LLukas22/scidocs huggingface dataset:
Motivational theory of human robot teamwork

Human‒robot teams, teams of humans and robots, are being deployed across many work settings.1 This is reflected in the increased use of robots in the workforce, where they are expected to replace as much as half the workforce in 10‒20 years.2‒4 The ability to effectively integrate robots into teams can either hinder or facilitate successful teamwork.5 However, advances in technology have far outpaced our theorizing with regard to the relationships between humans and robots.5‒7 Motivational theories of teamwork highlight the role of effort or a lack of effort when it comes to promoting effective teamwork. Motivation is defined as an individual or team’s intention of achieving a goal, which is followed by an allocation of effort to achieve this goal.8 In this paper, more effective teamwork is assumed to lead to better performance, team satisfaction and viability. All three outcomes are widely recognized as important measures of successful teamwork.7 Motivational theories have been used to explain both individual and team performance.9‒12 Working with robots often involves both physical and mental activities. This implies that motivation might be particularly important to the success of these teams. Unfortunately, despite the potential importance there is much we do not know with regard to the role of motivation in effective teamwork with robots.13‒15 With this in mind, our goal in this paper is to advance our understanding of teamwork with robots through a motivational view (Figure 1). In this paper we propose the “Motivational Theory of Human‒Robot Teamwork” to better understand teamwork in human‒robot teams. In doing so, we leverage the research on robot personality. Personality has consistently demonstrated an impact on the actions and outcomes of teamwork among humans and with robots.16 In this paper we present a theory that allows us to better understand motivation in human‒robot teamwork. Here we make three key contributions. First, we theoretically integrate the literature on human‒robot personality with theories of individual and team motivation. In doing so, we put forth a more coherent explanation of the relationship between prior HRI research on personality and future HRI research on motivation. Second, we identify the robot’s competence as a key theoretical mechanism linking robot personality and human motivation in human‒robot teams. Finally, the proposed theory goes beyond the individual level of analysis to explicate the mechanisms driving motivation at the team level as well linking both individual and team outcomes. The following section presents the general relationships between a robot’s personality traits, motivation, and individual and team outcomes. This first set of propositions presents the impacts of the robot’s personality on a human’s perceptions of its competence. The next section discusses the effects of the robot’s competence on human motivation. This is followed by propositions related to the impact of motivation on individual and team outcomes. Finally, we conclude the paper.
A Multi-Stage CUDA Kernel for Floyd-Warshall

We present a new implementation of the Floyd-Warshall AllPairs Shortest Paths algorithm on CUDA. Our algorithm runs approximately 5 times faster than the previously best reported algorithm. In order to achieve this speedup, we applied a new technique to reduce usage of on-chip shared memory and allow the CUDA scheduler to more effectively hide instruction latency.
Applications of machine learning in animal behaviour studies

http://dx.doi.org/10.1016/j.anbehav.2016.12.005 0003-3472/© 2017 The Authors. Published by Elsevie license (http://creativecommons.org/licenses/by/4.0/) In many areas of animal behaviour research, improvements in our ability to collect large and detailed data sets are outstripping our ability to analyse them. These diverse, complex and often highdimensional data sets exhibit nonlinear dependencies and unknown interactions across multiple variables, and may fail to conform to the assumptions of many classical statistical methods. The field of machine learning provides methodologies that are ideally suited to the task of extracting knowledge from these data. In this review, we aim to introduce animal behaviourists unfamiliar with machine learning (ML) to the promise of these techniques for the analysis of complex behavioural data. We start by describing the rationale behind ML and review a number of animal behaviour studies where ML has been successfully deployed. The ML framework is then introduced by presenting several unsupervised and supervised learning methods. Following this overview, we illustrate key ML approaches by developing data analytical pipelines for three different case studies that exemplify the types of behavioural and ecological questions ML can address. The first uses a large number of spectral and morphological characteristics that describe the appearance of pheasant, Phasianus colchicus, eggs to assign them to putative clutches. The second takes a continuous data stream of feeder visits from PIT (passive integrated transponder)-tagged jackdaws, Corvus monedula, and extracts foraging events from it, which permits the construction of social networks. Our final example uses aerial images to train a classifier that detects the presence of wildebeest, Connochaetes taurinus, to count individuals in a population. With the advent of cheaper sensing and tracking technologies an unprecedented amount of data on animal behaviour is becoming available. We believe that ML will play a central role in translating these data into scientific knowledge and become a useful addition to the animal behaviourist's analytical toolkit. © 2017 The Authors. Published by Elsevier Ltd on behalf of The Association for the Study of Animal Behaviour. This is an open access article under the CC BY license (http://creativecommons.org/licenses/ by/4.0/).
A mind-body technique for symptoms related to fibromyalgia and chronic fatigue.

