Miracle-dz/UniFAR-FTUs huggingface dataset:
Implementation and evaluation of statistical parametric speech synthesis methods for the Persian language

Scattered and little research in the field of Persian speech synthesis systems has been performed during the last ten years. Comprehensive framework that properly implements and adapts statistical speech synthesis methods for Persian has not been conducted yet. In this paper, recent statistical parametric speech synthesis methods including CLUSTERGEN, traditional HMM-based speech synthesis and its STRAIGHT version, are implemented and adapted for Persian language. CCR test is carried out to compare these methods with each other and with unit selection method. Listeners Score samples based on CMOS. The methods were ranked by averaging the CCR scores. The results show that STRAIGHT-based system produces the best quality. Traditional HMM-based and unit selection are second and third in quality ranking. These approximately produce the same quality. Finally CLUSTERGEN produces the worst quality among these four systems.
Production of recombinant DTctGMCSF fusion toxin in a baculovirus expression vector system for biotherapy of GMCSF-receptor positive hematologic malignancies.

The fusion toxin DTctGMCSF has been constructed by genetically replacing the native receptor-binding domain of diphtheria toxin (DT) with human granulocyte-macrophage colony stimulating factor (GMCSF). This recombinant fusion toxin preserves the catalytic (c) and membrane translocation (t) domains of DT and includes a sterically neutral peptide linker separating the toxin and growth factor domains. Previous work using DTctGMCSF produced in Escherichia coli has shown that this chimeric toxin is selectively cytotoxic to GMCSF receptor (R)-positive acute myeloid leukemia (AML) cells both in vitro and in vivo. Its clinical development has been hampered due to very low expression levels, requirements for solubilization with guanidine hydrochloride and subsequent refolding, and concerns about bacterial endotoxin contamination. These difficulties prompted us to investigate the utility of a baculovirus/insect cell expression system for the production of DTctGMCSF. Here, we report that a soluble form of DTctGMCSF can be produced in the baculovirus expression vector system (BEVS) and purified to homogeneity by column chromatography. The BEVS-derived DTctGMCSF fusion toxin caused apoptotic death in GMCSF-R-positive human AML cells at nanomolar concentrations. In contrast to the 100 microg/L yields of purified DTctGMCSF obtained from E. coli, the BEVS allows us to routinely generate 8-10 mg/L of purified DTctGMCSF. This increased capacity provided by the BEVS for the production of DTctGMCSF makes it now possible to obtain sufficient quantities to carry out preclinical and clinical trials. To our knowledge, this is the first report of the successful utilization of the BEVS for producing a therapeutic fusion toxin.
Vehicle logo recognition by weighted multi-class support vector machine ensembles based on sharpness histogram features

Classical methods recognise vehicle logos with image feature matching approaches. Different from these methods, this study proposes a novel algorithm to recognise the vehicle logos in real time by constructing the weighted multi-class support vector machine (SVM) ensemble model to classify the vehicle logos based on sharpness histogram features. To evaluate the performance of the proposed algorithm, extensive experiments have been performed. Experimental results indicate that the sharpness histogram features proposed by the authors has better distinguishability than colour histogram features. Moreover, they show that the proposed algorithm has the best average recognition performance, and its performance is the most robust. Conveniently, the proposed algorithm can avoid the burden of choosing the appropriate kernel function and parameters comparing with multi-class SVM model.
Population history in social spiders repeated: colony structure and lineage evolution in Stegodyphus mimosarum (Eresidae)

Social cooperative spiders from diverse taxonomic families share life‐history and demographic traits, including highly inbred colony structure. The combination of traits suggests constrained pathways for social evolution in spiders. The genus Stegodyphus has three independently evolved social species, which can be used as replicate samples to analyse population constraints in evolutionary time. We tested colony structure and population history of the social S. mimosarum from South and East Africa using mitochondrial DNA variation, and we compared the results to published data for the independently evolved social congener S. dumicola. S. mimosarum had many and diverse haplotypes (5–7% sequence divergence for ND1) but colonies were monomorphic and genealogically similar haplotypes occurred in abutting regions. These findings are nearly identical to results for S. dumicola and imply similar colony‐level processes over evolutionary time in independently evolved social species. These population dynamics are discussed with respect to the apparent lack of cladogenesis in social spiders.
Elderly people and morality in virtual worlds: A cross-cultural analysis of elderly people’s morality in interactive media

