Abstract: Maximum oxygen consumption (VO2max) is the ability to absorb, transport, and use oxygen in the body to produce useful energy for muscle activation in a unit of time. For years, devices have been developed to estimate physical performance, including VO2max. In view of the above, it can be considered that the use of artificial intelligence can facilitate interpretation and even generate estimates based on available data. In this regard, this study aims to review the use of artificial intelligence in the assessment of maximum oxygen consumption. A scoping review was conducted in accordance with the following stages: (i) identification of the research question: What would be the use of AI to predict VO2? (ii) identification of relevant studies: searching academic databases and AI search engines; (iii) selection of studies: the PRISMA ScR protocol was applied, selecting 50 studies; (iv) graphing the data in the results (v): finding studies published since 2009 with a higher publication rate in countries in the Americas and Asia; it is concluded that the use of deep learning fed with validated algorithms allows for a more accurate estimation of VO2max and that its evaluation requires the use of explainable AI training, starting with the linear regressions available in the literature and continuing with decision trees, to predict performance and offer a classification of it.

Abstract: Raman Spectroscopy is non-destructive, label free analytical technique that can probe the biochemical alterations in tissues and cell. Raman Spectroscopy, being sensitive to biochemical perturbations, can potentially provide early and real-time identification of changes proceeding morphological changes, allowing early diagnosis as well as diseases monitoring. Recent research has demonstrated its broad utility across diverse clinical domains, including cancers, neurological conditions and infections. Raman spectroscopy combined with machine learning algorithms allows rapid assessment and automated pipelines and can act as a clinical adjunct, enhanced by integrating tools like principal component analysis (PCA), linear discriminant analysis (LDA), random forests, and deep learning architectures. These models allow interpretation of complex spectra, and decipher meaningful biomarkers in heterogeneous clinical samples. This review highlights the earliest and recent progress in Raman based non-destructive diagnosis underscoring advances in cancer diagnosis and challenges faced in clinical settings.

Abstract: Fatigue is a leading contributor to maritime accidents, yet recreational sailors lack the regulatory frameworks and fatigue management tools available to commercial mariners. Peer-reviewed research published in Nature demonstrates that after 17 hours of sustained wakefulness, cognitive performance degrades to a level equivalent to a blood alcohol concentration of 0.05% — the legal driving limit in most countries (Dawson & Reid, 1997). After 24 hours, this rises to 0.10%, well past the threshold for legal intoxication. These findings have been independently replicated (Williamson & Feyer, 2000) and confirmed in field studies aboard racing yachts (Hurdiel et al., 2014). This paper synthesises more than three decades of peer-reviewed research spanning chronobiology, sleep medicine, occupational health, and maritime safety into a biomathematical fatigue model calibrated specifically for pleasure boat passage-making. The model integrates sleep-wake homeostasis, circadian rhythm modulation, sleep fragmentation effects, environmental sleep degradation from sea state, and cumulative multi-day sleep debt into a single framework that outputs impairment as a BAC (blood alcohol concentration) equivalence — an intuitive metric that any sailor can understand. Critically, the model is not merely theoretical. It has been implemented as a freely available, open-access passage fatigue calculator for mobile and web platforms, making it accessible to the widest possible population of recreational mariners. The application faithfully reproduces every formula, constant, and coefficient described in this paper, allowing sailors to simulate any passage plan — varying crew size, watch schedule, departure time, pre-departure sleep, and sea state — and see the predicted fatigue trajectory hour by hour. The purpose is to bridge the gap between laboratory science and practical seamanship: to give pleasure boat crews the same evidence-based fatigue awareness that professional mariners receive through regulation.

Abstract: Multilocular intratesticular cysts are uncommon benign lesions. We report a case associated with testicular microlithiasis in an 85-year-old man presenting with painless enlargement of the left scrotum. Ultrasonography revealed a multilocular cystic lesion with a 3.0-cm main cyst and several adjacent smaller cysts showing posterior acoustic enhancement without mural irregularity or solid components. Bilateral microlithiasis and small epididymal cysts were also detected, and serum tumor markers were normal. The lesions remained stable during 36 months of follow-up. Recognition of the characteristic ultrasonographic features of benign intratesticular cysts is important to avoid unnecessary surgical intervention.

