Search Results (29,523)

Background and Objectives: This study aimed to evaluate the impact of body mass index (BMI) on post- operative outcomes in patients undergoing aortic arch repair with the frozen elephant trunk technique (FET). Materials and Methods: A total of 387 patients who underwent an FET procedure between 04/2014 and 11/2024 were retrospectively analyzed. Patients were divided into four groups according to BMI: underweight (BMI < 18.5, n = 12) normal weight (BMI: 18.5 to <25, n = 150), overweight (BMI: 25 to <30, n = 154), and obese (BMI: ≥30, n = 71). Patient characteristics and clinical outcomes were compared across groups. Multivariable Cox regression, interaction analysis, and restricted cubic spline modelling were performed using R (Version 4.4.3). Results: Interaction analysis revealed BMI-dependent effect modification for several predictors. Insulin-dependent diabetes mellitus was associated with increased mortality only in patients with BMI < 25 kg/m² (interaction p = 0.003). Transfusion of packed red blood cells (PRBCs) also showed a significant interaction with BMI (p = 0.016), with a stronger effect in patients with BMI < 25 kg/m², although significant in both strata. Moreover, cross-clamp time demonstrated a BMI-dependent interaction (p = 0.047), with numerically higher mortality hazards in overweight patients (BMI > 25 kg/m²), but without statistically significant subgroup effects. Spline analysis indicated a non-linear, threshold-based association between overall mortality and BMI but does not reach statistical significance. Kaplan–Meier analysis showed no significant difference in 5-year survival among BMI categories. Conclusions: BMI should not be used as a primary risk stratification tool for survival after an FET procedure. Rather, attention should be paid to comorbid conditions and intraoperative factors that interact with BMI. For patients with lower BMI (<25 kg/m²), optimizing glycemic control and minimizing transfusion may improve outcomes. Data suggests that a reduction in cross-clamp time may be particularly beneficial in patients with higher BMI (>25 kg/m²). Future studies should aim to clarify the impact of BMI on outcomes after FET, particularly in the context of patient selection and perioperative optimization strategies. Full article

The construction of green mines is a core strategy for promoting ecological civilization in China’s mining sector, yet its long-term ecological effects require quantitative assessment. Using a cement-grade limestone mine operated by Linyi Zhonglian Cement Co., Ltd. in Shandong Province as an illustrative case, we employed Landsat 8 OLI/TIRS imagery acquired in 2015, 2020, and 2025 to develop a five-indicator framework for assessing ecological environment quality. The selected indicators comprised greenness (NDVI), wetness, dryness (NDBSI), land surface temperature (LST), and dust concentration (MECDI). These five indicators were subsequently integrated via principal component analysis to generate the Mine Ecological Quality Index (Mine-EQI). Using this index, we applied the Theil–Sen median slope estimator alongside zonal statistics to examine ecological change trajectories across the full study area and three functional zones—the industrial square, haul roads, and active mining area—over the 2015–2025 period. The ecological outcomes attributable to the green mine policy were then quantified. The results show that (1) the mean Mine-EQI of the study area decreased from 0.3713 in 2015 to 0.3460 in 2025, exhibiting a slight overall decline. However, the rate of decline decreased from −6.1% during 2015–2020 to −0.7% during 2020–2025, yielding a Temporal Change Intensity index (TCI) of +88.5%, indicating that the ecological degradation trend has been effectively curbed. (2) Significant spatial heterogeneity was observed. The industrial square showed substantial improvement (Theil–Sen slope = +0.0726), while the haul roads (slope = −0.0705) and mining area (slope = −0.0408) continued to exhibit degradation trends. The improved areas (9.7% of the study area) were spatially coincident with green mine engineering projects. (3) The dust indicator (MECDI) decreased by 24.7% during 2020–2025, and the vegetation index (NDVI) increased by 19.5% over the decade, representing the dominant contributors to ecological improvement. This study reveals that China’s green mine policy has yielded remarkable ecological improvements in relatively stable functional zones such as industrial squares. In contrast, ecological restoration within persistently disturbed areas, including haul roads and mining pits, demands long-term sustained investment and governance. By integrating remote sensing techniques with policy analysis, this research establishes a replicable framework for evaluating progress toward sustainable mining practices. The findings directly support the monitoring of SDG 12 (Responsible Consumption and Production) and SDG 15 (Life on Land), providing a quantitative pathway to balance mineral resource extraction with ecological protection—a core sustainability challenge for resource-dependent regions. Full article

