nils-herrmann/clean_scirepeval huggingface dataset:
Analysis of 1.2 kV 4H-SiC Trench-Gate MOSFETs with Thick Trench Bottom Oxide

The 1.2 kV-rated trench-gate SiC power MOSFET with thick trench bottom oxide is analyzed and compared with previous trench-gate SiC power MOSFET structures. Specific on-resistance (R<inf>on, sp</inf>), breakdown voltage (BV), threshold voltage (V<inf>TH</inf>), gate-drain capacitance (C<inf>gd, sp</inf>) and gate charge (Q<inf>gd</inf>) were extracted using numerical simulations for trench bottom oxide thickness between 500 A and 8000 A. It was found that the electric field in the trench bottom oxide was below 4 MV/cm for oxide thickness beyond 4000 A. An analytical model is proposed to allow estimation of the electric field in the trench bottom oxide. The R<inf>on, sp</inf> for the thick bottom oxide structure was 1.9 m Ω - cm2(at Vgs of 20 V), Cgd, sp (at Vds= 1000 V) was 417 pF/cm<sup>2</sup> and Qgd, sp (at Vgs =20 V, R<inf>g</inf>=10 Ω, Vds=800V) was 671 nC / cm <sup>2</sup>, which is significantly better than most planar-gate devices. This structure has superior specific on-resistance compared with previous trench-gate and planar-gate structures.
Microservices for Scalability

Microservice architectures provide small services that may be deployed and scaled independently of each other, and may employ different middleware stacks for their implementation. Microservice architectures emphasize transaction-less coordination between services, with explicit acceptance of eventual consistency. Polyglott persistence in this context means that the individual microservices may employ multiple data storage technologies. Microservice architectures are “cloud native” allowing for automated and rapid elasticity. Fault-tolerance mechanisms achieve that failures of individual mircroservices do not affect other services thanks to container isolation. Since services can fail at any time, it is important to be able to detect the failures quickly and, if possible, automatically restore services. Essential for success in such a setting is advanced monitoring. In this keynote, I discuss how mircoservices support scalability for both, runtime performance and development performance, via polyglott persistence, eventual consistency, loose coupling, open source frameworks, and continuous monitoring for elastic capacity management.
Model reference control for timed event graphs in dioids

This paper deals with feedback controller synthesis for Timed Event Graphs in dioids. We discuss here the existence and the computation of a controller which leads to a closed-loop system whose behavior is as close as possible to the one of a given reference model and which delays as much as possible the input of tokens inside the (controlled) system. The synthesis presented here is mainly based on residuation theory results and some Kleene star properties.
Feature correspondence and motion recovery in vehicle planar navigation

This paper describes a strategy to feature point correspondence and motion recovery in vehicle navigation. A transformation of the image plane is proposed that keeps the motion of the vehicle on a plane parallel to the transformed image plane. This permits to de"ne linear tracking "lters to estimate the real-world positions of the features, and allows us to select the matches that accomplish the rigidity of the scene by a Hough transform. Candidate correspondences are selected by similarity, taking into account the smoothness of motion. Further processing brings out the "nal matching. The methods have been tested in a real application. ( 1999 Pattern Recognition Society.
Flexible affix classification for stemming Indonesian Language

The stemming is the process to derive the basic word by removing affix of the word. The stemming is tightly related to basic word or lemma and the sub lemmas. The lemma and sub lemma of Indonesian Language have been grown and absorb from foreign languages or Indonesian traditional languages. Our approach provides the easy way of stemming Indonesian language through flexibility affix classification. Therefore, the affix additional can be applied in easy way. We experiment with 1,704 text documents with 255,182 tokens and the stemmed words is 3,648 words. In this experiment, we compare our approach performance to the confix-stripping approach performance. The result shows that our performance can cover the failure in stemming reduplicated words of confix-stripping approach.
Calibration of a fully polarimetrie 8×8 MIMO FMCW radar system at 77 GHz

State-of-the-art millimeter wave (MMW) multiple-input, multiple-output (MIMO) frequency-modulated continuous-wave (FMCW) radars allow high precision direction of arrival (DOA) estimation with an optimized antenna aperture size . Typically, these systems operate using a single polarization. Fully polarimetric radars on the other hand are used to obtain the polarimetric scattering matrix (S-matrix) and extract polari-metric scattering information that otherwise remains concealed . Combining both approaches by assembly of a dual-polarized waveguide antenna and a 77 GHz MIMO FMCW radar system results in the fully polarimetric MIMO radar system presented in this paper. By applying a MIMO-adapted version of the isolated antenna calibration technique (IACT) from [3], the radar system is calibrated and laboratory measurements of different canonical objects such as spheres, plates, dihedrals and trihedrals are performed. A statistical evaluation of these measurement results demonstrates the usability of the approach and shows that basic polarimetric scattering phenomena are reliably identified.
Cross-layer architecture for adaptive video multicast streaming over multirate wireless LANs

