nils-herrmann/clean_scirepeval huggingface dataset:
Automatic Human-like Mining and Constructing Reliable Genetic Association Database with Deep Reinforcement Learning

The increasing amount of scientific literature in biological and biomedical science research has created a challenge in continuous and reliable curation of the latest knowledge discovered, and automatic biomedical text-mining has been one of the answers to this challenge. In this paper, we aim to further improve the reliability of biomedical text-mining by training the system to directly simulate the human behaviors such as querying the PubMed, selecting articles from queried results, and reading selected articles for knowledge. We take advantage of the efficiency of biomedical text-mining, the exibility of deep reinforcement learning, and the massive amount of knowledge collected in UMLS into an integrative artificial intelligent reader that can automatically identify the authentic articles and effectively acquire the knowledge conveyed in the articles. We construct a system, whose current primary task is to build the genetic association database between genes and complex traits of human. Our contributions in this paper are three-fold: 1) We propose to improve the reliability of text-mining by building a system that can directly simulate the behavior of a researcher, and we develop corresponding methods, such as Bi-directional LSTM for text mining and Deep Q-Network for organizing behaviors. 2) We demonstrate the effectiveness of our system with an example in constructing a genetic association database. 3) We release our implementation as a generic framework for researchers in the community to conveniently construct other databases.
Methods for presenting statistical information: {The} box plot

The display of statistical information is ubiquitous in all fields of visualization. Whether aided by graphs, tables, plots, or integrated into the visualizations themselves, understanding the best way to convey statistical information is important. Highlighting the box plot, a survey of traditional methods for expressing specific statistical characteristics of data is presented. Reviewing techniques for the expression of statistical measures will be increasingly important as data quality, confidence and uncertainty are becoming influential characteristics to integrate into visualizations.
Classification of radical hysterectomy adopted by the Gynecological Cancer Group of the European Organization for Research and Treatment of Cancer.

The Piver classification of radical hysterectomy for the treatment of cervical cancer is outdated and misused. The Surgery Committee of the Gynecological Cancer Group of the European Organization for Research and Treatment of Cancer (EORTC) produced, approved, and adopted a revised classification. It is hoped that at least within the EORTC participating centers, a standardization of procedures is achieved. The clinical indications of the new classification are discussed.
A review on switched capacitor converters with high power density for OLED lamp driving

This paper presents a review of high-power-density non-resonant and resonant switched-capacitor (SC) converters topologies for driving organic-lighting-emitting-diode (OLEDs) lamps. These converters are light, small and cheaper in comparison with the linear power supplies and conventional DC-DC converters owing to the avoidance of large magnetic components. Resonant SC (RSC) converters show high efficiency and low EMI noise because they employ a small resonant inductor, which is connected in series with a switched capacitor in order to resonate at a frequency higher than switching frequency, thus allowing them to attain zero-current-switching (ZCS). The bidirectional step-up RSC converter has been identified as one of the best candidates to be used as an OLED driver. Simulation and experimental results from a laboratory prototype designed to supply a 60V 25W OLED lamp from a dc 30 V voltage source are presented.
Adoption of E-Learning in Higher Education : Expansion of UTAUT Model

This research is aimed at identifying the determinants that influence higher educational students’ behavioral intention to utilize elearning systems. The study, therefore, proposed an extension of Unified Theory of Acceptance and use of Technology (UTAUT) model by integrating it with four other variables. Data collected from 264 higher educational students using e-learning systems in Ghana through survey questionnaire were used to test the proposed research model. The study indicated that six variables, Performance expectancy (PE), Effort Expectancy (EE), Social Influence (SI), Facilitating Factor (FF), personal innovativeness (PI) and Study Modes (SM) had significant impact on students’ behavioral intention on e-learning system. The empirical outcome reflects both theoretical and practical consideration in promoting e-learning systems in higher education in Ghana.
Recent advances in polymyalgia rheumatica.