The genus Bacillus is widely recognized for its metabolic versatility, enabling it to colonize extreme environments, including sites contaminated with metals. In this study, we report the genome of B. velezensis strain HM1, isolated from sulfur-rich mine tailings from silver mining activities in southwestern Mexico. Isolation was performed by heat treatment followed by selective cultivation in a medium enriched with mine tailings extract (metals and sulfates), resulting in a single dominant morphotype corresponding to strain HM1. Whole-genome sequencing was carried out using the Illumina NovaSeq platform (2 × 250 bp). The assembled genome of strain HM1 has a size of 4,044,128 bp, distributed across 20 contigs, with an N50 of 700,388 bp and an L50 of 3, and an average coverage of 66.8×. The GC content was 46.31%, with an estimated completeness of 99.81% and contamination of 0.01%. Genome analyses indicate that the assembly corresponds to a single chromosome, with no evidence of plasmid replicons. Genome annotation identified 3950 coding sequences (CDSs), 83 tRNAs, 11 rRNAs, 26 ncRNAs, and 4 sORFs. Phylogenomic analysis, together with genomic similarity metrics (ANI > 98.6%, AAI > 98.8%, dDDH > 87%), confirms its classification as Bacillus velezensis. Functionally, the genome encodes multiple genes involved in resistance to metals and metalloids (including ABC transporters, efflux pumps, and biotransformation enzymes), as well as a complete pathway for sulfate assimilation. Collectively, these genomic features reveal a broad repertoire of adaptive strategies employed by strain HM1 to thrive in metal-contaminated environments. Full article

This study presents a sustainable approach for processing low-grade lithium-bearing aluminosilicate ores via carbothermic treatment with selective lithium stabilization in the slag phase. The proposed method is based on controlled phase transformations that suppress lithium volatilization and promote its retention in the condensed phases. Thermodynamic analysis revealed that lithium volatilization is unfavorable within a defined temperature window, enabling its stabilization in the slag. Experimental smelting, conducted at 1550–1600 °C with the addition of an iron-bearing component, resulted in the selective reduction of silicon and aluminum into a ferro silicon aluminum alloy, while lithium was efficiently concentrated in the slag phase. Lithium recovery to the slag reached up to 94%, with losses to the gas phase below 6%, demonstrating a significant reduction in volatilization compared to conventional high-temperature processes. X-ray diffraction (XRD) analysis confirmed that lithium is predominantly immobilized in the form of LiAlSiO₄ (pseudo-eucryptite), which enhances the chemical reactivity of the slag. From a sustainability perspective, the proposed process enables efficient utilization of low-grade lithium resources, minimizes lithium losses, and eliminates the need for energy-intensive pre-treatment steps such as roasting or vacuum processing. The resulting lithium-bearing slag represents a reactive intermediate suitable for subsequent hydrometallurgical extraction, enabling an integrated and resource-efficient process route. The results demonstrate that phase-controlled carbothermic processing is a viable and sustainable strategy for lithium recovery from low-grade aluminosilicate ores. Full article

Cyberworthiness extends the concept of cybersecurity by evaluating whether systems and networks can perform their intended functions securely while maintaining protection against cyber threats. In corporate environments, cyberworthiness aims to ensure security, operational resilience, and trustworthiness across interconnected business processes and digital infrastructures. Modern organisations increasingly rely on complex cyber–physical and information systems, where vulnerabilities in software, networks, and devices can introduce significant operational and security risks. Cyberworthiness, therefore, encompasses security controls, risk management practices, and compliance with recognised cybersecurity standards and governance frameworks. It supports the assessment of information technology components and their exposure to both known and emerging cyber attacks, enabling organisations to evaluate system robustness and operational continuity. While cyberworthiness has historical foundations in system assurance and dependability, it also provides a conceptual basis for contemporary cyber resilience strategies. This paper discusses the concept of cyberworthiness in corporate organisations and identifies potential pathways for its practical implementation. It analyses existing cybersecurity standards and governance frameworks to support structured cyberworthiness assessment. This study presents a structured comparative review of fifteen cyberworthiness-relevant standards, supported by a Source Quality Appraisal Framework, a Framework Selection Guide specifying when each standard should be preferred and where conflicts arise, and a five-dimensional Cyberworthiness Assessment Readiness Model (CARM), a directional self-assessment instrument. The Efficient Automatic Safety and Security Assurance (EASSA) concept is proposed as a direction for future research, not a validated deployed system. Ensuring cyberworthiness remains challenging due to automation limitations in all reviewed standards, evolving threat landscapes, and governance complexity, requiring organisations to adopt integrated and measurable approaches to safeguard their digital assets and operational systems. Full article

