nils-herrmann/clean_scirepeval huggingface dataset:
Overlapping community detection through an improved multi-objective quantum-behaved particle swarm optimization

Community detection is one of the most important problems in the field of complex networks in recent years. Themajority of present algorithms only find disjoint communities, however, community often overlap to some extent in many real-world networks. In this paper, an improvedmulti-objective quantum-behaved particle swarm optimization (IMOQPSO) based on spectral-clustering is proposed to detect the overlapping community structure in complex networks. Firstly, the line graph of the graph modeling the network is formed, and a spectral method is employed to extract the spectral information of the line graph. Secondly, IMOQPSO is employed to solve the multi-objective optimization problem so as to resolve the separated community structure in the line graph which corresponding to the overlapping community structure in the graph presenting the network. Finally, a fine-tuning strategy is adopted to improve the accuracy of community detection. The experiments on both synthetic and real-world networks demonstrate our method achieves cover results which fit the real situation in an even better fashion.
The Nature of Feedback : How Peer Feedback Features Affect Students ’ Implementation Rate and Quality of Revisions

Although feedback is often seen as a critical component of the learning process, many open questions about how specific feedback features contribute to the effectiveness of feedback remain— especially in regards to peer feedback of writing. Nelson and Schunn (2009) identified several important features of peer feedback in their nature of feedback model. In the current study, we test an updated theoretical model that includes a broader set of features and considers not only students' likelihood of implementing a comment but also the quality of their revisions. To empirically test the updated theoretical model, we analyze over 7,500 comments from 351 reviewers to 189 authors. Each comment was coded for the presence of praise, a problem description, a suggested solution, localization, focus (i.e., low prose, high prose, substance), implementation, and revision quality. To account for the cross-classified nesting of data, we used a 2-level, cross-classified, hierarchical logistic regression model. Only 2 feedback features increased students' likelihood of implementation (i.e., overall praise and localization), while several feedback features reduced students' likelihood of implementation (i.e., mitigating praise, solutions, and high-prose comments). Overlapping feedback features affected students' ability to revise and in opposing directions from their effect on likelihood of implementation: Revisions were less likely to improve the quality of their paper when implementing comments that included a specific location in the text, but they were more likely to improve the quality of their paper when implementing comments that focused on high-prose and substance issues. Implications of these findings are discussed. Although feedback is often seen as a critical component of the Many open questions about effectiveness remain, especially in particular contexts. Furthermore , as the use of peer feedback during writing assignments increases, an understanding of how various feedback features affect students' use of peer feedback is critical to improving the advice given to students about how to construct useful feedback. Therefore, the goal of the current study was to further examine the effect of several important features of peer feedback, and in particular how peer feedback affects college students' likelihood to implement a comment and the quality of the revisions within Writing in the Discipline courses. The research on feedback in general has a long history. At least two classic explanations for how feedback in general improves learning also apply to peer feedback: motivation that increases a general behavior (Brown, 1932; Symonds & Chase, 1929) and information that can be used …
Perpetual Assurances for Self-Adaptive Systems

Providing assurances for self-adaptive systems is challenging. A primary underlying problem is uncertainty that may stem from a variety of different sources, ranging from incomplete knowledge to sensor noise and uncertain behavior of humans in the loop. Providing assurances that the self-adaptive system complies with its requirements calls for an enduring process spanning the whole lifetime of the system. In this process, humans and the system jointly derive and integrate new evidence and arguments, which we coined perpetual assurances for self-adaptive systems. In this paper, we provide a background framework and the foundation for perpetual assurances for self-adaptive systems. We elaborate on the concrete challenges of offering perpetual assurances, requirements for solutions, realization techniques and mechanisms to make solutions suitable. We also present benchmark criteria to compare solutions. We then present a concrete exemplar that researchers can use to assess and compare approaches for perpetual assurances for self-adaptation.
The impact of progesterone on memory consolidation of threatening images in women

Recent findings suggest that consolidation of emotional memories is influenced by menstrual phase in women. In contrast to other phases, in the mid-luteal phase when progesterone levels are elevated, cortisol levels are increased and correlated with emotional memory. This study examined the impact of progesterone on cortisol and memory consolidation of threatening stimuli under stressful conditions. Thirty women were recruited for the high progesterone group (in the mid-luteal phase) and 26 for the low progesterone group (in non-luteal phases of the menstrual cycle). Women were shown a series of 20 neutral or threatening images followed immediately by either a stressor (cold pressor task) or control condition. Participants returned two days later for a surprise free recall test of the images and salivary cortisol responses were monitored. High progesterone levels were associated with higher baseline and stress-evoked cortisol levels, and enhanced memory of negative images when stress was received. A positive correlation was found between stress-induced cortisol levels and memory recall of threatening images. These findings suggest that progesterone mediates cortisol responses to stress and subsequently predicts memory recall for emotionally arousing stimuli.
Who's misbehaving? Perceptions of unprofessional social media use by medical students and faculty.

