Miracle-dz/UniFAR-FTUs huggingface dataset:
Structural Chemistry of the Histone Methyltransferases Cofactor Binding Site

Histone methyltransferases (HMTs) transfer a methyl group from the cofactor S-adenosyl methionine to lysine or arginine residues on histone tails, thereby regulating chromatin compaction, binding of effector proteins and gene transcription. HMTs constitute an emerging target class in diverse disease areas, and selective chemical probes are necessary for target validation. Potent and selective competitors of the substrate peptide have been reported, but the chemical tractability of the cofactor binding site is poorly understood. Here, a systematic analysis of this site across structures of 14 human HMTs or close homologues was conducted. The druggability, interaction hotspots, and diversity of the cofactor binding pocket were dissected. This analysis strongly suggests that this site is chemically tractable. General principles underlying tight binding and specific guidelines to achieve selective inhibition are presented.
Roadside Magnetic Sensor System for Vehicle Detection in Urban Environments

Intelligent Transportation Systems (ITS) are widely researched to improve the traffic situation. In ITS, vehicle detection system plays a significant role. At present, vehicle detection is often conducted by inductive loops, which are very expensive and inconvenient to install and maintain. Video camera is another frequently used detector, but it needs high computing power. In order to solve these problems, this paper focuses on the development of a roadside magnetic sensor system for vehicle detection. The device is installed at the side of the road and measures traffic in the adjacent lane (the closest lane to the sensor node). The data are transmitted by the IEEE 802.15. 4 communication protocol. A novel adapted threshold state machine algorithm is proposed to detect vehicles. Since false judgments created by large vehicles passing in the nonadjacent lane (the lane next to the closest lane to the sensor node) are frequent in urban environments, a novel feature extracted by fusion of three magnetic sensor signals are proposed to reduce this error. The developed magnetic sensor system is wireless, compact, and cost-effective. The experimental results show that the proposed system achieves high accuracy and is viable in urban environments.
Comprehensive genomic transcriptomic tumor-normal gene panel analysis for enhanced precision in patients with lung cancer

A CMS approved test for lung cancer is based on tumor-only analysis of a targeted 35 gene panel, specifically excluding the use of the patient’s normal germline tissue. However, this tumor-only approach increases the risk of mistakenly identifying germline single nucleotide polymorphisms (SNPs) as somatically-derived cancer driver mutations (false positives). 621 patients with 30 different cancer types, including lung cancer, were studied to compare the precision of tumor somatic variant calling in 35 genes using tumor-only DNA sequencing versus tumor-normal DNA plus RNA sequencing. When sequencing of lung cancer was performed using tumor genomes alone without normal germline controls, 94% of variants identified were SNPs and thus false positives. Filtering for common SNPs still resulted in as high as 48% false positive variant calling. With tumor-only sequencing, 29% of lung cancer patients had a false positive variant call in at least one of twelve genes with directly targetable drugs. RNA analysis showed 18% of true somatic variants were not expressed. Thus, sequencing and analysis of both normal germline and tumor genomes is necessary for accurate identification of molecular targets. Treatment decisions based on tumor-only analysis may result in the administration of ineffective therapies while also increasing the risk of negative drug-related side effects.
Improving Neural Fine-Grained Entity Typing With Knowledge Attention

Fine-grained entity typing aims to identify the semantic type of an entity in a particular plain text. It is an important task which can be helpful for a lot of natural language processing (NLP) applications. Most existing methods typically extract features separately from the entity mention and context words for type classification. These methods inevitably fail to model complex correlations between entity mentions and context words. They also neglect rich background information about these entities in knowledge bases (KBs). To address these issues, we take information from KBs into consideration to bridge entity mentions and their context together, and thereby propose Knowledge-Attention Neural Fine-Grained Entity Typing. Experimental results and case studies on real-world datasets demonstrate that our model significantly outperforms other state-of-the-art methods, revealing the effectiveness of incorporating KB information for entity typing. Code and data for this paper can be found at https://github.com/thunlp/KNET.
Co-Stimulation-Impaired Bone Marrow-Derived Dendritic Cells Prevent Dextran Sodium Sulfate-Induced Colitis in Mice

