bluuebunny/crossref_metadata_2025 huggingface dataset:
Qualitative exploration of melanoma awareness in black people in the USA
Authors: de Vere Hunt Isabella , Owen Sidney , Amuzie Adaure , Nava Vanessa , Tomz Anna , Barnes Leandra , Robinson June K , Lester Jenna , Swetter Susan , Linos Eleni
Published: January 2023

Objective

Although black patients are more likely to have advanced melanomas at diagnosis, with a 5-year survival rate among black patients of 70% compared with 92% for white patients, black people are generally not the focus of melanoma public health campaigns. We sought to explore awareness and perspectives of melanoma among black people to inform the development of relevant and valued public health messages to promote early detection of melanoma.

Design

Inductive thematic analysis of in-depth semistructured interviews.

Setting

Interviews were conducted with participants via video software or telephone in the USA.

Participants

Participants were adults from the USA who self-identified as African American or black. Recruitment flyers were posted around the San Francisco Bay Area and shared on our team Facebook page, with further participants identified through snowball sampling.

Results

We interviewed 26 participants from 10 different states. Overall, 12 were men and 14 were women, with a mean age of 43 years (range 18–85). We identified five key themes regarding melanoma awareness in black people: (1) lack of understanding of term ‘melanoma’ and features of skin cancer; (2) do not feel at risk of melanoma skin cancer; (3) surprise that melanoma can occur on palms, soles and nails; (4) skin cancer awareness messages do not apply to or include black people; and (5) Importance of relationship with healthcare and habits of utilisation.

Conclusions

Analysis of these in-depth semistructured interviews illuminate the pressing need for health information on melanoma designed specifically for black people. We highlight two key points for focused public health messaging: (1) melanoma skin cancer does occur in black people and (2) high-risk sites for melanoma in black people include the palms, soles and nail beds. Therefore, public health messages for black people and their healthcare providers may involve productively checking these body surface areas.
Systematic review and meta-analysis of the diagnostic value of four biomarkers in detecting neonatal sepsis in low- and middle-income countries
Authors: Rees Chris A , Lim Jamie , Westbrook Adrianna L , El Helou Rachelle , Schmid Alexis , Rubin-Smith Julia , Shreeve Kyra , Rotman Chloe , Govindapillai Sindu , Dorney Kate , Niescierenko Michelle
Published: January 2023

Background

Biomarkers may enhance diagnostic capability for common paediatric infections, especially in low- and middle-income countries (LMICs) where standard diagnostic modalities are frequently unavailable, but disease burden is high. A comprehensive understanding of the diagnostic capability of commonly available biomarkers for neonatal sepsis in LMICs is lacking. Our objective was to systematically review evidence on biomarkers to understand their diagnostic performance for neonatal sepsis in LMICs.

Methods

We conducted a systematic review and meta-analysis of studies published in English, Spanish, French, German, Dutch, and Arabic reporting the diagnostic performance of C reactive protein (CRP), erythrocyte sedimentation rate (ESR), white blood cell count (WBC) and procalcitonin (PCT) for neonatal sepsis. We calculated pooled test characteristics and the area under the curve (AUC) for each biomarker compared with the reference standards blood culture or clinical sepsis defined by each article.

Results

Of 6570 studies related to biomarkers in children, 134 met inclusion criteria and included 23 179 neonates. There were 80 (59.7%) studies conducted in LMICs. CRP of ≥60 mg/L (AUC 0.87, 95% CI 0.76 to 0.91) among 1339 neonates and PCT of ≥0.5 ng/mL (AUC 0.87, 95% CI 0.70 to 0.92) among 617 neonates demonstrated the greatest discriminatory value for the diagnosis of neonatal sepsis using blood culture as the reference standard in LMICs.

Conclusions

PCT and CRP had good discriminatory value for neonatal sepsis in LMICs. ESR and WBC demonstrated poor discrimination for neonatal sepsis in LMICs. Future studies may incorporate biomarkers into clinical evaluation in LMICs to diagnose neonatal sepsis more accurately.

PROSPERO registration number

CRD42020188680.
Systematic review of outbreaks of COVID-19 within households in the European region when the child is the index case
Authors: Vardavas Constantine I , Nikitara Katerina , Aslanoglou Katerina , Kamekis Apostolos , Puttige Ramesh Nithya , Symvoulakis Emmanouil , Agaku Israel , Phalkey Revati , Leonardi-Bee Jo , Fernandez Esteve , Condell Orla , Lamb Favelle , Deogan Charlotte , Suk Jonathan E
Published: January 2023

Objectives

This systematic review aims to identify the secondary attack rates (SAR) to adults and other children when children are the index cases within household settings.

Methods

This literature review assessed European-based studies published in Medline and Embase between January 2020 and January 2022 that assessed the secondary transmission of SARS-CoV-2 within household settings. The inclusion criteria were based on the Population, Exposure, Outcome framework for systematic reviews. Thus, the study population was restricted to humans within the household setting in Europe (population), in contact with paediatric index cases 1–17 years old (exposure) that led to the transmission of SARS-CoV-2 reported as either an SAR or the probability of onward infection (outcome).

Results

Of 1819 studies originally identified, 19 met the inclusion criteria. Overall, the SAR ranged from 13% to 75% in 15 studies, while there was no evidence of secondary transmission from children to other household members in one study. Evidence indicated that asymptomatic SARS-CoV-2 index cases also have a lower SAR than those with symptoms and that younger children may have a lower SAR than adolescents (>12 years old) within household settings.

