nils-herrmann/clean_scirepeval huggingface dataset:
Client-Centric Benchmarking of Eventual Consistency for Cloud Storage Systems

Eventually consistent storage systems give up the ACID semantics of conventional databases in order to gain better scalability, higher availability, and lower latency. A side-effect of this design decision is that application developers must deal with stale or out of order data. As a result, substantial intellectual effort has been devoted to studying the behavior of eventually consistent systems, in particular finding quantitative answers to the questions "how eventual" and "how consistent"?
Information Technology Service Management (ITSM): contributing Factors to IT Service disruptions - a Case of Malaysia Public Service Agencies

Researchers have highlighted that the main factors that contribute to IT service failure are the people, process and technology. However, relatively few empirical studies examine to what degree these factors contribute to service disruptions in the public sector organizations. This study explores the IT service management (ITSM) at eight (8) Front-end Agencies, four (4) Ministries and six (6) Departments in Malaysian public service to identify the level of contribution of each factor to the public IT service disruptions. This study was undertaken using questionnaires via stratified sampling. The empirical results reveal that human action, decision, management, error and failure are the major causes to the IT service disruptions followed by an improper process or procedures and technology failure. In addition, we can conclude that human is an important factor and need to give more attention by the management since human is the creator, who uses, manages and maintains the technology and process to enable the delivery of services as specified in the objectives, vision and mission of the organization. Although the literature states that human failure was due to knowledge, skill, attitude and behavior of an individual and the organization environment, but no literature was found studies on what characteristics of human and environmental organizations that make up the resilience service delivery and the creation of an organization that is resilient. Future research on what characteristics on human and organization environmental that contribute to organizational and business resilience is suggested at the end of the paper. However, this paper only covers literature that discussed in depth the type of human failure and the cause of failure. Nevertheless, it is believed that the findings provide a valuable understanding of the current situation in this research field.
Automatic Learning of Predictive CEP Rules: Bridging the Gap between Data Mining and Complex Event Processing

Due to the undeniable advantage of prediction and proactivity, many research areas and industrial applications are accelerating the pace to keep up with data science and predictive analytics. However and due to three well-known facts, the reactive Complex Event Processing (CEP) technology might lag behind when prediction becomes a requirement. 1st fact: The one and only inference mechanism in this domain is totally guided by CEP rules.  The only way to define a CEP rule is by writing it manually with the help of a human expert. 3rd fact: Experts tend to write reactive CEP rules, because and regardless of the level of expertise, it is nearly impossible to manually write predictive CEP rules. Combining these facts together, the CEP is---and will stay--- a reactive computing technique. Therefore in this article, we present a novel data mining-based approach that automatically learns predictive CEP rules. The approach proposes a new learning algorithm where complex patterns from multivariate time series are learned. Then at run-time, a seamless transformation into the CEP world takes place. The result is a ready-to-use CEP engine with enrolled predictive CEP rules. Many experiments on publicly-available data sets demonstrate the effectiveness of our approach.
New findings and concepts about the G-spot in normal and absent vagina: precautions possibly needed for preservation of the G-spot and sexuality during surgery.

The aim of this study was to extend the clinicohistological study to involve the whole normal and absent vagina for confirming the presence of the G-spot and its relation to the surrounding organs and sexuality and to identify certain precautions for its preservation during surgery.



This study was a descriptive randomized prospective study conducted at Kasr El Aini School of Medicine, Cairo University, Egypt. The G-spot was examined in 1500 women, 500 of them having vaginal and vulval surgery done for gynecological reasons. The G-spot was examined for its clinical and histological features and for determining the effect of surgery on its state and function.



The G-spot was found to be present in all women. It was a localized spot in 58% and diffuse in 42% of cases. Associated ejaculation was reported in all cases of the localized type and in 24.5% of the diffuse types. Clinical examination was found to be associated with certain local response in 52.7% of the local types. The G-spot was also found to be connected to the hymen in 100%, the urethra in 52.7%, the vulva in 82.2% and the cervix in 10.8% of cases. The mean of the sex scores and sexuality were significantly decreased in surgery involving the G-spot area. Recorded figures were 93.6 ± 3.4 and 88.2 ± 3.3 before and after surgery, respectively. The corresponding figures in the cases having a general spot were 86.4 ± 4.4 and 84.5 ± 2.4, respectively. The G-spot was found in cases of absent vagina to be localized in 59%, generalized in 28.2% and absent in 12.8% of cases.