Dendritic cells (DC) are important in the onset and severity of inflammatory bowel disease (IBD). Tolerogenic DC induce T-cells to become therapeutic Foxp3+ regulatory T-cells (Tregs). We therefore asked if experimental IBD could be prevented by administration of bone marrow-derived DC generated under conventional GM-CSF/IL-4 conditions but in the presence of a mixture of antisense DNA oligonucleotides targeting the primary transcripts of CD40, CD80, and CD86. These cell products (which we call AS-ODN BM-DC) have demonstrated tolerogenic activity in preventing type 1 diabetes and preserving beta cell mass in new-onset type 1 diabetes in the NOD mouse strain, in earlier studies. In addition to measuring efficacy in prevention of experimental IBD, we also sought to identify possible mechanism(s) of action. Weight, behavior, stool frequency, and character were observed daily for 7–10 days in experimental colitis in mice exposed to dextran sodium sulfate (DSS) following injection of the AS-ODN BM-DC. After euthanasia, the colons were processed for histology while spleen and mesenteric lymph nodes (MLNs) were made into single cells to measure Foxp3+ Treg as well as IL-10+ regulatory B-cell (Breg) population frequency by flow cytometry. AS-ODN BM-DC prevented DSS-induced colitis development. Recipients of these cells exhibited significant increases in Foxp3+ Treg and IL-10+ Breg in MLN and spleen. Histological examination of colon sections of colitis-free mice remained largely architecturally physiologic and mostly free of leukocyte infiltration when compared with DSS-treated animals. Although DSS colitis is mainly an innate immunity-driven condition, our study adds to the growing body of evidence showing that Foxp3+ Treg and IL-10 Bregs can suppress a mainly innate-driven inflammation. The already-established safety of human DC generated from monocytic progenitors in the presence of the mixture of antisense DNA targeting the primary transcripts of CD40, CD80, and CD86 in humans offers the potential to adapt them for clinical IBD therapy.
ProTox-II: a webserver for the prediction of toxicity of chemicals

Abstract Advancement in the field of computational research has made it possible for the in silico methods to offer significant benefits to both regulatory needs and requirements for risk assessments, and pharmaceutical industry to assess the safety profile of a chemical. Here, we present ProTox-II that incorporates molecular similarity, pharmacophores, fragment propensities and machine-learning models for the prediction of various toxicity endpoints; such as acute toxicity, hepatotoxicity, cytotoxicity, carcinogenicity, mutagenicity, immunotoxicity, adverse outcomes pathways (Tox21) and toxicity targets. The predictive models are built on data from both in vitro assays (e.g. Tox21 assays, Ames bacterial mutation assays, hepG2 cytotoxicity assays, Immunotoxicity assays) and in vivo cases (e.g. carcinogenicity, hepatotoxicity). The models have been validated on independent external sets and have shown strong performance. ProTox-II provides a freely available webserver for in silico toxicity prediction for toxicologists, regulatory agencies, computational and medicinal chemists, and all users without login at http://tox.charite. de/protox_II. The webserver takes a two-dimensional chemical structure as an input and reports the possible toxicity profile of the chemical for 33 models with confidence scores, and an overall toxicity radar chart along with three most similar compounds with known acute toxicity.
Möbius 2.3: An extensible tool for dependability, security, and performance evaluation of large and complex system models

Möbius 2.3 is an extensible dependability, security, and performance modeling environment for large-scale discrete-event systems. It provides multiple model formalisms and solution techniques, facilitating the representation of each part of a system in the formalism that is most appropriate for it, and the application of the solution method or methods best-suited to estimating the system's behavior. Since its initial release in 2001, many advances have been made in Möbius's design and implementation that have strengthened its place in the modeling and analysis community. With almost a decade of widespread academic and industrial use, Möbius has proven itself to be useful in a wide variety of modeling situations. This paper documents the current feature set of Möbius 2.3, emphasizing recent significant enhancements.
Effect of Permeation Enhancers on the Release and Permeation Kinetics of Oxytetracycline Hydochloride Organogel Formulations

