nils-herrmann/clean_scirepeval huggingface dataset:
From Visual Exploration to Storytelling and Back Again

The primary goal of visual data exploration tools is to enable the discovery of new insights. To justify and reproduce insights, the discovery process needs to be documented and communicated. A common approach to documenting and presenting findings is to capture visualizations as images or videos. Images, however, are insufficient for telling the story of a visual discovery, as they lack full provenance information and context. Videos are difficult to produce and edit, particularly due to the non-linear nature of the exploratory process. Most importantly, however, neither approach provides the opportunity to return to any point in the exploration in order to review the state of the visualization in detail or to conduct additional analyses. In this paper we present CLUE (Capture, Label, Understand, Explain), a model that tightly integrates data exploration and presentation of discoveries. Based on provenance data captured during the exploration process, users can extract key steps, add annotations, and author "Vistories", visual stories based on the history of the exploration. These Vistories can be shared for others to view, but also to retrace and extend the original analysis. We discuss how the CLUE approach can be integrated into visualization tools and provide a prototype implementation. Finally, we demonstrate the general applicability of the model in two usage scenarios: a Gapminder-inspired visualization to explore public health data and an example from molecular biology that illustrates how Vistories could be used in scientific journals.
The Web at Graduation and Beyond

s from the hardware actually present. This abstraction happens between the hardware and the software layer of a system, as indicated in Fig. 2.8; which shows two virtual machines mapped to the same hardware and encapsulated by individual containers. Note that virtual machines (VM) can run distinct operating systems atop the same hardware. Virtualization typically simplifies the administration of a system, and it can help increase system security; a crash of a virtual machine has no impact on other virtual machines. Technically a virtual machine is nothing but a file. Virtualization is implemented using a Virtual Machine Monitor or Hypervisor which takes care of resource mapping and management. We finally mention another precursor to cloud computing, which can be observed during the past 25 years as a major paradigm shift in software development, namely a departure from large and monolithic software applications to light-weight services which ultimately can be composed and orchestrated into more powerful services that finally carry entire application scenarios. Service-orientation especially in the form of service calls to an open application programming interface (API) that can be contacted over the Web as long as the correct input parameters are delivered have not only become very popular, but are also exploited these days in numerous ways, for the particular reason of giving users an increased level of functionality from a single source. A benefit of the service approach to software development has so far been the fact that platform development especially on the Web has received a high amount of attention in recent years. Yet it has also contributed to the fact that services which a provider delivers behind the scenes to some well-defined interface can be enhanced and modified and even permanently corrected and updated without the user even noticing, and it has triggered the development of the SOA (Service-Oriented Architecture) concept that was mentioned in the previous section. Operating System App. 1 App. 2 Virtualization Layer Operating System App. 3 App. 4 Hardware VM Container VM Container Fig. 2.8 Virtualized infrastructure 2.2 Virtualization and Cloud Computing 73
Body enhancement through female genital cosmetic surgery creates ethical and rights dilemmas.

Female genital cosmetic surgery is surgery performed on a woman within a normal range of variation of human anatomy. The issues are heightened by a lack of long-term and substantive evidence-based literature, conflict of interest from personal financial gain through performing these procedures, and confusion around macroethical and microethical domains. It is a source of conflict and controversy globally because the benefit and harm of offering these procedures raise concerns about harmful cultural views, education, and social vulnerability of women with regard to both ethics and human rights. The rights issues of who is defining normal female anatomy and function, as well as the economic vulnerability of women globally, bequeath the profession a greater responsibility to ensure that there is adequate health and general education-not just among patients but broadly in society-that there is neither limitation nor interference in the decision being made, and that there are no psychological disorders that could be influencing such choices.
The test of functional health literacy in adults

To develop a valid, reliable instrument to measure the functional health literacy of patients.  The Test of Functional Health Literacy in Adults (TOFHLA) was developed using actual hospital materials. The TOFHLA consists of a 50-item reading comprehension and 17-item numerical ability test, taking up to 22 minutes to administer. The TOFHLA, the Wide Range Achievement Test-Revised (WRAT-R), and the Rapid Estimate of Adult Literacy in Medicine (REALM) were administered for comparison. A Spanish version was also developed (TOFHLA-S).  Outpatient settings in two public teaching hospitals.  256 English- and 249 Spanish-speaking patients were approached. 78% of the English- and 82% of the Spanish-speaking patients gave informed consent, completed a demographic survey, and took the TOFHLA or TOFHLA-S.  The TOFHLA showed good correlation with the WRAT-R and the REALM (correlation coefficients 0.74 and 0.84, respectively). Only 52% of the English speakers completed more than 80% of the questions correctly. 15% of the patients could not read and interpret a prescription bottle with instructions to take one pill by mouth four times daily, 37% did not understand instructions to take a medication on an empty stomach, and 48% could not determine whether they were eligible for free care.  The TOFHLA is a valid, reliable indicator of patient ability to read health-related materials. Data suggest that a high proportion of patients cannot perform basic reading tasks. Additional work is needed to determine the prevalence of functional health illiteracy and its effect on the health care experience.
Structural balance: a generalization of Heider's theory.

