bluuebunny/crossref_metadata_2025 huggingface dataset:
Evaluating associations of joint swelling, joint stiffness and joint pain with physical activity in first-degree relatives of patients with rheumatoid arthritis: Studies of the Aetiology of Rheumatoid Arthritis (SERA), a prospective cohort study
Authors: Hughes-Austin Jan M , Ix Joachim H , Ward Samuel R , Weisman Michael H , ODell James R , Mikuls Ted R , Buckner Jane H , Gregersen Peter K , Keating Richard M , Demoruelle M Kristen , Deane Kevin D , Holers V Michael , Norris Jill M
Published: September 2021

Objective

Physical activity (PA) in preclinical rheumatoid arthritis (RA) is associated with lower RA risk and disease severity. As joint signs and symptoms of inflammatory arthritis serve as a barrier to PA in RA, it is important to consider whether they affect PA in the time prior to RA. Therefore, we investigated whether joint swelling, stiffness or pain were associated with PA in first-degree relatives (FDRs) of patients with RA, a population at higher risk for future RA.

Design

Prospective study design.

Setting

We recruited FDRs of patients with RA from academic centres, Veterans’ hospitals and rheumatology clinics or through responses to advertising from six sites across the USA.

Participants

We evaluated associations of joint stiffness, joint swelling and joint pain with PA time in 268 FDRs with ≥2 visits over an average 1.2 years. Clinicians confirmed joint swelling. Participants self-reported joint stiffness and/or pain.

Primary outcome measures

PA during a typical 24-hour day was quantified via questionnaire, weighted to reflect metabolic expenditure, where 24 hours was the minimum PA time. Linear mixed models evaluated associations between symptoms and change in PA over time, adjusting for age, sex, race, body mass index, smoking and RA-related autoantibodies.

Results

Average weighted PA time was 37±7 hours. In the cross-sectional analysis, PA time was 1.3±0.9 hours higher in FDRs reporting joint pain (p=0.15); and 0.8±1.6 and 0.4±1 hours lower in FDRs with joint swelling (p=0.60) and stiffness (p=0.69), respectively. Longitudinally, adjusting for baseline PA time, baseline symptoms were not significantly associated with changes in PA time. However, on average over time, joint stiffness and pain were associated with lower PA time (pinteraction=0.0002, pinteraction=0.002), and joint swelling was associated with higher PA time (pinteraction<0.0001).

Conclusion

Baseline symptoms did not predict future PA time, but on average over time, joint symptoms influenced PA time.
Development of a culturally and linguistically sensitive virtual reality educational platform to improve vaccine acceptance within a refugee population: the SHIFA community engagement-public health innovation programme
Authors: Streuli Samantha , Ibrahim Najla , Mohamed Alia , Sharma Manupriya , Esmailian Markie , Sezan Ibrahim , Farrell Carrie , Sawyer Mark , Meyer Dan , El-Maleh Khaled , Thamman Ritu , Marchetti Alex , Lincoln Alan , Courchesne Eric , Sahid Ahmed , Bhavnani Sanjeev P
Published: September 2021

Objectives

To combat misinformation, engender trust and increase health literacy, we developed a culturally and linguistically appropriate virtual reality (VR) vaccination education platform using community-engaged approaches within a Somali refugee community.

Design

Community-based participatory research (CBPR) methods including focus group discussions, interviews, and surveys were conducted with Somali community members and expert advisors to design the educational content. Co-design approaches with community input were employed in a phased approach to develop the VR storyline.

Participants

60 adult Somali refugees and seven expert advisors who specialise in healthcare, autism research, technology development and community engagement.

Setting

Somali refugees participated at the offices of a community-based organisation, Somali Family Service, in San Diego, California and online. Expert advisors responded to surveys virtually.

Results

We find that a CBPR approach can be effectively used for the co-design of a VR educational programme. Additionally, cultural and linguistic sensitivities can be incorporated within a VR educational programme and are essential factors for effective community engagement. Finally, effective VR utilisation requires flexibility so that it can be used among community members with varying levels of health and technology literacy.

Conclusion

We describe using community co-design to create a culturally and linguistically sensitive VR experience promoting vaccination within a refugee community. Our approach to VR development incorporated community members at each step of the process. Our methodology is potentially applicable to other populations where cultural sensitivities and language are common health education barriers.
Attitudes of Chinese immigrants in Canada towards the use of Traditional Chinese Medicine for prevention and management of COVID-19: a cross-sectional survey during the early stages of the pandemic
Authors: Kong Yujia , Shaver Lance Garrett , Shi Fuyan , Yang Lixia , Zhang Weiguo , Wei Xiaolin , Zhu Yun , Wang Yiran , Wang Peizhong Peter
Published: September 2021

Objection

The objective of this study was to assess attitudes towards the use of Traditional Chinese Medicine (TCM) for COVID-19 among Chinese immigrants in Canada during the early stage of the COVID-19 pandemic.

Methods

A cross-sectional study was conducted in April 2020 in Canada. Individuals aged 16 or older who were of Chinese origin and living in Canada at the time of the survey were invited to participate in an online survey. Descriptive and univariate statistics were performed to describe participant attitudes towards various preventive and treatment measures for COVID-19. Multiple logistic regression was used to identify independent associations with sociodemographic factors and attitudes.

