Miracle-dz/UniFAR-FTUs huggingface dataset:
Calcium homeostasis disruption and endoplasmic reticulum stress mediats ischemia / reperfusion-induced PC 12 cells apoptosis

Background: Ischemic stroke is a major cause of morbidity and mortality in the world today. Endoplasmic reticulum stress (ERS) is an essential signaling event for neuronal injury resulting from IR. Calcium signals play important roles in physiological activities which regulate many fundamental cellular processes. However, the role of intracellular calcium signals and ERS at the early stage of IR-induced apoptosis remains largely elusive. Objective: To investigate whether intracellular Ca2+ participate in IR-induced apoptosis as an upstream messenger in an in vitro model of ischemia-reperfusion (IR). Methods: An in vitro model of IR was established according to literature. The expression of SERCA2, GRP78, caspase-12 and CHOP were evaluated by western blot during different reperfusion time intervals. Results: The apoptotic rates and [Ca]i in PC12 cells increased in a reperfusion time-dependent manner, the vitality of SERCA decreased with reperfusion time gradually. A stable SERCA protein decrease was observed throughout the entire time course. The expression of GRP78, caspase-12 and CHOP were up-regulated after IR. Conclusion: IR induced [Ca]i elevation at the early stage of apoptosis, which might involve Ca 2+ efflux from the endoplasmic reticulum and Ca2+ influx from extracellular medium. Calcium signals and ERS were the important upstream messengers in IR-induced apoptosis in PC12 cells.
Chapter 3 Design and Analysis of Computer Experiments

Computer experiments refer to the study of complex systems using mathematical models and computer simulations. The use of computer experiments becomes popular for studying complex systems in science and engineering. The design and analysis of computer experiments have received broad attention in the past decades. In this chapter, we present several widely used statistical approaches for design and analysis of computer experiments, including space-filling designs and Gaussian process modeling. A special emphasis is given to recently developed design and modeling techniques for computer experiments with quantitative and qualitative factors.
245147 ( 2019 ) Single pair of Weyl fermions in the half-metallic semimetal EuCd 2 As 2

Materials with the ideal case of a single pair of Weyl points (WPs) are highly desirable for elucidating the unique properties of Weyl fermions. EuC d 2 A s 2 is an antiferromagnetic topological insulator or Dirac semimetal depending on the different magnetic configurations. Using first-principles band-structure calculations, we show that inducing ferromagnetism in EuC d 2 A s 2 can generate a single pair of WPs from splitting the single pair of antiferromagnetic Dirac points due to its half-metallic nature. Analysis with a lowenergy effective Hamiltonian shows that a single pair of WPs is obtained in EuC d 2 A s 2 because the Dirac points are very close to the zone center and the ferromagnetic exchange splitting is large enough to push one pair of WPs to merge and annihilate at Γ while the other pair survives. Furthermore, we predict that alloying with Ba at the Eu site can stabilize the ferromagnetic configuration and generate a single pair of Weyl points without application of a magnetic field. Disciplines Condensed Matter Physics | Materials Science and Engineering Authors Lin-Lin Wang, Na Hyun Jo, Brinda Kuthanazhi, Yun Wu, Robert J. McQueeney, Adam Kaminski, and Paul C. Canfield This article is available at Iowa State University Digital Repository: https://lib.dr.iastate.edu/ameslab_manuscripts/415 PHYSICAL REVIEW B 99, 245147 (2019) Single pair of Weyl fermions in the half-metallic semimetal EuCd2As2 Lin-Lin Wang,1,* Na Hyun Jo,2 Brinda Kuthanazhi,2 Yun Wu,2 Robert J. McQueeney,1,2 Adam Kaminski,1,2 and Paul C. Canfield1,2 1Ames Laboratory, U.S. Department of Energy, Ames, Iowa 50011, USA 2Department of Physics and Astronomy, Iowa State University, Ames, Iowa 50011, USA (Received 25 January 2019; published 26 June 2019) Materials with the ideal case of a single pair of Weyl points (WPs) are highly desirable for elucidating the unique properties of Weyl fermions. EuCd2As2 is an antiferromagnetic topological insulator or Dirac semimetal depending on the different magnetic configurations. Using first-principles band-structure calculations, we show that inducing ferromagnetism in EuCd2As2 can generate a single pair of WPs from splitting the single pair of antiferromagnetic Dirac points due to its half-metallic nature. Analysis with a low-energy effective Hamiltonian shows that a single pair of WPs is obtained in EuCd2As2 because the Dirac points are very close to the zone center and the ferromagnetic exchange splitting is large enough to push one pair of WPs to merge and annihilate at while the other pair survives. Furthermore, we predict that alloying with Ba at the Eu site can stabilize the ferromagnetic configuration and generate a single pair of Weyl points without application of a magnetic field. DOI: 10.1103/PhysRevB.99. 245147
Multi-Study Proteomic and Bioinformatic 2 Identification of Molecular Overlap between ALS 3 and SMA 4

