Miracle-dz/UniFAR-FTUs huggingface dataset:
INCREASED EXPRESSION OF GLIAL CELL LINE-DERIVED NEUROTROPHIC FACTOR IN RAT BRAIN AFTER TRAUMATIC BRAIN INJURY

Glial cell line-derived neurotrophic factor (GDNF) plays important roles not only for the differentiation of neurons during normal development but also for the survival and recovery of many populations of mature neurons. The effect of traumatic brain injury (TBI) on the expression of GDNF is currently unknown. To determine if there is alteration in GDNF after TBI we examined the effect of controlled cortical impact (CCI) injury on GDNF protein levels at 6 hours, 1 day, 1 week, and 4 weeks following injury by utilizing a commercially available antibody specific to GDNF. Rats were anesthetized and surgically prepared for CCI injury (4 m/sec, 2.7 mm) and sham surgery. Injured and sham animals (n=6 per group) were sacrificed at 6 hours, 1 day, 1 week, and 4 weeks and perfused with 4% paraformaldehyde. Coronal sections (35 mm thick) were cut through the hippocampus. An increased expression of GDNF protein was observed by immunohistochemistry in the dentate gyrus of hippocampus and the cortex in injured rats compared to sham controls. The increased expression of GDNF was more evidently observed in the ipsilateral dentate gyrus and the area around the contusion in the cortex. In the cortex, GDNF immunoreactivity appeared greatest in cells with glial morphology but in the hippocampus, GDNF immunoreactivity was greatest in neuronal-like cells. These changes were observed at 1 day, 1 and 4 weeks postinjury. We speculate that the up-regulation of the GDNF protein may reflect its neurotrophic and neuroprotective effect on dopaminergic system responding to the TBI insult.
Antibody-mediated Prevention of Fusarium Mycotoxins in the Field

Fusarium mycotoxins directly accumulated in grains during the infection of wheat and other cereal crops by Fusarium head blight (FHB) pathogens are detrimental to humans and domesticated animals. Prevention of the mycotoxins via the development of FHB-resistant varieties has been a challenge due to the scarcity of natural resistance against FHB pathogens. Various antibodies specific to Fusarium fungi and mycotoxins are widely used in immunoassays and antibody-mediated resistance in planta against Fusarium pathogens has been demonstrated. Antibodies fused to antifungal proteins have been shown to confer a very significantly enhanced Fusarium resistance in transgenic plants. Thus, antibody fusions hold great promise as an effective tool for the prevention of mycotoxin contaminations in cereal grains. This review highlights the utilization of protective antibodies derived from phage display to increase endogenous resistance of wheat to FHB pathogens and consequently to reduce mycotoxins in field. The role played by Fusarium-specific antibody in the resistance is also discussed.
Mechanism of Heparin Acceleration of Tissue Inhibitor of Metalloproteases-1 (TIMP-1) Degradation by the Human Neutrophil Elastase

Heparin has been shown to regulate human neutrophil elastase (HNE) activity. We have assessed the regulatory effect of heparin on Tissue Inhibitor of Metalloproteases-1 [TIMP-1] hydrolysis by HNE employing the recombinant form of TIMP-1 and correlated FRET-peptides comprising the TIMP-1 cleavage site. Heparin accelerates 2.5-fold TIMP-1 hydrolysis by HNE. The kinetic parameters of this reaction were monitored with the aid of a FRET-peptide substrate that mimics the TIMP-1 cleavage site in pre-steady-state conditionsby using a stopped-flow fluorescence system. The hydrolysis of the FRET-peptide substrate by HNE exhibits a pre-steady-state burst phase followed by a linear, steady-state pseudo-first-order reaction. The HNE acylation step (k 2 = 21±1 s−1) was much higher than the HNE deacylation step (k 3 = 0.57±0.05 s−1). The presence of heparin induces a dramatic effect in the pre-steady-state behavior of HNE. Heparin induces transient lag phase kinetics in HNE cleavage of the FRET-peptide substrate. The pre-steady-state analysis revealed that heparin affects all steps of the reaction through enhancing the ES complex concentration, increasing k 1 2.4-fold and reducing k −1 3.1-fold. Heparin also promotes a 7.8-fold decrease in the k 2 value, whereas the k 3 value in the presence of heparin was increased 58-fold. These results clearly show that heparin binding accelerates deacylation and slows down acylation. Heparin shifts the HNE pH activity profile to the right, allowing HNE to be active at alkaline pH. Molecular docking and kinetic analysis suggest that heparin induces conformational changes in HNE structure. Here, we are showing for the first time that heparin is able to accelerate the hydrolysis of TIMP-1 by HNE. The degradation of TIMP-1is associated to important physiopathological states involving excessive activation of MMPs.
Comparative evaluation of recommender system quality

