Search Results (163)

The increasing demand for real-time, energy-efficient, and interference-resilient communication in smart healthcare environments has intensified interest in Biomedical Internet of Things (Bio-IoT) systems. However, ensuring reliable wireless connectivity for wearable and implantable biomedical sensors remains a challenge due to mobility, latency sensitivity, power constraints, and multi-user interference. This paper addresses these issues by proposing a reconfigurable massive multiple-input multiple-output (MIMO) antenna architecture, incorporating hybrid analog–digital beamforming and adaptive signal processing. The methodology combines conventional algorithms—such as Least Mean Square (LMS), Zero-Forcing (ZF), and Minimum Variance Distortionless Response (MVDR)—with a novel mobility-aware beamforming scheme. System-level simulations under realistic channel models (Rayleigh, Rician, 3GPP UMa) evaluate signal-to-interference-plus-noise ratio (SINR), bit error rate (BER), energy efficiency, outage probability, and fairness index across varying user loads and mobility scenarios. Results show that the proposed hybrid beamforming system consistently outperforms benchmarks, achieving up to 35% higher throughput, a 65% reduction in packet drop rate, and sub-10 ms latency even under high-mobility conditions. Beam pattern analysis confirms robust nulling of interference and dynamic lobe steering. This architecture is well-suited for next-generation Bio-IoT deployments in smart hospitals, enabling secure, adaptive, and power-aware connectivity for critical healthcare monitoring applications. Full article

Background and Objectives: Indoxyl sulfate (IS), a gut microbiota-derived metabolite of tryptophan, is implicated in vascular dysfunction through oxidative stress and inflammation. This study evaluated the association between serum IS levels and aortic stiffness (AS) in patients with type 2 diabetes mellitus (T2DM). Materials and Methods: This cross-sectional study enrolled 80 patients with T2DM from a medical center in eastern Taiwan, excluding patients with malignancy, acute infection, heart failure, or recent cardiovascular events. Serum IS concentrations were quantified using liquid chromatography–mass spectrometry. AS was assessed using carotid–femoral pulse wave velocity (cfPWV), with values > 10 m/s indicating AS. Results: A total of 30 patients (37.5%) had AS. IS levels were significantly higher in the AS group than in the control group (p < 0.001). After multivariate adjustment, IS remained an independent predictor of AS (odds ratio: 2.565, 95% confidence interval: 1.145–5.748, p = 0.022). Linear regression analysis confirmed IS as an independent contributor to cfPWV values (β = 0.261, p = 0.019). Receiver operating characteristic analysis showed fair discriminatory ability (area under the curve = 0.739, p < 0.001). Conclusions: In patients with T2DM, serum IS is an independent predictor of AS and may serve as a promising nontraditional biomarker for cardiovascular risk stratification. Full article

Submicron particles (SPs), with diameters less than 1.0 μm, are a serious health risk, and urban meteorology variables (MVs), impacted by human activity, can support their sustainability. This study, in a city immersed in a basin geomorphology, is carried out during the summer period of high temperatures and variable relative humidity. An area of high urban density was selected, with the presence of high-rise buildings, urban canyons that favor heat islands, low forestation, intense vehicular traffic, and extreme conditions for MVs. Hourly measurements, in the form of time series, record the number of SPs (for diameters of 0.3, 0.5, and 1.0 μm) along with MVs (temperature (T), relative humidity (RH), and wind speed magnitude (WS)). The objective is to verify whether MVs (RH, T) promote the sustainability of SPs. For this purpose, Spearman’s analysis and a heavy-tailed probability function were used. The central tendency probability, a Gaussian distribution, was discarded since its probability does not discriminate extreme events. Spearman’s analysis yielded significant p-values and correlations between PM₁₀, PM_5.0, PM_2.5, and SPs. However, this was not the case between MVs and SPs. By applying a heavy-tailed probability analysis to extreme events, the results show that MVs such as T and RH act in ways that can favor the accumulation and persistence of SP concentrations. This tendency could have been exacerbated during the measurement period by heat waves and a geographical environment under the influence of a prolonged drought resulting from climate change and global warming. Full article

