bluuebunny/crossref_metadata_2025 huggingface dataset:
PD232 A New Process For Patients And Caregivers To Suggest Health Technologies For Funding Consideration In Singapore
Authors: Koh Jen Hun , Pearce Fiona , Quek Shawn , Tan Ping-Tee
Published: January 2025

Introduction

In Singapore, health technologies were previously identified for funding consideration through horizon scanning or annual applications from clinicians, before being prioritized by the Ministry of Health advisory committees for evaluation by the Agency for Care Effectiveness (ACE). This poster describes a new process co-developed with local patient organizations to enable patients and caregivers to suggest health technologies for evaluation.

Methods

An application form was developed in plain language for patients and caregivers which requested the name of the health technology and its formulation, the medical condition it is used for, the perceived benefits and disadvantages, and the reasons why it should be funded. A factsheet explaining the selection process was codeveloped with patients, published online, and sent electronically with the application form in October 2023 to all local patient organizations, alongside the open application call for clinicians. Applications were accepted until January 2024 and then collated for prioritization in line with predefined selection criteria. All patients were notified of the outcome of their application.

Results

Fifty applications were received from patients during the first two months of the open call compared to 75 from clinicians. Most of the patient applications (66%) requested drugs for treating asthma or respiratory conditions. Drugs requested by clinicians generally differed from those requested by patients except for 5 topics, suggesting that patients may perceive clinical need differently. Most patient applicants had used the requested drugs before and considered they were effective and convenient, but unaffordable. Health technologies were more likely to be prioritized for evaluation when their benefits were plausible and supported by evidence, and they could fill an unmet clinical need for patients.

Conclusions

The process will be updated in line with feedback to encourage continued patient participation annually. Enabling patients and caregivers to suggest health technologies for evaluation provides ACE with a better understanding of their needs, preferences, lived experiences, and expectations, and ensures that subsequent funding recommendations informed by ACE’s evaluations address therapeutic gaps and improve treatment affordability and patient outcomes.
PD233 Does Patient Input Add Value To Healthcare Decision-Making? A Two-Year Reflection On Patient Involvement Processes In Singapore
Authors: Tan Ping-Tee , Pearce Fiona
Published: January 2025

Introduction

In 2022, the Agency for Care Effectiveness (ACE) co-developed patient involvement processes with local patient organizations to enable patients and caregivers to share their experiential knowledge about different medical conditions and treatments to inform health technology assessments (HTAs). This presentation describes the impact of patient input on funding recommendations during the first two years of this initiative in Singapore.

Methods

A literature search was conducted to identify frameworks and indicators used by different HTA agencies that could be contextualized to evaluate local patient involvement efforts. Systematic data extraction was performed by two authors to compare patient testimonials received for HTAs conducted between May 2022 and April 2024 with key information in HTA reports, minutes from committee meetings, and published HTA guidance documents to determine the impact of patient and caregiver involvement on the committees’ deliberations and subsequent funding recommendations. The impact of patient involvement on ACE staff, existing processes, and patient participation in future HTAs was also assessed through qualitative surveys.

Results

In the first year (May 2022 to April 2023), 112 patient responses informed 11 HTAs, while 243 responses informed 16 HTAs in the subsequent year (May 2023 to April 2024). At least one testimonial was received for 84.6 percent of HTAs in the first year, increasing to 88.9 percent in the subsequent year. Patient input addressed uncertainties in the scientific evidence and helped decision-making committees understand how different conditions affect patients and their caregivers, the outcomes that matter most to patients, and the benefits and disadvantages of different treatments. In response to feedback, ACE continually evolved its processes to meet the needs of patients and to encourage broader patient participation. Industry and patient organizations also expanded their capacity so that they can meaningfully participate in future ACE HTAs.

Conclusions

Continuous process improvement in response to feedback; providing patient input templates in different formats and languages to improve accessibility; and regular feedback to patient organizations on how their inputs have informed HTAs have increased patient participation, improved the legitimacy of ACE HTAs, and added value to decision-making about which health technologies should be funded in Singapore.
PD235 Impact Of A Consumer Panel To Inform Health Technology Assessments And Policy Development: The Singapore Experience
Authors: Teo Sok Huang , Pearce Fiona , Tan Ping-Tee
Published: January 2025

Introduction

Patient involvement in health technology assessment (HTA) at the organizational level is vital to drive process development and capacity-building, and to ensure patients have the same opportunities as other stakeholders to effect policy changes. This presentation discusses the role and impact of the Agency for Care Effectiveness (ACE) Consumer Panel in the co-development of patient involvement and education initiatives in Singapore.

Methods

The composition and terms of reference of patient and citizen groups in overseas HTA or government agencies were reviewed to identify key aspects that could be generalized to Singapore’s context. Using selection criteria, 20 individuals from local patient or voluntary groups representing a broad range of health conditions were shortlisted; 15 were formally appointed to the Panel in April 2022. Their contributions and impact on ACE’s work and healthcare decision-making were documented throughout their two-year term. A qualitative survey was also conducted to seek members’ feedback on their participation in the Panel and identify areas to improve collaboration.

