Search Results (11,454)

Geospatial artificial intelligence (GeoAI) offers opportunities to translate heterogeneous agricultural observations into site-specific management decisions. This systematic review synthesizes literature published in 2019–2026, identified through Scopus, Web of Science, and supplementary searches, to examine applications, multimodal data integration, and decision support in precision agriculture. The narrative synthesis indicates a shift from isolated mapping and prediction toward integrated workflows combining satellite and UAV imagery, field sensors, weather, soil, and management records. Reported benefits include improved yield prediction, earlier stress and disease detection, more detailed soil mapping, and more targeted irrigation and input use. However, farming yield, environmental, and economic gains remain dependent on local conditions and operational validation. A central finding is that georeferenced data alone do not ensure genuinely geospatial AI: reliable workflows must address spatial dependence, scale mismatch, transferability, and uncertainty. Interpretability and integration into farm operations are equally important for actionable recommendations. Adoption remains constrained by data interoperability, connectivity, affordability, privacy, and technical capacity. Heterogeneous evidence and single-reviewer assessment limit interpretation. Future progress requires spatially informed, field-validated models, accessible decision support tools, and participatory governance to support sustainable and inclusive agricultural management. Full article

Targeted down-modulation of monocytes and macrophages is a promising strategy for controlling excessive inflammatory processes. Bacterial protein toxins are attractive pharmacological modulation tools for this purpose because of their potency and specificity. Here, we combined the specific properties of the two protein toxins C3lim from Clostridium limosum and CyaA from Bordetella pertussis in the preferentially monocyte/macrophage-targeting bioconjugate C2IN-C3lim_E174Q-Cys_His-AC. The enzymatically inactive and monocytic cell-targeting transporter C2IN-C3lim_E174Q-Cys was recombinantly produced and chemically coupled to the isolated adenylate cyclase (AC) domain of CyaA, which mediates down-modulation of monocytic cell functions through intracellular cAMP accumulation Within 1 h, the bioconjugate showed preferential cell association with monocytic cells relative to HeLa cells, which served as the non-target cell model, without impairing overall cellular viability. Intracellular enzymatic activity was successfully confirmed by significantly elevated cAMP levels in all target cell types. Moreover, in migration assays with primary human monocytes, the bioconjugate markedly reduced both general motility and targeted chemotaxis, demonstrating that the delivery of the enzyme moiety translates into a measurable functional response. Therefore, we conclude that the novel bioconjugate C2IN-C3lim_E174Q-Cys_His-AC enables preferential targeting of monocytes and macrophages under the experimental conditions investigated here and provides proof-of-concept for a targeted protein delivery platform for functional modulation of monocytic cells. Full article

Radio-frequency (RF) fingerprint distributions vary across collection dates, and changes in propagation conditions and hardware states can degrade transmitter-identification performance. To address this issue, we propose Source-Free Class-Balanced Pseudo-Label Adaptation (SF-CBPA) for cross-day WiFi transmitter identification. SF-CBPA requires only an unlabeled target-day dataset and a pretrained source model. It recalibrates batch-normalization statistics, freezes the source classifier, and uses Sinkhorn-balanced pseudo-labeling with within-class confidence selection; an exponential-moving-average teacher and information maximization provide auxiliary stabilization. Experiments were carried out using the public WiSig-ManyTx subset with 140 transmitters and one fixed receiver. The first three collection days trained the source model, while Day 4 provided 25 unlabeled adaptation samples and 25 independent test samples per class. Across three random seeds, SF-CBPA achieved 63.80 ± 0.90% accuracy and 0.6330 ± 0.0121 Macro-F1. A protocol-aligned SHOT implementation achieved 61.72 ± 1.95% accuracy and 0.5963 ± 0.0285 Macro-F1, while source-only and TENT-style achieved 57.93 ± 0.58% and 58.58 ± 0.43% accuracy, respectively. Direct analysis shows that Sinkhorn reduced the hard pseudo-label count range from 1–54 to 13–35 and the class-count standard deviation from 11.75 to 3.42. Component-isolated ablation identifies Sinkhorn balancing as the principal contributor under seed 123; the independent benefits of EMA and the auxiliary information-maximization term are small or inconsistent. These conclusions are restricted to the balanced, closed-set, fixed-receiver protocol evaluated here. Full article

