Search Results (11,241)

Redox balance is essential for maintenance of the hematopoietic stem cell (HSC) pool, which ensures the lifelong hematopoiesis. However, oxidative attack induced by various physiopathological stresses always compromises HSC maintenance, while there remains lack of safe and effective antioxidative measures combating these conditions. Here, we show that ferulic acid (FA), a natural antioxidant abundantly present in Angelica sinensis which is a traditional Chinese herb commonly used for promotion of blood production, distinctively and directly promotes HSC maintenance and thereby boosts hematopoiesis at homeostasis, whether supplemented over the long term in vivo or in HSC culture ex vivo. Using a mouse model of acute myelosuppressive injury induced by ionizing radiation, we further reveal that FA supplementation effectively safeguards HSC maintenance and accelerates hematopoietic regeneration after acute myelosuppressive injury. Mechanistically, FA diminishes ferroptosis susceptibility of HSCs through limiting the labile iron pool (LIP), thus favoring HSC maintenance. In addition, the LIP limitation and anti-ferroptosis activity of FA is independent of nuclear-factor erythroid 2-related factor 2 (NRF2), probably relying on its iron-chelating ability. These findings not only uncover a novel pharmacological action and mechanism of FA in promoting HSC maintenance, but also provides a therapeutic rationale for using FA or FA-rich herbs to treat iron overload- and ferroptosis-associated pathologies such as acute myelosuppressive injury. Full article

Change detection (CD) in optical remote-sensing images is a critical task for applications such as urban planning, disaster monitoring, and environmental assessment. While UNet-based architecture has demonstrated strong performance in CD tasks, it often struggles with capturing deep hierarchical features due to the limitations of plain convolutional layers. Conversely, ResNet architectures excel at learning deep features through residual connections but may lack precise localization capabilities. To address these challenges, we propose ResUNet++, a novel hybrid architecture that combines the strengths of ResNet and UNet for accurate and robust change detection. ResUNet++ integrates residual blocks into the UNet framework to enhance feature representation and mitigate gradient vanishing problems. Additionally, we introduce a Multi-Scale Feature Fusion (MSFF) module to aggregate features at different scales, improving the detection of both large and small changes. Experimental results on multiple datasets (EGY-CD, S2Looking, and LEVIR-CD) demonstrate that ResUNet++ outperforms state-of-the-art methods, achieving higher precision, recall, and F1-scores while maintaining computational efficiency. Full article

Uncooled microbolometers play a pivotal role in infrared detection owing to their compactness, low power consumption, and cost-effectiveness. This review comprehensively summarizes recent progress in thermistor materials and focal plane arrays (FPAs), highlighting improvements in sensitivity and integration. Vanadium oxide (VO_x) remains predominant, with Al-doped films via atomic layer deposition (ALD) achieving a temperature coefficient of resistance (TCR) of −4.2%/K and significant 1/f noise reduction when combined with single-walled carbon nanotubes (SWCNTs). Silicon-based materials, such as phosphorus-doped hydrogenated amorphous silicon (α-Si:H), exhibit a TCR exceeding −5%/K, while titanium oxide (TiO_x) attains TCR values up to −7.2%/K through ALD and annealing. Emerging materials including GeSn alloys and semiconducting SWCNT networks show promise, with SWCNTs achieving a TCR of −6.5%/K and noise equivalent power (NEP) as low as 1.2 mW/√Hz. Advances in FPA technology feature pixel pitches reduced to 6 μm enabled by vertical nanotube thermal isolation, alongside the 3D heterogeneous integration of single-crystalline Si-based materials with readout circuits, yielding improved fill factors and responsivity. State-of-the-art VO_x-based FPAs demonstrate noise equivalent temperature differences (NETD) below 30 mK and specific detectivity (D*) near 2 × 10¹⁰ cm⋅Hz ^1/2/W. Future advancements will leverage materials-driven innovation (e.g., GeSn/SWCNT composites) and process optimization (e.g., plasma-enhanced ALD) to enable ultra-high-resolution imaging in both civil and military applications. This review underscores the central role of material innovation and system optimization in propelling microbolometer technology toward ultra-high resolution, high sensitivity, high reliability, and broad applicability. Full article

