bluuebunny/crossref_metadata_2025 huggingface dataset:
Protocol for CARES–HAPIN: an ambidirectional cohort study on exposure to environmental tobacco smoke and risk of early childhood caries
Authors: Patil Sneha S , Puttaswamy Naveen , Cardenas Andres , Barr Dana Boyd , Ghosh Santu , Balakrishnan Kalpana
Published: May 2024

Introduction

Prenatal and postnatal exposure to environmental tobacco smoke (ETS) has been linked with early childhood caries (ECC), but the specific molecular mechanisms and pathways remain largely unknown. The Caries Risk from exposure to Environmental tobacco Smoke (CARES) within the Household Air Pollution Intervention Network (HAPIN) study aims to establish the association between ETS and ECC by employing epidemiological and novel biomarker-based approaches. Here, we outline the overall design and rationale of the project.

Methods and analysis

We will leverage the infrastructure and data from the HAPIN trial (India) to mount the CARES study. In this ambidirectional cohort study, children (n=735, aged: 3–5 years) will undergo ECC examination by a trained dentist using standard criteria and calibrated methods. Structured questionnaires will be used to gather information on sociodemographic variables, dietary habits, oral hygiene, oral health-related quality of life and current exposure to ETS. We will collect non-invasive or minimally invasive biospecimens (i.e., saliva, buccal cells, dried blood spots and urine) from a subset of HAPIN children (n=120) to assess a battery of biomarkers indicative of exposure to ETS, early biological effect and epigenetic modifications. Both self-reported and objective measures of ETS exposure collected longitudinally during in utero and early postnatal periods will be accessed from the HAPIN database. We will apply current science data techniques to assess the association and interrelationships between ETS, ECC, and multiple biomarkers.

Ethics and dissemination

Information gathered in this research will be published in peer-reviewed journals and summaries will be shared with the key stakeholders as well as patients and their parents/guardians involved in this study. Sri Ramachandra Institute of Higher Education and Research Ethics Board has approved the study protocol (IEC-NI22/JUL/83/82).

Trial registration number

NCT02944682.
Ward-based in situ simulation: lessons learnt from a UK District General Hospital
Authors: Schwartze Julian Tristan , Das Souvik , Suggitt Deborah , Baxter Jeanette , Tunstall Simon , Ronan Nicholas , Stannard Helen , Rezgui Amina , Jafar Wisam , Baxter David Neil
Published: May 2024

Introduction

In situ simulation (ISS) enables multiprofessional healthcare teams to train for real emergencies in their own working environment and identify latent patient safety threats. This study aimed to determine ISS impact on teamwork, technical skill performance, healthcare staff perception and latent error identification during simulated medical emergencies.

Materials and methods

Unannounced ISS sessions (n=14, n=75 staff members) using a high-fidelity mannequin were conducted in medical, paediatric and rehabilitation wards at Stepping Hill Hospital (Stockport National Health Service Foundation Trust, UK). Each session encompassed a 15 min simulation followed by a 15 min faculty-led debrief.

Results

The clinical team score revealed low overall teamwork performances during simulated medical emergencies (mean±SEM: 4.3±0.5). Linear regression analysis revealed that overall communication (r=0.9, p<0.001), decision-making (r=0.77, p<0.001) and overall situational awareness (r=0.73, p=0.003) were the strongest statistically significant predictors of overall teamwork performance. Neither the number of attending healthcare professionals, their professional background, age, gender, degree of clinical experience, level of resuscitation training or previous simulation experience statistically significantly impacted on overall teamwork performance. ISS positively impacted on healthcare staff confidence and clinical training. Identified safety threats included unknown location of intraosseous kits, poor/absent airway management, incomplete A–E assessments, inability to activate the major haemorrhage protocol, unknown location/dose of epinephrine for anaphylaxis management, delayed administration of epinephrine and delayed/absence of attachment of pads to the defibrillator as well as absence of accessing ALS algorithms, poor chest compressions and passive behaviour during simulated cardiac arrests.

Conclusion

Poor demonstration of technical/non-technical skills mandate regular ISS interventions for healthcare professionals of all levels. ISS positively impacts on staff confidence and training and drives identification of latent errors enabling improvements in workplace systems and resources.
Prevalence, Medicaid use and mortality risk of low FEV1in adults aged 20–35 years old in the USA: evidence from a population-based retrospective cohort study
Authors: Wang Zihui , Li Yun , Tan Lunfang , Liu Shuyi , Wang Zhufeng , Zhang Qing , Lin Junfeng , Huang Jinhai , Liang Lina , Gao Yi , Zhong Nanshan , Zheng Jinping
Published: May 2024

Background

The prevalence, Medicaid use and mortality risk associated with low forced expiratory volume in 1 s (FEV1) among young adults aged 20–35 years are not well understood, despite its potential implications for the development of chronic pulmonary disease and overall prognosis.

Methods

A retrospective cohort study was conducted among young adults aged 20–35 years old, using data from the National Health and Nutrition Examination Survey, National Death Index and Centers for Medicare & Medicaid Services. Participants were categorised into a low FEV1group (pre-bronchodilator FEV1%pred <80%) and a normal FEV1group (FEV1%pred ≥80%). Weighted logistic regression analysis was employed to identify the risk factors associated with low FEV1, while Cox proportional hazard models were used to calculate the hazard ratio (HR) for Medicaid use and the all-cause mortality between the two groups.

