Search Results (293)

Background: Pressure injury (PI) prevention relies heavily on the application of the Braden Scale, yet its predictive performance is limited mainly due to subjective measurements and fixed cut-off points, yielding potential errors in terms of false-positive alarm rates and workforce misuse. Machine learning (ML) has emerged as a promising approach to improve discrimination, but fair comparisons with traditional tools remain scarce in clinical settings. Methods: Using data from 446 hospitalized patients in a tertiary hospital in Chile, we compared five classic ML models for classification against the Braden Scale. ML models were trained exclusively on routinely collected clinical and nursing variables, excluding Braden inputs. A matched operating-point framework was applied, aligning ML decision thresholds with Braden cutoffs based on equivalent recall or specificity. Results: The XGB model showed the highest overall discrimination performance (AUC = 0.835). When matched to Braden recall, XGB achieved about 17% gains in specificity, substantially reducing false positives. When matched on specificity, recall improvements ranged from 13% to 25%. These gains were consistent across clinically relevant thresholds considered during the comparison. Conclusions: ML models, particularly XGB, outperform the Braden Scale under equivalent clinical operating conditions. Rather than replacing Braden, ML has emerged as a promising approach that preserves patient safety while improving precision and resource allocation. Full article

This paper proposes a mathematical co-design framework for synchronous Boost DC-DC converters and their PI voltage controllers. In contrast to the conventional sequential design approach, where the power stage is sized first and the controller is tuned afterward, the proposed method treats the converter and the controller as a single coupled design problem. A nonlinear averaged model of the synchronous boost converter operating in continuous conduction mode is considered, explicitly incorporating the inductor series resistance, the capacitor equivalent series resistance, and the on-state resistances of the active switches. In addition, a simplified but physically interpretable loss model is included in order to capture inductor copper loss, capacitor ESR loss, semiconductor conduction loss, and switching loss. Based on this formulation, the joint design of the power stage and the PI controller is cast as a constrained multi-objective optimization problem whose decision variables include the inductance, capacitance, switching frequency, and controller gains. The optimization criteria account for output-voltage ripple, settling time, total losses, and current stress, while practical constraints related to duty cycle, current limits, ripple bounds, and closed-loop feasibility are enforced. The proposed framework makes it possible to compute Pareto-efficient designs and to reveal trade-offs that remain hidden under classical decoupled design procedures. Numerical case studies are structured to compare the proposed co-design strategy with a conventional sequential-design baseline. An optional technology-aware extension is also considered, allowing the influence of different semiconductor classes, such as Si, SiC, and GaN, to be assessed through technology-dependent loss and switching-frequency assumptions. The results indicate that the proposed framework provides a mathematically grounded and practically useful basis for integrated converter–controller synthesis in nonideal power electronic systems. Full article

The sustainable management of agri-food waste is a key challenge in the context of the circular economy and energy transition. Anaerobic digestion is an effective method for converting organic waste into renewable energy; however, its efficiency is often limited by substrate properties, such as high lignin content, low biodegradability, and unfavorable C: N ratios. This study evaluates a low-energy pretreatment method based on a Vortex Layer Reactor (VLR, equivalent to the AVS-100 system) applied to slaughterhouse waste, swine manure, and spent mushroom substrate. The analysis included biogas yield, methane production, carbon conversion, process kinetics, and net energy efficiency. The results showed that pretreatment effectiveness depends on substrate type. No improvement was observed in slaughterhouse waste, with net energy efficiency decreasing by approximately 9%. In contrast, biogas yield increased by 14% for swine manure and 18% for spent mushroom substrate, with a maximum net energy gain of 17.6%. The process required only 2.16–3.6 kWh·Mg⁻¹ (about 9 kWh·Mg⁻¹ TS), significantly less than conventional methods. The findings indicate that pretreatment should be applied selectively, depending on substrate characteristics. This study supports decision-making in biogas plant management by integrating technological efficiency with energy and operational criteria. Full article

With the continuous reduction in equivalent inertia in modern power systems, thermal power units are required to provide faster and more sensitive primary frequency regulation. Under this background, small frequency deviation amplification (compensation) has been widely implemented in governing systems. However, while such high-gain control improves frequency response performance, it may significantly deteriorate system damping and even induce low-frequency oscillations (LFO). The underlying mechanism, however, has not been fully clarified from a theoretical perspective. To address this issue, a refined electromechanical coupled model of a thermal power unit governing system incorporating small frequency deviation amplification is established, and the corresponding linearized model is derived. Based on the damping torque analysis method, the influence of amplification gain on mechanical damping is rigorously analyzed in the frequency domain, and the fundamental mechanism leading to damping degradation is revealed. Furthermore, time-domain simulations are conducted to compare system dynamic responses under different compensation parameter settings. The results indicate that the amplification gain has a significant impact on LFO characteristics. Improper parameter settings can directly reduce system damping and trigger oscillations. Full article

