Search Results (5,222)

In recent years, remote sensing technologies have become indispensable for the documentation, analysis, and virtual preservation of historical, architectural, and archaeological heritage. Advances in 3D scanning have enabled the precise digital recording of complex structures as large-scale point clouds, facilitating highly detailed virtual reconstructions. This study evaluates the capability of LiDAR-based Terrestrial Laser Scanning (TLS) for documenting historical monument façades within a 3D environment and generating accurate visualisation models from registered, colourised point clouds. The integration of high-resolution RGB imagery, processed through Reality Capture 1.5 software, enables the automatic production of realistic 3D models that combine geometric accuracy with visual fidelity. Simultaneously, Geographic Information Systems (GIS), particularly cloud-based platforms like ArcGIS Pro Online, enhance spatial data management, mapping, and analysis. When combined with TLS, GIS is part of a broader remote sensing framework that improves heritage documentation regarding precision, speed, and interpretability. The digital survey of the Shanasheel house in Al-Basrah, Iraq, demonstrates the effectiveness of this interdisciplinary approach. These architecturally and culturally significant buildings, renowned for their intricately decorated wooden façades, were digitally recorded using CAD-based methods to support preservation and mitigation against urban and environmental threats. This interdisciplinary workflow demonstrates how remote sensing technologies can play a vital role in heritage conservation, enabling risk assessment, monitoring of urban encroachment, and the protection of endangered cultural landmarks for future generations. Full article

This paper does not describe the results of a systematic search for the mechanism of action of cyclophosphamide and the consequences and possible indications arising from this mechanism. Rather, it describes a puzzle in which our own results, with some of them being very old, were re-evaluated with the latest biochemical knowledge and supplemented by results from the scientific literature. The mechanism of action of cyclophosphamide, which has been indispensable in clinical practice for 60 years, was unknown until recently simply because biochemical knowledge was lacking and because results from in vitro experiments were uncritically extrapolated to in vivo conditions. In vitro, the DNA alkylating metabolite phosphoramide mustard (PAM) is formed from the CP metabolite aldophosphamide (ALD) by phosphate and bicarbonate ion-catalyzed β-elimination of acrolein; in vivo, however, ALD is cleaved by phosphoesterases or DNA polymerase δ and ε, which are associated with 3′-5′ exonucleases, into the complementary metabolites PAM and 3-hydroxypropanal (HPA). The following describes the mechanism of action of CP, namely the complementary interaction of alkylating PAM and apoptosis-enhancing HPA, and it is shown that by optimizing the complementary effects of PAM and HPA, the antitumor efficacy in the P388 mouse tumor model can be increased by more than ten thousand-fold. Further experiments show that by optimizing the interaction of DNA alkylation and enhancing the resulting apoptosis by HPA, the formation of resistant metastases can be prevented and low-toxicity chemotherapy can be achieved. Full article

The study at the Sanctuary of Eukleia in Aigai (Vergina, Greece) evaluates the planimetric and vertical accuracy of Digital Surface Model (DSM) generated by a Hesai XT32M2X LiDAR system mounted on UAS WingtraOne GEN II. The paper begins by outlining the evolution of UAS-LiDAR, then describing the acquisition of RGB, multispectral (MS) images and LiDAR data. Twenty-two Check Points (CPs) were measured using an RTK-GNSS receiver, which also served to establish the PPK calibration base point. This is followed by processing the images to generate DSMs and orthophotomosaics, as well as processing the LiDAR point cloud to produce both DSM and DTM products. The DSMs and orthophotomosaics were evaluated by comparing field-measured CP coordinates with those extracted from the products, computing mean values and standard deviations. RGB images yielded DSMs and orthophotomosaics with planimetric accuracy of 1.4 cm (with a standard deviation σ = ±1 cm) in X, 0.9 cm (with σ = ±0.9 cm) in Y and a vertical accuracy of 2.4 cm (with σ = ±1.7 cm). The LiDAR-derived DSM achieved similar planimetric accuracy and an overall vertical accuracy of 7.5 cm (with σ = ±6 cm). LiDAR’s ability to penetrate vegetation enabled near-complete mapping of a densely vegetated streambank, highlighting its clear advantage over images. While high-precision RGB-PPK products can surpass LiDAR in vertical accuracy, UAS-LiDAR remains indispensable for under-canopy terrain mapping. Full article