Social media use by physicians offers potential benefits but may also be associated with professionalism problems. The objectives of this study were: 1) to examine and compare characteristics of social media use by medical students and faculty; 2) to explore the scope of self- and peer-posting of unprofessional online content; and 3) to determine what actions were taken when unprofessional content was viewed.



An anonymous, web-based survey was sent to medical students and faculty in October, 2013 at the Albert Einstein College of Medicine in Bronx, New York.



Three-quarters of medical students reported using social media "very frequently" (several times a day), whereas less than one-third of faculty did so (p < .001). Medical students reported using privacy settings more often than faculty (96.5 % v. 78.1 %, p < .001). Most medical students (94.2 %) and faculty (94.1 %) reported "never" or "occasionally" monitoring their online presence (p = 0.94). Medical students reported self-posting of profanity, depiction of intoxication, and sexually suggestive material more often than faculty (p < .001). Medical students and faculty both reported peer-posting of unprofessional content significantly more often than self-posting. There was no association between year of medical school and posting of unprofessional content.



Medical students reported spending more time using social media and posting unprofessional content more often than did faculty.
Proofreading Tile Sets: Error Correction for Algorithmic Self-Assembly

For robust molecular implementation of tile-based algorithmic self-assembly, methods for reducing errors must be developed. Previous studies suggested that by control of physical conditions, such as temperature and the concentration of tiles, errors (ε) can be reduced to an arbitrarily low rate – but at the cost of reduced speed (r) for the self-assembly process. For tile sets directly implementing blocked cellular automata, it was shown that r ≈ βε was optimal. Here, we show that an improved construction, which we refer to as proofreading tile sets, can in principle exploit the cooperativity of tile assembly reactions to dramatically improve the scaling behavior to r ≈ βε and better. This suggests that existing DNA-based molecular tile approaches may be improved to produce macroscopic algorithmic crystals with few errors. Generalizations and limitations of the proofreading tile set construction are discussed.
A double piezo — Snap through buckling device for energy harvesting

This paper presents a low cost solution for energy harvester based on a bistable clamped-clamped PET (PolyEthyleneTerephthalate) beam and two piezoelectric transducers. The beam switching is activated by environmental vibrations. The mechanical-to-electrical energy conversion is performed by two piezoelectric transducers laterally installed to experience beam impacts each time the device switches from one stable state to the other one. Main advantages of the proposed approach are related to the wide frequency band assuring high device efficiency and the adopted low cost technology.
Ultrasonography Diagnosis and Imaging-Based Management of Thyroid Nodules: Revised Korean Society of Thyroid Radiology Consensus Statement and Recommendations

The rate of detection of thyroid nodules and carcinomas has increased with the widespread use of ultrasonography (US), which is the mainstay for the detection and risk stratification of thyroid nodules as well as for providing guidance for their biopsy and nonsurgical treatment. The Korean Society of Thyroid Radiology (KSThR) published their first recommendations for the US-based diagnosis and management of thyroid nodules in 2011. These recommendations have been used as the standard guidelines for the past several years in Korea. Lately, the application of US has been further emphasized for the personalized management of patients with thyroid nodules. The Task Force on Thyroid Nodules of the KSThR has revised the recommendations for the ultrasound diagnosis and imaging-based management of thyroid nodules. The review and recommendations in this report have been based on a comprehensive analysis of the current literature and the consensus of experts.
Co-design of augmented reality book for collaborative learning experience in primary education

Through co-design of Augmented Reality (AR) based teaching material, this research aims to enhance collaborative learning experience in primary school education. It will introduce an interactive AR Book based on primary school textbook using tablets as the real time interface. The development of this AR Book employs co-design methods to involve children, teachers, educators and HCI experts from the early stages of the design process. Research insights from the co-design phase will be implemented in the AR Book design. The final outcome of the AR Book will be evaluated in the classroom to explore its effect on the collaborative experience of primary school students. The research aims to answer the question - Can Augmented Books be designed for primary school students in order to support collaboration? This main research question is divided into two sub-questions as follows - How can co-design methods be applied in designing Augmented Book with and for primary school children? And what is the effect of the proposed Augmented Book on primary school students' collaboration? This research will not only present a practical application of co-designing AR Book for and with primary school children, it will also clarify the benefit of AR for education in terms of collaborative experience.
Calculating Medium and Image Gamut Boundaries for Gamut Mapping

