Search Results (294)

Jilin Province, an important commodity grain base in China, relies on groundwater resources for its agricultural development. The implementation of a series of policies, including agricultural subsidies and food security policies, has led to a rapid expansion of the sowing area in recent decades, resulting in an increase in agricultural water demand. This has had a significant impact on the groundwater system. It is therefore imperative to understand the dynamics of the groundwater to ensure the security of water resources, ecological security, and food security. An evaluation of the sustainability of groundwater resources in Jilin Province was conducted through a quantitative analysis of the reliability, resilience, and vulnerability of groundwater. This analysis was informed by the inversion of changes in groundwater reserves over a period of 249 months, commencing from 2002-04 to 2022-12. The inversion process utilized data from the Gravity Recovery and Climate Experiment (GRACE) gravity satellite and Global Land Data Assimilation System (GLDAS), offering a comprehensive view of the temporal dynamics of groundwater reserves in the region. The results indicated the following: (1) Groundwater storage (total amount of water below the surface) in Jilin Province exhibited an overall decreasing trend, with the highest groundwater level recorded in June and the lowest in September on a monthly basis. (2) Prior to September 2010, groundwater reserves were in surplus most of the time. From October 2010 to August 2018, however, they began to fluctuate between surplus and deficit states. Since September 2018, the reserves have been in a long-term deficit, showing an overall downward trend. (3) Prior to 2005, the groundwater system was at a high/extremely high level of sustainability. However, following 2011, it fell to a very low level of sustainability and has continued to deteriorate. (4) The maximum information coefficient and correlation analysis indicate that the sown area is the most significant factor contributing to the decline in the sustainability of the groundwater system. This study reveals the spatial and temporal distribution pattern and evolution trend of groundwater resources sustainability in Jilin Province, and provides theoretical and data support for regional groundwater resources protection and management. Full article

Vehicular communication is crucial for the future of intelligent transportation systems. However, providing continuous high-data-rate connectivity for vehicles in hard-to-reach areas, such as highways, rural regions, and disaster zones, is challenging, as deploying ground base stations (BSs) is either infeasible or too costly. In this paper, multiple unmanned aerial vehicles (UAVs) using millimeter-wave (mmWave) bands are proposed to deliver high-data-rate and secure communication links to vehicles. This is due to UAVs’ ability to fly, hover, and maneuver, and to mmWave properties of high data rate and security, enabled by beamforming capabilities. In this scenario, the vehicle should autonomously select the optimal UAV to maximize its achievable data rate and ensure long coverage periods so as to reduce the frequency of UAV handovers, while considering the UAVs’ battery lives. However, predicting UAVs’ coverage periods and optimizing mmWave beam directions are challenging, since no prior information is available about UAVs’ positions, speeds, or altitudes. To overcome this, out-of-band communication using orthogonal time-frequency space (OTFS) modulation is employed to enable the vehicle to estimate UAVs’ speeds and positions by assessing channel state information (CSI) in the Delay-Doppler (DD) domain. This information is used to predict maximum coverage periods and optimize mmWave beamforming, allowing for the best UAV selection. Compared to other benchmarks, the proposed scheme shows significant performance in various scenarios. Full article

Life testing of products often requires extended observation periods. To shorten the duration of these tests, products can be subjected to more extreme conditions than those encountered in normal use; an approach known as accelerated life testing (ALT) is considered. This study investigates the estimation of unknown parameters and the acceleration factor for the modified Fréchet-Lomax exponential distribution (MFLED), utilizing Type II progressively first-failure censored (PFFC) samples obtained under the framework of constant-stress partially accelerated life testing (CSPALT). Maximum likelihood (ML) estimation is employed to obtain point estimates for the model parameters and the acceleration factor, while the Fisher information matrix is used to construct asymptotic confidence intervals (ACIs) for these estimates. To improve the precision of inference, two parametric bootstrap methods are also implemented. In the Bayesian context, a method for eliciting prior hyperparameters is proposed, and Bayesian estimates are obtained using the Markov Chain Monte Carlo (MCMC) method. These estimates are evaluated under both symmetric and asymmetric loss functions, and the corresponding credible intervals (CRIs) are computed. A comprehensive simulation study is conducted to compare the performance of ML, bootstrap, and Bayesian estimators in terms of mean squared error and coverage probabilities of confidence intervals. Finally, real-world failure time data of light-emitting diodes (LEDs) are analyzed to demonstrate the applicability and efficiency of the proposed methods in practical reliability studies, highlighting their value in modeling the lifetime behavior of electronic components. Full article

