nils-herrmann/clean_scirepeval huggingface dataset:
A Review on Proposal System of CPPCC
Year: 2015

After the Central Committee of the China Communism Party framed the Four Comprehensive Strategic Layout,Chinese People's Political Consultative Conference( CPPCC) is playing an increasingly important role in strengthening the construction of socialist deliberative democracy. CPPCC is also an important access to the reatization of people's democratic right. Motioning proposals is the most direct and effective means to perform CPPCC's duty. Therefore research on its proposal system is of great theoretical and practical significance. This essay sums up the progress phases of CPPCC's proposal system with relative researches done,especially important literature and studies in the new period. On this basis,some suggestions have been made in this paper to merit further study.
Teaching physical education teacher education (PETE) online: Challenges and solutions
Year: 2020

The COVID 19 pandemic has presented unprecedented challenges for physical education teacher education (PETE) and PETE appears to suffer the most when transitioning from face to face to virtual (online) environments due to the characteristics of PE. There is no literature found to address the profound challenges and solutions for teaching PETE online that we so desperately need nowadays. The present study examined specific challenges and solutions for online PETE. Future research directions are provided.
Elevated fecal levels of eosinophil granule proteins predict collagenous colitis in patients referred to colonoscopy due to chronic non bloody diarrhea
Venue: Scandinavian journal of gastroenterology
Year: 2016

Colonoscopy with biopsy sampling is often performed to detect collagenous colitis (CC) and lymphocytic colitis (LC) in patients with chronic non bloody diarrhea. However, the diagnostic yield is low and incurs high costs. Fecal calprotectin (FC) and myeloperoxidase (MPO) indicate intestinal inflammation in ulcerative colitis (UC) and Crohn's disease (CD) In CC, elevated fecal levels of eosinophil protein X (EPX) and eosinophil cationic protein (ECP) have been reported. We aimed to evaluate if F EPX, F ECP, FC, and F MPO could predict the diagnostic outcome in patients with chronic non bloody diarrhea referred to colonoscopy. We also evaluated serum (S) EPX and ECP in this regard.  Of 67 included patients, 63 (94% underwent colonoscopy with biopsy sampling. Fecal EPX, F ECP, FC, F MPO, S EPX, and S ECP were analyzed.  Diagnostic outcome: normal: n 46 (73% CC: n 9 (14% LC: n 4 (6% UC: n 2 (3% CD: n 2 (3% Higher levels of F EPX and F ECP were found in CC compared to a normal diagnostic outcome (p 0.01) No change was noted in any of the fecal markers in LC. When all of the fecal markers were normal the probability of a normal diagnostic outcome was 92% We found no differences in S EPX and S ECP between the groups.  Elevated F EPX and F ECP could predict CC. None of the fecal markers predicted LC. Serum EPX and S ECP are not useful for the diagnosis of CC, LC, UC, or CD. With normal levels in all of the analyzed fecal markers, there is a low probability of a pathologic diagnostic outcome.
ANALISIS PERMASALAHAN PELAJAR CACAT PENDENGARAN DALAM PEMBELAJARAN MATA PELAJARAN PENDIDIKAN ISLAM DI MALAYSIA
Year: 2016

