Search Results (7,339)

Digital rock technology is essential for characterizing the petrophysical properties of tight reservoirs. However, conventional construction methods often yield models with insufficient pore connectivity due to low porosity and complex nanopore structures. To address this limitation, we propose a novel connectivity algorithm for isolated pore systems. First, a digital rock model is constructed using a random particle packing algorithm that integrates high-resolution SEM parameters, including kaolinite particle morphologies and randomly distributed microfractures. Subsequently, the connectivity algorithm sequentially links isolated pore clusters to the largest continuous pore system, forming an interconnected channel. Pore network extraction reveals that the algorithm produces significantly denser and more continuous structures, with pore–throat size distributions aligning well with experimental observations. Single-phase flow simulations demonstrate that the enhanced model yields porosity and permeability values consistent with laboratory measurements, whereas unenhanced models deviate substantially. To further advance microscale flow characterization, we derive explicit fitting formulas for the dimensionless conductivity of canonical pore cross-sections (equilateral triangle, square, and circle) considering water film boundary layer (WFBL) effects. These formulations are based on a comprehensive parametric study using the ab initio finite element method, followed by regression analysis to yield closed-form expressions. Two-phase flow simulations reveal that the WFBL increases residual saturations, reduces relative permeabilities, and decreases waterflooding displacement efficiency, with effects being more pronounced during secondary imbibition. This integrated approach provides a robust framework for constructing representative digital rock models of tight reservoirs and offers essential theoretical support for accurately modeling nanoscale flow behaviors in complex subsurface systems. Full article

Plant growth-promoting bacteria (PGPB) enhance plant development through mechanisms such as the production of indole-3-acetic acid (IAA). However, endophytic bacteria associated with aquatic plants, particularly watermeal (Wolffia spp.), remain poorly explored. This study investigated the potential of bacterially derived crude IAA extract for enhancing watermeal growth and accumulation of secondary metabolites in watermeal. This study isolated and screened endophytic bacteria from watermeal for IAA production, identifying Klebsiella variicola W1/6 as the most efficient producer. Optimization using response surface methodology (RSM) revealed optimal conditions at pH 5.84, 5 days of incubation, and 10.63% (v/v) inoculum size. Crude IAA extract significantly enhanced watermeal growth under both laboratory and greenhouse conditions. Notably, the combination of 0.5 ppm crude IAA extract with 50% chemical fertilizer produced growth comparable to that of the full fertilizer treatment, indicating reduced fertilizer requirement. These findings highlight the potential of bacterially derived IAA from K. variicola W1/6 as a microbial biostimulant for sustainable aquatic plant cultivation. Full article

Drought stress poses a major threat to global wheat (Triticum aestivum L.) productivity by impairing physiological processes and inducing oxidative damage. Mutation breeding provides a valuable approach to generate novel genetic variation and identify stress-tolerant germplasms. In this study, phenotypic, physiological, and transcriptomic analyses were integrated to elucidate the drought adaptation mechanisms of a gamma-ray-induced mutant wheat line, PL6, alongside its wild-type parent, PL1. Under osmotic stress and soil drought conditions, PL6 exhibited an enhanced germination rate and higher photosynthetic efficiency (Fv/Fm). Furthermore, PL6 maintained lower malondialdehyde (MDA) accumulation, which was supported by elevated activities of antioxidant enzymes including SOD, APX, and CAT. Time-series transcriptomic analysis via WGCNA and GSEA revealed that PL6 actively maintains environmental sensing, transmembrane transport, and photosynthetic processes under PEG-induced osmotic stress. Conversely, pathways associated with the cell cycle and DNA metabolism were transiently suppressed. To isolate key regulatory genes without computational bias, a multi-algorithm machine learning framework—combining Random Forest, LightGBM, and LASSO—was applied to variance-stabilizing transformed (VST) expression profiles. This approach successfully identified 45 consensus core drought-responsive genes enriched in targeted protein turnover, redox balance, cell wall restructuring, and lipid metabolism, from which ten representative candidate genes were experimentally validated via qRT-PCR. Collectively, this study demonstrates an effective analytical framework for selection of high-confidence transcripts, providing candidate targets for future targeted gene editing and molecular breeding in wheat. Full article

