Search Results (10,836)

As the reserves of these raw materials continue to dwindle, their extraction is becoming increasingly difficult, with shaft depth increasing and sometimes exceeding three kilometres. As shaft depths increase, the costs, as well as the risks of mining and other shaft operations, increase non-linearly. There is also a significant increase in the costs associated with condition assessment, which depend on the inspection and testing method used and increase with the lifetime of the facility. New technical and organisational solutions are emerging to meet these requirements. This paper addresses the operation of steel ropes. This article analyses the results of strength tests on two selected modern hoisting rope designs that have recently come into service. These structures are relatively unknown to users in terms of their wear. In their operation, significant problems of condition assessment and safety, as well as disqualification due to the level of wear reached, arise. Strength tests were performed using classic non-destructive methods (tensile test, torsion test, bending test) to assess the technical condition of ropes after their replacement. The tests on two rope structures carried out before and after they were put down by expert decision were analyzed. The results of these tests were statistically processed and presented graphically to determine similarities and differences. Statistical analyses were used to evaluate the results by examining the distribution of variable strength parameters. All results were commented on, and specific and general conclusions were drawn. The article presents the conclusions, the most important of which is that new and complex ropes exhibit varying degrees of wear across the layers. This is due to their compaction process. These should be useful to users of similar rope designs, personnel carrying out the obligatory tests imposed by the legislation, and those making strategic decisions regarding the operation of entire mining plants. The analyses may contribute to the subsequent assessment of the technical condition of new ropes, which in many cases have wear parameters (corrosion, strength loss, etc.) assessed in a subjective, not quantitative, manner. Full article

This paper introduces the Construction 4.0 Value Proposition Score (CVPS4.0)—a structured framework that enables Architecture, Engineering, and Construction (AEC) organizations to evaluate and communicate the value proposition of Construction 4.0 decisions. Grounded in the “Futures Triangle” theory, the study draws on existing research to identify three key dimensions: past barriers constraining AEC organizations, current trends driving industry change, and future transformations toward which the sector is evolving. In total, 45 barriers, 13 trends, and four transformations were identified as the foundation of the scoring framework. The model assesses how a decision influences each dimension, producing a composite score that reflects its overall value proposition. This score incorporates three considerations: the applicability of each factor to the organization, the degree of impact the decision has on it, and the relevance of the factor to the decision. The framework was validated through proof-of-concept with a subject-matter expert, who confirmed its value in supporting strategic, data-informed decision-making. As one of the first studies to evaluate the value proposition of Construction 4.0, this research offers both a practical decision-support tool and a consolidated reference on the forces shaping organizational change. CVPS4.0 provides AEC organizations with a proactive means to guide decisions, mitigate risks, and enhance long-term value creation. Full article

Climate change is elevating temperatures, shifting weather patterns, and increasing frequency and severity of extreme weather events. Despite the urgency with which solutions are needed, relatively few studies comprehensively investigate the effectiveness of alternative flood risk management options under different climate conditions. Specifically, we are interested in a comparison of the effectiveness of resistance, nature-based, and managed retreat strategies. Using an integrated 1D-2D PCSWMM model, this paper presents a comprehensive investigation into the effectiveness of alternative adaptation strategies in reducing flood risks in Eastwick, a community of Philadelphia, PA, subject to fluvial, pluvial, and coastal flood hazards. While addressing the urgent public need to develop local solutions to this community’s flood problems, the research also presents transferable insights into the limitations and opportunities of different flood risk reduction strategies, manifested here by a levee, watershed-scale green stormwater infrastructure (GSI) program, and a land swap. The effectiveness of these options is compared, respectively, under compound climate change conditions, with the spatiotemporal patterns of precipitation and Delaware river tidal conditions based on Tropical Storm Isaias (2020). The hypothesis was that the GSI and managed retreat approaches would be superior to the levee, due to their intrinsic ability to address the compound climate hazards faced by this community. Indeed, the findings illustrate significant differences in the predicted flood extents, depths, and duration of flooding of the various options under both current and future climate scenarios. However, the ideal remedy to flooding in Eastwick is more likely to require an integrated approach, based on more work to evaluate cost-effectiveness, stakeholder preferences, and various logistical factors. The paper concludes with a call for integrating multiple strategies into multifunctional flood risk management. Full article

