Miracle-dz/UniFAR-FTUs huggingface dataset:
Recursive Mahalanobis Separability Measure for Gene Subset Selection

Mahalanobis class separability measure provides an effective evaluation of the discriminative power of a feature subset, and is widely used in feature selection. However, this measure is computationally intensive or even prohibitive when it is applied to gene expression data. In this study, a recursive approach to Mahalanobis measure evaluation is proposed, with the goal of reducing computational overhead. Instead of evaluating Mahalanobis measure directly in high-dimensional space, the recursive approach evaluates the measure through successive evaluations in 2D space. Because of its recursive nature, this approach is extremely efficient when it is combined with a forward search procedure. In addition, it is noted that gene subsets selected by Mahalanobis measure tend to overfit training data and generalize unsatisfactorily on unseen test data, due to small sample size in gene expression problems. To alleviate the overfitting problem, a regularized recursive Mahalanobis measure is proposed in this study, and guidelines on determination of regularization parameters are provided. Experimental studies on five gene expression problems show that the regularized recursive Mahalanobis measure substantially outperforms the nonregularized Mahalanobis measures and the benchmark recursive feature elimination (RFE) algorithm in all five problems.
Prelude to cultural software agents: cultural backgrounds in agent simulation

The aim is to glean appropriate theories and pragmatic findings on human culture and explore ways in which they can be embedded on the decision making of advanced software agents. For this purpose, bases for fuzzy computational agents to represent cultural background and cultural biases of individuals are presented. Some definitions of culture and dimensions, layers and descriptions of differences among cultures are reviewed. Culture models of Hofstede and Schwartz are reviewed and a special questionnaire to specify cultural values is explained. A preliminary model for cultural agents is described briefly and simulation of a cultural agent in Fuzzy Clips environment is reported.
Argus: Low-Cost, Comprehensive Error Detection in Simple Cores

Argus, a novel approach for detecting errors in simple processor cores, dynamically verifies the correctness of the four tasks performed by a von Neumann core: control flow, data flow, computation, and memory access. Argus detects transient and permanent errors, with far lower impact on performance and chip area than previous techniques.
Are capital taxes racing to the bottom in the European Union

This paper tests the central predictions of the theoretical tax competition literature for capital tax rates for a panel of European Union countries, notably a race to the bottom in capital tax rates. One measure of capital mobility is found to exhibit a downward pressure on capital taxes while another measure shows a positive correlation. Empirical tests imply that the latter positive relationship may be caused by neglecting to control for the agglomeration forces linked with capital mobility. If this is indeed the case, the results lend strong empirical support to the hypothesis of a downward pressure on capital tax rates in absolute terms and relative to labor taxes, but add to this that agglomeration forces mitigate, and might even outweigh the race to the bottom effect of increasing capital mobility.
A Promising Future for Prostate Cancer Diagnostics

It has been estimated that globally there is a death attributable to prostate cancer every four minutes. As life expectancy in all world regions increases, so too incidence of this disease of the ageing male will increase. For many men diagnosis occurs after presentation with symptoms of altered urinary dynamics. Unfortunately, these changes, whilst also associated with benign disease, are evident quite late in the aetiology of prostate cancer. Early detection provides for better management and prognosis. This Special Issue provides an up to date view of the advances made towards early diagnosis and prognosis. It provides reviews of advanced imaging techniques (e.g., multiparametric MRI and protocols), and of biomaterials and molecular biomarkers currently being explored (e.g., microRNAs, proteomics) and the technologies that are revolutionizing this field. It describes the multi-disciplinary approaches that are essential to inexpensive, deliverable and accurate platforms for prostate cancer diagnostics.
SOUND OBJECT CLASSIFICATION FOR SYMBOLIC AUDIO MOSAICING: A PROOF-OF-CONCEPT

Sample-based music composition often involves the task of manually searching appropriate samples from existing audio. Audio mosaicing can be regarded as a way to automatize this process by specifying the desired audio attributes, so that sound snippets that match these attributes are concatenated in a synthesis engine. These attributes are typically derived from atargetaudio sequence, which might limit the musical control of the user. In our approach, we replace the target audio sequence by a symbolic sequence constructed with pre-defined sound object categories. These sound objects are extracted by means of automatic classification techniques. Three steps are involved in the sound object extraction process: supervised training, automatic classification and user-assisted selection. Two sound object categories are considered:percussiveand noisy. We present an analysis/synthesis framework, where the user explores first a song collection using symbolic concepts to create a set of sound objects. Then, the selected sound objects are used in a performance environment based on a loop-sequencer paradigm.
On-Demand Reliable Routing Mechanism for MANET Based on Link Lifetime Predicting