Results

A total of 754 eligible respondents were included in the analysis. 65.8% of the participants were female, 77.2% had a university degree or higher and 28.6% were 55 years of age or older. Overall, 48.8% of the study participants believed that TCM was effective in preventing COVID-19% and 46.2% would use TCM if they had COVID-19-related symptoms. However, the corresponding numbers for western medicine were 20.8% and 39.9%, which were statistically lower (p<0.01). Older participants (55+vs <35, OR=3.55 (95% CI 2.05 to 6.14); 35–54 vs <35, OR=1.98 (95% CI 1.27 to 3.08)) and those who were dissatisfied with their income (OR=2.47(95% CI 1.56 to 3.92)) were more likely to believe TCM was effective against COVID-19. Similarly, older participants (55+vs <35, OR=3.13 (95% CI 1.79 to 5.46); 35–54 vs <35, OR=2.25 (95% CI 1.35 to 3.74)), females (OR=1.60 (95% CI 1.15 to 2.23)), and those born in mainland China (OR=10.49 (95% CI 2.32 to 47.39)) were more likely to use TCM if they had symptoms of COVID-19.

Conclusion

Despite the lack of scientific evidence to support its use, TCM was widely believed by Chinese immigrants in Canada to be an effective means of preventing COVID-19 and many also stated they would use it if they were experiencing symptoms of COVID-19.
Risk of out-of-hospital cardiac arrest among sepsis survivors in Taiwan: analysis of a nationwide population-based cohort
Authors: Hsu Wan-Ting , Sherrod Charles Fox , Tehrani Babak , Papaila Alexa , Porta Lorenzo , Hsu Tzu-Chun , Sheng Wang-Huei , Lee Chien-Chang
Published: September 2021

Objectives

There is minimal literature examining the association of sepsis with out-of-hospital cardiac arrest (OHCA). Using a large national database, we aimed to quantify the risk of OHCA among sepsis patients after hospital discharge.

Design

Population-based cohort study.

Setting

Nationwide sepsis cohort retrieved from the National Health Insurance Research Database of Taiwan between 2000 and 2013.

Participants

We included 17 304 patients with sepsis. After hospital discharge, 144 patients developed OHCA within 30 days and 640 between days 31 and 365.

Primary and secondary outcome measures

The main outcomes were OHCA events following hospital discharge for sepsis. To evaluate the independent association between sepsis and OHCA after a sepsis hospitalisation, we constructed two non-sepsis comparison cohorts using risk set sampling and propensity score matching techniques (non-infection cohort, non-sepsis infection cohort). We plotted the daily number and daily risk of OHCA within 1 year of hospital discharge between sepsis and matched non-sepsis cohorts. We used Cox regression to evaluate the risk of early and late OHCA, comparing sepsis to non-sepsis patients.

Results

Compared with non-infected patients, sepsis patients had a higher rate of early (HR 1.66, 95% CI: 1.27 to 2.16) and late (HR 1.19, 95% CI: 1.06 to 1.33) OHCA events. This association was independent of age, sex or cardiovascular history. Compared with non-sepsis patients with infections, sepsis patients had a higher rate of both early (HR 1.28, 95% CI: 1.00 to 1.63) and late (HR 1.13, 95% CI: 1.01 to 1.27) OHCA events, especially among patients with cardiovascular disease (OR 1.35, 95% CI: 1.01 to 1.81).

Conclusions

Sepsis patients had increased risk of OHCA compared with matched non-sepsis controls, which lasted up to 1 year after hospital discharge.
European knowledge alliance for innovative measures in prevention of work-related musculoskeletal pain disorders (Prevent4Work Project): protocol for an international mixed-methods longitudinal study
Authors: Bellosta-López Pablo , Domenech-Garcia Victor , Palsson Thorvaldur Skuli , Christensen Steffan Wittrup , Silva Priscila de Brito , Langella Francesco , Berjano Pedro , Jensen Palle Schlott , Riis Allan , Baroncini Alice , Blasco-Abadía Julia , Jiménez-Sánchez Carolina , Calvo Sandra , Jaén-Carrillo Diego , Herrero Pablo , Hoegh Morten
Published: September 2021

Introduction

Work-related musculoskeletal (MSK) pain is a highly prevalent condition and one of the main contributors to disability and loss of work capacity. Current approaches to the management and prevention of work-related MSK pain do not consistently integrate current evidence-based knowledge and seem to be outdated. The Prevent4Work (P4W) Project aims to collect and spread evidence-based information to improve the management and prevention of work-related MSK pain. P4W will longitudinally investigate (1) risk factors associated with the prevalence of work-related MSK pain, (2) predictive factors for new events of work-related MSK pain in the short term and (3) the modification of pain beliefs after participating in evidence-based e-learning courses.

Methods and analysis

This project employs a mixed-methods design with international cohorts of workers from Spain, Italy and Denmark. All participants will be assessed using self-reported variables at baseline (ie, cross-sectional design) with follow-up after 3 and 6 months (ie, prospective–predictive design). Throughout the first phase (0–3 months), all participants will be offered to self-enrol in e-learning courses on work-related MSK pain. Changes in pain beliefs (if any) will be assessed. The dataset will include sociodemographic characteristics, physical and psychological job demands, lifestyle-related factors, MSK pain history and pain beliefs. At baseline, all participants will additionally complete the P4W questionnaire developed to detect populations at high risk of suffering work-related MSK pain.

