Search Results (12,647)

The escalating intensity and depth of coal mining operations have exacerbated underground strata pressure, resulting in fracture-induced air leakage channels that heighten risks of coal spontaneous combustion and gas explosions. These challenges necessitate enhanced flexibility and strength in cementitious materials used for roadway support. This study investigated the mechanical properties of fiber-reinforced polymer concrete (FRPC) for mining applications through response surface methodology (RSM) using Design Expert software. Three critical factors: styrene–acrylic emulsion content (5–15 wt.%), polypropylene fiber length (9–15 mm), and fiber content (0.7–1.1 kg/m³), were systematically investigated to establish factor-performance correlations via 3D response surfaces. This study experimentally investigated the effects of styrene–acrylic emulsion content, polypropylene fiber length, and fiber content on the mechanical properties of fiber-reinforced polymer concrete for mining roadway support. Response surface methodology was used as an empirical statistical tool to describe the response trends and factor interactions within the selected experimental range. The regression models developed in this study should therefore be interpreted as local empirical models rather than mechanics-based predictive equations. Using the flexural-to-compressive strength ratio as an index, the optimal formulation of FRPC was 10% emulsion, 12 mm fibers, and 1.1 kg/m³ fiber content. Microstructural characterization indicated that polypropylene fibers effectively inhibited crack propagation through bridging effects, while styrene–acrylic emulsion formed continuous film-like network structures on cement surfaces. Synergistically, both components enhanced matrix densification, achieving concurrent improvements in flexibility and strength. Field applications demonstrated that FRPC significantly reduced air leakage channels, decreased the risk of coal spontaneous combustion, and improved the safety of coal mine production. Full article

Background: Composite well-being indicators are typically built by aggregating dimension scores with subjectively elicited or transferred weights, computed on raw sample means without formal reliability checks. Methods: We propose the Reliability-Weighted, Empirical-Bayes-Shrunk Composite (RWEB-CWBI), which shrinks each dimension’s group-level mean via the dimension-specific DerSimonian–Laird random-effects models, derives aggregation weights from a group-level principal component analysis of the shrunk dimension matrix, and rescales each loading by its empirical area-level reliability ratio (RR), automatically reducing the influence of dimensions with lower estimated reliability, and thus providing an alternative to automatic exclusion. RWEB-CWBI is applied within a broader Child Well-Being Index (CWBI) framework, building on participatory CWBI1-CWBI5 specifications estimated on a 10-governorate Takaful-beneficiary sample (n = 8716 households; the 2016 UNICEF sample), and evaluated alongside data-driven weighting, empirical Bayes shrinkage, and machine-learning benchmarking on an independent, nationally representative sample (EFHS-2021; n = 49,936 children, 26 governorates). Results: Participatory CWBI4 and CWBI5 showed the strongest alignment with the available subjective well-being measures. RWEB-CWBI down-weighted the least reliable EFHS dimension (RR = 0.75) automatically, while preserving close agreement with the simpler indices’ governorate rankings (ρ = 0.988–0.989). Gradient boosting improved cross-validated R2 over OLS by 2.5 points (0.798 vs. 0.773), with urban residence dominating permutation importance. The EFHS-UNICEF ranking correlation stayed weak and non-significant under every specification, including RWEB-CWBI (ρ = 0.14–0.19, n = 10, p ≥ 0.60). Conclusion: RWEB-CWBI is presented as a statistically motivated methodological proposal for handling heterogeneous dimension-level precision and availability. The persistence of the weak EFHS-UNICEF correlation across conventional, data-driven, and reliability-weighted specifications indicates that the finding is robust to the choice of weighting method, although contributions from population differences, measurement differences, and survey-design differences cannot be distinguished conclusively. Full article

