Search Results (30,700)

Background/Objectives: Anxiety symptoms are common in older adults and are associated with cognitive changes; however, the specific pattern of deficits and the effects of anxiety diagnosis, symptom severity, and depressive symptoms remain unclear. This study compared cognitive performance between older adults with anxiety-related diagnoses and psychiatrically healthy controls and examined factors associated with cognitive outcomes. Methods: This cross-sectional study included 130 participants aged ≥ 65 years: 70 with an anxiety-related diagnosis (SCID-5-CV) and 60 controls without psychiatric diagnoses. Cognition was assessed using the SMMSE, Enhanced Cue Recall Test, Clock Drawing Test, Verbal Fluency Test, and Trail Making Test Parts A and B; anxiety and depressive symptoms were assessed with validated scales. Results: The anxiety group had higher anxiety and depression scores than controls (FDR-adjusted q < 0.001). They showed longer Trail Making Test A, B, and B–A times and lower free recall and enhanced cue recall scores (q = 0.019 and q < 0.001, respectively). No differences were observed in global cognition, clock drawing, or verbal fluency after correction. Most symptom–cognition correlations did not survive Bonferroni correction, except for state anxiety and enhanced cue recall. In regression analyses, anxiety-related diagnosis showed a more consistent association with cognition than anxiety symptom severity, along with education, age, gender, and depressive symptoms. Conclusions: Older adults with anxiety-related diagnoses showed selective impairments in processing speed, attention, executive functions, and memory despite preserved global cognitive screening. Cognitive outcomes in late-life anxiety appear more closely related to diagnostic status and other clinical/demographic factors than to anxiety severity alone. Full article

Background: Climate change is being recognized as a factor associated with increased suicidal behavior, especially in the older adult population. Extreme temperatures, thermal anomalies, and intense weather events can amplify pre-existing physical, psychological, and social vulnerabilities, increasing the risk of suicidal ideation and behavior in older adults. Objectives: This systematic review aims to map the literature on the relationship between climate change and suicidal behavior in older people, identifying risk and protective factors, as well as the prevention and intervention strategies aimed at this age group. Methods: A systematic review was conducted according to PRISMA guidelines. The literature search was performed in the EBSCO PsycINFO, Scopus and MEDLINE (PubMed) databases in the period 2007–2025, using combinations of the keywords “climate change”, “global warming”, “older adults”, “elderly”, “suicide”, “suicidal ideation” and related terms. Out of 35 studies, 16 articles were included in the final analysis. Results: Five thematic areas emerged from the analysis of the studies: (1) risk factors, (2) protective factors, (3) sociodemographic factors, (4) prevention and intervention strategies and (5) variables associated with suicidal behavior. Across the included studies, suicidal ideation, non-fatal attempts, and suicide mortality were examined with differing frequency and are reported separately in the thematic synthesis rather than pooled, reflecting the heterogeneity of outcome definitions and study designs. Significant limitations in the literature remain, including the paucity of longitudinal studies, the widespread use of aggregate data and the limited integration of environmental, social, and psychological factors. Conclusions: Climate change and extreme weather events may contribute to suicidal behavior in older adults. It is therefore necessary to develop multidimensional approaches that address structural vulnerabilities and promote the active role of older adults in climate resilience and social cohesion. Full article

