nils-herrmann/clean_scirepeval huggingface dataset:
The state of the art of application restrictions and sandboxes: A survey of application-oriented access controls and their shortfalls

Under most widely-used security mechanisms the programs users run possess more authority than is strictly necessary, with each process typically capable of utilising all of the user’s privileges. Consequently such security mechanisms often fail to protect against contemporary threats, such as previously unknown (‘zero-day’) malware and software vulnerabilities, as processes can misuse a user’s privileges to behave maliciously. Application restrictions and sandboxes can mitigate threats that traditional approaches to access control fail to prevent by limiting the authority granted to each process. This developing field has become an active area of research, and a variety of solutions have been proposed. However, despite the seriousness of the problem and the security advantages these schemes provide, practical obstacles have restricted their adoption. This paper describes the motivation for application restrictions and sandboxes, presenting an indepth review of the literature covering existing systems. This is the most comprehensive review of the field to date. The paper outlines the broad categories of existing application-oriented access control schemes, such as isolation and rule-based schemes, and discusses their limitations. Adoption of these schemes has arguably been impeded by workflow, policy complexity, and usability issues. The paper concludes with a discussion on areas for future work, and points a way forward within this developing field of research with recommendations for usability and abstraction to be considered to a further extent when designing application-oriented access
Test Automation Architectures : Planning for Test Automation

Designing a practical test automation architecture provides a solid foundation for a successful automation effort. This paper describes key elements of automated testing that need to be considered, models for testing that can be used for designing a test automation architecture, and considerations for successfully combining the elements to form an automated test environment. The paper first develops a general framework for discussion of software testing and test automation. This includes a definition of test automation, a model for software tests, and a discussion of test oracles. The remainder of the paper focuses on using the framework to plan for a test automation architecture that addresses the requirements for the specific software under test (SUT).
A New Multi-level Inverter with FACTS Capabilities for Wind Applications

The modular multilevel converter (MMC) is an attractive topology for HVDC/FACTS systems. In this paper a new single-phase MMC-based D-STATCOM inverter for grid connection is proposed. The proposed inverter is designed for grid-connected wind turbines in the small- to mid-sized (10kW-20kW) range using the most advanced multi-level inverter topology. The proposed MMC D-STATCOM inverter controls the DC link voltage as well as the active and reactive power transferred between the renewable energy source, specifically wind turbine, and the grid in order to regulate the power factor (PF) of the grid regardless of the input active power from wind turbine. The goal of this paper is to present a new inverter with D-STATCOM capability in a single unit without any additional cost. The 5-level D-STATCOM inverter is simulated and the results are presented to verify the operation of the proposed system. The simulation studies are carried out in the MATLAB/Simulink environment. To validate the simulation results, an experimental configuration of a 5-Level DSTATCOM inverter has been built and tested.
Modeling of lithium-ion battery degradationfor cell life assessment

Rechargeable lithium-ion batteries are promising candidates for building grid-level storage systems because of their high energy and power density, low discharge rate, and decreasing cost. A vital aspect in energy storage planning and operations is to accurately model the aging cost of battery cells, especially in irregular cycling operations. This paper proposes a semi-empirical lithium-ion battery degradation model that assesses battery cell life loss from operating profiles. We formulate the model by combining fundamental theories of battery degradation and our observations in battery aging test results. The model is adaptable to different types of lithium-ion batteries, and methods for tuning the model coefficients based on manufacturer's data are presented. A cycle-counting method is incorporated to identify stress cycles from irregular operations, allowing the degradation model to be applied to any battery energy storage (BES) applications. The usefulness of this model is demonstrated through an assessment of the degradation that a BES would incur by providing frequency control in the PJM regulation market.
Role of depression, stress, and trauma in HIV disease progression.

Despite advances in HIV treatment, there continues to be great variability in the progression of this disease. This paper reviews the evidence that depression, stressful life events, and trauma account for some of the variation in HIV disease course. Longitudinal studies both before and after the advent of highly active antiretroviral therapies (HAART) are reviewed. To ensure a complete review, PubMed was searched for all English language articles from January 1990 to July 2007. We found substantial and consistent evidence that chronic depression, stressful events, and trauma may negatively affect HIV disease progression in terms of decreases in CD4 T lymphocytes, increases in viral load, and greater risk for clinical decline and mortality. More research is warranted to investigate biological and behavioral mediators of these psychoimmune relationships, and the types of interventions that might mitigate the negative health impact of chronic depression and trauma. Given the high rates of depression and past trauma in persons living with HIV/AIDS, it is important for healthcare providers to address these problems as part of standard HIV care.
Ovulation as a male mating prime: subtle signs of women's fertility influence men's mating cognition and behavior.