A persistent problem of psychology has been how to deal conceptually with patterns of interdependent properties. This problem has been central, of course, in the theoretical treatment by Gestalt psychologists of phenomenal or neural configurations or fields (12, 13, 15). It has also been of concern to social psychologists and sociologists who attempt to employ concepts referring to social systems (18). Heider (19), reflecting the general field-theoretical approach, has considered certain aspects of cognitive fields which contain perceived people and impersonal objects or events. His analysis focuses upon what he calls the P-O-X unit of a cognitive field, consisting of P (one person), 0 (another person), and X (an impersonal entity). Each relation among the parts of the unit is conceived as interdependent with each other relation. Thus, for example, if P has a relation of affection for 0 and if 0 is seen as responsible for X, then there will be a tendency for P to like or approve of X. If the nature of X is such that it would "normally" be evaluated as bad, the whole P-O-X unit is placed in a state of imbalance, and pressures
A Survey of Arabic Named Entity Recognition and Classification

As more and more Arabic textual information becomes available through the Web in homes and businesses, via Internet and Intranet services, there is an urgent need for technologies and tools to process the relevant information. Named Entity Recognition (NER) is an Information Extraction task that has become an integral part of many other Natural Language Processing (NLP) tasks, such as Machine Translation and Information Retrieval. Arabic NER has begun to receive attention in recent years. The characteristics and peculiarities of Arabic, a member of the Semitic languages family, make dealing with NER a challenge. The performance of an Arabic NER component affects the overall performance of the NLP system in a positive manner. This article attempts to describe and detail the recent increase in interest and progress made in Arabic NER research. The importance of the NER task is demonstrated, the main characteristics of the Arabic language are highlighted, and the aspects of standardization in annotating named entities are illustrated. Moreover, the different Arabic linguistic resources are presented and the approaches used in Arabic NER field are explained. The features of common tools used in Arabic NER are described, and standard evaluation metrics are illustrated. In addition, a review of the state of the art of Arabic NER research is discussed. Finally, we present our conclusions. Throughout the presentation, illustrative examples are used for clarification.
Feature Extraction Techniques for Recognition of Malayalam Handwritten Characters : Review

The Character recognition is one of the most important areas in the field of pattern recognition. Recently Indian Handwritten character recognition is getting much more attention and researchers are contributing a lot in this field. But Malayalam, a South Indian language has very less works in this area and needs further attention. Malayalam OCR is a complex task owing to the various character scripts available and more importantly the difference in ways in which the characters are written. The dimensions are never the same and may be never mapped on to a square grid unlike English characters. Selection of a feature extraction method is the most important factor in achieving high recognition performance in character recognition systems. Different feature extraction methods are designed for different representation of characters. As an important component of pattern recognition, feature extraction has been paid close attention by many scholars, and currently has become one of the research hot spots in the field of pattern recognition. This article gives a general discussion of feature extraction techniques used in handwritten character recognition of other Indian languages and some of them are implemented for Malayalam handwritten characters.
L Ow Precision Storage for Deep Learning

We train a set of state of the art neural networks, the Maxout networks (Goodfellow et al., 2013a), on three benchmark datasets: the MNIST, CIFAR10 and SVHN, with three distinct storing formats: floating point, fixed point and dynamic fixed point. For each of those datasets and for each of those formats, we assess the impact of the precision of the storage on the final error of the training. We find that very low precision storage is sufficient not just for running trained networks but also for training them. For example, Maxout networks state-of-the-art results are nearly maintained with 10 bits for storing activations and gradients, and 12 bits for storing parameters.
Gender and the nocebo response following conditioning and expectancy.

To investigate the role of Pavlovian conditioning and expectancy and of gender on the nocebo effects.



Conditioning experiment: Forty-eight healthy male and female volunteers were investigated for 3 days using a standard rotation procedure. Subjects in the experimental group received a salient oral stimulus prior to rotation; subjects in the control group received the stimulus 12 h after rotations on Days 1 and 2; on Day 3, all subjects received the stimulus prior to rotation.  subjects in the experimental group were told that the symptoms might worsen with the stimulus; controls did not receive additional information. In both experiments, symptom rating (SR) and rotation tolerance (RT) were determined.