This study examines elderly people’s innate moral foundations in influencing decisions, and their subsequent enjoyment in an interactive media environment. The Moral Foundation Questionnaire was used to distinguish between the moral intuitions of elderly US and German respondents, who were believed to have divergent yet stable moral codes that would be salient in a novel virtual world. In an experimental design, participants (N=116) were confronted with a computer simulation in which they could decide to violate or uphold each of five moral intuitions. Germans and Americans differed in their moral foundations, yet for both groups higher moral salience led to a decrease in decisions to commit moral violations in a virtual world. Results for enjoyment were mixed.
Actions of Selective Estrogenic Drugs Implanted Into the Medial Amygdala on Male Rat Mating Behavior

Estrogen stimulation of the medial amygdala (MEA) of the brain promotes male rat mating behavior. However, selective stimulation of either of the estrogen receptor subtypes found in the MEA (ERα or ERβ) does not support mating behavior. We tested the hypothesis that dual stimulation of ERα and ERβ is required to activate estrogen-dependant neural circuits in the MEA responsible for mating by local treatment of MEA with a combination of selective estrogenic agonists: propyl pyrazole triol (PPT, an ERα agonist ) and diarylpropionitrile (DPN, an ERβ agonist) administered to castrated, DHT maintained male rats. Estradiol (E2) or cholesterol (Chol) MEA implants served as positive and negative controls respectively. The animals receiving a mixture of PPT and DPN into the MEA displayed higher levels of mating behavior than the Chol treated animals but lower levels of mating behavior than the E2 treated animals. INDEX WORDS: Estradiol, Estrogen receptor, Medial amygdala, Sexual behavior, Propyl pyrazole triol (PPT), Diarylpropionitrile (DPN), Methyl-piperidino-pyrazole (MPP), Mating ACTIONS OF SELECTIVE ESTROGENIC DRUGS IMPLANTED INTO THE MEDIAL AMYGDALA ON MALE RAT MATING BEHAVIOR
Feature Tracking in Time-Varying Volumetric Data through Scale Invariant Feature Transform

Recent advances in medical imaging technology enable dynamic acquisitions of objects under movement. The acquired dynamic data has shown to be useful in different application scenarios. However, the vast amount of timevarying data put a great demand on robust and efficient algorithms for extracting and interpreting the underlying information. In this paper, we present a gpu-based approach for feature tracking in time-varying volumetric data set based on the Scale Invariant Feature Transform (SIFT) algorithm. Besides, the improved performance, this enables us to robustly and efficiently track features of interest in the volumetric data over the time domain. As a result, the proposed approach can serve as a foundation for more advanced analysis on the features of interest in dynamic data sets. We demonstrate our approach using a time-varying data set for the analysis of internal motion of breathing lungs.
Ciliary neurotrophic factor suppresses Phox2a in sympathetic neurons

The cholinergic differentiation factor ciliary neurotrophic factor (CNTF) suppresses noradrenergic properties while inducing cholinergic and peptidergic properties in sympathetic neurons. In the rat, this includes suppression of the noradrenergic enzymes tyrosine hydroxylase and dopamine &bgr;-hydroxylase. Lower enzyme levels result in part from suppression of gene transcription, but the mechanisms are unknown. We found that ciliary neurotrophic factor decreased the transcriptional activator Phox2a in neuroblastoma cells and cultured sympathetic neurons, suggesting that the loss of Phox2a is part of the mechanism by which CNTF suppresses tyrosine hydroxylase and dopamine &bgr;-hydroxylase. Consistent with this model, Phox2a is suppressed in rat cholinergic sympathetic neurons where noradrenergic enzymes decrease, but is not altered in mouse cholinergic neurons where these enzymes remain high.
The passive CNV: carving out the contribution of task-related processes to expectancy

