nils-herrmann/clean_scirepeval huggingface dataset:
Effect of Whole Body Vibration Training on Trunk Muscle Strength and Physical Performance in Healthy Adults: Preliminary Results of a Randomized Controlled Trial.
Venue: Journal of sport rehabilitation

Whole body vibration (WBV) stimulus equipment has been used as a new training method for health promotion. Its use in the clinic has expanded to the field of sports and rehabilitation for disabled patients. WBV training is rapidly gaining popularity in health and fitness centers as an alternative method for improving muscle performance. Acute positive effects of WBV have been shown on lower extremity muscle power and vertical jump ability; however, there have not been any studies focusing on the long term effects of WBV for trunk muscle and dynamic balance.  To investigate the effects of an 8 wk program of WBV in combination with trunk muscle training on muscle performance in healthy, untrained adults.  Laboratory based, repeated measures study.  University laboratory.  20 healthy university men.  Participants were randomly assigned to a WBV or non WBV group. The WBV group performed a trunk muscle training program in combination with WBV; the non WBV group performed the same muscle training program without WBV for 8 wk.  In the pre and posttraining period, the participants were evaluated using the Functional Movement Screen (FMS) Y Balance Test (Y test) (anterior, posteromedial, and posterolateral reach) trunk muscle isometric strength (flexor, extensor, and flexor:extensor ratio) squat jump, and countermovement jump.  The WBV group had greater improvement than the non WBV group in both trunk flexor muscle strength (P .02) and the Y test (anterior reach) (P .004) between pre and posttraining.  Adding WBV to a trunk muscle strengthening program may improve trunk flexor isometric strength and anterior reach during the Y test more than training without WBV. The WBV protocol used in this study had no significant impact on FMS scores, squat jumping, countermovement jumping, trunk extensor isometric strength, or trunk flexor:extensor ratio.
POST SECONDARY PROJECT BASED LEARNING IN SCIENCE, TECHNOLOGY, ENGINEERING AND MATHEMATICS

Project based learning (PjBL to distinguish from problem based learning PBL) has become a recurrent practice in K 12 classroom environments. As PjBL has become prominent in K 12 classrooms, it has also surfaced in post secondary institutions. The purpose of this paper is to examine the research that has studied a variety of science, technology, engineering and mathematic subjects using PjBL in post secondary classrooms. Eleven articles (including qualitative, quantitative and mixed methods) were included. The format includes: an introduction and background (which defines PjBL and STEM) research methods, quality appraisal used, results, and a discussion, future research and a conclusion. Two tables and two figures are included. In this paper, theoretical backgrounds and key terms were identified, followed by a literature review discussing four themes: content knowledge, interdisciplinary skills, collaboration and skill development for future education and careers. Results suggested that there is a positive connection between content knowledge learning and PjBL in collaborative settings. Additionally, some negative perceptions arose regarding teamwork situations. Interdisciplinary skills were achieved, but quite limited in post secondary classrooms. PjBL and STEM were perceived to be important for future education and careers. Future research needs to be completed and institutional curriculum changes informed by the results of this research need to occur to further explore interdisciplinary courses and the use of PjBL.
Deep learning for sentiment analysis
Venue: Lang. Linguistics Compass

Research and industry are becoming more and more interested in finding automatically the polarised opinion of the general public regarding a specific subject. The advent of social networks has opened the possibility of having access to massive blogs, recommendations, and reviews. The challenge is to extract the polarity from these data, which is a task of opinion mining or sentiment analysis. The specific difficulties inherent in this task include issues related to subjective interpretation and linguistic phenomena that affect the polarity of words. Recently, deep learning has become a popular method of addressing this task. However, different approaches have been proposed in the literature. This article provides an overview of deep learning for sentiment analysis in order to place these approaches in context.
Spatio Temporal Matching for Human Pose Estimation in Video
Venue: IEEE Transactions on Pattern Analysis and Machine Intelligence

Detection and tracking humans in videos have been long standing problems in computer vision. Most successful approaches (e.g. deformable parts models) heavily rely on discriminative models to build appearance detectors for body joints and generative models to constrain possible body configurations (e.g. trees) While these 2D models have been successfully applied to images (and with less success to videos) a major challenge is to generalize these models to cope with camera views. In order to achieve view invariance, these 2D models typically require a large amount of training data across views that is difficult to gather and time consuming to label. Unlike existing 2D models, this paper formulates the problem of human detection in videos as spatio temporal matching (STM) between a 3D motion capture model and trajectories in videos. Our algorithm estimates the camera view and selects a subset of tracked trajectories that matches the motion of the 3D model. The STM is efficiently solved with linear programming, and it is robust to tracking mismatches, occlusions and outliers. To the best of our knowledge this is the first paper that solves the correspondence between video and 3D motion capture data for human pose detection. Experiments on the CMU motion capture, Human3.6M, Berkeley MHAD and CMU MAD databases illustrate the benefits of our method over state of the art approaches.
What Are Student Loan Borrowers Thinking? Insights From Focus Groups on College Selection and Student Loan Decision Making
Venue: Journal of Financial Counseling and Planning

