Search Results (235)

Background: Acute kidney injury (AKI) is one of the more serious complications following cardiac surgery, consistently linked to prolonged mechanical ventilation and higher in-hospital mortality. This study examined whether preoperative anaemia and impaired renal function are associated with AKI and death in a high-risk cardiac-surgery cohort requiring extended postoperative ICU monitoring and how these associations behave after adjustment for procedure type and intraoperative variables. Methods: In this single-centre retrospective cohort study, we screened 950 patients admitted to a cardiothoracic ICU between January 2018 and January 2024. After standard exclusion criteria and an audit of operative records, 553 cardiac-surgery patients formed the principal analysis cohort. AKI was defined by KDIGO criteria using serial postoperative serum-creatinine measurements during the first 7 days. Multivariable logistic regression for AKI and in-hospital mortality was built sequentially: Model A (baseline only); Model B (+procedure type); and Model C (+intraoperative variables: aortic cross-clamp time, intraoperative RBC units, and intraoperative inotrope use). Calibration was assessed by the Hosmer–Lemeshow test. Total cardiopulmonary bypass duration was not separately captured in the institutional database and is disclosed as a limitation. Results: AKI occurred in 174 of 553 patients (31.5%), and in-hospital mortality was 16.6% (92/553). Patients with AKI were older (median 77 vs. 68 years, p < 0.001), with lower preoperative haemoglobin (11.4 vs. 12.3 g/dL, p < 0.001) and lower eGFR (38.1 vs. 63.7 mL/min/1.73 m², p < 0.001). The aortic cross-clamp time was shorter in AKI patients (56 vs. 70 min, p = 0.043), a counterintuitive finding likely reflecting residual confounding by case-mix and procedure selection rather than a protective operative effect. In the fully adjusted multivariable model, the haemoglobin–AKI association attenuated and was no longer independently significant (OR 0.89 per 1 g/dL, 95% CI 0.73–1.08, p = 0.24), while intraoperative RBC transfusion emerged as an independent predictor (OR 1.12 per unit, p = 0.046). For mortality, AKI remained an independent predictor after full adjustment for procedure type and intraoperative variables (OR 7.14, 95% CI 1.45–35.13, p = 0.016), with cross-clamp time (OR 1.30 per 10 min, p = 0.010) and intraoperative RBC units (OR 1.48 per unit, p < 0.001) also independently associated. Both fully adjusted models showed acceptable calibration (Hosmer–Lemeshow p = 0.48 for AKI, p = 0.56 for mortality). Conclusions: In cardiac-surgery patients with a prolonged ICU stay, AKI is independently associated with in-hospital mortality even after adjustment for operative variables. The univariable association between preoperative haemoglobin and AKI is attenuated after adjustment for procedure type and intraoperative transfusion exposure, suggesting confounding or mediation by operative and case-mix factors rather than an independent direct association. The contribution of this analysis is aetiological/analytical rather than predictive (modest discrimination, AUROC 0.67 for AKI), and findings should be interpreted within the selected high-risk ICU ≥ 72 h population. Full article