Descriptive statistics, binary logistic regression, and analysis of variance will be used to identify the significant factors that influence the history of work-related MSK pain, evaluate the short-term prediction capacity of the P4W questionnaire, and investigate whether workers’ participation in e-learning courses will modify their pain beliefs.

Ethics and dissemination

The study received ethical approval from the Ethical Committee of San Jorge University (USJ011-19/20). The results will be made available via peer-reviewed publications, international conferences and P4W official channels.
Using social networks to scale up and sustain community-based programmes to improve physical activity and diet in low-income and middle-income countries: a scoping review protocol
Authors: Abrahams Nina , Lambert Estelle V , Marais Frederick , Toumpakari Zoi , Foster Charlie
Published: September 2021

Introduction

The World Health Organisation endorses community-based programmes as a cost-effective, feasible and a ‘best buy’ in the prevention and management of non-communicable diseases (NCDs). These programmes are particularly successful when the community actively participates in its design, implementation and evaluation. However, they may be only useful insofar as they can be scaled up and sustained in some meaningful way. Social network research may serve as an important tool for determining the underlying mechanisms that contribute to this process. The aim of this planned scoping review is to map and collate literature on the role of social networks in scaling-up and sustaining community-based physical activity and diet programmes in low-income and middle-income countries.

Methods and analysis

This scoping review protocol has been planned around the Arksey and O"Malley framework and its enhancement. Inclusion criteria are peer-reviewed articles and grey literature exploring the role of social networks in the scale-up and/or sustainability of NCD prevention community-based programmes in adult populations. Studies must have been published since 2000, in English, and be based in a low-income or middle-income country. The following databases will be used for this review: PubMed, Cochrane, Scopus, Web of Science, CINAHL, SocIndex, the International Bibliography of the Social Sciences, Google and Google Scholar. Books, conference abstracts and research focused only on children will be excluded. Two reviewers will independently select and extract eligible studies. Included publications will be thematically analysed using the Framework Approach.

Ethics and dissemination

Ethical approval will not be sought for this review as no individual-level data or human participants will be involved. This protocol is registered on the Open Science Framework (https://doi.org/10.17605/OSF.IO/KG7TX). The findings from the review will be published in an accredited journal. The Preferred Reporting Items for Systematic Reviews and Meta-analyses extension for Scoping Reviews checklist will be used to support transparency and guide translation of the review.
Cardiac arrest in the paediatric intensive care unit: defining the problem and developing solutions
Authors: Ray Candice M , Pizzuto Matthew , Reyes-Alvarado Edith , Jackson Kimberly , Turner David A , Kamath Sameer
Published: September 2021

Thousands of children experience a cardiac arrest event in the hospital each year, with more than half of these patients not surviving to hospital discharge. Cardiopulmonary resuscitation (CPR) depth, rate, velocity and percentage of high-quality chest compressions are modifiable factors associated with improved survival. Therefore, we created a novel and standardised process to track and analyse cardiac arrests in the Duke paediatric intensive care unit (PICU). Our aim was to identify areas for improved American Heart Association (AHA) compliance and implement education and communication-based initiatives to enhance early recognition of at-risk patients leading to improved outcomes. From January 2017 to December 2018, all cardiac arrests in our PICU were tracked, reviewed and presented at monthly morbidity and mortality conference. We used the data to track compliance with AHA guidelines and identify opportunities for improvement. Through these efforts, we established a multidisciplinary cardiac arrest education and review programme. Over the 2-year period, we tracked 45 cardiac arrests, which comprised 2% of all PICU admissions. In 2017, during the first year of development, 16 of 22 arrests (73%) were not reported to code committee members in time for complete review. Of the six cardiac arrests with complete reviews, only 17% followed AHA guidelines. In 2018, all 23 arrest events were communicated and 76% of resuscitations were found to be compliant with AHA guidelines. Survival of patients to discharge was 47% in 2017 and increased to 63% in 2018 with similar percentage of PICU admissions having a cardiac arrest between the 2 years. The primary aim of this project was to establish a multidisciplinary comprehensive cardiac arrest review process. This programme allowed for comprehensive analysis of individual events, promoted quality improvement initiatives and improved consistent delivery of high-quality CPR.
Opioid and healthcare service use in medical cannabis patients with chronic pain: a prospective study
Authors: Sznitman Sharon , Mabouk Carolyn , Said Zahi , Vulfsons Simon
Published: September 2021

Background

Various jurisdictions have legalised medical cannabis (MC) for use in chronic pain treatment. The objective of this study was to determine if the use of MC is related to a reduction in the use of prescription opioids and other prescription medications and healthcare services.

Methods

A retrospective cohort study was conducted using the medical files of 68 Israeli patients with chronic pain using MC. Number of prescription medications filled and healthcare services used were recorded separately for the baseline period (6 months prior to the start of MC treatment) and 6 months’ follow-up. Paired t-tests were used to compare each individual to himself/herself from baseline to follow-up.

Results

Patients filled less opioid prescription medication at follow-up compared with baseline, and the reduction was of small effect size. There were no significant changes in the use of other medications or use of healthcare services from pre-MC treatment to follow-up.

