nils-herrmann/clean_scirepeval huggingface dataset:
Cascade of Refusal What Does It Mean for the Future of Treatment as Prevention in Sub Saharan Africa?
Venue: Current HIV/AIDS Reports

Recent recommendations by the World Health Organization support treatment for all people living with HIV (PLWH) globally to be initiated at the point of testing. While there has been marked success in efforts to identify and expand treatment for PLWH throughout sub Saharan Africa, the goal of universal treatment may prove challenging to achieve. The pre ART phase of the care cascade from HIV testing to HIV treatment initiation includes several social and structural barriers. One such barrier is antiretroviral therapy (ART) treatment refusal, a phenomenon in which HIV infected individuals choose not to start treatment upon learning their ART eligibility. Our goal is to provide further understanding of why treatment eligible adults may choose to present for HIV testing but not initiate ART when indicated. In this article, we will discuss factors driving pre ART loss and present a framework for understanding the impact of decision making on early losses in the care cascade, with a focus on ART refusal.
Neural Network based Novelty Detection for Incremental Semi supervised Learning in Multi class Gesture Recognition
Venue: VISIGRAPP

The problems of infinitely long data streams and its concept drift as well as non linearly separable classes and the possible emergence of "novel classes" are topics of high relevance for gesture data streaming based automatic recognition systems. To address these problems we apply a semi supervised learning technique using a neural network in combination with an incremental update rule. Neural networks have been shown to handle non linearly separable data and the incremental update ensures that the parameters of the classifier follow the "concept drift" without the necessity of an increased training set. Since a semi supervised learning technique is sensitive to false labels, we apply an outlier detection method based on extreme value theory and confidence band intervals. The proposed algorithm uses the extreme learning machine, which is easily updated and works with multi classes. A comparison with an auto encoder neural network shows that the proposed algorithm has superior properties. Especially, the processing time is greatly reduced.
Underwater image processing method for fish localization and detection in submarine environment
Venue: J. Vis. Commun. Image Represent.

A new underwater image preprocessing method for underwater detection is proposed.This method consists of three procedures. One is image denoising, another is image segmentation via mean shift algorithm, and the other is log likelihood ratio test.Poisson Gauss mixture algorithm is proposed for noise reduction.Log Likelihood ratio test is applied for robust fish detection.Experimental results outperform the state of the art methods. Object detection is an important process in image processing, it aims to detect instances of semantic objects of a certain class in digital images and videos. Object detection has applications in many areas of computer vision such as underwater fish detection. In this paper we present a method for preprocessing and fish localization in underwater images. We are based on a Poisson Gauss theory, because it can accurately describe the noise present in a large variety of imaging systems. In the preprocessing step we denoise and restore the raw images. These images are split into regions utilizing the mean shift algorithm. For each region, statistical estimation is done independently in order to combine regions into objects. The method is tested under different underwater conditions. Experimental results show that the proposed approach outperforms state of the art methods.
Challenges of Computational Processing of Code Switching
Venue: CodeSwitch@EMNLP

This paper addresses challenges of Natural Language Processing (NLP) on non canonical multilingual data in which two or more languages are mixed. It refers to code switching which has become more popular in our daily life and therefore obtains an increasing amount of attention from the research community. We report our experience that cov ers not only core NLP tasks such as normalisation, language identification, language modelling, part of speech tagging and dependency parsing but also more downstream ones such as machine translation and automatic speech recognition. We highlight and discuss the key problems for each of the tasks with supporting examples from different language pairs and relevant previous work.
New Inflectional Lexicons and Training Corpora for Improved Morphosyntactic Annotation of Croatian and Serbian
Venue: LREC

In this paper we present newly developed inflectional lexcions and manually annotated corpora of Croatian and Serbian. We introduce hrLex and srLex two freely available inflectional lexicons of Croatian and Serbian and describe the process of building these lexicons, supported by supervised machine learning techniques for lemma and paradigm prediction. Furthermore, we introduce hr500k, a manually annotated corpus of Croatian, 500 thousand tokens in size. We showcase the three newly developed resources on the task of morphosyntactic annotation of both languages by using a recently developed CRF tagger. We achieve best results yet reported on the task for both languages, beating the HunPos baseline trained on the same datasets by a wide margin.
The FAIR Guiding Principles for scientific data management and stewardship
Venue: Scientific data

