Miracle-dz/UniFAR-FTUs huggingface dataset:
STEAN: A storage and transformation engine for advanced networking context

Legacy Internet systems and protocols are mostly static and keep state information in silo-style storage, thus making state migration, transformation and re-use difficult. Software Defined Networking (SDN) approaches in unison with Network Functions Virtualization (NFV) allow for more flexibility, yet they are currently restricted to a limited set of state migration options. Impeding the sharing of networking and system state severely limits the ability to optimally manage resources and dynamically adapt to a desirable overall configuration. We propose a generalized way to collect, store, transform, and share context between NFs in both the legacy Internet and NFV/SDN-driven systems. To this end, we design and implement a Storage and Transformation Engine for Advanced Networking Context (STEAN), which constitutes a shared context storage, making network state information available to other systems and protocols. Its pivotal feature is the ability to allow for state transformation as well as for persisting state to enable future reuse. By means of experimentation, we show that STEAN covers a diverse set of challenging use cases in legacy systems as well as in NFV/SDN-enabled systems.
Brief Communication: Maternal Plasma Autoantibodies Screening in Fetal Down Syndrome

Imbalance in the metabolites levels which can potentially be related to certain fetal chromosomal abnormalities can stimulate mother's immune response to produce autoantibodies directed against proteins. The aim of the study was to determine the concentration of 9000 autoantibodies in maternal plasma to detect fetal Down syndrome. Method. We performed 190 amniocenteses and found 10 patients with confirmed fetal Down syndrome (15th–18th weeks of gestation). For the purpose of our control we chose 11 women without confirmed chromosomal aberration. To assess the expression of autoantibodies in the blood plasma, we used a protein microarray, which allows for simultaneous determination of 9000 proteins per sample. Results. We revealed 213 statistically significant autoantibodies, whose expression decreased or increased in the study group with fetal Down syndrome. The second step was to create a classifier of Down syndrome pregnancy, which includes 14 antibodies. The predictive value of the classifier (specificity and sensitivity) is 100%, classification errors, 0%, cross-validation errors, 0%. Conclusion. Our findings suggest that the autoantibodies may play a role in the pathophysiology of Down syndrome pregnancy. Defining their potential as biochemical markers of Down syndrome pregnancy requires further investigation on larger group of patients.
Deep neural networks for kannada phoneme recognition

Deep neural network (DNN) based speech recognizers have recently replaced Gaussian Mixture Model (GMM) based systems as the state-of-the-art. Developing a phonetic engine and enhancing its performance can lead to significant improvement in Automatic Speech Recognition (ASR). However only a less work has been reported in developing Phonetic engine on large vocabulary Kannada speech corpus. In this paper, the comparative study of speech recognition baselines: HMM-GMM, HMM-ANN and HMM-DNN are analyzed. Our first set of experiments use the Kannada speech corpus, which contains continuous utterances recorded in three different modes namely read mode, lecture mode and conversation mode. Context independent phone modeling is carried out on the three baselines and evaluated on different modes of the corpus. Phone Error Rate is measured and compared on all the three baselines. Acoustic modeling using HMM-DNN baseline shows significant improvement of about 7–8 % over HMM-GMM and HMM-ANN baselines.
Local Binary Patterns Calculated over Gaussian Derivative Images

In this paper we present a new static descriptor for facial image analysis. We combine Gaussian derivatives with Local Binary Patterns to provide a robust and powerful descriptor especially suited to extracting texture from facial images. Gaussian features in the form of image derivatives form the input to the Linear Binary Pattern(LBP) operator instead of the original image. The proposed descriptor is tested for face recognition and smile detection. For face recognition we use the CMU-PIE and the YaleB+extended YaleB database. Smile detection is performed on the benchmark GENKI 4k database. With minimal machine learning our descriptor outperforms the state of the art at smile detection and compares favourably with the state of the art at face recognition.
Cache Oblivious Dense and Sparse Matrix Multiplication Based on Peano Curves