Kajian ini mengupas permasalahan yang timbul semasa pelaksanaan pengajaran dan pembelajaran mata pelajaran Pendidikan Islam kepada pelajar cacat pendengaran di peringkat Sekolah Menengah Khas dan Program Pendidikan Khas Integrasi Sekolah Menengah di Malaysia. Kajian berbentuk kualitatif ini melibatkan 5 orang Guru Pendidikan Islam(GPIK) 3 orang Bekas Pelajar Cacat Pendengaran (BPP) dan 2 orang pakar cacat pendengaran Pendidikan Islam dan Pendidikan Khas (PPIK) dan 4 orang Pentadbir (GPKK) yang bertindak sebagai responden temubual. Hasil kajian bertujuan menzahirkan masalah yang sering berlaku kepada pelajar cacat pendengaran, khususnya dalam aspek masalah dari segi kemahiran bahasa. Masalah ini timbul adalah kerana sikap pelajar cacat pendengaran kurang membaca menyebabkan tiada input, masalah Bahan Bantu Belajar (BBM) di pasaran yang mesra pelajar murid tipikal. Dalam masa yang sama, masalah kurikulum yang begitu luas, kesukaran memahami sesuatu konsep yang disampaikan oleh guru, masalah ingatan jangka pendek (short memory) guru tidak mahir menggunakan bahasa isyarat, kod tangan terhad dan buku teks yang tidak sesuai. Kebanyakan buku teks hari ini adalah dalam bentuk tulisan jawi. Buku teks ini hanya sesuai untuk rujukan guru. Justeru itu, beberapa penambahbaikan perlu diberi perhatian serius dan disegerakan tindakan dengan menyemak semula kurikulum untuk murid cacat pendengaran dengan modifikasi mengikut keupayaan pelajar berkenaan, di samping berkolaborasi dengan pihak berkaitan bagi menghasilkan BBM yang sesuai dengan tahap kemampuan pelajar cacat pendengaran. Akhir sekali, guru dan ibubapa perlu sentiasa berfikiran terbuka dalam menerima anak anak istimewa ini.
"DRL FL" An intelligent resource allocation model based on deep reinforcement learning for Mobile Edge Computing
Venue: Comput. Commun.
Year: 2020

With the emergence of a large number of computation intensive and time sensitive applications, smart terminal devices with limited resources can only run the model training part of most intelligent applications in the cloud, so a large amount of training data needs to be uploaded to the cloud. This is an important cause of core network communication congestion and poor Quality of Experience (QoE) of user. As an important extension and supplement of cloud computing, Mobile Edge Computing (MEC) sinks computing and storage resources from the cloud to the vicinity of User Mobile Devices (UMDs) greatly reducing service latency and alleviating the burden on core networks. However, due to the high cost of edge servers deployment and maintenance, MEC also has the problems of limited network resources and computing resources, and the edge network environment is complex and mutative. Therefore, how to reasonably allocate network resources and computing resources in a changeable MEC environment has become a great aporia. To combat this issue, this paper proposes an intelligent resource allocation model "DRL FL" Based on this model, an intelligent resource allocation algorithm DDQN RA based on the emerging DRL algorithm framework DDQN is designed to adaptively allocate network and computing resources. At the same time, the model integrates the FL framework with the mobile edge system to train DRL agents in a distributed way. This model can well solve the problems of uploading large amounts of training data via wireless channels, Non IID and unbalance of training data when training DRL agents, restrictions on communication conditions, and data privacy. Experimental results show that the proposed "DRL FL" model is superior to the traditional resource allocation algorithms SDR and LOBO and the intelligent resource allocation algorithm DRLRA in three aspects: minimizing the average energy consumption of the system, minimizing the average service delay, and balancing resource allocation.
Machine Learning in Seismology: Turning Data into Insights
Year: 2019

This article provides an overview of current applications of machine learning (ML) in seismology. ML techniques are becoming increasingly widespread in seismology, with applications ranging from identifying unseen signals and patterns to extracting features that might improve our physical understanding. The survey of the applications in seismology presented here serves as a catalyst for further use of ML. Five research areas in seismology are surveyed in which ML classification, regression, clustering algorithms show promise: earthquake detection and phase picking, earthquake early warning (EEW) ground motion prediction, seismic tomography, and earthquake geodesy. We conclude by discussing the need for a hybrid approach combining data driven ML with traditional physical modeling.
Fast Video Completion using patch based synthesis and image registration
Venue: 2014 International Symposium on Intelligent Signal Processing and Communication Systems (ISPACS)
Year: 2014

