Browse Articles

Practical predefined-time adaptive fuzzy control for quantized nonlinear systems via observer-differentiator scheme

Lightweight convolutional neural network for real-time earthquake P-wave detection on edge devices in New Zealand

Kinematic and aerodynamic modeling of flexible wings with wing root adjustment for flapping wing micro aerial vehicles

Abstract In the field of insect-like flapping-wing micro aerial vehicle (FWMAV) research, this study focuses on a specific type of FWMAV that is tailless and possesses hovering capabilities. The most common method for generating aerodynamic moment in these vehicles is wing-root adjustment. By varying the twist of the wing root, an uneven or asymmetric aerodynamic distribution is created, which generates control moments. This study develops a kinematic model of flexible wings based on wing-root adjustment for aerodynamic design of insect-like FWMAVs and proposes a new aerodynamic simulation method based on multi-rigid-plane fitting to validate the kinematic model. The complete modeling framework for insect-like FWMAVs is first established, which includes the drive system transmission model, the kinematic model of wing motion under wing-root adjustment, an aerodynamic model based on a quasi-steady method, and a multi-rigid-body dynamics model. Next, the kinematics of the flexible wings are divided into three components: the relaxation phase angle equation, the wing motion equation, and the amplitude calibration equation. Then, multi-rigid plane fitting is carried out for the flexible wings based on the topological structure of the wing vein network. Taking the wing kinematics model as input, aerodynamic simulation is conducted by combining with the blade element theory. Finally, the aerodynamic simulation results are compared with results from single-plane simulations and experimental measurements. The results show that the kinematic model of the flexible wings under wing-root adjustment and the multi-plane aerodynamic simulation method are highly effective in predicting the variation of aerodynamic moment in flexible wings. The estimation error for lift does not exceed 20%, providing valuable guidance for subsequent controller design.

Exploring the burden of diarrheal disease and associated WASH practices in rural West Bengal, India: an explanatory sequential mixed-method approach

Multimodal AI-based 28-day mortality prediction of pneumonia patients at ED discharge: a multicenter study

A cascaded group attention mechanism-based object detection algorithm for construction and demolition waste

Asymmetric effects of heating and cooling degree days on carbon dioxide emissions in Germany using cross quantile regression

Integrating attractor dynamics and connectivity features for EEG-based dementia classification

New energy vehicle fault identification based on improved activation functions and parameter-free attention mechanisms

Unraveling the impact of pilot fuel injection pressure on hydrogen-diesel engine performance through PCA and RSM analysis

Abstract Hydrogen has garnered significant interest as a viable renewable energy source capable of revolutionizing conventional fuel systems. This study investigates the impact of engine load and liquid fuel injection pressure variations on the operational efficiency and emission characteristics of a hydrogen-enriched dual-fuel diesel engine, utilizing Jatropha biodiesel as the pilot ignition fuel. Advanced statistical methods, including Principal Component Analysis and Response Surface Methodology, were employed to optimize engine performance while minimizing emissions. The research aimed to achieve an Optimal Balance between efficiency requirements and emission constraints. Using Response Surface analysis, optimal engine parameters were identified at an liquid fuel injection pressure of 205.593 bar and an engine load of 70.816 %, yielding a brake thermal efficiency of 24. 3625 %, a liquid fuel replacement of 73.984 %, and NOx emissions of 188.687 ppm. These findings provide essential insights for enhancing the performance and environmental sustainability of hydrogen-assisted dual-fuel combustion systems.

The Natufian Epipalaeolithic and Pre-Pottery Neolithic in the desert of northern Arabia

Abstract The Fertile Crescent region, spanning from the upper Euphrates to the head of the Gulf of Aqaba, witnessed the earliest transition in the world from hunting and gathering wild foods to farming domesticates. Natufian Epipalaeolithic and Pre-Pottery Neolithic (PPN) communities in this region created distinctive stone tools across the Pleistocene-Holocene transition. Here we present archaeological evidence from the site of Sahout, demonstrating that communities using material culture characteristic of the Natufian and PPN were also present hundreds of kilometres south of the Fertile Crescent, in the much more arid interior of the Arabian Peninsula. Repeated occurrence of distinctive stone tools from 13.5 to 8.7 thousand years ago indicates intimate links to the Levant; showing both the far greater scale of these cultural connections than previously known, and the capacity of Natufian and PPN tool makers to subsist in marginal environments. Obsidian sourcing shows long-distance movement further southward into Arabia. At Sahout, PPN tools are associated with a regional rock art tradition of naturalistic life-sized camel engravings, which overlie representations of curvaceous women. The material culture of these communities suggests that long-term survival in relatively arid environments was based on a combination of local adaptation and a network of long-distance connections.

