nils-herrmann/clean_scirepeval huggingface dataset:
Akt Regulates Axon Wrapping and Myelin Sheath Thickness in the PNS
Venue: The Journal of Neuroscience

The signaling pathways that regulate myelination in the PNS remain poorly understood. Phosphatidylinositol 4,5 bisphosphate 3 kinase 1A, activated in Schwann cells by neuregulin and the extracellular matrix, has an essential role in the early events of myelination. Akt/PKB, a key effector of phosphatidylinositol 4,5 bisphosphate 3 kinase 1A, was previously implicated in CNS, but not PNS myelination. Here we demonstrate that Akt plays a crucial role in axon ensheathment and in the regulation of myelin sheath thickness in the PNS. Pharmacological inhibition of Akt in DRG neuron Schwann cell cocultures dramatically decreased MBP and P0 levels and myelin sheath formation without affecting expression of Krox20/Egr2, a key transcriptional regulator of myelination. Conversely, expression of an activated form of Akt in purified Schwann cells increased expression of myelin proteins, but not Krox20/Egr2, and the levels of activated Rac1. Transgenic mice expressing a membrane targeted, activated form of Akt under control of the 2',3' cyclic nucleotide 3' phosphodiesterase promoter, exhibited thicker PNS and CNS myelin sheaths, and PNS myelin abnormalities, such as tomacula and myelin infoldings/outfoldings, centered around the paranodes and Schmidt Lanterman incisures. These effects were corrected by rapamycin treatment in vivo. Importantly, Akt activity in the transgenic mice did not induce myelination of nonmyelinating Schwann cells in the sympathetic trunk or Remak fibers of the dorsal roots, although, in those structures, they wrapped membranes redundantly around axons. Together, our data indicate that Akt is crucial for PNS myelination driving axonal wrapping by unmyelinated and myelinated Schwann cells and enhancing myelin protein synthesis in myelinating Schwann cells.  Although the role of the key serine/threonine kinase Akt in promoting CNS myelination has been demonstrated, its role in the PNS has not been established and remains uncertain. This work reveals that Akt controls several key steps of the PNS myelination. First, its activity promotes membrane production and axonal wrapping independent of a transcriptional effect. In myelinated axons, it also enhances myelin thickness through the mTOR pathway. Finally, sustained Akt activation in Schwann cells leads to hypermyelination/dysmyelination, mimicking some features present in neuropathies, such as hereditary neuropathy with liability to pressure palsies or demyelinating forms of Charcot Marie Tooth disease. Together, these data demonstrate the role of Akt in regulatory mechanisms underlying axonal wrapping and myelination in the PNS.
Optimal control of complex atomic quantum systems
Venue: Scientific reports

Quantum technologies will ultimately require manipulating many body quantum systems with high precision. Cold atom experiments represent a stepping stone in that direction: a high degree of control has been achieved on systems of increasing complexity. However, this control is still sub optimal. In many scenarios, achieving a fast transformation is crucial to fight against decoherence and imperfection effects. Optimal control theory is believed to be the ideal candidate to bridge the gap between early stage proof of principle demonstrations and experimental protocols suitable for practical applications. Indeed, it can engineer protocols at the quantum speed limit the fastest achievable timescale of the transformation. Here, we demonstrate such potential by computing theoretically and verifying experimentally the optimal transformations in two very different interacting systems: the coherent manipulation of motional states of an atomic Bose Einstein condensate and the crossing of a quantum phase transition in small systems of cold atoms in optical lattices. We also show that such processes are robust with respect to perturbations, including temperature and atom number fluctuations.
Longitudinal Dynamics in Connected Trains

The present work aims to describe currents developments for the connected train technique for Russian Railways. Longitudinal dynamics are a major issue for long freight train integrity and safety. Using the developed wireless measurement equipment, detailed data was obtained and a thorough analysis of longitudinal dynamics made. This provides new methods of implementation for the haulage of connected trains for a thousand kilometers of the Transsib and Baikal Amur mainlines.
A flexible parametric approach for estimating continuous time inverse probability of treatment and censoring weights.
Venue: Statistics in medicine

Marginal structural Cox models are used for quantifying marginal treatment effects on outcome event hazard function. Such models are estimated using inverse probability of treatment and censoring (IPTC) weighting, which properly accounts for the impact of time dependent confounders, avoiding conditioning on factors on the causal pathway. To estimate the IPTC weights, the treatment assignment mechanism is conventionally modeled in discrete time. While this is natural in situations where treatment information is recorded at scheduled follow up visits, in other contexts, the events specifying the treatment history can be modeled in continuous time using the tools of event history analysis. This is particularly the case for treatment procedures, such as surgeries. In this paper, we propose a novel approach for flexible parametric estimation of continuous time IPTC weights and illustrate it in assessing the relationship between metastasectomy and mortality in metastatic renal cell carcinoma patients.
Reference set for performance testing of pediatric vaccine safety signal detection methods and systems.
Venue: Vaccine