Several researchers suggest that the Recommendation Systems (RSs) that are the "best" according to statistical metrics might not be the most satisfactory for the user. We explored this issue through an empirical study that involved 210 users and considered 7 RSs using different recommender algorithms on the same dataset. We measured user's perceived quality of each RS, and compared these results against measures of statistical quality of the considered algorithms as they have been assessed by past studies in the field, highlighting some interesting results.
Perfil de usuários de tecnologias para a agricultura irrigada.

Este trabalho apresenta a analise dos resultados do levantamento do perfil dos usuarios da Plataforma IrrigaWeb e do Servico de Atendimento ao Consumidor (SAC) da Embrapa, com enfase no uso de tecnologias de irrigacao. Esta iniciativa esta inserida no contexto do Portfolio de Agricultura Irrigada da Embrapa, contribuindo para o alinhamento estrategico dos objetivos do Portfolio com as demandas atuais de usuarios dos servicos oferecidos pela Empresa. Por meio deste estudo, espera-se oferecer subsidios a inducao de novos eixos tematicos para projetos de pesquisa, direcionados ao desenvolvimento de politicas publicas e ao aumento da eficiencia dos sistemas de irrigacao.
against Sql Injection Attacks

: SQL injection attack is the most common attack in websites now-a-days. Some malicious codes gets injected to the database by unauthorized users and because of this attack, the actual database can be stolen or destroyed or modified or the device can be taken control by the hacker. The main cause of this type of attacks is poor coding by the developers. Hence, the login phase is more vulnerable to SQL injection attack and prevention technique should be applied on this phase to secure the database. In this paper, some predefined methods are discussed and hybrid encryption method is applied in the database to avoid attack on login phase. This applied hybrid encryption method is a combination of Advanced Encryption Standard (AES) and Rabin cryptosystem. These two level encryption methods are applied to a system where faculty’s information are kept and the designing of this system are done by using PHP and MYSQL .
An embedded circumnuclear disk in Mrk 273

Radio observations using very long baseline interferometry (VLBI) and the Westerbork interferometer have been carried out to study the hydroxyl Megamaser emission in Mrk 273 at different spatial resolutions. Line and continuum observations were carried out by the European VLBI network (EVN) at 1.6 GHz and display a number of distinct structural components in the central arcsec(2) region. The observed continuum emission shows three prominent regions with both flat and steep spectral indexes. The hydroxyl (OH) emission detected by the EVN measurements accounts for only 12 percent of the total OH emission in Mrk 273, but it does show the same dominant 1667 MHz line emission components as the WSRT observations. The spatial distribution of the maser emission provides a high resolution view of the molecular environment in the nuclear region. The OH emission has only been detected toward a distinct radio source in the northern nucleus with a spatial extent of 108 pc. The OH emission is only partially superposed on the radio continuum and is associated with the near-infrared emission source. The low pump efficiency of the maser and the OH main-line ratio suggest that this emission originates in an optically thin and unsaturated maser environment with a complex pumping scheme that cannot be explained by radiative infrared pumping with a single dust temperature. The specific line emission pattern and the line-of-sight velocities indicate the organized structure of an edge-on disk/TORUS with a Keplerian rotation surrounding a central object with a binding mass of 1.39 +/- 0.16 x 10(9) M-circle dot.
Diagrammatic Reasoning by Propagating Constraints Through Geometric Objects : An Application to Truss Analysis