Abstract: Background/Objectives: Malnutrition is highly prevalent in patients with advanced colorectal cancer (CRC) and is associated with poorer treatment tolerance, reduced quality of life, and worse clinical outcomes. Chemotherapy regimens incorporating irinotecan are commonly used in later treatment lines but present a distinct toxicity profile characterized mainly by gastrointestinal symptoms and functional decline, which may negatively affect nutritional status. This study aimed to evaluate the impact of irinotecan-containing chemotherapy regimens on nutritional status and functional capacity in patients with advanced CRC using the Patient-Generated Subjective Global Assessment (PG-SGA). Methods: A cross-sectional observational study was conducted in 91 adult patients with histologically confirmed stage III–IV colorectal adenocarcinoma undergoing active systemic chemotherapy between November 2023 and June 2024. Demographic and clinical variables, treatment regimens, and exposure to irinotecan were recorded. Nutritional status was assessed using the PG-SGA, and body composition was evaluated by multifrequency bioelectrical impedance analysis. Associations between irinotecan exposure and nutritional, functional, and symptom-related variables were analyzed using χ² or Fisher’s exact tests. Results: Thirteen patients (14.3%) received irinotecan-containing regimens, most frequently combined with FOLFOX. Patients exposed to irinotecan presented higher PG-SGA scores, indicating a greater nutritional burden. Although most gastrointestinal symptoms did not reach statistical significance, early satiety (p = 0.041) and functional deterioration (p = 0.039) were significantly associated with irinotecan administration, while nausea (p = 0.089) and vomiting (p = 0.087) showed trends toward significance. The subgroup treated with FOLFOX–irinotecan also demonstrated a higher frequency of functional impairment compared with those receiving FOLFOX alone. Conclusions: Irinotecan-containing chemotherapy regimens in advanced CRC are associated with a distinct pattern of nutritional deterioration primarily driven by functional decline and gastrointestinal symptoms affecting food intake. Systematic nutritional assessment using validated tools such as the PG-SGA may allow early identification of vulnerable patients and support the implementation of timely multimodal interventions aimed at improving treatment tolerance and clinical outcomes.

Abstract: Accurate estimation of the mean-reversion speed $\alpha$ in the AR(1) process $X_{t+1} = (1-\alpha)X_t + \varepsilon_t$ is central to energy-commodity modelling. Classical estimators such as GARCH, jump-diffusion, and regime-switching produce model-conditioned estimates by embedding $\alpha$ within distributional assumptions, so that different model choices yield different $\hat{\alpha}$ values from the same series without a principled criterion to adjudicate. We propose a distribution-free estimator based on a Temporal Convolutional Network (TCN) trained on synthetic AR(1) series with Sinh-ArcSinh innovations of varying tail weight and asymmetry. The SAS family serves as a training vehicle---not a distributional hypothesis---chosen for its ability to span innovation profiles from near-Gaussian to strongly leptokurtic and skewed through its tail-weight and asymmetry parameters. Because the autocorrelation structure $\rho_k = (1-\alpha)^k$ is invariant to the marginal innovation distribution (Yule-Walker invariance), the TCN learns to extract $\alpha$ from temporal dependence alone, independently of distributional assumptions. On held-out test series the estimator outperforms all three classical estimators across the training innovation kurtosis range, with the advantage growing monotonically with non-Gaussianity. A robustness analysis on three out-of-distribution innovation families confirms stable or improved performance well beyond the training boundary. The distribution-free $\hat{\alpha}$ enables a two-stage pipeline in which $\alpha$ and the innovation distribution are characterised independently---a decoupling structurally impossible in classical likelihood-based approaches. Once trained, the TCN acts as a universal mean-reversion estimator applicable to any price series without re-fitting. Applied to four energy markets---Italian natural gas (PSV price), Italian electricity (PUN price), US Henry Hub, and US PJM West Hub---spanning log-return kurtosis from near-Gaussian to strongly heavy-tailed, the TCN yields robust, model-free estimates not conditioned on any distributional hypothesis.

Abstract: Mpox re-emerged as a global public health concern during the 2022 international out-break, underscoring the necessity of preparedness among future healthcare professionals. This study sought to evaluate knowledge and attitudes toward Mpox among medical students in Bulgaria and North Macedonia. A cross-sectional, online survey was con-ducted from May to September 2022 among undergraduates attending medical universi-ties in both nations. The questionnaire evaluated demographic variables, knowledge of Mpox, and attitudes toward conspiracy theories associated with the emerging infectious disease. A total of 1,313 students participated, with a mean age of 22.6 ± 4.4 years and 63.7% being female. While 56.3% of respondents were familiar with Mpox, hardly 16.9% indicated having received formal or specialized information regarding the disease. Signif-icant information deficiencies were observed: merely 38.1% accurately acknowledged that antibiotics are ineffective against Mpox, and 25.0% were knowledgeable of the availability of vaccinations for prophylaxis. Common misconceptions regarding transmission and resemblances to other vesicular illnesses were prevalent. Attitudinal research indicated significant uncertainty and partial support for conspiracy theories concerning new path-ogens. The findings reveal inadequate readiness among prospective healthcare workers and highlight the necessity to enhance medical education on emerging infectious illnesses to facilitate early detection, risk communication, and epidemic preparedness in South-eastern Europe.

