Search Results (4,661)

Continuous blood pressure (BP) monitoring provides valuable insight into the body’s dynamic cardiovascular regulation across various physiological states such as physical activity, emotional stress, postural changes, and sleep. Continuous BP monitoring captures different variations in systolic and diastolic pressures, reflecting autonomic nervous system activity, vascular compliance, and circadian rhythms. This enables early identification of abnormal BP trends and allows for timely diagnosis and interventions to reduce the risk of cardiovascular diseases (CVDs) such as hypertension, stroke, heart failure, and chronic kidney disease as well as chronic stress or anxiety disorders. To facilitate continuous BP monitoring, we propose an AI-powered estimation framework. The proposed framework first uses an expert-driven feature engineering approach that systematically extracts physiological features from photoplethysmogram (PPG)-based arterial pulse waveforms (APWs). Extracted features include pulse rate, ascending/descending times, pulse width, slopes, intensity variations, and waveform areas. These features are fused with demographic data (age, gender, height, weight, BMI) to enhance model robustness and accuracy across diverse populations. The framework utilizes a Tab-Transformer to learn rich feature embeddings, which are then processed through an ensemble machine learning framework consisting of CatBoost, XGBoost, and LightGBM. Evaluated on a dataset of 1000 subjects, the model achieves Mean Absolute Errors (MAE) of 3.87 mmHg (SBP) and 2.50 mmHg (DBP), meeting British Hypertension Society (BHS) Grade A and Association for the Advancement of Medical Instrumentation (AAMI) standards. The proposed architecture advances non-invasive, AI-driven solutions for dynamic cardiovascular health monitoring. Full article

Background: Diabetes and cancer are two of the most life-threatening disorders affecting individuals of all ages worldwide. This study aimed to develop a novel Acrocomia aculeata (bocaiuva) fruit pulp oil-loaded nanoemulsion and evaluate its inhibitory effects on α-glucosidase and pancreatic lipase, as well as its antiglycant activity and cytotoxicity against cancer cells. Additionally, this study assessed the impact of both the oil and the nanoemulsion on blood cells. Methods: The pulp oil was extracted by cold pressing. The oil’s physicochemical properties were determined according to the AOAC and the Brazilian Pharmacopeia. The lipid profile was performed by GC-MS. The nanoemulsion was prepared by the phase inversion method using ultrasonic stirring for particle size reduction and for homogenization. Response Surface Methodology was used for optimizing nanoemulsion preparation. Enzyme inhibition tests were conducted using assay kits. Cytotoxicity in cancer cells was evaluated using the Sulforhodamine B assay. Results: Comprehensive physicochemical and chemical characterization of bocaiuva oil was performed, identifying oleic acid (71.25%) as the main component. The oil contains 23.04% saturated fatty acids, 73.79% monounsaturated acids, and 3.0% polyunsaturated fatty acids. The nanoemulsion (particle size 173.6 nm; zeta potential −14.10 mV) inhibited α-glucosidase (IC₅₀: 43.21 µg/mL) and pancreatic lipase (IC₅₀: 41.99 µg/mL), and revealed a potent antiglycation effect (oxidative IC₅0: 18.36 µg/mL; non-oxidative pathway IC₅₀: 16.33 µg/mL). The nanoemulsion demonstrated good cytotoxicity and selectivity against prostate cancer cells (IC₅₀: 19.13 µg/mL) and breast cancer cells (IC₅₀: 27.22 µg/mL), without inducing hemolysis, platelet aggregation, or anticoagulant effects. Conclusions: In this study, a comprehensive physical and chemical characterization of bocaiuva fruit pulp oil was conducted for the first time as a preliminary step toward its future standardization as an active ingredient in cosmetic and pharmaceutical formulations. The resulting nanoemulsion represents a novel alternative for managing diabetes and cancer. Although the nanoemulsion exhibited lower cytotoxicity compared to doxorubicin, it remains promising due to its composition of essential fatty acids, phenols, and carotenoids, which offer multiple health benefits. Further studies are needed to validate its efficacy and safety in clinical applications. Full article