There is an urgent need to improve the infrastructure supporting the reuse of scholarly data. A diverse set of stakeholders representing academia, industry, funding agencies, and scholarly publishers have come together to design and jointly endorse a concise and measureable set of principles that we refer to as the FAIR Data Principles. The intent is that these may act as a guideline for those wishing to enhance the reusability of their data holdings. Distinct from peer initiatives that focus on the human scholar, the FAIR Principles put specific emphasis on enhancing the ability of machines to automatically find and use the data, in addition to supporting its reuse by individuals. This Comment is the first formal publication of the FAIR Principles, and includes the rationale behind them, and some exemplar implementations in the community.
A comparative study of SMILES based compound similarity functions for drug target interaction prediction
Venue: BMC Bioinformatics

BackgroundMolecular structures can be represented as strings of special characters using SMILES. Since each molecule is represented as a string, the similarity between compounds can be computed using SMILES based string similarity functions. Most previous studies on drug target interaction prediction use 2D based compound similarity kernels such as SIMCOMP. To the best of our knowledge, using SMILES based similarity functions, which are computationally more efficient than the 2D based kernels, has not been investigated for this task before.ResultsIn this study, we adapt and evaluate various SMILES based similarity methods for drug target interaction prediction. In addition, inspired by the vector space model of Information Retrieval we propose cosine similarity based SMILES kernels that make use of the Term Frequency (TF) and Term Frequency Inverse Document Frequency (TF IDF) weighting approaches. We also investigate generating composite kernels by combining our best SMILES based similarity functions with the SIMCOMP kernel. With this study, we provided a comparison of 13 different ligand similarity functions, each of which utilizes the SMILES string of molecule representation. Additionally, TF and TF IDF based cosine similarity kernels are proposed.ConclusionThe more efficient SMILES based similarity functions performed similarly to the more complex 2D based SIMCOMP kernel in terms of AUC ROC scores. The TF IDF based cosine similarity obtained a better AUC PR score than the SIMCOMP kernel on the GPCR benchmark data set. The composite kernel of TF IDF based cosine similarity and SIMCOMP achieved the best AUC PR scores for all data sets.
A State Aware Model and Architecture for the Monitoring and Enforcement of Electronic Contracts
Venue: 2016 IEEE 18th Conference on Business Informatics (CBI)

Internet, Cloud, and IoT (Internet of Things) based business relationships involve electronic interactions that are normally regulated using Service Level Agreements (SLAs) and contracts that specify the rights, obligations, and prohibitions of the entities involved in the interactions. After a contract has been negotiated and agreed, all parties will need assurances that the service interactions comply with the clauses of the agreements between the parties, and that any violations are detected, prevented, and their causes identified. Because of the dynamic nature of emerging IoT and Cloud based relationships, there is a need for automated support for the monitoring and enforcement of service agreement policies. This paper develops a novel model for representing contract clauses using business rules that is specifically designed for contract compliance checking and enforcement. We identify what events need to be generated and captured from the underlying messaging middleware, and describe key design issues for a state aware contract monitoring and enforcement service.
ESE: Efficient Speech Recognition Engine with Compressed LSTM on FPGA
Venue: ArXiv