Results

Since their appointment, ACE Consumer Panel members have played a key role in providing the collective voice of local patient organizations to guide ACE’s work and have co-developed processes that ensure meaningful patient involvement in policy development and HTA. They have also informed ACE’s workplan by providing advice on priority-setting, communication strategies, and patients’ information needs. During their term, processes to include patient input in HTAs were formalized leading to the co-development of a process guide and supporting fact sheets, a patient glossary, and two patient training modules, which will be continually updated based on patient feedback.

Conclusions

The ACE Consumer Panel is the first long-standing engagement of healthcare consumers by Singapore’s Ministry of Health. The Panel’s contributions and impact on ACE’s work serve as an example for other decision-makers on how to meaningfully involve patients at the organizational level, to understand their priorities and preferences, and to ensure healthcare policies remain relevant for the people affected by them.
Dietary intakes, nutritional and biochemical status of 6 months to 12-year-old children before the COVID-19 pandemic era: the South East Asian Nutrition Survey II Indonesia (SEANUTS II) study in Java and Sumatera Islands, Indonesia
Authors: Kekalih Aria , Chandra Dian Novita , Mirtha Listya Tresnanti , Khouw Ilse , Wong Gerard , Sekartini Rini
Published: January 2025

Objective:

The South East Asian Nutrition Survey II Indonesia aimed to provide up-to-date data on dietary intake, nutritional and biochemical status of children aged 0·5–12 years in Indonesia 2019–2020.

Design:

Multistage cluster sampling, stratified by geographical location.

Setting:

Out of forty-six targeted districts in Indonesia, the study only covered twenty-one districts/cities in Java and Sumatera islands, Indonesia due to COVID-19 pandemic.

Participants:

A total of 2475 children aged 0·5–12 years were included.

Result:

The growth (weight-for-age, height-for-age, weight-for-height and BMI-for-age) of Indonesian pre-school- and school-aged children was below the WHO standards. The prevalence of stunting in Java and Sumatera islands was 20·6 and 33·4 % in urban and rural areas, respectively. Stunting was higher in the 1·0–3·9-year age group, boys and rural areas. Overall, 9–12 percent of all children were overweight -obese, with 23·7 % of urban 7–12-year-olds having the highest prevalence.

Anaemia was 22·8 % in < 5-year-old and highest in < 1-year-old children. Fe, Zn, vitamins A and D insufficiency was observed in 20·3 %, 11·9 %, 1·9 % and 27·1 % of the children. Dietary intakes of energy, fibre, Ca, Fe, Zn, vitamins A, B1, C and vitamin D below the Indonesian RDA were prevalent and observed in more than half of the children.

Conclusion:

High stunting, increasing trends of overweight/ obesity, anaemia, serum vitamin D insufficiency, inadequate energy and micronutrient intake in children highlighted the triple burden of malnutrition in Java and Sumatera, Indonesia’s most populous regions in 2019–2020, shortly before COVID-19 pandemic era.
Equipping our public health nutrition workforce to promote planetary health: a case example of tertiary education co-designed with students
Authors: Chau Ka Po , Chong Wing , Londono Raquel , Cubillo Beau , McCartan Julia , Barbour Liza
Published: January 2025

Objective:

The public health nutrition workforce is well placed to contribute to bold climate action; however, tertiary educators are seeking practical examples of how to adequately prepare our future workforce. This study examines the responses of university students engaged in a co-designed planetary health education workshop as part of their public health nutrition training.

Design:

A mixed-methods approach was used to collect and interpret student responses to four interactive tasks facilitated during an in-person workshop. Data were analysed using statistical tests, frequency counting and content analysis.

Setting:

The intervention was co-designed by students (n 5) and an educator over a 4-week period as part of a larger multi-disciplinary study at an Australian university.

Participants:

The workshop engaged nutrition and dietetics students (n 44) enrolled in public health nutrition coursework.

Results:

Students reported an increase in self-perceived knowledge about planetary health as a concept and how they can promote it within their future professional roles. Students’ descriptions of what planetary health means to them were focused on humans’ role in protecting and preserving the ecosystem, the responsible and sustainable use of natural resources and a need to sustain a healthy life for future generations. Students prioritised the values of ‘collaboration’ and ‘respect’ as being critical to guide personal and professional practice to promote planetary health.

Conclusions:

This study demonstrated that incorporating planetary health curricula designed by, and for, university students could be a feasible and effective way to prepare the future public health nutrition workforce to address planetary health challenges.
Decreased frequency of sugar-sweetened beverages intake among young children following the implementation of the health promotion levy in South Africa
Authors: Kruger H Salome , van Zyl Tertia , Monyeki Makama A , Ricci Cristian , Kruger Ruan
Published: January 2025

Objective:

This study assessed the association between baseline sociodemographic variables, body composition and 4-year changes in the intake of food groups, including sugar-sweetened beverages (SSB) among children, after the implementation of the health promotion levy.

Design:

Prospective cohort study.

Setting:

Ten schools in North West Province, South Africa.

