bluuebunny/crossref_metadata_2025_split huggingface dataset:
Phosphate removal from aqueous solutions using reversal mode electrocoagulation with iron and aluminum electrodes: RSM optimization and ANN modeling
Authors: Tuyet Nguyen Thi , Nguyen Vinh Dinh , Nguyet Nguyen Thi , Balasubramani Ravindran , Nghia Nguyen Trong 
Published: September 2024

Abstract
Phosphate pollution significantly contributes to eutrophication and the degradation of aquatic ecosystems. The removal of phosphate from wastewater before discharging into the environment is essential for the sustainability of the ecosystem. This work focuses on using a polarity reversal mode electrocoagulation (PRM-EC) system integrated with iron (Fe) and aluminum (Al) electrodes to remove phosphate from wastewater. The conditions for the removal process were optimized using response surface methodology (RSM). Central composite design (CCD) was used to design the experiment and numerical optimization was utilized to find the optimal conditions. The phosphate removal efficiency could reach 93.12% at a current density of 40 A m−2, time of 30 min, pH of 6.4, and electrode distance of 10.5 mm. The energy consumption was about 0.4 kW m−3. The artificial neural network (ANN) modeling showed that the current density was the most influencing factor, followed by time, pH, and electrode distance. The mechanism underlying the PRM-EC process encompassed electrode dissolution, floc formation, phosphate adsorption, and precipitation. The findings in the work show that PRM-EC is an environmentally friendly and effective solution for phosphate removal.
The compact cookbook of structured modes of light
Authors: Rosales-Guzmán Carmelo , Perez-Garcia Benjamin , Cox Mitchell A 
Published: September 2024

Abstract
This concise tutorial serves as a guide to the generation and characterisation of higher-order optical mode bases, such as HG, LG, OAM, IG, MG, BG, and various vector modes. It succinctly outlines the creation methods and practicalities for these structured light forms using liquid crystal spatial light modulators and digital micro-mirror devices. An overview of measurement and characterisation using modal decomposition, and approaches to measure and characterise vector beams is also given (Stokes polarimetry and vector quality factor). The tutorial concludes with a brief discussion on the effects of varying coherence on these complex light structures, providing essential insights for anyone starting out in the field of photonics.
Study on bearing capacity characteristics of Cement-Flyash-Gravel piles and cement-soil compacted piles in composite foundations
Authors: Cheng Xuansheng , Wang Hao , Gong Lijun , Zhou Yingchao 
Published: September 2024

Abstract
To investigate the mechanical performance of Cement-Flyash-Gravel (CFG) piles and Cement-Soil Compacted (CSC) piles in composite foundations (CF), this study uses numerical simulation methods combined with field tests to examine the bearing capacity characteristics and behavior patterns of CFG and CSC pile composite foundations in the collapsible loess area of the Yinxi high-speed railway. The results indicate that the stress ratio between the CFG piles and the surrounding soil follows a trend of ‘steady-sharp rise-steady transition-sharp drop. Additionally, the side friction resistance of the CFG pile reaches its maximum negative value at 2/3 of the pile length and its maximum positive value at 7/8 of the pile length. These findings provide important insights and practical guidance for the design and construction of composite foundations in collapsible loess regions.
A PNP ion channel deep learning solver with local neural network and finite element input data
Authors: Lee Hwi , Chao Zhen , Cobb Harris , Liu Yingjie , Xie Dexuan 
Published: September 2024

Abstract
This paper presents a deep learning method for solving an improved one-dimensional Poisson–Nernst–Planck ion channel (PNPic) model, called the PNPic deep learning solver. The solver combines a novel local neural network, adapted from the neural network with local converging inputs, with an efficient PNPic finite element solver, developed in this work. In particular, the local neural network is extended to handle the complexities of the PNPic model—a system of nonlinear convection–diffusion and elliptic equations with multiple subdomains connected by interface conditions. The PNPic finite element solver efficiently generates input and reference datasets for fast training the local neural network, as well as input datasets for quickly predicting PNPic solutions with high accuracy for a family of PNPic models. Initial numerical tests, involving perturbations of model parameters and interface locations, demonstrate that the PNPic deep learning solver can generate highly accurate numerical solutions.
New horizons in prediction modelling using machine learning in older people’s healthcare research
Authors: Stahl Daniel 
Published: September 2024