Long Short Term Memory (LSTM) is widely used in speech recognition. In order to achieve higher prediction accuracy, machine learning scientists have built larger and larger models. Such large model is both computation intensive and memory intensive. Deploying such bulky model results in high power consumption given latency constraint and leads to high total cost of ownership (TCO) of a data center. In order to speedup the prediction and make it energy efficient, we first propose a load balance aware pruning method that can compress the LSTM model size by 20x (10x from pruning and 2x from quantization) with negligible loss of the prediction accuracy. The pruned model is friendly for parallel processing. Next, we propose scheduler that encodes and partitions the compressed model to each PE for parallelism, and schedule the complicated LSTM data flow. Finally, we design the hardware architecture, named Efficient Speech Recognition Engine (ESE) that works directly on the compressed model. Implemented on Xilinx XCKU060 FPGA running at 200MHz, ESE has a performance of 282 GOPS working directly on the compressed LSTM network, corresponding to 2.52 TOPS on the uncompressed one, and processes a full LSTM for speech recognition with a power dissipation of 41 Watts. Evaluated on the LSTM for speech recognition benchmark, ESE is 43x and 3x faster than Core i7 5930k CPU and Pascal Titan X GPU implementations. It achieves 40x and 11.5x higher energy efficiency compared with the CPU and GPU respectively.
Angle Based Multiblock Independent Component Analysis Method with a New Block Dissimilarity Statistic for Non Gaussian Process Monitoring

In recent years, the multiblock method has attracted substantial attention. Conventional multiblock methods divide an entire data set into several blocks, and the monitoring in each block is conducted separately. The multiblock method highlights local information but ignores the information among different blocks. In this paper, we propose an angle based multiblock independent component analysis (MBICA) method and create a new block dissimilarity (BD) statistic to measure the changes between blocks. Hierarchical clustering is adopted to cluster variables with small angles into a block. ICA models are then built into each block. Support vector data description (SVDD) is introduced to yield a final monitoring decision. The changes of blocks are determined by the differences between the angles of the monitored data and the benchmark data, leading to BD statistics. The proposed MBICA BD method is applied to the Tennessee Eastman process. The simulation results demonstrate the superiority of the MBICA BD method.
Fault detection of multimode non Gaussian dynamic process using dynamic Bayesian independent component analysis
Venue: Neurocomputing

Independent component analysis (ICA) has been widely used in non Gaussian multivariate process monitoring. However, it assumes only one normal operation mode and omits the dynamic characteristic of process data. In order to overcome the shortcomings of traditional ICA based fault detection method, an improved ICA method, referred to as dynamic Bayesian independent component analysis (DBICA) is proposed to monitor the multimode non Gaussian dynamic process. In this method, matrix dynamic augmentation is applied to extract dynamic information from original data. Then for analyzing multimode non Gaussian data, Bayesian inference and ICA are combined to establish a probability mixture model. The ICA model parameters are obtained by the iterative optimization algorithm and the mode of each observation is determined by Bayesian inference simultaneously. Lastly case studies on one continuous stirring tank reactor (CSTR) simulation system and the Tennessee Eastman (TE) benchmark process are used to demonstrate the effectiveness of the proposed method.
Drug eluting biodegradable ureteral stent: New approach for urothelial tumors of upper urinary tract cancer.
Venue: International journal of pharmaceutics

Upper urinary tract urothelial carcinoma (UTUC) accounts for 5 10% of urothelial carcinomas and is a disease that has not been widely studied as carcinoma of the bladder. To avoid the problems of conventional therapies, such as the need for frequent drug instillation due to poor drug retention, we developed a biodegradable ureteral stent (BUS) impregnated by supercritical fluid CO2 (scCO2) with the most commonly used anti cancer drugs, namely paclitaxel, epirubicin, doxorubicin, and gemcitabine. The release kinetics of anti cancer therapeutics from drug eluting stents was measured in artificial urine solution (AUS) The in vitro release showed a faster release in the first 72h for the four anti cancer drugs, after this time a plateau was achieved and finally the stent degraded after 9days. Regarding the amount of impregnated drugs by scCO2, gemcitabine showed the highest amount of loading (19.57mg drug/mg polymer: 2% loaded) while the lowest amount was obtained for paclitaxel (0.067mg drug/mg polymer: 0.01% loaded) A cancer cell line (T24) was exposed to graded concentrations (0.01 2000ng/ml) of each drugs for 4 and 72h to determine the sensitivities of the cells to each drug (IC50) The direct and indirect contact study of the anti cancer biodegradable ureteral stents with the T24 and HUVEC cell lines confirmed the anti tumoral effect of the BUS impregnated with the four anti cancer drugs tested, reducing around 75% of the viability of the T24 cell line after 72h and demonstrating minimal cytotoxic effect on HUVECs.
Advances in ureteral stent development
Venue: Current opinion in urology