CONTEXT
A novel mind-body approach (amygdala retraining) is hypothesized to improve symptoms related to fibromyalgia and chronic fatigue.


OBJECTIVE
To examine the use of a mind-body approach for improving symptoms related to fibromyalgia and chronic fatigue.


DESIGN
This was a single-blind, randomized controlled trial.


SETTING
The study was conducted in a tertiary-care fibromyalgia and chronic fatigue clinic.


PATIENTS
Patients with fibromyalgia, chronic fatigue, or both were included.


INTERVENTIONS
Patients were randomly assigned to receive amygdala retraining along with standard care or standard care alone. Standard care involved attending a 1.5-day multidisciplinary program. The amygdala retraining group received an additional 2.5-hour training course in which the key tools and techniques adapted from an existing program were taught to the patient. A home-study video course and associated text were provided to supplement the on-site program. Both groups received telephone calls twice a month to answer questions related to technique and to provide support.


MAIN OUTCOME MEASURES
Validated self-report questionnaires related to general health, well-being, and symptoms, including Short Form-36, Measure Yourself Medical Outcome Profile, Multidimensional Fatigue Inventory, Epworth Sleepiness Scale, and Fibromyalgia Impact Questionnaire.


RESULTS
Of the 44 patients randomly assigned who completed baseline assessments, 21 patients completed the study (14 in the standard care group and 7 in the study group). Median age was 48 years (range, 27-56 years), and female subjects comprised 91% of the group. Analyses demonstrated statistically significant improvements in scores for physical health, energy, pain, symptom distress, and fatigue in patients who received the amygdala retraining compared with standard care.
Relationships between the quality of blended learning experience, self-regulated learning, and academic achievement of medical students: a path analysis

PURPOSE
This study examined the relationships between the different aspects of students' course experience, self-regulated learning, and academic achievement of medical students in a blended learning curriculum.


METHODS
Perceptions of medical students (n=171) from the Royal College of Surgeons in Ireland, Medical University of Bahrain (RCSI Bahrain), on the blended learning experience were measured using the Student Course Experience Questionnaire (SCEQ), with an added e-Learning scale. In addition, self-regulated learning was measured using the Motivated Strategies for Learning Questionnaire (MSLQ). Academic achievement was measured by the scores of the students at the end of the course. A path analysis was created to test the relationships between the different study variables.


RESULTS
Path analysis indicated that the perceived quality of the face-to-face component of the blended experience directly affected the motivation of students. The SCEQ scale "quality of teaching" directly affected two aspects of motivation: control of learning and intrinsic goal orientation. Furthermore, appropriate course workload directly affected the self-efficacy of students. Moreover, the e-Learning scale directly affected students' peer learning and critical thinking but indirectly affected metacognitive regulation. The resource management regulation strategies, time and study environment, and effort regulation directly affected students' examination scores (17% of the variance explained). However, there were no significant direct relationships between the SCEQ scales and cognitive learning strategies or examination scores.