This study used data from online focus groups collected from November 2014 to April 2015 to understand college students' decision making processes when borrowing money to finance their education. Data were collected using an online course management system. Results suggest that (a) students relied heavily on advice from parents, guidance counselors, and friends; (b) attending college was not possible without student loans; and (c) students knew very little about the loans they would be responsible for repaying. Recommendations for financial educators and counselors to help student borrowers make prudent decisions about education debt are presented.
Green IT in Practice: Virtual Meetings in Swedish Public Agencies

This paper presents and discusses how virtual meetings (VMs) can be used as a Green IT measure in an organization, by analyzing the experiences and results from the project 'REMM' involving 20 public agencies in Sweden. The paper describes the methodology used in the REMM project, how progress and results have been monitored, evaluating how well the approach has worked out and discussing how applicable it could be outside the Swedish public agency context. Some of the challenges the agencies have faced when trying to alter their employees' meetings and communication routines are presented. The idea of using VMs as a tool to reduce environmental impact by substituting business travel is also discussed, taking rebound effects into account, as well as the need for complementary policy tools. The REMM project was initiated to support agencies in building capacity for more and better VMs in their organization. The methodology, based on a ten step implementation approach, was well received and applied by the agencies. In the cases where follow up progress measurements could be made, the share of VMs increased in REMM agencies on average from 46 60 between the years 2011 2013. Employees in the REMM agencies experienced that one out of three VMs replaced a business trip that they would have made if the VM option was not at hand. But the time and money saved by avoiding a trip is in seven out of ten times used for more work. This, in turn, can lead to the generation of more emissions, counteracting the reduction from the replaced trips in the first place. Hence the reductions in travel volumes or emission cuts are lower than what would be expected from the amounts of substituted trips.
Organisational effects of virtual meetings

Virtual meetings (VMs) i.e. audio video and web conferencing, could be used to decrease the environmental impact of business activities, reduce travel costs, increase business mobility and collaboration, and improve flexibility and productivity of the employees. Swedish national policy supports the implementation of VMs as one of the solutions towards low carbon infrastructure and sustainable transportation. There are, however, uncertainties and disagreements about the organisational effects of the increased VM use. This article explores the potential effects that VMs may have on an organisation. It does so by examining the presence and strength of these effects in a number of public and private organisations in Sweden. Data has been collected through a literature review and 23 in depth interviews complemented by a survey in three organisations. The results are analysed with a special focus on seeking explanations for diverging opinions among the respondents and in the literature. The findings indicate that organisational effects of VMs depend on the following factors: organisational perception of the virtual toolbox, behaviour and rebound effects, and the organisation's virtual maturity. The later refers to the penetration and diversity of the collaborative tools used in the organisation and is divided into three stages: substitution, diffusion and integration. As the use of VMs grows in the organisation, different effects will emerge and eventually subside.
Opportunities During Early Life for Cancer Prevention: Highlights From a Series of Virtual Meetings With Experts
Venue: Pediatrics

Compelling evidence suggests that early life exposures can affect lifetime cancer risk. In 2014, the Centers for Disease Control and Prevention's (CDC's) Cancer Prevention Across the Lifespan Workgroup hosted a series of virtual meetings with select experts to discuss the state of the evidence linking factors during the prenatal period and early childhood to subsequent risk of both pediatric and adult cancers. In this article, we present the results from a qualitative analysis of the meeting transcripts and summarize themes that emerged from our discussions with meeting participants. Themes included the state of the evidence linking early life factors to cancer risk, research gaps and challenges, the level of evidence needed to support taking public health action, and the challenges of communicating complex, and sometimes conflicting, scientific findings to the public. Opportunities for collaboration among public health agencies and other stakeholders were identified during these discussions. Potential next steps for the CDC and its partners included advancing and building upon epidemiology and surveillance work, developing and using evidence from multiple sources to inform decision making, disseminating and communicating research findings in a clear and effective way, and expanding collaborations with grantees and other partners. As the science on early life factors and cancer risk continues to evolve, there are opportunities for collaboration to translate science into actionable public health practice.
Distillation as a Defense to Adversarial Perturbations Against Deep Neural Networks
Venue: 2016 IEEE Symposium on Security and Privacy (SP)

