nils-herrmann/clean_scirepeval huggingface dataset:
'Let's Move It' a school based multilevel intervention to increase physical activity and reduce sedentary behaviour among older adolescents in vocational secondary schools: a study protocol for a cluster randomised trial
Venue: BMC Public Health

BackgroundPhysical activity (PA) has been shown to decline during adolescence, and those with lower education have lower levels of activity already at this age, calling for targeted efforts for them. No previous study has demonstrated lasting effects of school based PA interventions among older adolescents. Furthermore, these interventions have rarely targeted sedentary behaviour (SB) despite its relevance to health. The Let's Move It trial aims to evaluate the effectiveness and the cost effectiveness of a school based, multi level intervention, on PA and SB, among vocational school students. We hypothesise that the intervention is effective in increasing moderate to vigorous intensity physical activity (MVPA) particularly among those with low or moderate baseline levels, and decreasing SB among all students.MethodsThe design is a cluster randomised parallel group trial with an internal pilot study. The trial is conducted in six vocational schools in the Helsinki Metropolitan area, Finland. The intervention is carried out in 30 intervention classes, and 27 control classes retain the standard curriculum. The randomisation occurs at school level to avoid contamination and to aid delivery.Three of the six schools, randomly allocated, receive the 'Let's Move It' intervention which consists of 1) group sessions and poster campaign targeting students' autonomous PA motivation and self regulation skills, 2) sitting reduction in classrooms via alterations in choice architecture and teacher behaviour, and 3) enhancement of PA opportunities in school, home and community environments. At baseline, student participants are blind to group allocation. The trial is carried out in six batches in 2015 2017, with main measurements at pre intervention baseline, and 2 month and 14 month follow ups. Primary outcomes are for PA, MVPA measured by accelerometry and self report, and for SB, sedentary time and breaks in sedentary time (accelerometry).Key secondary outcomes include measured body composition, self reported well being, and psychological variables. Process variables include measures of psychosocial determinants of PA (e.g. autonomous motivation) and use of behaviour change techniques. Process evaluation also includes qualitative interviews. Intervention fidelity is monitored.DiscussionThe study will establish whether the Let's Move It intervention is effective in increasing PA and reducing SB in vocational school students, and identify key processes explaining the results.
Shedding Light on the Adoption of Let's Encrypt
Venue: ArXiv

Let's Encrypt is a new entrant in the Certificate Authority ecosystem that offers free and automated certificate signing. It is visionary in its commitment to Certificate Transparency. In this paper, we shed light on the adoption patterns of Let's Encrypt "in the wild" and inform the future design and deployment of this exciting development in the security landscape. We analyze acquisition patterns of certificates as well as their usage and deployment trends in the real world. To this end, we analyze data from Certificate Transparency Logs containing records of more then 18 million certificates. We also leverage other sources like Censys, Alexa's historic records, Geolocation databases, and VirusTotal. We also perform active HTTPS measurements on the domains owning Let's Encrypt certificates. Our analysis of certificate acquisition shows that (1) the impact of Let's Encrypt is particularly visible in Western Europe; (2) Let's Encrypt has the potential to democratize HTTPS adoption in countries that are recent entrants to Internet adoption; (3) there is anecdotal evidence of popular domains quitting their previously untrustworthy or expensive CAs in order to transition to Let's Encrypt; and (4) there is a "heavy tailed" behavior where a small number of domains acquire a large number of certificates. With respect to usage, we find that: (1) only 54% of domains actually use the Let's Encrypt certificates they have procured; (2) there are many non trivial incidents of server misconfigurations; and (3) there is early evidence of use of Let's Encrypt certificates for typosquatting and for malware laden sites.
Extending the OpenAI Gym for robotics: a toolkit for reinforcement learning using ROS and Gazebo
Venue: ArXiv

This paper presents an extension of the OpenAI Gym for robotics using the Robot Operating System (ROS) and the Gazebo simulator. The content discusses the software architecture proposed and the results obtained by using two Reinforcement Learning techniques: Q Learning and Sarsa. Ultimately, the output of this work presents a benchmarking system for robotics that allows different techniques and algorithms to be compared using the same virtual conditions.
Pile Design and Construction Rules of Thumb Ed. 2