Background/Objectives: Nocturnal glycemic variability in pediatric type 1 diabetes (T1D) disrupts caregiver sleep and quality of life; advanced hybrid closed-loop (AHCL) systems may be associated with reduced caregiver burden by providing more stable overnight glucose control. We aimed to evaluate changes in caregiver-reported sleep quality and continuous glucose monitoring (CGM) targets three months after transition to an AHCL system. Methods: We conducted a prospective single-center real-world study in a tertiary pediatric diabetes unit that included children aged 6–17 years with T1D who switched from continuous subcutaneous insulin infusion (MiniMed) and intermittently scanned CGM (FreeStyle Libre 2) to an AHCL system (MiniMed 780G) with Guardian 4 sensor. Caregivers completed the Pittsburgh Sleep Quality Index (PSQI) at baseline and after 3 months; CGM metrics (TIR 70–180 mg/dL, TAR1 180–250 mg/dL, TAR2 > 250 mg/dL, TBR1 54–70 mg/dL, TBR2 < 54 mg/dL) were extracted at the same time points. Analyses used Shapiro–Wilk, Wilcoxon signed-rank, Spearman correlations, and McNemar tests (α = 0.05). Results: Twenty-two caregivers completed baseline PSQI; 16 provided PSQI data at three months. The proportion with PSQI > 5 decreased from 56.3% to 18.8% (p = 0.034), and 81.3% showed lower global PSQI at 3 months (p = 0.018). The largest mean improvements were observed in daytime dysfunction (−0.94), subjective sleep quality (−0.81), and sleep duration (−0.63), with slight increases in sleep disturbance (+0.13) and sleep-medication use (+0.13). The proportion of participants meeting international CGM consensus targets improved: the percentage achieving TIR > 70% increased from 26.7% to 80.0% (p = 0.008); those meeting TAR > 180 mg/dL < 30% increased from 26.7% to 80.0% (p = 0.008); and those meeting TAR2 > 250 mg/dL < 5% increased from 20.0% to 53.3% (p = 0.008). Hypoglycemia-related targets showed no significant change, and no episodes of symptomatic or level 3 hypoglycemia were reported. Exploratory analyses suggested that poorer PSQI at 3 months was associated with greater Δ TBR1, and increases in TAR2 with higher sleep disturbance and sleep-medication use. Conclusions: Transition to an AHCL system was associated with improvements in caregiver-reported sleep and attainment of CGM consensus targets within three months. Residual nocturnal hyperglycemia was associated with features of ongoing sleep disturbance, highlighting the potential relevance of individualized alert settings, sleep-focused education, and inclusion of objective sleep measures in future studies. Full article

Objective: Rapid vertical manoeuvres and intermittent vibration in autonomous electric vertical take-off and landing (eVTOL) aircraft can provoke pronounced psychological anxiety in passengers. To address this, we propose a closed-loop adaptive system that integrates an in-ear wearable sensor with dynamic regulation of the cabin microenvironment, enabling real-time monitoring of each passenger’s autonomic state and delivering individualised mitigation through a continuous sense–analyse–intervene–feedback loop. Methods: The system is built around a pair of custom in-ear modules that integrate dual-wavelength photoplethysmography (PPG; 525 nm green and 940 nm infrared), galvanic skin response (GSR), and a six-axis inertial measurement unit (IMU) sampled at 200 Hz. To suppress the 20–80 Hz vibration generated by the distributed electric propulsion system, a compliant silicone damping sleeve attenuates high-frequency components at the hardware level, while a Kalman filter fuses the IMU and PPG streams and an adaptive notch filter removes residual rotor harmonics. The pipeline raises the heart-rate-variability (HRV) signal-to-noise ratio (SNR) to 24.1 dB, with a Pearson correlation of 0.96 against a medical-grade chest strap. A hybrid CNN–LSTM network—two convolutional layers (32 filters each) followed by two LSTM layers (128 hidden units)—predicts impending anxiety from HRV time-domain features (RMSSD, pNN50) and frequency-domain features (LF/HF ratio), triggering intervention 8.2 s in advance on average. According to the predicted anxiety level (mild/moderate/severe), a fuzzy controller modulates transcutaneous auricular vagus nerve stimulation (1–5 mA), the binaural-beat frequency (4–8 Hz, theta band), and the cabin lighting colour temperature (2700–6500 K) in real time. The intervention parameters are continuously refined by SPSA-based stochastic optimisation of the HRV recovery rate (step size 0.01; updated every 30 s). Results: In a randomised controlled experiment conducted in a simulated flight environment (N = 50; aged 22–45 years; 1:1 sex ratio), the active group reached physiological recovery in 52.3 s on average, compared with 98.6 s for the sham-controlled group—a 47% reduction (Cohen’s d = 1.24, p < 0.001). User acceptance reached 94%. Conclusions: The proposed in-ear platform enables closed-loop adaptive regulation of anxiety in the eVTOL cabin and overcomes the limitations of conventional passive mitigation strategies. By combining vibration-tolerant physiological sensing with multimodal environmental control, the work offers a practical pathway for improving passenger experience in urban air mobility and provides a useful reference for human-factors standards governing autonomous aircraft. Full article