In this perspective article, I summarized certain theoretical and methodological issues concerning the investigation of the contribution of cognitive and motor processes to the electrophysiological stimulus-preceding activity. In particular, the question of whether the contingent negative variation (CNV) is a marker reflecting both cognitive expectancy and motor preparation in the S1–S2 paradigms was discussed. New evidence suggests that it is possible to isolate an automatic temporal expectancy-related cognitive mechanism relying on a passive CNV after ruling out the contribution of task-related processes, including motor and decisional processes, to it. This can be achieved by simply manipulating the trial temporal structure according to a probabilistic, oddball distribution. The scientific value of this finding is framed within a historical perspective in the attempt to bridge together the classic literature linking the CNV to stimulus preparation and the more recently published literature linking the CNV to temporal processing.
Open Tubular Lab-On-Column/Mass Spectrometry for Targeted Proteomics of Nanogram Sample Amounts

A novel open tubular nanoproteomic platform featuring accelerated on-line protein digestion and high-resolution nano liquid chromatography mass spectrometry (LC-MS) has been developed. The platform features very narrow open tubular columns, and is hence particularly suited for limited sample amounts. For enzymatic digestion of proteins, samples are passed through a 20 µm inner diameter (ID) trypsin + endoproteinase Lys-C immobilized open tubular enzyme reactor (OTER). Resulting peptides are subsequently trapped on a monolithic pre-column and transferred on-line to a 10 µm ID porous layer open tubular (PLOT) liquid chromatography LC separation column. Wnt/ß-catenein signaling pathway (Wnt-pathway) proteins of potentially diagnostic value were digested+detected in targeted-MS/MS mode in small cell samples and tumor tissues within 120 minutes. For example, a potential biomarker Axin1 was identifiable in just 10 ng of sample (protein extract of ∼1,000 HCT15 colon cancer cells). In comprehensive mode, the current OTER-PLOT set-up could be used to identify approximately 1500 proteins in HCT15 cells using a relatively short digestion+detection cycle (240 minutes), outperforming previously reported on-line digestion/separation systems. The platform is fully automated utilizing common commercial instrumentation and parts, while the reactor and columns are simple to produce and have low carry-over. These initial results point to automated solutions for fast and very sensitive MS based proteomics, especially for samples of limited size.
Tag-based top-N recommendation using a pairwise topic model

Tagging systems enable users to organise their online entities with distinct tags. Exploiting these user generated content and underlying bilingual information have become more and more important in recommendation system. Probabilistic topic model has been widely used in document management and social network mining. In this paper, we propose a new method to do tag-based recommendation with topic model. Some existing methods are based on mining association rules and similarity measures. In these cases, tags serve as the essential intermediates for statistical computation, but they have the drawbacks that results are sensitive to parameter setup. Even though they are popular in some real application situations, they are simply lack of scalability as the computational procedure differs over distinguished platforms. It's natural to take tags as words, from which topics can be effectively extracted by using topic model. Under the assumption of the generating process in topic model, user's topic distribution parameter implies his or her topic preference. Recommendation results are obtained according to the final probability calculated by summing over topics. Our experiments show that the proposed model is effective to do both tags and items recommendation on two sparse datasets.
Identification of Peptidoglycan-Associated Proteins as Vaccine Candidates for Enterococcal Infections

