Miracle-dz/UniFAR-FTUs huggingface dataset:
Preferential localization of a vesicular monoamine transporter to dense core vesicles in PC12 cells

Neurons and endocrine cells have two types of secretory vesicle that undergo regulated exocytosis. Large dense core vesicles (LDCVs) store neural peptides whereas small clear synaptic vesicles store classical neurotransmitters such as acetylcholine, gamma-aminobutyric acid (GABA), glycine, and glutamate. However, monoamines differ from other classical transmitters and have been reported to appear in both LDCVs and smaller vesicles. To localize the transporter that packages monoamines into secretory vesicles, we have raised antibodies to a COOH- terminal sequence from the vesicular amine transporter expressed in the adrenal gland (VMAT1). Like synaptic vesicle proteins, the transporter occurs in endosomes of transfected CHO cells, accounting for the observed vesicular transport activity. In rat pheochromocytoma PC12 cells, the transporter occurs principally in LDCVs by both immunofluorescence and density gradient centrifugation. Synaptic-like microvesicles in PC12 cells contain relatively little VMAT1. The results appear to account for the storage of monoamines by LDCVs in the adrenal medulla and indicate that VMAT1 provides a novel membrane protein marker unique to LDCVs.
Towards a trustworthy privacy in pervasive video surveillance systems

The consideration of security and privacy is a linchpin of the social acceptance of pervasive technology. This paper paves the way to the development of trustworthy pervasive video surveillance systems, by emphasizing the need to properly combine different aspects that current systems do not manage. In particular, in this paper we propose the combination of the following issues into a common framework: proper people identification mainly based on computer vision techniques, content protection not only by using convenient cryptographic techniques, but also law enforcement and user cooperation in order to get feedback with regard to the whole video surveillance system. Furthermore, an analysis focused on the current computer vision techniques used for people identification is presented. Finally, a score to measure the trust offered by video surveillance systems is proposed.
Local averaging and differentiating of spectral plane for TRAP-based ASR

Local frequency and time averaging and differentiating operators, using three neighboring points of critical-band time-frequency plane, are used to process the plane prior to its use in TRAP-based ASR. In that way, ﬁve alternative TRAP-based ASR systems (the original one and the time/frequency integrated/differentiated ones)are created. We show that the frequency differentiating operator improves performance of the TRAP-based ASR
Parent teaching, cumulative instability and school readiness for children attending Head Start preschool

ABSTRACT This study investigated relations between parent teaching, cumulative instability/chaos and school readiness in a group of 130 children attending a Head Start preschool. Cumulative instability/chaos negatively predicted fall school readiness as well as spring school readiness. Parent teaching did not predict fall school readiness but did predict spring school readiness. Fall school readiness predicted spring school readiness, suggesting the possibility that this variable helped to carry the effect of cumulative instability/chaos, as measured in the fall of the preschool year, to spring school readiness. Fall school readiness mediated the relationship between fall cumulative instability and spring school readiness. Implications for intervention efforts are discussed.
Machinic rhetorics and the influential movements of robots

ABSTRACT From spiritual vehicles, channeling the miracle of Christ, to science incarnate, operating beyond human interest, machines can communicate. Building from literatures on posthuman performance and ambient rhetoric, this article develops “machinic rhetoric” as a framework useful for appreciating the tacitly persuasive actions of machines (such as robots and computers). A selective history of machinic movement is traced to highlight the historico-cultural meanings that can be associated with the movements of machines. Expert systems, machine learning platforms, and voice-based interfaces are examined as contemporary examples of machinic rhetorics. Implications of machinic rhetoric to scholarship of technology and rhetoric are considered.
High-resolution rotation curves of low surface brightness galaxies

We present high-resolution rotation curves of a sample of 26 low surface brightness galaxies. From these curves we derive mass distributions using a variety of assumptions for the stellar mass-to-light ratio. We show that the predictions of current Cold Dark Matter models for the density proles of dark matter halos are inconsistent with the observed curves. The latter indicate a core-dominated structure, rather than the theoretically preferred cuspy structure.
Profile-Based Load Balancing for Heterogeneous Clusters *

