snu-aidas/HVMap-dataset huggingface dataset:
The effect of Bikram yoga on arterial stiffness in young and older adults.

BACKGROUND AND OBJECTIVE
Bikram yoga is the most popular form of hot yoga, despite the limited information available on its cardiovascular benefits. This study sought to determine the effect of Bikram yoga on arterial stiffness and insulin resistance in young and older adults.


METHODS
Twenty-four young (mean age±standard deviation, 30±1 years) and 18 middle-aged and older (mean age, 53±2 years) adults completed an 8-week Bikram yoga intervention. Bikram yoga classes were performed for 90 minutes per session, three times per week, in a room heated to 40.5°C with 40%--60% relative humidity.


RESULTS
Body mass, body fat percentage, blood pressure, and fasting blood glucose and triglyceride concentrations did not significantly change as a result of the intervention in either the young or the older group. Trunk flexibility, as measured by the sit-and-reach test, increased in both groups (p<0.01). Total (p<0.05) and low-density lipoprotein cholesterol (p<0.05) levels, plasma insulin concentrations (p<0.01), and scores on the homeostatic model of the assessment of insulin resistance (p<0.01) decreased in older adults, whereas total and high-density lipoprotein cholesterol concentrations were reduced in young adults (all p<0.05). Carotid artery compliance (p<0.05) was increased and β-stiffness index decreased in young (p<0.05) but not in older adults. Carotid pulse pressure did not significantly change in either group.


CONCLUSION
A relatively short-term Bikram yoga intervention improved arterial stiffness in young but not older adults and significantly reduced insulin resistance index in older but not young adults.
Motion correction with PROPELLER MRI: application to head motion and free-breathing cardiac imaging.

A method for motion correction, involving both data collection and reconstruction, is presented. The PROPELLER MRI method collects data in concentric rectangular strips rotated about the k-space origin. The central region of k-space is sampled for every strip, which (a) allows one to correct spatial inconsistencies in position, rotation, and phase between strips, (b) allows one to reject data based on a correlation measure indicating through-plane motion, and (c) further decreases motion artifacts through an averaging effect for low spatial frequencies. Results are shown in which PROPELLER MRI is used to correct for bulk motion in head images and respiratory motion in nongated cardiac images. Magn Reson Med 42:963-969, 1999.
Sentential Representations in Distributional Semantics

This thesis is about the problem of representing sentential meaning in distributional semantics. Distributional semantics obtains the meanings of words through their usage, based on the hypothesis that words occurring in similar contexts will have similar meanings. In this framework, words are modeled as distributions over contexts and are represented as vectors in high dimensional space. Compositional distributional semantics attempts to extend this approach to higher linguistics structures. Some basic composition models proposed in literature to obtain the meaning of phrases or possibly sentences show promising results in modeling simple phrases. The goal of the thesis is to further extend these composition models to obtain sentence meaning representations. The thesis puts more focus on unsupervised methods which make use of the context of phrases and sentences to optimize the parameters of a model. Three different methods are presented. The first model is the PLF model, a practical composition and linguistically motivated model which is based on the lexical function model introduced by Baroni and Zamparelli (2010) and Coecke et al. (2010). The second model is the Chunk-based Smoothed Tree Kernels (CSTKs) model, extending Smoothed Tree Kernels (Mehdad et al., 2010) by utilizing vector representations of chunks. The final model is the C-PHRASE model, a neural network-based approach, which jointly optimizes the vector representations of words and phrases using a context predicting objective. The thesis makes three principal contributions to the field of compositional distributional semantics. The first is to propose a general framework to estimate the parameters and evaluate the basic composition models. This provides a fair way to comparing the models using a set of phrasal datasets. The second is to extend these basic models to the sentence level, using syntactic information to build up the sentence vectors. The third contribution is to evaluate all the proposed models, showing that they perform on par with or outperform competing models presented in the literature. Thesis Supervisor: Marco Baroni Title: Associate Professor
An Automatic Collocation Extraction from Arabic Corpus

