nils-herrmann/clean_scirepeval huggingface dataset:
Cloud Gaming: Understanding the Support From Advanced Virtualization and Hardware
Venue: IEEE Transactions on Circuits and Systems for Video Technology
Year: 2015

Existing cloud gaming platforms have mainly focused on private nonvirtualized environments with proprietary hardware. Modern public cloud platforms heavily rely on virtualization for efficient resource sharing, the potentials of which have yet to be explored. Migrating gaming to a public cloud is nontrivial, however, particularly considering the overhead for virtualization and that the graphics processing units (GPUs) for game rendering has long been an obstacle in virtualization. This paper takes a first step toward bridging the online gaming system and the public cloud platforms. We present the design and implementation of a fully virtualized cloud gaming platform with the latest hardware support for both remote servers and local clients. We explore many critical design issues inherent in cloud gaming, including the choice of hardware or software video encoding, and the configuration and the detailed power consumption of thin client. We demonstrate that with the latest hardware and virtualization support, gaming over virtualized cloud can be made possible with careful optimization and integration of the different modules. We also highlight critical challenges toward full fledged deployment of gaming services over the public virtualized cloud.
Enhancement of thermoelectric properties of CoSb3 based skutterudites by double filling of Tl and In
Year: 2012

Thermoelectric (TE) generators can directly generate electrical power from waste heat, and thus could be an important part of the solution to future power supply and sustainable energy management. The main obstacle to the widespread use of TE materials in diverse industries, e.g. for exhaust heat recovery in automobiles, is their low efficiency in converting heat to electricity. The conversion efficiency of TE materials is quantified by the dimensionless figure of merit, ZT, and the way to enhance ZT is to decrease the lattice thermal conductivity (klat) of the material, while maintaining a high electrical conductivity, i.e. to create a situation in which phonons are scattered but electrons are unaffected. Here, we report skutterudites filled by Tl and In, Tl0.1InxCo4Sb12, which allow a dramatic reduction of klat, yielding a ZT of 1.2 at 700 K. We demonstrate that the reduction of klat is due to the effective phonon scattering induced both by the rattling of Tl and In and by the naturally formed In2O3 n.
Comparative analysis of 7 short read sequencing platforms using the Korean Reference Genome: MGI and Illumina sequencing benchmark for whole genome sequencing
Venue: GigaScience
Year: 2021

DNBSEQ T7 is a new whole genome sequencer developed by Complete Genomics and MGI using DNA nanoball and combinatorial probe anchor synthesis technologies to generate short reads at a very large scale up to 60 human genomes per day. However, it has not been objectively and systematically compared against Illumina short read sequencers.  By using the same KOREF sample, the Korean Reference Genome, we have compared 7 sequencing platforms including BGISEQ 500, DNBSEQ T7, HiSeq2000, HiSeq2500, HiSeq4000, HiSeqX10, and NovaSeq6000. We measured sequencing quality by comparing sequencing statistics (base quality, duplication rate, and random error rate) mapping statistics (mapping rate, depth distribution, and percent GC coverage) and variant statistics (transition/transversion ratio, dbSNP annotation rate, and concordance rate with single nucleotide polymorphism [SNP] genotyping chip) across the 7 sequencing platforms. We found that MGI platforms showed a higher concordance rate for SNP genotyping than HiSeq2000 and HiSeq4000. The similarity matrix of variant calls confirmed that the 2 MGI platforms have the most similar characteristics to the HiSeq2500 platform.  Overall, MGI and Illumina sequencing platforms showed comparable levels of sequencing quality, uniformity of coverage, percent GC coverage, and variant accuracy; thus we conclude that the MGI platforms can be used for a wide range of genomics research fields at a lower cost than the Illumina platforms.
Public Interest and EU Competition Law
Year: 2020

