and provides an effective framework for simultaneously segmenting multiple touching cells. Several modifications to the original network snake were necessary for high‐quality segmentation, including linear Gaussian derivative filtering to reconstruct edge maps from DIC images and a new energy function to improve the segmentation of critical cell‐cell vertices. We find that post‐intercalation ascidian notochord cells exhibit two distinct cell behaviors: lateral cell edges expand along the AP axis while showing a rapid pulsatile behavior, whereas anterior and posterior cell edges contract smoothly. Microsc. Res. Tech., 2011. © 2010 Wiley‐Liss, Inc.
The role of forest tent caterpillar defoliations and partial harvest in the decline and death of sugar maple.

BACKGROUND AND AIMS Natural and anthropogenic disturbances can act as stresses on tree vigour. According to Manion's conceptual model of tree disease, the initial vigour of trees decreases as a result of predisposing factors that render these trees more vulnerable to severe inciting stresses, stresses that can then cause final vigour decline and subsequent tree death. This tree disease model was tested in sugar maple (Acer saccharum) by assessing the roles of natural and anthropogenic disturbances in tree decline and death. METHODS Radial growth data from 377 sugar maple trees that had undergone both defoliations by insects and partial harvest were used to estimate longitudinal survival probabilities as a proxy for tree vigour. Radial growth rates and survival probabilities were compared among trees subjected to different levels of above- and below-ground disturbances, between periods of defoliation and harvest, and between live and dead trees. KEY RESULTS Manion's tree disease model correctly accounts for vigour decline and tree death in sugar maple; tree growth and vigour were negatively affected by a first defoliation, predisposing these trees to death later during the study period due to a second insect outbreak that initiated a final vigour decline. This decline was accelerated by the partial harvest disturbance in 1993. Even the most severe anthropogenic disturbances from partial harvest did not cause, unlike insect defoliation, any growth or vigour declines in live sugar maple. CONCLUSIONS Natural disturbances acted as predisposing and inciting stresses in tree sugar maple decline and death. Anthropogenic disturbances from a partial harvest at worst accelerated a decline in trees that were already weakened by predisposing and inciting stresses (i.e. repeated insect defoliations). Favourable climatic conditions just before and after the partial harvest may have alleviated possible negative effects on growth resulting from harvesting.
Human Body Parts Tracking and Kinematic Features Assessment Based on RSSI and Inertial Sensor Measurements

Acquisition of patient kinematics in different environments plays an important role in the detection of risk situations such as fall detection in elderly patients, in rehabilitation of patients with injuries, and in the design of treatment plans for patients with neurological diseases. Received Signal Strength Indicator (RSSI) measurements in a Body Area Network (BAN), capture the signal power on a radio link. The main aim of this paper is to demonstrate the potential of utilizing RSSI measurements in assessment of human kinematic features, and to give methods to determine these features. RSSI measurements can be used for tracking different body parts' displacements on scales of a few centimeters, for classifying motion and gait patterns instead of inertial sensors, and to serve as an additional reference to other sensors, in particular inertial sensors. Criteria and analytical methods for body part tracking, kinematic motion feature extraction, and a Kalman filter model for aggregation of RSSI and inertial sensor were derived. The methods were verified by a set of experiments performed in an indoor environment. In the future, the use of RSSI measurements can help in continuous assessment of various kinematic features of patients during their daily life activities and enhance medical diagnosis accuracy with lower costs.
Privacy-Preserving Internet Traffic Publication

As machine learning (ML)-based traffic classification develops, Internet traffic data is published in public to serve as test data. Although the IP addresses therein are anonymized, it is given explicitly which data belongs to an identical user. Then using the information, an adversary can identify a user from the anonymized users. The paper first gives a k-anonymity method to reduce the probability of information leak to P/k, where P is the probability of information leak without k-anonymity. Assume the number of the flows belonging to an IP address follows Normal distribution, the information loss is shown µ2+σ2/kµ2+σ2, where µ and σ are respectively the mean and the variance of the Normal distribution. Later, random noise is added to further reduce the probability of information leak to P/k2, with an expected distortion rate of approximately 2d+log k-log|X|, where d is the number of dimensions and |X| is the number of the vectors. At last, real-world Internet traffic data is used to evaluate the utility of the anonymized traffic data. According to the experimental results, the k-anonymized noised data can be clustered with an overall accuracy rate close to the state-of-the-art results for non-anonymized traffic data.
Distributed security architecture for authentication in 4G networks