Metabolic dysfunction-associated steatotic liver disease (MASLD) is a widespread condition with a complex pathogenesis. Cell-based models are important tools for studying the mechanisms underlying its development and progression. The aim of this review is to analyze the HepaRG, Huh-7, immortalized human hepatocyte (IHH), and primary human hepatocyte (PHH) cell lines for modeling and studying MASLD. HepaRG represents the most metabolically competent immortalized hepatocyte model with preserved biotransformation activity and a physiological bioenergetic response to lipid loading, making it valuable for pharmacological and toxicological studies. Huh-7 is distinguished by its accessibility and suitability for studying steatosis, lipotoxicity, insulin resistance, and paracrine mechanisms of fibrogenesis; however, its use is limited by its tumor origin, impaired carbohydrate metabolism, and low activity of xenobiotic-metabolizing enzymes. The IHH model occupies an intermediate position because of its non-tumor origin and is of interest for studies of senescence, epigenetic regulation, and signaling pathways involved in steatosis, although interpretation of results requires consideration of immortalization-related effects and specific metabolic limitations. PHH remains the most physiologically relevant platform for MASLD modeling, particularly in three-dimensional (3D) and microphysiological formats; however, its use is limited by high cost, interindividual variability, and the limited duration of the differentiated phenotype. Increasing model complexity—from two-dimensional (2D) monocultures to co-cultures, spheroids, and organ-on-chip systems—enhances physiological relevance and enables reproduction not only of steatosis but also of the inflammatory and fibrogenic components of MASLD progression, yet it reduces reproducibility and complicates standardization. Overall, none of the existing models is universal, and the optimal strategy is to select models according to the specific research question. A key direction for future research is the standardization of steatosis induction protocols and the unification of criteria for evaluating results. Full article

This study presents the first systematic evaluation of the capability of the Surface Water and Ocean Topography (SWOT) satellite Level-2 High Rate Pixel Cloud (L2_HR_PIXC) product for retrieving topography in reservoir drawdown zones under varying terrain conditions in arid and semi-arid regions. Three representative reservoirs in southern Xinjiang, China—characterized by plain, canyon, and pocket-shaped canyon morphologies—were selected to establish a terrain-dependent validation framework. A novel multi-feature clustering strategy integrating elevation and radar backscatter coefficients was explored to reduce the misclassification of wet mudflats as water pixels in the PIXC product, aiming to improve DEM accuracy in reservoir drawdown zones. Based on this framework, multi-cycle SWOT-derived digital elevation models (DEMs) were generated and quantitatively evaluated against high-resolution unmanned aerial vehicle (UAV) Light Detection and Ranging (LiDAR) DEMs. Results demonstrate a strong terrain dependency in SWOT-derived elevation accuracy. In low-relief environments, sub-meter accuracy is achieved, with the root mean square error (RMSE) below 0.25 m, confirming the suitability of SWOT for high-precision monitoring. However, errors increase significantly in steep and complex terrains, reaching up to ±6 m, primarily due to interferometric decorrelation, geometric distortion, and slope-induced biases. Despite these limitations, multi-temporal observations exhibit generally similar spatial error patterns across terrains, indicating reasonable repeatability under the tested conditions. This study reveals the performance boundaries of SWOT-derived DEMs in dynamic land–water transition zones and provides a robust methodological framework for improving DEM extraction in similar environments. The findings contribute to advancing the application of SWOT data in hydrological monitoring and geomorphological analysis at regional scales. Full article

