nils-herrmann/clean_scirepeval huggingface dataset:
A Case of Cancer associated Dermatomyositis in a Patient with Thymic Carcinoma

Thymic carcinoma is a cause of a cancer associated dermatomyositis.  A 73year old female was referred to our hospital with sudden onset dermatitis and was diagnosed with dermatomyositis. Since steroid therapy was accompanied by the waxing and waning of the patient's skin symptoms, cancerassociated dermatomyositis was suspected. Chest computed tomography revealed a lobular anterior mediastinal tumor of 42 mm in diameter with mediastinal and supraclavicular lymphadenopathy. Thymectomy with resection of the invaded pericardium and left brachiocephalic vein and lymphadenectomy were performed via median sternotomy. A pathological examination revealed a poorly differentiated squamous cell carcinoma of the thymus with metastatic lymph nodes (pT1aN2M0, stage IVb) Although the clinical symptoms of dermatomyositis were ameliorated soon after resection, the patient's skin rashes worsened after the recurrence of thymic carcinoma.  The abrupt development of symptoms and the remission of skin symptoms in response to the therapeutic process were helpful as evidence of thymic cancer associated dermatomyositis.
Distributed Clustering of Linear Bandits in Peer to Peer Networks
Venue: ICML

We provide two distributed confidence ball algorithms for solving linear bandit problems in peer to peer networks with limited communication capabilities. For the first, we assume that all the peers are solving the same linear bandit problem, and prove that our algorithm achieves the optimal asymptotic regret rate of any centralised algorithm that can instantly communicate information between the peers. For the second, we assume that there are clusters of peers solving the same bandit problem within each cluster, and we prove that our algorithm discovers these clusters, while achieving the optimal asymptotic regret rate within each one. Through experiments on several real world datasets, we demonstrate the performance of proposed algorithms compared to the state of the art.
Dissociating perception from action during conscious and unconscious conflict adaptation.
Venue: Journal of experimental psychology. Learning, memory, and cognition

The detection of a conflict between relevant and irrelevant information on a given trial typically results in a smaller conflict effect on the next trial. This sequential effect has been interpreted as an expression of cognitive control implemented to resolve conflict. In this context, 2 different but related issues have received increasing attention in the literature. The first issue is whether the detection of motor conflict is necessary to induce cognitive control or, alternatively, whether the detection of perceptual conflict is sufficient. The second issue concerns whether awareness of the conflict is necessary to induce cognitive control. Here, we address both issues in a single design. Our reaction time (RT) results indicate that conflict driven control is domain specific. The detection of perceptual conflict on the previous trial selectively reduces perceptual conflict on the next trial. Similarly, the detection of motor conflict on the previous trial selectively reduces motor conflict on the next trial. For errors, adaptive control seemed to be more general: The detection of perceptual or motor conflict on the previous trial reduced the frequency of errors on response conflict trials. Furthermore, unconsciously triggered conflict adaptation was observed, but not systematically. Results on errors provide some evidence that sensitivity to an unconscious conflict on the previous trial reduces the frequency of errors on the current trial. For RT analyses however, unconscious conflict appeared not to be sufficient to induce cognitive control. This pattern of results is in line with previous studies examining the role of consciousness in conflict adaptation.
Environmental Kuznets Curve hypothesis and the role of globalization in selected African countries

