Miracle-dz/UniFAR-FTUs huggingface dataset:
Synapse-Associated Protein 97 Selectively Associates with a Subset of AMPA Receptors Early in their Biosynthetic Pathway

The regulation of AMPA receptors at the postsynaptic membrane is a fundamental component of synaptic plasticity. In the hippocampus, the induction of long-term potentiation increases the delivery of GluR1, a major AMPA receptor subunit in hippocampal pyramidal neurons, to the synaptic plasma membrane through a mechanism that requires the PDZ binding domain of GluR1. Synapse-associated protein 97 (SAP97), a member of the membrane-associated guanylate kinase family, is believed to associate with AMPA receptors (AMPARs) containing the GluR1 subunit, but the functional significance of these interactions is unclear. We investigated the interaction of GluR1 with SAP97, the only PDZ protein known to interact with GluR1. We find that interactions involving SAP97 and GluR1 occur early in the secretory pathway, while the receptors are in the endoplasmic reticulum orcis-Golgi. In contrast, few synaptic receptors associate with SAP97, suggesting that SAP97 dissociates from the receptor complex at the plasma membrane. We also show that internalization of GluR1, as triggered by NMDAR activation, does not require SAP97. These results implicate GluR1–SAP97 interactions in mechanisms underlying AMPA receptor targeting.
Image segmentation using colour

This paper presents research-in-progress using colour as a means of image segmentation for use in biometric security methods on mobile devices. The limited processing capability of mobile devices has restricted the computational complexity of security algorithms that can be used. The purpose of our system is to use a colour based method to reduce the amount of information that must be processed by biometric algorithms. This is accomplished by creating a mug shot of a target individual from an image with an unknown background and unknown target/camera positions. Specific security algorithms can then be applied to the generated mug shot. An overall reduction in data processing will allow more effective biometric security measures to be implemented.
Fighting Insomnia: A Secure Wake-Up Scheme for Wireless Sensor Networks

Sleep deprivation attacks are still an unsolved but critical problem in sensor networks. They aim on quickly exhausting energy reserves of battery-powered sensor nodes by continuously sending messages to the node, preventing the attacked node to switch to an energy-saving sleep state. Sleep deprivation attacks come also in the form of sending traffic that causes a sleeping node to wake-up. Sleep deprivation attacks have the potential to lessen the lifetime of typical sensor nodes from years to days or even hours. One important communication standard for sensor networks is IEEE 802.15. 4 that defines cryptographic protection of frames. While many attacks like eavesdropping or modification of frames are covered by the available security mechanisms, these mechanisms do not address sleep deprivation attacks. This paper proposes a secure wake-up scheme that activates a sensor node by a secure wake-up radio from a sleep state only if messages from an authenticated and legitimate node are pending. A lightweight security verification scheme is used that can easily be performed without requiring the node to change to active state.
JaSkel: a Java skeleton-based framework for structured cluster and grid computing

This paper presents JaSkel, a skeleton-based framework to develop parallel and grid applications. The framework provides a set of Java abstract classes as a skeleton catalogue, which implements recurring parallel interaction paradigms. This approach aims to improve code efficiency and portability. It also helps to structure scalable applications through the refinement and composition of skeletons. Evaluation results show that using the provided skeletons do contribute to improve both application development time and execution performance.
Is alternate rapid maxillary expansion and constriction an effective protocol in the treatment of Class III malocclusion? A systematic review