Polymyalgia rheumatica (PMR) is a chronic inflammatory disorder of unknown cause characterised by the subacute onset of shoulder and pelvic girdle pain, and early morning stiffness in men and women over the age of 50 years. Due to the lack of a gold standard investigation, diagnosis is based on a clinical construct and laboratory evidence of inflammation. Heterogeneity in the clinical presentation and disease course of PMR has long been recognised. Aside from the evolution of alternative diagnoses, such as late-onset rheumatoid arthritis, concomitant giant cell arteritis is also recognised in 16-21% of cases. In 2012, revised classification criteria were released by the European League Against Rheumatism and American College of Rheumatology in order to identify a more homogeneous population upon which future studies could be based. In this article, we aim to provide an updated perspective on the pathogenesis and diagnosis of PMR, with particular focus on imaging modalities, such as ultrasound and whole body positron emission tomography/computed tomography, which have advanced our current understanding of this disease. Future treatment directions, based on recognition of the key cytokines involved in PMR, will also be explored.
Integrated Optimization of Airport Taxiway and Runway Scheduling

Capacity limitation of runway and taxiway in an airport is often the major limiting factor of air traffic operation. The congestions on the apron of an airport cause severe delay on aircraft schedule. This paper proposes an integrated algorithm to solve problems of runway scheduling and taxiway routing simultaneously for both departure and arrival aircrafts. A set partitioning model with side constraint is proposed in which each possible aircraft route in the taxiway and runway is regarded as a decision variable. Beside traditional set partitioning constraints, two types of constraints are proposed to maintain a minimum separation distance between aircrafts in the taxiway and runway. The preliminary results show that our integrated algorithm outperforms the sequential method.
The Anatomy of a Design Theory

Design work and design knowledge in Information Systems (IS) is important for both research and practice. Yet there has been comparatively little critical attention paid to the problem of specifying design theory so that it can be communicated, justified, and developed cumulatively. In this essay we focus on the structural components or anatomy of design theories in IS as a special class of theory. In doing so, we aim to extend the work of Walls, Widemeyer and El Sawy (1992) on the specification of information systems design theories (ISDT), drawing on other streams of thought on design research and theory to provide a basis for a more systematic and useable formulation of these theories. We identify eight separate components of design theories: (1) purpose and scope, (2) constructs, (3) principles of form and function, (4) artifact mutability, (5) testable propositions, (6) justificatory knowledge (kernel theories), (7) principles of implementation, and (8) an expository instantiation. This specification includes components missing in the Walls et al. adaptation of Dubin (1978) and Simon (1969) and also addresses explicitly problems associated with the role of instantiations and the specification of design theories for methodologies and interventions as well as for products and applications. The essay is significant as the unambiguous establishment of design knowledge as theory gives a sounder base for arguments for the rigor and legitimacy of IS as an applied discipline and for its continuing progress. A craft can proceed with the copying of one example of a design artifact by one artisan after another. A discipline cannot.
Random eye state change detection in real-time using EEG signals

Maximum and minimum computed across channels is used to monitor the Electroencephalogram signals for possible change of the eye state. Upon detection of a possible change, the last two seconds of the signal is passed through Multivariate Empirical Mode Decomposition and relevant features are extracted. The features are then fed into Logistic Regression and Artificial Neural Network classifiers to confirm the eye state change. The proposed algorithm detects the eye state change with 88.2% accuracy in less than two seconds. This provides a valuable improvement in comparison to a recent procedure that takes about 20 minutes to classify new instances with 97.3% accuracy. The introduced algorithm is promising in the real-time eye state classification as increasing the training examples would increase its accuracy.
Computational Complexity between K-Means and K-Medoids Clustering Algorithms for Normal and Uniform Distributions of Data Points

