Search Results (186)

In developed countries such as Spain, where the population is increasingly aging, retirement planning and longevity risk represent major societal challenges. In Spain, in particular, a significant proportion of household wealth is concentrated in real estate, primarily in the form of owner-occupied housing. For this reason, one emerging financial product in the retirement savings space is the reverse mortgage (RM). This study examines the determinants of acceptance of this financial product using survey data collected from Spanish individuals. The intention to take out an RM is explained through performance expectancy (PE), effort expectancy (EE), social influence (SI), bequest motive (BM), financial literacy (FL), and risk (RK). The analysis applies machine learning techniques: decision tree regression is used to visualize variable interactions that lead to acceptance; random forest to improve predictive capability; and Shapley Additive Explanations (SHAP) to estimate the relative importance of predictors. Finally, Importance–Performance Map Analysis (IPMA) is employed to identify the variables that merit greater attention in the acceptance of RMs. SHAP values indicate that PE and SI are the most influential predictors of intention to use RMs, followed by BM and EE with moderate importance, whereas the positive influence of RK and FL is more reduced. The IPMA highlights PE and SI as the most strategic drivers, and RK and BM act as relevant barriers to the widespread adoption of RMs. Full article

There are no studies that have investigated factors influencing the outcome of dressage horses with suspensory ligament (SL) branch injuries. The aim was to determine if age, breed, work level, injury severity, anatomical localisation of injury, number of injured branches, periligamentous fibrosis, persistence of power Doppler signal or coexistent osteoarthritis of a metacarpophalangeal (MCP) or metatarsophalangeal (MTP) joint influenced the prognosis of 70 dressage horses. Outcome was defined as good (return to pre-injury level of work or higher), poor (return to a lower level of work) or retirement. Chi-squared or Fisher’s exact test and the Kruskal–Wallis test were used to identify relationships between variables of interest and follow-up outcome. Follow-up outcome was good in 44/70 horses (62.9%), poor in 13/70 (18.6.%) and 13/70 horses (19.1%) were retired due to no response to treatment. Ultrasonographic lesion grade (p = 0.07), cross-sectional area (CSA) of the SL (p = 0.96), CSA of the lesion (p = 0.28) and the lesion CSA as a percentage of the SL CSA (p = 0.40) were not associated with outcome. Power Doppler signal was present in 75.8% of injured branches at the initial examination. The severity of power Doppler signal was not associated with outcome (p = 0.20); however, persistence of power Doppler signal was negatively associated with outcome (p < 0.001). Other variables did not influence the follow-up outcome. Early recognition of SL branch injury is likely to result in a more favourable outcome with appropriate treatment and management. Full article

Rapid and accurate prediction of the maximum remaining life of lithium-ion batteries is a critical technical challenge for enhancing battery management system reliability and enabling the efficient secondary utilization of retired batteries. Traditional approaches that rely on full charge–discharge cycles or complex electrochemical models often suffer from long detection time and limited adaptability, making them unsuitable for fast testing scenarios. To address these limitations, this study proposes a novel capacity prediction method that integrates charging segment feature extraction with a back-propagation neural network (BPNN) co-optimized using the genetic algorithm (GA) and dung beetle optimizer (DBO). Leveraging the public CALCE datasets, key degradation-related features were extracted from partial charging segments to serve as inputs to the prediction framework. The hybrid GA_DBO algorithm is employed to jointly optimize the BPNN’s weights, learning rate, and activation thresholds. A comparative analysis is conducted across various charging durations (900 s, 1800 s, and 2700 s) to evaluate performance under different input lengths. Results reveal that the model using 1800 s charging segment features achieves the best overall accuracy, with a test set mean squared error (MSE) of 0.0001 Ah², mean absolute error (MAE) of 0.0092 Ah, root mean square error (RMSE) of 0.0122 Ah, and a coefficient of determination (R²) of 99.66%, demonstrating strong robustness and predictive capability. This research overcomes the traditional reliance on full cycles, demonstrating the effectiveness of short charging segments combined with intelligent optimization algorithms. The proposed method offers a high-precision, low-cost solution for online battery health monitoring and rapid sorting of retired batteries, highlighting its significant engineering application potential. Full article