Objectives: This study evaluated the association of resting heart rate (RHR) with major adverse cardiovascular events (MACEs) and all-cause mortality among adults without prior cardiovascular disease, stratified by baseline burden of cardiovascular risk factors (CVRFs). Methods: This was a prospective cohort study in a random sample of the general population aged ≥18 years in southeastern Spain. RHR was measured using an electrocardiogram. CVRFs (sedentary or light-to-moderate physical activity, body-mass index ≥ 25 kg/m², non-HDL cholesterol ≥ 130 mg/dL, diabetes, hypertension, and smoking) were grouped in three clusters based on whether each subject has 0–2, 3, or ≥4 factors. During a mean 21.5-year follow-up, MACEs were collected and classified as all-cause mortality (outcome-1, n = 193 events) and combined cardiovascular morbidity and mortality (outcome-2, n = 291 events). Cox regression models were adjusted for multiple confounders. Results: The mean age of the participants (n = 1169) was 47.4 years (55.8% women). For every 10 bpm increase in RHR, the fully adjusted hazard ratio was 1.15 (95% CI: 1.03–1.28) for outcome-1 and 1.09 (1.00–1.20) for outcome-2. In the cluster with three CVRFs, the fully adjusted hazard ratios per 10 bpm RHR increase were 1.18 (95% CI 1.04–1.36) for outcome-1 and 1.15 (1.03–1.27) for outcome-2. In the clusters with 0–2 and ≥4 CVRFs, there were no statistically significant differences. Conclusions: RHR was independently associated with both cardiovascular events and all-cause mortality in the 3 CVRF cluster (intermediate cluster in terms of the burden of CVRFs), whose prognostic value may be clinically meaningful. These results highlight the importance of RHR and the comprehensive assessment of CVRFs in the primary prevention setting. Full article

We address the design of global quantum internet topologies that jointly optimise four physical objectives: average end-to-end Werner-state fidelity, entanglement rate, latency and coverage, evaluated with an analytical BDCZ oracle whose path selection is exact under the stated Werner-composition model and whose satellite links respect a single-satellite visibility limit. The search space is heterogeneous (fibre, satellite, free-space optical), comprising $\left({\displaystyle \genfrac{}{}{0pt}{}{100}{2}}\right)=4950$ possible edges over 100 cities; direct per-edge categorical optimisation degenerates. We propose a mixed representation of ten physical design parameters plus one stochastic realisation index (eleven decision variables in total) decoding into a topology via k-nearest-neighbour rules. Seven many-objective algorithms (NSGA-II, NSGA-III, MOEA/D, SMS-EMOA, RVEA, SPEA2, AGE-MOEA-II) are compared at a matched budget over 30 seeds, scored against a shared reference front. NSGA-II attains the highest mean hypervolume ($0.353\pm 0.040$) but is statistically indistinguishable from SPEA2 and AGE-MOEA-II ($0.352$, $0.347$); after Holm correction across all 63 tests, this top group separates significantly from NSGA-III, SMS-EMOA, RVEA and MOEA/D, though NSGA-III and SMS-EMOA remain indistinguishable in HV/IGD (spacing unresolved). NSGA-II’s lead is driven by 6 of its 30 seeds reaching a higher-HV region, a bimodality we report. An eight-variant decoder ablation (NSGA-III) shows fibre is necessary while satellite’s contribution is not detectable, and one classical constructor (a Random Geometric Graph) remains non-dominated; none of the 561 front points connects all 100 cities under the satellite model. On four additional real-city instances (five algorithms), MOEA/D is last throughout; SMS-EMOA/RVEA ranks vary by instance, and NSGA-II/NSGA-III reverses, without significance, twice; the fibre transmittance law is cross-checked against SeQUeNCe (Spearman $\rho =1.0$). The pooled front is released as QI-Bench-Pareto-v1. Full article