Tillage is a major factor influencing soil biological communities, particularly earthworms, which play a key role in soil structure and nutrient cycling. To address soil degradation, less-intensive tillage practices are increasingly being adopted globally and have shown positive effects on earthworm populations when applied consistently over extended periods. However, understanding of the earthworm population dynamics in the period following the implementation of changes in tillage practices remains limited. This three-year field study (2021–2023) investigates earthworm populations during the early transition phase (4–6 years) following the conversion from conventional ploughing to conservation (<8 cm depth, with residue retention) and no-tillage systems in a temperate arable system in central Slovenia. Earthworms were sampled annually in early October from three adjacent fields, each following the same three-year crop rotation (maize—winter cereal + cover crop—soybeans), using a combination of hand-sorting and allyl isothiocyanate (AITC) extraction. Results showed that reduced tillage practices significantly increased both earthworm biomass and abundance compared to conventional ploughing. However, a significant interaction between tillage and year was observed, with a sharp decline in earthworm abundance and mass in 2022, likely driven by a combination of 2022 summer tillage prior to cover crop sowing and extreme drought conditions. Juvenile earthworms were especially affected, with their proportion decreasing from 62% to 34% in ploughed plots and from 63% to 26% in conservation tillage plots. Despite interannual fluctuations, no-till showed the lowest variability in earthworm population. Long-term monitoring is essential to disentangle management and environmental effects and to inform resilient soil management strategies. Full article

Background/Objectives: This retrospective multicenter study, conducted within the ORCHESTRA Project, investigated SARS-CoV-2 reinfections among 5777 healthcare workers (HCWs) from four University Hospitals (Modena, Verona, Padova and Trieste) in northern Italy, aiming to assess the risk of reinfection and its determinants, comparing the clinical characteristics of reinfections with those of first infections, and examining the impact of preventive measures and vaccination strategies. Methods: HCWs completed an online questionnaire between June and August 2022. The survey collected demographic, occupational, and clinical data, including information on first infections and reinfections. Statistical analyses were performed using SPSS 28.0, through bivariate and multivariate approaches. Results: Response rates were 41.8% for Modena, 39.5% for Verona, 17.9% for Padova, and 17.4% for Trieste. Among the respondents, 4.8% (n = 276) experienced 2 infections and 0.5% (n = 27) reported 3 infections, out of a total of 330 reinfection cases. Additionally, 43.0% (n = 2787) reported only one infection, while 51.5% were never infected. Reinfection rates increased across five study phases (based on the epidemiological context), likely due to the emergence of new SARS-CoV-2 variants. A booster vaccine dose significantly reduced reinfection risk. Higher reinfection risk was found among HCWs aged ≤30 years, those with chronic respiratory diseases, and those working in COVID-19 wards, particularly nurses and allied health professionals. Reinfections were associated with a lower frequency of symptoms both during the period of swab positivity and after a negative swab, as well as with a shorter duration of swab positivity. No significant differences in symptom duration were found between first infections and reinfections. Conclusions: Despite its limitations, the online questionnaire proved a useful tool. Natural infection and vaccination reduced both reinfection risk and symptom severity. Prior infections should be considered in planning vaccination schedules and prioritizing HCWs. Full article

