Miracle-dz/UniFAR-FTUs huggingface dataset:
Stochastic Markov Recurrent Neural Network for Source Separation

Monaural source separation based on recurrent neural network is learned to characterize the sequential patterns in source signals based on dynamic states which are propagated through time. The hidden states are assumed to be deterministic along a single path where a shared long short-term memory (LSTM) is used. Such assumptions may not faithfully reflect the randomness and the variety of temporal features in mixed signals. To strengthen the capability of LSTM in source separation, we propose a stochastic Markov LSTM where the regression from the mixed signal to its source signals is learned with a stochastic indicator of Markov state which selects the state-dependent LSTM for signal separation at each time. A set of LSTMs is discovered to capture the structural diversity of temporal signals or the stochastic trajectory of state transitions for sequential prediction. A new state machine is constructed to learn the complicated latent semantics in heterogeneous and structural mappings between mixed signals and source signals. The Gumbel-softmax sampling is implemented in the backpropagation algorithm with discrete Markov states. Experiments on speech enhancement illustrate the merit of the proposed stochastic Markov LSTM in terms of short-term objective intelligibility measure of the separated speech.
Marvin: Semantic annotation using multiple knowledge sources

People are producing more written material then anytime in the history. The increase is so high that professionals from the various fields are no more able to cope with this amount of publications. Text mining tools can offer tools to help them and one of the tools that can aid information retrieval and information extraction is semantic text annotation. In this report we present Marvin, a text annotator written in Java, which can be used as a command line tool and as a Java library. Marvin is able to annotate text using multiple sources, including WordNet, MetaMap, DBPedia and thesauri represented as SKOS.
KnockAround: Location Based Service via Social Knowledge

With the proliferation of location awareness in smartphones, location-based services (LBSs), such as finding nearby Sushi restaurants, have become popular. In traditional LBS applications, the user's location is sent from her smartphone to an LBS server over the Internet and the LBS server then serves the information from its database. We observe that people who share space-time context may have overlapping needs for location-based information. Based on this observation, in this paper, we propose a pure P2P-based, pull-type LBS application for smartphones, which exploits the location information already uncovered by the surrounding people (including strangers) during their day-to-day visits, to serve the need for location information of a user. Our application is free from a single point of failure. The database of location information in our system is distributed over people's smartphones and the users themselves update the database dynamically without the need of centralized maintenance. Also our application can serve location information that is volatile and highly idiosyncratic to a particular locality, and thus a central location server is unlikely to contain it. We present the detailed architecture, algorithms, implementation, and survey-based evaluation of our LBS application along with a discussion on the potential caveats and their possible solutions in using our system. We also propose an incentive mechanism to fight against free-riders and evaluate the mechanism using real-life data and simulation.
Double archive Pareto local search

Many real-world problems have multiple, conflicting objectives and a large complex solution space. The conflicting objectives give rise to a set of non-dominating solutions, known as the Pareto front. In the absence of any prior information on the relative importance of the objectives, none of these solutions can be said to be better than others, and they should all be presented to the decision maker as alternatives. In most cases, the number of Pareto solutions can be huge and we would like to provide a good representative approximation of the Pareto front. Moreover, the search space can be too large and complex for the problem to be solved by exact methods. Therefore efficient heuristic search algorithms are needed that can handle such problems. In this paper, we propose a double archive based Pareto local search. The two archives of our algorithm are used to maintain (i) the current set of non-dominated solutions, and (ii) the set of promising candidate solutions whose neighbors have not been explored yet. Our selection criteria is based on choosing the candidate solutions from the second archive. This method improves upon the existing Pareto local search and queued Pareto local search methods for bi-objective and tri-objective quadratic assignment problem.
Identification of Treponema pallidum penicillin-binding proteins

Penicillin-binding proteins of 180, 89, 80, 68, 61, 41, and 38 kilodaltons were identified in Treponema pallidum (Nichols) by their covalent binding of [35S]benzylpenicillin. Penicillin-binding proteins are localized in the plasma membranes of many bacterial species and may serve as useful markers for determining plasma membrane intactness in T. pallidum fractionation studies.
Some growth parameters of Chondrostoma regium (Heckel, 1843) inhabiting Karasu River (East Anatolia, Turkey)