Conclusions

SARS-CoV-2 secondary transmission from paediatric index cases ranged from 0% to 75%, within household settings between January 2020 and January 2022, with differences noted by age and by symptomatic/asymptomatic status of the index case. Given the anticipated endemic circulation of SARS-CoV-2, continued monitoring and assessment of household transmission is necessary.
Clinical examination for athletes with inguinal-related groin pain: interexaminer reliability and prevalence of positive tests
Authors: Heijboer Willem M P , Vuckovic Zarko , Weir Adam , Tol Johannes L , Hölmich Per , Serner Andreas
Published: January 2023

Objectives

To evaluate the interexaminer reliability of abdominal palpation and resistance tests in athletes with longstanding groin pain, and to identify the prevalence of positive clinical tests in athletes classified with inguinal-related groin pain.

Methods

Male athletes (18–40 years) with longstanding groin pain were prospectively recruited between March 2019 and October 2020 at a sports medicine hospital. Two examiners performed history taking and standardised clinical examination (including abdominal palpation, scrotal invagination and abdominal resistance tests) blinded to each other’s findings. Interexaminer reliability was calculated using Cohen’s Kappa statistic (κ). Examiners classified groin pain using the Doha agreement meeting terminology. A differentiation was made between ‘defined inguinal-related groin pain’ (according to recommended definition criteria) and ‘likely inguinal-related groin pain’ (expert-based application of the Doha agreement classification when not all recommended criteria were present).

Results

Overall, 44 athletes were included (61 symptomatic sides). Interexaminer reliability of inguinal palpation pain provocation tests varied from fair to moderate (κ=0.35–0.49). Reliability of posterior wall structure palpation (firm/soft) was slight (κ=0.01), and posterior wall bulging (yes/no) fair (κ=0.29). Reliability for abdominal resistance tests varied from fair to substantial (κ=0.35–0.72). In athletes classified with defined inguinal-related groin pain, recognisable injury pain on palpation during scrotal invagination when athletes performed a Valsalva manoeuvre was the most prevalent positive palpation test (79%). Abdominal resistance tests were positive in 21%–49% of these cases.

Conclusion

The interexaminer reliability for clinical examination tests used to classify inguinal-related groin pain in athletes varies from slight to substantial. There is no single perfect clinical examination test.

Trial registration number

NCT03842826.
Doctors’ perceived working conditions, psychological health and patient care: a meta-analysis of longitudinal studies
Authors: Teoh Kevin , Singh Jasmeet , Medisauskaite Asta , Hassard Juliet
Published: January 2023

Objectives

Studies have demonstrated an association between doctors’ perceived working conditions, and their psychological well-being and patient care. However, few have examined inter-relationships among these three domains, and even fewer using longitudinal designs. Using meta-analytical structural equation modelling, we tested longitudinal relationships among doctors’ perceived working conditions, their psychological well-being and patient care. We further tested if doctors’ psychological well-being mediates the relationship between perceived working conditions and patient care.

Methods

We carried out a systematic review using Academic Search Premier, Business Source Premier, PsycInfo, PsycArticles and Medline for the 20-year period between January 2000 and the start of the pandemic (January 2020). We included studies with practising doctors as participants, and that reported a quantifiable bivariate effect size between at least two of the three constructs of interest—perceived working conditions (ie, job demands, job resource), psychological well-being (ie, emotional exhaustion, work engagement) and patient care (ie, clinical care, patient safety). We pooled relationship effect sizes using random-effects meta-analysis, before testing for indirect effects using two-stage structural equation modelling.

Results

Twenty-three samples from 11 countries representing 7275 doctors were meta-analysed. The results indicated that job resources predicted work engagement (ρ=0.18; 95% CI 0.11 to 0.24) and emotional exhaustion (ρ=−0.21; 95% CI −0.31 to −0.11), while job demands predicted emotional exhaustion (ρ=0.27; 95% CI 0.17 to 0.36). Better clinical care was also associated with higher levels of job resources (ρ=0.16; 95% CI 0.04 to 0.29), and lower levels of emotional exhaustion (ρ=−0.21; 95% CI −0.37 to −0.12) and job demands (ρ=−0.27; 95% CI −0.43 to −0.10). Both factors of the work environment were associated with clinical care through doctors’ emotional exhaustion, but there were insufficient studies to test the indirect effects for work engagement or patient safety.

Conclusion

Our results demonstrate the need for a systems perspective to address working conditions to support both doctors’ psychological well-being and patient care. Interventions should target doctors’ job resources as they are more strongly associated with psychological well-being. However, given that job demands were strongly associated with emotional exhaustion, and in turn, clinical care, there is a need to better manage doctors’ workload, conflict and pressure to support the current psychological well-being crises among this occupational group.

PROSPERO registration number

CRD42020189070.
Increased odds of mortality from non-malignant respiratory disease and lung cancer are highest among US coal miners born after 1939
Authors: Almberg Kirsten S , Halldin Cara N , Friedman Lee S , Go Leonard H T , Rose Cecile S , Hall Noemi B , Cohen Robert A
Published: January 2023

Objectives

Coal miners suffer increased mortality from non-malignant respiratory diseases (NMRD), including pneumoconioses and chronic obstructive pulmonary disease, compared with the US population. We characterised mortality trends from NMRD, lung cancer and ischaemic heart disease (IHD) using data from the Federal Black Lung Program, National Coal Workers’ Health Surveillance Program and the National Death Index.

