Search Results (1,785)

Detecting surface cracks on sugarcane is a critical step in ensuring product quality control, with detection precision directly impacting raw material screening efficiency and economic benefits in the sugar industry. Traditional methods face three core challenges: (1) complex background interference complicates texture feature extraction; (2) variable crack scales limit models’ cross-scale feature generalization capabilities; and (3) high computational complexity hinders deployment on edge devices. To address these issues, this study proposes a lightweight sugarcane surface crack detection model, SCS-YOLO (Surface Cracks on Sugarcane-YOLO), based on the YOLOv10 architecture. This model incorporates three key technical innovations. First, the designed RFAC2f module (Receptive-Field Attentive CSP Bottleneck with Dual Convolution) significantly enhances feature representation capabilities in complex backgrounds through dynamic receptive field modeling and multi-branch feature processing/fusion mechanisms. Second, the proposed DSA module (Dynamic SimAM Attention) achieves adaptive spatial optimization of cross-layer crack features by integrating dynamic weight allocation strategies with parameter-free spatial attention mechanisms. Finally, the DyHead detection head employs a dynamic feature optimization mechanism to reduce parameter count and computational complexity. Experiments demonstrate that on the Sugarcane Crack Dataset v3.1, compared to the baseline model YOLOv10, our model achieves mAP50:95 to 71.8% (up 2.1%). Simultaneously, it achieves significant reductions in parameter count (down 19.67%) and computational load (down 11.76%), while boosting FPS to 122 to meet real-time detection requirements. Considering the multiple dimensions of precision indicators, complexity indicators, and FPS comprehensively, the SCS—YOLO detection framework proposed in this study provides a feasible technical reference for the intelligent detection of sugarcane quality in the raw materials of the sugar industry. Full article

The sharp increase in Internet of Things (IoT) terminal numbers imposes significant pressure on energy and wireless spectrum resources. Battery-free IoT technology has become an effective solution to address the high power consumption and cost issues of traditional IoT systems. While leveraging backscatter communication, battery-free IoT faces challenges such as low throughput and poor fairness among wireless links. To tackle these problems, this study proposes a low-power hybrid communication mechanism for terminals. Within this mechanism, a time-frame partitioning method for hybrid communication strategies is designed based on sensing results of licensed spectrum channels. Considering terminal power constraints, quality of service (QoS) requirements of primary communication links, and time resource limitations, a hybrid communication strategy model is established to jointly optimize fairness and maximize throughput. To resolve the non-convexity in the Multi-objective Lexicographical Optimization Problem (MLOP), the Block Coordinate Descent (BCD) method and auxiliary variables are introduced. Simulation results demonstrate that, compared to the baseline scheme, the proposed approach reduces the throughput gap between links from 85.4% to 0.32% when the channel gain differences are small, while the total system throughput decreases by only 8.81%. As the channel gain disparity increases, the baseline scheme exhibits a more pronounced disadvantage in terms of throughput fairness, while the proposed approach still reduces the throughput gap between the best and worst links from 91.02% to 0.684% at the cost of a 9.18% decrease in total system throughput. These results demonstrate that the proposed scheme effectively balances fairness and throughput performance across diverse channel conditions, ensuring relatively equitable quality of service for all users in the IoT network. Full article

The optimization of trajectories for multiple robotic arms in a shared workspace is critical for industrial automation but presents significant challenges, including data sharing, communication overhead, and adaptability in dynamic environments. Traditional centralized control methods require sharing raw sensor data, raising concerns and creating computational bottlenecks. This paper proposes a novel Federated Learning (FL) framework for distributed multi-robotic arm trajectory optimization. Our method enables collaborative learning where robots train a shared model locally and only exchange gradient updates, preserving data privacy. The framework integrates an adaptive Rapidly exploring Random Tree (RRT) algorithm enhanced with a dynamic pruning strategy to reduce computational overhead and ensure collision-free paths. Real-time synchronization is achieved via EtherCAT, ensuring precise coordination. Experimental results demonstrate that our approach achieves a 17% reduction in average path length, a 22% decrease in collision rate, and a 31% improvement in planning speed compared to a centralized RRT baseline, while reducing inter-robot communication overhead by 45%. This work provides a scalable and efficient solution for collaborative manipulation in applications ranging from assembly lines to warehouse automation. Full article