Participants:

950 children aged 5–9 years at baseline and data of 672 children at follow-up. The frequency of intake from healthy and unhealthy food groups was assessed by questionnaire. Anthropometric and sociodemographic information were collected; BMI-for-age z-scores were calculated. The health promotion levy was implemented after baseline and follow-up measurements were done after 4 years. A random intercept generalised linear mixed model analysis was applied to investigate the time effect of the weekly intake of the foods adjusting for BMI-for-age z-scores and sociodemographic characteristics of the children.

Results:

The weekly frequency of intake from most food groups remained unchanged at follow-up. The frequency of SSB intake decreased significantly over 4 years. Decreased intake of SSB was not linked to increased intake of healthy foods. Changes in intakes from SSB were not associated with household income, parental education or BMI-for-age z-score categories. A decreased frequency of intake from SSB was observed following the implementation of the health promotion levy after baseline, in line with reports of national decreases in SSB sales in South Africa since 2017.

Conclusions:

The decreased frequency of SSB intakes following the implementation of the health promotion levy in South Africa may indicate that health policies can promote healthier dietary habits.
Meals, Mealtimes and moments for learning: Assessment of quality in Early Childhood Education and Care services
Authors: Searle Bonnie , Houen Sandy , Staton Sally , Thorpe Karen
Published: January 2025

Objective:

Early education and care (ECEC) is part of the everyday life of most children in developed economies presenting exceptional opportunity to support nutrition and ongoing food preferences. Yet, the degree to which such opportunity is captured in policy-driven assessment and quality ratings of ECEC services is unknown.

Design:

Abductive thematic analysis was conducted, guided by key domains of knowledge in nutrition literature and examining identified themes within these domains.

Setting:

ECEC services (n=38) in Queensland, Australia.

Participants:

Data were a random sample of field notes pertaining to mealtimes and food provision (n=182) collected as evidence to inform quality ratings during assessment visits to ECEC services.

Results:

The field notes mapped to three theory-driven domains: Provisions, Practices and Education. Reflecting policy specification, health, hygiene, and safety were a key focus but food quality and quantity were not. Assessors noted promotion of child autonomy at mealtimes yet little evidence pertaining to characteristics of educator-child interactions.

Conclusions:

Despite evidence that childhood nutrition is crucial for optimal development and learning, quality and quantity of food is not directly assessed. Relationships and interactions at mealtimes provide an environment ideal for promoting learning and development yet the policy guiding inspection and assessment of ECEC services directs focus to a more limited lens of safety, hygiene and promotion of ‘healthy foods’. Our findings identify a narrow conceptualisation of mealtimes focused on ‘health’ as limiting the potential to leverage mealtimes as places to support children’s nutrition and attendant development and learning.
Précis of Open and Inclusive: Fair Processes for Financing Universal Health Coverage
Authors: Voorhoeve Alex , Dale Elina , Gopinathan Unni
Published: January 2025

We summarise key messages from the World Bank Report Open and Inclusive: Fair Processes for Financing Universal Health Coverage. A central lesson of the Report is that in decision-making on the path to Universal Health Coverage (UHC), procedural fairness matters alongside substantive fairness. Decision systems should be assessed using a complete conception of procedural fairness that embodies core commitments to impartial and equal consideration of interests and perspectives. These commitments demand that comprehensive information is gathered and disclosed and that justifications for policies are publicly debated; that participation in decision-making is enabled; and that these characteristics of the decision system are institutionalised rather than up to the good will of decision-makers. Procedural fairness can improve equity in outcomes, raise legitimacy and trust, and can help make reforms last. While improving procedural fairness can be costly and there are barriers to achieving it, the range of instruments that countries at varying levels of income and institutional capacity have used with some success shows that, in many contexts, advances in procedural fairness in health financing are possible and worthwhile.
Relating Dimethyl Sulphide and Methanethiol Fluxes to Surface Biota in the South‐West Pacific Using Shipboard Air‐Sea Interface Tanks
Authors: Rocco M. , Dunne E. , Salignat R. , Saint‐Macary A. , Peltola M. , Barthelmeß T. , Chamba G. , Barr N. , Safi K. , Marriner A. , Deppeler S. , Rose C. , Uitz J. , Harnwell J. , Engel A. , Colomb A. , Saiz‐Lopez A. , Harvey M. J. , Law C. S. , Sellegri K.
Published: January 2025

Dimethyl sulphide (DMS) and methanethiol (MeSH) emissions from South Pacific surface seawater were determined in deck board Air‐Sea Interface Tanks during the Sea2Cloud voyage in March 2020. The measured fluxes from water to headspace (F) varied with water mass type, with lowest fluxes observed with Subtropical and Subantarctic waters and highest fluxes from Frontal waters. Measured DMS fluxes were consistent with fluxes calculated using a two‐layer model and seawater DMS concentrations. The MeSH:DMS flux ratio was 11%–18% across the three water mass types, confirming that MeSH may represent a significant unaccounted contribution to the atmospheric sulfur budget, with potentially important implications for marine aerosol formation and growth in models. Combining data from the ASITs and ambient surface seawater identified significant Spearman rank correlations for both dissolved DMS and MeSH with nanophytoplankton cell abundance (pvalue < 0.012), suggesting an important role for this phytoplankton size class in determining regional DMS and MeSH emissions. Applying a nanophytoplankton‐based parameterization to estimate DMSw provided good agreement with a recent DMS climatology. Consequently, the observed relationship between DMSw, MeSHw and nanophytoplankton cell abundances may be applicable for modeling atmospheric fluxes.
Teaching Justice in the Geosciences Matters
Authors: Gomby Gary
Published: January 2025