Cancer remains a leading cause of global mortality, entailing the exploration of novel therapeutic agents from natural sources. This study evaluated the in vitro anti-cancer potential of essential oils (EOs) extracted from the needles of Pinus sylvestris L. (Scots pine) and Picea abies (L.) H. Karst. (Norway spruce). GC–MS analysis revealed that both EOs are rich in monoterpenes; the primary constituents were α-pinene (35.27%) for Pinus sylvestris sylvestris EO (Pinus EO) and β-pinene (31.40%) for Picea abies EO (Picea EO). Cell viability assay (Alamar Blue) demonstrated that both EOs exert a dose-dependent cytotoxic effect across all tested malignant lines: melanoma (A375), colorectal adenocarcinoma (HT-29), and pancreatic adenocarcinoma (PANC-1). Notably, Pinus EO consistently displayed higher potency toward cancer cells when compared with normal keratinocytes (HaCaT), with the highest selectivity noticed in HT-29 cells. Immunofluorescence analysis revealed morphological changes consistent with apoptosis, such as nuclear condensation, DNA fragmentation, and the disruption of the β-actin cytoskeleton. High-resolution respirometry indicated that the EOs increase LEAK respiration, while also significantly reducing the oxidative phosphorylation (OXPHOS) efficiency. Furthermore, network pharmacology and molecular docking predicted EP300 as a common hub target for both EOs, with β-caryophyllene showing the most favourable predicted binding affinity among the investigated constituents. Overall, these preliminary in vitro and in silico findings support the further investigation of Pinus EO and Picea EO as potential candidates for the development of future adjuvant strategies in cancer therapy. Full article

In the context of global energy transition and climate change, exogenous energy shocks (such as energy price volatility, renewable energy uncertainty, and increasing power demand) pose growing challenges to power system carbon neutrality. However, existing studies mainly focus on optimizing emission-reduction pathways while neglecting system resilience under energy shocks. This study applies a coupled LEAP-NEMO model for Guangdong Province, integrating demand growth, generation evolution, dispatch optimization, system costs, and carbon constraints. Five scenarios (BAS, COM, COM_ES1, COM_ES2, and COM_ES3) are established to assess the impacts of exogenous energy shocks on carbon-neutral transition pathways. The results show that under COM scenario, Guangdong’s power system’s carbon emissions will peak by 2030 and reach net-zero by 2055. Different energy shocks produce substantially different effects on the carbon-neutral transition. Fossil fuel price shocks (COM_ES1) have limited impacts, with cumulative emissions changing by only 2.1% relative to COM. Renewable energy volatility (COM_ES2) reduces wind and solar generation and raises cumulative emissions by 73.7%, preventing carbon neutrality by 2060. Demand growth (COM_ES3) poses the most severe challenge, with cumulative emissions reaching 2.04 times those of the COM scenario. Resilience analysis further shows that renewable energy volatility causes the largest deterioration in reserve margin performance, while demand growth has the strongest effects on emissions and cost performance. These results identify renewable generation uncertainty and electricity demand growth as the key risks to a smooth carbon-neutral transition, highlighting the need for coordinated deployment of energy storage, nuclear power, flexible resources, and demand-side management. Full article

Background: Cardiac contractility modulation (CCM) improves cardiac performance in heart failure, but its acute spatial effects on myocardial voltage and calcium-transient behavior remain incompletely characterized, particularly in the setting of early myocardial remodeling. Methods: In this exploratory, fixed-sequence study, isolated Langendorff-perfused hearts from Control and isoproterenol (ISO)-treated rats (n = 5 per group) underwent simultaneous voltage and calcium optical mapping during a 40-s protocol consisting of pre-stimulation (Base), active CCM stimulation (CCM-ON), and post-stimulation (CCM-OFF) phases. Global metrics were derived across the mapped ventricular surface and regional metrics from predefined regions proximal and distal to the stimulation electrodes. No time-matched sham-stimulation condition was included. Results: Relative optical action-potential (AP) and calcium-transient (CaT) amplitudes were approximately 5–6% higher during CCM-ON and CCM-OFF than during Base in both groups. Global AP duration at 90% repolarization (APD90) showed modest phase-dependent prolongation, whereas global CaT duration at 90% recovery (CTD90) showed modest shortening. Global CTD90 was longer overall in ISO-treated hearts, without a group-by-phase interaction. Three-way repeated-measures analyses identified phase-by-region interactions for CTD90 and AP–CaT delay (the interval from the 50% AP upstroke to the 50% CaT upstroke) and a group-by-region interaction for CTD90, with no significant phase-by-group-by-region interactions. CTD90 spatial dispersion and the absolute proximal–distal difference in AP–CaT delay showed phase effects, whereas mapped-surface APD90 dispersion did not change detectably. Conclusions: During the acute CCM sequence, CaT recovery and AP–CaT timing showed spatially nonuniform phase-associated patterns in Control hearts and ISO-treated hearts with features compatible with early remodeling, without a parallel detectable increase in mapped-surface APD90 dispersion. These exploratory, hypothesis-generating findings support a spatial dissociation between calcium-related temporal responses and mapped-surface APD90 dispersion under the present experimental conditions. Full article

