Search Results (374)

Magnesium oxychloride (MOA) adhesive plywood represents a novel inorganic matrix panel technology that eliminates organic volatile compounds from the adhesive system and avoids high-temperature hot pressing, potentially offering significant carbon footprint advantages. This study presents a comparative life cycle carbon footprint assessment of conventional urea–formaldehyde (UF) plywood and MOA plywood manufactured in China, using 1 m³ of a finished panel as the functional unit under a cradle-to-grave system boundary, comprising the production stage (Modules A1–A3)—explicitly including forestry operations (silviculture, felling, extraction/forwarding, loading and log haulage) and veneer manufacture within Module A1, now reported as a disaggregated inventory and delimited in a system boundary diagram—and the end-of-life stage (Modules C2–C4), evaluated across three end-of-life (EOL) scenarios: incineration, landfill, and mechanical recycling. Foreground data (process energy, adhesive formulation, transport distances) are metered/primary data collected over a full production year at a single large-scale plywood plant in Suqian, Jiangsu; background data are from ecoinvent v3.9.1 (cut-off), characterised with IPCC AR6 GWP100. Results indicate that MOA plywood generates approximately 253 kg CO₂-e/m³ at the production stage (A1–A3), compared with 301 kg CO₂-e/m³ for UF plywood, a reduction of 15.8% (47.5 kg CO₂-e/m³). Contribution analysis attributes virtually the entire gap to process energy (steam 65.7%, electricity 34.3%), while adhesive raw materials and inbound transport cancel to within rounding, demonstrating that the advantage is a process energy rather than a green chemistry phenomenon. A parameter-specific one-at-a-time analysis and a 200,000-run Monte Carlo simulation with triangular distributions show no reversal of the UF–MOA ranking in any of the 200,000 realisations within the adopted uncertainty ranges, with an approximately 56 kg CO₂-e/m³ median advantage (5th–95th percentile of about 31–85). Under EOL incineration, MOA plywood retains a substantial advantage even after the newly quantified burden of flue gas HCl neutralisation (13.3 kg CO₂-e/m³) and inorganic residue management (0.9 kg CO₂-e/m³) arising from the chloride content of the Sorel cement binder are charged to the MOA system. Under landfill, both products behave similarly, as wood carbon dynamics dominate. A break-even analysis shows that the service life of MOA plywood would have to fall below 25.3 years (against a 30-year reference) for its cradle-to-gate advantage to be erased. These findings clarify the lifecycle trade-offs of inorganic adhesive plywood and provide actionable data for environmental product declarations and procurement frameworks. Full article

Coupling-coordination degree (CCD) indices are often interpreted as evidence that urban systems are developing in a mutually supportive manner. The standard formula, however, combines similarity between subsystem scores with their average level. This article evaluates those two components against the following external outcome: municipal environmental services. A city panel for China in 2002–2024 combines broadband and mobile adoption, urban road provision, licensed internet data-center records, and seven indicators of water, gas, drainage, sewage, waste, and urban greening. The preferred sample contains 6094 observations for 275 cities in 28 provinces. We estimate city fixed-effect models with province-by-year fixed effects and report province-clustered, two-way-clustered, and 9999-repetition wild-cluster-bootstrap inference. In the baseline rank-based construction, a one-standard-deviation increase in relative digital-transport alignment is associated with a 0.046-standard-deviation increase in the environmental-service index (wild-bootstrap p = 0.042), whereas the portfolio-level coefficient is 0.191 (p < 0.001). The alignment estimate is concentrated in water and gas access and is not robust to complete-component outcomes, PCA or entropy weighting, logarithmic standardization, road density, or lags beyond one year. Portfolio level remains positive across these tests, although lead and reverse-direction estimates preclude causal interpretation. The findings show why infrastructure scale, relative configuration, and realized service outcomes should be monitored separately. For SDGs 9 and 11, city governments should target documented service bottlenecks and operating capacity rather than maximize a composite coordination score. Full article

