nils-herrmann/clean_scirepeval huggingface dataset:
SediFoam: A general-purpose, open-source CFD-DEM solver for particle-laden flow with emphasis on sediment transport

With the growth of available computational resource, CFD–DEM (computational fluid dynamics–discrete element method) becomes an increasingly promising and feasible approach for the study of sediment transport. Several existing CFD–DEM solvers are applied in chemical engineering and mining industry. However, a robust CFD–DEM solver for the simulation of sediment transport is still desirable. In this work, the development of a threedimensional, massively parallel, and open-source CFD–DEM solver SediFoam is detailed. This solver is built based on open-source solvers OpenFOAM and LAMMPS. OpenFOAM is a CFD toolbox that can perform three-dimensional fluid flow simulations on unstructured meshes; LAMMPS is a massively parallel DEM solver for molecular dynamics. Several validation tests of SediFoam are performed using cases of a wide range of complexities. The results obtained in the present simulations are consistent with those in the literature, which demonstrates the capability of SediFoam for sediment transport applications. In addition to the validation test, the parallel efficiency of SediFoam is studied to test the performance of the code for large-scale and complex simulations. The parallel efficiency tests show that the scalability of SediFoam is satisfactory in the simulations using up to O(10) particles.
A Reduced feature based neural network approach to classify the category of students

To ensure more effectiveness in the learning process in educational institutions, categorization of students is a very interesting method to enhance student's learning capabilities by identifying the factors that affect their performance and use their categories to design targeted inventions for improving their quality. Many research works have been conducted on student performances, to improve their grades and to stop them from dropping out from school by using a data driven approach  . In this paper, we have proposed a new model to categorize students into 3 categories to determine their learning capabilities and to help them to improve their studying techniques. We have chosen the state of the art of machine learning approach to classify student's nature of study by selecting prominent features of their activity in their academic field. We have chosen a data driven approach where key factors that determines the base of student and classify them into high, medium and low ranks. This process generates a system where we can clearly identify the crucial factors for which they are categorized. Manual construction of student labels is a difficult approach. Therefore, we have come up with a student categorization model on the basis of selected features which are determined by the preprocessing of Dataset and implementation of Random Forest Importance; Chi2 algorithm; and Artificial Neural Network algorithm. For the research we have used Python's Machine Learning libraries: Scikit-Learn . For Deep Learning paradigm we have used Tensor-Flow, Keras. For data processing Pandas library and Matplotlib and Pyplot has been used for graph visualization purpose.
A high-power 200 kV power supply for capacitor charging applications

Development and testing of a compact 200-kV, 10-kJ/s industrial-grade power supply for capacitor charging applications is described. Pulse repetition rate (PRR) can be from single shot to 250 Hz, depending on the storage capacitance. Energy dosing (ED) topology enables high efficiency at switching frequency of up to 55 kHz using standard slow IGBTs. Circuit simulation examples are given. They clearly show zero-current switching at variable frequency during the charge set by the ED governing equations. Peak power drawn from the primary source is about only 60% higher than the average power, which lowers the stress on the input rectifier. Insulation design was assisted by electrostatic field analyses. Field plots of the main transformer insulation illustrate field distribution and stresses in it. Subsystem and system tests were performed including limited insulation life test. A precision, high-impedance, fast HV divider was developed for measuring voltages up to 250 kV with risetime down to 10 μs. The charger was successfully tested with stored energy of up to 550 J at discharge via a custom designed open-air spark gap at PRR up to 20 Hz (in bursts). Future work will include testing at customer sites.
On the prospects of full-duplex military radios

In-band full-duplex (FD) operation can be regarded as one of the greatest discoveries in civilian/commercial wireless communications so far in this century. The concept is significant because it can as much as double the spectral efficiency of wireless data transmission by exploiting the new-found capability for simultaneous transmission and reception (STAR) that is facilitated by advanced self-interference cancellation (SIC) techniques. As the first of its kind, this paper surveys the prospects of exploiting the emerging FD radio technology in military communication applications as well. In addition to spectrally efficient two-way data transmission, the STAR capability could give a major technical advantage for armed forces by allowing their radio transceivers to conduct electronic warfare at the same time when they are also receiving or transmitting information signals at the same frequency band. After providing a detailed introduction to FD transceiver architectures and SIC requirements in military communications, this paper outlines and analyzes some potential defensive and offensive applications of the STAR capability.
A Single-Stage Integrated Boost-LLC AC–DC Converter With Quasi-Constant Bus Voltage for Multichannel LED Street-Lighting Applications