Reliable ECG classification using parallel hybrid models with limited resources

Single-nucleus RNA sequencing uncovers cell type-specific alterations in OSA-related liver injury

Evaluating resolution requirements for subtle caenorhabditis elegans strain discrimination using classical descriptors and CNN–transformer models

Inspection of pollination transfer and success in coffee flowering detection using intersection over union based cascade RCNN in a vision environment

Quantitative analysis of myeloid cell patterns and immunosuppressive enzyme (IDO, ARG1) expression in colorectal cancer pulmonary metastases and corresponding primary tumours

Scenario analysis of HAZMAT transportation road traffic crashs on China’s highways based on AcciNet-RFs

Assessing InSAR observability of landslides interfering with bridges

Abstract Landslides are among the most widespread natural hazards worldwide and a major cause of disruption to infrastructure networks, with significant impacts on safety and territorial resilience. Understanding the conditions under which they can be effectively monitored is crucial for reducing risk and supporting mitigation strategies. Satellite radar interferometry enables the detection of ground deformation with high precision and wide spatial coverage, but the main challenge lies in identifying when this technology can detect and characterise landslides, as radar visibility is strongly influenced by topography and acquisition geometry. This study addresses this challenge by analysing the interferometric observability of landslides near infrastructure, integrating European Ground Motion Service data with the Italian landslide inventory. This combination enables a systematic quantification of how geomorphological factors and movement characteristics influence the radar detectability of landslides interacting with infrastructure. The analysis shows how topographic settings and movement types control radar visibility, and how InSAR can identify activity states and reveal the internal variability of deformation. The comparison between landslides and interfering bridges highlights differences attributable to local conditions, emphasising the importance of interpreting structural deformation within the geomorphological context. The results provide a quantitative basis to guide monitoring strategies and risk management in complex infrastructural settings.

Undamped climate change poses the need for substantial shifts in cultivated crop types in Germany

Abstract Numerous studies have highlighted the severe implications of climate change for agriculture across the planet, due to shifting climate patterns, heat waves, flood and drought events. Combining state-of-the-art high-resolution observational and model-based climate data with elaborate land use data and the method of climate analogues now allows to foreshadow future agricultural landscapes, anticipating adaptational and transformational needs towards enhanced climate resilience of regional agriculture. The approach is exemplified for a highly diversified farming area in southern Germany. Until the end of the 21st century a clear shift towards typical Mediterranean crops prevails, while many of today’s common crops are expected to become less important. Only higher-elevation parts are projected to face climate analogues in Germany itself, whereas most subregions may exhibit climate conditions that are nowadays found in the northern Mediterranean area. Altogether, undamped climate change will require a radical transformation of the German agricultural sector.

Temporal dynamics of the tomato rhizosphere microbiome in response to synthetic communities of plant growth-promoting rhizobacteria

Abstract The rhizosphere microbiome plays a crucial role in plant health and productivity, yet intensive agriculture has diminished soil microbial diversity, increasing reliance on chemical inputs. Plant growth-promoting rhizobacteria offer a sustainable alternative, enhancing nutrient uptake, stress tolerance, and pathogen resistance. While single-strain inoculants have shown promise, microbial consortia may improve resilience through functional diversity. However, their impact on resident microbial communities remains understudied. In this study, three SynComs (four, six, and ten strains) were assembled from taxonomically diverse native PGPR strains identified as part of the tomato core microbiome, including Bacillus , Pseudomonas, Glutamicibacter, Paenarthrobacter, Chryseobacterium and Leclercia . All consortia significantly enhanced tomato growth, with the six- and ten-strain SynComs (containing Pseudomonas ) exhibiting the most pronounced effects, increasing plant height by up to 94% in the indeterminate-growth variety ‘Proxy’. High-throughput sequencing revealed that while temporal factors were the primary drivers of community assembly, SynCom application triggered dynamic, time-dependent shifts specifically targeting the bacterial “rare biosphere”. Early-stage (T1) responses were characterized by the enrichment of rare bacterial taxa involved in key biogeochemical processes, such as the sulphur ( Sulfurovum, Desulfosporosinus ) and nitrogen ( Azospirillum ) cycles. By four weeks post-inoculation, community responses converged, primarily through the depletion of rare taxa and a predicted functional redirection toward xenobiotic degradation pathways. While SynCom strains showed a decline in absolute abundance over time, the persistence of growth-promoting effects suggests that these consortia act through early-stage indirect microbiome modulation rather than long-term high-density colonization. Furthermore, the consortia exerted a subtle cross-kingdom influence, modulating fungal succession by sustaining Basidiomycota and Mucoromycota populations. These findings demonstrate that small, host-derived, taxonomically diverse SynComs can enhance tomato growth and restructure rhizosphere microbial communities, especially impacting rare bacterial taxa and metabolic potential of the communities, with Pseudomonas -containing consortia exerting the most pronounced effects. These insights support the use of tailored, core-based microbial communities to improve crop productivity and soil health, though further research is needed to optimize SynCom design for agricultural applications.