Cache oblivious algorithms are designed to benefit from any existing cache hierarchy—regardless of cache size or architecture. In matrix computations, cache oblivious approaches are usually obtained from block-recursive approaches. In this article, we extend an existing cache oblivious approach for matrix operations, which is based on Peano space-filling curves, for multiplication of sparse and dense matrices (sparse-dense, dense-sparse, sparse-sparse). We present the respective block-oriented data structure to store sparse matrices, and give first performance results on multicore platforms.
Power allocation in repetition time diversity hybrid automatic repeat request feedback

This paper addresses the problem of optimal power allocation for hybrid automatic repeat request (HARQ) feedback over slowly-fading channels. We mainly focus on the repetition time diversity HARQ scheme where the results are obtained for both continuous and bursting communication models. Moreover, the effect of an outage probability constraint on the system data transmission efficiency is studied under different transmission power constraints. Simulation results show that 1) for Nakagami fading channels, the optimal HARQ-based (re)transmission powers maximizing the system throughput should be decreasing in every (re)transmission round, 2) higher rates are achieved in the continuous communication, when compared with the bursting model, and 3) HARQ feedback leads to considerable performance improvement even in outage-limited conditions.
Effect of cofactor-binding on the specific interactions between androgen receptor and its ligand: Ab initio molecular simulations

To elucidate the effect of cofactor YLO on the structure and electronic properties of the androgen receptor (AR) and its ligand (TES) complex, we investigate the change in structure for the AR+TES and the AR+TES+YLO complexes by molecular dynamics simulations in explicit waters. We moreover perform ab initio fragment molecular orbital calculations for the complexes, in order to reveal the change in the specific interactions between AR and TES induced by YLO.
Multilevel selective harmonic elimination PWM technique in series-connected voltage inverters

The selective harmonic elimination PWM (SHEPWM) method is systematically applied for the first time to multilevel series-connected voltage source PWM inverters. The method is implemented based on optimization techniques. The optimization starting point is obtained using a phase-shift harmonic suppression approach. Another less computationally demanding harmonic suppression technique, called a mirror surplus harmonic method, is proposed for five-level (double-cell) inverters. Theoretical results of both methods are verified by experiments and simulations for a double-cell inverter. Simulation results for a five-cell (11-level) inverter are also presented for the multilevel SHEPWM method.
TL1A Induces TCR Independent IL-6 and TNF-α Production and Growth of PLZF+ Leukocytes

An elevated level of the cytokine TL1A is known to be associated with several autoimmune diseases, e.g. rheumatoid arthritis and inflammatory bowel disease. However, the mode of action of TL1A remains elusive. In this study, we investigated the role of TL1A in a pro-inflammatory setting, using human leukocytes purified from healthy donors. We show that TL1A, together with IL-12, IL-15 and IL-18, directly induces the production of IL-6 and TNF-α from leukocytes. Interestingly, TL1A-induced IL-6 was not produced by CD14+ monocytes. We further show that the produced IL-6 is fully functional, as measured by its ability to signal through the IL-6 receptor, and that the induction of IL-6 is independent of TCR stimulation. Furthermore, the transcription factor PLZF was induced in stimulated cells. These results offer a substantial explanation for the role of TL1A, since TNF-α and IL-6 are directly responsible for much of the inflammatory state in many autoimmune diseases. Our study suggests that TL1A is a possible target for the treatment of autoimmune diseases.
CURRENT MODELS FOR THE STRUCTURE OF BIOLOGICAL MEMBRANES