Background: Catestatin (CST) is a neuropeptide involved in autonomic regulation, inflammation, and immune responses. This study aimed to compare serum CST levels between patients with fibromyalgia syndrome (FMS) and healthy controls and to examine their associations with pain severity, disease impact, and fibromyalgia-specific quality of life. Methods: Forty women with FMS and 40 healthy women were included. Serum CST levels were measured by enzyme-linked immunosorbent assay. Pain severity, disease impact, and quality of life were assessed using the Visual Analog Scale (VAS), Fibromyalgia Impact Questionnaire (FIQ), and Fibromyalgia Quality of Life Scale (FM-QoLS), respectively. Results: No statistically significant difference in serum CST levels was detected between women with FMS and healthy women in this sample (p = 0.111). CST was inversely correlated with daytime (ρ = −0.510, p = 0.001) and nighttime pain (ρ = −0.364, p = 0.021); after correction for multiple comparisons, only the association with daytime pain remained significant. In multivariable analyses, lower CST levels remained associated with greater daytime pain severity after adjustment for age, Body Mass Index, and symptom duration; an inverse association was also observed for nighttime pain, although findings for nighttime pain were less consistent across analyses. CST was not significantly associated with symptom duration, FIQ, or FM-QoLS scores. Conclusions: Serum CST levels did not differ significantly between women with FMS and healthy women in this sample. Within the FMS group, lower CST levels were associated with greater pain severity, with the most consistent association observed for daytime pain. These findings should be considered exploratory and hypothesis-generating and do not establish CST as a diagnostic, prognostic, or clinically useful biomarker for FMS. Further studies in larger and more diverse populations are needed to confirm these findings and determine their clinical relevance. Full article

Background: Relocating logistics infrastructure under wartime conditions requires more than identifying a theoretically suitable location, as available facilities, costs, and emerging risks must also be considered. This study examines the relocation of an enterprise from the frontline Zaporizhzhia region of Ukraine and aims to develop and substantiate a Hybrid Adaptive Model for Relocating Logistics Infrastructure (HAMRLI). Methods: The methodology combines resilience assessment, spatial modelling, digital facility screening, and expert evaluation. The Normalized Resilience Index (NRI) was calculated using EWM and TOPSIS. HAMRLI integrates the Center of Gravity (COG) method, digital verification of available warehouses, and enterprise-specific multi-criteria assessment. Results: COG identified Zhytomyr as a potential relocation area. Seven warehouse offers were identified, and two were shortlisted for expert evaluation. Weighted assessment selected Offer 6. Sensitivity analysis showed that its preference remained stable across the tested scenarios but changed with substantial shifts in criterion weights. The results support the applicability of HAMRLI for relocation decisions under high uncertainty. Conclusions: This study provides an initial empirical application rather than statistical generalization. Further testing of HAMRLI under different enterprise operating conditions is required. Full article

In data-sparse Central Asian watersheds, machine learning and Geographic Information Systems (GIS) are increasingly applied to hydrological hazard classification. This article compares Random Forest (RF), XGBoost, and Long Short-Term Memory (LSTM) models for daily elevated-discharge classification in the Koksu River basin, Zhetysu Region, Kazakhstan (1614 km², semi-arid, snowmelt- and glacier-influenced climate; 2005–2023), using verified discharge, precipitation, and temperature records from four monitoring stations. The elevated-discharge threshold (80th percentile, ~90.5 m³/s) was computed using only the training period (2005–2017) to avoid temporal data leakage into validation and test periods. Class imbalance, addressed via class weighting, was moderate under this threshold. All models were benchmarked against a naive persistence baseline. Contrary to expectation, the persistence baseline achieved the highest Critical Success Index (CSI = 0.821, 95% block-bootstrap CI [0.725, 0.891]), narrowly ahead of XGBoost (CSI = 0.813, [0.703, 0.897]), Random Forest (CSI = 0.809, [0.691, 0.897]), and LSTM (CSI = 0.763, [0.630, 0.873]); the confidence intervals overlap substantially, indicating no statistically distinguishable advantage of any trained model over simple persistence in this basin. Feature-importance and ablation analyses confirmed that lagged discharge, not precipitation, drove nearly all predictive skill: a discharge-lags-only model performed as well as or better than the complete pipeline, while a meteorology-and-seasonality-only model performed markedly worse (CSI ≈ 0.57–0.59). As a preliminary, exploratory illustration rather than a core result, Gumbel-derived return-period discharges (Q10, Q25, and Q100) were separately translated into illustrative, uncalibrated, DEM-proximity-based inundation extents, a candidate direction for future work rather than an engineering-grade flood-mapping contribution of this study. These results indicate that, in this basin and period, machine learning classifiers provide no clearly demonstrated advantage over simple discharge persistence, underscoring the necessity of routine persistence benchmarking before adopting machine learning approaches for early warning in Central Asian watersheds facing increasing flood risk under climate change. Full article