Conclusions

MC may be related to a significant yet small reduction in opioid prescription medication. Further prospective studies with representative samples are warranted to confirm the potential small opioid-sparing effects of MC treatment, its clinical importance, if any, and potential lack of association with other healthcare-related services and medication use. Due to methodological limitations of the data used in this study, results may be regarded as preliminary and causal inferences cannot be made.
Using genetics to detangle the relationships between red cell distribution width and cardiovascular diseases: a unique role for body mass index
Authors: Thayer Timothy E , Huang Shi , Farber-Eger Eric , Beckman Joshua A , Brittain Evan L , Mosley Jonathan D , Wells Quinn S
Published: September 2021

Objective

Red cell distribution width (RDW) is an enigmatic biomarker associated with the presence and severity of multiple cardiovascular diseases (CVDs). It is unclear whether elevated RDW contributes to, results from, or is pleiotropically related to CVDs. We used contemporary genetic techniques to probe for evidence of aetiological associations between RDW, CVDs, and CVD risk factors.

Methods

Using an electronic health record (EHR)-based cohort, we built and deployed a genetic risk score (GRS) for RDW to test for shared genetic architecture between RDW and the cardiovascular phenome. We also created GRSs for common CVDs (coronary artery disease, heart failure, atrial fibrillation, peripheral arterial disease, venous thromboembolism) and CVD risk factors (body mass index (BMI), low-density lipoprotein, high-density lipoprotein, systolic blood pressure, diastolic blood pressure, serum triglycerides, estimated glomerular filtration rate, diabetes mellitus) to test each for association with RDW. Significant GRS associations were further interrogated by two-sample Mendelian randomisation (MR). In a separate EHR-based cohort, RDW values from 1-year pre-gastric bypass surgery and 1–2 years post-gastric bypass surgery were compared.

Results

In a cohort of 17 937 subjects, there were no significant associations between the RDW GRS and CVDs. Of the CVDs and CVD risk factors, only genetically predicted BMI was associated with RDW. In subsequent analyses, BMI was associated with RDW by multiple MR methods. In subjects undergoing bariatric surgery, RDW decreased postsurgery and followed a linear relationship with BMI change.

Conclusions

RDW is unlikely to be aetiologically upstream or downstream of CVDs or CVD risk factors except for BMI. Genetic and clinical association analyses support an aetiological relationship between BMI and RDW.
Long-term survival in patients with isolated pulmonary valve stenosis: a not so benign disease?
Authors: Skoglund Kristofer , Rosengren Annika , Lappas Georgios , Fedchenko Maria , Mandalenakis Zacharias
Published: September 2021

Background and objectives

During the last decades, the survival rates in patients with congenital heart disease have increased dramatically, particularly in patients with complex heart malformations. However, the survival in patients with simple defects is still unknown. We aimed to determine the characteristics and the risk of mortality in patients with isolated pulmonary valve stenosis (PS).

Methods

Swedish inpatient, outpatient and cause of death registries were used to identify patients born between 1970 and 2017 with a diagnosis of PS, without any other concomitant congenital heart lesion. For each patient with PS, 10 control individuals without congenital heart disease were matched by birth year and sex from the total population registry. We used median-unbiased method and Kaplan-Meier survival analysis to examine the risk of mortality.

Results

We included 3910 patients with PS and 38 770 matched controls. The median age of diagnosis of PS was 0.7 years (IQR 0.3–7.0). During a median follow-up of 13.5 years (IQR 6.5–23.5), 88 patients with PS and 192 controls died; 500 patients with PS (12%) underwent at least one transcatheter or surgical valve intervention. The overall mortality rate was significantly higher in patients with PS compared with matched controls (HR 4.67, 95% CI 3.61 to 5.99, p=0.001). Patients with an early diagnosis of PS (0–1 year) had the highest risk of mortality (HR 10.99, 95% CI 7.84 to 15.45).

Conclusions

In this nationwide, register-based cohort study, we found that the risk of mortality in patients with PS is almost five times higher compared with matched controls. Patients with an early diagnosis of PS appears to be the most vulnerable group and the regular follow-up in tertiary congenital heart units may be the key to prevention.
$$X_1(2900)$$ as a $$\bar{D}_1 K$$ molecule
Authors: Chen Hao , Qi Hong-Rong , Zheng Han-Qing
Published: September 2021

The analyses of the LHCb data on X(2900) in the $$D^- K^+$$

D
-

K
+

spectrum are performed. Both dynamically generated and explicitly introduced $$X_1(2900)$$

X
1

(
2900
)

are considered. The results show that both these two approaches support the interpretation of $$X_1(2900)$$

X
1

(
2900
)

as a $$\bar{D}_1 K$$

D

¯

1

K

molecular state, with $$J^{P}=1^-$$

J
P

=

1
-

and an iso-singlet interpretation is much more favorable. The effect of triangle singularity on the production of $$X_1(2900)$$

X
1

(
2900
)

is also discussed, and it is found that it cannot be interpreted as a pure triangle cusp.
A Comparative Analysis of Hysteresis Current Control SVM and 3D-SVM for 3-Level NPC Inverter
Authors: Palanisamy R. , Shanmugasundaram V. , Vidyasagar S. , Vijayakumar K.
Published: September 2021