A major challenge in the operation of aerostructures made of carbon fiber-reinforced polymer (CFRP) composites is their vulnerability to impact-induced damage, particularly when access is limited to only one side of the affected structure. This issue becomes even more complex considering that damage typically occurs in components subjected to initial static preloading. The objective of this study was to investigate the influence of static preload on the extent of damage in CFRP composites subjected to impact energy and to evaluate the effectiveness of selected non-destructive testing (NDT) methods in damage detection. Experimental investigations were conducted on a series of CFRP specimens impacted using a drop-weight tower. Each impact event was recorded with a high-speed camera operating at ultra-high frame rates. It was demonstrated that both the contact time between the impactor and the specimen, as well as the extent of internal damage assessed using ultrasonic testing (UT) and computed tomography (CT), were significantly affected by the level of applied static preload. Full article

Rheumatoid arthritis (RA) is a systemic autoimmune disorder characterized by chronic inflammation of the synovial membrane, leading to synovial hyperplasia, infiltration of immune cells, and subsequent cartilage and bone erosion. This progressive joint pathology results in persistent pain and functional impairment. Currently, convenient oral traditional disease-modifying anti-rheumatic drugs (DMARDs) are available, and increasingly precise biologic agents and targeted synthetic DMARDs (tsDMARDs) have been developed, offering promising therapeutic options. However, systemic administration generally fails to achieve therapeutic drug concentrations in the joints owing to poor biodistribution and dose-limiting systemic toxicity. Intra-articular (IA) administration has demonstrated promising potential in addressing these challenges. Among the various strategies employed for IA administration, hydrogels have gained significant attention due to their tunable mechanical properties, biocompatibility, and controlled release capabilities. These unique properties enable hydrogel-based IA delivery systems to simultaneously modulate the inflammatory microenvironment and protect cartilage tissue. This review comprehensively summarizes the histopathological changes and associated cellular and molecular events in RA, while also highlighting the design principles of hydrogels and advanced strategies for hydrogel-based IA administration. By addressing the limitations of conventional treatments, hydrogel-based IA injection holds significant promise for improving RA treatment. Full article

Jet fuels are a complex mixture of hydrocarbons and performance additives, including some compounds with established human toxicity. They represent a significant occupational hazard for military personnel; however, little is known about possible long-term health effects, particularly following cessation of exposure. In response to United States (US) Veterans’ concerns, the US Department of Veterans Affairs (VA) and the Department of Defense (DoD) launched a large retrospective cohort study to assess the impact of military occupational jet fuel exposure on Veterans’ health. The Long-Term Impact of Fuel Exposure (LIFE) cohort consists of over 1.3 million Veterans who entered service on or after 1 January 1995, including both individuals with jet fuel-exposed occupations in their service history and a random sample of unexposed Veterans. Data from multiple VA and DoD administrative datasets were linked to evaluate morbidity, disability, and mortality endpoints. Analyses are underway to assess associations between jet fuel exposure and adverse health outcomes in multiple body systems. This study represents the largest effort to date to investigate these effects, with the intention of informing policies affecting Veterans for years to come. Full article

This essay proposes operative creativity as a conceptual and artistic response to the shifting roles of images in the age of algorithmic perception. Departing from Harun Farocki’s seminal artwork Eye/Machine, which first introduced the operative image as functioning not to represent but to activate within machinic processes, it traces the transformation of images from representational devices to machinic agents embedded in systems of simulation and realization. Although operative images were initially engineered for strictly technological functions, they have, from their inception, been subject to repurposing for human perception and interpretation. Drawing on literature theorizing the redirection of operative images within military, computational, and epistemic domains, the essay does not attempt a comprehensive survey. Instead, it opens a conceptual aperture within the framework, expanding it to illuminate the secondary redeployment of operative images in contemporary visual culture. Concluding with the artwork Terms and Conditions, co-created by Ruti Sela and the author, it examines how artistic gestures might neutralize the weaponized gaze, offering a mode of operative creativity that troubles machinic vision and reclaims a space for human opacity. Full article

