Search Results (48,629)

Soil bacterial communities are vital for ecosystem functioning in the humid tropics, yet their response to land-use change remains poorly understood. This knowledge gap is exacerbated by the lack of long-term studies. We employed a space-for-time substitution approach to assess the effects of land-use intensification on soil bacterial communities across a gradient of anthropogenic disturbance in Trinidad. Three sub-watersheds (Arouca = pristine, Maracas = intermediate, Tacarigua = intensive) were selected, each containing adjacent forest, grassland, and agricultural land uses. We combined geophysical soil apparent electrical conductivity (ECa-directed) sampling with 16S rDNA gene amplicon sequencing to characterize bacterial communities and their relationships with soil and landscape properties. Soil properties were the primary determinant of bacterial community structure, explaining 56% of the variation (p < 0.001), with pH, clay content, hygroscopic water, and nutrient availability as key drivers. Bacterial α-diversity differed significantly among sub-watersheds (p < 0.01), with Tacarigua exhibiting lower richness and diversity compared to Arouca and Maracas, but not across land uses. While a core microbiome of ten bacterial families was ubiquitous across land uses, indicating a stable foundational community, land-use intensification significantly altered β-diversity (p < 0.01 among sub-watersheds). Agricultural soils showed the greatest divergence from forest soils (p < 0.05), with a marked decline in key Proteobacterial families (e.g., Xanthomonadaceae, Pseudomonadaceae) involved in nutrient cycling and plant growth promotion. Although inherent soil properties shape the core microbiome, land-use intensification acts as a strong secondary filter, shifting soil bacterial communities toward more stress-resistant Firmicutes with potentially less diverse functions. Our findings demonstrate the utility of integrating space-for-time substitution with molecular profiling to predict long-term microbial responses to environmental change in vulnerable tropical ecosystems. Full article

Preeclampsia (PE) and intrauterine growth restriction (IUGR) are major pregnancy complications that are linked to placental dysfunction and environmental stimulation such as the use of electronic cigarettes (eCig). This study investigates the molecular impacts of timed eCig exposure in a C57BL/6 mouse model of PE and IUGR using bulk RNA-sequencing of placental tissues. Pregnant mice were exposed to eCig vapor via nose-only system starting at embryonic day 12.5 (eCig-6d, before spiral artery (SA) invasion) or 14.5 (eCig-4d, after SA invasion) until E18.5 (necropsy), with healthy controls exposed to room air (n = 6/group). The eCig-4d group developed PE, whereas the eCig-6d group developed both PE and IUGR. RNA-seq analysis revealed 429 differentially expressed genes (DEGs) in eCig-4d (IUGR-like) group and 64 DEGs in eCig-6d (PE + IUGR-like) group compared to controls. Pathway and gene network analyses indicated that eCig-4d exposure activated NF-κB–driven inflammation, suppressed ECM organization and collagen biosynthesis, and downregulated vasoactive genes/mitochondrial-associated genes (NOS1/2), accompanied by impaired complement initiation and reduced both macrophage and monocyte signals. Similarly, eCig-6d exposure led to downregulation of complement-associated genes and granule-related components, possibly implicating weakened neutrophil responsiveness and compromised inflammatory resolution at the maternal–fetal interface. Our findings align with prior studies on physiological dysfunctions in PE and IUGR, while also providing novel insights into the temporally specific cellular responses induced by eCig exposure. Full article

In horizontal well technology, hydraulic fracturing has been established as an essential technique for enhancing hydrocarbon production. However, the complex architecture of fracture networks challenges conventional monitoring methods. Micro-seismic monitoring, recognized for its superior resolution and sensitivity, enables precise fracture morphology characterization. This study advances diagnostic capabilities through integrated field–laboratory investigations and multi-domain signal processing. Hydraulic fracturing experiments under varied geological conditions generated critical micro-seismic datasets, with quantitative analyses revealing asymmetric propagation patterns (total length 312 ± 15 m, east wing 117 m/west wing 194 m) forming a 13.37 × 10⁴ m³ stimulated reservoir volume. Spatial event distribution exhibited density disparities correlating with geophone offsets (west wing 3.8 events/m vs. east 1.2 events/m at 420–794 m distances). Advanced time–frequency analyses and inversion algorithms differentiated signal characteristics demonstrating logarithmic SNR (Signal-to-Noise Ratio)–magnitude relationships (SNR 0.49–4.82, R² = 0.87), with near-field events (<500 m) showing 68% reduced magnitude variance compared to far-field counterparts. Coupled numerical simulations confirmed stress field interactions where fracture trajectories deviated 5–15° from principal stress directions due to prior-stage stress shadows. Branch fracture networks identified in Stages 4/7/9/10 with orthogonal/oblique intersections (45–65° dip angles) enhanced stimulation reservoir volume (SRV) by 37–42% versus planar fractures. These geometric parameters—including height (20 ± 3 m), width (44 ± 5 m), spacing, and complexity—were quantitatively linked to micro-seismic response patterns. The developed diagnostic framework provides operational guidelines for optimizing fracture geometry control, demonstrating how heterogeneity-driven signal variations inform stimulation strategy adjustments to improve reservoir recovery and economic returns. Full article