Background/Objectives: Lifestyle modification is central to non-alcoholic fatty liver disease, now termed metabolic dysfunction-associated steatotic liver disease (NAFLD/MASLD), yet comparable health-promoting lifestyle (HPL) data for patients and family members are limited. This study compared two independent samples and examined psychosocial correlates. Methods: Two convenience samples recruited at one tertiary hospital were analyzed: 305 adults with NAFLD/MASLD and 299 adult family members of affected patients. A self-administered electronic questionnaire comprised the Health-Promoting Lifestyle Profile II (HPLP-II), the Self-Rated Abilities for Health Practices scale, autonomous-motivation items from the Treatment Self-Regulation Questionnaire, the Medical Outcomes Study Social Support Survey, and sociodemographic items. Group comparisons used parametric and non-parametric tests. HPL correlates were examined using complete-case regression, HC3 inference, and rank-based sensitivity analysis. Cross-sectional indirect-association decompositions used 5000 bootstrap resamples. Results: HPLP-II scores were 102.2 ± 17.5 in patients and 104.2 ± 17.4 in family members (p = 0.171; Mann–Whitney p = 0.166); the adjusted patient-minus-family difference was −1.14 (HC3 95% CI −3.89 to 1.60; p = 0.413). Physical activity was the lowest-scoring dimension. Self-efficacy was the most robust correlate in both samples; social support was associated in the primary models but weakened under rank transformation in family members. Group-by-correlate interactions were not significant. Exploratory indirect associations through self-efficacy were 0.355 (95% bootstrap CI 0.234–0.512) in patients and 0.163 (0.071–0.287) in family members; reverse-order models were also non-zero. Conclusions: The independent unmatched samples reported similar moderate, physically inactive lifestyles. The results identify associations, not shared-household effects or causal mechanisms; objectively characterized, dyad-matched longitudinal studies are needed. Full article

Fuzzy multi-criteria decision-making is important for technology assessment when expert judgments contain uncertainty, hesitation, and inconsistent evidence. This study develops a T-Spherical Fuzzy-Valued Neutrosophic Set (T-SFVNS)-based MEREC-EDAS framework for evaluating low-carbon cooling and energy-management technologies for data centers. Expert linguistic assessments are represented by T-Spherical Fuzzy-Valued Neutrosophic Numbers and aggregated before a score function is used at the explicit scalarization boundary. Standard MEREC then derives objective criterion weights from criterion-removal effects, and standard EDAS ranks alternatives by their positive and negative distances from the average score profile. The application evaluates nine technologies against ten criteria using assessments from thirty domain specialists. The corrected MEREC calculation assigns the greatest weights to carbon reduction potential (0.127), electricity demand reduction (0.125), maintenance complexity (0.124), operational cost efficiency (0.123), and cooling efficiency (0.123). The final ranking is Direct-to-Chip Liquid Cooling, Liquid Immersion Cooling, AI-Enabled Energy Management, Water-Side Free Cooling, Free-Air Cooling, Rear-Door Heat Exchanger Cooling, Hot/Cold Aisle Containment, Renewable-Powered Cooling, and Thermal Storage-Assisted Cooling. Weight perturbation, q-parameter, leave-one-expert-out, alternative-deletion, dominated-alternative, and multi-method comparisons show that the leading tier is robust, although the exact order of the two liquid-cooling technologies is sensitive in some scenarios. The findings provide a transparent and reproducible decision-support basis while explicitly acknowledging the information compression and rank-reversal limitations of score-based MCDM. Full article