Conditioning significantly reduced RT (P=.015) and increased SR (P=.024). For both RT and SR, a significant "day x group x gender" effect was found (P=.044; SR: P=.011) indicating that conditioning was more effective in women. Expectancies lowered RT (P=.085) without affecting SR. There was a significant "rotation x gender" interaction on RT (P=.005) indicating that the expectancy was more effective in men.



Women responded stronger to conditioning while men responded to expectancies, but to a lesser degree. It needs to be determined whether this is restricted to nausea-specific conditions or can be generalized across clinical and experimental conditions.
Detection of semantically similar code

The traditional similar code detection approaches are limited in detecting semantically similar codes, impeding their applications in practice. In this paper, we have improved the traditional metrics-based approach as well as the graph-based approach and presented a metrics-based and graph-based combined approach. First, source codes are represented as augmented system dependence graphs. Then, metrics-based candidate similar code extraction is performed to filter out most of the dissimilar code pairs so as to lower the computational complexity. After that, code normalization is performed on the candidate similar codes to remove code variations so as to detect similar code at the semantic level. Finally, program matching is performed on the normalized control dependence trees to output semantically similar codes. Experiment results show that our approach can detect similar codes with code variations, and it can be applied to large software.
Probabilistic risk analysis and terrorism risk.

Since the terrorist attacks of September 11, 2001, and the subsequent establishment of the U.S. Department of Homeland Security (DHS), considerable efforts have been made to estimate the risks of terrorism and the cost effectiveness of security policies to reduce these risks. DHS, industry, and the academic risk analysis communities have all invested heavily in the development of tools and approaches that can assist decisionmakers in effectively allocating limited resources across the vast array of potential investments that could mitigate risks from terrorism and other threats to the homeland. Decisionmakers demand models, analyses, and decision support that are useful for this task and based on the state of the art. Since terrorism risk analysis is new, no single method is likely to meet this challenge. In this article we explore a number of existing and potential approaches for terrorism risk analysis, focusing particularly on recent discussions regarding the applicability of probabilistic and decision analytic approaches to bioterrorism risks and the Bioterrorism Risk Assessment methodology used by the DHS and criticized by the National Academies and others.
State-dependent μ-opioid modulation of social motivation

Social mammals engage in affiliative interactions both when seeking relief from negative affect and when searching for pleasure and joy. These two motivational states are both modulated by μ-opioid transmission. The μ-opioid receptor (MOR) system in the brain mediates pain relief and reward behaviors, and is implicated in social reward processing and affiliative bonding across mammalian species. However, pharmacological manipulation of the μ-opioid system has yielded opposite effects on rodents and primates: in rodents, social motivation is generally increased by MOR agonists and reduced by antagonists, whereas the opposite pattern has been shown in primates. Here, we address this paradox by taking into account differences in motivational state. We first review evidence for μ-opioid mediation of reward processing, emotion regulation, and affiliation in humans, non-human primates, rodents and other species. Based on the consistent cross-species similarities in opioid functioning, we propose a unified, state-dependent model for μ-opioid modulation of affiliation across the mammalian species. Finally, we show that this state-dependent model is supported by evidence from both rodent and primate studies, when species and age differences in social separation response are taken into account.
A feature selection-based framework for human activity recognition using wearable multimodal sensors

Human activity recognition is important for many applications. This paper describes a human activity recognition framework based on feature selection techniques. The objective is to identify the most important features to recognize human activities. We first design a set of new features (called physical features) based on the physical parameters of human motion to augment the commonly used statistical features. To systematically analyze the impact of the physical features on the performance of the recognition system, a single-layer feature selection framework is developed. Experimental results indicate that physical features are always among the top features selected by different feature selection methods and the recognition accuracy is generally improved to 90%, or 8% better than when only statistical features are used. Moreover, we show that the performance is further improved by 3.8% by extending the single-layer framework to a multi-layer framework which takes advantage of the inherent structure of human activities and performs feature selection and classification in a hierarchical manner.
Clinical applications of the attachment framework: Relational treatment of complex trauma.

