bluuebunny/crossref_metadata_2025 huggingface dataset:
Exploring symptoms perception and barriers to medication adherence among Thai Muslim patients with non-communicable diseases in a rural community in southern Thailand: a mixed-methods study
Authors: Buathong Napakkawat , Naruephai Surawut , Wanichanon Worawit , Rodkitvitthaya Kananas , Thananinkul Peeraphol , Jankaew Napat , Wessamanon Phisit , Khaotrakul Samatchaya , Boonmak Ratthakorn , Choo-eard Nichamon , Nintap Thanakrit , Sarakitphan Teera , Kaewchuay Paweeorn , Naruephai Kittiya , Chaison Monchai
Published: December 2024

Objectives

This study aimed to explore the prevalence of medication non-adherence and influence of symptom perception and various barriers on medication adherence among Thai Muslim patients in a rural subdistrict of southern Thailand.

Design

Explanatory sequential mixed-methods approach.

Setting

A rural community in southern Thailand.

Methods

Data collection spanned from March to December 2023. In the quantitative phase, 138 Muslim patients diagnosed with non-communicable diseases were enrolled, and their medication adherence and associated factors were assessed. In the qualitative phase, 22 participants were selected for in-depth interviews, and their symptom perceptions and the obstacles they faced in adhering to medication were explored. A focus group discussion involving 10 healthcare workers from a subdistrict health-promoting hospital was conducted to gain insights into healthcare providers’ perspectives on patients’ perceptions of symptoms and barriers to medication adherence.

Outcome measures

Medication non-adherence was assessed, and the influence of symptom perception and various barriers on medication adherence was evaluated

Results

The prevalence of medication non-adherence in the study sample was 75.36%. The following factors were significantly associated with medication non-adherence: occupation (farmer) (adjusted OR=3.93; 95% CI 1.04 to 12.64), lack of recommendations on adjusting medication schedules/dosages during Ramadan (adjusted OR=2.65; 95% CI 1.06 to 6.61) and patients’ perception of no symptoms (adjusted OR=3.72; 95% CI 1.23 to 11.25). The qualitative analysis highlighted patient-related issues, such as lack of symptom perception, limited health literacy regarding disease information and treatment and personal reasons for non-adherence (eg, forgetfulness, occupational constraints and transportation challenges for medical appointments). Additionally, healthcare system-related factors, patient–doctor relationships and communication gaps in medication management during Ramadan were identified as factors influencing medication non-adherence.

Conclusions

To improve adherence, healthcare providers should prioritise fostering positive patient–provider relationships and promoting patient care through enhanced health literacy initiatives.
Engaging stakeholders in Non-communicable diseases (NCDs) Implementation Research in low- and middle-income countries (LMICs): a scoping review protocol
Authors: Pedro Mariano Joaquim Creyghton , Covane Arlindo , Emmanuel Paul
Published: December 2024

Introduction

Non-communicable diseases (NCDs) present a significant health challenge globally, especially in low- and middle-income countries (LMICs). Effective Implementation Research (IR) is vital in addressing this challenge, with stakeholder engagement playing a crucial role. However, the landscape of stakeholder engagement in NCD IR within LMICs faces unique challenges, including resource constraints and power imbalances. Despite these challenges, stakeholder engagement offers substantial benefits, including improved research relevance and sustainability of interventions.

Methods and analysis

This scoping review aims to comprehensively describe the current practices of stakeholder engagement in NCD IR within LMICs. Employing a two-stage screening process and a thematic synthesis approach based on the International Association for Public Participation Spectrum of Public Participation, the review will analyse studies meeting predefined eligibility criteria. A rigorous search strategy will be implemented across identified electronic databases and grey literature sources, including published studies from 2011 to present. Data will be charted using a standardised form, and information regarding study characteristics, NCD focus, LMIC context, stakeholder engagement method and reported outcomes/findings will be collected. This scoping review will follow a standard protocol adhering to the methodological framework outlined by Arksey and O'Malley to comprehensively map existing evidence on stakeholder engagement in NCD IR within LMICs.

Ethics and dissemination

Ethical considerations involve respecting original authors, maintaining integrity and transparency, managing data ethically and disclosing conflicts of interest. Dissemination will occur through publication in peer-reviewed journals, conference presentations, open-access repositories, policy briefs, stakeholder engagement activities and social media platforms.

Registration

This scoping review protocol is registered on Open Science Framework, with the Digital Object Identifier 10.17605/OSF.IO/ACQ52, ensuring transparency and accountability in the research process.
Risk factors of large for gestational age among pregnant women with gestational diabetes mellitus: a protocol for systematic review and meta-analysis
Authors: Liang Yingni , Dong Weilei , Shangguan Fuliang , Li Hanbing , Yu Huixi , Shen Jiayu , Su Yinhua , Li Zhongyu
Published: December 2024

Introduction

Women with gestational diabetes mellitus (GDM) are more likely to give birth to large for gestational age (LGA) infants, due to abnormalities in glucose metabolism during pregnancy. Although previous studies have explored the risk factors for LGA delivery in GDM women, the results are quite different and still lack of unified understanding.