Background/Objectives: Population aging and its associated chronic conditions have become an unprecedented challenge in the United States and worldwide. Many aged individuals experience certain forms of cognitive decline, which increases their risk of developing a pre-dementia condition called mild cognitive impairment and even dementia. No effective pharmacological treatments are available to treat normal age-associated cognitive decline or mild cognitive impairment. Our previous study has shown the potent anti-inflammatory effects of shiitake mushroom-derived vesicle-like nanoparticles (S-VLNs) in vitro and in an acute inflammatory disease model. In this study, we aimed to investigate the potential benefits of orally administered S-VLNs in aged mice. Methods: S-VLNs were extracted from fresh shiitake mushrooms. S-VLNs in phosphate-buffered saline (PBS) or vehicle only was orally administered to 13-month-old male C57BL/6J mice weekly for 9 months. These mice were subjected to a series of physiological tests, followed by euthanasia at 22 months of age. Their fecal samples were subjected to 16S rRNA and untargeted metabolomics analyses, followed by comprehensive bioinformatics analyses. Results: The long-term oral administration of S-VLNs significantly improved the cognitive function of aged mice. Orally administered S-VLNs did not travel to the brain. Instead, they impacted the composition of the gut microbiota and reshaped the fecal metabolome. Functional predictions of the gut microbiota and fecal metabolome suggested that S-VLNs regulated tryptophan metabolism. Specifically, S-VLNs markedly decreased the tryptophan-related metabolite kynurenic acid (KYNA). The integrative analyses of omics data identified a strong correlation between 18 gut bacterial genera and 66 fecal metabolites. KYNA was found to highly correlate with five genera positively and twelve genera negatively. Conclusions: The oral intake of S-VLNs represents a new and superior dietary approach with the ability to modulate the gut microbiota and fecal metabolome and to improve cognitive function during aging. Full article

Burn wounds are complex injuries that require timely and accurate assessment to guide treatment decisions and improve healing outcomes. Traditional clinical evaluations are largely subjective, often leading to delays in intervention and increased risk of complications. Imaging technologies have emerged as valuable tools that enhance diagnostic accuracy and enable objective, real-time assessment of wound characteristics. This review aims to evaluate the range of imaging modalities currently applied in burn wound care and assess their clinical relevance, diagnostic accuracy, and cost-effectiveness. It explores how these technologies address key challenges in wound evaluation, particularly related to burn depth, perfusion status, bacterial burden, and healing potential. A comprehensive narrative review was conducted, drawing on peer-reviewed journal articles, NICE innovation briefings, and clinical trial data. The databases searched included PubMed, Ovid MEDLINE, and the Cochrane Library. Imaging modalities examined include Laser Doppler Imaging (LDI), Fluorescence Imaging (FI), Near-Infrared Spectroscopy (NIR), Hyperspectral Imaging, Spatial Frequency Domain Imaging (SFDI), and digital wound measurement systems. The clinical application and integration of these modalities in UK clinical practice were also explored. Each modality demonstrated unique clinical benefits. LDI was effective in assessing burn depth and perfusion, improving surgical planning, and reducing unnecessary procedures. FI, particularly the MolecuLight i:X device (MolecuLight Inc., Toronto, ON, Canada), accurately identified bacterial burden and guided targeted interventions. NIR and Hyperspectral Imaging provided insights into tissue oxygenation and viability, while SFDI enabled early detection of infection and vascular compromise. Digital measurement tools offered accurate, non-contact assessment and supported telemedicine use. NICE recognized both LDI and MolecuLight as valuable tools with the potential to improve outcomes and reduce healthcare costs. Imaging technologies significantly improve the precision and efficiency of burn wound care. Their ability to offer objective, non-invasive diagnostics enhances clinical decision-making. Future research should focus on broader validation and integration into clinical guidelines to ensure widespread adoption. Full article