The implementation of global net-zero emission policies and carbon pricing mechanisms, including the Carbon Border Adjustment Mechanism (CBAM), has increased the need for export-oriented manufacturers to make carbon-related costs visible in production decisions. Taiwan’s fastener industry is particularly exposed because of its multi-stage production structure, intensive use of steel-based inputs, and reliance on international markets. Traditional single-base cost allocation can obscure differences in resource consumption across products and processes. To enhance the decision-making value of cost information, this study develops an Activity-Based Costing (ABC) framework that assigns modeled resource consumption to activities and products while separately internalizing carbon-related costs in a mixed-integer production-planning model. Theory of Constraints (TOC) is used as a bottleneck-focused managerial interpretation of finite production capacities rather than as a separate objective function. Using Taiwan’s fastener manufacturing industry as the research context, the model is demonstrated through an illustrative numerical example parameterized to reflect representative production and resource consumption relationships. The reported findings are therefore numerical results of the model rather than statistical empirical validation of a sampled population or a disclosed company dataset. Under the specified baseline parameters, Product 4 is selected because its revenue, purchasing-tier, activity driver, capacity, and carbon-related cost coefficients jointly dominate the alternatives. Product exclusion scenarios further show how the preferred product changes when individual products are exogenously removed while carbon price parameters are held fixed. The framework provides a transparent decision support structure for jointly examining activity costs, constrained resources, and carbon-related charges; it should not be interpreted as a legal replication of CBAM certificate obligations. Industry 5.0 extensions are positioned as future research. Full article

Drought is one of the most damaging abiotic stresses affecting global crop productivity, and its frequency and severity are projected to increase under ongoing climate change. Silicon (Si), although not classified as an essential nutrient, is increasingly regarded as a “quasi-essential” beneficial element that improves crop performance under water-limited conditions. This review summarises the physiological mechanisms of Si-induced drought tolerance, based mainly on literature published in the past five years. Rather than presenting these mechanisms as an inventory of separate physiological effects, the review reframes them as a coordinated stress-tolerance network linked by shared transcriptional regulation, and it organises the evaluation around three conceptual tensions that remain unresolved in the literature: the opposite direction of Si’s effect on transpiration, the extent to which Si-accumulating grasses and Si-excluding dicots rely on equivalent mechanisms, and the non-linearity of dose responses. Si uptake and transport via Lsi1, Lsi2, and Lsi6, and the resulting difference between Si-accumulating and Si-excluding species, are discussed together with the enhancement of root growth and aquaporin-mediated hydraulic conductance; stomatal and photosynthetic regulation; osmotic adjustment through compatible solute accumulation; enzymatic and non-enzymatic antioxidant defence; hormonal signalling involving abscisic acid, jasmonic acid, ethylene, and auxin; reinforcement of cell walls and vascular tissue; and the transcriptional networks coordinating these responses. Si’s influence on rhizosphere nutrient dynamics and the dependence of its efficacy on genotype, dose, and application method are also considered. A consolidated mechanistic scheme is presented, showing how these pathways converge on a drought-tolerant phenotype characterised by sustained growth, improved water-use efficiency, and faster recovery. Future research priorities, including field validation, standardisation of application protocols, multi-omics integration, and Si–microbiome interactions, are outlined to support the translation of these mechanistic insights into practical drought-management strategies. Full article