4G network is the highly advanced wireless network which aids broadband as well as multimedia applications. 4G uses the TCP/IP architecture as the network backbone with open interfaces, which makes it susceptible to various network security risks. The increased set of features available at the user terminal also leads to the maximization of the security risks in 4G network. Hence, to overcome the security problems in the 4G network, in this paper we propose to develop distributed security architecture for authentication. In this proposed architecture, the Elliptic Curve Diffie-Hellman (ECDH) protocol is used for authenticating the mobile nodes within the network through hop by hop authentication and neighbor authentication.
QUALITATIVE PHYTOCHEMICAL SCREENING, ANTI-OXIDANT AND ANTI-MICROBIAL ACTIVITY STUDIES ON ETHANOLIC FLOWERS EXTRACT OF CARYOTA URENES LINN.

The distribution of the main active principles (alkaloids, flavanoids, phenols, steroids and tannins) in the ethanolic extracts of Caryota urens flowers were screened by using various different solvents system. The anti-oxidant activity of ethanolic extracts was followed by methods of DPPH, Hydrogen per-oxide and reducing power scavenging activity. Furthermore the extract was found to possess excellent antimicrobial resistance against different pathagones of 20 bacterea and 6 fungus was determined by Agar Well diffusion method. It reveals that these flowers extracts are of therapeutic potential due to their high free-radical scavenging and antimicrobial susceptibility. The activities may be attributed to the presence of flavanoids and phenolics present in the drug.
N-Acetylglucosamine-1-Phosphate Transferase, WecA, as a Validated Drug Target in Mycobacterium tuberculosis

ABSTRACT The mycobacterial phosphoglycosyltransferase WecA, which initiates arabinogalactan biosynthesis in Mycobacterium tuberculosis, has been proposed as a target of the caprazamycin derivative CPZEN-45, a preclinical drug candidate for the treatment of tuberculosis. In this report, we describe the functional characterization of mycobacterial WecA and confirm the essentiality of its encoding gene in M. tuberculosis by demonstrating that the transcriptional silencing of wecA is bactericidal in vitro and in macrophages. Silencing wecA also conferred hypersensitivity of M. tuberculosis to the drug tunicamycin, confirming its target selectivity for WecA in whole cells. Simple radiometric assays performed with mycobacterial membranes and commercially available substrates allowed chemical validation of other putative WecA inhibitors and resolved their selectivity toward WecA versus another attractive cell wall target, translocase I, which catalyzes the first membrane step in the biosynthesis of peptidoglycan. These assays and the mutant strain described herein will be useful for identifying potential antitubercular leads by screening chemical libraries for novel WecA inhibitors.
Pro-Black Political Opinions, Participation, and Stereotype Threat among African American College Students

We investigate how implicit racial attitudes and stereotype threat affect Black students’ political opinions, political knowledge, and political participation. We use implicit reaction-time procedures to measure relational and evaluative associations (Craemer 2010) among 351 self-identified Black participants mainly from Historically Black Colleges and Universities (HBCUs). Relational associations indicate how closely a student identifies with African Americans as a group, while evaluative associations indicate whether the student associates positive or negative word meaning with the group. We manipulate stereotype threat (Steele & Aronson, 1995, 1998) by presenting an introductory screen either with an all-White research team (high-threat condition), an all-Black research team, or no team-picture at all (low-threat conditions). We find that relational and evaluative associations are uncorrelated: Significant pro-Black implicit group identification coexists with anti-Black evaluative association bias (we refer to this phenomenon as “double non-consciousness”). Implicit Black identification predicts pro-Black political opinions, political knowledge, and political participation. Powerful stereotype threat effects emerge among Black students with strong implicit Black group identification. They answer significantly fewer political knowledge questions correctly when the research team is all-White compared to when it is all-Black or when no picture is presented (p
Traffic Load-Based LPI Control Mechanism in Ethernet Access Network

IEEE802.3az working group has recommended LPI based Energy Efficient Ethernet standard in order to efficiently reduce unnecessary waste of energy that might occur while there is no data to be transmitted. This paper proposes an enhanced LPI control mechanism to improve energy efficiency between terminal equipment and Ethernet switch in an EEE environment. The proposed mechanism measures the amount of traffic coming to the terminal during specific period of time. According to the measured traffic amount, ON and OFF duration for the following basic cycle will be decided. The performance evaluation results indicate that the suggested mechanism improves the overall performance in a way of significant reduction of energy consumption while it maintains an average packet delay to similar levels compared to the traditional method.
DC Microgrids—Part I: A Review of Control Strategies and Stabilization Techniques