Deploying deep learning (DL) models in real-world environments remains a major challenge, particularly under resource-constrained conditions where achieving both high accuracy and compact architectures is essential. While effective, Conventional pruning methods often suffer from high computational overhead, accuracy degradation, or disruption of the end-to-end training process, limiting their practicality for embedded and real-time applications. We present Dynamic Attention-Guided Pruning (DAGP), a Dynamic Attention-Guided Soft Channel Pruning framework that overcomes these limitations by embedding learnable, differentiable pruning masks directly within convolutional neural networks (CNNs). These masks act as implicit attention mechanisms, adaptively suppressing non-informative channels during training. A progressively scheduled L1 regularization, activated after a warm-up phase, enables gradual sparsity while preserving early learning capacity. Unlike prior methods, DAGP is retraining-free, introduces minimal architectural overhead, and supports optional hard pruning for deployment efficiency. Joint optimization of classification and sparsity objectives ensures stable convergence and task-adaptive channel selection. Experiments on CIFAR-10 (VGG16, ResNet56) and PlantVillage (custom CNN) achieve up to 98.82% FLOPs reduction with accuracy gains over baselines. Real-world validation on an enhanced PlantDoc dataset for agricultural monitoring achieves 60 ms inference with only 2.00 MB RAM on a Raspberry Pi 4, confirming efficiency under field conditions. These results illustrate DAGP’s potential to scale beyond agriculture to diverse edge-intelligent systems requiring lightweight, accurate, and deployable models. Full article

Background: Fixed-duration venetoclax plus rituximab (VR) is a standard therapy for relapsed/refractory (R/R) chronic lymphocytic leukemia (CLL). However, evidence supporting its use after covalent BTK inhibitor (c-BTKi) therapy is scarce in clinical trials and limited in real-world settings. Objectives: To assess the efficacy and safety of VR in a real-world cohort of patients with R/R CLL, including cBTKi-pretreated individuals, and to contextualize outcomes alongside published real-world studies and registrational trials of alternative therapies. Methods: We retrospectively analyzed 37 patients with R/R CLL treated with VR at our center between April 2018 and November 2024. Baseline characteristics, treatment responses, minimal residual disease (MRD), and adverse events were recorded. Survival was estimated using the Kaplan–Meier method. A structured review of relevant real-world evidence and pirtobrutinib clinical trials was also conducted. Results: Median age was 67 years; 35.1% had prior cBTKi exposure. The overall response rate (ORR) was 91.7% (22/24 evaluable patients), with 66.7% achieving complete remission (CR). Among evaluable c-BTKi-pretreated patients, the ORR was 87.5% (7/8) and the CR rate was 62.5%. Undetectable MRD (uMRD) rates were 78.6% in peripheral blood and 71.4% in bone marrow. Thirty-month progression-free survival (PFS), time to next treatment (TTNT), and overall survival (OS) were >90% for the whole cohort and for c-BTKi-pretreated patients. The most frequent adverse event was neutropenia grade ≥ 3, especially during combination therapy, which is easily managed with GCSF support. Conclusions: Our real-world evidence shows that VR is an effective and well-tolerated option even after c-BTKi therapy in R/R CLL. These data complement evidence from emerging therapies and inform post-c-BTKi treatment selection in clinical practice. Full article

The objective of this study was to assess the changes in adiponectin concentrations and inflammatory markers in men with abdominal obesity following physical exercise and exercise combined with dietary intervention. This study included 44 males with abdominal obesity (mean age 34.7 ± 5.5 years, waist circumference [WC] 110.3 ± 8.5, BMI 32.0 ± 3.9), who were randomly assigned to three groups: a control group without interventions (CG, n = 12), an experimental group engaging in aerobic-resistance exercise (EG, n = 16) and a group engaging in aerobic-resistance exercise combined with an ad libitum high-protein, low-glycemic index carbohydrate diet (EDG, n = 16). Body composition metrics: the body fat-, fat-free mass-, and abdominal fat-to body mass (BF/BM, FFM/BM, ABD/BM) indexes and the body adiposity index (BAI), along with biochemical blood analyses—adiponectin (ADIPO), interleukin-6 (IL-6), high-sensitivity C-reactive protein (hs-CRP), Castelli-II Index (CRI II) and fasting glucose–insulin (FG/I) ratio—were measured at baseline and after the intervention. The effects of the interventions on the analyzed variables across groups were assessed using mixed ANOVA tests with post hoc comparisons. Effect size (ES) was also calculated using partial eta squared (ηp²). The exercise intervention (EG) resulted in a significant reduction in the BAI (p < 0.01), insulin resistance FG/I (p < 0.02), and IL-6 concentrations (p < 0.01) and initiated an increase in ADIPO secretion (p = 0.03). The combined intervention (EDG) reduced the insulin resistance FG/I (p = 0.02) and atherogenic index CRI II (p = 0.01), decreased inflammatory markers IL-6 (p = 0.01) by 48% and hs-CRP (p = 0.04) by 30%, and simultaneously increased the ADIPO (p = 0.02) concentration by 15%. These effects were accompanied by significant changes in body composition: reductions in visceral fat ABD/BM (p < 0.01), total fat BF/BM (p < 0.01), and BAI (p = 0.02) and an increase in FFM/BM (p < 0.01). A crucial role in achieving these outcomes was played by dietary modifications, i.e., the inclusion of low-glycemic index carbohydrates (p < 0.01), a 23% increase in protein intake (p < 0.01), and a 50% increase in dietary fiber intake (p < 0.01), which consistently deepened the energy deficit (p < 0.01) and reduced fat intake (p < 0.01). These findings underscore that short-term interventions, whether exercise alone or combined with dietary modifications, can effectively reduce inflammation and lower insulin resistance in men with visceral obesity. However, the combined intervention, involving both exercise and dietary modifications, resulted in more pronounced beneficial changes in both body composition and concentrations of adipokines, inflammatory markers, and atherogenic indices and insulin resistance. Full article

