Miracle-dz/UniFAR-FTUs huggingface dataset:
Sentiment Classification based on Linguistic Patterns in Citation Context

clustering. In Companion of the Web Conference 2018, International World Wide Web Conferences Steering Committee, Lyon, France, 2018, pp. 1699–1706. 35. Chengzhang, X. and Dan, L. , Chinese text summarization algorithm based on Word2vec. J. Phys.: Conf. Ser. , 2018, 976(1), 012006. 36. Fauzi, M. A. , Word2Vec model for sentiment analysis of product reviews in Indonesian language. Int. J. Electr. Comput. Eng., 2019, 9(1), 525–530. 37. Yao, Y. et al., Sensing spatial distribution of urban land use by integrating points-of-interest and Google Word2Vec model. Int. J. Geogr. Inf. Sci., 2017, 31, 825–848. ACKNOWLEDGEMENTS. This work was supported by the National Natural Science Foundation of China (Grant No. 71473034; 717D1063), and the financial assistance from Postdoctoral Scientific Research Developmental Fund of Heilongjiang Province, China (Grant No. LBH-Q16003). Received 9 May 2019; revised accepted 30 May 2019 doi: 10.18520/cs/v117/i4/606-616
Scheduling of Composite Services in Multi-Cloud Environment

In cloud computing, resource allocation and scheduling of composite web services is very challenging and have many constraints. In a multi cloud environment, nodes can host more than one web service instances. Each web service instance can accept more than one request concurrently. Each node have different load (number of requests being served) at different time. Further, in composite web service, outputs of one service are input to another service which are required to be transferred through the cloud networks, which adds additional substantial data transfer time. The data transfer time among clouds and nodes is very important to depict the practical scenario. This paper presents an efficient scheduling mechanism which can efficiently schedule abstract services of the composite web services considering all above constrains and dynamism of the cloud. In this approach composite services are schedule at cloud, node and then at instance level. In this work, a multi-level chromosome based genetic algorithm is presented to schedule composite web services and to study its effectiveness. The paper also studies the importance of the cloud locality (inter cloud distance) and node locality (inter node distance) in the proposed scheduling of composite services in multi-cloud environment. Keywordsweb-service composition;Scheduling; Algorithm; Cloud computing;Genetic algorithm.
Prospective Study A Prospective Comparison of CT-Epidurogram Between Th 1-Transforaminal Epidural Injection and Th 1 / 2-Parasagittal Interlaminar Epidural Injection for Cervical Upper Limb Pain

by 2 methods: transforaminal and interlaminar. Many serious complications caused by inadvertent intravascular injection have been reported with the use of cervical transforaminal epidural steroid injection through the anterior-lateral approach. Despite international practical guidelines that have been proposed, cervical transforaminal epidural injection is still less recommended than cervical interlaminar epidural injection.
TEACHERS ' PERCEPTION OF BEGINNING AND LONG-SERVING TEACHERS ' EFFICACY IN TEACHING MATHEMATICS

This paper reports a survey on the perceived success beginning and long-serving teachers in teaching primary mathematics. The results indicate that about 61 per cent of the 78 teachers who participated in the survey perceived beginning teachers as either successful or more successful in handling primary mathematics, while just 47 per cent of teachers perceived long serving teachers as either successful or more successful. A paired t-test carried out yielded a significant difference between the perceived success of beginning and long-serving teachers in teaching primary mathematics, with the former having the higher mean rating of success. It was also found that the majority of beginning teachers preferred to go to other beginning teachers and/or teachers with 4 – 10 years teaching experience when in difficulty in an aspect of mathematics. That is, about 85 per cent and 80 per cent of the teachers who made responses preferred to go to beginning teachers and teacher with 4 – 10 years teaching experience respectively. The paper argues that the trend could be a probable explanation for the lack of support for newly qualified teachers in Ghanaian schools. The paper in this light concludes by considering how partnership and co-operation between training colleges and schools can help to make teachers, both beginning and long-serving, engage in fruitful professional activities in mathematics to support each other.
Jugador virtual del Go, basado en el algoritmo de Monte Carlo