Pile Design and Construction Rules of Thumb presents Geotechnical and Civil Engineers a comprehensive coverage of Pile Foundation related theory and practice. Based on the author's experience as a PE, the book brings concise theory and extensive calculations, examples and case studies that can be easily applied by professional in their day to day challenges. In its first part, the book covers the fundamentals of Pile Selection: Soil investigation, condition, pile types and how to choose them. In the second part it addresses the Design of Pile Foundations, including different types of soils, pile groups, pile settlement and pile design in rock. Next, the most extensive part covers Design Strategies and contains chapters on loading analysis, load distribution, negative skin friction, design for expansive soils, wave equation analysis, batter piles, seismic analysis and the use of softwares for design aid. The fourth part covers Construction Methods including hammers, Inspection, cost estimation, load tests, offshore piling, beams and caps. In this new and updated edition the author has incorporated new pile designs such as helical, composite, wind turbine monopiles, and spiral coil energy piles. All calculations have been updated to most current materials characteristics and designs available in the market. Also, new chapters on negative skin friction, pile driving, and pile load testing have been added. Practicing Geotechnical, and Civil Engineers will find in this book an excellent handbook for frequent consult, benefiting from the clear and direct calculations, examples, and cases. Civil Engineering preparing for PE exams may benefit from the extensive coverage of the subject.Convenient for day to day consults;Numerous design examples for sandy soils, clay soils, and seismic loadings;Now including helical, composite, wind turbine monopiles, and spiral coil energy piles;Methodologies and case studies for different pile types;Serves as PE exam preparation material.
Image Super Resolution Using Deep Convolutional Networks
Venue: IEEE Transactions on Pattern Analysis and Machine Intelligence

We propose a deep learning method for single image super resolution (SR) Our method directly learns an end to end mapping between the low/high resolution images. The mapping is represented as a deep convolutional neural network (CNN) that takes the low resolution image as the input and outputs the high resolution one. We further show that traditional sparse coding based SR methods can also be viewed as a deep convolutional network. But unlike traditional methods that handle each component separately, our method jointly optimizes all layers. Our deep CNN has a lightweight structure, yet demonstrates state of the art restoration quality, and achieves fast speed for practical on line usage. We explore different network structures and parameter settings to achieve trade offs between performance and speed. Moreover, we extend our network to cope with three color channels simultaneously, and show better overall reconstruction quality.
Accurate Image Super Resolution Using Very Deep Convolutional Networks
Venue: 2016 IEEE Conference on Computer Vision and Pattern Recognition (CVPR)

We present a highly accurate single image superresolution (SR) method. Our method uses a very deep convolutional network inspired by VGG net used for ImageNet classification [19] We find increasing our network depth shows a significant improvement in accuracy. Our final model uses 20 weight layers. By cascading small filters many times in a deep network structure, contextual information over large image regions is exploited in an efficient way. With very deep networks, however, convergence speed becomes a critical issue during training. We propose a simple yet effective training procedure. We learn residuals only and use extremely high learning rates (104 times higher than SRCNN [6] enabled by adjustable gradient clipping. Our proposed method performs better than existing methods in accuracy and visual improvements in our results are easily noticeable.
Destination management organizations (DMOs) and Digital Natives: the neglected "informal expertise" in web 2.0 implementation and social media presence. Insights from the Italian Friuli Venezia Giulia DMO
Venue: J. Inf. Technol. Tour.

The present paper wishes to investigate the perspective of Digital Natives (DNs) described in literature as "informal experts" in respect of digital strategies' implementation of destination management organizations (DMOs) In particular, focus groups of students and workers in the tourism field were asked to browse and discuss the website and social media presence of an Italian regional DMO (i.e. PromoTurismoFVG) Comments were collected and analyzed with the GABEK/Winrelan method for qualitative analysis. Results confirmed the DMO's adoption of a digital format but with limited social and consumer generated contents (CGC) DNs recognized the implementation of a Web 2.0 destination site in a rather traditional marketing mix strategy. Furthermore DMO websites and social media (SM) (i.e. Facebook, Instagram, Twitter and YouTube) content analysis showed that the DMO lacks products and offers for the young market segment. The combination of limited social content and the weak attention to youth market makes the current digital DMO not attractive enough to the digital natives. The work highlights the importance on focusing on DN "informal expertise" in the planning and development of digital strategies, DMO websites and SM presence. Their proved social media knowledge and digital competences have to be considered as a key opportunity for DMOs and for the improvement of the destination marketing strategies. This research contributes to the academic discussion on SM/Web 2.0 implementation in destination management, by presenting an exploratory study on DNs' informal expert perspective supported by the use of GABEK/Winrelan as an innovative method.
How Instagram Influences Visual Destination Image a Case Study of Jordan and Costa Rica

The Social Web is increasingly taking up the daily time of consumers and is becoming a primary source of impressions about tourism destinations. The recent shift towards more visual content, as evidenced in the fast growing social network Instagram being largely a photo sharing site, means that DMOs need to consider how photos of their destinations can be influencing consumers' destination image. We present our study on how the selection of images from a social media site (Instagram) to promote a destination can be used to influence destination image. As a basis for our study, we have selected the DMO channels of Jordan and Costa Rica in Instagram. Through focus groups and a Likert scale survey, we draw first conclusions on which types of photos are most effective to positively promote a destination and how the consumers' previous image of a destination could affect this.
El sedentarismo y la actividad fisica en trabajadores administrativos del sector publico Sedentary lifestyle and physical activity in administrative public sector workers