The Segment Maxima Method for calculating gamut boundary descriptors of both colour reproduction media and colour images is introduced. Methods for determining the gamut boundary along a given line of mapping used by gamut mapping algorithms are then described, whereby these methods use the Gamut Boundary Descriptor obtained using the Segment Maxima  Throughout the article, the focus is both on colour reproduction media and colour images as well as on the suitability of the methods for use in gamut mapping.
Reinforcement learning in multidimensional continuous action spaces

The majority of learning algorithms available today focus on approximating the state (V ) or state-action (Q) value function and efficient action selection comes as an afterthought. On the other hand, real-world problems tend to have large action spaces, where evaluating every possible action becomes impractical. This mismatch presents a major obstacle in successfully applying reinforcement learning to real-world problems. In this paper we present an effective approach to learning and acting in domains with multidimensional and/or continuous control variables where efficient action selection is embedded in the learning process. Instead of learning and representing the state or state-action value function of the MDP, we learn a value function over an implied augmented MDP, where states represent collections of actions in the original MDP and transitions represent choices eliminating parts of the action space at each step. Action selection in the original MDP is reduced to a binary search by the agent in the transformed MDP, with computational complexity logarithmic in the number of actions, or equivalently linear in the number of action dimensions. Our method can be combined with any discrete-action reinforcement learning algorithm for learning multidimensional continuous-action policies using a state value approximator in the transformed MDP. Our preliminary results with two well-known reinforcement learning algorithms (Least-Squares Policy Iteration and Fitted Q-Iteration) on two continuous action domains (1-dimensional inverted pendulum regulator, 2-dimensional bicycle balancing) demonstrate the viability and the potential of the proposed approach.
A case of autoenucleation associated with a contralateral field defect.

To report a case of autoenucleation associated with contralateral field defect.



Observational case report.



A 36-year-old man was referred to the emergency ward with his right eye attached to a fork. His history revealed drug abuse with ecstasy.



Visual field examination revealed a temporal hemianopia on the left eye. There was no change in the visual field defect after intravenous steroid, two months after initial presentation.



Contralateral visual field defect may be associated with autoenucleation. A visual field test is recommended in all cases with traumatic enucleation.
Eye Tracking Using Built-in Camera for Smartphone-based HMD

Virtual reality (VR) using head-mounted displays (HMDs) is becoming popular. Smartphone-based HMDs (SbHMDs) are so low cost that users can easily experience VR. Unfortunately, their input modality is quite limited. We propose a real-time eye tracking technique that uses the built-in front facing camera to capture the user's eye. It realizes stand-alone pointing functionality without any additional device.
Compact wideband quarter-wave transformer using stepped impedance microstrip lines

A compact wideband quarter-wave transformer using microstrip lines is presented. The design relies on replacing a uniform microstrip line with a multi-stage equivalent circuit. The equivalent circuit is a cascade of either T or π networks. Design equations for both types of equivalent circuits have been derived. A quarter-wave transformer operating at 1 GHz is implemented. Simulation results indicate a −15 dB impedance bandwidth exceeding 64% for a 3-stage network with less than 0.25 dB of attenuation within the bandwidth. Both types of equivalent circuits provide more than 40% compaction with proper selection of components. Measured results for the fabricated unit deviate within acceptable limits. The designed quarter-wave transformer may be used to replace 90° transmission lines in various passive microwave components.
Efficient Collision Detection of Complex Deformable Models using AABB Trees

We present a scheme for exact collision detection between complex models undergoing rigid motion and deformation. The scheme relies on a hierarchical model representation using axis-aligned bounding boxes (AABBs). In recent work, AABB trees have been shown to be slower than oriented bounding box (OBB) trees. In this paper, we describe a way to speed up overlap tests between AABBs, such that for collision detection of rigid models, the difference in performance between the two representations is greatly reduced. Furthermore, we show how to quickly update an AABB tree as a model is deformed. We thus find AABB trees to be the method of choice for collision detection of complex models undergoing deformation. In fact, because they are not much slower to test, are faster to build, and use less storage than OBB trees, AABB trees might be a reasonable choice for rigid
2003 European Society of Hypertension-European Society of Cardiology guidelines for the management of arterial hypertension.

In preparing these guidelines the Committee established by the European Society of Hypertension (ESH) and the European Society of Cardiology (ESC) has aimed at offering the best available and most balanced information to all those involved in the management of arterial hypertension. The Committee is aware that it is easier to prepare guidelines on a medical condition in general than to deal with the individual patients with that condition requiring medical advice and intervention. Because of this awareness, the Committee has tried to avoid giving rigid rules that would constrain judgement on the management of individual patients differing in their personal, medical and cultural characteristics.
Stress among medical students in a Thai medical school.