The present study incorporates globalization and energy intensity into the CO2 emissions function and investigates the presence of Environmental Kuznets Curve (EKC) in 19 African countries for the time period of 1971 2012. We have applied the ARDL bounds testing approach for cointegration to examine the long run relationship in the variables. Our results confirmed the presence of cointegration between the series in Africa, Algeria, Angola, Cameroon, Congo Republic, Ghana, Kenya, Libya, Morocco, Nigeria, South Africa, Sudan, Tanzania, Togo, Tunisia, Zambia and Zimbabwe. The results indicated the positive effect of energy intensity on CO2 emissions in Africa, Algeria, Angola, Cameroon, Congo Republic, Ghana, Kenya, Libya, Morocco, Nigeria, South Africa, Sudan, Togo, and Tunisia while energy intensity declines CO2 emissions in the case of Zambia and Zimbabwe. Globalization decreases CO2 emissions in Africa, Angola, Cameroon, Congo Republic, Egypt, Kenya, Libya, Tunisia and Zambia but increases CO2 emissions in Ghana, Morocco, South Africa, Sudan and Tanzania. The EKC exists in Africa, Algeria, Cameroon, Congo Republic, Morocco, Tunisia and Zambia but U shaped relationship is found between economic growth and CO2 emissions in Sudan and Tanzania.
Solid contact potassium selective electrodes for biomedical applications a review.
Venue: Talanta

Ion selective electrodes (ISE) are used in several biomedical applications, including laboratory sensing of potassium concentration in blood and urine samples. For on site determination of potassium concentration and usage in other applications such as determination of extracellular potassium concentration, miniaturization of the sensors is required. To that extent, solid contacts have proven to be an adequate substitute of liquid contacts as inner layer for ion to electron transduction, allowing industrial production of miniaturized ISEs. This review paper covers relevant developments of solid state ISEs in the past decade, critically compares current potassium ISEs and discusses future prospects for biomedical applications. Performances of three main types of solid contact materials in potassium sensing are compared, namely polypyrrole, polythiophenes and conducting nanomaterials. With these new materials, numerous improvements in stability, selectivity and time response of solid state ISEs have been made. Current developments are new operational methods of sensing, flexible miniaturized sensors and multi electrode designs able to measure electrolyte concentrations in one drop blood samples or transmembrane ionic flows.
Heavy metal oxide glasses as gamma rays shielding material

The gamma rays shielding parameters for heavy metal oxide glasses and concrete samples are comparable. However, the transparent nature of glasses provides additional feature to visualize inside the shielding material. Hence, different researchers had contributed in computing/measuring different shielding parameters for different configurations of heavy metal oxide glass systems. In the present work, a detailed study on different heavy metal (56Ba, 64Gd, 82Pb, 83Bi) oxide glasses has been presented on the basis of different gamma rays shielding parameters as reported by different researchers in the recent years. It has been observed that among the selected heavy metal oxide glass systems, Bismuth based glasses provide better gamma rays shielding. Hence, Bismuth based glasses can be better substitute to concrete walls at nuclear reactor sites and nuclear labs.
Cosmic ray nuclei, antiprotons and gamma rays in the galaxy: a new diffusion model

We model the transport of cosmic ray nuclei in the galaxy by means of a new numerical code. At variance with previous numerical models, ours accounts for a generic spatial distribution of the diffusion coefficient. We found that in the case of radially uniform diffusion, the main secondary/primary ratios (B/C, N/O and sub Fe/Fe) and the modulated antiproton spectrum consistently match the available observations. Convection and re acceleration do not seem to be required in the energy range that we consider: 1<=E<=103 GeV/nucleon. We generalize these results, accounting for radial dependence of the diffusion coefficient, which is assumed to trace that of the cosmic ray sources. While this does not affect the prediction of secondary/primary ratios, the simulated longitude profile of the diffuse g ray emission is significantly different from that for the uniform case and may agree with EGRET measurements without requiring invoking ad hoc assumptions on the galactic gas density distribution.
Blue Growth and the relationship between ecosystem services and human activities: The Salento artisanal fisheries case study

This paper proposes a tool for the management of marine and coastal areas based on the ecosystem service framework and the Bayesian network approach. The participative methodology used makes this tool very suitable for addressing issues related to community led coastal development and Blue Growth. The Salento (Italy) artisanal fisheries case study is used to test the usefulness of our approach. Salento is characterized by declining fisheries and increasing tourism development. Cause effect relationships between human activities and ecosystem services are modeled to show the differences in stakeholder behavior under different scenarios. Results indicate that increasing tourist flow and related infrastructure are not perceived as threats to the local ecosystem equilibrium, but the problem of water quality should be carefully considered to prevent future negative feedback. The model can be used as a methodological guide by local public authorities as well as economic and civil society groups. It may be particularly useful for the Fisheries Local Action Groups, which have been explicitly created to design and implement bottom up strategies that fit their regions' needs to increase economic, social, and environmental welfare.
A flexible hierarchical approach for facial age estimation based on multiple features
Venue: Pattern Recognit.