Methods

We compared mortality ORs (MORs) for NMRD, lung cancer and IHD in former US coal miners to US white males. MORs were computed for the study period 1979–2017 by birth cohort (<1920, 1920–1929, 1930–1939, ≥1940), with a subanalysis restricted to Central Appalachia.

Results

The study population totalled 235 550 deceased miners, aged >45 years. Odds of death from NMRD and lung cancer across all miner birth cohorts averaged twice those of US males. In Central Appalachia, MORs significantly increased across birth cohorts. There was an eightfold increase in odds of death from NMRD among miners born after 1940 (MORBC≥19408.25; 95% CI 7.67 to 8.87). Miners with progressive massive fibrosis (PMF) were younger at death than those without PMF (74 vs 78 years; p<0.0001). We observed a pattern of reduced MORs from IHD in coal miners compared with national and regional counterparts.

Conclusion

US coal miners have excess mortality from NMRD and lung cancer compared with total US and Appalachian populations. Mortality is highest in the most recent birth cohorts, perhaps reflecting increased rates of severe pneumoconiosis.
Malignant mesothelioma among US Medicare beneficiaries: incidence, prevalence and therapy, 2016–2019
Authors: Kurth Laura , Mazurek Jacek M , Blackley David J
Published: January 2023

Objectives

Mesothelioma is a rare, aggressive cancer caused by exposure to asbestos fibres. Mesothelioma patients who receive trimodal therapy (chemotherapy, surgical resection and radiation) survive longer than those who receive two or fewer therapy modalities. This study analyses the 2016–2019 Medicare claims data to estimate the burden of malignant mesothelioma and describe therapy patterns (when available) among continuously enrolled fee-for-service (FFS; Medicare parts A and B) beneficiaries.

Methods

We analysed claims and enrolment information from 42 529 117 FFS Medicare beneficiaries using three mesothelioma case definitions (broad, intermediate and narrow) with varying levels of diagnostic requirements. Results are presented as ranges of values for the three definitions.

Results

Among FFS beneficiaries, 8213–19 036 beneficiaries with mesothelioma were identified depending on the case definition. The annual prevalence per 100 000 beneficiaries ranged from 8.8 in 2016 (narrow) to 31.3 in 2019 (broad) and annual incidence per 100 000 beneficiaries ranged from 4.5 in 2019 (narrow) to 12.6 in 2017 (broad). Depending on the mesothelioma case definition, 41.8%–81.5% had available therapy claim information indicating that 7.6%–11.3% received chemotherapy alone, 1.3%–1.5% received radiation alone, and 14.3%–27.0% underwent surgery only, with 4.6%–10.5% receiving all three therapy modalities.

Conclusions

Mesothelioma was a prevalent disease among FFS Medicare beneficiaries during 2016–2019, and a limited proportion of beneficiaries received all three therapy modalities. Medicare data build on findings from cancer registry data to enhance our understanding of the mesothelioma burden and therapy patterns.
Multicentre experience with Optimus balloon-expandable cobalt–chromium stents in congenital heart disease interventions
Authors: Haddad Raymond N , Hascoet Sébastien , Karsenty Clément , Houeijeh Ali , Baruteau Alban-Elouen , Ovaert Caroline , Valdeolmillos Estibaliz , Jalal Zakaria , Bonnet Damien , Malekzadeh-Milani Sophie
Published: January 2023

Objectives

To evaluate bare-metal Optimus and polytetrafluoroethylene (PTFE)-covered Optimus-CVS balloon-expandable, cobalt–chromium, hybrid cell–designed stents in congenital heart disease (CHD) interventions.

Methods

Retrospective multicentre review of patients with CHD receiving Optimus stents. Stent mechanical behaviour, clinical indications and outcomes were assessed.

Results

183 stents (49.2% XXL/15-ZIG, 33.3% XL/12-ZIG, 17.5% L/9-ZIG) were implanted (98.9% success rate, 2.3% serious procedural complication rate) in 170 patients (57.6% men, 64.1% adults), median age 23.6 years (IQR, 15.2–39.2) and weight 63.5 kg (IQR, 47–75.7). Indications were right ventricular outflow tract stand-alone stenting or before revalvulation (62.4%), aortic coarctation treatment (15.3%), Fontan-circuit fenestration closure (12.4%) and miscellaneous (10%). 86/170 (50.6%) patients had PTFE-covered stenting (50% prophylactic). In 86/170 (50.6%) patients with stenotic lesions, median percentage of achieved stent expansion was 93.4% (IQR, 85.5%–97.7%), median gradient decreased from 28 mm Hg (IQR, 19–41) to 5 mm Hg (IQR, 1–9) (p<0.001), median vessel diameters increased from 13 mm (IQR, 7.9–17) to 18.9 mm (IQR, 15.2–22) (p<0.001) and percentage of vessel expansion was 45.2% (IQR, 19.8%–91.3%). In 30/36 (83.3%) patients with graft, median dilation of 2 mm (IQR, 2–5) above nominal diameter was achieved. Median stent shortening was 10.9% (IQR, 6.1–15.1) and was associated only with expansion diameter (OR: 0.66, 95% CI: 0.38 to 0.93). No clinically relevant fracture, stent embolisation or dysfunction occurred on a median follow-up of 9 (IQR, 4–14) months.