Abstract: This paper represents a further academic deepening and upgrading of the authors' 2019 publication A Hypothesis on the Spatial Motion Mode of Photons. It should be explicitly stated that this paper falls within the category of natural philosophical thought experiments—its core value lies in constructing a unified physical image of the nature of light through rigorous logical deduction, and proposing verifiable theoretical hypotheses and experimental schemes; the validity of all conclusions must ultimately be verified by rigorous and extensive scientific experiments before being incorporated into the theoretical system of physics. As a foundational concept of quantum mechanics, the wave-particle duality of light has been accompanied by profound philosophical perplexities and theoretical tensions since its proposal, becoming a core bottleneck in the integration of classical and quantum physics. This paper systematically sorts out the logical incompleteness in the current quantum interpretation system—including the self-negation of the complementarity concept, the problem of photon localization, the fundamental opposition between the statistical and non-statistical interpretations of the wave function, and the philosophical controversy over the Heisenberg Uncertainty Principle, revealing the inherent contradictions of the traditional wave-particle duality framework. On this basis, adopting classical physical images and the logic of reduction to absurdity, and based on six axioms and six preparatory propositions, this paper puts forward a natural philosophical hypothesis on the essence of photons: a photon is an energetic mass point with a diameter smaller than the Planck length, moving in a uniform spiral linear motion in space. The paper deduces the core characteristics such as velocity frequency, and wavelength of the photon's uniform spiral linear motion, and designs three operable, repeatable, and quantifiable physical experimental schemes to provide specific paths for the empirical verification of the hypothesis. The research deduces that the angular momentum of photon spatial motion (excluding photon spin motion) is always the reduced Planck constant ℏ , the energy E=mc² is naturally unified with E=hν (the standard formula for wave energy), and the standard expression of the Heisenberg Uncertainty Principle ΔxΔpₓ≥ℏ /2 can be given a classical physical interpretation from the perspective of superposition of measurement deviations. This paper systematically responds to potential questions regarding the origin of photon particle nature, wave nature, and compatibility with relativity, arguing that the hypothesis provides a logically consistent and clearly visualized path for understanding the nature of light, builds a new natural philosophical framework for the integration of quantum and classical theories of light, and also offers a new thinking perspective for the paradigm shift in the study of the nature of light.

Abstract: Translation process research (TPR) relies on objective behavioral data to uncover the cognitive mechanisms underlying translation. This paper provides a comprehensive methodology for using Translog-II, a specialized tool for recording user activity data during translation tasks. We outline the complete experimental workflow—from project configuration to data collection—demonstrated through an English-to-Chinese translation-from-scratch case study. The study details the integration of Translog-II with the CRITT Translation Process Research Database (TPR-DB) to facilitate advanced post-processing. Key technical challenges are addressed, specifically the complexities of keystroke-to-word mapping for logo-graphic scripts requiring Input Method Editors (IMEs). We further demonstrate automated alignment protocols, multidimensional error annotation, and data visualization techniques utilizing Python scripts and Shiny R interfaces. The results indicate that while automated mapping is generally robust, specific technical noise, particularly regarding long deletions, can be mitigated through systematic analysis. Ultimately, this protocol establishes a reproducible framework for exploring translator behavior, enhancing the precision of data-driven insights into cognitive translation processes.

Abstract: This paper presents a certification-oriented, system-level argument that Linux is fundamentally unsuitable for safety-critical avionics. Because Linux is a feature-rich, high-performance general-purpose OS, it exhibits open and dynamic execution semantics that cannot be finitely bounded or frozen at integration time. Two consequences follow. First, airworthiness infeasibility: an oversized TCB, prohibitive DO-330 toolchain qualification burden, and continuous patch churn that prevents stable, certifiable baselines. Second, semantic complexity: temporal non-isolation and spatial non-isolation, materializing as mutable logical-to-physical mappings, driver-induced contamination of global kernel state, and lack of fault containment. We consolidate these observations into an avionics-oriented OS evaluation framework that makes certification implications explicit—closed-world timing analysis at the partition level, provable spatial and fault isolation, TCB minimization, and lifecycle-stable evidence under DO-178C/DO-330 and ARINC 653. The framework turns architectural properties into concrete certification risks and provides actionable guidance for OS selection and governance in integrated modular avionics.

