nils-herrmann/clean_scirepeval huggingface dataset:
Analysis of DNA methylation and microRNA expression in NUT (nuclear protein in testis) midline carcinoma of the sinonasal tract: a clinicopathological, immunohistochemical and molecular genetic study.

The aim of this study was a detailed clinicopathological investigation of sinonasal NUT midline carcinoma (NMC), including analysis of DNA methylation and microRNA (miRNA) expression. Three (5%) cases of NMC were detected among 56 sinonasal carcinomas using immunohistochemical screening and confirmed by fluorescence in situ hybridization. The series comprised 2 males and 1 female, aged 46, 60, and 65 years. Two tumors arose in the nasal cavity and one in the maxillary sinus. The neoplasms were staged pT1, pT3, and pT4a (all cN0M0). All patients were treated by radical resection with adjuvant radiotherapy. Two patients died 3 and 8 months after operation, but one patient (pT1 stage; R0 resection) experienced no evidence of disease at 108 months. Microscopically, all tumors consisted of infiltrating nests of polygonal cells with vesicular nuclei, prominent nucleoli and basophilic cytoplasm. Abrupt keratinization was present in only one case. Immunohistochemically, there was a diffuse expression of cytokeratin (CK) cocktail, CK7, p40, p63, and SMARCB1/INI1. All NMCs tested negative for EBV and HPV infection. Two NMCs showed methylation of RASSF1 gene. All other genes (APC, ATM, BRCA1, BRCA2, CADM1, CASP8, CD44, CDH13, CDKN1B, CDKN2A, CDKN2B, CHFR, DAPK1, ESR1, FHIT, GSTP1, HIC1, KLLN, MLH1a, MLH1b, RARB, TIMP3, and VHL) were unmethylated. All NMCs showed upregulation of miR-9 and downregulation of miR-99a and miR-145 and two cases featured also upregulation of miR-21, miR-143, and miR-484. In summary, we described three cases of sinonasal NMCs with novel findings on DNA methylation and miRNA expression, which might be important for new therapeutic strategies in the future.
Benchmark Dalvik and Native Code for Android System

Google's Android Native Development Kit (NDK) is a toolset that lets you embed components to use of native code in your Android applications. It makes possible for developers to easily compile in C/C++ for the Android development platform. Generally, developer does not concern how effective between native code and Dalvik Java code that will causes poor performance of Android. There are some researches discussed about benchmark Java and C/C++. But they do not consider the issues of Dalvik and native code for Android programming or evaluate them in real Android device. In this work, we use a more complete approach to benchmark Dalvik java code and Native code on real Android device. We conducted 12 test programs to analyze the performance and found that native code faster than Dalvik Java code for about 34.2%.
Isolation of Cellulose-Degrading Bacteria and Determination of Their Cellulolytic Potential

Eight isolates of cellulose-degrading bacteria (CDB) were isolated from four different invertebrates (termite, snail, caterpillar, and bookworm) by enriching the basal culture medium with filter paper as substrate for cellulose degradation. To indicate the cellulase activity of the organisms, diameter of clear zone around the colony and hydrolytic value on cellulose Congo Red agar media were measured. CDB 8 and CDB 10 exhibited the maximum zone of clearance around the colony with diameter of 45 and 50 mm and with the hydrolytic value of 9 and 9.8, respectively. The enzyme assays for two enzymes, filter paper cellulase (FPC), and cellulase (endoglucanase), were examined by methods recommended by the International Union of Pure and Applied Chemistry (IUPAC). The extracellular cellulase activities ranged from 0.012 to 0.196 IU/mL for FPC and 0.162 to 0.400 IU/mL for endoglucanase assay. All the cultures were also further tested for their capacity to degrade filter paper by gravimetric method. The maximum filter paper degradation percentage was estimated to be 65.7 for CDB 8. Selected bacterial isolates CDB 2, 7, 8, and 10 were co-cultured with Saccharomyces cerevisiae for simultaneous saccharification and fermentation. Ethanol production was positively tested after five days of incubation with acidified potassium dichromate.
A multicentre validation of the 1-min sit-to-stand test in patients with COPD.