Background: Enteropathy-associated T-cell lymphoma (EATL) is a rare subtype of mature T-cell lymphoma, accounting for fewer than 5% of peripheral T-cell lymphomas, with an aggressive course and poor prognosis. There are two types of this disease based on morphology and immunophenotype: type I, which is often, but not always, associated with celiac disease (classic EATL), and type 2, monomorphic epitheliotropic intestinal T-cell lymphoma (MEITL). Risk factors for classic EATL are poor adherence to a gluten-free diet, advanced age, male sex, and HLA-DQ2 homozygosity. The treatment options include surgery and various chemotherapy regimens with autologous stem cell transplantation, but the outcomes are discouraging, and clinical trials with targeted and biologic therapies are needed. Case Presentation: We report three cases of type 1 EATL, all with lethal outcomes, with one patient dying during initial treatment, one dying following several surgical interventions and without waiting to start chemotherapy, and one dying following a good treatment response but with severe infection. Full article

Urban traffic congestion remains a major contributor to vehicle emissions and travel inefficiency, prompting the need for adaptive and intelligent traffic management systems. In response, we introduce DeepSIGNAL-ITS (Deep Learning Signal Intelligence for Adaptive Lights in Intelligent Transportation Systems), a unified framework that leverages real-time traffic perception and learning-based control to optimize signal timing and reduce congestion. The system integrates vehicle detection via the YOLOv8 architecture at roadside units (RSUs) and manages signal control using Proximal Policy Optimization (PPO), guided by global traffic indicators such as accumulated vehicle waiting time. Secure communication between RSUs and cloud infrastructure is ensured through Transport Layer Security (TLS)-encrypted data exchange. We validate the framework through extensive simulations in SUMO across diverse urban settings. Simulation results show an average 30.20% reduction in vehicle waiting time at signalized intersections compared to baseline fixed-time configurations derived from OpenStreetMap (OSM). Furthermore, emissions assessed via the HBEFA-based model in SUMO reveal measurable reductions across pollutant categories, underscoring the framework’s dual potential to improve both traffic efficiency and environmental sustainability in simulated urban environments. Full article

Major depressive disorder (MDD) is a prevalent and disabling psychiatric condition with limited treatment options for patients who are resistant to conventional pharmacological and psychotherapeutic interventions. Stem cell (SC)-based therapies have emerged as a promising experimental approach, offering multifaceted mechanisms of action including neurogenesis, immunomodulation, antioxidative protection, and neuromodulation. This narrative review synthesizes current evidence from preclinical studies and early-phase clinical trials on the efficacy of mesenchymal stem cells (MSCs), neural stem cells (NSCs), and induced pluripotent stem cells (iPSCs) in alleviating depressive-like behaviors. Mechanistic insights include enhanced hippocampal neurogenesis, modulation of the brain-derived neurotrophic factor (BDNF)–TrkB pathway, attenuation of neuroinflammation through microglial polarization, and restoration of serotonergic signaling via peripheral-to-central pathways such as via the vagus nerve. In addition, the therapeutic potential of extracellular vesicles (EVs) and intranasal administration as non-invasive delivery strategies is discussed. While animal and first preclinical studies suggest potential benefit, significant translational barriers remain, including issues of scalability, long-term safety, and ethical considerations. Further rigorous studies are needed to validate stem-cell-based therapies as viable treatments for MDD. Full article

Accurate modeling of event sequences is valuable in domains like electronic health records, financial risk management, and social networks. Random time intervals in these sequences contain key dynamic information, and temporal point processes (TPPs) are widely used to analyze event triggering mechanisms and probability evolution patterns in asynchronous sequences. Neural TPPs (NTPPs) enhanced by deep learning improve modeling capabilities, but most suffer from limited interpretability due to predefined functional structures. This study proposes KANJDP (Kolmogorov–Arnold Neural Jump-Diffusion Process), a novel event sequence modeling method: it decomposes the intensity function via stochastic differential equations (SDEs), with each component parameterized by learnable spline functions. By analyzing each component’s contribution to event occurrence, KANJDP quantitatively reveals core event generation mechanisms. Experiments on real-world and synthetic datasets show that KANJDP achieves higher prediction accuracy with fewer trainable parameters. Full article

