nils-herrmann/clean_scirepeval huggingface dataset:
Scaling and assessment of data quality.

The various physical factors affecting measured diffraction intensities are discussed, as are the scaling models which may be used to put the data on a consistent scale. After scaling, the intensities can be analysed to set the real resolution of the data set, to detect bad regions (e.g. bad images), to analyse radiation damage and to assess the overall quality of the data set. The significance of any anomalous signal may be assessed by probability and correlation analysis. The algorithms used by the CCP4 scaling program SCALA are described. A requirement for the scaling and merging of intensities is knowledge of the Laue group and point-group symmetries: the possible symmetry of the diffraction pattern may be determined from scores such as correlation coefficients between observations which might be symmetry-related. These scoring functions are implemented in a new program POINTLESS.
Ontologies and Semantics for Seamless Connectivity

The goal of having networks of seamlessly connected people, software agents and IT systems remains elusive. Early integration efforts focused on connectivity at the physical and syntactic layers. Great strides were made; there are many commercial tools available, for example to assist with enterprise application integration. It is now recognized that physical and syntactic connectivity is not adequate. A variety of research systems have been developed addressing some of the semantic issues. In this paper, we argue that ontologies in particular and semantics-based technologies in general will play a key role in achieving seamless connectivity. We give a detailed introduction to ontologies, summarize the current state of the art for applying ontologies to achieve semantic connectivity and highlight some key challenges.
Modeling and simulation tools for teaching protective relaying design and application for the smart grid

As the smart grid concepts are emphasized lately the need to modernize the power engineering education is also well recognized. This paper presents a set of newly developed modeling, simulation and testing tools aimed at better understanding the design concept and related applications for protective relaying and substation automation solutions for the smart grid. Since the smart grid applications require integration of data from multiple IEDs, understanding properties of each IED type in detail, as well as their responses to the power system events is needed. In addition, understanding the communication requirements to perform data integration is also important. To illustrate how the mentioned smart grid issues may be taught, the following advanced teaching approaches are presented: 1) Use of modeling and simulation means to better understand interaction between the relays and power system; 2) Use of IED test facilities to better understand performance of physical devices used for protection, monitoring and control; 3) Utilization of communication network modeling tools to simulate the communication network within Substation Automation System (SAS). Examples showing the use of proposed techniques for teaching the fundamentals and applications are presented. The examples demonstrate the adequacy and efficiency of the proposed techniques.
On 3D face reconstruction via cascaded regression in shape space

Cascaded regression has been recently applied to reconstruct 3D faces from single 2D images directly in shape space, and has achieved state-of-the-art performance. We investigate thoroughly such cascaded regression based 3D face reconstruction approaches from four perspectives that are not well been studied: (1) the impact of the number of 2D landmarks; (2) the impact of the number of 3D vertices; (3) the way of using standalone automated landmark detection methods; (4) the convergence property. To answer these questions, a simplified cascaded regression based 3D face reconstruction method is devised. This can be integrated with standalone automated landmark detection methods and reconstruct 3D face shapes that have the same pose and expression as the input face images, rather than normalized pose and expression. An effective training method is also proposed by disturbing the automatically detected landmarks. Comprehensive evaluation experiments have been carried out to compare to other 3D face reconstruction methods. The results not only deepen the understanding of cascaded regression based 3D face reconstruction approaches, but also prove the effectiveness of the proposed method.
Idiopathic Recurrent Gigantomastia: A Case Report

Gigantomastia is relatively rare and mostly unknown manifestation in its diagnostic and therapeutic approach. It is composed by many categories (idiopathic, Juvenile, pregnancy, Medication) that can affect women with strict profile. We report the case of a very important idiopathic gigantomastia which was operated using a technique with superior pedicle with resection of 5kg per breast. The evolution was marked by the occurrence of recurrence at 18 months. Through, the analysis of this observation and review of the literature, the authors review the different aspects of this pathology.
WSCOM: Online Task Scheduling with Data Transfers

This paper considers the online problem of task scheduling with communication. All information on tasks and communication are not available in advance except the DAG of task topology. This situation is typically encountered when scheduling DAG of tasks corresponding to Make files executions. To tackle this problem, we introduce a new variation of the work-stealing algorithm: WSCOM. These algorithms take advantage of the knowledge of the DAG topology to cluster communicating tasks together and reduce the total number of communications. Several variants are designed to overlap communication or optimize the graph decomposition. Performance is evaluated by simulation and our algorithms are compared with off-line list-scheduling algorithms and classical work-stealing from the literature. Simulations are executed on both random graphs and a new trace archive of Make file DAG. These experiments validate the different design choices taken. In particular we show that WSCOM is able to achieve performance close to off-line algorithms in most cases and is even able to achieve better performance in the event of congestion due to less data transfer. Moreover WSCOM can achieve the same high performances as the classical work-stealing with up to ten times less bandwidth.
Artificial perches promote vegetation restoration