Background: Estimated pulse wave velocity (ePWV) is a non-invasive marker of arterial stiffness with potential relevance for chronic kidney disease (CKD) risk assessment. This study aimed to investigate the association between ePWV and CKD risk in the US and Chinese populations and to evaluate its discriminative performance using machine learning approaches. Methods: Data were obtained from the National Health and Nutrition Examination Survey (NHANES, 2005–2018, weighted n ≈ 100.9 million) and the China Health and Retirement Longitudinal Study (CHARLS, 2011–2015, n = 21,853). In NHANES, CKD was defined according to the 2021 KDIGO criteria as estimated glomerular filtration rate (eGFR) < 60 mL/min/1.73 m² or a urinary albumin-to-creatinine ratio (ACR) ≥ 30 mg/g; in CHARLS, where urinary albumin was not measured, CKD was defined by the eGFR criterion alone, and this difference in case definition was taken into account when interpreting the results. Logistic regression and restricted cubic spline models were used to examine the association between ePWV and CKD, with subgroup analyses stratified by demographic and clinical characteristics. Multiple machine learning models were developed in NHANES and externally validated in CHARLS; model discrimination was assessed using the area under the receiver operating characteristic curve (AUROC), and feature importance was interpreted using SHapley Additive exPlanations (SHAP) values. Results: Higher ePWV was consistently associated with higher odds of CKD in both cohorts (NHANES: odds ratio [OR] = 1.505 per 1 m/s, 95% confidence interval [CI] = 1.459–1.552; CHARLS: OR = 1.434 per 1 m/s, 95% CI = 1.368–1.503; both p < 0.0001), with dose–response relationships observed. Formal interaction tests confirmed significant effect modification by sex (both cohorts) and by BMI and diabetes (NHANES only). Point estimates were higher in men and in NHANES obese and diabetic subgroups, but interactions across smoking and alcohol strata were not statistically significant. Among the machine learning models evaluated, discrimination was moderate and comparable across algorithms (LightGBM: AUROC = 0.804 in internal validation and 0.793 in external validation), and DeLong tests showed no significant difference between LightGBM and XGBoost (p = 0.0655 and 0.0684, respectively). SHAP analysis identified ePWV as the highest-ranking feature, surpassing uric acid, lipid levels, and diabetes history. Using the Youden index, the optimal ePWV cutoff for identifying CKD was 10.15 m/s in NHANES (sensitivity 0.658, specificity 0.695) and 10.568 m/s in CHARLS (sensitivity 0.658, specificity 0.718). Conclusions: Elevated ePWV is significantly associated with eGFR-defined CKD across the US and Chinese populations studied. These findings support ePWV as a potentially useful marker for CKD risk stratification; however, given the cross-sectional design of both cohorts, its predictive value requires confirmation in prospective studies. It is important to emphasize that no non-invasive calculated metric can replace direct measurement of serum creatinine and urinalysis for identifying individuals at risk of CKD in routine clinical practice. Full article

