Search Results (130,135)

Background: Age-related cognitive decline is linked to reduced gait complexity and higher fall risk. Traditional linear gait measures may miss subtle motor-cognitive deficits in older adults with dementia. This study examined whether an 8-week motor-cognitive exercise program could improve gait adaptability in institutionalized older adults with cognitive impairment. Gait complexity, measured using Sample Entropy, was the primary outcome. Methods: Forty-two institutionalized older adults completed follow-up assessments, including 26 with cognitive impairment and 16 controls. Gait was assessed during normal walking (single-task) and while performing cognitive tasks (dual-task), such as naming animals or counting backward. Inertial sensors recorded stride intervals, and Sample Entropy was calculated to evaluate gait regularity and adaptability, (gait complexity). The intervention included 24 structured sessions combining physical and cognitive exercises targeting balance, coordination, and executive function. Non-parametric tests (Wilcoxon) were used, with Bonferroni correction for multiple comparisons. Results: Participants with cognitive impairment showed increased gait complexity, especially during dual-task walking. Significant improvements were found in both limbs under dual-task conditions (left: p = 0.015, effect size = 0.34; right: p = 0.030, effect size = 0.31). During single-task walking, a significant improvement was observed in the left limb (p = 0.006, effect size = 0.39). Conclusions: Motor-cognitive exercise may enhance non-linear gait complexity in institutionalized older adults with cognitive impairment. The use of dual-task training in rehabilitation and highlight the value of entropy-based gait assessment for detecting subtle functional changes. However, the lack of a randomized non-exercising cognitive impairment control group limits definitive conclusions about causality. Full article

Intrusion detectors are often evaluated using average metrics at unconstrained thresholds, yet deployments require explicit control over false alarms. We investigate zero-day (out-of-distribution, OOD) intrusion detection under a target-FPR calibrated protocol, where a threshold is set on benign validation traffic to satisfy a target false positive rate α and transferred, unchanged, to a seen-test and OOD-test. Using CICIDS2017-derived host-session nodes aggregated in 1min and 5min windows, we compare tabular baselines, message-passing GNNs on a rule-based graph, and employ a method that builds a k-nearest-neighbor similarity graph with lightweight feature pre-smoothing. Robustness is measured using the OOD violation ratio, percentile tail risk, and feasibility under explicit false-alarm budgets. Base-graph GNNs exhibit heavy-tailed false-alarm amplification under OOD shifts: at α = 0.001, the p95 violation ratio reaches 68.50 (1m) and 67.95 (5m). In contrast, the proposed method reduces p95 to 3.41 (1m) and 1.15 (5m) and improves budget feasibility. We further verify robustness beyond a single held-out family by evaluating additional unseen-family splits (e.g., DDoS and DDoS+DoS) under the same calibrated operating point. We also quantify deployment-oriented cost via edge-list size and practical parsing/loading time. These findings suggest that similarity-based graphs with light pre-smoothing improve deployability under distribution shifts. Full article

Passiflora germplasm represents an important genetic resource for improving fruit yield and quality in breeding programs targeting semi-arid environments. This study aimed to assess the phenotypic diversity, genetic parameters, and breeding potential of Passiflora accessions conserved in the Passion Fruit Active Germplasm Bank of Embrapa Semiárido. A total of 55 accessions, predominantly Passiflora cincinnata Mast., were evaluated using morphoagronomic descriptors related to plant, flower, and fruit traits. Quantitative data were analyzed using mixed linear models (REML/BLUP) to estimate genetic parameters, and multivariate analyses were applied to characterize phenotypic divergence. Substantial phenotypic variability was observed, particularly for fruit-related traits. Fruit weight ranged from 43.25 to 142.88 g, pulp weight ranged from 7.86 to 51.37 g, and pulp yield ranged from 17.06% to 40.27% among accessions. Broad-sense heritability estimates for key fruit traits were moderate to high, reaching 0.50 for fruit weight, 0.49 for pulp weight, and 0.36 for pulp yield, indicating favorable prospects for selection. Principal Component Analysis explained 66.0% of the total variation in the first two components, with fruit size, pulp-related traits, and seed number contributing most strongly to accession differentiation. Multivariate analyses consistently identified accessions 1 and 16 as superior for fruit weight and pulp yield, whereas accession 55 combined high fruit weight with elevated soluble solid content (up to 14.24 °Brix) but lower pulp yield. Overall, the observed variability highlights the relevance of Passiflora germplasm conserved under semi-arid conditions as a valuable resource for breeding programs focused on fruit yield, quality, and adaptation to water-limited environments. Full article