A three-year (January 2020–December 2022) daily dataset of 16 polycyclic aromatic hydrocarbons (PAHs) collected in parallel with PM_2.5 and a suite of meteorological variables at a coastal Mediterranean urban site in southern Italy (Pomigliano d’Arco, Campania) is presented and analysed. Raw PAH time series were decomposed into a long-term trend component (LT), a seasonal component (ST), and a residual component (RT) using an iterative missing-value-robust Kolmogorov–Zurbenko (KZ) moving-average filter. Spearman rank correlations between PAH concentrations and four meteorological predictors (mean temperature, relative humidity, mean wind speed, and maximum wind speed) were computed for each congener. Diagnostic molecular ratios—Fla/(Fla + Pyr), BaP/BghiP, Indeno[1,2,3-cd]pyrene/(IcdP + BghiP), and BaA/(BaA + Chr)—were evaluated seasonally and interpreted jointly with an information-theoretic Bayesian mixture modelling procedure (SNOB/MML) and with the documented susceptibility of some PAH ratios, especially BaP-containing ratios, to atmospheric ageing, phase repartitioning and summer photodegradation. Total PAH concentrations (sum of 16 congeners) ranged from <1 ng m⁻³ in summer to 46 ng m⁻³ during winter high-pollution episodes, with BaP peaking at ≈6.7 ng m⁻³. Because BaP was measured in the PM_2.5 fraction, comparisons with the EU annual target value of 1 ng m⁻³ established for PM₁₀-bound BaP are treated as indicative context only, not as formal compliance statements. Pronounced seasonal variability was driven primarily by residential heating emissions, and the incremental lifetime cancer risk (ILCR) for inhalation exposure reached $1.03\times {10}^{-4}$ (95% CI: $0.88$–$1.20\times {10}^{-4}$) during the heating season under a continuous outdoor-exposure worst-case scenario. The absolute ILCR magnitude is conditional on the selected TEF scheme and on the adopted BaP unit-risk coefficient; under an additional indoor-dominated scenario (16 h day⁻¹, infiltration factor 0.6), the corresponding risk remained above the conventional ${10}^{-6}$ benchmark. An anomalous near-background PAH signal during spring 2020 is attributed to the COVID-19 national lockdown, which reduced total PAH concentrations by approximately 85% relative to the seasonal component predicted by the iterative moving-average filter for the same calendar window. Source apportionment via diagnostic ratios identifies residential/biomass combustion as the dominant cold-season source and vehicular emissions as the prevailing warm-season source. These results provide a novel characterisation of PAH pollution dynamics in the undersampled southern Mediterranean and provide evidence to support targeted abatement policies. Full article

Projection-based spatial augmented reality (P-SAR) supports appearance-oriented design evaluation by projecting digital materials onto physical mock-ups, but the projected result may deviate from the intended screen-rendered appearance in both colour distribution and normal-induced shading. This paper proposes a screen-referenced, measurement-driven appearance optimisation framework in which a calibrated monitor serves as the visual reference and the projected mock-up as the optimisation target. The workflow combines controlled Unity rendering, colourimetric measurement, D65 CIE Lab analysis, and MATLAB (R2024b)-based iterative update, and separates the problem into albedo appearance optimisation and shading appearance optimisation. The albedo branch uses dominant-colour grouping and CIEDE2000-guided group-wise correction, while the shading branch uses a lightness-contrast descriptor derived from flat and normal-modulated renderings to update the normal-map-driven shading response. Experiments on ten material textures showed that all 23 identified colour groups converged below the adopted $\Delta E_{00}$ threshold of 2.3; the mean texture-level colour difference decreased from 6.24 to 1.36, corresponding to an average reduction of 77.43%. Comparative evaluation showed that the proposed group-wise optimisation outperformed global neutral-grey and global Lab-offset correction baselines. For shading, the mean residual $r_D=|D_{\mathrm{proj}}-D_{\mathrm{ref}}|$ decreased from 1.164 to 0.264 $L^{\ast }$ units, and all ten normal-map cases satisfied the 1.0 $L^{\ast }$ tolerance. A comparison with a global luminance-contrast baseline further supported the benefit of material-level normal-map update over image-domain contrast adjustment. Additional analyses examined the sensitivity to the number of dominant colour groups and clarified the rationale and scope of the adopted thresholds. Integrated photographic examples provided qualitative illustrations of the overall appearance tendency after the complete workflow, while the quantitative assessment was based on colourimetric and lightness-domain measurements. The full workflow required approximately 26 min per material case, indicating practical feasibility for controlled or semi-controlled P-SAR material appearance preparation and design-review scenarios. Full article