Abstract
Machine learning (ML) and prediction modelling have become increasingly influential in healthcare, providing critical insights and supporting clinical decisions, particularly in the age of big data. This paper serves as an introductory guide for health researchers and readers interested in prediction modelling and explores how these technologies support clinical decisions, particularly with big data, and covers all aspects of the development, assessment and reporting of a model using ML. The paper starts with the importance of prediction modelling for precision medicine. It outlines different types of prediction and machine learning approaches, including supervised, unsupervised and semi-supervised learning, and provides an overview of popular algorithms for various outcomes and settings. It also introduces key theoretical ML concepts. The importance of data quality, preprocessing and unbiased model performance evaluation is highlighted. Concepts of apparent, internal and external validation will be introduced along with metrics for discrimination and calibration for different types of outcomes. Additionally, the paper addresses model interpretation, fairness and implementation in clinical practice. Finally, the paper provides recommendations for reporting and identifies common pitfalls in prediction modelling and machine learning. The aim of the paper is to help readers understand and critically evaluate research papers that present ML models and to serve as a first guide for developing, assessing and implementing their own.
The risk of geriatric syndromes in older COVID-19 survivors among the nonvaccinated population: a real world retrospective cohort study
Authors: Su Chien-Chou , Yang Yi-Ching , Yu Yu-Huai , Tsai Yu-Hsuan , Yang Deng-Chi 
Published: September 2024

Abstract

Background
We aimed to analyse the differences in the risk of geriatric syndromes between older adults with and without coronavirus disease 2019 (COVID-19).

Methods
We conducted a retrospective cohort study of patients from the US Collaborative Network in the TriNetX between January 1, 2020, and December 31, 2022. We included individuals aged older than 65 years with at least 2 health care visits who underwent severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) polymerase chain reaction (PCR) tests during the study period. We excluded those with SARS-CoV-2 vaccination, diagnosis with neoplasm and geriatric syndromes before the index date, and death within 30 days after the index date. The index date was defined as the first date of the PCR test for SARS-CoV-2 during the study period. Hazard ratios (HRs) and 95% confidence intervals (CIs) for eight geriatric syndromes were estimated for propensity score-matched older adults with and without COVID-19. Subgroup analyses of sex and age were also performed.

Results
After propensity score matching, 315 826 patients were included (mean [standard deviation] age, 73.5 [6.4] years; 46.7% males and 51.7% females). The three greatest relative increases in the risk of geriatric syndromes in the COVID-19 cohort were cognitive impairment (HR: 3.13; 95% CI: 2.96–3.31), depressive disorder (HR: 2.72; 95% CI: 2.62–2.82) and pressure injury (HR: 2.52; 95% CI: 2.34–2.71).

Conclusions
The risk of developing geriatric syndromes is much higher in the COVID-19 cohort. It is imperative that clinicians endeavour to prevent or minimise the development of these syndromes in the post-COVID-19 era.
Risk factors for Lyme disease among residents of rural, suburban, and urban areas in the United States: A Case-Control Study
Authors: Gould L Hannah , Fee Rebecca , White John , Webb Noah , Carlyle Maureen , Dick Laura , Tan Ye , Walker Valery , Angulo Frederick J , Moïsi Jennifer C , Stark James H , Pugh Sarah 
Published: September 2024

Abstract
lyme disease (LD) is the most common vector-borne disease in the United States, with 476,000 cases estimated each year. It is unclear how LD risk factors vary by residential setting. We conducted a case-control study on LD risk by rural, urban, and suburban residential settings. Individuals from 15 high-incidence states and the District of Columbia in the Optum Research Database were identified as cases (LD medical claim) or controls (no LD medical claim, matched by county of residence and census block group population density). Participants were surveyed about LD history, outdoor activities, and residential characteristics. The final analytic dataset had 750 LD cases and 965 controls. Residence in a rural setting had increased LD risk (OR 1.41, 95% CI 1.16, 1.72). In multivariable analyses, activities associated with LD were hiking/walking/running or having an occupation in forests, wooded areas, or areas of tall grass (all respondents), and spending time in a yard (rural and urban residents only). Public health interventions can help prevent LD in high-incidence jurisdictions by reinforcing the nearuniversal LD risk for rural residents, and highlighting activities that lead to increased LD risk for those in areas with less ubiquitous tick exposure like in urban and suburban settings.
Development and Validation of an Algorithm to Predict Stillbirth Gestational Age in Medicaid Billing Records
Authors: Thai Thuy N , Smolinski Nicole E , Nduaguba Sabina , Bird Steven , Straub Loreen , Bateman Brian T , Hernandez-Diaz Sonia , Huybrechts Krista F , Rasmussen Sonja A , Winterstein Almut G 
Published: September 2024

Abstract

Introduction
With Medicaid covering half of US pregnancies, Medicaid Analytic eXtract (MAX) provides a valuable data source to enrich understanding about stillbirth etiologies.