Air–liquid interface (ALI) cultures offer a physiologically relevant in vitro model of the airway epithelium (AE), capable of recapitulating key structural and functional features observed in vivo. In this study, we established and validated a murine ALI culture system comprising pseudostratified epithelia with functional tight junctions, ciliated cells and goblet cells. To assess their innate immune functions, we designed and 3D-printed an autoclavable aerosol deposition chamber, which allowed us to expose differentiated AE cultures to house dust mite (HDM) allergen. Upon HDM exposure, AE cells mounted a time-dependent innate immune response characterized by the secretion of complement component C3, the generation of its active cleavage products C3a and increased expression of C3aR and C5aR1. This was associated with increased intracellular TSLP and IL-25 production and TSLP release in AE cells. Progressive loss of tight junction integrity and reduced transepithelial electrical resistance (TEER) demonstrated epithelial susceptibility to allergen protease-induced cell damage. Together, we established a murine ALI system preserving airway epithelial architecture and a nebulization system to study innate immune activation of AE cells in response to HDM mimicking the initial phase of allergen sensitization. More generally, we described a powerful and accessible platform for studying epithelial-driven mechanisms in murine airway immune responses. Full article

Notonectidae belongs to the infraorder Nepomorpha within the order Hemiptera. The aim of this study was to analyze the morphological types and arrangement of leg sensilla in Anisops, Enithares and Notonecta. A variety of sensilla are distributed on the legs. These sensilla are responsible for receiving signals from the external environment. Mechanoreceptors exhibit the highest diversity. Using a scanning electron microscope, ten types of sensilla were identified on the legs of seventeen species from Notonectidae. Basic types of mechanoreceptors, including sensilla trichodea (ST1, ST2), sensilla chaetica (SCh1, SCh2), sensilla basiconica (SB2) and sensilla campaniformia (SCa), were distributed across all the studied species. In Anisops, sensilla arch-shaped (SAr) and sensilla spoon-shaped (SSp) were reported for the first time. Additionally, six subtypes of ST were distinguished in Anisops, among which ST3, ST4, ST5 and ST6 are unique. In Enithares and Notonecta, sensilla styloconica (SS) were observed; these sensilla are hypothesized to function as both mechanoreceptors and gustatory receptors. Beyond mechanoreceptors, we also identified thermo-hygroreceptors—sensilla ampullacea (SA) and sensilla coeloconica (SCo)—as well as a potential olfactory sensilla type, namely, sensilla placodea multilobated (SPM). These findings suggest that Notonectidae leg sensilla play an important role in the perception of aquatic environments and prey localization. Full article

Single-molecule detection (SMD) has reformed analytical science by enabling the direct observation of individual molecular events, thus overcoming the limitations of ensemble-averaged measurements. This review presents a comprehensive analysis of the principles, devices, and emerging materials that have shaped the current landscape of SMD. We explore a wide range of sensing mechanisms, including surface plasmon resonance, mechanochemical transduction, transistor-based sensing, optical microfiber platforms, fluorescence-based techniques, Raman scattering, and recognition tunneling, which offer distinct advantages in terms of label-free operation, ultrasensitivity, and real-time responsiveness. Each technique is critically examined through representative case studies, revealing how innovations in device architecture and signal amplification strategies have collectively pushed the detection limits into the femtomolar to attomolar range. Beyond the sensing principles, this review highlights the transformative role of advanced nanomaterials such as graphene, carbon nanotubes, quantum dots, MnO₂ nanosheets, upconversion nanocrystals, and magnetic nanoparticles. These materials enable new transduction pathways and augment the signal strength, specificity, and integration into compact and wearable biosensing platforms. We also detail the multifaceted applications of SMD across biomedical diagnostics, environmental monitoring, food safety, neuroscience, materials science, and quantum technologies, underscoring its relevance to global health, safety, and sustainability. Despite significant progress, the field faces several critical challenges, including signal reproducibility, biocompatibility, fabrication scalability, and data interpretation complexity. To address these barriers, we propose future research directions involving multimodal transduction, AI-assisted signal analytics, surface passivation techniques, and modular system design for field-deployable diagnostics. By providing a cross-disciplinary synthesis of device physics, materials science, and real-world applications, this review offers a comprehensive roadmap for the next generation of SMD technologies, poised to impact both fundamental research and translational healthcare. Full article