Our aim was to comprehensively validate the 1-min sit-to-stand (STS) test in chronic obstructive pulmonary disease (COPD) patients and explore the physiological response to the test.We used data from two longitudinal studies of COPD patients who completed inpatient pulmonary rehabilitation programmes. We collected 1-min STS test, 6-min walk test (6MWT), health-related quality of life, dyspnoea and exercise cardiorespiratory data at admission and discharge. We assessed the learning effect, test-retest reliability, construct validity, responsiveness and minimal important difference of the 1-min STS test.In both studies (n=52 and n=203) the 1-min STS test was strongly correlated with the 6MWT at admission (r=0.59 and 0.64, respectively) and discharge (r=0.67 and 0.68, respectively). Intraclass correlation coefficients (95% CI) between 1-min STS tests were 0.93 (0.83-0.97) for learning effect and 0.99 (0.97-1.00) for reliability. Standardised response means (95% CI) were 0.87 (0.58-1.16) and 0.91 (0.78-1.07). The estimated minimal important difference was three repetitions. End-exercise oxygen consumption, carbon dioxide output, ventilation, breathing frequency and heart rate were similar in the 1-min STS test and 6MWT.The 1-min STS test is a reliable, valid and responsive test for measuring functional exercise capacity in COPD patients and elicited a physiological response comparable to that of the 6MWT.
Simulation of Peak Temperature & Flow Stresses during Friction Stir Welding of AA 7050-T 7451 Aluminium Alloy Using Hyperworks

To overcome limitations of fusion welding of the AA7050-T7451aluminum alloy friction stir welding (FSW) has become a prominent process which uses a non-consumable FSW tool to weld the two abutting plates of the workpiece. The FSW produces a joint with advantages of high joint strength, lower distortion and absence of metallurgical defects. Process parameters such as tool rotational speed, tool traverse speed and axial force and tool dimensions play an important role in obtaining a specific temperature distribution and subsequent flow stresses within the material being welded. Friction stir welding of AA7050-T7451 aluminum alloy has been simulated to obtain the temperature profiles & flow stresses using a recent FEA software called HyperWorks.; the former controlling the microstruture and in turn, mechanical properties and later, the flow of material which depends up on the peak temperatures obtained during FSW. A software based study has been carried out to avoid the difficulty in measuring the temperatures directly and explore the capabilities of the same to provide a basis for further research work related to the said aluminum alloy.
HyperGCN: Hypergraph Convolutional Networks for Semi-Supervised Classification

In many real-world network datasets such as co-authorship, co-citation, email communication, etc., relationships are complex and go beyond pairwise. Hypergraphs provide a flexible and natural modeling tool to model such complex relationships. The obvious existence of such complex relationships in many real-world networks naturally motivates the problem of learning with hypergraphs. A popular learning paradigm is hypergraph-based semi-supervised learning (SSL) where the goal is to assign labels to initially unlabelled vertices in a hypergraph. Motivated by the fact that a graph convolutional network (GCN) has been effective for graph-based SSL, we propose HyperGCN, a novel GCN for SSL on attributed hypergraphs. Additionally, we show how HyperGCN can be used as a learning-based approach for combinatorial optimisation on NP-hard hypergraph problems. We demonstrate HyperGCN’s effectiveness through detailed experimentation on real-world hypergraphs. We have made HyperGCN’s source code available to foster reproducible research.
: 2277-3754 ISO 9001 : 2008

In the future, intelligent machines will replace or enhance human capabilities in many areas. Artificial intelligence is the intelligence exhibited by machines or software. It is the subfield of computer science. Artificial Intelligence is becoming a popular field in computer science as it has enhanced the human life in many areas. Artificial intelligence in the last two decades has greatly improved performance of the manufacturing and service systems. Study in the area of artificial intelligence has given rise to the rapidly growing technology known as expert system. Application areas of Artificial Intelligence is having a huge impact on various fields of life as expert system is widely used these days to solve the complex problems in various areas as science, engineering, business, medicine, weather forecasting. The areas employing the technology of Artificial Intelligence have seen an increase in the quality and efficiency. This paper gives an overview of this technology and the application areas of this technology. This paper will also explore the current use of Artificial Intelligence technologies in the PSS design to damp the power system oscillations caused by interruptions, in Network Intrusion for protecting computer and communication networks from intruders, in the medical areamedicine, to improve hospital inpatient care, for medical image classification, in the accounting databases to mitigate the problems of it and in the computer games.
StormDroid: A Streaminglized Machine Learning-Based System for Detecting Android Malware