Statistical monitoring of lifetime processes is commonly based on a single process characteristic, which may fail to detect distributional changes that affect different aspects of process behavior. This study proposes a component-wise adaptive joint exponentially weighted moving average (EWMA) control chart for simultaneously monitoring a Weibull lower quantile and Shannon entropy. Unlike conventional joint monitoring schemes that apply a common smoothing mechanism, the proposed framework preserves the quantile and entropy as separate standardized components, adaptively updates each according to its own departure, and subsequently combines them through a correlation-adjusted quadratic statistic that retains their dependence. Control limits are calibrated by Monte Carlo simulation to achieve a target in-control average run length of approximately 370. Extensive simulations consider scale, shape, and combined Weibull parameter shifts, together with quantile-preserving and entropy-preserving alternatives specifically designed to isolate changes in the individual characteristics. Comparisons with single-component Q-EWMA and H-EWMA charts and a fixed joint EWMA chart demonstrate that the proposed procedure maintains the desired in-control performance while providing robust and balanced detection across heterogeneous process changes. Its advantage is particularly evident when one monitored characteristic remains relatively stable while the other changes substantially, a setting in which single-characteristic charts may become insensitive. Practical applicability is demonstrated through two complementary real-data applications involving medical rehabilitation length-of-stay data and rolling-contact fatigue-life data under different lubrication conditions. In both settings, the proposed chart successfully identifies meaningful distributional departures, while the component-wise adaptive mechanism responds selectively to the relative magnitudes of quantile and entropy changes. Overall, the proposed framework provides a robust and flexible monitoring strategy for heterogeneous lifetime-process changes without requiring prior knowledge of whether deterioration will primarily affect lower-tail performance, distributional uncertainty, or both. Full article

The transition towards low-carbon energy systems is fundamentally reshaping the relationships between energy security, affordability, and environmental sustainability. Although the energy trilemma has become a widely adopted framework for analysing these objectives, existing studies often examine individual dimensions or bilateral trade-offs in isolation, providing limited understanding of how interactions evolve throughout the transition process. This review synthesises recent evidence on the energy trilemma in the context of the low-carbon transition and develops a dynamic, context-sensitive interpretation of interactions between its three dimensions. A structured integrative literature review with thematic synthesis was conducted using systematic searches of the Scopus and Web of Science databases, followed by multi-stage screening and qualitative synthesis. Rather than evaluating individual studies separately, the review integrates evidence across complementary research streams to identify recurring interaction patterns, trade-offs, synergies, and the conditions under which they emerge. The findings demonstrate that interactions within the energy trilemma are neither static nor universally characterised by unavoidable trade-offs. Energy security increasingly depends on electricity system resilience, critical mineral supply chains, and institutional capacity rather than fossil fuel availability alone. Affordability is shaped primarily by distributional processes, adaptive capacity, and equitable access to low-carbon transition opportunities rather than average energy prices. Security–affordability interactions evolve across different risk regimes, highlighting the economic value of resilience under geopolitical uncertainty and market disruption. Across all three dimensions, technological innovation, infrastructure development, governance quality, temporal dynamics, and socio-economic context determine whether policy interventions generate trade-offs or mutually reinforcing outcomes. Building on these findings, the review reconceptualises the energy trilemma as a dynamic and context-sensitive analytical framework rather than a static balancing exercise. The proposed framework integrates technological, institutional, temporal, distributional, and geopolitical perspectives to explain how interactions among energy security, affordability, and environmental sustainability evolve under different transition conditions. Full article

With the rapid electrification of transportation, electric vehicles (EVs) have become an increasingly important component of sustainable mobility, making the efficient operation and management of charging infrastructure increasingly critical. Accurately forecasting future charging service states is therefore essential for charging resource scheduling, energy management, and intelligent EV charging operations. However, existing EV charging forecasting studies mainly focus on predicting isolated indicators. Such formulations overlook the inherently multi-dimensional nature of charging services, where different indicators describe complementary aspects of future operational conditions. As a result, single-indicator forecasting provides only a partial characterization of charging states and limits its effectiveness for downstream tasks such as risk awareness and intelligent charging management. To address this limitation, this paper reformulates EV charging forecasting as a service-state forecasting problem and proposes EleState, a framework designed to learn and forecast multi-dimensional charging service states. EleState constructs comprehensive service-state representations by jointly modeling temporal evolution, inter-state dependency, and spatial interaction among charging stations. Based on the learned representations, EleState forecasts three key service-state dimensions, including occupancy, charging duration, and charging volume, enabling a more complete characterization of future charging conditions. Extensive experiments on the UrbanEV dataset demonstrate that EleState achieves the best target-wise MAE and RMSE across all three service-state dimensions, reducing target-wise MAE by 1.4–2.4% and RMSE by 1.2–3.2% compared with the strongest baseline. Furthermore, EleState provides stronger operational risk awareness than conventional load-oriented forecasting and maintains robust performance across different forecasting horizons. Overall, this work extends EV charging forecasting beyond conventional single-indicator prediction toward comprehensive service-state forecasting, providing a more effective foundation for intelligent EV charging management. Full article

