nils-herrmann/clean_scirepeval huggingface dataset:
Estimates of Seismic Potential in the Marmara Sea Region from Block Models of Secular Deformation Constrained by Global Positioning System Measurements

We model the geodetically observed secular velocity field in northwestern Turkey with a block model that accounts for recoverable elastic-strain accumulation. The block model allows us to estimate internally consistent fault slip rates and locking depths. The northern strand of the North Anatolian fault zone (NAFZ) carries approximately four times as much right-lateral motion ( 24 mm/yr) as does the southern strand. In the Marmara Sea region, the data show strain accumulation to be highly localized. We find that a straight fault geometry with a shallow locking depth of 6–7 km fits the observed Global Positioning System velocities better than does a stepped fault geometry that follows the northern and eastern edges of the sea. This shallow locking depth suggests that the moment release associated with an earthquake on these faults should be smaller, by a factor of 2.3, than previously inferred assuming a locking depth of 15 km.  an updated version of velocity-field data.
Normative beliefs about aggression as a mediator of narcissistic exploitativeness and cyberbullying.

The current study examined normative beliefs about aggression as a mediator between narcissistic exploitativeness and cyberbullying using two Asian adolescent samples from Singapore and Malaysia. Narcissistic exploitativeness was significantly and positively associated with cyberbullying and normative beliefs about aggression and normative beliefs about aggression were significantly and positively associated with cyberbullying. Normative beliefs about aggression were a significant partial mediator in both samples; these beliefs about aggression served as one possible mechanism of action by which narcissistic exploitativeness could exert its influence on cyberbullying.  extended previous empirical research by showing that such beliefs can be the mechanism of action not only in offline but also in online contexts and across cultures. Cyberbullying prevention and intervention efforts should include modification of norms and beliefs supportive of the legitimacy and acceptability of cyberbullying.
Issues in Design and Deployment of Ad Hoc Networks

Mobile computing is where the future is. This theme is not far fetched. We all want anywhere anytime communication. Ubiquitous communication has been made possible in the recent years with the advent of mobile ad hoc networks. The benefits of ubiquitous connectivity not only makes our lives more comfortable but also helps businesses efficiently deploy and manage their resources. These infrastructureless networks that enable " anywhere anytime " information access pose several challenging issues. There are several issues in the design and realization of these networks. Mobility planning is tricky and needs to be designed more carefully. Keeping track of mobiles in the infrastructure, the problem more popularly known as the location management problem, is another key issue to be addressed. The load on the servers, for handling location updates and queries, needs to be balanced. Moreover, the operation needs to be robust due to a high probability of temporary or permanent unavailability of one or more of the intermediate nodes. The transport protocols also need to be robust as a high degree of interference and noise can be expected in such environments. Applications will have to designed to incorporate environment-specific features in order to make them more robust. We believe that satisfactory solutions to these problems are essential in order to create smart environments using ad hoc networking infrastructure. While medium access in wireless networks still remains an active research area due to the limited availability of wireless bandwidth, the absence of infrastructure makes the problem more challenging. Mobility, being one of the inherent properties of ad hoc networks, results in frequent changes in the network topology, making routing in such dynamic environments complex. In short, the presence of wireless medium, mobility, and lack of infrastructure makes the problem of routing and scheduling far more challenging in ad hoc networks. Providing services in such networks while guaranteeing the performance requirements specified by the users remains an interesting and active research area. This issue of MONET is dedicated to papers relating to this topic. These papers are selected from the papers published in The papers were revised and reviewed again. In this special issue, we have selected seven papers covering various aspects of routing, multicasting, and Quality-of-Service in these networks. The first paper by Tang, Correa and Gerla, " Effects of Ad Hoc MAC Layer Medium Access Mechanisms under TCP " , deals with the issues in medium access control …
An overview of global gold market and gold price forecasting

The global gold market has recently attracted a lot of attention and the price of gold is relatively higher than its historical trend. For mining companies to mitigate risk and uncertainty in gold price fluctuations, make hedging, future investment and evaluation decisions, depend on forecasting future price trends. The first section of this paper reviews the world gold market and the historical trend of gold prices from January 1968 to December 2008. This is followed by an investigation into the relationship between gold price and other key influencing variables, such as oil price and global inflation over the last 40 years. The second section applies a modified econometric version of the longterm trend reverting jump and dip diffusion model for forecasting natural-resource commodity prices. This method addresses the deficiencies of previous models, such as jumps and dips as parameters and unit root test for long-term trends. The model proposes that historical data of mineral commodities have three terms to demonstrate fluctuation of prices: a long-term trend reversion component, a diffusion component and a jump or dip component. The model calculates each term individually to estimate future prices of mineral commodities. The study validates the model and estimates the gold price for the next 10 years, based on monthly historical data of nominal gold price. & 2010 Elsevier Ltd. All rights reserved.
A practical guide to treatment of infantile hemangiomas of the head and neck.