This paper elucidates a comparative analysis of hysteresis current control space vector modulation (HCC-SVM) and 3-dimensional space vector modulation (3D-SVM) for control of 3-level neutral point clamped (NPC) inverter. The NPC inverter topology is much suitable for single input applications and medium and high power applications. The detailed comparative analysis of total harmonic distortion (THD) for both modulation control strategies is analyzed. Among various modulation strategies, these two control strategies increased more attention due to the improved output compared to the other conventional methods. The simulation and hardware results are evident that 3D-SVM is the most efficient controller for capacitor balancing, common mode voltage minimization, THD minimization and attain low voltage stress across switch, but in terms of system design and complexity in switching time calculation is simple in the HCC-SVM method. The simulation and hardware results are verified using simulink and FPGA processor, respectively.
Real-Time System Design for Sensing, Recording and Analyzing Elephant Seismic Waves Through Ground Vibration Algorithm
Authors: Ramkumar R , Deb Sanjoy
Published: September 2021

In this paper, a real-time low-cost geophone-based Elephant Footstep Vibration Detection and Identification (EFVDI) system is proposed. The system design started with a real-time low-cost generalized Footstep Vibration Recording and Analyzing (FVRA) system. A series of field experiments to record elephant footstep vibration (target) signals and other possible interfering ground vibration (noise) sources are conducted using the FVRA system. System’s actual field performance was evaluated in terms of maximum detection range, signal amplitude, detection ratio, signal frequency, signal time span, etc. Variations of system’s performance with several input parameters are also investigated. The recorded signals from target as well as noise sources are analyzed to extract different Signal Parameters (SPs). All SPs are saved in a Ground Vibration Signal Pattern Library (GVSPL) which is then used to frame accurate indigenous Elephant Identification Algorithm (EIA). The EIA is embedded in FVRA system to reshape it as specific Elephant Footstep Vibration Detection and Identification (EFVDI) system. The EFVDI system has successfully segregated elephant footsteps from other noise vibrations with high accuracy under simulated field experiment. The results from the proposed system will provide important data to the ongoing research of developing the much needed highly accurate Elephant Early Warning System (EEWS) in future.
External field effect in gravity
Authors: Mannheim Philip D. , Moffat John W.
Published: September 2021

In both Newtonian gravity and Einstein gravity there is no force on a test particle located inside a spherical cavity cut out of a static, spherically symmetric mass distribution. Inside the cavity exterior matter is decoupled and there is no external field effect that could act on the test particle. However, for potentials other than the Newtonian potential or for geometries other than Ricci flat ones this is no longer the case, and there then is an external field effect. We explore this possibility in various alternate gravity scenarios, and suggest that such (Machian) external field effects can serve as a diagnostic for gravitational theory.
Towards Compact Broad Learning System by Combined Sparse Regularization
Authors: Miao Jianyu , Yang Tiejun , Jin Jun-Wei , Sun Lijun , Niu Lingfeng , Shi Yong
Published: September 2021

Broad Learning System (BLS) has been proven to be one of the most important techniques for classification and regression in machine learning and data mining. BLS directly collects all the features from feature and enhancement nodes as input of the output layer, which neglects vast amounts of redundant information. It usually leads to be inefficient and overfitting. To resolve this issue, we propose sparse regularization-based compact broad learning system (CBLS) framework, which can simultaneously remove redundant nodes and weights. To be more specific, we use group sparse regularization based on [Formula: see text] norm to promote the competition between different nodes and then remove redundant nodes, and a class of nonconvex sparsity regularization to promote the competition between different weights and then remove redundant weights. To optimize the resulting problem of the proposed CBLS, we exploit an efficient alternative optimization algorithm based on proximal gradient method together with computational complexity. Finally, extensive experiments on the classification task are conducted on public benchmark datasets to verify the effectiveness and superiority of the proposed CBLS.
DOES CULTURAL DIVERSITY MATTER FOR TEAM PERFORMANCE IN MULTINATIONAL COMPANIES? AN ANALYSIS OF CONFLICT, COMMUNICATION, SOCIAL INTEGRATION, CREATIVITY AND SATISFACTION
Authors: OBSUWAN SORNSAWAN , CHANDRASHEKAR DEEPAK , KRAUS SASCHA , BREM ALEXANDER , BOUNCKEN RICARDA
Published: September 2021

Team performance is key in each organisation. Hence, cultural effects in teams are a relevant matter of subject clarifying the ambiguous findings from previous research. With this background, we investigate how the macro-constructs of conflict, communication effectiveness, social integration, creativity and satisfaction interact with cultural diversity on team performance in an environment characterised by a largely homogeneous and ethnic workforce. We test our hypotheses on a sample of firms in Thailand. Our results indicate that creativity and satisfaction have a significant positive impact on team performance whereas cultural diversity has a significant positive impact on influencing conflict in a team-based environment. However, cultural diversity has no significant impact on communication effectiveness and social integration, and it has no significant impact on team performance.

