nils-herrmann/clean_scirepeval huggingface dataset:
Effects of diclofenac sodium on the hippocampus of rats with acute subdural hematoma: histological, stereological, and molecular approach.
Venue: Folia neuropathologica

This study was aimed at evaluating the potential effects of acute subdural hematoma (ASDH) and diclofenac sodium (DS) therapy following ASDH on the rat hippocampus. Twenty four male Sprague Dawley rats were used and divided into four groups. 0.1 ml of non heparinized autologous blood from the tail vein of the animals in the non treatment group (NTG) and treatment group (TG) was injected into the subdural space. The TG received intramuscular diclofenac sodium at a 15 mg/kg dose daily from the postoperative second hour to the seventh day after the operation. The control group (CG) and sham group (SG) were used for control and sham operations, respectively. On the postoperative eighth day, all animals were sacrificed, and the hippocampi of all animals were stereologically and histologically evaluated. Also blood samples of the animals were biochemically analyzed. As a result of the study, the mean number of neurons in CA1, CA2, and CA3 regions of the hippocampus and the total number of neurons were decreased in the hippocampus samples of the NTG and especially the TG subjects. When comparing the second blood samples, there was no difference between the levels of adrenaline and serotonin among the groups. However, after the operation, noradrenalin levels in the treatment group were found to be higher than those of the sham and control groups (p 0.05) In the NTG and TG, histopathological findings were observed such as Nissl condensation as well as completely dead and indistinguishable neurons with abnormally shaped, shrunken cytoplasm and nuclei. Also necrotic areas on the specimens of the TG were seen. In immunohistochemical sections, c FOS positivity was decreased in the NTG and especially the TG. Otherwise, PGC 1 positive cells were increased in the NTG and especially the TG. In this study, it was shown for the first time by means of stereological techniques that using DS after ASDH caused a decrease in the number of hippocampal neurons (CA1, CA2, and CA3 regions)
Variants of early onset restrictive eating disturbances in middle childhood.
Venue: The International journal of eating disorders

This study sought to determine the factor structure of the newly developed self report screening questionnaire Eating Disturbances in Youth Questionnaire (EDY Q) as well as to report the distribution of variants of early onset restrictive eating disturbances characteristic of avoidant/restrictive food intake disorder (ARFID) in a middle childhood population sample.  Using the EDY Q, a total of 1,444 children aged 8 13 years were screened in elementary schools in Switzerland via self report. The factor analysis of the 12 items covering ARFID related symptoms was performed using a principal component analysis (PCA) RESULTS The PCA showed a four factor solution, with clear allocation to the scales covering three variants of early onset restrictive eating disturbances and weight problems. Inadequate overall food intake was reported by 19.3% of the children, a limited accepted amount of food by 26.1% and food avoidance based on a specific underlying fear by 5.0%  The postulated factor structure of the EDY Q was confirmed, further supporting the existence of distinct variants of early onset restrictive eating disturbances. Avoidant/restrictive eating behavior seems to be a common experience in middle childhood, but results have to be confirmed using validated interviews.
The Framework Design of Information System Audit in E government

Information system audit is a new auditing model derived from the digital information age. This method can not only detect the problems existing in the information system itself, but also carry out more systematic examination and evaluation, which has a positive role in promoting the quality of the audit and help to optimize the level of business as well as avoid audit risk. A case study of information system audit in a city was selected as subject investigated in this paper. The audit objectives and contents of government service center were summarized in this paper. Based on the general situation of information construction in the city, the security and reliability of the information system of the city were reviewed through the analysis of system structure and the corresponding software analysis method in this paper, and typical problems in the operation of the information system service center of the city were discussed combining the results of the review. Finally, the corresponding solutions were given.
Implementing heuristic miner for information system audit based on DSS01 COBIT5 (Case study: CV Narnia distribution)
Venue: 2016 International Conference on Computer, Control, Informatics and its Applications (IC3INA)

Information systems are able to support the operational activities and provide useful information for users. In fact almost every large companies implementing information systems, but controlling the information system needs additional efforts, one of which is the audit of information systems. Audit is believed to be able to identify risks and evaluate the adequacy of the important controls on information systems. Audits are generally examining data or document but the modern companies stored more detailed information in event logs, transaction logs, databases, data warehouses etc. In this research, COBIT 5 framework is offered as part of the assessment process improvement initiative or part of a capability determination approach. This research aims to renew two important steps in the assessment process, namely the data collection and validation, using a process mining approach. Thus the information systems audit uses process mining to extract knowledge from event logs into useful information for audit purposes. The output of this study is the finding of how process mining can be combined with other data collection methods to improve the results of the assessment program.
Implementing Lean Six Sigma to overcome the production challenges in an aerospace company

