nils-herrmann/clean_scirepeval huggingface dataset:
Gut microbiota in health and disease.

Gut microbiota is an assortment of microorganisms inhabiting the length and width of the mammalian gastrointestinal tract. The composition of this microbial community is host specific, evolving throughout an individual's lifetime and susceptible to both exogenous and endogenous modifications. Recent renewed interest in the structure and function of this "organ" has illuminated its central position in health and disease. The microbiota is intimately involved in numerous aspects of normal host physiology, from nutritional status to behavior and stress response. Additionally, they can be a central or a contributing cause of many diseases, affecting both near and far organ systems. The overall balance in the composition of the gut microbial community, as well as the presence or absence of key species capable of effecting specific responses, is important in ensuring homeostasis or lack thereof at the intestinal mucosa and beyond. The mechanisms through which microbiota exerts its beneficial or detrimental influences remain largely undefined, but include elaboration of signaling molecules and recognition of bacterial epitopes by both intestinal epithelial and mucosal immune cells. The advances in modeling and analysis of gut microbiota will further our knowledge of their role in health and disease, allowing customization of existing and future therapeutic and prophylactic modalities.
Cardiovascular Involvement in Erdheim–Chester Disease

Erdheim-Chester disease (ECD) is a rare, multiorgan, non-Langerhans cell histiocytosis of uncertain origin, characterized by systemic xanthogranulomatous infiltration from CD68+CD1a- histiocytes. Skeletal involvement is present in up to 96% of cases with bilateral osteosclerosis of meta-diaphysis of long bones. Furthermore, in more than 50% of cases there is 1 extraskeletal manifestation. In this case report, we describe an interesting case of ECD with an extensive pan-cardiac and vascular involvement, in addition to skeletal, retro-orbital, and retroperitoneum one.A 44-year-old woman with a long history of exophthalmos referred to our hospital for elective surgical orbital decompression. At preoperative examinations a large pericardial effusion was discovered. Echocardiography, computed tomography (CT), and magnetic resonance imaging (MRI) described an inhomogeneous mass involving pericardium and the right heart, abdominal aorta and its main branches and the retroperitoneum, suggestive for a systemic inflammatory disorder. Histological examination on a biopsy sample confirmed the diagnosis of ECD. Radiology showed the pathognomonic long-bone involvement. Surgical orbital decompression was performed and medical therapy with interferon-α (INF-α) was started.Among extraskeletal manifestations of ECD, cardiovascular involvement is often asymptomatic and thus under-diagnosed but linked to poor prognosis. This is why clinician should always look for it when a new case of ECD is diagnosed.
Temporal Patterns of Scientific Evolution : A Case Study in SOFSEM Conference

A rising issue in the scientific community entails the identification of patterns in the evolution of the scientific enterprise and the emergence of trends that influence scholarly impact. In this direction, this paper investigates the mechanism with which citation accumulation occurs over time and how this affects the overall impact of scientific output. Utilizing data regarding the SOFSEM Conference (International Conference on Current Trends in Theory and Practice of Computer Science), we study a corpus of 1006 publications with their associated authors and affiliations to uncover the effects of collaboration on the conference output. We proceed to group publications into clusters based on the trajectories they follow in their citation acquisition. Representative patterns are identified to characterize dominant trends of the conference, while exploring phenomena of early and late recognition by the scientific community and their correlation with impact.
Designing high-quality interactive multimedia learning modules.

Modern research has broadened scientific knowledge and revealed the interdisciplinary nature of the sciences. For today's students, this advance translates to learning a more diverse range of concepts, usually in less time, and without supporting resources. Students can benefit from technology-enhanced learning supplements that unify concepts and are delivered on-demand over the Internet. Such supplements, like imaging informatics databases, serve as innovative references for biomedical information, but could improve their interaction interfaces to support learning. With information from these digital datasets, multimedia learning tools can be designed to transform learning into an active process where students can visualize relationships over time, interact with dynamic content, and immediately test their knowledge. This approach bridges knowledge gaps, fosters conceptual understanding, and builds problem-solving and critical thinking skills-all essential components to informatics training for science and medicine. Additional benefits include cost-free access and ease of dissemination over the Internet or CD-ROM. However, current methods for the design of multimedia learning modules are not standardized and lack strong instructional design. Pressure from administrators at the top and students from the bottom are pushing faculty to use modern technology to address the learning needs and expectations of contemporary students. Yet, faculty lack adequate support and training to adopt this new approach. So how can faculty learn to create educational multimedia materials for their students? This paper provides guidelines on best practices in educational multimedia design, derived from the Virtual Labs Project at Stanford University. The development of a multimedia module consists of five phases: (1) understand the learning problem and the users needs; (2) design the content to harness the enabling technologies; (3) build multimedia materials with web style standards and human factors principles; (4) user testing; (5) evaluate and improve design.
ProCRob Architecture for Personalized Social Robotics Extended Abstract