Resumen. En este trabajo se presenta el desarrollo de un jugador virtual del Go, basado en Monte-Carlo Tree Search (MCTS). Inicialmente se desarrolla una librerı́a general, adaptable y eficiente para el algoritmo MCTS, con múltiples ejemplos de uso en distintos dominios. Luego, se procede a trabajar en el problema particular del juego Go, introduciendo mejoras principalmente en la etapa de simulación a través de la incorporación de conocimiento de dominio. En particular, se implementan mejoras a través de la detección de patrones en el tablero y la consideración de múltiples movimientos claves en el juego. También, se exponen diferentes decisiones en el diseño del programa haciendo énfasis en una plataforma eficiente y reusable. Finalmente se presentan los resultados obtenidos del jugador desarrollado en comparación a otros programas alternativos.
Veröffentlichungsreihe der Forschungsgruppe Gesundheitsrisiken und Präventionspolitik Wissenschaftszentrum Berlin für Sozialforschung KSN-0935-8137 P93-207 Work-Disability and Low Back Pain: A New Classification Model for Research and Intervention

Bemühungen auf dem Gebiet der Erforschung und Prävention rückenschmerzbedingter Arbeitsunfähigkeit wurden bislang durch die Verwendung inadäquater Klassifikationen des Rückenschmerzes behindert. Die Notwendigkeit eines neuen Klassifi­ zierungssystems wird daher zunehmend anerkannt. Das hier vorgeschlagene neue Klas­ sifizierungssystem basiert auf einem Phasenmodell von Arbeitsunfähigkeit, das die Be­ grenztheiten statischer medizinischer Rückenschmerz-Modelle übenvindet und die Be­ sonderheit und Dynamik der sozialen Umstände des Arbeitsunfähigkeits-Prozesses re­ flektiert. Die Einfachheit dieses in erster Linie auf der Arbeitsunfähigkeits-Dauer und weniger auf klinischen Kategorien basierenden Klassifikationssystems gestattet es allen, die mit Arbeitsunfähigkeit befaßt sind Forschern ebenso wie Praktikern -, Rückenprobleme zu analysieren und abzuschätzen. Gleichzeitig ist das Modell ausreichend flexibel und er­ weiterbar, um detaillierte Erkenntnisse, die der Biomedizin und den Sozialwis­ senschaften, der klinischen wie auch der Arbeitsschutz-Perspektive entspringen, einzu­ beziehen. Dieses Arbeitsunfähigkeits-Modell kann für die Wissenssystematisierung ebenso nützlich sein wie für die Anleitung zu rechtzeitiger Untersuchung und Interven­ tion. Das vorliegende Papier entstand im Rahmen des Projekts "Arbeitsweltbezogene Präven­ tion und Gesundheitsförderung am Beispiel von Rückenschmerzen Präventionspoliti­ sche Konstellationen für Entwurf und Umsetzung zielgerichteter Interventionen" (Bear­ beiter: Rolf Rosenbrock, Thomas Elkeles, Uwe Lenhardt) im Berliner Forschungsver­ bund Public Health, gefördert vom BMFT (Förderkennzeichen: 07 PHF 01).
Recent Trends on Real Time Object Detection using Single Shot Multibox Detector

: This research paper investigates the running of object detection algorithm on low-end devices to detect different kinds of objects in images. Deep convolutional neural networks (CNNs) which are used in SSD have recently proven extremely capable of performing object detection in single-frame images. Single shot multi-box object detectors have been recently shown to achieve state-of-the-art performance on object detection tasks. The implementation can be done using Pytorch object detection library, and COCO (Common Objects and Context) or Pascal VOC (Visual Object Classes) dataset to detect the common objects around a person like cars, dogs, laptops, etc. The main advantage of using SSD is that, unlike other methods it can be used in laptops and other personal devices.
Movement velocity can be used to estimate the relative load during the bench press and leg press exercises in older women

