Miracle-dz/UniFAR-FTUs huggingface dataset:
Classifier fusion interactive software toolbox for EMG signal decomposition

A classifier fusion interactive software package has been constructed for implementing the classification task in the electromyographic (EMG) signal decomposition process using the MATLAB high-level programming language and its interactive environment. The package employs classifier fusion schemes of multiple classifier combination for the purpose of fusing the decisions of a set of heterogeneous base classifiers to make a final decision that achieves improved classification performance. The base classifiers used are ensembles of error-independent certainty, fuzzy k-NN, and template matched filter classifiers. The interactive package consists of several graphical user interfaces (GUIs) to extract individual motor unit potential (MUP) waveforms from raw EMG signals; extract relevant features; classify MUPs into motor unit potential trains (MUPTs) using certainty-based, assertion-based, and similarity-based classifiers; and combine classifier decisions. The proposed software package is useful for enhancing the EMG signal analysis quality and providing a systematic approach to the EMG signal decomposition process. It worked as a very helpful environment for testing and evaluating algorithms developed for EMG signal decomposition research.
Basic statistics and variational concepts behind the reverse Monte Carlo technique

We revise the statistical foundations of the reverse Monte Carlo (RMC) technique by constructing the associated functional of a variational principle which incorporates, without any ad hoc assumptions, the inherent errors accompanying the simulation and the experimental data. We propose a Bayesian criteria for acceptance/rejection of configurations, in terms of the variations of the functional. The loss function and variational functional minimization approaches are compared.
Single center TAVR experience with a focus on the prevention and management of catastrophic complications

Transcatheter aortic valve replacement (TAVR) is an important treatment option for patients with severe symptomatic aortic stenosis (AS) who are inoperable or at high risk for complications with surgical aortic valve replacement. We report here our single‐center data on consecutive patients undergoing transfemoral (TF) TAVR since the inception of our program, with a special focus on minimizing and managing complications.
Moxibustion as an adjuvant for benign prostatic hyperplasia with lower urinary tract symptoms: a protocol for a parallel-group, randomised, controlled pilot trial

Introduction This study aims to explore the feasibility of using moxibustion as a supplementary intervention and to assess the sample size for verifying the effectiveness and safety of integrative treatment involving moxibustion compared with conventional treatment for patients with benign prostatic hyperplasia accompanying moderate to severe lower urinary tract symptoms. Methods and analysis A total of 60 patients diagnosed with benign prostatic hyperplasia by a urologist based on prostate size, prostate-specific antigen and clinical symptoms will participate of their own free will; urologists will monitor the patients and evaluate their symptoms. The patients will be randomised to either a conventional group or an integrative group with a 1:1 allocation according to computer-generated random numbers concealed in opaque, sealed, sequentially numbered envelopes. Watchful waiting or oral medication including α blocker, 5α-reductase inhibitors or antimuscarinic drugs will be offered as conventional treatment. Integrative treatment will include moxibustion therapy in addition to the conventional treatment. The moxibustion therapy will be conducted twice a week for 4 weeks on the bilateral acupoints SP6, LR3 and CV4 by a qualified Korean medical doctor. The primary outcome will be the International Prostate Symptom Score (IPSS) after eight sessions. The secondary outcomes will be the post-void residual urine volume, the maximum urinary flow rate, IPSS, the results of a Short-Form 36-Question Health Survey after 12 weeks, and the patients’ global impression of changes at each visit. Ethics and dissemination Written informed consent will be obtained from all participants. This study was approved by the institutional review boards of both Pusan National University Yangsan Hospital and Pusan National University Korean Medicine Hospital. The trial results will be disseminated through open-access journals and conferences. Trial registration number NCT02051036.
Skin Barrier Function and Its Importance at the Start of the Atopic March

Atopic dermatitis can be due to a variety of causes from nonatopic triggers to food allergy. Control of egress of water and protection from ingress of irritants and allergens are key components of cutaneous barrier function. Current research suggests that a degraded barrier function of the skin allows the immune system inappropriate access to environmental allergens. Epidermal aeroallergen exposure may allow sensitization to allergen possibly initiating the atopic march. Further research into connections between epidermal barrier function and possible allergen sensitization will be important to undertake. Future clinical trials focused on skin barrier protection may be of value as a possible intervention in prevention of the initiation of the atopic march.
Model-Based Genetic Algorithms for Algorithm Configuration