CONCLUSION
The results of this study will have important implications for designing blended learning courses in medical schools.
Frequency selective surface absorber for WLAN security

A frequency selective surface (FSS) with absorber characteristics is presented for 5 GHz wireless local area network (WLAN) security. The proposed FSS has great potential to absorb WLAN signals by reducing multipath fading effects while allowing the transmission of other useful RF/microwave signals such as mobile phones, VHF/UHF TV etc. It consists of two layers, one with resistive FSS and other with conducting FSS. It has a stable frequency response for both TE and TM polarizations when the angle of incident wave is varied from 0° to 45°. Preliminary simulation results are presented.
The use of qualitative methods to inform Delphi surveys in core outcome set development

BACKGROUND
Core outcome sets (COS) help to minimise bias in trials and facilitate evidence synthesis. Delphi surveys are increasingly being used as part of a wider process to reach consensus about what outcomes should be included in a COS. Qualitative research can be used to inform the development of Delphi surveys. This is an advance in the field of COS development and one which is potentially valuable; however, little guidance exists for COS developers on how best to use qualitative methods and what the challenges are. This paper aims to provide early guidance on the potential role and contribution of qualitative research in this area. We hope the ideas we present will be challenged, critiqued and built upon by others exploring the role of qualitative research in COS development. This paper draws upon the experiences of using qualitative methods in the pre-Delphi stage of the development of three different COS. Using these studies as examples, we identify some of the ways that qualitative research might contribute to COS development, the challenges in using such methods and areas where future research is required.


RESULTS
Qualitative research can help to identify what outcomes are important to stakeholders; facilitate understanding of why some outcomes may be more important than others, determine the scope of outcomes; identify appropriate language for use in the Delphi survey and inform comparisons between stakeholder data and other sources, such as systematic reviews. Developers need to consider a number of methodological points when using qualitative research: specifically, which stakeholders to involve, how to sample participants, which data collection methods are most appropriate, how to consider outcomes with stakeholders and how to analyse these data. A number of areas for future research are identified.


CONCLUSIONS
Qualitative research has the potential to increase the research community's confidence in COS, although this will be dependent upon using rigorous and appropriate methodology. We have begun to identify some issues for COS developers to consider in using qualitative methods to inform the development of Delphi surveys in this article.
User perception of adapting video quality

In general, video quality adaptation and video quality evaluation are distinct activities. Most adaptive delivery mechanisms for streaming multimedia content do not explicitly consider user-perceived quality when making adaptation decisions. Equally, video quality evaluation techniques are not designed to evaluate instantaneous quality where the quality is changing over time. We propose that an Optimal Adaptation Trajectory (OAT) through the set of possible encoding exists, and that it indicates how to adapt encoding quality in response to changes in network conditions in order to maximize user-perceived quality. The subjective and objective tests carried out to find such trajectories for a number of different MPEG-4 video clips are described. Experimental subjective testing results are presented that demonstrate the dynamic nature of user perception with adapting multimedia. The results demonstrate that adaptation using the OAT out-performs conventional adaptation strategies in which only a single aspect of the video quality is adapted. In contrast, the OAT provides a mechanism to adapt multiple aspects of the video quality thereby giving better user-perceived quality in both the short and long term. r 2006 Elsevier Ltd. All rights reserved.
Resource Intensity , Institutions , and Development

— We examine the relationship between resource abundance and several indicators of human welfare. Consistent with the existing literature on the relationship between resource abundance and economic growth we find that, given an initial income level, resource-intensive countries tend to suffer lower levels of human development. While we find only weak support for a direct link between resources and welfare, there is an indirect link that operates through institutional quality. There are also significant differences in the effects that resources have on different measures of institutional quality. These results imply that the ‘‘resource curse’’ is a more encompassing phenomenon than previously considered, and that key differences exist between the effects of different resource types on various aspects of governance and human welfare. 2005 Elsevier Ltd. All rights reserved.
Constructing Risk Measures from Uncertainty Sets

We illustrate the correspondence between uncertainty sets in robust optimization and some popular risk measures in finance, and show how robust optimization can be used to generalize the concepts of these risk measures. We also show that by using properly defined uncertainty sets in robust optimization models, one can construct coherent risk measures. Our results have implications for efficient portfolio optimization under different measures of risk. Department of Mathematics, National University of Singapore, Singapore 117543. Email: matkbn@nus.edu.sg. The research of the author was partially supported by Singapore-MIT Alliance, NUS Risk Management Institute and NUS startup grants R-146-050-070-133 & R146-050-070-101. Division of Mathematics and Sciences, Babson College, Babson Park, MA 02457, USA. E-mail: dpachamanova@babson.edu. Research supported by the Gill grant from the Babson College Board of Research. NUS Business School, National University of Singapore. Email: dscsimm@nus.edu.sg. The research of the author was partially supported by Singapore-MIT Alliance, NUS Risk Management Institute and NUS academic research grant R-314-000-066-122 and R-314-000-068-122.
An empirical investigation of online consumer purchasing behavior

