Search Results (462)

(1) Background: Dioxins and dioxin-like polychlorinated biphenyls (dl-PCBs) are persistent organic pollutants (POPs), characterized by high toxicity and strong lipophilicity, which promote their bioaccumulation in human tissues. Their detection in breast milk raises concerns about early-life exposure during lactation. Although dietary intake is the primary route of maternal exposure, environmental pathways—including inhalation, dermal absorption, and residential proximity to contaminated sites—may also significantly contribute to the maternal body burden. (2) Methods: This narrative review examined peer-reviewed studies investigating maternal and environmental determinants of dioxin and dl-PCB concentrations in human breast milk. A comprehensive literature search was conducted in PubMed, Scopus, and Web of Science (2000–2024), identifying a total of 325 records. Following eligibility screening and full-text assessment, 20 studies met the inclusion criteria. (3) Results: The included studies consistently identified key exposure determinants, such as high consumption of animal-based foods (e.g., meat, fish, dairy), living near industrial facilities or waste sites, and maternal characteristics including age, parity, and body mass index (BMI). Substantial geographic variability was observed, with higher concentrations reported in regions affected by industrial activity, military pollution, or inadequate waste management. One longitudinal study from Japan demonstrated a declining trend in dioxin levels in breast milk, suggesting the potential effectiveness of regulatory interventions. (4) Conclusions: These findings highlight that maternal exposure to dioxins is influenced by identifiable environmental and behavioral factors, which can be mitigated through public health policies, targeted dietary guidance, and environmental remediation. Breast milk remains a critical bioindicator of human exposure. Harmonized, long-term research is needed to clarify health implications and minimize contaminant transfer to infants, particularly among vulnerable populations. Full article

Background: Since the election of Hamas in 2006, Gaza has endured eight major military conflicts, culminating in the ongoing 2023–2025 war, now surpassing 520 days. This protracted violence, compounded by a 17-year blockade, has resulted in the near-total collapse of Gaza’s health system. Over 49,000 deaths, widespread displacement, and the destruction of more than 60% of health infrastructure have overwhelmed both local capacity and international humanitarian response. Objectives: This narrative review aims to examine and synthesize the current literature (October 2023–April 2025) on the health crisis in Gaza, with a specific focus on identifying key themes and knowledge gaps relevant to rebuilding a sustainable health system. The review also seeks to outline strategic pathways for recovery in the context of ongoing conflict and systemic deprivation. Methods: Given the urgency and limitations of empirical data from conflict zones, a narrative review approach was adopted. Fifty-two sources—including peer-reviewed articles, editorials, reports, and correspondence—were selected through targeted searches using Medline and Google Scholar. The analysis was framed within a public health and political economy perspective, also taking health system building blocks into consideration. Results: The reviewed literature emphasizes emergency needs: trauma care, infectious disease control, and supply chain restoration. Innovations such as mobile clinics and telemedicine offer interim solutions. Gaps include limited attention to mental health (including that of health workers), local governance, and sustainable planning frameworks. Conclusions: Sustainable reconstruction requires a durable ceasefire; international stewardship aligned with local ownership; and a phased, equity-driven strategy emphasizing primary care, mental health, trauma management, and community engagement. Full article