Objective

To explore the elements linked to LGA delivery in GDM women, and thus provide a reference for medical staff to formulate relevant clinical interventions.

Methods and analysis

Systematic search of seven electronic databases (PubMed, Scopus, Cochrane Library, Web of Science, EMBASE, OVID and CINAHL) will be undertaken between the inception of the database to 1 August 2024. Quantitative studies published in English and focused on the risk factors for LGA delivery in GDM women will be included. Two researchers will independently screen the literature and any disagreements will be resolved by a third-party researcher. Joanna Briggs’s Institutional Critical Appraisal Tools will be used for the quality assessment of included studies. RevMan V.5.4 software will be used for data processing and summarising. To ensure the reliability and stability of the results, Q test and I2test will be used to identify the heterogeneity between studies, while subgroup analysis and sensitivity analysis will be performed based on study quality.

Ethics and dissemination

This systematic review and meta-analysis will be based on published literature, and the findings will be published in a peer-reviewed journal and presented at major conferences focused on clinical nursing.

PROSPERO registration number

CRD42024559013.
Intersecting social relations of care: a protocol for an ethnographic and interview study with South Asian people ageing in place with dementia
Authors: Gibson Kate , Robinson Louise , Bains Manpreet , Samsi Kritika , Cîrstea Ana-Maria , Brittain Katie
Published: December 2024

Introduction

People living at home with dementia are often cared for by family members, especially those from minority ethnic groups. Many people living with dementia from minority ethnic communities face barriers to accessing formal care. However, there is a paucity of dementia research, which foregrounds diversity within minority ethnic populations. This study, conducted between July 2024 and August 2026, will explore the diverse care experiences of South Asian people living with dementia. Conducted across four sites (Newcastle, Nottingham, Birmingham and London), it aims to understand how inequalities related to ethnicity intersect with other factors (eg, gender, age and class) to shape the dementia care experiences of people living in South Asian communities and apply this learning to explore how public policy and care systems could be improved to reduce health and social inequalities.

Methods and analysis

In Newcastle, ethnographic research will be undertaken with up to 20 people living with dementia (or with memory concerns) in South Asian communities for a period of 12 months. The lengthy research period will enable a deep understanding about how experiences change as dementia progresses over time. In Nottingham and Birmingham, semi-structured interviews and/or focus groups will be conducted with up to 30 people living with dementia (or with memory concerns) in South Asian communities. This will enhance the data generated via the ethnographic research. Analysis will follow the principles of reflexive thematic analysis and will involve identifying themes and synthesising and theorising the data. Following this, findings will be reflected upon in 4–6 task groups convened in London, Nottingham and Newcastle with practitioners from health and social care, voluntary organisations or faith groups involved in dementia care. Task groups will focus on developing practical goals based on the research findings.

Ethics and dissemination

Ethical approval for this study has been granted by Newcastle University Faculty of Medical Sciences Ethics Committee (Reference: 2773/43721). Findings will be disseminated to academics, practitioners, policymakers and members of the public via a range of channels including conferences, peer-reviewed publications, lay reports, leaflets and non-written formats such as animated videos.
Impact of exposure to extreme heat events during pregnancy on the incidence of congenital heart disease in offspring: a meta-analysis
Authors: Krishnakumar Malavika , Hari Aparna , Gutjahr Georg , Bendapudi Perraju , Ahamed Hisham , Prabhakaran Poornima , Kumar Raman Krishna , Raj Manu
Published: December 2024

Background

The aetiology of congenital heart disease (CHD) is multifactorial. Environmental risk factors have emerged as an important modifiable determinant of several congenital cardiac conditions. Previous studies have shown a strong relationship between CHD and air pollution. Much less is known about the influence of ambient temperature on CHD. The primary objective of this meta-analysis was to examine the association between exposure to extreme heat events (EHE) during pregnancy and CHD in the offspring.

Methods

comprehensive literature search was conducted using electronic databases such as Scopus and PubMed, along with a review of secondary references. This process yielded eight studies that met the inclusion criteria: four from the USA, two from China, one from Israel and one from Canada. The risk of bias was assessed using the Newcastle Ottawa scale. Mixed-effect regression was used to pool the estimates of individual studies. Heterogeneity was measured by I2. Results were visualised by a forest plot, a Baujat plot and an albatross plot. Subgroup analyses were performed for climate zones, exposure definitions and the study region. As a sensitivity analysis, a leave-one-out meta-analysis was performed to assess the robustness of the estimates.

Results

Exposure to EHE during pregnancy increased the risk for CHD in the offspring (OR=1.12, 95% CI 1.04 to 1.34). Studies from the USA observed the smallest effect (OR=1.01, 95% CI 0.91 to 1.13), studies in the continental climate zone observed a slightly larger effect (OR=1.07, 95% CI 0.97 to 1.19), and studies from the temperate climate zone observed the largest effect (OR=1.35, 95% CI 1.23 to 1.48). Subgroup analysis was conducted with respect to exposure, effect definition and region. The residual heterogeneity measures were 88% (exposure), 61% (effect definition) and 38% (Region).