Background/objective: Tailoring involves adapting research findings and evidence to suit specific contexts and audiences. This study examines how international stroke guidelines can be tailored to address gait issues after a stroke. Methods: A three-phase consensus method approach was used. A 10-member health experts panel extracted recommendations from three national clinical guidelines in the first phase. In the second phase, 362 physiotherapists completed an online questionnaire to assess the feasibility of adopting the extracted recommendations. In the third phase, a 15-physical therapist consensus workshop was convened to clarify factors that might affect the tailoring process of the extracted recommendations of gait disorder rehabilitation. Results: In phase one, 21 recommendations reached consensus. In the second phase, 362 stroke physiotherapists rated the applicability of these recommendations: 14 rated high, 7 rated low, and none were rejected. The third phase, a nominal group meeting (NGM), explored four themes related to tailoring. The first theme, “organizational factors”, includes elements such as clinical setting, culture, and regulations. The second theme, “individual clinician factors”, assesses aspects like clinical experience, expertise, abilities, knowledge, and attitudes toward tailoring. The third theme, “patient factors”, addresses issues related to multimorbidity, comorbidities, patient engagement, and shared decision-making. The final theme, “other factors”, examines the impact of research design on tailoring. Conclusions: Tailoring international clinical guidelines involves multiple factors. This situation brings home the importance of a systematic strategy for tailoring that incorporates various assessment criteria to enhance the use of clinical evidence. Future research should investigate additional implementation theories to enhance the translation of evidence into practice. Full article

A State of Health (SOH) estimation of lithium-ion batteries is a core function of battery management systems, directly affecting the safe operation, lifetime prediction, and economic efficiency of batteries. However, existing methods still face challenges in balancing feature robustness and model generalization ability; for instance, some studies rely on features whose physical correlation with SOH lacks strict verification, or the models struggle to simultaneously capture the temporal dynamics of health factors and nonlinear mapping relationships. To address this, this paper proposes an SOH estimation method based on incremental capacity (IC) curves and a Temporal Convolutional Network—Relevance Vector Machine (TCN-RVM) model, with core innovations reflected in two aspects. Firstly, five health factors are extracted from IC curves, and the strong correlation between these features and SOH is verified using both Pearson and Spearman coefficients, ensuring the physical rationality and statistical significance of feature selection. Secondly, the TCN-RVM model is constructed to achieve complementary advantages. The dilated causal convolution of TCN is used to extract temporal local features of health factors, addressing the insufficient capture of long-range dependencies in traditional models; meanwhile, the Bayesian inference framework of RVM is integrated to enhance the nonlinear mapping capability and small-sample generalization, avoiding the overfitting tendency of complex models. Experimental validation is conducted using the lithium-ion battery dataset from the University of Maryland. The results show that the mean absolute error of the SOH estimation using the proposed method does not exceed 0.72%, which is significantly superior to comparative models such as CNN-GRU, KELM, and SVM, demonstrating higher accuracy and reliability compared with other models. Full article

Unconventional food plants (UFPs) are increasingly valued for their nutritional composition and bioactive potential. This study proposes a comprehensive characterization of the chemical and bioactive properties of Pereskia aculeata Miller (Cactaceae) (PA); Xanthosoma sagittifolium (L.) Schott (Araceae) (XS); Stachys byzantina K. Koch (Lamiaceae) (SB); and inflorescences from three cultivars of Musa acuminata (Musaceae) var. Dwarf Cavendish, var. BRS Platina, and var. BRS Conquista (MAD, MAP, and MAC), including the assessment of physical, nutritional, phytochemical, and biological parameters. Notably, detailed phenolic profiles were established for these species, many of which are poorly documented in the literature. XS was characterized by a unique abundance of C-glycosylated flavones, especially apigenin and luteolin derivatives, rarely described for this species. SB exhibited high levels of phenylethanoid glycosides, particularly verbascoside and its isomers (up to 21.32 mg/g extract), while PA was rich in O-glycosylated flavonols such as quercetin, kaempferol, and isorhamnetin derivatives. Nutritionally, XS had the highest protein content (16.3 g/100 g dw), while SB showed remarkable dietary fiber content (59.8 g/100 g). Banana inflorescences presented high fiber (up to 66.5 g/100 g) and lipid levels (up to 7.35 g/100 g). Regarding bioactivity, PA showed the highest DPPH radical scavenging activity (95.21%) and SB the highest reducing power in the FRAP assay (4085.90 µM TE/g). Cellular antioxidant activity exceeded 2000% in most samples, except for SB. Cytotoxic and anti-inflammatory activities were generally low, with only SB showing moderate effects against Caco-2 and AGS cell lines. SB and PA demonstrated the strongest antimicrobial activity, particularly against Yersinia enterocolitica, methicillin-resistant Staphylococcus aureus (MRSA), and Enterococcus faecalis, with minimum inhibitory concentrations ranging from 0.156 to 0.625 mg/mL. Linear discriminant analysis revealed distinctive chemical patterns among the species, with organic acids (e.g., oxalic up to 7.53 g/100 g) and fatty acids (e.g., linolenic acid up to 52.38%) as key discriminant variables. Overall, the study underscores the nutritional and functional relevance of these underutilized plants and contributes rare quantitative data to the scientific literature regarding their phenolic signatures. Full article