Unravelling the complex molecular pathways responsible for motor neuron degeneration 16 in amyotrophic lateral sclerosis (ALS) and spinal muscular atrophy (SMA) remains a persistent 17 challenge. Interest is growing in the potential molecular similarities between these two diseases, 18 with the hope of better understanding disease pathology for the guidance of therapeutic 19 development. The aim of this study was to conduct a comparative analysis of published proteomic 20 studies of ALS and SMA, seeking commonly dysregulated molecules to be prioritised as future 21 therapeutic targets. Fifteen proteins were found to be differentially expressed in two or more 22 proteomic studies of both ALS and SMA, and bioinformatics analysis identified 23 over-representation of proteins known to associate in vesicles, and molecular pathways, including 24 metabolism of proteins and vesicle-mediated transport; both of which converge on ER-Golgi 25 trafficking processes. Calreticulin, a calcium-binding chaperone found in the ER, was associated 26 with both pathways and we independently confirm that its expression was decreased in spinal 27 cords from SMA and increased in spinal cords from ALS mice. Together, these findings offer 28 significant insights into potential common targets that may help to guide the development of new 29 therapies for both diseases. 30
An Integration of Round Robin with Shortest Job First Algorithm for Cloud Computing Environment

Cloud computing is a recent scientific revolution in information technology that promises a delivery of computing as a service rather than a product, whereby shared resources, software, and information are provided to computers and other devices as a utility (like the electricity grid) over a network (typically the Internet). Delivery of services is provided to computers and other devices upon request. In other words, it is a technology based on the internet and central remote servers to maintain data and applications. This technology allows consumers and enterprises to use applications without the need of installing them or allowing access to their personal files at any computer with internet access. It has many merits except that there are some crucial issues that need to be resolved in order to improve reliability of cloud environment. These issues are related with the job Scheduling, fault tolerance and different security issues in cloud environment. One of the most popular job scheduling algorithms that gives satisfactory load balancing is Round Robin (RR). This paper proposes an enhancement to the traditional RR, namely Round Robin with Shortest Job First (RRSJF). The enhanced version of RR algorithm is based on the integration of round-robin with shortest job first algorithm that selects for processes based on shortest job first in a round robin fashion to give optimal selection of job. A simulation has been carried out using CloudSim simulator V 3.0 to test the performance of the proposed scheme in terms of different evaluation metrics such as average turnaround, average waiting time and context switches. This Scheduling algorithm gives better result compared to Round Robin (RR).
Polyphyly of Bikkia Reinw . ( Rubiaceae ) based on multi-locus sequence analysis ( ITS , rps 16 , trnL-F ) , with emphasis on the endemic Bikkia philippinensis Val . including its conservation status

Bikkia Reinw. is a shrubby genus of the tribe Chiococceae s.s. (Rubiaceae) with ca. 20 species. A recent molecular phylogenetic study of the tribe using two markers showed that Bikkia is polyphyletic forming two separate clades, the bases of which are habitat and corolla shape. The endemic Bikkia philippinensis was excluded in their analysis due to the lack of plant material. The present study utilized three molecular markers (ITS, rps16, and trnL-F) to test the polyphyly of Bikkia as currently circumscribed, determine the phylogenetic position of the B. philippinensis in the previously identified two groups, and assess its conservation status. Our combined data tree showed that Bikkia is highly polyphyletic. The B. philippinensis is nested within the coastal group, together with the type species Bikkia tetranda. The result of the molecular analysis is also congruent with the habitat data and morphology wherein B. philippinensis was found to thrive in coastal areas and possess infundibular corolla. Finally, B. philippinensis was found to be a critically endangered species based on population size.
Understanding Worker Moods and Reactions to Rejection in Crowdsourcing

Requesters on crowdsourcing platforms typically exercise the power to decide the fate of tasks completed by crowd workers. Rejecting work has a direct impact on workers; (i) they may not be rewarded for the work completed and for their effort that has been exerted, and (ii) rejection affects worker reputation and may limit their access to future work opportunities. This paper presents a comprehensive study that aims to understand worker moods and how workers react to rejections in microtask crowdsourcing. We experimentally investigate the effect of the mood of workers on their performance, and the interaction of their moods with their reactions to rejection. Finally, we explore techniques such as presenting social comparative explanations to foster positive reactions to rejection. We found that workers in pleasant moods significantly outperform those in unpleasant moods. Workers whose work is rejected due to narrowly failing pre-screening tests exhibited the most negative emotional responses.
Construction of an Expression Vector Containing a Novel Fusion Sequence from Middle Region of NS 3 and Truncated Core Genes of Hepatitis C Virus