Results

A total of 5346 participants aged 20–35 were included in the study, with 329 in the low FEV1group and 5017 in the normal group. The weighted prevalence of low FEV1among young adults was 7.1% (95% CI 6.0 to 8.2). Low body mass index (OR=3.06, 95% CI 1.79 to 5.24), doctor-diagnosed asthma (OR=2.25, 1.28 to 3.93), and wheezing or whistling (OR=1.57, 1.06 to 2.33) were identified as independent risk factors for low FEV1. Over a 15-year follow-up, individuals in the low FEV1group exhibited a higher likelihood of Medicaid use compared with those in the normal group (HR=1.73, 1.07 to 2.79). However, there was no statistically significant increase in the risk of all-cause mortality over a 30-year follow-up period (HR=1.48, 1.00 to 2.19).

Conclusions

A considerable portion of young adults demonstrated low FEV1levels, a characteristic that was associated with a higher risk of Medicaid use over a long-term follow-up, yet not linked to an augmented risk of all-cause mortality.
Atrial remodelling associated with sporting discipline, sex and duration in elite sports: a cross-sectional echocardiographic study among Danish elite athletes
Authors: Aaroee Mikkel , Tischer Susanne Glasius , Christensen Robin , Dall Christian Have , Thune Jens Jakob , Rasmusen Hanne
Published: May 2024

Background

Elite endurance training is characterised by a high-volume load of the heart and has been associated with atrial fibrillation (AF) in middle-aged men. We compared left atrial (LA) remodelling among elite athletes engaged in sports, categorised as having low, intermediate, and high cardiac demands.

Methods

This cross-sectional echocardiographic study of healthy elite athletes evaluated LA size and function measured as LA maximum volume (maxLAVi) and contraction strain. Athletes were grouped according to the cardiac demands of their sport (low, intermediate, high). Morphological measures were indexed to body surface area and reported as least square means; differences between groups were reported with 95% CIs.

Results

We included 482 elite athletes (age 21±5 years (mean±SD), 39% women). MaxLAVi was larger in the high group (28.4 mL/m2) compared with the low group (20.2 mL/m2; difference: 8.2, CI 5.3 to 11.1 mL/m2; p<0.001), where measurements in men exceed those in women (26.4 mL/m2vs 24.7 mL/m2; difference 1.6 mL/m2; CI 0.3 to 2.9 mL/m2; p=0.0175). In the high group, LA contraction strain was lower compared with the low group (−10.1% vs −12.9%; difference: 2.8%; CI 1.3 to 4.3%; p<0.001), and men had less LA contraction strain compared with women (−10.3% vs −11.0%; difference 0.7%; CI 0.0 to 1.4%; p=0.049). Years in training did not affect maxLAVi or LA contraction strain.

Conclusion

MaxLAVi was higher while LA contraction strain was lower with increased cardiac demands. MaxLAVi was larger, and LA contraction was lower in men compared with women. Whether these sex-based differences in LA remodelling are a precursor to pathological remodelling in male athletes is unknown.
Colorectal cancer-specific IFNβ delivery overcomes dysfunctional dsRNA-mediated type I interferon signaling to increase the abscopal effect of radiotherapy
Authors: Huang Kevin Chih-Yang , Chiang Shu-Fen , Chang Hsin-Yu , Hong Wei-Ze , Chen Jhen-Yu , Lee Pei-Chih , Liang Ji-An , Ke Tao-Wei , Peng Shin-Lei , Shiau An‑Cheng , Chen Tsung-Wei , Yang Pei-Chen , Chen William Tzu-Liang , Chao K S Clifford
Published: May 2024

Background

Cancer-intrinsic type I interferon (IFN-I) production triggered by radiotherapy (RT) is mainly dependent on cytosolic double-stranded DNA (dsDNA)-mediated cGAS/STING signaling and increases cancer immunogenicity and enhances the antitumor immune response to increase therapeutic efficacy. However, cGAS/STING deficiency in colorectal cancer (CRC) may suppress the RT-induced antitumor immunity. Therefore, we aimed to evaluate the importance of the dsRNA-mediated antitumor immune response induced by RT in patients with CRC.

Methods

Cytosolic dsRNA level and its sensors were evaluated via cell-based assays (co-culture assay, confocal microscopy, pharmacological inhibition and immunofluorescent staining) and in vivo experiments. Biopsies and surgical tissues from patients with CRC who received preoperative chemoradiotherapy (neoCRT) were collected for multiplex cytokine assays, immunohistochemical analysis and SNP genotyping. We also generated a cancer-specific adenovirus-associated virus (AAV)-IFNβ1 construct to evaluate its therapeutic efficacy in combination with RT, and the immune profiles were analyzed by flow cytometry and RNA-seq.