Intestinal inflammation involves barrier impairment, immune hyperactivation, and oxidative stress imbalance. Bioactive polysaccharides universally alleviate inflammation via anti-inflammatory, antioxidant, and microbiota-modulating effects, yet exhibit distinct core mechanisms. Elucidating these differences is vital for targeted polysaccharide applications. This research examines distinct regulatory pathways through which diverse bioactive polysaccharides mitigate lipopolysaccharide-triggered intestinal inflammation in male Kunming (KM) mice. This experiment employed Lentinula edodes polysaccharide (LNT), Auricularia auricula polysaccharide (AAP), Cordyceps militaris polysaccharide (CMP), Lycium barbarum polysaccharide (LBP), and Brassica rapa polysaccharide (BRP). The expression levels of biomarkers associated with the TLR4 signaling pathway, oxidative stress, and intestinal barrier function were quantified, along with comprehensive gut microbiota profiling. The results showed that all five polysaccharides alleviated inflammatory responses in mice by inhibiting inflammatory cytokine release, reducing oxidative damage, and modulating gut microbiota, but their modes of action differed: LBP significantly suppressed the TLR-4/MyD88 signaling pathway and its downstream pro-inflammatory cytokine expression, thereby blocking inflammatory signal transduction and reducing oxidative damage; LNT and CMP enhanced the body’s antioxidant capacity by increasing antioxidant enzyme activities and decreasing malondialdehyde (MDA) levels; AAP and BRP enriched Akkermansia (Akk.) within the Verrucomicrobia (Ver.) phylum, upregulating tight junction protein expression to strengthen the intestinal mucosal barrier and indirectly reduce oxidative damage. This research demonstrates that different polysaccharides alleviate inflammation through multi-target synergistic mechanisms: LBP primarily inhibits inflammatory pathways; AAP and BRP focus on intestinal barrier protection and microbiota modulation; and LNT and CMP exert effects via antioxidant enzyme activation. These data support designing polysaccharide blends that leverage complementary inflammatory modulation mechanisms. Full article

Infrared small target detection is crucial for military surveillance and autonomous driving. However, complex scenes and weak signal characteristics make the identification of such targets particularly difficult. This study proposes YOLO-SSFA, an enhanced You Only Look Once version 11 (YOLOv11) model with three modules: Scale-Sequence Feature Fusion (SSFF), LiteShiftHead detection head, and Noise Suppression Network (NSN). SSFF improves multi-scale feature representation through adaptive fusion; LiteShiftHead boosts efficiency via sparse convolution and dynamic integration; and NSN enhances localization accuracy by focusing on key regions. Experiments on the HIT-UAV and FLIR datasets show mAP50 scores of 94.9% and 85%, respectively. These findings showcase YOLO-SSFA’s strong potential for real-time deployment in challenging infrared environments. Full article

Cordycepin, a bioactive adenosine analog, holds promise in pharmaceutical and health product development. However, large-scale production remains constrained by the limitations of natural producers, Cordyceps spp. Herein, we report the reconstruction of the first genome-scale metabolic model (GSMM) for a cordycepin-producing strain of recombinant Aspergillus oryzae. The model, iNR1684, incorporated 1684 genes and 1947 reactions with 93% gene-protein-reaction coverage, which was validated by the experimental biomass composition and growth rate. In silico analyses identified key gene amplification targets in the pentose phosphate and one-carbon metabolism pathways, indicating that folate metabolism is crucial for enhancing cordycepin production. Nutrient optimization simulations revealed that chitosan, D-glucosamine, and L-aspartate preferentially supported cordycepin biosynthesis. Additionally, a carbon-to-nitrogen ratio of 11.6:1 was identified and experimentally validated to maximize production, higher than that reported for Cordyceps militaris. These findings correspond to a faster growth rate, enhanced carbon assimilation, and broader substrate utilization by A. oryzae. This study demonstrates the significant role of GSMM in uncovering rational engineering strategies and provides a quantitative framework for precision fermentation, offering scalable and sustainable solutions for industrial cordycepin production. Full article

Blast-induced polytrauma (BIPT) is a common injury among military personnel exposed to explosive blasts. It is increasingly recognized as a complex, multisystem disorder that extends beyond neurological damage to include systemic metabolic and inflammatory dysfunction. Adipokines, particularly leptin and adiponectin, are hormones secreted by adipose tissue and are emerging as key mediators in the pathophysiology of traumatic brain injuries. Yet, their long-term dynamics following blast exposure remain unclear. This study investigated the temporal profiles of plasma leptin and adiponectin in a longitudinal rat model of BIPT. Adult male Sprague Dawley rats were subjected to either a single (B) or repeated (BB) blast exposure (20 psi) or served as sham controls. Plasma samples were collected at 24 h, 1 month, 6 months, and 12 months post-exposure, and adipokine levels were measured using Enzyme-linked Immunosorbent Assay. Adiponectin levels exhibited a biphasic response: both B and BB groups showed significant early decrease at 24 h and 1 month compared to sham animals, followed by robust elevation at 6 and 12 months, particularly in the repeated blast group. In contrast, leptin levels remained unchanged acutely but rose significantly at 6 and 12 months post-blast, with the BB group again showing the highest levels. These patterns indicate sustained, exposure-dependent dysregulation of adipokine signaling after blast trauma. The study provides the first longitudinal profile of systemic adipokine responses to BIPT, revealing their potential as accessible biomarkers and therapeutic targets. These findings support a model of chronic metabolic and inflammatory imbalance in BIPT and warrant further investigation in human cohorts and mechanistic studies. Full article