Background and Aims: DNA constructs containing HCV antigens have become one of the vaccine candidates for induction of anti-HCV cellular and humoral immunity. In this study, we constructed a novel expressing vector harboring a fusion sequence derived from an overlapping fragment in the middle of NS3 and a truncated core fragment to avoid troubles reported to be associated with full gene expression. Methods: The partial NS3 (pNS3) and core genes were amplified by RT-PCR method using serum of HCV infected patient harboring genotype 1a of virus. After purification and cloning the genes into TA-cloning vector, they were evaluated by sequencing and restriction digestion analysis. The resultant pNS3 and core gene subcloned into expression vector separately followed by expression evaluation using RT-PCR and western blotting. The core expressing vector exploited for amplification of a new truncated core (50-160aa) sequence using PCR. Truncated core fragment was first cloned into TA vector at a natural restriction site downstream of pNS3 fragment. The resulting fused sequence was cut and subcloned into expression vector. The integrity and ability of expression of this fused sequence was evaluated by sequencing followed by RT-PCR analysis after DNA transfection into 293 cells. Results: The repeated sequencing data showed sequence integrity among the gene fragments as well as homology among them and reference 1a sequences. The colony-PCR, RT-PCR and western blotting confirmed insertion of genes into expressing vector, expression of genes in 293 cell line and production of protein in 293 respectively. Conclusion: This new expressing vector harboring a novel fused fragments of NS3 and core genes may overcome shortcomings in vaccine design in the setting of HCV disease.
PROBABILITY DENSITY FUNCTIONS FOR SECONDARY SEISMIC PHASE ARRIVALS

Seismic sources can be easily located with high confidence using only first-arriving P phases when there are large numbers of recording stations, well distributed in azimuth and distance. This is seldom the case, however, for seismic sources of interest to the nuclear explosion monitoring community. In cases of poor azimuthal distribution or small numbers of recording stations, improved accuracy may be gained by incorporating arrival times of secondary phases, but only if phase associations and weighting can be done in a statistically-valid manner. Under this project, we are developing a methodology to use probability density functions (PDFs) for this purpose, with the ultimate goal of making the use of secondary phases a standard part of routine earthquake location procedures. Following Buland (1986) we model the PDFs as a combination of Gaussian and Cauchy distributions, and we explore the usefulness of allowing the relative proportions of these parent distributions to vary for different phases. Sets of PDFs (for secondary phases of interest) are closely tied to the data sets from which they are derived, because the observability of different phases depends on the instrumentation, processing, and analysis procedures employed by contributing stations. A standard methodology for deriving estimates of PDF sets from different data sets is presented, with preliminary results of the analysis of two important arrival time data sets: a subset of ~17,000 welllocated seismic sources from the International Seismic Centre (ISC) catalog, processed according to the methodology developed by Engdahl, van der Hilst, and Buland (the EHB standard, Engdahl et al, 1998), and an equivalent data set of arrival times from the Center for Monitoring Research. We propose an algorithm for phase association and weighting, based on these PDF sets, and compare locations of test data sets using traditional and PDF-based location methods. 252 24th Seismic Research Review – Nuclear Explosion Monitoring: Innovation and Integration
Apr 25 th , 9 : 05 AM Data Mining Techniques for Fraud Detection

The paper presents application of data mining techniques to fraud analysis. We present some classification and prediction data mining techniques which we consider important to handle fraud detection. There exist a number of data mining algorithms and we present statistics-based algorithm, decision tree-based algorithm and rule-based algorithm. We present Bayesian classification model to detect fraud in automobile insurance. Naïve Bayesian visualization is selected to analyze and interpret the classifier predictions. We illustrate how ROC curves can be deployed for model assessment in order to provide a more intuitive analysis of the models.
Baseline Evaluation of Smartphone based Finger-photo Verification System : A Preliminary Study of Technology Readiness

Increasingly, smartphones come embedded with more and more advanced biometric recognition systems. The high quality embedded sensors capture the biometric data which helps to get higher biometric recognition accuracy and security. On the other hand, these sensors increase the cost in terms of battery usage, take up extra physical space also some hardware cost. This paper investigates the reliability and effectiveness of fingerphoto verification system developed using a smartphone. Consequently, biometric samples can be collected without the need for dedicated hardware, thus providing a cost-effective and reliable way to do biometric authentication. The focus of this paper is to study various baselines to evaluate the readiness of the technology. To this extent, we present a comparison between three non-commercial baseline systems with one commercial system. The commercial off-the-shelf (COTS) system shows the best performance of an equal error rate of 6.08%.
Robotic tool use and problem solving based on probabilistic planning and learned affordances