Results

Our studies revealed that RT stimulates the autonomous release of dsRNA from cancer cells to activate TLR3-mediated IFN-I signatures to facilitate antitumor immune responses. Patients harboring a dysfunctional TLR3 variant had reduced serum levels of IFN-I-related cytokines and intratumoral CD8+immune cells and shorter disease-free survival following neoCRT treatment. The engineered cancer-targeted construct AAV-IFNβ1 significantly improved the response to RT, leading to systematic eradication of distant tumors and prolonged survival in defective TLR3 preclinical models.

Conclusion

Our results support that increasing cancer-intrinsic IFNβ1 expression is an immunotherapeutic strategy that enhances the RT-induced antitumor immune response in locally patients with advanced CRC with dysfunctional TLR3.
Exploring complement biomarkers in suspected axial spondyloarthritis
Authors: Mistegård Clara Elbæk , Troldborg Anne , Loft Anne Gitte , Thiel Steffen , Spiller Laura , Protopopov Mikhail , Rios Rodriguez Valeria , Muche Burkhard , Rademacher Judith , Weber Anne-Katrin , Lüders Susanne , Sieper Joachim , Poddubnyy Denis , Proft Fabian
Published: May 2024

Objectives

To investigate lectin pathway proteins (LPPs) as biomarkers for axial spondyloarthritis (axSpA) in a cross-sectional cohort with a suspicion of axSpA, comprising newly diagnosed axSpA and chronic low back pain (cLBP) individuals.

Methods

Serum samples from 515 participants within the OptiRef cohort, including 151 axSpA patients and 364 cLBP patients, were measured using immunoassays for LPPs (mannan-binding lectin (MBL), collectin liver-1 (CL-L1), M-ficolin, H-ficolin and L-ficolin, MBL-associated serine proteases (MASP)−1, –2 and –3, MBL-associated proteins (MAp19 and MAp44) and the complement activation product C3dg).

Results

Serum levels of L-ficolin, MASP-2 and C3dg were elevated in axSpA patients, whereas levels of MASP-3 and CL-L1 were decreased, and this remained significant for C3dg and MASP-3 after adjustment for C reactive protein (CRP). A univariate regression analysis showed serum levels of CL-L1, MASP-2, MASP-3 and C3dg to predict the diagnosis of axSpA, and MASP-3 and C3dg remained significant in a multivariate logistic regression analysis. Assessment of the diagnostic potential showed that a combination of human leukocyte antigen B27 (HLA-B27) and measurements of L-ficolin, MASP-3 and C3dg increased the diagnostic specificity for axSpA, however, with a concomitant loss of sensitivity.

Conclusions

Serum levels of complement activation, that is, C3dg, and MASP-3 differed significantly between axSpA and cLBP patients after adjustment for CRP. Although combining HLA-B27 with measurements of L-ficolin, MASP-3 and C3dg increased the diagnostic specificity for axSpA, this seems unjustified due to the concomitant loss of sensitivity. However, both C3dg and MASP-3 were associated with axSpA diagnosis in multivariate logistic regression, suggesting an involvement of complement in the inflammatory processes and possibly pathogenesis in axSpA.
Impacts of road salt on seed germination of Thuja occidentalis found in natural communities adjacent to the Illinois Tollway in northeastern IL, USA
Authors: Janssen Eric , Johnson Sara A. , Glass Nicholas , Dickerson Patricia , Whelan Christopher J. , Molano-Flores Brenda
Published: May 2024

In the USA, road salt usage in urban areas has increased since the 1950s. In the greater Chicago area over 175 000 tons of salt are applied every year. The salt runoff from this application has the potential to negatively impact nearby plants and alter native plant communities. We evaluated how varying salt concentrations affect overall germination, germination probability, and multiple metrics of germination speed for seeds from five source populations of Thuja occidentalis L. Two populations in a native forested fen system are susceptible to salt runoff from the Illinois Tollway. We found that increased salt concentrations decreased both the probability of germination and overall germination, and increased the time to germination. Seeds from the two natural populations performed poorly compared to the other populations. Salt pollution impacts the health and survival of adult trees, and may also inhibit the reproduction and recruitment of T. occidentalis. Reduction of salt pollution is necessary to maintain the long-term survival and persistence of this species, other sensitive species, and native fen habitats.
An experimental test of niche versus dispersal limitation of the distribution limit of the Ghost Antler Lichen,Pseudevernia cladonia, along a temperate–boreal elevation gradient
Authors: Rinas Christina L. , Vellend Mark
Published: May 2024

Understanding the mechanisms underlying species’ distribution limits is critical for predicting how species may respond to environmental change. For species restricted to mountain summits, there is concern that climatic changes may result in increasingly restricted distributions. Two central mechanisms govern species distribution limits: (i) niche limitations–environmental conditions beyond distribution limits that are insufficient for survival and reproduction, and (ii) dispersal limitations that prevent colonization of suitable habitat beyond distribution limits. Here, we conducted a transplant experiment to examine the effect of niche versus dispersal limitation on the altitudinal distribution limit of the Ghost Antler Lichen ( Pseudevernia cladonia (Tuck.) Hale & Culb.) that, within Québec, Canada, is restricted to high-elevation mountain summits in the southeast. Along an elevation gradient, we transplanted individuals into sites within its distribution, at the edge, and beyond its distribution. We observed that survival and performance were greatest within its distribution and decreased markedly beyond its distribution, supporting our prediction that this lichen is niche limited along the elevation gradient. We suggest that cooler and more humid conditions at the summit are important environmental factors for this species’ persistence. Our findings suggest that projected climatic changes in these montane habitats may result in less suitable habitat for this species.
Effects of spruce budworm defoliation on in-stream algal production and carbon use by food webs
Authors: Ju K. Sally , Kidd Karen A. , Stastny Michael , Gray Michelle A. , Venier Lisa , Emilson Erik J.S.
Published: May 2024