I. Introduction II. Problems in the characterization of biological membranes A. Structural characteristics B. Functional characteristics III. The models A. The Danielli or bilayer model 1. Evidence and arguments supporting the Danielli model 2. Evidence and arguments against the Danielli model 3. General evaluation of the Danielli model B. The subunit model 1. Possible categories of subunits a. Subunits of structure b. Subunits of function c. Subunits of assembly 2. Identification of subunits a. Morphological techniques b. Membrane fractionation techniques and reaggregation of membranes 3. Variations of the subunit model 4. Membranes for which a subunit structure has been postulated a. The inner membrane of mitochondria b. Halobacterium membranes c. Mycoplasma membranes d. Cell junction membranes e. Photosynthetic membranes f. Photoreceptor membranes of the eye g. Sarcoplasmic reticulum 5. General evaluation of the subunit model IV. Conclusions I. INTRODUCTION During the last 100 years permeability studies the exchange of water and solutes between the cell had led to the conclusion that there exists on the and its environment. The accumulated indirect surface of cells a thin membrane which controls evidence had been so compelling that the direct
Iterated Strict Dominance in General Games

We offer a definition of iterated elimination of strictly dominated strategies (IESDS) for games with (in)finite players, (non)compact strategy sets, and (dis)continuous payoff functions. IESDS is always a well-defined order independent procedure that can be used to solve Nash equilibrium in dominance-solvable games. We characterize IESDS by means of a "stability"" criterion, and offer a sufficient and necessary epistemic condition for IESDS. We show by an example that IESDS may generate spurious Nash equilibria in the class of Reny's better-reply secure games. We provide sufficient/necessary conditions under which IESDS preserves the set of Nash equilibria. " Nous donnons une definition de l'elimination iterative des strategies qui sont strictement donimees (EISSD) pour les jeux avec un nombre fini (ou infini) de joueurs , des ensembles de strategies compactes (ou non-compactes), et des fonctions de gains continues (ou non-continues). Le processus EISSD est bien defini et independant de l'ordre d'elimination. Nous donnons une caracterisation du processus EISSD en utilisant un critere de stabilite et offrons une condition epistemologique. Nous demontrons que le processus EISSD peut produire des equilibres faux dans la classe des jeux de meilleures reponses securitaires de Reny. Nous donnons des conditions necessaires et suffisantes pour que le processus EISSD conserve l'ensemble des equilibre de Nash.
Molecular characterization of field infectious bursal disease virus isolates from Nigeria

Aim: To characterize field isolates of infectious bursal disease virus (IBDV) from outbreaks in nine states in Nigeria through reverse transcription polymerase chain reaction (RT-PCR) and sequence analysis of portions of the VP2 and VP1 genes and to determine the presence or absence of reassortant viruses. Materials and Methods: A total of 377 bursa samples were collected from 201 suspected IBD outbreaks during 2009 to 2014 from nine states in Nigeria. Samples were subjected to RT-PCR using VP2 and VP1 gene specific primers, and the resulting PCR products were sequenced. Results: A total of 143 samples were positive for IBDV by RT-PCR. These assays amplified a 743 bp fragment from nt 701 to 1444 in the IBDV VP2 hypervariable region (hvVP2) of segment A and a 722 bp fragment from nt 168 to 889 in the VP1 gene of segment B. RT-PCR products were sequenced, aligned and compared with reference IBDV sequences obtained from GenBank. All but one hvVP2 sequence showed similarity to very virulent IBDV (vvIBDV) reference strains, yet only 3 of the VP1 67 VP1 sequences showed similarity to the VP1 gene of vvIBDV. Phylogenetic analysis revealed a new lineage of Nigerian reassortant IBDV strains. Conclusion: Phylogenetic analysis of partial sequences of genome segment A and B of IBDV in Nigeria confirmed the existence of vvIBDV in Nigeria. In addition, we noted the existence of reassortant IBDV strains with novel triplet amino acid motifs at positions 145, 146 and 147 in the reassorted Nigerian IBDV.
Optoelectronic implementation of a genetic algorithm

Genetic algorithms are the search and optimization methods based on the principles of natural evolution. An optoelectronic implementation is proposed in this paper to realize a genetic algorithm. Based on binary logic operations, crossover and mutation of a population of chromosomes can be carried out in parallel, which is very suitable for optical implementation. An electron trapping device is employed to serve as an optical-logic-array processor. Experimental results are presented.
Prevalence and Genetic Diversity of Giardia duodenalis and Cryptosporidium spp. among School Children in a Rural Area of the Amhara Region, North-West Ethiopia