Objective: Atherosclerotic renal artery stenosis (ARAS) is increasingly prevalent among aging populations and in patients with diabetes, hyperlipidemia, aortoiliac obstructive disease, coronary artery disease, and/or hypertension. Patients with severe ARAS are at a substantially elevated risk of cardiovascular disease, recurrent congestive heart failure, stroke, ischemic nephropathy, and chronic kidney disease. Therefore, the ARAS-TR study aims to evaluate the effect of renal artery stenting on the clinical outcomes in patients with severe ARAS and renovascular hypertension. Materials: This study was conducted as a multicenter, prospective study between July 2024 and September 2025. It encompassed 278 patients with angiographically confirmed severe ARAS who underwent renal artery stent implantation. Patients were subsequently monitored for 6 months. A paired-samples t-test was used to compare continuous variables pre- and post-intervention, while categorical variables were analyzed using the Pearson chi-square test and Fisher’s exact test. Results: The mean age of the patients was 63.6 [±13.4] years, and the male gender ratio was 52.5%. After renal artery stenting, systolic and diastolic blood pressures decreased significantly at the 6-month follow-up compared with the pre-procedure levels (SBP 166.99 [21.24] vs. 135.40 [15.69], p < 0.001; DBP 96.28 [13.03] vs. 80.39 [11.03], p < 0.001, respectively). GFR (61.23 [28.33] vs. 63.35 [26.36], p = 0.029) and creatinine (1.40 [0.93] vs. 1.29 [0.66], p = 0.004) levels improved compared to baseline. The mean number of antihypertensive drugs required for patients to remain normotensive decreased significantly (3.19 [1.04] vs. 2.48 [1.13], p < 0.001) during the follow-up period. Conclusions: Percutaneous renal artery intervention appears to be a promising and safe strategy for carefully selected high-risk patients presenting with severe ARAS, renovascular hypertension, and non-atrophic kidneys. In this specific clinical context, restoring renal artery patency through percutaneous stenting was associated with improved renal function and observed reduction in the burden of antihypertensive drugs required to sustain normotension. Full article

Series arc faults on the DC side of photovoltaic (PV) systems are a critical hazard that can trigger system fires. Conventional contact-based detection methods suffer from cumbersome installation and high retrofit cost, whereas existing non-contact approaches mostly rely on megahertz-level high-frequency sampling and therefore require expensive radio-frequency instrumentation or high-performance computing platforms. As a result, it remains difficult to simultaneously achieve strong interference immunity and real-time performance on low-cost embedded devices with limited resources. To address this engineering paradox between high-frequency sampling and constrained computational capability, this paper proposes a fully embedded, non-contact arc fault detection system based on a 12–80 kHz low-frequency sub-band selection strategy. By exploiting the physical characteristic of broadband energy elevation induced by arc faults, the proposed strategy avoids dependence on high-bandwidth hardware. Guided by this strategy, a Moebius-topology coaxial shielded loop antenna is employed as the near-field sensor, while an ultra-simplified passive analog front end is constructed directly by using the on-chip programmable gain amplifier and analog-to-digital converter of the microcontroller unit, enabling efficient signal acquisition and fast Fourier transform processing within the target sub-band. To cope with complex background noise in the low-frequency range, an environment-adaptive baseline mechanism based on exponential moving average and exponential absolute deviation is developed for dynamic decoupling. In addition, a lightweight INT8-quantized multilayer perceptron is introduced as a nonlinear auxiliary module, thereby forming a robust hybrid decision architecture with complementary rule-based and artificial intelligence components. Experimental results show that, under the tested household, laboratory, and PV-site conditions, the proposed system achieved an overall detection rate of 97%, while the remaining 3% mainly corresponded to failed ignition or non-sustained arc attempts rather than persistent false triggering during normal monitoring. Full article

Inflammation plays a key role in the pathogenesis of many diseases, including cardiovascular disease and ischemic stroke. However, despite the existence of known inflammatory genes, the question of estimating their total number and the possibility of discovering new ones remains open. This study sought and analyzed genes involved in inflammation among genes related to cardiovascular disease and ischemic stroke. Human genes associated with ischemic stroke (N = 1177) and cardiovascular disease (N = 1756) were retrieved from the DisGeNET platform. Inflammatory and immune response genes were obtained from the Gene Ontology, NCBI, and Reactome databases. An additional list of 140 inflammatory genes was compiled based on our previously obtained data on the differential gene expression in a rat brain under transient middle cerebral artery occlusion. Genes that occurred simultaneously in both the inflammatory gene lists and gene lists of diseases were selected and considered. The resulting combined gene list included 1285 inflammatory genes. The NFKB1 and RELA genes demonstrated the highest frequencies across the various inflammatory gene selection resources we examined. Using a combination of experimental and bioinformatics approaches, a representative list of inflammatory genes important for the pathogenesis of ischemic stroke was compiled. The identified genes may be crucial for the development of anti-inflammatory therapeutic strategies for this disease. Full article