Problem statement: The identification of collocations is very importa n part in natural language processing applications that require some degree of semantic interpretation such as, machine translation, information retrieval and text summari z tion. Because of the complexities of Arabic, the collocations undergo some variations such as, morph ological, graphical, syntactic variation that constitutes the difficulties of identifying the col location. Approach: We used the hybrid method for extracting the collocations from Arabic corpus that is based on linguistic information and association measures. Results: This method extracted the bi-gram candidates of Ar abic collocation from corpus and evaluated the association measures by using the n-best evaluation method. We reported the precision values for each association measure in ea ch n-best list. Conclusion: The experimental results showed that the log-likelihood ratio is the best as ociation measure that achieved highest precision.
Collaborative Edge and Cloud Neural Networks for Real-Time Video Processing

The efficient processing of video streams is a key component in many emerging Internet of Things (IoT) and edge applications, such as Virtual and Augmented Reality (V/AR) and self-driving cars. These applications require real-time high-throughput video processing. This can be attained via a collaborative processing model between the edge and the cloud—called an Edge-Cloud model. To this end, many approaches were proposed to optimize the latency and bandwidth consumption of Edge-Cloud video processing, especially for Neural Networks (NN)-based methods. In this demonstration. We investigate the efficiency of these NN techniques, how they can be combined, and whether combining them leads to better performance. Our demonstration invites participants to experiment with the various NN techniques, combine them, and observe how the underlying NN changes with different techniques and how these changes affect accuracy, latency and bandwidth consumption. PVLDB Reference Format: Philipp M. Grulich and Faisal Nawab. Collaborative Edge and Cloud Neural Networks for Real-Time Video Processing. PVLDB, 11 (12): 2046-2049, 2018. DOI: https://doi.org/10.14778/3229863.3236256
Reversible Alopecia with Localized Scalp Necrosis After Accidental Embolization of the Parietal Artery with Hyaluronic Acid

Hyaluronic acid (HA) filler injection is widely used for soft-tissue augmentation. Complications associated with HA filling are not uncommon; however, HA-induced alopecia is a rarely reported complication that could result in severe secondary psychological trauma. The etiology, clinical traits, treatment strategies, outcomes, and possible reversibility of HA-induced alopecia have not been characterized. Here, we report a case in which bilateral temple injections of 6.5 mL of HA led to persistent pain over the left scalp for several days. Although the pain was relieved at day 9 after 600 U of hyaluronidase were injected in the left temple, the patient developed localized alopecia at the left temporoparietal region with central skin necrosis at day 15. After topical applications of recombinant bovine basic fibroblast growth factor gel and 2% minoxidil spay, the necrotic skin wound was healed at day 42. Hair regrowth and normal hair density were restored at day 74. Analyses of Doppler ultrasound examinations and histopathology of the skin biopsy suggested that mild ischemia of the left temporoparietal region led to reversible alopecia, while the permanent hair loss in the left parietal area was associated with severe skin ischemia. Therefore, the key to treatment would be to focus on the effective correction of severe ischemia-induced skin necrosis to prevent permanent hair loss. Level of Evidence V This journal requires that authors assign a level of evidence to each article. For a full description of these Evidence-Based Medicine ratings, please refer to the Table of Contents or the online Instructions to Authors www.springer.com/00266 .
A Survey of Homomorphic Encryption for Nonspecialists