Aquilaria sinensis (Lour.) Gilg, the exclusive botanical source of Chinese agarwood, holds significant medicinal value. This study investigated the agarwood-inducing potential of a Fusarium strain obtained through prior isolation work. Through integrated morphological characterization and molecular phylogenetic analysis, the strain was conclusively identified as Fusarium equiseti. GC-MS analysis revealed that fungal inoculation induced the synthesis of characteristic sesquiterpenes and aromatic compounds consistent with natural agarwood profiles. Quantitative determination demonstrated progressive accumulation of agarotetrol, a key quality marker, reaching 0.034%, 0.039%, and 0.038% at 2, 4, and 6 months post-inoculation, respectively—significantly exceeding levels from physical wounding (p < 0.05) and PDA control treatments. Histological examination showed characteristic yellow-brown oleoresin deposits concentrated in the inner phloem, mirroring the anatomical features of wild-type agarwood. Critical quality parameters measured in December-harvested samples included ethanol extractives (17.69%), chromone derivatives 2-[2-(4-methoxyphenyl) ethyl] chromone, and 2-(2-phenylethyl) chromone (2.13%), all meeting or surpassing the specifications outlined in the National Standard for Agarwood Classification (LY/T 3223-2020). These comprehensive findings establish F. equiseti as a promising microbial agent for sustainable agarwood production in A. sinensis plantations. Full article

In this paper, mussel shells were used to produce chitin, chitosan, and calcium acetate using chemical processes, searching for an alternative environmentally friendly biopolymer and calcium source. Mussel shells were treated with acetic acid as a demineralizing agent, resulting in separate solid fractions and calcium solution. The solid was further purified to produce chitin by deproteinization and decolorization processes, and then the deacetylation process was used to obtain chitosan. The calcium solution was evaporated to produce calcium acetate powder. The yields of extracted chitin, chitosan, and calcium acetate from 100 g of mussel shells were 2.98, 2.70, and 165.23 g, respectively. The prepared chitin, chitosan, and calcium acetate were analyzed by Fourier transform infrared (FTIR) spectrophotometry, X-ray diffraction (XRD), thermogravimetric analysis (TGA), and scanning electron microscope (SEM) to confirm the chemical and physical properties. The analysis results of chitin and chitosan revealed the similarity to chitosan derived from crustaceans and insects in terms of functional group, structure and morphologies. The prepared calcium acetate shows FTIR and XRD data corresponding to calcium acetate monohydrate (Ca(CH₃COO)₂·H₂O) similar to synthesized calcium acetate in previous research. In addition, the mineral contents of calcium acetate identified by X-ray fluorescence (XRF) analysis exhibit 97.8% CaO with non-toxic impurities. This work demonstrated the potential of the production process of chitin, chitosan, and calcium acetate for the development of a sustainable industrial process with competitive functional performance against the commercial chitin and chitosan production process using crustacean shells and supported the implementation of a circular economy. Full article

Strategies to interpret short-wave infrared hyperspectral images of rocks involve the application of analysis and classification steps that guide the extraction of geological and mineralogical information with the aim of creating mineral maps. Pre-existing strategies often rely on the use of statistical measures between reference and image spectra that are scene dependent. Therefore, classification thresholds based on statistical measures to create mineral maps are also scene dependent. This is problematic because thresholds must be adjusted between images to produce mineral maps of the same accuracy. We developed an innovative, knowledge-based strategy to perform mineralogical analyses and create classifications that overcome this problem by using physics-based wavelength positions of absorption features that are invariant between scenes as the main sources of mineral information. The strategy to interpret short-wave infrared hyperspectral images of rocks is implemented using the open source Hyperspectral Python package (HypPy) and demonstrated on a series of hyperspectral images of hydrothermally altered rock samples. The results show how expert knowledge can be embedded into a standardized processing chain to develop reproducible mineral maps without relying on statistical matching criteria. Full article