Background Movement velocity has been proposed as an effective tool to prescribe the load during resistance training in young healthy adults. This study aimed to elucidate whether movement velocity could also be used to estimate the relative load (i.e., % of the one-repetition maximum (1RM)) in older women. Methods A total of 22 older women (age = 68.2 ± 3.6 years, bench press 1RM = 22.3 ± 4.7 kg, leg press 1RM = 114.6 ± 15.9 kg) performed an incremental loading test during the free-weight bench press and the leg press exercises on two separate sessions. The mean velocity (MV) was collected with a linear position transducer. Results A strong linear relationship between MV and the relative load was observed for the bench press (%1RM = −130.4 MV + 119.3; r2 = 0.827, standard error of the estimate (SEE) = 6.10%1RM, p < 0.001) and leg press exercises (%1RM = −158.3 MV + 131.4; r2 = 0.913, SEE = 5.63%1RM, p < 0.001). No significant differences were observed between the bench press and leg press exercises for the MV attained against light-medium relative loads (≤70%1RM), while the MV associated with heavy loads (≥80%1RM) was significantly higher for the leg press. Conclusions These results suggest that the monitoring of MV could be useful to prescribe the loads during resistance training in older women. However, it should be noted that the MV associated with a given %1RM is significantly lower in older women compared to young healthy individuals.
SSC200190 33..45

S port should be considered one of the more important aspects of daily life. This may be supported by the fact that there are magazines, television stations, Web sites, and newspaper sections that are dedicated to sport. Additionally, the Olympic Games, Super Bowl, and Soccer World Cup are some of the most watched sporting events throughout the world. There is a great potential for science to positively impact performance during sporting events. The discipline of sport science would thus appear to be essential to the optimization of sports performance. In this capacity, sport science would involve a tight interaction between the sport scientists and the direction of the development and implementation of the training interventions the athlete undergoes in an attempt to optimize sports performance at all levels (1).
Principal Component Analysis Based Transformation for Privacy Preserving in Data Stream Mining

— Data stream can be conceived as a continuous and changing sequence of data that continuously arrive at a system to store or process. Examples of data streams include computer network traffic, phone conversations, web searches and sensor data etc. The data owners or publishers may not be willing to exactly reveal the true values of their data due to various reasons, most notably privacy considerations. To preserve data privacy during data mining, the issue of privacy preserving data mining has been widely studied and many techniques have been proposed. However, existing techniques for privacy preserving data mining is designed for traditional static data sets and are not suitable for data streams. So the privacy preservation issue of data streams mining is need for the time. This paper focused on techniques for Principal Component Analysis (PCA) based transformation for stream data using Massive Online Analysis (MOA). The clustering accuracy while using the transformed data is almost equal to the original dataset.
Do Consumers Value Fuel Economy ?

season sent gasoline prices to historical highs, rising fuel prices were leading to calls for a political response for relief. Some focused on augmenting supply, renewing the push to open the Arctic National Wildlife Refuge to drilling and to increase offshore drilling. Others focused on decreasing demand by raising fuel economy requirements and encouraging conservation. Enacted in 1975, the “Energy Policy Conservation Act” established Corporate Average Fuel Economy (cafe) standards for passenger cars and light trucks, with a stated objective of doubling new car fuel economy by 1985. In 1986–87, average fleet fuel economy reached 25.9 miles per gallon. Since then, fuel economy has slid back somewhat as sport utility vehicles and light trucks, which are subject to lower fuel economy standards, have become popular, constituting more than 50 percent of new vehicle sales in recent years. Still, current average fuel economy is only seven percent below the 1986–87 high, while vehicle weight has increased 24 percent, horsepower has increased 93 percent, and zero-to-60 mph acceleration has improved 29 percent. In other words, today’s vehicle owners enjoy more size and performance while sacrificing only a little in terms of fuel costs.
Multilingual Sequence Labeling With One Model