Heavy metal pollution remains a major global environmental challenge due to persistent ecological risks and potential threats to food safety. Microbial remediation and phytoremediation represent sustainable alternatives to conventional treatments; however, their effectiveness is strongly influenced by number of factors including nutrient availability. This review critically examines how nutritional regulation governs microbial metabolism, plant physiological responses, and rhizosphere interactions to enhance heavy metal transformation and removal. Metal bioavailability depends on type, concentration, soil pH, redox potential, and microbial processes. Interventions including fertilizers, chelating agents, inoculation with arbuscular mycorrhizal fungi and plant-growth-promoting rhizobacteria enhance phytoremediation processes through regulating plant nutrient and heavy metal uptake, while selection between ammonium/nitrate changes rhizosphere pH consequently affects plant metal uptake. Similarly, nutrients, i.e., phosphate, iron, zinc and manganese competitively affect metal uptake. Organic amendments enhance phytostabilization, especially for selenium and mercury, while enhancing chromium reduction. Sulfur-reducing bacteria precipitate metals as insoluble sulfides with 90% efficiency. In addition, soil amendments including plant-growth-promoting rhizobacteria, arbuscular mycorrhizal fungi, and metal-chelating agents can be strategically used to enhance the phytoextraction from metal from contaminated soils. We suggest that the future integration of modern approaches such as multi-omics and cisgenesis supported by artificial intelligence tools can help to accurately predict the efficiency of nutrient regulation strategies and their remediation outcomes, thereby supporting evidence-based soil management Full article

NanoArduSiPM represents a paradigm shift in the ArduSiPM (Architected Detection Unit for Silicon Photomultipliers) roadmap, evolving from a standalone instrument into a high-density modular building block (36 mm × 42 mm × 3 mm, 7 g). This revision does not merely pursue miniaturization; it re-engineers the signal-processing chain to maintain high performance within a scaled-down footprint, enabling the transition from single-unit detection to scalable, distributed multi-detector systems. NanoArduSiPM is based on a three-layer architecture comprising an external scintillator and Silicon Photomultiplier (SiPM) detection module, a dedicated high-speed discrete analog front-end, and a System-on-Chip (SoC) for embedded acquisition and processing. The physical implementation adopts high-integrity PCB routing and rigorous isolation techniques designed to suppress digital–analog coupling, a critical requirement in such a compact form factor. This deterministic layout strategy provides the architectural foundation for time-tagging capabilities, currently under quantitative characterization, by addressing the fundamental sources of signal interference at the hardware level. Beyond hardware integration, NanoArduSiPM introduces the capability for extended firmware functionality, including event tagging via external inputs and the implementation of coincidence and veto logic. This framework supports the acquisition of multiple correlated histograms and allows multiple units to be interconnected on a shared SPI bus. By shifting from standalone operation to a coordinated, hierarchical architecture, NanoArduSiPM enables distributed detection schemes where event selection and correlation are handled natively within the system, reducing the dependency on external data acquisition electronics. The compact modular architecture, together with the high-performance discrete analog front-end and embedded data handling, makes NanoArduSiPM suitable for applications where low mass and low power consumption are critical, targeting applications such as space-based payloads, laboratory instrumentation, remote sensing, and large-scale distributed multi-channel detection systems. While no radiation-tolerance qualification of the complete system has been performed in this work, the microcontroller family used in the design is also available in radiation-tolerant variants, which may support future implementations targeting more demanding radiation environments. Full article