Awareness of design when planning public urban spaces assumes particular importance through its mission to meet the diverse needs of the different segments within the community. The elderly is considered one of the pivotal segments, with their influence on strengthening social cohesion, fortifying values, and upholding traditions. On the other hand, such a segment demands special physical, behavioral, and mental requirements that would entail specific consideration in the design process of public common spaces. The study aimed to identify and evaluate the most relevant and important indicators pertaining to the most effective design of an age-friendly public space, with community parks taken as a particular case. The study relies on a mixed approach, combining desk research, expert views, the Delphi technique, and the Analytical Hierarchy Process to achieve that purpose. It resulted in a group of sourced, filtered, and evaluated indicators classified into Physical, Experiential, and Social/Emotional categories, which were evaluated by a mixed representative group of academics, practitioners, governmental officials, and end users, being the elderly or their caretakers. Focus was placed on the central park in the Dahiyat Al-Hussein suburb in Amman, Jordan, which was utilized as a contextual case through which a refined design framework was extracted. This framework serves as a potential base that can be expanded and adapted to create a more generalizable model. Full article

In modern industrial environments, quickly and accurately identifying faults is crucial for ensuring the smooth operation of production processes. Non-negative Matrix Factorization (NMF)-based fault detection technology has garnered attention due to its wide application in industrial process monitoring and machinery fault diagnosis. As an effective dimensionality reduction tool, NMF can decompose complex datasets into non-negative matrices with practical and physical significance, thereby extracting key features of the process. This paper presents a novel approach to fault detection in industrial processes, called Graph-Regularized Orthogonal Non-negative Matrix Factorization with Itakura–Saito Divergence (GONMF-IS). The proposed method addresses the challenges of fault detection in complex, non-Gaussian industrial environments. By using Itakura–Saito divergence, GONMF-IS effectively handles data with probabilistic distribution characteristics, improving the model’s ability to process non-Gaussian data. Additionally, graph regularization leverages the structural relationships among data points to refine the matrix factorization process, enhancing the robustness and adaptability of the algorithm. The incorporation of orthogonality constraints further enhances the independence and interpretability of the resulting factors. Through extensive experiments, the GONMF-IS method demonstrates superior performance in fault detection tasks, providing an effective and reliable tool for industrial applications. The results suggest that GONMF-IS offers significant improvements over traditional methods, offering a more robust and accurate solution for fault diagnosis in complex industrial settings. Full article

Background: This paper aims to conduct an umbrella review of the effects of physical activity programmes for older adults (aged 70 and above). Methods: Comprehensive literature searches were conducted in MEDLINE, PubMed, EMBASE, PsychINFO, and Cochrane Library databases for English SRs through July 2024. Inclusion criteria were systematic reviews that included randomised controlled trials examining physical activity interventions in older adults. The data extracted were participant characteristics, physical activity interventions, and outcomes examined. A synthesis of results was conducted using the PRISMA guidelines, and the quality of the studies was assessed using the Assessment of Multiple Systematic Reviews-2 (AMSTAR-2). Results: Ten systematic reviews on 186 research articles were included. The AMSTAR-2 revealed that 4 out of 10 reviews were of high quality and 1 out of 10 were of moderate quality. The study samples in each systematic review ranged from 6 to 1254 participants. The total overall sample size for the 10 included studies was 22,652 participants. Across the included reviews, there was mixed evidence on whether physical activity interventions could improve outcomes in older adults across various settings. Conclusions: Sample sizes and findings in each included systematic review varied. The findings of this review emphasise the importance of physical activity as a vital component in maintaining and enhancing health, as well as combating poor health as we age. It also highlights the need for a deeper understanding of the specific physical activity requirements for those aged 70 and above. Future systematic reviews may focus on streamlined reporting of dosing of physical activity and specific intervention types, such as group versus single. Full article

Objective: To systematically review the scientific literature on lysergic acid amide (LSA), focusing on its physical, neurobiological, and social effects, as well as its potential risks and therapeutic uses. Methods: A systematic review was conducted across PubMed, Google Scholar, and Web of Science up to December 2023, using keywords such as “ergine,” “lysergic acid amide,” and “legal high.” Studies were included if they reported original human data on the physical, neurobiological, psychological, or social effects of LSA; seventeen studies were included. Animal studies, in vitro research, and non-original articles were excluded. Two independent reviewers screened and selected the studies, with a third resolving discrepancies. Data were extracted using a standardized form. The review followed PRISMA guidelines and was prospectively registered on the Open Science Framework. Results: LSA is primarily consumed through preparations made from the seeds of Convolvulaceae plants. Reported effects include euphoria, hallucinations, nausea, and anxiety. Severe adverse outcomes, such as psychosis, hypertension, and hospitalization, have also been documented. Some evidence suggests its potential therapeutic application for cluster headaches. However, variability in dosing and misinformation on digital platforms heighten the risks associated with LSA use. Conclusions: LSA poses significant health risks, exacerbated by online misinformation and variability in its effects, and a lack of scientific studies. Further research is essential to clarify its pharmacological profile, establish guidelines for safe use, and raise public awareness about its dangers. Full article