A large family of NLP tasks such as named entity recognition (NER) and part-of-speech (PoS) tagging may be formulated as sequence labeling problems; text is treated as a sequence of words to be labeled with linguistic tags. However, industrial applications of sequence labeling are often faced with multilingual text, i.e. data in more than one natural language. The standard approach to address multilingual data is to train separate sequence labeling models for each language, and to employ automatic language identification to select the appropriate model for a given text document. However, this approach effectively multiplies the effort of training a model, pre-training and selecting appropriate word embeddings, and requires an array of models to be managed in production use. One model for many languages. In this extended abstract, we present a novel approach in which we train a single model to perform part-of-speech (PoS) tagging for 12 distinct languages from 4 different language groups. Our approach leverages neural language modeling with recurrent neural networks (RNNs) to model text at the character level. We show that it is possible to train a single language model (LM) over multilingual text data, causing it to implicitly capture language as a feature in its internal representation. This enables us to extract meaningful word embeddings from pre-trained, multilingual LMs against which we train a single downstream sequence labeling model over aggregate multilingual training data. Our experiments indicate that this model internally performs language identification and is thus immediately applicable to multilingual data.
ANovel LocalDensityHierarchicalClusteringAlgorithmBasedon Reverse Nearest Neighbors

Clustering is widely used in data analysis, and density-based methods are developed rapidly in the recent 10 years. Although the state-of-art density peak clustering algorithms are efficient and can detect arbitrary shape clusters, they are nonsphere type of centroid-based methods essentially. In this paper, a novel local density hierarchical clustering algorithm based on reverse nearest neighbors, RNN-LDH, is proposed. By constructing and using a reverse nearest neighbor graph, the extended core regions are found out as initial clusters. en, a new local density metric is defined to calculate the density of each object; meanwhile, the density hierarchical relationships among the objects are built according to their densities and neighbor relations. Finally, each unclustered object is classified to one of the initial clusters or noise. Results of experiments on synthetic and real data sets show that RNN-LDH outperforms the current clustering methods based on density peak or reverse nearest neighbors.
Downscaling GRACE data to estimate groundwater use at the aquifer scale

Sustainable groundwater management requires an operational in situ monitoring network. Concerning groundwater quantity, the EU Water Framework Directive (WFD) requires groundwater level and abstraction monitoring so as to ensure that changes in groundwater storage do not exceed the natural replenishment of the groundwater system. However, there are cases, e.g. Greece, where WFD monitoring program has not yet become fully operational due to various constraints which are more evident during the recent economic crisis. Over the last few decades, satellites have provided useful information to hydrologists, not only concerning surface water resources but also concerning groundwater conditions. The present study aims at quantifying groundwater use at the aquifer scale by using Gravity Recovery and Climate Experiment (GRACE) satellite data in combination with available meteorological data of the study area. To achieve this goal, gridded GRACE Total Water Storage data were statistically downscaled using an Artificial Neural Network (ANN). The methodology was applied in an aquifer in Thrace region (NE Greece) during the time period 2005 2014. Results showed that monthly quantity of water extracted from a certain aquifer can be efficiently estimated offering an inexpensive alternative when in situ observations are not available.
Connections between the stratosphere and synoptic variability

While US CLIVAR has traditionally focused on ocean-atmosphere coupling and its role on climate variability, in this edition of Variations we examine the coupling between the two lowest layers of the atmosphere, the troposphere and the stratosphere. The stratosphere, the region 10-50 km above the earth’s surface, exhibits variability driven by radiation, ozone chemistry, and momentum transport by a broad spectrum of waves propagating up from the troposphere. In the tropics, the stratospheric circulation is dominated by the verticallyoscillating pattern of downward propagating zonal winds known as the Quasi-Biennial Oscillation (QBO). In the extratropics of both hemispheres, the stratospheric polar vortex is a region of strong westerly circumpolar winds that persists through the fall and winter seasons. Increasingly, it has been recognized that variability in both the tropical and extratropical stratosphere can exert influence on surface climate.
Low-Power LSI Technology of 0