Cluster computing is becoming increasingly popular for providing cost-effective and affordable parallel computing for day-to-day computational needs [2, 11, 16]. Such environments consist of clusters of workstations connected by Local Area Networks (LANs). The possibility of the incremental expansion of clusters by incorporating new generations of computing nodes and networking technologies is another factor contributing to the popularity of cluster computing. However, this incremental expansion leads to heterogeneity in speed and communication capability of workstations, systems with different memory and cache organization, coexistence of multiple network architectures, and availability of alternative communication protocols. This is forcing the cluster computing environments to be redefined as heterogeneous clusters.
Whom Does Your Android App Talk To?

Smartphone privacy and security work has focused mostly on malicious apps. We take a different angle by questioning whether good apps suffer from a lack of judgment and interact with "bad" websites. We use the term bad websites to refer to entities that engage in dangerous or annoying activities that range from distributing malware, to phishing and overly aggressive ad spamming. The focus of our work is this relatively neglected aspect of security: "Whom does an app talk to? " In this paper, we design and implement AURA, a framework for identifying the hosts that an app talks to and evaluating the risks this communication entails. AURA makes use of both static and dynamic analysis. We studied 13,500 popular free Android apps that connect to 254,022 URLs and 1,260 malicious Android apps that connect to 19,510 URLs. Our main contribution is showing that good apps pose security risks as they contact at least one website that: (a) distributes malware (8.8% of apps), (b) are in a blacklist (15% of apps) based on the classification by VirusTotal and Web of Trust. Our work can raise awareness that even good apps need to be carefully evaluated, especially as people become more concerned about smartphone security and privacy.
The Beginning of the End: Hubble Space Telescope Images of Seyfert’s Sextet

Hubble Space Telescope (HST) Wide Field Planetary Camera 2 images of Hickson Compact Group (HCG) 79, Seyfert's Sextet, are presented. Both point sources and extended sources detected on the three wide-field chips were photometered in four filters: F336W, F439W, F555W, and F814W. Unlike other HCGs that have been imaged with HST, there do not appear to be any candidate young star clusters among the detected point sources. The majority of the point sources that may be star clusters associated with the Sextet have red colors consistent with stellar populations older than 1 Gyr. A similar conclusion is drawn with regard to the extended sources. The majority of these appear to be background galaxies, but a few candidate dwarf galaxies are identified as potentially associated with Seyfert's Sextet. However, no blue, star-forming objects similar to the tidal dwarf galaxy candidates identified in other HCGs are found among the extended objects identified in this study. A redshift for one dwarf galaxy candidate was measured from a spectrum obtained with the Hobby-Eberly Telescope, and this object was found to have a redshift similar to NGC 6027e, the discordant spiral formerly identified as a member of this compact group. The HST observations presented here and previous radio observations of the neutral gas content of this group suggest that the interactions that have taken place in the Sextet only redistributed the stars from the member galaxies within the group. We speculate that future interactions may be strong enough to strip the gas from NGC 6027d and trigger star-cluster formation.
A System for Synchronous Distance Learning

Providing an effective mechanism for an instructor to interact with one or more remote classrooms is a complex problem in synchronous distance learning. Although a human operator at the remote classroom could be used to direct a video camera and hence provide feedback to the instructor as to the state of the class and to coordinate the instructor’s attention to the class as questions are raised, more automated techniques are desirable. Here we describe a novel audiovisual sensor to support distance learning. This sensor provides the instructor with a panoramic view of the class and can automatically attend to students who signal their intent to interact with the instructor either by raising their hand or by asking a question vocally. This paper describes the sensor and the user interface that is provided to the instructor so (s)he can interact with the students in the remote class.
FLCFE: A Novel Method for Extracting Content Features of Flash