Detecting far-range cyclists from LiDAR point clouds is challenging because cyclists are small road users and are often represented by only a limited number of points at long distances. This study proposes a training-time object-level temporal merge teacher that uses frame-level object IDs in the Waymo Open Dataset to improve single-frame 3D detection of sparse far-range cyclists while preserving the inference-time efficiency of PointPillars. Current-frame cyclist objects are defined as sparse/far targets when their ground-truth boxes are at least 40 m from the ego vehicle and contain no more than 20 LiDAR points. During teacher construction, previous-frame cyclist points with the same object ID are aligned to the current object coordinate system and used to construct the teacher input. The student detector receives only the original single-frame point cloud during inference; therefore, previous frames and ground-truth object IDs are not required at deployment. In validation experiments, the F2 temporal-merge teacher improved cyclist L2 APH from 0.1500 to 0.1903 over the baseline, and the F2 KD student achieved cyclist L2 AP/APH scores of 0.3119/0.1906. The results indicate that the temporal-merge teacher, pair-based fine-tuning, and KD signals can jointly improve cyclist AP for a single-frame detector. However, because the no-KD control also outperformed the baseline, the observed improvement should be interpreted as the combined effect of the temporal teacher construction and the training pipeline rather than the isolated effect of the KD loss alone. Full article

Background: Pathological angiogenesis and stromal fibrosis after ocular chemical injury are primary drivers of corneal opacification and permanent vision loss. Topical administration of anti-VEGFA antibody is hampered by rapid tear clearance and poor penetration across the corneal epithelial barrier, resulting in insufficient intraocular drug accumulation and suboptimal therapeutic efficacy. Although intraocular injection elevates local drug concentration, this invasive procedure carries risks of complications and is not suitable for long-term repeated treatment. This study constructed red cabbage-derived exosome-like nanovesicles (Rabexo) to load an anti-VEGFA antibody, formulated into PVA/HA hydrogel, aiming to develop a topical sustained-release ocular delivery system for alleviating corneal angiogenic and fibrotic lesions. Methods: Rabexo was isolated and physicochemically characterized. Anti-VEGFA antibody was encapsulated into Rabexo via electroporation to prepare aV-Rabexo, which was further incorporated into commercial PVA/HA hydrogel. Cellular uptake, anti-angiogenic functions were verified in vitro, and therapeutic efficacy was evaluated in a mouse corneal alkali burn model via ophthalmic topical administration. Results: The prepared Rabexo showed uniform size and favorable colloidal stability with 40.3% antibody encapsulation efficiency. aV-Rabexo exhibited stronger in vitro anti-migration, anti-proliferation and anti-tube formation effects than free antibody. In vivo, aV-Rabexo-Gel substantially suppressed corneal neovascular area and length, restored stromal collagen arrangement, and downregulated CD31, VEGFA and α-SMA expression at day 14 post-injury, with statistically significant differences compared with the free antibody gel. Conclusions: This plant-derived nanocarrier hydrogel system realizes synergistic therapeutic effects via nanocarrier delivery, antibody neutralization and prolonged ocular retention. With advantages of easy production and low immunogenicity, it provides a promising non-surgical strategy for treating ocular surface pathological angiogenesis and fibrosis. Full article

Secure QR-based data transfer requires a careful balance between confidentiality, payload size, decoding reliability, and resistance to visual degradation. This paper presents a reproducible comparative framework for studying secure QR code transmission under controlled distortions. The framework combines protected payload generation, batch experimentation, and comparative visual analysis to examine how payload mode, error-correction level, decoder backend, and image degradation influence transmission success, overhead, QR complexity, and processing time. The results highlight key trade-offs among robustness, efficiency, and symbol density, and provide practical guidance for selecting suitable secure QR transmission settings in distortion-prone environments. Unlike existing evaluation approaches that address security and robustness factors in isolation, the proposed framework offers the first unified experimental environment for their joint reproducible assessment, making it directly applicable to systematic research in secure QR transmission design. Full article