Infantile hemangiomas are the most common benign vascular tumors in infancy and childhood. As hemangioma could regress spontaneously, it generally does not require treatment unless proliferation interferes with normal function or gives rise to risk of serious disfigurement and complications unlikely to resolve without treatment. Various methods for treating infant hemangiomas have been documented, including wait and see policy, laser therapy, drug therapy, sclerotherapy, radiotherapy, surgery and so on, but none of these therapies can be used for all hemangiomas. To obtain the best treatment outcomes, the treatment protocol should be individualized and comprehensive as well as sequential. Based on published literature and clinical experiences, we established a treatment guideline in order to provide criteria for the management of head and neck hemangiomas. This protocol will be renewed and updated to include and reflect any cutting-edge medical knowledge, and provide the newest treatment modalities which will benefit our patients.
Universal Transformers

Self-attentive feed-forward sequence models have been shown to achieve impressive results on sequence modeling tasks including machine translation , image generation [30] and constituency parsing [18], thereby presenting a compelling alternative to recurrent neural networks (RNNs) which has remained the de-facto standard architecture for many sequence modeling problems to date. Despite these successes, however, feed-forward sequence models like the Transformer  fail to generalize in many tasks that recurrent models handle with ease (e.g. copying strings or even simple logical inference when the string or formula lengths exceed those observed at training time [28]). Moreover, and in contrast to RNNs, the Transformer model is not computationally universal, limiting its theoretical expressivity. In this paper we propose the Universal Transformer which addresses these practical and theoretical shortcomings and we show that it leads to improved performance on several tasks. Instead of recurring over the individual symbols of sequences like RNNs, the Universal Transformer repeatedly revises its representations of all symbols in the sequence with each recurrent step. In order to combine information from different parts of a sequence, it employs a self-attention mechanism in every recurrent step. Assuming sufficient memory, its recurrence makes the Universal Transformer computationally universal. We further employ an adaptive computation time (ACT) mechanism to allow the model to dynamically adjust the number of times the representation of each position in a sequence is revised. Beyond saving computation, we show that ACT can improve the accuracy of the model. Our experiments show that on various algorithmic tasks and a diverse set of large-scale language understanding tasks the Universal Transformer generalizes significantly better and outperforms both a vanilla Transformer and an LSTM in machine translation, and achieves a new state of the art on the bAbI linguistic reasoning task and the challenging LAMBADA language modeling task.
Immigrants and borderline personality disorder at a psychiatric emergency service.

Several studies have suggested that immigrants have higher rates of psychiatric emergency service use and a higher risk of mental disorders such as schizophrenia than indigenous populations.



To compare the likelihood that immigrants (immigrant group) v. indigenous population (indigenous group) will be diagnosed with borderline personality disorder in a psychiatric emergency service and to determine differences according to area of origin.



A total of 11 578 consecutive admissions over a 4-year period at a tertiary psychiatric emergency service were reviewed. The collected data included socio-demographic and clinical variables and the Severity of Psychiatric Illness rating score. Psychiatric diagnosis was limited to information available in the emergency room given that a structured interview is not usually feasible in this setting. The diagnosis of borderline personality disorder was based on DSM-IV criteria. Immigrants were divided into five groups according to region of origin: North Africa, sub-Saharan Africa, South America, Asia and Western countries.



Multivariate statistical logistic regression analysis showed that all subgroups of immigrants had a lower likelihood of being diagnosed with borderline personality disorder than the indigenous population independently of age and gender. Furthermore, the rates of borderline personality disorder diagnosis were considerably lower in Asian and sub-Saharan subgroups than in South American, North African, Western or native subgroups.



