nils-herrmann/clean_scirepeval huggingface dataset:
Verbal working memory and sentence comprehension.

This target article discusses the verbal working memory system used in sentence comprehension. We review the concept of working memory as a short-duration system in which small amounts of information are simultaneously stored and manipulated in the service of accomplishing a task. We summarize the argument that syntactic processing in sentence comprehension requires such a storage and computational system. We then ask whether the working memory system used in syntactic processing is the same as that used in verbally mediated tasks that involve conscious controlled processing. Evidence is brought to bear from various sources: the relationship between individual differences in working memory and individual differences in the efficiency of syntactic processing; the effect of concurrent verbal memory load on syntactic processing; and syntactic processing in patients with poor short-term memory, patients with poor working memory, and patients with aphasia. Experimental results from these normal subjects and patients with various brain lesions converge on the conclusion that there is a specialization in the verbal working memory system for assigning the syntactic structure of a sentence and using that structure in determining sentence meaning that is separate from the working memory system underlying the use of sentence meaning to accomplish other functions. We present a theory of the divisions of the verbal working memory system and suggestions regarding its neural basis.
Phi.sh/$oCiaL: the phishing landscape through short URLs

Size, accessibility, and rate of growth of Online Social Media (OSM) has attracted cyber crimes through them. One form of cyber crime that has been increasing steadily is phishing, where the goal (for the phishers) is to steal personal information from users which can be used for fraudulent purposes. Although the research community and industry has been developing techniques to identify phishing attacks through emails and instant messaging (IM), there is very little research done, that provides a deeper understanding of phishing in online social media. Due to constraints of limited text space in social systems like Twitter, phishers have begun to use URL shortener services. In this study, we provide an overview of phishing attacks for this new scenario. One of our main conclusions is that phishers are using URL shorteners not only for reducing space but also to hide their identity. We observe that social media websites like Facebook, Habbo, Orkut are competing with e-commerce services like PayPal, eBay in terms of traffic and focus of phishers.  Habbo, and Facebook are amongst the top 5 brands targeted by phishers. We study the referrals from Twitter to understand the evolving phishing strategy. A staggering 89% of references from Twitter (users) are inorganic accounts which are sparsely connected amongst themselves, but have large number of followers and followees. We observe that most of the phishing tweets spread by extensive use of attractive words and multiple hashtags. To the best of our knowledge, this is the first study to connect the phishing landscape using blacklisted phishing URLs from PhishTank, URL statistics from bit.ly and cues from Twitter to track the impact of phishing in online social media.
Anatomy of the facial nerve branching patterns, the marginal mandibular branch and its extraparotid ramification in relation to the lateral palpebral line.

Surgery of face and parotid gland may cause injury to branches of the facial nerve, which results in paralysis of muscles of facial expression. Knowledge of branching patterns of the facial nerve and reliable landmarks of the surrounding structures are essential to avoid this complication.  Determine the facial nerve branching patterns, the course of the marginal mandibular branch (MMB), and the extraparotid ramification in relation to the lateral palpebral line (LPL).  One hundred cadaveric half-heads were dissected for determining the facial nerve branching patterns according to the presence of anastomosis between branches. The course of the MMB was followed until it entered the depressor anguli oris in 49 specimens. The vertical distance from the mandibular angle to this branch was measured. The horizontal distance from the LPL to the otobasion superious (LPL-OBS) and the apex of the parotid gland (LPL-AP) were measured in 52 specimens.  The branching patterns of the facial nerve were categorized into six types. The least common (1%) was type I (absent of anastomosis), while type V, the complex pattern was the most common (29%). Symmetrical branching pattern occurred in 30% of cases. The MMB was coursing below the lower border of the mandible in 57% of cases. The mean vertical distance was 0.91±0.22 cm. The mean horizontal distances of LPL-OBS and LPLAP were 7.24±0.6 cm and 3.95±0.96 cm, respectively. The LPL-AP length was 54.5±11.4% of LPL-OBS.  More complex branching pattern of the facial nerve was found in this population and symmetrical branching pattern occurred less of ten. The MMB coursed below the lower border of the angle of mandible with a mean vertical distance of one centimeter. The extraparotid ramification of the facial nerve was located in the area between the apex of the parotid gland and the LPL.
Personality and adaptive performance at work: a meta-analytic investigation.