Age estimation from facial images is increasingly receiving attention to solve age based access control, age adaptive targeted marketing, amongst other applications. Since even humans can be induced in error due to the complex biological processes involved, finding a robust method remains a research challenge today. In this paper, we propose a new framework for the integration of Active Appearance Models (AAM) Local Binary Patterns (LBP) Gabor wavelets (GW) and Local Phase Quantization (LPQ) in order to obtain a highly discriminative feature representation which is able to model shape, appearance, wrinkles and skin spots. In addition, this paper proposes a novel flexible hierarchical age estimation approach consisting of a multi class Support Vector Machine (SVM) to classify a subject into an age group followed by a Support Vector Regression (SVR) to estimate a specific age. The errors that may happen in the classification step, caused by the hard boundaries between age classes, are compensated in the specific age estimation by a flexible overlapping of the age ranges. The performance of the proposed approach was evaluated on FG NET Aging and MORPH Album 2 datasets and a mean absolute error (MAE) of 4.50 and 5.86 years was achieved respectively. The robustness of the proposed approach was also evaluated on a merge of both datasets and a MAE of 5.20 years was achieved. Furthermore, we have also compared the age estimation made by humans with the proposed approach and it has shown that the machine outperforms humans. The proposed approach is competitive with current state of the art and it provides an additional robustness to blur, lighting and expression variance brought about by the local phase features.  highly discriminative feature representation, which is able to model shape and appearance as well as wrinkles and skin spots.A novel hierarchical method consisting of a multi class SVM and a SVR.The errors are compensated in the detailed age estimation by overlapping flexibly the age ranges of each age function.Experiments have been carried out on the publicly available FG NET Aging and MORPH Album 2 datasets.An increased robustness to blur, lighting and expression variance through local phase features.
If Dung Beetles (Scarabaeidae: Scarabaeinae) Arose in Association with Dinosaurs, Did They Also Suffer a Mass Co Extinction at the K Pg Boundary?
Venue: PloS one

The evolutionary success of beetles and numerous other terrestrial insects is generally attributed to co radiation with flowering plants but most studies have focused on herbivorous or pollinating insects. Non herbivores represent a significant proportion of beetle diversity yet potential factors that influence their diversification have been largely unexamined. In the present study, we examine the factors driving diversification within the Scarabaeidae, a speciose beetle family with a range of both herbivorous and non herbivorous ecologies. In particular, it has been long debated whether the key event in the evolution of dung beetles (Scarabaeidae: Scarabaeinae) was an adaptation to feeding on dinosaur or mammalian dung. Here we present molecular evidence to show that the origin of dung beetles occurred in the middle of the Cretaceous, likely in association with dinosaur dung, but more surprisingly the timing is consistent with the rise of the angiosperms. We hypothesize that the switch in dinosaur diet to incorporate more nutritious and less fibrous angiosperm foliage provided a palatable dung source that ultimately created a new niche for diversification. Given the well accepted mass extinction of non avian dinosaurs at the Cretaceous Paleogene boundary, we examine a potential co extinction of dung beetles due to the loss of an important evolutionary resource, i.e. dinosaur dung. The biogeography of dung beetles is also examined to explore the previously proposed "out of Africa" hypothesis. Given the inferred age of Scarabaeinae as originating in the Lower Cretaceous, the major radiation of dung feeders prior to the Cenomanian, and the early divergence of both African and Gondwanan lineages, we hypothesise that that faunal exchange between Africa and Gondwanaland occurred during the earliest evolution of the Scarabaeinae. Therefore we propose that both Gondwanan vicariance and dispersal of African lineages is responsible for present day distribution of scarabaeine dung beetles and provide examples.
The direct costs of fatal and non fatal falls among older adults United States.
Venue: Journal of safety research