Our results showed that in the psychiatric emergency service borderline personality disorder was diagnosed less frequently in the immigrant group v. the indigenous group. Our results do not support the concept of migration as a risk factor for borderline personality disorder.
Few-shot learning for short text classification

Due to the limited length and freely constructed sentence structures, it is a difficult classification task for short text classification. In this paper, a short text classification framework based on Siamese CNNs and few-shot learning is proposed. The Siamese CNNs will learn the discriminative text encoding so as to help classifiers distinguish those obscure or informal sentence. The different sentence structures and different descriptions of a topic are viewed as ‘prototypes’, which will be learned by few-shot learning strategy to improve the classifier’s generalization. Our experimental results show that the proposed framework leads to better results in accuracies on twitter classifications and outperforms some popular traditional text classification methods and a few deep network approaches.
Community Detection and Mining in Social Media

The chapter 1 on Social Media and Social Computing has documented the nature and characteristics of social networks and community detection. The explanation about the emerging of social networks and their properties constitute this chapter followed by a discussion on social community. The nodes, ties and influence in the social networks are the core of the discussion in the second chapter. Centrality is the core discussion here and the degree of centrality and its measure is explained. Understanding network topology is required for social networks concepts.
People thinking about thinking people: The role of the temporo-parietal junction in “theory of mind”

Humans powerfully and flexibly interpret the behaviour of other people based on an understanding of their minds: that is, we use a "theory of mind." In this study we distinguish theory of mind, which represents another person's mental states, from a representation of the simple presence of another person per se. The studies reported here establish for the first time that a region in the human temporo-parietal junction (here called the TPJ-M) is involved specifically in reasoning about the contents of another person's mind. First, the TPJ-M was doubly dissociated from the nearby extrastriate body area (EBA; Downing et al., 2001). Second, the TPJ-M does not respond to false representations in non-social control stories. Third, the BOLD response in the TPJ-M bilaterally was higher when subjects read stories about a character's mental states, compared with stories that described people in physical detail, which did not differ from stories about nonhuman objects. Thus, the role of the TPJ-M in understanding other people appears to be specific to reasoning about the content of mental states.
Current saturation in zero-bandgap, top-gated graphene field-effect transistors.

The novel electronic properties of graphene, including a linear energy dispersion relation and purely two-dimensional structure, have led to intense research into possible applications of this material in nanoscale devices. Here we report the first observation of saturating transistor characteristics in a graphene field-effect transistor. The saturation velocity depends on the charge-carrier concentration and we attribute this to scattering by interfacial phonons in the SiO2 layer supporting the graphene channels. Unusual features in the current-voltage characteristic are explained by a field-effect model and diffusive carrier transport in the presence of a singular point in the density of states. The electrostatic modulation of the channel through an efficiently coupled top gate yields transconductances as high as 150 microS microm-1 despite low on-off current ratios. These results demonstrate the feasibility of two-dimensional graphene devices for analogue and radio-frequency circuit applications without the need for bandgap engineering.
Effect of propranolol on word fluency in autism.

Autism is characterized by repetitive behaviors and impaired socialization and communication. Preliminary evidence showed possible language benefits in autism from the β-adrenergic antagonist propranolol. Earlier studies in other populations suggested propranolol might benefit performance on tasks involving a search of semantic and associative networks under certain conditions. Therefore, we wished to determine whether this benefit of propranolol includes an effect on semantic fluency in autism.



A sample of 14 high-functioning adolescent and adult participants with autism and 14 matched controls were given letter and category word fluency tasks on 2 separate testing sessions; 1 test was given 60 minutes after the administration of 40 mg propranolol orally, and 1 test was given after placebo, administered in a double-blinded, counterbalanced manner.



Participants with autism were significantly impaired compared with controls on both fluency tasks. Propranolol significantly improved performance on category fluency, but not letter fluency among autism participants. No drug effect was observed among controls. Expected drug effects on heart rate and blood pressure were observed in both the groups.



Results are consistent with a selective beneficial effect of propranolol on flexibility of access to semantic and associative networks in autism, with no observed effect on phonological networks. Further study will be necessary to understand potential clinical implications of this finding.
Befriending Computer Programming: A Proposed Approach to Teaching Introductory Programming

The problems encountered by students in first year computer programming units are a common concern in many universities including Victoria University. A fundamental component of a computer science curriculum, computer programming is a mandatory unit in a computing course. It is also one of the most feared and hated units by many novice computing students who, having failed or performed poorly in a programming unit, often drop out from a course. This article discusses some of the difficulties experienced by first year programming students, and reviews some of the initiatives undertaken to counter the problems. The article also reports on the first stage of a current research project at Victoria University that aims to develop a balanced approach to teaching first year programming units; its goal is to ‘befriend’ computer programming to help promote success among new programming students.
Web Usability: Principles and Evaluation Methods

Current Web applications are very complex and high sophisticated software products, whose usability can heavily determine their success or failure. Defining methods for ensuring usability is one of the current goals of the Web Engineering research. Also, much attention on usability is currently paid by Industry, which is recognizing the importance of adopting methods for usability evaluation before and after the application deployment. This chapter introduces principles and evaluation methods to be adopted during the whole application lifecycle for promoting usability. For each evaluation method, the main features, as well as the emerging advantages and drawbacks are illustrated, so as to support the choice of an evaluation plan that best fits the goals to be pursued and the available resources. The design and evaluation of a real application is also described for exemplifying the introduced concepts and methods.
The neurocognitive effects of alcohol on adolescents and college students.

