nils-herrmann/clean_scirepeval huggingface dataset:
A 2-phase labeling and choice architecture intervention to improve healthy food and beverage choices.

We assessed whether a 2-phase labeling and choice architecture intervention would increase sales of healthy food and beverages in a large hospital cafeteria.



Phase 1 was a 3-month color-coded labeling intervention (red = unhealthy, yellow = less healthy, green = healthy). Phase 2 added a 3-month choice architecture intervention that increased the visibility and convenience of some green items. We compared relative changes in 3-month sales from baseline to phase 1 and from phase 1 to phase 2.



At baseline (977,793 items, including 199,513 beverages), 24.9% of sales were red and 42.2% were green. Sales of red items decreased in both phases (P < .001), and green items increased in phase 1 (P < .001). The largest changes occurred among beverages. Red beverages decreased 16.5% during phase 1 (P < .001) and further decreased 11.4% in phase 2 (P < .001). Green beverages increased 9.6% in phase 1 (P < .001) and further increased 4.0% in phase 2 (P < .001). Bottled water increased 25.8% during phase 2 (P < .001) but did not increase at 2 on-site comparison cafeterias (P < .001).



A color-coded labeling intervention improved sales of healthy items and was enhanced by a choice architecture intervention.
Creating a Future for Occupational Health.

Economic, social, technical, and political drivers are fundamentally changing the nature of work and work environments, with profound implications for the field of occupational health. Nevertheless, researchers and practitioners entering the field are largely being trained to assess and control exposures using approaches developed under old models of work and risks.



A speaker series and symposium were organized to broadly explore current challenges and future directions for the occupational health field. Broad themes identified throughout these discussions are characterized and discussed to highlight important future directions of occupational health.



Despite the relatively diverse group of presenters and topics addressed, some important cross-cutting themes emerged. Changes in work organization and the resulting insecurity and precarious employment arrangements change the nature of risk to a large fraction of the workforce. Workforce demographics are changing, and economic disparities among working groups are growing. Globalization exacerbates the 'race to the bottom' for cheap labor, poor regulatory oversight, and limited labor rights. Largely, as a result of these phenomena, the historical distinction between work and non-work exposures has become largely artificial and less useful in understanding risks and developing effective public health intervention models. Additional changes related to climate change, governmental and regulatory limitations, and inadequate surveillance systems challenge and frustrate occupational health progress, while new biomedical and information technologies expand the opportunities for understanding and intervening to improve worker health.



The ideas and evidences discussed during this project suggest that occupational health training, professional practice, and research evolve towards a more holistic, public health-oriented model of worker health. This will require engagement with a wide network of stakeholders. Research and training portfolios need to be broadened to better align with the current realities of work and health and to prepare practitioners for the changing array of occupational health challenges.
Attachment from infancy to early adulthood in a high-risk sample: continuity, discontinuity, and their correlates.

This study explores the stability of attachment security and representations from infancy to early adulthood in a sample chosen originally for poverty and high risk for poor developmental outcomes. Participants for this study were 57 young adults who are part of an ongoing prospective study of development and adaptation in a high-risk sample. Attachment was assessed during infancy by using the Ainsworth Strange Situation (Ainsworth & Wittig) and at age 19 by using the Berkeley Adult Attachment Interview (George, Kaplan, & Main). Possible correlates of continuity and discontinuity in attachment were drawn from assessments of the participants and their mothers over the course of the study. Results provided no evidence for significant continuity between infant and adult attachment in this sample, with many participants transitioning to insecurity. The evidence, however, indicated that there might be lawful discontinuity. Analyses of correlates of continuity and discontinuity in attachment classification from infancy to adulthood indicated that the continuous and discontinuous groups were differentiated on the basis of child maltreatment, maternal depression, and family functioning in early adolescence. These results provide evidence that although attachment has been found to be stable over time in other samples, attachment representations are vulnerable to difficult and chaotic life experiences.
A New Approch For Ridge Preservation : Socket Shield Technique : A Review *

Tooth loss and subsequent ridge collapse continue to burden restorative implant treament. Careful management of the post-extraction tissues is needed to preserve the alveolar ridge. In-lieu of surgical augmentation to correct a ridge defect, the socket-shield technique offers a promising solution. As the root submergence technique retains the periodontal attachment and maintains the alveolar ridge for pontic site development, this review article demonstrates the hypothesis that retention of a prepared tooth root section as a socket-shield prevents the recession of tissues buccofacial to an immediately placed implant.  Alveolar bone preservation, buccal bone, esthetic zone, extraction socket, immediate implant, socket shield --------------------------------------------------------------------------------------------------------------------------------------Date of Submission: 0X -XX-2017 Date of acceptance: 18-10-2017 ---------------------------------------------------------------------------------------------------------------
A Detailed CFD and Experimental Investigation of a Benchmark Turbulent Backward Facing Step Flow