Deep learning algorithms have been shown to perform extremely well on many classical machine learning problems. However, recent studies have shown that deep learning, like other machine learning techniques, is vulnerable to adversarial samples: inputs crafted to force a deep neural network (DNN) to provide adversary selected outputs. Such attacks can seriously undermine the security of the system supported by the DNN, sometimes with devastating consequences. For example, autonomous vehicles can be crashed, illicit or illegal content can bypass content filters, or biometric authentication systems can be manipulated to allow improper access. In this work, we introduce a defensive mechanism called defensive distillation to reduce the effectiveness of adversarial samples on DNNs. We analytically investigate the generalizability and robustness properties granted by the use of defensive distillation when training DNNs. We also empirically study the effectiveness of our defense mechanisms on two DNNs placed in adversarial settings. The study shows that defensive distillation can reduce effectiveness of sample creation from 95% to less than 0.5% on a studied DNN. Such dramatic gains can be explained by the fact that distillation leads gradients used in adversarial sample creation to be reduced by a factor of 1030. We also find that distillation increases the average minimum number of features that need to be modified to create adversarial samples by about 800% on one of the DNNs we tested.
Physiological responses of selected African sorghum landraces to progressive water stress and re watering

Sorghum is particularly drought tolerant compared with other cereal crops and is favoured for subsistence farming in water scarce regions of the world. This study was conducted to identify South African sorghum landraces with superior drought tolerance compared with a drought tolerant breeding line (P898012) Seedlings of 14 South African sorghum landrace accessions were initially screened for drought tolerance by assessing percentage leaf water content (LWC) during progressive water deficit. Four landraces (designated LR5, LR6, LR35, and LR36) recorded higher LWC than P898012. These were subsequently evaluated with P898012 during the reproductive growth stage, for their physiological responses to mild (4 days) and severe (6 days) water stress treatments and a moderate re watered treatment on day 7. Plant height, soil moisture, and LWC were measured during harvests. Chlorophyll, carotenoid, and proline contents were quantified. All five genotypes maintained LWC above 80% during mild and severe stress treatments. For LR35 and LR36, LWC were recorded within 8% less in comparison to their well watered controls following the moderate re watered treatment. Significantly higher chlorophyll and carotenoid contents were recorded for both LR6 and LR35 in comparison to P898012 during severe stress. When LWC was reduced in LR36 (to 73.68% and LR35 (to 73.51% their proline content significantly increased by 14 and 16 fold, respectively. In this study, we have identified four previously uncharacterised sorghum genotypes exhibiting drought tolerance and described their physiological responses during water deficit and moderate re watering. Aside from their application to breeding, these landraces are valuable resources to elucidate genetic mechanisms that enable drought tolerance in South African sorghum.
Identity and Discourse

Research has highlighted the struggles involved in constructing an identity as a teacher of science during the vulnerable time of teacher education and during the first year of teaching, where personal biographies and visions meet the cultural expectations from teacher educators and schools (Hayes, 2002; Saka, Southerland, Kittleson, Hutner, 2013; Wilson Kittleson, 2012; Volkmann Anderson, 1998) In contemporary recommendations for science teaching practice, inquiry forms of teaching and learning hold a central position across the world (Gott Duggan, 2007; Hayes, 2002;  2011; Poon, Lee, Tan, Lim, 2012; Warwick Siraj Blatchford, 2006)
Enjoying the third age! Discourse, identity and liminality in extra care communities
Venue: Ageing and Society

Extra care housing has been an important and growing element of housing and care for older people in the United Kingdom since the 1990s. Previous studies have examined specific features and programmes within extra care locations, but few have studied how residents negotiate social life and identity. Those that have, have noted that while extra care brings many health related and social benefits, extra care communities can also be difficult affective terrain. Given that many residents are now 'ageing in place' in extra care, it is timely to revisit these questions of identity and affect. Here we draw on the qualitative element of a three year, mixed method study of 14 extra care villages and schemes run by the ExtraCare Charitable Trust. We follow Aleman in regarding residents' ambivalent accounts of life in ExtraCare as important windows on the way in which liminal residents negotiate the dialectics of dependence and independence. However, we suggest that the dialectic of interest here is that of the third and fourth age, as described by Gilleard and Higgs. We set that dialectic within a post structuralist/Lacanian framework in order to examine the different modes of enjoyment that liminal residents procure in ExtraCare's third age public spaces and ideals, and suggest that their complaints can be read in three ways: as statements about altered material conditions; as inter subjective bolstering of group identity; and as fantasmatic support for liminal identities. Finally, we examine the implications that this latter psycho social reading of residents' complaints has for enhancing and supporting residents' wellbeing.
Tweeting as Health Communication: Health Organizations' Use of Twitter for Health Promotion and Public Engagement
Venue: Journal of health communication