ABSTRACT Introduction: the treatment of Class III malocclusion in early age is one of the greatest challenges for orthodontists, and the establishment of more effective treatment method is a constant concern for these professionals. Thus, the objective of this systematic review is to verify the effectiveness of the therapy protocol for alternate rapid maxillary expansion and constriction (Alt-RAMEC) in the early treatment of Class III malocclusion. Methods: searches were performed in the following electronic databases: Cochrane Library, Medline (EBSCO and PubMed), SciELO, LILACS and Scopus. The following inclusion criteria were used: in vivo studies conducted with early intervention (patient in craniofacial development phase) with the use of the Alt-RAMEC protocol. Reviews, case reports, editorials, and studies with syndromic patients or under use of systemic drug were excluded. Duplicates were also excluded. The studies were assessed for methodological quality using the Cochrane tool for assessment of risk of bias, and classified as high or low risk of bias. Results: 53 articles were found. Duplicates exclusion was thus performed and 35 articles remained. After inclusion analysis, only 5 matched the criteria. Two articles were classified as low risk of bias and three as high risk of bias. It was observed that the Alt-RAMEC enable protraction in less time and with better results, promoting greater effectiveness in the protraction treatment of Class III malocclusion. Conclusions: Although there is positive evidence of the effectiveness of early treatment with the Alt-RAMEC protocol in patients with Class III malocclusion, further studies are needed to confirm its effectiveness using long-term methodology.
Purification and characterization of a low-molecular-mass T-cell antigen secreted by Mycobacterium tuberculosis

A novel immunogenic antigen, the 6-kDa early secretory antigenic target (ESAT-6), from short-term culture filtrates of Mycobacterium tuberculosis was purified by hydrophobic interaction chromatography and anion-exchange chromatography by use of fast protein liquid chromatography. The antigen focused at two different pIs of 4.0 and 4.5 during isoelectric focusing, and each of these components separated into three spots ranging from 4 to 6 kDa during two-dimensional sodium dodecyl sulfate-polyacrylamide gel electrophoresis. The apparent differences in molecular masses or pIs of these isoforms were not due to posttranslational glycosylation. The molecular weight of the purified native protein was determined by applying gel filtration and nondenaturing polyacrylamide gel electrophoresis and found to be 24 kDa. ESAT-6 is recognized by the murine monoclonal antibody HYB 76-8, which was used to screen a recombinant lambda gt11 M. tuberculosis DNA library. A phage expressing a gene product recognized by HYB 76-8 was isolated, and a 1.7-kbp fragment of the mycobacterial DNA insert was sequenced. The structural gene of ESAT-6 was identified as the sequence encoding a polypeptide of 95 amino acids. The N terminus of the deduced sequence could be aligned with the 10 amino-terminal amino acids derived from sequence analyses of the native protein. N-terminal sequence analysis showed that the purified antigen was essentially free from contaminants, and the amino acid analysis of the antigen was in good agreement with the DNA sequence-deduced amino acid composition. Thus, the heterogeneities observed in the pI and molecular weight of the purified antigen do not derive from contaminating proteins but are most likely due to heterogeneity of the antigen itself. Native and recombinant ESAT-6 are immunologically active in that both elicited a high release of gamma interferon from T cells isolated from memory-immune mice challenged with M. tuberculosis. Analyses of subcellular fractions of M. tuberculosis showed the presence of ESAT-6 in cytosol- and cell wall-containing fractions. Interspecies analyses showed the presence of ESAT-6 in filtrates from M. tuberculosis complex species. Among filtrates from mycobacteria not belonging to the M. tuberculosis complex, reactivity was observed in Mycobacterium kansasii, Mycobacterium szulgai, and Mycobacterium marinum.
Characterisation of polyoma late mRNA leader sequences by molecular cloning and DNA sequence analysis.

The leader sequences of two of the three polyoma virus late mRNAs were characterised by molecular cloning and DNA sequence analysis. A short single-stranded DNA fragment complementary to the 5' end of the body of mVP1 was used to prime cDNA synthesis, and double-stranded cDNA was inserted into a derivative of pAT 153. Analysis of fourteen mVP1 cDNAs and two mVP3 cDNAs allowed the precise determination of the leader-body joints, and demonstrated that the majority of polyoma late leader sequences consist of exact tandem repeats of a 57 nucleotide sequence present only once in the genomic DNA at 66-67 m.u. The sequences in the genomic DNA borderline this unit are typical of those found at RNA splice points. Leader sequences contained on average three to four repeat units. Nuclease S1 mapping of total late mRNA demonstrated that most mRNA 5' ends map heterogeneously in the 50 nucleotides 5' to the repeated sequence unit. The structures of the leader sequences strongly suggest that they are generated by appropriate splicing events from a tandemly repeated transcript of the entire circular viral genome.
Identifying Risk Factors for PTSD in Women Seeking Medical Help after Rape