Insect defoliation is a widespread cause of forest disturbance in Canada, and it has the potential to alter terrestrial carbon contributions to stream consumers and thus affect stream ecosystems. Although defoliation by spruce budworms ( Choristoneura fumiferana) is considered a natural disturbance with importance to forest succession, the magnitude and duration of outbreaks are increasing, and there is a growing need to understand their downstream consequences. To examine this, algal productivity and autochthonous (in-stream) energy supporting macroinvertebrate and fish consumers (using δ13C, δ15N) were examined in 12 streams in the Gaspé Peninsula, Québec, Canada, that ranged in watershed defoliation from spruce budworm. Hierarchical partitioning models were used to assess the contributions of watershed and stream variables to these endpoints. Total seasonal algal production ranged fourfold among sites, and cumulative defoliation was the strongest predictor. Consumers from streams with greater defoliation (cumulative or annual) had lower reliance on autochthonous carbon, despite increased algal production, and this effect was greater for brook trout than macroinvertebrates. These findings demonstrate for the first time that insect outbreaks—which alter forest structure and function—also similarly affect downstream aquatic ecosystems by causing changes in the production and contributions of carbon sources. This suggests that insect control strategies and forest management decisions should also consider implications for downstream aquatic ecosystems.
NN scattering with $$N\varDelta $$ coupling: dibaryon resonances without “dibaryons”?
Authors: Niskanen J. A.
Published: May 2024

It is known that at their threshold intermediate two-baryon $$N\varDelta $$

N
Δ

states can produce resonance-like structures in some isospin one states, often interpreted as more exotic manifest six-quark states. This paper applies the coupled-channel method to study vital details of the $$N\varDelta $$

N
Δ

effect in isospin one NN scattering with interactions constrained to exclude the influence of such extraneous hypothetical particles in two respects. Firstly, the calculated phase parameters are fitted only below pion inelasticity, i.e. far below the region of “dibaryons”. Secondly, the strength of the $$NN \rightarrow N\varDelta $$

N
N
→
N
Δ

transition is constrained to agree with the pion production reaction $$NN\rightarrow d\pi $$

N
N
→
d
π

, fairly independent of the details of the pure “diagonal” NN potential and its effect practically as strong as the NN itself. The strongly angular momentum dependent ingredients and results may be considered as a necessary background for searches of any additional dibaryon effects. Optimal conditions for resonant $$N\varDelta $$

N
Δ

appearances involve a decrease of the orbital angular momentum in the transition $$NN\rightarrow N\varDelta $$

N
N
→
N
Δ

, as is the case in the $$^1D_2$$

1

D
2

and $$^3F_3$$

3

F
3

waves. Detailed complex phase shift results are further presented also for isospin one peripheral partial waves up to $$J=6$$

J
=
6

, where, contrary to common prejudice, $$N\varDelta $$

N
Δ

excitation is still found to be comparable to or even larger than one pion exchange.
Double Dualism, Economic Growth Slowdown, and Falling Income Inequality in Thailand
Authors: VECHSURUCK TANADEJ , PRATOOMCHAT PRAOPAN
Published: May 2024

Thailand has experienced a decline in income inequality coupled with unimpressive economic growth since the end of the 1997/98 Asian financial crisis. This paper uses the structuralist approach to understand how these concurrent economic phenomena have become deeply intertwined. We argue that this intertwining results from Thailand’s economic structure, manifesting two types of dualism: (i) the dualism of the formal–informal sectors and (ii) the dualism of the dynamic–stagnant sectors. A decline in the informal sector in recent years coincides with a decrease in income inequality. Further, the second type of dualism between the dynamic and stagnant sectors has emerged since 2000. The stagnant sectors’ employment share has grown faster than that of the dynamic sectors, resulting in a slowdown in economic growth and less inequality. The decline of the informal sector and the rise of the stagnant sectors are the primary engines weighing down economic growth and reducing income inequality in Thailand.
Effect of anion (S−2 & Se−2) replacement on photovoltaic properties in transition metal (Ba-Barium) chalcogenide perovskites
Authors: Pandit Naincy , Dubey Anusha , Joshi Tarun Kumar , Shukla Akash , Rani Upasana , Kamlesh Peeyush Kumar , Gupta Rajeev , Kumar Tanuj , Kaur Kulwinder , Verma Ajay Singh
Published: May 2024

Material scientists have stepped up their search for efficient materials in low-cost, high-stability, nontoxic energy conversion devices. In this paper, emerging materials inspire us to study one of the perovskite chalcogens made from alkaline-earth metals (Barelium). Therefore, we determined some fundamental properties with some application-based properties, which explained their applicability in energy conversion device fabrication by first-principles calculation within the WIEN2K Code. Structure stability has been verified by Birch–Murnaghan fits and thermal stability at different temperatures and pressure ranges is explained by Gibbs function in thermodynamic properties. By using modified Becke–Johnson (mBJ) potential, electronic and optical characteristics of these materials provide insight into their nature: they were revealed to be direct bandgap semiconductors with the calculated values of 1.77[Formula: see text]eV (1.25[Formula: see text]eV) for BaZrS3(BaZrSe3), respectively. Both materials exhibit transparency on low-energy striking photons and demonstrate absorption and optical conduction in the UV region.