Infections by opportunistic bacteria have significant contributions to morbidity and mortality of hospitalized patients and also lead to high expenses in healthcare. In this setting, one of the major clinical problems is caused by Gram-positive bacteria such as enterococci and staphylococci. In this study we extract, purify, identify and characterize immunogenic surface-exposed proteins present in the vancomycin resistant enterococci (VRE) strain Enterococcus faecium E155 using three different extraction methods: trypsin shaving, biotinylation and elution at high pH. Proteomic profiling was carried out by gel-free and gel-nanoLC-MS/MS analyses. The total proteins found with each method were 390 by the trypsin shaving, 329 by the elution at high pH, and 45 using biotinylation. An exclusively extracytoplasmic localization was predicted in 39 (10%) by trypsin shaving, in 47 (15%) by elution at high pH, and 27 (63%) by biotinylation. Comparison between the three extraction methods by Venn diagram and subcellular localization predictors (CELLO v.2.5 and Gpos-mPLoc) allowed us to identify six proteins that are most likely surface-exposed: the SCP-like extracellular protein, a low affinity penicillin-binding protein 5 (PBP5), a basic membrane lipoprotein, a peptidoglycan-binding protein LysM (LysM), a D-alanyl-D-alanine carboxypeptidase (DdcP) and the peptidyl-prolyl cis-trans isomerase (PpiC). Due to their close relationship with the peptidoglycan, we chose PBP5, LysM, DdcP and PpiC to test their potential as vaccine candidates. These putative surface-exposed proteins were overexpressed in Escherichia coli and purified. Rabbit polyclonal antibodies raised against the purified proteins were able to induce specific opsonic antibodies that mediated killing of the homologous strain E. faecium E155 as well as clinical strains E. faecium E1162, Enterococcus faecalis 12030, type 2 and type 5. Passive immunization with rabbit antibodies raised against these proteins reduced significantly the colony counts of E. faecium E155 in mice, indicating the effectiveness of these surface-related proteins as promising vaccine candidates to target different enterococcal pathogens.
Model reduction of consensus networks by graph simplification

In this paper we consider the problem of approximating a consensus network by a less complex network, by removing cycles from the original network graph. The consensus network consists of agents that exchange relative state information with their neighbors in the network. We assume the agents have single-integrator dynamics and the network graph is undirected. The network used to approximate the original system has the same nodes as the original graph, but its edge set is a strict subset of the original edge set. We obtain a priori upper bounds on the absolute approximation error, depending on the length of the removed cycles, the algebraic connectivity of a chosen spanning tree of the network graph, and the largest eigenvalue of the Laplacian matrix of that spanning tree.
Opinion Analysis based on Lexical Clues and their Expansion

The challenge of an automatic opinion analysis has been the focus of attention in recent years in many domains such as online product review. Especially, in online news articles opinion analysis has good prospects, since newspaper is the most powerful media to disseminate people’s opinions. We introduce a lexical information based approach to this task by exploiting lexical information, based on the quantitative analysis of opinions in the news articles. The method comprises semi-supervised subjectivity classification, gloss based sentiment classification, and rule based opinion holder finder. The method we present is remarkable since numbers of lexical clues we discovered were effective to this task. The experimental results show that our system achieves 45% of performance to extract opinionated sentences and 35% of performance to identify opinion holders.
Impact of reduced heart rate variability on risk for cardiac events. The Framingham Heart Study.

BACKGROUND Although heart rate variability (HRV) is altered in a variety of pathological conditions, the association of reduced HRV with risk for new cardiac events has not been studied in a large community-based population. METHODS AND RESULTS The first 2 hours of ambulatory ECG recordings obtained on subjects of the Framingham Heart Study who were free of clinically apparent coronary heart disease or congestive heart failure were reprocessed to assess HRV. Five frequency-domain measures and three time-domain measures were obtained. The associations between HRV measures and the incidence of new cardiac events (angina pectroris, myocardial infarction, coronary heart disease death, or congestive heart failure) were assessed with proportional hazards regression analyses. There were 2501 eligible subjects with a mean age of 53 years. During a mean follow-up of 3.5 years, cardiac events occurred in 58 subjects. After adjustment for age, sex, cigarette smoking, diabetes, left ventricular hypertrophy, and other relevant risk factors, all HRV measures except the ratio of low-frequency to high-frequency power were significantly associated with risk for a cardiac event (P = .0016 to .0496). A one-standard deviation decrement in the standard deviation of total normal RR intervals (natural log transformed) was associated with a hazard ratio of 1.47 for new cardiac events (95% confidence interval of 1.16 to 1.86). CONCLUSIONS The estimation of HRV by ambulatory monitoring offers prognostic information beyond that provided by the evaluation of traditional cardiovascular disease risk factors.
Synthesis for multi-robot controllers with interleaved motion