Background/Objectives: To evaluate the association between adjunct tendon vibration and changes over 12 months in dual-energy X-ray absorptiometry (DXA)-derived bone mineral density (BMD) T-score and bone turnover markers in older adults with osteoporosis receiving standard care in a non-randomised controlled cohort study. Methods: This 12-month prospective non-randomised controlled cohort study included 100 adults aged ≥60 years with DXA-confirmed osteoporosis recruited from orthopaedic clinics in the Greater Thessaloniki area. Fifty participants received adjunct tendon vibration therapy in addition to usual care, while 50 received usual care alone. Usual care consisted of calcium and vitamin D supplementation. The primary outcome was post-intervention BMD T-score, analysed using analysis of covariance (ANCOVA) adjusted for baseline T-score. Secondary outcomes included changes in bone turnover markers and calcium/phosphate metabolism. Sensitivity analysis was conducted using a linear mixed-effects model with repeated BMD measurements. Results: Baseline characteristics were comparable between groups. Over 12 months, the intervention group showed greater improvement in BMD T-score than controls (median change 0.90 [0.70–1.00] vs. −0.10 [−0.10–0.10], p < 0.001). The adjusted between-group difference was 0.871 (95% CI 0.773–0.968; p < 0.001). Results remained consistent after adjustment for age and sex. The mixed-effects model confirmed a significant group × time interaction (β = 0.922, 95% CI 0.806–1.038; p < 0.001). Bone resorption markers decreased more in the intervention group. The magnitude of the observed BMD improvement (~0.9 T-score units) is notable for a non-pharmacological intervention and should be interpreted cautiously. Conclusions: Adjunct tendon vibration was associated with a more favourable BMD trajectory and changes in bone turnover markers in older adults with osteoporosis receiving standard care. Given the non-randomised design and potential residual confounding, these findings should be interpreted as associative rather than causal. Full article