Myalgic Encephalomyelitis/Chronic Fatigue Syndrome (ME/CFS) is a complex, multi-system disease characterized by a multitude of symptoms across various organ systems. Diagnosis has relied heavily on heterogeneous clinical symptom presentation and evolving case definitions, with treatment focused on addressing presenting symptoms due to the paucity of validated biomarkers. Meanwhile, advances have been made in understanding the underlying pathophysiology through strong epidemiologic, clinical, and basic science studies. This narrative review synthesizes recent advances that are likely to drive a shift in understanding from symptom-based classification toward a molecularly defined understanding of the disease. This shift in understanding will likely provide the foundation for future research efforts focused on targeting diagnosis and treatment more effectively. Specifically, we reference the identification of rare genetic risk variants through the HEAL2 deep learning framework, the large-scale DecodeME genome-wide association study, and dynamic epigenetic markers of disease state. In addition, the findings revealed the downstream consequences of this genetic and epigenetic priming: chronic innate immune activation, CD8+ T cell exhaustion characterized by upregulation of the exhaustion-driving transcription factors Thymocyte Selection-Associated HMG Box (TOX) and Eomesodermin (EOMES), and a cellular energy crisis centered on mitochondrial dysfunction. Furthermore, results of recent studies have revealed sex-specific transcriptomic and proteomic signatures of maladaptive recovery. We also highlight the role of machine learning and artificial intelligence integrations in translating high-dimensional multi-omics data into actionable biological insights, including the identification of monocyte subsets via Positive Unlabeled Learning, circulating cell-free RNA diagnostic signatures, and integrated multi-modal disease models such as BioMapAI. The combination of these findings, which highlight multiple identifiable mechanisms of molecular activity, support the feasibility of molecular subtyping, precision diagnostics, and targeted therapeutic strategies for ME/CFS. Full article

Background and Objectives: Elective electrical cardioversion (eECV) in patients with atrial fibrillation (AF) or atrial flutter is associated with a low risk of thromboembolic events (TEs) when adequate anticoagulation is provided. However, the role of routine transesophageal echocardiography (TEE) prior to eECV remains uncertain. This study aimed to assess thromboembolic outcomes in patients undergoing eECV with or without TEE guidance in a real-world clinical setting. Methods: A single-center, combined retrospective–prospective observational study including 296 adequately anticoagulated patients with AF or atrial flutter scheduled for eECV was conducted. The retrospective cohort (n = 220) underwent eECV without routine TEE, while the prospective cohort (n = 85) underwent TEE prior to eECV. The primary outcome was the occurrence of thromboembolic events (ischemic stroke or systemic embolism) within 30 days after eECV. Arrhythmia recurrence at 30 days was assessed as a secondary, exploratory outcome. Results: Among patients undergoing eECV, thromboembolic events were rare. In the retrospective cohort, 3/220 patients (1.36%) experienced a TE, whereas no events were observed in the prospective cohort (0/76). Due to the low number of events, the study was underpowered to detect meaningful differences between strategies (RR 2.44; 95% CI 0.13–46.7; p = 0.55). TEE identified left atrial appendage thrombus in 9/85 screened patients (10.6%), who were subsequently excluded from cardioversion. Arrhythmia recurrence at one month was more frequent in the prospective cohort (19.7% vs. 7.3%), likely reflecting differences in baseline clinical characteristics. Conclusions: Thromboembolic events after eECV in adequately anticoagulated patients were infrequent in this real-world cohort. While the study design limits direct comparison between strategies, the results indicate that a conventional anticoagulation-based approach without routine TEE is associated with a low risk of thromboembolic events in most patients. At the same time, the detection of left atrial appendage thrombus in a subset of patients underscores the importance of individualized risk assessment and supports the selective use of TEE in higher-risk clinical settings. Full article

Infrared (IR) object detection on unmanned aerial vehicle (UAV) platforms is fundamentally challenged by low signal-to-noise ratios and extremely tight onboard computational budgets. Conventional CNNs lack sufficient global context, while Transformers suffer from quadratic complexity, hindering real-time deployment. To address these bottlenecks, we propose EfficientIR-Det, a lightweight end-to-end detector featuring a holistic optimization of the backbone, encoder, and sampling mechanisms. Specifically, we design a Partial Star Network (PSN) backbone that achieves implicit high-dimensional feature expansion via element-wise multiplication to amplify weak IR signals with minimal redundancy. Furthermore, a Hierarchical Mamba (HiMamba) encoder leverages selective state-space modeling to provide linear-complexity global enhancement with superior hardware efficiency. To refine cross-scale representations, we introduce an Adaptive Gated Sampling (AGS) module and a Hierarchical Sampling Strategy (HSS) to optimize feature fusion and sampling budget allocation toward dim-small targets. On HIT-UAV, EfficientIR-Det achieves 88.4% mAP@0.5, outperforming the RT-DETR-R18 baseline by 3.3 points while reducing FLOPs and parameters by 48.9% and 44.2%, respectively. On the larger-scale DroneVehicle dataset, it consistently leads with a 74.1% mAP@0.5 and a high inference speed of 140.8 FPS. Our results offer a promising research scheme for robust, real-time infrared perception on edge-constrained UAV platforms. Full article