Conclusion

The association between prenatal EHE exposure and future risk of CHD has important implications for pregnant mothers, infant health and health policy. Future studies should explore the additional burden of CHD contributed by current trends in global ambient temperature in other parts of the world.

PROSPERO registration number

CRD42023455934
Alcohol-related injuries from e-scooter and e-bike use in the US (2019–2022): a retrospective study
Authors: Akomaning Edwin , Osei Samuel Prince , Bhagavathula Akshaya Srikanth
Published: December 2024

Background

The use of electric-powered scooters and bikes (e-scooters/bikes) is rising, but little is known about associated injuries and substance use. This study analysed the trends and factors associated with e-scooter/bike-related injuries and alcohol/substance use emergency department (ED) visits from 2019 to 2022.

Methods

A retrospective analysis of US ED visit data from the 2019–2022 National Electronic Injury Surveillance System (NEISS) identified visits for e-scooter/bike-related injuries. NEISS data were collected using stratified, multistage sampling, and the analysis accounted for this complex sampling design. Outcomes included yearly visits, patient demographics, injury details and alcohol/substance use associations. Multivariable logistic regression analysed factors associated with e-bike/scooter-related injury ED visits and alcohol/substance use.

Results

Of 4020 e-scooter/bike injury ED visits, 3700 (weighted estimate 279 990) were e-scooters and 320 (weighted estimate 16 600) were e-bikes. Visits increased three-fold from 2019 (n=22 835) to 2022 (n=65 892). Most of the injuries involved males, with 79.6% of e-scooter injuries and 79.7% of e-bike injuries), aged 18–39 years (51.5% e-scooter, 48.5% e-bike) and non-Hispanic White (34.9% e-scooter, 38.8% e-bike). Alcohol use was reported in 8.6% of e-scooters and 2.5% of e-bike injury-related ED visits. Males had 2.6 times higher odds of alcohol use (OR: 2.61, 95% CI: 1.84 to 3.69) and 2.2 times higher odds of substance use (OR: 2.23, 95% CI: 1.19 to 4.16) associated ED visits, compared with females. Compared with the 18–39-year age group, those aged 10–17 years had 7.5 and 4.1 times higher odds of alcohol and substance use leading to e-scooter and e-bike injury-related ED visits, respectively.

Conclusions

E-scooter injuries are increasing rapidly, especially among younger males, with a three-fold increase from 2019 to 2022. Alcohol and substance use both contribute significantly to morbidity. Strengthening policy and prevention approaches like the use of helmets are warranted to improve e-scooter/bike safety.
Lower Ticagrelor Dosing in the Dual Antiplatelet Regimen for Neurointerventional Procedures
Authors: Mehta Amol , Reddi Preethi , Bose S Javin , Finesilver Joshua , Goldman Daryl , Sembhi Paramjit , De Leacy Reade Andrew , Fifi Johanna T , Mocco J , Yim Benjamin , Majidi Shahram
Published: December 2024

Background

Ticagrelor, a P2Y12 inhibitor, offers a rapid onset and consistent platelet inhibition, making it a viable alternative for dual antiplatelet therapy (DAPT). The optimal ticagrelor dose for neurointerventional procedures, however, remains unclear. We report our experience with ticagrelor 60 mg twice daily plus aspirin 81 mg daily compared with the standard aspirin and clopidogrel regimen for intracranial stenting.

Methods

We conducted a retrospective analysis of a prospectively maintained database, identifying consecutive patients who underwent intracranial stenting for aneurysm treatment or intracranial atherosclerosis. Patients received either ticagrelor 60 mg with aspirin or aspirin with clopidogrel 75 mg daily. Primary outcomes included peri-procedural ischemic and/or hemorrhagic events within 30 days. Secondary outcomes were the median P2Y12 reaction unit and in-stent stenosis rates at 6-month follow-up.

Results

Among 119 patients, 59 received ticagrelor and 60 (50.4%) received clopidogrel. Baseline characteristics including age and gender were comparable between the two groups, although the ticagrelor group had a higher proportion of African-American patients. The majority of patients underwent aneurysm treatment (n=105; 88.23%), while the remainder received stenting for intracranial atherosclerosis (n=14; 11.77%). No ischemic events occurred in either group and intracranial hemorrhage rates were comparable (1.7% in both groups). The median P2Y12 reaction unit was significantly lower in the ticagrelor group (69 vs 126, P<0.001). In-stent stenosis rates were lower with ticagrelor (5% vs 21%).

Conclusion

Ticagrelor 60 mg for DAPT in intracranial stenting is safe and effective. Larger prospective studies may be required to validate these findings.
Treatment trends of systemic lupus erythematosus from 2007 to 2023 in the USA
Authors: Figueroa-Parra Gabriel , Heien Herbert C , Warrington Kenneth J , Shah Nilay D , Crowson Cynthia S , McCoy Rozalina G , Duarte-García Alí
Published: December 2024

Objective

To characterise the changing trends in the pharmacological management of SLE in the USA between 2007 and 2023 as new treatment options emerged.

Methods

In a retrospective cohort study using data from OptumLabs Data Warehouse, we characterised the annual prevalent (ie, all) and incident (ie, new) use of antimalarials, glucocorticoids and immunosuppressive medications among patients with SLE from 2007 to 2023 and assessed for changing trends over time.

