nils-herrmann/clean_scirepeval huggingface dataset:
Comparing exploration strategies for Q learning in random stochastic mazes
Venue: 2016 IEEE Symposium Series on Computational Intelligence (SSCI)

Balancing the ratio between exploration and exploitation is an important problem in reinforcement learning. This paper evaluates four different exploration strategies combined with Q learning using random stochastic mazes to investigate their performances. We will compare: UCB 1, softmax, greedy, and pursuit. For this purpose we adapted the UCB 1 and pursuit strategies to be used in the Q learning algorithm. The mazes consist of a single optimal goal state and two suboptimal goal states that lie closer to the starting position of the agent, which makes efficient exploration an important part of the learning agent. Furthermore, we evaluate two different kinds of reward functions, a normalized one with rewards between 0 and 1, and an unnormalized reward function that penalizes the agent for each step with a negative reward. We have performed an extensive grid search to find the best parameters for each method and used the best parameters on novel randomly generated maze problems of different sizes. The results show that softmax exploration outperforms the other strategies, although it is harder to tune its temperature parameter. The worst performing exploration strategy is greedy.
Herbalist Customer Profile in Medicinal and Aromatic Herbs Trade: A Case Study of Kahramanmaras, Turkey

This study was conducted with nine herb firms and 99 customers shopping at those herb stores. A questionnaire consisting of two separate sections was given to the herbalists and their customers, and face to face interviews were conducted. The study revealed that the top three most frequently purchased and sold herbs were Mentha x piperita, Thymbra spicata subsp. spicata, and Tilia tomentosa. Thus, the first ranking of the causes for buying and selling these herbs are digestive system disorders, respiratory system disorders, nervous system disorders, cardiovascular disorders, and dermatological disorders.
On implantable sensors for totally implantable hearing devices

Conventional hearing devices, such as cochlear implants and hearing aids, use a microphone as a sensor for capturing the external sound field. Currently, the microphone is located in an external element, which is also responsible for processing the sound signal, but its presence is the cause of problems like discomfort, impossibility of being used during physical activities and sleeping, and social stigma. These limitations have driven studies with the goal of developing totally implantable hearing devices, and the design of an implantable sensor has been of the main issues to be overcome. Different designs of implantable sensors can be found in the literature and on some commercial implantable hearing aids, including different transduction mechanisms (capacitive, piezoelectric, electromagnetic, etc. configurations (microphones, accelerometers, force sensor, etc. and locations (subcutaneous or located in the middle ear) In this work, a detail review of such designs is presented and a general classifi.
Selektive katalytische Synthesen mit Kohlendioxid und Wasserstoff: Katalyse Schach an der Nahtstelle zwischen Energie und Chemie

Dieser Aufsatz diskutiert die Chancen und Herausforderungen fur die Nutzung der Kombination aus Kohlendioxid und Wasserstoff als C1 Synthon in katalytischen Reaktionen und Prozessen. Die Transformationen werden anhand des Reduktionsgrades und der Bindungsknupfung geordnet, wobei die chemische Wertschopfungskette von grosvolumigen Grundchemikalien bis hin zu komplexen Molekulen mit biologischer Wirkung abgedeckt wird. Die chemischen Transformationen erlauben zum einen die Speicherung und Nutzung von erneuerbaren Energien in stofflichen Produkten und bieten gleichzeitig Moglichkeiten fur ressourcenschonende und umweltfreundliche Herstellungsprozesse. Interdisziplinare Grundlagenforschung von Chemikern und Ingenieuren kann so zu nachhaltigen Technologien an der Schnittstelle von Energie und Chemie beitragen. Der Aufsatz ladt den Leser dazu ein, das "katalytische Schachbrett" der Nutzung von CO2 und H2 kennenzulernen und vielleicht selbst einige Partien darauf zu beginnen.
Kombinierte Eisen und Biokatalyse Eisencarbonylkomplexe als effiziente Wasserstoff Autotransferkatalysatoren fur die dynamische kinetische Racematspaltung