Technology has historically served as a fundamental driver of human welfare and progress. Contemporary calls for temporary moratoria on technological development, motivated by concerns about existential threats to humanity, represent a misguided approach that may ultimately prove counterproductive to human flourishing. This paper argues that technology itself is not inherently problematic; rather, the issue lies in contemporary society’s fragmented ontological framework. Drawing on African philosophical traditions, particularly Kemetic cosmology and ubuntu philosophy, we examine how ancient Kemetic civilization exemplified transhumanist principles through its integration of technological advancement within a holistic worldview. The Kemetic understanding of Reality as a sacred, differentiated Whole, embodied in their conception of Atum as the self-developing divine principle, always connected to and guided by Shu (life) and Tefnut/Ma’at (order), provided a cosmological foundation that enabled beneficial coexistence with technology as a life-giving human contingency regulated by ma’at. Similarly, the ubuntu cosmo-philosophical vision in contemporary African thought emphasizes Reality as an interconnected totality, with technology being an independent yet connected excitation in this Reality. This study, therefore, contends that the fundamental challenge facing modern society today is not technological or AI development per se, but rather the need to reconstruct our fragmented perception of Reality. Within a properly integrated cosmological vision, technology functions not as a selfish instrument or an object readily available for our exploitative purposes but as an inherently life-affirming, sustaining, and enhancing force indispensable for the well-being of the Whole. The implications suggest that, rather than constraining technological advancement, which could be detrimental to our well-being due to our inherent reliance on it, as it relies on us, efforts should be directed toward cultivating a holistic yet relational understanding of technology, with the cosmos. Full article

This policy insight outlines Latvia’s national strategy for integrating simulation-based education into all levels of medical and healthcare education by 2027. It is framed as a direct response to the 2024 Global Consensus Statement on Simulation-Based Practice in Healthcare, operationalizing its recomme ndations within a national policy context for Latvia. Grounded in international and national standards—including WHO guidance, EU directives, and principles of healthcare safety and education quality—the strategy promotes simulation as a transitional and indispensable phase between theoretical instruction and clinical practice. The strategy emphasises structured collaboration among universities, professional associations, healthcare providers, and government bodies. It sets out a governance and resource model for simulation-based learning environments, ensuring quality, sustainability, and alignment with ethical and professional standards. By embedding simulation-based education into undergraduate, postgraduate, and continuing medical education, Latvia aims to enhance healthcare professionals’ clinical competence, reduce preventable medical errors, and improve patient outcomes. The approach supports deliberate practice, facilitates safe and realistic training conditions, and strengthens the preparedness of healthcare workers for both routine and complex clinical scenarios. The strategy also calls for standardised quality-assurance mechanisms, accreditation procedures, and integration into national regulatory frameworks. This national roadmap aims to establish Latvia as a regional leader in simulation-based healthcare education, improving not only the safety and efficiency of healthcare services but also public trust and professional development. As such, the strategy serves both as a practical implementation plan and a model for countries pursuing similar goals. Full article

The health and productivity of rabbits are highly sensitive to the environmental conditions within the rabbit house, particularly to fluctuations and deviations in temperature, relative humidity, and carbon dioxide (CO₂) concentration. However, owing to the thermal inertia and residual evaporation effects inherent in ventilation and cooling systems, environmental changes often exhibit delayed responses, rendering real-time control inadequate. Accurate prediction of key environmental parameters is indispensable for formulating effective environmental control strategies, as it enables consideration of their future dynamics and thereby enhances the rationality of regulation in rabbit farming. Existing prediction models often exhibit unsatisfactory accuracy and weak generalization, which restricts the incorporation of prediction into effective environmental control strategies. To address these limitations, summer indoor and outdoor environmental data were collected from rabbit houses in Nanping, Fujian; Jiyuan, Henan; and Qingyang, Gansu, China—three climatically distinct regions—forming three datasets. Based on these datasets, a multi-parameter time-series prediction model, Patch and Cross-Attention Enhanced Transformer for Rabbit House Prediction (PatchCrossFormer-RHP), is introduced, integrating patching and attention mechanisms. The model partitions the sequences of rabbit house temperature, relative humidity, and CO₂ concentration into patches and incorporates auxiliary parameters, such as indoor air velocity and outdoor temperature and humidity, to enhance feature representation. Furthermore, it applies cross-attention with differentiated encoding to disentangle multi-parameter relationships and improve predictive performance. This study used the Fujian dataset as the primary benchmark. On this dataset, PatchCrossFormer-RHP achieved root mean square error (RMSE) values of 0.290 °C, 1.554%, and 38.837 ppm for rabbit house temperature, humidity, and CO₂ concentration, respectively, with corresponding R² values of 0.963, 0.956, and 0.838, consistently outperforming RNN, GRU, and LSTM. Transfer experiments with single- and multi-source pretraining followed by fine-tuning on Fujian demonstrated that strong cross-regional generalization can be achieved with only limited target-domain data. Full article