Results

We identified 19 122 adults with SLE; they were 51.2 (SD 16.1) years of age, 89% were female, 61.3% were White, 18.5% were Black and 13.1% were Hispanic. The proportion of prevalent users of antimalarials has decreased from 79.4% in 2007 to 77.2% in 2023 (p=0.0055), while the proportion of incident users fluctuated between a lowest 5.8% in 2021 and a highest 8.1% in 2008 (p=0.008). The proportion of prevalent users of glucocorticoids increased from 64.6% in 2007 to 66.7% in 2023 (p=0.0132), as did the proportion of incident users (12.4% in 2007 to 21.7% in 2023; p<0.0001). The use of cyclophosphamide (2.0% in 2007 to 0.4% in 2023, p<0.0001) has decreased; the use of mycophenolate mofetil (7.7% in 2007 to 10.3% in 2023, p<0.0001), rituximab (1.4% in 2007 to 2.1% in 2023, p<0.0001) and belimumab (0.8% in 2011 to 6.1% in 2023, p=0.0001) has increased.

Conclusions

Despite increasing availability of alternative treatment options, patients with SLE in the USA increasingly rely on glucocorticoid-based therapy. Efforts to improve the use of antimalarials and steroid-sparing immunosuppressants are needed.
Comparative study of hypertension, diabetes, dementia and smoking in military veterans and non-veterans: a quantitative study using primary healthcare data
Authors: Finnegan Alan , Salem K
Published: December 2024

Introduction

Primary healthcare (PHC) patient medical records contain Systematised Nomenclature of Medicine-Clinical Terms (SNOMED-CT) that include information regarding diagnosis, demographics and veterans’ status. This study intended to identify, analyse and compare the prevalence of type 2 diabetes, hypertension, dementia and smoking tobacco in veterans and non-veterans, including stratification by age and gender.

Methods

The authors partnered with 13 PHC practices with a population of 137 410 patients. Staff extracted matched veteran and non-veteran SNOMED-CT data from patient medical records; then sent the authors anonymised data in an amalgamated format between October 2023 and January 2024. Patients were from a local community and therefore social and environmental factors would be similar. Submitted information was inputted into an SPSS database 28 for analysis which included descriptive and inferential statistics to indicate statistical significance.

Results

In total, 5458 PHC electronic records were examined comprising 2729 veterans and 2729 demographically matched for age and gender non-veterans. Each group contained 86.4% (N=2359) men and 13.6% (N=370) women. The mean age was 63.8 years (SD 17.7). Rates of hypertension were 20.9% in veterans compared with 17.6% in non-veterans (p=0.002). Type 2 diabetes mellitus was 8.3% in veterans compared with 6.4% in non-veterans (p=0.007). Dementia was 2.1% of veterans compared with 2.5% of non-veterans (p=0.32). Smoking was 11.8% of veterans compared with 10.6% of non-veterans (p=0.16).

Conclusion

These results reveal that veterans were statistically more likely to be diagnosed with hypertension and diabetes. This study should assist in a better understanding of the healthcare needs of the veteran population to potentially inform better patient-centred care. However, the effectiveness of using PHC patient medical records requires increased efforts to improve data quality which needs improved PHC staff knowledge, consistency in SNOMED-CT coding, better veteran medical e-record registration and coding and better data transmission between the Defence Medical Services and PHC.
A hybrid cohesive phase-field numerical method for the stability analysis of rock slopes with discontinuities
Authors: Wang Feiyang , Zhai Wuzhou , Man Jianhong , Huang Hongwei
Published: December 2024

The stability of rock slope is predominantly controlled by the fracture behavior of structural discontinuities, such as joints, faults, and bedding planes. Landslides of rock slopes usually involve concurrent tensile and shear fracture evolution within a continuous-discontinuous medium, occurring along the discontinuities and within rock mass, which poses challenges for accurately and efficiently predicting landslides and determining the factor of safety (FS). To address this issue, a hybrid cohesive phase-field numerical method based on the gravity increase method (GIM) is developed. This approach integrates the cohesive joint model and the unified fracture phase-field method, effectively bridging the scale gap between discontinuity and rock mass. Numerical simulations indicate that the developed hybrid method is validated through physical tests on both discontinuities and rock mass, and achieves computational efficiency comparable to continuum methods. It is worth noting that the critical energy release rate has a more significant effect on the stability of rock slopes than the shear strength. Furthermore, the developed hybrid method accurately captures sliding surfaces and highlights the role of rock bridges in resisting landslides, enabling reliable predictions of FS of rock slopes with persistent discontinuities and non-persistent discontinuities.
Advancing quantum technology workforce: industry insights into qualification and training needs
Authors: Greinert Franziska , Ubben Malte S. , Dogan Ismet N. , Hilfert-Rüppell Dagmar , Müller Rainer
Published: December 2024