Both materials exhibit transparency on low-energy striking photons and demonstrate absorption and optical conduction in the UV region. In the thermoelectric parameter, the figure of merit (ZT) is unity at room temperature and decreases up to 0.98 with temperature increment which reveals that these materials will be helpful in thermoelectric devices. As per the application part, we carried out the calculation of the spectroscopic limited maximum efficiency (SLME) and found that efficiency increases from 6.5% to 27.1% (8.1% to 31.9%) for BaZrS3 (BaZrSe3), respectively. The film thickness increased from 100[Formula: see text]nm to 1[Formula: see text][Formula: see text]m at room temperature and then stabilized. This emerging study shows that these materials can be used as an alert substance in energy conversion device fabrications and the proposed outcomes are in good acceptance with the experimental and other theoretical data. As per the optical and thermoelectric parameters of these materials, we infer that both are promising candidates in energy conversion device fabrication.
Dynamic Analysis, Image Encryption Application and FPGA Implementation of a Discrete Memristor-Coupled Neural Network
Authors: Yu Fei , Xu Si , Lin Yue , Gracia Yumba Musoya , Yao Wei , Cai Shuo
Published: May 2024

This paper presents a novel discrete memristor model that incorporates exponential and absolute value functions. A discrete coupled memristor neural network model is constructed based on this memristor design. The periodic and chaotic regions of the discrete neural network model are determined using bifurcation and Lyapunov exponent spectrum. Furthermore, by varying the initial values of the discrete memristive neural network, we observe the coexistence of chaos and periodic attractors, as well as periodic attractors. Additionally, an application to color image encryption based on the discrete system model is given. Security analysis is conducted in the aspects of key space, histogram analysis, correlation analysis, sensitivity analysis, Peak Signal-to-Noise Ratio (PSNR), and information entropy analysis. The analysis results show that the algorithm has a key space size of [Formula: see text], and the information entropy of baboon graph is 7.9993, which is very close to the ideal value of 8. It shows that the image encryption algorithm is feasible and effective. Finally, the implementation of the discrete memristive neural network model is realized using Field Programmable Gate Array (FPGA). The experimental implementation is conducted using the Verilog language on the Vivado 2018.3 platform, and the obtained results align with the numerical simulation results obtained through MATLAB.
Approach to Detect Windows Malware Based on Malicious Tendency Image and ResNet Algorithm
Authors: Zhang Bing , Zhang Hongchang , Ren Rong , Wen Zhen , Wang Qian
Published: May 2024

Timely detection of self-replicating malware in the high market share Windows operating system can effectively prevent personal or corporate financial losses. The form and characteristics of malware are constantly evolving, leading to a concept drift issue that gradually decreases the effectiveness of traditional detection methods. Therefore, we propose WinMDet, a Windows malware detection method based on malicious tendency image and ResNet algorithm. First, to tackle the complexity and difficulty in accurately characterizing malware features, WinMDet retains detailed malware features and encodes them into malicious tendency images to better describe malware across different periods. Secondly, WinMDet utilizes previously generated malicious tendency images to train the initial detection model. Then, to alleviate the issue of malware concept drift, WinMDet employs Local Maximum Mean Discrepancy (LMMD) as the criterion for model transfer, enhancing the initial detection model’s ability to distinguish between malware and benign software. We conducted a comprehensive evaluation of WinMDet using common metrics such as accuracy, precision and recall. The results indicate that WinMDet performs remarkably well in terms of accuracy, exceeding 82%. Additionally, significant improvements were observed in precision and recall, surpassing 82.42% and 82.06%, respectively. After employing our LMMD-based transfer method, the initial detection model improved the detection accuracy of malware in 2021 and 2022 by approximately 4.22% to 8.06%. The false negative rate decreased by at most 4.34%, and the false positive rate decreased by at most 4.61%.
Globalization — Inequality Nexus in the US and UK: A Multi-Dimensional Perspective
Authors: Uche Emmanuel , Koyama Torcia-Chanelle Banengai , Ngepah Nicholas
Published: May 2024