One critical issue for routing in Mobile Ad Hoc Networks (MANET) is how to select a reliable path that can last longer since mobility may cause links to break down frequently. Based on the estimated link lifetime, a novel routing mechanism is proposed in this paper. In order to describe the received signal strength continuously, the Newton interpolation polynomial is constructed according to several sample values; thus, the link lifetime can be estimated with reference points calculated from polynomial. With the manner of maximum link lifetime, the source nodes set up route hop-by-hop. Simulation results show that the received signal strength can be described by Newton interpolation polynomial accurately; moreover, the route discovery times and packet drop ratio can be reduced obviously by our mechanism.
Ensemble of deep long short term memory networks for labelling origin of replication sequences

Advancement in sequence data generation technologies are churning out voluminous omics data and posing a massive challenge to annotate the biological functional features. Sequence data from the well studied model organism Saccharomyces cerevisiae has been commonly used to test and validate in silico prediction methods. DNA replication is a critical step in the cellular process and the sequence location where this process originates in the genomic landscape is generally referred as origin of replication. In this paper we investigate the application bidirectional Long Short Term (LSTM) Networks to predict origin of replication sequences. Long Short Term Memory (LSTM) networks have recently been shown to yield state of the art performance in speech recognition, and music generation. These networks are capable of learning long term patterns via the use of multiplication gates. This paper utilizes Deep bidirectional LSTM for prediction of origin of replication sequences belonging to the organism Saccharomyces cerevisiae. Results demonstrate that LSTMs outperform the commonly used machine learning classifiers such as Support Vector Machine (SVM), Random Forest (RF), Artificial Neural Network (ANN), and Hidden Markov Model (HMM). An important additional advantage of LSTMs is that they work directly on the sequences and obviate the need for hand coded features.
Order Selection Based on Performance Simulation of FS-DFE

To select the order (tap number) of feedforward filter of a fractionally spaced decision feedback equalizer (FS-DFE), the relationship between the order and the equalization perfor-mance was studied. Under the known channel characteristics, in variant signal noise ratio and order of feedforward filter, the optimal tap coefficients of FS-DFE was calculated with given algorithm, then the bit error rate performance was simulated using Monte Carlo method and compared with that of symbol spaced decision feedback equalizer (SS-DFE). Finally a method of how to select the order of FS-DFE feedforward filter based on simulation result was proposed and this method could be taken as a reference of FS-DFE engineering design.
On the choice of basis functions for the meshless radial point interpolation method with small local support domains

The behavior of two different types of basis functions for the meshless Radial Point Interpolation Method (RPIM) is investigated in this paper. A 2D test function is interpolated through Gaussian and Wendland basis functions and the approximation errors on the low-order derivatives of the test function are calculated. It is shown that the Gaussian basis function is more appropriate for the interpolation in small support domains whereas Wendland basis function is more accurate for larger support domains.
IHS R&D Belarus: Cross-domain extraction of product features using CRF

This paper describes the aspect extraction system submitted by IHS R&D Belarus team at the SemEval-2014 shared task related to Aspect-Based Sentiment Analysis. Our system is based on IHS Goldfire linguistic processor and uses a rich set of lexical, syntactic and statistical features in CRF model. We participated in two domain-specific tasks – restaurants and laptops – with the same system trained on a mixed corpus of reviews. Among submissions of constrained systems from 28 teams, our submission was ranked first in laptop domain and fourth in restaurant domain for the subtask A devoted to aspect extraction.
An approach to monitoring and assertion-checking of real-time specifications

The paper describes the development of a monitoring and assertion checking tool, MAC, which supports monitoring of symbolic execution traces generated by the Modechart Toolset, permitting testing of specifications early in the design phase and providing a mechanism for evaluating properties of the system on a particular execution trace. This approach avoids many of the difficulties of run time monitoring and testing such as interference and the probe effect. Monitoring and assertion checking capabilities are provided by the automatic translation of assertions in a declarative language (such as Real Time Logic) into monitoring fragments, written in Modechart, which augment the original specification to perform monitoring and assertion checking during simulation.
Hydrology and Earth System Sciences Modelling of Monsoon Rainfall for a Mesoscale Catchment in North-west India Ii: Stochastic Rainfall Simulations