Ureteral stents are commonly used in urology, but there is no perfect ureteral stent. This review documents developing ureteral technologies and strategies over the past 2 years. This area has some progressive advances in the foreseeable future. Recent findings Publications from 2014 and 2015 from a PubMed search with the words 'ureter' and 'stent' in the title were reviewed. Topics that affected patient symptoms from stents include selecting the proper length of stent, patient education regarding stent symptoms, and how the stent is removed. Stent extraction strings have been studied and not increased the incidence of infection or pain. There have been several publications examining antirefluxing ureteral stents that reduced vesicoureteral reflux during micturition and infection of transplanted kidneys. Other novel methods of removing a stent include new biodegradable ureteral stents and metal beads attached to the stent used in tandem with a magnetic catheter. Several new metal and mesh stents were described for use in patients with malignant ureteral obstruction. Last, new stent coatings with antimicrobial peptides have also been described.  The search continues for the perfect stent and there has been promising progress over the past 2 years.
A Randomized Controlled Comparison of Nephrostomy Drainage vs Ureteral Stent Following Percutaneous Nephrolithotomy Using the Wisconsin StoneQOL.
Venue: Journal of endourology

We compared postoperative outcomes and quality of life (QoL) between patients who received a nephrostomy tube vs a ureteral stent following percutaneous nephrolithotomy (PCNL) in a prospective, double blind, randomized manner.  Between September 2015 and March 2016, we randomized 30 patients undergoing PCNL to receive nephrostomy drainage (Group 1: 8F or 10F) or Double J ureteral stent (Group 2) at conclusion of surgery. Nephrostomy tubes were removed within 48 hours (before discharge) and ureteral stents were removed at least 2 weeks after surgery. Patients' QoL was assessed with the Wisconsin StoneQOL questionnaire preoperatively and then 7 to 10 days and 30 days following surgery. Inclusion criteria included an uncomplicated procedure, normal preoperative renal function, and clinically insignificant residual stone fragments on postoperative imaging. We calculated the preoperative and postoperative QoL score difference between the two groups. We also evaluated perioperative characteristics, inpatient analgesic requirements, length of stay (LOS) and postsurgical complications. OUTCOME Patient characteristics between Groups 1 and 2 were comparable with similar age (58.3 vs 54.7, p 0.534) gender ratio, and stone burden (276.6 mm2 vs 259 mm2, p 0.84) and composition. There was no significant difference between perioperative outcomes, including stone free rate (93.3% vs 86.7% operative times (125.7 minutes vs 115 minutes, p 0.29) estimated blood loss (103.3 mL vs 100.7 mL, p 0.9) LOS (3.2 days vs 1.9 days, p 0.1) and complications (2 in each group) Inpatient analgesic requirements were also the same (both 21.1 mg, p 1.0) Assessment of QoL using the Wisconsin StoneQOL questionnaire showed significant differences between preoperative and postoperative health related QoL in 18 of the 28 question instrument at 7 to 10 days. Patients in Group 2 had significantly worse QoL change and a multitude of negative responses on the StoneQOL assessment, not only those commonly associated with stent irritation. Eighty percent of participants in Group 2 also attributed their complaints to having a stent placed. Both groups had similar QoL status at 30 days after surgery.  Despite the literature advocating "tubeless" PCNL with ureteral stent placement at conclusion of surgery, our randomized prospective study shows that QoL is significantly worse with stent placement than with temporary nephrostomy drainage in the immediate aftermath following PCNL, using a validated QoL assessment instrument specific for nephrolithiasis.
Why do People Attend Sport Events at Mature Tourist Destinations? An Analysis of Visitors' Motivation to Attend the Windsurf World Cup on Sylt