Infrared small-target detection remains a critical challenge in military reconnaissance, environmental monitoring, forest-fire prevention, and search-and-rescue operations, owing to the targets’ extremely small size, sparse texture, low signal-to-noise ratio, and complex background interference. Traditional convolutional neural networks (CNNs) struggle to detect such weak, low-contrast objects due to their limited receptive fields and insufficient feature extraction capabilities. To overcome these limitations, we propose a Multi-Scale Edge-Aware Convolution (MEAC) module that enhances feature representation for small infrared targets without increasing parameter count or computational cost. Specifically, MEAC fuses (1) original local features, (2) multi-scale context captured via dilated convolutions, and (3) high-contrast edge cues derived from differential Gaussian filters. After fusing these branches, channel and spatial attention mechanisms are applied to adaptively emphasize critical regions, further improving feature discrimination. The MEAC module is fully compatible with standard convolutional layers and can be seamlessly embedded into various network architectures. Extensive experiments on three public infrared small-target datasets (SIRSTD-UAVB, IRSTDv1, and IRSTD-1K) demonstrate that networks augmented with MEAC significantly outperform baseline models using standard convolutions. When compared to eleven mainstream convolution modules (ACmix, AKConv, DRConv, DSConv, LSKConv, MixConv, PConv, ODConv, GConv, and Involution), our method consistently achieves the highest detection accuracy and robustness. Experiments conducted across multiple versions, including YOLOv10, YOLOv11, and YOLOv12, as well as various network levels, demonstrate that the MEAC module achieves stable improvements in performance metrics while slightly increasing computational and parameter complexity. These results validate the MEAC module’s significant advantages in enhancing the detection of small and weak objects and suppressing interference from complex backgrounds. These results validate MEAC’s effectiveness in enhancing weak small-target detection and suppressing complex background noise, highlighting its strong generalization ability and practical application potential. Full article

Colombia is a megadiverse, multiethnic, and multicultural country with a tremendous socio-ecological systems (SESs) diversity, which faces essential challenges arising from human activities, low levels of sustainable economic development, poverty, and social inequality rates, and the persistence of multiple forms of military, political, and social violence. Understanding the resilience of this complex system is both fundamental and challenging due to the contradictory effects of economic development and regional ecosystem degradation. This research proposes the Socio-Ecological Resilience Integrated Index (SERII) to assess historical changes in socio-ecological resilience in Colombia’s departments (political-administrative units) between 1985–2022. The SERII considers the trade-offs between ecosystems, social systems, and production systems, providing a complete perspective of integrated management with a geographic resolution at the level of general political-administrative units. The results reveal a spatial variation in the SERII, with worse conditions in the Caribbean, the Pacific, and the Colombian Amazon (on the country periphery) and better conditions in departments of the country center. From 1985 to 2022, the SERII experienced a decrease (51.5%), driven by ecosystem degradation, increased extractive activities (illegal and illegal), and the persistence of military, political, and social violence. While the limitations of the proposed indicator are described, the SERII effectively replicates the overall resilience of Colombia’s departments to external shocks and allows for suggesting regional management priorities for the targeted promotion of sustainable development. Full article

Disruptive color on animals’ bodies can reduce the risk of being caught. This study explores the camouflaging effect of disruptive color when applied to military targets. Disruptive and non-disruptive color patterns were placed on the target surface to form simulation materials. Then, the simulation target was set in woodland-, grassland-, and desert-type background images. The detectability of the target in the background was obtained by collecting eye movement indicators after the observer observed the background targets. The influence of background type (local and global), camouflage pattern type, and target viewing angle on the disruptive-color camouflage pattern was investigated. This study aims to design eye movement observation experiments to statistically analyze the indicators of first discovery time, discovery frequency, and first-scan amplitude in the target area. The experimental results show that the first discovery time of mixed disruptive-color targets in a forest background was significantly higher than that of non-mixed disruptive-color targets (t = 2.54, p = 0.039), and the click frequency was reduced by 15% (p < 0.05), indicating that mixed disruptive color has better camouflage effectiveness in complex backgrounds. In addition, the camouflage effect of mixed disruptive colors on large-scale targets (viewing angle ≥ 30°) is significantly improved (F = 10.113, p = 0.01), providing theoretical support for close-range reconnaissance camouflage design. Full article