Background/Objectives: Dental metallic implants cause severe streaking artifacts in kilovoltage CT (kVCT), compromising dose calculation in radiotherapy (RT) treatment planning. The purpose of this study is to assess the dosimetric agreement of synthetic MVCT (sMVCT) images generated from artifact-affected kVCT using a deep learning network with respect to true MVCT (tMVCT) acquired at the treatment machine. Methods: Nineteen head and neck cancer patients with dental metallic implants treated with RT were included. Planning kVCT images were converted to sMVCT using Metal Artifact Reduction through Domain Transformation Network (MAR-DTN), a UNet-inspired deep learning network. The sMVCT images were rigidly registered to true MVCT (tMVCT) acquired on the Hi-Art II Tomotherapy system. Mean Hounsfield Unit (HU) values were compared across seven structures (thyroid, bilateral parotids, brainstem, spinal cord, GTV, PTV70) using pairwise Wilcoxon tests and Two One-Sided Tests (TOST) for statistical equivalence within a pre-specified margin of ±20 HU (corresponding to a 2% deviation in physical density). Dose distributions were recalculated on sMVCT using the AAA algorithm and compared to reference tMVCT-based plans via dose–volume histogram (DVH) metrics, evaluated for equivalence by TOST within a margin of ±2% of the prescribed dose (±142 cGy of 70.95 Gy), and via 3D gamma index, evaluated by one-sided non-inferiority test against the clinically accepted thresholds of 90% (2 mm/2%) and 95% (3 mm/3%). A pre-specified sensitivity analysis was performed by repeating all comparisons on the strictly independent sub-cohort (n = 16) excluding three patients drawn from the MAR-DTN training set. Results: All seven anatomical structures showed statistical equivalence between sMVCT and tMVCT under the ±20 HU margin (TOST p < 0.05; mean HU differences in the range −1.1 to +8.4 HU; all Wilcoxon p > 0.05). All nine DVH metrics achieved formal dosimetric equivalence within ±2% of the prescribed dose (TOST p < 0.05). Mean 3D gamma pass rates were 94.3% (95% CI: 89.3–97.1) for the 2 mm/2% criterion and 97.6% (95% CI: 94.8–99.0) for the 3 mm/3% criterion, both formally non-inferior to the respective clinical thresholds (p < 0.0001). Residual gamma failures were concentrated at the patient surface, consistent with inter-session repositioning uncertainty rather than errors in synthetic image generation. Sensitivity analysis on the n = 16 sub-cohort confirmed all conclusions, with mean HU and DVH differences smaller than in the full cohort for the structures showing the largest mean differences, and comparable for the remaining structures, with all TOST equivalence and gamma non-inferiority tests confirmed in both cohorts. Conclusions: sMVCT images generated via MAR-DTN show dosimetric agreement with physically acquired tMVCT in head and neck patients with dental implants, formally demonstrated by TOST equivalence within ±2% of prescribed dose for all DVH metrics. The combined HU and gamma index framework presented here represents a promising quality assurance approach for AI-based synthetic imaging tools in radiotherapy, pending validation in larger prospective multicentre cohorts. Full article

We develop a design-aware framework that combines penalized prediction and causal inference for finite populations observed through complex survey designs. The framework integrates survey-weighted pseudo-likelihoods, ${\mathsf{\ell }}_1$-penalized estimation, Neyman-orthogonal moment functions, and a bootstrap procedure that resamples primary sampling units within strata. Methodologically, the contribution is an explicit pipeline that supports design-based inference while separating predictive associations from structurally adjusted effects in high-dimensional, clustered data. We illustrate the framework using data from the Chilean National Health Survey (ENS) 2016–2017 to study the relationship between chronic kidney disease (CKD) and high cardiovascular (CV) risk. In the ENS adult population, the survey-weighted prevalence of CKD was 3.1% (95% CI: 2.4–3.8), and the prevalence of high CV risk was 23.9% (95% CI: 21.5–26.3). High CV risk was markedly more frequent among individuals with CKD than among those without CKD (90.9% versus 21.5%). Predictive and associational analyses combined survey-weighted penalized logistic regression (LASSO) with refitted unpenalized models. In conventional survey-weighted logistic regressions, CKD showed a strong association with high CV risk (odds ratio = 5.66; 95% CI: 2.71–11.82; $p<0.001$), and effect sizes remained stable after LASSO-based variable selection. To assess causal relevance under confounding and potential endogeneity, we implemented two endogeneity-aware estimators: two-stage residual inclusion (2SRI) and double/debiased machine learning (DML). The DML estimator, defined as the primary causal estimand, reports an orthogonalized estimate of the average treatment effect of CKD on the probability of high CV risk. After adjustment for age and major cardiometabolic comorbidities, the DML estimate was attenuated and statistically non-significant (average treatment effect = $-0.094$; 95% CI: $[-0.409,0.220]$). The 2SRI approach yielded unstable estimates with wide confidence intervals, consistent with the limited effective sample size of CKD cases ($n_{CKD}\approx 190$ in a sample with n ≈ 6233) and weak identification conditions under low-prevalence settings. Simulation experiments under ENS-like complex sampling suggest that naive predictive associations may overestimate the structural contribution of CKD under confounding, whereas orthogonalized estimators yield more conservative estimates when identification holds. The causal interpretation relies on a conditional mean independence assumption given observed covariates and survey design, while control-function specifications are treated as diagnostic sensitivity analyses due to the absence of credible exclusion-based instruments. Overall, the results demonstrate a fundamental divergence between predictive relevance and causal importance in finite-population settings, underscoring the need for design-aware and endogeneity-robust methods in statistical modeling. Full article