Women's reproductive fertility peaks for a few days in the middle of their cycle around ovulation. Because conception is most likely to occur inside this brief fertile window, evolutionary theories suggest that men possess adaptations designed to maximize their reproductive success by mating with women during their peak period of fertility. In this article, we provide evidence from 3 studies that subtle cues of fertility prime mating motivation in men, thus facilitating psychological and behavioral processes associated with the pursuit of a sexual partner. In Study 1, men exposed to the scent of a woman near peak levels of fertility displayed increased accessibility to sexual concepts. Study 2 demonstrated that, among men who reported being sensitive to odors, scent cues of fertility triggered heightened perceptions of women's sexual arousal. Study 3 revealed that, in a face-to-face interaction, high levels of female fertility were associated with a greater tendency for men to make risky decisions and to behaviorally mimic a female partner. Hence, subtle cues of fertility led to a cascade of mating-related processes-from lower order cognition to overt behavior-that reflected heightened mating motivation. Implications for theories of goal pursuit, romantic attraction, and evolutionary psychology are discussed.
Generative Communication in Linda

Generative communication is the basis of a new distributed programming langauge that is intended for systems programming in distributed settings generally and on integrated network computers in particular. It differs from previous interprocess communication models in specifying that messages be added in tuple-structured form to the computation environment, where they exist as named, independent entities until some process chooses to receive them. Generative communication results in a number of distinguishing properties in the new language, Linda, that is built around it. Linda is fully distributed in space and distributed in time; it allows distributed sharing, continuation passing, and structured naming. We discuss these properties and their implications, then give a series of examples. Linda presents novel implementation problems that we discuss in Part II. We are particularly concerned with implementation of the dynamic global name space that the generative communication model requires.
Japanese Classification of Esophageal Cancer, 11th Edition: part I

English Edition Committee Members Kenji Nemoto Yamagata University Naohisa Yahagi Keio University Soji Ozawa Tokai University Yoshiaki Kajiyama Juntendo University Tatsuyuki Kawano Tokyo Medical and Dental University Tomio Arai Tokyo Metropolitan Geriatric Hospital and Institute of Gerontology Yuji Tachimori National Cancer Center Hospital Shoji Natsugoe Kagoshima University Kumiko Momma Tokyo Metropolitan Cancer and Infectious Diseases Center Komagome Hospital Yasuyuki Seto Tokyo University Yuichiro Doki Osaka University
Rainmakers: why bad weather means good productivity.

People believe that weather conditions influence their everyday work life, but to date, little is known about how weather affects individual productivity. Contrary to conventional wisdom, we predict and find that bad weather increases individual productivity and that it does so by eliminating potential cognitive distractions resulting from good weather. When the weather is bad, individuals appear to focus more on their work than on alternate outdoor activities. We investigate the proposed relationship between worse weather and higher productivity through 4 studies: (a) field data on employees' productivity from a bank in Japan, (b) 2 studies from an online labor market in the United States, and (c) a laboratory experiment. Our findings suggest that worker productivity is higher on bad-, rather than good-, weather days and that cognitive distractions associated with good weather may explain the relationship. We discuss the theoretical and practical implications of our research.
Brain-size evolution and sociality in Carnivora.

Increased encephalization, or larger brain volume relative to body mass, is a repeated theme in vertebrate evolution. Here we present an extensive sampling of relative brain sizes in fossil and extant taxa in the mammalian order Carnivora (cats, dogs, bears, weasels, and their relatives). By using Akaike Information Criterion model selection and endocranial volume and body mass data for 289 species (including 125 fossil taxa), we document clade-specific evolutionary transformations in encephalization allometries. These evolutionary transformations include multiple independent encephalization increases and decreases in addition to a remarkably static basal Carnivora allometry that characterizes much of the suborder Feliformia and some taxa in the suborder Caniformia across much of their evolutionary history, emphasizing that complex processes shaped the modern distribution of encephalization across Carnivora. This analysis also permits critical evaluation of the social brain hypothesis (SBH), which predicts a close association between sociality and increased encephalization. Previous analyses based on living species alone appeared to support the SBH with respect to Carnivora, but those results are entirely dependent on data from modern Canidae (dogs). Incorporation of fossil data further reveals that no association exists between sociality and encephalization across Carnivora and that support for sociality as a causal agent of encephalization increase disappears for this clade.
Keyphrase Extraction using Sequential Labeling

Keyphrases efficiently summarize a document’s content and are used in various document processing and retrieval tasks. Several unsupervised techniques and classifiers exist for extracting keyphrases from text documents. Most of these methods operate at a phrase-level and rely on part-of-speech (POS) filters for candidate phrase generation. In addition, they do not directly handle keyphrases of varying lengths. We overcome these modeling shortcomings by addressing keyphrase extraction as asequential labelingtask in this paper. We explore a basic set of features commonly used in NLP tasks as well as predictions from various unsupervised methods to train our taggers. In addition to a more natural modeling for the keyphrase extraction problem, we show that tagging models yield significant performance benefits over existing stateof-the-art extraction methods.
Computational Drug Discovery with Dyadic Positive-Unlabeled Learning