A diagrammatic reasoning for structural analysis on trusses is proposed and demonstrated on many examples . In the reasoning, deflected shape of a substructure is drawn at first then it is reasoned how the remaining substructure is affected by the deflection . By identifying the elongated parts are in tension and shortened parts are in compression, a qualitative stress analysis can be done diagrammatically . The method is implemented on a graphical tool that allows direct operation on geometrical objects constraining with each other by geometric constraints. Some theoretical correspondence between drawing diagram and qualitative determinacy of a stress is also addressed.
Statistical Estimation of Statistical Mechanical Models: Helix-Coil Theory and Peptide Helicity Prediction

Analysis of biopolymer sequences and structures generally adopts one of two approaches: use of detailed biophysical theoretical models of the system with experimentally-determined parameters, or largely empirical statistical models obtained by extracting parameters from large datasets. In this work, we demonstrate a merger of these two approaches using Bayesian statistics. We adopt a common biophysical model for local protein folding and peptide configuration, the helix-coil model. The parameters of this model are estimated by statistical fitting to a large dataset, using prior distributions based on experimental data. L(1)-norm shrinkage priors are applied to induce sparsity among the estimated parameters, resulting in a significantly simplified model. Formal statistical procedures for evaluating support in the data for previously proposed model extensions are presented. We demonstrate the advantages of this approach including improved prediction accuracy and quantification of prediction uncertainty, and discuss opportunities for statistical design of experiments. Our approach yields a 39% improvement in mean-squared predictive error over the current best algorithm for this problem. In the process we also provide an efficient recursive algorithm for exact calculation of ensemble helicity including sidechain interactions, and derive an explicit relation between homo- and heteropolymer helix-coil theories and Markov chains and (non-standard) hidden Markov models respectively, which has not appeared in the literature previously.
Product design and hierarchized persuasion process: An application to three household electrical products

Product design can be considered a communication tool that results in cognitive and affective responses. This research builds on MacKenzie et al.’s advertising persuasion models to determine whether the persuasion process induced by product design operates according to a hierarchy of effects, both directly through an affect transfer process and indirectly through product cognitions. The findings provide evidence of the existence of direct and indirect routes for both functional and symbolic beliefs. They highlight the effect of stylistic choices on consumers’ affective, cognitive and behavioural responses.
Kernel Quantile Estimators

Abstract For an estimator of quantiles, the efficiency of the sample quantile can be improved by considering linear combinations of order statistics, that is, L estimators. A variety of such methods have appeared in the literature; an important aspect of this article is that asymptotically several of these are shown to be kernel estimators with a Guassian kernel, and the bandwidths are identified. It is seen that some implicit choices of the smoothing parameter are asymptotically suboptimal. In addition, the theory of this article suggests a method for choosing the smoothing parameter. How much reliance should be placed on the theoretical results is investigated through a simulation study. Over a variety of distributions little consistent difference is found between various estimators. An important conclusion, made during the theoretical analysis, is that all of these estimators usually provide only modest improvement over the sample quantile. The results indicate that even if one knew the best estimator .
Neutrino Flux Predictions for Known Galactic Microquasars

It has been proposed recently that Galactic microquasars may be prodigious emitters of TeV neutrinos that can be detected by upcoming km2 neutrino telescopes. In this paper we consider a sample of identified microquasars and microquasar candidates for which available data enable rough determination of the jet parameters. By employing the parameters inferred from radio observations of various jet ejection events, we determine the neutrino fluxes that should have been produced during these events by photopion production in the jet. Despite the large uncertainties in our analysis, we demonstrate that in several of the sources considered the neutrino flux at Earth, produced in events similar to those observed, would exceed the detection threshold of a km2 neutrino detector. The class of microquasars may contain also sources with bulk Lorentz factors larger than those characteristic of the sample considered here, directed along our line of sight. Such sources, which may be very difficult to resolve at radio wavelengths and hence may be difficult to identify as microquasar candidates, may emit neutrinos with fluxes significantly larger than those typically obtained in the present analysis. These sources may eventually be identified through their neutrino and gamma-ray emission.
Cloud computing data storage security framework relating to data integrity, privacy and trust