While European Union (EU) competition law has long been understood as a variety of public interest law, the extent to which the rules can be applied directly to advance noneconomic public interest oriented goals is more contentious. This contribution considers whether and how such concerns can be accommodated within the framework of Articles 101 and 102 of the Treaty on the Functioning of the European Union (TFEU) It considers both the conventional approach to addressing public interest concerns within the analytical structure of the antitrust rules and also how broader public interest objectives have shaped recent EU level enforcement efforts in three key sectors: the liberalizing public utilities markets, the pharmaceutical sector, and the digital economy.
Automatic Volumetric Brain Tumor Segmentation using Convolutional Neural Networks
Year: 2019

Convolutional Neural Networks (CNNs) have recently been gaining popularity in the medical image analysis field because of their image segmentation capabilities. In this paper, we present a CNN that performs automated brain tumor segmentations of sparsely annotated 3D Magnetic Resonance Imaging (MRI) scans. Our CNN is based on 3D U net architecture, and it includes separate Dilated and Depth wise Convolutions. It is fully trained on the BraTS 2018 data set, and it produces more accurate results even when compared to the winners of the BraTS 2017 competition despite having a significantly smaller amount of parameters.
Social Justice in Consumer Protection: The Indonesian Framework
Year: 2013

The legal system of Indonesia is underpinned by the Pancasila, a political philosophy introduced by President Sukarno when Indonesia obtained independence from the Dutch in 1945. Its fifth pillar, the 'Keadilan Sosial bagi Seluruh Rakyat Indonesia' which is literally translated as "social justice for the whole people of Indonesia" calls for the equitable allocation of resources while protecting the weaker sector of the Indonesian population. Adopting a substantive procedural dichotomy approach, this paper examines how this indigenous conception of social justice has shaped and influenced consumer protection in Indonesia. It explores specific aspects of social justice in the formulation of consumer rights and obligations, representation, education and dispute settlement, particularly in the establishment of the National Consumer Protection Agency (NCPA) and the Consumer Dispute Settlement Board (CDSB) As expected, the paper finds evidence that the Pancasilan notion of social justice advances a liberal consumer protection framework as embodied in Indonesia's Law on Consumer Protection (LCP) which while balancing substantive rights procedurally tilts the regime in favour of consumers to temper the stronger position of entrepreneurs. It also predictably confirms that consistent with social justice tenets, consumer protection in Indonesia is pro consumer and encourages shared responsibility between the government and the private sector.
Antileishmanial activities of leaf latex and compound isolated from Aloe ghibensis Sebsebe Friis
Year: 2020

Aloe ghibensis Sebsebe Friis is traditionally used in Ethiopia for the treatment of various ailments including skin problem, wounds and malaria. Phytochemical constituents and antileshimanial properties of the leaf latex of A. ghibensis have not been reported. The objective of this study was, therefore, to determine the phytochemical constituents and in vitro antileishmanial activities of the leaf latex of A. ghibensis and its major compounds against two Leishmania species. Preparative TLC was used to isolate compounds from the leaf latex of A. ghibensis and spectroscopic techniques including 1D and 2D NMR as well as ESI MS were employed to elucidate structures of the isolated compounds. In vitro antileishmanial activity was performed against promastigotes and axenically cultured amastigotes of Leishmania aethiopica and Leishmania donovani clinical isolates using Alamar Blue assay. Phytochemical investigation led to the isolation of two major anthrones, identified as aloin A/B and 7 hydroxyaloin A/B. Both the leaf latex of A. ghibensis and isolated compounds showed antileishmanial activity with IC50 values ranging from 1.6 0.43 to 3.64 0.09 ug/ml and 1.87 0.21 to 3.72 0.12 against promastigotes and axenically cultured amastigotes of L. aethopica and L. donovani, respectively. Moreover, the test substances were found to be less toxic (LC50 145 0.72 to 156 0.08 ug/ml) than amphotericin B (LC50 12.11 0.51 ug/ml) towards human monocytic cell line (THP 1) The present study revealed that the latex and pure compounds possess genuine antileishmanial activity with high selectivity indices (SIs) Therefore, the isolated compounds can be used as a scaffold for the development of effective drugs for leishmaniasis.
Maximum Entropy Inverse Reinforcement Learning
Venue: AAAI
Year: 2008