Expanded polystyrene (EPS) waste poses a major environmental concern due to its high volume, low density, and resistance to biodegradation. In this study, post-consumer EPS was reprocessed into continuous microfibers by Air Jet Spinning (AJS) using chloroform and chloroform/D-limonene as solvent systems. The effects of polymer concentration, air pressure, and solvent ratio on fiber formation were systematically investigated through rheological and surface tension analyses. The incorporation of 10 vol. % D-limonene improved jet stability and reduced bead formation, attributed to its lower volatility and favorable solubility with EPS, as supported by Hansen solubility parameters. SEM analysis confirmed uniform microfiber formation within a defined processing window. FTIR spectra indicated preservation of the polystyrene chemical structure, while TGA and DSC analyses were used to evaluate thermal behavior and assess potential residual solvent retention, particularly related to D-limonene. The results elucidate the interplay between solvent volatility, solution properties, and fiber morphology, establishing a sustainable processing framework for converting EPS waste into value-added fibrous materials via AJS. This work contributes to the United National Sustainable Development Goals, particularly SDG 12 (Responsible Consumption and Production) by promoting EPS waste valorization, and SDG 13 (Climate Action) through the partial replacement of conventional solvents with sustainable alternative. Full article

The application of organic residues in agriculture helps to replenish soil organic carbon (OC), improve soil fertility and biodiversity, reinforce aggregate stability, and favour water infiltration. Moreover, its application as a soil amendment alters the fate of herbicides applied to the soil. The objective here was (i) to evaluate soil quality by determining the physicochemical and biological parameters of an agricultural soil (Soil) amended with green compost (Soil + GC) over an arable pea–wheat crop rotation in a short-term experiment; and (ii) to study the dissipation and persistence of iodosulfuron-methyl-sodium applied in field plots sown with winter wheat under real field conditions. The experimental field design consisted of 24 plots (10 m²) involving 12 with control and 12 with GC-amended soils. The plots were sown with pea after GC application (~11 t ha⁻¹) in February 2023, and with winter wheat in October 2023. Iodosulfuron-methyl-sodium (Hussar^® Plus, Bayer CropScience S.L., Barcelona, Spain) was applied in post-emergence at the agronomic dose (D1 = 176 mL ha⁻¹) and double dose (D2 = 352 mL ha⁻¹). Soil samples were taken from the plots to assess the soil physicochemical and biological parameters at six sampling times after GC application, with extraction and determination of residual herbicide and metabolite (metsulfuron-methyl) concentrations. In addition, the yield and characteristics of the pea and wheat grain crops were determined. The application of GC to the soil significantly increased pH (0.5 units by July 2024) and electrical conductivity (up to 5.2 times) compared to control soil, which remained constant throughout the experiment. The OC in Soil + GC increased by 40% in July 2024 compared to control soil. Total nitrogen content increased up to 2.0 and 1.3 times during the pea–wheat growing seasons in Soil + GC compared to unamended soil. Soil dehydrogenase activity, respiration, and biomass increased by up to 1.4, 2.2 and 1.4 times, respectively, in Soil + GC compared to unamended soil over the growing seasons. The soil microbial structure, determined by phospholipid fatty acid (PLFA) analysis, recorded no significant differences between the microbial groups in both soil treatments. A non-significant increase in pea and wheat yield was observed in Soil + GC compared to unamended soil. The results revealed an increase in the residual amounts of herbicide and metabolite, being slightly more persistent, with DT₅₀ and DT₉₀ values up to 1.6 times higher, in the Soil + GC plots over time. Much higher amounts of metabolite (DT₅₀ = 24.8–29.7 days) than iodosulfuron-methyl (DT₅₀ = 5.2–8.8 days) were found in all the treatments. This may be due to wheat plants intercepting the herbicide initially at the time of application in post-emergence, the rapid dissipation of the herbicide reaching the soil, and/or the higher persistence of the metabolite compared to that of the herbicide. Overall, the soil’s physicochemical and biological properties were improved in GC-amended soil, and organic amendment increased slightly the persistence of iodosulfuron-methyl-sodium and its metabolite in the soil. Full article