Automatic algorithm configurators are important practical tools for improving program performance measures, such as solution time or prediction accuracy. Local search approaches in particular have proven very effective for tuning algorithms. In sequential local search, the use of predictive models has proven beneficial for obtaining good tuning results. We study the use of non-parametric models in the context of population-based algorithm configurators. We introduce a new model designed specifically for the task of predicting high-performance regions in the parameter space. Moreover, we introduce the ideas of genetic engineering of offspring as well as sexual selection of parents. Numerical results show that model-based genetic algorithms significantly improve our ability to effectively configure algorithms automatically.
Take time to smell the frogs: vocal sac glands of reed frogs (Anura: Hyperoliidae) contain species-specific chemical cocktails

Males of all reed frog species (Anura: Hyperoliidae) have a prominent, often colourful, gular patch on their vocal sac, which is particularly conspicuous once the vocal sac is inflated. Although the presence, shape, and form of the gular patch are well-known diagnostic characters for these frogs, its function remains unknown. By integrating biochemical and histological methods, we found strong evidence that the gular patch is a gland producing volatile compounds, which might be emitted while calling. Volatile compounds were confirmed by gas chromatography–mass spectrometry in the gular glands in 11 species of the hyperoliid genera Afrixalus, Heterixalus, Hyperolius, and Phlyctimantis. Comparing the gular gland contents of 17 specimens of four sympatric Hyperolius species yielded a large variety of 65 compounds in species-specific combinations. We suggest that reed frogs might use a complex combination of at least acoustic and chemical signals in species recognition and mate choice.
Interest Rate Models

n interest rate model is a probabilistic description of the future evolution of interest rates. Based on today's information, future interest rates are uncertain: An interest rate model is a characterization of that uncertainty. Quantitative analysis of securities with rate dependent cash flows requires application of such a model in order to find the present value of the uncertainty. Since virtually all financial instruments other than default-and option-free bonds have interest rate sensitive cash flows, this matters to most fixed-income portfolio managers and actuaries, as well as to traders and users of interest rate derivatives. For financial instrument valuation and risk estimation one wants to use only models that are arbitrage free and matched to the currently observed term structure of interest rates. " Arbitrage free " means just that if one values the same cash flows in two different ways, one should get the same result. For example, a 10-year bond putable at par by the holder in 5 years can also be viewed as a 5-year bond with an option of the holder to extend the maturity for another 5 years. An arbitrage-free model will produce the same value for the structure viewed either way. This is also known as the law of one price. The term structure matching condition means that when a default-free straight bond is valued according to the model, the result should be the same as if the bond's cash flows are simply discounted according to the current default-free term structure. A model that fails to satisfy either of these conditions cannot be trusted for general problems, though it may be usable in some limited context.
A location-aided routing protocol for cognitive radio networks

Multi-hop cognitive radio networks (CRNs) are gaining interest recently in many practical applications. With location information becoming more available, designing location-aware routing protocols that fit the nature of CRNs becomes a necessity. We present LAUNCH as a location-aided routing protocol for CRNs that has a set of desirable properties: efficient use of the common control channel, has a minimal route setup delay, prefers stable routes, handles primary users heterogeneity, and handles secondary users mobility. LAUNCH is based on four main concepts: (1) a novel location-aware CRN routing metric that takes into account the PUs activity; (2) distributed calculations at the neighbors; (3) a channel locking mechanism to achieve the route stability and minimize channel switching time; (4) an efficient route maintenance strategy. Evaluation of LAUNCH on the NS2 simulator shows that its performance significantly outperforms the current state-of-the-art CRNs routing protocols in terms of end-to-end delay and packet loss rate. In addition, LAUNCH incurs a low control overhead with a fast route establishment delay.
Risk-Based Capital and Solvency Screening in Property-Liability Insurance: Hypotheses and Empirical Tests

For a fixed probability of wrongly classifying a strong insurer as being weak (Type I error), this paper examines the classification power (the probability of correctly identifying a weak insurer as being weak) for two potential solvency detection methods. The first is to classify insurers using ratios based on risk-based capital (RBC) standards and the second is to use the Financial Analysis Tracking System (FAST) solvency screening mechanism created by the National Association of Insurance Commissioners (NAIC). We test the hypothesis that the RBC system has at least as much power for identifying financially weak insurers as the FAST scoring system does. Our empirical results are largely inconsistent with this hypothesis: RBC ratios are less powerful than FAST scores in identifying financially weak property-liability insurers during our sample periods. We also provide limited evidence that RBC ratios and FAST scores are jointly more powerful in identifying weak insurers than FAST scores alone, which suggests that RBC ratios may convey new information about insolvency risk despite their relatively low power on a univariate basis.
Using GIS to Explore the Relationship between Socioeconomic Status and Demographic Variables and Crime in Pittsburgh , Pennsylvania