This paper presents a review of control strategies, stability analysis, and stabilization techniques for dc microgrids (MGs). Overall control is systematically classified into local and coordinated control levels according to respective functionalities in each level. As opposed to local control, which relies only on local measurements, some line of communication between units needs to be made available in order to achieve the coordinated control. Depending on the communication method, three basic coordinated control strategies can be distinguished, i.e., decentralized, centralized, and distributed control. Decentralized control can be regarded as an extension of the local control since it is also based exclusively on local measurements. In contrast, centralized and distributed control strategies rely on digital communication technologies. A number of approaches using these three coordinated control strategies to achieve various control objectives are reviewed in this paper. Moreover, properties of dc MG dynamics and stability are discussed. This paper illustrates that tightly regulated point-of-load converters tend to reduce the stability margins of the system since they introduce negative impedances, which can potentially oscillate with lightly damped power supply input filters. It is also demonstrated that how the stability of the whole system is defined by the relationship of the source and load impedances, referred to as the minor loop gain. Several prominent specifications for the minor loop gain are reviewed. Finally, a number of active stabilization techniques are presented.
Cluster Based Web Search

The rapid growth of the Internet has made the Web a popular place for collecting information. Internet user access billions of web pages online using search engines. Information in the Web comes from many sources, including websites of companies, organizations, communications and personal homepages, etc. Effective representation of Web search results remains an open problem in the Information Retrieval community and also it put burden of collecting pages relevant to query on user. We develop an approach to organize search results into semantically meaningful groups of web pages and present these to the user as clusters, one for each meaning of the query. With each cluster, our approach provide a summary description that is representative of the real entity associated with that cluster (for the query “mouse”, the summary description may be a list of words such as “a small mammal and a popular pet”). The user can hone in on the cluster of interest to her and get all pages in that cluster.
Building Deep Dependency Structures using a Wide-Coverage CCG Parser

This paper describes a wide-coverage statistical parser that uses Combinatory Categorial Grammar (CCG) to derive dependency structures. The parser differs from most existing wide-coverage treebank parsers in capturing the long-range dependencies inherent in constructions such as coordination, extraction, raising and control, as well as the standard local predicate-argument dependencies. A set of dependency structures used for training and testing the parser is obtained from a treebank of CCG normal-form derivations, which have been derived (semi-) automatically from the Penn Treebank. The parser correctly recovers over 80% of labelled dependencies, and around 90% of unlabelled dependencies.
Transcription factor regulation can be accurately predicted from the presence of target gene signatures in microarray gene expression data

Deciphering transcription factor networks from microarray data remains difficult. This study presents a simple method to infer the regulation of transcription factors from microarray data based on well-characterized target genes. We generated a catalog containing transcription factors associated with 2720 target genes and 6401 experimentally validated regulations. When it was available, a distinction between transcriptional activation and inhibition was included for each regulation. Next, we built a tool (www.tfacts.org) that compares submitted gene lists with target genes in the catalog to detect regulated transcription factors. TFactS was validated with published lists of regulated genes in various models and compared to tools based on in silico promoter analysis. We next analyzed the NCI60 cancer microarray data set and showed the regulation of SOX10, MITF and JUN in melanomas. We then performed microarray experiments comparing gene expression response of human fibroblasts stimulated by different growth factors. TFactS predicted the specific activation of Signal transducer and activator of transcription factors by PDGF-BB, which was confirmed experimentally. Our results show that the expression levels of transcription factor target genes constitute a robust signature for transcription factor regulation, and can be efficiently used for microarray data mining.
Identifying confusable contexts for automatic generation of activities in second language pronunciation training

This paper presents a new technique in the development of tools for Computer-Aided Language Learning (CALL) in Second Language (L2) pronunciation training. Instead of the usual pinpointing and feedback strategies, which address all production errors in the L2 speaker equally, this technique aims at honing in on where a pronunciation error can lead to a confusion in the transmission of the message and providing these contexts for practice. To provide this new correction strategy, it is necessary to first identify the words and contexts which can lead to a confusion in a message when there is a mispronunciation in them. This paper describes a Basic Identification of Confusable Contexts (BICC) procedure for detecting these cases providing a measure of their relevance. It also includes a methodological validation of BICC with humans assessing the quality and comprehensibility of a dataset of automatically generated sentences which shows that the prediction of these contexts is possible with good precision.