This study examined how major health organizations use Twitter for disseminating health information, building relationships, and encouraging actions to improve health. The sampled organizations were the American Heart Association, American Cancer Society, and American Diabetes Association. A content analysis was conducted on 1,583 tweets to examine these organizations' use of Twitter's interactive features and to understand the message functions and topics of their tweets. The numbers of retweets and favorites were also measured as engagement indicators and compared by different message functions. The results revealed that all of the organizations posted original tweets most, but they differed in the degree to which they used the retweet and reply functions. Hashtags and hyperlinks were the most frequently used interactive tools. The majority of the tweets were about organization related topics, whereas personal health related tweets represented a relatively small portion of the sample. Followers were most likely to like and retweet personal health action based messages.
Forgive and Forget, or Forgive and Regret? Whether Forgiveness Leads to Less or More Offending Depends on Offender Agreeableness
Venue: Personality social psychology bulletin

How does forgiveness predict the likelihood of reoffending? One survey study, one experiment, one 4 year longitudinal study, and one 2 week diary study examined the implications of forgiveness for reoffending in relationships. In all four studies, agreeableness interacted with partner forgiveness to predict subsequent offending; partner forgiveness was negatively associated with subsequent offending among more agreeable people but positively associated with subsequent offending among less agreeable people. Furthermore, Study 4 demonstrated a unique mechanism of each simple effect; relatively agreeable people engaged in fewer transgressions against more forgiving partners because they felt obligated to refrain from transgressing against such partners whereas relatively disagreeable people engaged in more transgressions against more forgiving partners because they perceived those partners were less easily angered. These studies indicate that completely understanding the intrapersonal and interpersonal consequences of forgiveness requires recognizing the dyadic nature of forgiveness and attending to qualities of the offender.
Tutorial on Variational Autoencoders
Venue: ArXiv

In just three years, Variational Autoencoders (VAEs) have emerged as one of the most popular approaches to unsupervised learning of complicated distributions. VAEs are appealing because they are built on top of standard function approximators (neural networks) and can be trained with stochastic gradient descent. VAEs have already shown promise in generating many kinds of complicated data, including handwritten digits, faces, house numbers, CIFAR images, physical models of scenes, segmentation, and predicting the future from static images. This tutorial introduces the intuitions behind VAEs, explains the mathematics behind them, and describes some empirical behavior. No prior knowledge of variational Bayesian methods is assumed.
Multi object tracking via discriminative appearance modeling
Venue: Comput. Vis. Image Underst.

Tracking multiple objects is important for automatic video content analysis and virtual reality. Recently, how to formulate data association optimization more effectively to overcome ambiguous detected responses and how to build more effective association affinity model have attracted more concerns. To address these issues, we propose a metric learning and multi cue fusion based hierarchical multiple hypotheses tracking method (MHMHT) which conducts data association more robustly and incorporates more temporal context information. The association appearance similarity is calculated using the distances between feature vectors in each associated tracklet and the salient templates of each track hypothesis, which is then fused with the dynamic similarity calculated according to Kalman filter online to get association affinity. To make appearance similarity more discriminative, the spatial temporal relationships of reliable tracklets in sliding temporal window are used as constraints to learn the discriminative appearance metric which measures the distance between feature vectors and salient templates. The salient templates of generated track hypotheses are updated using an incremental clustering method, considering the high order temporal context information. We evaluate our MHMHT tracker on challenging benchmark datasets. Qualitative and quantitative evaluations demonstrate that the proposed tracking algorithm performs favorably against several state of the art methods.
Effective and Efficient Image Copy Detection with Resistance to Arbitrary Rotation
Venue: IEICE Trans. Inf. Syst.

For detecting the image copies of a given original image generated by arbitrary rotation, the existing image copy detection methods can not simultaneously achieve desirable performances in the aspects of both accuracy and efficiency. To address this challenge, a novel effective and efficient image copy detection method is proposed based on two global features extracted from rotation invariant partitions. Firstly, candidate images are preprocessed by an averaging operation to suppress noise. Secondly, the rotation invariant partitions of the preprocessed images are constructed based on pixel intensity orders. Thirdly, two global features are extracted from these partitions by utilizing image gradient magnitudes and orientations, respectively. Finally, the extracted features of images are compared to implement copy detection. Promising experimental results demonstrate our proposed method can effectively and efficiently resist rotations with arbitrary degrees. Furthermore, the performances of the proposed method are also desirable for resisting other typical copy attacks, such as flipping, rescaling, illumination and contrast change, as well as Gaussian noising. key words: image copy detection, copy attacks, arbitrary rotation, rotation invariant, intensity orders