Background and Objectives: Long-acting cabotegravir and rilpivirine (LA-CAB/RPV) offers an alternative to daily oral antiretroviral therapy (ART) for people living with HIV (PLWH). Although LA-CAB/RPV has been approved in Turkey, the country remains in the pre-rollout period, and national data on patient perspectives are lacking. This is the first nationwide study from Turkey, a setting of increasing HIV incidence, assessing PLWH perspectives on switching to LA-CAB/RPV and the influence of motivational factors on treatment preferences. Materials and Methods: A prospective, multicenter, cross-sectional study was conducted across 11 HIV treatment centers representing all regions of Turkey. Virologically suppressed PLWH meeting current eligibility criteria for LA-CAB/RPV were included. Treatment preferences (switch to LA-CAB/RPV or remain on oral ART) and five anticipated motivational domains, namely perceived efficacy, safety, convenience, privacy, and cost, were systematically assessed through structured, face-to-face interviews. Results: Among 200 eligible participants, 86% (n = 172) preferred switching to LA-CAB/RPV. In all subgroups, LA-CAB/RPV was preferred over oral ART, except for those with no formal literacy. Prior awareness of LA-CAB/RPV was significantly associated with the switching preference (p < 0.001), with healthcare providers being the most common source of information, at 45.5% (n = 172) (p < 0.001). Residential proximity to the healthcare center (p = 0.018) and all motivational factors significantly influenced the preference (p < 0.05). Notably, when participants who initially chose to remain on oral ART were asked whether they would reconsider switching if injections were administered every six months, overall preference for long-acting therapy increased from 86% to 98%. Conclusions: High clinical eligibility and strong acceptability for LA-CAB/RPV were observed among Turkish PLWH. Our findings demonstrate that structured motivational factors significantly influence the treatment preference. Addressing these patient-centered factors and logistical barriers may support the successful integration of long-acting therapies into routine HIV care. Future longer-interval agents may improve patient-centered acceptability. Full article

High-precision positioning is the foundation for the functionality of various intelligent agents. In complex environments, such as urban canyons, relative pose estimation using cameras is a crucial step in high-precision positioning. To take advantage of the ability of an inertial measurement unit (IMU) to provide relatively accurate gravity prior information over a short period, we propose a minimal solution method for the relative pose estimation of a stereo camera system assisted by the IMU. We rigidly connect the IMU to the camera system and use it to obtain the rotation matrices in the roll and pitch directions for the entire system, thereby reducing the minimum number of corresponding points required for relative pose estimation. In contrast to classic pose-estimation algorithms, our method can also calculate the camera focal length, which greatly expands its applicability. We constructed a simulated dataset and used it to compare and analyze the numerical stability of the proposed method and the impact of different levels of noise on algorithm performance. We also collected real-scene data using a drone and validated the proposed algorithm. The results on real data reveal that our method exhibits smaller errors in calculating the relative pose of the camera system compared with two classic reference algorithms. It achieves higher precision and stability and can provide a comparatively accurate camera focal length. Full article

Banana is an important cash and food crop worldwide. Recent outbreaks of banana diseases are threatening the global banana industry and smallholder livelihoods. Remote sensing data offer the potential to detect the presence of disease, but formal analysis is needed to compare inferred disease data with observed disease data. In this study, we present a novel remote-sensing-based framework that combines Landsat-8 imagery with meteorology-informed phenological models and machine learning to identify anomalies in banana crop health. Unlike prior studies, our approach integrates domain-specific crop phenology to enhance the specificity of anomaly detection. We used a pixel-level random forest (RF) model to predict 11 key vegetation indices (VIs) as a function of historical meteorological conditions, specifically daytime and nighttime temperature from MODIS and precipitation from NASA GES DISC. By training on periods of healthy crop growth, the RF model establishes expected VI values under disease-free conditions. Disease presence is then detected by quantifying the deviations between observed VIs from Landsat-8 imagery and these predicted healthy VI values. The model demonstrated robust predictive reliability in accounting for seasonal variations, with forecasting errors for all VIs remaining within 10% when applied to a disease-free control plantation. Applied to two documented outbreak cases, the results show strong spatial alignment between flagged anomalies and historical reports of banana bunchy top disease (BBTD) and Fusarium wilt Tropical Race 4 (TR4). Specifically, for BBTD in Australia, a strong correlation of 0.73 was observed between infection counts and the discrepancy between predicted and observed NDVI values at the pixel with the highest number of infections. Notably, VI declines preceded reported infection rises by approximately two months. For TR4 in Mozambique, the approach successfully tracked disease progression, revealing clear spatial spread patterns and correlations as high as 0.98 between VI anomalies and disease cases in some pixels. These findings support the potential of our method as a scalable early warning system for banana disease detection. Full article