Background: T cell regeneration in the thymus is intrinsically linked to the T cell-biased lineage differentiation of hematopoietic stem and progenitor cells (HSPCs). Although nonhuman primates (NHPs) serve as indispensable models for studying thymic output under physiological and pathological conditions, a non-animal technology facilitating efficient TCR-selected T cell development and evaluating T cell output from NHP-derived HSPCs has been lacking. To address this gap, we established a rhesus macaque-specific artificial thymic organoid (RhATO) modeling primary thymus-tissue-free thymopoiesis. Methods: The RhATO was developed by expressing Rhesus macaque (RM) Delta-like Notch ligand 1 in mouse bone marrow stromal cell line (MS5-RhDLL1). The bone marrow-derived HSPCs were aggregated with MS5-RhDLL1 and cultured forming 3D artificial thymic organoids. These organoids were maintained under defined cytokine conditions to support complete T cell developmental ontogeny. T cell developmental progression was assessed by flow cytometry, and TCR-selected subsets were analyzed for phenotypic and functional properties. Results: RhATOs recapitulated the complete spectrum of thymopoietic events, including emergence of thymus-seeding progenitors, CD4⁺CD3⁻ immature single-positive and CD4⁺CD8⁺ double-positive early thymocytes, and mature CD4⁺ or CD8⁺ single-positive subsets. These subsets expressed CD38, consistent with the recent thymic emigrant phenotype, and closely mirrored canonical T cell ontogeny described in humans. RhATO-derived T cells were TCR-selected and demonstrated cytokine expression upon stimulation. Conclusions: This study provides the first demonstration of an NHP-specific artificial thymic technology that faithfully models thymopoiesis. RhATO represents a versatile ex vivo platform for studying T cell development, immunopathogenesis, and generating TCR selected T cells. Full article

Nonunions and fracture-related infections represent a significant complication in orthopedic and trauma care, with their incidence rising due to an aging, more comorbid global population and the escalating threat of multi-resistant pathogens. This narrative review highlights pivotal advancements in diagnostics and therapeutic approaches, while also providing an outlook on future directions. Diagnostic methodologies have significantly evolved from traditional cultures to sophisticated molecular techniques like metagenomic next-generation sequencing and advanced imaging. Simultaneously, therapeutic strategies have undergone substantial refinement, encompassing orthoplastic management for infected open fractures and the innovative application of antibiotic-loaded bone substitutes for local drug delivery. The effective integration of these possibilities into daily patient care critically depends on specialized centers. These institutions play an indispensable role in managing complex cases and fostering innovation. Despite considerable progress over the past 25 years, ongoing research, interdisciplinary collaboration, and a steadfast commitment to evidence-based practice remain crucial to transforming management for the future. Full article

Heterotrimeric G_i proteins are crucial modulators of G protein-coupled receptor signaling, with Gα_i2 ubiquitously expressed and implicated in diverse physiological processes. Previous reports described partial lethality in Gnai2-deficient mice, but the timing and mechanism of death remained unclear. Here, we demonstrate that impaired neonatal respiratory adaptation contributes to mortality in Gnai2-deficient neonates. Despite normal Mendelian distribution at birth and no overt malformations, at least 20% of the expected Gnai2-deficient neonates died within minutes after birth, displaying abnormal breathing, cyanosis, and features resembling neonatal respiratory distress syndrome (RDS). Histological and ultrastructural analyses revealed reduced alveolar surface area, thickened septa, increased mesenchymal tissue, and impaired surfactant ultrastructure, despite unaltered alveolar surfactant phospholipid levels. These findings suggest that Gα_i2 modulates the structural deployment and functional organization of surfactant within alveoli, although the incomplete phenotype and survival of some neonates indicate a regulatory rather than indispensable role of Gα_i2. Our data underscore the complexity of neonatal respiratory adaptation and highlight potential systemic and intercellular mechanisms underlying alveolar stabilization. Full article