Fire refugia are critical for post-disturbance recovery, yet microhabitats such as stones remain understudied despite their ubiquity and thermal persistence. This study tested whether the depth- and area-dependent refugial capacity of stones previously demonstrated in Mediterranean oak forests also operates in intensively managed plantations and how forest type and management modulate this capacity. Immediate wildfire effects (1–8 days post-fire) on ground-dwelling macroinvertebrates were quantified under 660 stones across burnt and unburnt native maritime pine and exotic eucalypt plantations following a medium- to high-severity wildfire. Stones acted as thermal refugia in both plantation types, with burial depths greater than 5 cm and surface areas greater than 500 cm² predicting survival. Despite severe impacts (richness declined by 56% in pine and 63% in eucalypt; overall mortality exceeding 50%), diverse taxa persisted under stones, particularly ground spiders, ants, centipedes, rock bristletails, and harvestmen, while plant-associated and moisture-dependent groups suffered the highest losses. Native pine supported a higher abundance and richness per stone than exotic eucalypt in both burnt and unburnt conditions, reflecting management-driven differences in stone size, depth, and availability. These findings show that retaining sufficiently large, deeply buried stones during plantation establishment can enhance post-fire biodiversity recovery in increasingly fire-prone production landscapes. Full article

Background: The COVID-19 pandemic severely restricted access to routine dental care, resulting in delayed treatment and increased presentation of dental emergencies. When combined with SARS-CoV-2 infection, these conditions may significantly impair psycho-social well-being and quality of life (QoL). This study assessed the impact of dental emergencies on QoL in patients with COVID-19. Methods: A cross-sectional case–control study was conducted between January 2022 and April 2024, including 240 adult patients with confirmed COVID-19. The case group comprised 60 patients presenting with dental emergencies, while the control group included 180 COVID-19 patients without emergency dental needs. Quality of life was evaluated using the 32-item Quality-of-Life Inventory (QOLI), yielding a continuous global score (SBQ) and an ordinal quality-of-life category (CGV). Group comparisons were performed using Welch’s t-test and logistic regression, with effect sizes and 95% confidence intervals reported. Multivariable analyses were adjusted for age and sex. Results: Patients with dental emergencies reported markedly poorer global QoL compared to controls (mean SBQ difference = −2.04 points; Cohen’s d = −1.50; p < 0.001). The presence of a dental emergency was strongly associated with severe QoL impairment, with emergency patients showing substantially higher odds of unfavorable CGV categories (adjusted OR ≈ 20.4; 95% CI: 8.6–48.5; p < 0.001). These associations remained robust after adjustment for demographic covariates. Conclusions: Dental emergencies in patients with COVID-19 are associated with a profound deterioration in quality of life. Ensuring timely access to emergency dental services during public health crises may substantially reduce psycho-social burden and improve patient-centered outcomes. Full article

Background/Objectives: Although discrepancies between bioelectrical impedance analysis (BIA) devices are well documented, their clinical relevance in vulnerable populations remains unclear. This study aims to assess the impact of device choice on muscle mass classification criteria in patients with cancer or obesity and to identify modifiers of device variability. Methods: BIA data from 224 adults (85 with cancer, 139 with obesity) measured with two segmental multi-frequency devices (seca mBCA 515 and InBody 970) were analyzed. Device differences were assessed using the Wilcoxon signed-rank test and agreement analyses. Differences in classification of body composition cut-offs cited in the GLIM criteria for malnutrition and the ESPEN and EASO criteria for sarcopenic obesity were evaluated using McNemar’s test. The impact of disease type, sex, and age on device differences was examined through multivariable models. Results: Significant device differences were found for all parameters (all p ≤ 0.0050). Discrepancies were largest for skeletal muscle mass (kg and %), with effect sizes r > 0.8 and poor agreement (Lin’s CCC < 0.90). A significant impact of device choice on muscle mass classification was observed for both cancer and obesity patients (p < 0.001), with seca classifying more patients as having low fat-free mass (50% vs. 20%) and as having a body composition consistent with sarcopenic obesity (90% vs. 50%) than InBody. Discrepancies were more pronounced in cancer patients and females. Conclusions: Muscle mass assessment by BIA is highly dependent on device choice, potentially leading to clinically relevant discrepancies in classification when rigid cut-offs are applied. An individualized interpretation of BIA data and further validation of prediction equations in disease-specific subpopulations is warranted. Full article