Ein duales Eisen/Lipase Katalysesystem wurde entwickelt und in der dynamischen kinetischen Racematspaltung von benzylischen und aliphatischen Alkoholen angewendet. Eine detaillierte Studie von Eisenkomplexen des Knolker Typs zeigte, dass der Wasserstoff Autotransfer von Alkoholen unter milden Reaktionsbedingungen stattfindet und die Kombination mit enzymatischer Racematspaltung ermoglicht.  Alkohole wurden so effizient zu chiralen Acetaten in hohen Ausbeuten und mit exzellenten Enantioselektivitaten umgesetzt.
Metallfreie Aktivierung von Wasserstoff, Kohlenstoffdioxid und Ammoniak durch das offenschalige Singulett Biradikaloid [P(m NTer)]2

Das offenschalige Singulett Biradikaloid [P(m NTer)]2 (Ter=2,6 Bis(2,4,6 trimethylphenyl)phenyl) wurde in der Aktivierung kleiner stabiler Molekule eingesetzt, wobei schnelle Reaktionen mit H2, CO2 und NH3 beobachtet wurden. Wasserstoff reagiert bei Raumtemperatur mit [P(m NTer)]2 zu [HP(m NTer)]2, wohingegen die Freisetzung von Wasserstoff bei Temperaturen oberhalb 60 degC gefunden wurde.
Proposal Scaling Distributed Machine Learning with System and Algorithm Co design

For a lot of important machine learning problems, due to the rapid growth of data and the ever increasing model complexity, which often manifests itself in the large number of model parameters, no single machine can solve them fast enough. Therefore, distributed optimization and inference is becoming more and more inevitable for solving large scale machine learning problems in both academia and industry. Obtaining an efficient distributed implementation of an algorithm, however, is far from trivial. Both intensive computational workloads and the volume of data communication demand careful design of distributed computation systems and distributed machine learning algorithms. In this thesis, we focus on the co design of distributed computing systems and distributed optimization algorithms that are specialized for large machine learning problems. We propose two distributed computing frameworks: a parameter server framework which features efficient data communication, and MXNet, a multi language library aiming to simplify the development of deep neural network algorithms. In less than two years, we have witnessed the wide adoption of the proposed systems. We believe that as we continue to develop these systems, they will enable more people to take advantage of the power of distributed computing to design efficient machine learning applications to solve large scale computational problems. Leveraging the two computing platforms, we examine a number of distributed optimization problems in machine learning. We present new methods to accelerate the training process, such as data partitioning with better locality properties, communication friendly optimization methods, and more compact statistical models. We implement the new algorithms on the two systems and test on large scale real data sets. We successfully demonstrate that careful co design of computing systems and learning algorithms can greatly accelerate large scale distributed machine learning.
Large scale Submodular Greedy Exemplar Selection with Structured Similarity Matrices
Venue: UAI

Exemplar clustering attempts to find a subset of data points that summarizes the entire data set in the sense of minimizing the sum of distances from each point to its closest exemplar. It has many important applications in machine learning including document and video summarization, data compression, scalability of kernel methods and Gaussian processes, active learning and feature selection. A key challenge in the adoption of exemplar clustering to large scale applications has been the availability of accurate and scalable algorithms. We propose an approach that combines structured similarity matrix representations with submodular greedy maximization that can dramatically increase the scalability of exemplar clustering and still enjoys good approximation guarantees. Exploiting structured similarity matrices within the context of submodular greedy algorithms is by no means trivial, as naive approaches still require computing all the entries of the matrix. We propose a randomized approach based on sampling sign patterns of columns of the similarity matrix and establish accuracy guarantees. We demonstrate significant computational speed ups while still achieving highly accurate solutions, and solve problems with up to millions of data points in around a minute or less on a single commodity computer.
Effect of a Brown Rice Based Vegan Diet and Conventional Diabetic Diet on Glycemic Control of Patients with Type 2 Diabetes: A 12 Week Randomized Clinical Trial
Venue: PloS one