To investigate the effects of substrate selenium on mushroom growth, nutritional quality, and associated microbial community structure, the thermo-tolerant Pleurotus ostreatus cultivar “Daye 39” was used as the experimental material. Sodium selenite was applied at gradient concentrations (0–4000 mg·kg⁻¹), and the total selenium, organic selenium, crude protein, and soluble polysaccharide contents of the fruiting bodies were determined across successive flushes. High-throughput sequencing of bacterial 16S rRNA and fungal internal transcribed spacer (ITS) regions was performed on the substrate, and selenium-tolerant bacterial strains were isolated and identified. Our results showed that substrate selenium concentrations ranging from 80 to 400 mg·kg⁻¹ significantly increased fruiting body yield by 8.60% to 13.87%, whereas concentrations equal to or exceeding 600 mg·kg⁻¹ resulted in progressive yield declines. Both total and organic selenium contents in the fruiting bodies increased markedly after the third flush, with the organic selenium proportion stabilizing at ≥65%, predominantly in the forms of selenomethionine (81.6%). The crude protein content increased from 25.52 g·100 g⁻¹ in the first flush to 42.99 g·100 g⁻¹ in the eighth flush. Selenium caused the relative abundance of Pseudomonadota increasing sharply from 34.35% in the control to 74.76% in the Se2–Se7 treatments, whereas Bacillota decreased from 38.96% to 15.16%. The fungal community was consistently dominated by P. ostreatus at all timepoints throughout the experiment. Two highly efficient selenium-transforming bacterial strains, Cedecea neteri S1 and Pseudomonas composti S15, both belonging to the phylum Pseudomonadota, were successfully isolated from the high-selenium substrate and attained organic selenium proportions of 98.02% and 99.23% in their cells, respectively. The present study elucidates the dual role of selenium in simultaneously increasing the nutritional value of edible mushrooms and reshaping the substrate microbial ecology. Our findings suggest that the recommended substrate selenium concentration of 160 mg·kg⁻¹ is appropriate to optimize selenium-enriched P. ostreatus cultivation techniques and to explore functional microbial resources relevant to selenium biofortification. Full article

Accurate trajectory prediction is critical for autonomous driving safety and energy-efficient motion planning in sustainable urban mobility. This study isolates the effect of local lane graph conditioning by proposing a waterflow method that extracts an ego-centric lane topology via breadth-first traversal of the HD map (For convenience, all acronyms used throughout this manuscript (e.g., HD, LSTM, ADE, FDE, minADE, minFDE, BFS, GNN, SOTA) are collected in the Abbreviations section at the end of the paper), fusing lane features into trajectory encoders through cross-attention. The evaluation is deliberately scoped to ego-vehicle prediction at signal-controlled intersections: we evaluate across two architectures (LSTM and Transformer), two horizons (3 s and 8 s), and both single- and multi-modal ($K=6$) settings on 89,258 such scenarios from the Waymo Open Motion Dataset, so that “generality” refers to consistency across architectures, horizons, and output settings within this scope, rather than across prediction tasks. Lane conditioning consistently improves accuracy: $+9.3\%$ ADE at 3 s ($p=0.007$, 3 seeds), $+26.6\%$ minADE at 8 s ($K=6$, $p=0.003$, 3 seeds), and $+26.8\%$ ADE for the Transformer ($p=0.030$, 3 seeds)—with only ∼$8\%$ additional parameters for the LSTM. A controlled full-graph ablation (nearest 64 lanes) shows a consistent but not statistically significant trend favouring topologically guided local selection over brute-force spatial proximity ($+11.4\%$ minADE, $p=0.063$). Error decomposition reveals balanced lateral ($+26.5\%$) and longitudinal ($+25.4\%$) improvements, and a per-maneuver analysis over all 13,388 validation scenarios shows the largest gains for turning maneuvers. The lane-conditioned model (<700,000 parameters) runs in 0.8 ms per prediction on a desktop GPU (0.7 ms single-threaded CPU) with below 30 MB peak memory and an estimated 51 mJ per prediction, suggesting feasibility for resource-constrained deployment, pending validation on production automotive hardware. Full article