For robot tutors, autonomy and personalizations are important factors in order to engage users as well as to personalize the content and interaction according to the needs of individuals. is paper presents the Programming Cognitive Robot (ProCRob) soware architecture to target personalized social robotics in two complementary ways. ProCRob supports the development and personalization of social robot applications by teachers and therapists without computer programming background. It also supports the development of autonomous robots which can adapt according to the human-robot interaction context. ProCRob is based on our previous research on autonomous robotics and has been developed since 2015 by a multi-disciplinary team of researchers from the elds of AI, Robotics and Psychology as well as artists and designers at the University of Luxembourg. ProCRob is currently being used and further developed for therapy of children with autism, and for encouraging rehabilitation activities in patients with post-stroke. is paper presents a summary of ProCRob and its application in autism.
Hypoadiponectinemia in obesity and type 2 diabetes: close association with insulin resistance and hyperinsulinemia.

Plasma concentrations of adiponectin, a novel adipose-specific protein with putative antiatherogenic and antiinflammatory effects, were found to be decreased in Japanese individuals with obesity, type 2 diabetes, and cardiovascular disease, conditions commonly associated with insulin resistance and hyperinsulinemia. To further characterize the relationship between adiponectinemia and adiposity, insulin sensitivity, insulinemia, and glucose tolerance, we measured plasma adiponectin concentrations, body composition (dual-energy x-ray absorptiometry), insulin sensitivity (M, hyperinsulinemic clamp), and glucose tolerance (75-g oral glucose tolerance test) in 23 Caucasians and 121 Pima Indians, a population with a high propensity for obesity and type 2 diabetes. Plasma adiponectin concentration was negatively correlated with percent body fat (r = -0.43), waist-to-thigh ratio (r = -0.46), fasting plasma insulin concentration (r = -0.63), and 2-h glucose concentration (r = -0.38), and positively correlated with M (r = 0.59) (all P < 0.001); all relations were evident in both ethnic groups. In a multivariate analysis, fasting plasma insulin concentration, M, and waist-to-thigh ratio, but not percent body fat or 2-h glucose concentration, were significant independent determinates of adiponectinemia, explaining 47% of the variance (r(2) = 0.47). Differences in adiponectinemia between Pima Indians and Caucasians (7.2 +/- 2.6 vs. 10.2 +/- 4.3 microg/ml, P < 0.0001) and between Pima Indians with normal, impaired, and diabetic glucose tolerance (7.5 +/- 2.7, 6.1 +/- 2.0, 5.5 +/- 1.6 microg/ml, P < 0.0001) remained significant after adjustment for adiposity, but not after additional adjustment for M or fasting insulin concentration. These results confirm that obesity and type 2 diabetes are associated with low plasma adiponectin concentrations in different ethnic groups and indicate that the degree of hypoadiponectinemia is more closely related to the degree of insulin resistance and hyperinsulinemia than to the degree of adiposity and glucose intolerance.
Categorizing Obstacles in e-Government: Formal and Informal

E-Government implementation and adoption is influenced by several factors having either an enhancing or an aggravating effect on e-government implementation and use. This paper aims at shedding light on obstacles hindering mainly e-government implementation from two perspectives: the supply- and the demand-side of e-government services. The contribution to research is seen in summarized insights into what obstacles in e-government were identified in prior research and the suggestion of a classification of obstacles into the two categories of formal and informal obstacles. Literature was reviewed following a conceptual model encompassing a merger and extension of existing approaches. A process of identifying obstacles and improving services in the form of a loop is discussed before possible future research lines will be pointed to.
Eye movement desensitization and reprocessing (EMDR) in the treatment of war veterans.

Recent practice guidelines and meta-analyses have designated eye movement desensitization and reprocessing (EMDR) as a first-line treatment for trauma. Eye movement desensitization and reprocessing is an eight-phase therapeutic approach guided by an information-processing model that addresses the combat veteran's critical incidents, current triggers, and behaviors likely to prove useful in his or her future. Two case examples of combat veterans illustrate the ability of EMDR to achieve symptom reduction in a variety of clinical domains (e.g., anxiety, depression, anger, physical pain) simultaneously without requiring the patient to carry out homework assignments or discuss the details of the event. The treatment of phantom limb pain and other somatic presentations is also reviewed. The ability of EMDR to achieve positive effects without homework indicates that it can be effectively employed on consecutive days, making it especially useful during combat situations.
Integration of GMR Sensors with Different Technologies