A benchmark turbulent Backward Facing Step (BFS) airflow was studied in detail through a program of tightly coupled experimental and CFD analysis. The theoretical and experimental approaches were developed simultaneously in a “building block” approach and the results used to verify each “block”. Information from both CFD and experiment was used to develop confidence in the accuracy of each technique and to increase our understanding of the BFS flow.
HSA-RNN: Hierarchical Structure-Adaptive RNN for Video Summarization

Although video summarization has achieved great success in recent years, few approaches have realized the influence of video structure on the summarization results. As we know, the video data follow a hierarchical structure, i.e., a video is composed of shots, and a shot is composed of several frames. Generally, shots provide the activity-level information for people to understand the video content. While few existing summarization approaches pay attention to the shot segmentation procedure. They generate shots by some trivial strategies, such as fixed length segmentation, which may destroy the underlying hierarchical structure of video data and further reduce the quality of generated summaries. To address this problem, we propose a structure-adaptive video summarization approach that integrates shot segmentation and video summarization into a Hierarchical Structure-Adaptive RNN, denoted as HSA-RNN. We evaluate the proposed approach on four popular datasets, i.e., SumMe, TVsum, CoSum and VTW. The experimental results have demonstrated the effectiveness of HSA-RNN in the video summarization task.
Top-k Exploration of Query Candidates for Efficient Keyword Search on Graph-Shaped (RDF) Data

Keyword queries enjoy widespread usage as they represent an intuitive way of specifying information needs. Recently, answering keyword queries on graph-structured data has emerged as an important research topic. The prevalent approaches build on dedicated indexing techniques as well as search algorithms aiming at finding substructures that connect the data elements matching the keywords. In this paper, we introduce a novel keyword search paradigm for graph-structured data, focusing in particular on the RDF data model. Instead of computing answers directly as in previous approaches, we first compute queries from the keywords, allowing the user to choose the appropriate query, and finally, process the query using the underlying database engine. Thereby, the full range of database optimization techniques can be leveraged for query processing. For the computation of queries, we propose a novel algorithm for the exploration of top-k matching subgraphs. While related techniques search the best answer trees, our algorithm is guaranteed to compute all k subgraphs with lowest costs, including cyclic graphs. By performing exploration only on a summary data structure derived from the data graph, we achieve promising performance improvements compared to other approaches.
Cognitive HF — New perspectives to use the high frequency band

The HF band, located in between 3-30 MHz, can offer single hop communication channels over a very long distances - even up to around the world. Traditionally, the HF is seen primarily as a solution for long communication ranges although it may also be a perfect choice for much shorter communication ranges when high data rates are not a primary target. It is well known that the HF channel is a demanding environment to operate since it changes rapidly, i.e., channel is available at a moment but the next moment it is not. Therefore, a big problem in HF communications is channel access or channel selection. By choosing the used HF channels wisely, i.e., cognitively, the channel behavior and system reliability considerably improves. This paper discusses about a change of paradigm in HF communication that will take place after applying cognitive principles on the HF system.
A 1.2-V 2.7-mW 160MHz continuous-time delta-sigma modulator with input-feedforward structure

A power and area efficient continuous-time inputfeedforward delta-sigma modulator (DSM) structure is proposed. The coefficients are optimized to increase the input range and reduce the power. The feedforward paths and the summer are embedded into the quantizer, hence the circuit is simplified, and the power consumption and area are reduced. The prototype chip, fabricated in a 0.13-µm CMOS technology, achieves a 68-dB DR (Dynamic Range) and 66.1-dB SNDR (signal-to-noise-and-distortion ratio) over a 1.25-MHz signal bandwidth with a 160-MHz clock. The power consumption of the modulator is 2.7 mW under a 1.2-V supply, and the chip core area is 0.082mm2.
The SDN Approach for the Aggregation/Disaggregation of Sensor Data