Video completion has many applications in movie post production, such as removing unwanted objects, artifacts, or logos. Most state of the art video completion techniques are time consuming in order to ensure spatial temporal coherence. This paper presents a Fast Video Completion (FVC) technique that is based on patch based synthesis and image registration. FVC generates key frames without the unwanted objects over the input video using a patch based synthesis. The rest of the video completion process requires a low computing time using the registered prior frame. The results of the proposed technique show that FVC preserves the spatial temporal coherence in an acceptable time, that makes the proposed technique is applicable for long videos.
Canada's longest experience with extracorporeal membrane oxygenation as a bridge to lung transplantation: a case report.
Venue: Transplantation proceedings
Year: 2015

Extracorporeal membrane oxygenation (ECMO) is a method of enabling gas exchange through an external membrane used to treat respiratory failure in critically ill patients. ECMO as a bridge to lung transplantation has been investigated as a potential method of reducing lung transplantation waitlist mortality. Herein we describe a case of ECMO as a bridge to lung transplantation for the duration of 35 days, which is the longest documented length of ECMO support before successful transplantation in Canada.  The prospective recipient was a 28 year old female suffering from stage 4 pulmonary sarcoidosis. Given an acute exacerbation of her chronic respiratory failure, ECMO had to be initiated. She remained on ECMO for 35 days until a suitable set of donor lungs became available. The recipient had a prolonged course in hospital but was successfully discharged home where she continues to have good lung function. She remains alive and well at home 5 months post transplantation and continues to improve and gain strength.  Our case provides hope that in the future we may be able to expand the population of recipients who may be candidates for lung transplantation. This case adds to the growing literature on the role of ECMO as a bridge to lung transplantation with the potential to reduce patient deaths while wait listed for lung transplantation as well as increase the number of transplantations being performed.
The effect of pro environmental preferences on bond prices: Evidence from green bonds
Year: 2019

We use green bonds as an instrument to identify the effect of non pecuniary motives, specifically pro environmental preferences, on bond market prices. We perform a matching method, followed by a two step regression procedure, to estimate the yield differential between a green bond and a counterfactual conventional bond from July 2013 to December 2017. The results suggest a small negative premium: the yield of a green bond is lower than that of a conventional bond. On average, the premium is 2 basis points for the entire sample and for euro and USD bonds separately. We show that this negative premium is more pronounced for financial and low rated bonds. The results emphasize the low impact of investors' pro environmental preferences on bond prices, which does not represent, at this stage, a disincentive for investors to support the expansion of the green bond market.
Strictly Proper Scoring Rules, Prediction, and Estimation
Year: 2007

Scoring rules assess the quality of probabilistic forecasts, by assigning a numerical score based on the predictive distribution and on the event or value that materializes. A scoring rule is proper if the forecaster maximizes the expected score for an observation drawn from the distributionF if he or she issues the probabilistic forecast F, rather than G F. It is strictly proper if the maximum is unique. In prediction problems, proper scoring rules encourage the forecaster to make careful assessments and to be honest. In estimation problems, strictly proper scoring rules provide attractive loss and utility functions that can be tailored to the problem at hand. This article reviews and develops the theory of proper scoring rules on general probability spaces, and proposes and discusses examples thereof. Proper scoring rules derive from convex functions and relate to information measures, entropy functions, and Bregman divergences. In the case of categorical variables, we prove a rigorous version of the Savage representation. Examples of scoring rules for probabilistic forecasts in the form of predictive densities include the logarithmic, spherical, pseudospherical, and quadratic scores. The continuous ranked probability score applies to probabilistic forecasts that take the form of predictive cumulative distribution functions. It generalizes the absolute error and forms a special case of a new and very general type of score, the energy score. Like many other scoring rules, the energy score admits a kernel representation in terms of negative definite functions, with links to inequalities of Hoeffding type, in both univariate and multivariate settings. Proper scoring rules for quantile and interval forecasts are also discussed. We relate proper scoring rules to Bayes factors and to cross validation, and propose a novel form of cross validation known as random fold cross validation. A case study on probabilistic weather forecasts in the North American Pacific Northwest illustrates the importance of propriety. We note optimum score approaches to point and quantile estimation, and propose the intuitively appealing interval score as a utility function in interval estimation that addresses width as well as coverage.
Hybrid Clustering of Text Mining and Bibliometrics Applied to Journal Sets
Venue: SDM
Year: 2009