Objective
We developed and validated a claims-based algorithm to predict GA at stillbirth.

Method
We linked the stillbirths identified in MAX 1999-2013 to Florida Fetal Death Records (FDRs) to obtain clinical estimates of GA (N=825). We tested several algorithms including using a fixed median GA, median GA at the time of specific prenatal screening tests, and expanded versions considering additional predictors of stillbirth within including linear regression and random forest models. We estimated the proportion of pregnancies with differences of ± 1, 2, 3 and 4 weeks between the predicted and FDR GA and the model mean square error (MSE). We validated the selected algorithms in two external samples.

Results
The best performing algorithm was a random forest model (MSE of 12.67 weeks2) with 84% of GAs within ± 4 weeks. Assigning a fixed GA of 28 weeks resulted in an MSE of 60.21 weeks2 and proportions of GA within ± 4 weeks of 32%. We observed consistent results in the external samples.

Discussion
Our prediction algorithm for stillbirths can facilitate pregnancy research in the Medicaid population.
Effort-reward imbalance at work assessed at midlife and prediabetes prevalence assessed 18 years later in a prospective cohort of white-collar workers
Authors: Riopel Camille , Trudel Xavier , Milot Alain , Laurin Danielle , Gilbert-Ouimet Mahée , Brisson Chantal 
Published: September 2024

Abstract

Objectives
Evidence suggests that workers exposed to psychosocial stressors at work from the effort-reward imbalance (ERI) model are at increased risk for type 2 diabetes mellitus (T2DM). However, evidence about the effect of ERI on prediabetes is scarce. This study aimed to examine the association between effort-reward imbalance at work, glycated hemoglobin level and the prevalence of prediabetes in women and men from a prospective cohort study.

Methods
This study was conducted among 1354 white-collar workers followed for an average of 18 years. Effort-reward imbalance at work was measured in 1999 to 2001 using a validated instrument. Glycated hemoglobin was assessed at follow-up (2015 to 2018). Differences in mean glycated hemoglobin levels were estimated with linear models. Prediabetes prevalence ratios (PRs) were computed using robust Poisson regression models.

Results
In women, those exposed to effort-reward imbalance at work at baseline had a higher prevalence of prediabetes (PR = 1.60, 95% confidence interval: 1.02–2.49) at follow-up following adjustment for sociodemographic, lifestyle-related, clinical, and other occupational risk factors. There was no difference in mean glycated hemoglobin levels.

Conclusion
Among women, effort-reward imbalance at work at midlife was associated with the prevalence of prediabetes, at older age. Preventive workplace interventions aiming to reduce the prevalence of effort-reward imbalance at work may be effective to reduce the prevalence of prediabetes among women.
A cross-sectional study on occupational hygiene in biowaste plants
Authors: Madsen Anne Mette , Rasmussen Pil Uthaug , Delsuz Mohammad Seeiar , Frederiksen Margit W 
Published: September 2024

Abstract
Recycling demands are increasing and new biowaste plants are established. The aim of this study is to obtain knowledge about occupational hygiene in biowaste pretreatment plants. At 6 plants, bioaerosol exposure, hand hygiene, and bioaerosol concentrations in work areas were investigated repeatedly. The total inflammatory potential (TIP) of exposures was measured using the human HL-60 cell line. Exposure to airborne bacteria, bacteria able to grow anaerobic, fungi(37°C), endotoxin, and TIP differed between plants and was lowest in a plant transporting waste in closed pipes compared to plants where waste was delivered on the receiving hall floor. Conversely, high exposures were measured in a plant that also processes compost. All microbial components had an impact on TIP of workers’ exposure with main effects of fungi and endotoxin. Seasonality was found for several exposures and TIP, and they were lowest in the winter. Concentrations of bacteria and fungi on workers’ hands at the end of the workday were 15 times higher for production than for nonproduction workers. In work areas, the concentrations of airborne fungi were highest in the waste-receiving area. Bacteria (3.2 µm) and anaerobic bacteria (4.0 µm) were present as larger airborne particles than fungi (2.8 µm), and bacteria were largest in the waste-receiving area. The microbial community compositions of exposures and work areas differed between plants and work areas. In conclusion, measures to reduce exposure should focus on the waste-receiving area and on the production workers. Differences in exposures and community compositions were found between seasons, work areas, work groups, and plants.
DrugDoctor: enhancing drug recommendation in cold-start scenario via visit-level representation learning and training
Authors: Kuang Yabin , Xie Minzhu 
Published: September 2024