Introduction: Traumatic brain injury (TBI) represents one of the leading health concerns worldwide, and it is associated with high morbidity, mortality, and substantial healthcare costs. This study aimed to assess inpatient cost determinant factors among TBI patients admitted to an Eastern European hospital, Cluj County Emergency Hospital, Romania, in 2022. Methods: A retrospective observational analysis was conducted on 90 TBI patients. Data on demographic factors, clinical variables, injury characteristics, and inpatient hospital costs were collected. Inpatient total cost differences considering categorical variables were analyzed using Wilcoxon and Kruskal–Wallis tests, and correlations of inpatient total costs with other continuous variables were analyzed using Spearman correlations. Results: Most patients were male (67.8%), urban residents (67.8%), retired (64.4%), and had a mild TBI (96.7%), and the main listed cause was falls (74.4%). The average inpatient cost was EUR 1115.79. There were no statistically significant differences for costs in TBI severity, PTA, or comorbidities. Inpatient costs were correlated with hospital length of stay (ρ = 0.979, 95% CI rho: 0.969 and 986, p < 0.001). While higher costs were seen in patients with PTA, more comorbidities, severe Marshall Scores, or return-to-work status, these differences were not statistically significant. Conclusions: Further research with larger, multicenter cohorts is needed to better understand the cost structure of TBI care and to inform policy decisions that are aimed at resource allocation and cost efficiency. Full article

Retired chemically polluted sites in southern Jiangsu Province, China, are characterized by dense nonaqueous phase liquids (DNAPLs) and extremely thick aquifers (>30 m), which pose substantial challenges for determining investigation and remediation depths during redevelopment and exploitation. This study constructed a 2D groundwater transport model using TMVOC to systematically investigate the migration, diffusion, and natural attenuation processes of two typical DNAPLs—1,2-dichloroethane (DCE) and carbon tetrachloride (CTC)—under three scenarios: individual transport, mixed transport, and heterogeneous aquifer conditions, with a simulation period of 35 years. In individual transport scenarios, DCE and CTC showed distinct migration behaviors. DCE achieved a maximum vertical transport distance of 14.01 m and a downstream migration distance of 459.58 m, while CTC reached 13.57 m vertically and 453.51 m downstream. When transported as a mixture, their migration was inhibited: DCE’s vertical and downstream distances decreased to 13.76 m and 440.46 m, respectively; and CTC’s to 13.23 m and 420.32 m, likely due to mutual solvent effects that altered their physicochemical properties such as viscosity and solubility. Under natural attenuation conditions, both DNAPLs ceased downstream transport by the end of the 6th year. DCE concentrations dropped below its risk control value (0.81 mg/L) by the 14th year, and CTC (with a risk control value of 0.23 mg/L) by the 11th year. By the 10th year, DCE’s downstream plume had retreated to 48.65 m, and CTC’s to 0.95 m. In heterogeneous aquifers, vertical upward transport of DCE and CTC increased to 14.82 m and 14.22 m, respectively, due to the partial absence of low-conductivity silt layers, while their downstream distances decreased to 397.99 m and 354.11 m, constrained by low-permeability lenses in the migration path. These quantitative results clarify the dynamic differences in DNAPL transport under varying conditions, highlighting the impacts of multicomponent interactions, natural attenuation, and aquifer heterogeneity. They provide critical references for risk management, scientific determination of remediation depths, and safe exploitation of retired chemically polluted sites with similar hydrogeological characteristics. Full article

Background: Late-life depression is a critical public health concern, particularly among older adults with chronic multimorbidity. Existing studies often focus on single-disease associations, neglecting the complex interplay of coexisting conditions. Understanding how multimorbidity patterns contribute to depression risk and identifying high-risk subgroups through integrated statistical and machine learning approaches remain underexplored, limiting targeted prevention strategies. Methods: Using data from the China Health and Retirement Longitudinal Study (CHARLS), latent class analysis (LCA) was employed to cluster multimorbidity patterns. Associations between these patterns and depression were analyzed using multivariable logistic regression, while predictive performance and interaction effects were evaluated via an XGBoost machine learning model. Results: Four distinct multimorbidity patterns were identified: cardio-metabolic, digestive–joint, respiratory, and cardiovascular–digestive pattern. All clusters showed significant independent associations with depression, with the cardiovascular–digestive pattern exhibiting the strongest association (OR = 4.56). However, the digestive–joint pattern demonstrated the highest predictive effects for depression. Sociodemographic factors—low income, limited education, female gender, and rural residence—emerged as robust predictors, amplifying depression risk in older adults with multimorbidity. Conclusions: This study bridges epidemiological insights with predictive analytics to inform depression risk stratification. We recommend routine depression screening for all individuals with cardiovascular–digestive diseases and prioritize screening for women with digestive–joint diseases. Additionally, low-income and rural-dwelling older adults with chronic conditions warrant heightened clinical vigilance. These findings provide a framework for integrating multimorbidity profiling into depression prevention protocols, addressing both biological and socioeconomic determinants. Full article