Geoscience educators owe it to their students to incorporate conversations of environmental justice and equity into their classrooms. Case studies are an effective approach to do this.
Liquid bidentate ligand for full ligand coverage towards efficient near-infrared perovskite quantum dot LEDs
Authors: Liu Zong-Shuo , Wang Ye , Zhao Feng , Li Hua-Hui , Liu Wei-Zhi , Shen Wan-Shan , Duan Hong-Wei , Wang Ya-Kun , Liao Liang-Sheng
Published: January 2025

Perovskite quantum dots (PQDs) show promise in light-emitting diodes (LEDs). However, near-infrared (NIR) LEDs employing PQDs exhibit inferior external quantum efficiency related to the PQD emitting in the visible range. One fundamental issue arises from the PQDs dynamic surface: the ligand loss and ions migration to the interfacial sites serve as quenching centers, resulting in trap-assisted recombination and carrier loss. In this work, we developed a chemical treatment strategy to eliminate the interface quenching sites and achieve high carrier utilization. We employ a bidentate and liquid agent (Formamidine thiocyanate, FASCN) with tight binding to suppress the ligand loss and the formation of interfacial quenching sites: the FASCN-treated films exhibit fourfold higher binding energy than the original oleate ligands. Furthermore, the short ligands (carbon chain <3) enable the treated films to show eightfold higher conductivity; and the liquid characteristics of FASCN avoid the use of high polar solvents and guarantee better passivation. The high conductivity ensures efficient charge transportation, enabling PQD-based NIR-LEDs to have a record-low voltage of 1.6 V at 776 nm. Furthermore, the champion EQE of the treated LEDs is ~23%: this is twofold higher than the control, and represents the highest among reported PQD-based NIR-LEDs.
Low-threshold surface-emitting colloidal quantum-dot circular Bragg laser array
Authors: Tan Yangzhi , Huang Yitong , Wu Dan , Wang Yunjun , Sun Xiao Wei , Choi Hoi Wai , Wang Kai
Published: January 2025

Colloidal quantum dots (CQDs) are attractive gain media due to their wavelength-tunability and low optical gain threshold. Consequently, CQD lasers, especially the surface-emitting ones, are promising candidates for display, sensing and communication. However, it remains challenging to achieve a low-threshold surface-emitting CQD laser array with high stability and integration density. For this purpose, it is necessary to combine the improvement of CQD material and laser cavity. Here, we have developed high-quality CQD material with core/interlayer/graded shell structure to achieve a low gain threshold and high stability. Subsequently, surface-emitting lasers based on CQD-integrated circular Bragg resonator (CBR) have been achieved, wherein the near-unity mode confinement factor (Γ of 89%) and high Purcell factor of 22.7 attributed to the strong field confinement of CBR enable a low lasing threshold of 17 μJ cm−2, which is 70% lower than that (56 μJ cm−2) of CQD vertical-cavity surface-emitting laser. Benefiting from the high quality of CQD material and laser cavity, the CQD CBR laser is capable of continuous stable operation for 1000 hours (corresponding to 3.63 × 108 pulses) at room temperature. This performance is the best among solution-processed lasers composed of nanocrystals. Moreover, the miniaturized mode volume in CBR allows the integration of CQD lasers with an unprecedentedly high density above 2100 pixels per inch. Overall, the proposed low-threshold, stable and compactly integrated CQD CBR laser array would advance the development of CQD laser for practical applications.
Roof renewal disparities widen the equity gap in residential wildfire protection
Authors: Reining Sebastian , Wussow Moritz , Zanocco Chad , Neumann Dirk
Published: January 2025

Wildfires are having disproportionate impacts on U.S. households. Notably, in California, over half of wildfire-destroyed homes (54%) are in low-income areas. We investigate the relationship between social vulnerability and wildfire community preparedness using building permits from 16 counties in California with 2.9 million buildings (2013–2021) and the U.S. government’s designation of disadvantaged communities (DACs), which classifies a census tract as a DAC if it meets a threshold for certain burdens, such as climate, environmental, and socio-economic. Homes located in DACs are 29% more likely to be destroyed by wildfires within 30 years, partly driven by a gap in roof renewals, one of several important home hardening actions. Homes in DACs have 28% fewer roof renewals than non-DACs and post-wildfire, non-DAC homes have more than twice the increase in renewals (+17%) compared to DAC homes (+7%). Our research offers policy insights for narrowing this equity gap in renewals for wildfire-prone areas. We recommend increasing financial support for roof renewals and targeted awareness campaigns for existing programs which are not sufficiently emphasized in wildfire strategies, particularly in DACs.
Septuple XBi2Te4 (X=Ge, Sn, Pb) intercalated MnBi2Te4 for realizing interlayer ferromagnetism and quantum anomalous hall effect
Authors: Yang Ruixia , Man Xiaoxiao , Peng Jiahui , Zhang Jingjing , Wang Fei , Wang Fang , Zhang Huisheng , Xu Xiaohong
Published: January 2025