Backgroud Giardia duodenalis and Cryptosporidium spp. are enteric protozoan causing gastrointestinal illness in humans and animals. Giardiasis and cryptosporidiosis are not formally considered as neglected tropical diseases, but belong to the group of poverty-related infectious diseases that impair the development and socio-economic potential of infected individuals in developing countries. Methods We report here the prevalence and genetic diversity of G. duodenalis and Cryptosporidium spp. in children attending rural primary schools in the Bahir Dar district of the Amhara Region, Ethiopia. Stool samples were collected from 393 children and analysed by molecular methods. G. duodenalis was detected by real-time PCR, and the assemblages and sub-assemblages were determined by multilocus sequence-based genotyping of the glutamate dehydrogenase and β-giardin genes of the parasite. Detection and identification of Cryptosporidium species was carried out by sequencing of a partial fragment of the small-subunit ribosomal RNA gene. Principal Findings The PCR-based prevalences of G. duodenalis and Cryptosporidium spp. were 55.0% (216/393) and 4.6% (18/393), respectively. A total of 78 G. duodenalis isolates were successfully characterized, revealing the presence of sub-assemblages AII (10.3%), BIII (28.2%), and BIV (32.0%). Discordant typing results AII/AIII and BIII/BIV were identified in 7.7% and 15.4% of the isolates, respectively. An additional five (6.4%) isolates were assigned to assemblage B. No mixed infections of assemblages A+B were found. Extensive genetic variation at the nucleotide level was observed within assemblage B (but no within assemblage A), resulting in the identification of a large number of sub-types. Cryptosporidium diversity was demonstrated by the occurrence of C. hominis, C. parvum, and C. viatorum in the population under study. Conclusions Our data suggest an epidemiological scenario with an elevated transmission intensity of a wide range of G. duodenalis genetic variants. Importantly, the elevated degree of genetic diversity observed within assemblage B is consistent with the occurrence of intra-assemblage recombination in G. duodenalis.
A risk sensitive performance index for control problems with a view to Markov jump systems

A new concept of risk sensitivity is given which unveils a wide class of functions not detected as risk sensitive in the classical scenario. Benefiting from the broadening of this class beyond the classical real-valued convex format, the concept allows, for instance, to further inroads concerning risk sensitive optimal control problems - as did Jacobson (1973) for the so-called LEQG control problem ([12], [15]). Of particular interest are those control problems associated to linear systems with Markov jump parameters ([2],[3],[7]). Focusing the niche of the standard risk sensitive functions, we study - via a risk measure criteria - the connections between the two concepts. It turns out that both have a same risk measure whenever the original cost r.v. of interest is additive - which is the case of ([12]). Due to its richer structure, the correspondence between the cost r.v. of original interest and its risk sensitive version, as presented herein, typically does not exist as a function. Nonetheless, in a probabilistic sense, a characterization by means of a family of convex functions is made, which parallels the risk sensitive standard case.
Partitioning-based Methods for VLSI Placement

The technique of using balanced min-cut partitioning in placement was presented by Breuer in 1977 [7]. Such min-cut placers use scalable and extensible divide-and-conquer algorithmic framework and tend to produce routable placements [9]. Recent work offers extensions to block placement and large-scale mixed-size placement [15, 18, 31], and robust incremental placement [33]. Over the years partitioning-based placement has seen many revisions and enhancements, but the underlying framework (illustrated in Figure 1) remains much the same. Top-down partitioningbased placement algorithms seek to decompose a given placement instance into smaller instances by sub-dividing the placement region, assigning modules to subregions and cutting the netlist hypergraph [7,19]. The top-down placement process can be viewed as a sequence of passes where each pass examines all bins and divides some of them into smaller bins. Most commonly the division step is accomplished with balanced min-cut partitioning that minimizes the number of signal nets connecting modules in multiple regions [7]. These techniques leverage well-understood and scalable algorithms for hypergraph partitioning and typically lead to routable placements [9]. This chapter is organized as follows: Section 2 introduces the basic framework for min-cut partitioning-based placement. Next, Section 3 presents recent enhancements to min-cut placement. Section 4 describes adapting partitioning based methods to mixed-size placement and Section 5 outlines recent techniques that give min-cut placement an edge over other placement algorithms. Lastly, Section 6 discusses the workings of state-of-the-art min-cut placers such as Dragon [38,39, 43], FengShui [4, 27], NTUPlace2 [22] and Capo [30–35] and illustrates how they differ from the basic min-cut framework and each other.
West Nile Virus State of the Art Report of MALWEST Project