When a space target malfunctions and is no longer controlled by its attitude control system, it usually tumbles in orbit and exhibits a slow spinning state. Accurately estimating the on-orbit attitude of spinning space targets is of vital importance for ensuring the operation of space assets. Moreover, it plays a significant role in tasks such as reentry observation and collision avoidance. Currently, most existing methods estimate the attitude of space targets by using a single inverse synthetic aperture radar (ISAR) for long-term observation. However, this approach not only requires a long observation time but also fails to estimate the attitude of spinning targets. To address these limitations, this paper proposes a novel approach for estimating the attitude of spinning space targets, which utilizes the joint observations of a multiple-station ISAR. Specifically, the proposed method fully exploits the projection principle of ISAR imaging and uses an ISAR high-resolution network (ISAR-HRNet) to automatically extract the projection features of typical components of the target. Then, the analytical expressions for the target’s instantaneous attitude and spin vector under the multi-station observation imaging projection model are derived. Based on the extracted features of the typical components, the lengths, orientations, and spin vectors of the space target are determined. Importantly, the proposed method can achieve the attitude estimation of the spinning space targets within a single observation period, without the need for manual intervention or prior information about the target’s three-dimensional (3D) model. Additionally, the analytical method for solving the spin vector offers high efficiency and accuracy. Finally, the effectiveness of the proposed attitude estimation algorithm is verified by experiments on simulated data, and the performance of the ISAR-HRNet is also tested in the key point extraction experiments using measured data. Full article

Purpose: Suicide is a leading cause of death among children and adolescents worldwide. This study examined the prevalence and characteristics of suicides among children and adolescents (aged ≤ 19 years) over a 13-year period in the broader area of Athens, Greece. Key aspects analyzed included victim demographics, circumstances surrounding the incidents, and methods employed. Methods: A retrospective analysis was conducted on autopsy cases performed at the Department of Forensic Medicine and Toxicology, National and Kapodistrian University of Athens, from 1 January 2011, to 31 December 2023. Results: Out of 5819 autopsies conducted between 2011 and 2023, 371 were classified as suicides. Among these, 12 cases (representing 3.2% of suicides) involved children and adolescents aged ≤ 19 years and met the study’s inclusion criteria for detailed forensic analysis. The average age of the victims was 17.7 ± 2.1 years (range: 14–19), with males representing 58.3% of cases. Hanging was the most common method of suicide (9 cases, 75.0%), followed by firearm use, falls from height, and hydrogen sulfide inhalation (one case each). Death occurred in the home in 10 cases (83.3%), with 6 specifically taking place in the bedroom. Scars indicative of prior self-harming behavior were present in two cases (16.7%), while suicide notes were found in three cases (25.0%). Toxicological analysis revealed alcohol and cannabis use in one case, cannabis alone in one case, and alcohol alone in two cases. Four victims (33.3%) had a documented psychiatric diagnosis, with two of them under antidepressant treatment at the time of death. Conclusions: This study highlights the forensic value of autopsy-based investigations in unveiling hidden patterns of adolescent suicidality and informs targeted prevention strategies. Integrating medico-legal findings into public health responses may enhance early identification and intervention in vulnerable youth populations. Full article