Several intervention studies have suggested that vegetarian or vegan diets have clinical benefits, particularly in terms of glycemic control, in patients with type 2 diabetes (T2D) however, no randomized controlled trial has been conducted in Asians who more commonly depend on plant based foods, as compared to Western populations. Here, we aimed to compare the effect of a vegan diet and conventional diabetic diet on glycemic control among Korean individuals.  Participants diagnosed with T2D were randomly assigned to follow either a vegan diet (excluding animal based food including fish; n 46) or a conventional diet recommended by the Korean Diabetes Association 2011 (n 47) for 12 weeks. HbA1c levels were measured at weeks 0, 4, and 12, and the primary study endpoint was the change in HbA1c levels over 12 weeks.  The mean HbA1c levels at weeks 0, 4, and 12 were 7.7% 7.2% and 7.1% in the vegan group, and 7.4% 7.2% and 7.2% in the conventional group, respectively. Although both groups showed significant reductions in HbA1C levels, the reductions were larger in the vegan group than in the conventional group 0.5% vs. 0.2% p for interaction 0.017) When only considering participants with high compliance, the difference in HbA1c level reduction between the groups was found to be larger 0.9% vs. 0.3% The beneficial effect of vegan diets was noted even after adjusting for changes in total energy intake or waist circumference over the 12 weeks.  Both diets led to reductions in HbA1c levels; however, glycemic control was better with the vegan diet than with the conventional diet. Thus, the dietary guidelines for patients with T2D should include a vegan diet for the better management and treatment. However, further studies are needed to evaluate the long term effects of a vegan diet, and to identify potential explanations of the underlying mechanisms.
Diet, diabetes and Unani medicine: An evidence based approach

Diet is a substance, which after administration and Istihala (metabolism) becomes the part of the body or organ and provides Badl Ma Yatahallal (Replacement for wear and tear) It has been documented for over long years ago as being vital to the overall management of diseases. Today dietary advice for the persons with diabetes continues to play just as an imperative role as antioxidant, immunomodulator, hepatoprotective, nootropic activity and also for control and prevention of complications. The diet containing all the essential nutrients such as vitamin, protein, fat, carbohydrates and minerals in balanced proportion is known as balance diet which is beneficial to reduce the complication of Diabetes. Diabetes Mellitus may lead to many acute and chronic complications. Such type of chronic complications are mainly due to the result of longstanding damage to blood vessels. These complications are mainly classified as microvascular due to basement membrane thickening or macrovascular due to accelerated atherosclerosis. The major microvascular complications are diabetic retinopathy, diabetic neuropathy and diabetic nephropathy. The diabetic foot ulcer is due to the result of longstanding peripheral neuropathy, if untreated it may lead to the amputation. Good glycaemic control is challenging for the physicians and patients. Complications of diabetes are totally due to poor glycemic control. Unani Medicine is the thrust area for research to control or reduce the complications of diabetes. Various Unani drugs (mufrad and murakkab) exhibit anti diabetic activity, nootropic activity, antioxidant activity and immunomodulator activity such as Post Kachnar, Darehald, Aqerqarha, Beesh, Azaraqui, Saadkofi, Balchhar, Tukhme Khurfa, Dammul Akhwain, Kabab Chini, Filfil Daraz, Darchini, Tukhm Methi, Gurmar Booti, or Asgand etc. and some compound drugs are Qurs Gulnar, Habbe Asab, Habbe Azaraqui, Safofe Ziabetus, Qurs Tabsheer, Qurs Ziabetus and Kushta Qalai etc. Aim of this review is to explore the benefits of diets and Unani drugs on the scientific parameters to reduce the burden of diabetes associated complications.
Detection of Natural Resistance Associated Substitutions by Ion Semiconductor Technology in HCV1b Positive, Direct Acting Antiviral Agents Naive Patients
Venue: International journal of molecular sciences