This study sought to estimate the incidence, average cost, and total direct medical costs for fatal and non fatal fall injuries in hospital, ED, and out patient settings among U.S. adults aged 65 or older in 2012, by sex and age group and to report total direct medical costs for falls inflated to 2015 dollars. METHOD Incidence data came from the 2012 National Vital Statistics System, 2012 Healthcare Cost and Utilization Project Nationwide Inpatient Sample, 2012 Health Care Utilization Program National Emergency Department Sample, and 2007 Medical Expenditure Panel Survey. Costs for fatal falls were derived from the Centers for Disease Control and Prevention's Web based Injury Statistics Query and Reporting System; costs for non fatal falls were based on claims from the 1998/1999 Medicare fee for service 5% Standard Analytical Files. Costs were inflated to 2015 estimates using the health care component of the Personal Consumption Expenditure index.  In 2012, there were 24,190 fatal and 3.2 million medically treated non fatal fall related injuries. Direct medical costs totaled $616.5 million for fatal and $30.3 billion for non fatal injuries in 2012 and rose to $637.5 million and $31.3 billion, respectively, in 2015. Fall incidence as well as total cost increased with age and were higher among women.  Medically treated falls among older adults, especially among older women, are associated with substantial economic costs.  Widely implementing evidence based interventions for fall prevention is essential to decrease the incidence and healthcare costs associated with these injuries.
The importance of early bonding on the long term mental health and resilience of children
Venue: London journal of primary care

Human babies are born very dependent on their parents. They undergo huge brain development, growth and neuron pruning in the first two years of life. The brain development of infants (as well as their social, emotional and cognitive development) depends on a loving bond or attachment relationship with a primary caregiver, usually a parent. There is increasing evidence from the fields of development psychology, neurobiology and animal epigenetic studies that neglect, parental inconsistency and a lack of love can lead to long term mental health problems as well as to reduced overall potential and happiness. In this paper, the authors consider the evidence for this claim across several disciplines and conclude that the support of babies and their parents in the first two years of life to be a crucial aim of public health groups in the community.
Natural Language Processing for Arabic Metaphors: A Conceptual Approach
Venue: AISI

Metaphor is a literary device that allows us to express a concept in terms of another. In other words, it is based on similarity between concepts. Metaphorical expressions represent a great variety and they are used in conventional metaphors, which we reproduce and comprehend every day, poetic, novel, and Holy Qur'an. The use of metaphor is ubiquitous in natural language text and it is a serious bottleneck in automatic text understanding, and developing methods to identify and deal with metaphors is an open problem in Arabic natural language processing, especially Machine Translation. Due to the complexities involved in metaphor, it semantically influenced the meaning of machine translated text. This makes metaphor an important research area for computational and cognitive linguistics, and its automatic identification and interpretation is indispensable for any semantics oriented Arabic natural language processing. In this paper, we present the challenges of Arabic NLP of metaphors, which is very important in developing a computational NLP based system for in Classical Arabic, Modern Standard Arabic and Dialect Arabic. We also highlight main problems that arises when translating an Arabic metaphor to another language.
Unpacking the politics of natural capital and economic metaphors in environmental policy discourse

Economic metaphors including natural capital, natural assets, ecosystem services, and ecological debt are becoming commonplace in environmental policy discourse. Proponents consider such terms provide a clearer idea of the 'value' of nature, and are useful for ensuring the environment is given due attention in decision making. Critical discourse analysis highlights the ideological work language does; the way in which we think, write, and talk about the environment has important implications for how it is governed. Consequently, the widespread use of economic metaphors is politically significant. This article discusses how metaphors have been analysed in environmental policy research, surveys the use of prominent economic metaphors in environmental policy, and considers the politics associated with such terms. The uptake of various economic metaphors represents a form of reverse discourse, varies in politically significant ways, and narrows the terms of environmental debate.
Deep Feature Learning for Hyperspectral Image Classification and Land Cover Estimation