Background/Objectives: The COVID-19 pandemic exposed critical vulnerabilities in healthcare systems, especially in ensuring continuity of care for patients with chronic diseases. Rehabilitation services, essential for recovery following SARS-CoV-2 infection, were among the most disrupted. This exploratory study aimed to assess Romanian patients’ perceptions of the accessibility and quality of post-COVID-19 rehabilitation services, focusing on individuals with chronic conditions. Methods: This exploratory cross-sectional study was conducted over a 12-month period in 2024. Data were collected from 76 adult patients diagnosed with at least one chronic condition (hypertension, diabetes mellitus, ischemic heart disease, cancer, or chronic obstructive pulmonary disease) and with confirmed prior SARS-CoV-2 infection. Most participants were recruited during outpatient specialty consultations, with a smaller number included from hospital settings, all located in Bucharest. A structured questionnaire was administered by the principal investigator after obtaining informed consent. Quantitative data were analyzed using non-parametric methods following confirmation of non-normal distribution via the Shapiro–Wilk test (p < 0.05). Satisfaction scores were reported as medians with interquartile ranges (IQR), and group comparisons were performed using the Mann–Whitney U test. A mixed-methods approach was employed, including thematic analysis of open-ended responses. Results: Patient satisfaction with rehabilitation services was consistently low. The median satisfaction scores [IQR] were accessibility 1.0 [0.0–2.0], quality of services 0.0 [0.0–4.0], staff empathy 0.0 [0.0–5.0], and perceived effectiveness 0.0 [0.0–5.0]. The median score for perceived difficulties in access was 1.0 [1.0–2.0], indicating widespread barriers. No statistically significant differences were observed between urban and rural participants or across chronic disease categories. Thematic analysis (n = 65) revealed key concerns including lack of publicly funded services, cost barriers, limited physician referral, service scarcity in rural areas, and demand for home-based rehabilitation options. Conclusions: Romanian patients with chronic illnesses and previous SARS-CoV-2 infection continue to face substantial barriers in accessing post-COVID-19 rehabilitation services. These findings highlight the need for more equitable and integrated recovery programs, especially for vulnerable populations in underserved settings. Full article

Background/Objectives: Prognostic information for nonmetastatic prostate cancer (nmPC) patients with prevalent vertebral fractures (PVFs) is very limited. Vertebral fractures can impair physical function, limit activities of daily living, and decrease quality of life. Prevention of vertebral fractures may be important to improve patient prognosis. This study aims to investigate the impact of the presence and severity of PVFs on overall survival in patients with nmPC undergoing androgen deprivation therapy (ADT). Methods: A total of 275 men (median age: 73 years) with nmPC who underwent ADT were studied retrospectively. The median observation period was 55 months. Variables included age, body mass index, T classification, N classification, Gleason score, and pretreatment serum prostate-specific antigen levels. PVF was diagnosed from the sagittal computed tomography images of Th1 to L5 before initiating ADT, and the severity was determined by the number of PVFs and the Semiquantitative (SQ) method. Hazard ratios and 95% confidence intervals for overall survival were calculated using the Cox proportional hazards model. Results: During the observation period, 30 patients died from all causes. Multivariate Cox regression analysis identified multiple PVFs and high-grade PVFs, as determined by the SQ method, as significant predictors of overall survival. The analysis utilized two adjustment models: one adjusted for age only and the other adjusted for age, Gleason score, and clinical T stage. Conclusions: Multiple PVFs and high-grade PVF determined by the SQ method prior to ADT initiation were associated with higher all-cause mortality in nmPC patients treated with ADT. Full article