The goal of encryption is to ensure confidentiali y of data in communication and storage processes. Recently, its use in constrained devices led to consider additional features, such as the ability to delegate computations to untrusted computers. For this purpose, we would like to give the untrusted computer only an encrypted version of the data to process. The computer will perform the computation on this encrypted data, hence without knowing anything on its real value. Finally, it will send back the result, and we will decrypt it. For coherence, the decrypted result has to be equal to the intended computed value if performed on the original data. For this reason, the encryption scheme has to present a particular structure. Rivest et al. proposed in 1978 to solve this issue through homomorphic encryption [1]. Unfortunately, Brickell and Yacobi pointed out in [2] some security f aws in the firs proposals of Rivest et al. Since this f rst attempt, a lot of articles have proposed solutions dedicated to numerous application contexts: secret sharing schemes, threshold schemes (see, e.g., [3]), zero-knowledge proofs (see, e.g., [4]), oblivious transfer (see, e.g., [5]), commitment schemes (see, e.g., [3]), anonymity, privacy, electronic voting, electronic auctions, lottery protocols (see, e.g., [6]), protection ofmobile agents (see, e.g., [7]), multiparty computation (see, e.g., [3]), mix-nets (see, e.g., [8, 9]), watermarking or finge printing protocols (see, e.g., [10–14]), and so forth. The goal of this article is to provide nonspecialists with a survey of homomorphic encryption techniques. Section 2 recalls some basic concepts of cryptography and presents homomorphic encryption; it is particularly aimed at noncryptographers, providing guidelines about the main characteristics of encryption primitives: algorithms, performance, security. Section 3 provides a survey of homomorphic encryption schemes published so far, and analyses their characteristics. Most schemes we describe are based onmathematical notions the reader may not be familiar with. In the cases these notions can easily be introduced, we present them briefl . The reader may refer to [15] for more information concerning those we could not introduce properly, or algorithmic problems related to their computation. Before going deeper in the subject, let us introduce some notation. The integer (x) denotes the number of bits constituting the binary expansion of x. As usual, Zn will denote the set of integers modulo n, and Z∗n the set of its invertible elements.
Alignment by Agreement

We present an unsupervised approach to symmetric word alignment in which two simple asymmetric models are trained jointly to maximize a combination of data likelihood and agreement between the models. Compared to the standard practice of intersecting predictions of independently-trained models, joint training provides a 32% reduction in AER. Moreover, a simple and efficient pair of HMM aligners provides a 29% reduction in AER over symmetrized IBM model 4 predictions. Disciplines Computer Sciences Comments Percy Liang, Ben Taskar, and Dan Klein. 2006. Alignment by agreement. In Proceedings of the main conference on Human Language Technology Conference of the North American Chapter of the Association of Computational Linguistics (HLT-NAACL '06). Association for Computational Linguistics, Stroudsburg, PA, USA, 104-111. DOI=10.3115/1220835.1220849 http://dx.doi.org/10.3115/1220835.1220849 © ACM, 2006. This is the author's version of the work. It is posted here by permission of ACM for your personal use. Not for redistribution. The definitive version was published in Proceedings of the main conference on Human Language Technology Conference of the North American Chapter of the Association of Computational Linguistics, {(2006)} http://doi.acm.org/10.3115/1220835.1220849" Email permissions@acm.org This conference paper is available at ScholarlyCommons: http://repository.upenn.edu/cis_papers/533 Alignment by Agreement Percy Liang UC Berkeley Berkeley, CA 94720 pliang@cs.berkeley.edu Ben Taskar UC Berkeley Berkeley, CA 94720 taskar@cs.berkeley.edu Dan Klein UC Berkeley Berkeley, CA 94720 klein@cs.berkeley.edu
Occupational risks and challenges of seafaring.

UNLABELLED
Seafarers are exposed to a high diversity of occupational health hazards onboard ships.


OBJECTIVE
The aim of this article is to present a survey of the current, most important hazards in seafaring including recommendations on measures how to deal with these problems.


METHODS
The review is based on maritime expert opinions as well a PubMed analysis related to the occupational risks of seafaring.


RESULTS
Despite recent advances in injury prevention, accidents due to harmful working and living conditions at sea and of non-observance of safety rules remain a main cause of injury and death. Mortality in seafaring from cardiovascular diseases (CVD) is mainly caused by increased risks and impaired treatment options of CVD at sea. Further, shipboard stress and high demand may lead to fatigue and isolation which have an impact on the health of onboard seafarers. Communicable diseases in seafaring remain an occupational problem. Exposures to hazardous substances and UV-light are important health risks onboard ships. Because of harsh working conditions onboard including environmental conditions, sufficient recreational activities are needed for the seafarers' compensation both onboard and ashore. However, in reality there is often a lack of leisure time possibilities.