Oxytetracycline is an antibacterial drug used in the treatment of acne vulgaris and dermatitis. Its oral bioavailability is intermediate i.e., 60% and it is rapidly excreted through renal route. This drug has many side effects such as epigastric pain, nausea, vomiting, diarrhea, hypersensitivity, and tooth discoloration when taken orally. To overcome the side effects and to increase the bioavailability of Oxytetracycline, topical formulations were prepared. Organogels were prepared using sorbitan monostearate as gelling agent and isopropyl myristate as vehicle with different permeation enhancers. The prepared formulations were evaluated for drug content, viscosity, extrudability, homogeneity, skin irritation test, in vitro drug release, and antimicrobial activity. A formulation containing eucalyptus oil with isopropyl myristate, showed better in vitro permeation and higher antimicrobial activity as compared to other formulations with different penetration enhancers. Key words : Eucalyptus oil, organogel, oxytetracycline, penetration enhancer.
Can We Predict the Surgical Margin Positivity in Patients Treated with Radical Prostatectomy? A Multicenter Cohort of Turkish Association of Uro-Oncology

correspondence deniz Bolat Md, İzmir Bozyaka Training and Research Hospital, Clinic of Urology, İzmir, Turkey Phone: +90 505 638 30 10 E-mail: drbolat@hotmail.com Received: 01.12. 2014 accepted: 06.01. 2015 Abstract of this study was presented in 10th Urooncology Congress (26-30th October 2011, Antalya). Deniz Bolat1, Saadettin Eskiçorapcı2, Erdem Karabulut3, Sümer Baltacı4, Asıf Yıldırım5, Sinan Sözen6, Ferhat Ateş7, Çağrı Akın Şekerci8, Fatih Kurtuluş9, Ayhan Dirim10, Talha Muezzioğlu11, Cavit Can12, Murat Bozlu13, Hakan Gemalmaz14, Sinan Ekici15, Haluk Özen16, Levent Turkeri17
End-to-End Speech Separation with Unfolded Iterative Phase Reconstruction

This paper proposes an end-to-end approach for single-channel speaker-independent multi-speaker speech separation, where time-frequency (T-F) masking, the short-time Fourier transform (STFT), and its inverse are represented as layers within a deep network. Previous approaches, rather than computing a loss on the reconstructed signal, used a surrogate loss based on the target STFT magnitudes. This ignores reconstruction error introduced by phase inconsistency. In our approach, the loss function is directly defined on the reconstructed signals, which are optimized for best separation. In addition, we train through unfolded iterations of a phase reconstruction algorithm, represented as a series of STFT and inverse STFT layers. While mask values are typically limited to lie between zero and one for approaches using the mixture phase for reconstruction, this limitation is less relevant if the estimated magnitudes are to be used together with phase reconstruction. We thus propose several novel activation functions for the output layer of the T-F masking, to allow mask values beyond one. On the publicly-available wsj0-2mix dataset, our approach achieves state-of-the-art 12.6 dB scale-invariant signal-to-distortion ratio (SI-SDR) and 13.1 dB SDR, revealing new possibilities for deep learning based phase reconstruction and representing a fundamental progress towards solving the notoriously-hard cocktail party problem.
Legibility as a result of geometry space: analyzing and comparing hypothetical model and existing space by space syntax

In modern and developed cities, large office buildings and factories occupy the center of city destroying the legibility of these areas. The city center of Kuala Lumpur (KLCC) was chosen as a case study because this area faces these challenges. In this study, the relationship between geometry and legibility was reviewed using two models that were created base on the literature. The two models were an existing vicinity of KLCC and a hypothetical model that analyzed by Space Syntax. The results were further analyzed using a T-test and the correlations were examined using SPSS. Enhanced integration as a result accessibility was observed. There was also a strong correlation between integration and connectivity in the hypothetical model. According to this simulation study, regular geometry can increase integration, accessibility, intelligibility and legibility in urban spaces.
An Integrated Scienceometric Information System Infrastructure for the Assessment of Scientific Impacts of Nations