Abstract
Medication recommendation is a crucial application of artificial intelligence in healthcare. Current methodologies mostly depend on patient-level longitudinal representation, which utilizes the entirety of historical electronic health records for making predictions. However, they tend to overlook a few key elements: (1) The need to analyze the impact of past medications on previous conditions. (2) Similarity in patient visits is more common than similarity in the complete medical histories of patients. (3) It is difficult to accurately represent patient-level longitudinal data due to the varying numbers of visits. To our knowledge, current models face difficulties in dealing with initial patient visits (i.e. in cold-start scenarios) which are common in clinical practice. This paper introduces DrugDoctor, an innovative drug recommendation model crafted to emulate the decision-making mechanics of human doctors. Unlike previous methods, DrugDoctor explores the visit-level relationship between prescriptions and diseases while considering the impact of past prescriptions on the patient’s condition to provide more accurate recommendations. We design a plug-and-play block to effectively capture drug substructure-aware disease information and effectiveness-aware medication information, employing cross-attention and multi-head self-attention mechanisms. Furthermore, DrugDoctor adopts a fundamentally new visit-level training strategy, aligning more closely with the practices of doctors. Extensive experiments conducted on the MIMIC-III and MIMIC-IV datasets demonstrate that DrugDoctor outperforms 10 other state-of-the-art methods in terms of Jaccard, F1-score, and PRAUC. Moreover, DrugDoctor exhibits strong robustness in handling patients with varying numbers of visits and effectively tackles “cold-start” issues in medication combination recommendations.
Poppers, the Politics of Exemption and the Characteristics of Poppers Users in the annual English Festival Study, 2014–23
Authors: Measham Fiona , McCormack Mark , Simmons Henry , Wignall Liam 
Published: September 2024

Abstract
This paper explores the relationship between socio-demographic characteristics, self-reported alkyl nitrite (‘poppers’) use and sexual behaviours against a backdrop of UK policy change and ambiguity surrounding legal status. In 2024, the Advisory Council on the Misuse of Drugs recommended a unique, government-initiated, legal exemption from the Psychoactive Substances Act 2016 for poppers, because of its use by gay and bisexual men to reduce the risk of injury during anal sexual intercourse. Data from the annual convenience sample English Festival Study 2014–23 (n = 11,566) were used for Bayesian regression analyses of self-reported poppers use in three-time frames: lifetime, past year and past month use. Gay men were significantly more likely to report poppers use and particularly those reporting past-year participation in anal sex. Providing a critical analysis of recent trends in UK drug policy, the authors highlight how differential discrimination occurs within drug control where targeted exemption meets the politics of protected characteristics in UK law. This paper argues that poppers, therefore, provide a unique example in UK drug policy of how an apparent liberalization of legislative control could bolster the overarching drug prohibition regime while maintaining the appearance of rationality and fairness.
Does the risk of hypersensitivity reactions to iopromide differ by sex, race, or across regions/countries? An analysis of 152 233 patients from 4 observational studies and the company’s pharmacovigilance database
Authors: Endrikat Jan , Ullmann Alexander , Gerlinger Christoph , Bhatti Aasia , Lengsfeld Philipp , Michel Alexander 
Published: September 2024

Abstract

Objective
To analyse the potential impact of patients’ sex, race, and region/country on the risk of hypersensitivity reactions after intra-venous or intra-arterial administration of iopromide.