In recent years, the increasing frequency of global seismic events has imposed severe impacts on human society. Timely and accurate assessment of post-earthquake damage and recovery is essential for developing effective emergency response strategies and enhancing urban resilience. This study investigates 11 provinces in Turkey affected by the February 2023 Turkey–Syria earthquake, conducting a multidimensional evaluation of disaster loss and recovery. For loss assessment, existing studies typically focus on changes in the total value of nighttime lights at the regional level, overlooking variations at the pixel scale. In this study, we introduce a pixel-level NTL loss metric, which provides finer-grained insights and helps interpret outcomes driven by spatial heterogeneity. For recovery assessment, we propose a Composite Nighttime Light Index (CNLI) that integrates multiple recovery-phase indicators into a single quantitative measure, thus capturing more information than a one-dimensional metric. To account for complex interrelationships among indicators, a Bayesian network is employed, which moves beyond the conventional independence assumption. Moreover, an information gain (IG) approach is applied to optimize indicator weights, minimizing subjectivity and avoiding abnormal weight distributions compared with traditional methods, thereby ensuring a more objective construction of the Resilience Index (RI). Results show that Sanliurfa, Kilis, and Hatay suffered the most severe damage; Kahramanmaras and Malatya exhibited the lowest CNLI values, while Hatay, Kilis, and Gaziantep showed higher CNLI values. In contrast, Gaziantep and Adana obtained the highest RI values. Since CNLI reflects actual recovery performance while RI characterizes inherent resilience, accordingly, effectively linking CNLI and RI establishes a dual-perspective and novel framework, the 11 provinces are classified into four categories, and differentiated recovery strategies are suggested. This study contributes a refined quantitative framework for post-earthquake loss and recovery assessment and provides scientific evidence to support emergency response and targeted reconstruction. Full article

To address the issues of high stalk breakage rate and the mismatch between extraction force and operational speed in current horizontal shaft counter-rolling cotton stalk pullers, this study presents a novel clamping mechanism. The mechanism enables precise adjustment of the rollers’ rotational speed, inter-roller gap, and surface topography. The objective is to systematically investigate the effects of these key parameters on the peak extraction force and its timing during the stalk pulling process. Initially, pre-compressed cotton stalks were employed as test specimens. Their tensile properties post-compression were investigated by simulating the extraction forces using a universal testing machine. Subsequently, the structural design of the critical components for the test rig was created based on these experimental findings. Theoretical analysis identified the surface texture of the clamping rollers, their rotational speed, and the clamping gap as the primary experimental factors. The effects of these factors on the peak extraction force and its timing were analyzed using Response Surface Methodology (RSM). The results indicated that the optimal combination—striped surface texture for both rollers, a speed of 220 rpm, and a zero gap—yielded a time to peak force of 0.05 s and a peak force of 710.77 N, which is significantly below the measured tensile strength limit of 994.60 N for compressed stalks. This indicates that the designed clamping device for the horizontal shaft counter-rolling cotton stalk extraction machine achieves faster extraction speed while ensuring stalk integrity, and the research results can provide theoretical foundation and design guidance for the development of horizontal shaft counter-rolling cotton stalk extraction machinery. Full article

In large-scale radiological events, there is a need to triage affected individuals based on their biological absorbed dose. Biodosimetry measures biological responses in relation to the received dose. Radiation-responsive protein biomarkers in peripheral blood lymphocytes, especially intracellular proteins, have been validated for biodosimetry with immunochemical-based measurement methods. However, these antibody-based assays can suffer from stability and batch-to-batch variations. Aptamers are single-stranded oligonucleotide alternatives to antibodies that are stable and much smaller in size, making them ideal probes for intracellular targets. However, few aptamers have been developed against intracellular targets, and these efforts are especially hampered due to the time-consuming nature of the conventional aptamer selection method. An efficient method for isolating aptamers against intracellular radiation-responsive proteins is not available yet. Herein, we used a microfluidic aptamer isolation method to develop an aptamer against the intracellular radiation biomarker BAX in blood lymphocytes. The isolated aptamer has a dissociation constant of 6.95 nM against human BAX protein and a bright detail similarity score of 1.9 when colocalizing with anti-BAX aptamer intracellularly. The in situ labeling of the intracellular BAX protein also shows the aptamer can be used to differentiate 2.5 Gy or 3 Gy of radiation in ex vivo human and in vivo mouse peripheral blood samples exposed to X-rays. In conclusion, this proof-of-concept study indicates that the microfluidic-enabled aptamer isolation method could be used for the development of a panel of targeted intracellular proteins for radiation biodosimetry applications. Full article