Multicast video streaming over multirate wireless LANs imposes strong demands on video codecs and the underlying network. It is not sufficient that only the video codec or only the underlying protocols adapt to changes in the wireless link quality. Research efforts should be applied in both and in a synchronized way. Cross layer design is a new paradigm that addresses this challenge by optimizing communication network architectures across traditional layer boundaries. This paper presents cross-layer architecture for adaptive video multicast streaming over multirate wireless LANs where layer-specific information is passed in both directions, top-down and bottom-up. The authors jointly consider three layers of the protocol stack: the application, data link and physical layers. The authors analyze the performance of the proposed architecture and extensively evaluate it via simulations. The results show that the real-time video quality of the overall system can be greatly improved by cross-layer signaling.
A Ka-Band Broadband Integrated Transition of Air-Filled Waveguide to Laminated Waveguide

In this letter, a novel compact and broadband integrated transition between a laminated waveguide and an air-filled rectangular waveguide operating in Ka band is proposed. A three-pole filter equivalent circuit model is employed to interpret the working mechanism and to predict the performance of the transition. A back-to-back prototype of the proposed transition is designed and fabricated for proving the concept. Good agreement of the measured and simulated results is obtained. The measured result shows that the insertion loss of better than 0.26 dB from 34.8 to 37.8 GHz can be achieved.
Neurodevelopmental sequelae associated with gray and white matter changes and their cellular basis: A comparison between Autism Spectrum Disorder, ADHD and dyslexia

Many psychiatric diseases, such as major depression and schizophrenia, are accompanied by patterns of gray matter and white matter changes in the cortex that may be due to structural pathologies of synapses and their dendrites in the gray matter on the one hand and to pathologies in myelinating oligodendrocytes on the other. Here the possibility has been briefly examined that such a generalization might also hold for Autistic Spectrum Disorders (ASD). Evidence is presented that gray matter changes that accompany ASD may in fact reflect changes in synapses and subsequently of their dendrites, whereas those in the white matter reflect changes in myelination due to pathologies of oligodendrocytes. It is proposed that such structural pathologies during development provide a coherent biological model not only for the onset and course of ASD but also provide the basis for development and systematic evaluation of new treatment strategies.
WhoTracks.Me: Monitoring the online tracking landscape at scale

We present the largest and longest measurement of online tracking to date based on real users. The data, which is made publicly available, is generated from more than 780 million page loads over the course of the last 10 months. Previous attempts to measure the tracking ecosystem, are done via measurement platforms that do not interact with websites the same way a user does. We instrument a crowd-sourced measurement of third-parties across the web via users who consent to data collection via a browser extension. The collection is done with privacy-by-design in mind, and introduces no privacy side effects. This approach overcomes limitations of previous work by collecting real web usage across multiple countries, ISP and browser configurations, and on difficult to crawl pages, such as those behind logins, giving a more accurate portrayal of the online-tracking ecosystem. The data1, which we plan to continue contributing to and maintain in the future, and WhoTracks.Me website – the living representation of the data, are available for researchers, regulators, journalists, web developers and users to detect tracking behaviours, analyse the tracking landscape, develop efficient tools, devise policies and raise awareness of the negative externalities tracking introduces. We believe this work provides the transparency needed to shine a light on a very opaque industry.
VR Video Conferencing over Named Data Networks

We propose a VR video conferencing system over named data networks (NDN). The system is designed to support real-time, multi-party streaming and playback of 360 degree video on a web player. A centralized architecture is used, with a signaling server to coordinate multiple participants. To ensure real-time requirement, a protocol featuring prefetching is used for producer-consumer communication. Along with the native support of multicast in NDN, this design is expected to better support large amount of data streaming between multiple users.
 As a proof of concept, a protoype of the system is implemented with one-way real-time 360 video streaming. Experiments show that seamless streaming and interactive playback of 360 video can be achieved with low latency. Therefore, the proposed system has the potential to provide immersive VR experience for real-time multi-party video conferencing.
Chemical composition and toxicity of the essential oils from Cunila species (Lamiaceae) on the cattle tick Rhipicephalus (Boophilus) microplus

The essential oils obtained from the aerial parts of five species of Cunila (Lamiaceae) native to Southern Brazil were analyzed by GC and GC/MS. The oil of Cunila angustifolia was characterized by sabinene; Cunila incana is rich in α-pinene and β-pinene, Cunila spicata and Cunila microcephala presented menthofuran as the main component, and in the essential oil of Cunila incisa, the major component was 1,8-cineole. Laboratory tests were carried out to determine the effect of the essential oils of the above cited plants on larvae of the cattle tick Riphicephalus (Boophilus) microplus. C. angustifolia, C. incana, and C. spicata were the most active samples killing almost the totality of the larvae. C. incisa and C. microcephala showed low acaricidal effect.
Driver Fatigue Detection System Using Electroencephalography Signals Based on Combined Entropy Features