This paper addresses the problem of designing control schemes for teams of robots engaged in complex highlevel tasks. It presents a method for automatically creating hybrid controllers that ensure that a team of possibly heterogeneous robots satisfies a user-defined high-level task. The proposed approach relaxes constraints on the simultaneous and interleaved motion of the robots, while maintaining constraints on their relative location to guarantee collision-avoidance and prevent deadlock. The approach is demonstrated in the context of a team of robots engaged in sorting objects for recycling.
Canonical Filtrations and Local Tabularity

The paper deals with a special type of filtration in modal logic called “canonical”. This filtration has been known since the 1970s, but was used only occasionally. Applying it in a systematic way allows us to prove new results on finite model property (and in some cases — local tabularity) for different polymodal logics. In particular, we consider products of logics of finite depth with S5 and DL, and also temporal logics of finite depth.
Multi-pitch estimation via fast group sparse learning

In this work, we consider the problem of multi-pitch estimation using sparse heuristics and convex modeling. In general, this is a difficult non-linear optimization problem, as the frequencies belonging to one pitch often overlap the frequencies belonging to other pitches, thereby causing ambiguity between pitches with similar frequency content. The problem is further complicated by the fact that the number of pitches is typically not known. In this work, we propose a sparse modeling framework using a generalized chroma representation in order to remove redundancy and lower the dictionary's block-coherency. The found chroma estimates are then used to solve a small convex problem, whereby spectral smoothness is enforced, resulting in the corresponding pitch estimates. Compared with previously published sparse approaches, the resulting algorithm reduces the computational complexity of each iteration, as well as speeding up the overall convergence.
Detecting Local Haplotype Sharing and Haplotype Association

A novel haplotype association method is presented, and its power is demonstrated. Relying on a statistical model for linkage disequilibrium (LD), the method first infers ancestral haplotypes and their loadings at each marker for each individual. The loadings are then used to quantify local haplotype sharing between individuals at each marker. A statistical model was developed to link the local haplotype sharing and phenotypes to test for association. We devised a novel method to fit the LD model, reducing the complexity from putatively quadratic to linear (in the number of ancestral haplotypes). Therefore, the LD model can be fitted to all study samples simultaneously, and, consequently, our method is applicable to big data sets. Compared to existing haplotype association methods, our method integrated out phase uncertainty, avoided arbitrariness in specifying haplotypes, and had the same number of tests as the single-SNP analysis. We applied our method to data from the Wellcome Trust Case Control Consortium and discovered eight novel associations between seven gene regions and five disease phenotypes. Among these, GRIK4, which encodes a protein that belongs to the glutamate-gated ionic channel family, is strongly associated with both coronary artery disease and rheumatoid arthritis. A software package implementing methods described in this article is freely available at http://www.haplotype. org.
Simultaneous Determination of Multiple microRNA Levels Utilizing Biotinylated Dideoxynucleotides and Mass Spectrometry

MicroRNAs (miRNAs) are important regulators of gene translation and have been suggested as potent biomarkers in various disease states. In this study, we established an efficient method for simultaneous determination of multiple miRNA levels, employing the previously developed SPC-SBE (solid phase capture-single base extension) approach and MALDI-TOF mass spectrometry (MS). In this approach, we first perform reverse transcription of miRNAs extracted using stem-loop primers. Then the cDNA is co-amplified with competitors, synthetic oligonucleotides whose sequences precisely match cDNA except for one base, and the amplicons serve as templates for a multiplexed SBE reaction. Extension products are isolated using SPC and quantitatively analyzed with MALDI-TOF MS to determine multiple miRNA levels. Here we demonstrated concurrent analysis of four miRNA levels utilizing the approach. Furthermore, we showed the presented method significantly facilitated MS analysis of peak area ratio owing to SPC. The SPC process allowed effective removal of irrelevant reaction components prior to MS and promoted MS sample purification. Data obtained in this study was verified with RT-qPCR and agreement was shown on one order of magnitude scale, suggesting the SPC-SBE and MS approach has strong potential as a viable tool for high throughput miRNA analysis.