Oxidative stress is increasingly recognized as a significant contributor to the pathogenesis of inflammatory bowel disease (IBD). However, the clinical utility of oxidative stress-related biomarkers for assessing and predicting disease activity remains unclear. This prospective observational study aimed to evaluate the diagnostic and predictive performance of oxidative stress-related biomarkers in distinguishing between active IBD and remission across clinical, biochemical, and endoscopic criteria. A total of 76 patients with IBD were followed across three visits: baseline (biological treatment initiation), post-induction (6–12 weeks), and final follow-up (24–36 weeks). Associations with clinical, biochemical, and endoscopic remission status at the final follow-up were evaluated using correlation matrices, receiver operating characteristic curve analysis, principal component analysis, and logistic regression. Ceruloplasmin, plasma free thiols, gamma-glutamyl transferase, and albumin showed significant diagnostic values for distinguishing active disease from remission, using C-reactive protein (CRP)-based criteria. Serum uric acid, advanced oxidation protein products, gamma-glutamyl transferase, total antioxidant capacity, and ceruloplasmin predicted clinical or CRP-based remission when measured at baseline or post-induction, with predictive value varying by biomarker and the time point. Overall, our findings reinforce the role of oxidative stress in the pathogenesis of IBD and highlight the potential of oxidative stress-related biomarkers to be used as tools for monitoring disease activity and predicting IBD treatment outcomes. Full article

Background: KRAS mutations are among the most common oncogenic drivers in non-small cell lung cancer (NSCLC), with KRAS G12C emerging as a therapeutically targetable subtype. However, the prognostic relevance of KRAS G12C compared with non-G12C mutations in patients receiving immune checkpoint inhibitors (ICIs) remains unclear. Methods: We retrospectively analyzed 80 NSCLC patients treated with ICIs between January 2020 and July 2024; data were censored on 3 July 2025. The cohort included 32 KRAS-mutant (20 G12C, 12 non-G12C) and 48 KRAS wild-type patients. Clinicopathological features, treatment details, and survival outcomes were collected. Overall survival (OS) and progression-free survival (PFS) were estimated using the Kaplan–Meier method, with group comparisons made using the log-rank test. Univariate and multivariate Cox regression analyses were conducted to identify independent prognostic factors. Results: Among 80 NSCLC patients treated with ICIs, the median OS and PFS were 14.3 and 8.2 months, respectively. Survival outcomes were comparable between KRAS-mutant and wild-type patients. Within the KRAS-mutant subgroup (n = 32), baseline characteristics were generally balanced between G12C (n = 20) and non-G12C (n = 12) cases, with non-significant trends toward higher metastatic burden and PD-L1 ≥ 50% in the G12C group. Median OS was significantly longer in G12C patients than in non-G12C patients (20.7 vs. 6.4 months; p = 0.021), whereas PFS did not differ significantly (10.2 vs. 3.7 months; p = 0.181). In multivariate analysis, non-G12C mutation independently predicted increased mortality risk (HR 3.35, 95% CI 1.26–8.89; p = 0.015). For PFS, recurrent disease status was associated with improved outcomes in univariate analysis (HR 0.30, 95% CI 0.09–0.94; p = 0.040), but no independent predictors were identified in multivariate modeling. Conclusions: In NSCLC patients treated with ICIs, the KRAS G12C mutation was associated with significantly improved OS compared with other KRAS subtypes, independent of clinicopathological characteristics. These findings suggest distinct biological behavior of KRAS variants in immunotherapy response and warrant further prospective validation. Full article