Abstract: The COVID-19 pandemic has spread rapidly across the world and caused several economic, social, and demographic impacts, even though there were strong geographical disparities. This study aims to assess the effect of socio-demographic factors and the use of non conventional medicines on COVID-19 risk perception in West Africa using Structural Equation Modeling (SEM) approach. A quantitative survey was conducted in four countries (Benin, Togo, Ghana and Côte d’Ivoire). Data were collected on demographic characteristics, COVID-19 risk perception (risk feeling and risk analysis), affective attitude, trust predictors and non-conventional medicine. Nominal polychotomous logistic regression, binary logistic regression and partial least squares were used for the data analysis. Among the respondents 59.11% from the in-person survey, 28.08% were from Benin, 32.84% from Côte d’Ivoire, 24.96% from Togo and 14.12% from Ghana. The results showed a very high level of risk perception within the countries. Participants aged between 18 and 40 used less non-conventional medicine. Also, people with a low level of education or no formal education often perceive a higher risk associated with COVID-19 and use more non-conventional medicine than others. The PLS-SEM model’s loadings were higher compared to those of the Consistent PLS (PLSc-SEM), but the Consistent PLS showed robust values in the structural model with lower RMSE than the linear model. Our results also indicated that non-conventional medicine has a positive relationship with COVID-19 risk perception. For decision-makers and health workers, this research underscores the importance of unconventional medicine and the emotional state of local population in managing epidemic.

Abstract: Approximately 10% of the general population reports a penicillin allergy, making it one of the most commonly documented drug allergies in clinical practice. Yet formal evaluation confirms true hypersensitivity in fewer than 10% of these cases. This gap has practical consequences. Patients who carry an inaccurate allergy label are more likely to receive broader-spectrum alternative antibiotics, with downstream effects on cost, adverse drug events, and antimicrobial resistance. Although primary care physicians are often the first to record these labels and the ones who face their consequences most often in daily prescribing, they have remained peripheral to most systematic de-labeling efforts. In this narrative review, we examine how antibiotic allergy labels arise, why they persist, and what they cost—clinically, economically, and from a stewardship perspective. We also discuss emerging approaches to reassessment in primary care, along with the possible role of digital health tools and patient education in improving the accuracy of allergy documentation.

Abstract: Hydroponic fodder production can be applied to a wide range of forage crops, optimizing the use of water, arable land, and other resources in a sustainable manner. This study aimed to evaluate the effects of hydroponically sprouted seeds on bull meat quality. Wheat, barley, alfalfa, and peas were germinated in a hydroponic system for seven days, and dairy–meat crossbred bulls were fed these sprouts for 18 months. The chemical composition of the sprouted seeds, including proteins, fats, fiber, mineral elements, and amino and fatty acids, was analyzed. Samples of the Longissimus dorsi (LD) muscle were collected from the carcasses for comprehensive meat quality assessment. The study revealed that while sprouted grains did not significantly alter the chemical composition of meat, they influenced its physical characteristics, depending on the type of grain. Meat from bulls fed sprouted alfalfa seeds was significantly lighter in color and contained less water. The inclusion of sprouted grains also positively affected the amino acid and fatty acid profiles. The content of undesirable saturated fatty acids was 13.78–15.70% lower compared with meat from the control group. Furthermore, meat from bulls receiving sprouted alfalfa seeds contained 2.86% more essential amino acids, while meat from bulls fed sprouted peas contained 0.58% more than the control. Overall, the addition of sprouted grains enhanced the biological value of beef protein, with alfalfa seeds demonstrating the greatest effect on protein integrity indicators.

Abstract:

Jatropha curcas L. is a bioenergy crop of interest because of the high oil content in its seeds suitable for conversion into biofuels. However, its oil content is extremely variable among accessions and the mechanism of oil accumulation is poorly understood in this oleaginous species. In this study we analyzed cloned plants of three chemotypes of J. curcas collected in Chiapas, Mexico: CAC-3, COM-1 and MAP-2. All are monoecious and accumulating different amounts of seed oil: 10 %, 30 % and 54 %. We studied the expression of the β-ketoacyl-acyl carrier protein (ACP) synthase genes (KAS) in developing seeds and their relationship with the content and composition of the oil. Differences of the levels of expression of the KASI and KASII genes were found, while KASIII gene was expressed at high levels in all three chemotypes. The expression of KASI and KASII was statistically associated to the oil accumulation. Results of this study are discussed based on the regulation of the transcription of the KAS genes, in order to contribute to the understanding of the oil accumulation in the seed and could be of value for designing biotechnological strategies with which to improve this species.