Bu calisma, Karasu Nehri’nin 14 farkli istasyonunda yasayan kababurun (Chondrostoma regium (Heckel, 1843))’un yas tayini ve bazi buyume ozelliklerinin arastirilmasi ile ilgilidir. Bu amacla, 2014 ve 2016 yillari arasinda elektrosokerle toplam 236 C. regium balik ornegi (124 disi ve 112 erkek) yakalandi. Orneklenen C. regium bireylerinin total boy ve agirligi sirasiyla 11,0-33,0 cm ile 33,0-324,0 g arasinda degistigi gorulmustur. Incelenen bireylerin yaslarinin 1-7 arasinda degistigi gorulmus ve disi:erkek orani 1:0.903 olarak belirlenmistir. von Bertalanffy buyume parametreleri tum bireyler icin Lt=40,17[1-e-0,154(t+2,14)]; Wt=495,009[1-e-0,154(t+2,14)]2,50 ve buyume performans indeks degeri (Ф') ise 2,395 olarak hesaplanmistir. Incelenen populasyon icin boy-agirlik iliskileri ise W=0,0503L2,50 (R² = 0,97; b’nin guven araliklari=2,41-2,70; p<0,001) seklinde bulunmustur. Bu degerlere gore, C. regium’un buyume tipinin negatif allometrik ozellik gosterdigi gorulmustur.
I want my MTV ! 4 G : Content Distribution Re-defined

Vehicular communication networks have been gaining significant popularity and importance recently, primarily to cater to the emerging services involving road safety and a need for data-on-move. Existing content distribution technologies like VANETs, infrastructure based solution or 3G networks suffer from either cost issues, latency, bandwidth or a combination of them. Moreover, they assume that data can tolerate delays and support only non-realtime content distribution. In this paper, we argue that i) with emergence of new vehicular applications, content delivery will no longer remain a non-realtime operation, and ii) that no current generation wireless communication technology alone is sufficiently powerful to support content distribution for all types of new and emerging vehicular applications. We also discuss possible solutions like i) a hybrid system that makes use of a combination of existing technologies and ii) the next generation 4G system, which presents an attractive solution for vehicular communication, where voice, data and streamed multimedia can be given to users on an “anytime, anywhere” basis.
A system for real-time fabric inspection and industrial decision

This work presents an application of software engineering to fabric inspection. An inspection system has been developed for textile industries that aims automatic failure detection. Such as wood, paper and steel industries, this environment has particular characteristics in which surface defect detection is used for quality control. This system combines concept from software engineering and decision support. Detection of defects within the inspected texture is performed in a first step acquiring images by CCD cameras, then extracting texture features and, finally by classifiers being trained a priori on database of defective and non-defective samples. The extracted data depend on the type of method selected for image analysis. The used types are based on segmentation or fractal dimension. Two usual segmentation techniques were adapted and improved. A new algorithm was developed to calculate efficiently fractal dimension of textures. Experiments show the accuracy and applicability of the proposed techniques for a real factory environment.
Network partition for coordinated control in active distribution networks

This paper addresses the issue of network partition used in power system analysis for ancillary services in distribution networks with distributed generation. Simplification and reduction of the computational effort in network calculation for centralized control can be achieved, through a definition of suitable partitioned clusters. The zoning problem is explored using a clustering process based on the k-means algorithm. The proposed method is implemented within a study case of voltage profile calculation in a 20 kV distribution network for steady state voltage control. The results show the performance of the method, with the caveat of the need of preliminary fitting of the parameters.
Elimination of the last reactions in ergosterol biosynthesis alters the resistance of Saccharomyces cerevisiae to multiple stresses

