Search Results (1,230)

Background: The consumption of coffee has been widely debated regarding its effects on health. This study aims to analyze the correlations between daily coffee intake and sleep, blood pressure, anthropometric measurements, and biochemical markers in individuals with type 2 diabetes (T2D) and hypertension over a 12-month period. Methods: An observational study was conducted with 40 participants with T2D and hypertension, comprising 20 females and 20 males. Participants were monitored for their daily coffee consumption over a 12-month period, being assessed every 3 months. Linear regression was utilized to assess interactions and relationships between variables, providing insights into potential predictive associations. Additionally, correlation analysis was performed using Pearson’s and Spearman’s tests to evaluate the strength and direction of linear and non-linear relationships. Statistical significance was set at p < 0.05. Results: Significant changes were observed in fasting blood glucose (FBG), glycated hemoglobin (HbA1c), body weight, body mass index, sleep duration, nocturnal awakenings, and waist-to-hip ratio (p < 0.05) over the 12-month study in both sexes. No significant differences were noted in the remaining parameters (p > 0.05). The coffee consumed by the participants was of the “traditional type” and contained sugar (2 g per cup) for 100% of the participants. An intake of 4.17 ± 0.360 cups per day was found at baseline and 5.41 ± 0.316 cups at 12 months (p > 0.05). Regarding correlation analysis, a higher coffee intake was significantly associated with shorter sleep duration in women (r = −0.731; p = 0.037). Conversely, greater coffee consumption correlated with lower LDL cholesterol (LDL-C) levels in women (r = −0.820; p = 0.044). Additionally, a longer sleep duration was linked to lower FBG (r = −0.841; p = 0.031), HbA1c (r = −0.831; p = 0.037), and LDL-C levels in women (r = −0.713; p = 0.050). No significant correlations were observed for the other parameters in both sexes (p > 0.05). Conclusions: In women, coffee consumption may negatively affect sleep duration while potentially offering beneficial effects on LDL-C levels, even when sweetened with sugar. Additionally, a longer sleep duration in women appears to be associated with improvements in FBG, HbA1c, and LDL-C. These correlations emphasize the importance of a balanced approach to coffee consumption, weighing both its potential health benefits and drawbacks in postmenopausal women. However, since this study does not establish causality, further randomized clinical trials are warranted to investigate the underlying mechanisms and long-term implications—particularly in the context of T2D and hypertension. Full article

Amidst the escalating demand for high-precision structural health monitoring in large-scale engineering applications, carbon fiber-reinforced polymer fiber Bragg grating (CFRP-FBG) sensors have emerged as a pivotal technology for fatigue life evaluation, owing to their exceptional sensitivity and intrinsic immunity to electromagnetic interference. A time-series predictive architecture based on long short-term memory (LSTM) networks is developed in this work to facilitate intelligent fatigue life assessment of structures subjected to complex cyclic loading by capturing and modeling critical spectral characteristics of CFRP-FBG sensors, specifically the side-mode suppression ratio and main-lobe peak-to-valley ratio. To enhance model robustness and generalization, Principal Component Analysis (PCA) was employed to isolate the most salient spectral features, followed by data preprocessing via normalization and model optimization through the integration of the Adam optimizer and Dropout regularization strategy. Relative to conventional Backpropagation (BP) neural networks, the LSTM model demonstrated a substantial improvement in predicting the side-mode suppression ratio, achieving a 61.62% reduction in mean squared error (MSE) and a 34.99% decrease in root mean squared error (RMSE), thereby markedly enhancing robustness to outliers and ensuring greater overall prediction stability. In predicting the peak-to-valley ratio, the model attained a notable 24.9% decrease in mean absolute error (MAE) and a 21.2% reduction in root mean squared error (RMSE), thereby substantially curtailing localized inaccuracies. The forecasted confidence intervals were correspondingly narrower and exhibited diminished fluctuation, highlighting the LSTM architecture’s enhanced proficiency in capturing nonlinear dynamics and modeling temporal dependencies. The proposed method manifests considerable practical engineering relevance and delivers resilient intelligent assistance for the seamless implementation of CFRP-FBG sensor technology in structural health monitoring and fatigue life prognostics. Full article