The G-spot is actually present in all women. It is originally related to the lower urinary tract and it is connected to different parts of the genital tract. It may be localized or generalized. Its integrity is essential for obtaining normal physiological sexuality. Surgery may affect the integrity of the G-spot, so surgical precautions must be carried out to maintain the integrity of this spot and the patient's sexuality.
Representing Image Matrices : Eigenimages vs . Eigenvectors

We consider the problem of representing image matrices with a set of basis functions. One common solution for that problem is to first transform the 2D image matrices into 1D image vectors and then to represent those 1D image vectors with eigenvectors, as done in classical principal component analysis. In this paper, we adopt a natural representation for the 2D image matrices using eigenimages, which are 2D matrices with the same size of original images and can be directly computed from original 2D image matrices. We discuss how to compute those eigenimages effectively. Experimental result on ORL image database shows the advantages of eigenimages method in representing the 2D images.
Assessing the impact of life changes: development of the Life Experiences Survey.

This article describes the development of a new instrument, the Life Experiences Survey, for the measurement of life changes. It was designed to eliminate certain shortcomings of previous life stress measures and allows for separate assessment of positive and negative life experiences as well as individualized ratings of the impact of events. Several studies bearing on the usefulness of the Life Experiences Survey are presented, and the implications of the findings are discussed.
Artificial neural networks for pattern recognition

This tutorial article deals with the basics of artificial neural networks (ANN) and their applications in pattern recognition. ANN can be viewed as computing models inspired by the structure and function of the biological neural network. These models are expected to deal with problem solving in a manner different from conventional computing. A distinction is made between pattern and data to emphasize the need for developing pattern processing systems to address pattern recognition tasks. After introducing the basic principles of ANN, some fundamental networks are examined in detail for their ability to solve simple pattern recognition tasks. These fundamental networks together with the principles of ANN will lead to the development of architectures for complex pattern recognition tasks. A few popular architectures are described to illustrate the need to develop an architecture specific to a given pattern recognition problem. Finally several issues that still need to be addressed to solve practical problems using ANN approach are discussed.
State-of-the-art Vietnamese word segmentation

Word segmentation is the first step of any tasks in Vietnamese language processing. This paper reviews state-of-the-art approaches and systems for word segmentation in Vietnamese. To have an overview of all stages from building corpora to developing toolkits, we discuss building the corpus stage, approaches applied to solve the word segmentation and existing toolkits to segment words in Vietnamese sentences. In addition, this study shows clearly the motivations on building corpus and implementing machine learning techniques to improve the accuracy for Vietnamese word segmentation. According to our observation, this study also reports a few of achievements and limitations in existing Vietnamese word segmentation systems.
Efficient Multilabel Classification Algorithms for Large-Scale Problems in the Legal Domain

In this paper we applied multilabel classification algorithms to the EUR-Lex database of legal documents of the European Union. On this document collection, we studied three different multilabel classification problems, the largest being the categorization into the EUROVOC concept hierarchy with almost 4000 classes. We evaluated three algorithms: (i) the binary relevance approach which independently trains one classifier per label; (ii) the multiclass multilabel perceptron algorithm, which respects dependencies between the base classifiers; and (iii) the multilabel pairwise perceptron algorithm, which trains one classifier for each pair of labels. All algorithms use the simple but very efficient perceptron algorithm as the underlying classifier, which makes them very suitable for large-scale multilabel classification problems. The main challenge we had to face was that the almost 8,000,000 perceptrons that had to be trained in the pairwise setting could no longer be stored in memory. We solve this problem by resorting to the dual representation of the perceptron, which makes the pairwise approach feasible for problems of this size. The results on the EUR-Lex database confirm the good predictive performance of the pairwise approach and demonstrates the feasibility of this approach for large-scale tasks.
2 8 Ja n 20 18 HONE : Higher-Order Network Embeddings

This paper describes a general framework for learning Higher-Order Network Embeddings (HONE) from graph data based on network motifs. The HONE framework is highly expressive and flexible with many interchangeable components. The experimental results demonstrate the effectiveness of learning higher-order network representations. In all cases, HONE outperforms recent embedding methods that are unable to capture higher-order structures with a mean relative gain in AUC of 19% (and up to 75% gain) across a wide variety of networks and embedding methods.
Jointly modeling aspects, ratings and sentiments for movie recommendation (JMARS)

Recommendation and review sites offer a wealth of information beyond ratings. For instance, on IMDb users leave reviews, commenting on different aspects of a movie (e.g. actors, plot, visual effects), and expressing their sentiments (positive or negative) on these aspects in their reviews. This suggests that uncovering aspects and sentiments will allow us to gain a better understanding of users, movies, and the process involved in generating ratings.
 The ability to answer questions such as "Does this user care more about the plot or about the special effects?" or "What is the quality of the movie in terms of acting?" helps us to understand why certain ratings are generated. This can be used to provide more meaningful recommendations.
 In this work we propose a probabilistic model based on collaborative filtering and topic modeling. It allows us to capture the interest distribution of users and the content distribution for movies; it provides a link between interest and relevance on a per-aspect basis and it allows us to differentiate between positive and negative sentiments on a per-aspect basis. Unlike prior work our approach is entirely unsupervised and does not require knowledge of the aspect specific ratings or genres for inference.
 We evaluate our model on a live copy crawled from IMDb. Our model offers superior performance by joint modeling. Moreover, we are able to address the cold start problem -- by utilizing the information inherent in reviews our model demonstrates improvement for new users and movies.
Best practice in forensic entomology—standards and guidelines