This article is focused on examining the factors and relationships that influence the browsing and buying behavior of individuals when they shop online. Specifically, we are interested in individual buyers using business-to-consumer sites. We are also interested in examining shopping preferences based on various demographic categories that might exhibit distinct purchasing attitudes and behaviors for certain categories of products and services. We examine these behaviors in the context of both products and services. After a period of decline in recent months, online shopping is on the rise again. By some estimates, total U.S. spending on online sales increased to $5.7 billion in December 2001 from $3.2 billion in June of 2001 [3, 5]. By these same estimates, the number of households shopping online increased to 18.7 million in December 2001 from 13.1 million in June 2001. Consumers spent an average of $304 per person in December 2001, compared with $247 in June 2001. According to an analyst at Forrester: “The fact that online retail remained stable during ... such social and economic instability speaks volumes about how well eCommerce is positioned to stand up to a poor economy” [4]. What do consumers utilize the Internet for? Nie and Erbring suggest that 52% of the consumers use the Internet for product information, 42% for travel information, and 24% for buying [9]. Recent online consumer behavior-related research refers to any Internet-related activity associated with the consumption of goods, services, and information [6]. In the definition of Internet consumption, Goldsmith and Bridges include “gathering information passively via exposure to advertising; shopping, which includes both browsing and deliberate information search, and the selection and buying of specific goods, services, and information” [7]. For the purposes of this study, we focus on all aspects of this consumption. We include all of them because information gathering aspects of e-commerce serve to educate the consumer, which is ulti-
Generating Sentences from Semantic Vector Space Representations

The first work of this kind in a monolingual setting successfully generates two and threeword phrases with predetermined syntactic structures by decoupling the task into three phases: synthesis, decomposition, and search [4]. During the synthesis phase, a vector is constructed from some input text. This vector is decomposed into multiple output vectors that are then matched to words in the vocabulary using a nearest-neighbor search.
A Comparison of Student Teachers' Perceptions of Important Elements of the Student Teaching Experience before and after an 11-Week Field Experience.

Manuscript Issue Page Advancing Agricultural Education Within The Context Of An Increasingly Diverse Society--Blannie E. Bowen 1 1 A Comparison Of Student Teachers’ Perceptions Of Important Elements Of The Student Teaching Experience Before And After An 11-Week Field Experience --Julie F. Harlin, M. Craig Edwards, & Gary E. Briers 3 72 A Comparison Of The Inservice Education Needs Of Two Cohorts Of Beginning Minnesota Agricultural Education Teachers--Richard M. Joerger 3 11 A Comparison Of Traditional And World Wide Web Methodologies, Computer Anxiety And Higher Order Thinking Skills In The In-Service Training Of Mississippi 4-H Extension Agents--Julie S. Sexton, Matt R. Raven, & Michael E. Newman 3 25 A Follow-Up Study Of Agricultural Education Program Graduates On Teaching Competencies--Thomas J. Dormody & Robert M. Torres 4 33 A Qualitative Study Of Prospective Elementary Teachers’ Grasp Of Agricultural And Science Educational Benchmarks For Agricultural Technology--Cary J. Trexler & Deanna Meischen 2 68 A Recruiting Challenge For Extension Education: A Comparison Of Nonparticipants And Participants In Homeowner Landscaping Programs --Glenn D. Israel & Glenn W. Hague 4 76 Active Learning: The Impact On Students Participating In An Extended Field Trip To Puerto Rico--Thomas H. Bruening, Josue Lopez, David F. McCormick, & David R. Dominguez 4 67 Adult Education Philosophies Practiced By Agricultural Education Teachers In Pennsylvania, Virginia, And West Virginia--Harry N. Boone, Stacy A. Gartin, Crystal B. Wright, Layle D. Lawrence, & Kerry S. Odell 3 37 Agricultural Education At A Distance: Let’s Hear From The Students—Kathleen D. Kelsey, James R. Lindner, & Kim E. Dooley 4 24 Agricultural Education Competencies And Progress Toward A Doctoral Degree --James R. Lindner & Kim E. Dooley 1 57 An Analysis Of The Perceived Benefits And Affordances Of Course Websites By On-Campus Agricultural Students And Faculty Members--Tim H. Murphy 2 44 An Interactive Communication Network’s Potential As A Communication And Student Teacher Supervision Tool In Agricultural Education--Greg Miller, Wade Miller, & John Kessell 2 11 Aspirations Of Rural Youth--Duane H. Bajema, W. Wade Miller, & David L.Williams 3 61 Can Selected Learning Strategies Influence The Success Of Adult Distance Learners In Agriculture?--Greg Miller & Carol L. Pilcher 2 34 Competency-Based Behavioral Anchors As Authentication Tools To Document Distance Education Competencies--Kim E. Dooley & James R. Lindner 1 24 Evaluation Of A Computer-Based, Asynchronous Activity On Student Learning Of Leadership Concepts--Barry L. Boyd & Theresa P. Murphrey 1 36
Status of the pelvic floor in young primiparous women.