Background and Objectives: Obesity and type 2 diabetes (T2D) are closely linked and associated with a higher risk of complications. This study aims to evaluate the effectiveness of once-weekly semaglutide in achieving a composite endpoint of A1C and weight reduction. Materials and Methods: This retrospective cohort study assessed the effectiveness of semaglutide in obese patients with T2D at a tertiary care hospital in Saudi Arabia. This study included patients who received semaglutide treatment for 12 months, and the endpoint was reducing A1C by ≥ 1% and body weight by ≥ 5% after 12 months of starting semaglutide. Secondary endpoints include predictors of achieving the composite endpoint and the effect on the lipid profile. Results: The present study enrolled 459 participants, with dyslipidemia and hypertension being the most common comorbidities. After 12 months of treatment with semaglutide, 42% of the patients achieved the composite endpoint. Semaglutide significantly reduced weight, BMI, A1C, FBG, total cholesterol, LDL, and triglycerides. The subgroup analysis showed that patients who achieved the composite endpoint were younger and had significantly lower use of insulin. Females in the study had significantly higher BMI, A1C, and HDL levels and lower levels of triglycerides compared to males. Multivariate analysis revealed that baseline BMI (aOR = 0.953; 95% CI: 0.915 to 0.992; p = 0.02), baseline A1C (aOR = 1.213; 95% CI: 1.062 to 1.385; p = 0.004), and receiving insulin (aOR = 0.02; 95% CI: 0.001 to 0.343; p = 0.007) were significant predictors of composite endpoint achievement. Conclusions: Semaglutide is a valuable option for the treatment of obese patients with T2D. This study found that semaglutide is effective in reducing weight and A1C and improving the lipid profile. The predictors of achievement of the composite endpoint were lower baseline BMI, higher baseline A1C, and insulin non-use. Full article

To prolong the service life of asphalt pavement and reduce its maintenance cost, a fiber Bragg grating (FBG) sensor encapsulated in carboxylated carbon nanotube (CNT-COOH)-modified gel material suitable for strain monitoring of asphalt pavement was developed. Through tensile and bending tests, the effects of carboxylated carbon nanotubes on the mechanical properties of gel materials under different dosages were evaluated and the optimal dosage of carbon nanotubes was determined. Infrared spectrometer and scanning electron microscopy were used to compare and analyze the infrared spectra and microstructure of carbon nanotubes before and after carboxyl functionalization and modified gel materials. The results show that the incorporation of CNTs-COOH increased the tensile strength, elongation at break, and tensile modulus of the gel material by 36.2%, 47%, and 17.2%, respectively, and increased the flexural strength, flexural modulus, and flexural strain by 89.7%, 7.5%, and 63.8%, respectively. Through infrared spectrum analysis, it was determined that carboxyl (COOH) and hydroxyl (OH) were successfully introduced on the surface of carbon nanotubes. By analyzing the microstructure, it can be seen that the carboxyl functionalization of CNTs improved the agglomeration of carbon nanotubes. The tensile section of the modified gel material is rougher than that of the pure epoxy resin, showing obvious plastic deformation, and the toughness is improved. According to the data from the calibration experiment, the strain and temperature sensitivity coefficients of the packaged sensor are 1.9864 pm/μm and 0.0383 nm/°C, respectively, which are 1.63 times and 3.61 times higher than those of the bare fiber grating. The results of an applicability study show that the internal structure strain of asphalt rutting specimen changed linearly with the external static load, and the fitting sensitivity is 0.0286 με/N. Combined with ANSYS finite element analysis, it is verified that the simulation analysis results are close to the measured data, which verifies the effectiveness and monitoring accuracy of the sensor. The dynamic load test results reflect the internal strain change trend of asphalt mixture under external rutting load, confirming that the encapsulated FBG sensor is suitable for the long-term monitoring of asphalt pavement strain. Full article