Mining tailings are considered a significant environmental challenge due to their large quantities and high residual metal content, particularly iron. Recent developments in biogenic technologies offer a sustainable approach to recovering valuable materials from these waste streams. We consider a biogenic iron oxide nanoparticles production process from mining tailings as an environmentally friendly route to magnetic materials. Microorganisms, including iron-oxidizing and iron-reducing bacteria, microalgae, and fungi, can convert soluble and mineral-bound iron into iron oxide nanoparticles (NPs) phases such as magnetite, maghemite, and hematite. These biogenic iron oxide NPs often exhibit specific physicochemical properties, including controlled particle size, high surface area, and engineered magnetic properties, which make them potentially important for applications in environmental remediation, catalysis, and agriculture. The processes behind microbial iron conversion, the parameters governing mineral phase formation, and the approaches for optimizing the process are presented. This strategy supports the circular economy concept by combining biogenic synthesis with various forms of mining waste, thereby reducing environmental threats associated with tailings confinement and providing an environmentally friendly mechanism for the production of value-added magnetic materials. Full article

Electromagnetic imaging in a slab medium presents significant challenges due to complex wave reflections and refractions at the interfaces of different layers. Multiple scattering and interference increase ill-posedness and nonlinearity, degrading reconstruction accuracy and stability. Under transverse magnetic (TM) and transverse electric (TE) excitations, we compare the CNN-refined reconstructions based on the Back Propagation Scheme (BPS) and the Dominant Current Scheme (DCS) to solve the Electromagnetic Inverse Scattering (EMIS) problem. Numerical results demonstrate that our proposed method can accurately reconstruct buried objects of various sizes and positions, even in the presence of noise. In particular, the DCS-CNN framework yields superior reconstruction performance compared to the BPS-CNN approach, highlighting the advantage of integrating the DCS with DL for imaging in a slab medium. Overall, this work validates the feasibility and effectiveness of combining preliminary imaging with DL, offering practical potential for solving complex inverse scattering problems. Full article

As societies confront accelerating sustainability challenges, understanding the individual-level orientations that support collective action has become increasingly important. This study examines the association between educational attainment and three theoretically distinct sustainability-relevant value orientations using cross-national survey data. Drawing on the World Values Survey Wave 7, we analyze responses from 65,608 individuals across 65 countries using weighted least squares regression with country fixed effects to investigate how education relates to norm orientation, future orientation, and inclusion. The analysis reveals substantial variation in the strength of these associations across value dimensions. Education demonstrates a particularly strong relationship with future orientation, yielding a standardized effect size of 0.497, while showing considerably weaker associations with inclusion and norm orientation. Moderation analyses uncover important demographic contingencies, indicating that education gradients for norm orientation and inclusion weaken significantly with age, whereas the education-future orientation relationship remains stable across age groups. A modest gender difference emerges for future orientation, with slightly attenuated education effects among women. These findings suggest that education contributes to sustainability-relevant values primarily through cognitive pathways that enhance temporal perspective rather than through socialization into normative compliance or expansion of social tolerance. The results carry implications for education policy design and sustainable development initiatives. Full article

Sorting defective cocoons is a critical procedure in the silk reeling industry to ensure the quality of raw silk products. Currently, this process relies heavily on manual inspection, which is labor-intensive, subjective, and inefficient. While automated sorting based on machine vision offers a promising alternative, existing object detection algorithms struggle to balance accuracy and computational complexity, particularly when detecting tiny surface defects or distinguishing morphologically similar cocoons in dense scenarios. To address these challenges, this paper proposes an efficient silkworm cocoon defect detection model named LMD-YOLO, based on the YOLOv10 architecture. In this model, we introduce three key improvements to enhance feature extraction and multi-scale perception. First, we integrate a Large Separable Kernel Attention (LSKA) module into the C2f structure (C2f-LSKA) of the backbone. This design decomposes large kernels to capture global shape features with minimal computational cost, effectively distinguishing double cocoons from normal ones. Second, we replace standard upsampling with a DySample module in the neck, which utilizes dynamic point sampling to recover fine-grained texture details of tiny defects like surface stains. Third, a Multi-Scale Dilated Attention (MSDA) mechanism is embedded before the detection heads to aggregate semantic information across different scales, improving robustness against background interference. YOLOv10 was selected as the baseline due to its NMS-free characteristic, which mitigates the latency caused by post-processing in high-speed sorting tasks. Evaluations on a self-constructed multi-category dataset indicate that LMD-YOLO surpasses established detectors, including YOLOv8n and Faster R-CNN. Relative to the YOLOv10n baseline, our method improves mAP@0.5 by 3.11%, achieving 94.46%. Notably, Precision and Recall are increased by 3.50% and 2.97%, reaching 89.98% and 93.61%, respectively. With a compact size of 2.68 M parameters and an inference speed of 115 FPS, the proposed model offers a practical trade-off between accuracy and latency for real-time cocoon defect detection. Full article