Equitable income distributions occupy a top spot on the list of the United Nations (UN) Sustainable Development Goals (SDG10). Nonetheless, prior empirical inquiries noted several factors, including globalization as the determinant of income inequality, albeit divergent inferences. However, very little is known about the potential effects of other variants of globalization (economic, social, cultural and political) on income inequality. Hence, this study, through a multi-dimensional scale, provides a comprehensive empirical overview of the effects of globalization on income inequality in the United States and the United Kingdom between 1970 and 2018. The study adopts the Autoregressive Distributed Lag (ARDL) and Kernel Regularized Least Squares (KRLS) models for broad-based empirical narratives. The empirical estimates rectify that globalization and its variants influenced income distributions significantly more in the US than in the UK. Particularly, at the 25th and 50th quantiles, globalization produced significant inequality-reducing effects in the UK. This indicates varying outcomes across the distributions of income inequality. Hence, constant monitoring is critical to curtail the influence of globalization on income distributions. The study also revealed that the existing patterns of income distributions in both countries would not guarantee the attainment of SDG10. However, if laborers are compensated adequately, the attainment of SDG10 is certain. Thus, relevant policy options that will ensure equitable prosperity in both countries are highlighted.
User-directed Assembly Code Transformations Enabling Efficient Batteryless Arduino Applications
Authors: Kraemer Christopher , Gelder William , Hester Josiah
Published: May 2024

The time for battery-free computing is now. Lithium mining depletes and pollutes local water supplies and dead batteries in landfills leak toxic metals into the ground[20][12]. Battery-free devices represent a probable future for sustainable ubiquitous computing and we will need many more new devices and programmers to bring that future into reality. Yet, energy harvesting and battery-free devices that frequently fail are challenging to program. The maker movement has organically developed a considerable variety of platforms to prototype and program ubiquitous sensing and computing devices, but only a few have been modified to be usable with energy harvesting and to hide those pesky power failures that are the norm from variable energy availability (platforms like Microsoft's Makecode and AdaFruit's CircuitPython). Many platforms, especially Arduino (the first and most famous maker platform), do not support energy harvesting devices and intermittent computing. To bridge this gap and lay a strong foundation for potential new platforms for maker programming, we build a tool called BOOTHAMMER: a lightweight assembly re-writer for ARM Thumb. BOOTHAMMER analyzes and rewrites the low-level assembly to insert careful checkpoint and restore operations to enable programs to persist through power failures. The approach is easily insertable in existing toolchains and is general-purpose enough to be resilient to future platforms and devices/chipsets. We close the loop with the user by designing a small set of program annotations that any maker coder can use to provide extra information to this low-level tool that will significantly increase checkpoint efficiency and resolution. These optional extensions represent a way to include the user in decision-making about energy harvesting while ensuring the tool supports existing platforms. We conduct an extensive evaluation using various program benchmarks with Arduino as our chosen evaluation platform. We also demonstrate the usability of this approach by evaluating BOOTHAMMER with a user study and show that makers feel very confident in their ability to write intermittent computing programs using this tool. With this new tool, we enable maker hardware and software for sustainable, energy-harvesting-based computing for all.
M3BAT: Unsupervised Domain Adaptation for Multimodal Mobile Sensing with Multi-Branch Adversarial Training
Authors: Meegahapola Lakmal , Hassoune Hamza , Gatica-Perez Daniel
Published: May 2024

Over the years, multimodal mobile sensing has been used extensively for inferences regarding health and well-being, behavior, and context. However, a significant challenge hindering the widespread deployment of such models in real-world scenarios is the issue of distribution shift. This is the phenomenon where the distribution of data in the training set differs from the distribution of data in the real world---the deployment environment. While extensively explored in computer vision and natural language processing, and while prior research in mobile sensing briefly addresses this concern, current work primarily focuses on models dealing with a single modality of data, such as audio or accelerometer readings, and consequently, there is little research on unsupervised domain adaptation when dealing with multimodal sensor data. To address this gap, we did extensive experiments with domain adversarial neural networks (DANN) showing that they can effectively handle distribution shifts in multimodal sensor data. Moreover, we proposed a novel improvement over DANN, called M3BAT, unsupervised domain adaptation for multimodal mobile sensing with multi-branch adversarial training, to account for the multimodality of sensor data during domain adaptation with multiple branches. Through extensive experiments conducted on two multimodal mobile sensing datasets, three inference tasks, and 14 source-target domain pairs, including both regression and classification, we demonstrate that our approach performs effectively on unseen domains. Compared to directly deploying a model trained in the source domain to the target domain, the model shows performance increases up to 12% AUC (area under the receiver operating characteristics curves) on classification tasks, and up to 0.13 MAE (mean absolute error) on regression tasks.
PRECYSE: Predicting Cybersickness using Transformer for Multimodal Time-Series Sensor Data
Authors: Jeong Dayoung , Han Kyungsik
Published: May 2024

Cybersickness, a factor that hinders user immersion in VR, has been the subject of ongoing attempts to predict it using AI. Previous studies have used CNN and LSTM for prediction models and used attention mechanisms and XAI for data analysis, yet none explored a transformer that can better reflect the spatial and temporal characteristics of the data, beneficial for enhancing prediction and feature importance analysis. In this paper, we propose cybersickness prediction models using multimodal time-series sensor data (i.e., eye movement, head movement, and physiological signals) based on a transformer algorithm, considering sensor data pre-processing and multimodal data fusion methods. We constructed the MSCVR dataset consisting of normalized sensor data, spectrogram formatted sensor data, and cybersickness levels collected from 45 participants through a user study. We proposed two methods for embedding multimodal time-series sensor data into the transformer: modality-specific spatial and temporal transformer encoders for normalized sensor data (MS-STTN) and modality-specific spatial-temporal transformer encoder for spectrogram (MS-STTS). MS-STTN yielded the highest performance in the ablation study and the comparison of the existing models. Furthermore, by analyzing the importance of data features, we determined their relevance to cybersickness over time, especially the salience of eye movement features. Our results and insights derived from multimodal time-series sensor data and the transformer model provide a comprehensive understanding of cybersickness and its association with sensor data. Our MSCVR dataset and code are publicly available: https://github.com/dayoung-jeong/PRECYSE.git.
CrossHAR: Generalizing Cross-dataset Human Activity Recognition via Hierarchical Self-Supervised Pretraining
Authors: Hong Zhiqing , Li Zelong , Zhong Shuxin , Lyu Wenjun , Wang Haotian , Ding Yi , He Tian , Zhang Desheng
Published: May 2024