In many Internet of Things (IoT) applications, large numbers of small sensor data are delivered in the network, which may cause heavy traffics. To reduce the number of messages delivered from the sensor devices to the IoT server, a promising approach is to aggregate several small IoT messages into a large packet before they are delivered through the network. When the packets arrive at the destination, they are disaggregated into the original IoT messages. In the existing solutions, packet aggregation/disaggregation is performed by software at the server, which results in long delays and low throughputs. To resolve the above issue, this paper utilizes the programmable Software Defined Networking (SDN) switch to program quick packet aggregation and disaggregation. Specifically, we consider the Programming Protocol-Independent Packet Processor (P4) technology. We design and develop novel P4 programs for aggregation and disaggregation in commercial P4 switches. Our study indicates that packet aggregation can be achieved in a P4 switch with its line rate (without extra packet processing cost). On the other hand, to disaggregate a packet that combines N IoT messages, the processing time is about the same as processing N individual IoT messages. Our implementation conducts IoT message aggregation at the highest bit rate (100 Gbps) that has not been found in the literature. We further propose to provide a small buffer in the P4 switch to significantly reduce the processing power for disaggregating a packet.
Patent overlay mapping: Visualizing technological distance

This paper presents a new global patent map that represents all technological categories, and a method to locate patent data of individual organizations and technological fields on the global map. This overlay map technique may support competitive intelligence and policy decision-making. The global patent map is based on similarities in citing-to-cited relationships between categories of the International Patent Classification (IPC) of European Patent Office (EPO) patents from 2000 to 2006. This patent dataset, extracted from the PATSTAT database, includes 760,000 patent records in 466 IPC-based categories. We compare the global patent maps derived from this categorization to related efforts of other global patent maps. The paper overlays nanotechnology-related patenting activities of two companies and two different nanotechnology subfields on the global patent map. The exercise shows the potential of patent overlay maps to visualize technological areas and potentially support decision-making. Furthermore, this study shows that IPC categories that are similar to one another based on citing-to-cited patterns (and thus are close in the global patent map) are not necessarily in the same hierarchical IPC branch, thus revealing new relationships between technologies that are classified as pertaining to different (and sometimes distant) subject areas in the IPC scheme. Appearing in the Journal of the Association for Information Science and Technology
Homography flow for dense correspondences

We present a unified framework for dense correspondence estimation, called Homography flow, to handle large photometric and geometric deformations in an efficient manner. Our algorithm is inspired by recent successes of the sparse to dense framework. The main intuition is that dense flows located in same plane can be represented as a single geometric transform. Tailored to dense correspondence task, the Homography flow differs from previous methods in the flow domain clustering and the trilateral interpolation. By estimating and propagating sparsely estimated transforms, dense flow field is estimated with very low computation time. The Homography flow highly improves the performance of dense correspondences, especially in flow discontinuous area. Experimental results on challenging image pairs show that our approach suppresses the state-of-the-art algorithms in both accuracy and computation time.
Early warning- and track and trigger systems for newborn infants: A review.

Tools for clinical assessment and escalation of observation and treatment are insufficiently established in the newborn population. We aimed to provide an overview over early warning- and track and trigger systems for newborn infants and performed a nonsystematic review based on a search in Medline and Cinahl until November 2015. Search terms included 'infant, newborn', 'early warning score', and 'track and trigger'. Experts in the field were contacted for identification of unpublished systems. Outcome measures included reference values for physiological parameters including respiratory rate and heart rate, and ways of quantifying the extent of deviations from the reference. Only four neonatal early warning scores were published in full detail, and one system for infants with cardiac disease was considered as having a more general applicability. Temperature, respiratory rate, heart rate, SpO2, capillary refill time, and level of consciousness were parameters commonly included, but the definition and quantification of 'abnormal' varied slightly. The available scoring systems were designed for term and near-term infants in postpartum wards, not neonatal intensive care units. In conclusion, there is a limited availability of neonatal early warning scores. Scoring systems for high-risk neonates in neonatal intensive care units and preterm infants were not identified.
Electronic white cane for blind people navigation assistance

In modern daily life people need to move, whether in business or leisure, sightseeing or addressing a meeting. Often this is done in familiar environments, but in some cases we need to find our way in unfamiliar scenarios. Visual impairment is a factor that greatly reduces mobility. Currently, the most widespread and used means by the visually impaired people are the white stick and the guide dog; however both present some limitations. With the recent advances in inclusive technology it is possible to extend the support given to people with visual impairment during their mobility. In this context we propose a system, named SmartVision, whose global objective is to give blind users the ability to move around in unfamiliar environments, whether indoor or outdoor, through a user friendly interface that is fed by a geographic information system (GIS). In this paper we propose the development of an electronic white cane that helps moving around, in both indoor and outdoor environments, providing contextualized geographical information using RFID technology.
A Review of Audio Fingerprinting

An audio fingerprint is a compact content-based signature that summarizes an audio recording. Audio Fingerprinting technologies have attracted attention since they allow the identification of audio independently of its format and without the need of meta-data or watermark embedding. Other uses of fingerprinting include: integrity verification, watermark support and content-based audio retrieval. The different approaches to fingerprinting have been described with different rationales and terminology: Pattern matching, Multimedia (Music) Information Retrieval or Cryptography (Robust Hashing). In this paper, we review different techniques describing its functional blocks as parts of a common, unified framework.
Assessment of low-frequency fatigue with two methods of electrical stimulation.