Conclusions

Optimus stents are effective tools for transcatheter treatment of simple and complex CHD. Optimus stents’ reliable mechanical behaviour and particular covering design can promote widespread use.
COPD in Africa: risk factors, hospitalisation, readmission and associated outcomes—a systematic review and meta-analysis
Authors: Njoku Chidiamara Maria , Hurst John R , Kinsman Leigh , Balogun Saliu , Obamiro Kehinde
Published: January 2023

Background

This review aims to synthesise available evidence on the prevalence of chronic obstructive pulmonary disease (COPD), associated risk factors, hospitalisations and COPD readmissions in Africa.

Method

Using the Met-Analyses and Systematic Reviews of Observational Studies guideline, electronic databases were searched from inception to 1 October 2021. The quality of studies was assessed using the Newcastle-Ottawa Scale. Evidence from retrieved articles was synthesised, and a random-effect model meta-analysis was conducted. The protocol was registered on PROSPERO.

Results

Thirty-nine studies met the inclusion criteria, with 13 included in the meta-analysis. The prevalence of COPD varied between the Global Initiative for Chronic Obstructive Lung Disease (2%–24%), American Thoracic Society/European Respiratory Society (1%–17%) and Medical Research Council chronic bronchitis (2%–11%) criteria, respectively. Increasing age, wheezing and asthma were consistent risk factors for COPD from studies included in the narrative synthesis. Our meta-analysis indicated that prior tuberculosis ((OR 5.98, 95% CI 4.18 to 8.56), smoking (OR 2.80, 95% CI: 2.19 to 3.59) and use of biomass fuel (OR 1.52, 95% CI: 1.39 to 1.67)) were significant risk factors for COPD. Long-term oxygen therapy (HR 4.97, 95% CI (1.04 to 23.74)) and frequent hospitalisation (≥3 per year) (HR 11.48, 95% CI (1.31 to 100.79)) were risk factors associated with 30-day COPD readmission.

Conclusion

This study not only highlights specific risk factors for COPD risk in Africa but also demonstrates the paucity and absence of research in several countries in a continent with substantial COPD-related mortality. Our findings contribute towards the development of evidence-based clinical guidelines for COPD in Africa.

PROSPERO registration number

CRD42020210581.
Preventing and controlling nonnative species invasions to bend the curve of global freshwater biodiversity loss
Authors: Britton J. Robert , Lynch Abigail J. , Bardal Helge , Bradbeer Stephanie J. , Coetzee Julie A. , Coughlan Neil E. , Dalu Tatenda , Tricarico Elena , Gallardo Belinda , Lintermans Mark , Lucy Frances , Liu Chunlong , Olden Julian D. , Raghavan Rajeev , Pritchard Eleri G.
Published: January 2023

The Emergency Recovery Plan for freshwater biodiversity recognizes that addressing nonnative species is one of six principal actions needed to bend the curve in freshwater biodiversity loss. This is because introduction rates of nonnative species continue to accelerate globally and where these species develop invasive populations, they can have severe impacts on freshwater biodiversity. The most effective management measure to protect freshwater biodiversity is to prevent introductions of nonnative species. Should a nonnative species be introduced, however, then its early detection and the implementation of rapid reaction measures can avoid it establishing and dispersing. If these measures are unsuccessful and the species becomes invasive, then control and containment measures can minimize its further spread and impact. Minimizing further spread and impact includes control methods to reduce invader abundance and containment methods such as screening of invaded sites and strict biosecurity to avoid the invader dispersing to neighbouring basins. These management actions have benefitted from developments in invasion risk assessment that can prioritize species according to their invasion risk and, for species already invasive, ensure that management actions are commensurate with assessed risk. The successful management of freshwater nonnative species still requires the overcoming of some implementation challenges, including nonnative species often being a symptom of degraded habitats rather than the main driver of ecological change, and eradication methods often being nonspecies specific. Given the multiple anthropogenic stressors in freshwaters, nonnative species management must work with other restoration strategies if it is to deliver the Emergency Recovery Plan for freshwater biodiversity.
On convective heat and mass transport of radiative double diffusive Williamson hybrid nanofluid by a Riga surface
Authors: Faisal Muhammad , Mabood F. , Asogwa K. K. , Badruddin I. A.
Published: January 2023

Convective heat and mass transport of radiative Williamson hybrid [Formula: see text] nanofluid (NF) by a Riga surface with the novel features of Cattaneo–Christov double-diffusion has been investigated. Thermal contributions of internal heat mechanism and Arrhenius energy in Darcy–Forchheimer medium have also been incorporated in the modeling. Mathematical modeling has been completed by using suitable mathematical expressions for thermophysical features of hybrid nanofluid (HNF). Transport partial differential equations (PDEs) have been transformed into ordinary differential equations (ODEs) by means of similarity variables. Numerical approximation of the transformed system has been obtained by using shooting-based Runge–Kutta–Fehlberg approach. Results have been presented through various graphs and discussed physically in detail. Solution is validated for limited cases. Concentration of the hybrid mixture is reduced for progressive concentration-relaxation parameter. Temperature is alleviated for developing thermal-relaxation parameter. Nusselt number is observed to be higher for Williamson HNF than simple ordinary NF.
Equivariant annular Khovanov homology
Authors: Akhmechet Rostislav
Published: January 2023