Achieving the full potential of wind energy in the global renewable transition depends critically on enhancing the performance and reliability of polymer composite components. This review synthesizes recent advances from 2022 to 2025, including the development of next-generation hybrid composites and the application of high-fidelity computational methods—finite element analysis (FEA), computational fluid dynamics (CFD), and fluid–structure interaction (FSI)—to optimize structural integrity and aerodynamic performance. It also explores the transformative role of artificial intelligence (AI) in structural health monitoring (SHM) and the integration of Internet of Things (IoT) systems, which are becoming essential for predictive maintenance and lifecycle management. Special focus is given to harsh offshore environments, where polymer composites must withstand extreme wind and wave conditions. This review further addresses the growing importance of circular economy strategies for managing end-of-life composite blades. While innovations such as the geometric redesign of floating platforms and the aerodynamic refinement of blade components have yielded substantial gains—achieving up to a 30% mass reduction in PLA prototypes—more conservative optimizations of internal geometry configurations in GFRP blades provide only around 7% mass reduction. Nevertheless, persistent challenges related to polymer composite degradation and fatigue under severe weather conditions are driving the adoption of real-time hybrid predictive models. A bibliometric analysis of over 1000 publications confirms more than 25 percent annual growth in research across these interconnected areas. This review serves as a comprehensive reference for engineers and researchers, identifying three strategic frontiers that will shape the future of wind turbine blade technology: advanced composite materials, integrated computational modeling, and scalable recycling solutions. Full article

Agricultural nondestructive testing technology is pivotal in safeguarding food quality assurance, safety monitoring, and supply chain transparency. While conventional optical methods such as near-infrared spectroscopy and hyperspectral imaging demonstrate proficiency in surface composition analysis, their constrained penetration depth and environmental sensitivity limit effectiveness in dynamic agricultural inspections. This review highlights the transformative potential of microwave technologies, systematically examining their operational principles, current implementations, and developmental trajectories for agricultural quality control. Microwave technology leverages dielectric response mechanisms to overcome traditional limitations, such as low-frequency penetration for grain silo moisture testing and high-frequency multi-parameter analysis, enabling simultaneous detection of moisture gradients, density variations, and foreign contaminants. Established applications span moisture quantification in cereal grains, oilseed crops, and plant tissues, while emerging implementations address storage condition monitoring, mycotoxin detection, and adulteration screening. The high-frequency branch of the microwave–millimeter wave systems enhances analytical precision through molecular resonance effects and sub-millimeter spatial resolution, achieving trace-level contaminant identification. Current challenges focus on three areas: excessive absorption of low-frequency microwaves by high-moisture agricultural products, significant path loss of microwave high-frequency signals in complex environments, and the lack of a standardized dielectric database. In the future, it is essential to develop low-cost, highly sensitive, and portable systems based on solid-state microelectronics and metamaterials, and to utilize IoT and 6G communications to enable dynamic monitoring. This review not only consolidates the state-of-the-art but also identifies future innovation pathways, providing a roadmap for scalable deployment of next-generation agricultural NDT systems. Full article

Electromagnetic wave (EMW) absorption materials are crucial for a wide range of applications, yet most existing materials suffer from complex fabrication and narrow absorption bands, particularly under harsh environmental conditions. In this study, we introduce a broadband metamaterial absorber based on Ti₃C₂O₂ MXene, a novel two-dimensional material that uniquely combines high electrical and metallic conductivity with hydrophilicity, biocompatibility, and an extensive surface area. Through advanced finite-difference time-domain (FDTD) simulations, the proposed absorber achieves over 95% absorption from 0.3 µm to 18 µm. Additionally, other MXene variants, including Ti₃C₂F₂ and Ti₃C₂(OH)₂, demonstrate robust absorption above 85%. This absorber not only outperforms previously reported structures in terms of efficiency and spectral coverage but also opens avenues for integration into applications such as infrared sensing, energy harvesting, wearable electronics, and Internet of Things (IoT) systems. Full article