The key theoretical contributions from our study are that cultural diversity can contribute to conflict even in a team composition that is seemingly cohesive and homogeneous in nature. Further, our study establishes that creativity and satisfaction have a positive effect on team performance even in the context of a homogeneous and ethnically majority-based team. For the practitioners, the results of the study indicate that initial actions need to be taken by the leaders of multicultural teams as they create teams to avoid the initial pitfalls due to conflict.
Geochemistry and environmental effects of rare-earth elements in laterites from Yunnan province, SW China
Authors: Liang Bin , Han Guilin , Zeng Jie , Qu Rui , Liu Man , Liu Jinke
Published: September 2021

Rare-earth elements (REEs) in soils are influenced by pedogenic processes and anthropogenic activities. To interpret the fractionation and migration of REEs during weathering in (sub-)tropical regions, the distribution, fractionation patterns and environmental effects of REEs in laterites were investigated in this study. Soil samples from two laterite profiles (labelled S1 and S2) were collected and the concentrations of REEs were measured with an inductively coupled plasma mass spectrometer. The results suggest that the

Σ

REEs of S2 (119 ± 10 mg kg
–1
to 209 ± 10  mg kg
–1
) have a higher concentration and a wider variation than those of S1 (114 ± 5  mg kg
–1
to 154 ± 8  mg kg
–1
). The REEs in both laterite profiles are enriched in the order HREEs > LREEs > MREEs. The distribution patterns of laterite profiles show evidence of inheritance from parent granites. The laterites preferentially incorporated HREEs, and secondary Fe
2
O
3
and clay minerals were likely to affect the fractionation of REEs in laterites. The enrichment factor of REEs varied from 11.1 to 18.9 for S1 and 10.0 to 27.6 for S1, indicating potential pollution by REEs. The accumulation of REEs in laterites by mining activity should be a concern of government environmental agencies.

Supplementary material:
Table S1, Reference values of REEs and Fe
2
O
3
in standard materials (GSS-18 and GSS-20); Table S2, Measurement parameters of ICP-MS; Table S3, Concentrations of REEs and Fe
2
O
3
in laterite profiles from Yunnan province, SW China; Table S4, The enrichment factor for the laterite profiles from Yunnan province, SW China are available at
https://doi.org/10.6084/m9.figshare.c.5609234
QoS–aware Mesh-based Multicast Routing Protocols in Edge Ad Hoc Networks: Concepts and Challenges
Authors: Singal Gaurav , Laxmi Vijay , Gaur Manoj Singh , Rao D. Vijay , Kushwaha Riti , Garg Deepak , Kumar Neeraj
Published: September 2021

Multicast communication plays a pivotal role in Edge based Mobile Ad hoc Networks (MANETs). MANETs can provide low-cost self-configuring devices for multimedia data communication that can be used in military battlefield, disaster management, connected living, and public safety networks. A Multicast communication should increase the network performance by decreasing the bandwidth consumption, battery power, and routing overhead. In recent years, a number of multicast routing protocols (MRPs) have been proposed to resolve above listed challenges. Some of them are used for dynamic establishment of reliable route for multimedia data communication. This article provides a detailed survey of the merits and demerits of the recently developed techniques. An ample study of various Quality of Service (QoS) techniques and enhancement is also presented. Later, mesh topology-based MRPs are classified according to enhancement in routing mechanism and QoS modification. This article covers the most recent, robust, and reliable QoS-aware mesh based MRPs, classified on the basis of their operational features, and pros and cons. Finally, a comparative study has been presented on the basis of their performance parameters on the proposed protocols.
Proactive Defense for Internet-of-things: Moving Target Defense With Cyberdeception
Authors: Ge Mengmeng , Cho Jin-Hee , Kim Dongseong , Dixit Gaurav , Chen Ing-Ray
Published: September 2021

Resource constrained Internet-of-Things (IoT) devices are highly likely to be compromised by attackers, because strong security protections may not be suitable to be deployed. This requires an alternative approach to protect vulnerable components in IoT networks. In this article, we propose an integrated defense technique to achieve intrusion prevention by leveraging cyberdeception (i.e., a decoy system) and moving target defense (i.e., network topology shuffling). We evaluate the effectiveness and efficiency of our proposed technique analytically based on a graphical security model in a software-defined networking (SDN)-based IoT network. We develop four strategies (i.e., fixed/random and adaptive/hybrid) to address “when” to perform network topology shuffling and three strategies (i.e., genetic algorithm/decoy attack path-based optimization/random) to address “how” to perform network topology shuffling on a decoy-populated IoT network, and we analyze which strategy can best achieve a system goal, such as prolonging the system lifetime, maximizing deception effectiveness, maximizing service availability, or minimizing defense cost. We demonstrated that a software-defined IoT network running our intrusion prevention technique at the optimal parameter setting prolongs system lifetime, increases attack complexity of compromising critical nodes, and maintains superior service availability compared with a counterpart IoT network without running our intrusion prevention technique. Further, when given a single goal or a multi-objective goal (e.g., maximizing the system lifetime and service availability while minimizing the defense cost) as input, the best combination of “when” and “how” strategies is identified for executing our proposed technique under which the specified goal can be best achieved.
Programming and Synthesis for Software-defined FPGA Acceleration: Status and Future Prospects
Authors: Lai Yi-Hsiang , Ustun Ecenur , Xiang Shaojie , Fang Zhenman , Rong Hongbo , Zhang Zhiru
Published: September 2021