Six Sigma (LSS) has established itself as one of the key business process improvement strategies available to companies today. With roots based in the single strategies of Lean and Six Sigma, LSS offers a dual strategy towards systematically reducing waste and increasing value whilst resolving Critical to Quality (CTQ) issues that affect consistency and repeatability in a product and process. However, the predominating LSS approach is to employ the DMAIC cycle as the key driver in the implementation process. The authors argue that this reduces the effectiveness of LSS since a systematic lean thinking does not take place through this approach. This paper proposes a new Strategic Lean Six Sigma Framework (SLSSF) that attempts to create a more balanced and integrated approach between the Lean and Six Sigma elements and one that is capable of achieving greater efficiency of production whilst also ensuring variation reduction and CTQ issues are eradicated from the production process. The case study involves the application of the SLSSF in an aerospace manufacturing company. The work highlights the key stages of the framework before closing with an analysis of its effectiveness and the difficulties encountered in its application. When the LSS model was implemented, it achieved significant improvements in business performance. The key improvements were seen as; Build time reduction of 20.5% improved on time in full delivery to customer by 26.5% reduced value added time by 5% and reduced Non value added time by 44.5% Also, estimated financial savings of over PS2 Million are proposed.
Contractor Work Preparation Process Improvement Using Lean Six Sigma

To ensure the health and safety of their workforce and protection of their assets and the environment, a global oil and gas company operating in Indonesia requires comprehensive identification and evaluation of job hazards that were included in work permitting process prior work execution in the field. Based on 20 data points obtained in August 2013, start working time for contractors who worked for Capital Project Management (CPM) Team in Facility B was in average at 09.05 a.m. The aim of this paper is to present how the firm implemented Lean Six Sigma to reduce non added value activities while fulfilling to its safety requirements and to share lessons learned from practical and theory testing perspective. The methodology used is Lean Six Sigma's DMAIC (Define, Measure, Analyze, Improve, Control) as mandated by the corporate policy of the firm. This research adopts a mix methods approach, by using both qualitative and quantitative data. This study was a one year longitudinal study of the Lean Six Sigma implementation to improve contractors' work preparation process. The improvement resulted in reduction of non value added activities and successfully increased the available working time per day by 59.3 minutes in average. The results of this case study reconfirm Lean Six Sigma as a good management theory since it shows a consistency between the theory and the real practice in a global oil and gas company in Indonesia.
Evaluation of the performance of organizations that implemented Lean Manufacturing and Six Sigma methods application to French industries

Many industries conduct research in order to decide on the appropriate methodology for delivering optimal performance outcomes such as Lean Manufacturing or Six Sigma. Therefore, this research shows the influence of different categories based on the implementation method against three criteria: financial performance, operational performance and innovation performance. Research results indicate that companies implementing Lean Manufacturing and Six Sigma were more effective in improving company performance across financial and operational dynamics. Additionally, it shows companies who implemented Lean Manufacturing only saw improvements in innovation performance. Moreover, we found that Lean Manufacturing and Six Sigma practices such as One Piece Flow, Kanban, 5S, etc, supported increases in companies' performance. The statistical results also show that the key factors for the success of Lean Manufacturing and Six Sigma implementation could differ depending on the method employed.
Information extraction of extend relation in scientific papers
Venue: 2016 International Conference on Data and Software Engineering (ICoDSE)

Extend relation is one of the papers' relations obtained by using the citation context based approach where this approach can identify more varied papers relations than two other approaches i.e. content based and citation analysis. However, the recent research with citation context based approach only focuses on identification of relations, and cannot give out information related to this relation in more detail. The information of relation is very necessary for researchers in developing a research. In this paper, the scheme of information extraction process for extend relations is proposed which covers the classification process of extend categories and information extraction process based on the classification of extend categories. The experimental results show that the most optimal process in extend information extraction is reached by classifying extend categories from all sentences directly. The combination between the best extend categories classification and the proposed regular expression for relations information extraction delivered F Measure more than 50% This result can be said as good by considering that the proportion of extend sentence in the corpus is very small. The other experiment also shows that the optimal rule is reached for Data and Tool category.
Identifying Anomalous Citations for Objective Evaluation of Scholarly Article Impact
Venue: PloS one