Climate change perception among youth has gained increasing scholarly attention; however, immigrant youth remain underrepresented in empirical research despite navigating climate change impacts across multiple sociocultural and geopolitical contexts. This study investigates (1) immigrant youths’ beliefs about climate change, (2) how climate risks are perceived across space and time, and (3) how they construct their climate change beliefs and associated risks. Drawing on Social Constructivism, and Risk Perception Theory, the study employs a qualitative descriptive design using eight focus group discussions with 41 immigrant youth aged 14–18 in Calgary, Canada. Reflexive thematic analysis reveals that immigrant youth widely recognise climate change as real and intensifying, with beliefs shaped through lived and observed environmental experiences, social interaction, family narratives, and transnational comparisons rather than abstract scientific reasoning alone. Climate risk perception emerges as complex and relational. Participants associated climate change with impacts on health, wellbeing, food security, and everyday life; however, they often perceived its most severe consequences as temporally and spatially distant. This produces a notable “belief–risk gap,” where acceptance of climate change does not translate into a strong sense of personal vulnerability or urgency. Risk perceptions are mediated by everyday experiences, institutional trust in the host country, and comparisons with other global crises. The findings highlight the critical role of transnational experiences in shaping climate understanding and advance an integrated interpretation linking socially constructed climate knowledge with perceptions of risk and psychological distance, with implications for climate communication and public health communication strategies for immigrant youth. Full article

Extracting dominant points from complex building outlines is an important task in cartography and building footprint simplification. This study proposes a semi-supervised, geometric-aware graph-Transformer framework for automatic dominant point selection from vector point sequences. The framework combines geometric rules, topological constraints, and data-driven learning to facilitate dominant point detection. A graph network is used to capture local neighborhood structures, while a Transformer models global morphology and long-range dependencies. To improve detection stability, Gaussian scale space is introduced to analyze contours across multiple smoothing scales, and multi-scale geometric features are extracted to distinguish structural changes from local noise. Experimental results demonstrate that the proposed method achieves the best overall performance in building footprint simplification. Indicates that the proposed method provides more accurate, robust, and geometrically stable dominant points for subsequent building reconstruction. Full article

Background/Objectives: Adolescent idiopathic scoliosis (AIS) is associated not only with structural spinal deformities but also with alterations in postural control and sensorimotor integration. Objective assessment of balance and plantar-load distribution may provide additional insight into functional impairments, particularly in patients with mild and moderate curves. The aim of this study was to compare static plantar-load distribution and stabilometry parameters in children and adolescents with idiopathic scoliosis under different sensory and postural conditions. Methods: This pilot study included 19 children and adolescents (18 female, 1 male) diagnosed with mild and moderate AIS. Load distribution and stabilometric parameters were assessed using a capacitive platform under three testing conditions: eyes open, eyes closed, and head extension. Parameters evaluated included load distribution across plantar regions and center-of-pressure-related stability measures. Comparisons were performed between conditions to evaluate the influence of visual and vestibular modulation on postural control. Results: Total plantar load did not differ between the right and left foot, and global relative plantar-load distribution remained stable across the three testing conditions. A consistent side-to-side asymmetry was present at the fifth metatarsal head, where load on the left side was significantly lower than on the right in every condition and remained significant after Holm correction for multiple comparisons (p = 0.001–0.002; |r| = 0.94–0.99). Higher left-sided load was also observed at the first metatarsal head and heel; the heel asymmetry remained significant after correction only in the eyes-open condition (Holm p = 0.044), whereas the remaining differences did not survive correction and are reported as exploratory. The left side corresponded to the side of lumbar convexity. Postural stability differed markedly between conditions: center-of-pressure path length, 90% confidence-ellipse area and maximum center-of-pressure speed were greater under the eyes-closed and head-extension conditions than with eyes open, indicating reduced postural stability when visual input was removed or head position was altered. The two challenge conditions did not differ significantly from each other. Conclusions: In this uncontrolled pilot study, children and adolescents with mild-to-moderate idiopathic scoliosis showed a consistent reduction in load under the left fifth metatarsal head, whereas, apart from a higher left heel load that was significant only with eyes open, other regional asymmetries were exploratory. Stabilometric parameters deteriorated under both visual deprivation and head extension, with no statistically significant difference between the two challenge conditions. Because postural changes became apparent mainly when visual or head-position conditions were altered, assessment under such conditions may reveal condition-related changes in postural control within this AIS cohort. However, because no healthy control group was included, these findings should not be interpreted as evidence of AIS-specific sensory-integration deficits. These preliminary findings require confirmation in larger controlled studies including healthy age-matched participants. Full article