This study investigated the prevalence and genomic characteristics of Bacillus cereus group organisms in animal-origin foods sold in Guangzhou, China. A total of 505 retail samples, including 117 milk samples and 388 commercially available smoked sausage products, were collected from supermarkets and farmers’ markets. The isolation rates of B. cereus group organisms were 8.5% in milk and 44.9% in smoked sausages. Whole-genome sequencing of 169 isolates showed that antimicrobial-resistance genes, including bacII, fosB and vanZF, and diarrheal virulence-associated genes, including nheA, nheB and nheC, were widely distributed among the isolates. Most representative isolates showed biofilm-forming ability, and three antimicrobial-resistant isolates carrying multiple virulence-associated genes showed pathogenic potential in mice under high-dose experimental administration. These findings indicate that retail smoked sausage products can serve as a reservoir of B. cereus group organisms with antimicrobial-resistance, virulence-associated and biofilm-forming traits. However, the detection of resistance- or virulence-associated genes does not necessarily prove gene expression, toxin production, phenotypic resistance or consumer exposure risk. This study did not directly evaluate growth of B. cereus in sausage matrices during storage. Therefore, the present results indicate a potential microbiological hazard rather than a quantified consumer risk. Product-specific challenge studies under defined storage conditions are required to determine whether B. cereus can proliferate in particular sausage products and reach hazardous levels at consumption. Full article

Autism spectrum disorder (ASD) is a heterogeneous neurodevelopmental condition with wide differences in cognitive, behavioral, and adaptive outcomes across the lifespan. Current evidence suggests that part of this heterogeneity may be related to interactions among genetic susceptibility, environmental exposures, and immune processes acting during important periods of brain development. This narrative review examines the molecular and cellular mechanisms through which immune dysregulation and autoimmunity may contribute to neurodevelopmental variability in ASD. It also explores possible links with age-related neuropsychological trajectories. Main topics include maternal immune activation, maternal brain-reactive autoantibodies, cytokine signaling, peripheral immune cell changes, microglial and astrocytic function, complement-mediated synaptic remodeling, and gut–immune–brain pathways. These mechanisms are discussed in relation to language, attention, executive functions, sensory processing, social cognition, emotional regulation, adaptive functioning, and psychiatric comorbidity from childhood to adulthood. Current evidence supports immune dysfunction as a possible modifier of ASD phenotypes rather than a universal or isolated cause. Direct longitudinal evidence linking specific immune profiles to defined neuropsychological trajectories is still limited, especially in adults. Integrating molecular, immunological, and neuropsychological data may help identify biologically meaningful ASD subgroups and support future biomarker development, developmental stratification, and more personalized therapeutic approaches. Full article

Vehicle-damage assessment in intelligent transportation maintenance often requires one decision from several views of the same vehicle. We developed a paired, auditable protocol for comparing two complete vision–language model configurations at the vehicle level. The protocol uses source_vehicle_id as the sampling unit; isolates Gold and adjudication records during inference; retains structured, non-binary outputs; and combines classification, coverage–risk, paired-bootstrap, and processing-time analyses. The frozen dataset contained 160 vehicles and 355 deduplicated media items, with 119 State 0, 41 State 1, and no State 9 cases. Thus, the primary analysis could not estimate performance for insufficient-reference-evidence cases. Under the frozen configuration-specific inputs; instructions; and preprocessing, software, and output constraints, Models A and B achieved Macro-F1 scores of 0.8645 and 0.1923. The paired difference was 0.6722, with a 95% bootstrap confidence interval of [0.5878, 0.7475] from 10,000 vehicle-level resamples. Binary coverage was 0.9438 for Model A and 0.3938 for Model B, and selective risk was 0.0464 and 0.4444, respectively. End-to-end single-arm processing took 157.75 s for Model A and 654.09 s for Model B under the recorded execution conditions. These findings compare the two complete configurations and do not isolate an architectural effect. Energy use, carbon emissions, repair-material savings, and life-cycle outcomes were not measured. The protocol provides a basis for future matched-task studies of human-in-the-loop maintenance workflows. Full article