Forensic entomology, the use of insects and other arthropods in forensic investigations, is becoming increasingly more important in such investigations. To ensure its optimal use by a diverse group of professionals including pathologists, entomologists and police officers, a common frame of guidelines and standards is essential. Therefore, the European Association for Forensic Entomology has developed a protocol document for best practice in forensic entomology, which includes an overview of equipment used for collection of entomological evidence and a detailed description of the methods applied. Together with the definitions of key terms and a short introduction to the most important methods for the estimation of the minimum postmortem interval, the present paper aims to encourage a high level of competency in the field of forensic entomology.
Autoranking Amazon Reviews

We consider the problem of predicting real valued scores for reviews based on various categories of features of the review text, and other metadata associated with the review, with the purpose of generating a rank for a given list of reviews. For this task, we explore various machine learning models and evaluate the effectiveness of them through a well known measure for goodness of fit. We also explored regularization methods to reduce variance in the model. Random forests was the most effective regressor in the end, outperforming all the other models that we have tried.
Novel terephthaloyl thiourea cross-linked chitosan hydrogels as antibacterial and antifungal agents.

Four novel terephthaloyl thiourea chitosan (TTU-chitosan) hydrogels were synthesized via a cross-linking reaction of chitosan with different concentrations of terephthaloyl diisothiocyanate. Their structures were investigated by elemental analyses, FTIR, SEM and X-ray diffraction. The antimicrobial activities of the hydrogels against three species of bacteria (Bacillis subtilis, Staphylococcus aureus and Escherichia coli) and three crop-threatening pathogenic fungi (Aspergillus fumigatus, Geotrichum candidum and Candida albicans) are much higher than that of the parent chitosan. The hydrogels were more potent in case of Gram-positive bacteria than Gram-negative bacteria. Increasing the degree of cross-linking in the hydrogels resulted in a stronger antimicrobial activity.
Relationships between personality, emotional labor, work engagement and job satisfaction in service professions.

Although there have been studies linking personality to selected aspects of functioning at work, Polish literature reports a shortage of detailed analyses considering, e.g., specific professional groups or certain variables. The aim of our study was to explore the links between personality traits and emotional labor, work engagement and job satisfaction among service workers.



The study was based on a cross-sectional, self-report survey of 137 workers representing different service industries in Poland. Each participant received a demographic data sheet and a set of questionnaires: NEO Five-Factor Inventory, the Deep Acting and Surface Acting Scale, the Job Satisfaction Scale and the Utrecht Work Engagement Scale - all in their Polish versions.



A correlation analysis revealed numerous relationships between the examined variables. However, results of the regression analysis showed that only some personality traits were related with individual aspects of functioning at work. Neuroticism accounted for the phenomenon of faking emotions. Conscientiousness was significantly related to general work engagement, vigor and dedication. Agreeableness and neuroticism significantly predicted job satisfaction.



Individual personality traits account for various aspects of work functioning.  Environ Health 2016;29(5):767-782.
Prevalence of eating disorders amongst dancers: a systemic review and meta-analysis.

Eating disorders in dancers are thought to be common, but the exact rates remain to be clarified. The aim of this study is to systematically compile and analyse the rates of eating disorders in dancers. A literature search, appraisal and meta-analysis were conducted. Thirty-three relevant studies were published between 1966 and 2013 with sufficient data for extraction. Primary data were extracted as raw numbers or confidence intervals. Risk ratios and 95% confidence intervals were calculated for controlled studies. The overall prevalence of eating disorders was 12.0% (16.4% for ballet dancers), 2.0% (4% for ballet dancers) for anorexia, 4.4% (2% for ballet dancers) for bulimia and 9.5% (14.9% for ballet dancers) for eating disorders not otherwise specified (EDNOS). The dancer group had higher mean scores on the EAT-26 and the Eating Disorder Inventory subscales. Dancers, in general, had a higher risk of suffering from eating disorders in general, anorexia nervosa and EDNOS, but no higher risk of suffering from bulimia nervosa. The study concluded that as dancers had a three times higher risk of suffering from eating disorders, particularly anorexia nervosa and EDNOS, specifically designed services for this population should be considered.
Dual-fisheye lens stitching and error correction