Safety signal detection in spontaneous reporting system databases and electronic healthcare records is key to detection of previously unknown adverse events following immunization. Various statistical methods for signal detection in these different datasources have been developed, however none are geared to the pediatric population and none specifically to vaccines. A reference set comprising pediatric vaccine adverse event pairs is required for reliable performance testing of statistical methods within and across data sources.  The study was conducted within the context of the Global Research in Paediatrics (GRiP) project, as part of the seventh framework programme (FP7) of the European Commission. Criteria for the selection of vaccines considered in the reference set were routine and global use in the pediatric population. Adverse events were primarily selected based on importance. Outcome based systematic literature searches were performed for all identified vaccine adverse event pairs and complemented by expert committee reports, evidence based decision support systems (e.g. Micromedex) and summaries of product characteristics. Classification into positive (PC) and negative control (NC) pairs was performed by two independent reviewers according to a pre defined algorithm and discussed for consensus in case of disagreement.  We selected 13 vaccines and 14 adverse events to be included in the reference set. From a total of 182 vaccine adverse event pairs, we classified 18 as PC, 113 as NC and 51 as unclassifiable. Most classifications (91) were based on literature review, 45 were based on expert committee reports, and for 46 vaccine adverse event pairs, an underlying pathomechanism was not plausible classifying the association as NC.  A reference set of vaccine adverse event pairs was developed. We propose its use for comparing signal detection methods and systems in the pediatric population.
Health Professionals' Knowledge, Attitudes and Practices about Pharmacovigilance in India: A Systematic Review and Meta Analysis
Venue: PloS one

Spontaneous or voluntary reporting of suspected adverse drug reactions (ADRs) is one of the vital roles of all health professionals. In India, under reporting of ADRs by health professionals is recognized as one of the leading causes of poor ADR signal detection. Therefore, reviewing the literature can provide a better understanding of the status of knowledge, attitude and practice (KAP) of Pharmacovigilance (PV) activities by health professionals.  A systematic review was performed through Pubmed, Scopus, Embase and Google Scholar scientific databases. Studies pertaining to KAP of PV and ADR reporting by Indian health professionals between January 2011 and July 2015 were included in a meta analysis.  A total of 28 studies were included in the systematic review and 18 of them were selected for meta analysis. Overall, 55.6% (95% CI 44.4 66.9; p<0.001) of the population studied were not aware of the existence of the Pharmacovigilance Programme in India (PvPI) and 31.9% (95% CI 16.3 47.4; p<0.001) thought that "all drugs available in the market are safe" Furthermore, 28.7% (95% CI 16.4 40.9; p<0.001) of them were not interested in reporting ADRs and 74.5% (95% CI 67.9 81.9; p<0.001) never reported any ADR to PV centers.  There was an enormous gap of KAP towards PV and ADR reporting, particularly PV practice in India. There is therefore an urgent need for educational awareness, simplification of the ADR reporting process, and implementation of imperative measures to practice PV among healthcare professionals. In order to understand the PV status, PvPI should procedurally assess the KAP of health professionals PV activities in India.
On the early diagnosis of Alzheimer's Disease from multimodal signals: A survey
Venue: Artif. Intell. Medicine

The number of Alzheimer's Disease (AD) patients is increasing with increased life expectancy and 115.4 million people are expected to be affected in 2050. Unfortunately, AD is commonly diagnosed too late, when irreversible damages have been caused in the patient.  An automatic, continuous and unobtrusive early AD detection method would be required to improve patients' life quality and avoid big healthcare costs. Thus, the objective of this survey is to review the multimodal signals that could be used in the development of such a system, emphasizing on the accuracy that they have shown up to date for AD detection. Some useful tools and specific issues towards this goal will also have to be reviewed.  An extensive literature review was performed following a specific search strategy, inclusion criteria, data extraction and quality assessment in the Inspec, Compendex and PubMed databases.  This work reviews the extensive list of psychological, physiological, behavioural and cognitive measurements that could be used for AD detection. The most promising measurements seem to be magnetic resonance imaging (MRI) for AD vs control (CTL) discrimination with an 98.95% accuracy, while electroencephalogram (EEG) shows the best results for mild cognitive impairment (MCI) vs CTL (97.88% and MCI vs AD distinction (94.05% Available physiological and behavioural AD datasets are listed, as well as medical imaging analysis steps and neuroimaging processing toolboxes. Some issues such as "label noise" and multi site data are discussed.  The development of an unobtrusive and transparent AD detection system should be based on a multimodal system in order to take full advantage of all kinds of symptoms, detect even the smallest changes and combine them, so as to detect AD as early as possible. Such a multimodal system might probably be based on physiological monitoring of MRI or EEG, as well as behavioural measurements like the ones proposed along the article. The mentioned AD datasets and image processing toolboxes are available for their use towards this goal. Issues like "label noise" and multi site neuroimaging incompatibilities may also have to be overcome, but methods for this purpose are already available.
Short Communication Determination of amino acid and free sugar contents in Korean traditional fermented soybean products of Doenjang and evaluation of their sensory attributes.
Venue: Pakistan journal of pharmaceutical sciences