We construct an equivariant version of annular Khovanov homology via the Frobenius algebra associated with [Formula: see text]-equivariant cohomology of [Formula: see text]. Motivated by the relationship between the Temperley–Lieb algebra and annular Khovanov homology, we also introduce an equivariant analog of the Temperley–Lieb algebra.
Spectral Collocation Method for Stochastic Differential Equations Driven by Fractional Brownian Motion
Authors: He Jie , Xing Zhuo , Guo Qian
Published: January 2023

In this paper, a spectral collocation method is developed to numerically approximate a class of stochastic differential equations driven by the fractional Brownian motion. The convergence of the proposed method is proved. Numerical simulations are conducted to illustrate the performance of the proposed method in different cases.
Polynomial automorphisms of a generalized extraspecial ℚ-group and its extension
Authors: Xu Tao
Published: January 2023

Let [Formula: see text] be the direct product of a generalized extraspecial [Formula: see text]-group and finitely many copies of [Formula: see text], where [Formula: see text] is a set of primes. It is proved that every polynomial automorphism of [Formula: see text] is an inner automorphism. As an application of this result, the structure of the group generated by all polynomial automorphisms of an extension of [Formula: see text] by a direct sum of finitely many copies of [Formula: see text] is determined.
Structural, Ferroelectric and Magnetic Properties of NiTiO3–CoTiO3 Solid Solutions Synthesized by Sol–Gel Method
Authors: Bac Luong Huu , Phuong Nguyen Thanh , Kim Thoa Do Thi , Tuan Nguyen Hoang , Dung Dang Duc , Diem Ngoc Tran Vu , Hung Pham Phi
Published: January 2023

The Ni[Formula: see text]CoxTiO3[Formula: see text] solid solution powders were prepared by an aqueous sol–gel method. The structural, optical, magnetic and ferroelectric properties of NiTiO3 were investigated by X-ray diffraction, scanning electron microscope, UV–Vis absorption, vibration samples magnetometer and ferroelectric test system. The X-ray diffraction analysis revealed that prepared materials were in a single phase with rhombohedral structure with [Formula: see text] up to 1. The increasing Co content resulted in decreasing of tolerance factor and increasing of the lattice constant. The crystalline size increased with an increase of Co content. The optical bandgap value of solid solution increased from 2.23[Formula: see text]eV for NiTiO3 to 2.36[Formula: see text]eV for CoTiO3. The magnetic hysteresis loop results indicate that all samples showed paramagnetic state at room temperature. A correlation between magnetization values and composition of the materials was observed with magnetization values which increased with increasing of CoTiO3 content in solid solution. Ferroelectric polarization analysis showed that the polarization of the Ni[Formula: see text]CoxTiO3 solid solution depended on x value and reached the maximum with [Formula: see text].
RiRPSSP: A unified deep learning method for prediction of regular and irregular protein secondary structures
Authors: Sofi Mukhtar Ahmad , Wani M. Arif
Published: January 2023

Protein secondary structure prediction (PSSP) is an important and challenging task in protein bioinformatics. Protein secondary structures (SSs) are categorized in regular and irregular structure classes. Regular SSs, representing nearly 50% of amino acids consist of helices and sheets, whereas the remaining amino acids represent irregular SSs. [Formula: see text]-turns and [Formula: see text]-turns are the most abundant irregular SSs present in proteins. Existing methods are well developed for separate prediction of regular and irregular SSs. However, for more comprehensive PSSP, it is essential to develop a uniform model to predict all types of SSs simultaneously. In this work, using a novel dataset comprising dictionary of secondary structure of protein (DSSP)-based SSs and PROMOTIF-based [Formula: see text]-turns and [Formula: see text]-turns, we propose a unified deep learning model consisting of convolutional neural networks (CNNs) and long short-term memory networks (LSTMs) for simultaneous prediction of regular and irregular SSs. To the best of our knowledge, this is the first study in PSSP covering both regular and irregular structures. The protein sequences in our constructed datasets, RiR6069 and RiR513, have been borrowed from benchmark CB6133 and CB513 datasets, respectively. The results are indicative of increased PSSP accuracy.
Unsteady MHD Flow of Casson Fluid Past Vertical Surface Using Laplace Transform Solution
Authors: Ali Farhan , Zaib A. , Khalid M. , Padmavathi T. , Hemalatha B.
Published: January 2023

The study explores the velocity of Casson fluid that is time-independent over an exponentially infinite isotherm vertical permeable sheet. The impact of magnetohydrodynamic (MHD) with Casson flow over the permeability sheet is examined. In contrast, thermal radiation and heat sink parameters have been incorporated. This study’s primary goal is to determine the significance of thermal radiation on Casson flow with MHD using an analytical solution over a permeable sheet. The flow of the fluid occurs above the sheet when [Formula: see text] is greater than zero, and the sheet extends far away in the [Formula: see text]-direction. The model of governing equations is reduced by applying a suitable set of dimensionless parameters. These dimensionless systems of equations are solved through the Laplace transformation method. The impacts of various variables over velocity, temperature, concentration, skin friction, and Nuseelt number are scrutinized. These variables contain magnetic field [Formula: see text], Casson fluid parameter [Formula: see text], Ghroshof number [Formula: see text], modified Grashof number [Formula: see text], Prandtl number [Formula: see text], thermal radiation [Formula: see text] and Scimdth number [Formula: see text]. These plots are sketched for the considerable magnitude of these variables through the Mathematica Software, and these plots are discussed in detail. Results show that the increasing value of [Formula: see text] reduces the fluid velocity but velocity of fluid is enhanced with larger values of [Formula: see text], [Formula: see text] and [Formula: see text]. The impact of Skin friction and Nusselt number is elaborated by tabular outlined.
DRG-Keyboard
Authors: Liang Chen , Hsia Chi , Yu Chun , Yan Yukang , Wang Yuntao , Shi Yuanchun
Published: January 2023