Background: Chronic kidney disease (CKD) significantly affects health-related quality of life (HRQoL), impacting physical and mental well-being. This study aimed to identify the key determinants influencing HRQoL among patients with CKD. Methods: A cross-sectional observational study was conducted from July 2022 to March 2023 at the Rajiv Gandhi Cooperative Multi-Specialty Hospital, Palakkad, Kerala, South India, including 154 patients diagnosed with CKD stages 3 to 5. Eligible participants were required to be at least 18 years of age and have a confirmed diagnosis of CKD, specifically stages 3 to 5, with prior treatment. CKD stages were defined according to the Kidney Disease: Improving Global Outcomes (KDIGO) 2012 guidelines, based on estimated glomerular filtration rate (eGFR) thresholds as follows: Stage 3 (eGFR 30–59 mL/min/1.73 m²), Stage 4 (eGFR 15–29 mL/min/1.73 m²), and Stage 5 (eGFR < 15 mL/min/1.73 m²). Participants were classified into stages based on their most recent stable eGFR value at the time of recruitment. HRQoL was assessed using the European Quality of Life-5 Dimensions-3 Levels (EQ-5D-3L) questionnaire. Chi-square, ANOVA, and multivariate regression were used to analyze associations with EQ-5D-3L domains. Results: Out of 154 participants, 68.8% were male, 91.6% were aged over 50 years, and 63.6% were from rural areas. Most had primary education (55.2%) and were unemployed, retired, or housewives (66.2%). As CKD progressed, comorbidities, particularly diabetes mellitus and coronary artery disease (CAD), increased, with Stage 5 showing the highest prevalence. Clinical markers showed significant declines in the glomerular filtration rate (GFR) (Stage 3: 49.16 ± 7.59, Stage 4: 22.37 ± 3.88, Stage 5: 8.79 ± 1.68) and hemoglobin (Stage 3: 10.45 ± 0.84, Stage 4: 8.88 ± 0.60, Stage 5: 7.12 ± 0.53) and an increase in serum creatinine (Stage 3: 1.72 ± 0.40, Stage 4: 3.21 ± 0.44, Stage 5: 7.05 ± 1.46). HRQoL assessments showed significant declines in mobility, self-care, usual activities, pain, and anxiety/depression with advancing CKD. Mobility issues increased from 61.2% in Stage 3 to 62.0% in Stage 5, with greater difficulties in self-care and usual activities at Stage 5. Pain and anxiety/depression worsened across stages. Multivariate analysis identified female gender, older age (≥50 years), lower education, unemployment, multiple comorbidities, smoking, lack of social support, and advanced CKD stages as significant factors linked to impaired HRQoL. CKD stage 5 (GFR < 29 mL/min/1.73 m²) and high serum creatinine (>1.2 mg/dL) were associated with significantly higher odds of impairment in all HRQoL domains. Conclusions: This study highlights that factors such as female gender, older age, lower education, unemployment, multiple comorbidities, smoking, advanced CKD stages, and high serum creatinine levels are associated with reduced quality of life in CKD patients. Conversely, social support acts as a protective factor. The findings emphasize the need for targeted interventions that address both medical care and psychosocial aspects, including lifestyle changes, patient education, mental health support, and community involvement, to improve CKD patients’ well-being. Full article

Osteoarthritis (OA) is a chronically progressive degenerative arthropathy characterized by the loss of cartilage, changes in subchondral architecture, and ongoing inflammation resulting in reduced mobility and pain. This study assessed the treatment potential of a combination of chondroitin and glucosamine enriched with Curcumin C3 Complex (C3GC) in modulating the pathophysiological features in mouse models with surgically induced OA and in dogs with naturally occurring OA. A cohort of 24 male C57BL/6 mice aged 3 months old were surgically destabilized with medial meniscus (DMM) to cause osteoarthritis. These animals underwent a nutritional intervention with C3GC or with GC over a course of 8 weeks. In order to evaluate cartilage health and subchondral bone structure, we carried out a combination of behavioral tests, micro-computed tomography (micro-CT), and histopathological examinations. In addition, a cohort of 12 OA-diagnosed retired police dogs were administered C3GC supplements or conventional care over a course of 30 days, with pain measurement and serum concentrations of MMP-3 and TNF-α determined before and after treatment. According to our findings, the administration of C3GC was determined to preserve subchondral microarchitectural structure integrity (p < 0.05) and resulted in better motor function in comparison with GC. In animals taking nutritional supplements, the OARSI scores of joint tissue sections were reduced, with the medial tibial plateau OARSI score being particularly low in the C3GC group (p < 0.0001). In dogs, treatment with C3GC resulted in a 24.5% reduction in serum MMP-3 levels (p < 0.01), and there was also a 20.8% decrease in serum TNF-α levels (p < 0.05), along with a decrease in subjective pain assessment. The results are in support of the chondroprotective, anti-inflammatory, and analgesic properties of C3GC and justify future research on the potential utility of C3GC in treating osteoarthritis. Full article