The transition of second-generation quantum technologies from a research topic to a topic of industrial relevance has led to a growing number of quantum companies and businesses that are exploring quantum technologies. Examples would include a start-up building a quantum key distribution device, a large company working on integrating a quantum sensing core into a product, or a company providing quantum computing consultancy. They all face different challenges and needs in terms of building their quantum workforce and training in quantum concepts, technologies and how to derive value from them. With the study documented in this paper, we aim to identify these needs and provide a picture of the industry’s requirements in terms of workforce development and (external) training and materials. We discuss, for example, the shortage of engineers and jobs relevant to the quantum industry, the challenge of getting people interested in quantum, and the need for training at different levels and in different formats – from awareness raising and self-learning materials to university courses in quantum systems engineering. The findings are based on 34 semi-structured interviews with industry representatives and a follow-up questionnaire to validate some of the issues raised in the interviews. These results have influenced activities in EU projects, including an update of the European Competence Framework for Quantum Technologies.
Research on the Chinese Characteristics Advanced Apprenticeship Training Model Based on Embedded Neural Network Analysis
Authors: Chen Xiaolong
Published: December 2024

In order to deeply analyze the feasibility and optimization strategies of this model in vocational education, this paper focuses on the application of embedded neural network technology. By comparing with other talent cultivation models, especially delving into the essence of project-based teaching, this paper defines the practical, refined, and entrepreneurial characteristics unique to project-based teaching under modern apprenticeship systems. These characteristics constitute the core competitiveness of the advanced apprenticeship training model. This paper emphasizes the establishment of a quality management system based on standards, rigorous processes, and customized solutions. Embedded neural networks, with their powerful data processing and pattern recognition capabilities, help this paper reveal the significant advantages of this training model in resource integration, personalized teaching, skill inheritance, and market docking.
Research on Low-Carbon Site Selection Decision Model and Algorithm for Green Logistics
Authors: Wang Hui
Published: December 2024

This work proposes a low-carbon site selection decision model and algorithm for green logistics. The focus is to minimize carbon emissions while optimizing the distribution network. With the development of smart shared logistics and increasing environmental awareness, there is an urgent need to tackle issues in urban logistics, including pollution, resource inefficiency, high carbon energy usage, and greenhouse gas emissions. By integrating geographic, environmental, and operational data, the proposed site selection model incorporates multi-objective optimization to balance carbon efficiency with cost-effectiveness in logistics site selection. We employ a hybrid algorithm combining Genetic Algorithm (GA) and Particle Swarm Optimization (PSO) to solve the complex decision-making process. The model is tested using real-world logistics data, and the results demonstrate significant reductions in carbon emissions and transportation costs when compared to conventional logistics site selection methods. Further sensitivity analysis reveals that the model is robust under varying transportation demands and geographic constraints. Also, we highlight the role of green logistics in achieving corporate sustainability goals aligning with global carbon neutrality initiatives. We believe this model offers a practical approach to fostering environmentally responsible supply chains and will contribute to the advancement of sustainable logistics operations, helping organizations make informed, eco-friendly decisions in site selection.
Design of Public Physical Education Curriculum Quality Evaluation System Based on the “5V” Characteristics of Computer Big Data
Authors: Changming Xu
Published: December 2024

In order to improve the teaching effect of public physical education courses to the greatest extent and lay the foundation for the process of teaching reform, this paper puts forward the design of a public physical education course quality evaluation system based on the “5V” characteristics of computer big data. Analyze the characteristics of big data “5V” and study its application in public physical education courses; analyze the action estimation, prior, and update, failure recovery of public physical education course teaching, and get the three-dimensional visual positioning result of public physical education course teaching; collect the upper arm action image, extract the upper arm action image contour feature through edge contour detection, analyze the contour feature error characteristics, obtain the pixel component weighted value of the contour feature, further obtain the fuzzy error value of the upper arm action image contour feature through calculation, and according to the fuzzy error value, the design of public physical education course quality evaluation system is completed. The experimental results show that the average error recognition accuracy of the research method is 99.63%. The class hours are adjusted according to the proportion of disciplines, and the corresponding teaching plan is formulated. The accuracy of recommending internship posts for students is relatively high.
Research on NBA Event Prediction Based on Hybrid Machine Learning Model
Authors: Liu Zhongwei , Guo Jianfeng
Published: December 2024

NBA is one of the top basketball events in the world. It is of great significance to predict NBA events comprehensively and accurately. Therefore, this paper puts forward the research on the prediction of NBA events based on a hybrid machine learning model. Construct a hybrid machine learning model, set the pre-processing flow of NBA event prediction data, solve the probability core cluster of NBA event prediction data, and form a data stream mining matrix of NBA event prediction; based on the integrated learning method in machine learning, according to the principle of constructing the prediction index of NBA events, the prediction index is constructed; based on the deep learning method in machine learning, the weight of target factors is used as a parameter to measure the prediction accuracy, and hierarchical evaluation is carried out to realize the prediction of NBA events. The experimental results show that the research method shows a high goodness of fit in all NBA games, and the predicted results are highly consistent with the actual results, and the predicted results are closer to the real results, with small root mean square error and average absolute error, which has a good prediction effect.
Design of Traditional Inkblot Pattern Plane System Based on Graphics and Visual Perception
Authors: Li Yan , Duan Wenqi
Published: December 2024