Recent technological advances have expanded the use of 3D-printed polymer components across industries, including a growing interest in military applications. The effective defensive use of such materials depends on a thorough understanding of polymer properties, printing techniques, structural design, and influencing parameters. This paper analyzes the ballistic resistance of 3D-printed polymer structures against 9 × 19 mm projectiles. Cuboid targets with different infill patterns—cubic, grid, honeycomb, and gyroid—were fabricated and tested experimentally using live ammunition. Post-impact, CT scans were used to non-destructively measure projectile penetration depths. The honeycomb infill demonstrated superior bullet-stopping performance. Additionally, mechanical properties were experimentally determined and applied in FEM simulations, confirming the ability of commercial software to predict projectile–target interaction in complex geometries. A simplified analytical model also produced satisfactory agreement with experimental observations. The results contribute to a better understanding of impact behavior in 3D-printed polymer structures, supporting their potential application in defense systems. Full article

Background: Individuals with ADHD may perform poorly on tasks targeting executive functioning skills such as the ImPACT, which requires the test-taker to employ judgement in non-routine situations Objective: To determine whether ADHD serves as a mediating variable for increasing the likelihood of an invalid score. Materials and Methods: A total of 39,140 collegiate athletes and United States military cadets consented to the Concussion Assessment, Research, and Education (CARE) Consortium study. Participants completed the CARE Baseline Packet which included various sections through which study participants provide self-report data, including demographic, personal, and family history sections. The personal history portion of the CARE Baseline Packet addressed the participant’s neurological history, including self-reported diagnosis of ADHD and history of traumatic brain injury. Variables utilized for the current study included age, gender, race, ethnicity, the participant’s primary college sport, use of mouthguards for athletes competing in sports requiring them, and the presence of an ADHD diagnosis. Participants responded to a question, inquiring if they had ever been diagnosed by a medical professional with ADHD, ultimately producing a dichotomous yes/no response. Results: We found that participants with ADHD were more likely to produce invalid baseline scores (ß = −0.884; p < 0.001). Similar results were found when controlling for sex, race, age, sport played, mouthguard use, and number of previous concussions (ß = −0.786; p < 0.001). Sex, race, sport played, and mouthguard use each played a significant role in determining profile validity, independent of ADHD diagnosis. With ADHD removed from the model, age negatively affected the likelihood of a valid score (ß = −0.052; p = 0.048). Conclusions: Our study suggests that the relationship between age and ImPACT validity is explained by the presence of ADHD. Results support adjusting ImPACT’s validity thresholds for individuals with ADHD. Full article

In recent years, the use of unmanned aerial vehicles (UAVs), commonly known as drones, has significantly surged across civil, military, and commercial sectors. Ensuring reliable and efficient communication between UAVs and between UAVs and base stations is challenging due to dynamic factors such as altitude, mobility, environmental obstacles, and atmospheric conditions, which existing communication models fail to address fully. This paper presents a multi-ray channel model that captures the complexities of the airspace network, applicable to both ground-to-air (G2A) and air-to-air (A2A) communications to ensure reliability and efficiency within the network. The model outperforms conventional line-of-sight assumptions by integrating multiple rays to reflect the multipath transmission of UAVs. The multi-ray channel model considers UAV flights’ dynamic and 3-D nature and the conditions in which UAVs typically operate, including urban, suburban, and rural environments. A technique that calculates the received power at a target UAV within a networked airspace is also proposed, utilizing the reflective characteristics of UAV surfaces along with the multi-ray channel model. The developed multi-ray channel model further facilitates the characterization and performance evaluation of G2A and A2A communications. Additionally, this paper explores the effects of various factors, such as altitude, the number of UAVs, and the spatial separation between them on the power received by the target UAV. The simulation outcomes are validated by empirical data and existing theoretical models, providing comprehensive insight into the proposed channel modelling technique. Full article