The Hyperspectral Infrared Atmospheric Sounder II (HIRAS-II) onboard the Fengyun-3 satellites is a Fourier-transform infrared spectrometer that requires high radiometric calibration accuracy, making the characterization and correction of polarization effects essential. Although the gold-coated scan mirror introduces only weak polarization, its rotation changes the polarization orientation relative to the fixed polarization-sensitive axis of the downstream optics, producing scan-angle-dependent radiometric errors. To characterize and correct this effect, we designed and constructed a dedicated polarization test apparatus and used it to conduct a prelaunch thermal-vacuum (TVAC) polarization test. During the test, HIRAS-II observed the same stable 290 K area-source blackbody over a densely sampled scan-angle range, with the internal calibration target and cold shield serving as the warm and cold references, respectively. Guided by a polarization-induced radiometric error model formulated within the two-point calibration framework, we developed a decoupled two-step least-squares method to retrieve the polarization parameters from the resulting measurements. The method first estimates the equivalent polarization-axis angle of the downstream optical system from the phase of the band-averaged angular modulation and then retrieves the effective combined polarization parameter separately for each field of view (FOV) and spectral channel. The retrieved parameters were subsequently used to calculate the scan-angle-dependent polarization correction term and correct the calibrated spectra. After correction, the FOV-averaged standard deviation over the scan angle decreased from 0.023 to 0.007 K, from 0.024 to 0.007 K, and from 0.045 to 0.014 K in the long-wave (LW), mid-wave 1 (MW1), and mid-wave 2 (MW2) bands, respectively. The corresponding maximum reductions in brightness temperature deviation were 0.093, 0.064, and 0.174 K. The model, experimental approach, and retrieved prelaunch parameters establish a basis for the on-orbit evaluation and correction of scan-angle-dependent polarization-induced radiometric errors. Reducing these errors improves the radiometric calibration accuracy of HIRAS-II and helps provide more reliable Level-1 radiance data for atmospheric profile retrievals and data assimilation in global numerical weather prediction (NWP) systems. Full article

Mycotoxin contamination in food and feed remains a major public health concern because of its potential toxicological impact and its global economic implications. Aflatoxins and ochratoxin A are of particular concern due to their carcinogenic, hepatotoxic, and nephrotoxic effects, highlighting the need for effective surveillance systems to reduce dietary exposure in the population. This study analyzes 2479 mycotoxin-related notifications concerning both food and feed reported through the iRASFF system during the period 2020–2024, with the aim of characterizing temporal notification trends, identifying the most affected food products and geographical regions, and evaluating the evolution of control strategies implemented by competent authorities. The results did not show a statistically significant long-term increasing trend in the number of mycotoxin notifications, although interannual fluctuations may reflect both changes in contamination patterns and improvements in detection and reporting systems. Products originating outside the European Union accounted for 90.44% of notifications and showed a significantly higher mean number of notifications than products originating within the European Union. Turkey (24%) and the United States (14%) were the most frequently reported countries of origin at a global level. Aflatoxins were the most frequently detected mycotoxins in food (84%), followed by ochratoxin A (15%), mainly affecting nuts, cereals, fruits, vegetables and herbs and spices. These findings demonstrate that mycotoxins continue to represent a persistent challenge for European food safety. Strengthening surveillance systems, enhancing international cooperation, and adapting control strategies to emerging environmental and trade-related factors are essential to minimize consumer exposure, particularly to compounds with genotoxic and carcinogenic potential, and to improve risk management within the food supply chain. Full article