Many areas across the United States have experienced rising crime rates over the last few decades. The identification of variables related to crime could allow policymakers to develop improved approaches to combating crime. Using multiple regression analysis, relationships between socioeconomic status/demographic variables and crime variables were investigated for Pittsburgh, Pennsylvania in a spatial context using census tracts as the geographic unit of analysis. Using Geographic Information Systems (GIS), choropleth maps were created in order to provide visual representations of the statistically related variables. Hotspot analyses were conducted to identify areas having high or low concentrations of values for crime and demographic variables.
A dense surface motion capture system for accurate acquisition of cloth deformation

This paper presents a system for accurate dense cloth motion capture. In the proposed pipeline cloth motion and dynamics are captured and reconstructed from a multi-view camera set-up. To allow precise tracking of a high number of surface points a tailored pattern is printed on the cloth. Several existing approaches make use of a printed pattern where point correspondence is determined using color-coded vertex neighbourhoods [3, 1]. In this paper we show that point correspondence can be improved and refined using a Laplacian mesh fitting process in the image domain.
Monitoring the Web Sentiment, The Italian Prime Minister's Case

The world has fundamentally changed as the Internet has become a universal means of communication. The Web is a huge virtual space where to express individual opinions and influence any aspect of life. Internet contains a wealth of data that can be mined to detect valuable opinions, with implications even in the political arena. Nowadays the Web sources are more accessible and valuable than ever before, but most of the times the true valuable information is hidden in thousands of textual pages. Their transformation into information is therefore strongly linked to their automatic lexical analysis and semantic synthesis. This poster describes a Knowledge Mining study performed on over 1000 news articles or posts in forum/blogs, concerning the Italian Prime Minister Silvio Berlusconi, involved last year in the sexual scandal. All these textual contributions have been Morpho-Syntactically analysed, Semantically Role labelled and Clustered in order to find meaningful similarities, hilite possible hidden relationships and evaluate their sentiment polarity.
Recommending scientific articles using bi-relational graph-based iterative RWR

The overabundance of scientific article information has created much inconvenience to researchers seeking interesting articles online. In this paper, we provide a Bi-Relational graph to represent the heterogenous information of scientific article recommendation system, which includes three parts: the article content similarity, researcher interest correlation, and researcher-article readership. Meanwhile, an iterative random walk with restarts learning method is proposed on the Bi-Relational graph to recommend a researcher rating for each article by making use of the known information. The proposed method has ability to perform both old and new article recommendation. A series of experiments on CiteULike dataset have shown that our method is more effective than other testing methods in the paper.
Inhibition of Sonic Hedgehog and Notch Pathways Enhances Sensitivity of CD133+ Glioma Stem Cells to Temozolomide Therapy

Malignant gliomas are currently treated with temozolomide (TMZ), but often exhibit resistance to this agent. CD133+ cancer stem cells, a population believed to contribute to the tumor’s chemoresistance, bear the activation of Notch and Sonic hedgehog (SHH) pathways. In this study, we examined whether inhibition of both pathways enhances the efficacy of TMZ monotherapy in the context of glioma stem cells. Transcriptional analysis of Notch and SHH pathways in CD133+-enriched glioma cell populations showed the activity of these pathways. CD133+ cells were less susceptible to TMZ treatment than the unsorted glioma counterparts. Interestingly, Notch and SHH pathway transcriptional activity in CD133+ glioma cells was further enhanced by TMZ exposure, which led to NOTCH 1, NCOR2, and GLI1 upregulation (6.64-, 3.73-, and 2.79-fold, respectively) and CFLAR downregulation (4.22-fold). The therapeutic effect of TMZ was enhanced by Notch and SHH pathway pharmacological antagonism with GSI-1 and cyclopamine. More importantly, simultaneous treatment involving TMZ with both of these compounds led to a significant increase in CD133+ glioma cytotoxicity than treatment with any of these agents alone (P < 0.05). In conclusion, CD133+ glioma cells overexpress genes involved in Notch and SHH pathways. These pathways contribute to the chemoresistant phenotype of CD133+ glioma cells, as their antagonism leads to an additive effect when used in combination with TMZ.
Fine-grained parallel application specific computing for RNA secondary structure prediction using SCFGS on FPGA