Currently, infrared object detection is utilized in a broad spectrum of fields, including military applications, security, and aerospace. Nonetheless, the limited computational power of edge devices presents a considerable challenge in achieving an optimal balance between accuracy and computational efficiency in infrared object detection. In order to enhance the accuracy of infrared target detection and strengthen the implementation of robust models on edge platforms for rapid real-time inference, this paper presents LKD-YOLOv8, an innovative infrared object detection method that integrates YOLOv8 architecture with masked generative distillation (MGD), further augmented by the lightweight convolution design and attention mechanism for improved feature adaptability. Linear deformable convolution (LDConv) strengthens spatial feature extraction by dynamically adjusting kernel offsets, while coordinate attention (CA) refines feature alignment through channel-wise interaction. We employ a large-scale model (YOLOv8s) as the teacher to imparts knowledge and supervise the training of a compact student model (YOLOv8n). Experiments show that LKD-YOLOv8 achieves a 1.18% mAP@0.5:0.95 improvement over baseline methods while reducing the parameter size by 7.9%. Our approach effectively balances accuracy and efficiency, rendering it applicable for resource-constrained edge devices in infrared scenarios. Full article

Vegetable intake among military Service Members (SMs) is well below public health guidelines, with only 12.9% meeting the Dietary Guidelines for Americans (DGAs). Low vegetable consumption negatively impacts diet quality as measured by the Healthy Eating Index (HEI), and poses risks to health and performance. Given the high physical and mental demands of military life, improving diet quality, including through increased vegetable intake, is crucial for optimizing health and readiness. Providing meal kits may help improve vegetable intake by reducing access-related barriers for SMs living or working on a military base. Furthermore, the addition of spices and herbs is a readily modifiable accompanying approach to address taste-related barriers and increase intake that has shown promise in other populations with poor diet quality. Background/Objectives: This study aimed to evaluate whether heat-and-serve meal kits with spices and herbs could increase vegetable intake and liking among active-duty SM by simultaneously targeting barriers to healthy eating and modifiable sensory factors. Methods: Conducted at Naval Support Activity Bethesda, the study randomly distributed heat-and-serve meal kits (n = 400) featuring either spiced (n = 200) or plain versions (n = 200) of four vegetables (broccoli, carrots, cauliflower, and kale). Each kit contained a quick response (QR) code for participants to upload post-consumption photos and rate vegetable liking on a nine-point Likert scale. Food photography (SmartIntake^®) was used to estimate vegetable consumption. Paired t-tests were used to determine differences between the intake of plain and spiced vegetables. Results: Intake of the heat-and-serve vegetables was very high for both the spiced and plain preparations (1.73 out of 2 cups, 87%). There was minimal difference (p = 0.87) between the consumption of spiced (1.75 cups) and plain (1.725 cups) vegetables, suggesting that both were well accepted. Overall, convenient and accessible meal options, alongside sensory-driven strategies, appear to improve some barriers to vegetable consumption in SM populations. Conclusions: Future studies should explore long-term outcomes and adaptability across different military environments, while considering additional factors, including convenience and time constraints, that influence dietary choices in the military. Full article

Coordinate measuring machines (CMMs) are increasingly used in manufacturing, mechanical engineering, and wherever special geometries need to be measured with the utmost precision. CMMs are very important in various fields including the automotive, aerospace, and military industries. For certain specific tasks, such as measuring roundness or contour, they are not as accurate as specialized measuring machines, for instance, roundness measuring machines, especially if the circle is to be measured on an oblique surface. The CMM servo loop is not as accurate as the CMM readings, as it leads to differences between the theoretical target coordinates of a point and the actual coordinates obtained. On a conical surface, for example, where height and radius are linked, these differences are the cause of errors on circle dimensions. In this case, it is necessary to construct the feature instead of measuring it directly. This article proposes innovative methods for performing specific tasks on a CMM and for taking faults due to servo-control into account. The results show significant improvements for standard parts or skewed surfaces. Full article