Evaluating the impact of a scholarly article is of great significance and has attracted great attentions. Although citation based evaluation approaches have been widely used, these approaches face limitations e.g. in identifying anomalous citations patterns. This negligence would inevitably cause unfairness and inaccuracy to the article impact evaluation. In this study, in order to discover the anomalous citations and ensure the fairness and accuracy of research outcome evaluation, we investigate the citation relationships between articles using the following factors: collaboration times, the time span of collaboration, citing times and the time span of citing to weaken the relationship of Conflict of Interest (COI) in the citation network. Meanwhile, we study a special kind of COI, namely suspected COI relationship. Based on the COI relationship, we further bring forward the COIRank algorithm, an innovative scheme for accurately assessing the impact of an article. Our method distinguishes the citation strength, and utilizes PageRank and HITS algorithms to rank scholarly articles comprehensively. The experiments are conducted on the American Physical Society (APS) dataset. We find that about 80.88% articles contain contributed citations by co authors in 26,366 articles and 75.55% articles among these articles are cited by the authors belonging to the same affiliation, indicating COI and suspected COI should not be ignored for evaluating impact of scientific papers objectively. Moreover, our experimental results demonstrate COIRank algorithm significantly outperforms the state of art solutions. The validity of our approach is verified by using the probability of Recommendation Intensity.
Genome wide identification and expression profiling reveal tissue specific expression and differentially regulated genes involved in gibberellin metabolism between Williams banana and its dwarf mutant
Venue: BMC Plant Biology

BackgroundDwarfism is one of the most valuable traits in banana breeding because semi dwarf cultivars show good resistance to damage by wind and rain. Moreover, these cultivars present advantages of convenient cultivation, management, and so on. We obtained a dwarf mutant '8818 1' through EMS (ethyl methane sulphonate) mutagenesis of Williams banana 8818 (Musa spp. AAA group) Our research have shown that gibberellins (GAs) content in 8818 1 false stems was significantly lower than that in its parent 8818 and the dwarf type of 8818 1 could be restored by application of exogenous GA3. Although GA exerts important impacts on the 8818 1 dwarf type, our understanding of the regulation of GA metabolism during banana dwarf mutant development remains limited.ResultsGenome wide screening revealed 36 candidate GA metabolism genes were systematically identified for the first time; these genes included 3 MaCPS, 2 MaKS, 1 MaKO, 2 MaKAO, 10 MaGA20ox, 4 MaGA3ox, and 14 MaGA2ox genes. Phylogenetic tree and conserved protein domain analyses showed sequence conservation and divergence. GA metabolism genes exhibited tissue specific expression patterns. Early GA biosynthesis genes were constitutively expressed but presented differential regulation in different tissues in Williams banana. GA oxidase family genes were mainly transcribed in young fruits, thus suggesting that young fruits were the most active tissue involved in GA metabolism, followed by leaves, bracts, and finally approximately mature fruits. Expression patterns between 8818 and 8818 1 revealed that MaGA20ox4, MaGA20ox5, and MaGA20ox7 of the MaGA20ox gene family and MaGA2ox7, MaGA2ox12, and MaGA2ox14 of the MaGA2ox gene family exhibited significant differential expression and high expression levels in false stems. These genes are likely to be responsible for the regulation of GAs content in 8818 1 false stems.ConclusionOverall, phylogenetic evolution, tissue specificity and differential expression analyses of GA metabolism genes can provide a better understanding of GA regulated development in banana. The present results revealed that MaGA20ox4, MaGA20ox5, MaGA20ox7, MaGA2ox7, MaGA2ox12, and MaGA2ox14 were the main genes regulating GA content difference between 8818 and 8818 1. All of these genes may perform important functions in the developmental processes of banana, but each gene may perform different functions in different tissues or during different developmental stages.
Hybrid system for automatic classification of Diabetic Retinopathy using fundus images
Venue: 2016 Online International Conference on Green Engineering and Technologies (IC GET)

Diabetes over long duration causes damage of tiny blood vessel that nourishes the retina. This blood vessel leaks the blood and other fluids that cause swelling of retinal tissues. This leads to the Diabetic Retinopathy. Prolonged Diabetic Retinopathy may lead to vision loss. To prevent blindness, accurate detection at early stage is essential. We present a system for automatic classification of subjects as Diabetic Retinopathy and Normal by using fundus images which gives fast results when there is mass screening of Diabetic Retinopathy. Clinical features like blood vessel area, exudates area, bifurcation point and Non segmented texture based features were extracted from fundus images by using different techniques which helps in classifying the subjects. SVM a classifier is used, which classify subjects into Normal and DR based on features extracted.
Winning Arguments: Interaction Dynamics and Persuasion Strategies in Good faith Online Discussions
Venue: WWW