Sport events have become a popular tool for the marketing of tourist destinations. In this regard, it has to be kept in mind that the effects events can generate for destinations largely depend on the motivation of the attendees. Building on this insight, the aim of this paper is to compare the motivational structures of two types of visitors (primary purpose event visitors and casual visitors) to the German island of Sylt during a Windsurf World Cup. This event destination combination was chosen because it represents the tendency for popular tourist resorts to use small scale sport events in their marketing efforts.  The research was conducted using an a priori segmentation of event attendees as casual visitors and primary purpose event visitors that is based on a well established theoretical background.  The results revealed that both visitor groups were mainly motivated by cheering for the surfers and indulging in vicarious achievement. Furthermore, both showed some interest in learning more about the destination. Interestingly, many other motives that had been identified in (sport) tourism research did not seem to be very relevant for the respondents.  Event marketers should heavily emphasise the opportunity to watch and closely relate to the surfers. Thus, including internationally popular athletes if they are also popular in Germany as well as local heroes in the event seems to be reasonable.
Thoracoscopic side to side esophagogastrostomy by use of linear stapler a simplified technique facilitating a minimally invasive Ivor Lewis operation
Venue: Langenbeck's Archives of Surgery

PurposeMinimally invasive esophagectomy (MIE) has been met with increased interest for the surgical treatment of esophageal cancer. One critical obstacle for the implementation of MIE has been the intrathoracic anastomosis. In this study, we describe a technique of thoracoscopic intrathoracic anastomosis using a linear stapler in prone position and present the short term outcomes of this procedure.MethodsThis prospective pilot study included 46 consecutive patients with a cancer either of the gastroesophageal junction (GEJ) or the distal esophagus who underwent either total MIE or thoracoscopic assisted esophagectomy followed by intrathoracic stapled side to side anastomosis. The short term outcomes including postoperative complications were recorded and analyzed.ResultsThis pilot study included 41 males (89 and 5 females (11 with a mean age of 65.7 years. The majority had adenocarcinoma (93 Before surgery, 4 patients (8.7 had an incomplete endoscopic submucosal resection, 5 patients (11 received chemotherapy alone, and 33 patients (71 had chemoradiotherapy. Mean operation time was 408 minutes. Postoperative complications classified as Clavien Dindo Grade IIIa or more severe occurred in 7 patients (15 of whom 4 patients (8.7 developed anastomotic leakages without any need for intensive care. Another 2 patients (4.3 required intensive care due to aspiration pneumonia and acute renal failure. No in hospital mortality was registered. Only one patient (2.2 with anastomotic leakage developed postoperative anastomotic stenosis requiring balloon dilatation.ConclusionsThe intrathoracic stapled side to side anastomosis technique seems to be feasible, safe, and easy to perform, associated with a limited postsurgical complication rate and a good functional outcome.
Management of giant cell arteritis: Recommendations of the French Study Group for Large Vessel Vasculitis (GEFA)
Venue: La Revue de medecine interne

Management of giant cell arteritis (GCA, Horton's disease) involves many uncertainties. This work was undertaken to establish French recommendations for GCA management.  Recommendations were developed by a multidisciplinary panel of 33 physicians, members of the French Study Group for Large Vessel Vasculitis (Groupe d'etude francais des arterites des gros vaisseaux [GEFA] The topics to be addressed, selected from proposals by group members, were assigned to subgroups to summarize the available literature and draft recommendations. Following an iterative consensus seeking process that yielded consensus recommendations, the degree of agreement among panel members was evaluated with a 5 point Likert scale. A recommendation was approved when 80% of the voters agreed or strongly agreed.  The 15 retained topics resulted in 31 consensus recommendations focusing on GCA nomenclature and classification, the role of temporal artery biopsy and medical imaging in the diagnosis, indications and search modalities for involvement of the aorta and its branches, the glucocorticoid regimen to prescribe, treatment of complicated GCA, indications for use of immunosuppressants or targeted biologic therapies, adjunctive treatment measures, and management of relapse and recurrence.  The recommendations, which will be updated regularly, are intended to guide and harmonize the standards of GCA management.