Less than thirty years after the giant magnetoresistance (GMR) effect was described, GMR sensors are the preferred choice in many applications demanding the measurement of low magnetic fields in small volumes. This rapid deployment from theoretical basis to market and state-of-the-art applications can be explained by the combination of excellent inherent properties with the feasibility of fabrication, allowing the real integration with many other standard technologies. In this paper, we present a review focusing on how this capability of integration has allowed the improvement of the inherent capabilities and, therefore, the range of application of GMR sensors. After briefly describing the phenomenological basis, we deal on the benefits of low temperature deposition techniques regarding the integration of GMR sensors with flexible (plastic) substrates and pre-processed CMOS chips. In this way, the limit of detection can be improved by means of bettering the sensitivity or reducing the noise. We also report on novel fields of application of GMR sensors by the recapitulation of a number of cases of success of their integration with different heterogeneous complementary elements. We finally describe three fully functional systems, two of them in the bio-technology world, as the proof of how the integrability has been instrumental in the meteoric development of GMR sensors and their applications.
Resilient architecture pathways to establish and operate a pioneering base on Mars

We outline an architecture pathway to establish a permanent base on Mars that can support a 50-person crew. After base establishment, a long-term colony is formed with a gradual reduction in support and supplies from Earth. A steady cadence of missions is used to validate new technologies, build capabilities, reduce risks, and minimize costs. The missions prior to 2050 include assembly of an interplanetary vehicle in lunar vicinity, a deep space mission, a Mars orbital mission, and two Mars surface missions. We also examine the logistics associated with the base's growth in personnel, capability, and operations to the year 2100. Using a human exploration cost tool developed at Purdue, we find a peak yearly spending of $14.9 billion in 2030 with an average cost of $11.8 billion per year until 2050 and $8.2 billion per year after 2050. Assuming a starting budget of $9 billion per year (2016 NASA human spaceflight budget), an 8.8% increase per year from 2018 to 2024 would be required to meet the peak yearly costs. Unfortunately, such an increase is unlikely given NASA's relatively flat inflation-adjusted budget over the past 20 years. In addition, while commercial launch vehicle costs are dropping due to the emergence of reusable launch vehicles (e.g. SpaceX's Falcon 9), hardware costs are yet to reduce within NASA and their contractors, which suggests one or more of the following scenarios: 1) NASA must change how program costs are managed, 2) the publicized timeline for humans landing on Mars must slip, or 3) a new Mars architecture paradigm must be found.
Body Image of Greek Breast Cancer Patients Treated with Mastectomy or Breast Conserving Surgery

The aim of this study was to assess and compare the body image of breast cancer patients (n = 70) whom underwent breast conserving surgery or mastectomy, as well as to compare patients’ scores with that of a sample of healthy control women (n = 70). A secondary objective of this study was to examine the reliability and validity of the 10-item Greek version of the Body Image Scale, a multidimensional measure of body image changes and concerns. Exploratory and confirmatory factor analyses on the items of this scale resulted in a two factor solution, indicating perceived attractiveness, and body and appearance satisfaction. Comparison of the two surgical groups revealed that women treated with mastectomy felt less attractive and more self-conscious, did not like their overall appearance, were dissatisfied with their scar, and avoided contact with people. Hierarchical regression analysis showed that more general body image concerns were associated with belonging to the mastectomy group, compared to the cancer-free group of women. Implications for clinical practice and recommendations for future investigations are discussed.
Generating Finite-State Transducers for Semi-Structured Data Extraction from the Web

| Integrating a large number of Web information sources may signiicantly increase the utility of the WorldWide Web. A promising solution to the integration is through the use of a Web Information mediator that provides seamless, transparent access for the clients. Information mediators need wrappers to access a Web source as a structured database, but building wrappers by hand is impractical. Previous work on wrapper induction is too restrictive to handle a large number of Web pages that contain tuples with missing attributes, multiple values, variant attribute permutations, exceptions and typos. This paper presents SoftMealy, a novel wrapper representation formalism. This representation is based on a nite-state transducer (FST) and contextual rules. This approach can wrap a wide range of semistructured Web pages because FSTs can encode each diierent attribute permutation as a path. A SoftMealy wrapper can be induced from a handful of labeled examples using our generalization algorithm. We have implemented this approach into a prototype system and tested it on real Web pages. The performance statistics shows that the sizes of the induced wrappers as well as the required training eeort are linear with regard to the structural variance of the test pages. Our experiment also shows that the induced wrappers can generalize over unseen pages.
Software defined environments: An introduction