As climate policy and energy costs increasingly influence housing markets, understanding how energy efficiency is capitalized into home prices has become a critical question for both researchers and policymakers. While prior studies confirm the existence of a green premium—the price advantage of more energy-efficient homes—less is known about how this premium evolves over time in response to shifting regulations, awareness, and market conditions. This study provides new empirical evidence on the dynamic valuation of energy efficiency in the London housing market between 2013 and 2021. Using a repeat-sales framework, we isolate within-property price changes and examine how energy performance is capitalized over time. We find that the green premium associated with higher current energy efficiency strengthened steadily, rising from statistically insignificant levels in 2013 to approximately 0.47% per Energy Performance Certificate (EPC) point by 2021. Meanwhile, the price penalty for a large efficiency gap, reflecting unrealized upgrade potential, narrowed substantially in 2020 and 2021, indicating a marked reduction in buyers’ aversion to less efficient homes. This study adds a new dimension to the green premium literature. It provides empirical evidence that the relationship between energy efficiency and housing value is not static, but responsive to regulatory, economic, and social changes. By tracking year-by-year changes in London, our analysis offers insight into how quickly market preferences adjust and how interventions like minimum efficiency standards translate into property values. This enriched understanding moves the field beyond the question of whether a green premium exists, to how and why it evolves. Full article

Accidental opioid overdose and Sudden Unexpected Death in Epilepsy (SUDEP) represent major forms of preventable mortality, often involving sudden-onset catastrophic events that could be survivable with rapid detection and intervention. The current physiological monitoring technologies are potentially applicable, but face challenges, including complex setups, poor patient compliance, high costs, and uncertainty about community-based use. Paradoxically, simple clinical observation in supervised injection facilities has proven highly effective, suggesting observable changes in central body motion may be sufficient to detect life-threatening events. We describe a novel wearable biosensor for continuous central body motion monitoring, offering a potential early warning system for life-threatening events. The biosensor incorporates a low-power, triaxial MEMS accelerometer within a discreet, chest-worn device, enabling long-term monitoring with minimal user burden. Two system architectures are described: stored data for retrospective analysis/research, and an in-development system for real-time overdose detection and response. Early user research highlights the importance of accuracy, discretion, and trust for adoption among people who use opioids. The initial clinical data collection, including the OD-SEEN study, demonstrates feasibility for capturing motion data during real-world opioid use. This technology represents a promising advancement in non-invasive monitoring, with potential to improve the outcomes for at-risk populations with multiple health conditions. Full article

Low Earth orbit (LEO) satellites, characterized by low altitudes, high velocities, and strong ground signal reception, have become an essential and dynamic component of modern global navigation satellite systems (GNSS). However, orbit decay induced by atmospheric drag poses persistent challenges to maintaining stable trajectories. Frequent orbit maneuvers, though necessary to sustain nominal orbits, introduce significant difficulties for precise orbit determination (POD) and navigation augmentation, especially under complex operational conditions. Unlike most existing methods that rely on Two-Line Element (TLE) data—often affected by noise and limited accuracy—this study directly utilizes onboard GNSS observations in combination with real-time precise ephemerides. A novel time-series indicator is proposed, defined as the geometric root-mean-square (RMS) distance between reduced-dynamic and kinematic orbit solutions, which is highly responsive to orbit disturbances. To further enhance robustness, a sliding window-based adaptive thresholding mechanism is developed to dynamically adjust detection thresholds, maintaining sensitivity to maneuvers while suppressing false alarms. The proposed method was validated using eight representative maneuver events from the GRACE-FO satellites (May 2018–June 2022), successfully detecting seven of them. One extremely short-duration maneuver was missed due to the limited number of usable GNSS observations after quality-control filtering. To examine altitude-related applicability, two Sentinel-3A maneuvers were also analyzed, both successfully detected, confirming the method’s effectiveness at higher LEO altitudes. Since the thrust magnitudes and durations of the Sentinel-3A maneuvers are not publicly available, these cases primarily serve to verify applicability rather than to quantify sensitivity. Experimental results show that for GRACE-FO maneuvers, the proposed method achieves near-real-time responsiveness under long-duration, high-thrust conditions, with an average detection delay below 90 s. For Sentinel-3A, detections occurred approximately 7 s earlier than the reported maneuver epochs, a discrepancy attributed to the 30 s observation sampling interval rather than methodological bias. Comparative analysis with representative existing methods, presented in the discussion section, further demonstrates the advantages of the proposed approach in terms of sensitivity, timeliness, and adaptability. Overall, this study presents a practical, efficient, and scalable solution for real-time maneuver detection in LEO satellite missions, contributing to improved GNSS augmentation, space situational awareness, and autonomous orbit control. Full article