The circadian rhythm controls the sleep/wake cycle and a wide variety of metabolic and physiological functions. Clock genes regulate it in response to both external and endogenous stimuli, and their expression may change because of aging, leading to an increased risk of health problems. Despite the well-described benefits of physical exercise as a circadian synchronizer, there is a lack of literature regarding the role of chronic exercise intensity in clock gene expression during aging. This article aims to analyze the differential expression of genes that regulate the biological clock under the effects of variable-intensity aerobic swimming training in aging mice, determining whether these exercise regimens interfere with the genomic regulation of the circadian rhythm. For this purpose, the mice were exposed to low- and high-intensity exercise and had their heart and gastrocnemius tissues molecularly analyzed by cDNA synthesis and qPCR to determine the expression levels of the selected genes: Clock, Arntl, Per1, Per2, Cry1, Cry2, and Nr1d1. The results showed that low-intensity exercise, performed at workloads below the anaerobic threshold, significantly changed their expression in the gastrocnemius muscle (p < 0.05), while high-intensity exercise had no statistically significant effects (p > 0.05), with the heart being immune to exercise influence except when it comes to the Per1 gene, for which expression was increased (p = 0.031) by low-intensity exercise. Additionally, both body weight and lactate thresholds had no change during the experiment (p > 0.05), while the maximum supported workload was maintained for high-intensity exercise (p > 0.05) and increased for low-intensity exercise (p < 0.01), with the control group experiencing a decay instead (p < 0.05). Thus, the present study highlights the importance of chronic exercise in modulating clock genes and opens exciting possibilities for circadian medicine, such as improvements in exercise capacity, heart condition, and lipid metabolism for subjects of low-intensity regimens. Full article

Reproductive biotechnologies, such as embryo transfer (ET) and fixed-time artificial insemination (FTAI), are increasingly adopted to enhance genetic progress in tropical cattle production systems. However, the high prevalence of reproductive infectious diseases in tropical regions may compromise reproductive outcomes. This study evaluated the impact of eight reproductive pathogens (Neospora caninum, Leptospira spp., Anaplasma spp., Babesia spp., Trypanosoma spp., BVDV, IBR, and BLV) on pregnancy success, embryonic loss, and abortion in 296 bovine females subjected to ET and FTAI in Huila, Colombia. Animals were classified into six genetic groups and monitored for pregnancy at 45 and 90 days post-treatment. Logistic regression models were used to evaluate associations between disease prevalence and reproductive outcomes. Neospora caninum emerged as the most detrimental pathogen, significantly reducing pregnancy rates (OR = 0.443; p = 0.034) and increasing both embryonic loss (OR = 7.35; p = 0.073) and abortion risk (ET: OR = 20.3; p = 0.0002; FTAI: OR = 3.95; p = 0.0436). Leptospira spp. and BLV were also associated with increased embryonic losses, whereas Babesia spp. and IBR were linked to a reduced risk of embryo resorption because of enhanced care, monitoring, or vaccination. Creole cattle showed lower disease susceptibility than crossbred or commercial breeds. These findings highlight the need for comprehensive disease control, targeted vaccination, and reproductive planning to improve biotechnology outcomes in tropical cattle systems. Full article