Modern intrusion detection systems (IDSs) are often evaluated under matched training and test conditions, whereas deployment environments involve changing traffic distributions, heterogeneous feature-generation pipelines, and shifting attack prevalence. This study investigates benchmark-shift-aware intrusion detection through harmonized cross-dataset evaluation of HIKARI-2021, CICIDS2017, and a CICIoT2023 sample subset. Two payload-free feature spaces are constructed: Rich-64 for detailed HIKARI-2021/CICIDS2017 analysis and Minimal-13 for three-way comparison. Using XGBoost, a supervised Transformer, and a masked-feature self-supervised Transformer, we evaluate discrimination, calibration, threshold transfer, alert-budget behavior, chronological robustness, and score-orientation stability. Across five in-domain XGBoost settings, observed false-positive rates were 4.94–5.40%, and F1-scores ranged from 0.507 to 0.995. Under strict Rich-64 HIKARI-2021-to-CICIDS2017 transfer, all models had zero recall at source-derived thresholds, with two showing inverted score orientation. In the reverse direction, XGBoost reached an 18.9% target false-positive rate, while a nominal 5% target-side alert budget yielded F1 = 0.112. Chronological evaluation further showed that improved ranking metrics did not guarantee stable validation-derived operating behavior. The study provides a reproducible diagnostic framework for evaluating IDS robustness under evolving benchmark conditions. Full article

Background and Objectives: Wearable health technologies have become increasingly important in the remote management of cardiovascular diseases (CVDs); however, their successful implementation depends not only on technical performance but also on patient usability and technology acceptance. This study aimed to evaluate the perceived usability and technology acceptance of a wearable monitoring system among patients with CVDs and to investigate whether demographic and clinical characteristics influenced these outcomes. Materials and Methods: A cross-sectional observational study was conducted among 60 patients with CVDs enrolled in a six-month wearable monitoring program at the Medical Rehabilitation Outpatient Clinic of the Avram Iancu Clinical Hospital, Oradea, Romania. Participants used a Garmin vívosmart^® 5 fitness tracker to continuously monitor physiological and behavioral parameters. At the end of the monitoring period, perceived ease of use (PEU) was assessed using the System Usability Scale (SUS), while technology acceptance was evaluated using a Technology Acceptance Model (TAM)-based questionnaire. Descriptive statistics, reliability analysis, Spearman’s rank correlation, and multiple linear regression analyses were performed. Results: The wearable monitoring system demonstrated high PEU, with a median SUS score of 82.5 (IQR = 23.1) and a mean score of 75.5 ± 17.6. Overall, 75.0% of participants rated the system as having good or excellent usability. The SUS questionnaire demonstrated acceptable internal consistency (Cronbach’s α = 0.730; McDonald’s ω = 0.741). Technology acceptance was generally favorable, with an overall median TAM-based score of 1.33 (IQR = 0.78). Age and comorbidity burden were not associated with PEU, and no participant characteristics independently predicted SUS scores. Although the overall regression model was not statistically significant, age showed a statistically significant association with the overall TAM-based score (β = 0.328, p = 0.037). Significant positive correlations were observed between PU, self-efficacy (SE), and reverse-scored technology anxiety (TA) measure (p < 0.001). Conclusions: Patients with CVDs reported high PEU and favorable acceptance of wearable monitoring technology. While usability appeared independent of demographic and clinical characteristics, technology acceptance showed an exploratory association with age, although the overall regression model was not statistically significant. These findings support the integration of wearable monitoring systems into routine cardiovascular care and highlight the importance of patient-centered implementation strategies to promote long-term engagement. Full article