The increasing availability of low-cost wearable devices and smartphones has significantly advanced the field of sensor-based human activity recognition (HAR), attracting considerable research interest. One of the major challenges in HAR is the domain shift problem in cross-dataset activity recognition, which occurs due to variations in users, device types, and sensor placements between the source dataset and the target dataset. Although domain adaptation methods have shown promise, they typically require access to the target dataset during the training process, which might not be practical in some scenarios. To address these issues, we introduce CrossHAR, a new HAR model designed to improve model performance on unseen target datasets. CrossHAR involves three main steps: (i) CrossHAR explores the sensor data generation principle to diversify the data distribution and augment the raw sensor data. (ii) CrossHAR then employs a hierarchical self-supervised pretraining approach with the augmented data to develop a generalizable representation. (iii) Finally, CrossHAR fine-tunes the pretrained model with a small set of labeled data in the source dataset, enhancing its performance in cross-dataset HAR. Our extensive experiments across multiple real-world HAR datasets demonstrate that CrossHAR outperforms current state-of-the-art methods by 10.83% in accuracy, demonstrating its effectiveness in generalizing to unseen target datasets.
Push the Limit of Highly Accurate Ranging on Commercial UWB Devices
Authors: Ma Junqi , Zhang Fusang , Jin Beihong , Su Chang , Li Siheng , Wang Zhi , Ni Jiazhi
Published: May 2024

Ranging plays a crucial role in many wireless sensing applications. Among the wireless techniques employed for ranging, Ultra-Wideband (UWB) has received much attention due to its excellent performance and widespread integration into consumer-level electronics. However, the ranging accuracy of the current UWB systems is limited to the centimeter level due to bandwidth limitation, hindering their use for applications that require a very high resolution. This paper proposes a novel system that achieves sub-millimeter-level ranging accuracy on commercial UWB devices for the first time. Our approach leverages the fine-grained phase information of commercial UWB devices. To eliminate the phase drift, we design a fine-grained phase recovery method by utilizing the bi-directional messages in UWB two-way ranging. We further present a dual-frequency switching method to resolve phase ambiguity. Building upon this, we design and implement the ranging system on commercial UWB modules. Extensive experiments demonstrate that our system achieves a median ranging error of just 0.77 mm, reducing the error by 96.54% compared to the state-of-the-art method. We also present three real-life applications to showcase the fine-grained sensing capabilities of our system, including i) smart speaker control, ii) free-style user handwriting, and iii) 3D tracking for virtual-reality (VR) controllers.
Detecting Users' Emotional States during Passive Social Media Use
Authors: Gebhardt Christoph , Brombach Andreas , Luong Tiffany , Hilliges Otmar , Holz Christian
Published: May 2024

The widespread use of social media significantly impacts users' emotions. Negative emotions, in particular, are frequently produced, which can drastically affect mental health. Recognizing these emotional states is essential for implementing effective warning systems for social networks. However, detecting emotions during passive social media use---the predominant mode of engagement---is challenging. We introduce the first predictive model that estimates user emotions during passive social media consumption alone. We conducted a study with 29 participants who interacted with a controlled social media feed. Our apparatus captured participants' behavior and their physiological signals while they browsed the feed and filled out self-reports from two validated emotion models. Using this data for supervised training, our emotion classifier robustly detected up to 8 emotional states and achieved 83% peak accuracy to classify affect. Our analysis shows that behavioral features were sufficient to robustly recognize participants' emotions. It further highlights that within 8 seconds following a change in media content, objective features reveal a participant's new emotional state. We show that grounding labels in a componential emotion model outperforms dimensional models in higher-resolutional state detection. Our findings also demonstrate that using emotional properties of images, predicted by a deep learning model, further improves emotion recognition.
BreathPro: Monitoring Breathing Mode during Running with Earables
Authors: Hu Changshuo , Kandappu Thivya , Liu Yang , Mascolo Cecilia , Ma Dong
Published: May 2024