OBJECTIVES
To investigate the postnatal prevalence of sonographically diagnosed pelvic floor trauma, and the correlations with various antenatal/intrapartum predictors in primiparous women.


METHODS
This was a prospective cohort study performed in a tertiary hospital with 9000 deliveries per annum. Of those invited, 202 (23.2%) primiparous participants were assessed clinically at least 1 year after delivery by Pelvic Organ Prolapse Quantification (POP-Q), two/three-dimensional transperineal sonography and quantification of serum collagen type III levels.


RESULTS
There was a high prevalence of clinically significant pelvic organ prolapse (POP) on POP-Q staging: uterine prolapse, 63%; cystocele, 42%; and rectocele, 23%. Ballooning of the levator ani muscle (LAM) hiatus was detected in 33% and LAM avulsion in 29% of participants, with partial LAM avulsion occurring in 15% and complete avulsion in 14%. Postnatal POP symptoms (odds ratios (ORs) given here for presence of multiple prolapse symptoms) were positively associated with similar prepregnancy symptoms (OR, 7.2 (95% CI, 1.19-44.33)), LAM avulsion (OR, 4.8 (95% CI, 1.99-11.34)) and forceps delivery (borderline significance; OR, 1.8 (95% CI, 0.96-3.25)) and negatively associated with elective (OR, 0.2 (95% CI, 0.09-0.63)) and emergency (OR, 0.3 (95% CI, 0.12-0.83)) Cesarean section. LAM abnormality was associated with forceps delivery (OR, 4.9 (95% CI, 1.44-16.97)) and prolapse (OR, 6.8-11.7 (95% CI, 2.34-78.51)), whereas collagen levels did not play a role (OR, 1.001 (95% CI, 0.99-1.02)).


CONCLUSIONS
Clinically significant POP was common in relatively young premenopausal primiparous women. Partial or full levator avulsion was seen in 29% of participants and was associated with POP and related symptoms. Congenital factors seem to play little role in the etiology of LAM trauma, and the main risk factor seems to be forceps delivery. Avoidance of difficult vaginal deliveries may prevent severe pelvic floor trauma.
Putting the pieces together: multimodal analysis of social attention in meetings

This paper presents a multimodal framework employing eye-gaze, head-pose and speech cues to explain observed social attention patterns in meeting scenes. We first investigate a few hypotheses concerning social attention and characterize meetings and individuals based on ground-truth data. This is followed by replication of ground-truth results through automated estimation of eye-gaze, head-pose and speech activity for each participant. Experimental results show that combining eye-gaze and head-pose estimates decreases error in social attention estimation by over 26%.