Background: In recent decades, the incidence of colorectal cancer (CRC) has been rising worldwide. CRC ranks second in cancer-related mortality. The identification of reliable biomarkers for early diagnosis and prognosis prediction, along with a deeper understanding of the underlying molecular events, holds substantial promise for improving patient outcomes. The tissue inhibitor of the metalloproteinase 1 (TIMP1) gene is overexpressed in various gastrointestinal malignancies and contributes to tumor progression. However, its role in regulating the CRC tumor immune microenvironment (TIME) and its potential as a clinically actionable prognostic biomarker remain unclear. Methods: To probe how TIMP1 acts as a prognosis-related candidate biomarker in colorectal carcinoma, TCGA-derived datasets were adopted to conduct Kaplan–Meier survival assessment. We also investigated the connection between the expression abundance of TIMP1 and the infiltration of immune populations and intratumoral lymphocytes; furthermore, immune checkpoint-related genes were systematically assessed across multiple tumor types via the TISIDB and TIMER2.0 platforms, with particular emphasis on CRC. We adopted the ESTIMATE scoring system to figure out how TIMP1 gene expression correlates with the phenotypic properties of the colorectal-cancer TIME. We relied on the limma toolkit for the screening of differential transcripts from high-TIMP1 and low-TIMP1 cohorts. Enrichment assessments covering Gene Ontology terms and Kyoto Encyclopedia of Genes and Genomes entries were then carried out to predict the potential biological pathways associated with TIMP1. We constructed the protein–protein interaction map for TIMP1-interacting partners via the STRING repository. To further explore TIMP1-correlated genes, we performed Venn diagram intersection analysis combined with Spearman’s correlation test. Finally, quantitative reverse-transcription PCR was then implemented to detect TIMP1 messenger-RNA abundance inside the RKO colorectal carcinoma cell line as well as normal colonic epithelial CCD-18Co cells, which offered in vitro experimental verification for our bioinformatic outcomes. Results: According to outcome data, TIMP1 transcripts were markedly up-regulated in CRC specimens and cell lines relative to normal samples. Elevated TIMP1 expression served as a poor-prognosis indicator for overall survival (hazard ratio [HR] = 0.43, 95% confidence interval [CI] = 0.29–0.64, p < 0.001) and disease-specific survival (HR = 0.39, 95% CI = 0.22–0.68, p = 0.001) among colorectal-carcinoma patients. TIMP1-high and TIMP1-low groups exhibited notable differences in immune cell infiltration (CD8⁺ T, macrophage, mast, neutrophil, B, monocyte, dendritic, and CD4⁺ T cells). TIMP1 expression was also significantly correlated with tumor-infiltrating lymphocytes, key immune checkpoint genes (e.g., CD274 [PD-L1] and CTLA4), and immunomodulatory chemokines (e.g., CCL3 and CCL5). Twelve TIMP1-interacting DEGs were selected: COL5A1, FN1, PRG4, and a cluster of nine MMPs (MMP1/2/3/7/8/9/11/13/14), all of which showed significant positive correlations with TIMP1 (r = 0.31–0.63, all p < 0.001). Conclusions: TIMP1 expression correlates with features of the tumor immune microenvironment and extracellular matrix remodeling in CRC, suggesting that TIMP1 shows potential as a candidate biomarker. However, its potential as a therapeutic target warrants further experimental investigation. Full article

The large-scale integration of photovoltaic generation into distribution grids has introduced significant operational challenges, including voltage excursions, reverse power flows, and increased variability. Battery energy storage systems (BESSs) offer a versatile solution by providing coordinated active- and reactive-power support. However, their scheduling in active distribution networks is challenging because of the non-convex alternating-current (AC) power-flow equations, the nondifferentiability of battery-degradation modeling, and uncertainty in renewable generation and demand. This paper proposes a two-stage methodology for the day-ahead operation of BESSs in ADNs. In the first stage, parallel particle swarm optimization (PPSO) determines the hourly active- and reactive-power schedules of the BESS units. In the second stage, a matrix-based multi-period AC power flow based on successive approximations evaluates the schedules and verifies voltage, thermal, converter-capability, and state-of-charge (SoC) constraints. A rainflow-counting degradation model is incorporated into the objective function to account for cycling and calendar aging costs. The methodology is assessed through ablation analyses comparing active-power-only and coordinated P–Q dispatches, degradation-unaware and degradation-aware scheduling, and serial and parallel PSO implementations. It is validated on modified 33-, 69-, and 136-node systems under deterministic and uncertainty-based operating conditions, including 100 demand and PV-generation scenarios. PPSO is compared with parallel versions of the adaptive Jaya algorithm (AJAYA), genetic algorithm (GA), multi-verse optimizer (MVO), salp swarm algorithm (SSA), grey wolf optimizer (GWO), and vortex search algorithm (VSA), using operating-cost reduction, computational time, solution variability, feasibility indicators, BESS lifetime, and weekly cost analysis. Additionally, exact one-sided Wilcoxon signed-rank tests with Holm adjustment are used to assess the statistical significance of the economic differences between PPSO and the benchmark methods. Results show that PPSO provides the lowest or most competitive operating costs and the shortest computational time in the evaluated cases, while all network and storage constraints remain satisfied. Full article