En el presente articulo se plantea como objetivo caracterizar el nivel de sedentarismo y actividad fisica, que realiza el personal administrativo de diferentes instituciones del sector publico de la ciudad de Milagro, Ecuador, considerando algunos espacios como el lugar de trabajo, forma de traslado y tiempo libre. Se trata de una investigacion de tipo descriptiva de corte transversal, con una muestra de 240 participantes, de los cuales el 48,5% son de sexo masculino (109) y 51,5% femenino (131) Como instrumento se utilizo el Global Physical Activity Questionnaire (GPAQ) elaborado por la Organizacion Mundial de la Salud, aplicado en la version corta en espanol 2002: Cuestionario Internacional de Actividad Fisica (IPAQ) que consta de 7 preguntas. Entre los principales resultados estan que mas del 54% del personal permanece sentado entre 7 y 12 horas diariamente. El 39% realiza una actividad moderada en su lugar de trabajo, el 8.8% actividad intensa y en su tiempo libre, el 67% de los participantes no realiza ningun deporte. Finalmente se concluye que al menos la mitad de los empleados administrativos de las empresas publicas en estudio, no realiza ninguna actividad que les permita disminuir el estado de sedentarismo. ABSTRACTThis study aims to characterize the level of sedentary behavior and physical activity, of the administrative staff of various Organism of public sector at the city of Milagro, Ecuador, considering some areas as: the workplace, way of transportation, and their spare time. This is a descriptive research cross section, with a sample of 240 participants, of which 48.5% are male (109) and 51.5% are female (131) The instrument that was used is the Global Physical Activity Questionnaire (GPAQ) prepared by the World Health Organization, implemented in the short Spanish version 2002: International Physical Activity Questionnaire (IPAQ) which consists of 7 questions. As main results are that more than 54% of staff remains seated between 7 and 12 hours daily. The 39% perform moderate activity in their workplace, 8.8% intense activity and in their spare time, 67% of participants did not perform any sport. Finally it was concluded that at least half of the administrative employees of public companies in the city of Milagro, do not perform any activity that allows them to reduce the state of inactivity.
Neural Data Driven Musculoskeletal Modeling for Personalized Neurorehabilitation Technologies
Venue: IEEE Transactions on Biomedical Engineering

The development of neurorehabilitation technologies requires the profound understanding of the mechanisms underlying an individual's motor ability and impairment. A major factor limiting this understanding is the difficulty of bridging between events taking place at the neurophysiologic level (i.e. motor neuron firings) with those emerging at the musculoskeletal level (i.e. joint actuation) in vivo in the intact moving human. This review presents emerging model based methodologies for filling this gap that are promising for developing clinically viable technologies.  We provide a design overview of musculoskeletal modeling formulations driven by recordings of neuromuscular activity with a critical comparison to alternative model free approaches in the context of neurorehabilitation technologies. We present advanced electromyography based techniques for interfacing with the human nervous system and model based techniques for translating the extracted neural information into estimates of motor function.  We introduce representative application areas where modeling is relevant for accessing neuromuscular variables that could not be measured experimentally. We then show how these variables are used for designing personalized rehabilitation interventions, biologically inspired limbs, and human machine interfaces.  The ability of using electrophysiological recordings to inform biomechanical models enables accessing a broader range of neuromechanical variables than analyzing electrophysiological data or movement data individually. This enables understanding the neuromechanical interplay underlying in vivo movement function, pathology, and robot assisted motor recovery.  Filling the gap between our understandings of movement neural and mechanical functions is central for addressing one of the major challenges in neurorehabilitation: personalizing current technologies and interventions to an individual's anatomy and impairment.
MS MARCO: A Human Generated MAchine Reading COmprehension Dataset
Venue: CoCo@NIPS

This paper presents our recent work on the design and development of a new, large scale dataset, which we name MS MARCO, for MAchine Reading COmprehension. This new dataset is aimed to overcome a number of well known weaknesses of previous publicly available datasets for the same task of reading comprehension and question answering. In MS MARCO, all questions are sampled from real anonymized user queries. The context passages, from which answers in the dataset are derived, are extracted from real web documents using the most advanced version of the Bing search engine. The answers to the queries are human generated. Finally, a subset of these queries has multiple answers. We aim to release one million queries and the corresponding answers in the dataset, which, to the best of our knowledge, is the most comprehensive real world dataset of its kind in both quantity and quality. We are currently releasing 100,000 queries with their corresponding answers to inspire work in reading comprehension and question answering along with gathering feedback from the research community.
The Relationships Between School Climate, Teacher Self Efficacy, and Teacher Beliefs