In order to improve the graphic design effect of traditional pattern with ink and wash elements, this paper puts forward a graphic and visual perception-based graphic system design scheme of traditional pattern with ink and wash elements. Taking plane space media parameters, creative display patterns, characters and other elements as constraint parameters, this paper constructs a plane design model under traditional pattern fusion ink elements, extracts the graphic and visual perception element feature space structure of plane design graphics under traditional pattern fusion ink elements, and combines the three-dimensional internal structure characteristics of plane design graphics under traditional pattern fusion ink elements to carry out information reorganization. The method of color space color feature decomposition is used to decompose the visual elements of graphic design under traditional pattern fusion ink elements, and the virtual reconstruction model of graphic design under traditional pattern fusion ink elements and RGB-D image of visual perception element is established by the method of image aesthetic and emotional factors fusion. The feature recombination method of converting graphic design into materialized image is used to design the three-dimensional reconstruction model of graphic design under traditional pattern fusion ink elements. The 3D multi-viewpoint tracking and recognition method is adopted to reconstruct the graphic design and visual perception elements under the traditional pattern fusion ink elements, so as to improve the graphic design ability under the traditional pattern fusion ink elements. The simulation results show that this method has good visual expression ability, good graphic design effect, and good visual communication ability of graphic design with traditional pattern and ink elements.
A Survey on Privacy-Preserving Caching at Network Edge: Classification, Solutions, and Challenges
Authors: Zhang Xianzhi , Zhou Yipeng , Wu Di , Sheng Quan Z. , Riaz Shazia , Hu Miao , Xiao Linchang
Published: December 2024

Caching content at the edge network is a popular and effective technique widely deployed to alleviate the burden of network backhaul, shorten service delay, and improve service quality. However, there has been some controversy over privacy violations in caching content at the edge network. On the one hand, the multi-access open edge network provides an ideal entrance or interface for external attackers to obtain private data from edge caches by extracting sensitive information. On the other hand, privacy can be infringed on by curious edge caching providers through caching trace analysis targeting the achievement of better caching performance or higher profits. Therefore, an in-depth understanding of privacy issues in edge caching networks is vital and indispensable for creating a privacy-preserving caching service at the edge network. In this article, we are among the first to fill this gap by examining privacy-preserving techniques for caching content at the edge network. First, we provide an introduction to the background of privacy-preserving edge caching. Next, we summarize the key privacy issues and present a taxonomy for caching at the edge network from the perspective of private information. Additionally, we conduct a retrospective review of the state-of-the-art countermeasures against privacy leakage from content caching at the edge network. Finally, we conclude the survey and envision challenges for future research.
Strict Fibonacci Heaps
Authors: Brodal Gerth Stølting , Lagogiannis George , Tarjan Robert E.
Published: December 2024

We present the
strict Fibonacci heap
, the first pointer-based heap implementation with time bounds matching those of Fibonacci heaps in the worst case. Strict Fibonacci heaps support make-heap, insert, find-min, meld and decrease-key in worst-case

\(O(1)\)

time, and delete and delete-min in worst-case

\(O(\lg n)\)

time, where

\(n\)

is the size of the heap. The data structure uses linear space.

A previous solution achieving the same time bounds in the RAM model made essential use of arrays and extensive use of redundant counter schemes to maintain balance. Our solution uses neither. Our key simplification is to discard the structure of the smaller heap when doing a meld, and to use the pigeonhole principle in place of the redundant counter mechanism to maintain balance.
TENSAI - Practical and Responsible Observability for Data Quality-aware Large-scale Analytics
Authors: Truong Hong-Linh , Nguyen Ngoc Nhu Trang
Published: December 2024

Given a large-scale mobile network with a variety of equipment and radio access network technologies for an approximate 20 million subscribers, there are many types of data that can be used for big data analytics and machine learning (ML) tasks for network operations, monitoring, and optimization. However, a variety of data is measured, collected, and propagated through numerous complex data and software systems. Thus, people, software components, and data-driven operations for big data and ML pipelines face great challenges in dealing with data quality impacts. Data quality related problems occur and are propagated through complex operations involving different types of data, people, software components, and analytics that cannot be solved purely through data quality engineering. This article discusses our TENSAI framework, as a practical and responsible observability for ensuring data quality in such a mobile network. TENSAI focuses on methods of communication, strategy specifications, and data quality engineering for diverse types of data and analytics among different types of operations. TENSAI presents techniques for capturing and communicating causes/effects of data quality problems clearly to all relevant stakeholders, developing data quality-aware adaptation strategies for actions on data that can be integrated into analytics processes, and engineering data quality awareness in software and data pipelines. Thus, TENSAI supports full visibility of data quality problems and impacts among related systems to empower the utilization and adaptation of data analytics for different types of operations. We will illustrate our TENSAI with several real-world data types, pipelines, and cases based on a real-world mobile network.
Exercise as Mitochondrial Medicine: How Does the Exercise Prescription Affect Mitochondrial Adaptations to Training?
Authors: Bishop David J. , Lee Matthew J.-C. , Picard Martin
Published: December 2024