Background: Medial arterial calcification (MAC) is a vascular disorder that affects the arterial media layer. It represents a predictor of major adverse limb events in patients affected by diabetes mellitus (DM). This single-center retrospective observational study investigates whether ultrasound (US) detection of MAC in below-the-knee (BTK) vessels represents a negative predictor of major adverse cardiovascular events (MACE) in asymptomatic patients. Methods: In 2019, 584 patients, referred to the Vascular Surgery Unit for lower limb US, were examined by the same operator, who assessed the presence of BTK MAC. The primary outcome was the rate of MACE during a 5-year follow-up period. The secondary outcomes included the development of peripheral arterial disease (PAD), the overall survival rates, lower limb revascularizations, and major amputations. Results: MAC in BTK vessels was highlighted in 239 patients (MAC+) who exhibited a younger age (p < 0.001), DM (p < 0.001), and chronic kidney disease (CKD) (p = 0.048). The 345 subjects without MAC (MAC−) showed prior myocardial infarction (p < 0.001), stroke (p = 0.034), and smoking habits (p < 0.001). After propensity score matching, the MAC+ group presented a higher risk of MACE (HR: 1.84; CI: 1.01–3.38; p = 0.047) during a median follow-up of 57 months. Age (HR: 1.06; CI: 1.01–1.12) and MAC (HR: 1.22; CI: 1.06–1.57) were independently associated with MACE. New diagnoses of PAD mainly occurred in the MAC− group (p < 0.001). No differences were observed in major amputations, revascularization procedures, or overall survival rates. Conclusions: Ultrasound detection of BTK MAC was associated with the presence of DM and CKD and with a 1.8-fold increased risk of developing a MACE within 5 years in asymptomatic patients. Full article

Relevance of the problem and aim of the work: Ankylosis of the temporomandibular joint (TMJ) affects physical, psychological, and social well-being and quality of life. One of the most frequently used surgical interventions for the treatment of temporomandibular joint ankylosis is interpositional arthroplasty, particularly in cases where joint preservation is feasible, with different autologous fats: dermis fat, buccal fat pad, and full thickness skin-subcutaneous fat. The aim of the work was to evaluate the efficiency of using different autologous fats in temporomandibular joint ankylosis treatment with interposition arthroplasty method. Materials and Methods: This systematic literature review was conducted according to PRISMA guidelines and registered in the PROSPERO database (CRD420251038325). A comprehensive search was performed in PubMed, the Cochrane Library, and ScienceDirect databases using combinations of keywords: (temporomandibular joint disorders OR temporomandibular joint) AND (adipose tissue or autologous) AND (ankylosis OR arthroplasty). Inclusion criteria were clinical studies conducted on human subjects, written in English, that evaluated the use of autologous fat in interpositional arthroplasty for TMJ ankylosis. The main outcome measures included postoperative maximum mouth opening (MMO), pain intensity, and relative fat volume contraction. Risk of bias was assessed using the Cochrane RoB 2 tool for randomized controlled trials and the Newcastle–Ottawa Scale for cohort studies. Most included studies were of moderate to high quality. Results: A total of 20 publications were selected, including a total of 369 patients. In a qualitative analysis, the best results for maximal opening of mouth (MOM) at 3, 6, 12, and more than 12 months were obtained with dermal fat. After 3 months, the MOM was 40.0 ± 2.7 mm, after 6 months—40.80 ± 4.26 mm, after 12 months—41.9 ± 4.0 mm, after more than 12 months—43.5 mm. The lowest pain intensity was observed using dermal fat taken from the iliac crest region. The rate of volumetric fat shrinkage was greater using buccal fat pad than dermis fat. Conclusions: The most commonly used types of autologous fat in interposition arthroplasty in ankylosis are the following: dermal fat from the abdominal region (iliac crest, subumbilical area, groin), buccal fat pad and full-thickness subcutaneous fat. The best results after the surgical treatment of TMJ ankylosis with interposition arthroplasty are obtained using dermis fat. Full article