With the advancement and development of the Internet, Flash has penetrated into all aspects of people's lives. As a popular multimedia, Flash has the advantages of strong artistic expressions, simple manufacture, flexible interaction and small storage, so Flash is widely used on the Internet. Currently, the shortages of researches about extracting content features of Flash seriously impose restrictions on the retrieval and utilization of Flash. Therefore, this paper proposes a novel method called FLCFE which is used for extracting content structure features from Flash. The method can effectively extract the content features of Flash, such as metadata information and component elements. On the basis of optimizing the efficiency of FLCFE, we build an experimental prototype of FLCFE through C++. Several simulation experiments based on three parameters, the Precision Ratio, the Recall Ratio and the Time Consumption, have been carried out respectively. Results show that FLCFE not only has good performances of the Recall Ratio and the Precision Ratio, but also has stable performance of time efficiency.
Privacy Preserving SQL Queries

One of the most substantial ways to protect sensitive information is encryption of data. However, the cryptographic method brings in some problems such as inefficiency and malfunctioning, especially impossibility of arithmetic. The previous works in this area have been proved insecure or can provide only a few or several SQL queries. Actually, there is no scheme which can support secure all kinds of SQL queries and arithmetic. We propose a novel scheme to solve this problem. We do not encrypt every data itself but permute all the data within each attribute so that we can break the relation of the data and the owner. Accordingly, the proposed scheme guarantees intractability of re-identification for data-owners' privacy and at the same time enables the miner to get the information he wants.
The Development of Argument Structure in Central Taurus Sign Language

Abstract:One of the fundamental issues for a language is its capacity to express argument structure unambiguously. This study presents evidence for the emergence and the incremental development of these basic mechanisms in a newly developing language, Central Taurus Sign Language. Our analyses identify universal patterns in both the emergence and development of these mechanisms and in language-specific trajectories.
Hypotensive, Angiotensin Converting Enzyme (ACE) Inhibitory and Diuretic Activities of the Aqueous-methanol Extract of Ipomoea reniformis

Ipomoea reniformis Roxb. (Convolvulaceae) is a small, weedy herb used for the management of cardiac problems in traditional systems of medicine in India and Pakistan. Objective of the present study was to investigate the hypotensive, diuretic and angiotensin converting enzyme (ACE) inhibitory activities of the aqueous-methanol (30:70) crude extract of the dried aerial parts of I. reniformis (Ir.Cr.) in rats. To record blood pressure lowering effects of the Ir.Cr, different doses of the extract were administered through jugular vein to the ketamine-diazepam anesthetized normotensive rats and blood pressure was recorded via carotid artery. ACE inhibitory activity of the extract was studied in-vitro; using hippuryl-l-histidyl-l-leucine as substrate, the product hippurate was quantified spectrophotometrically after reacting with cyanuric chloride/dioxane reagent. Effects of intraperitoneal administration of the extract on urine and urinary electrolyte excretion were also investigated in rats. The extract (Ir.Cr.) produced 21.51 ± 3.41, 28.99 ± 2.30, 53.34 ± 0.88 and 61.71 ± 3.37% fall in mean arterial blood pressure of the anesthetized rats at the doses of 0.1, 0.3, 1.0 and 3.0 mg/Kg, respectively. Ir.Cr. was found to have serum ACE inhibitory activity, with IC50 value of 422 ± 21.16 μg/mL. The extract also increased urine volume and urinary Na+ excretion significantly at the doses of 30 and 50 mg/Kg in rats. The study concludes that the crude extract of Ipomoea reniformis (Ir.Cr.) has hypotensive, ACE inhibitory and diuretic activities, which provide the scientific justification for the traditional uses of the plant as cardioprotective, antihypertensive and diuretic remedy.
An Evaluation of Different Training Sample Allocation Schemes for Discrete and Continuous Land Cover Classification Using Decision Tree-Based Algorithms