This study aimed to determine the prevalence and sources of stress among Thai medical students. The questionnaires,which consisted of the Thai Stress Test (TST) and questions asking about sources of stress, were sent to all medical students in the Faculty of Medicine, Ramathibodi Hospital, Thailand. A total of 686 students participated. The results showed that about 61.4% of students had some degree of stress. Seventeen students (2.4%) reported a high level of stress. The prevalence of stress is highest among third-year medical students. Academic problems were found to be a major cause of stress among all students. The most prevalent source of academic stress was the test/exam. Other sources of stress in medical school and their relationships are also discussed. The findings can help medical teachers understand more about stress among their students and guide the way to improvement in an academic context, which is important for student achievement.
Stochastic Gradient Descent Performs Variational Inference, Converges to Limit Cycles for Deep Networks

Stochastic gradient descent (SGD) is widely believed to perform implicit regularization when used to train deep neural networks, but the precise manner in which this occurs has thus far been elusive. We prove that SGD minimizes an average potential over the posterior distribution of weights along with an entropic regularization term. This potential is however not the original loss function in general. So SGD does perform variational inference, but for a different loss than the one used to compute the gradients. Even more surprisingly, SGD does not even converge in the classical sense: we show that the most likely trajectories of SGD for deep networks do not behave like Brownian motion around critical points. Instead, they resemble closed loops with deterministic components. We prove that such “out-of-equilibrium” behavior is a consequence of highly nonisotropic gradient noise in SGD; the covariance matrix of mini-batch gradients for deep networks has a rank as small as 1% of its dimension. We provide extensive empirical validation of these claims. This article summarizes the findings in . See the longer version for background, detailed results and proofs.
Dagger: Digging for Interesting Aggregates in RDF Graphs

RDF is the format of choice for representing Semantic Web data. RDF graphs may be large and their structure is heterogeneous and complex, making them very hard to explore and understand. To help users discover valuable insights from RDF graph, we have developed Dagger, a tool which automatically recommends interesting aggregation queries over the RDF graphs; Dagger evaluates the queries and graphically shows their results to the user, in the ranked order of their interestingness. We propose to demonstrate Dagger to the ISWC audience, based on popular real and synthetic RDF graphs.
Parenting stress among mothers of children with different physical, mental, and psychological problems

Parents of children with developmental problems are always bearing a load of stress. The aim of this study is to compare the stress in mothers of children with different disabilities to each other, considering their demographic background.



This was a cross-sectional study conducted in Isfahan, Iran during 2012 on 285 mothers of 6-12 years old children with chronic physical disease, psychological disorder, and sensory-motor and mental problems. Abedin's parenting stress questionnaire was used and obtained data were analyzed using multivariate analysis of variance or covariance as appropriate.



Mothers of children with sensory-motor mental and chronic physical problems experience more stress than mothers of children with psychological disorders (P < 0.05). The stress score of mothers of children with psychological disorders was lower than the other two groups. Also there was a significant difference between the score of mothers of children with chronic physical problems and mothers of children with psychological disorders regarding parent-child dysfunctional interaction (P < 0.01). A significant difference was observed in terms of stress among mothers of children with sensory-motor mental problems with different number of children (P < 0.05); also mothers of children with chronic physical problems in different levels of education have experienced different levels of parenting stress (P < 0.05).



Due to high level of parenting stress among our studied samples, special education and early intervention are needed for parents in our study population in order to deepening their diagnostic knowledge and professional consultation on stress management.
Democratizing online controlled experiments at Booking.com

There is an extensive literature about online controlled experiments, both on the statistical methods available to analyze experiment results [1, 2, 3] as well as on the infrastructure built by several large scale Internet companies [4, 5, 6, 7] but also on the organizational challenges of embracing online experiments to inform product development [6, 8]. At Booking.com we have been conducting evidenced based product development using online experiments for more than ten years. Our methods and infrastructure were designed from their inception to reflect Booking.com culture, that is, with democratization and decentralization of experimentation and decision making in mind. In this paper we explain how building a central repository of successes and failures to allow for knowledge sharing, having a generic and extensible code library which enforces a loose coupling between experimentation and business logic, monitoring closely and transparently the quality and the reliability of the data gathering pipelines to build trust in the experimentation infrastructure, and putting in place safeguards to enable anyone to have end to end ownership of their experiments have allowed such a large organization as Booking.com to truly and successfully democratize