We present DRG-Keyboard, a gesture keyboard enabled by dual IMU rings, allowing the user to swipe the thumb on the index fingertip to perform word gesture typing as if typing on a miniature QWERTY keyboard. With dual IMUs attached to the user's thumb and index finger, DRG-Keyboard can 1) measure the relative attitude while mapping it to the 2D fingertip coordinates and 2) detect the thumb's touch-down and touch-up events combining the relative attitude data and the synchronous frequency domain data, based on which a fingertip gesture keyboard can be implemented. To understand users typing behavior on the index fingertip with DRG-Keyboard, we collected and analyzed user data in two typing manners. Based on the statistics of the gesture data, we enhanced the elastic matching algorithm with rigid pruning and distance measurement transform. The user study showed DRG-Keyboard achieved an input speed of 12.9 WPM (68.3% of their gesture typing speed on the smartphone) for all participants. The appending study also demonstrated the superiority of DRG-Keyboard for better form factors and wider usage scenarios. To sum up, DRG-Keyboard not only achieves good text entry speed merely on a tiny fingertip input surface, but is also well accepted by the participants for the input subtleness, accuracy, good haptic feedback, and availability.
Designing Reflective Derived Metrics for Fitness Trackers
Authors: Bentvelzen Marit , Niess Jasmin , Woźniak Paweł W.
Published: January 2023

Personal tracking devices are equipped with more and more sensors and offer an ever-increasing level of accuracy. Yet, this comes at the cost of increased complexity. To deal with that problem, fitness trackers use derived metrics---scores calculated based on sensor data, e.g. a stress score. This means that part of the agency in interpreting health data is transferred from the user to the tracker. In this paper, we investigate the consequences of that transition and study how derived metrics can be designed to offer an optimal personal informatics experience. We conducted an online survey and a series of interviews which examined a health score (a hypothetical derived metric) at three levels of abstraction. We found that the medium abstraction level led to the highest level of reflection. Further, we determined that presenting the metric without contextual information led to decreased transparency and meaning. Our work contributes guidelines for designing effective derived metrics.
EarSpiro
Authors: Xie Wentao , Hu Qingyong , Zhang Jin , Zhang Qian
Published: January 2023

Spirometry is the gold standard for evaluating lung functions. Recent research has proposed that mobile devices can measure lung function indices cost-efficiently. However, these designs fall short in two aspects. First, they cannot provide the flow-volume (F-V) curve, which is more informative than lung function indices. Secondly, these solutions lack inspiratory measurement, which is sensitive to lung diseases such as variable extrathoracic obstruction. In this paper, we present EarSpiro, an earphone-based solution that interprets the recorded airflow sound during a spirometry test into an F-V curve, including both the expiratory and inspiratory measurements. EarSpiro leverages a convolutional neural network (CNN) and a recurrent neural network (RNN) to capture the complex correlation between airflow sound and airflow speed. Meanwhile, EarSpiro adopts a clustering-based segmentation algorithm to track the weak inspiratory signals from the raw audio recording to enable inspiratory measurement. We also enable EarSpiro with daily mouthpiece-like objects such as a funnel using transfer learning and a decoder network with the help of only a few true lung function indices from the user. Extensive experiments with 60 subjects show that EarSpiro achieves mean errors of 0.20L/s and 0.42L/s for expiratory and inspiratory flow rate estimation, and 0.61L/s and 0.83L/s for expiratory and inspiratory F-V curve estimation. The mean correlation coefficient between the estimated F-V curve and the true one is 0.94. The mean estimation error for four common lung function indices is 7.3%.
GLOBEM
Authors: Xu Xuhai , Liu Xin , Zhang Han , Wang Weichen , Nepal Subigya , Sefidgar Yasaman , Seo Woosuk , Kuehn Kevin S. , Huckins Jeremy F. , Morris Margaret E. , Nurius Paula S. , Riskin Eve A. , Patel Shwetak , Althoff Tim , Campbell Andrew , Dey Anind K. , Mankoff Jennifer
Published: January 2023

There is a growing body of research revealing that longitudinal passive sensing data from smartphones and wearable devices can capture daily behavior signals for human behavior modeling, such as depression detection. Most prior studies build and evaluate machine learning models using data collected from a single population. However, to ensure that a behavior model can work for a larger group of users, its generalizability needs to be verified on multiple datasets from different populations. We present the first work evaluating cross-dataset generalizability of longitudinal behavior models, using depression detection as an application. We collect multiple longitudinal passive mobile sensing datasets with over 500 users from two institutes over a two-year span, leading to four institute-year datasets. Using the datasets, we closely re-implement and evaluated nine prior depression detection algorithms. Our experiment reveals the lack of model generalizability of these methods. We also implement eight recently popular domain generalization algorithms from the machine learning community. Our results indicate that these methods also do not generalize well on our datasets, with barely any advantage over the naive baseline of guessing the majority. We then present two new algorithms with better generalizability. Our new algorithm, Reorder, significantly and consistently outperforms existing methods on most cross-dataset generalization setups. However, the overall advantage is incremental and still has great room for improvement. Our analysis reveals that the individual differences (both within and between populations) may play the most important role in the cross-dataset generalization challenge. Finally, we provide an open-source benchmark platform GLOBEM- short for Generalization of Longitudinal BEhavior Modeling - to consolidate all 19 algorithms. GLOBEM can support researchers in using, developing, and evaluating different longitudinal behavior modeling methods. We call for researchers' attention to model generalizability evaluation for future longitudinal human behavior modeling studies.
Embracing Consumer-level UWB-equipped Devices for Fine-grained Wireless Sensing
Authors: Zhang Fusang , Chang Zhaoxin , Xiong Jie , Ma Junqi , Ni Jiazhi , Zhang Wenbo , Jin Beihong , Zhang Daqing
Published: January 2023