Urban building color is a key environmental factor shaping visual identity and public spatial experience. However, the relationships among basic color attributes, objective color organization, and public perception remain poorly integrated, and the applicability of cross-regional perception models to local settings requires clearer boundaries. We propose a Color Attribute–Organization–Perception (CAOP) framework that evaluates building color through three progressive layers: basic attributes, objective organization, and public perception. Using Shenyang, China, as a case study, we collected 56,520 street-view images and applied a SegFormer model with ADE20K-trained weights to extract building façades. Evaluation against locally annotated samples yielded a building-class IoU of 0.75, an F1-score of 0.82, and an overall mIoU of 0.71. After quality control, 38,274 valid samples entered statistical analysis and K-means clustering. For cluster-number selection, the elbow method indicated approximately K = 4, while the silhouette coefficient and Calinski–Harabasz index supported K = 2. The Davies–Bouldin index favored larger K values, and equal-weight rank aggregation produced a tie between K = 2 and K = 5. Considering model parsimony and repeated-subsample stability (ARI = 0.944 ± 0.026), we used K = 2 as a coarse-grained typology. Building color in Shenyang showed pronounced spatial heterogeneity and road dependence. The central urban area generally had higher color complexity, effective number of colors, and contrast. Peripheral areas were more stable, although local hotspots remained near transport corridors and functional nodes. Lightness dispersion was strongly associated with color contrast, while dominant color share was positively associated with hierarchy clarity and negatively associated with complexity and effective number of colors. Clustering identified two patterns, “dominant-color control–clear hierarchy” and “multicolor composition–continuous richness”, accounting for 24.8% and 75.2% of the samples, respectively. The absolute Cliff’s δ values for all six perception indicators were below 0.08, and the difference in perceived liveliness was not significant (q = 0.396). These indicators were inferred from images by a Place Pulse 2.0-derived model and were used only for within-sample comparisons. They do not represent direct evaluations by Shenyang residents. The study establishes a continuous analytical pathway from machine-recognized basic color information and objective color organization to model-inferred perception. It supports quantitative diagnosis of urban building color and preliminary screening of candidate street segments, while specific renewal strategies require field investigation and local public evaluation. Full article

Background: Healthcare university students face disruptive sleep schedules and irregular meals caused by busy schedules, multiple activities, and stressful internships. This study aimed to investigate the complex relationships between sleep quality, psychological eating dimensions (cognitive restraint, uncontrolled eating, and emotional eating), accommodation, history of diets and late-night food intake, while evaluating the impact of demographic factors such as age, sex, and residential background. Methods: A cross-sectional survey was conducted among a sample of Romanian healthcare university students (n = 265; 74.3% women). Psychometric evaluation included the Pittsburgh Sleep Quality Index (PSQI) and the Three-Factor Eating Questionnaire (TFEQ-R21). Sociodemographic data (age, gender, environment and accommodation) and information about diets were collected. Late-night food intake was defined as eating after 21:00. Data processing and analysis were performed using IBM Statistical Package for the Social Sciences (SPSS) for Windows, version 26 (SPSS Inc., Chicago, IL, USA). Results: Students exhibit poor global sleep quality, which positively correlated with all TFEQ-R21 subscales. Students with a prior history of following weight-loss diets demonstrated significantly elevated levels of intentional food monitoring and psychological eating disinhibition compared to non-dieters. Urban students feel greater psychological pressure to constantly and consciously control what they eat. Students living in dormitories (Mdn = 2.50, IQR = 1.83) and those living in rented apartments (Mdn = 2.17, IQR = 1.50) reported significantly higher Emotional Eating scores compared to students residing with their parents. Male students demonstrated a substantially higher prevalence of late-night food consumption compared to female students (77.9% vs. 59.4%). Cognitive restraint and female gender protect against nighttime snacking, while uncontrolled eating and poor-quality sleep significantly increase this risk. After adjusting for age, sleep disturbances were positively associated with emotional eating (Path a: B = 0.0967, β = 0.320, p < 0.001, R² = 0.109), which in turn was strongly associated with uncontrolled eating (Path b: B = 0.4621, β = 0.709, p < 0.001). While the model explained 52.16% of the variance in uncontrolled eating, this was driven almost entirely by path b, as the initial contribution of sleep was considerably smaller (Path a: R² = 0.109), yielding a significant standardized indirect association (β = 0.227, 95% BootCI [0.148, 0.309]). Conclusions: Sleep disturbances are linked to uncontrolled eating patterns primarily through their shared indirect association with emotion-driven eating. Prioritizing weight loss over health promotion increases students’ psychological vulnerability. Full article