Realizing the quantum anomalous Hall effect (QAHE) at high temperatures remains a significant challenge in condensed matter physics. MnBi2Te4, an intrinsic magnetic topological insulator, presents a promising platform for QAHE. However, its inherent interlayer antiferromagnetic coupling hinders practical realization at high temperatures. In this study, we propose a novel approach to achieve interlayer ferromagnetic (FM) coupling in MBT bilayer by intercalating the septuple-layer of topological insulators XBi2Te4 (X=Ge, Sn, Pb). Using first-principles calculations, we demonstrate that the pz orbital of the X atom mediates interactions between interlayer Mn atoms, enabling FM coupling. Monte Carlo simulations predict a magnetic transition temperature of 38 K for the MnBi2Te4/PbBi2Te4/MnBi2Te4 heterostructure. Our band structure and topological analyses confirm the preservation of QAHE in all MnBi2Te4/XBi2Te4/MnBi2Te4 heterostructures, while the MnBi2Te4/PbBi2Te4/MnBi2Te4 heterostructure exhibits a topological band gap of 72 meV, significantly exceeding that of the pure MnBi2Te4 bilayer. Furthermore, a continuum model is developed to elucidate the underlying mechanism of the nontrivial topological states. Our work provides a practical pathway to achieving interlayer FM coupling in MnBi2Te4 bilayers, paving the way for high-temperature QAHE and advancing the development of magnetic topological insulators for quantum and spintronic applications.
Deep CRISPR mutagenesis characterizes the functional diversity of TP53 mutations
Authors: Funk Julianne S. , Klimovich Maria , Drangenstein Daniel , Pielhoop Ole , Hunold Pascal , Borowek Anna , Noeparast Maxim , Pavlakis Evangelos , Neumann Michelle , Balourdas Dimitrios-Ilias , Kochhan Katharina , Merle Nastasja , Bullwinkel Imke , Wanzel Michael , Elmshäuser Sabrina , Teply-Szymanski Julia , Nist Andrea , Procida Tara , Bartkuhn Marek , Humpert Katharina , Mernberger Marco , Savai Rajkumar , Soussi Thierry , Joerger Andreas C. , Stiewe Thorsten
Published: January 2025

The mutational landscape of TP53, a tumor suppressor mutated in about half of all cancers, includes over 2,000 known missense mutations. To fully leverage TP53 mutation status for personalized medicine, a thorough understanding of the functional diversity of these mutations is essential. We conducted a deep mutational scan using saturation genome editing with CRISPR-mediated homology-directed repair to engineer 9,225 TP53 variants in cancer cells. This high-resolution approach, covering 94.5% of all cancer-associated TP53 missense mutations, precisely mapped the impact of individual mutations on tumor cell fitness, surpassing previous deep mutational scan studies in distinguishing benign from pathogenic variants. Our results revealed even subtle loss-of-function phenotypes and identified promising mutants for pharmacological reactivation. Moreover, we uncovered the roles of splicing alterations and nonsense-mediated messenger RNA decay in mutation-driven TP53 dysfunction. These findings underscore the power of saturation genome editing in advancing clinical TP53 variant interpretation for genetic counseling and personalized cancer therapy.
A comprehensive guide to selecting suitable wavelet decomposition level and functions in discrete wavelet transform for fault detection in distribution networks
Authors: Shalby Esraa M. , Abdelaziz Almoataz Y. , Ahmed Eman S. , Abd-Elhamed Rashad Basem
Published: January 2025

The paper presents a comprehensive analysis of the IEEE-16 bus system under different operating conditions. It discusses the selection of suitable decomposition level and wavelet function for analyzing non-stationary signals to enhance power distribution network fault detection. MATLAB/Simulink is used to simulate the system, and transient fault current signals are processed with the MATLAB Wavelet Toolbox. The optimal decomposition level is determined by energy concentration, with the highest energy found in scales D9 (b4), D8 (b5), and D7 (b6), and D8 having the most concentration. Using MATLAB classifier learner, the article evaluates seven common mother wavelets with 53 wavelet functions, and sym3 is found to be the most efficient wavelet function in terms of training time, prediction speed, and accuracy of SVM classifiers. All fault types both symmetrical/unsymmetrical types, and various normal transient conditions such as load/capacitor/DG switching are detected/discriminated with nearly 100% accuracy at the midpoint of line 6–7 with various fault conditions, inception angles (0, 30, 45, 60, 90 and 120°) and a fault resistance of (5,10, 15, and 20 ohms). Additionally, 9 MW wind Farm is integrated at busbar 10, and various fault scenarios are simulated to assess system performance with 100% Accuracy.
Enhancing in search of Milankovitch cycles from stratigraphic record using convex optimization algorithm
Authors: Alam Syaiful , Hadian Mohamad Sapari Dwi , Hamdani Ahmad Helman , Sulaiman Noorzamzarina
Published: January 2025

