Miracle-dz/UniFAR-FTUs huggingface dataset:
Asymptotic and Finite User PER Analysis of Successive Interference Cancellation for DS-CDMA

An expression is derived for the average Packet Error Rate (PER) of a Successive Interference Canceller (SIC) for DS-CDMA when the number of users asymptotically tends to infinity. The asymptotic probability density function of the interference power is governed by a Fokker-Planck differential equation with drift and (asymptotically vanishing) diffusion depending on the PER function of the adopted forward error correcting code (FEC). In addition to the asymptotic solution for the PER, a particle-based algorithm is also developed for computing efficiently the PER in the finite user case.
Tensor GSVD of Patient- and Platform-Matched Tumor and Normal DNA Copy-Number Profiles Uncovers Chromosome Arm-Wide Patterns of Tumor-Exclusive Platform-Consistent Alterations Encoding for Cell Transformation and Predicting Ovarian Cancer Survival

The number of large-scale high-dimensional datasets recording different aspects of a single disease is growing, accompanied by a need for frameworks that can create one coherent model from multiple tensors of matched columns, e.g., patients and platforms, but independent rows, e.g., probes. We define and prove the mathematical properties of a novel tensor generalized singular value decomposition (GSVD), which can simultaneously find the similarities and dissimilarities, i.e., patterns of varying relative significance, between any two such tensors. We demonstrate the tensor GSVD in comparative modeling of patient- and platform-matched but probe-independent ovarian serous cystadenocarcinoma (OV) tumor, mostly high-grade, and normal DNA copy-number profiles, across each chromosome arm, and combination of two arms, separately. The modeling uncovers previously unrecognized patterns of tumor-exclusive platform-consistent co-occurring copy-number alterations (CNAs). We find, first, and validate that each of the patterns across only 7p and Xq, and the combination of 6p+12p, is correlated with a patient’s prognosis, is independent of the tumor’s stage, the best predictor of OV survival to date, and together with stage makes a better predictor than stage alone. Second, these patterns include most known OV-associated CNAs that map to these chromosome arms, as well as several previously unreported, yet frequent focal CNAs. Third, differential mRNA, microRNA, and protein expression consistently map to the DNA CNAs. A coherent picture emerges for each pattern, suggesting roles for the CNAs in OV pathogenesis and personalized therapy. In 6p+12p, deletion of the p21-encoding CDKN1A and p38-encoding MAPK14 and amplification of RAD51AP1 and KRAS encode for human cell transformation, and are correlated with a cell’s immortality, and a patient’s shorter survival time. In 7p, RPA3 deletion and POLD2 amplification are correlated with DNA stability, and a longer survival. In Xq, PABPC5 deletion and BCAP31 amplification are correlated with a cellular immune response, and a longer survival.
Morphologic based feature extraction for arrhythmia beat detection

Heart disease is one of the diseases which has highest mortality rate recently. Heart's electrical activity examination and interpretation are very important for the understanding of diseases. In this study, electrocardiogram signals are analyzed, then patient's healthy and arrhythmia beats are extracted. RR, QRS, Skewness and Linear Predictive Coding coefficients of the signals are considered for classification of the data. K-NN, Random SubSpaces, Naive Bayes and K-Star classifiers are used. The highest accuracy is obtained with the K-NN algorithm (98.32%). At the second stage of the K-NN algorithm, accuracy levels are examined by changing the ‘k’ parameter.
When zero is not zero: The problem of ambiguous baseline conditions in fMRI

By using blocked and rapid event-related functional MRI studies of memory, we explored the implications of using rest periods as a baseline condition in functional MRI studies. Activity in the medial temporal lobe (as well as in other brain regions) was substantially higher during rest than during several alternative baseline conditions. The effect of this elevated activity during rest was to reduce, eliminate, or even reverse the sign of the activity during task conditions relevant to memory functions. The results demonstrate that periods of rest are associated with significant cognitive activity and, therefore, provide a nonoptimal baseline for memory tasks. These results were observed not only when relatively long blocks of rest were used (experiment 1), but also when rest consisted of the short null trials typically used in rapid event-related designs (experiment 2). The findings have important implications for the design and interpretation of a wide range of fMRI studies of cognition.
Towards automatic derivation of a product performance model from a UML software product line model