RF sensing has been actively exploited in the past few years to enable novel IoT applications. Among different wireless technologies, WiFi-based sensing is most popular owing to the pervasiveness of WiFi infrastructure. However, one critical issue associated with WiFi sensing is that the information required for sensing can not be obtained from consumer-level devices such as smartphones or smart watches. The commonly-seen WiFi devices in our everyday lives actually can not be utilized for sensing. Instead, dedicated hardware with a specific WiFi card (e.g., Intel 5300) needs to be used for WiFi sensing. This paper involves Ultra-Wideband (UWB) into the ecosystem of RF sensing and makes RF sensing work on consumer-level hardware such as smartphones and smart watches for the first time. We propose a series of methods to realize UWB sensing on consumer-level electronics without any hardware modification. By leveraging fine-grained human respiration monitoring as the application example, we demonstrate that the achieved performance on consumer-level electronics is comparable to that achieved using dedicated UWB hardware. We show that UWB sensing hosted on consumer-level electronics is able to achieve fine granularity, robustness against interference and also multi-target sensing, pushing RF sensing one step towards real-life adoption.
SleepMore
Authors: Zakaria Camellia , Yilmaz Gizem , Mammen Priyanka Mary , Chee Michael , Shenoy Prashant , Balan Rajesh
Published: January 2023

The availability of commercial wearable trackers equipped with features to monitor sleep duration and quality has enabled more useful sleep health monitoring applications and analyses. However, much research has reported the challenge of long-term user retention in sleep monitoring through these modalities. Since modern Internet users own multiple mobile devices, our work explores the possibility of employing ubiquitous mobile devices and passive WiFi sensing techniques to predict sleep duration as the fundamental measure for complementing long-term sleep monitoring initiatives. In this paper, we propose SleepMore, an accurate and easy-to-deploy sleep-tracking approach based on machine learning over the user's WiFi network activity. It first employs a semi-personalized random forest model with an infinitesimal jackknife variance estimation method to classify a user's network activity behavior into sleep and awake states per minute granularity. Through a moving average technique, the system uses these state sequences to estimate the user's nocturnal sleep period and its uncertainty rate. Uncertainty quantification enables SleepMore to overcome the impact of noisy WiFi data that can yield large prediction errors. We validate SleepMore using data from a month-long user study involving 46 college students and draw comparisons with the Oura Ring wearable. Beyond the college campus, we evaluate SleepMore on non-student users of different housing profiles. Our results demonstrate that SleepMore produces statistically indistinguishable sleep statistics from the Oura ring baseline for predictions made within a 5% uncertainty rate. These errors range between 15-28 minutes for determining sleep time and 7-29 minutes for determining wake time, proving statistically significant improvements over prior work. Our in-depth analysis explains the sources of errors.
ECG-grained Cardiac Monitoring Using UWB Signals
Authors: Wang Zhi , Jin Beihong , Li Siheng , Zhang Fusang , Zhang Wenbo
Published: January 2023

With the development of wireless sensing, researchers have proposed many contactless vital sign monitoring systems, which can be used to monitor respiration rates, heart rates, cardiac cycles and etc. However, these vital signs are ones of coarse granularity, so they are less helpful in the diagnosis of cardiovascular diseases (CVDs). Considering that electrocardiogram (ECG) is an important evidence base for the diagnoses of CVDs, we propose to generate ECGs from ultra-wideband (UWB) signals in a contactless manner as a fine-grained cardiac monitoring solution. Specifically, we analyze the properties of UWB signals containing heartbeats and respiration, and design two complementary heartbeat signal restoration methods to perfectly recover heartbeat signal variation. To establish the mapping between the mechanical activity of the heart sensed by UWB devices and the electrical activity of the heart recorded in ECGs, we construct a conditional generative adversarial network to encode the mapping between mechanical activity and electrical activity and propose a contrastive learning strategy to reduce the interference from noise in UWB signals. We build the corresponding cardiac monitoring system named RF-ECG and conduct extensive experiments using about 120,000 heartbeats from more than 40 participants. The experimental results show that the ECGs generated by RF-ECG have good performance in both ECG intervals and morphology compared with the ground truth. Moreover, diseases such as tachycardia/bradycardia, sinus arrhythmia, and premature contractions can be diagnosed from the ECGs generated by our RF-ECG.
C-Cube
Authors: He Shiyue , Ma Wenyuan , Dong Huixin , Xiao Lixia , Jiang Tao
Published: January 2023