Carbon nanotube field-effect transistors (CNTFETs) are becoming a strong competitor for the next generation of high-performance, energy-efficient integrated circuits due to their near-ballistic carrier transport characteristics and excellent suppression of short-channel effects. However, CNT FETs with large diameters and small band gaps exhibit obvious bipolarity, and gate-induced drain leakage (GIDL) contributes significantly to the off-state leakage current. Although the asymmetric gate strategy and feedback gate (FBG) structures proposed so far have shown the potential to suppress CNT FET leakage currents, the devices still lack scalability. Based on the analysis of the conduction mechanism of existing self-aligned gate structures, this study innovatively proposed a design strategy to extend the length of the source–drain epitaxial region (L_ext) under a vertically stacked architecture. While maintaining a high drive current, this structure effectively suppresses the quantum tunneling effect on the drain side, thereby reducing the off-state leakage current (I_off = 10⁻¹⁰ A), and has good scaling characteristics and leakage current suppression characteristics between gate lengths of 200 nm and 25 nm. For the sidewall gate architecture, this work also uses single-walled carbon nanotubes (SWCNTs) as the channel material and uses metal source and drain electrodes with good work function matching to achieve low-resistance ohmic contact. This solution has significant advantages in structural adjustability and contact quality and can significantly reduce the off-state current (I_off = 10⁻¹⁴ A). At the same time, it can solve the problem of off-state current suppression failure when the gate length of the vertical stacking structure is 10 nm (the total channel length is 30 nm) and has good scalability. Full article

Background: Metabolic syndrome (MetS) is a multifactorial condition involving central obesity, dyslipidemia, hypertension, and impaired glucose metabolism, significantly increasing the risk of type 2 diabetes and cardiovascular disease. Objectives: Given the clinical heterogeneity of MetS, this study aimed to identify distinct metabolic phenotypes, referred to as metabotypes, using validated biomarkers and to examine their association with MetS. Materials and Methods: A total of 1245 Korean adults aged 19–79 years were selected from the 2016–2023 Korea National Health and Nutrition Examination Survey. Metabotype risk clusters were derived using k-means clustering based on five biomarkers: body mass index (BMI), uric acid, fasting blood glucose (FBG), high-density lipoprotein cholesterol (HDLc), and non-HDL cholesterol (non-HDLc). Multivariable logistic regression was used to assess associations with MetS. Results: Three distinct metabotype risk clusters (low, intermediate, and high risk) were identified. The high-risk cluster exhibited significantly worse metabolic profiles, including elevated BMI, FBG, HbA1c, triglyceride, and reduced HDLc. The prevalence of MetS increased progressively across metabotype risk clusters (OR: 5.46, 95% CI: 2.89–10.30, p < 0.001). In sex-stratified analyses, the high-risk cluster was strongly associated with MetS in both men (OR: 9.22, 95% CI: 3.49–24.36, p < 0.001) and women (OR: 3.70, 95% CI: 1.56–8.75, p = 0.003), with notable sex-specific differences in lipid profiles, particularly in HDLc. Conclusion: These findings support the utility of metabotyping using routine biomarkers as a tool for early identification of high-risk individuals and the development of personalized prevention strategies in clinical and public health settings. Full article

Background: Polycystic Ovary Syndrome (PCOS) is a prevalent endocrine disorder characterized by excess body weight, hyperandrogenism, hyperglycemia, and insulin resistance often resulting in hirsutism and infertility. Dietary strategies have been shown to ameliorate metabolic disturbances, hormonal imbalances, and inflammation associated with PCOS. Recent evidence indicates that intermittent fasting (IF) could effectively enhance health outcomes and regulate circadian rhythm; however, its impact on PCOS remain unclear. Objective: Therefore, this systematic review and meta-analysis aims to examine the effect of IF on women diagnosed with PCOS. Methods: Comprehensive research was conducted across three major databases including PubMed, Scopus, and Web of Science without date restrictions. Meta-analysis was performed using Cochrane Review Manager Version 5.4 software. Results: Five studies fulfilled the inclusion criteria. IF significantly reduced body weight (MD = −4.25 kg, 95% CI: −7.71, −0.79; p = 0.02), BMI (MD = −2.05 kg/m², 95% CI: −3.26, −0.85; p = 0.0008), fasting blood glucose (FBG; MD = −2.86 mg/dL, 95% CI: −4.83, −0.89; p = 0.004), fasting blood insulin (FBI; MD = −3.17 μU/mL, 95% CI: −5.18, −1.16; p = 0.002), insulin resistance (HOMA-IR; MD = −0.94, 95% CI: −1.39, −0.50; p < 0.0001), triglycerides (TG; MD = −40.71 mg/dL, 95% CI: −61.53, −19.90; p = 0.0001), dehydroepiandrosterone sulfate (DHEA-S; MD = −33.21 μg/dL, 95% CI: −57.29, −9.13; p = 0.007), free androgen index (FAI; MD = −1.61%, 95% CI: −2.76, −0.45; p = 0.006), and C-reactive protein (CRP; MD = −2.00 mg/L, 95% CI: −3.15, −0.85; p = 0.006), while increasing sex hormone-binding globulin (SHBG; SMD = 0.50, 95% CI: 0.22, 0.77; p = 0.004). No significant changes were observed in waist-to-hip ratio (WHR), total cholesterol (TC), LDL, HDL, total testosterone (TT), or anti-Mullerian hormone (AMH). Conclusions: IF represents a promising strategy for improving weight and metabolic, hormonal, and inflammatory profiles in women with PCOS. However, the existing evidence remains preliminary, necessitating further robust studies to substantiate these findings. Full article