This study investigates how various renewable energy technologies influence national carbon intensity (CO₂ emissions per unit of GDP) across 184 countries over the period 2000–2020. In the context of Sustainable Development Goals (SDG 7 and SDG 13) and the post-Paris-Agreement policy landscape, it addresses the gap in understanding technology-specific decarbonization effects and the role of governance. A dynamic panel framework employing the Dynamic Common Correlated Effects (DCCE) estimator accounts for cross-sectional dependence and temporal persistence, while disaggregating total renewables into hydropower, wind, solar, and geothermal generation. Environmental regulation is incorporated as a moderating variable using the World Bank’s Regulatory Quality index. Empirical results demonstrate that higher renewable generation is associated with statistically significant reductions in carbon intensity, with hydropower showing the most consistent negative effect across all income groups. Solar and geothermal technologies yield substantial carbon-reducing impacts in lower-middle-income settings once supportive policies are in place. Wind exhibits heterogeneous outcomes: positive or insignificant effects in some high- and upper-middle-income panels prior to 2015, shifting toward neutral or negative after more stringent regulation. Interaction terms reveal that stronger regulatory environments amplify renewable-driven decarbonization, particularly for intermittent sources such as wind and solar. Key contributions include (1) a comprehensive global assessment of four disaggregated renewable technologies; (2) integration of regulatory quality into decarbonization pathways, illustrating post-2015 policy moderations; and (3) methodological advancement through a large-sample DCCE approach that captures unobserved common shocks and heterogeneous country dynamics. These findings inform targeted policy measures—such as prioritizing hydropower where feasible, strengthening regulatory frameworks, and tailoring technology strategies—to accelerate low-carbon energy transitions worldwide. Full article

Background: Preconception diet and nutritional status are important determinants of reproductive and pregnancy health. As a comprehensive evaluation, this paper describes harmonization of diet data across multiple cohorts including over 50,000 participants and the differences between them. This information may be useful for developing targeted strategies to improve women’s diet prior to pregnancy for optimal prenatal health outcomes. Methods: The Preconception Period Analysis of Risks and Exposures influencing health and Development (PrePARED) consortium incorporates studies covering the preconception period and includes both couples planning pregnancy and studies covering the reproductive period but not focused on pregnancy. We harmonized data on 56,520 participants from seven cohort studies that collected data during the preconception period. We generated data on diet quality according to the International Federation of Gynecology and Obstetrics (FIGO) nutrition checklist to examine diet quality measures across the cohorts and compare estimates of diet quality across studies. Four studies used food frequency questionnaires; one used a study-specific diet history; one used two 24 h dietary recalls; and one used a short series of general diet questions. Positive responses on the six FIGO questions were tallied to calculate a total diet quality score. Results: Cohort samples varied in terms of age; socioeconomic status; race; ethnicity; and geographic region. Across the cohorts, participants met a median of three or four of the FIGO criteria for diet quality; those most commonly met were recommendations for consumption of meat and protein, while those least commonly met were recommendations for limiting consumption of processed foods and snacks. There was greater variation in meeting recommendations for the consumption of fruits and vegetables; dairy; fish; and whole grains. The percentage meeting ≤ 2 criteria ranged from 6.4% (Coronary Artery Risk Development in Young Adults) to 40.4% (Bogalusa Heart Study). Discussion: There was wide variability across preconception cohort studies in the extent to which participants met FIGO dietary guidelines. Although studies were conducted in populations that were not likely to be malnourished, it was rare for women to meet all the preconception dietary recommendations. These findings illustrate a need for strategies to promote meeting dietary guidelines prior to conception to improve health outcomes. Full article

Heterogeneous change detection refers to using image data from different sensors or modalities to detect change information in the same region by comparing images of the same region at different time periods. In recent years, methods based on deep learning and domain adaptation have become mainstream, which can effectively improve the accuracy and robustness of heterogeneous image change detection through feature alignment and multimodal data fusion. However, a lack of credible labels has stopped most current learning-based heterogeneous change detection methods from being put into application. To overcome this limitation, a weakly supervised heterogeneous change detection framework with a structure similarity-guided sample generating (${\mathrm{S}}^3$${\mathrm{G}}^2$) strategy is proposed, which employs differential structure similarity to acquire prior information for iteratively generating reliable pseudo-labels. Moreover, a Statistical Difference representation Transformer (SDFormer) is proposed to lower the influence of modality difference between bitemporal heterogeneous imagery and better extract relevant change information. Extensive experiments have been carried out to fully investigate the influences of inner manual parameters and compare them with state-of-the-art methods in several public heterogeneous change detection data sets. The experimental results indicate that the proposed methods have shown competitive performance. Full article