Background: Nivolumab plus chemotherapy is a standard first-line treatment for advanced gastric cancer (GC), but reliable early biomarkers for predicting treatment outcomes remain lacking. This study aimed to identify early immunological predictors through dynamic immune profiling. Methods: Fifty patients with advanced or unresectable GC receiving nivolumab plus XELOX or FOLFOX were enrolled. Peripheral blood was collected at baseline, week 1, and week 6. Plasma biomarkers (Granzyme B, Ki-67, CXCL10, IFN-γ, TGF-β1) were measured by ELISA, and immune cell subsets, including cytotoxic T cells, immune checkpoint–positive populations, and memory T-cell subsets, were analyzed by flow cytometry. Cutoffs were defined by medians, established thresholds for NLR and lymphocyte count, and criteria for long-term response (≥9.5 months). Associations with response and progression-free survival (PFS) were evaluated using Kaplan–Meier analysis, Cox regression, and ROC curves. Results: Early responders exhibited significant increases in Granzyme B and CXCL10, with ΔGranzyme B alone and in combination with ΔKi-67 predicting response with high accuracy. A lower week 1 neutrophil-to-lymphocyte ratio was associated with long-term benefit. Elevated week 1 CD8⁺ T-cell proportion and greater decreases in PD1⁺CD69⁺Ki-67⁺CD8⁺ T cells were linked to improved PFS. Higher baseline PD1⁺LAG-3⁺Ki-67⁺CD8⁺ T-cell levels and combined TIM-3⁺/LAG-3⁺ expression enhanced prognostic stratification. Additionally, elevated baseline activated TEMRA cells and declines at week 6 in the same subset correlated with better outcomes. Conclusions: These findings highlight the clinical utility of serial immune monitoring to enable early treatment stratification and guide personalized immunotherapy strategies in advanced GC. Full article

Background/Objectives: [¹⁸F]FDG-PET is often used for staging thymic epithelial tumours (TETs). However, its prognostic role remains uncertain. The aim of this present systematic review and meta-analysis is to assess the prognostic value of baseline [¹⁸F]FDG-PET-derived semiquantitative parameters in predicting progression-free survival (PFS) in patients with TETs. Methods: A systematic review and meta-analysis were conducted according to PRISMA guidelines. PubMed, Embase, and Scopus databases were searched up to 30 May 2025. Studies evaluating the prognostic impact of [¹⁸F]FDG-PET parameters on PFS in TETs were included. Pooled hazard ratios (HRs) with 95% confidence intervals (CIs) were calculated. Results: Six retrospective studies involving 593 patients were included. Maximum standardized uptake value (SUVmax), analysed as a continuous variable in four studies, significantly predicted worse PFS (HR: 1.18, 95% CI: 1.08–1.29, p < 0.001), with high inter-study heterogeneity (I² = 79.7%). When dichotomized (two studies), higher SUVmax was associated with significantly poorer PFS (HR: 9.00, 95% CI: 2.93–27.71). Similarly, mean SUV (SUVmean) as a continuous predictor was also significantly associated with impaired PFS (HR: 1.41, 95% CI: 1.25–1.59), but only two studies assessed this parameter. Conversely, metabolic tumour volume (MTV) and total lesion glycolysis (TLG), both assessed as continuous prognosticators, did not show a significant prognostic value. Notably, in both MTV and TLG analyses, two studies contributed a weight of 0%, reflecting limited precision and highlighting the need for larger data. Conclusions: Baseline [¹⁸F]FDG-PET parameters such as SUVmax and SUVmean showed a potential prognostic value in patients with TETs. However, these results are based on a limited number of retrospective studies with significant heterogeneity. Prospective multicentre investigations are necessary to confirm the potential role of [¹⁸F]FDG-PET for risk stratification in TETs. Full article