The built environment has been widely recognized as a critical determinant of physical activity among older adults. However, urban–rural disparities and the non-linear effects of environmental features remain underexplored. Using interpretable machine learning (random forest model) on nationwide representative data from 2526 older adults in the China Health and Retirement Longitudinal Study (CHARLS) database, this study identified both common and distinct risk factors for insufficient moderate-to-vigorous physical activity (MVPA) across diverse urban and rural contexts. The results revealed a location-based gradient in physical activity insufficiency: rural areas < suburban areas < central urban areas. Rural older adults faced greater constraints from safety concerns and transportation accessibility limitations. In comparison, urban older adults would benefit from targeted improvements in built environment quality, particularly elevator accessibility and diverse public activity spaces. Furthermore, non-linear relationships were observed between built environment features and physical activity, elucidating the “density paradox”: while moderate urban compactness promoted active behaviors, excessive density (>24,000 persons/km²), perceived overcrowding, and over-proximity to specific facilities (<1 km) were linked to reduced MVPA. These findings underscore the necessity for differentiated policy interventions in urban and rural settings to address the distinct environmental needs of older adults. Meanwhile, in urban planning, it is crucial that we balance spatial compactness and functional diversity within optimal thresholds for creating sustainable and inclusive built environments. Although a compact design may enhance mobility, equal attention must be paid to preventing spatial disorder from over-densification. Full article

China’s population is aging rapidly, with a large proportion of elderly individuals “aging in place”. In central areas of large cities, the amount of community and home-based elderly care services provided by the government and for-profit organizations are insufficient to meet the demands of these “aging in place” elderly. Taking the core area of Beijing as the spatial scope, this empirical study collects the demand on services of the main types of elderly residents in community and home-based dwelling through questionnaires (n = 242) and employs a mixed-methods approach for analysis. Descriptive statistics and exploratory factor analysis are used to determine the categories and levels of those demands, and machine learning methods (random forest regression model) are used to calculate the importance of various influencing factors (features of the elderly and subdistricts’ built environment) on them. It is shown that elderly residents have a higher demand for psychological and physical condition maintenance services (mean = 3.40), and a lower demand for reconciliation and rights defense services (mean = 3.08). The results also show that the built environment factors are very important for the elderly on choosing demands, especially mean distance of CECSs (community elderly care stations) to downtown landmarks and main roads in subdistricts, and characteristics of CECS. The elderly’s own features also have a relatively important impact, especially their living arrangements, caregivers, and occupations before retirement. This study applies machine learning techniques to sociological survey analysis, helping to understand the intensity of elderly people’s demand for various community and home-based elderly care services. It provides a reference for the allocation of such service resources. Full article

This paper delves into the impact of the Tracking and Data Relay Satellite (TDRS) constellation orbit accuracy on Differenced One-Way Doppler (DOWD)-based user spacecraft orbit determination, specifically when the TDRS orbit is derived solely from Telemetry, Tracking, and Command (TT&C) range-only tracking. The study revealed that retiring the Bilateration Ranging Transponder System (BRTS) without fully comprehending the TT&C bias and its uncertainty could hinder achieving the required level of orbit precision for both TDRS satellites (<75 m) and user spacecraft (<300 m). If the TT&C range bias and its associated uncertainties are not accurately calibrated in a TT&C-based TDRS orbit, it could lead to an orbit error of up to 17 km in the TDRS, yielding a DOWD-based orbit error of up to 5 km for the user spacecraft. The research identifies a linear relationship between TDRS orbit error and user spacecraft orbit error, with several factors impacting the slope of this relationship, including the number of DOWD passes obtained, the TDRS’s relative position during DOWD measurement acquisition, and dynamic errors in the user spacecraft orbit. Despite the imprecision in the orbits of the TDRS and user spacecraft, the Local Oscillator Frequency drift estimation remains accurate. Full article