Objectives Rape has been found to be the trauma most commonly associated with Posttraumatic Stress Disorder (PTSD) among women. It is therefore important to be able to identify those women at greatest risk of developing PTSD. The aims of the present study were to analyze the PTSD prevalence six months after sexual assaults and identify the major risk factors for developing PTSD. Methods Participants were 317 female victims of rape who sought help at the Emergency Clinic for Raped Women at Stockholm South Hospital, Sweden. Baseline assessments of mental health were carried out and followed up after six months. Results Thirty-nine percent of the women had developed PTSD at the six month assessment, and 47% suffered from moderate or severe depression. The major risk factors for PTSD were having been sexually assaulted by more than one person, suffering from acute stress disorder (ASD) shortly after the assault, having been exposed to several acts during the assault, having been injured, having co-morbid depression, and having a history of more than two earlier traumas. Further, ASD on its own was found to be a poor predictor of PTSD because of the substantial ceiling effect after sexual assaults. Conclusions Development of PTSD is common in the aftermath of sexual assaults. Increased risk of developing PTSD is caused by a combination of victim vulnerability and the extent of the dramatic nature of the current assault. By identifying those women at greatest risk of developing PTSD appropriate therapeutic resources can be directed.
Learning Analytics in Mobile and Ubiquitous Learning Environments

Learning analytics (LA) is one of the promising techniques that has been developed in recent times to effectively utilise the astonishing volume of student data available in higher education. Despite many difficulties in its widespread implementation, it has proved to be a very useful way to support failing learners. An important feature of the literature review of LA is that LA has not provided a significant benefit in terms of learner mobility to date since not much research has been carried out to determine the importance of LA in facilitating or enhancing the learning experience of mobile learners. Therefore, this paper describes the potential advantages of using LA techniques to enhance learning in mobile and ubiquitous learning environments from a theoretical perspective. Furthermore, we describe our simplified Mobile and Ubiquitous Learning Analytics Model (MULAM) for analysing mobile learners’ data which is based on Campbell and Oblinger’s five-step model of learning analytics. Finally, we answer the question why now might be the most suitable time to consider analysing mobile learners’ data.
Managing Supply Chain Events to Build Sense-and-Respond Capability

As supply chains become more dynamic, there is a need for a sense-and-respond capability to react to events in a real-time manner. In this paper, we propose Petri nets extended with time and color (for case data) as a formalism for doing so. Hence, we describe seven basic patterns that are used to capture modeling concepts that arise commonly in supply chains. These basic patterns may be used by themselves and also be combined to create new patterns. Next, we show how to use the patterns as building blocks to model a complete supply chain and analyze it using dependency graphs and simulation. Dependency graphs can be used to analyze the various events and their causes. Simulation was, in addition, used to analyze various performance indicators (e.g. fill rates, replenishment times, and lead times) under different supply chain strategies. We performed sensitivity analysis to study the effect of changing parameter values on the performance indicators. In the experiments, by cutting resolution time for production delays in half (strategy 1), we were able to increase order fill rate from 89% to 95%. Similarly, upon raising the probability of successful alternative sourcing (strategy 2) from 0.5 to 0.7 the order fill rate again increased from 89% to 95%. We show that by modeling timing and causality issues accurately, it is possible to improve supply chain performance.
Tumorigenic Properties of Iron Regulatory Protein 2 (IRP2) Mediated by Its Specific 73-Amino Acids Insert