Native ecosystems are continuously being transformed mostly into agricultural lands. Simultaneously, a large proportion of fields are abandoned after some years of use. Without any intervention, altered landscapes usually show a slow reversion to native ecosystems, or to novel ecosystems. One of the main barriers to vegetation regeneration is poor propagule supply. Many restoration programs have already implemented the use of artificial perches in order to increase seed availability in open areas where bird dispersal is limited by the lack of trees. To evaluate the effectiveness of this practice, we performed a series of meta-analyses comparing the use of artificial perches versus control sites without perches. We found that setting-up artificial perches increases the abundance and richness of seeds that arrive in altered areas surrounding native ecosystems. Moreover, density of seedlings is also higher in open areas with artificial perches than in control sites without perches. Taken together, our results support the use of artificial perches to overcome the problem of poor seed availability in degraded fields, promoting and/or accelerating the restoration of vegetation in concordance with the surrounding landscape.
Sentiment Analysis of Customer Review Data using Big Data: A Survey

Rapid evolution in technology and the internet brought us to the era of online services. E-commerce is nothing but trading goods or services online. Many customers share their good or bad opinions about products or services online nowadays. These opinions become a part of the decision-making process of consumer and make an impact on the business model of the provider. Also, understanding and considering reviews will help to gain the trust of the customer which will help to expand the business. Many users give reviews for the single product. Such thousands of review can be analyzed using big data effectively. The results can be presented in a convenient visual form for the non-technical user. Thus, the primary goal of research work is the classification of customer reviews given for the product in the map-reduce framework.
Rule based synonyms for entity extraction from noisy text

Identification of named entities such as person, organization and product names from text is an important task in information extraction. In many domains, the same entity could be referred to in multiple ways due to variations introduced by different user groups, variations of spellings across regions or cultures, usage of abbreviations, typographical errors and other reasons associated with conventional usage. Identifying a piece of text as a mention of an entity in such noisy data is difficult, even if we have a dictionary of possible entities. Previous approaches treat the synonym problem as part entity disambiguation and use learning-based methods that use the context of the words to identify synonyms. In this paper, we show that existing domain knowledge, encoded as rules, can be used effectively to address the synonym problem to a considerable extent. This makes the disambiguation task simpler, without the need for much training data. We look at a subset of application scenarios in named entity extraction, categorize the possible variations in entity names, and define rules for each category. Using these rules, we generate synonyms for the canonical list and match these synonyms to the actual occurrence in the data sets. In particular, we describe the rule categories that we developed for several named entities and report the results of applying our technique of extracting named entities by generating synonyms for two different domains.
Trajectories of resilience and dysfunction following potential trauma: A review and statistical evaluation.

Given the rapid proliferation of trajectory-based approaches to study clinical consequences to stress and potentially traumatic events (PTEs), there is a need to evaluate emerging findings. This review examined convergence/divergences across 54 studies in the nature and prevalence of response trajectories, and determined potential sources of bias to improve future research. Of the 67 cases that emerged from the 54 studies, the most consistently observed trajectories following PTEs were resilience (observed in: n = 63 cases), recovery (n = 49), chronic (n = 47), and delayed onset (n = 22). The resilience trajectory was the modal response across studies (average of 65.7% across populations, 95% CI [0.616, 0.698]), followed in prevalence by recovery (20.8% [0.162, 0.258]), chronicity (10.6%, [0.086, 0.127]), and delayed onset (8.9% [0.053, 0.133]). Sources of heterogeneity in estimates primarily resulted from substantive population differences rather than bias, which was observed when prospective data is lacking. Overall, prototypical trajectories have been identified across independent studies in relatively consistent proportions, with resilience being the modal response to adversity. Thus, trajectory models robustly identify clinically relevant patterns of response to potential trauma, and are important for studying determinants, consequences, and modifiers of course following potential trauma.
Stochastic separation theorems

The problem of non-iterative one-shot and non-destructive correction of unavoidable mistakes arises in all Artificial Intelligence applications in the real world. Its solution requires robust separation of samples with errors from samples where the system works properly. We demonstrate that in (moderately) high dimension this separation could be achieved with probability close to one by linear discriminants. Based on fundamental properties of measure concentration, we show that for M1-ϑ, where 1>ϑ>0 is a given small constant. Exact values of a,b>0 depend on the probability distribution that determines how the random M-element sets are drawn, and on the constant ϑ. These stochastic separation theorems provide a new instrument for the development, analysis, and assessment of machine learning methods and algorithms in high dimension. Theoretical statements are illustrated with numerical examples.
Performance of Islamic Banking and Conventional Banking in Pakistan: A Comparative Study