Within this study we present a robust method for generating precipitation time series for the Anas catchment in North Western India. The method employs a multivari-ate stochastic simulation model that is driven by a time series of objectively classified circulation patterns (CPs). In a companion study (Zehe et al., 2006) it was already shown that CPs classified from the 500 or 700 Hpa levels are suitable to explain space-time variability of precipitation in that area. The model is calibrated using observed rainfall time series for the period 1985–1992 for two different CP time series, one from the 500 Hpa level and the over from the 700 Hpa level, and 200 realizations of daily rainfall are simulated for the period 85–94. Simulations using the CPs from the 500 Hpa level as input yield a good match of the observed averages and standard deviations of daily rainfall. They show furthermore good performance at the monthly scale. When used with the 700 Hpa level CPs as inputs the model clearly underestimates the standard deviation and performs much worse at the monthly scale, especially in the validation period 93–94. The presented results give evidence that CPs from the 500 Hpa, level in combination with a multivariate stochastic model, make up a suitable tool for reducing the sparsity of precipitation data in developing regions with sparse hydro-meteorological data sets.
EOCTC: Energy Efficient Ordered Congestion Tolerant and Control Routing Topology for Mobile Ad hoc Networks

The impacts of moving directions and speed of the nodes in mobile ad hoc networks leads link failure very often. This route failures causes resource cost due to route rediscovery and multiple transmissions. Often the protocol used in mobile ad hoc routing mislead by assuming link failure as congestion state and then continues retransmissions of the dropped packets, which is severely effects by wasting energy resources. In this context, our earlier work proposed a cross layered routing topology in short OCC to improve the clogging recognition and managing policy. With the motivation gained from OCC, we further proposed an Energy Efficient Ordered Congestion Control routing topology (EOCC) for mobile ad hoc networks. The goal of EOCC is to advance communication performance of OCC with energy efficiency that used for packet transmission. Here in this paper we introduced a novel path restoration strategy to tolerate the congestion state at hop level node that participating in routing. The Proposed protocol is a cross layered and power conserved routing topology for congestion tolerance and control, which is an extension to our earlier cross layered and power conserved routing topology in short EOCC. The proposed protocol can be referred as Energy Efficient Ordered Congestion Tolerant and Control (EOCTC) Routing Topology. The experiment results emerged as an evidence for EOCTC performance and scalability. Better resource utilization, energy efficiency can be observed in data transmission and congestion tolerance achieved due to path restoration strategy and congestion control is effective.
A Protein-Interaction Array Inside a Living Cell**

Cell phenotype is determined by protein network states that are maintained by the dynamics of multiple protein interactions.1 Fluorescence microscopy approaches that measure protein interactions in individual cells, such as by Forster resonant energy transfer (FRET), are limited by the spectral separation of fluorophores and thus are most suitable to analyze a single protein interaction in a given cell. However, analysis of correlations between multiple protein interactions is required to uncover the interdependence of protein reactions in dynamic signal networks. Available protein-array technologies enable the parallel analysis of interacting proteins from cell extracts, however, they can only provide a single snapshot of dynamic interaction networks. Moreover, because of the high level of variance from cell to cell in protein expression levels and reaction state, cell extracts only provide an average measure of protein interaction states and therefore the detection of the relations between proteins is blurred. As an intermediate step, a visual immunoprecipitation assay was developed that allowed direct observation of multiple, dynamic protein interactions on immobilized, distinguishable beads in cell extracts.2 A microstructuring approach allowed for analysis of the interaction of one naturally occurring receptor type with one of its interaction partners inside cells.3 To analyze multiple protein interactions inside a single living cell, multiple receptors must be arranged in a defined pattern to distinguish their identity. Herein, we developed a general strategy to generate protein arrays with multiple arbitrary bait proteins by way of artificial-receptor constructs at sub-cellular feature size and applied this technology to simultaneously measure two-protein interaction kinetics inside an individual living cell.
Impact of Two Factors on Several Domain Decomposition Based Parallel Incomplete Factorizations for the Meso-scale Simulation of Concrete

It is an efficient technique to parallelize incomplete factorizations based on domain decomposition. In this paper, three are considered for solving the derived sparse linear systems from the meso-scale simulation of concrete, including the block Jacobi analog, the classical additive Schwarz, and the so-called factors combination method. For the grid may be of unstructured ones, the graph partitioning method is exploited to perform domain decomposition. The different partitioning schemes are compared and analyzed. The results show that the communication structure is one of the vital factors for the efficiency but not the all. Further, the degree of overlapping is also tested and the results show that for the current simulation, the degree of 1 is enough.
Very Small Array observations of the anomalous microwave emission in the Perseus region