BP decoding of BATS codes may stop when no residual batch satisfies the full-row-rank condition. To resume BP decoding, this paper proposes an Important-Packet-Guided Left-Nullspace Rank-Completion (LNRC) method. LNRC first identifies the unrecovered source packet that connects to the largest number of undecoded batches, denotes it as the Important Packet, and uses it as a guidance packet to locate the undecoded batches containing it as repair candidates. For a selected batch with rank deficit one, the destination computes a nonzero left-null vector and selects a local repair coordinate that provides the missing independent direction. The destination sends the corresponding global source-packet index and finite-field coefficient through a reliable reverse feedback-control link, and the source returns the scaled repair packet through a reliable forward repair-data link. The associated completion column increases the target residual transfer-matrix rank by one and makes the batch BP-decodable. Thus, LNRC exploits the column-space structure of the target undecoded batch to select the repair coordinate, rather than selecting the Important Packet solely by the number of connected undecoded batches. Under equal encoding redundancy, simulations show that LNRC achieves a lower packet error rate (PER) compared with conventional Important Packet feedback, with average relative PER reductions of approximately 0.40–12.17% across the evaluated settings. Full article

This study directly compares a photovoltaic (PV)-powered vapor-compression chiller with a solar-thermal-driven absorption chiller for localized cooling of the tomato crop zone in a 1536 m² smart greenhouse under a hot-arid climate. The principal contribution is a controlled system-level comparison of two solar-cooling pathways under the same greenhouse load, solar-aperture area, terminal equipment, rated cooling capacity, and crop-zone temperature-control constraints. The previously validated greenhouse model was transitioned from EnergyPlus 8.9 to Version 23.1, after which the two alternative plants were connected to the same base model. Base-case annual simulations produced nearly identical chiller cooling energy (1669.3 and 1668.9 MWh) and was only 4 and 5 h above 28 °C. The PV-powered system required 101.6 MWh of net grid electricity, whereas the absorption system used 202.3 MWh of electricity and 253.2 MWh of natural gas and achieved an 84.23% solar fraction. Static operational primary energy was 331.2 and 912.7 MWhPE, respectively; HSDH28 was 0.50 and 0.81 °C·h; and peak grid import was 113.46 and 63.61 kW. The absorption case additionally required 10,103.6 m³/yr of cooling-tower makeup water. Storage/EMS sensitivity changed the absorption solar fraction from 58.17% to 88.30% and natural-gas use from 187.7 to 674.0 MWh/yr without materially changing cooling service. Matched 50–100 W/m² daytime latent-load sensitivity increased annual cooling by 14.7–28.8%. At the 100 W/m² bound, HSDH28 increased to 49.32 °C·h for PV and 8.06 °C·h for absorption, while the principal energy–infrastructure trade-off remained: static primary energy was 712.4 versus 1354.2 MWhPE and peak grid import was 137.46 versus 63.96 kW. A bounded hourly primary-energy-factor stress test did not reverse the technology ranking, and balanced TOPSIS scores were 0.766 for PV and 0.234 for absorption. The results show that PV vapor compression minimizes operational primary energy and cooling-water use, whereas solar-thermal absorption reduces electrical peak demand and shows greater thermal-control resilience at the highest tested latent-load bound. Full article