The majority of approved drug products comprise formulations of either chemically synthesized small molecules or large molecular entities derived from living cells, commonly referred to as biologics. Over the past two decades, there has been remarkable growth in the approval of biologics for a variety of disorders, including respiratory diseases. The preference for biologics stems from their high target specificity, strong binding affinity, and favorable safety profiles. Most approved biologics are peptides or proteins, which are unsuitable for oral administration due to negligible bioavailability, resulting from their large molecular size, polarity, and susceptibility to enzymatic degradation in the gastrointestinal tract. Consequently, the majority of biologics are administered parenterally, delivering the drug systemically to reach target sites. However, achieving therapeutic concentrations of locally acting respiratory drugs in the lungs via systemic delivery often requires high doses, which increases the risk of adverse effects. For respiratory disorders, nasal and pulmonary drug deliveries are the preferred noninvasive routes. These routes bypass gastrointestinal and first-pass metabolism and deliver therapeutic agents directly to their local site of action. This approach enables a faster onset of action, reduces the required dose by orders of magnitude, and significantly lowers the risk of systemic adverse effects. These advantages have driven the successful development of inhaled formulations for certain rescue and maintenance medications that were originally administered orally or parenterally. Despite this, treatment options for respiratory diseases remain largely limited to small molecules, with only a single inhaled biologic approved in 1993, even though several parenterally administered biologics have since been approved for pulmonary disorders. The scarcity of inhaled biologics is primarily due to the inherent complexity of these drug substances, which impacts all stages of product development, including manufacturing, characterization, purification, stability, formulation design, delivery, and preclinical and clinical evaluations of safety and efficacy. Additionally, sponsors’ interest in developing inhaled biologics may be tempered by the lack of regulatory guidance addressing the multidisciplinary and intricate nature of their development. This article, together with the accompanying review, addresses both regulatory considerations and scientific challenges in the development of inhaled biologics. To the authors’ knowledge, these works represent seminal efforts to examine available regulatory guidance and the applicable literature across various phases of product development beyond safety and efficacy evaluations. We examined the formal regulatory expectations and summarized the requirements as they apply to inhaled products and inhaled biologic protein therapeutics. In parallel, we explored scientifically relevant considerations in the development of inhalation-specific protein therapeutics for which regulatory guidance remains limited, evolving, or absent. While they should not be considered definitive, it is hoped that these contributions will stimulate scientific and regulatory interest, ultimately promoting the identification and resolution of gaps to advance the development of locally acting biologics and address unmet patient needs. Full article

This paper proposes a learning-based contact force controller using deep neural networks (DNN) and a PI controller. Stable contact force control between the foot and the ground is essential for humanoid robots to maintain balance during bipedal walking. While admittance controllers have been extensively employed for contact force control in humanoid robots, their performance is limited by the high nonlinearity inherent in robot systems. To overcome these limitations, we propose a deep neural network (DNN)–based inverse model, which leverages input–output data that inherently capture system nonlinearities. The proposed learning-based contact force controller computes the target foot height based on the target force, measured force, and measured foot height, without relying on a dynamic model of the articulated robotic leg. Furthermore, a PI controller is integrated to mitigate steady-state errors. Experimental comparisons between the proposed controller and an admittance controller were conducted using an articulated robotic leg. Compared with an admittance controller, the proposed method reduced overshoot by 96% and settling time by 61% on average in step responses and decreased force-tracking RMSE by 66.3% on average across both step and sinusoidal experiments. Full article