During the last three years Greece is experiencing the emergence of West Nile virus (WNV) epidemics. Within this framework, an integrated surveillance and control programme (MALWEST project) with thirteen associate partners was launched aiming to investigate the disease and suggest appropriate interventions. One out of seven work packages of the project is dedicated to the State of the Art report for WNV. Three expert working groups on humans, animals and mosquitoes were established. Medical databases (PubMed, Scopus) were searched together with websites: e.g., WHO, CDC, ECDC. In total, 1,092 relevant articles were initially identified and 258 of them were finally included as references regarding the current knowledge about WNV, along with 36 additional sources (conference papers, reports, book chapters). The review is divided in three sections according to the fields of interest: (1) WNV in humans (epidemiology, molecular characteristics, transmission, diagnosis, treatment, prevention, surveillance); (2) WNV in animals (epidemiological and transmission characteristics concerning birds, horses, reptiles and other animal species) and (3) WNV in mosquitoes (control, surveillance). Finally, some examples of integrated surveillance programmes are presented. The introduction and establishment of the disease in Greece and other European countries further emphasizes the need for thorough research and broadening of our knowledge on this viral pathogen.
CFAR detection for the complex approximated message passing reconstructed SAR image

Complex approximated message passing (CAMP) is an iterative recovery algorithm for L1 regularization reconstruction which can achieve sparse and non-sparse estimations of original signal simultaneously. This paper demonstrates a CAMP-based synthetic aperture radar (SAR) image regularization reconstruction method along with a constant false alarm rate (CFAR) detection via the output non-sparse image of CAMP iterative algorithm. Compared with iterative thresholding algorithm (ITA) and orthogonal matching pursuit (OMP), the conventional L1 regularization reconstruction techniques, it not only can improve SAR image performance, but also its non-sparse estimation retains a similar background statistical distribution as conventional matched filtering (MF)-based techniques, which can be used for CFAR detection efficiently. Simulated and experimental results validate the effectiveness of the designed CFAR detector for the CAMP reconstructed SAR image.
Architectural design recovery using data mining techniques

The paper presents a technique for recovering the high level design of legacy software systems according to user defined architectural plans. Architectural plans are represented using a description language and specify system components and their interfaces. Such descriptions are viewed as queries that are applied on a large database which stores information extracted from the source code of the subject legacy system. Data mining techniques and a modified branch and bound search algorithm are used to control the matching process, by which the query is satisfied and query variables are instantiated. The matching process allows the alternative results to be ranked according to data mining associations and clustering techniques and, finally, be presented to the user.
Semi-automatic registration of retinal images based on line matching approach

Accurate retinal image registration is essential to track the evolution of eye-related diseases. We propose a semiautomatic method based on features relying upon retinal graphs for temporal registration of retinal images. The features represent straight lines connecting vascular landmarks on the retina vascular tree: bifurcations, branchings, crossings, end points. In the built retinal graph, one straight line between two vascular landmarks indicates that they are connected by a vascular segment in the original retinal image. The locations of the landmarks are manually extracted to avoid the information loss due to errors in a retinal vessels segmentation algorithms. A straight line model is designed to compute a similarity measure to quantify the line matching between images. From the set of matching lines, corresponding points are extracted and a global transformation is computed. The performance of the registration method is evaluated in the absence of ground truth using the cumulative inverse consistency error (CICE).