‘Wellness-at-sea’ is an integral part of the cruise holiday service bundle. Marketed within an image of experiential diversity within a safe, controlled environment, it features medical centers, spa facilities and restoration-focused itineraries. Nevertheless, epidemiologically speaking, cruise ships rank amongst the riskiest transmission environments in tourism. This perspective paper proposes a typology of wellness cruising along two axes (i.e., offer scope: themed voyages versus onboard amenities and promotion focus: borrowed credibility versus narrative ‘storyscaping’) and uses it to develop the ‘wellness-risk paradox’, a boundary case for health-tourism literature. Three testable propositions emerge: reputational risk exposure increases with the offer’s wellness centrality; narrative-based promotion is more susceptible than credibility-based promotion and a quadrant-adjusted health-assurance scheme is more effective than current inspection standards. The argument draws on the 2026 Andes hantavirus outbreak aboard the MV Hondius (three deaths among thirteen cases), the 2020 Diamond Princess outbreak, and a decade of official outbreak surveillance, reporting an increase in gastrointestinal outbreaks from 0.34 to 0.62 per million passengers between 2019 and 2025 (rate ratio 1.84, 95% CI 0.87–3.86), which reverses the pre-pandemic downward trend although annual counts remain too small for the change to reach conventional statistical significance. Sanitation-inspection compliance cannot reliably predict outbreaks, nor does it facilitate trust. Four domains of action are proposed: continuous air-quality monitoring, wastewater surveillance, behavioral risk modeling and jurisdictional coordination. Full article

Interval censoring commonly arises in clinical trials, screening studies, and longitudinal medical investigations in which event status is assessed only at scheduled examination times. Rank-based procedures provide flexible tools for comparing interval-censored (IC) event-time distributions, but inference is usually based on first-order normal approximations that may be inaccurate in small or moderately sized samples and under substantial censoring. We develop a saddlepoint approximation (SPA) to the conditional permutation distribution of a linear rank statistic derived from the proportional reversed-hazard model with IC data. Conditional on the observed group size, the permutation distribution is represented through a bivariate cumulant generating function, and Skovgaard’s approximation is used to obtain computationally efficient tail probabilities without exhaustive permutation enumeration. The finite-sample performance of the proposed method is evaluated under log-normal, Weibull, and Gompertz event-time distributions and under monitoring schemes producing predominantly left, interval, or right-censored observations. Monte Carlo (MC) permutation p-values based on ${10}^6$ random permutations are used as a numerical benchmark (not the exact permutation distribution). Across the evaluated simulation scenarios, the SPA generally produces p-values that are closer to the MC permutation benchmark than those obtained from the standard normal approximation (NA). Applications to lung tumor, HIV drug-resistance, and breast-cosmesis data illustrate the relevance of the method to biomedical event-time studies. The proposed approximation provides an accurate and computationally efficient approach to rank-based inference for IC medical data. Full article

Post-2020 changes in cross-country log GDP per capita dispersion are directionally consistent across macroeconomic data systems but concentrated in a few country trajectories. Using the IMF WEO 1980–2024 baseline, a provisional 2025 extension, and a 167-country WEO–WDI–PWT panel for 2000–2023, the analysis compares sigma, level inequality, weighting, contributions, mobility, and horizon. Sigma rises by 0.018–0.024 across the sources. Paired country-resampling intervals support sign stability, not broad-based widening. The top five contributors account for 60.3–66.9% of the variance increase and the top ten for 86.6–96.3%; positive residuals remain after joint exclusion. The WEO 2020–2024 increase was exceeded by only two of the 36 preceding four-year changes, although sigma in 2024 remained below its 2000 level. Gini and Theil decline or remain approximately flat, while fixed-quartile separation and persistent ranks locate the change within a durable hierarchy. The contribution is an integrated diagnostic of scale, weighting, concentration, persistence, and horizon; it neither measures global interpersonal inequality nor establishes a structural reversal of long-run convergence. Full article