Fiber Bragg grating (FBG) exhibits strong resistance to electromagnetic interference and excellent linear strain response, making it highly promising for structural health monitoring (SHM) in pavement. This research investigates the strain transfer characteristics of embedded FBG in pavement structure and materials by using the relevant theoretical models. Results indicate adhesive layer thickness and sheath modulus are the primary factors influencing the strain transfer coefficient. A thinner adhesive layer and high modulus of sheath enhance the coefficient. Additionally, the strain distribution of sheath significantly affects the transfer efficiency. When the stress level near the grating region is lower than the both ends, the coefficient increases and even exceeds 1, which typically occurs under multi-axle conditions. As for asphalt mixture, high temperature leads to lower efficiency, while accumulated plastic strain improves it. Although the increased load frequency results a higher strain transfer coefficient, the magnitude of this change is negligible. By employing polynomial fitting to the sheath strain distribution, the boundary condition of theoretical equation could be removed. The theoretical and numerical results of strain transfer coefficient for pavement embedded FBG demonstrate good consistency, indicating the polynomial fitting is adoptable for the theoretical calculation with non-uniform strain distribution. This study utilizes the FEM to clarify the evolution of FBG strain transfer in pavement structures and materials, providing a theoretical basis for the design and implementation of embedded FBG in pavement. Full article

Machine learning (ML)-based techniques have received significant attention in various fields of industry and science. In civil and bridge engineering, they can facilitate the identification of specific patterns through the analysis of data acquired from structural health monitoring (SHM) systems. To evaluate the prediction capabilities of ML, this study examines the performance of several ML algorithms in estimating the total weight and location of vehicles on a bridge using strain sensing. A novel framework based on a combined model and data-driven approach is described, consisting of the establishment of the finite element (FE) model, its updating according to load testing results, and data augmentation to facilitate the training of selected physics-informed regression models. The article discusses the design of the Fiber Bragg Grating (FBG) sensor-based Bridge Weigh-in-Motion (BWIM) system, specifically focusing on several supervised regression models of different architectures. The current work proposes the use of the updated FE model to generate training data and evaluate the accuracy of regression models with the possible exclusion of selected input features enabled by the structural specificity of a bridge. The data were sourced from the SHM system installed on a network arch bridge in Wolin, Poland. It confirmed the possibility of establishing the BWIM system based on strain measurements, characterized by a reduced number of sensors and a satisfactory level of accuracy in the estimation of loads, achieved by exploiting the network arch bridge structural specificity. Full article