In the field of RNA secondary structure prediction, the CYK (Coche-Younger-Kasami) algorithm is a most popular methods using SCFG (stochastic context-free grammars) model. However, general purpose parallel computers including SMP multiprocessors or cluster systems exhibit low parallel efficiency and they are too expensive to be used easily for many research institutes. FPGA chips provide a new approach to accelerate the CYK algorithm by exploiting fine-grained custom design. The CYK algorithm shows complicated data dependence, in which the dependence distance is variable, and the dependence direction is also across two dimensions. We propose a systolic array structure including one master PE and multiple slave PEs for fine grain hardware implementation on FPGA. We partition tasks by columns and assign tasks to PEs for load balance. We exploit data reuse schemes to reduce the need to load matrix from external memory. To our knowledge, our implementation with 16 PEs is the only FPGA accelerator implementing the complete CYK/inside algorithm. The experimental results show a factor of more than 14 speedup over the Infernal-0.55 software running on a PC platform with Pentium 4 2.66GHz CPU. The computational power of our platform with FPGA accelerator is comparable to a PC cluster consisting of 20 Intel-Xeon CPUs for RNA secondary structure prediction using SCFGs, but the hardware cost and power consumption is only about 15% and 10% of the latter respectively.
Systems engineering in commercial and government organizations

Systems engineering (SE) practitioners in research and development (R&D) projects have much general but little specific guidance to manage them. Previous research in SE has contributed to growing advice on tailoring SE efforts given particular project characteristics. This study bolsters this effort by comparing, contrasting, and exploring interactions between commercial and government project risks, success, and SE processes. Demographic company and project information provide insight into commercial and government populations of interest. Coupled with distributed team member interactions, a clearer context for discussing results and conclusions is achieved. Commercial and government projects prove to be principally similar, yet appreciably unique. Introduction Commercial and government organizations have similar intentions, yet a fundamental difference of their respective operating environments is of critical importance in appreciating how systems engineering (SE) is performed and judged as a success or failure in research and development (R&D). Both work to meet customer demands on time and within budget, but the robustness, or lackthereof, of the business case leads to an intuitive notion that commercial and
Modern Communication Instruments for the Imparting of Sustainable Management - By the Example of an Avatar

Not few small and medium-size businesses (SMB’s) in the German-speaking countries are in the meantime sensitized for the problems of the sustainable or environment-conscious management, however until now the necessary resources for the realization of suitable measures were missing. Besides limited means for appropriate human resources, in particular in economical weaker periods, the lack of generally accepted, integrative concepts and methods in the domain of sustainable management is a reason for the non-optimal acting of the decision makers in many places. Since the costs of an extensive and professional consulting by environmental experts often exceed the budgets of SMB's, most responsible persons try to get an idea of possible measures by themselves and apply thereby frequently the instrument of an internet investigation. In the worldwide web they face an enormous amount of unstructured information relating to the topic of the operational environmental protection or the sustainable management. Thus they rarely find the right contributions for their individual problem. The portal for sustainable management of the Ecoradar project (http://www.oekoradar.de or http://www.oekoavatar.de) offers a solution (cf. Schulz (et al.) 2002, 71 et sqq. ): Instead of leaving the users alone with many documents and articles, they are guided individually to suitable pages with the assistance of an avatar. This approach tries to combine the supply of information regarding sus-
Sunlight is associated with decreased multiple sclerosis risk: no interaction with human leukocyte antigen‐DRB1*15

Background: Both insufficient exposure to sunlight and vitamin D deficiency have been associated with an increased risk for multiple sclerosis (MS). An interaction between human leukocyte antigen HLA‐DRB1*15 and vitamin D in MS was recently proposed. We investigated the association between previous exposure to ultraviolet radiation (UVR), vitamin D status at inclusion in the study, and MS risk including the interaction of these factors with HLA‐DRB1*15.
Risk Aversion and Expected Utility Theory: A Calibration Theorem

Within the expected-utility framework, the only explanation for risk aversion is that the utility function for wealth is concave: A person has lower marginal utility for additional wealth when she is wealthy than when she is poor. This paper provides a theorem showing that expected-utility theory is an utterly implausible explanation for appreciable risk aversion over modest stakes: Within expected-utility theory, for any concave utility function, even very little risk aversion over modest stakes implies an absurd degree of risk aversion over large stakes. Illustrative calibrations are provided.
A Methodology to Calculate a Program's Robustness against Transient Faults

Computer chips implementation technologies are evolving to obtain more performance. The side effect of such a scenario is that processors are less robust than ever against transient faults. As on-chip solutions are expensive or tend to degrade processor performance, the efforts to deal with these transient faults in higher levels are increasing. Software based fault tolerance approaches against transient faults often use fault injection experiments to evaluate the behavior of applications with and without their fault detection or fault tolerance proposals. Those fault injection experiments consumes lots of CPU time by running or simulating the application being evaluated as many times as necessary to obtain a reasonable valid statistical approximation. This paper proposes the concept of a program's robustness against transient faults and presents a methodology for exhaustively calculate this robustness based on program's execution trace over an architecture and on information about the used architecture. The presented approach, besides calculating a precise robustness, accomplishes its work faster than using fault injection experiments with ±2% of confidence interval.