Recent innovations significantly advance the communication capabilities of backscatter networks, while energy harvesting remains the bottleneck of these backscatters. To tackle this problem, existing studies explore distributed beamforming techniques to beam enhanced energy for a battery-free tag. However, they cannot concurrently transfer high-density power to multiple tags since the system is unable to estimate accurate channel state information (CSI). In this paper, we argue that by deploying a lightweight beamforming helper, we can push the limit of CSI estimation with negligible overhead on the tag. The big gap between the wireless charging threshold and the CSI estimation sensitivity can provide stable estimation result of CSI for the charging system even the signal experiences double fading. On this basis, we propose C-Cube, a concurrent charging system for backscatter networks. C-Cube employs distributed beamforming with the help of CSI to indicate the phase alignment process. To bring it into practice, we design a cold start scheme to activate tags by transmitting a distributed orthogonal frequency (DOF) signal. Moreover, to ensure all tags' CSIs have been successfully received, a spatial-based CSI classifier is explored in C-Cube. We further align the beamforming phase to optimize a novel metric called relative power, instead of the received power metric. The new metric can eliminate the impact of the unknown tag-to-helper channel. We implement our system with USRP/GNURadio platform and customized tags in a real environment. C-Cube can achieve the same coverage as the state-of-the-art and reduce the charge time by 44.1% and 30.2%.
Naturalistic E-Scooter Maneuver Recognition with Federated Contrastive Rider Interaction Learning
Authors: Tabatabaie Mahan , He Suining
Published: January 2023

Smart micromobility, particularly the electric (e)-scooters, has emerged as an important ubiquitous mobility option that has proliferated within and across many cities in North America and Europe. Due to the fast speed (say, ~15km/h) and ease of maneuvering, understanding how the micromobility rider interacts with the scooter becomes essential for the e-scooter manufacturers, e-scooter sharing operators, and rider communities in promoting riding safety and relevant policy or regulations.

In this paper, we propose FCRIL, a novel Federated maneuver identification and Contrastive e-scooter Rider Interaction Learning system. FCRIL aims at: (i) understanding, learning, and identifying the e-scooter rider interaction behaviors during naturalistic riding (NR) experience (without constraints on the data collection settings); and (ii) providing a novel federated maneuver learning model training and contrastive identification design for our proposed rider interaction learning (RIL). Towards the prototype and case studies of FCRIL, we have harvested an NR behavior dataset based on the inertial measurement units (IMUs), e.g., accelerometer and gyroscope, from the ubiquitous smartphones/embedded IoT devices attached to the e-scooters. Based on the harvested IMU sensor data, we have conducted extensive data analytics to derive the relevant rider maneuver patterns, including time series, spectrogram, and other statistical features, for the RIL model designs. We have designed a contrastive RIL network which takes in these maneuver features with class-to-class differentiation for comprehensive RIL and enhanced identification accuracy. Furthermore, to enhance the dynamic model training efficiency and coping with the emerging micromobility rider data privacy concerns, we have designed a novel asynchronous federated maneuver learning module, which asynchronously takes in multiple sets of model gradients (e.g., based on the IMU data from the riders' smartphones) for dynamic RIL model training and communication overhead reduction. We have conducted extensive experimental studies with different smartphone models and stand-alone IMU sensors on the e-scooters. Our experimental results have demonstrated the accuracy and effectiveness of FCRIL in learning and recognizing the e-scooter rider maneuvers.
A Type-Based Approach to Divide-and-Conquer Recursion in Coq
Authors: Abreu Pedro , Delaware Benjamin , Hubers Alex , Jenkins Christa , Morris J. Garrett , Stump Aaron
Published: January 2023

This paper proposes a new approach to writing and verifying divide-and-conquer programs in Coq. Extending the rich line of previous work on algebraic approaches to recursion schemes, we present an algebraic approach to divide-and-conquer recursion: recursions are represented as a form of algebra, and from outer recursions, one may initiate inner recursions that can construct data upon which the outer recursions may legally recurse. Termination is enforced entirely by the typing discipline of our recursion schemes. Despite this, our approach requires little from the underlying type system, and can be implemented in System
F
ω
plus a limited form of positive-recursive types. Our implementation of the method in Coq does not rely on structural recursion or on dependent types. The method is demonstrated on several examples, including mergesort, quicksort, Harper’s regular-expression matcher, and others. An indexed version is also derived, implementing a form of divide-and-conquer induction that can be used to reason about functions defined via our method.
From SMT to ASP: Solver-Based Approaches to Solving Datalog Synthesis-as-Rule-Selection Problems
Authors: Bembenek Aaron , Greenberg Michael , Chong Stephen
Published: January 2023

Given a set of candidate Datalog rules, the Datalog synthesis-as-rule-selection problem chooses a subset of these rules that satisfies a specification (such as an input-output example). Building off prior work using counterexample-guided inductive synthesis, we present a progression of three solver-based approaches for solving Datalog synthesis-as-rule-selection problems. Two of our approaches offer some advantages over existing approaches, and can be used more generally to solve arbitrary SMT formulas containing Datalog predicates; the third—an encoding into standard, off-the-shelf answer set programming (ASP)—leads to significant speedups (∼ 9× geomean) over the state of the art while synthesizing higher quality programs.

Our progression of solutions explores the space of interactions between SAT/SMT and Datalog, identifying ASP as a promising tool for working with and reasoning about Datalog. Along the way, we identify Datalog programs as monotonic SMT theories, which enjoy particularly efficient interactions in SMT; our plugins for popular SMT solvers make it easy to load an arbitrary Datalog program into the SMT solver as a custom monotonic theory. Finally, we evaluate our approaches using multiple underlying solvers to provide a more thorough and nuanced comparison against the current state of the art.