Maintaining grain production security in drylands requires improvements in land productivity and stability under climatic and resource constraints. Existing studies have often examined production dynamics, yield-related conditions, and per-capita grain availability separately, leaving their long-term relationships across contrasting agro-ecological systems insufficiently understood. Using county-level data for Gansu Province, China, from 2000 to 2024, this study integrated trend and stability analysis, Getis–Ord G_i^* statistics, random forests, and principal component analysis to examine production dynamics, county yield clusters, predictor importance, and the relationship between a production input-scale index (F) and per-capita grain availability (P). Grain production increased by 81.7% and yield by 87.2%, while grain-sown area decreased by 2.9%, indicating yield-led growth. Detrended departures generally narrowed after 2016. High-yield clusters persisted in the Hexi Corridor, whereas a limited cold-spot cluster emerged in the Southern Alpine and Mountainous Region after 2018. Random forest predictive profiles differed among zones, with greater grouped climatic importance in the Hexi Corridor, greater socioeconomic importance on the Loess Plateau, and a more uncertain mixed profile in the Southern Alpine and Mountainous Region. F increased overall but retained its regional hierarchy, and its association with P remained weak to moderate (r = 0.19–0.38). Shortage counties declined from 53 to 19, while surplus counties increased from 17 to 52—most of this transition occurred on the Loess Plateau and involved both lower- and higher-F surplus types. Overall, grain production security in Gansu improved through higher productivity and smaller recent departures from long-term trends. County-level yield remained spatially clustered, and improvements in per-capita grain availability occurred under different input-scale conditions. By integrating productivity, temporal stability, spatial heterogeneity, and the relationship between input scale and per-capita availability, this study provides a more comprehensive understanding of grain production security and an empirical basis for differentiated management in resource-constrained drylands. Full article

Background: Data guiding the choice of energy source for redo pulmonary vein isolation (PVI) after index cryoballoon (CB) PVI are limited. We compared procedural findings, pulmonary vein (PV) reconnection patterns, and reported clinical outcomes after CB-redo versus radiofrequency (RF)-redo ablation in patients with recurrent atrial fibrillation (AF) following an index CB-PVI. Methods: We included a retrospective single-center cohort of 61 consecutive patients with symptomatic recurrent AF after prior CB-PVI who underwent redo ablation between 2019 and 2020 (CB redo, n = 32 vs. RF redo, n = 29). All patients had an index CB PVI (28 mm balloon). The primary reported outcome was freedom from atrial tachyarrhythmia after the blanking period. Results: Mean age was 66 ± 10 years; 41 (67%) were men. Time from index procedure to redo: CB redo 323 ± 72 days vs. RF redo 238 ± 48 days (p < 0.001). All patients had ≥1 PV at redo. Mean reconnected PVs per patient: CB 2.1 ± 1.1 vs. RF 1.7 ± 0.6 (p = 0.08). Right inferior PV reconnection was more frequent after CB redo (69% vs. 41%; p = 0.03). Early recurrence during the 90-day blanking period was CB 8/32 (25.0%) vs. RF 9/29 (31.0%) (p = 0.54). At 12 months, recurrence was CB 7/32 (21.9%) vs. RF 6/29 (20.7%) (unadjusted p = 0.75). Kaplan–Meier log-rank p = 0.88. Adjusted Cox HR (CB vs. RF) = 1.05 (95% CI 0.40–2.76; p = 0.92). Total outcome events = 13. No major periprocedural complications were observed. Conclusions: No statistically significant difference in arrhythmia recurrence between CB redo and RF redo strategies was detected. However, the small sample size, limited event count, non-random treatment selection, and wide statistical uncertainty preclude conclusions regarding equivalence. Full article