Non-alcoholic fatty liver disease (NAFLD) is a highly prevalent condition worldwide and represents a major global health challenge. Pharmacological and pharmacodynamic results indicate that aspirin eugenol ester (AEE) performs various pharmacological activities. However, it is unclear whether AEE can ameliorate the NAFLD. This study investigated the ameliorative effects of AEE on glucose and lipid metabolism disorders by in vitro and in vivo experiments. In the cellular model, TC increased to 0.104 μmol/mg and TG increased to 0.152 μmol/mg in the model group, while TC decreased to 0.043 μmol/mg and TG decreased to 0.058 μmol/mg in the AEE group. In the model group, the area occupied by lipid droplets within the visual field was significantly elevated to 17.338%. However, the administration of AEE resulted in a substantial reduction in this area to 10.064%. AEE significantly reduced the lipid droplet area and TC and TG levels (p < 0.05), increased bile acids in the cells and in the medium supernatant (p < 0.05), and significantly up-regulated the expression of LRH-1, PPARα, CYP7A1, and BSEP mRNA levels (p < 0.05) compared to the model group. In the animal model, different doses of AEE administration significantly down-regulated the levels of TC, TG, LDL, GSP, and FBG (p < 0.05) compared to the high-fat-diet (HFD) group, and 216 mg/kg of AEE significantly improved hepatocellular steatosis, attenuated liver injury, and reduced the area of glycogen staining (p < 0.05). In the HFD group, the glycogen area within the visual field exhibited a significant increase to 18.250%. However, the administration of AEE resulted in a notable reduction in the glycogen area to 13.314%. Liver and serum metabolomics results show that AEE can reverse the metabolite changes caused by a HFD. The major metabolites were involved in seven pathways, including riboflavin metabolism, glycerophospholipid metabolism, tryptophan metabolism, primary bile acid biosynthesis, biosynthesis of unsaturated fatty acids, nicotinate and nicotinamide metabolism, and tryptophan metabolism. In conclusion, AEE had a positive regulatory effect on NAFLD. Full article

Shape-sensing optical fibers have become increasingly important in applications requiring flexible navigation, spatial awareness, and deformation monitoring. Fiber Bragg Grating (FBG) sensors inscribed in multi-core optical fibers have been democratized over the years and nowadays offer a compact and robust platform for shape reconstruction. In this work, we propose a novel, computationally efficient method for determining the 3D tip position of a bent multi-core FBG-based optical fiber using a second-order polynomial approximation of the fiber’s shape. The method begins with a calibration procedure, where polynomial coefficients are fitted for known bend configurations and subsequently modeled as a function of curvature using exponential decay functions. This allows for real-time estimation of the fiber tip position from curvature measurements alone, with no need for iterative numerical solutions or high processing power. The method was validated using miniaturized test structures and achieved sub-millimeter accuracy (<0.1 mm) over a 4.5 mm displacement range. Its simplicity and accuracy make it suitable for embedded or edge-computing applications in confined navigation, structural inspection, and medical robotics. Full article

Carbon fiber-reinforced polymer (CFRP) laminates have been widely coated on aged and damaged structures for recovering or enhancing their structural performance. The health conditions of the coated composite structures have been given high attention, as they are critically important for assessing operational safety and residual service life. However, the current problem is the lack of an efficient, long-term, and stable monitoring technique to characterize the structural behavior of coated composite structures in the whole life cycle. For this reason, bare and packaged fiber Bragg grating (FBG) sensors have been specially developed and designed in sensing networks to monitor the structural performance of CFRP-coated composite beams under different loads. Some optical fibers have also been inserted in the CFRP laminates to configure the smart CFRP component. Detailed data interpretation has been conducted to declare the strengthening process and effect. Finite element simulation and simplified theoretical analysis have been conducted to validate the experimental testing results and the deformation profiles of steel beams before and after the CFRP coating has been carefully checked. Results indicate that the proposed FBG sensors and sensing layout can accurately reflect the structural performance of the composite beam structure, and the CFRP coating can share partial loads, which finally leads to the downward shift in the centroidal axis, with a value of about 10 mm. The externally bonded sensors generally show good stability and high sensitivity to the applied load and temperature-induced inner stress variation. The study provides a straightforward instruction for the establishment of a structural health monitoring system for CFRP-coated composite structures in the whole life cycle. Full article