ACKNOWLEDGEMENT First of all I would like to thank my ALLAH Almighty Who gave me the courage, health, and energy to accomplish my thesis in due time and without Whose help this study which required untiring efforts would have not been possible to complete within the time limits. key elements required from the supervisor(s) to write and complete a thesis of a good standard and a quality within deadlines. It is a matter of utmost pleasure for me to extend my gratitude and give due credit to my supervisor Yinghong Chen whose support has always been there in need of time and who provided me with all these key elements to complete my dissertation within the time frame. Acknowledgement would be incomplete without extending my gratitude to one of my friends in Pakistan Mr. mammoth help in data collection made this study possible. Moreover, he has been supporting me enthusiastically throughout my work to make my thesis ready in due time. My thanks is also due to my examiner Max Zamanian whose valuable comments and suggestions made colossal contribution in improving my dissertation. Last but not least, I extend my thanks to my entire family for moral support and prays for my health and successful completion of my dissertation within time limits.  Islamic banking and finance in Pakistan started in 1977-78 with the elimination of interest in compliance with the Principles of Islamic Shari'ah in Islamic banking practices. Since then, amendments in financial system to allow the issuance of new interest-free instrument of corporate financing, promulgation of ordinance to permit the establishment of Mudaraba companies and floatation of Mudaraba Certificates, constitution of Commission for Transformation of Financial System (CTFS), and the establishments of Islamic Banking Department by the State Bank of Pakistan are some of the key steps taken place by the governments. The aim of this study is to examine and to evaluate the performance of the first Islamic bank in Pakistan, i.e. Meezan Bank Limited (MBL) in comparison with that of a group of 5 Pakistani conventional banks. The study evaluates performance of the Islamic bank (MBL) in profitability, liquidity, risk, and efficiency for the period of 2003-2007. Asset Utilization (AU), and Income to Expense ratio (IER) are used to assess banking performances. T-test and F-test are used in determining the significance of the differential performance of the two groups of banks. The study found that MBL …
Low intensity blood flow restriction training: a meta-analysis

The primary objective of this investigation was to quantitatively identify which training variables result in the greatest strength and hypertrophy outcomes with lower body low intensity training with blood flow restriction (LI-BFR). Searches were performed for published studies with certain criteria. First, the primary focus of the study must have compared the effects of low intensity endurance or resistance training alone to low intensity exercise with some form of blood flow restriction. Second, subject populations had to have similar baseline characteristics so that valid outcome measures could be made. Finally, outcome measures had to include at least one measure of muscle hypertrophy. All studies included in the analysis utilized MRI except for two which reported changes via ultrasound. The mean overall effect size (ES) for muscle strength for LI-BFR was 0.58 [95% CI: 0.40, 0.76], and 0.00 [95% CI: −0.18, 0.17] for low intensity training. The mean overall ES for muscle hypertrophy for LI-BFR training was 0.39 [95% CI: 0.35, 0.43], and −0.01 [95% CI: −0.05, 0.03] for low intensity training. Blood flow restriction resulted in significantly greater gains in strength and hypertrophy when performed with resistance training than with walking. In addition, performing LI-BFR 2–3 days per week resulted in the greatest ES compared to 4–5 days per week. Significant correlations were found between ES for strength development and weeks of duration, but not for muscle hypertrophy. This meta-analysis provides insight into the impact of different variables on muscular strength and hypertrophy to LI-BFR training.
Development of artificial empathy

We have been advocating cognitive developmental robotics to obtain new insight into the development of human cognitive functions by utilizing synthetic and constructive approaches. Among the different emotional functions, empathy is difficult to model, but essential for robots to be social agents in our society. In my previous review on artificial empathy (Asada, 2014b), I proposed a conceptual model for empathy development beginning with emotional contagion to envy/schadenfreude along with self/other differentiation. In this article, the focus is on two aspects of this developmental process, emotional contagion in relation to motor mimicry, and cognitive/affective aspects of the empathy. It begins with a summary of the previous review (Asada, 2014b) and an introduction to affective developmental robotics as a part of cognitive developmental robotics focusing on the affective aspects. This is followed by a review and discussion on several approaches for two focused aspects of affective developmental robotics. Finally, future issues involved in the development of a more authentic form of artificial empathy are discussed.
Being good at doing good? Quality and accountability of humanitarian NGOs.