Background and Objectives: This study aimed to investigate the association between circulating monocyte subset profiles and carotid artery stenosis (CAS) severity and to examine their relationships with inflammatory and atherosclerosis-related parameters. Materials and Methods: This cross-sectional study included 73 adult patients who underwent carotid Doppler ultrasonography. Participants were classified according to internal CAS severity as <50% (n = 44) or ≥50% (n = 29). Monocyte subsets were analyzed using flow cytometry and categorized as classical (CD14++CD16−), intermediate (CD14++CD16+), and non-classical (CD14+CD16++) monocytes. Serum MCP-1 concentrations were measured using an enzyme-linked immunosorbent assay. Clinical characteristics, biochemical parameters, inflammatory indices, and carotid intima–media thickness (cIMT) were compared between the groups. Multivariate logistic regression analyses were performed to identify independent associations with significant stenosis. Results: Patients with CAS ≥50% exhibited significantly higher classical monocyte percentages and lower non-classical monocyte percentages than those with CAS < 50% (p = 0.044 and p = 0.027, respectively). Intermediate monocyte percentages did not differ significantly between the groups. Significant stenosis was also associated with a higher white blood cell count, neutrophil count, systemic inflammatory response index, fibrinogen, and HbA1c levels. Non-classical monocyte percentages showed a significant inverse correlation with cIMT (r = −0.320, p = 0.006). In a multivariable model adjusted for age, sex, and systolic blood pressure, lower non-classical monocyte percentage was associated with significant CAS (OR 0.872, 95% CI 0.765–0.994; p = 0.040). However, this association was no longer statistically significant after further adjustment for fibrinogen, neutrophil count, and HbA1c, whereas fibrinogen remained independently associated with significant CAS. Conclusions: Lower circulating non-classical monocyte percentages were associated with significant CAS and inversely correlated with cIMT and inflammatory markers. However, the attenuation of this association after adjusting for inflammatory parameters suggests that monocyte subset distribution should be interpreted within the broader inflammatory context that accompanies advanced carotid atherosclerosis. Full article

The rapid expansion of smart agriculture and precision aquaculture necessitates continuous, high-resolution environmental monitoring to optimize ecosystem stability and prevent catastrophic biomass loss. Conventional Internet of Things (IoT) solutions routinely treat atmospheric and aquatic parameters as isolated domains, neglecting the dynamic physicochemical coupling occurring across the air–water boundary layer. To overcome this domain fragmentation, this study presents an integrated edge-cloud telemetry architecture designed for concurrent, multi-domain environmental monitoring and cross-domain spatial-statistical analysis. The proposed framework employs low-cost, multi-sensor edge nodes integrated with Narrowband IoT (NB-IoT) cellular communication, achieving high signal penetration, energy-efficient operation, and direct base-station connectivity without local gateway dependencies. The system continuously acquires atmospheric parameters (temperature, relative humidity, particulate matter ${\mathrm{PM}}_{1.0}$/${\mathrm{PM}}_{2.5}$/${\mathrm{PM}}_{10}$, ozone ${\mathrm{O}}_3$, total volatile organic compounds TVOC, equivalent ${\mathrm{CO}}_2$, Air Quality Index AQI, and Ultraviolet Index UVI) alongside aquatic indicators (water temperature, pH, dissolved oxygen DO, electrical conductivity EC, and turbidity). Telemetry is streamed via Message Queuing Telemetry Transport (MQTT) to a centralized MySQL cloud database, providing real-time Grafana dashboards, spatial Inverse Distance Weighting (IDW) mapping, and automated multi-channel alerting via LINE Notify and email. The architecture was deployed and validated across the Tunghai University aquatic research facility, capturing n = 14,400 synchronized 1-min observations (with an initial raw Packet Delivery Rate of $99.24\%$). Statistical evaluations accounting for temporal autocorrelation ($N_{\mathrm{eff}}\approx 892$) and False Discovery Rate correction revealed significant cross-domain associations ($p_{\mathrm{adj}}<0.001$), notably an inverse association ($r=-0.782$, $\rho =-0.794$, $\tau =-0.612$) between ambient air temperature and aquatic dissolved oxygen physically consistent with Henry’s Law of gas solubility, an inverse association ($r=-0.763$) between atmospheric humidity and dissolved oxygen, and a positive association ($r=+0.789$, $\rho =+0.812$) between humidity and aquatic turbidity. First-order partial correlation analysis ($r_{T_a,\mathrm{DO}\mid T_w}=-0.172$) confirmed that water temperature serves as the primary thermal mediator of dissolved oxygen depletion. By synergizing low-power NB-IoT telemetry with robust multi-domain analytics, this work provides a scalable, empirical foundation for transitioning from reactive threshold alerting to proactive predictive management in precision aquaculture. Full article