The failure of large gravity dams during an earthquake could lead to calamitous flooding, severe infrastructural damage, and massive environmental destruction. This paper aims to demonstrate reliable methods for evaluating dam performance after a seismic event. The work included a seismic hazard analysis and nonlinear finite element modelling of concrete cracking for two large dams (D1 and D2, of 35 and 90 m in height, respectively) in Eastern Canada. Dam D1 is located in Montreal, and Dam D2 is located in La Malbaie, Quebec. The modelling approach was validated using the Koyna Dam, which was subjected to the 1967 Mw 6.5 earthquake. This paper reports tensile cracks of D1 and D2 under combined hydrostatic and seismic loading. The latter was generated from ground motion records from 11 sites during the 1988 Mw 5.9 Saguenay earthquake. These records were each scaled to two times the design level. It is shown that D1 remained stable, with minor localised cracking, whereas D2 experienced widespread tensile damage, particularly at the crest and base under high-energy and transverse inputs. These findings highlight the influence of dam geometry and frequency characteristics on seismic performance. The analysis and modelling procedures reported can be adopted for seismic risk classification and safety compliance verification of other dams and for recommendations such as monitoring and upgrading. Full article

Forest tourism visitation in U.S. national forests has grown by approximately 8 percent over the past decade (from 2014 to 2022) from 147 million to 158.7 million visits per year, indicating a clear upward trajectory in demand for nature-based leisure experiences, yet the determinants of traveler satisfaction in this context remain insufficiently understood. Existing studies have primarily emphasized destination attributes, overlooking the interplay between psychological motivations, lifestyle orientations, and physical conditions. This omission is critical because it limits a holistic understanding of forest traveler’s experiences, which prevents us from fully capturing how internal dispositions, everyday life contexts, and well-being concerns interact with destination attributes to shape satisfaction. Therefore, the purpose of this study is to explore how motivation, lifestyle, and physical condition jointly shape satisfaction in forest tourism, drawing on Push–Pull Theory and environmental psychology. A dataset of 10,792 TripAdvisor reviews of U.S. national forests was analyzed using LIWC 2022 for psycholinguistic feature extraction and Ordered Logit Regression for hypothesis testing. Results show that positive emotional tone, leisure-oriented language, health references, and reward motivation significantly enhance satisfaction, while negative tone, illness, and work-related language reduce it. Curiosity and risk motivations were non-significant, and allure exerted only a marginal effect. These findings extend the Push–Pull framework by incorporating lifestyle and physical condition as moderating variables and validate emotional tone in user-generated content as a proxy for subjective evaluations. The study refines motivation theory by revealing context-specific effects of motivational dimensions. The results offer actionable insights for destination managers, service providers, marketers, and policymakers aiming to enhance forest travel experiences and promote sustainable tourism development. Full article