This quantitative study examined the relationship between school climate, teacher self efficacy, and teacher beliefs. Teachers at two middle schools in rural southern Virginia participated in the study. Middle school teachers were surveyed using the School Climate Index to collect information about teacher perceived views on their school's climate and the Teacher Sense of Efficacy Scale to gather information about teacher self efficacy. Pearson Product Moment Correlations were used to measure the relationship between school climate and teacher selfefficacy as well as teacher self efficacy and four teacher perceived climate factors, including collegial leadership, teacher professionalism, academic press, and community engagement. Data analysis did not provide evidence of a significant relationship between school climate and teacher self efficacy. A positive correlation, however, was found in the relationship between teacher self efficacy and community engagement. Recommendations for future research include replicating this study in elementary and high schools as well as in schools with different demographics, populations, and accreditation statuses to determine generalizations about school climate and teacher self efficacy.
Guidance to international business to consumer logistics through online marketplace Weecos.com

Tampereen ammattikorkeakoulu Tampere University of Applied Sciences Degree Programme in International Business Supply Chain Management ROURU,  Guidance to international business to consumer logistics through online marketplace Weecos.com Thesis supervisor: Anasse Bouhlal, Principal Lecturer Bachelor's thesis 45 pages, appendices 10 pages November 2016 This thesis has been carried out as a case study for an online marketplace, Weecos.com. The main objective of the thesis was that the company could provide logistics support to the sellers in the marketplace, so that the common goals in internationalization could be met. The thesis supports export and the growth of e commerce in general. The purpose of this study was to provide a clear step by step guidance to international business to consumer logistics for e commerce business implemented through the marketplace Weecos.com. The thesis covers the logistics process from recieving the order to the delivery to the end customer, as well as the reverse logistics process, which is an important process in e commerce. The ultimate goal of the thesis was to communicate international business to consumer logistics in an efficient form for companies without expertise in the field. The study was completed as a case study based on literature and interviews with different professionals, and by using an example case of how the guidance works in practice. With a combination of theories the study brings together essential information on business to consumer logistics, from an e commerce point of view. The research questions were formed from real workplace problems, with an objective to make the process clear and efficient for employees. Based on the thesis Weecos Oy is able to offer logistics support to its partners, and Papu Design Oy received a detailed and customized guidance to international business toconsumer logistics for their e commerce business. As e commerce is growing and the competition in the field is fierce, the consumer logistics is an important issue for small and medium sized businesses. The customer expectations are growing, and logistics issues have a big impact on how the customer makes the purchasing decision. Based on the research of this thesis small and medium sized enterprises can improve their logistics processes.
Environmental Monitoring and Greenhouse Control by Distributed Sensor Network

A sensor is a miniature component which measure physical parameters from the nvironment. Sensors measure the physical parameters and transmit them either by wired or wireless medium. In wireless medium the sensor and its associated components are called as node. A node is self possessed by a processor, local memory, sensors, radio, battery and a base station responsible for receiving and processing data collected by the nodes. They carry out joint activities due to limited resources such as battery, processor and memory. Nowadays, the applications of these networks are numerous, varied and the applications in agriculture are still budding. One interesting application is in environmental monitoring and greenhouse control, where the crop conditions such as climate and soil do not depend on natural agents. To control and monitor the environmental factors, sensors and actuators are necessary. Under these circumstances, these devices must be used to make a distributed measure, spreading sensors all over the greenhouse using distributed clustering. This paper reveals an idea of environmental monitoring and greenhouse control using a sensor network. The hardware implementation shows periodic monitoring and control of greenhouse gases in an enhanced manner. Future work is concentrated in application of the same mechanism using wireless sensor network.
Multivariable Greenhouse Control Using the Filtered Smith Predictor

The increasing demand for high efficiency greenhouse control systems motivates the interest in ensuring optimal growth climate conditions into the system. The greenhouse climate control is complex because of the strong coupling between the two main controlled variables (temperature and humidity) the time delays present within the control loop and the high nonlinear interaction between the physical and the biological subsystems. In this context, the idea of this work is to improve the robust behavior of the Filtered Smith Predictor (FSP) in an equivalent greenhouse climate model with multiple time delays as a function of the uncertainty degree of the process model to be controlled. An automated tuning technique is proposed for the robustness filter of MIMO FSP through online estimation of the modeling error. Simulation results show that the proposed technique is able to improve disturbance rejection dynamics while assuring robust stability.