Background/Objectives: Chest radiographs contain hierarchical relationships between global thoracic configuration and organ-specific findings, together with scale-dependent anatomical boundary geometry and heterogeneous texture distributions. Coarse image–report alignment may overlook regional evidence, whereas isolated local alignment can fragment complete-examination semantics. We propose Anatomy-Guided Image–Report Alignment (AGIRA) for fine-grained chest X-ray (CXR) representation learning and investigate its behavior through post hoc finite-scale fractal and multifractal analysis. Methods: AGIRA constructs whole-image, left-lung, right-lung, and heart image–text pairs, adapts frozen vision and language backbones using lightweight Anatomy Sensors, and retains masked image and language reconstruction objectives to preserve global–local semantic continuity. Temporal–multiview fusion and hybrid soft labels reduce false-negative supervision. Post hoc analysis estimates effective box-counting dimensions, generalized dimensions, multifractal spectrum width, and a finite-scale attention concentration index. We additionally compare these descriptors with conventional intensity, texture, and uncertainty features using nested cross-validated incremental-value analyses. Results: AGIRA achieves 92.0% AUC, 84.2% accuracy, and 79.0% F1-score on RSNA Pneumonia, together with 57.5% zero-shot accuracy and 53.7% image-to-text P@5 on CheXpert 5 × 200, while updating only 7.54% of the complete model. On an independently annotated 600-unit report-routing set, the deterministic parser obtains macro-F1 0.953 and exact multi-label routing accuracy 0.918. Under the identical 34,080-record cohort, AGIRA remains above GLoRIA-ViT, MLIP, and BCC on all reported downstream metrics. Adding finite-scale descriptors to conventional intensity/texture/uncertainty features increases cross-validated AUROC for identifying anatomy-alignment-sensitive cases from 0.671 to 0.731 for zero-shot classification and from 0.651 to 0.704 for retrieval. Mild anatomical crop perturbations (±5%) change CheXpert P@5 and zero-shot accuracy by less than one percentage point, whereas severe 10% perturbations and explicit anatomy swaps cause progressively larger degradation. Conclusions: AGIRA improves cross-dataset benchmark transfer and retrieval while preserving parameter efficiency. The post hoc fractal/multifractal analysis contributes measurable incremental explanatory information about anatomy-alignment-sensitive model behavior beyond conventional descriptors without entering model training, and the added controlled experiments support parser reliability, cohort fairness, parameter robustness, and tolerance to moderate anatomical-localization noise. Full article

Cyclic trimetaphosphate (cTmp) has been used as a prebiotically plausible compound to generate chemically activated nucleoside 5′-phosphates. While cTmp is mainly available as a trisodium salt, some experiments benefit from different cations. This study describes a simple procedure for exchanging the sodium with potassium in solution and isolating the K₃cTmp via ethanol precipitation, involving materials and equipment available in most biochemistry and molecular biology laboratories. Repeating the solution exchange and precipitation cycle four times allowed conversion of Na₃cTmp, with more than 99% ion exchange efficiency, into K₃cTmp, with an overall yield of 92%. This method has advantages over the usually used ion exchange chromatography and may be especially useful to prebiotic chemists working on cyclic trimetaphosphate. Analogous solution/precipitation ion exchange cycles could also be useful for ion exchange procedures of other compounds. Full article

Conventional international rankings assess urban efficiency via context-blind metrics, a design that the literature suggests may structurally disadvantage Mediterranean centres and obscure the sustainable policy pathways mandated by the Sustainable Development Goals, most notably the governance of urban transitions under SDG 11. This paper proposes the Context-Weighted Liveability Index (CWLI), which introduces context-sensitive weights into the aggregation of standard smart city KPIs, bridging the global comparability of IMD-style indices with the Mediterranean-specific assessment logic of the ASCIMER framework. Weights derive from five geographic coefficients—climate, culture, economy, historical density, and demography—through a transparent weighted additive formulation with an explicit sensitivity matrix, whose robustness is verified through Monte Carlo uncertainty analysis over 5000 perturbed configurations spanning parameters, coefficients, measurements and benchmarks. Coefficients and KPIs are computed from open spatial data through a replicable GIS protocol (QGIS; OpenStreetMap, Copernicus land cover and land surface temperature, and ISTAT/ELSTAT census data at sub-municipal scale). Applied comparatively to Bologna and Athens, the framework shows that contextual weighting concentrates over 60% of the total weight on climate-sensitive indicators and yields, through the decomposition of contributions, a policy diagnosis that differs from the one suggested by reading an overall smart city rank in isolation: Athens’ largest contribution is digital and its liveability deficit territorial—a profile with direct consequences for sustainable urban transition and talent attraction. Implications for SDG 11 monitoring, equitable access to urban green space, and digital twin integration are discussed. Full article

Here, (CH₃NH₃)₂CoCl₄ and (CH₃NH₃)₂CoBr₄ were prepared via a solvent-free mechanochemical route and characterized by powder X-ray diffraction, electron microscopy, X-ray photoelectron spectroscopy, magnetic susceptibility, and thermal analysis. Both compounds crystallize in the monoclinic P2₁/c space group and exhibit paramagnetic behavior consistent with isolated high-spin Co²⁺ tetrahedra and negligible inter-site exchange. Diffuse reflectance spectroscopy yielded optical band gaps of 1.65 and 1.60 eV for the chloride and bromide, respectively. Valence-band XPS and cyclic voltammetry provided consistent experimental band-edge positions, confirming favorable alignment with TiO₂ and Spiro-OMeTAD in an n-i-p architecture. SCAPS-1D simulations using experimentally determined optical and electronic parameters predicted power conversion efficiencies of 6.63% and 4.86%, at an optimum absorber thickness of 1.28 μm. Defect density was identified as the dominant performance-limiting parameter, while the parity-forbidden Co²⁺ d-d transitions intrinsically constrain the attainable photocurrent. These results provide the first experimental grounded photovoltaic assessment of hybrid halocobaltates, combining measured optical and electronic parameters with SCAPS-1D device simulations, and establish design parameters for future device optimization. Full article