Iron regulatory proteins, IRP1 and IRP2, bind to mRNAs harboring iron responsive elements and control their expression. IRPs may also perform additional functions. Thus, IRP1 exhibited apparent tumor suppressor properties in a tumor xenograft model. Here we examined the effects of IRP2 in a similar setting. Human H1299 lung cancer cells or clones engineered for tetracycline-inducible expression of wild type IRP2, or the deletion mutant IRP2Δ73 (lacking a specific insert of 73 amino acids), were injected subcutaneously into nude mice. The induction of IRP2 profoundly stimulated the growth of tumor xenografts, and this response was blunted by addition of tetracycline in the drinking water of the animals, to turnoff the IRP2 transgene. Interestingly, IRP2Δ73 failed to promote tumor growth above control levels. As expected, xenografts expressing the IRP2 transgene exhibited high levels of transferrin receptor 1 (TfR1); however, the expression of other known IRP targets was not affected. Moreover, these xenografts manifested increased c-MYC levels and ERK1/2 phosphorylation. A microarray analysis identified distinct gene expression patterns between control and tumors containing IRP2 or IRP1 transgenes. By contrast, gene expression profiles of control and IRP2Δ73-related tumors were more similar, consistently with their growth phenotype. Collectively, these data demonstrate an apparent pro-oncogenic activity of IRP2 that depends on its specific 73 amino acids insert, and provide further evidence for a link between IRPs and cancer biology.
Low-rank decomposition of multi-way arrays: a signal processing perspective

In many signal processing applications of linear algebra tools, the signal part of a postulated model lies in a so-called signal sub-space, while the parameters of interest are in one-to-one correspondence with a certain basis of this subspace. The signal sub-space can often be reliably estimated from measured data, but the particular basis of interest cannot be identified without additional problem-specific structure. This is a manifestation of rotational indeterminacy, i.e., non-uniqueness of low-rank matrix decomposition. The situation is very different for three-or higher-way arrays, i.e., arrays indexed by three or more independent variables, for which low-rank decomposition is unique under mild conditions. This has fundamental implications for DSP problems which deal with such data. This paper provides a brief lour of the basic elements of this theory, along with many examples of application in problems of current interest in the signal processing community.
Protective Effects of Simvastatin, a Lipid Lowering Agent, against Oxidative Damage in Experimental Diabetic Rats

The present study was undertaken to evaluate the possible protective effects of simvastatin (SMV) against oxidative stress in streptozotocin- (STZ)-induced diabetic rats. Diabetes was induced experimentally in rats by i.p. injection of STZ in a dose of 60 mg/kg bwt. After 5 weeks of STZ injection, there were apparent reductions in the animal body weight and significant increase in blood glucose, HbA1c, urea, creatinine, AST, ALT, and lipid profiles with a concomitant decrease in total hemoglobin, plasma glutathione and vitamin C as compared to the control group. The treatment with SMV at a dose (10 mg/kg, orally) normalized all the above-mentioned biochemical parameters in STZ-induced diabetic rats. In vitro studies confirmed the free radical scavenging and antioxidant activity of SMV. Therefore, the present results revealed that SMV has a protective effect against STZ-induced oxidative damage by scavenging the free radicals generation and restoring the enzymatic and nonenzymatic antioxidant systems.
A New Upper Bound for Free Space Optical Channel Capacity Using a Simple Mathematical in Equality 1

In this paper, by using a simple mathematical inequality, we derive a $ new upper bound fkr the capacity of$ free space optical channel in coherent case. Then, by applying general fading distribution, we obtain an upper bound for mutual information in non-coherent case. Finally, we derive the corresponding optimal input distributions for both coherent and non-coherent cases, compare the results with previous works numerically and illustrate that our results subsume some of previous results in special cases.
Copy Move Image Forgery Detection using Block and Feature Based Method