The sterol composition of membranes is known to influence many phenotypes of yeast. However, a systematic study of the relationship between sterol composition and stress resistances has not been conducted. Here, we therefore constructed single or double gene deletion mutants of the last four enzymes in ergosterol biosynthesis in a prototrophic genetic background of Saccharomyces cerevisiae. Identification of the sterol composition of these mutants revealed a high flexibility of the sterol-processing steps instead of the previously proposed sequential conversion. Compared with the wild type, the mutants showed altered resistances to different exogenous stresses regarding the specific growth rate and duration of lag phase. The erg5 deletion mutant whose sterol has a saturated side chain exhibited overall robust growth under the tested stress conditions. The thermotolerant phenotype of erg5 deletion mutant was reproduced in filamentous fungus Penicillium oxalicum. These results highlight the important role of sterols in the response of yeast cells to environmental stresses, and suggest the possibility of improving the robustness of industrial yeast strains by engineering their sterol composition.
p53-Pathway activity and apoptosis in hydrogen sulfide-exposed stem cells separated from human gingival epithelium.

BACKGROUND AND OBJECTIVE Hydrogen sulfide ( H₂S ) is a volatile sulfur compound responsible for physiological halitosis. H₂S was also reported as having periodontal pathologic activities. Gingival crevicular epithelium is the first barrier against periodontal pathogens and their products; oral keratinocyte stem cells OKSCs play key roles in maintaining this barrier. The p53 pathway is responsible for regulating key biological events. Increased apoptosis and cell-cycle arrest of DNA repair can affect keratinocyte stem cells, having a direct impact on the architecture of the oral epithelial tissue. However, the link between H₂S , p53 activity and OKSCs has not yet been fully explored. The main objective of the present study was to explore the implications of the p53 pathway in OKSCs following exposure to H₂S. MATERIAL AND METHODS OKSCs were isolated from human gingival epithelium and incubated with physiological levels of H₂S for 24 and 48 h. Apoptosis and the mitochondrial membrane potential were detected using flow cytometry. Cytochrome c, total p53, phosphorylated p53 and caspase activity were assessed using specific ELISAs. p53 Pathway gene activity was assayed using quantitative RT-PCR. RESULTS The levels of apoptosis were significantly increased following incubation in the presence of H₂S, especially after 48 h (36.95 ± 1.91% vs. 4.77 ± 0.74%). Caspases 9 and 3 were activated, whereas caspase-8 activity remained low. Total p53 activity and particularly phosphorylated p53 at serine 46, were significantly enhanced compared with controls (47.11 ± 9.84 units/mL vs. 1.5 ± 0 units/mL and 32.22 ± 10.23 units/mL vs. 0.15 ± 0 units/mL, respectively, at 48 h). Among p53 pathway genes, apoptosis-related genes [i.e. phosphatase and tensin homolog ( PTEN ), B-cell CLL/lymphoma 2 ( BCL2), sirtuin 3 ( SIRT3) and caspases]) were dramatically increased when compared with controls. Moreover, cell-cycle progression genes [i.e. E2F transcription factor (E2F) family and histone deacetylase ( HDAC )] and DNA-repair genes [i.e. growth arrest and DNA-damage-inducible, gamma ( GADD45G ) family and serine/threonine-protein kinase Chk2 ( CHEK2)] were also increased. CONCLUSION Following incubation with H2 S , OKSCs express multiple p53-associated genes, including programmed cell death, cell-cycle control and DNA-repair genes.
Generating Optimum Number of Clusters Using Median Search and Projection Algorithms

K-means Clustering is an important algorithm for identifying the structure in data. In this work, a novel approach to seeding the clusters with the latent data structure is proposed. This is expected to minimize: the need for number of clusters apriory and time for convergence by providing near optimal cluster centers. Also these algorithms are tested on the latest standards for data warehouses – the column store databases.
How regularization affects the critical points in linear networks