This study quantitatively determined contents of amino acids and free sugars in soybean fermented samples (Doenjang) using amino acid autoanalyzer and HPLC, respectively. As a result, hreonine, serine, glycine, alanine and lysine categorized as total sweet amino acids and free sugars (sucrose, maltose, glucose, galactose and fructose) were found in the range of 32.7 to 117.1 and 5.85 to 23.66mg/100 g, respectively. However, average of total sugar content was noted to be 71.63mg% Three samples possessing the best sensory characteristics were selected for further study. The mean values of four sensory attributes such as sweet, sour, savory and bitter tastes of Doenjang samples were found to be 709.53, 210.25, 241.90 and 276.05. These findings confirm nutritive properties of fermented food products of Doenjang with improved quality and utilization.
Blind Super Resolution of Real Life Video Sequences
Venue: IEEE Transactions on Image Processing

Super resolution (SR) for real life video sequences is a challenging problem due to complex nature of the motion fields. In this paper, a novel blind SR method is proposed to improve the spatial resolution of video sequences, while the overall point spread function of the imaging system, motion fields, and noise statistics are unknown. To estimate the blur(s) first, a nonuniform interpolation SR method is utilized to upsample the frames, and then, the blur(s) is(are) estimated through a multiscale process. The blur estimation process is initially performed on a few emphasized edges and gradually on more edges as the iterations continue. Also for faster convergence, the blur is estimated in the filter domain rather than the pixel domain. The high resolution frames are estimated using a cost function that has the fidelity and regularization terms of type Huber Markov random field to preserve edges and fine details. The fidelity term is adaptively weighted at each iteration using a masking operation to suppress artifacts due to inaccurate motions. Very promising results are obtained for real life videos containing detailed structures, complex motions, fast moving objects, deformable regions, or severe brightness changes. The proposed method outperforms the state of the art in all performed experiments through both subjective and objective evaluations. The results are available online at http:/lyle.smu.edu/~rajand/Video_SR/
Spatio temporal Pain Recognition in CNN Based Super Resolved Facial Images
Venue: VAAM/FFER@ICPR

Automatic pain detection is a long expected solution to a prevalent medical problem of pain management. This is more relevant when the subject of pain is young children or patients with limited ability to communicate about their pain experience. Computer vision based analysis of facial pain expression provides a way of efficient pain detection. When deep machine learning methods came into the scene, automatic pain detection exhibited even better performance. In this paper, we figured out three important factors to exploit in automatic pain detection: spatial information available regarding to pain in each of the facial video frames, temporal axis information regarding to pain expression pattern in a subject video sequence, and variation of face resolution. We employed a combination of convolutional neural network and recurrent neural network to setup a deep hybrid pain detection framework that is able to exploit both spatial and temporal pain information from facial video. In order to analyze the effect of different facial resolutions, we introduce a super resolution algorithm to generate facial video frames with different resolution setups. We investigated the performance on the publicly available UNBC McMaster Shoulder Pain database. As a contribution, the paper provides novel and important information regarding to the performance of a hybrid deep learning framework for pain detection in facial images of different resolution.
Role of non coding sequence variants in cancer
Venue: Nature Reviews Genetics

Patients with cancer carry somatic sequence variants in their tumour in addition to the germline variants in their inherited genome. Although variants in protein coding regions have received the most attention, numerous studies have noted the importance of non coding variants in cancer. Moreover, the overwhelming majority of variants, both somatic and germline, occur in non coding portions of the genome. We review the current understanding of non coding variants in cancer, including the great diversity of the mutation types from single nucleotide variants to large genomic rearrangements and the wide range of mechanisms by which they affect gene expression to promote tumorigenesis, such as disrupting transcription factor binding sites or functions of non coding RNAs. We highlight specific case studies of somatic and germline variants, and discuss how non coding variants can be interpreted on a large scale through computational and experimental methods.
Subdomain and Access Pattern Privacy Trading off Confidentiality and Performance
Venue: SECRYPT