Software Product Line (SPL) engineering is a software development approach that takes advantage of the commonality and variability between products from a family, and supports the generation of specific products by reusing a set of core family assets. This paper proposes a UML model transformation approach for software product lines to derive a performance model for a specific product. The input to the proposed technique, the "source model", is a UML model of a SPL with performance annotations, which uses two separate profiles: a "product line" profile from literature for specifying the commonality and variability between products, and the MARTE profile recently standardized by OMG for performance annotations. The source model is generic and therefore its performance annotations must be parameterized. The proposed derivation of a performance model for a concrete product requires two steps: a) the transformation of a SPL model to a UML model with performance annotations for a given product, and b) the transformation of the outcome of the first step into a performance model. This paper focuses on the first step, whereas the second step will use the PUMA transformation approach of annotated UML models to performance models, developed in previous work. The output of the first step, named "target model", is a UML model with MARTE annotations, where the variability expressed in the SPL model has been analyzed and bound to a specific product, and the generic performance annotations have been bound to concrete values for the product. The proposed technique is illustrated with an e-commerce case study.
Butyrate Induced Cell Cycle Arrest in Bovine Cells through Targeting Gene Expression Relevant to DNA Replication Apparatus1

Using real-time RT-PCR and Western blot analysis in bovine kidney epithelial cells, we systematically investigated the effects of butyrate on patterns of gene expression relevant to DNA replication apparatus. The real-time PCR and Western blot data generally confirmed previously reported microarray data. Of the five genes tested by quantitative RT-PCR, CDKN1A (p21waf1) was up regulated, CDC2/cdk1, MCM6, ORC1L were down regulated, while ORC3L expression remained unchanged following butyrate treatment. Also consistent with RT-PCR results, Western blot analysis confirmed that butyrate up-regulated cyclin-kinase inhibitor p21waf1 in a does-dependent manner. In contrast, butyrate treatment had no effect on the expression of ERK 1/2 proteins. Also consistent with mRNA results, ORC1 and MCM3 proteins were down-regulated by butyrate treatment, while ORC2 protein remained unchanged. The present results suggest that ORC1, not ORC2 or ORC3, along with MCM proteins play a critical role in regulating the initiation of DNA replication and cell cycle progression in MDBK cells and are targets of butyrate regulation.
Neural Networks on GPUs : Restricted Boltzmann Machines

Despite the popularity and success of neural networks in research, the number of resulting commercial or industrial applications have been limited. A primary cause of this lack of adoption is due to the fact that neural networks are usually implemented as software running on general-purpose processors. In this paper, we investigate how GPUs can be used to take advantage of the inherent parallelism in neural networks to provide a better implementation in terms of performance. We will focus on the Restricted Boltzmann machine, a popular type of neural network. The algorithm is tested on a NVIDIA GTX280 GPU, resulting in a computational speed of 672 million connections-per-second and a speed-up of 66-fold over an optimized C++ program running on a 2.83GHz Intel processor.
The Future Use of in Vitro Data in Risk Assessment to Set Human Exposure Standards: Challenging Problems and Familiar Solutions

Background The vision of a National Research Council (NRC) committee (the Committee on Toxicity Testing and Assessment of Environmental Agents) for future toxicity testing involves the testing of human cells in in vitro assays for “toxicity pathways”—normal signaling pathways that when perturbed can lead to adverse effects. Risk assessments would eventually be conducted using mathematical models of toxicity pathways (TP models) to estimate exposures that will not cause biologically significant perturbations in these pathways. Objectives In this commentary we present our vision of how risk assessment to support exposure standards will be developed once a suitable suite of in vitro assays becomes available. Discussion Issues to be faced basing risk assessments on in vitro data are more complex than, but conceptually similar to, those faced currently when applying in vivo data. Absent some unforeseen technical breakthrough, in vitro data will be used in ways similar to current practices that involve applying uncertainty or safety factors to no observed adverse effect levels or benchmark doses. TP models are unlikely to contribute quantitatively to risk assessments for several reasons, including that the statistical variability inherent in such complex models severely limits their usefulness in estimating small changes in response, and that such models will likely continue to involve empirical modeling of dose responses. Conclusion The vision of the committee predicts that chemicals will be tested more quickly and cheaply and that animal testing will be reduced or eliminated. Progress toward achieving these goals will be expedited if the issues raised herein are given careful consideration.
Audio-based age and gender identification to enhance the recommendation of TV content

Recommending TV content to groups of viewers is best carried out when relevant information such as the demographics of the group is available. However, it can be difficult and time consuming to extract information for every user in the group. This paper shows how an audio analysis of the age and gender of a group of users watching the TV can be used for recommending a sequence of N short TV content items for the group. First, a state of the art audio-based classifier determines the age and gender of each user in an M-user group and creates a group profile. A genetic recommender algorithm then selects for each user in the profile, a single personalized multimedia item for viewing. When the number of items to be presented is different to the number of viewers in the group, i.e. M = N, a novel adaptation algorithm is proposed that first converts the M-user group profile to an N-slot content profile, thus ensuring that items are proportionally allocated to users with respect to their demographic categorization. The proposed system is compared to an ideal system where the group demographics are provided explicitly. Results using real speaker utterances show that, in spite of the inaccuracies of state-of-the-art age-and-gender detection systems, the proposed system has a significant ability to predict an item with a matching age and gender category. User studies were conducted where subjects were asked to rate a sequence of advertisements, where half of the advertisements were randomly selected, and the other half were selected using the audio-derived demographics. The recommended advertisements received a significant higher median rating of 7.75, as opposed to 4.25 for the randomly selected advertisements.
Relating perceptual judgments of upcoming prosodic breaks to F0 features