This paper is concerned with the problem of representing and learning a linear transformation using a linear neural network. In recent years, there has been a growing interest in the study of such networks in part due to the successes of deep learning. The main question of this body of research and also of this paper pertains to the existence and optimality properties of the critical points of the mean-squared loss function. The primary concern here is the robustness of the critical points with regularization of the loss function. An optimal control model is introduced for this purpose and a learning algorithm (regularized form of backprop) derived for the same using the Hamilton's formulation of optimal control. The formulation is used to provide a complete characterization of the critical points in terms of the solutions of a nonlinear matrix-valued equation, referred to as the characteristic equation. Analytical and numerical tools from bifurcation theory are used to compute the critical points via the solutions of the characteristic equation. The main conclusion is that the critical point diagram can be fundamentally different even with arbitrary small amounts of regularization.
A Traveling-Wave-Based Protection Technique Using Wavelet/PCA Analysis

This paper proposes a powerful high-speed traveling-wave-based technique for the protection of power transmission lines. The proposed technique uses principal component analysis to identify the dominant pattern of the signals preprocessed by wavelet transform. The proposed protection algorithm presents a discriminating method based on the polarity, magnitude, and time interval between the detected traveling waves at the relay location. A supplemental algorithm consisting of a high-set overcurrent relay as well as an impedance-based relay is also proposed. This is done to overcome the well-known shortcomings of traveling-wave-based protection techniques for the detection of very close-in faults and single-phase-to-ground faults occurring at small voltage magnitudes. The proposed technique is evaluated for the protection of a two-terminal transmission line. Extensive simulation studies using PSCAD/EMTDC software indicate that the proposed approach is reliable for rapid and correct identification of various fault cases. It identifies most of the internal faults very rapidly in less than 2 ms. In addition, the proposed technique presents high noise immunity.
Swarm Coordination for Pursuit Evasion Games using Sensor Networks

In this work we consider the problem of pursuit evasion games (PEGs) where a group of pursuers is required to detect, chase and capture a group of evaders with the aid of a sensor network in minimum time. Differently from standards PEGs where the environment and the location of evaders is unknown and a probabilistic map is built based on the pursuer’s onboard sensors, here we consider a scenario where a sensor network, previously deployed in the region of concern, can detect the presence of moving vehicles and can relay this information to the pursuers. Here we propose a general framework for the design of a hierarchical control architecture that exploits the advantages of a sensor network by combining both centralized and decentralized real-time control algorithms. We also propose a coordination scheme for the pursuers to minimize the time-to-capture of all evaders. In particular, we focus on PEGs with sensor networks orbiting in space for artificial space debris detection and removal.
Expression Profiling of Exosomal miRNAs Derived from Human Esophageal Cancer Cells by Solexa High-Throughput Sequencing

Cellular genetic materials, such as microRNAs (miRNAs), mRNAs and proteins, are packaged inside exosomes, small membrane vesicles of endocytic origin that are released into the extracellular environment. These cellular genetic materials can be delivered into recipient cells, where they exert their respective biological effects. However, the miRNA profiles and biological functions of exosomes secreted by cancer cells remain unknown. The present study explored the miRNA expression profile and distribution characteristics of exosomes derived from human esophageal cancer cells through Solexa high-throughput sequencing. Results showed that 56,421 (2.94%) unique sequences in cells and 7727 (0.63%) in exosomes matched known miRNAs. A total of 342 and 48 known miRNAs were identified in cells and exosomes, respectively. Moreover, 64 and 32 novel miRNAs were predicted in cells and exosomes, respectively. Significant differences in miRNA expression profiles were found between human esophageal cancer cells and exosomes. These findings provided new insights into the characteristics of miRNAs in exosomes derived from human esophageal cancer cells and the specific roles of miRNAs in intercellular communication mediated by exosomes in esophageal cancer.
Chapter 11 Heparin Regulation of the Complement System