The aim of this study was to compare the use of transcutaneous vs. motor nerve stimulation in the evaluation of low-frequency fatigue. Nine female and eleven male subjects, all physically active, performed a 30-min downhill run on a motorized treadmill. Knee extensor muscle contractile characteristics were measured before, immediately after (Post), and 30 min after the fatiguing exercise (Post30) by using single twitches and 0.5-s tetani at 20 Hz (P20) and 80 Hz (P80). The P20-to-P80 ratio was calculated. Electrical stimulations were randomly applied either maximally to the femoral nerve or via large surface electrodes (ES) at an intensity sufficient to evoke 50% of maximal voluntary contraction (MVC) during a 80-Hz tetanus. Voluntary activation level was also determined during isometric MVC by the twitch-interpolation technique. Knee extensor MVC and voluntary activation level decreased at all points in time postexercise (P < 0.001). P20 and P80 displayed significant time x gender x stimulation method interactions (P < 0.05 and P < 0.001, respectively). Both stimulation methods detected significant torque reductions at Post and Post30. Overall, ES tended to detect a greater impairment at Post in male and a lesser one in female subjects at both Post and Post30. Interestingly, the P20-P80 ratio relative decrease did not differ between the two methods of stimulation. The low-to-high frequency ratio only demonstrated a significant time effect (P < 0.001). It can be concluded that low-frequency fatigue due to eccentric exercise appears to be accurately assessable by ES.
Double emulsion solvent evaporation techniques used for drug encapsulation.

Double emulsions are complex systems, also called "emulsions of emulsions", in which the droplets of the dispersed phase contain one or more types of smaller dispersed droplets themselves. Double emulsions have the potential for encapsulation of both hydrophobic as well as hydrophilic drugs, cosmetics, foods and other high value products. Techniques based on double emulsions are commonly used for the encapsulation of hydrophilic molecules, which suffer from low encapsulation efficiency because of rapid drug partitioning into the external aqueous phase when using single emulsions. The main issue when using double emulsions is their production in a well-controlled manner, with homogeneous droplet size by optimizing different process variables. In this review special attention has been paid to the application of double emulsion techniques for the encapsulation of various hydrophilic and hydrophobic anticancer drugs, anti-inflammatory drugs, antibiotic drugs, proteins and amino acids and their applications in theranostics. Moreover, the optimized ratio of the different phases and other process parameters of double emulsions are discussed. Finally, the results published regarding various types of solvents, stabilizers and polymers used for the encapsulation of several active substances via double emulsion processes are reported.
E-Learning Change Management: Challenges And Opportunities

The role of e-learning technologies entirely depends on the acceptance and execution of required-change in the thinking and behaviour of the users of institutions. The research are constantly reporting that many e-learning projects are falling short of their objectives due to many reasons but on the top is the user resistance to change according to the digital requirements of new era. It is argued that the suitable way for change management in e-learning environment is the training and persuading of users with a view to enhance their digital literacy and thus gradually changing the users’ attitude in positive direction. This paper discusses change management in transition to e-learning system considering pedagogical, cost and technical implications. It also discusses challenges and opportunities for integrating these technologies in higher learning institutions with examples from Turkey GATA (Gülhane Askeri Tıp Akademisi-Gülhane Military Medical Academy).
K-set tilable surfaces

This paper introduces a method for optimizing the tiles of a quad-mesh. Given a quad-based surface, the goal is to generate a set of K quads whose instances can produce a tiled surface that approximates the input surface. A solution to the problem is a K-set tilable surface, which can lead to an effective cost reduction in the physical construction of the given surface. Rather than molding lots of different building blocks, a K-set tilable surface requires the construction of K prefabricated components only. To realize the K-set tilable surface, we use a cluster-optimize approach. First, we iteratively cluster and analyze: clusters of similar shapes are merged, while edge connections between the K quads on the target surface are analyzed to learn the induced flexibility of the K-set tilable surface. Then, we apply a non-linear optimization model with constraints that maintain the K quads connections and shapes, and show how quad-based surfaces are optimized into K-set tilable surfaces. Our algorithm is demonstrated on various surfaces, including some that mimic the exteriors of certain renowned building landmarks.