The emphasis on enhancing higher education, scientific and research institutions in the member states of the Arab League is increasing. Such attention originates from the outcomes of the studies that highlight the low contribution of these states in global scientific production. The basic aim of this study is to examine the context of scientific impact of these states, examine the reasons for the decline of scientific impact of such states and propose some recommendations and an integrated information system infrastructure. [Tagelsir Mohamed Gasmelseid, Shakeel Ahmed, Al-Eknah, M.M. An Integrated Scienceometric Information System Infrastructure for the Assessment of Scientific Impacts of Nations. Life Sci J 2014;11(8):155-164]. (ISSN:1097-8135). http://www.lifesciencesite. com. 20
Purification and biochemical characterization of plantaricin UG1: a bacteriocin produced by Lactobacillus plantarum UG1 isolated from dry sausage

The bacteriocin plantericin UG1 produced by Lactobacillus (Lb.) plantarum UG1 was purified herein by three steps including ammonium sulphate precipitation, dissociation of bacteriocin activity and chromatographic separation. At pH 6.0 and 60% ammonium sulphate saturation, the precipitated pellets contained maximal plantaricin UG1 activity of about 22880 AU/ml. Some dissociating agents dissociated plantaricin UG1 activity, thereby releasing more active subunits. The bacteriocin plantaricin UG1 existed in ammonium sulphate pellets was dialysed against potassium phosphate buffer pH 6.5 and was easily purified using chromatographic separation. Purified plantaricin UG1 activity showed 54.69 fold -increase than that obtained in cell free supernatant (CFS). The purity of plantaricin UG1 was judged by SDS-PAGE which resolved a 3.7 KDa and 1.8 KDa protein bands; indicating that plantaricin UG1 is two polypeptides. Consequently it is another bacteriocin within class 11 b bacteriocins. Amino acid composition of plantaricin UG1 showed 29 to 31 amino acids. Amino acid sequence of plantaricin UG1 showed a double glycine leader and proved that it is a novel variant of plantaricins. (Sahar M. Ouda, Johan Debevere and Gamal Enan. Purification and biochemical characterization of Plantaricin UG1: a bacteriocin produced by Lactobacillus plantarum UG1 isolated from dry sausage. Life Sci J 2014;11(8):271-279). (ISSN:1097-8135). http://www.lifesciencesite. com. 37
State of the Art and Recent Research Advances in Software Defined Networking

Emerging network services and subsequent growth in the networking infrastructure have gained tremendous momentum in recent years. Application performance requiring rapid real-time network provisioning, optimized traffic management, and virtualization of shared resources has induced the conceptualization and adoption of new networking models. Software defined networking (SDN), one of the predominant and relatively new networking paradigms, seeks to simplify network management by decoupling network control logic from the underlying hardware and introduces real-time network programmability enabling innovation. The present work reviews the state of the art in software defined networking providing a historical perspective on complementary technologies in network programmability and the inherent shortcomings which paved the way for SDN. The SDN architecture is discussed along with popular protocols, platforms, and existing simulation and debugging solutions. Furthermore, a detailed analysis is presented around recent SDN development and deployment avenues ranging from mobile communications and data centers to campus networks and residential environments. The review concludes by highlighting implementation challenges and subsequent research directions being pursued in academia and industry to address issues related to application performance, control plane scalability and design, security, and interdomain connectivity in the context of SDN.
Noisy Information Signals and Endogenous Preferences for Labeled Attributes

Consumer preferences for labeled products are often assumed to be exogenous to the presence of labels. However, the label itself (and not the information on the label) can be interpreted as a noisy warning signal. We measure the impact of “contains” labels and additional information about the labeled ingredients, treating preferences for labeled characteristics as endogenous. We find that for organic-food shoppers, the “contains” label absent additional information serves as a noisy warning signal leading them to overestimate the riskiness of consuming the product. Providing additional information mitigates the large negative signaling effect of the label.
Ectoparasites cause increased bilateral asymmetry of naturally selected traits in a colonial bird