Blasting-induced seismic waves are typically nonlinear and non-stationary signals. The EMD-Hilbert transform is commonly used for time–frequency analysis of such signals. However, during the empirical mode decomposition (EMD) processing of blasting-induced seismic waves, endpoint effects occur, resulting in varying degrees of divergence in the obtained intrinsic mode function (IMF) components at both ends. The further application of the Hilbert transform to these endpoint-divergent IMFs yield artificial time–frequency analysis results, adversely impacting the assessment of blasting-induced seismic wave hazards. This paper proposes an improved EMD endpoint effect suppression algorithm that considers local endpoint development trends, global time distribution, energy matching, and waveform matching. The method first analyzes global temporal characteristics and endpoint amplitude variations to obtain left and right endpoint extension signal fragment S(t)_L and S(t)_R. Using these as references, the original signal is divided into “b” equal segments S(t)₁, S(t)₂ … S(t)_b. Energy matching and waveform matching functions are then established to identify signal fragments S(t)_i and S(t)_j that match both the energy and waveform characteristics of S(t)_L and S(t)_R. Replacing S(t)_L and S(t)_R with S(t)_i and S(t)_j effectively suppresses the EMD endpoint effects. To verify the algorithm’s effectiveness in suppressing EMD endpoint effects, comparative studies were conducted using simulated signals to compare the proposed method with mirror extension, polynomial fitting, and extreme value extension methods. Three evaluation metrics were utilized: error standard deviation, correlation coefficient, and computation time. The results demonstrate that the proposed algorithm effectively reduces the divergence at the endpoints of the IMFs and yields physically meaningful IMF components. Finally, the method was applied to the analysis of actual blasting seismic signals. It successfully suppressed the endpoint effects of EMD and improved the extraction of time–frequency characteristics from blasting-induced seismic waves. This has significant practical implications for safety assessments of existing structures in areas affected by blasting. Full article

A FEM model of Shallow Wave Equations (SWE-FEM) is studied, taking into account the variable bathymetry of semi-enclosed sea basins. The model, with a spatially varying Coriolis term, is implemented for the description of combined refraction–diffraction effects, from which the eigenperiods and eigenmodes of extended geographical sea areas are calculated by means of a low-order FEM scheme. The model is applied to the western Mediterranean basin, illustrating its versatility to easily include the effects of geographical characteristics like islands and other coastal features. The calculated resonant frequencies and modes depend on the domain size and characteristics as well as the location of the open sea boundary, and it is shown to provide results compatible with tide measurements at several stations in the coastal region of France. The calculation of the natural oscillation modes in the western Mediterranean basin, bounded by open boundaries at the Strait of Gibraltar and the Strait of Sicily, reveals a natural period of around 6 h corresponding to the quarter-diurnal tidal components, which are stationary and of roughly constant amplitude on the northern coast of the basin and on the west coast of Corsica (France). On the east coast of Corsica, on the other hand, these components are of very low amplitude and in phase opposition. The semi-diurnal tidal components observed on the same tide gauges north of the basin and west of Corsica are also quasi-stationary although they are not resonant. Resonant oscillations are also observed at lower periods, especially at a period of around 3 h at the Sète station. This period corresponds to a higher-order natural mode of the western Mediterranean basin, but this resonance seems to be essentially linked to the presence of the Gulf of Lion, whose shallowness and the width of the shelf at this point induce a resonance. Other oscillations are also observed at lower periods (T = 1.5 h at station Fos-sur-Mer, T = 45 min in the Toulon harbour station), due to more local forcing. Full article