Background: Angioimmunoblastic T-cell lymphoma (AITL) and peripheral T-cell lymphomas (PTCL), not otherwise specified (NOS), share overlapping histology and T-follicular helper (TFH) biology but often show divergent outcomes and treatment needs. The clinical significance of KMT2A rearrangement (KMT2A-r) in nodal PTCL remains undefined. We aimed to investigate the clinicogenomic features and prognostic impact of KMT2A-r in AITL and PTCL-NOS. Methods: We retrospectively analyzed consecutive patients diagnosed with AITL or PTCL-NOS between 2021 and 2024 at two centers. All patients underwent 523-gene DNA/RNA next-generation sequencing. Gene co-variation and diagnostic splits were summarized using network and decision-tree analyses. Results: Overall, 37 patients were included (AITL: 14; PTCL-NOS: 23), with similar baseline clinical characteristics. In AITL, TFH markers were more frequently expressed, and RHOA mutations were enriched. KMT2A-r occurred in 24% of cases without histology-specific enrichment. AITL showed better 2-year overall survival (OS) than PTCL-NOS (70.7% vs. 38.8%; p = 0.040) but similar progression-free survival (PFS). Univariate analysis revealed that KMT2A-r, lactate dehydrogenase elevation, and bone-marrow involvement predicted inferior PFS (Hazard ratio for KMT2A-r: 2.56). Median PFS was 5.9 versus 12.5 months in the KMT2A-r and non-KMT2A-r groups, respectively (p = 0.039). Brentuximab vedotin (BV) plus cyclophosphamide, doxorubicin, and prednisone did not significantly improve OS or PFS overall; however, exploratory analysis indicated improved PFS in the KMT2A-r subset. Conclusions: KMT2A-r delineates an adverse-risk biology in nodal PTCL, aligns with non-TFH genomic hubs and markers of tumor burden, and may serve as a stratifier and hypothesis-generating target for BV-based strategies. Full article

Background/Objectives: Cerebral infarction significantly worsens outcomes after aneurysmal subarachnoid hemorrhage (SAH). This retrospective study analyzed early predictors of infarct-free survival and the impact of infarct timing on clinical outcomes. Methods: We reviewed 988 consecutive SAH patients treated from 2003 to 2016, all with follow-up CT scans. Baseline clinical and SAH characteristics were recorded to identify predictors of infarct-free survival and assess the relationship between infarct timing and outcomes. Results: Cerebral infarctions occurred in 475 patients (48.1%) at a median of 3.4 days post-SAH; 70.9% happened within the first week. Earlier infarctions were associated with higher in-hospital mortality (odds ratio [OR] = 0.91 per day increase, p < 0.0001) and poor 6-month outcomes (modified Rankin Scale > 3; OR = 0.96 per day increase, p = 0.012), especially within 48 h. Independent predictors of infarct-free survival included poor initial condition (WFNS ≥ 4, adjusted hazard ratio [aHR] = 1.82, p < 0.0001), intraventricular hemorrhage (aHR = 1.25, p = 0.041), aneurysm rebleeding (aHR = 1.76, p < 0.0001), acute hydrocephalus (aHR = 1.38, p = 0.020), and daily aspirin intake (aHR = 0.68, p = 0.002). The number of baseline risk factors (0–5) strongly influenced both infarction likelihood and timing (p < 0.0001). Conclusions: Cerebral infarctions predominantly occur within the first week after SAH, with earlier infarctions having a more severe impact on outcomes. Initial risk factor-adapted SAH management may improve functional outcomes. Full article

Objective: Oral frailty is associated with an increased risk of cognitive decline, yet practical tools for early identification remain limited. The Oral Frailty 5-item Checklist (OF-5), recently standardized in Japan, does not account for severe tooth loss, which is a known risk factor for brain atrophy. We developed a revised version of the OF-5 that includes the criterion of having nine or fewer teeth. This study aimed to validate the revised OF-5 as a screening tool for detecting early brain structural changes related to dementia risk in cognitively unimpaired older adults. Methods: We analyzed 732 cognitively unimpaired participants from a population-based Japanese cohort (baseline 2016–2018). Oral frailty was assessed using both the original OF-5 and the revised OF-5. Brain volumes were measured by MRI and processed with FreeSurfer. Associations between oral frailty status and regional brain volumes were tested using multivariable-adjusted models, with further adjustment for nutrient intake and food consumption. Results: The revised OF-5, which adds severe tooth loss (≥9 teeth) as a criterion, showed greater sensitivity in detecting dementia-related brain changes than the original version. With the original OF-5, oral frailty was associated only with reduced fusiform gyrus volume (1.088% vs. 1.109% of estimated total intracranial volume [eTIV]; p < 0.05). In contrast, the revised OF-5 detected broader changes: orally frail participants showed significantly higher white matter hyperintensity (WMH) volume (0.366% vs. 0.302% of eTIV; p < 0.05) and smaller volumes in the medial temporal lobe (1.824% vs. 1.856%), pars triangularis (0.401% vs. 0.412%), and fusiform gyrus (1.080% vs. 1.111%)—all p < 0.05 (FWE-corrected). These associations persisted after adjusting for nutrient intake and food consumption. Conclusions: The revised OF-5 improves identification of pre-symptomatic brain changes in cognitively healthy older adults, independent of nutrition. It may serve as a simple and practical tool for early screening of dementia risk in clinical and community settings. Full article