Background: Trophoblast retrieval and isolation from the cervix (TRIC) has emerged as a promising alternative to invasive prenatal diagnostic procedures. However, contamination by maternal immune cells remains a major challenge that may compromise trophoblast purity and the reliability of downstream fetal genetic analyses. Methods: Maternal immune cells were selectively depleted by immunomagnetic sorting using antibodies targeting CD45 or CD56. The remaining cells were subsequently enriched for HLA-G-positive trophoblasts and characterized by immunofluorescence and gene-expression analyses using CD45, CD56, HLA-G, cytokeratin 7 (CK7), and β-human chorionic gonadotropin (β-hCG). Results: Compared with CD45-mediated depletion, CD56-mediated depletion demonstrated more efficient removal of maternal immune cells, as indicated by significantly reduced CD56 expression. CK7 expression showed an increasing trend following CD56 depletion, whereas β-hCG expression remained largely unchanged. Immunofluorescence analysis further demonstrated a significant increase in the proportion of CK7⁺/β-hCG⁺ trophoblast cells after CD56 depletion. Conclusions: Among the evaluated depletion strategies, CD56-mediated depletion demonstrated a more favorable profile for trophoblast-associated characteristics than CD45-mediated depletion, suggesting its potential contribution to further methodological optimization of trophoblast isolation in TRIC-based noninvasive prenatal genetic testing. Full article

Ebola alerts reveal the truth about preparedness. They show whether a health system can recognize danger early, protect health workers, isolate and care for patients, trace contacts, communicate clearly, and sustain public trust before fear replaces cooperation. In the Pandemic Agreement Era, this truth has become harder to ignore. The 2026 Bundibugyo virus disease outbreak in the Democratic Republic of the Congo and Uganda is a sharp reminder that the principles of pandemic prevention, preparedness, response, equity, and cooperation become meaningful only when they work where the first cases occur. In the absence of licensed vaccines and specific treatments for Bundibugyo virus disease, preparedness depends on the basic functions of public health: surveillance, diagnosis, infection prevention and control, referral, risk communication, community engagement, and operational coordination. These functions are often described as routine. They are not. During high-consequence infectious disease alerts, they serve as the primary protective infrastructure. Ebola also exposes a deeper ethical failure. Frontline countries and communities are expected to contain threats of global relevance, but international support often intensifies only after the risk becomes visible beyond the affected area. This reactive model is neither fair nor efficient. The WHO Pandemic Agreement defines a political direction for a more equitable and coordinated global response. Here, Ebola is not presented as a typical pandemic event but as an operational test of preparedness, solidarity, early support to affected settings, and international cooperation. Ebola alerts test whether that direction can become an operational reality before escalation. Digital tools, telemedicine, and artificial intelligence may strengthen this agenda but only when they make local systems faster, safer, more trusted, and more usable. Ebola preparedness is therefore not only a technical task. It is a test of responsibility. Full article

Porcine rotavirus (PoRV), a major enteric pathogen, causes severe diarrhea, dehydration, high morbidity, and mortality, leading to significant economic losses in the porcine industry. In this study, we established a porcine small intestinal organoid culture system and developed an in vitro model for PoRV infection. Jejunal crypts were isolated from neonatal piglets and subsequently cultured to generate porcine small intestinal organoids in both three-dimensional (3D) and two-dimensional (2D) organoid formats, properties of which were verified via morphological assessment and immunostaining for Lgr5, villin, Ki-67, and lysozyme. Furthermore, a PoRV infection model was established in both 3D and 2D organoid cultures, and growth kinetics demonstrated efficient PoRV replication. PoRV infection also significantly increased the expression of inflammatory cytokines, including IL-6 and IFN-α. Collectively, these results demonstrate that the established porcine small intestinal organoid models support efficient PoRV replication and provide a physiologically relevant platform for studying PoRV pathogenesis and evaluating potential antiviral strategies. Full article