Digital images are the most important source of information. The availability of powerful digital image processing software's, makes it relatively easy to create as well as manipulate and make digital forgery from one or multiple images. In today's world it is easy to developed the image forgery by adding or removing some elements from the image which result in a of image tampering. A copy-move forgery is created by copying and pasting content within the same image, and post-operating it. The detection of copy-move forgeries has become one of the most actively researched topics in image forensics department. The key objectives of the proposed method is to study the effect of different types of tampering on the digital image, detect image forgery by copy-move under many types of attacks by combining block-based and feature based method and accurately locating the duplicated region.
Elitist Evolutionary Multi-Agent System in solving noisy multi-objective optimization problems

Evolutionary Multi-Agent System approach for optimization (for multi-objective optimization in particular) is a promising computational model. Its computational as well as implemental simplicity cause that approaches based on EMAS model can be widely used for solving optimization tasks. It turns out that introducing some additional mechanisms into basic EMAS-such as presented in the course of this paper elitist extensions cause that results obtained with the use of proposed elEMAS (elitist Evolutionary Multi-Agent System) approach are as high-quality results as results obtained by such famous and commonly used algorithms as NSGA-II or SPEA2. Apart from the computational simplicity especially important and interesting aspects of EMAS-based algorithms it is characteristic for them a kind of soft selection which can be additionally easily adjusted depending on a particular situation-in particular it is possible to introduce auto-adapting selection into such systems. Such a kind of selection seems to be especially important and valuable in solving optimization tasks in uncertain or ldquonoisedrdquo environments. In the course of this paper the model and experimental results obtained by elEMAS system in solving noisy multi-objective optimization problems are presented and the general conclusion is as follows: EMAS-based optimization system seems to be more effective alternative than classical (i.e. non agent-based) evolutionary algorithms for multi-objective optimization, in particular, in uncertain environment, it seems to be better alternative than NSGA-II algorithm.
Prospective randomised phase II study of docetaxel versus paclitaxel administered weekly in patients with non-small-cell lung cancer previously treated with platinum-based chemotherapy.

BACKGROUND Docetaxel and paclitaxel have activity in the second-line treatment of non-small-cell lung cancer (NSCLC), and can be administered as weekly schedules. This phase II randomised study was designed to test the efficacy and toxicity of both taxanes in patients with NSCLC previously treated with platinum-based chemotherapy. PATIENTS AND METHODS Patients (n = 71) with documented NSCLC were randomised to receive docetaxel (n = 35 patients; 36 mg/m(2)) or paclitaxel (n = 36 patients; 80 mg/m(2)) as a 1 h weekly infusion for 6 weeks followed by a 2-week rest. The cycles were repeated until disease progression or non-acceptable toxicities occurred. RESULTS Treatment achieved partial response of one versus five patients, median time-to-progression of 74 versus 68 days, and overall survival of 184 versus 105 days, with docetaxel and paclitaxel, respectively. The most common non-haematological toxicities were (docetaxel versus paclitaxel): grade 3/4 pulmonary toxicity in seven versus one patient; grade 2/3 diarrhoea in nine versus five; and grade 3/4 haematological toxicities occurred in two versus four patients. There were no treatment-related deaths. CONCLUSIONS Docetaxel and paclitaxel administered weekly have discrete efficacy in patients with NSCLC previously treated with platinum-based chemotherapy. The higher non-haematological toxicity of docetaxel, particularly pulmonary toxicity and diarrhoea, is of concern and warrants further investigation.
Improving taxonomies for large-scale hierarchical classifiers of web documents

We focused on taxonomy modification algorithms for gradually improving the relevance performances of large-scale hierarchical classifiers of web documents. Considering the research results of Tang et al. [5,4], who took the same approach, we investigated and implemented two heuristic taxonomy modification algorithms for performing practical classification processes for large-scale taxonomies. Although a taxonomy modification algorithm continuously improves the relevance performances of hierarchical classifiers, it increases the computational costs of those classifiers for training and predicting processes. We developed an improved taxonomy modification algorithm for reducing computational costs by preventing child node concentration. Although the relevance performances of the algorithm-modified taxonomy classifiers improved without increasing computational costs until the fourth generation by spreading the set of predicted classes, their relevance performances and behaviors went in opposite directions from the fifth generation.