Background/Objectives: As dietary and environmental exposures change, interacting with genetic susceptibility, the prevalence of thyroid function abnormality and subclinical thyroid dysfunction in children is rising, yet systematic research in this population remains scarce. Methods: From 13 districts of Tianjin, China, all characterized by adequate iodine levels, 997 children between the ages of 8–10 years were recruited using a school-based sampling approach. Peripheral venous blood samples were drawn for genotyping analysis of two single nucleotide polymorphisms (SNPs): thyroid stimulating hormone receptor (TSHR) rs2268458 and NK2 homeobox 1 (NKX2-1) rs2076735 using the Sequenom MassARRAY platform. In addition, data on 31 non-genetic factors, including urinary iodine concentration (UIC), were collected. Restricted cubic spline (RCS) models were used to examine the non-linear associations between UIC and thyroid abnormalities. Multivariable Poisson regression was applied to identify factors associated with thyroid outcomes. Results: The overall prevalence of thyroid function abnormality in the study population was 17.35%, with detection rates of 3.51% for subclinical hyperthyroidism and 2.21% for subclinical hypothyroidism. After adjusting for age, sex, body mass index z-score (BMI-z-score), district of residence, and recruitment year, RCS models revealed significant U-shaped non-linear associations between UIC and both free triiodothyronine (FT₃) abnormality (P_overall = 0.003, P_nonlinear < 0.001) and overall thyroid function abnormality (P_overall = 0.042, P_nonlinear = 0.029). In multivariable analysis, after Bonferroni correction within prespecified hypothesis families, family history of thyroid disease in first-degree relatives remained significantly associated with subclinical hyperthyroidism (adjusted p = 0.015), and UIC < 100 μg/L remained significantly associated with overall thyroid function abnormality (adjusted p = 0.036). In addition, district of residence was associated with subclinical hypothyroidism after correction (adjusted p = 0.009). Stratified analyses revealed potential subgroup-specific effects. Children with the NKX2-1 rs2076735 TT + TC genotype and UIC < 100 μg/L had a higher prevalence of thyroid function abnormality compared with the reference group (UIC 100–299 μg/L) (p = 0.031, PR = 3.093, 95% CI: 1.108, 8.636). Frequent consumption of kelp or laver soup was associated with a higher prevalence of subclinical hyperthyroidism among children with the NKX2-1 rs2076735 CC genotype or the TSHR rs2268458 TT genotype (p = 0.049, PR = 3.636, 95% CI: 1.006, 13.140; p = 0.023, PR = 4.814, 95% CI: 1.245, 18.610, respectively). Among children with the NKX2-1 rs2076735 CC genotype, those with a family history of thyroid disease had a higher prevalence of subclinical hyperthyroidism (p = 0.029, PR = 4.114, 95% CI: 1.152, 14.688). After Benjamini–Hochberg false discovery rate correction, none of the subgroup-specific associations remained statistically significant (adjusted p-values: 0.058–0.065). Conclusions: The prevalence of thyroid function abnormality and subclinical thyroid dysfunction was relatively high among school-aged children in this study population from Tianjin, China. After adjustment for covariates and correction for multiple comparisons, family history of thyroid disease, UIC < 100 μg/L, and district of residence remained significantly associated with subclinical hyperthyroidism, overall thyroid function abnormality, and subclinical hypothyroidism, respectively. A U-shaped association was observed between UIC and thyroid health, highlighting the importance of maintaining adequate iodine nutrition. However, stratified analyses suggested potential subgroup-specific associations that require validation in larger, independent cohorts. Full article