Clustering is one of the most important research ar eas in the field of data mining. Clustering means creating groups of ob jects based on their features in such a way that th e objects belonging to the same groups are similar an d those belonging to different groups are dissimila r. Clustering is an unsupervised learning technique. T he main advantage of clustering is that interesting patterns and structures can be found directly from very large data sets with little or none of the background knowledge. Clustering algorithms can be applied in many domains.  In this research, the most representative algorithms K-Mean s and K-Medoids were examined and analyzed based on their basic approach. The best algorithm i n each category was found out based on their performance. The input data points are generated by two ways, one by using normal distribution and another by applying uniform distribution.  The randomly distributed data points were taken as input to these algorithms and clusters are found ou t for each algorithm. The algorithms were implement ed using JAVA language and the performance was analyze d based on their clustering quality. The execution time for the algorithms in each category was compar ed for different runs. The accuracy of the algorith m was investigated during different execution of the program on the input data points.  The average time taken by K-Means algorithm is greater than the time taken by K-Medoids algorithm for both the case of normal and uniform distributions. The r esults proved to be satisfactory.
Effectiveness of ultrasound treatment applied with exercise therapy on patients with ankylosing spondylitis: a double-blind, randomized, placebo-controlled trial

The aim of our study was to evaluate effectiveness of ultrasound treatment applied with exercise therapy in patients with ankylosing spondylitis. Fifty-two patients, who were diagnosed according to modified New York criteria, were aged 25–60, and have spine pain, were randomly assigned to two groups. Ultrasound (US) and exercise therapy were applied to treatment group (27); placebo US treatment and exercise therapy were applied to control group (25). Patients were evaluated before treatment, at the end of treatment, and 4 weeks after the treatment. Daily and night pain, morning stiffness, patient global assessment (PGA), doctor global assessment (DGA), Bath Ankylosing Spondylitis Disease Activity Index (BASDAI), Bath Ankylosing Spondylitis Functional Index (BASFI), Bath Ankylosing Spondylitis Metrology Index (BASMI), Ankylosing Spondylitis Quality of Life (ASQoL) questionnaire, Ankylosing Spondylitis Disease Activity Score (ASDAS) erythrocyte sedimentation rate (ESR), and ASDAS C-reactive protein (CRP) were used as clinical parameters. In US group, all parameters showed significant improvements at 2 and 6 weeks, in comparison with the baseline. In placebo US group, significant improvement was obtained for all parameters (except tragus-to-wall distance and modified Schober test at 2 weeks and lumbar side flexion and modified Schober test at 6 weeks). Comparison of the groups showed significantly superior results of US group for parameters of BASMI (p < 0.05), tragus–wall distance (p < 0.05), PGA (p < 0.01), and DGA (p < 0.05) at 2 weeks as well as for the parameters of daily pain (p < 0.01), PGA (p < 0.05), DGA (p < 0.01), BASDAI (p < 0.05), ASDAS-CRP (p < 0.05), ASDAS-ESR (p < 0.01), lumbar side flexion (p < 0.01), the modified Schober test (p < 0.01), and ASQoL (p < 0.05) at 6 weeks. Our study showed that ultrasound treatment increases the effect of exercise in patients with ankylosing spondylitis.
Exosomal miR-21-5p derived from gastric cancer promotes peritoneal metastasis via mesothelial-to-mesenchymal transition