FPGA-based accelerators are increasingly popular across a broad range of applications, because they offer massive parallelism, high energy efficiency, and great flexibility for customizations. However, difficulties in programming and integrating FPGAs have hindered their widespread adoption. Since the mid 2000s, there has been extensive research and development toward making FPGAs accessible to software-inclined developers, besides hardware specialists. Many programming models and automated synthesis tools, such as high-level synthesis, have been proposed to tackle this grand challenge. In this survey, we describe the progression and future prospects of the ongoing journey in significantly improving the software programmability of FPGAs. We first provide a taxonomy of the essential techniques for building a high-performance FPGA accelerator, which requires customizations of the compute engines, memory hierarchy, and data representations. We then summarize a rich spectrum of work on programming abstractions and optimizing compilers that provide different trade-offs between performance and productivity. Finally, we highlight several additional challenges and opportunities that deserve extra attention by the community to bring FPGA-based computing to the masses.
DANA
Authors: Malekzadeh Mohammad , Clegg Richard , Cavallaro Andrea , Haddadi Hamed
Published: September 2021

Motion sensors embedded in wearable and mobile devices allow for dynamic selection of sensor streams and sampling rates, enabling several applications, such as power management and data-sharing control. While deep neural networks (DNNs) achieve competitive accuracy in sensor data classification, DNN architectures generally process incoming data from a fixed set of sensors with a fixed sampling rate, and changes in the dimensions of their inputs cause considerable accuracy loss, unnecessary computations, or failure in operation. To address these limitations, we introduce a dimension-adaptive pooling (DAP) layer that makes DNNs flexible and more robust to changes in sensor availability and in sampling rate. DAP operates on convolutional filter maps of variable dimensions and produces an input of fixed dimensions suitable for feedforward and recurrent layers. Further, we propose a dimension-adaptive training (DAT) procedure for enabling DNNs that use DAP to better generalize over the set of feasible data dimensions at inference time. DAT comprises the random selection of dimensions during the forward passes and optimization with accumulated gradients of several backward passes. Combining DAP and DAT, we show how to transform existing non-adaptive DNNs into a Dimension-Adaptive Neural Architecture (DANA), while keeping the same number of parameters. Compared to existing approaches, our solution provides better average classification accuracy over the range of possible data dimensions at inference time and does not require up-sampling or imputation, thus reducing unnecessary computations. Experimental results on seven datasets (four benchmark real-world datasets for human activity recognition and three synthetic datasets) show that DANA prevents significant losses in classification accuracy of the state-of-the-art DNNs and, compared to baselines, it better captures correlated patterns in sensor data under dynamic sensor availability and varying sampling rates.
REHASH
Authors: Bakar Abu , Ross Alexander G. , Yildirim Kasim Sinan , Hester Josiah
Published: September 2021

Battery-free sensing devices harvest energy from their surrounding environment to perform sensing, computation, and communication. This enables previously impossible applications in the Internet-of-Things. A core challenge for these devices is maintaining usefulness despite erratic, random or irregular energy availability; which causes inconsistent execution, loss of service and power failures. Adapting execution (degrading or upgrading) seems promising as a way to stave off power failures, meet deadlines, or increase throughput. However, because of constrained resources and limited local information, it is a challenge to decide when would be the best time to adapt, and how exactly to adapt execution. In this paper, we systematically explore the fundamental mechanisms of energy-aware adaptation, and propose heuristic adaptation as a method for modulating the performance of tasks to enable higher sensor coverage, completion rates, or throughput, depending on the application. We build a task based adaptive runtime system for intermittently powered sensors embodying this concept. We complement this runtime with a user facing simulator that enables programmers to conceptualize the tradeoffs they make when choosing what tasks to adapt, and how, relative to real world energy harvesting environment traces. While we target battery-free, intermittently powered sensors, we see general application to all energy harvesting devices. We explore heuristic adaptation with varied energy harvesting modalities and diverse applications: machine learning, activity recognition, and greenhouse monitoring, and find that the adaptive version of our ML app performs up to 46% more classifications with only a 5% drop in accuracy; the activity recognition app captures 76% more classifications with only nominal down-sampling; and find that heuristic adaptation leads to higher throughput versus non-adaptive in all cases.
The Empathetic Car
Authors: Liu Shu , Koch Kevin , Zhou Zimu , Föll Simon , He Xiaoxi , Menke Tina , Fleisch Elgar , Wortmann Felix
Published: September 2021

An empathetic car that is capable of reading the driver's emotions has been envisioned by many car manufacturers. Emotion inference enables in-vehicle applications to improve driver comfort, well-being, and safety. Available emotion inference approaches use physiological, facial, and speech-related data to infer emotions during driving trips. However, existing solutions have two major limitations: Relying on sensors that are not built into the vehicle restricts emotion inference to those people leveraging corresponding devices (e.g., smartwatches). Relying on modalities such as facial expressions and speech raises privacy concerns. By contrast, researchers in mobile health have been able to infer affective states (e.g., emotions) based on behavioral and contextual patterns decoded in available sensor streams, e.g., obtained by smartphones. We transfer this rationale to an in-vehicle setting by analyzing the feasibility of inferring driver emotions by passively interpreting the data streams of the control area network (CAN-bus) and the traffic context (inferred from the front-view camera). Therefore, our approach does not rely on particularly privacy-sensitive data streams such as the driver facial video or driver speech, but is built based on existing CAN-bus data and traffic information, which is available in current high-end or future vehicles. To assess our approach, we conducted a four-month field study on public roads covering a variety of uncontrolled daily driving activities. Hence, our results were generated beyond the confines of a laboratory environment. Ultimately, our proposed approach can accurately recognise drivers' emotions and achieve comparable performance as the medical-grade physiological sensor-based state-of-the-art baseline method.
ExpressEar
Authors: Verma Dhruv , Bhalla Sejal , Sahnan Dhruv , Shukla Jainendra , Parnami Aman
Published: September 2021