An introduction C.-S. Li B. L. Brech S. Crowder D. M. Dias H. Franke M. Hogstrom D. Lindquist G. Pacifici S. Pappe B. Rajaraman J. Rao R. P. Ratnaparkhi R. A. Smith M. D. Williams During the past few years, enterprises have been increasingly aggressive in moving mission-critical and performance-sensitive applications to the cloud, while at the same time many new mobile, social, and analytics applications are directly developed and operated on cloud computing platforms. These two movements are encouraging the shift of the value proposition of cloud computing from cost reduction to simultaneous agility and optimization. These requirements (agility and optimization) are driving the recent disruptive trend of software defined computing, for which the entire computing infrastructureVcompute, storage and networkVis becoming software defined and dynamically programmable. The key elements within software defined environments include capability-based resource abstraction, goal-based and policy-based workload definition, and outcome-based continuous mapping of the workload to the available resources. Furthermore, software defined environments provide the tooling and capabilities to compose workloads from existing components that are then continuously and autonomously mapped onto the underlying programmable infrastructure. These elements enable software defined environments to achieve agility, efficiency, and continuous outcome-optimized provisioning and management, plus continuous assurance for resiliency and security. This paper provides an overview and introduction to the key elements and challenges of software defined environments.
Know Your Mind: Adaptive Brain Signal Classification with Reinforced Attentive Convolutional Neural Networks

Electroencephalography (EEG) signals reect activities on certain brain areas. Eective classication of time-varying EEG signals is still challenging. First, EEG signal processing and feature engineering are time-consuming and highly rely on expert knowledge. In addition, most existing studies focus on domain-specic classication algorithms which may not be applicable to other domains. Moreover, the EEG signal usually has a low signal-to-noise ratio and can be easily corrupted. In this regard, we propose a generic EEG signal classication framework that accommodates a wide range of applications to address the aforementioned issues. e proposed framework develops a reinforced selective aention model to automatically choose the distinctive information among the raw EEG signals. A convolutional mapping operation is employed to dynamically transform the selected information to an over-complete feature space, wherein implicit spatial dependency of EEG samples distribution is able to be uncovered. We demonstrate the eectiveness of the proposed framework using three representative scenarios: intention recognition with motor imagery EEG, person identication, and neurological diagnosis. ree widely used public datasets and a local dataset are used for our evaluation. e experiments show that our framework outperforms the state-of-the-art baselines and achieves the accuracy of more than 97% on all the datasets with low latency and good resilience of handling complex EEG signals across various domains. ese results conrm the suitability of the proposed generic approach for a range of problems in the realm of Brain-Computer Interface applications.
Long-loop reflex from arm afferents to remote muscles in normal man

The present study was designed to examine the effects of median nerve stimulation on motoneurones of remote muscles in healthy subjects using H-reflex, averaged EMG and PSTH methods. Stimulation of the median nerve induced facilitation of soleus H-reflex from about 50 ms and it reached a peak at about 100 ms of conditioning-test interval. Afferents that induced the facilitation consisted of at least two types of fibres, the high-threshold cutaneous fibres and the low-threshold fibres. When the effects were examined by the averaged surface EMG and PSTH, no facilitation but rather inhibition or inhibition-facilitation was induced in all tested muscles except for the upper limb muscles on the stimulated side. The inhibition latency was shortest in masseter muscle and longest in leg muscles, while values for the contralateral upper limb muscles were in the middle, indicating that the onset of inhibition was delayed from rostral to caudal muscles. Inputs from the median nerve converged to inhibitory interneurones, which mediate the masseter inhibitory reflex. Our findings suggested that inputs from the median nerve initially ascend to the brain, at least to the brainstem, and then descend to the spinal cord. Therefore, inhibition induced by median nerve stimulation was not considered as an interlimb reflex mediated by a propriospinal pathway, but long-loop reflex, at least via the pons. The discrepancy between the results of reflex and motor units suggests that facilitation of soleus H-reflex following median nerve stimulation was mainly due to reduced presynaptic inhibition.
Modelling Information Needs in Collaborative Search Conversations

The increase of voice-based interaction has changed the way people seek information, making search more conversational. Development of effective conversational approaches to search requires better understanding of how people express information needs in dialogue. This paper describes the creation and examination of over 32K spoken utterances collected during 34 hours of collaborative search tasks. The contribution of this work is three-fold. First, we propose a model of conversational information needs (CINs) based on a synthesis of relevant theories in Information Seeking and Retrieval. Second, we show several behavioural patterns of CINs based on the proposed model. Third, we identify effective feature groups that may be useful for detecting CINs categories from conversations. This paper concludes with a discussion of how these findings can facilitate advance of conversational search applications.
Edge detection using adaptive thresholding and Ant Colony Optimization

In this paper, we present an approach for edge detection using adaptive thresholding and Ant Colony Optimization (ACO) algorithm to obtain a well-connected image edge map. Initially, the edge map of the image is obtained using adaptive thresholding. The end points obtained using adaptive threshoding are calculated and the ants are placed at these points. The movement of the ants is guided by the local variation in the pixel intensity values. The probability factor of only undetected neighboring pixels is taken into consideration while moving an ant to the next probable edge pixel. The two stopping rules are implemented to prevent the movement of ants through the pixel already detected using the adoptive thresholding. The results are qualitative analyze using Shanon's Entropy function.