Single-stage boost-LLC ac–dc converters are popularly utilized as the front-end stage of multichannel LED street-lighting drivers. Pulse frequency modulation (PFM) strategy with a duty cycle of 0.5 is commonly utilized in these ac–dc converters. However, PFM has the following drawbacks: 1) high bus voltage limits the ac input voltage range, which makes it only suitable for the input voltage range of 85~135 V and 2) the maximum bus voltage can reach up to three times of the minimum bus voltage, which increases the difficulty of the LLC design. This paper proposed a hybrid modulation strategy, which consists of a bus voltage control loop using asymmetric pulsewidth modulation and an output voltage control loop using PFM. The stable output voltage and the quasi-constant bus voltage can be simultaneously achieved. Furthermore, by increasing bus voltage ripple and employing the twin-bus configuration, the short-lifetime electrolytic capacitors are eliminated, and the efficiency of the total LED driver can be greatly improved. Therefore, universal-input operation, high efficiency, low cost, and long lifetime are the key innovations of the proposed solution. A universal-input 100-W prototype is built to demonstrate the feature of the proposed solution. The experimental results show that the converter achieves a peak efficiency of 92.5% at the input voltage of 130 V and a high power factor value of above 0.95 over the whole input voltage range. With the proposed modulation strategy, the maximum bus voltage is just 500 V under universal input voltage condition, which is greatly lower than that of the traditional PFM controlled boost-LLC converters.
A Role for the Superior Colliculus in Decision Criteria

Simple decisions arise from the evaluation of sensory evidence. But decisions are determined by more than just evidence. Individuals establish internal decision criteria that influence how they respond. Where or how decision criteria are established in the brain remains poorly understood. Here, we show that neuronal activity in the superior colliculus (SC) predicts changes in decision criteria. Using a novel "Yes-No" task that isolates changes in decision criterion from changes in decision sensitivity, and computing neuronal measures of sensitivity and criterion, we find that SC neuronal activity correlates with the decision criterion regardless of the location of the choice report. We also show that electrical manipulation of activity within the SC produces changes in decisions consistent with changes in decision criteria and are largely independent of the choice report location. Our correlational and causal results together provide strong evidence that SC activity signals the position of a decision criterion.
Multiview Physician-Specific Attributes Fusion for Health Seeking

Community-based health services have risen as important online resources for resolving users health concerns. Despite the value, the gap between what health seekers with specific health needs and what busy physicians with specific attitudes and expertise can offer is being widened. To bridge this gap, we present a question routing scheme that is able to connect health seekers to the right physicians. In this scheme, we first bridge the expertise matching gap via a probabilistic fusion of the physician-expertise distribution and the expertise-question distribution. The distributions are calculated by hypergraph-based learning and kernel density estimation. We then measure physicians attitudes toward answering general questions from the perspectives of activity, responsibility, reputation, and willingness. At last, we adaptively fuse the expertise modeling and attitude modeling by considering the personal needs of the health seekers. Extensive experiments have been conducted on a real-world dataset to validate our proposed scheme.
One-Step or Two-Step Optimization and the Overfitting Phenomenon: A Case Study on Time Series Classification

For the last few decades, optimization has been developing at a fast rate. Bio-inspired optimization algorithms are metaheuristics inspired by nature. These algorithms have been applied to solve different problems in engineering, economics, and other domains. Bio-inspired algorithms have also been applied in different branches of information technology such as networking and software engineering. Time series data mining is a field of information technology that has its share of these applications too. In previous works we showed how bio-inspired algorithms such as the genetic algorithms and differential evolution can be used to find the locations of the breakpoints used in the symbolic aggregate approximation of time series representation, and in another work we showed how we can utilize the particle swarm optimization, one of the famous bio-inspired algorithms, to set weights to the different segments in the symbolic aggregate approximation representation. In this paper we present, in two different approaches, a new meta optimization process that produces optimal locations of the breakpoints in addition to optimal weights of the segments. The experiments of time series classification task that we conducted show an interesting example of how the overfitting phenomenon, a frequently encountered problem in data mining which happens when the model overfits the training set, can interfere in the optimization process and hide the superior performance of an optimization algorithm.
“Orthotopic” ossiculum terminale persistens and atlantoaxial instability in a child less than 12 years of age: a case report and review of the literature