The paper reports on a study of perceptually based predictions of upcoming prosodic breaks in spontaneous Swedish speech materials. The question tackled here is to what extent listeners are able, on the basis of prosodic features, to predict the occurrence of upcoming boundaries, and if so, whether they are able to differentiate different degrees of boundary strength. To answer these questions, an experiment is conducted in which spontaneous utterance fragments (both long and short versions) are presented to listeners, who are instructed to guess whether or not the fragments are followed by a prosodic break, and if so, what the strength of the break is. Results reveal that listeners are indeed able to predict whether or not a boundary (of a particular strength) is following the fragment.
Early Assessment of Induction Chemotherapy Response of Nasopharyngeal Carcinoma by Pretreatment Diffusion-Weighted Magnetic Resonance Imaging

Objectives This study aimed to evaluate the feasibility of pretreatment diffusion-weighted imaging in predicting response after induction chemotherapy (IC) in nasopharyngeal carcinoma (NPC). Methods Fifty-four patients with stage III and IV NPC underwent MRI examination at baseline, after 2 cycles of chemotherapy, and at the end of chemoradiotherapy. Apparent diffusion coefficient (ADC) values were compared between effective and ineffective subjects after IC. Results Mean ADC in effective groups was significantly (P < 0.05) higher than that in the ineffective group. Average and minimum ADCs demonstrated higher sensitivity than maximum ADC for predicting IC response, with 68.4%, 71.1%, and 50.0%, respectively, at an equivalent 68.7% specificity. We observed negative correlations between pretreatment ADC and tumor regression after chemotherapy (&ggr; = − 0.425, P = 0.001) and after chemoradiotherapy (&ggr; = − 0.418, P = 0.003). Conclusions Pretreatment ADC was a valuable biomarker for predicting IC response of NPC. Noninvasive diffusion-weighted imaging provides additional indicator in guiding optical therapeutic options for patients with NPC.
Management Of Recent Elbow Dislocations: Functional Treatment Versus Immobilization; A Prospective Study About 60 Cases

Objective: To determine our therapeutic posture trough a comparison of functional treatment results versus immobilization in two different periods. Introduction: For years, the treatment of recent elbow dislocations consisted of reduction and immobilization during 21 days. Given the frequency of stiffness other methods have been tried out. Method: A prospective study was carried out from January 2010 to December 2014. Sixty patients averaging 28.3 years of age underwent elbow dislocation reduction. They were categorized into three separate groups. Patients in the first group had their elbow immobilized for 21 days whereas Group 2 patients were immobilized for 10 days. Group 3 patients were applied a functional treatment followed by a functional rehabilitation. Patients were evaluated according to the Mayo Clinic Elbow Performance Index and the results analyzed with statistical software (SPSS, version 18). Results: During the first month, the functional results of the patients were excellent and good in 19%, 94.7% and 90% respectively for Groups 1, 2 and 3. The pain was intense (10 on the visual analogue scale) in group 3 associated with swelling. At day 90, the results of the patients in Groups 2 and 3 were excellent in 100% of the cases versus 90% for Group 1. At 6 months, all the results were the same. We have not noted any instability, or recurrence or periarticular ossification in our patients. Conclusion: The treatment of stable elbow dislocations remains orthopedic. The risk of instability and pain motivates a short 10-day immobilization period followed by early mobilization.
Learning the kernel matrix for XML document clustering

The rapid growth of XML adoption has urged for the need of a proper representation for semi-structured documents, where the document structural information has to be taken into account so as to support more precise document analysis. In this paper, an XML document representation named "structured link vector model" is adopted, with a kernel matrix included for modeling the similarity between XML elements. Our formulation allows individual XML elements to have their own weighted contribution to the overall document similarity while at the same time allows the between-element similarity to be captured. An iterative algorithm is derived to learn the kernel matrix. For performance evaluation, the ACM SIGMOD record dataset as well as the CEDE dataset have been tested. Our proposed method outperforms significantly the traditional vector space model and the edit-distance based methods. In addition, the kernel matrix obtained as a by-product provides knowledge about the conceptual relationship between the XML elements.
A fundamental study of novel speech interface for computer games