Cloud Computing is next generation computing technology with the dynamic capabilities of adding new resources and services as per user demand and requirement. Cloud computing is fast growing technology which facilitates more and more users and organizations shifting towards opting their services to cloud. Data security is considered as the constant issue leading towards a hitch in the adoption of cloud computing. Data privacy, Integrity and trust issues are few severe security concerns leading to wide adoption of cloud computing. The advent of the proposed model has sufficient functionalities and capabilities which ensures the data security and integrity. The proposed framework focuses on the encryption and decryption approach facilitating the cloud user with data security assurance. The proposed solution only talks about the increased security but does not talk about the performance. The solution also includes the functioning of forensic virtual machine, malware detection and real time monitoring of the system. In this paper, a survey of different security issues and threats are also presented. A data security framework also provides the transparency to both the cloud service provider and the cloud user thereby reducing data security threats in cloud environment.
Domain-Specific Programming Technology for Heterogeneous Manycore Platforms

Nowadays embedded systems solve tasks in various domains (avionics, space industry, automotive, mobile devices, domestic appliances and so on). Moreover, these tasks are composed in various concepts: IoT, cyber-physical systems etc. Different classes of problems of the market and its needs make manufacturers of embedded systems to design heterogeneous many/multi core hardware platforms. Such platforms includes dozens of different cores: CPU, GPU, DSP, FPGA etc. Additionally, there is a high pressure of time to market. That makes them incredibly hard to program, especially in case when more and more domain experts are involved in the solution development process. For example, domain expert has knowledge in the area of image recognition or signal processing, but usually does not fully understand the specificity of programming for various kinds of hardware cores. In this article, we propose the complex technology and tools that allows involving domain experts in software development for embedded systems. The proposed technology has various aspects and abilities that can be used to build verifiable and portable software for a wide range of heterogeneous embedded platforms.
Ancient Adaptive Evolution of the Primate Antiviral DNA-Editing Enzyme APOBEC3G

Host genomes have adopted several strategies to curb the proliferation of transposable elements and viruses. A recently discovered novel primate defense against retroviral infection involves a single-stranded DNA-editing enzyme, APOBEC3G, that causes hypermutation of HIV. The HIV-encoded virion infectivity factor (Vif) protein targets APOBEC3G for destruction, setting up a genetic conflict between the APOBEC3G and Vif genes. This kind of conflict leads to rapid fixation of mutations that alter amino acids at the protein–protein interface, referred to as positive selection. We show that the APOBEC3G gene has been subject to strong positive selection throughout the history of primate evolution. Unexpectedly, this selection appears more ancient than, and is likely only partially caused by, modern lentiviruses. Furthermore, five additional APOBEC genes in the human genome appear to be engaged in similar genetic conflicts, displaying some of the highest signals for positive selection in the human genome. Despite being only recently discovered, editing of RNA and DNA may thus represent an ancient form of host defense in primate genomes.
In Vivo Chronic Intermittent Ethanol Exposure Reverses the Polarity of Synaptic Plasticity in the Nucleus Accumbens Shell