The differences in spatial sampling between field measurements and remote sensing imagery can hinder the exploitation of contemporary data. When the field based sampling is higher than airborne and spaceborne imagery, each pixel is naturally associated with multiple pixels due to the multiplexing of the reflectances of different materials. To address this scale inconsistency, we propose the introduction of the multi label classification framework where classifiers are trained to predict multiple labels per pixel. Furthermore, instead of relying on raw hyperspectral measurements for the classification process, we investigate the Stacked Sparse Autoencoders framework, an example of a deep learning network, for descriptive feature extraction. To validate the merits of the proposed scheme, we consider real data from the Hyperion instrument on board the EO 1 and NYC land cover data from 2010.
Essential Virtual SAN (VSAN) Administrator's Guide to VMware Virtual SAN (2nd Edition)

Plan, implement, and manage VMwares radically simple, enterprise class software defined storage platform VMwares Virtual SAN has rapidly proven itself in environments ranging from hospitals to oil rigs to e commerce platforms. Along the way, it has matured to offer unsurpassed features for data integrity, availability, and space efficiency. Virtual SAN 6.x makes all flash storage practical for even more use cases, while radically simplifying IT operations and supporting the transition to hyper converged infrastructures (HCI) Now, the authors of Essential Virtual SAN (VSAN) have thoroughly updated their definitive guide to this transformative technology. Writing for vSphere administrators, architects, and consultants, Cormac Hogan and Duncan Epping explain what Virtual SAN is, how it has evolved, what it now offers, and how to gain maximum value from it. Hogan and Epping draw on unsurpassed experience shaping Virtual SAN and helping VMware customers deploy it. They offer expert insight into preparation, installation, configuration, policies, provisioning, clusters, and more. Youll also find practical guidance for using its new Health and Performance Services to gain end to end visibility into infrastructure and resource consumption. Both an up to the minute reference and hands on tutorial, Essential Virtual SAN, Second Edition uses realistic examples to demonstrate the immense power of Virtual SAN 6.x. Youll learn all you need to successfully plan and deploy the newest versions, and operate them smoothly and efficiently.  Understanding the goals and concepts of Software Defined Storage and Virtual SAN Meeting updated requirements for safe Virtual SAN 6.x implementation Architecting, installing, and configuring Virtual SAN for your unique environment Simplifying deployment with VM storage policies and provisioning Controlling availability, performance, and reliability Efficiently managing and maintaining Virtual SAN Providing resiliency and scale out storage functionality Designing and sizing clusters (with examples) Using stretched clusters to address rigorous downtime requirements Applying valuable new features such as deduplication, compression, checksums, and encryption Using Health and Performance Services to troubleshoot hardware, configurations, and performance
Multicast Delayed Authentication for Streaming Synchrophasor Data in the Smart Grid
Venue: SEC

Multicast authentication of synchrophasor data is challenging due to the design requirements of Smart Grid monitoring systems such as low security overhead, tolerance of lossy networks, time criticality and high data rates. In this work, we propose inf TESLA, Infinite Timed Efficient Stream Loss tolerant Authentication, a multicast delayed authentication protocol for communication links used to stream synchrophasor data for wide area control of electric power networks. Our approach is based on the authentication protocol TESLA but is augmented to accommodate high frequency transmissions of unbounded length. inf TESLA protocol utilizes the Dual Offset Key Chains mechanism to reduce authentication delay and computational cost associated with key chain commitment. We provide a description of the mechanism using two different modes for disclosing keys and demonstrate its security against a man in the middle attack attempt. We compare our approach against the TESLA protocol in a 2 day simulation scenario, showing a reduction of 15.82% and 47.29% in computational cost, sender and receiver respectively, and a cumulative reduction in the communication overhead.