Accurately identifying Milankovitch cycles has been a significant challenge in cyclostratigraphic studies, as it is essential for improving geochronology. This manuscript focuses on developing a method that distinguishes Milankovitch cycles from sedimentary noise to enhance stratigraphic precision. Despite their often-conspicuous magnitude, these periodicities frequently intertwine with noise, posing a challenge for conventional spectral analysis. Therefore, to address this issue, we have developed an algorithm that enhances the resolution of the Milankovitch signal by employing convex optimization in spectral analysis. To evaluate the effectiveness of this new algorithm, we applied it to four distinct types of local stratigraphy where the Milankovitch signal has been confirmed. These include the stratigraphic sections in the middle Miocene molluscan beds of Java and the Mahakam Delta, Pleistocene sediments of Hominin Flores, and the Towuti Lake in Sulawesi Island, Indonesia. Our findings demonstrate the preservation of all targeted signals, with a confidence level surpassing 99%. By setting the significance level to 1%, we can reject the null hypothesis, which assumes noise or the absence of a Milankovitch signal in the stratigraphic data being tested. The absence of deviations from the identified periodicities further strengthens the Milankovitch signal, underscoring the robustness of our algorithm. However, we acknowledge that achieving optimal results still hinges on the accurate selection of the initial parameters z and λ.
Strength prediction of ECC-CES columns under eccentric compression using adaptive sampling and ML techniques
Authors: Megahed Khaled
Published: January 2025

A novel type of concrete-encased steel (CES) composite column implementing Engineered Cementitious Composites (ECC) confinement (ECC-CES) has recently been introduced, offering significantly enhanced failure behavior, ductility, and toughness when compared to conventional CES columns. This study presents an innovative method for predicting the eccentric compressive capacity of ECC-CES columns, utilizing adaptive sampling and machine learning (ML) techniques. Initially, the research introduces a finite element (FE) model for ECC-CES columns, incorporating material and geometric nonlinearities to capture the inelastic behavior of both ECC and steel through appropriate constitutive material laws. The FE model was validated against experimental data, demonstrating strong predictive accuracy. An adaptive sampling process was employed to efficiently explore the design space, resulting in a database of 2,908 FE models. Subsequently, six machine learning models were used to predict the eccentric compressive capacity based on the generated FE database. These models were thoroughly evaluated and demonstrated superior prediction accuracy compared to established design standards like EC4 and AISC360. Based on evaluation metrics, the Gaussian Process Regression (GPR), CatBoost (CATB), and LightGBM (LGBM) models emerged as the most accurate and reliable, with over 97% of the finite element (FE) samples falling within a 10% error range. While the ML models demonstrate impressive performance, their black-box nature restricts their practical use in design applications. Consequently, this study introduces a proposed design that offers competitive performance metrics. The novelty of this work lies in integrating adaptive sampling through Bayesian Optimization (BO) with the power of machine learning (ML) to generate training data that effectively covers a large input space while minimizing error. SVR, CatBoost, and GPR models demonstrated mean μ, R2, and a20-index values near 1.0, with CoV and MAPE% values consistently low, indicating highly accurate predictions across testing subsets.
A case study on using a large language model to analyze continuous glucose monitoring data
Authors: Healey Elizabeth , Tan Amelia Li Min , Flint Kristen L. , Ruiz Jessica L. , Kohane Isaac
Published: January 2025

Continuous glucose monitors (CGM) provide valuable insights about glycemic control that aid in diabetes management. However, interpreting metrics and charts and synthesizing them into linguistic summaries is often non-trivial for patients and providers. The advent of large language models (LLMs) has enabled real-time text generation and summarization of medical data. The objective of this study was to assess the strengths and limitations of using an LLM to analyze raw CGM data and produce summaries of 14 days of data for patients with type 1 diabetes. We first evaluated the ability of GPT-4 to compute quantitative metrics specific to diabetes found in an Ambulatory Glucose Profile (AGP). Then, using two independent clinician graders, we evaluated the accuracy, completeness, safety, and suitability of qualitative descriptions produced by GPT-4 across five different CGM analysis tasks. GPT-4 performed 9 out of the 10 quantitative metrics tasks with perfect accuracy across all 10 cases. The clinician-evaluated CGM analysis tasks had good performance across measures of accuracy [lowest task mean score 8/10, highest task mean score 10/10], completeness [lowest task mean score 7.5/10, highest task mean score 10/10], and safety [lowest task mean score 9.5/10, highest task mean score 10/10]. Our work serves as a preliminary study on how generative language models can be integrated into diabetes care through data summarization and, more broadly, the potential to leverage LLMs for streamlined medical time series analysis.
Deep learning-based encryption scheme for medical images using DCGAN and virtual planet domain
Authors: Kumar Manish , Chivukula Aneesh Sreevallabh , Barua Gunjan
Published: January 2025