A novel speech interface for computer game systems is addressed. For typical computer game systems, users have input game commands with touching devices such as gamepad, keyboard, touch-panel and foot-board. Acceleration sensors which can detect player's motion have been general. Some systems have speech interface for controlling games, namely, voice controller. A simple speech interface just detects large sound signals, and some game systems can recognize what users say with automatic speech recognition (ASR) module. Although ASR works well for polite speech, it dose not work well for exciting speeches such as shout by excited game players. In this paper, we focus on the speech interface which can deal with excited speech, and describe ASR which can discriminate shout from natural speech based on the understanding of speech events.
Genetics and Assembly Line Enzymology of Siderophore Biosynthesis in Bacteria

SUMMARY The regulatory logic of siderophore biosynthetic genes in bacteria involves the universal repressor Fur, which acts together with iron as a negative regulator. However in other bacteria, in addition to the Fur-mediated mechanism of regulation, there is a concurrent positive regulation of iron transport and siderophore biosynthetic genes that occurs under conditions of iron deprivation. Despite these regulatory differences the mechanisms of siderophore biosynthesis follow the same fundamental enzymatic logic, which involves a series of elongating acyl-S-enzyme intermediates on multimodular protein assembly lines: nonribosomal peptide synthetases (NRPS). A substantial variety of siderophore structures are produced from similar NRPS assembly lines, and variation can come in the choice of the phenolic acid selected as the N-cap, the tailoring of amino acid residues during chain elongation, the mode of chain termination, and the nature of the capturing nucleophile of the siderophore acyl chain being released. Of course the specific parts that get assembled in a given bacterium may reflect a combination of the inventory of biosynthetic and tailoring gene clusters available. This modular assembly logic can account for all known siderophores. The ability to mix and match domains within modules and to swap modules themselves is likely to be an ongoing process in combinatorial biosynthesis. NRPS evolution will try out new combinations of chain initiation, elongation and tailoring, and termination steps, possibly by genetic exchange with other microorganisms and/or within the same bacterium, to create new variants of iron-chelating siderophores that can fit a particular niche for the producer bacterium.
Error diffused intra prediction for HEVC

HEVC uses up to 35 prediction modes for intra prediction and it can well predict blocks with uni-directional structures or sharp edges, but the intra prediction still suffers from its discontinuous characteristics. To improve coding performance of intra prediction, the inpainting technique has been studied but it is impractical because of its high computational complexity. In this paper, we employ error diffusion technique for HEVC intra prediction to improve its coding efficiency with reasonable increase in computational complexity. The experimental results show that the error diffusion technique outperforms the inpainting technique subjectively and objectively, especially with much lower computational complexity. The results demonstrate that average 0.5% BDBR reduction can be achieved in the proposed algorithm, compared to HEVC intra prediction.
Towards a Benchmark for Evaluating Design Pattern Miner Tools

Recovering design pattern usage in source code is a very difficult task. Several tools are described in the literature for this purpose, but there is little work invested in evaluating them. The main reason for this is the lack of an approved benchmark for these tools. In this paper we present work in progress towards creating a benchmark, called DEEBEE (design pattern evaluation benchmark environment), for evaluating and comparing design pattern miner tools. It is programming language, tool, pattern and software independent, and it is open to the community and freely available. Currently, the benchmark database contains the results of three tools: Columbus (C++), Maisa (C++), and design pattern detection tool (Java). The tools were evaluated on reference implementations of patterns and on open source software (Mozilla, NotePad++, JHotDraw, JRefactory and JUnit). Additionally, instances recovered by researchers are added from NotePad++ as well. Some recovered patterns are already verified by experienced developers. This work is the first step in building a large reference database of design pattern usage in open source software and we expect that researchers will join us in this effort.
Nanofibers as novel drug carrier – An overview

Presently polymer nanofibers have received much attention due to their unique properties such as large surface area, high porosity, small pore size, superior mechanical properties and ease of addition of surface functionalities compared with any other material. Nanofibers particularly polymeric nanofiber prepared by electrospinning process can be used as carriers for the controlled drug delivery of bioactive molecules such as cytokines, growth factors, anticancer drugs, enzymes and certain vitamins. This article presents an overview of nanofibers, various techniques involved in fabrication of nanofibers, their characterization, parameters affecting electrospinning process and their applications.
Verification and validation of language processing systems: Is it evaluation?

If Natural Language Processing (NLP) systems are viewed as intelligent systems then we should be able to make use of verification and validation (V&V) approaches and methods that have been developed in the intelligent systems community. This paper addresses language engineering infrastructure issues by considering whether standard V&V methods are fundamentally different than the evaluation practices commonly used for NLP systems, and proposes practical approaches for applying V&V in the context of language processing systems. We argue that evaluation, as it is performed in the NL community, can be improved by supplementing it with methods from the V&V community.