Abstract Parasitism has been shown to correlate with levels of bilateral symmetry in some organisms, with more asymmetric individuals often having more parasites. However, few studies have shown experimentally that parasitism directly causes increased asymmetry. By fumigating some cliff swallow (Petrochelidon pyrrhonota) colonies and leaving others untreated, we investigated experimentally whether ectoparasitism by the cimicid swallow bug led to higher levels of asymmetry in length of wings, outer tail feathers, and tarsus among juvenile and adult birds. Juveniles from fumigated colonies measured soon after fledging had significantly less asymmetry in wing and outer tail length than juveniles from nonfumigated colonies; asymmetry in tarsus length was unaffected by parasitism. Adults that had undergone one or more post‐juvenal molts on the wintering grounds showed no differences in asymmetry between those reared in fumigated vs. nonfumigated colonies. These results show that ectoparasitism directly leads to increased feather asymmetry in cliff swallows, probably through parasite‐induced nutritional stress. Because wing and tail asymmetry impair flight performance and reduce foraging efficiency, the increased asymmetry caused by parasites represents a fitness cost to cliff swallows. This is among the few experimental studies to show an effect of parasites on asymmetry of naturally selected characters.
Effect of Perceived Teacher's Autonomy Support on Junior Middle School Students' Academic Burnout: The Mediating Role of Basic Psychological Needs and Autonomous Motivation 121

The present study investigated the relationships between students' perceived teacher's autonomy supporting,basic psychological needs, self-determined motivation and academic burnout. Modified Learning Climate Questionnaire,Basic Need Satisfaction Scale( BNSS),Academic Self-Regulation Questionnaire( SRQ-A) and Maslach Burnout Inventory-Student Survey( MBI) were administered to 613 junior middle school students. Results showed that basic psychological needs and autonomous motivation were positively associated with perceived teacher's autonomy support,and were negatively associated with academic burnout. Structural equation analysis showed that basic psychological needs and autonomous motivation played the mediating role separately in the relation between perceived teacher's autonomy support and academic burnout. Furthermore,the basic psychological needs- autonomous motivation meditational chain also played a mediating effect in the relation between students perceived teacher's autonomy support and academic burnout. Finally,the implications for teaching are discussed.
Journal of Orthopedics and Rheumatology The Carbon Fiber Intramedullary Nail in Pathological Humeral Shaft Fractures : Two Case Reports

The Carbon Fiber Intramedullary Nail in Pathological Humeral Shaft Fractures: Two Case Reports Maniscalco Pietro1, Caforio Marco1*, Groppi Giulia1, Vallisa Daniele2, Cavanna Luigi3 1 Department of Orthopedics and Traumatology, Piacenza Hospital, Italy 2 Department of Hematology, Piacenza Hospital, Italy 3 Department of Medical Oncology, Piacenza Hospital, Italy *Corresponding author: Dr. Marco Caforio MD, Department of Orthopaedics and Traumatology – “Guglielmo da Saliceto” Hospital Piacenza – Italy, Via Taverna, 49 – 20121 Piacenza, Italy, Fax: +39 0523 303120; Tel: +39 349 4507950; Email: marco.caforio@tiscali.it Received: 08-05-2015 Accepted: 09-09-2015 Published: 09-14-2015 Copyright: © 2015 Marco Case Report
Deep Speech Denoising with Vector Space Projections

We propose an algorithm to denoise speakers from a single microphone in the presence of non-stationary and dynamic noise. Our approach is inspired by the recent success of neural network models separating speakers from other speakers and singers from instrumental accompaniment. Unlike prior art, we leverage embedding spaces produced with source-contrastive estimation, a technique derived from negative sampling techniques in natural language processing, while simultaneously obtaining a continuous inference mask. Our embedding space directly optimizes for the discrimination of speaker and noise by jointly modeling their characteristics. This space is generalizable in that it is not speaker or noise specific and is capable of denoising speech even if the model has not seen the speaker in the training set. Parameters are trained with dual objectives: one that promotes a selective bandpass filter that eliminates noise at time-frequency positions that exceed signal power, and another that proportionally splits time-frequency content between signal and noise. We compare to state of the art algorithms as well as traditional sparse non-negative matrix factorization solutions. The resulting algorithm avoids severe computational burden by providing a more intuitive and easily optimized approach, while achieving competitive accuracy.