This work presents a compact, self-powered wireless CO₂ sensing node for autonomous environmental monitoring. The system integrates a high-efficiency multijunction photovoltaic (PV) module, a 4000 F hybrid supercapacitor operating at 3.6–4.2 V, and a custom power management system in a LiPo-sized form factor. The PV module, composed of nine parallel triple-junction solar cells, achieves an average efficiency of 27% and delivers peak power at 4.26 V under 600 W/m² irradiance. The sensing unit includes miniaturized CO₂, humidity, and temperature sensors with LoRa-based wireless communication. The low-power NDIR CO₂ sensor provides a resolution of 15–20 ppm and a response time of ~45 s. Week-long tests demonstrated fully autonomous operation with reliable 5 min data transmission, capturing diurnal CO₂ variations associated with plant activity even under low irradiance. Energy storage occurs for irradiance levels ≥65 W/m², and long-term simulations confirm stable supercapacitor voltage over yearly cycles. This work demonstrates a compact multijunction solar–hybrid supercapacitor platform capable of sustaining WSN for long-term, maintenance-free CO₂ monitoring under real-world and low-irradiance conditions. Our results demonstrate that the sensing node can reliably monitor plant-driven CO₂ dynamics, clearly resolving the expected photosynthesis–respiration cycles and their dependence on incident solar radiation, while simultaneously sustaining its energy budget under highly challenging illumination and transmission conditions. Full article

This paper proposes a quasi-dynamic Volt–Var control strategy for radial distribution networks based on the optimal sizing of a distribution static synchronous compensator (D-STATCOM) using a genetic algorithm (GA). The objective is to enhance voltage regulation and reduce technical energy losses under variable loading conditions while preserving nonlinear AC power flow fidelity. The IEEE 33-bus test system was modeled in DIgSILENT PowerFactory (v2021), and the D-STATCOM installation bus was selected based on a rigorous literature-supported placement criterion derived from optimization-based studies. Three representative demand scenarios—minimum, average, and maximum loading—were defined to approximate quasi-dynamic operation over a daily cycle. The GA was implemented in MATLAB (R2023b) to solve a normalized nonlinear multi-objective optimization problem that simultaneously minimizes total active power losses and the aggregate voltage deviation index. The optimized reactive power capacities obtained were 0.49 Mvar, 1.1933 Mvar, and 2.30 Mvar for the minimum, average, and maximum demand scenarios, respectively. These configurations achieved active power loss reductions of 27.5%, 24.602%, and 23.44% under the corresponding loading levels while improving voltage regulation at the critical bus (bus 18) and maintaining system voltages within the admissible 0.95–1.05 p.u. range. Through quasi-dynamic interpolation of operating points, the daily performance assessment showed a 24.11% reduction in total energy losses and a 38.28% decrease in the average voltage deviation. A statistical robustness analysis confirmed stable convergence behavior across independent executions. The results demonstrate that the proposed framework provides a computationally efficient, planning-oriented approach for reactive power compensation in distribution systems subject to demand variability. Full article

Plant domestication studies have traditionally focused on morphological factors that are under direct selection, e.g., fruit size, overlooking the consequences of domestication on ecosystem services. We addressed this knowledge gap by documenting for first time the soil carbon (C) sequestration potential in wild relatives and domesticated cultivars of breadfruit (Artocarpus), a long-lived tree crop. We evaluated aggregate-bound and bulk organic C pools in breadfruit wild relatives and domesticates in soils that varied in nitrogen (N) and phosphorus (P) fertility with management practices (fertilizer and mulch). We determined whether C levels were linked to plant domestication, abiotic factors (N, P, pH, and texture), or biotic factors with known links to C accrual (arbuscular mycorrhizal fungi (AMF), and microbial biomass). In low N or N: P soils, increasing breadfruit domestication was associated with reductions in macroaggregate C (by 50%) and bulk C (host determinism); these shifts were associated with AMF hyphal productivity (50% lower than in wild relatives), soil N and P, and microbial biomass. With a high soil N fertility, the levels of aggregate and bulk soil C were similar between wild relatives and domesticates (plasticity). Despite the limited number of cultivars sampled (n = 10) and the different management practices among sites, our findings suggest domestication effects on ecosystem services, especially those modulated by AMF and soil N fertility. The calculated soil C stocks averaged 99.5 Mg C/ha (range 70–122 Mg C/ha), supporting the possibility of C accrual in breadfruit agroforestry. Full article