Background: Anthracycline-based chemotherapy, while highly effective for breast cancer, poses a significant risk for chemotherapy-related cardiac dysfunction (CTRCD), mainly determined by left ventricular ejection fraction (LVEF) reduction. Objectives: We aimed to evaluate the diagnostic utility of speckle tracking analysis (STA) and Diastolic Stress Test Echocardiography (DSTE) for the early detection of cardiac dysfunction either CTRCD or heart failure with preserved ejection fraction (HFpEF) in women undergoing chemotherapy for breast cancer and developed exertional dyspnea and/or fatigue during follow-up. Methods: In this prospective case–control study, 133 women receiving anthracycline-based chemotherapy (with or without anti-HER2 therapy) (chemotherapy group-CTG) and 65 age-matched healthy women as the control group (CG) underwent resting echocardiographic assessment, including LVEF, global longitudinal strain (GLS), myocardial work indices, biomarkers assay (NT-proBNP, troponin, galectin-3) and DSTE at baseline. That assessment was repeated after 12 months in CTG. Results: In this prospective case—control study, 133 women receiving anthracycline-based chemotherapy (with or without anti-HER2 therapy) were included. Based on the presence of CTRCD, they were further subdivided into a CTRCD subgroup (n = 37) and a CTRCD-free subgroup (n = 88). At the end of this study, CTG showed worse values of LVEF, GLS, myocardial work indices than baseline and CG (p < 0.05). Subgroup comparison (CTRCD vs. CTRCD-free) showed significant impairment in LVEF (53.60% vs. 62.60%, p < 0.001), GLS (–16.68% vs. −20.31%, p < 0.001), DSTE-derived tricuspid regurgitation maximum velocity (TRVmax) (3.05 vs. 2.31 m/s, p < 0.001) and elevated biomarkers (NT-proBNP: 200.06 vs. 61.49 pg/mL; troponin: 12.42 vs. 3.95 ng/L, p < 0.001) in the former subgroup. Regression analysis identified GLS, NT-proBNP, troponin, and TRVmax as independent predictors of CTRCD. Notably, a subgroup of CTRCD-free patients (n = 16) showed a high probability for HFpEF based on the HFA-PEFF score, with elevated GLS, NT-proBNP and DSTE-derived TRVmax compared to the rest of CTRCD-free patients and the CG (p < 0.001). Conclusions: STA and DSTE significantly outperform conventional LVEF in detecting subclinical cardiac dysfunction among women with breast cancer receiving chemotherapy. The combination of novel echocardiographic techniques and biomarkers may enable the detection of early CTRCD, including the under-estimated presence of HFpEF among breast cancer women with HF symptoms. Full article

This study proposes a comprehensive framework for establishing an Emissions Trading System (ETS) in Thailand, addressing three core design elements: scope, cap setting, and allowance allocation. Using a mixed-methods approach that combines quantitative data analysis with qualitative insights from expert and stakeholder consultations, the research identifies a practical and strategic pathway for implementation. The proposed framework recommends a phased approach, with the initial phase covering 222 high-emitting facilities across seven key sub-industrial sectors. This scope, defined by a 25,000 tCO₂e threshold, is estimated to cover approximately 42.64% of the country’s total greenhouse gas (GHG) emissions. The ETS cap for the first phase is set at 20 MtCO₂e, aligning with national climate targets outlined in Thailand’s draft NDC 3.0. For allowance allocation, free allocation via output-based benchmarking is identified as the most suitable method for initial implementation, given its feasibility and effectiveness in incentivizing efficiency improvements. Furthermore, the standard cost model (SCM) was applied to assess compliance costs, indicating an annual administrative burden of 21,534 h and THB 42.18 million. These insights provide policymakers with a baseline for streamlining monitoring, reporting, and verification (MRV) requirements. The findings suggest that the proposed framework is a robust and strategic model, tailored to the unique economic and regulatory context of Thailand, providing a clear path to achieving the nation’s ambitious sustainable climate goals. Full article