Recent research has shown the benefit of framing problems of imitation learning as solutions to Markov Decision Problems. This approach reduces learning to the problem of recovering a utility function that makes the behavior induced by a near optimal policy closely mimic demonstrated behavior. In this work, we develop a probabilistic approach based on the principle of maximum entropy. Our approach provides a well defined, globally normalized distribution over decision sequences, while providing the same performance guarantees as existing methods. We develop our technique in the context of modeling real world navigation and driving behaviors where collected data is inherently noisy and imperfect. Our probabilistic approach enables modeling of route preferences as well as a powerful new approach to inferring destinations and routes based on partial trajectories.
A RELACAO ENTRE A PESTE NEGRA E OS JUDEUS
Year: 2018

25 A RELACAO  A PESTE NEGRA E OS JUDEUS THE RELATIONSHIP BETWEEN THE BLACK DEATH AND JEWS Kellen Jacobsen Follador1 Resumo: Na Idade Media, existia uma intima relacao entre religiao e medicina e algumas doencas eram interpretadas como castigo divino. Nesse contexto, o surto de peste negra que afligiu os reinos europeus entre 1348 1350 foi interpretado de forma religiosa por uma parcela da populacao crista. A partir dessa proposta, o objetivo deste artigo e apresentar a relacao entre a peste negra e a minoria judaica. Palavras chave: peste negra, judeus, violencia.  In the Middle Ages there was a close relationship between religion and medicine and some diseases were interpreted as divine punishment. In this context, the outbreak of the Black Death which afflicted the European kingdoms between 1348 1350 was interpreted religiously for a portion of the Christian population. Therefore, the intent of this paper is to present the relationship between the Black Death and the Jewish minority.
A Novel Noninvasive Method for Predicting Liver Fibrosis by Quantifying the Estrangement of Indocyanine Green Retention Rate and Tc 99m diethylenetriamine penta acetic Acid galactosyl Human Serum Albumin Scintigraphy
Venue: In Vivo
Year: 2020

Indocyanine green (ICG) clearance test is one of the most popular dynamic methods for evaluating preoperative liver function to avoid posthepatectomy liver failure (PHLF) Tc 99m diethylenetriamine penta acetic acid galactosyl human serum albumin scintigraphy (GSA) also facilitates the direct estimation of functional hepatocytes and can estimate the ICG retention rate (R15) however, in some cases, there is a discrepancy between results of a preoperative examination of ICG R15 and the estimated ICG R15 obtained by 99mTc GSA (GSA R15) This study evaluated the gap between ICG R15 and GSA R15 (DICG) for predicting background liver fibrosis in patients who underwent hepatectomy.  Sixty four consecutive patients who underwent hepatectomy and preoperative ICG R15 and GSA R15 examinations from 2016 to 2019 were retrospectively evaluated. The gap between GSA R15 and ICG R15 was defined as DICG and the factors predicting liver fibrosis were investigated.  In the pathologically proven cirrhotic group, platelet counts were significantly lower and DICG values were significantly larger than those in the non /early cirrhotic group. A multivariate analysis identified a higher total bilirubin level, a higher AST level, and a larger DICG level as significant predictive factors for liver cirrhosis.  Larger DICG was found to be an independent preoperative predictor of liver fibrosis and may positively contribute to decision making before hepatectomy to avoid PHLF.
Issuer Responsibilities Due to Securities Delisting on the Exchange
Year: 2020

Delisting is the removal of securities from the list of securities listed on the exchange so that these securities cannot be traded on the exchange. This occurs when the shares listed on the exchange have decreased the criteria so that they do not meet the listing requirements, thus the shares can be excluded from the listing on the exchange. Research on the liability of issuers due to delisting of securities on the stock exchange is normative. This research is designed to examine the responsibilities of issuers to investors due to delisting in the capital market. The results show that the issuer's responsibility to delisted investors, namely, the issuer has a role to buy back shares, the IDX has a role to buy shares owned by investors in accordance with Article 37 of the Company Law, the IDX has a role to create an orderly market and OJK has a role to defend. law for investors who have suffered losses in accordance with Article 30 of the OJK Law and Article 111 of the UUPM. Both OJK and the stock exchange must supervise and examine the reasons for delisting and regulating their accountability after delisting in the Indonesian capital market.
Stability analysis and autonomous stabilization control of a bicycle based on a three dimensional detailed physical model
Venue: IECON 2016 42nd Annual Conference of the IEEE Industrial Electronics Society
Year: 2016