Land cover mapping for large regions often employs satellite images of medium to coarse spatial resolution, which complicates mapping of discrete classes. Class memberships, which estimate the proportion of each class for every pixel, have been suggested as an alternative. This paper compares different strategies of training data allocation for discrete and continuous land cover mapping using classification and regression tree algorithms. In addition to measures of discrete and continuous map accuracy the correct estimation of the area is another important criteria. A subset of the 30 m national land cover dataset of 2006 (NLCD2006) of the United States was used as reference set to classify NADIR BRDF-adjusted surface reflectance time series of MODIS at 900 m spatial resolution. Results show that sampling of heterogeneous pixels and sample allocation according to the expected area of each class is best for classification trees. Regression trees for continuous land cover mapping should be trained with random allocation, and predictions should be normalized with a linear scaling function to correctly estimate the total area. From the tested algorithms random forest classification yields lower errors than boosted trees of C5.0, and Cubist shows higher accuracies than random forest regression.
Reversal of Ampicillin Resistance in MRSA via Inhibition of Penicillin-Binding Protein 2a by Acalypha wilkesiana

The inhibitory activity of a semipure fraction from the plant, Acalypha wilkesiana assigned as 9EA-FC-B, alone and in combination with ampicillin, was studied against methicillin-resistant Staphylococcus aureus (MRSA). In addition, effects of the combination treatment on PBP2a expression were investigated. Microdilution assay was used to determine the minimal inhibitory concentrations (MIC). Synergistic effects of 9EA-FC-B with ampicillin were determined using the fractional inhibitory concentration (FIC) index and kinetic growth curve assay. Western blot experiments were carried out to study the PBP2a expression in treated MRSA cultures. The results showed a synergistic effect between ampicillin and 9EA-FC-B treatment with the lowest FIC index of 0.19 (synergism ≤ 0.5). The presence of 9EA-FC-B reduced the MIC of ampicillin from 50 to 1.56 μg mL−1. When ampicillin and 9EA-FC-B were combined at subinhibitory level, the kinetic growth curves were suppressed. The antibacterial effect of 9EA-FC-B and ampicillin was shown to be synergistic. The synergism is due the ability of 9EA-FC-B to suppress the activity of PBP2a, thus restoring the susceptibility of MRSA to ampicillin. Corilagin was postulated to be the constituent responsible for the synergistic activity showed by 9EA-FC-B.
Efficient Maximum-Likelihood Inference For The Isolation-With-Initial-Migration Model With Potentially Asymmetric Gene Flow

The isolation-with-migration (IM) model is commonly used to make inferences about gene flow during speciation, using polymorphism data. However, Becquet and Przeworski (2009) report that the parameter estimates obtained by fitting the IM model are very sensitive to the model's assumptions (including the assumption of constant gene flow until the present). This paper is concerned with the isolation-with-initial-migration (IIM) model of Wilkinson-Herbots (2012), which drops precisely this assumption. In the IIM model, one ancestral population divides into two descendant subpopulations, between which there is an initial period of gene flow and a subsequent period of isolation. We derive a very fast method of fitting an extended version of the IIM model, which also allows for asymmetric gene flow and unequal population sizes. This is a maximum-likelihood method, applicable to data on the number of segregating sites between pairs of DNA sequences from a large number of independent loci. In addition to obtaining parameter estimates, our method can also be used to distinguish between alternative models representing different evolutionary scenarios, by means of likelihood ratio tests. We illustrate the procedure on pairs of Drosophila sequences from approximately 30,000 loci. The computing time needed to fit the most complex version of the model to this data set is only a couple of minutes. The R code to fit the IIM model can be found in the supplementary files of this paper.
Evidence of Insulin Resistance and Other Metabolic Alterations in Boys with Duchenne or Becker Muscular Dystrophy