Abstract: Large Language Model (LLM) agents are increasingly deployed to interact with untrusted external data, exposing them to Indirect Prompt Injection (IPI) attacks. While current black-box defenses (i.e., model-agnostic methods) such as “Sandwich Defense” and “Spotlighting” provide baseline protection, they remain brittle against adaptive attacks like Actor-Critic (where injections evolve to better evade LLM’s internal defense). In this paper, we introduce Real User Instruction (RUI), a lightweight, black-box middleware that enforces strict instruction-data separation without model fine-tuning. RUI operates on three novel mechanisms: (1) a Privileged Channel that encapsulates user instructions within a cryptographic-style schema; (2) Explicit Adversarial Identification, a cognitive forcing strategy that compels the model to detect and list potential injections before response generation; and (3) Dynamic Key Rotation, a moving target defense that re-encrypts the conversation state at every turn, rendering historical injection attempts obsolete. We evaluate RUI against a suite of adaptive attacks, including Context-Aware Injection, Token Obfuscation, and Delimitation Spoofing. Our experiments demonstrate that RUI reduces the Attack Success Rate (ASR) from 100% (undefended baseline) to less than 8.1% against cutting-edge adaptive attacks, while maintaining a Benign Performance Preservation (BPP) rate of over 88.8%. These findings suggest that RUI is an effective and practical solution for securing agentic workflows against sophisticated, context-aware adversaries.

Abstract: Abstract To assess the electromagnetic effect on the children’s sensitive organs when they using the smartwatches, this study analyzes the electromagnetic dose absorbed by the children, especially calculate the combind electromagnetic exposure, We propose a multi-frequency smartwatch antenna (GPS L1, LTE FDD band1, 2.4G Wi-Fi/Bluetooth) and construct a 6-year-old human model including ten tissues from three sensitive organs (brain, eyes, heart). The Specific Absorption Rate (SAR) distributions are simulated under speaking and listening postures at different frequencies using CST Studio Suite. Furthermore, the SAR distributions under multi-frequency combined electromagnetic exposure are evaluated to investigate the superposition effects of electromagnetic fields. The results show that, when the child uses the smartwatch for 4G communication in the listening posture, the maximum local SAR reaches 1.683 W/kg, which is nearly half of the ICNIRP exposure limit. Electromagnetic radiation in the child’s brain is mainly concentrated on the surface of the cerebrum and cerebellum, while the radiation in the eyes is mainly distributed in the outer and anterior tissues. Under combined electromagnetic exposure, the SAR values of tissues increase by 1.17 to 3.53 times compared with single-frequency conditions but remain within safety limits. Considering the long-term use of smartwatches, the potential health risks to developing children still deserve attention.

Abstract: Astaxanthin (AST), despite its high bioactivity, exhibits poor stability and low bioavailability due to its strong lipophilicity and inherent degradation susceptibility. To overcome such a challenge, we developed a food-grade oleogel delivery system using a soy protein-arabinoxylan (SA) glycosylated complex modulated by different concentrations (0.5%–3%) of sucrose ester (SE) or soy lecithin. We show that the emulsifier concentration has a non-linear effect on the oleogel microstructure: an optimal level of 1% had a significant impact on the interfacial compactness and network density, giving rise to improved thermal stability, rheological strength and AST encapsulation efficiency (81.27%). During in vitro digestion, the SA matrix in combination with emulsifiers allowed gastric protection and intestinal-targeted release of AST with a bioaccessibility of up to 88.84% (SAO-SE-AST). This controlled-release profile directly translated into enhanced in vivo antioxidant efficacy in wild-type Bristol N2 Caenorhabditis elegans as evidenced by reduced lipofuscin accumulation, elevated thermotolerance (survival rate: 64.44%-73.33%), suppressed reactive oxygen species levels and activation of endogenous antioxidant enzymes (superoxide dismutase as well as glutathione peroxidase). Collectively, this research has uncovered that food-grade emulsifiers are not only stabilizers, but also key regulators of oleogel architecture and bioactive functionality. These results provide a structure-digestion-bioactivity correlation for protein-polysaccharide oleogels, representing a rational design strategy for high-performance delivery systems of lipid-soluble nutraceuticals.