Methods
Two analyses were performed. (1) The “Phase-IV-Analysis” evaluated an integrated pooled database of 4 non-interventional studies. (2) The “GPV-Analysis” evaluated case reports from the company’s pharmacovigilance database. The Phase-IV-Analysis was a nested case–control analysis of patients who received an injection of iopromide 300/370 mg iodine/mL. Cases had typical/unequivocal HSRs as defined by the ACR Committee on Drugs and Contrast Media 2018. The global pharmacovigilance (GPV)-Analysis was based on HSR case reports in the company database. Exposure estimates were derived from sales/market research data.

Results
The Phase-IV-Analysis comprised 152 233 patients from 37 countries. In the full-analysis set 145 033, 59 412, and 146 649 patients were included in the sex, race, and region/country cohort, respectively. The GPV-Analysis was based on 78.72 million administrations for sex and 118.56 million administrations for region/country. No GPV exposure data by race were available. Sex: Phase-IV-Analysis: The HSR incidence was significantly higher for women (0.72%) vs men (0.55%) (P ≤ .0001). The unadjusted odds ratio (OR) was 1.3 (95% CI, 1.154-1.499), the adjusted OR was 1.156 (95% CI, 1.006-1.328) (P = .04). GPV-Analysis: Reporting rates were 0.0102% for women and 0.0075% for men (P &lt; .0001). OR: 1.36 (95% CI, 1.3-1.43). Race: Phase-IV-Analysis: No significantly different HSR incidences for white (0.70%) and Asian (0.61%) patients (P = .3094) were detected. Region/country: Phase-IV-Analysis: The overall world HSR-incidence was 0.62%. Europe: 0.52%, Asia: 0.70%, United States: 0.75%, Germany: 0.51%, China: 0.41%, South Korea: 0.76%. GPV-Analysis: The overall world HSR-reporting rate was 0.015%, varying across regions/countries.

Conclusion
Women showed a slightly higher risk for HSRs than men. Impact of race was not found. HSR-reporting varied by region/country.

Advances in knowledge
Risk for HSRs was increased by female sex but not by race or region/country.
Theoretical and experimental studies on the effect of the 1,2-diketone group on geometry distortion for phenacene-type polycyclic aromatic compounds
Authors: Hamamoto Nobutsugu , Rakumitsu Kenta , Kusumoto Sotaro , Yokoyama Akihiro , Inokuchi Makoto 
Published: September 2024

Abstract
This paper addresses the geometry distortion of orthoquinone-containing phenacene-type compounds by comparing the structures of phenanthrene-9,10-dione, chrysene-5,6-dione, and picene-13,14-dione. Interestingly, the calculated geometry of chrysene-5,6-dione under the isolated state was drastically different from the experimental one observed by single-crystal X-ray analysis. Theoretical calculations suggested that the molecular geometry of the o-quinone derivatives was sensitive not only to the sterically intramolecular proximity between the carbonyl oxygen and the hydrogen atoms of the benzene rings but also to intermolecular interactions. The twist distortion affects properties such as oscillator strength and 1-electron transitions, for low-lying excited states.
Refocusing social work education on community work in Hong Kong: an urgent call
Authors: Cheung Johnson Chun-Sing 
Published: September 2024

Abstract
A dominant discourse in social work literature and textbooks is that community workers should take a proactive stance to pressure government officials to reform policy. Without any mission to downplay the political role of social work in the first place, the author of this paper argues that activist discourses from the 1970s are too old to inform contemporary struggles. In light of the neo-liberal, neo-managerial, post-colonial, and pan-political realities, antagonistic relationships between stakeholders in the community, politicians, opinion leaders, and the establishment have ushered in new-look community work in Hong Kong. Social work education on community development should undergo a transformation to help social work students reposition themselves in these chaotic times.
Significant low-temperature activity of tetragonal-type ZrO2-supported Ru catalysts for CO2 methanation
Authors: Sato Katsutoshi , Higuchi Hitomi , Nagaoka Katsutoshi 
Published: September 2024

Abstract
Conversion of CO2 with H2 to CH4 is a potential route for the utilization of CO2. Because CO2 methanation is an exothermic reaction, the equilibrium yield decreases with increasing temperature. A catalyst that exhibits high activity at low temperatures is thus highly desirable. We report here that a tetragonal-type ZrO2-supported Ru catalyst prepared by low-temperature calcination showed significant low-temperature activity for CO2 methanation. We surmise that an intermediate formate species formed over the tetragonal-type ZrO2 and enhanced the catalytic activity.