We examined emotional stability, ambition (an aspect of extraversion), and openness as predictors of adaptive performance at work, based on the evolutionary relevance of these traits to human adaptation to novel environments. A meta-analysis on 71 independent samples (N = 7,535) demonstrated that emotional stability and ambition are both related to overall adaptive performance. Openness, however, does not contribute to the prediction of adaptive performance. Analysis of predictor importance suggests that ambition is the most important predictor for proactive forms of adaptive performance, whereas emotional stability is the most important predictor for reactive forms of adaptive performance. Job level (managers vs. employees) moderates the effects of personality traits: Ambition and emotional stability exert stronger effects on adaptive performance for managers as compared to employees.
Theory of Planned Behavior and Personality

Academic misconduct in the forms of cheating and plagiarism is a large and growing problem that has been acknowledged in both the public and academic realms. In 2000, three-quarters of American college and university students said they had cheated on an exam (Williams, 2001). Additionally, according to a survey by Who’s Who  2001). Cheating, plagiarism and other forms of academic misconduct have been documented in several large, multi-institution survey-based studies (Davis, Grover, Becker, & McGregor, 1992; McCabe & Trevino, 1993, 1997; Whitley, 1998) as well as in a number of smaller survey and experimental studies conducted at individual institutions (Bolin, 2004; Bunn, Caudill, & Gropper, 1992; Smyth, & Davis, 2004). There has been a relative paucity of work, however, that has tried to explain academic misconduct behaviors based on a theoretical model. In the current study, we draw on Ajzen’s (1991) Theory of Planned Behavior to integrate previous research and predict academic misconduct.
3DContextNet: K-d Tree Guided Hierarchical Learning of Point Clouds Using Local and Global Contextual Cues

Classification and segmentation of 3D point clouds are important tasks in computer vision. Because of the irregular nature of point clouds, most of the existing methods convert point clouds into regular 3D voxel grids before they are used as input for ConvNets. Unfortunately, voxel representations are highly insensitive to the geometrical nature of 3D data. More recent methods encode point clouds to higher dimensional features to cover the global 3D space. However, these models are not able to sufficiently capture the local structures of point clouds. Therefore, in this paper, we propose a method that exploits both local and global contextual cues imposed by the k-d tree. The method is designed to learn representation vectors progressively along the tree structure. Experiments on challenging benchmarks show that the proposed model provides discriminative point set features. For the task of 3D scene semantic segmentation, our method significantly outperforms the state-of-the-art on the Stanford Large-Scale 3D Indoor Spaces Dataset (S3DIS).
Simplified Reactive Power Control for Single-Phase Grid-Connected Photovoltaic Inverters

A simple photovoltaic (PV) system capable of operating in grid-connected mode and using multilevel boost converter (MBC) and line commutated inverter (LCI) has been developed for extracting the maximum power and feeding it to a single phase utility grid with harmonic reduction. Theoretical analysis of the proposed system is done and the duty ratio of the MBC is estimated for extracting maximum power from PV array. For a fixed firing angle of LCI, the proposed system is able to track the maximum power with the determined duty ratio which remains the same for all irradiations. This is the major advantage of the proposed system which eliminates the use of a separate maximum power point tracking (MPPT) Experiments have been conducted for feeding a single phase voltage to the grid. So by proper and simplified technique we are reducing the harmonics in the grid for unbalanced loads.
Connectivity Stability in Autonomous Multi-level UAV Swarms for Wide Area Monitoring

Many different types of unmanned aerial vehicles (UAVs) have been developed to address a variety of applications ranging from searching and mapping to surveillance. However, for complex wide-area surveillance scenarios, where fleets of autonomous UAVs must be deployed to work collectively on a common goal, multiple types of UAVs should be incorporated forming a heterogeneous UAV system. Indeed, the interconnection of two levels of UAVs---one with high altitude fixed-wing UAVs and one with low altitude rotary-wing UAVs---can provide applicability for scenarios which cannot be addressed by either UAV type. This work considers a bi-level flying ad hoc networks (FANETs), in which each UAV is equipped with ad hoc communication capabilities, in which the higher level fixed-wing swarm serves mainly as a communication bridge for the lower level UAV fleets, which conduct precise information sensing. The interconnection of multiple UAV types poses a significant challenge, since each UAV level moves according to its own mobility pattern, which is constrained by the UAV physical properties. Another important challenge is to form network clusters at the lower level, whereby the intra-level links must provide a certain degree of stability to allow a reliable communication within the UAV system. This article proposes a novel mobility model for the low-level UAVs that combines a pheromone-based model with a multi-hop clustering algorithm. The pheromones permit to focus on the least explored areas with the goal to optimize the coverage while the multi-hop clustering algorithm aims at keeping a stable and connected network. The proposed model works online and is fully distributed. The connection stability is evaluated against different measurements such as stability coefficient and volatility. The performance of the proposed model is compared to other state-of-the-art contributions using simulations. Experimental results demonstrate the ability of the proposed mobility model to significantly improve the network stability while having a limited impact on the wide-area coverage.
Cyberbullying: its nature and impact in secondary school pupils.