The motivation for this article stems from the fact that medical image security is crucial for maintaining patient confidentiality and protecting against unauthorized access or manipulation. This paper presents a novel encryption technique that integrates the Deep Convolutional Generative Adversarial Networks (DCGAN) and Virtual Planet Domain (VPD) approach to enhance the protection of medical images. The method uses a Deep Learning (DL) framework to generate a decoy image, which forms the basis for generating encryption keys using a timestamp, nonce, and 1-D Exponential Chebyshev map (1-DEC). Experimental results validate the efficacy of the approach in safeguarding medical images from various security threats, including unauthorized access, tampering, and adversarial attacks. The randomness of the keys and encrypted images are demonstrated through the National Institute of Standards and Technology (NIST) SP 800-22 Statistical test suite provided in Tables 4 and 14, respectively. The robustness against key sensitivity, noise, cropping attacks, and adversarial attacks are shown in Figs. 15–18, 22–23, and 24. The data presented in Tables 5, 6, and 7 shows the proposed algorithm is robust and efficient in terms of time and key space complexity. Security analysis results are shown (such as histogram plots in Figs. 11–14 and correlation plots in Figs. 19–21). Information Entropy ($$7.9993 \pm 0.0001$$), correlation coefficient ($$\pm 0.09$$), Mean Square Error (MSE) ($$4166.3107 \pm 1645.2980$$), Peak Signal to Noise Ratio (PSNR) ($$12.2643 \pm 1.7032$$), Number of Pixel Change Rate (NPCR) ($$99.60\% \pm 0.2\%$$), and Unified Average Changing Intensity (UACI) ($$33.47\% \pm 0.1\%$$) underscore the high security and reliability of the encrypted images, are shown in Tables 8–11. Further, statistical NPCR and UACI are calculated in Tables 12 and 13, respectively. The proposed algorithm is also compared with existing algorithms, and compared values are provided in Table 15. The data presented in Tables 3–15 suggest that the proposed algorithm can opt for practical use.
Multi-level clustering and Prediction based energy efficient routing protocol to eliminate Hotspot problem in Wireless Sensor Networks.
Authors: Prince Bhaskar , Kumar Prabhat , Singh Sunil Kumar
Published: January 2025

Conserving energy of sensor nodes and ensuring balanced workloads among them are fundamental concerns in Wireless Sensor Network (WSN) design. Clustering strategies offer a promising avenue to minimize node energy consumption, thereby prolonging network lifespan. Nevertheless, numerous multi-hop routing protocols using clustering technique face the challenge of nodes nearer to the Base Station (BS) depleting their energy faster due to forwarding data from the entire network leading to premature node failure and network partitioning known as ‘hotspot problem’. The paper introduces an Energy-Efficient Mega-Cluster-Based Routing (EEMCR) protocol specially designed for expansive coverage area. The primary principle behind designing this protocol is to eliminate the hotspot problem and restrict the transmission range of nodes to the threshold distance defined by the radio energy model, thereby enhancing the overall network lifespan. The protocol adopts a centralized approach employing fixed clustering wherein the BS partitions the network into square-shaped clusters. The cluster size is determined by the threshold transmission range of the sensor radio energy model, guaranteeing that all network communication stays within this threshold distance. Four such clusters form a mega-cluster with a Mega-Cluster-Head (MCH) elected among the four Cluster Heads (CHs). The MCH role is evenly distributed among nodes of all four clusters in subsequent rounds for uniform distribution of its overhead. Implementing data aggregation at two levels (CH level as well as MCH level) leads to reduced data traffic and energy consumption throughout the network. Moreover, data collection by two data mules based on odd–even round number ensures balanced data traffic and energy distribution across the network. Analysis indicates that the proposed protocol effectively mitigates the hot-spot problem and reduces data transmission overhead of sensor nodes. In simulation, the proposed protocol on an average improves network life by 34.5%, 23.5%, 14.5% and 5.5% as compared to existing protocols FCEEC, DBSCAN, LPGCR and FBECS respectively for deployment of nodes between 600 to 1200. Also, approximately 46%, 32%, 21% and 14% of lesser sensor nodes are dead for proposed protocol in respective rounds as compared to existing protocols FCEEC, DBSCAN, LPGCR and FBECS respectively. Comparative evaluations demonstrate improved network lifetime when compared to equivalent recent routing protocols.
Numerical simulation of coal particle motion characteristics in the envelope region of spiral drum based on discrete element method
Authors: Tian Zhen , Gao Shan , Ma Lianwei , Wang He , Ge Yang
Published: January 2025