Continuous and unobtrusive monitoring of facial expressions holds tremendous potential to enable compelling applications in a multitude of domains ranging from healthcare and education to interactive systems. Traditional, vision-based facial expression recognition (FER) methods, however, are vulnerable to external factors like occlusion and lighting, while also raising privacy concerns coupled with the impractical requirement of positioning the camera in front of the user at all times. To bridge this gap, we propose ExpressEar, a novel FER system that repurposes commercial earables augmented with inertial sensors to capture fine-grained facial muscle movements. Following the Facial Action Coding System (FACS), which encodes every possible expression in terms of constituent facial movements called Action Units (AUs), ExpressEar identifies facial expressions at the atomic level. We conducted a user study (N=12) to evaluate the performance of our approach and found that ExpressEar can detect and distinguish between 32 Facial AUs (including 2 variants of asymmetric AUs), with an average accuracy of 89.9% for any given user. We further quantify the performance across different mobile scenarios in presence of additional face-related activities. Our results demonstrate ExpressEar's applicability in the real world and open up research opportunities to advance its practical adoption.
Is Someone Listening?
Authors: Dunbar Julia C. , Bascom Emily , Boone Ashley , Hiniker Alexis
Published: September 2021

Smart devices with the capability to record audio can create a trade-off for users between convenience and privacy. To understand how users experience this trade-off, we report on data from 35 interview, focus group, and design workshop participants. Participants' perspectives on smart-device audio privacy clustered into the pragmatist, guardian, and cynic perspectives that have previously been shown to characterize privacy concerns in other domains. These user groups differed along four axes in their audio-related behaviors (for example, guardians alone say they often move away from a microphone when discussing a sensitive topic). Participants surfaced three usage phases that require design consideration with respect to audio privacy: 1) adoption, 2) in-the-moment recording, and 3) downstream use of audio data. We report common design solutions that participants created for each phase (such as indicators showing when an app is recording audio and annotations making clear when an advertisement was selected based on past audio recording).
Multi-Head Spatio-Temporal Attention Mechanism for Urban Anomaly Event Prediction
Authors: Huang Huiqun , Yang Xi , He Suining
Published: September 2021

Timely forecasting the urban anomaly events in advance is of great importance to the city management and planning. However, anomaly event prediction is highly challenging due to the sparseness of data, geographic heterogeneity (e.g., complex spatial correlation, skewed spatial distribution of anomaly events and crowd flows), and the dynamic temporal dependencies.

In this study, we propose M-STAP, a novel Multi-head Spatio-Temporal Attention Prediction approach to address the problem of multi-region urban anomaly event prediction. Specifically, M-STAP considers the problem from three main aspects: (1) extracting the spatial characteristics of the anomaly events in different regions, and the spatial correlations between anomaly events and crowd flows; (2) modeling the impacts of crowd flow dynamic of the most relevant regions in each time step on the anomaly events; and (3) employing attention mechanism to analyze the varying impacts of the historical anomaly events on the predicted data. We have conducted extensive experimental studies on the crowd flows and anomaly events data of New York City, Melbourne and Chicago. Our proposed model shows higher accuracy (41.91% improvement on average) in predicting multi-region anomaly events compared with the state-of-the-arts.
The Crowd Wisdom for Location Privacy of Crowdsensing Photos
Authors: Zhou Tongqing , Cai Zhiping , Liu Fang
Published: September 2021

The incorporation of the mobile crowd in visual sensing provides a significant opportunity to explore and understand uncharted physical places. We investigate the gains and losses of the involvement of the crowd wisdom on users' location privacy in photo crowdsensing. For the negative effects, we design a novel crowdsensing photo location inference model, regardless of the robust location protection techniques, by jointly exploiting the visual representation, correlation, and geo-annotation capabilities extracted from the crowd. Compared with existing retrieval-based and model-based location inference techniques, our proposal poses more pernicious threats to location privacy by considering the no-reference-photos situations of crowdsensing. We conduct extensive analyses on the model with four photo datasets and crowdsourcing surveys for geo-annotation. The results indicate that being in a crowd of photos will, unfortunately, increase one's risk to be geo-identified, and highlights that the model can yield a considerable high inference accuracy (48%~70%) and serious privacy exposure (over 80% of users get privacy disclosed) with a small portion of geo-annotated samples. In view of the threats, we further propose an adaptive grouping-based signing model that hides a user's track with the camouflage of a crowd of users. Wherein, ring signature is tailored for crowdsensing to provide indistinguishable while valid identities for every user's submission. We theoretically analyze its adjustable privacy protection capability and develop a prototype to evaluate the effectiveness and performance.