360-Degree panoramic cameras have been widely used in the field of computer vision and virtual reality recently. The use of fisheye lens to actualize a panoramic camera has become the industry trend. Fisheye lens has large distortion, and fisheye images have to be unwarped and blended to get 360-degree panoramic images, which has become two difficulties in fisheye lens practice. In this paper, a set of automatic 360-degree panoramic image generation algorithm which can be easily realized is proposed to solve these difficulties. The result shows that this software method can achieve high quality and low cost.
Mechanisms underlying skin disorders induced by EGFR inhibitors

The epidermal growth factor receptor (EGFR) is a receptor tyrosine kinase that is frequently mutated or overexpressed in a large number of tumors such as carcinomas or glioblastoma. Inhibitors of EGFR activation have been successfully established for the therapy of some cancers and are more and more frequently being used as first or later line therapies. Although the side effects induced by inhibitors of EGFR are less severe than those observed with classic cytotoxic chemotherapy and can usually be handled by out-patient care, they may still be a cause for dose reduction or discontinuation of treatment that can reduce the effectiveness of antitumor therapy. The mechanisms underlying these cutaneous side effects are only partly understood. Important questions, such as the reasons for the correlation between the intensity of the side effects and the efficiency of treatment with EGFR inhibitors, remain to be answered. Optimized adjuvant strategies to accompany anti-EGFR therapy need to be found for optimal therapeutic application and improved quality of life of patients. Here, we summarize current literature on the molecular and cellular mechanisms underlying the cutaneous side effects induced by EGFR inhibitors and provide evidence that keratinocytes are probably the optimal targets for adjuvant therapy aimed at alleviating skin toxicities.
WiFi-Opp: ad-hoc-less opportunistic networking

Opportunistic networking offers many appealing application perspectives from local social-networking applications to supporting communications in remote areas or in disaster and emergency situations. Yet, despite the increasing penetration of smartphones, opportunistic networking is not feasible with most popular mobile devices. There is still no support for WiFi Ad-Hoc and protocols such as Bluetooth have severe limitations (short range, pairing). We believe that WiFi Ad-Hoc communication will not be supported by most popular mobile OSes (i.e., iOS and Android) and that WiFi Direct will not bring the desired features. Instead, we propose WiFi-Opp, a realistic opportunistic setup relying on (i) open stationary APs and (ii) spontaneous mobile APs (i.e., smartphones in AP or tethering mode), a feature used to share Internet access, which we use to enable opportunistic communications. We compare WiFi-Opp to WiFi Ad-Hoc by replaying real-world contact traces and evaluate their performance in terms of capacity for content dissemination as well as energy consumption. While achieving comparable throughput, WiFi-Opp is up to 10 times more energy efficient than its Ad-Hoc counterpart. Eventually, a proof of concept demonstrates the feasibility of WiFi-Opp, which opens new perspectives for opportunistic networking.
Evaluation of different turbine concepts for wind power

Every year the number of installed wind power plants in the world increases. The horizontal axis wind turbine is the most common type of turbine but there exist other types. Here, three different wind turbines are considered; the horizontal axis wind turbine and two different concepts of vertical axis wind turbines; the Darrieus turbine and the H-rotor. This paper aims at making a comparative study of these three different wind turbines from the most important aspects including structural dynamics, control systems, maintenance, manufacturing and electrical equipment. A case study is presented where three different turbines are compared to each other. Furthermore, a study of blade areas for different turbines is presented. The vertical axis wind turbine appears to be advantageous to the horizontal axis wind turbine in several aspects. r 2007 Elsevier Ltd. All rights reserved.
TTS-GAN : A GENERATIVE ADVERSARIAL NETWORK FOR STYLE MODELING IN A TEXT-TO-SPEECH SYSTEM

The modeling of style when synthesizing natural human speech from text has been the focus of significant attention. Some state-of-the-art approaches train an encoder-decoder network on paired text and audio samples 〈xtxt, xaud〉 by encouraging its output to reconstruct xaud. The synthesized audio waveform is expected to contain the verbal content of xtxt and the auditory style of xaud. Unfortunately, modeling style in TTS is somewhat under-determined and training models with a reconstruction loss alone is insufficient to disentangle content and style from other factors of variation. In this work, we introduce TTS-GAN, an end-to-end TTS model that offers enhanced content-style disentanglement ability and controllability. We achieve this by combining a pairwise training procedure, an adversarial game, and a collaborative game into one training scheme. The adversarial game concentrates the true data distribution, and the collaborative game minimizes the distance between real samples and generated samples in both the original space and the latent space. As a result, TTS-GAN delivers a highly controllable generator, and a disentangled representation. Benefiting from the separate modeling of style and content, TTS-GAN can generate human fidelity speech that satisfies the desired style conditions. TTS-GAN achieves start-of-the-art results across multiple tasks, including style transfer (content and style swapping), emotion modeling, and identity transfer (fitting a new speaker’s voice).