In order to study the movement characteristics of coal particles in the coal loading process of spiral drums, the spiral drum of a certain type of shearer was taken as the research object, and the intrinsic parameters of the materials were calibrated through the determination results of coal sample properties, the relevant parameters of coal particle adhesion were determined, and a discrete element model of spiral drum coal loading was established. The distribution of coal particle movement subsequent to the fracture of the coal wall was derived through simulation. By spatially dividing the envelope region of the spiral drum along the radial and axial directions, the number and velocity distribution of coal particles in different envelope regions were obtained. The study revealed that the number of coal particles in radial regions III and IV was significantly higher than that in regions I and II. Most of the coal particles in regions III and IV moved outward along the drum axis under the action of the spiral blades, while a small portion moved from regions III and IV towards regions I and II. The coal particles in the axial region near the outer side of the coal wall have a strong ability to flow towards the scraper conveyor, and the probability of coal particles being thrown towards the rear of the spiral drum is higher in the region near the end plate. The increase in traction speed has little effect on the velocity of coal particles in all directions within the envelope region, while the increase of drum rotation speed can significantly improve the velocity of coal particles in each region. Through statistical analysis, it was found that the coal loading rate decreases with the increasing of traction speed. As the drum speed increases, the coal loading rate first increases and then decreases. By comparing the results of industrial experiments and numerical simulations underground, the accuracy of the discrete element method used in this paper to analyze the particle motion in the envelope region of the spiral drum has been confirmed. The research results provide reference for the selection of motion parameters of coal shearer and the improving of coal loading efficiency of spiral drums.
Rapid quantitative analysis of double-stranded plasmid DNA with capillary gel electrophoresis for applications in quality control and radiation research
Authors: Hahn Marc Benjamin
Published: January 2025

The quantification of different structures, isoforms and types of damage in plasmid DNA is of importance for applications in radiation research, DNA based bio-dosimetry, and pharmaceutical applications such as vaccine development. The standard method for quantitative analysis of plasmid DNA damage such as single-strand breaks (SSB), double-strand breaks (DSB) or various types of base-damage is Agarose gel electrophoresis (AGE). Despite being well established, AGE has various drawbacks in terms of time consuming handling and analysis procedures. A more modern, faster, cheaper and more reliable method is capillary gel electrophoresis (CGE). However, to establish this method in biotechnology, radiation-research and related fields, certain criteria in terms of accuracy, repeatability and linearity have to be tested and protocols have to be established. This study performs the relevant tests with a common model plasmid (pUC19, double-stranded DNA with 2686 basepairs) to establish a CGE based methodology for quantitative analysis with readily available commercial CGE systems. The advantages and limitations of the methods are evaluated and discussed, and the range of applicability is presented. As a further example, the kinetics of enzyme digestion of plasmid DNA by capillary gel electrophoresis was studied. The results of the study show for a model system consisting out of pUC19, the suitability of CGE for the quantification of different types of DNA damage and the related isoforms, such as supercoiled, open-circular and linear plasmid DNA.
Association between abdominal obesity and nutritional supplement use among Iranian adults in the Shahedieh cohort study
Authors: Nouri Sina , Ghadiri-Anari Akram , Hosseini Saeed , Hazar Narjes
Published: January 2025

The relationship between the use of supplements and the presence of abdominal obesity is a topic that is currently being debated. The purpose of the present study was to evaluate the existence of such an association. The current cross-sectional investigation included a population of 9878 individuals who were the focus of the study’s initial phase in the Shahedieh cohort study, conducted in Yazd, Iran. Waist circumference was measured with the help of an inflexible tape measure. In addition, the data regarding the consumption of various supplements, including multivitamins, folic acid, ferric compounds, omega 3, calcium, vitamin D, zinc, and other supplements, were collected through interviews conducted by trained interviewers. Among the entire sample, 4785 individuals (50.6%) were found to have abdominal obesity, while 4093 individuals (43.3%) reported using at least one type of supplements. In the simple regression analysis, all of the supplements, except for multivitamins and zinc, were identified as adverse factors for abdominal obesity. However, in the multivariable regression analysis, only ferric compounds remained significant as a protective factor (OR = 0.73, 95%CI: 0.57‒0.94). The findings of this study suggest that dietary supplements, particularly ferric compounds, may have implications for managing abdominal obesity. These findings could inform public health strategies by incorporating ferric compound supplementation into dietary interventions aimed at reducing abdominal obesity prevalence. Furthermore, the potential clinical application of ferric compounds highlights the need for integrating nutritional approaches in obesity management programs. However, longitudinal studies are needed to establish causal relationships and confirm the long-term effectiveness and safety of such interventions.
Digital-twin driven alignment control method for marine shafting with air spring vibration isolation system
Authors: Liu Song , Shi Liang , Xu Wei , Hu ZeChao
Published: January 2025

Shafting alignment is crucial for marine propulsion systems and may affect the safety and stability of ship operations. Air spring vibration isolation systems (ASVISs) for marine shafting can help control the shafting alignment state by actively adjusting air spring pressures while effectively reducing the mechanical noise. However, how to accurately control the alignment state of marine shafting with air spring vibration isolation system remains a challenge. To address this issue, a digital twin (DT)-driven alignment control method is proposed in this paper. First, we design a digital twin prediction model based on the neural network to describe the data mapping relationship between the air spring pressures and shafting alignment state. Then, based on the prediction model, we transform the shafting alignment control problem into a non-linear optimization problem in which our objective is to minimize the alignment error while balancing the load on different air springs. To obtain the optimal air spring pressures, the genetic algorithm is introduced to solve the optimization problem, fully exploiting its global search capacity. Moreover, in order to achieve the optimized pressures, a soft-constrained controller based on proportional-integral-derivative (PID) algorithm is developed to accurately generate specific control policies based on the monitoring data. Finally, the feasibility and the effectiveness of the proposed alignment control method is verified with a real ASVIS.