Recently, there has been an increasing demand for portable, battery-operated devices like cellular phones. Achieving low-power, high-speed LSIs is essential to miniaturize these devices and improve performance and extend battery life. In order to meet such demands, we have applied the 0. 35μm and 0. 20μm Fully Depleted SOI CMOS device to LSIs, and low-power LSI technology has been developed. This paper describes the development of the 0. 15μm FD-SOI CMOS device fabricated for the purpose of miniaturization and speed improvement, and the performance of digital circuits using this device. First of all, the methods used to achieve a low-power LSI will be described. Secondly, the structure and electrical characteristics of the 0. 15μm FD-SOI CMOS device with multiple threshold voltages, will be described. Finally, the experimental results of low-voltage digital circuits are described.
Germline PARP 4 mutations in patients with primary thyroid and breast cancers

Germline mutations in the PTEN gene, which cause Cowden syndrome, are known to be one of the genetic factors for primary thyroid and breast cancers; however, PTEN mutations are found in only a small subset of research participants with non-syndrome breast and thyroid cancers. In this study, we aimed to identify germline variants that may be related to genetic risk of primary thyroid and breast cancers. Genomic DNAs extracted from peripheral blood of 14 PTEN WT female research participants with primary thyroid and breast cancers were analyzed by whole-exome sequencing. Gene-based case-control association analysis using the information of 406 Europeans obtained from the 1000 Genomes Project database identified 34 genes possibly associated with the phenotype with P! 1.0! 10. Among them, rare variants in the PARP4 gene were detected at significant high frequency (odds ratioZ5.2; PZ1.0! 10). The variants, G496V and T1170I, were found in six of the 14 study participants (43%) while their frequencies were only 0.5% in controls. Functional analysis using HCC1143 cell line showed that knockdown of PARP4 with siRNA significantly enhanced the cell proliferation, compared with the cells transfected with siControl (PZ0.02). Kaplan–Meier analysis using Gene Expression Omnibus (GEO), European Genome-phenome Archive (EGA) and The Cancer Genome Atlas (TCGA) datasets showed poor relapse-free survival (P! 0.001, Hazard ratio 1.27) and overall survival (PZ0.006, Hazard ratio 1.41) in a PARP4 low-expression group, suggesting that PARP4 may function as a tumor suppressor. In conclusion, we identified PARP4 as a possible susceptibility gene of primary thyroid and breast cancer. Key Words
Hybrid approach for woven fabric modelling based on discrete hypoelastic behaviour and experimental validation

A non-linear discrete hybrid approach based on the association of hypoelastic continuous elements (non-linear shear behaviour) with specific connectors (non-linear tension stiffness) is developed. It allows the simulation of a two-dimensional (2D) woven reinforcement forming via an accurate explicit finite element analysis. This approach allows the simulation of 2D unbalanced fabrics uncoupling tensile and shear behaviour. It only needs a few parameters to be identified, and shows a good agreement with the experiments. The identification of the model parameters is investigated, and their relevance is analysed in reference tests. To determine the continuous element behaviour, a VUMAT hypoelastic model is implemented in Abaqus/Explicit. This model allows the prediction of fibre stresses and the accurate determination of shear angle in large deformations. Identification and validation of the model are performed using standard characterisation fabric tests. The experimental characterisation provided the numerical data to produce a representational prediction of the deformed fabric geometry and shear angle distribution. Further, the behaviour of the carbon woven reinforcement is identified. A bias extension test is used to both calibrate and validate the model. The capability of the model is illustrated to simulate deep drawing, and to compare with the experimental results of hemispherical forming.