To obtain correlated and complementary information contained in text mining and bibliometrics, hybrid clustering to incorporate textual content and citation information has become a popular strategy. In this paper, we propose a new computational framework of integrating text mining and bibliometrics to provide a mapping of journal sets. Two different approaches of hybrid clustering methods are applied in this paper. The first category is ensemble clustering, which combines different clustering results obtained from individual data into a consolidated clustering result. The second category is kernel fusion, which maps heterogeneous data sets into the kernel space and combines the kernel matrices for clustering. Kernels can be combined either averagely, or by an optimized weighted linear combination model. In this paper, we propose a novel adaptive kernel K means clustering algorithm to combine textual content and citation information for clustering. The proposed algorithm is systematically compared with other methods on a clustering problem of 1869 journals published in 2002 2006. Based on several validation indices, the experimental results demonstrate that our hybrid clustering strategy is able to provide clustering result as well as the best individual data source.
Analysis of OpenMP and MPI implementations of meta heuristics for vehicle routing problems
Venue: Appl. Soft Comput.
Year: 2016

Graphical abstractDisplay Omitted HighlightsWe parallelize a sequential meta heuristic based on simulated annealing.The island and master worker models, and OpenMP and MPI implementations are used.Vehicle routing problems with time windows are used as benchmarks.The performance of multithreading and multi core processing is analyzed.The different implementation alternatives are statistically compared by using ANOVA. The parallelization of heuristic methods allows the researchers both to explore the solution space more extensively and to accelerate the search process. Nowadays, there is an increasing interest on developing parallel algorithms using standard software components that take advantage of modern microprocessors including several processing cores with local and shared cache memories. The aim of this paper is to show it is possible to parallelize algorithms included in computational software using standard software libraries in low cost multi core systems, instead of using expensive high performance systems or supercomputers. In particular, it is analyzed the benefits provided by master worker and island parallel models, implemented with MPI and OpenMP software libraries, to parallelize population based meta heuristics. The capacitated vehicle routing problem with hard time windows (VRPTW) has been used to evaluate the performance of these parallel strategies. The empirical results for a set of Solomon's benchmarks show that the parallel approaches executed on a multi core processor produce better solutions than the sequential algorithm with respect to both the quality of the solutions obtained and the runtime required to get them. Both MPI and OpenMP parallel implementations are able to obtain better or at least equal solutions (in terms of distance traveled) than the best known ones for the considered benchmark instances.
Nonlinear forced vibrations and static deformations of 3D beams with rectangular cross section: The influence of warping, shear deformation and longitudinal displacements
Year: 2010

The geometrically nonlinear vibrations of beams with rectangular cross section, which may experience longitudinal, torsional and bending deformations, in any plane, are investigated by the p version finite element method. Two main models are used: one of them is based on Bernoulli Euler theory for beam bending and the other is based on Timoshenko theory; both models assume that the cross section rotates as a rigid body and is free to warp in longitudinal direction, as in Saint Venants's theory for torsion. The geometrical nonlinearity is taken into account by considering Green's strain tensor and the importance of the longitudinal displacements of quadratic order, which are most often neglected in the strain displacement relation, is here examined. Generalized Hooke's law is used and the equation of motion is derived by the principle of virtual work. The importance of the warping function is analysed for different rectangular cross sections, and it is shown that its consideration can be fundamental to obtain correct results. Then, it is shown that the linearization of the trigonometric functions related with the twist angle, which is usually applied in the displacement field in models based on Saint Venant's hypothesis, should be done in the strain displacement relations. Comparisons of the models for 3D beams based on Bernoulli Euler's and Timoshenko's theories is presented. It is shown that if the rotations along the transverse axes are directly approximated by the respective derivatives of the transverse displacement functions, as is assumed in the model presented here that is based on Bernoulli Euler's theory, the additional shear stresses that appear when the bending and torsion motions are coupled, lead to wrong results. Finally, taking into account accuracy and simplicity, a model is chosen and employed to investigate the nonlinear forced vibrations of beams using direct integration of the equations of motion in the time domain. Examples of bending torsion couplings due to the nonlinear terms are presented in dynamical problems.
EFFECTS OF MONOCULAR DEPRIVATION ON THE THICKNESS OF NEURAL RETINA
Year: 2015