Vectorcardiography (VCG) is an electrophysiological investigation technique, giving supplementary information about the electrical activation of the heart, compared to traditional 12-lead electrocardiography (ECG). Whereas the 12-lead ECG has found its way into global clinical cardiology practice in numerous cardiac pathophysiological instances, VCG has not. In an investigation of the electrical activation of the heart in cardiac resynchronization therapy (CRT), in order to understand the baseline pathology in potentially eligible patients, and to understand and optimize CRT-derived paced activation of the heart in the therapy’s recipients, all of these aspects are essential to the success of the therapy. Due to a consistently present group of non-responders in CRT, VCG has gained interest as a potential improvement in this field. This review comprehensively summarizes the contemporary evidence for the additional value of VCG in CRT, as well as current deficiencies in evidence, to support its implementation in global practice in addition to, or as a substitution for, traditional 12-lead ECG. Full article

Developing efficient bifunctional oxygen reduction (ORR) and oxygen evolution (OER) electrocatalysts is critical for renewable energy technologies. Noble metal catalysts face limitations in cost, scarcity, and bifunctional compatibility. Herein, we report the synthesis of nickel nanoparticles encapsulated in nitrogen-doped carbon nanosheets (Ni@NC-T) via a solvothermal polymerization and pyrolysis process using a Ni-hexamine coordination framework (NiHMT) as a precursor. The Ni@NC-900 catalyst exhibits superior ORR and OER activity under alkaline conditions, with an ORR performance (half-wave potential = 0.86 V) comparable to commercial Pt/C and an OER overpotential of only 430 mV at 10 mA cm⁻². Structural analysis indicates that the hierarchical porous structure and high specific surface area (409 m² g⁻¹) of Ni@NC-900 facilitate the exposure of active sites and enhance mass transport. The surface-doped nitrogen species, predominantly in the form of pyridinic N and graphitic N, promote electron transfer during the ORR. Furthermore, its application as a bifunctional cathode in rechargeable zinc-air batteries results in a high power density of 137 mW cm⁻², surpassing the performance levels of many existing carbon-based bifunctional catalysts. This work highlights a facile strategy for the fabrication of transition metal-based catalysts encapsulated in MOF-derived carbon matrices, with promising potential for energy storage and conversion devices. Full article

Internet addiction has been associated with decreased prosocial behavior in adolescents, and minority studies have investigated the underlying mechanisms involved. This study aimed to examine the mediating effects of self-control and the moderating effects of peer rejection. A longitudinal study with two waves (6 months apart) was used to measure internet addiction (T1), peer rejection (T1), self-control (T1/T2), and prosocial behavior (T1/T2) among 1048 secondary school students (M_age = 14.80 years old, SD = 1.61) in a southern Chinese metropolitan area. A longitudinal path analysis model was applied to analyze the data and derive insights about the relationships between these variables. The findings indicated that T1 internet addiction negatively influenced later prosocial behavior through reduced self-control, particularly among adolescents with lower levels of peer rejection. These findings clarify how internet addiction impairs prosocial development, and we propose a framework for intervention: mitigating peer rejection and harnessing self-control as a mediator to counteract the adverse effects of internet addiction. Full article

The electrocardiogram (ECG) is a widely used, non-invasive tool for diagnosing a range of cardiovascular conditions, including arrhythmia and heart disease-related structural changes. Despite its critical role in clinical care, racial and ethnic differences in ECG readings are often underexplored or inadequately addressed in research. Variations in key ECG parameters, such as PR interval, QRS duration, QT interval, and T-wave morphology, have been noted across different racial groups. However, the limited research in this area has hindered the development of diagnostic criteria that account for these differences, potentially contributing to healthcare disparities, as ECG interpretation algorithms largely developed from major population data may lead to misdiagnoses or inappropriate treatments for minority groups. This review aims to help cardiac researchers and cardiovascular specialists better understand, explore, and address the impact of racial and ethnic differences in ECG readings. By identifying potential causes—ranging from genetic factors to environmental influences—and exploring the resulting disparities in healthcare outcomes, we propose strategies such as the development of race-specific ECG norms, the application of artificial intelligence (AI) to improve diagnostic accuracy, and the diversification of ECG databases. Through these efforts, the medical community can advance toward more personalized and equitable cardiovascular care. Full article