The Newton Downhill Optimizer (NDO) provides a compact derivative-free search framework, but its random dimension mask, uniform treatment of individuals, and limited use of supplementary global-best candidates may restrict performance on high-dimensional problems. This study proposes an Enhanced Newton Downhill Optimizer (ENDO) that incorporates three mechanisms: an adaptive dimension mask, a DE/rand/2-based greedy mutation for inferior individuals, and dynamic-boundary opposition-based best guidance. ENDO was evaluated on the CEC2017 benchmark at 10, 30, 50, and 100 dimensions. The primary comparison involved nine representative optimizers, and an additional 100-dimensional comparison was conducted with six advanced optimizers. In the primary 100-dimensional tests, ENDO ranked first on 18 of 29 functions, remained among the top three on 26 functions, and achieved an average rank of 1.79. In the additional comparison, ENDO ranked third with an average rank of 3.52. Across the four dimensions, its average ranks were 1.79, 1.66, 1.38, and 1.79, indicating stable performance under changes in problem scale. ENDO was further applied to a 168-dimensional thermal–pumped-storage economic dispatch problem, where it achieved the lowest mean operating cost, the best average rank of 1.87, and a feasibility rate of 100% over 30 independent runs. Statistical analyses further supported the competitiveness of ENDO across the benchmark and engineering evaluations. These results show that ENDO improves the sustained search capability of NDO and provides competitive performance for complex high-dimensional and constrained optimization problems. Full article

Model Predictive Control (MPC) offers a structured approach for autonomous-vehicle motion planning by optimizing predicted vehicle behavior over a finite horizon. As learning-based components become increasingly integrated into autonomous systems, interpretable interfaces between decision-making and control become increasingly important. Motivated by the need to examine how predictive depth should vary with maneuver context, this paper proposes and evaluates an adaptive phase-aware horizon-selection formulation within a hybrid Maximum Entropy Deep Inverse Reinforcement Learning-Model Predictive Control (MEDIRL-MPC) framework. The formulation conditions prediction depth explicitly on the recognized maneuver phase, providing an interpretable scheduling signal rather than maintaining the horizon as a globally fixed controller parameter. The considered architecture combines a MEDIRL-informed driving cost, a sampling-based Cross-Entropy Method planner, a kinematic vehicle model, and a scenario manager that identifies the current lane-change phase and provides the corresponding reference information. Controlled experiments are conducted in the CARLA simulator using a static-obstacle lane-change scenario. Fixed-horizon baselines, phase-wise analysis, common-state counterfactual comparisons, and controlled robustness experiments are used to evaluate the effect of prediction depth. The results indicate that the prediction horizon length greatly affects closed-loop behavior and computational demand, and that the relative suitability of different horizons varies across each scenario phase. The phase-aware policy further demonstrates that predictive depth can be allocated selectively across maneuver phases while preserving successful maneuver execution, and remains successful and lane-safe under controlled variations in target speed, obstacle distance, and activation distance. These findings support maneuver phase as an interpretable context for prediction-horizon adaptation within the evaluated architecture, while limiting the conclusions to the investigated scenario and experimental setting. Full article

The global energy transition is driving power systems toward lower-carbon electricity generation, requiring sustainability assessments that consider environmental burdens beyond direct carbon emissions. This study evaluates Mexico’s electricity system using life cycle assessment, resource analysis, and energy sustainability indices. The main novelty of this study is the development of four energy sustainability indices derived from EI99H damage results: the Index of Environmental Change per Energy Unit, Relative Environmental Change Index, Per Capita Environmental Impact, and Environmental Intensity Metric. These indices capture temporal environmental change, generation-related variation, population-related burden, and environmental impact per unit of electricity. Results show improvements in fuel oil, water, and biomass performance between 2013 and 2023, whereas natural gas and coal impacts increased. Mexico exhibits a lower per capita environmental burden than Germany and Spain, while France shows the lowest value, largely due to its nuclear-based electricity mix. Human Health damage is 55% higher than Ecosystem Quality, mainly due to fossil fuel combustion. Hydroelectric generation shows substantial water demand, while solar and wind have negligible requirements. Rising natural gas costs constrain competitiveness, whereas renewables maintain low operating costs. Full article