Computational Drug Discovery, which uses computational techniques to facilitate and improve the drug discovery process, has aroused considerable interests in recent years. Drug Repositioning (DR) and DrugDrug Interaction (DDI) prediction are two key problems in drug discovery and many computational techniques have been proposed for them in the last decade. Although these two problems have mostly been researched separately in the past, both DR and DDI can be formulated as the problem of detecting positive interactions between data entities (DR is between drug and disease, and DDI is between pairwise drugs). The challenge in both problems is that we can only observe a very small portion of positive interactions. In this paper, we propose a novel framework called Dyadic PositiveUnlabeled learning (DyPU) to solve the problem of detecting positive interactions. DyPU forces positive data pairs to rank higher than the average score of unlabeled data pairs. Moreover, we also derive the dual formulation of the proposed method with the rectifier scoring function and we show that the associated non-trivial proximal operator admits a closed form solution. Extensive experiments are conducted on real drug data sets and the results show that our method achieves superior performance comparing with the state-of-the-art.
Large Scale Text Classification Using Map Reduce and Naive Bayes Algorithm for Domain Specified Ontology Building

Internet that covers a large information gives an opportunity to obtain knowledge from it. Internet contains large unstructured and unorganized data such as text, video, and image. Problems arise on how to organize large amount of data and obtain a useful information from it. This information can be used as knowledge in the intelligent computer system. Ontology as one of knowledge representation covers a large area topic. For constructing domain specified ontology, we use large text dataset on Internet and organize it into specified domain before ontology building process is done. We try to implement naive bayes text classifier using map reduce programming model in our research for organizing our large text dataset. In this experiment, we use animal and plant domain article in Wikipedia online encyclopedia as our dataset. Our proposed method can achieve highest accuracy with score about 98.8%. This experiment shows that our proposed method provides a robust system and good accuracy for classifying document into specified domain in preprocessing phase for domain specified ontology building.
6-D Localization of a Magnetic Capsule Endoscope Using a Stationary Rotating Magnetic Dipole Field

Since the introduction of passive commercial capsule endoscopes, researchers have been pursuing methods to control and localize these devices, many utilizing magnetic fields [1, 2]. An advantage of magnetics is the ability to both actuate and localize using the same technology. Prior work from our group  developed a method to actuate screw-type magnetic capsule endoscopes in the intestines using a single rotating magnetic dipole located at any position with respect to the capsule. This paper presents a companion localization method that uses the same rotating dipole field for full 6-D pose estimation of a capsule endoscope embedded with a small permanet magnet and an array of magnetic-field sensors. Although several magnetic localization algorithms have been previously published, many are not compatible with magnetic actuation [4, 5]. Those that are require the addition of an accelerometer [6, 7], need a priori knowledge of the capsule’s orientation , provide only 3-D information [6], or must manipulate the position of the external magnetic source during localization [8, 9]. Kim et al. presented an iterative method for use with rotating magnetic fields, but the method contains errors [10]. Our proposed algorithm is less sensitive to data synchronization issues and sensor noise than our previous non-iterative method [11] because the data from the magnetic sensors is incorporated independently (rather than first using sensor data to estimate the field at the center of the capsule’s magnet), and the full pose is solved simultaneously (instead of position and orientation sequentially).
Evaluation of the genotoxic effects of formocresol application in vital pulp therapy of primary teeth: a clinical study and meta-analysis

This in vivo research investigated whether pulp treatments using formocresol for 7 days would cause mutagenic changes in children’s lymphocytes. The mutagenicity was tested in lymphocyte cultures established from the peripheral blood of children living in Brazil. The samples consisted of 2000 cells from teeth undergoing formocresol pulpotomies in which the formocresol pellet was sealed in the primary tooth for 7 days. It was removed on the seventh day, the base was placed, and the tooth was restored. Two venous blood samples (6–8 ml) were collected from each child; the first was prior to pulp therapy, and the second was 7 days later. Two thousand metaphases were analyzed. The level of significance adopted for the statistics was P < 0.05, and a random effects meta-analysis was performed combining this and two previous studies. There was no significant difference found in the metaphase analysis between the blood samples taken before and after the pulpotomy treatment (Wilcoxon signed rank test); however, the meta-analysis showed a significant difference between the combined studies. This study did not reveal any mutagenic effects, but based on the combined meta-analysis, we recommend the careful use of formocresol. This research helps to bring scientific evidence of the safe use of formocresol in deciduous pulpotomy treatments.
Thyroid storm: an updated review.