The large-scale integration of coordinated offshore wind and offshore photovoltaic (PV) generation introduces pronounced power fluctuations due to the intrinsic randomness and intermittency of renewable energy sources (RESs). These fluctuations pose significant challenges to the secure, stable, and economical operation of modern power systems. To address this issue, this study proposes a hybrid energy storage system (HESS)-based optimization framework that simultaneously enhances fluctuation suppression performance, optimizes storage capacity allocation, and improves life-cycle economic efficiency. First, a K-means fuzzy clustering algorithm is employed to analyze historical RES power data, extracting representative daily fluctuation profiles to serve as accurate inputs for optimization. Second, the time-varying filter empirical mode decomposition (TVF-EMD) technique is applied to adaptively decompose the net power fluctuations. High-frequency components are allocated to a flywheel energy storage system (FESS), valued for its high power density, rapid response, and long cycle life, while low-frequency components are assigned to a battery energy storage system (BESS), characterized by high energy density and cost-effectiveness. This decomposition–allocation strategy fully exploits the complementary characteristics of different storage technologies. Simulation results for an integrated offshore wind–PV generation scenario demonstrate that the proposed method significantly reduces the fluctuation rate of RES power output while maintaining favorable economic performance. The approach achieves unified optimization of HESS sizing, fluctuation mitigation, and life-cycle cost, offering a viable reference for the planning and operation of large-scale offshore hybrid renewable plants. Full article

In the current economic context, organizations providing automotive repair services face significant challenges in ensuring service quality, operational efficiency, and long-term sustainability. This paper examines the importance of implementing process monitoring systems through the integration of European quality frameworks and Japanese operational principles such as Kaizen, Lean Manufacturing, and Poka-Yoke, to improve the quality of services and increase performance within automotive repair organizations. The research is grounded in Sustainable Development Goals (SDG 9—Industry, Innovation and Infrastructure, and SDG 12—Responsible Consumption and Production), demonstrating how structured quality practices contribute to reducing waste, optimizing processes, and delivering responsible services. The main objectives of the study are to identify the elements that influence the performance of service-specific processes, to improve the quality management practices related to these processes, to eliminate non-conformities, and to enhance profitability and competitive differentiation through service quality assurance. A mixed-methods research design was applied, including direct participatory observation, performance monitoring, and correlational statistical analysis over a six-month period in two Romanian automotive service centers. Key performance indicators (KPIs) such as technician efficiency, rework rate, and order throughput time were collected and analyzed before and after the implementation of selected tools. Findings demonstrate measurable improvements: rework rates decreased from 7.8% to 2.6%, technician efficiency improved from 89% to 105%, and average service completion time was reduced by 1.6 days. Correlation analysis confirmed strong relationships between visual management adoption and rework reduction (r = −0.75), as well as between Lean implementation and technician efficiency (r = +0.89). The study’s novelty lies in its integration of cross-cultural quality management practices into a replicable and sustainable operational model for post-sale service environments. The results validate that implementing monitoring systems, combined with Kaizen, Lean, and Poka-Yoke, supported by visual management and active employee engagement, can lead to superior service quality management, increased customer satisfaction, and long-term organizational success in the automotive repair industry. Full article

Early warning of structural damage from induced seismic events requires rapid and reliable ground motion forecasting. This study presents a novel real-time framework that couples a deep learning approach with structural fragility assessment to generate immediate damage alerts following the onset of seismic shaking. Long Short-Term Memory (LSTM) neural networks are employed to predict full S-wave accelerograms from initial P-wave inputs, trained and tested on accelerometric records from induced seismicity scenarios. The predicted S-wave motion is then used as input for a suite of fragility curves in real time to estimate the probability of structural damage for masonry buildings typical in rural areas of geothermal platforms. The proposed method captures both the temporal evolution of shaking and the structural response potential, offering critical seconds of lead time for automated decision-making systems. Results demonstrate high predictive accuracy of the LSTM model and effective early classification of structural risk. This integrated system provides a practical tool for early warning or rapid response in regions experiencing anthropogenic seismicity, such as those affected by geothermal operations. Full article