Mitochondria are multifaceted organelles with several life-sustaining functions beyond energy transformation, including cell signaling, calcium homeostasis, hormone synthesis, programmed cell death (apoptosis), and others. A defining aspect of these dynamic organelles is their remarkable plasticity, which allows them to sense, respond, and adapt to various stressors. In particular, it is well-established that the stress of exercise provides a powerful stimulus that can trigger transient or enduring changes to mitochondrial molecular features, activities, integrated functions, behaviors, and cell-dependent mitochondrial phenotypes. Evidence documenting the many beneficial mitochondrial adaptations to exercise has led to the notion of exercise as a mitochondrial medicine. However, as with other medicines, it is important to understand the optimal prescription (i.e., type, dose, frequency, duration). In this review, we build on a systematic biological framework that distinguishes between domains of mitochondrial biology to critically evaluate how different exercise prescription variables influence mitochondrial adaptations to training.
Land and Politics
Authors: Albertus Michael , Klaus Kathleen
Published: December 2024

Human societies and their politics are deeply rooted in the land. Land shapes politics through its material nature and distribution across society, by serving as a mechanism of control and state-building, and by acting as a symbolic site that imbues identity and belonging. That land is inextricably intertwined with politics makes it a crucial driver of a wide range of social, political, and economic outcomes. We explain and survey these rich and complex relationships, focusing on the formation of political preferences and identities, the forms and dynamics of political violence, and the long-term structure of society, ranging from patterns of settlement and dispossession to inequality, state capacity, and economic development and urbanization. Land access, land rights, and land tenure institutions are all implicated in these outcomes. We conclude with reflections on promising research frontiers in the study of land and politics, including climate change, migration, and urbanization.
Human-Centered Design to Enhance Implementation and Impact in Health
Authors: Lyon Aaron R. , Aung Tricia , Bruzios Kathryn E. , Munson Sean
Published: December 2024

Human-centered design (HCD) is an approach that aligns innovation development with the needs of the people and the settings where those innovations will be used. HCD is increasingly being applied across a variety of health domains, most often with the goals of translating research into real-world settings and expanding innovation adoption. This review introduces key HCD concepts, reviews the growth of HCD in public health and its alignment with the complementary field of implementation science, and details four prominent proximal outcomes of design processes: (a) usability, (b) user burden, (c) contextual appropriateness, and (d) engagement. For each outcome, we provide a definition and background, measurement options, and critiques and future directions. We conclude with a series of opportunities and challenges, including an inclusive big tent spanning different design traditions, pathways for enhancing HCD's scientific legitimacy, and explicit promotion of equitable design processes to improve individual, community, and population health.
The QIBA Profile for Dynamic Susceptibility Contrast MRI Quantitative Imaging Biomarkers for Assessing Gliomas
Authors: Shiroishi Mark S. , Erickson Bradley J. , Hu Leland S. , Barboriak Daniel P. , Becerra Lino , Bell Laura C. , Boss Michael A. , Boxerman Jerrold L. , Cen Steven , Cimino Lisa , Fan Zhaoyang , Keenan Kathryn E. , Kirsch John E. , Ameli Nima , Nazemi Sina , Quarles C. Chad , Rosen Mark A. , Rodriguez Luis , Schmainda Kathleen M. , Zahlmann Gudrun , Zhou Yuxiang , Obuchowski Nancy , Wu Ona ,   for the RSNA QIBA Dynamic Susceptibility Contrast MRI Biomarker Committee, Hu Leland S. , Shiroishi Mark S. , Wu Ona , Barboriak Daniel P. , Bell Laura , Boss Michael , Boxerman Jerrold L. , Chakhoyan Ararat , Cimino Lisa , Conte Gian Marco , de Graaf Wolter , Dhakal Kiran , Ellingson Benjamin M. , Emblem Kyrre Eeg , Erickson Bradley J. , Fan Zhaoyang , Kadbi Mo , Keenan Kathryn , Nazemi Sina , Obuchowski Nancy , Quarles Christopher Chad , Rodriguez Luis , Rosen Mark A. , Schmainda Kathleen M. , Zahlmann Gudrun , Zhou Yuxiang
Published: December 2024

The Quantitative Imaging Biomarkers Alliance Profile for dynamic susceptibility contrast (DSC) MRI and its longitudinal claims for the precision of a DSC MRI–derived quantitative imaging biomarker to assess the relative cerebral blood volume changes in gliomas are summarized.
Low-Dose CT Screening in East Asian Women Who Have Never Smoked: Association between Family History of Lung Cancer and Ground-Glass Nodule Prevalence and Growth
Authors: Lee Ji Young , Choi Seung Ho , Kim Hyungjin , Goo Jin Mo , Yoon Soon Ho
Published: December 2024

In East Asian women who had never smoked and who underwent low-dose CT screening, family history of lung cancer (FHLC) was associated with an increased prevalence of persistent and multiple ground-glass nodules (GGNs), including proven adenocarcinomas; FHLC was an independent risk factor for GGN growth over a 10-year period.
Deep learning-based Remaining Useful Life Prediction of Lithium-ion Battery Considering Two-phase Aging Process
Authors: Ma Wenxin , Zhu Haiping , Wu Jun , Zhang Shaowen
Published: December 2024