As oil and gas exploration and development in the East China Sea advance toward deeper and hotter formations, direct contact between oil-based drilling fluid and water-based completion fluid can cause severe rheological incompatibility during open-hole completion. This study developed an amphiphilic SF-4 spacer based on AM/AMPS/ODAAC copolymerization and evaluated its structure, interfacial behavior, wettability alteration, rheology, thermal stability, and field performance. Characterization of the synthesized copolymer gave a weight-average molecular weight of 1.28 ± 0.06 × 10⁶ g/mol, a monomer conversion of 96.8 ± 0.7%, and total residual monomer content of 0.071 ± 0.008 wt%. Under the test oil/brine conditions, SF-4 reduced interfacial tension from 34.8 ± 1.6 to 3.2 ± 0.2 mN/m at 25 °C and from 31.4 ± 1.4 to 3.7 ± 0.3 mN/m at 150 °C, corresponding to reductions of 90.8% and 88.2%. The sandstone water-contact angle decreased from 132.4 ± 3.8° to 48.7 ± 2.9°, while oil-film surface coverage decreased from 92.1 ± 2.7% to 18.4 ± 3.0% after treatment. Compatibility tests showed that SF-4-containing mixed fluids remained free of harmful thickening after 16 h at 130–170 °C and after 10 d at 150 °C. In the field trial, 7 m³ of SF-4 was placed at 2000 L/min and approximately 1350 psi; the well achieved complete liquid recovery within 4.2 h and subsequently reached a maximum gas rate of 4.8 × 10⁵ m³/d. These results support SF-4 as a high-temperature spacer for isolating incompatible oil- and water-based working fluids during open-hole completion. Full article

Compression packers are widely used in oil and gas well operations for zonal isolation, yet the large-deformation mechanical behavior of their rubber sealing elements lacks a closed-form analytical solution. This paper presents a complete theoretical analysis of the axisymmetric compression of an annular rubber cylinder based on the incompressible Mooney–Rivlin hyper-elastic model. The deformation process is divided into three successive stages: free expansion, casing-constrained deformation, and fully constrained deformation. Analytical expressions for the principal stretches, stress fields, and axial force are derived for each stage by integrating the radial equilibrium equation with proper treatment of the Lagrange multiplier. The frictionless analytical results are validated against axisymmetric finite element simulations, showing excellent agreement for all stress components. The applicability of the frictionless theory to frictional conditions is then examined. Results show that although friction introduces non-uniform axial deformation and end bulging, the average contact pressure on the rubber–mandrel interface agrees closely with the theoretical prediction, especially at higher axial forces (150–250 kN). A linear relationship between the average contact pressure and the axial force is confirmed, providing a simple design tool. The theoretical solution offers a computationally efficient alternative to finite element analysis for preliminary packer design and parametric studies. Full article

Porcine endometritis, primarily resulting from mixed bacterial infections, adversely impacts sow reproductive performance and leads to substantial economic losses in the pig farming sector. Traditional antibiotic treatment is limited due to bacterial resistance and drug residue issues. Curcumin (Cur) possesses inherent antibacterial and anti-inflammatory properties; however, its use is restricted due to limited water solubility and low bioavailability. In this work, dominant pathogens were isolated and identified from vaginal swabs collected from 48 sows with clinical endometritis via 16S rRNA sequencing, followed by antibiotic susceptibility assessment. Cur-loaded ZIF-8 nanoparticles (Cur@ZIF-8) were synthesized for non-antibiotic therapeutic exploration against porcine endometritis. Physicochemical characterizations revealed that Cur@ZIF-8 possessed a hydrodynamic particle size of 106.2 nm, a curcumin loading efficiency of 10.8%, and an encapsulation efficiency of 86.4%. The nanoparticles exhibited uniform morphology, favorable dispersibility, and showed a moderate increase in curcumin release under acidic conditions. Hemolysis assays and mouse toxicity tests confirmed the favorable biocompatibility of Cur@ZIF-8 without obvious toxic effects. In vitro antibacterial evaluations demonstrated that Cur@ZIF-8 exerted potent bactericidal effects, with the minimum inhibitory concentration (MIC) against Proteus mirabilis determined to be 12.5 μg/mL. Consistent with clinical findings, Proteus mirabilis, Staphylococcus aureus, and Escherichia coli were confirmed as the major causative agents of porcine endometritis, which frequently occurred as mixed infections, and these clinical isolates exhibited prominent multi-drug resistance to common antibiotics. Using the isolated dominant clinical strains, we established mouse endometritis models and performed in vivo therapeutic evaluations via uterine bacterial load enumeration, histopathological observation, and immunofluorescence detection of macrophage polarization. The results demonstrated that Cur@ZIF-8 markedly mitigated uterine pathological injury, reduced intrauterine bacterial burden, and alleviated inflammatory infiltration. A decreased semi-quantitative histopathological inflammation score was observed in uterine tissues after Cur@ZIF-8 intervention. Mechanistically, Cur@ZIF-8 remodels the uterine inflammatory microenvironment through the modulation of macrophage polarization, achieving combined antibacterial and anti-inflammatory functions. Collectively, in vivo experiments in mouse endometritis models verified that the Cur@ZIF-8 nanoplatform produces antibacterial and anti-inflammatory effects and exhibits excellent biosafety and biocompatibility. This preclinical study offers a promising non-antibiotic nanotherapeutic candidate and provides an alternative strategy to reduce antibiotic consumption and combat antimicrobial resistance in livestock production; nevertheless, further systematic validation in sow models is still needed to support its practical clinical application for porcine endometritis control. Full article