DISCUSSION
Seafaring is still an occupation with specific work-related risks. Thus, a further reduction of occupational hazards aboard ships is needed and poses a challenge for maritime health specialists and stakeholders. Nowadays, maritime medicine encompasses a broad field of workplaces with different job-related challenges.
CENTURION: Incentivizing multi-requester mobile crowd sensing

The recent proliferation of increasingly capable mobile devices has given rise to mobile crowd sensing (MCS) systems that outsource the collection of sensory data to a crowd of participating workers that carry various mobile devices. Aware of the paramount importance of effectively incentivizing participation in such systems, the research community has proposed a wide variety of incentive mechanisms. However, different from most of these existing mechanisms which assume the existence of only one data requester, we consider MCS systems with multiple data requesters, which are actually more common in practice. Specifically, our incentive mechanism is based on double auction, and is able to stimulate the participation of both data requesters and workers. In real practice, the incentive mechanism is typically not an isolated module, but interacts with the data aggregation mechanism that aggregates workers' data. For this reason, we propose CENTURION, a novel integrated framework for multi-requester MCS systems, consisting of the aforementioned incentive and data aggregation mechanism. CENTURION's incentive mechanism satisfies truthfulness, individual rationality, computational efficiency, as well as guaranteeing non-negative social welfare, and its data aggregation mechanism generates highly accurate aggregated results. The desirable properties of CENTURION are validated through both theoretical analysis and extensive simulations.
FEATURE EXTRACTION USING SURF ALGORITHM FOR OBJECT RECOGNITION

Video surveillance is active research topic in computer vision research area for humans & vehicles, so it is used over a great extent. Multiple images generated using a fixed camera contains various objects, which are taken under different variations, illumination changes after that the object’s identity and orientation are provided to the user. This scheme is used to represent individual images as well as various objects classes in a single, scale and rotation invariant model.The objective is to improve object recognition accuracy for surveillance purposes & to detect multiple objects with sufficient level of scale invariance.Multiple objects detection& recognition is important in the analysis of video data and higher level security system. This method can efficiently detect the objects from query images as well as videos by extracting frames one by one. When given a query image at runtime, by generating the set of query features and it will find best match it to other sets within the database. Using SURF algorithm find the database object with the best feature matching, then object is present in the query image. Keywords— Image recognition, Query image, Local feature, Surveillance system, SURF algorithm.
Exposure of Children and Adolescents to Alcohol Marketing on Social Media Websites

AIMS
In 2011, online marketing became the largest marketing channel in the UK, overtaking television for the first time. This study aimed to describe the exposure of children and young adults to alcohol marketing on social media websites in the UK.


METHODS
We used commercially available data on the three most used social media websites among young people in the UK, from December 2010 to May 2011. We analysed by age (6-14 years; 15-24 years) and gender the reach (proportion of internet users who used the site in each month) and impressions (number of individual pages viewed on the site in each month) for Facebook, YouTube and Twitter. We further analysed case studies of five alcohol brands to assess the marketer-generated brand content available on Facebook, YouTube and Twitter in February and March 2012.


RESULTS
Facebook was the social media site with the highest reach, with an average monthly reach of 89% of males and 91% of females aged 15-24. YouTube had a similar average monthly reach while Twitter had a considerably lower usage in the age groups studied. All five of the alcohol brands studied maintained a Facebook page, Twitter page and YouTube channel, with varying levels of user engagement. Facebook pages could not be accessed by an under-18 user, but in most cases YouTube content and Twitter content could be accessed by those of all ages.