We report ossiculum terminale persistens associated with atlantoaxial instability in a child less than 12 years of age. Static and dynamic X-rays, thin-cut computed tomography with sagittal and coronal reconstructions, and magnetic resonance imaging of the cervical spine showed atlantoaxial instability and an "orthotopic" ossiculum terminale persistens. This pathologic state was differentiated from the primary ossification center at the tip of the odontoid, which normally is not expected to fuse with the body of the odontoid until the age of 12 years. The patient was taken to the operating room for a posterior instrumented fusion of C1 and C2. The patient has done well in short- and long-term follow-up.There have been only a few case reports and small case series regarding atlantoaxial instability, requiring surgical intervention, from ossiculum terminale persistens. Most have presented later in life or in association with Down syndrome. Furthermore, most cases have been of the "dystopic" variant. The terms - "orthotopic" and "dystopic" anatomic variants - have usually been reserved to describe os odontoideum. However, we introduce these terms in describing ossiculum terminale persistens and show a rare case of "orthotopic" ossiculum terminale persistens associated with atlantoaxial instability in a pediatric patient less than the age of 12.
A Compact Polyimide-Based UWB Antenna for Flexible Electronics

In this letter, we present a compact ultrawideband (UWB) antenna printed on a 50.8-μm Kapton polyimide substrate. The antenna is fed by a linearly tapered coplanar waveguide (CPW) that provides smooth transitional impedance for improved matching. The proposed design is tuned to cover the 2.2-14.3-GHz frequency range that encompasses both the 2.45-GHz Industrial, Scientific, Medical (ISM) band and the standard 3.1-10.6-GHz UWB band. Furthermore, the antenna is compared to a conventional CPW-fed antenna to demonstrate the significance of the proposed design. A parametric study is first performed on the feed of the proposed design to achieve the desired impedance matching. Next, a prototype is fabricated; measurement results show good agreement with the simulated model. Moreover, the antenna demonstrates a very low susceptibility to performance degradation due to bending effects in terms of impedance matching and far-field radiation patterns, which makes it suitable for integration within modern flexible electronic devices.
Ultraviolet radiation and cutaneous malignant melanoma

Recent years have seen a steady rise in the incidence of cutaneous malignant melanoma worldwide. Although it is now appreciated that the key to understanding the process by which melanocytes are transformed into malignant melanoma lies in the interplay between genetic factors and the ultraviolet (UV) spectrum of sunlight, the nature of this relation has remained obscure. Recently, prospects for elucidating the molecular mechanisms underlying such gene–environment interactions have brightened considerably through the development of UV-responsive experimental animal models of melanoma. Genetically engineered mice and human skin xenografts constitute novel platforms upon which to build studies designed to elucidate the pathogenesis of UV-induced melanomagenesis. The future refinement of these in vivo models should provide a wealth of information on the cellular and genetic targets of UV, the pathways responsible for the repair of UV-induced DNA damage, and the molecular interactions between melanocytes and other skin cells in response to UV. It is anticipated that exploitation of these model systems will contribute significantly toward the development of effective approaches to the prevention and treatment of melanoma.
Clinical Trial of Thermal Pulsation (LipiFlow) in Meibomian Gland Dysfunction With Preteatment Meibography

Thermal pulsation (LipiFlow) has been advocated for meibomian gland dysfunction (MGD) treatment and was found useful. We aimed to evaluate the efficacy and safety of thermal pulsation in Asian patients with different grades of meibomian gland loss.



A hospital-based interventional study comparing thermal pulsation to warm compresses for MGD treatment. Fifty patients were recruited from the dry eye clinic of a Singapore tertiary eye hospital. The ocular surface and symptom were evaluated before treatment, and one and three months after treatment. Twenty-five patients underwent thermal pulsation (single session), whereas 25 patients underwent warm compresses (twice daily) for 3 months. Meibomian gland loss was graded using infrared meibography, whereas function was graded using the number of glands with liquid secretion.



The mean age (SD) of participants was 56.4 (11.4) years in the warm compress group and 55.6 (12.7) years in the thermal pulsation group. Seventy-six percent of the participants were female. Irritation symptom significantly improved over 3 months in both groups (P<0.01), whereas tear breakup time (TBUT) was modestly improved at 1 month in only the thermal pulsation group (P=0.048), without significant difference between both groups over the 3 months (P=0.88). There was also no significant difference in irritation symptom, TBUT, Schirmer test, and gland secretion variables between patients with different grades of gland loss or function at follow-ups.