In arid environments such as the Namib Desert, non-rainfall water sources—including dew and fog—constitute indispensable yet understudied components of the regional hydrological cycle. These moisture inputs play a critical role in sustaining ecological functionality and biogeochemical processes, but remain among the least quantified facets of desert ecohydrology. The present study investigates multi-year trends in morning dew formation within the Namib Desert, utilizing observations from the Gobabeb–Namib Research Institute between 2015 and 2022. Meteorological data from the Southern African Science Service Centre for Climate and Adaptive Land Management (SASSCAL), in conjunction with direct field observations of dew, were used to develop an empirical equation to estimate dew occurrence. A sensitivity analysis verified the robustness of this formulation, and subsequent validation using field data confirmed its reliability (84.84% accuracy). During this eight-year period, the annual number of days with morning dew decreased from 170 in 2015 to 140 in 2022, representing an overall decline of approximately 18%. However, the total daily dew occurrence across 24 h remained relatively constant, indicating that the observed decline is confined primarily to morning condensation events. Dew formation was most prevalent during the wet season (December–May). Both monthly and annual analyses revealed a discernible declining trend in morning dew occurrence across this hyperarid ecosystem (p < 0.05). This decline corresponded with a gradual increase in both air and soil temperatures (approximately +0.03 °C yr⁻¹) and a slight but consistent decrease in relative humidity (approximately −0.26% yr⁻¹) between 2015 and 2022. The principal drivers of this decline include rising soil and air temperatures and decreasing atmospheric humidity. The analysis further identified an inverse relationship between air temperature and dew formation, implying that climatic warming intensifies evaporative demand and thereby suppresses dew condensation. Random forest analysis identified soil temperature, air temperature, and relative humidity as the most important predictors influencing dew occurrence, whereas wind speed and direction played lesser roles. Collectively, these findings underscore the vulnerability of dew-dependent ecosystems to anthropogenic climate change and highlight the imperative to continue investigating non-rainfall moisture dynamics in desert environments. Full article

While recent industrial automation trends emphasize the importance of non-destructive inspection by material-identifying millimeter-wave, terahertz-wave, and infrared (MMW, THz, IR) monitoring, fundamental tools in these wavelength bands (such as sensors) are still immature. Although inorganic semiconductors serve as diverse sensors with well-established large-scale fine-processing fabrication, the use of those devices is insufficient for non-destructive monitoring due to the lack of photo-absorbent properties for such major materials in partial regions across MMW–IR wavelengths. To satisfy the inherent advantageous non-destructive MMW–IR material identification, ultrabroadband operation is indispensable for photo-sensors under compact structure, flexible designability, and sensitive performances. This review then introduces the recent advances of carbon nanotube film-based photo-thermoelectric imagers regarding usable and high-yield device fabrication techniques and scientific synergy among computer vision to collectively satisfy material identification with three-dimensional (3D) structure reconstruction. This review synergizes material science, printable electronics, high-yield fabrication, sensor devices, optical measurements, and imaging into guidelines as functional non-destructive inspection platforms. The motivation of this review is to introduce the recent scientific fusion of MMW–IR sensors with visible-light computer vision, and emphasize its significance (non-invasive material-identifying sub-millimeter-resolution 3D-reconstruction with 660 nm–1.15 mm-wavelength imagers at noise equivalent power within 100 pWHz^−1/2) among the existing testing methods. Full article

The growing demand for air connectivity, coupled with the forecasted increase in passengers by 2040, implies an exigency in the aviation sector to adopt sustainable approaches for net zero emission by 2050. Sustainable Aviation Fuel (SAF) is currently the most promising short-term solution; however, ensuring its overall sustainability depends on reducing the life cycle carbon footprints. A key challenge prevails in hydrogen usage as a reactant for the approved ASTM routes of SAF. The processing, conversion and refinement of feed entailing hydrodeoxygenation (HDO), decarboxylation, hydrogenation, isomerisation and hydrocracking requires substantial hydrogen input. This hydrogen is sourced either in situ or ex situ, with the supply chain encompassing renewables or non-renewables origins. Addressing this hydrogen usage and recognising the emission implications thereof has therefore become a novel research priority. Aside from the preferred adoption of renewable water electrolysis to generate hydrogen, other promising pathways encompass hydrothermal gasification, biomass gasification (with or without carbon capture) and biomethane with steam methane reforming (with or without carbon capture) owing to the lower greenhouse emissions, the convincing status of the technology readiness level and the lower acidification potential. Equally imperative are measures for reducing hydrogen demand in SAF pathways. Strategies involve identifying the appropriate catalyst (monometallic and bimetallic sulphide catalyst), increasing the catalyst life in the deoxygenation process, deploying low-cost iso-propanol (hydrogen donor), developing the aerobic fermentation of sugar to 1,4 dimethyl cyclooctane with the intermediate formation of isoprene and advancing aqueous phase reforming or single-stage hydro processing. Other supportive alternatives include implementing the catalytic and co-pyrolysis of waste oil with solid feedstocks and selecting highly saturated feedstock. Thus, future progress demands coordinated innovation and research endeavours to bolster the seamless integration of the cutting-edge hydrogen production processes with the SAF infrastructure. Rigorous techno-economic and life cycle assessments, alongside technological breakthroughs and biomass characterisation, are indispensable for ensuring scalability and sustainability. Full article