Cyberbullying describes bullying using mobile phones and the internet. Most previous studies have focused on the prevalence of text message and email bullying.



Two surveys with pupils aged 11-16 years: (1) 92 pupils from 14 schools, supplemented by focus groups; (2) 533 pupils from 5 schools, to assess the generalisability of findings from the first study, and investigate relationships of cyberbullying to general internet use. Both studies differentiated cyberbullying inside and outside of school, and 7 media of cyberbullying.



Both studies found cyberbullying less frequent than traditional bullying, but appreciable, and reported more outside of school than inside. Phone call and text message bullying were most prevalent, with instant messaging bullying in the second study; their impact was perceived as comparable to traditional bullying. Mobile phone/video clip bullying, while rarer, was perceived to have more negative impact. Age and gender differences varied between the two studies. Study 1 found that most cyberbullying was done by one or a few students, usually from the same year group. It often just lasted about a week, but sometimes much longer. The second study found that being a cybervictim, but not a cyberbully, correlated with internet use; many cybervictims were traditional 'bully-victims'. Pupils recommended blocking/avoiding messages, and telling someone, as the best coping strategies; but many cybervictims had told nobody about it.



Cyberbullying is an important new kind of bullying, with some different characteristics from traditional bullying. Much happens outside school. Implications for research and practical action are discussed.
The Lattice Boltzmann Equation Method : Fundamentals , Place and Perspectives

The Lattice Boltzmann Equation (LBE) method is reviewed and analyzed. The focus is on the fundamental principles of the approach; its `pros' and `cons' in comparison to other methods of the computational uid dynamics (CFD); and its perspectives as a competitive alternative computational approach for uid dynamics. An excursion into the history, physical background and details of the theory and numerical implementation is made, with special attention paid to the method's advantages, limitations and perspectives to be a useful framework to incorporate molecular interactions for description of complex interfacial phenomena; eÆciency and simplicity for modeling of hydrodynamics, comparing it to the methods, which directly solve for transport equations of macroscopic variables (\traditional CFD").
A review of the literature on employee turnover

“Employee turnover” as a term is widely used in business circles. Although several studies have been conducted on this topic, most of the researchers focus on the causes of employee turnover but little has been done on the examining the sources of employee turnover, effects and advising various strategies which can be used by managers in various organisations to ensure that there is employee continuity in their organisations to enhance organizational competitiveness. This paper examines the sources of employee turnover, effects and forwards some strategies on how to minimize employee turnover in organisations.
YAGO3: A Knowledge Base from Multilingual Wikipedias

We present YAGO3, an extension of the YAGO knowledge base that combines the information from the Wikipedias in multiple languages. Our technique fuses the multilingual information with the English WordNet to build one coherent knowledge base. We make use of the categories, the infoboxes, and Wikidata, and learn the meaning of infobox attributes across languages. We run our method on 10 different languages, and achieve a precision of 95%-100% in the attribute mapping. Our technique enlarges YAGO by 1m new entities and 7m new facts.
Lipids and lipid-based formulations: optimizing the oral delivery of lipophilic drugs

Highly potent, but poorly water-soluble, drug candidates are common outcomes of contemporary drug discovery programmes and present a number of challenges to drug development — most notably, the issue of reduced systemic exposure after oral administration. However, it is increasingly apparent that formulations containing natural and/or synthetic lipids present a viable means for enhancing the oral bioavailability of some poorly water-soluble, highly lipophilic drugs. This Review details the mechanisms by which lipids and lipidic excipients affect the oral absorption of lipophilic drugs and provides a perspective on the possible future applications of lipid-based delivery systems. Particular emphasis has been placed on the capacity of lipids to enhance drug solubilization in the intestinal milieu, recruit intestinal lymphatic drug transport (and thereby reduce first-pass drug metabolism) and alter enterocyte-based drug transport and disposition.
The Effects of Functional Training on Pain, Function, and Performance in Taekwondo Players with Mechanical Low Back Pain

The aim of this study was to assess the effects of functional training (FT) on pain, function, and performance in elite male taekwondo players with CMLBP.  27 elite male taekwondo players (mean ± standard deviation: age 24.4 ± 4.9 years, body mass 75.7 ± 15.1 kg, height 181.4 ± 7.8 cm) were allocated to two experimental (n = 15) and control (n = 12) groups. The eight-week FT was divided into four distinct phases for the subjects of the experimental group. Variables of pain and function were assessed by Visual Analogue Scale (VAS) and Oswestry Disability Index (ODI), respectively. The movement time of Ap Douliou Chagi kick (MTAK) and speed of Ap Douliou Chagi kick (SAK) was used for the variable of performance.  Considering the results of pre-test before the implementation of the scores protocol, after FT intervention, VAS (p = 0.004), ODI (p = 0.005), MTAK on the right leg (p = 0.029) and the left leg (p = 0.013) decreased and SAK on both legs (p = 0.000) increased significantly in comparison with the control group.  It is assumed that FT can reduce the pain intensity and improve the function and performance in taekwondo players.
Hey Cortana ! Exploring the use cases of a Desktop based Digital