The dedieselization program is one of the PLN’s (Indonesia’s state-owned utility company) programs to reduce the greenhouse gas effect. The program manifestation is the integration of photovoltaic (PV) systems into isolated island networks by substituting diesel generators. This condition introduces challenges such as diminished system strength, specifically, decreased frequency and voltage stability. This study focuses on Panjang Island, one of the target locations for the PLN’s dedieselization program, which currently relies entirely on diesel generators for electricity. As part of the transition to a PV-based power supply, retired diesel generators are proposed for conversion into synchronous condensers (SCs) to enhance system stability by providing inertia and reactive power support. By employing system modeling, steady-state analysis, and dynamic simulations, this study evaluates the effects of SC penetration on Panjang Island. The findings demonstrate that SCs improve grid stability by offering voltage support, increasing short-circuit capacity, and contributing to system inertia. Furthermore, a system assessment flowchart is also proposed to guide SC deployment based on network characteristics. Short-circuit ratios (SCRs) and voltage drops are evaluated as key parameters to determine the feasibility of SC penetration in a system. Converting retired diesel generators into SCs provides a resilient, stable grid as renewable energy penetration increases, optimizing system performance and reducing network losses. Full article

The optimal management of pension funds has become increasingly critical. As the population ages, the effective management of pension funds is essential for the social security system. The primary goal of this paper is to develop a deterministic nonlinear multi-objective optimization model to determine the contribution rates in a defined contribution pension system. The computational optimization model was implemented using the LINGO language. In the first part of this study, three main scenarios were analyzed considering different inflation rates, focusing on the objective function that minimizes the salary percentages workers pay when saving for a specified period while aiming to achieve a certain number of coverage years. The first scenario assumes that the worker desires an economic quality equivalent to their working life, showing that contribution rates range from 10% to 30% (with a 3% inflation rate). The second scenario posits that the worker only requires 80% of their equivalent salary during retirement, resulting in contribution rates directly proportional to those in scenario 1 (using the same parameters). The third scenario speculates that inflation may reach 7% per year, causing contribution rates to rise significantly from 40% to 80%. Finally, the Pareto front illustrates the trade-off between the contribution rate and the coverage years based on scenario 1 parameters. Full article

This study investigated the individuals’ perspectives towards participating in retirement planning in the mining industry in South Africa. The study employed a quantitative research approach. The study sampled 172 mineworkers from the selected mining company. A self-administered questionnaire was tested for validity and reliability and was used to collect primary data from the respondents. This study employed the logistic regression model and performed the Hosmer–Lemeshow test to evaluate the fit of the logistic regression and the Chi-square to determine the significance of the results. In this study, the data were analysed using descriptive and inferential statistics. The findings revealed that some participants are satisfied with their involvement in the retirement funds and are contributing to the retirement funds provided by the company. Furthermore, this study found that the majority of the respondents will be financially independent after retirement; however, there is still a firm belief of uncertainty about not being financially independent. The study found a significant and positive relationship between age and participation in retirement planning. Furthermore, a positive and significant link was found between marital status and participation in retirement planning as well as between employment status and participation in retirement planning. The study was limited to the selected company based in Gauteng. The practical implication of this paper informs the companies, policymakers, and government to prioritise awareness of retirement planning based on demographical factors such as age, marital status, and employment status to prepare mineworkers for retirement. The findings are expected to persuade the mining sector to pay special attention to the awareness and understanding of retirement planning. Full article

Background/Objectives: The prevalence of type 2 diabetes and smoking is increasing in developing countries and is associated with deteriorated health outcomes. Also, addiction to smartphone use is an alarming behavior that can be associated with clinical factors. This study aimed to determine the prevalence and clinical correlates of smartphone addiction in smokers with T2DM in Jordan, with a particular focus on the role of medications. Methods: This cross-sectional study recruited patients from Prince Hamza Hospital, Jordan, according to pre-defined criteria. Besides demographics and clinical information, this study used the validated Arabic version of the Smartphone Addiction Scale to assess addiction to smartphones and a multivariable regression analysis to identify the correlates of smartphone addiction. Results: Data analyzed from 346 patients revealed that 117 (33.8%) of these participants reported addiction to smartphones. Patients who had been diagnosed with T2DM for less than five years (aOR = 3.30; 95% CI = 1.43–7.60), who were “employed” (aOR = 8.85; 95% CI = 2.20–35.64), and who were “retired” (aOR = 11.46; 95% CI = 2.72–48.23) all reported a significantly (p < 0.05) higher odds of smartphone addiction. In contrast, patients on “sulfonylurea” (aOR = 0.18; 95% CI = 0.06–0.53); “metformin” (aOR = 0.19; 95% CI = 0.06–0.66), and “gabapentin” (aOR = 0.16; 95% CI = 0.04–0.67) and those with “comorbid hypertension” (aOR = 0.15; 95% CI = 0.06–0.38) had a significantly (p < 0.05) lower odds of smartphone addiction. Conclusion: These alarming results require adequate action from the health authorities to raise awareness of adopting positive behaviors that could improve the well-being of this high-risk population. Full article