Quality enhancement of humanitarian assistance is far from a technical task. It is interwoven with debates on politics of principles and people are intensely committed to the various outcomes these debates might have. It is a field of strongly competing truths, each with their own rationale and appeal. The last few years have seen a rapid increase in discussions, policy paper and organisational initiatives regarding the quality of humanitarian assistance. This paper takes stock of the present initiatives and of the questions raised with regard to the quality of humanitarian assistance.
Lantana camara leaf extract mediated silver nanoparticles: Antibacterial, green catalyst.

Silver nanoparticles (AgNPs) have been synthesized by Lantana camara leaf extract through simple green route and evaluated their antibacterial and catalytic activities. The leaf extract (LE) itself acts as both reducing and stabilizing agent at once for desired nanoparticle synthesis. The colorless reaction mixture turns to yellowish brown attesting the AgNPs formation and displayed UV-Vis absorption spectra. Structural analysis confirms the crystalline nature and formation of fcc structured metallic silver with majority (111) facets. Morphological studies elicit the formation of almost spherical shaped nanoparticles and as AgNO3 concentration is increased, there is an increment in the particle size. The FTIR analysis evidences the presence of various functional groups of biomolecules of LE is responsible for stabilization of AgNPs. Zeta potential measurement attests the higher stability of synthesized AgNPs. The synthesized AgNPs exhibited good antibacterial activity when tested against Escherichia coli, Pseudomonas spp., Bacillus spp. and Staphylococcus spp. using standard Kirby-Bauer disc diffusion assay. Furthermore, they showed good catalytic activity on the reduction of methylene blue by L. camara extract which is monitored and confirmed by the UV-Vis spectrophotometer.
Workplace learning - providing recommendations of experts and learning resources in a context-sensitive and personalized manner: An approach for ontology supported workplace learning

Support of workplace learning is increasingly important as change in every form determines today's working world in industry and public administrations alike. Adapt quickly to a new job, a new task or a new team is a major challenge that must be dealt with ever faster. Workplace learning differs significantly from school learning as it should be strictly aligned to business goals. In our approach we support workplace learning by providing recommendations of experts and learning resources in a context-sensitive and personalized manner. We utilize users' workplace environment, we consider their learning preferences and zone of proximal development, and compare required and acquired competencies in order to issue the best suited recommendations. Our approach is part of the European funded project Learn PAd. Applied research method is Design Science Research. Evaluation is done in an iterative process. The recommender system introduced here is evaluated theoretically based on user requirements and practically in an early evaluation process conducted by the Learn PAd application partner.
Combinatorial constructions for maximum optical orthogonal signature pattern codes

An (m, n, k, λa, λc) optical orthogonal signature pattern code (OOSPC) is a family C of m × n (0, 1)-matrices of Hamming weight k satisfying two correlation properties. OOSPCs find application in transmitting two-dimensional image through multicore fiber in CDMA networks. Let Θ(m, n, k, λa, λc) denote the largest possible number of codewords among all (m, n, k, λa, λc)-OOSPCs. An (m, n, k, λa, λc)-OOSPCwithΘ(m, n, k, λa, λc) codewords is said to be maximum. For the case λa = λc = λ, the notations (m, n, k, λa, λc)-OOSPC and Θ(m, n, k, λa, λc) can be briefly written as (m, n, k, λ)-OOSPC and Θ(m, n, k, λ). In this paper, some direct constructions for (3, n, 4, 1)-OOSPCs, which are based on skew starters and an application of the Theorem of Weil on multiplicative character sums, are given for some positive integer n. Several recursive constructions for (m, n, k, 1)-OOSPCs are presented by means of incomplete different matrices and group divisible designs. By utilizing those constructions, the number of the codewords of a maximum (m, n, 4, 1)OOSPC is determined for any positive integers m, n such that gcd(m, 18) = 3 and n ≡ 0 (mod 12). It is established that Θ(m, n, 4, 1) = (mn − 12)/12 for any positive integers m, n such that gcd(m, 18) = 3 and n ≡ 0 (mod 12).
Critical Success Factors for ERP Implementation : A Classification

In recent years research on ERP implementation has gained prominence because ERP, in most cases, has resulted in improving the efficiency and productivity of the user company. However, the decision to implement ERP alone is not a recipe of success, a lot depends on the planning and quality of implementation. Several factors are found to have an important role in the success of ERP implementation. In the ERP literature these factors are commonly described as Critical Success Factors (CSF). Several researchers have contributed to the body of literature pertaining to these CSF. However, the research in this area is still fragmented and unorganized. Hence, there is a need to identify and classify the relevant success factors, which is paramount for the success of ERP implementation. In this work we have classified various CSFs identified from literature in seven broad categories. This may help the practitioners and researchers in getting a quick understanding of these CSFs.