Naturally occurring resistance associated substitutions (RASs) can negatively impact the response to direct acting antivirals (DAAs) agents based therapies for hepatitis C virus (HCV) infection. Herein, we set out to characterize the RASs in the HCV1b genome from serum samples of DAA naive patients in the context of the SINERGIE (South Italian Network for Rational Guidelines and International Epidemiology, 2014) project. We deep sequenced the NS3/4A protease region of the viral population using the Ion Torrent Personal Genome Machine, and patient specific majority rule consensus sequence summaries were constructed with a combination of freely available next generation sequencing data analysis software. We detected NS3/4A protease major and minor variants associated with resistance to boceprevir (V36L) telaprevir (V36L, I132V) simeprevir (V36L) and grazoprevir (V36L, V170I) Furthermore, we sequenced part of HCV NS5B polymerase using Sanger sequencing and detected a natural RAS for dasabuvir (C316N) This mutation could be important for treatment strategies in cases of previous therapy failure.
HCV1b genome evolution under selective pressure of the cyclophilin inhibitor alisporivir during the DEB 025 HCV 203 phase II clinical trial.
Venue: Infection, genetics and evolution journal of molecular epidemiology and evolutionary genetics in infectious diseases

Major advances have revolutionized the HCV antiviral treatment field, with interferon free combinations of direct acting antivirals (DAAs) resulting into success rates of >90% for all HCV genotypes. Nevertheless, viral eradication at a global level stills remains challenging, stimulating the continued search for new affordable pan genotypic drugs. To overcome selection of drug resistant variants, targeting host proteins can be an attractive mechanism of action. Alisporivir (Debio 025) is a potent pan genotypic host targeting antiviral agent, acting on cyclophilin A, which is necessary for HCV replication. The efficacy and safety of three different oral doses of alisporivir in combination with pegylated interferon a2a given over a period of four weeks, was investigated in a randomized, double blind and placebo controlled phase IIa clinical trial, in 90 treatment naive subjects infected with chronic hepatitis C, wherefrom 58 HCV1b samples were selected for genetic sequencing purposes. Sequencing results were used to study the HCV genome for amino acid changes potentially related with selective pressure and resistance to alisporivir. By comparing baseline and on treatment sequences, a large variation in proportion of amino acid changes was detected in all treatment arms. The NS5A variant D320E, which was previously identified during in vitro resistance selection and resulted in 3.6 fold reduced alisporivir susceptibility, emerged in two subjects in the alisporivir monotherapy arm. However, emergence of D320E appeared to be associated only with concurrent viral load rebound in one subject with 0.8log10IU/ml increase in HCV RNA. In general, for all datasets, low numbers of positions under positive selective pressure were observed, with no significant differences between naive and treated sequences. Additionally, incomplete sequence information for some of the 22 patients and the low number of individuals per treatment arm, is limiting the power to assess the association of alisporivir or interferon treatment with the observed amino acid changes.
[Registry of Acute Coronary Syndromes RECORD 3. Characteristics of Patients and Treatment During Initial Hospitalization]
Venue: Kardiologiia

Acute Coronary Syndrome (ACS) Registries RECORD 1 2 (2007 2001) gave valuable information on management of ACS patients in Russia. RECORD 3 was carried out in March April, 2015. Here we present characteristics of included patients (pts) and data on their treatment during initial hospitalization.  3 recruited pts with suspected ACS consecutively hospitalized in participating hospitals (n=47, 55% "invasive" during 1 month.  Number of included pts was 2370 (39% women, mean age 64.6 years) 72% were admitted to invasive hospitals, 37% had ST elevation ACS (STEACS) Median "onset of symptoms first medical contact" time was 3.4 (1.0 16.8) hours, "first medical contact hospital admission" time 1.5 (1.0 3.1) hours. Cardiac troponin was determined in 76% of pts. Coronary angiography was carried out in 70 and 46% of pts with STE and non STE ACS, respectively. (16% of all patients hospitalized in "noninvasive" cetnters were transferred for angiography to invasive ones) Primary percutaneous coronary intervention (PCI) was performed in 39% of patients with STEACS (in 65% of them with "door to pPCI" time less or equal 90 min) Thrombolytic therapy (TLT) was administered to 32% of pts (in half of them prehospitally) Overall reperfusion therapy received 68% of pts. Among non STEACS pts rate of PCI was 20% (1/3 of procedures within 2, 1/3 >2 24hours) Inhospital antiplatelet therapy (APT) included aspirin (88% clopidogrel (71% ticagrelor (14% 86% of pts received dual APT. Other medications were: unfractionated heparin (UFH, 47% [81% subcutaneously] enoxaparin (13% fondaparinux (10% angiotensin converting enzyme inhibitors/sartans (81% adrenoblockers (84% statins (87% Mortality during hospitalization (median 10 days) was 10% in STE, and 5% in non STE ACS.  Inhospital management of RECORD 3 population was characterized by relatively low rates of pPCI, reperfusion therapy in STEACS, urgent PCI in non STEACS. Preponderance of UFG including its subcutaneous use is of note. Use of other standard therapies appears satisfactory.
Using social media to challenge unwarranted clinical variation in the treatment of chronic noncancer pain: the "Brainman" story
Venue: Journal of pain research