Homomorphic encryption and secure multi party computation enable computations on encrypted data. However, both techniques suffer from a large performance overhead. While advances in algorithms might reduce the overhead, we show that achieving perfect (or even computational) confidentiality is not possible without increasing the running time compared to computations on plaintext more than exponentially in some cases. In practice, however, perfect confidentiality is not always required. The paper discusses mechanisms to trade off confidentiality and performance for computing on ciphertexts. It introduces a fine grained approach to define security levels for variables called (statistical) subdomain privacy. This concept differs substantially from prior work because it treats a variable as confidential or non confidential depending on the actual value. We further propose privacy preserving methods for memory access patterns. We apply our techniques to improve performance of control flow logic (loops, if then else logic) and arithmetic operations such as multiplications. The evaluation shows that the resulting speedup can be in the order of several magnitudes depending on the privacy needs.
Interference control in cognitive radio using joint beamforming and power optimization by applying artificial bee colony
Venue: 2016 19th International Multi Topic Conference (INMIC)

We consider a cognitive radio scenario in which two networks share a licensed spectrum. Primary network is the legitimate network while cognitive radio network utilizes the underutilized frequency sub bands. For this scenario our focus is primarily on controlling the interference to the legitimate user and in addition, to minimize the interference between the secondary users while assuring quality service to secondary as well as primary user. For this one of the most favorable methods we have found is joint beamforming and power control. Main aspiration of this scheme is to minimize the transmission powers to trim down the interference plus to find out the apposite beamforming weights that help in reducing interference. We are presenting artificial bee colony algorithm to optimize this problem. We consider two scenarios. One is cooperative scenario, in which primary network cooperates with cognitive radio network to jointly optimize the power and beamforming weights and second in which there is no cooperation between the two and only cognitive radio optimizes its beam and power to control interference. While optimizing the solution for both the scenarios, we consider some constraints which are different for both scenarios.
Modern management beyond traditional managerial practices

Traditional top bottom management in modern post industrial organizations has become cumbersome and costly. Moreover, the hierarchy of managers imposes a heavy burden on business companies seeking to get rid of X inefficiency and overspending. There are new approaches to management that include self management and delegation of decision making and constitute the keystones of so called "modern management" The goal of our paper is to show how management has evolved in the ever changing business environment and allowed for the employees to become a part of the corporate governance and management of the firm.
Shared decision making for psychiatric medication management: beyond the micro social
Venue: Health expectations an international journal of public participation in health care and health policy

Mental health care has lagged behind other health care domains in developing and applying shared decision making (SDM) for treatment decisions. This is despite compatibilities with ideals of modern mental health care such as self management and recovery oriented practice, and growing policy level interest. Psychiatric medication is a mainstay of mental health treatment, but there are known problems with prescribing practices, and service users report feeling uninvolved in medication decisions and concerned about adverse effects. SDM has potential to produce better tailoring of psychiatric medication to individuals' needs.
PAL XFEL Linac RF System

The PAL XFEL hard X ray linac has a 716 m long gallery and tunnel for 10 GeV. Forty nine modulators are necessary in the hard X ray gallery for an X band linearizer, an S band RF gun, two S band deflectors and 45 S band klystrons for accelerating structures. They have been installed completely from March 15, 2015 to December 30, 2015 after completing the building construction. There are 51 modulators, 178 accelerators structures, 42 SLEDs in the hard X ray linac and the soft X ray linac. The RF conditioning of the klystrons, SLEDs and accelerating structures were stated from November 24, 2015. We describe the PAL XFEL system and the current status of the linac RF system.
Classifying Computer Science Papers

This paper addresses the problem of classifying academic papers. It is a building block in constructing an advanced scholarly search engine, such as in crawling and recommending papers in a particular area. Our goal is to identify the best classification method for scholarly data, to choose appropriate parameters, and to gauge how accurate academic papers can be classified using document content only. In addition, we also want to find out whether the neural network approach, which has been proven very successful in many other areas, can help in this particular problem. Our experiments are conducted on 160,000 papers from arXiv data set, each is already labeled as either a computer science (CS) paper or a paper in other areas. We experimented with a variety of classification methods, including Multinomial Naive Bayes on unigram and bigram models, and Logistic Regression on distributional representation obtained from sentence2vec. We find that computer science papers can be identified with high accuracy (F1 close to 0.95) The best method is the bigram model using Multinomial Naive Bayes method and point wise mutual information (PMI) as the feature selection method.
Embeddings for Word Sense Disambiguation: An Evaluation Study
Venue: ACL

Recent years have seen a dramatic growth in the popularity of word embeddings mainly owing to their ability to capture semantic information from massive amounts of textual content. As a result, many tasks in Natural Language Processing have tried to take advantage of the potential of these distributional models. In this work, we study how word embeddings can be used in Word Sense Disambiguation, one of the oldest tasks in Natural Language Processing and Artificial Intelligence. We propose different methods through which word embeddings can be leveraged in a state of the art supervised WSD system architecture, and perform a deep analysis of how different parameters affect performance. We show how a WSD system that makes use of word embeddings alone, if designed properly, can provide significant performance improvement over a state ofthe art WSD system that incorporates several standard WSD features.