Thyroid storm, an endocrine emergency first described in 1926, remains a diagnostic and therapeutic challenge. No laboratory abnormalities are specific to thyroid storm, and the available scoring system is based on the clinical criteria. The exact mechanisms underlying the development of thyroid storm from uncomplicated hyperthyroidism are not well understood. A heightened response to thyroid hormone is often incriminated along with increased or abrupt availability of free hormones. Patients exhibit exaggerated signs and symptoms of hyperthyroidism and varying degrees of organ decompensation. Treatment should be initiated promptly targeting all steps of thyroid hormone formation, release, and action. Patients who fail medical therapy should be treated with therapeutic plasma exchange or thyroidectomy. The mortality of thyroid storm is currently reported at 10%. Patients who have survived thyroid storm should receive definite therapy for their underlying hyperthyroidism to avoid any recurrence of this potentially fatal condition.
Adaptive Geometry Image

We present a novel postprocessing utility called adaptive geometry image (AGIM) for global parameterization techniques that can embed a 3D surface onto a rectangular domain. This utility first converts a single rectangular parameterization into many different tessellations of square geometry images (GIMs) and then efficiently packs these GIMs into an image called AGIM. Therefore, undersampled regions of the input parameterization can be up-sampled accordingly until the local reconstruction error bound is met. The connectivity of AGIM can be quickly computed and dynamically changed at rendering time. AGIM does not have T-vertices, and therefore, no crack is generated between two neighboring GIMs at different tessellations. Experimental results show that AGIM can achieve significant PSNR gain over the input parameterization, AGIM retains the advantages of the original GIM and reduces the reconstruction error present in the original GIM technique. The AGIM is also suitable for global parameterization techniques based on quadrilateral complexes. Using the approximate sampling rates, the PolyCube-based quadrilateral complexes with AGIM can outperform state-of-the-art multichart GIM technique in terms of PSNR.
Broncho-biliary fistula secondary to biliary obstruction and lung abscess in a patient with pancreatic neuro-endocrine tumor.

We present a case report of broncho-biliary fistula that developed due to the blockage of biliary stent placed during the management of pancreatic neuroendocrine tumor (pNET); diagnosed on high clinical suspicion, percutaneous cholangiogram and contrast enhanced computed tomography (CECT); and successfully treated with percutaneous transhepatic biliary drainage (PTBD).
Full-Vector Finite-Element Beam Propagation Method for Helicoidal Waveguides and Its Application to Twisted Photonic Crystal Fibers

A full-vector beam propagation method based on a finite-element scheme for a helicoidal system is developed. The permittivity and permeability tensors of a straight waveguide are replaced with equivalent ones for a helicoidal system, obtained by transformation optics. A cylindrical, perfectly matched layer is implemented for the absorbing boundary condition. To treat wide-angle beam propagation, a second-order differentiation term with respect to the propagation direction is directly discretized without using a conventional Padé approximation. The transmission spectra of twisted photonic crystal fibers are thoroughly investigated, and it is found that the diameters of the air holes greatly affect the spectra. The calculated results are in good agreement with the recently reported measured results, showing the validity and usefulness of the method developed here.
Claustrum, consciousness, and time perception

The claustrum has been proposed as a possible neural candidate for the coordination of conscious experience due to its extensive ‘connectome’. Herein we propose that the claustrum contributes to consciousness by supporting the temporal integration of cortical oscillations in response to multisensory input. A close link between conscious awareness and interval timing is suggested by models of consciousness and conjunctive changes in meta-awareness and timing in multiple contexts and conditions. Using the striatal beatfrequency model of interval timing as a framework, we propose that the claustrum integrates varying frequencies of neural oscillations in different sensory cortices into a coherent pattern that binds different and overlapping temporal percepts into a unitary conscious representation. The proposed coordination of the striatum and claustrum allows for time-based dimensions of multisensory integration and decision-making to be incorporated into consciousness.
Concepts of happiness across time and cultures.

We explored cultural and historical variations in concepts of happiness. First, we analyzed the definitions of happiness in dictionaries from 30 nations to understand cultural similarities and differences in happiness concepts. Second, we analyzed the definition of happiness in Webster's dictionaries from 1850 to the present day to understand historical changes in American English. Third, we coded the State of the Union addresses given by U.S. presidents from 1790 to 2010. Finally, we investigated the appearance of the phrases happy nation versus happy person in Google's Ngram Viewer from 1800 to 2008. Across cultures and time, happiness was most frequently defined as good luck and favorable external conditions. However, in American English, this definition was replaced by definitions focused on favorable internal feeling states. Our findings highlight the value of a historical perspective in the study of psychological concepts.