The ability of predicting the consequences of actions is a distinctive sign of human intelligence. Predictions are used to efficiently plan actions sequences that allow problem solving. This ability is acquired incrementally by humans during development through sensorimotor experience: i.e. interacting with objects while perceiving salient events. An appealing concept to represent this sensorimotor knowledge has been proposed in psychology under the name of object affordances: action possibilities that an object offers to an agent. Affordances are learned by the agent (animal or robot) and exploited for action planning. Clearly, endowing artificial agents with such cognitive capabilities is a fundamental challenge both in artificial intelligence and robotics. We propose a framework in which an embodied agent (i.e. in our case, the humanoid robot iCub) explores the environment and learns object affordances as relationships between actions, object visual properties and observed effects. The learned affordances enable a number of cognitive skills: e.g. i) predicting the effects of an action over an object, or ii) selecting the best action to obtain a desired effect. By exploring object-object interactions the robot can develop the concept of tool (i.e. a hand-held object that allows to obtain a desired effect on another object), and eventually use the acquired knowledge to plan sequences of actions to attain a desired goal (i.e. problem solving).
Do Agricultural Loans Help Reduce Rural-Urban Income Inequality ? Evidence from Chinese Provincial Data 1978-2013

We hypothesize that (1) dualism (i.e., low agricultural productivity relative to economy-wide productivity) is an important contributing factor to rural-urban inequality; and (2) the degree of dualism is influenced by the agricultural sector’s ability to obtain loans. We present evidence from Chinese provincial data for the period 1978-2013 which confirm our hypotheses, and contend that improving access to agricultural loans would help reduce ruralurban income inequality.
Efficient Reduced-Bias Genetic Algorithm (ERBGA) for Generic Community Detection Objectives

Community structure identification has been an important research area for biology, physics, information systems, and social sciences for studying properties of networks representing complex relationships. Lately, Genetic Algorithms (GAs) are being utilized for community detection. GAs are machine-learning methods that mimic natural selection. However, previous approaches suffer from some deficiencies: redundant representation and linearity assumption, that we will try to address. in. The algorithm presented here is a novel framework that addresses both of these above issues. This algorithm is also flexible as it is easily adapted to any given mathematical objective. Additionally, our approach doesn’t require prior information about the number of true communities in the network. Overall, our efficient approach holds potential for sifting out communities representing complex relationships in networks of interest across different domains.
Ant Lion Optimization Based Controller Tuning for Automatic Generation Control of Multiarea Interconnected Thermal System

An AGC maintains the frequency of the system by balancing the active power generation to the load demand. The frequency of the system is dependent on the active power supply of the system according to the load changes. A conventional PID controller is generally employed to achieve AGC. However, proper tuning of controller parameter is required in order to achieve satisfactory controller performance. So, the proper choice of design objectives and the tuning method play very important part in AGC. In this work, a PID controller with derivative term is tuned to control the frequency and tie-line power deviations of a two-area non-reheat thermal system using Ant Lion optimization (ALO) algorithm. ALO is an efficient optimization algorithm which is based on the behavior of ant lions. For optimization purpose, the fitness function is formulated by considering settling times of deviations in frequency and tie-line power deviations and the integral errors. Four different cases of load perturbation conditions in both areas are considered. A comparative assessment of the proposed controller is carried out with PSO based controller and the obtained results are tabulated. Time-domain simulations are carried out to further establish the superior performance of the proposed controller.
Fuzzy Logic Analysis of Photovoltaic Data for Obstacle Avoidance or Mapping Robot

The utilization of only existing radiant sources in autonomous and mobile robotics is a relatively new field. These radiant sources, referred to as ambient radiation were “the noise and errors” in the production of various range finding and obstacle locating sensors. The research looks to developing methods to utilize this “noise” for autonomous robot mobility and addresses the inherent problems associated with dynamically changing environment analysis. A fuzzy logic topology is adapted in the processing of amplified data from an array of sensors in photovoltaic mode. The “fuzzified” data may be used for the purposes of obstacle avoidance or for higher level applications such as item location, fire detection and environmental mapping. DOI: http://dx.doi. org/10.5755/j01.eee. 19.1. 3243
University of Groningen Self-Esteem Instability in Current, Remitted, Recovered, and Comorbid Depression and Anxiety

Self-esteem has not only been observed to be generally low in depression and anxiety, but also unstable. Few studies have looked at unstable self-esteem in clinical samples. The present study compared self-reported self-esteem instability across current depression (n = 60), anxiety (n = 111), and comorbid depression/anxiety (n = 71), remitted depression (n = 41), and anxiety (n = 29), recovered depression (n = 136) and anxiety (n = 98), and a never clinically depressed or anxious comparison group (n = 382). The comparison group had more stable self-esteem than all groups. Once controlling for overall levels of self-esteem, differences with current depression or anxiety, remitted depression, and recovered depression or anxiety remained, but disappeared for the comorbid group. The current findings are consistent with the view that not only enduring low self-esteem per se, but also high selfesteem reactivity may contribute to the aetiology of affective disorders.