The self and attachment difficulties associated with chronic childhood abuse and other forms of pervasive trauma must be understood and addressed in the context of the therapeutic relationship for healing to extend beyond resolution of traditional psychiatric symptoms and skill deficits. The authors integrate contemporary research and theory about attachment and complex developmental trauma, including dissociation, and apply it to psychotherapy of complex trauma, especially as this research and theory inform the therapeutic relationship. Relevant literature on complex trauma and attachment is integrated with contemporary trauma theory as the background for discussing relational issues that commonly arise in this treatment, highlighting common challenges such as forming a therapeutic alliance, managing frame and boundaries, and working with dissociation and reenactments.
Person re-identification based on hierarchical bipartite graph matching

This work proposes a novel person re-identification method based on Hierarchical Bipartite Graph Matching. Because human eyes observe person appearance roughly first and then goes further into the details gradually, our method abstracts person image from coarse to fine granularity, and finally into a three layer tree structure. Then, three bipartite graph matching methods are proposed for the matching of each layer between the trees. At the bottom layer Non-complete Bipartite Graph matching is proposed to collect matching pairs among small local regions. At the middle layer Semi-complete Bipartite Graph matching is used to deal with the problem of spatial misalignment between two person bodies. Complete Bipartite Graph matching is presented to refine the ranking result at the top layer. The effectiveness of our method is validated on the CAVIAR4REID and VIPeR datasets, and competitive results are achieved on both datasets.
The will and the ways: development and validation of an individual-differences measure of hope.

Defining hope as a cognitive set that is composed of a reciprocally derived sense of successful (a) agency (goal-directed determination) and (b) pathways (planning of ways to meet goals), an individual-differences measure is developed. Studies demonstrate acceptable internal consistency and test-retest reliability, and the factor structure identifies the agency and pathways components of the Hope Scale. Convergent and discriminant validity are documented, along with evidence suggesting that Hope Scale scores augmented the prediction of goal-related activities and coping strategies beyond other self-report measures. Construct validational support is provided in regard to predicted goal-setting behaviors; moreover, the hypothesized goal appraisal processes that accompany the various levels of hope are corroborated.
An Overview of the IEEE Standard C37.118.2—Synchrophasor Data Transfer for Power Systems

Synchrophasor Standards have evolved since the introduction of the first one, IEEE Standard 1344, in 1995. 2005 introduced measurement accuracy under steady state conditions as well as interference rejection. In 2009, the IEEE started a joint project with IEC to harmonize real time communications in IEEE Standard C37.118-2005 with the IEC 61850 communication standard. These efforts led to the need to split the C37.118 into 2 different standards: IEEE Standard C37.118.1-2011 that now includes performance of synchrophasors under dynamic systems conditions; and IEEE Standard C37.118.2-2011 Synchrophasor Data Transfer for Power Systems, the object of this paper.
James Watson ’ s most inconvenient truth : Race realism and the moralistic fallacy

Recent editorials in this journal have defended the right of eminent biologist James Watson to raise the unpopular hypothesis that people of sub-Saharan African descent score lower, on average, than people of European or East Asian descent on tests of general intelligence. As those editorials imply, the scientific evidence is substantial in showing a genetic contribution to these differences. The unjustified ill treatment meted out to Watson therefore requires setting the record straight about the current state of the evidence on intelligence, race, and genetics. In this paper, we summarize our own previous reviews based on 10 categories of evidence: The worldwide distribution of test scores; the g factor of mental ability; heritability differences; brain size differences; trans-racial adoption studies; racial admixture studies; regression-to-the-mean effects; related life-history traits; human origins research; and the poverty of predictions from culture-only explanations. The preponderance of evidence demonstrates that in intelligence, brain size, and other life-history variables, East Asians average a higher IQ and larger brain than Europeans who average a higher IQ and larger brain than Africans. Further, these group differences are 50–80% heritable. These are facts, not opinions and science must be governed by data. There is no place for the ‘‘moralistic fallacy’’ that reality must conform to our social, political, or ethical desires.
Digital forensic analysis through Firewall for detection of information crimes in hospital networks

Digital forensics analysis was done by taking a view of Firewall on the Firewall used in the hospitals, and the data that could create a criminal element were determined. As is known, all network traffic on the networks is over the firewall. For this reason, the traffic on the entire network is recorded on the firewall. When these records need to be analyzed in terms of forensic information and criminal elements should be detected, the records on the firewall should be analyzed without deterioration. For this purpose, the image of the firewall needs to be taken. However, in order to obtain images, it is necessary to calculate MD5 and SHA-1 HASH values with international validity, which confirm the integrity of the image. For this purpose, the Juniper SSG 550 firewall device used in Firat University Hospital will be analyzed. For analysis, FTK Imager program which is developed by AccessData firm and offered for free use will be used. This image will be analyzed with forensic tools such as forensics explorer.