Glutamatergic synaptic plasticity in the nucleus accumbens (NAc) is implicated in response to sensitization to psychomotor-stimulating agents, yet ethanol effects here are undefined. We studied the acute in vitro and in vivo effects of ethanol in medium spiny neurons from the shell NAc subregion of slices of C57BL/6 mice by using whole-cell voltage-clamp recordings of α-amino-3-hydroxy-5-methyl-isoxazole-4-propionic acid (AMPA) excitatory postsynaptic current (EPSCs). Synaptic conditioning (low-frequency stimulation with concurrent postsynaptic depolarization) reliably depressed AMPA EPSCs by nearly 30%; this accumbal long-term depression (LTD) was blocked by a nonselective N-methyl-d-aspartate (NMDA) receptor antagonist (dl-2-amino-5-phosphonovaleric acid) and a selective NMDA receptor 2B antagonist [R-(R*,S*)-α-(4-hydroxyphenyl)-β-methyl-4-(phenylmethyl)-1-piperidine propanol]. Acute ethanol exposure inhibited the depression of AMPA EPSCs differentially with increasing concentrations, but this inhibitory action of ethanol was occluded by a D1-selective dopamine receptor agonist. Ethanol dependence was elicited in C57BL/6 mice by two separate 4-day bouts of chronic intermittent ethanol (CIE) vapor exposure. When assessed 24 h after a single bout of in vivo CIE vapor exposure, NAc LTD was absent, and instead NMDA receptor-dependent synaptic potentiation [long-term potentiation (LTP)] was reliably observed. It is noteworthy that both LTP and LTD were completely absent after an extended withdrawal (72 h) after a single 3-day CIE vapor bout. These observations demonstrate that 1) accumbal synaptic depression is mediated by NR2B receptors, 2) accumbal synaptic depression is highly sensitive to both acute and chronic ethanol exposure, and 3) alterations in this synaptic process may constitute a neural adaptation that contributes to the induction and/or expression of ethanol dependence.
An Unsupervised Dynamic Bayesian Network Approach to Measuring Speech Style Accommodation

Speech style accommodation refers to shifts in style that are used to achieve strategic goals within interactions. Models of stylistic shift that focus on specific features are limited in terms of the contexts to which they can be applied if the goal of the analysis is to model socially motivated speech style accommodation. In this paper, we present an unsupervised Dynamic Bayesian Model that allows us to model stylistic style accommodation in a way that is agnostic to which specific speech style features will shift in a way that resembles socially motivated stylistic variation. This greatly expands the applicability of the model across contexts. Our hypothesis is that stylistic shifts that occur as a result of social processes are likely to display some consistency over time, and if we leverage this insight in our model, we will achieve a model that better captures inherent structure within speech.
Fast non-rigid registration of medical image data for image guided surgery.

With the increasing importance of merging multiple datasets of different imaging modalities for image guided surgery applications, the speed by which such datasets can be registered is crucial. This paper presents a novel approach based on fast Radial Basis Function (RBF) evaluation using the biharmonic spline (BHS) and thin Plate spline (TPS) models for non-linear registration. The new algorithm is evaluated both in standard software and hardware assisted versions. A number of experiments on medical image data are presented, illustrating substantial speedups compared to a ‘brute-force’ implementation of a radial basis function based registration algorithm. The global transformation accuracy of these techniques has been evaluated by using two sets of anatomical landmarks, one set for calculating the model parameters, and the other set for assessing registration accuracy. Finally, we demonstrate that the technique yields sub-second performance and target registration errors of about 1.2mm on the intra-subject registration of CT and MRI image datasets obtained from the Vanderbilt database, when implemented on the GPU of a standard PC with high-end videoadapter card.
Artificial neural network approaches to intrusion detection: a review

Intrusion detection systems are the foremost tools for providing safety in computer and network system. There are many limitations in traditional IDSs like time consuming statistical analysis, regular updating, non adaptive, accuracy and flexibility. It is an Artificial Neural Network that supports an ideal specification of an Intrusion Detection System and is a solution to the problems of traditional IDSs. Therefore, An Artificial Neural Network inspired by nervous system has become an interesting tool in the applications of Intrusion Detection Systems due to its promising features. Intrusion detection by Artificial Neural Networks is an ongoing area. In this paper, we provide an introduction and review of the Artificial Neural Network Approaches within Intrusion Detection, in addition to make suggestions for future research. We also discuss on tools and datasets that are being used in Artificial Neural Network Intrusion Detection Systems. This review may help the researcher to develop new optimize approach in the field of Intrusion Detection.