Aim. Our aim was (1) to determine the frequency of insulin resistance (IR) in patients with Duchenne/Becker muscular dystrophy (DMD/BMD), (2) to identify deleted exons of DMD gene associated with obesity and IR, and (3) to explore some likely molecular mechanisms leading to IR. Materials and Methods. In 66 patients with DMD/BMD without corticosteroids treatment, IR, obesity, and body fat mass were evaluated. Molecules involved in glucose metabolism were analyzed in muscle biopsies. Results show that 18.3%, 22.7%, and 68% were underweight, overweight, or obese, and with high adiposity, respectively; 48.5% and 36.4% presented hyperinsulinemia and IR, respectively. Underweight patients (27.3%) exhibited hyperinsulinemia and IR. Carriers of deletions in exons 45 (OR = 9.32; 95% CI = 1.16–74.69) and 50 (OR = 8.73; 95% CI = 1.17–65.10) from DMD gene presented higher risk for IR than noncarriers. We observed a greater staining of cytoplasmic aggregates for GLUT4 in muscle biopsies than healthy muscle tissue. Conclusion. Obesity, hyperinsulinemia, and IR were observed in DMD/BMD patients and are independent of corticosteroids treatment. Carriers of deletion in exons 45 or 50 from DMD gene are at risk for developing IR. It is suggested that alteration in GLUT4 in muscle fibers from DMD patients could be involved in IR.
A new inverse optimal control method for discrete-time systems

This paper presents a new approach based on extended kalman filter (EKF) to construct a control lyapunov function (CLF). This function will be used in establishing the control law of inverse optimal control for discrete-time nonlinear systems. The main aim of the inverse optimal control is to avoid the solution of the difficult Hamilton-Jacobi-Bellman (HJB) equation which is resulted from the traditional solution of nonlinear optimal control problem. The relevance of the proposed scheme is illustrated through MATLAB simulation. The results show the effectiveness of the proposed method.
Recursive Self Organizing Maps with Hybrid Clustering

We introduce the concept of a neural network based recursive clustering which creates an ensemble of clusters by recursive decomposition of data. The work involves a hybrid combination of a global clustering algorithm followed by a corresponding local clustering algorithm. Evolutionary self organizing maps are used to create clusters. A set of core patterns is isolated and separately trained using a SOM. The process is recursively applied to the remaining patterns to create an ensemble of clusters. The partition of each recursion is integrated with the partition of the previous recursion. The correlation of the clusters with ground truth information (in the form of class labels) is used to measure algorithm robustness. The paper shows that a hybrid combination of evolutionary algorithms and neural network based clustering techniques is efficient in finding good partitions of clusters and in finding suitable resultant cluster shapes. The recursive self organizing map proposed aims to improve the clustering accuracy of the self organizing map. Empirical studies show that superior results are obtained when clustering artificially generated data as well as real world problems such as the Iris, Glass and Wine datasets
Volume is not enough: SVC-aware server allocation for peer-assisted streaming

Peer-assisted delivery of video content has shown a great potential to reduce upload bandwidth requirements for content providers by exploiting idle client resources in the video dissemination process. As primary content sources, the servers run by content providers play a critical role in such systems, making their adequate provisioning a key part of the streaming mechanism. While dynamic resource provisioning has been studied before, little is known about resource allocation for streaming of scalable media content. Besides the pure amount of resources, here, the quality level of the delivered video content becomes relevant. The spreading of video blocks with the wrong quality can lead to situations where peers are forced to reduce their video qualities, despite them having enough download capacity. To address this problem, in this paper, a new SVC-based adaptation policy and a request-based extension to it are proposed, enabling content providers to manage their streaming services in a video quality-aware manner. Prototypical evaluations show that the mechanisms outperform existing quality-agnostic approaches in terms of delivered SVC video quality.
ontoMATCH: A probabilistic architecture for ontology matching

There is a great deal of research on the structural and logical matching of ontologies, and there is also considerable work on matching data instances from heterogeneous schema or ontologies, however, little work exploits the fact that ontologies include both data and structure. In this paper, we aim to present a new ontology matching architecture that tightly integrates both semantic similarity measure and structure matching to achieve better matching of ontologies. Based on the observation that semantic similarity measure is a fundamental operation in ontology matching, we first proposed a semantic similarity measure (simDAG) based on WordNet using both the directed graph theory and the probabilistic theory, experimental results show its obvious advantages. Then, we proposed a compound ontology matching architecture (ontoMATCH) considering properties, elements and relationships in ontologies. At last, we evaluate ontoMATCH on the OAEI benchmark set of tests with encouraging results.