The purpose of this study is analysis and control of a bicycle based on the proposed thee dimensional physical model. There are errors between models and actual equipment because conventional models have not captured the three dimensional dynamics accurately in previous studies on a bicycle. For the problem, we have derived three dimensional physics model, analyzed structure of, and designed controller for self stabilization of a bicycle. In conclusion, parameters of a bicycle enhancing stability are calculated. Furthermore, the controller based on the proposed model is effective for attitude stabilization of a bicycle during low speed riding.
Ansiedade traco e estado na gestacao de alto risco em mulheres atendidas em um Hospital Escola de Alagoas
Year: 2020

O presente estudo tem como objeto de pesquisa a presenca de niveis elevados de ansiedade traco e estado em gestantes de alto risco. Sabe se que o ciclo gravidico puerperal demanda especial atencao por conta das alteracoes fisicas, hormonais e de carater social ocorridas, alem da ambivalencia emocional vivenciada neste periodo. O estudo tem como objetivo avaliar os niveis de ansiedade traco e estado em gestantes de alto risco e sua relacao com fatores de risco na gestacao. Trata se de um estudo transversal, descritivo com abordagem quantitativa. Foram entrevistadas 100 gestantes classificadas como alto risco, com idade gestacional a partir de 20 semanas e acompanhadas pelo servico do HUPPA. A coleta se deu por meio de um questionario de identificacao e o Inventario de ansiedade traco estado IDATE. Esse estudo identificou a relacao entre a idade gestacional, a escolaridade, a renda familiar e o nao planejamento da gestacao com a ansiedade traco, onde constata se que a maior idade gestacional, menor escolaridade, menor renda familiar e nao planejamento da gestacao acompanham maiores niveis de ansiedade traco. Alem disso, identificou que existe relacao entre o estado civil e a ansiedade estado, onde as gestantes casadas ou em uniao estavel apresentaram niveis de moderado a alto, remetendo a qualidade destes relacionamentos afetivos. Tendo em vista essa realidade e sabendo da relevancia da atuacao da enfermagem no pre natal de alto risco, acredita se que novas estrategias precisam ser trabalhadas com o intuito de identificar o sofrimento mental para promover intervencao precoce. Deste modo, a enfermagem deve atentar se aos sinais e sintomas de ansiedade a fim de contribuir para uma gestacao, parto e puerperio tranquilo e aprazivel, alem de diminuir complicacoes ao feto.
Use of the journal impact factor for assessing individual articles need not be statistically wrong.
Venue: F1000Research
Year: 2020

Most scientometricians reject the use of the journal impact factor for assessing individual articles and their authors. The well known San Francisco Declaration on Research Assessment also strongly objects against this way of using the impact factor. Arguments against the use of the impact factor at the level of individual articles are often based on statistical considerations. The skewness of journal citation distributions typically plays a central role in these arguments. We present a theoretical analysis of statistical arguments against the use of the impact factor at the level of individual articles. Our analysis shows that these arguments do not support the conclusion that the impact factor should not be used for assessing individual articles. In fact, our computer simulations demonstrate the possibility that the impact factor is a more accurate indicator of the value of an article than the number of citations the article has received. It is important to critically discuss the dominant role of the impact factor in research evaluations, but the discussion should not be based on misplaced statistical arguments. Instead, the primary focus should be on the socio technical implications of the use of the impact factor.
The Judge, the Politician, and the Press: Newspaper Coverage and Criminal Sentencing across Electoral Systems
Year: 2015

We study how media environments interact with political institutions that structure the accountability of public officials. Specifically, we quantify media influence on the behavior of US state court judges. We analyze around 1.5 million criminal sentencing decisions from 1986 to 2006 and new data on the newspaper coverage of 9,828 trial court judges. Since newspaper coverage is endogenous, we use the match between newspaper markets and judicial districts to identify effects. We find that newspaper coverage significantly increases sentence length by nonpartisan elected judges for violent crimes. For partisan elected and appointed judges, there are no significant effects.
Neural Factorization Machines for Sparse Predictive Analytics
Venue: SIGIR
Year: 2017