Driver fatigue has become one of the major causes of traffic accidents, and is a complicated physiological process. However, there is no effective method to detect driving fatigue. Electroencephalography (EEG) signals are complex, unstable, and non-linear; non-linear analysis methods, such as entropy, maybe more appropriate. This study evaluates a combined entropy-based processing method of EEG data to detect driver fatigue. In this paper, 12 subjects were selected to take part in an experiment, obeying driving training in a virtual environment under the instruction of the operator. Four types of enthrones (spectrum entropy, approximate entropy, sample entropy and fuzzy entropy) were used to extract features for the purpose of driver fatigue detection. Electrode selection process and a support vector machine (SVM) classification algorithm were also proposed. The average recognition accuracy was 98.75%. Retrospective analysis of the EEG showed that the extracted features from electrodes T5, TP7, TP8 and FP1 may yield better performance. SVM classification algorithm using radial basis function as kernel function obtained better results. A combined entropy-based method demonstrates good classification performance for studying driver fatigue detection.
Smart meter based short-term load forecasting for residential customers

This paper examines the potential impact of automatic meter reading (AMR) on short-term load forecasting for a residential customer. Real-time measurement data from customers' smart meters provided by a utility company is modeled as the sum of a deterministic component and a Gaussian noise signal. The shaping filter for the Gaussian noise is calculated using spectral analysis. Kalman filtering is then used for load prediction. The accuracy of the proposed method is evaluated for different sampling periods and planning horizons. The results show that the availability of more real-time measurement data improves the accuracy of the load forecast significantly. However, the improved prediction accuracy can come at a high computational cost. Our results qualitatively demonstrate that achieving the desired prediction accuracy while avoiding a high computational load requires limiting the volume of data used for prediction. Consequently, the measurement sampling rate must be carefully selected as a compromise between these two conflicting requirements.
Prediction of subscriber churn using social network analysis

In today's world, mobile phone penetration has reached a saturation point. As a result, subscriber churn has become an important issue for mobile operators as subscribers switch operators for a variety of reasons. Mobile operators typically employ churn prediction algorithms based on service usage metrics, network performance indicators, and traditional demographic information. A newly emerging technique is the use of social network analysis (SNA) to identify potential churners. Intuitively, a subscriber who is churning will have an impact on the churn propensity of his social circle. Call detail records are useful to understand the social connectivity of subscribers through call graphs but do not directly provide the strength of their relationship or have enough information to determine the diffusion of churn influence. In this paper, we present a way to address these challenges by developing a new churn prediction algorithm based on a social network analysis of the call graph. We provide a formulation that quantifies the strength of social ties between users based on multiple attributes and then apply an influence diffusion model over the call graph to determine the net accumulated influence from churners. We combine this influence and other social factors with more traditional metrics and apply machine-learning methods to compute the propensity to churn for individual users. We evaluate the performance of our algorithm over a real data set and quantify the benefit of using SNA in churn prediction.
Fractional CO2 laser resurfacing for atrophic acne scars: a randomized controlled trial with blinded response evaluation.

The treatment of acne scars with fractional CO(2) lasers is gaining increasing impact, but has so far not been compared side-by-side to untreated control skin.



In a randomized controlled study to examine efficacy and adverse effects of fractional CO(2) laser resurfacing for atrophic acne scars compared to no treatment.



Patients (n = 13) with atrophic acne scars in two intra-individual areas of similar sizes and appearances were randomized to (i) three monthly fractional CO(2) laser treatments (MedArt 610; 12-14 W, 48-56 mJ/pulse, 13% density) and (ii) no treatment. Blinded on-site evaluations were performed by three physicians on 10-point scales. Endpoints were change in scar texture and atrophy, adverse effects, and patient satisfaction.



Preoperatively, acne scars appeared with moderate to severe uneven texture (6.15 ± 1.23) and atrophy (5.72 ± 1.45) in both interventional and non-interventional control sites, P = 1. Postoperatively, lower scores of scar texture and atrophy were obtained at 1 month (scar texture 4.31 ± 1.33, P < 0.0001; atrophy 4.08 ± 1.38, P < 0.0001), at 3 months (scar texture 4.26 ± 1.97, P < 0.0001; atrophy 3.97 ± 2.08, P < 0.0001), and at 6 months (scar texture 3.89 ± 1.7, P < 0.0001; atrophy 3.56 ± 1.76, P < 0.0001). Patients were satisfied with treatments and evaluated scar texture to be mild or moderately improved. Adverse effects were minor.