Adolescents and college students are at high risk for initiating alcohol use and high-risk (or binge) drinking. There is a growing body of literature on neurotoxic and harmful cognitive effects of drinking by young people. On average, youths take their first drink at age 12 years.



MEDLINE search on neurologic and cognitive effects of underage drinking.



Problematic alcohol consumption is not a benign condition that resolves with age. Individuals who first use alcohol before age 14 years are at increased risk of developing alcohol use disorders. Underage drinkers are susceptible to immediate consequences of alcohol use, including blackouts, hangovers, and alcohol poisoning and are at elevated risk of neurodegeneration (particularly in regions of the brain responsible for learning and memory), impairments in functional brain activity, and the appearance of neurocognitive deficits. Heavy episodic or binge drinking impairs study habits and erodes the development of transitional skills to adulthood.



Underage alcohol use is associated with brain damage and neurocognitive deficits, with implications for learning and intellectual development. Impaired intellectual development may continue to affect individuals into adulthood. It is imperative for policymakers and organized medicine to address the problem of underage drinking.
A Globally Convergent Filter Method for Nonlinear Programming

In this paper we present a filter algorithm for nonlinear programming and prove its global convergence to stationary points. Each iteration is composed of a feasibility phase, which reduces a measure of infeasibility, and an optimality phase, which reduces the objective function in a tangential approximation of the feasible set. These two phases are totally independent, and the only coupling between them is provided by the filter. The method is independent of the internal algorithms used in each iteration, as long as these algorithms satisfy reasonable assumptions on their efficiency. Under standard hypotheses, we show two results: for a filter with minimum size, the algorithm generates a stationary accumulation point; for a slightly larger filter, all accumulation points are stationary.
Closed structure soft robotic gripper

This work describes a new kind of soft gripper. Inspiration on nature is usual in Soft Robotics device creation. In this case, the inspiration came from a sea lamprey in order to create a closed structure soft robotic gripper. Usually the grippers have one or more soft actuators that act like fingers. Since it is difficult to know whether the fingers are really grasping an object, it is being proposed a closed structure to deal with this problem. While the proposed gripper involves the object as whole, a homogeneous force is applied on it. In addition to the details of the closed structure actuator manufacture description, two procedure tests are presented: an analysis of load versus pressure function and of the force versus pressure characteristics. At the end, some new research topics to the proposed soft gripper are discussed.
Shedding light on photophobia.

Photophobia is a common yet debilitating symptom seen in many ophthalmic and neurologic disorders. Despite its prevalence, it is poorly understood and difficult to treat. However, the past few years have seen significant advances in our understanding of this symptom. We review the clinical characteristics and disorders associated with photophobia, discuss the anatomy and physiology of this phenomenon, and conclude with a practical approach to diagnosis and treatment.
Detecting Changes in Twitter Streams using Temporal Clusters of Hashtags

Detecting events from social media data has important applications in public security, political issues, and public health. Many studies have focused on detecting specific or unspecific events from Twitter streams. However, not much attention has been paid to detecting changes, and their impact, in online conversations related to an event. We propose methods for detecting such changes, using clustering of temporal profiles of hashtags, and three change point detection algorithms. The methods were tested on two Twitter datasets: one covering the 2014 Ottawa shooting event, and one covering the Sochi winter Olympics. We compare our approach to a baseline consisting of detecting change from raw counts in the conversation. We show that our method produces large gains in change detection accuracy on both datasets.
Zerocoin: Anonymous Distributed E-Cash from Bitcoin

Bitcoin is the first e-cash system to see widespread adoption. While Bitcoin offers the potential for new types of financial interaction, it has significant limitations regarding privacy. Specifically, because the Bitcoin transaction log is completely public, users' privacy is protected only through the use of pseudonyms. In this paper we propose Zerocoin, a cryptographic extension to Bitcoin that augments the protocol to allow for fully anonymous currency transactions. Our system uses standard cryptographic assumptions and does not introduce new trusted parties or otherwise change the security model of Bitcoin. We detail Zerocoin's cryptographic construction, its integration into Bitcoin, and examine its performance both in terms of computation and impact on the Bitcoin protocol.