The dust complex G159.6-18.5 in the Perseus region has previously been observed with the {COSMOSOMAS} experiment on angular scales of {\textasciitilde}1? ,and was found to exhibit anomalous microwave emission. We present thefirst high angular resolution observations of this dust complex,performed with the Very Small Array ({VSA}) at 33GHz, to help increase theunderstanding of the nature of this anomalous emission.On the angular scales observed with the {VSA} ({\textasciitilde}10-40arcmin), G159.6-18.5consists of five distinct components, all of which are found to exhibitan excess of emission at 33GHz that is highly correlated withfar-infrared emission. Within the region, we find a range of physicalconditions: one of the features, which is associated with the reflectionnebula {IC} 348, has a dust emissivity comparable to that of {HII} regions,while the other four features have values in agreement with previousobservations of intermediate Galactic latitudes. We provide evidencethat all of these compact components have anomalous emission that isconsistent with electric dipole emission from very small, rapidlyrotating dust grains. We find that these five components contribute {\textasciitilde}10per cent to the flux density of the diffuse extended emission detectedby {COSMOSOMAS}, implying that the bulk of the anomalous emission inPerseus is diffuse and not concentrated in these compact components.
Drug use monitoring in Australia (DUMA) : drug detection testing

A short overview of urine testing is presented along with the various issues associated with this procedure and its application to the Drug Use Monitoring in Australia program. The DUMA project uses urine results as one of its key indicators of drug use so Makkai explains urinalysis testing and the processes involved in obtaining a result. She also discusses the chemical changes that occur once a drug has been ingested, cut-off levels and concentration levels.
The role of peer drug users’ social networks and harm reduction programs in changing the dynamics of life for people who use drugs in the downtown eastside of Vancouver, Canada

The Downtown Eastside (DTES) of Vancouver, Canada has been the epicentre of HIV, hepatitis C and drug overdose related to people who inject drugs (PWIDs) since the mid1990s. In response to the growing government inaction, numbers of peer-run organizations were formed. This dissertation was conducted to capture the genesis and influence of peer drug users, their networks and harm reduction programs over the past 18 years in shaping the neighborhood. Semi-structured qualitative interviews were conducted with peers from various harm reduction volunteer locations in the DTES. Moreover, various drug users were recruited from a controversial harm reduction program in the DTES that provides pharmaceutical heroin. Interviews were analyzed thematically using two methods of coding analysis. Findings suggest that peers were taking on important education and safety roles, and were able to alter the behaviour, attitude, and intention of injection drug users within the DTES area of the city. Further, peer injection drug users were able to reach individuals who were reluctant to seek medical help, housing, and prevention services. Peers serve as an agent of change in the DTES to disseminate information and risk reduction skills to the most marginalized people. Peer drug users have not only been able to change the discriminatory rhetoric but they have been able to reduce the suffering that drug users have endured as a consequence of the war on drugs. Attending heroin trials in Vancouver has been particularly effective in creating a unique microenvironment where PWIDs who have attended heroin trials have been able to form a collective identity advocating for their rights. In physical terms, the DTES has become cleaner and safer for its residents because of availability of an injection facility and numerous peer-run harm reduction programs. In conceptual terms, PWIDs are less likely to experience discrimination by the city, hospital, and police. Moreover, the residents in the new DTES are more likely to be involved in their civic issues and raise concerns in a new political arena. Peer-run harm reduction programs have given a voice to the most marginalized members of society who otherwise would not be represented. The result of this dissertation and costing analyses conducted point to the need for the expansion of the peer and harm reduction programs beyond the current location in the DTES to other locations in Canada such as Montreal, Ottawa, Toronto, Saskatoon and Victoria.
Analysis of expected delay of LAR protocol for VANETs

Vehicular Ad-hoc Network (VANET) is a networking technology uses to create wireless network using mobile vehicles. In this network, the mobile vehicles work as intermediate node to transmit data over the wireless network. In VANET, routing of data packet is more challenging due to its highly dynamic nature. Performance of VANET depends upon the selection of the suitable next-hop nodes for further transmission in the network. Due to highly movable vehicular nodes, the link may break very frequently caused network delay; therefore, it is important to select the appropriate next-hop forwarding node to complete the data transmission. In this paper, we have computed the expected delay using one-hop distance between first two nodes. Further, we have analyzed the numerical results using MATLAB.
Iterate-averaging sign algorithms for adaptive filtering with applications to blind multiuser detection

Motivated by the developments on iterate averaging of recursive stochastic approximation algorithms and asymptotic analysis of sign-error algorithms for adaptive filtering, this work develops two-stage sign algorithms for adaptive filtering. The proposed algorithms are based on constructions of a sequence of estimates using large step sizes followed by iterate averaging. Our main effort is devoted to improving the performance of the algorithms by establishing asymptotic normality of a suitably scaled sequence of the estimation errors. The asymptotic covariance is calculated and shown to be the smallest possible. Hence, the asymptotic efficiency or asymptotic optimality is obtained. Then variants of the algorithm including sign-regressor procedures and constant-step algorithms are studied. The minimal window width of averaging is also dealt with. Finally, iterate-averaging algorithms for blind multiuser detection in direct sequence/code-division multiple-access (DS/CDMA) systems are proposed and developed, and numerical examples are examined.