Westernization of traditional diets has been implicated in the rising burden of overweight/obesity and type 2 diabetes, especially in developing countries. In recent times, diet therapy is increasingly being recognized as an essential component of diabetes care. This study assessed the effect of diet therapy on body composition, antioxidant nutrient intake, and glycemic status in individuals living with type 2 diabetes (ILWT2D). In this prospective observational cohort study, 45 ILWT2D who were receiving diet therapy (personalized dietary counseling) in addition to standard medical treatment (intervention group) were compared with 45 ILWT2D receiving only standard medical treatment (comparator group). Antioxidant micronutrient intake was assessed using a 24-h dietary recall. Body composition indices, including body mass index (BMI), percentage body fat (%BF), and visceral fat (VF), were assessed. Participants’ fasting blood glucose (FBG), glycated hemoglobin (HbA1C) levels, and blood pressure (BP) were measured. All measurements were performed before and after a three-month period. There were significant improvements in BMI (27.8 ± 6.0 kg/m² vs. 26.9 ± 5.5 kg/m², p = 0.003), %BF (37.8 ± 11.9% vs. 35.5 ± 10.5%, p < 0.001), visceral fat (9.8 ± 3.4 vs. 9.1 ± 3.2, p < 0.001), systolic BP (136.9 ± 19.9 mmHg vs. 124.6 ± 13.0 mmHg, p < 0.001), FBG (8.8 ± 2.8 mmol/L vs. 6.7 ± 1.5 mmol/L, p < 0.001), and HbA1c (7.3 ± 1.0% vs. 6.4 ± 0.8%, p < 0.001) in the intervention group from baseline to endline, but not in the comparator group. In contrast, %BF increased within the comparator group (39.9 ± 7.8 vs. 40.7 ± 7.4; p = 0.029). Vitamin A intake increased significantly (227.5 ± 184.3 µg vs. 318.8 ± 274.7 µg, p = 0.038) within the intervention group but not in the comparator group (174.9 ± 154.3 µg, 193.7 ± 101.4 µg, p = 0.54). There were no significant changes in zinc, copper, selenium, and vitamin C intakes (p > 0.05) in the intervention group from the baseline to endline, unlike those in the comparator group who showed a significant increase in the intake of these nutrients. There was a significant increase in vitamin A intake among the ILWT2D who received dietary counseling as an intervention compared to those who did not. Additionally, the ILWT2D who received dietary counseling had significant improvements in their body composition (BMI, body fat, and visceral fat) and systolic blood pressure, compared to those who did not. The ILWT2D who received the intervention had significantly better glycemic control (FBG and HbA1c) than their counterparts who did not. Thus, this study suggests the potential of diet therapy as a viable non-pharmacological treatment approach for individuals living with type 2 diabetes. Full article

A real-time structural health monitoring (SHM) system of an airplane composite wing with adjustable damage is reported, where testing under realistic flight conditions is carried out in the controllable and repeatable environment of an industrial wind tunnel. An FBG-based sensing array monitors a debonded region, whose compromised structural strength is regained by a set of lockable fasteners. Damage tunability is achieved by loosening some of or all these fasteners. Real-time analysis of the data collected involves Principal Component Analysis, followed by Hotelling’s T-squared and Q measures. With previously set criteria, real-time data collection and processing software can declare the structural health status as normal or abnormal. During testing, the system using the Q measure successfully identified the initiation of the damage and its extent, while the T-squared one returned limited outcomes. Full article

We demonstrate an all-fiber, high-sensitivity, dual-parameter sensor for humidity and temperature. The sensor consists of a symmetrical, non-adiabatic, tapered, single-mode optical fiber, operating at the wavelength near the dispersion turning point, and a cascaded fiber Bragg grating (FBG) for temperature compensation. At one end of the fiber’s tapered region, part of the fundamental mode is coupled to a higher-order mode, and vice versa at the other end. Under the circumstances that the two modes have the same group index, the transmission spectrum would show an interference fringe with uneven dips. In the tapered region of the sensor, some of the light transmits to the air, so it is sensitive to changes in the refractive index caused by the ambient humidity. In the absence of moisture-sensitive materials, the humidity sensitivity of our sensor sample can reach −286 pm/%RH. In order to address the temperature and humidity crosstalk and achieve a dual-parameter measurement, we cascaded a humidity-insensitive FBG. In addition, the sensor has a good humidity stability and a response time of 0.26 s, which shows its potential in fields such as medical respiratory dynamic monitoring. Full article