Mobile devices are especially vulnerable nowadays to malware attacks, thanks to the current trend of increased app downloads. Despite the significant security and privacy concerns it received, effective malware detection (MD) remains a significant challenge. This paper tackles this challenge by introducing a streaminglized machine learning-based MD framework, StormDroid: (i) The core of StormDroid is based on machine learning, enhanced with a novel combination of contributed features that we observed over a fairly large collection of data set; and (ii) we streaminglize the whole MD process to support large-scale analysis, yielding an efficient and scalable MD technique that observes app behaviors statically and dynamically. Evaluated on roughly 8,000 applications, our combination of contributed features improves MD accuracy by almost 10% compared with state-of-the-art antivirus systems; in parallel our streaminglized process, StormDroid, further improves efficiency rate by approximately three times than a single thread.
Fourth Workshop and Tutorial on Practical Use of Coloured Petri Nets and the CPN Tools

Petri Nets are a powerful technique for modelling, analysing, and validating all kinds of systems. In order to exploit the full power of Petri nets, different versions of Petri nets and tools need to be used, and, sometimes, we need to combine them with other techniques. This makes it necessary to model the same system in different Petri net formalisms or other notations over and over again. Moreover, systems will often be constructed from standard components so that the modeller would like to build his system from these components. This way, even users with no experience in Petri nets can model systems. In order to help this group of users, the analysis results obtained by Petri net tools or other formal methods must be presented and visualized independently from Petri nets. Component Tools is a platform designed for this purpose. Along with a 3D-visualisation of the behaviour of the system (PNVis), non-experts can build Petri net models and see their model running in (virtual) reality. The tutorial will cover the concepts of ComponentTools as well as the concepts and modelling philosophy of the 3D-visualisation. Moreover, the tutorial will discuss the underlying software technology which makes it easy to implement this kind of tools. In addition to the existing concepts the tutorial will give an overview of ideas for future work and challenging research projects -with the potential for many PhD theses. References E. Kindler and F. Nillies: Petri Nets and the Real World. Petri Net Newsletter 70, Cover Picture Story, pp. 3-8, April 2006.  E. Kindler and C. Páles: 3D-Visualization of Petri Net Models: Concept and Realization.  J. Cortadella and W. Reisig (eds.): International Conference on Theory and Application of Petri Nets 2004, 25th International Conference, Bolgna, Italy. Springer, LNCS 3099: 464-473, June 2004. E. Kindler, V. Rubin, and R. Wagner: Component Tools: Application and Integration of Formal Methods.  Electronic proceedings of the Workshop Object Orientierte Software Entwicklung 2005 (OOSE '05), Satellite event of Net.ObjectDays 2005, Erfurt, Germany, September 2005.  E. Kindler, V. Rubin, and R. Wagner: Component Tools: Integrating Petri nets with other formal methods. International Conference on Theory and Application of Petri Nets 2006, 27th International Conference, Turku, Finland. June 2006. LNCS 4024, pp. 37-56. E. Kindler and R.  Triple Graph Grammars: Concepts, Extensions, Implementations, and Application Scenarios. Tech. Rep. tr-ri-07-284, Software Engineering Group, Department of Computer Science, University of Paderborn, June 2007.
A S ] 8 M ay 2 01 8 Capsule Networks for Low Resource Spoken Language Understanding