Assessing climate performance through emission-centric metrics provides an incomplete picture of countries’ progress toward integrated climate objectives. This study proposes the Climate Integrated Performance Index (CIPI), a multidimensional and explainable composite indicator for 27 European countries during 2015–2023. CIPI integrates six thematic dimensions: emissions, energy systems, mitigation capacity, transport, agriculture, and waste–land-use interactions, using robust normalization, a policy-informed weighting framework, and formal statistical validation. Based on 243 country–year observations, the results indicate that CIPI is non-redundant. Pearson correlations reveal strong positive associations with the Energy Index (r = 0.899) and Mitigation Index (r = 0.894), alongside a significant negative association with the Agriculture Index (r = −0.659), highlighting sectoral trade-offs. Variance decomposition further shows that energy and mitigation dimensions jointly account for approximately 87% of explained variance, whereas agriculture exerts a systematic counterbalancing influence. To support structural interpretation, an explainable machine learning framework combining XGBoost and SHAP was implemented as a diagnostic layer. Renewable-energy capacity emerged as the dominant structural driver of integrated climate performance, and SHAP-based analyses revealed a nonlinear threshold effect, with positive contributions accelerating beyond a normalized renewable-capacity level of approximately 0.58 (95% bootstrap confidence interval: 0.54–0.62), particularly under low fossil-fuel dependency conditions. Because the machine learning models use indicators that also contribute to index construction, the results are interpreted as evidence of structural consistency and diagnostic interpretability rather than independent predictive discovery. To address this limitation, repeated cross-validation, subsample validation, benchmark comparisons, and weighting-sensitivity analyses were conducted. Ranking robustness remained high under alternative weighting schemes (Spearman ρ > 0.96), while comparison with an emission-centric benchmark demonstrated substantial rank reversals, indicating that broader sectoral and policy dimensions influence climate-performance assessment. Overall, CIPI functions not only as a benchmarking tool but also as a transparent diagnostic framework for identifying structural trade-offs, nonlinear relationships, and policy-relevant climate-transition dynamics. Full article

Background/Objectives: Glioblastoma (GBM) is the most lethal primary brain malignancy in adults, with a median overall survival of approximately 15 months. Temozolomide (TMZ) resistance develops in virtually all patients, and no second-line regimen has improved outcomes over the past two decades. The DNA methyltransferase inhibitor decitabine (DAC) has attracted interest as a chemosensitizer, but whether it directly reverses the TMZ-resistance transcriptome or operates through distinct, complementary mechanisms has not been tested at multi-omics resolution. Methods: We performed an integrative six-layer multi-omics analysis across five public GEO datasets (bulk RNA-seq, EPIC 850K methylation, and 21,676 single cells) re-purposed from studies conducted for unrelated aims, formally tested DAC-mediated reversal of the TMZ-resistance transcriptome across 11,707 genes, mapped pharmacogenomic targets with DGIdb v5, and built an exploratory, hypothesis-generating 11-gene prognostic model internally validated in TCGA-GBM (n = 166) and externally tested in the independent CPTAC-GBM cohort (n = 96). Results: DAC reprogrammed transcription across 1114–1882 differentially expressed genes per cohort and reactivated 146 direct epigenetic targets, identifying INPP5D/SHIP1 as the top-ranked direct epigenetic-reactivation target. Genome-wide reversal analysis across 11,707 co-detected genes showed a negligible effect (Spearman ρ = 0.073), but single-cell analysis revealed significant per-cell attenuation of MES-like and stem-like programs (Δ = −0.071 and −0.135, respectively; both p < 0.001). The 11-gene risk model achieved a Harrell’s C-index of 0.706 (apparent); after correcting for the two-stage gene selection with a full-pipeline bootstrap, the optimism-corrected C-index was 0.63, and external validation in an independent cohort (CPTAC-GBM, n = 96) showed only near-chance discrimination (C-index 0.55), indicating that the signature does not generalize and is exploratory. Pharmacogenomic mapping yielded 734 unique therapeutic agents (230 FDA-approved) across 69 druggable targets after excluding AR. Most of these agents are not GBM-directed, so this catalog-level mapping is hypothesis-generating rather than a set of therapeutic recommendations. Conclusions: DAC does not broadly reverse the TMZ-resistant transcriptome but acts through three complementary mechanisms: epigenetic reactivation of INPP5D/SHIP1, cancer-testis-antigen and type I interferon induction, and per-cell attenuation of mesenchymal–stem-like transcriptional intensity, supporting hypotheses for rationally designed DAC-based combination therapy in TMZ-resistant GBM. Full article