Abstract: In art and architecture, synchronicity—the parallel emergence of related ideas without direct causal links—has long shaped the evolution of design cultures. Recently, heritage architecture across Europe has become an active stage for fashion shows, art exhibitions, and live performances, encouraging audiences to experience buildings not merely as backdrops but as performative, meaning-generating spaces. Italy offers a significant field of observation through projects positioned beside restoration. While not constituting restoration activities in a conventional sense, these interventions engage critically with existing heritage by activating processes of reuse, management, and cultural valorisation. Such strategies contribute to sustainability on multiple levels: they address architectural and conservation constraints while simultaneously supporting environmental preservation, limiting land consumption and urban sprawl, reducing waste, and broadening public access to heritage. Through the analysis of selected case studies, this paper investigates the dialogue between performance art and heritage architecture as a sustainable practice. The discussion is enriched by interviews with three professionals whose work in central Italy exemplifies innovative approaches to engaging communities with their surrounding heritage. The study argues that performative practices can operate as complementary tools to restoration, fostering new forms of cultural sustainability and expanding contemporary understandings of heritage stewardship.

Abstract: Aim: To evaluate anxiety, depression, perceived stress, and sleep quality in the parents of children who underwent liver transplantation in Turkey. The impact of other factors on mental health status were also examined. Method: This was a single-center, cross-sectional study including the parents of 50 children after liver transplantation. Major sociodemographic variables included parental age, sex, education, chronic disease, and immigration status. We also recorded children’s demographics, transplant-related data, follow-up findings, and mental health status. Instruments for psychiatric assess-ment included the Generalized Anxiety Disorder 7-item scale (GAD-7; anxiety), Patient Health Questionnaire-9 (PHQ-9; depression), Perceived Stress Scale-10 (PSS-10; stress), and Pittsburgh Sleep Quality Index (PSQI; sleep quality). Results: We enrolled 50 parents of 50 pediatric liver transplant recipients (28 fathers, 22 mothers, mean age: 40.10 ± 6.65). Time since transplantation showed weak negative correlations with PHQ-9 and GAD-7. Stress (PSS) levels had weak to strong positive correlations with PSQI, PHQ-9, and GAD-7. Sleep quality (PSQI) was positively correlated with PHQ-9 and GAD-7. Depressive findings (PHQ-9) were strongly and positively correlated with GAD-7. High PHQ-9 scores were found to be independently associated with shorter time since transplant (p=0.006) and high PSS (p=0.011). High GAD-7 scores were independently associated with shorter time since transplant (p=0.034) and high PSS (p=0.005). Conclusion: The parents of pediatric liver transplant recipients experience high levels of stress, sleep issues, depression, and anxiety, which demonstrate multiple correlations.

Abstract: Background/Objectives: Rapid Eye Movement (REM) Sleep Behavior Disorder (RBD) is characterized by dream enactment due to reduced physiological muscle atonia during REM sleep and is clinically relevant as a potential prodromal marker for neurodegenerative disorders. This study aims to evaluate whether normalized beta-band power extracted from poly-somnographic signals can differentiate RBD subjects from healthy controls, and to compare the discriminative behavior of C4–A1 EEG versus EMG1–EMG2 channels during REM sleep. Methods: Polysomnographic recordings were obtained from the PhysioNet CAP Sleep Data-base. One-minute epochs were analyzed across sleep stages, with emphasis on REM. Signals were preprocessed to remove DC offset and were windowed with overlap prior to spectral estimation. Short time–frequency analysis of power spectral density (PSD) was applied to compute band-limited power in standard EEG frequency ranges (delta, theta, alpha, beta). Band power values were normalized by total spectral power to derive nor-malized indices. Comparative feature analysis was performed for C4–A1 and EMG1–EMG2 channels. Results: Normalized beta-band power during REM sleep showed clear separation between healthy subjects and RBD patients. In the C4–A1 channel, normalized beta power was higher in RBD than controls (controls: 0.0010–0.0049; RBD: 0.0076–0.014). In the EMG1–EMG2 channel, the difference was more pronounced (controls: 0.0020–0.0089; RBD: 0.053–0.0791). Conclusions: Normalized beta-band power, particularly during REM sleep, is a promising, low-complexity marker for RBD detection. The stronger separation in EMG1–EMG2 sug-gests that targeted channel selection may enhance practical screening pipelines for sleep disorder assessment.