Designing a spoken language understanding system for command-and-control applications can be challenging because of a wide variety of domains and users or because of a lack of training data. In this paper we discuss a system that learns from scratch from user demonstrations. This method has the advantage that the same system can be used for many domains and users without modifications and that no training data is required prior to deployment. The user is required to train the system, so for a user friendly experience it is crucial to minimize the required amount of data. In this paper we investigate whether a capsule network can make efficient use of the limited amount of available training data. We compare the proposed model to an approach based on Non-negative Matrix Factorisation which is the state-of-the-art in this setting and another deep learning approach that was recently introduced for end-to-end spoken language understanding. We show that the proposed model outperforms the baseline models for three command-and-control applications: controlling a small robot, a vocally guided card game and a home automation task.
A systematic review of vitamin D status in populations worldwide.

Vitamin D deficiency is associated with osteoporosis and is thought to increase the risk of cancer and CVD. Despite these numerous potential health effects, data on vitamin D status at the population level and within key subgroups are limited. The aims of the present study were to examine patterns of 25-hydroxyvitamin D (25(OH)D) levels worldwide and to assess differences by age, sex and region. In a systematic literature review using the Medline and EMBASE databases, we identified 195 studies conducted in forty-four countries involving more than 168 000 participants. Mean population-level 25(OH)D values varied considerably across the studies (range 4·9-136·2 nmol/l), with 37·3 % of the studies reporting mean values below 50 nmol/l. The highest 25(OH)D values were observed in North America. Although age-related differences were observed in the Asia/Pacific and Middle East/Africa regions, they were not observed elsewhere and sex-related differences were not observed in any region. Substantial heterogeneity between the studies precluded drawing conclusions on overall vitamin D status at the population level. Exploratory analyses, however, suggested that newborns and institutionalised elderly from several regions worldwide appeared to be at a generally higher risk of exhibiting lower 25(OH)D values. Substantial details on worldwide patterns of vitamin D status at the population level and within key subgroups are needed to inform public health policy development to reduce risk for potential health consequences of an inadequate vitamin D status.
The neurophysiology of P 300--an integrated review.

Event-related potentials (ERPs) are very small voltages recorded from the scalp which originate in the brain structures in response to specific events or stimuli. They appear as a series of peaks and troughs interspersed in the Electroencephalogram (EEG) waves. The exact neural origins and neuropsychological meaning of the P300 are imprecisely known, even though appreciable progress has been made in the last 25 years. In this review, we will focus on the possible neural generators of this potential. Given the attention and memory operations associated with P300 generation, the first human studies on the neural origins of this ERP focused on the hippocampal formation using depth electrodes implanted to assess sources of epileptic foci in patients. Other lesion studies have found that the integrity of the temporal-parietal lobe junction is involved with either generation or transmission processes subsequent to hippocampal activity and contributes to ERP measures. These findings imply that hippocampal absence does not eliminate the P300, but that the temporal-parietal junction does affect its production. As mentioned till now, the neuroelectric events that underlie P300 generation stem from the interaction between frontal lobe and hippocampal/temporal-parietal function. ERP and fMRI studies using oddball tasks have obtained patterns consistent with this frontal-to-temporal and parietal lobe activation pattern. Further support comes from magnetic resonance imaging (MRI) of gray matter volumes that suggest individual variation in P3a amplitude from distracter stimuli is correlated with frontal lobe area size, whereas P3b amplitude from target stimuli is correlated with parietal area size. Given distinct neuropsychological correlates for P3a and P3b, different neurotransmitters may be engaged for each constituent subcomponent under specific stimulus/task processing requirements. Available data suggest that dopaminergic/frontal processes for P3a and locus-coeruleus-norepinephrine/ parietal activity for P3b are reasonable to propose. This dual-transmitter P300 hypothesis is speculative but appears to account for a variety of findings and provides a useful framework for evaluating drug effects.
Parallel Connection of 1200-V/100-A SiC-MOSFET Half-Bridge Modules