The complement system consists of approximately 25 proteins that work to complement the activity of antibodies in destroying bacteria, either by facilitating phagocytosis or by puncturing the bacterial cell membrane resulting in bacterial cell lysis (1). Heparin, a clinically used anticoagulant, is a polydisperse, highly sulfated, linear polysaccharide consisting of 1! 4 linked uronic acid and glucosamine residues (2,3). The biological activities of pharmaceutical heparin are reviewed elsewhere (2–6). Heparin can bind to a variety of proteins, including growth factors (7), proinflammatory chemokines and cytokines (6), extracellular matrix proteins (8), and complement proteins (9). Binding takes place primarily through electrostatic interactions between heparin’s anionic groups (sulfo and carboxyl), and the positively charged amino acid residues (arginine and lysine) of the heparin-binding proteins (10,11). Heparin–protein interactions regulate such diverse processes as coagulation, homeostasis (12), cell adhesion (8), lipid metabolism (13), growth factor signal Garg / Chemistry and Biology of Heparin and Heparan Sulfate chap11 Revise Proof page 313 8.11. 2005 12:44pm
A Relay Selection and Power Allocation Scheme for Cooperative Wireless Sensor Networks

This paper investigates optimal relay selection and power allocation under an aggregate power constraint for cooperative wireless sensor networks assisted by amplify-and-forward relay nodes. By considering both transmission power and circuit power consumptions, the received signal-to-noise ratio (SNR) at the destination node is calculated, based on which, a relay selection and power allocation scheme is developed. The core idea is to adaptively adjust the selected relays and their transmission power to maximize the received SNR according to the channel state information. The proposed scheme is derived by recasting the optimization problem into a three-layered problem? determining the number of relays to be activated, selecting the active relays, and performing power allocation among the selected relays. Monte Carlo simulation results demonstrate that the proposed scheme provides a higher received SNR and a lower bit error rate as compared to the average power allocation scheme.
Molecular and Cellular Pathobiology NCOA 1 Directly Targets M-CSF 1 Expression to Promote Breast Cancer Metastasis

In breast cancer, overexpression of the nuclear coactivator NCOA1 (SRC-1) is associated with disease recurrence and resistance to endocrine therapy. To examine the impact of NCOA1 overexpression on morphogenesis and carcinogenesis in themammary gland (MG), we generatedMMTV-hNCOA1 transgenic [Tg(NCOA1)] mice. In the context of two distinct transgenic models of breast cancer, NCOA1 overexpression did not affect the morphology or tumor-forming capability of MG epithelial cells. However, NCOA1 overexpression increased the number of circulating breast cancer cells and the efficiency of lungmetastasis. Mechanistic investigations showed that NCOA1 and c-Fos were recruited to a functional AP-1 site in the macrophage attractant CSF1 promoter, directly upregulating colony-simulating factor 1 (CSF1) expression to enhance macrophage recruitment and metastasis. Conversely, silencing NCOA1 reduced CSF1 expression and decreased macrophage recruitment and breast cancer cell metastasis. In a cohort of 453 human breast tumors, NCOA1 and CSF1 levels correlated positively with disease recurrence, higher tumor grade, and poor prognosis. Together, our results define an NCOA1/AP-1/CSF1 regulatory axis that promotes breast cancermetastasis, offering a novel therapeutic target for impeding this process. Cancer Res; 74(13); 1–12. 2014 AACR.
Solving the Difference Initial-Boundary Value Problems by the Operator Exponential Method

Abstract We suggest a modification of the operator exponential method for the numerical solving the difference linear initial boundary value problems. The scheme is based on the representation of the difference operator for given boundary conditions as the perturbation of the same operator for periodic ones. We analyze the error, stability and efficiency of the scheme for a model example of the one-dimensional operator of second difference.
Path analysis of the genetic integration of traits in the sand cricket: a novel use of BLUPs

This study combines path analysis with quantitative genetics to analyse a key life history trade‐off in the cricket, Gryllus firmus. We develop a path model connecting five traits associated with the trade‐off between flight capability and reproduction and test this model using phenotypic data and estimates of breeding values (best linear unbiased predictors) from a half‐sibling experiment. Strong support by both types of data validates our causal model and indicates concordance between the phenotypic and genetic expression of the trade‐off. Comparisons of the trade‐off between sexes and wing morphs reveal that these discrete phenotypes are not genetically independent and that the evolutionary trajectories of the two wing morphs are more tightly constrained to covary than those of the two sexes. Our results illustrate the benefits of combining a quantitative genetic analysis, which examines statistical correlations between traits, with a path model that focuses upon the causal components of variation.