β-4′-Hydroxymethyl-deleted nucleosides are a class of four-carbon-sugar isonucleosides that possess significant research value in medicinal chemistry and artificial genetic polymer science. Nevertheless, current synthetic methodologies are hampered by several drawbacks, including poor diastereoselectivity, considerable side-product formation, and lengthy synthetic sequences. Herein, we report a cooperative catalytic strategy combining chiral phosphoric acid (CPA) and the achiral sulfur-containing Lewis base triphenylphosphine sulfide (Ph₃PS) for the stereoselective synthesis of β-4′-hydroxymethyl-deleted nucleosides via asymmetric alkene iodocyclization. Acting as a Brønsted acid, CPA anchors the hydroxyl nucleophilic site of the substrate through hydrogen-bonding interactions, whereas Ph₃PS activates the iodine source. The two catalysts work in concert to modulate the spatial conformation of iodonium intermediates, enabling the hydroxyl nucleophile to attack the iodonium carbon from the α-face of the substrate and thus construct the β-N-glycosidic bond with high stereoselectivity. This iodocyclization reaction delivers a diastereomeric ratio up to 98:2 and an isolated yield of 95%, and it can be readily scaled up to gram-scale preparation. Featuring mild reaction conditions and efficient practicality, the present synthetic strategy provides a concise and efficient asymmetric route toward 4′-hydroxymethyl-deleted isonucleosides. Full article

This study examines a sand bubbling fluidized bed containing cylindrical biomass pellets. It demonstrates the advantages of integrating fiber-optic measurements—such as those obtained with CREC-GS-Optiprobes—with CPFD Barracuda VR^® 25.0.1 computational modeling. Experimental data collected by using CREC fiber-optic probes in a 43.8 cm diameter, laboratory-scale cold gasifier unit are used to validate the radial phase distributions predicted by CPFD Barracuda VR^® simulations for the gas, emulsion, and biomass pellet phases. In addition, it is shown that the bubble rise velocity measurements provided by the CREC probes offer complementary insights into the limitations of CPFD Barracuda VR^® simulations. These measurements highlight the importance of bubble–bubble interactions, including the “push” exerted by neighboring bubbles on a target bubble. Based on this approach, a combined experimental–computational methodology is proposed, leading to the development of a bubble rise velocity equation. This equation is expressed as a function of the isolated bubble’s axial chord and as a function of the superficial gas velocity in excess present at minimum fluidization conditions. It is anticipated that this equation will be beneficial for the design and optimization of sand fluidized bed gasifiers operating with biomass pellets, particularly by improving the prediction and capture of bubble dynamics. Full article

Background/Objectives: Mesenchymal stromal cells (MSCs) isolated from neonatal sources have been proposed in clinical cell therapy to enhance hematopoietic stem cell transplantation due to their hematopoietic support capacity. Here we evaluated this capacity, particularly the lymphopoietic potential that remains poorly understood. Methods: In this in vitro study, MSCs obtained from bone marrow (BM), and neonatal sources such as placenta (PL), umbilical cord blood (UCB), and Wharton’s jelly (WJ) were cultured under the same conditions to compare their abilities to support the formation of myeloid (dendritic cell-like/non-classical monocyte-like) and lymphoid (NK and B cells) lineages from hematopoietic progenitor cells (HPCs). MSCs were co-cultured with CD34⁺CD38⁻ Lin⁻ HPCs in the presence or absence of exogenous cytokines; cell lineages obtained were evaluated through flow cytometry. Results: Our results demonstrate that similarly to BM-MSCs, MSCs from neonatal sources have potential to support the formation of dendritic cells, non-classical monocytes, NK, and B cells. However, in contrast to BM-MSCs, neonatal sources favor the generation of lymphoid populations of advanced stages of differentiation. Conclusions: These results indicate that MSCs from neonatal sources have increased lymphopoietic potential compared to BM-MSCs, a finding with significant implications for the selection of MSC sources in clinical trial design. Full article