Background: Polygonatum sibiricum (PS), a perennial herbaceous plant belonging to the Liliaceae family, is widely distributed in China and other East Asian countries. PS has been used as food and medicine for thousands of years, and its rhizomes are rich in Polygonatum sibiricum polysaccharides (PSP), which exhibit various bioactivities, yet their structural features and therapeutic mechanisms against ulcerative colitis (UC) remain unclear. Methods: A homogeneous polysaccharide, PSP-1b (57.45 kDa), was isolated from the rhizomes of PS via ion-exchange and gel filtration chromatography and structurally characterized using chromatographic and spectroscopic methods. In vivo, its effects were evaluated in a dextran sulfate sodium (DSS)-induced mouse model of UC, while in vitro mechanisms were explored using macrophages stimulated with lipopolysaccharide (LPS) and neutrophil extracellular traps (NETs). Results: PSP-1b was identified as a neutral polysaccharide with minimal branching. Its primary structural backbone was largely composed of →4)-β-D-Galp-(1→ residues. A portion of these backbone residues was substituted at the O-6 position by side chains primarily composed of β-D-Galp-(1→ units. In vivo, PSP-1b significantly alleviated DSS-induced colitis by reducing inflammatory cytokine secretion, suppressing colonic macrophage infiltration, and reversing neutrophil extracellular traps (NETs) deposition. In vitro, PSP-1b directly interacted with TLR4, inhibited the MAPK/NF-κB signaling pathway, and attenuated LPS- and NET-induced macrophage polarization and inflammation. Conclusions: PSP-1b as a promising candidate for functional foods or therapeutic agents targeting inflammatory bowel disease. Full article

This article addresses the problem of finding the shortest route for Automated Guided Vehicles (AGVs) in a production environment with constrained battery state-of-charge (SoC) and time-dependent operating conditions. The route map is divided into a uniform grid containing stationary obstacles and two types of dynamic obstacles: human, for which AGV transportation is prohibited, and inanimate (moving objects), which impose a penalty function. A key contribution of the proposed methodology is the introduction of a battery residual charge matrix, which embeds cell-level energy feasibility directly into the grid-based environment representation by determining minimum admissible SoC constraints and accounting for transition-dependent energy costs. This matrix restricts the set of traversable cells under low-energy conditions, enabling energy-aware route feasibility evaluation during both initial planning and adaptive replanning. The proposed approach is based on the A* and D* Lite algorithms, providing shortest-path construction that explicitly integrates battery SoC into the spatio-temporal cost function. To avoid collisions in a multi-agent environment during routing, a simplified hybrid scheme with M* elements performs local coordination and adaptive trajectory replanning. The effectiveness of the proposed methodology was assessed using travel time, temporal complexity, and spatial complexity metrics. Simulation results on a $10\times 10$ grid showed that agents with sufficient battery completed routes of 8 and 11 cells with travel times of 7.2 to 10.7 conventional units. A critically low-energy agent was initially unable to move, but after adjusting the minimum SoC constraint, all agents completed their routes with travel times up to 11.4 conventional units, demonstrating the direct impact of energy constraints on system performance. Additional experiments with varying agent counts and SoC thresholds confirmed reliable balancing of route feasibility and energy constraints across configurations. Full article