Monocular visual deprivation as a result of cataracts occurring in children who previously had normal vision may result in permanent visual deficits. However, if correction is done before the age of ten years, vision is usually restored to normal levels in the affected eye. This has been attributed to plastic changes that occur in the visual cortex, with no mention of the contribution of the retina to this plasticity.  To describe the effect of monocular deprivation on the thickness of neural retina.  Quasi experimental study using a rabbit model.  30 rabbits (18 experimental, 12 controls) were examined. Monocular deprivation was achieved through unilateral lid suture in the experimental animals. The rabbits were observed for three weeks. Each week, 6 experimental and 3 control animals were euthanized, their retina harvested and processed for light microscopy. In experimental animals, retina of both deprived (closed) and non deprived (open) eyes were studied. Haematoxylin Eosin stain was used to demonstrate the layers of the retina. Photomicrographs of the retina were taken using a digital camera then entered into FIJI software for analysis.  In the deprived eyes, the neural retina thickness reduced by 40.5% from the baseline (p 0.001) Compared to controls, statistically significant reduction in thickness was noted in the ganglion (p 0.001) inner nuclear (p 0.001) rod and cones (p 0.001) outer plexiform (p 0.008) nerve fiber (p 0.010) and inner plexiform (p 0.024) layers. Among the non deprived eyes, the neural retina thickness increased by 9.8% from baseline (p 0.075) Compared to controls, statistically significant increase in thickness was seen in the inner plexiform (p 0.001) inner nuclear (p 0.002) and rods and cones (p 0.007) layers.  Monocular deprivation results in atrophy of the retina in the deprived eye. Thus, pre retinal causes of blindness such as cataracts affects the retina and should be corrected early so as to minimize damage to the retina of the deprived eye.
Distinct prophase arrest mechanisms in human male meiosis
Year: 2017

To prevent chromosomal aberrations to be transmitted to the offspring, strict meiotic checkpoints are in place to remove aberrant spermatocytes. However, in about 1% of all males these checkpoints cause complete meiotic arrest leading to azoospermia and subsequent infertility. We here unravel two clearly distinct meiotic arrest mechanisms that act during the prophase of human male meiosis. Type I arrested spermatocytes display severe asynapsis of the homologous chromosomes, disturbed XY body formation and increased expression of the Y chromosome encoded gene ZFY and seem to activate a DNA damage pathway leading to induction of p63 mediated spermatocyte elimination. Type II arrested spermatocytes display normal chromosome synapsis, normal XY body morphology and meiotic crossover formation but have a lowered expression of several cell cycle regulating genes and fail to properly silence the X chromosome encoded gene ZFX. Discovery and understanding of these meiotic arrest mechanisms increases our knowledge on how genomic stability is guarded during human germ cell development.
Antecedents of ERP systems implementation success: a study on Jordanian healthcare sector
Venue: J. Enterp. Inf. Manag.
Year: 2016

Most small and medium sized enterprises (SMEs) use some business management software to manage their daily operations. Ultimately they consider transitioning to an enterprise resources planning (ERP) system. However, implementing ERP system successfully is costly and complex, and often shows high disappointment rates or even abandonment due to need of fit with the business or social culture. In Jordan, large businesses have been using the ERP system for a long time, but SMEs usage of the system is relatively new. The purpose of this paper is to study the effect of ERP implementation success antecedents which consists of training, supportive leadership and ease of use on ERP implementation success itself through a mediating effect of user satisfaction.  Empirical data were collected using a survey questionnaire which was distributed to ERP users in Jordanian healthcare organizations. A total of 175 responses were collected and analyzed using structure equation modeli.