Peritoneal metastasis is a primary metastatic route for gastric cancers, and the mechanisms underlying this process are still unclear. Peritoneal mesothelial cells (PMCs) undergo mesothelial-to-mesenchymal transition (MMT) to provide a favorable environment for metastatic cancer cells. In this study, we investigated how the exosomal miR-21-5p induces MMT and promotes peritoneal metastasis. Gastric cancer (GC)-derived exosomes were identified by transmission electron microscopy and western blot analysis, then the uptake of exosomes was confirmed by PKH-67 staining. The expression of miR-21-5p and SMAD7 were measured by quantitative real-time polymerase chain reaction (qRT-PCR) and western blot, and the interactions between miR-21-5p and its target genes SMAD7 were confirmed by Luciferase reporter assays. The MMT of PMCs was determined by invasion assays, adhesion assays, immunofluorescent assay, and western blot. Meanwhile, mouse model of tumor peritoneal dissemination model was performed to investigate the role of exosomal miR-21-5p in peritoneal metastasis in vivo. We found that PMCs could internalize GC-derived exosomal miR-21-5p and led to increased levels of miR-21-5p in PMCs. Through various types of in vitro and in vivo assays, we confirmed that exosomal miR-21-5p was able to induce MMT of PMCs and promote tumor peritoneal metastasis. Moreover, our study revealed that this process was promoted by exosomal miR-21-5p through activating TGF-β/Smad pathway via targeting SMAD7. Altogether, our data suggest that exosomal miR-21-5p induces MMT of PMCs and promote cancer peritoneal dissemination by targeting SMAD7. The exosomal miR-21-5p may be a novel therapeutic target for GC peritoneal metastasis.
Suicide of a man with known allergy to fish protein by ingesting tinned fish.

On a day in November, the body of a 31-year-old man was found near a swimming lake with two open and partly emptied fish tins lying next to him. Further investigations showed that the man had been allergic to fish protein and suffered from severe depression and drug psychosis. Already some days before the suicide, he had repeatedly asked for fish to kill himself. Although the results of the chemical and toxicological examinations were negative, the autopsy findings and histological tests suggest that death was caused by an anaphylactic reaction.
Congenital malformations: from superstition to understanding

Throughout most of human history, congenital anomalies were perceived as omens, portents, or punishments of supernatural origin. This concept is reflected in the term “monster,” probably derived from the Latin verb monstrare (to show or reveal). Other explanations for congenital abnormalities included witchcraft, astrological configurations, or emotional experiences of the pregnant mother. Malformed humans and animals also inspired many of the characters populating the literature, mythology, art, and religion of every culture. By the eighteenth century superstition still dominated public conceptions of malformations, but this topic was beginning to attract serious attention from physicians and scientists. Abnormalities such as conjoined twins were a popular subject for anatomists, who produced some superb morphological studies. However, scientific investigation of causes and mechanisms of abnormal development were delayed because of persisting support for the concept of preformation of embryos. Toward the end of the century, epigenesis finally achieved acceptance by leading scientists, opening the door to the investigation of normal and abnormal development. By the dawn of the nineteenth century, a foundation had been established for the study of abnormal development, which was destined to become one of the most productive of biomedical sciences. The ultimate mechanisms of normal and abnormal development are now explored at the molecular level, and the lives of countless individuals born with malformations have been greatly enhanced by advances in medicine and surgery. No other biomedical science provides a more colorful and instructive illustration of the long journey from superstition to understanding. The older literature in this field, in addition to its historical interest, is a source of knowledge and information of unique value for scientists and practitioners.
The Mobile MAV concept for Mars Sample Return

Mars Sample Return (MSR) is the highest priority planetary science objective as identified in the Planetary Science Decadal Survey. To return a sample to Earth would require the accomplishment of several critical steps in the collection and transfer of the sample from the surface of Mars to the surface of the Earth. While there are many architectures and approaches to returning a sample of Martian surface material to the Earth, the current architecture includes the following series of missions: (1) a sample caching mission which would scientifically select, acquire and cache the sampled material on the surface of Mars, (2) a sample retrieval mission which would collect the sample from the surface and place it into Mars orbit, and (3) a Sample return orbiter which would rendezvous with the sample and return it to Earth. A fourth element of the architecture, the Mars Returned Sample Handling facility (MRSH) would be developed to receive the returned sample and provide for the sample analysis and curation. The Mobile MAV concept is an approach to the sample retrieval and launch element of the architecture. The design concept that was extant during the Decadal Survey studies featured a stationary platform lander, which would land a small fetch rover to retrieve the sample cache (collected by the previous mission), and the Mars Ascent Vehicle (MAV), which would inject the sample cache into Mars orbit. MSL's success in demonstrating a new Entry, Descent, and Landing architecture, which placed the rover directly on the surface in a mobility touchdown configuration, motivates a closer assessment of a MSL class rover which is capable of supporting the MAV and retrieving the cached samples. This architecture eliminates the need for a return trip to a stationary lander, which would be required of a fetch rover in the Decadal Survey mission architecture, significantly reducing the required surface mission duration and traverse requirements.
From archetypes-based domain model of clinical laboratory to LIMS software