Changing someone's opinion is arguably one of the most important challenges of social interaction. The underlying process proves difficult to study: it is hard to know how someone's opinions are formed and whether and how someone's views shift. Fortunately, ChangeMyView, an active community on Reddit, provides a platform where users present their own opinions and reasoning, invite others to contest them, and acknowledge when the ensuing discussions change their original views. In this work, we study these interactions to understand the mechanisms behind persuasion. We find that persuasive arguments are characterized by interesting patterns of interaction dynamics, such as participant entry order and degree of back and forth exchange. Furthermore, by comparing similar counterarguments to the same opinion, we show that language factors play an essential role. In particular, the interplay between the language of the opinion holder and that of the counterargument provides highly predictive cues of persuasiveness. Finally, since even in this favorable setting people may not be persuaded, we investigate the problem of determining whether someone's opinion is susceptible to being changed at all. For this more difficult task, we show that stylistic choices in how the opinion is expressed carry predictive power.
Growth and development of soybean roots according to planting management systems and irrigation in lowland areas

The presence of a compacted soil layer near the ground surface in paddy fields may limit the growth and development of soybean roots. The objective of this study was to evaluate different planting management systems and irrigation on growth and development of soybean root systems in lowland area. The experiment was carried out in 2013/14 and 2014/15 crop seasons in randomized complete block design with factorial treatment (3x2) with four replications. The treatments consisted of different planting management systems: sowing with double disc (A1) sowing with shank (A2) and deep tillage sowing with double disc (A3) and irrigation: irrigated (D1) and non irrigated (D2) Planting management systems and irrigation influenced the growth of soybean roots. When double disc was used, roots have lower growth and increase in diameter. Use of shanks and deep tillage provide increased growth and development of soybean roots and greater depth distribution. An additional 55mm of irrigation during the V4 soybean development stage provides increased surface area and root volume in when the soil moisture reaches values below 60% of field capacity.
High Dimensional Continuous Control Using Generalized Advantage Estimation
Venue: ICLR

Policy gradient methods are an appealing approach in reinforcement learning because they directly optimize the cumulative reward and can straightforwardly be used with nonlinear function approximators such as neural networks. The two main challenges are the large number of samples typically required, and the difficulty of obtaining stable and steady improvement despite the nonstationarity of the incoming data. We address the first challenge by using value functions to substantially reduce the variance of policy gradient estimates at the cost of some bias, with an exponentially weighted estimator of the advantage function that is analogous to TD(lambda) We address the second challenge by using trust region optimization procedure for both the policy and the value function, which are represented by neural networks. Our approach yields strong empirical results on highly challenging 3D locomotion tasks, learning running gaits for bipedal and quadrupedal simulated robots, and learning a policy for getting the biped to stand up from starting out lying on the ground. In contrast to a body of prior work that uses hand crafted policy representations, our neural network policies map directly from raw kinematics to joint torques. Our algorithm is fully model free, and the amount of simulated experience required for the learning tasks on 3D bipeds corresponds to 1 2 weeks of real time.
Estimation of High Dimensional Graphical Models Using Regularized Score Matching.
Venue: Electronic journal of statistics

Graphical models are widely used to model stochastic dependences among large collections of variables. We introduce a new method of estimating undirected conditional independence graphs based on the score matching loss, introduced by Hyvarinen (2005) and subsequently extended in Hyvarinen (2007) The regularized score matching method we propose applies to settings with continuous observations and allows for computationally efficient treatment of possibly non Gaussian exponential family models. In the well explored Gaussian setting, regularized score matching avoids issues of asymmetry that arise when applying the technique of neighborhood selection, and compared to existing methods that directly yield symmetric estimates, the score matching approach has the advantage that the considered loss is quadratic and gives piecewise linear solution paths under l1 regularization. Under suitable irrepresentability conditions, we show that l1 regularized score matching is consistent for graph estimation in sparse high dimensional settings. Through numerical experiments and an application to RNAseq data, we confirm that regularized score matching achieves state of the art performance in the Gaussian case and provides a valuable tool for computationally efficient estimation in non Gaussian graphical models.