Background/Objective: The overnight 1-mg dexamethasone suppression test (DST) represents the conventional/standard tool for endogenous hypercortisolemia screening, typically in relationship with adrenal and pituitary masses. Nevertheless, an associated spectrum of challenges and pitfalls is found in daily practice. This analysis aimed to evaluate: (I.) the diagnosis relevance of 1-mg DST in patients with adrenal incidentalomas (AIs) with/without mild autonomous cortisol secretion (MACS) exploring different cutoffs of the second-day plasma cortisol after dexamethasone administration (cs-DST) with respect to cardio-metabolic outcomes; (II.) the potential utility of adding other biomarkers to DST [plasma morning adrenocorticotropic hormone (ACTH), 24-h urinary free cortisol (UFC), late-night salivary cortisol (LNSC), dehydroepiandrosterone sulfate (DHEAS)]; and (III.) DST variability in time. Methods: This narrative analysis was based on searching full-text, English articles in PubMed (between January 2023 and April 2025) via using different term combinations: “dexamethasone suppression test” (n = 239), “diagnosis test for autonomous cortisol secretion” (n = 22), “diagnosis test for mild autonomous cortisol secretion” (n = 13) and “diagnosis test for Cushing Syndrome” (n = 61). We manually checked the title and abstract and finally included only the studies that provided hormonal testing results in adults with non-functional adenomas (NFAs) ± MACS. We excluded: reviews, meta-analyses, editorials, conference abstracts, case reports, and case series; non-human research; studies that did not provide clear criteria for distinguishing between Cushing syndrome and MACS; primary aldosteronism. Results: The sample-focused analysis (n = 13 studies) involved various designs: cross-sectional (n = 4), prospective (n = 1), retrospective (n = 7), and cohort (n = 1); a total of 4203 patients (female-to-male ratio = 1.45), mean age of 59.92 years. I. Cs-DST cutoffs varied among the studies (n = 6), specifically, 0.87, 0.9, 1.2, and 1.4 µg/dL in relationship with the cardio-metabolic outcomes. After adjusting for age (n = 1), only the prevalence of cardiovascular disease remained significantly higher in >0.9 µg/dL vs. ≤0.9 group (OR = 2.23). Multivariate analysis (n = 1) found cs-DST between 1.2 and 1.79 µg/dL was independently associated with hypertension (OR = 1.55, 95%CI: 1.08–2.23, p = 0.018), diabetes (OR = 1.60, 95%CI: 1.01–2.57, p = 0.045), and their combination (OR = 1.96, 95%CI:1.12–3.41, p = 0.018) after adjusting for age, gender, obesity, and dyslipidemia. A higher cs-DST was associated with a lower estimated glomerular filtration rate (eGFR), independently of traditional cardiovascular risk factors. Post-adrenalectomy eGFR improvement was more pronounced in younger individuals, those with lower eGFR before surgery, and with a longer post-operative follow-up. Cs-DST (n = 1) was strongly associated with AIs size and weakly associated with age, body mass index and eGFR. Cortisol level increased by 9% (95% CI: 6–11%) for each 10 mL/min/1.73 m² decrease in eGFR. A lower cs-DST was associated with a faster post-adrenalectomy function recovery; the co-diagnosis of diabetes reduced the likelihood of this recovery (OR = 24.55, p = 0.036). II. Additional biomarkers assays (n = 5) showed effectiveness only for lower DHEAS to pinpoint MACS amid AIs (n = 2, cutoffs of <49.31 µg/dL, respectively, <75 µg/dL), and lower ACTH (n = 1, <12.6 pmol/L). III. Longitudinal analysis of DST’s results (n = 3): 22% of NFAS switch to MACS after a median of 35.7 months (n = 1), respectively, 29% (n = 1) after 48.6 ± 12.5 months, 11.8% (n = 1) after 40.4 ± 51.17 months. A multifactorial model of prediction showed the lowest risk of switch (2.4%) in individuals < 50 years with unilateral tumor and cs-DST < 0.45 µg/dL. In the subgroup of subjects without cardio-metabolic comorbidities at presentation, 25.6% developed ≥1 comorbidities during surveillance. Conclusions: The importance of exploring the domain of AIs/NFAs/MACS relates to an increasing detection in aging population, hence, the importance of their optimum hormonal characterization and identifying/forestalling cardio-metabolic consequences. The spectrum of additional biomarkers in MACS (other than DST) remains heterogeneous and still controversial, noting the importance of their cost-effectiveness, and availability in daily practice. Cs-DST serves as an independent predictor of cardio-metabolic outcomes, kidney dysfunction, while adrenalectomy may correct them in both MACS and NFAs, especially in younger population. Moreover, it serves as a predictor of switching the NFA into MACS category during surveillance. Changing the hormonal behavior over time implies awareness, since it increases the overall disease burden. Full article