Many predictive tasks of web applications need to model categorical variables, such as user IDs and demographics like genders and occupations. To apply standard machine learning techniques, these categorical predictors are always converted to a set of binary features via one hot encoding, making the resultant feature vector highly sparse. To learn from such sparse data effectively, it is crucial to account for the interactions between features. Factorization Machines (FMs) are a popular solution for efficiently using the second order feature interactions. However, FM models feature interactions in a linear way, which can be insufficient for capturing the non linear and complex inherent structure of real world data. While deep neural networks have recently been applied to learn non linear feature interactions in industry, such as the Wide&Deep by Google and DeepCross by Microsoft, the deep structure meanwhile makes them difficult to train. In this paper, we propose a novel model Neural Factorization Machine (NFM) for prediction under sparse settings. NFM seamlessly combines the linearity of FM in modelling second order feature interactions and the non linearity of neural network in modelling higher order feature interactions. Conceptually, NFM is more expressive than FM since FM can be seen as a special case of NFM without hidden layers. Empirical results on two regression tasks show that with one hidden layer only, NFM significantly outperforms FM with a 7.3% relative improvement. Compared to the recent deep learning methods Wide&Deep and DeepCross, our NFM uses a shallower structure but offers better performance, being much easier to train and tune in practice.
RelationNet+ Bridging Visual Representations for Object Detection via Transformer Decoder
Venue: NeurIPS
Year: 2020

Existing object detection frameworks are usually built on a single format of object/part representation, i.e. anchor/proposal rectangle boxes in RetinaNet and Faster R CNN, center points in FCOS and RepPoints, and corner points in CornerNet. While these different representations usually drive the frameworks to perform well in different aspects, e.g. better classification or finer localization, it is in general difficult to combine these representations in a single framework to make good use of each strength, due to the heterogeneous or non grid feature extraction by different representations. This paper presents an attention based decoder module similar as that in Transformer~\cite{vaswani2017attention} to bridge other representations into a typical object detector built on a single representation format, in an end to end fashion. The other representations act as a set of \emph{key} instances to strengthen the main \emph{query} representation features in the vanilla detectors. Novel techniques are proposed towards efficient computation of the decoder module, including a \emph{key sampling} approach and a \emph{shared location embedding} approach. The proposed module is named \emph{bridging visual representations} (BVR) It can perform in place and we demonstrate its broad effectiveness in bridging other representations into prevalent object detection frameworks, including RetinaNet, Faster R CNN, FCOS and ATSS, where about $1.5\sim3.0$ AP improvements are achieved. In particular, we improve a state of the art framework with a strong backbone by about $2.0$ AP, reaching $52.7$ AP on COCO test dev. The resulting network is named RelationNet+ The code will be available at this https URL.
Slacks based measure of efficiency of airports with airplanes delays as undesirable outputs
Venue: Comput. Oper. Res.
Year: 2011

This paper reports the slacks based measure (SBM) of efficiency of 39 Spanish airports for years 2006 and 2007. In addition to the conventional outputs (namely aircraft traffic movements, passenger movements and cargo handled) two undesirable outputs have been considered: percentage of delayed flights and average conditional delay of delayed flights. The inputs considered quantify the physical infrastructure of the airports and are considered non discretionary. The proposed Data Envelopment Analysis (DEA) approach assumes variable returns to scale and joint weak disposability of the desirable and undesirable outputs. The SBM model used has been found to have more discriminatory power than the common directional distance function approach. Also, the inclusion in the analysis of the undesirable effects of airport operations leads to more valid results. The results show that in both years more than half of the airports are technical efficient with the rest showing in general large inefficiencies due to slacks in the different outputs, slacks that the proposed SBM approach is able to identify and quantify. Overall, the system has significant improvement potential in cargo and to a less extent in passengers and percentage of delayed flights.