We present our approach for developing a laboratory information management system (LIMS) software by combining Björners software triptych methodology (from domain models via requirements to software) with Arlow and Neustadt archetypes and archetype patterns based initiative. The fundamental hypothesis is that through this Archetypes Based Development (ABD) approach to domains, requirements and software, it is possible to improve the software development process as well as to develop more dependable software. We use ADB in developing LIMS software for the Clinical and Biomedical Proteomics Group (CBPG), University of Leeds.
BLSTM-RNN Based 3D Gesture Classification

This paper presents a new robust method for inertial MEM (MicroElectroMechanical systems) 3D gesture recognition. The linear acceleration and the angular velocity, respectively provided by the accelerometer and the gyrometer, are sampled in time resulting in 6D values at each time step which are used as inputs for the gesture recognition system. We propose to build a system based on Bidirectional Long ShortTerm Memory Recurrent Neural Networks (BLSTM-RNN) for gesture classification from raw MEM data. We also compare this system to a geometric approach using DTW (Dynamic Time Warping) and a statistical method based on HMM (Hidden Markov Model) from filtered and denoised MEM data. Experimental results on 22 individuals producing 14 gestures in the air show that the proposed approach outperforms classical classification methods with a classification mean rate of 95.57% and a standard deviation of 0.50 for 616 test gestures. Furthermore, these experiments underline that combining accelerometer and gyrometer information gives better results that using a single inertial description.
Are "Facebook Murders" a Growing Trend?

Is Facebook becoming a place where people mistakenly think they can literally get away with murder? In a 2011 Facebook murder-for-hire case in Philadelphia, PA, a 19-yearold mother offered $1,000 on Facebook to kill her 22-year-old boyfriend, the father of her 2-year-old daughter. The boyfriend was killed while the only two suspects responding to the mother’s post were in custody, so there is speculation that the murder was drug related. The mother pleaded guilty to conspiracy to commit murder, and was immediately paroled on a 3to 23-month sentence. Other ‘‘Facebook murder’’ perpetrators are being brought to justice, one way or another:
Learning to Optimize via Wasserstein Deep Inverse Optimal Control

We study the inverse optimal control problem in social sciences: we aim at learning a user’s true cost function from the observed temporal behavior. In contrast to traditional phenomenological works that aim to learn a generative model to fit the behavioral data, we propose a novel variational principle and treat user as a reinforcement learning algorithm, which acts by optimizing his cost function. We first propose a unified KL framework that generalizes existing maximum entropy inverse optimal control methods. We further propose a two-step Wasserstein inverse optimal control framework. In the first step, we compute the optimal measure with a novel mass transport equation. In the second step, we formulate the learning problem as a generative adversarial network. In two real world experiments — recommender systems and social networks, we show that our framework obtains significant performance gains over both existing inverse optimal control methods and point process based generative models.
Implementation of a zero voltage switching Sepic-Cuk converter

This paper presents the system analysis and implementation of a soft switching Sepic-Cuk converter to achieve zero voltage switching (ZVS). In the proposed converter, the Sepic and Cuk topologies are combined together in the output side. The features of the proposed converter are to reduce the circuit components (share the power components in the transformer primary side) and to share the load current. Active snubber is connected in parallel with the primary side of transformer to release the energy stored in the leakage inductor of transformer and to limit the peak voltage stress of switching devices when the main switch is turned off. The active snubber can achieve ZVS turn-on for power switches. Experimental results, taken from a laboratory prototype rated at 300W, are presented to verify the effectiveness of the proposed converter.  Modern