Silicon (Si) insulated-gate bipolar transistors (IGBTs) are widely used in power converters. Silicon carbide (SiC) technology will push the limits of switching devices in three directions: higher blocking voltage, higher operating temperature, and higher switching speed. The first SiC-metal-oxide-semiconductor field-effect transistor (MOSFET) half-bridge modules (SiC HBM) are now commercially available and look promising. Although they are still limited in breakdown voltage, these components should, for instance, improve traction-chain efficiencies. In particular, a significant reduction in switching losses is to be expected which should lead to improvements in power-to-weight ratios-of particular interest for rolling-stock. Nevertheless, because of the high switching speed and the high current levels required by traction applications, the implementation of these modules is critical. In this paper, the authors investigate the parallel connection of SiC HBM with a focus on traction equipment. The key points are underlined and an original approach is proposed to design the bus-bar and the gate-drive circuit. Experimental results performed on an opposition method test bench, valid the correct operation of three SiC modules in parallel.
Multi-broadband radio over fiber system based on Generalized Frequency Division Multiplexing

We put forward and simulation demonstrated a multi-broadband radio over fiber (RoF) system based on Generalized Frequency Division Multiplexing (GFDM) by the using of Matlab software to call OptiSystem. The system simultaneously transmits four GFDM signals modulated to four different carriers. Each signal is with bit rate 10Gbit/s and bandwidth 2.5GHz and carriers are with frequency 10, 13, 16 and 19GHz respectively. The simulation results indicated that the signals can transmit through 24-km Single Mode Fiber (SMF) with EVM 2.6% when received optical power is −17.8dBm because of GFDM signals' ultra-low Out of Band (OOB) leakage to strictly avoid harmful interference to adjacent signals.
Learning for Video Super-Resolution through HR Optical Flow Estimation

Video super-resolution (SR) aims to generate a sequence of high-resolution (HR) frames with plausible and temporally consistent details from their low-resolution (LR) counterparts. The generation of accurate correspondence plays a significant role in video SR. It is demonstrated by traditional video SR methods that simultaneous SR of both images and optical flows can provide accurate correspondences and better SR results. However, LR optical flows are used in existing deep learning based methods for correspondence generation. In this paper, we propose an endto-end trainable video SR framework to super-resolve both images and optical flows. Specifically, we first propose an optical flow reconstruction network (OFRnet) to infer HR optical flows in a coarse-to-fine manner. Then, motion compensation is performed according to the HR optical flows. Finally, compensated LR inputs are fed to a superresolution network (SRnet) to generate the SR results. Extensive experiments demonstrate that HR optical flows provide more accurate correspondences than their LR counterparts and improve both accuracy and consistency performance. Comparative results on the Vid4 and DAVIS10 datasets show that our framework achieves the stateof-the-art performance. The codes will be released soon at: https://github.com/LongguangWang/SOF-VSR-SuperResolving-Optical-Flow-for-Video-Super-Resolution-.
Facebook Spam and Spam Filter Using Artificial Neural Networks

Spam is any unwanted electronic message or material in any form posted too many people. As the world is growing as global world, social networking sites play an important role in making world global providing people from different parts of the world a platform to meet and express their views. Among different social networking sites Facebook become the leading one. With increase in usage different users start abusive use of Facebook by posting or creating ways to post spam. This paper highlights the potential spam types nowadays Facebook users’ faces. This paper also provide the reason how user become victim to spam attack. A methodology is proposed in the end discusses how to handle different types of spam. Artificial neural networks, Facebook spam, social networking sites, spam filter.
Minimalist Jumping Robots for Celestial Exploration

In this paper we describe a novel approach to the design and deployment of small and minimally actuated jumping or hopping robots that are suitable for exploring the unstructured terrains of celestial bodies. We introduce the basic jumping mobility paradigm, as well as the evolution of our hopping robot concept by way of the main prototypes that we have developed. These prototypes show that a small number of actuators can control the vehicle’s steering, hopping, and self-righting motions. The last prototype is equipped with wheels so that precision motion can be combined with gross hopping motion. Lessons learned during the development of these prototypes have general applicability to the design of jumping robots. In addition to reviewing the issues relevant to the design of jumping systems, in this paper we describe some of the key mechanisms that enable our approach, we summarize tests obtained with these systems, and we present our future plans of localization and sensing for hopping