CONCLUSION
The rise in online marketing of alcohol and the high use of social media websites by young people suggests that this is an area requiring further monitoring and regulation.
Visualising the structure of architectural open spaces based on shape analysis

Visualisation and interpretation of architectural spaces are intellectually challenging and multifaceted exercises with fairly wide ranging applications and implications. In the context of urban planning, they are most commonly undertaken to evaluate the usage of the architectural space to ensure efficient navigation and accessibility [1]. These exercises clearly assume a certain influence of the built structures on the human cognition. However, what aspect of architectural space affects the human behaviour still remains an open debate. In this respect, it is closely similar to an exercise to identify the unknown visual variables in information visualization. Since a quantitative analysis of the architectural geometric structure on a large scale will be a daunting computational task, the open space bounded by the built structures is studied instead [2]. The study of architectural open spaces essentially involves the computation of the visibility polygon or isovist (space visible all around a viewpoint, see Figure 1a) from a viewpoint and calculating various shape measures of the visibility polygon. The isovist computation involves drawing rays
Should I use TensorFlow

Google’s Machine Learning framework TensorFlow was opensourced in November 2015 [1] and has since built a growing community around it. TensorFlow is supposed to be flexible for research purposes while also allowing its models to be deployed productively [7]. This work is aimed towards people with experience in Machine Learning considering whether they should use TensorFlow in their environment. Several aspects of the framework important for such a decision are examined, such as the heterogenity, extensibility and its computation graph. A pure Python implementation of linear classification is compared with an implementation utilizing TensorFlow. I also contrast TensorFlow to other popular frameworks with respect to modeling capability, deployment and performance and give a brief description of the current adaption of the framework.
devices and apps for health care professionals : uses and benefits table 1 uses for Mobile devices and apps by health care professionals
Non-Local Patch-Based Image Inpainting

Image inpainting is the process of filling in missing regions in an image in a plausible way. In this contribution, we propose and describe an implementation of a patch-based image inpainting algorithm. The method is actually a two-dimensional version of our video inpainting algorithm proposed in [16]. The algorithm attempts to minimise a highly non-convex functional, first introducted by Wexler et al. in [18]. The functional specifies that a good solution to the inpainting problem should be an image where each patch is very similar to its nearest neighbour in the unoccluded area. Iterations are performed in a multi-scale framework which yields globally coherent results. In this manner two of the major goals of image inpainting, the correct reconstruction of textures and structures, are addressed. We address a series of important practical issues which arise when using such an approach. In particular, we reduce execution times by using the PatchMatch [3] algorithm for nearest neighbour searches, and we propose a modified patch distance which improves the comparison of textured patches. We address the crucial issue of initialisation and the choice of the number of pyramid levels, two points which are rarely discussed in such approaches. We provide several examples which illustrate the advantages of our algorithm, and compare our results with those of state-of-the-art methods.
How does communication heal? Pathways linking clinician-patient communication to health outcomes.

OBJECTIVE
Although prior research indicates that features of clinician-patient communication can predict health outcomes weeks and months after the consultation, the mechanisms accounting for these findings are poorly understood. While talk itself can be therapeutic (e.g., lessening the patient's anxiety, providing comfort), more often clinician-patient communication influences health outcomes via a more indirect route. Proximal outcomes of the interaction include patient understanding, trust, and clinician-patient agreement. These affect intermediate outcomes (e.g., increased adherence, better self-care skills) which, in turn, affect health and well-being. Seven pathways through which communication can lead to better health include increased access to care, greater patient knowledge and shared understanding, higher quality medical decisions, enhanced therapeutic alliances, increased social support, patient agency and empowerment, and better management of emotions.


CONCLUSION
Future research should hypothesize pathways connecting communication to health outcomes and select measures specific to that pathway.


PRACTICE IMPLICATIONS
Clinicians and patients should maximize the therapeutic effects of communication by explicitly orienting communication to achieve intermediate outcomes (e.g., trust, mutual understanding, adherence, social support, self-efficacy) associated with improved health.