A single session of thermal pulsation was similar in its efficacy and safety profile to 3 months of twice daily warm compresses in Asians. Treatment efficacy was not affected by pretreatment gland loss.
Analyzing Information and Value Flows in High-Frequency Capital Markets

High-frequency trading has significant influence on today’s capital markets and has received massive attention in the media. This research aims to provide a conceptual understanding of high-frequency capital markets by analysing information and value flows between relevant high-frequency trading market participants. In a first step, market participants including traders, brokers, market platforms, technology providers, information providers, and clearing agencies are introduced. Second, the trading process is described focusing on the three most important phases, namely the information phase, order routing phase, and order matching phase. Furthermore, we review widely adopted highfrequency trading strategies such as market making, arbitrage trading, and pinging. Expert interviews are used to provide practical insights on the perception of high-frequency trading and the necessity for improved regulation. We merge theoretical knowledge and our findings from practice to develop the HFT Value Information Framework visualizing information and value flows between market participants. We discuss the interrelations between market participants in current high-frequency capital markets and describe implications for different stakeholders. Finally, the implications for regulatory bodies are discussed and possible future research opportunities are identified.
Dialogue Systems & Dialogue Management

A spoken dialogue system (SDS) is a specialised form of computer system that operates as an interface between users and the application, using spoken natural language as the primary means of communication. The motivation for spoken interaction with such systems is that it allows for a natural and efficient means of communication. It is for this reason that the use of an SDS has been considered as a means for furthering development of DST Group’s Consensus project by providing an engaging spoken interface to high-level information fusion software. This document provides a general overview of the key issues surrounding the development of such interfaces.
Mathematical modeling of photovoltaic cell / module / arrays with tags in Matlab / Simulink

Photovoltaic (PV) array which is composed of modules is considered as the fundamental power conversion unit of a PV generator system. The PV array has nonlinear characteristics and it is quite expensive and takes much time to get the operating curves of PV array under varying operating conditions. In order to overcome these obstacles, common and simple models of solar panel have been developed and integrated to many engineering software including Matlab/Simulink. However, these models are not adequate for application involving hybrid energy system since they need a flexible tuning of some parameters in the system and not easily understandable for readers to use by themselves. Therefore, this paper presents a step-by-step procedure for the simulation of PV cells/modules/ arrays with Tag tools in Matlab/Simulink. A DS-100M solar panel is used as reference model. The operation characteristics of PV array are also investigated at a wide range of operating conditions and physical parameters.  The output characteristics curves of the model match the characteristics of DS-100M solar panel. The output power, current and voltage decreases when the solar irradiation reduces from 1000 to 100 W/m. When the temperature decreases, the output power and voltage increases marginally whereas the output current almost keeps constant. Shunt resistance has significant effect on the operating curves of solar PV array as low power output is recorded if the value of shunt resistance varies from 1000 ohms to 0.1 ohms.  The proposed procedure provides an accurate, reliable and easy-to-tune model of photovoltaic array. Furthermore, it also robust advantageous in investigating the solar PV array operation from different physical parameters (series, shunt resistance, ideality factor, etc.) and working condition ( varying temperature, irradiation and especially partial shadow effect) aspects.
A Trusted Lightweight Communication Strategy for Flying Named Data Networking

Flying Ad hoc Network (FANET) is a new resource-constrained breed and instantiation of Mobile Ad hoc Network (MANET) employing Unmanned Aerial Vehicles (UAVs) as communicating nodes. These latter follow a predefined path called 'mission' to provide a wide range of applications/services. Without loss of generality, the services and applications offered by the FANET are based on data/content delivery in various forms such as, but not limited to, pictures, video, status, warnings, and so on. Therefore, a content-centric communication mechanism such as Information Centric Networking (ICN) is essential for FANET. ICN addresses the problems of classical TCP/IP-based Internet. To this end, Content-centric networking (CCN), and Named Data Networking (NDN) are two of the most famous and widely-adapted implementations of ICN due to their intrinsic security mechanism and Interest/Data-based communication. To ensure data security, a signature on the contents is appended to each response/data packet in transit. However, trusted communication is of paramount importance and currently lacks in NDN-driven communication. To fill the gaps, in this paper, we propose a novel trust-aware Monitor-based communication architecture for Flying Named Data Networking (FNDN). We first select the monitors based on their trust and stability, which then become responsible for the interest packets dissemination to avoid broadcast storm problem. Once the interest reaches data producer, the data comes back to the requester through the shortest and most trusted path (which is also the same path through which the interest packet arrived at the producer). Simultaneously, the intermediate UAVs choose whether to check the data authenticity or not, following their subjective belief on its producer's behavior and thus-forth reducing the computation complexity and delay. Simulation results show that our proposal can sustain the vanilla NDN security levels exceeding the 80% dishonesty detection ratio while reducing the generated end-to-end delay to less than 1 s in the worst case and reducing the average consumed energy by more than two times.