There is a substantial clinical variation in the contemporary treatment of chronic noncancer pain reflecting different explanatory models and treatment emphasis. Hunter Integrated Pain Service and collaborators developed three key messaging videos outlining the foundations of chronic pain treatment, thus challenging unwarranted clinical variation and calling for greater therapeutic consistency. The videos were released on YouTube as a low cost public health intervention. Each video used an evidenced informed script appropriate for low literacy and a cartoonist to provide matching images. The whole person approach emphasized the role of the nervous system and active self management approaches over passively received medical treatments. The first video was launched on YouTube in August 2011 and made freely available through a Creative Commons license. Multisource feedback led to refinement of key messages using a broader advisory group. Two further videos were launched on a dedicated YouTube channel in October 2014 and circulated through varied professional and consumer networks. All videos were widely viewed on YouTube, utilized by diverse health care organizations, and independently translated into multiple languages. They were embedded in multiple health related websites. The first video "Understanding pain in less than 5 minutes" is known to have been translated into 15 languages by other health care organizations. The subsequent two videos (Brainman stops his opioids, and Brainman chooses) were translated into German and subtitled in French and Japanese. When the organization hosting the first video ceased operation in 2015 due to changes in primary health care funding, the video had received >700,000 views. Each of the three videos continues to receive ~1,500 views per month on YouTube. Release of evidence informed key messages via YouTube is a simple method of challenging clinical variation and providing education about chronic pain across the health care system and community.
Fast radiation mapping and multiple source localization using topographic contour map and incremental density estimation
Venue: 2016 IEEE International Conference on Robotics and Automation (ICRA)

Toward a global picture of the radiation exposure of an area, particularly for fast emergency response, a UAV based exploration method is proposed. Without a priori knowledge of the radiation field, it is difficult to select the region of interest (ROI) which includes all radiation sources. For the case of a single radiation source, a greedy algorithm may localize the source by finding the maximum radiation value. However, when multiple sources generate a hotspot in a cumulative manner, the hotspot position does not coincide with one of the source positions. Therefore, we propose an efficient exploration method to quickly localize the radiation sources using the following procedures: (1) ROI selection using topographic maps with specific radiation level selection methods and (2) source localization estimating the number of sources and their positions with incremental variational Bayes inference of Gaussian mixtures. Under three different conditions according to the number of sources and their positions, we have shown that the proposed model can reduce the ROI and significantly improve the estimation accuracy than existing methods.
Understanding the Mechanisms of Deep Transfer Learning for Medical Images
Venue: LABELS/DLMIA@MICCAI

The ability to automatically learn task specific feature representations has led to a huge success of deep learning methods. When large training data is scarce, such as in medical imaging problems, transfer learning has been very effective. In this paper, we systematically investigate the process of transferring a Convolutional Neural Network, trained on ImageNet images to perform image classification, to kidney detection problem in ultrasound images. We study how the detection performance depends on the extent of transfer. We show that a transferred and tuned CNN can outperform a state of the art feature engineered pipeline and a hybridization of these two techniques achieves 20 higher performance. We also investigate how the evolution of intermediate response images from our network. Finally, we compare these responses to state of the art image processing filters in order to gain greater insight into how transfer learning is able to effectively manage widely varying imaging regimes.