In this single-blinded randomized controlled trial we demonstrated that moderate to severe atrophic acne scars can be safely improved by ablative fractional CO(2) laser resurfacing. The use of higher energy levels might have improved the results and possibly also induced significant adverse effects.
A Mathematical Trust Algebra for International Nation Relations Computation and Evaluation

This manuscript presents a trust computation for international relations and its calculus, which related to Bayesian inference, Dempster-Shafer theory and subjective logic. We proposed a method that allows a trust computation which is previously subjective and incomputable. An example of case study for the trust computation is the United States of America–Great Britain relations. The method supports decision makers in a government such as foreign ministry, defense ministry, presidential or prime minister office. The Department of Defense (DoD) may use our method to determine a nation that can be known as a friendly, neutral or hostile nation.
Putting evolution in elimination: Winning our ongoing battle with evolving malaria mosquitoes and parasites

Since 2000, the world has made significant progress in reducing malaria morbidity and mortality, and several countries in Africa, South America and South-East Asia are working hard to eliminate the disease. These elimination efforts continue to rely heavily on antimalarial drugs and insecticide-based interventions, which remain the cornerstones of malaria treatment and prevention. However, resistance has emerged against nearly every antimalarial drug and insecticide that is available. In this review we discuss the evolutionary consequences of the way we currently implement antimalarial interventions, which is leading to resistance and may ultimately lead to control failure, but also how evolutionary principles can be applied to extend the lifespan of current and novel interventions. A greater understanding of the general evolutionary principles that are at the core of emerging resistance is urgently needed if we are to develop improved resistance management strategies with the ultimate goal to achieve a malaria-free world.
The Effects of Music Tempo on Concentration and Task Performance

A frequently visited topic in cognitive physiology is music’s influence on simple tasks. Our study addressed the effect of differing music tempos on a subject’s typing performance. Utilizing EEG, ECG, and a sphygmomanometer, we recorded alpha and beta brain waves, heart rate, and blood pressure while a total of fifteen subjects completed a two-minute online typing test. This typing test was performed three times, once as a control without music, once with a song of 40 beats per minute, and once with a song of 80 beats per minute with a rest period between each trial. When compared to no music, slow tempo music did not significantly affect typing performance (p=0.479), heart rate (p=0.249), blood pressure (p=0.221), nor brain activity. Similarly, fast tempo music did not change typing performance (p=0.364), heart rate (p=0.0689), blood pressure (p=0.519), nor brain activity. Future research in this area must reconcile individual tastes in music, base-level typing proficiency, and should aim to increase the sample size.
Downsampling for sparse subspace clustering

Sparse subspace clustering (SSC) is a technique to partition unlabeled samples according to the subspaces they locate in. With the rapid increase of data amount, efficiently downsampling a big dataset, while at the same time keeping the structure of subspaces, becomes an important topic for SSC. In order to reduce the computational cost while preserving clustering accuracy, a new approach of SSC with downsampling (SSCD) is proposed in this paper. In SSCD, the numbers of samples located in respective subspaces are estimated utilizing the ℓ1 norm of the sparse representation. Then a downsampling strategy is designed to decimate samples with the probabilities that are in reverse ratio to the amounts of samples in respective subspaces. As a consequence, the samples in different subspaces are expected to be balanced after the downsampling operation. Theoretical analysis proves the correctness of the proposed strategy. Numerical simulations also verify the efficiency of SSCD.
Human Gut Microbiota Changes Reveal the Progression of Glucose Intolerance

To explore the relationship of gut microbiota with the development of type 2 diabetes (T2DM), we analyzed 121 subjects who were divided into 3 groups based on their glucose intolerance status: normal glucose tolerance (NGT; n = 44), prediabetes (Pre-DM; n = 64), or newly diagnosed T2DM (n = 13). Gut microbiota characterizations were determined with 16S rDNA-based high-throughput sequencing. T2DM-related dysbiosis was observed, including the separation of microbial communities and a change of alpha diversity between the different glucose intolerance statuses. To assess the correlation between metabolic parameters and microbiota diversity, clinical characteristics were also measured and a significant association between metabolic parameters (FPG, CRP) and gut microbiota was found. In addition, a total of 28 operational taxonomic units (OTUs) were found to be related to T2DM status by the Kruskal-Wallis H test, most of which were enriched in the T2DM group. Butyrate-producing bacteria (e.g. Akkermansia muciniphila ATCCBAA-835, and Faecalibacterium prausnitzii L2-6) had a higher abundance in the NGT group than in the pre-DM group. At genus level, the abundance of Bacteroides in the T2DM group was only half that of the NGT and Pre-DM groups. Previously reported T2DM-related markers were also compared with the data in this study, and some inconsistencies were noted. We found that Verrucomicrobiae may be a potential marker of T2DM as it had a significantly lower abundance in both the pre-DM and T2DM groups. In conclusion, this research provides further evidence of the structural modulation of gut microbiota in the pathogenesis of diabetes.