Running is a popular and accessible form of aerobic exercise, significantly benefiting our health and wellness. By monitoring a range of running parameters with wearable devices, runners can gain a deep understanding of their running behavior, facilitating performance improvement in future runs. Among these parameters, breathing, which fuels our bodies with oxygen and expels carbon dioxide, is crucial to improving the efficiency of running. While previous studies have made substantial progress in measuring breathing rate, exploration of additional breathing monitoring during running is still lacking. In this work, we fill this gap by presenting BreathPro, the first breathing mode monitoring system for running. It leverages the in-ear microphone on earables to record breathing sounds and combines the out-ear microphone on the same device to mitigate external noises, thereby enhancing the clarity of in-ear breathing sounds. BreathPro incorporates a suite of well-designed signal processing and machine learning techniques to enable breathing mode detection with superior accuracy. We implemented BreathPro as a smartphone application and demonstrated its energy-efficient and real-time execution.
SonicVista: Towards Creating Awareness of Distant Scenes through Sonification
Authors: Gupta Chitralekha , Sridhar Shreyas , Matthies Denys J.C. , Jouffrais Christophe , Nanayakkara Suranga
Published: May 2024

Spatial awareness, particularly awareness of distant environmental scenes known as vista-space, is crucial and contributes to the cognitive and aesthetic needs of People with Visual Impairments (PVI). In this work, through a formative study with PVIs, we establish the need for vista-space awareness amongst people with visual impairments, and the possible scenarios where this awareness would be helpful. We investigate the potential of existing sonification techniques as well as AI-based audio generative models to design sounds that can create awareness of vista-space scenes. Our first user study, consisting of a listening test with sighted participants as well as PVIs, suggests that current AI generative models for audio have the potential to produce sounds that are comparable to existing sonification techniques in communicating sonic objects and scenes in terms of their intuitiveness, and learnability. Furthermore, through a wizard-of-oz study with PVIs, we demonstrate the utility of AI-generated sounds as well as scene audio recordings as auditory icons to provide vista-scene awareness, in the contexts of navigation and leisure. This is the first step towards addressing the need for vista-space awareness and experience in PVIs.
A Digital Companion Architecture for Ambient Intelligence
Authors: Garcia Kimberly , Vontobel Jonathan , Mayer Simon
Published: May 2024

Ambient Intelligence (AmI) focuses on creating environments capable of proactively and transparently adapting to users and their activities. Traditionally, AmI focused on the availability of computational devices, the pervasiveness of networked environments, and means to interact with users. In this paper, we propose a renewed AmI architecture that takes into account current technological advancements while focusing on proactive adaptation for assisting and protecting users. This architecture consist of four phases: Perceive, Interpret, Decide, and Interact. The AmI systems we propose, called Digital Companions (DC), can be embodied in a variety of ways (e.g., through physical robots or virtual agents) and are structured according to these phases to assist and protect their users. We further categorize DCs into Expert DCs and Personal DCs, and show that this induces a favorable separation of concerns in AmI systems, where user concerns (including personal user data and preferences) are handled by Personal DCs and environment concerns (including interfacing with environmental artifacts) are assigned to Expert DCs; this separation has favorable privacy implications as well. Herein, we introduce this architecture and validate it through a prototype in an industrial scenario where robots and humans collaborate to perform a task.
Seeing through the Tactile
Authors: Wu Ziyu , Xie Fangting , Fang Yiran , Liang Zhen , Wan Quan , Xiong Yufan , Cai Xiaohui
Published: May 2024

Humans spend about one-third of their lives resting. Reconstructing human dynamics in in-bed scenarios is of considerable significance in sleep studies, bedsore monitoring, and biomedical factor extractions. However, the mainstream human pose and shape estimation methods mainly focus on visual cues, facing serious issues in non-line-of-sight environments. Since in-bed scenarios contain complicated human-environment contact, pressure-sensing bedsheets provide a non-invasive and privacy-preserving approach to capture the pressure distribution on the contact surface, and have shown prospects in many downstream tasks. However, few studies focus on in-bed human mesh recovery. To explore the potential of reconstructing human meshes from the sensed pressure distribution, we first build a high-quality temporal human in-bed pose dataset, TIP, with 152K multi-modality synchronized images. We then propose a label generation pipeline for in-bed scenarios to generate reliable 3D mesh labels with a SMPLify-based optimizer. Finally, we present PIMesh, a simple yet effective temporal human shape estimator to directly generate human meshes from pressure image sequences. We conduct various experiments to evaluate PIMesh's performance, showing that PIMesh archives 79.17mm joint position errors on our TIP dataset. The results demonstrate that the pressure-sensing bedsheet could be a promising alternative for long-term in-bed human shape estimation.
Technology which Makes You Think
Authors: Loerakker Meagan B. , Niess Jasmin , Woźniak Paweł W.
Published: May 2024

Reflection is widely regarded as a key design goal for technologies for well-being. Yet, recent research shows that technologies for reflection may have negative consequences, in the form of rumination, i.e. negative thought cycles. Understanding how technologies support thinking about oneself, which can take the form of rumination and reflection, is key for future well-being technologies. To address this research gap, we developed the Reflection, Rumination and Thought in Technology (R2T2) scale. Contrary to past research, R2T2 addresses ways of self-focused thinking beyond reflection. This scale can quantify how a technology supports self-focused thinking and the rumination and reflection aspects of that thinking. We developed the scale through a systematic scale development process. We then evaluated the scale's test-retest reliability along with its concurrent and discriminant validity. R2T2 enables designers and researchers to compare technologies which embrace self-focused thinking and its facets as a design goal.