The aging process of lithium-ion batteries is typically nonlinear, characterized by a knee point that divides it into two distinct phases: a slow aging phase and a rapid aging phase. Predicting the remaining useful life (RUL) in rapid phase is crucial for providing users with timely alerts to replace the battery before its end of life (EOL). A two-stage identification and prediction framework has been proposed to identify the current aging phase of a battery and predict its RUL if it is in the rapid aging phase, requiring data from only the most recent three cycles of the charge process. In the first stage, a 2D-ResNet is constructed for aging phase identification, offering strategies with high accuracy or low risk depending on user requirements. In the second stage, a Gated-ResNet-Attention model is innovatively constructed to filter out unreliable temperature features. The model achieved mean absolute error and root mean square error values of 6.94 and 8.12, respectively. The proposed framework can identify aging process and predict the RUL in rapid aging phase accurately with minimal input requirements. This approach reduces data storage requirements while providing users with sufficient indicative information for proactive battery maintenance.
Characterization of p‐Adic Mixed λ‐Central Bounded Mean Oscillation Space via Commutators of p‐Adic Hardy‐Type Operators
Authors: Sarfraz Naqash , Riaz Muhammad Bilal , Mehmood Sajid , Zaman Mir
Published: December 2024

In this note, we define p‐adic mixed Lebesgue space and mixed λ‐central Morrey‐type spaces and characterize p‐adic mixed λ‐central bounded mean oscillation space via the boundedness of commutators of p‐adic Hardy‐type operators on p‐adic mixed Lebesgue space. Moreover, we also furnish boundedness of commutators of p‐adic Hardy‐type operators generated with p‐adic mixed λ‐central bounded mean oscillation on mixed λ‐central Morrey space.
Nocturnal Light Pollution Synergistically Impairs Glucose Metabolism With Age and Weight in Monkeys
Authors: Wang Shuxing , Cheng Xuange , Liang Zihao , Chen Zhenyi , Zhang Jiankai , Xu Qiang
Published: December 2024

Over the past decades, the global prevalence of Type 2 diabetes mellitus (T2D) and impaired glucose tolerance (IGT) has been increasing at an epidemic rate, yet the exact cause remains unknown. It is widely accepted that glucose metabolism can be impaired by circadian rhythms and sleep disturbances. Concurrently, exposures to light at night have been closely linked to circadian and sleep disturbances. However, there is no direct experiment on primates to demonstrate the precise extent of how serious light pollution impairs glucose metabolism, whether people will eventually become accustomed to this environment, and whether the pollution has synergistic impairing effects with aging and weight on glucose metabolism. To quantitatively address these questions, 137 cynomolgus were exposed to three distinct nocturnal light intensities for consecutive 10 months. Monthly glucose metabolism assessments were conducted. Data pertaining to the mortality rate of preexisting diabetes, incidence of light‐induced diabetes and IGT, and alterations in insulin secretion were collected and analyzed. The results show that nocturnal light (1) caused premature deaths in individuals with preexisting diabetes; (2) intensity‐dependently induced diabetes and IGT in previous healthy monkeys; (3) intensity‐dependently reduced melatonin secretion; (4) had a synergistic impairing effect on glucose metabolism with aging and weight; and (5) although monkeys would eventually adapt to the environment, the disrupted glucose metabolism would not fully recover in most individuals. In conclusion, nocturnal light is associated with the global high prevalence of T2D and IGT. The harmful effects of light pollution on glucose metabolism are synergistic with age and weight.
Spatiotemporal Demand Prediction for Bike Sharing Based on WT‐ConvLSTM
Authors: Tang Wenyun , Yang Chenyang , Wang Hanbing , Huang Jie , Li Gen
Published: December 2024

To accurately predict the spatiotemporal demand for bike sharing, a hybrid model integrating wavelet transform (WT), long short‐term memory (LSTM), and convolutional neural network (CNN) was developed, referred to as the WT‐convolutional LSTM (ConvLSTM) model. In this model, Spearman’s rank correlation coefficient was employed to identify the factors influencing demand within the target grid from a spatiotemporal perspective. After processing historical bike‐sharing order data from Shanghai, the proposed model was applied to predict bike‐sharing demand on both working and nonworking days in downtown Shanghai. The prediction accuracy was assessed using mean square error (MSE), root MSE (RMSE), and mean absolute error (MAE) under both 10‐fold cross‐validation (CV) method and the regular validation method. The findings indicate that the prediction accuracy of the WT‐ConvLSTM model is influenced by the intensity of spatiotemporal demand, with better performance when demand is concentrated. Compared to predictions generated by LSTM and WT‐LSTM models, the proposed WT‐ConvLSTM demonstrated superior accuracy. The MSE values for the proposed model under both the 10‐fold CV and regular validation methods were 0.002 and 0.003, respectively. Overall, the WT‐ConvLSTM model enhances spatiotemporal prediction accuracy for bike‐sharing demand, offering valuable insights for resource allocation and management strategies in bike‐sharing systems.