The aging of China’s population has created significant challenges for the mental health of older adults. However, limited research has examined how public sports facility availability in living communities supports older adults’ mental health. To explore this association, data were extracted from the 2016 China Longitudinal Aging Social Survey, which involved 7811 respondents. The ordinary least squares model and the instrumental variable approach were employed to test the association between public sports facility availability in Chinese older adults’ living communities and their mental health. The bootstrapping method was used to estimate the mediating effect of physical activity and life satisfaction. The results indicate that public sports facility availability in living communities was significantly correlated with a decrease in depressive symptoms among older people (coefficient = −0.225; p < 0.01), which suggests that a greater availability of public sports facilities in living communities is related to the better mental health of older adults. The results of the mediation analysis show that physical activity and life satisfaction were identified as mediating mechanisms. This study suggests that increasing the availability of public sports facilities in older adults’ living communities can alleviate depression and promote better mental health. Our findings provide valuable policy implications for enhancing public sports infrastructure and promoting healthy aging. Full article

Background: Pre-season training is critical for developing tolerance to high physical demands in professional soccer, and nitric oxide (NO) precursors such as dietary nitrate (NO₃⁻) and citrulline malate (CM) can support performance and recovery during this demanding phase. This study aimed to examine the effects of a four-week supplementation protocol combining 500 mg of NO₃⁻ from amaranth extract and 8 g of CM (NIT + CM) on external training load and post-match recovery in professional female soccer players during pre-season. Methods: A randomized, double-blind, placebo-controlled trial was conducted with 34 female soccer players who received either the NIT + CM product or a placebo for four weeks during pre-season. Global positioning system (GPS)-derived external load was recorded throughout the intervention. Performance tests—a countermovement jump (CMJ) test and the Wingate anaerobic test (WAnT)—and blood sampling for plasma NO₃⁻ and nitrite (NO₂⁻) concentrations were conducted at baseline and the day after a competitive match. Results: The supplementation with NIT + CM increased maximal speed (Vmax) throughout training and match play. During post-match testing, the NIT + CM group exhibited a significantly smaller decline in mean (P_mean) and minimum (P_min) power during the WAnT, along with reduced power loss in both the first (0–15 s) and second (15–30 s) intervals. Plasma NO₃⁻ concentrations significantly increased from baseline in the NIT + CM group and remained elevated 24 h after the final dose, confirming sustained systemic exposure. Conclusions: Chronic NIT + CM supplementation may enhance Vmax and help preserve anaerobic performance the day after a match. These effects could reflect improved tolerance to high training loads and sustained NO₃⁻ availability during recovery. Full article

Mangrove forests are vital blue carbon (BC) ecosystems that significantly contribute to climate change mitigation through carbon sequestration. Accurate, scalable, and cost-effective methods for estimating carbon stocks in these environments are essential for conservation planning. In this study, we assessed the potential of drones, also known as unmanned aerial vehicles (UAVs), for estimating above-ground biomass (AGB) and BC in Avicennia marina stands by integrating drone-based canopy measurements with field-measured tree heights. Using structure-from-motion (SfM) photogrammetry and a consumer-grade drone, we generated a canopy height model and extracted structural parameters from individual trees in the Melgonze mangrove patch, southern Iran. Field-measured tree heights served to validate drone-derived estimates and calibrate an allometric model tailored for A. marina. While drone-based heights differed significantly from field measurements (p < 0.001), the resulting AGB and BC estimates showed no significant difference (p > 0.05), demonstrating that crown area (CA) and model formulation effectively compensate for height inaccuracies. This study confirms that drones can provide reliable estimates of BC through non-invasive means—eliminating the need to harvest, cut, or physically disturb individual trees—supporting their application in mangrove monitoring and ecosystem service assessments, even under challenging field conditions. Full article