This study investigates the application of two complementary risk analysis methods—risk matrix and Monte Carlo simulation—in the context of a large-scale office building construction project. The paper explores the theoretical and practical aspects of construction risk, focusing on how probabilistic and qualitative tools can support informed decision-making. Twelve key risks, including both threats and opportunities, were identified and quantified using expert judgment and historical data. The risk matrix provided an initial prioritization of risk severity and likelihood, while Monte Carlo simulations allowed for the modeling of uncertainty in cost outcomes across a probabilistic spectrum. The results indicate a high level of consistency between the methods, with both identifying value engineering as a dominant opportunity and network documentation errors as critical threats. Monte Carlo simulations further revealed that under proper risk management, the project is likely to avoid additional cost overruns with 60% certainty. This integrated approach provides practical insights for contractors and project managers seeking to enhance the robustness of risk assessment in complex construction environments. Full article

Human–environment interactions in antiquity were fundamentally shaped by environmental constraints, with spatial patterns of human construction works reflecting strategic resource optimization. This study employed Geographic Information System (GIS) and binary logistic regression (BLR) to analyze the siting principles of ancient postal buildings in Fujian, China, integrating related environmental factors of elevation, slope, relief amplitude, and distance to rivers. The results revealed significant spatial differentiation, with elevation exhibiting the strongest influence on siting preference, followed by slope, relief amplitude, and distance to rivers. Clustering patterns along coasts and rivers indicated a strategic balance between transmission efficiency and military defense needs. The applicability of the integrated GIS–BLR approach in studying the ancient postal system demonstrates its extensibility to other ancient settlement systems while offering insights for contemporary conservation practice and sustainable development. Full article

The subject of the research in this article were experimental tests of the M-346 Master aircraft model, carried out in a wind tunnel using the 3D printing method (FDM) in terms of the impact of surface post-processing technology on its aerodynamic characteristics. The measurements of key aerodynamic parameters concerned forces and moments in various airflow conditions taking into account variable angles of attack at a constant sideslip angle. The main purpose of the work was to verify the hypothesis that properly performed surface treatment significantly affects the accuracy of actual aerodynamic measurements in terms of solving the research problem using the post-processing technology, to conduct selected tests in a wind tunnel and analyze the obtained results. The obtained results of the tests, which showed a significant impact of the technological parameters of 3D printing and surface treatment methods on the correctness of the representation of real aerodynamic characteristics, were used mainly to analyze the aerodynamic performance of the model, verify the distribution of forces and moments, and evaluate the behavior of the structure in various flight scenarios. The obtained research results, the analysis of the obtained results, and selected tests were used to present important observations and formulate practical conclusions. Full article

The adhesion of endodontic sealers to dentin may be influenced both by the chemical composition of the sealer and the final irrigation protocol. The aim of this study was to examine the push-out bond strength of three differently formulated bioceramic sealers to root canal dentin, after different irrigation protocols. Four cavities were prepared in dentine discs obtained from middle thirds of third molars with fused roots. Discs were randomly divided into three groups (n = 8). Group 1: specimens were immersed in 2.5% NaOCl; group 2: in 2.5% NaOCl followed by 17% EDTA; and group 3: in a solution of 2.5% NaOCl with 9% etidronic acid (HEDP). The cavities on each disk were filled with four tested sealers: AH Plus Bioceramic, Bio C Angelus, BioRoot RCS, and AH Plus (n = 8 per sealer). The push-out bond strength test was performed after 7 days. The data were statistically analyzed using two-way analysis of variance with the Bonferroni post hoc test (α = 0.05). Irrigation with NaOCl resulted in significantly lower bond strength values of the sealers in comparison to NaOCl/EDTA and NaOCl/HEDP groups. In the NaOCl and NaOCl/HEDP groups, BioRoot RCS showed similar push-out bond strength compared to AH Plus and significantly higher compared to Bio-C and AH Plus Bioceramic. In the NaOCl/EDTA group, bioceramic sealers achieved a significantly weaker bond strength compared to AH Plus. The bond strength of BioRoot RCS was significantly higher compared to Bio-C and AH Plus Bioceramic. The irrigation protocols and the chemical composition of the sealers significantly influenced their bond strength to dentin. Epoxy resin-based sealer achieved the strongest bond strength, while within bioceramic sealers, the highest values were obtained for BioRoot RCS and the lowest for AH Plus Bioceramic. Full article