Laboratory astrophysics is an emerging interdisciplinary field bridging high-energy-density plasma physics and astrophysics. Optical diagnostic techniques offer high spatiotemporal resolution and the unique capability for simultaneous multi-field measurements. These attributes make them indispensable for deciphering extreme plasma dynamics in laboratory astrophysics. This review systematically elaborates on the physical principles and inversion methodologies of key optical diagnostics, including Nomarski interferometry, shadowgraphy, and Faraday rotation. Highlighting frontier progress by our team, we showcase the application of these techniques in analyzing jet collimation mechanisms, turbulent magnetic reconnection, collisionless shocks, and particle acceleration. Future trajectories for optical diagnostic development are also discussed. Full article

Binary code similarity detection serves as a critical front-line defense mechanism in cybersecurity, playing an indispensable role in identifying known vulnerabilities, detecting emergent malware families, and preventing intellectual property theft via code plagiarism. However, existing methods based on Control Flow Graphs (CFGs) often suffer from two major limitations: the inadequate capture of deep semantic information within CFG nodes, and the neglect of structural relationships across different functions. To address these issues, we propose Breg, a novel framework that synergistically integrates pre-trained semantic features with cross-graph structural features. Breg employs a BERT model pre-trained on a large-scale binary corpus to capture nuanced semantic relationships, and introduces a Cross-Graph Neural Network (CGNN) to explicitly model topological correlations between two CFGs, thereby generating highly discriminative embeddings. Extensive experimental validation demonstrates that Breg achieves leading F1-scores of 0.8682 and 0.8970 on Dataset3. In real-world vulnerability search tasks on Dataset4, Breg achieves an MRR@10 of 0.9333 in the challenging MIPS32-to-x64 search task, a clear improvement over the 0.8533 scored by the strongest baseline. This underscores its superior effectiveness and robustness across diverse compilation environments and architectures. To the best of our knowledge, this is the first work to integrate a pre-trained language model with cross-graph structural learning for binary code similarity detection, offering enhanced effectiveness, generalization, and practical applicability in real-world security scenarios. Full article

Degenerative cervical myelopathy (DCM) is a common cause of spinal cord dysfunction in adults and is frequently accompanied by pain, a symptom that remains under-recognised despite its profound impact on quality of life. Conventional magnetic resonance imaging (MRI) is indispensable for identifying structural spinal cord compression; however, it is unable to detect early microstructural alterations, particularly those that may contribute to pain pathophysiology. This narrative review critically appraises the limitations of standard MRI in the diagnostic assessment of DCM and examines the expanding role of advanced imaging modalities—most notably diffusion tensor imaging (DTI)—in evaluating spinal cord integrity. DTI-derived parameters, including fractional anisotropy (FA), mean diffusivity (MD), axial diffusivity (AD), and radial diffusivity (RD), demonstrate sensitivity to axonal and myelin injury. For example, reductions in FA and AD have been linked to axonal disruption in sensory pathways, while elevations in RD suggest demyelination, a hallmark of neuropathic pain. Despite this potential, the widespread implementation of DTI is constrained by technical heterogeneity, limited accessibility, and the absence of standardised protocols. Future research priorities include the incorporation of pain-specific imaging endpoints, longitudinal validation across diverse cohorts, and integration with artificial intelligence frameworks to enable automated analysis and predictive modelling. Collectively, these advances hold promise for enabling earlier diagnosis, refined symptom stratification, and more personalised therapeutic strategies in DCM. Full article