Rolling bearings exhibit nonlinear and non-stationary fault signals under complex working conditions, rendering single-modal representation insufficient for accurate diagnosis. To address this limitation, this paper proposes a novel parallel multimodal fusion fault diagnosis model based on a Gated Recurrent Unit (GRU), a Residual Network (ResNet), and a Convolutional Block Attention Module (CBAM). First, a systematic multimodal representation selection framework is introduced, identifying the Markov Transition Field (MTF) as the optimal two-dimensional (2D) image modality due to its superior texture clarity and noise resistance compared to other methods. Second, parallel dual-branch architecture is designed to simultaneously process heterogeneous data. The 1D-GRU branch captures long-range temporal dependencies directly from raw vibration signals, while the 2D ResNet-CBAM branch extracts deep spatial features from the MTF images, adaptively focusing on key fault regions. These heterogeneous features are then fused through concatenation to retain complementary diagnostic information. Experimental validation on the Case Western Reserve University (CWRU) dataset demonstrates that the proposed model achieves a 99.57% accuracy in a 10-classification task. Furthermore, it exhibits significant parameter efficiency and outstanding robustness, with the accuracy decreasing by no more than 1.2% under noise interference and cross-load scenarios, comprehensively outperforming existing single-modal and advanced fusion methods. Full article

Precise estimation of evapotranspiration (ET) is essential for sustainable water management in arid agroecosystems, particularly for high-water-demand crops such as rice. This study integrated very-high-resolution UAV thermal–multispectral imagery with a Two-Source Energy Balance model (UAV–TSEB) and a field-calibrated AquaCrop model to quantify daily ET and its components under continuous flooding on the arid Peruvian coast during the 2024–2025 season. A network of 24 drainage lysimeters provided an independent observational benchmark (ET_lys); to represent the treatment-level response, lysimeter observations were aggregated as the mean across the 24 units for each UAV campaign. Thirteen UAV surveys supplied radiometric surface temperature and biophysical inputs (e.g., NDVI and fractional cover) to derive spatially explicit ET, while AquaCrop provided continuous daily simulations between flight dates. Direct lysimeter-based validation indicated high agreement for AquaCrop (R² = 0.85; RMSE = 0.26 mm d⁻¹; MBE = 0.01 mm d⁻¹) and moderate agreement for UAV–TSEB (R² = 0.66; RMSE = 0.81 mm d⁻¹; MBE = 1.01 mm d⁻¹). Model intercomparison further showed consistent temporal dynamics of ET (R² = 0.70; RMSE = 1.35 mm d⁻¹) and robust partitioning of crop transpiration (R² = 0.79; RMSE = 0.99 mm d⁻¹) and soil evaporation (R² = 0.76; RMSE = 1.03 mm d⁻¹) while revealing a systematic divergence under near-complete canopy cover: AquaCrop tended to suppress evaporation, whereas UAV–TSEB detected residual evaporation from the flooded surface. Overall, the results highlight the complementarity of both approaches—UAV–TSEB as a spatial diagnostic tool and AquaCrop as a temporally continuous simulator—providing a robust framework for ET monitoring, flux partitioning, and water-use-efficiency assessment in water-scarce rice systems. Full article

A novel cucumber pulp certified reference material (CRM) was prepared for the analysis of plant growth regulator residues, specifically chlormequat chloride (CCC) and 2,4-dichlorophenoxyacetic acid (2,4-D). The matrix CRM candidates were prepared by cucumber pulping, spiking, homogenizing and subpackaging. A reference method of liquid chromatography tandem isotope dilution mass spectrometry (ID-LC-MS/MS) was established for simultaneous measurement of mass fractions of CCC and 2,4-D in cucumber pulp. Interlaboratory value assignment of CCC and 2,4-D in the cucumber pulp CRM was performed using the ID-LC-MS/MS method. The certified values with expanded uncertainties (coverage factor k = 2) were assigned to be 4.1 mg/kg ± 0.4 mg/kg for CCC, 2.0 mg/kg ± 0.2 mg/kg for 2,4-D. Homogeneity assessment was performed on fifteen randomly selected units, and statistical analysis confirmed the CRM’s homogeneity for both CCC and 2,4-D, both between and within packages. The long-term stability of the CRM at −20 °C storage condition and short-term stability at 30 °C were monitored for 14 months and nine days, respectively, and no significant trend differences were observed. The uncertainty contributions from characterization, homogeneity and stability were taken into account in uncertainty evaluation. The CRM was officially certified and registered under the number GBW(E)100932 by the State Administration for Market Regulation of the P. R. China. Full article