Acid leaching is an effective method for dephosphorization; however, it is time-consuming and requires a high amount of acid consumption, resulting in increased production costs and environmental risks. This work aims to remove silicon, aluminum, and phosphorus from high-phosphorus oolitic magnetite concentrate through high-pressure alkaline leaching and ultrasonic acid leaching. Compared with traditional acid leaching processes, the sulfuric acid dosage can be significantly reduced from 200 kg/t to 100 kg/t, and the pickling time is shortened from 60 min to 10 min. Thermodynamic and kinetic studies have demonstrated that acid leaching facilitates apatite dissolution at low temperatures, whereas the dephosphorization reaction is controlled mainly by diffusion. The application of ultrasonic waves leads to finer particle sizes and greatly increased specific surface areas, thereby accelerating the diffusion rate of the leaching agent. Furthermore, microscopic analysis revealed that under the influence of ultrasonic waves, numerous micro-fragments and pores form on particle surfaces due to cavitation effects and mechanical forces generated by ultrasonic waves. These factors promote both the reaction rates and diffusion processes of the leaching agent while enhancing the overall leaching efficiency. Full article

During its service life, a deep-sea floating structure is likely to encounter extreme marine disasters. The combined action of wind and wave loads poses a threat to its structural safety. In this study, elliptical copula, Archimedean copula, and vine copula models are employed to depict the intricate dependence structure between wind and waves in a specific sea area of the Shandong Peninsula. Moreover, hourly significant wave height, spectral peak period, and 10 m average wind speed hindcast data from 2004 to 2023 are utilized to explore the joint distribution of multidimensional parameters and environmental design values. The results indicate the following: (1) There exists a significant correlation between wind speed and wave parameters. Among them, the C-vine copula model represents the optimal trivariate joint distribution, followed by the Gaussian copula, while the Frank copula exhibits the poorest fit. (2) Compared with the high-dimensional symmetric copula models, the vine copula model has distinct advantages in describing the dependence structure among several variables. The wave height and period demonstrate upper tail dependence characteristics and follow the Gumbel copula distribution. The optimal joint distribution of wave height and wind speed is the t copula distribution. (3) The identification of extreme environmental parameters based on the joint probability distribution derived from environmental contour lines is more in line with the actual sea conditions. Compared with the design values of independent variables with target return periods, it can significantly reduce engineering costs. In conclusion, the vine copula model can accurately identify the complex dependency characteristics among marine variables, offering scientific support for the reliability-based design of floating structures. Full article

On 28 March 2005, a major M_w 8.6 earthquake occurred near Nias and Simeulueislands, in the vicinity of northwestern Sumatra (Indonesia). The earthquake generated a significant tsunami. Although it was not as destructive as the 2004 Sumatra tsunami, the 2005 event was of sufficient strength to be recorded by tide gauges throughout the entire Indian Ocean. We selected 12 records for analysis, most from open-ocean islands but also some from continental stations. The maximum wave heights were measured at Salalah (Oman) (87 cm), Colombo (Sri Lanka), Pointe La Rue (Seychelles) and Rodrigues Island (53–54 cm). The dominant wave periods, estimated from frequency–time (f-t) diagrams, were 60–66 min, 40–48 min, and 20 min, which we assume are associated with the 2005 tsunami source. From the same stations, we calculated the mean ratio of the 2004 to 2005 tsunami heights as 5.11 ± 0.60, with the maximum and minimum heights to the west and south of the source region as 9.0 and 2.49, respectively. We also used these data to estimate the mean energy index, $E_0$ = 65 cm², for the 2005 tsunami, which was 16 times smaller than for the 2004 event. The USGS seismic solution was used to construct a numerical model of the 2005 tsunami and to simulate the tsunami waveforms for all 12 tide gauge stations. The results of the numerical computations were in general agreement with the observations and enabled us to map the spatial wave field of the event. To estimate the influence of location and orientation of the source area on the propagating tsunami waves, we undertook a set of additional numerical experiments and found that this influence is substantial and that these factors explain some of the differences between the physical properties of the 2004 and 2005 events. Full article