Atrial fibrillation (AF) is a common arrhythmia associated with major adverse cardiovascular events. Early detection and short-horizon risk prediction are therefore clinically critical. Prior attention-based electrocardiogram (ECG) models typically treated subtype classification and short-horizon onset risk prediction as separate tasks and optimized attention in only one representational dimension rather than in a coordinated hierarchy. We propose a hierarchical multiattention temporal fusion network (HMA-TFN). The proposed framework jointly integrates lead-level, morphology-level, and rhythm-level attention, enabling the model to simultaneously highlight diagnostically informative leads, capture waveform abnormalities, and characterize long-range temporal dependencies. Moreover, the model is trained for dual tasks—AF subtype classification and 30-min onset prediction. Experiments were conducted on three open-source databases and the Fuzhou University–Fujian Provincial Hospital (FZU-FPH) clinical database, comprising thousands of dual-lead ECG recordings from a diverse subject population. Experimental results show that HMA-TFN achieves 95.77% accuracy in classifying paroxysmal AF (PAAF) and persistent AF (PEAF), and 96.36% accuracy in predicting PAAF occurrence 30 min in advance. Ablations show monotonic gains as each attention level is added, delivering 14.0% accuracy over the baseline for subtyping and 5.2% for prediction. Grad-CAM visualization highlights clinically relevant features such as absent P-waves, confirming model interpretability. On the FZU-FPH clinical database, it achieves a generalization performance of 94.31%, demonstrating its strong potential for clinical application. Full article

Modern antiretroviral therapy (ART) has transformed HIV into a chronic, manageable condition. This retrospective analysis of administrative data from Apulia (Southern Italy) covering 2018–2023 evaluated demographic changes, ART regimen trends, adherence, and the use of antihypertensives, statins, and antidiabetics among people with HIV (PWH). Temporal trends were assessed using compound annual growth rate (CAGR). ART adherence was measured as proportion of days covered (PDC), categorized as <75%, 75–90%, and ≥90%. Over the study period, the proportion of PWH aged 18–54 declined, while those aged 55–64 and ≥65 increased (CAGRs: +10.9%, +14.3%). Use of single-tablet regimens rose from 45.1% to 79.6% (CAGR +12.1%), and integrase-based regimens increased from 52.0% to 69.0%, while protease inhibitor and multi-tablet regimens declined. Antihypertensives were the most prescribed concomitant drugs, followed by statins and antidiabetics (CAGRs: +5.8%, +9.7%, +9.5%). In 2023, 81.9% of subjects achieved PDC ≥ 90%, although lower adherence was observed in women and treatment-naïve individuals. These findings indicate a shift toward simplified, integrase-based regimens and high ART adherence, alongside a growing cardiometabolic burden. Tailored strategies are needed to support adherence, particularly in women and treatment-naïve individuals, and to address cardiovascular risk in aging PWH. Full article

Drowsiness constitutes a significant risk factor in diverse occupational settings, including healthcare, industry, construction, and transportation, contributing to accidents, injuries, and fatalities. Electroencephalography (EEG) signals, offering direct measurements of brain activity, have emerged as a promising modality for drowsiness detection. However, the inherent non-stationary nature of EEG signals, coupled with substantial inter-subject variability, presents considerable challenges for reliable drowsiness detection. To address these challenges, this paper proposes a hybrid approach combining convolutional neural networks (CNNs), which excel at feature extraction, and support vector machines (SVMs) for drowsiness detection. The framework consists of two modules: a CNN for feature extraction from EEG scalograms generated by the Continuous Wavelet Transform (CWT), and an SVM for classification. The proposed approach is compared with 1D CNNs (using raw EEG signals) and transfer learning models such as VGG16 and ResNet50 to identify the most effective method for minimizing inter-subject variability and improving detection accuracy. Experimental evaluations, conducted on the publicly available DROZY EEG dataset, show that the CNN-SVM model, utilizing 2D scalograms, achieves an accuracy of 98.33%, outperforming both 1D CNNs and transfer learning models. These findings highlight the effectiveness of the hybrid CNN-SVM approach for robust and accurate drowsiness detection using EEG, offering significant potential for enhancing safety in high-risk work environments. Full article