With the advent of improved speech recognition and information retrieval systems, more and more users are increasingly relying on digital assistants to solve their information needs. Intelligent digital assistants on mobile devices and computers, such as Windows Cortana and Apple Siri, provide users with more functionalities than was possible in the traditional web search paradigm. While most user interaction studies have focused on the traditional web search seing; in this work, we instead consider user interactions with digital assistants (e.g. Cortana, Siri) and aim at identifying the dierences in user interactions, session characteristics and use cases. To our knowledge, this is one of the rst studies investigating the dierent use cases of user interactions with a desktop based digital assistant. Our analysis reveals that given the conversational nature of user interactions, longer sessions (i.e. sessions with a large number of queries) are more common than they were in the traditional web search paradigm. Exploring the dierent use cases, we observe that users go beyond general search and use a digital assistant to issue commands, seek instant answers and nd local information. Our analysis could inform the design of future support systems capable of proactively understanding user needs and developing enhanced evaluation techniques for developing appropriate metrics for the evaluation of digital assistants.
An Operation Sequence Model for Explainable Neural Machine Translation

We propose to achieve explainable neural machine translation (NMT) by changing the output representation to explain itself. We present a novel approach to NMT which generates the target sentence by monotonically walking through the source sentence. Word reordering is modeled by operations which allow setting markers in the target sentence and move a target-side write head between those markers. In contrast to many modern neural models, our system emits explicit word alignment information which is often crucial to practical machine translation as it improves explainability. Our technique can outperform a plain text system in terms of BLEU score under the recent Transformer architecture on JapaneseEnglish and Portuguese-English, and is within 0.5 BLEU difference on Spanish-English.
Serverless Computing: An Investigation of Factors Influencing Microservice Performance

Serverless computing platforms provide function(s)-as-a-Service (FaaS) to end users while promising reduced hosting costs, high availability, fault tolerance, and dynamic elasticity for hosting individual functions known as microservices. Serverless Computing environments, unlike Infrastructure-as-a-Service (IaaS) cloud platforms, abstract infrastructure management including creation of virtual machines (VMs), operating system containers, and request load balancing from users. To conserve cloud server capacity and energy, cloud providers allow hosting infrastructure to go COLD, deprovisioning containers when service demand is low freeing infrastructure to be harnessed by others. In this paper, we present results from our comprehensive investigation into the factors which influence microservice performance afforded by serverless computing. We examine hosting implications related to infrastructure elasticity, load balancing, provisioning variation, infrastructure retention, and memory reservation size. We identify four states of serverless infrastructure including: provider cold, VM cold, container cold, and warm and demonstrate how microservice performance varies up to 15x based on these states.
The effects of customer relationship management relational information processes on customer-based performance

This study investigated the influence of the completeness of CRM relational information processes on customer-based relational performance and profit performance. In addition, interaction orientation and CRM readiness were adopted as moderators on the relationship between CRM relational information processes and customer-based performance. Both qualitative and quantitative approaches were applied in this study. The results revealed that the completeness of CRM relational information processes facilitates customer-based relational performance (i.e., customer satisfaction, and positive WOM), and in turn enhances profit performance (i.e., efficiency with regard to identifying, acquiring and retaining, and converting unprofitable customers to profitable ones). The alternative model demonstrated that both interaction orientation and CRM readiness play a mediating role in the relationship between information processes and relational performance. Managers should strengthen the completeness and smoothness of CRM information processes, should increase the level of interactional orientation with customers and should maintain firm CRM readiness to service their customers. The implications of this research and suggestions for managers were also discussed.
Knowledge Base Question Answering Based on Deep Learning Models

This paper focuses on the task of knowledge-based question answering (KBQA). KBQA aims to match the questions with the structured semantics in knowledge base. In this paper, we propose a two-stage method. Firstly, we propose a topic entity extraction model (TEEM) to extract topic entities in questions, which does not rely on hand-crafted features or linguistic tools. We extract topic entities in questions with the TEEM and then search the knowledge triples which are related to the topic entities from the knowledge base as the candidate knowledge triples. Then, we apply Deep Structured Semantic Models based on convolutional neural network and bidirectional long short-term memory to match questions and predicates in the candidate knowledge triples. To obtain better training dataset, we use an iterative approach to retrieve the knowledge triples from the knowledge base. The evaluation result shows that our system achieves an AverageF1 measure of 79.57% on test dataset.