This paper proposes finite-time (FT) and fixed-time (FXT) neurodynamic models with time-varying coefficients for solving inverse quasi-variational inequality problems (IQVIPs). Two projected models with time-dependent gains are developed to enhance convergence speed and transient performance. A nominal model establishes the equivalence between equilibrium points and IQVIP solutions. Under Lipschitz continuity and strong monotonicity assumptions, the existence, uniqueness, and global convergence of the proposed models are ensured. By employing Lyapunov stability theory, finite-time and fixed-time convergence of the continuous-time models are rigorously established, where explicit settling-time bounds independent of initial conditions are derived for the FXT case. Furthermore, the robustness of the proposed models under bounded disturbances is analyzed. To validate the theoretical findings, a discrete-time implementation based on the forward Euler method is developed. Numerical experiments demonstrate that all trajectories converge within a uniform upper bound, showing convergence behavior consistent with the fixed-time characteristics of the continuous-time model. Although the convergence time varies with initial conditions, it remains uniformly bounded, which is consistent with the fixed-time stability characteristics of the continuous-time model. The proposed framework provides a computationally efficient and scalable approach for solving IQVIPs, with potential applications in traffic equilibrium, communication networks, distributed control systems, and multi-agent coordination. Its adaptive structure and fixed-time convergence properties make it particularly suitable for real-time optimization in dynamic and uncertain environments. Full article

Background: Additive manufacturing (AM) has gained increasing attention in prosthetics and orthotics (P&O), yet real-world evidence on its clinical and operational value remains limited, particularly across both prosthetic and orthotic device classes within tertiary hospital practice. This study evaluated the comparative performance of AM in transtibial prosthetic sockets and ankle-foot orthoses (AFOs) within Singapore’s public healthcare setting. Methods: Two comparative clinical evaluations were conducted. The transtibial socket component used a prospective two-period cross-over design across two P&O departments in NHG Health hospitals, comparing digitally fabricated Multi Jet Fusion (MJF) sockets against conventionally laminated sockets. The AFO component compared posterior cut-out MJF AFOs against conventional polypropylene AFOs within a tertiary hospital P&O service. Patient-reported outcomes were assessed using the Prosthesis Evaluation Questionnaire (PEQ) and Socket Comfort Score (SCS) for sockets, and the Quebec User Evaluation of Satisfaction with Assistive Technology (QUEST 2.0) for AFOs. Workflow time and cost outcomes were also examined. Results: No statistically significant differences were identified between 3D-printed and conventional transtibial sockets across PEQ domains or SCS measures. Of 15 participants contributing preference data, 9 preferred the 3D-printed socket. The digitally enabled socket workflow reduced technician time and total man-hours but increased total cost because of higher consumables costs. In the AFO cohort, overall QUEST scores did not differ significantly between the posterior cut-out MJF AFO and the conventional polypropylene AFO (mean 4.49 vs. 4.55; p = 0.432). Digital fabrication reduced clinician handling time from 60 to 27 min per device. A unilateral MJF AFO design was discontinued because of biomechanical insufficiency. Conclusions: AM demonstrated comparable short-term patient-reported outcomes to conventional fabrication in selected transtibial socket and AFO applications, although the study was not designed to prove clinical equivalence. Operational benefits were conditional and depended on workflow maturity, design suitability, and service context. Full article

Index-modulated orthogonal frequency division multiplexing (OFDM-IM) has been recognized as a promising multicarrier transmission scheme due to its flexibility and favorable bit error rate (BER) performance. However, for future wireless communication systems requiring high reliability, high spectral efficiency, and low complexity, existing OFDM-IM schemes still face challenges in simultaneously improving spectral efficiency, maintaining diversity gain, and controlling detection complexity at the receiver. To address these issues, this paper proposes a joint-mode and repeated-index modulation-based coordinate interleaved OFDM scheme (MRIM-CI-OFDM). Building upon the shared subcarrier activation pattern (SAP) and coordinate interleaving structure, the proposed scheme introduces cross-cluster mode-pair indexing, enabling information bits to be jointly carried by the SAP domain, mode domain, and constellation symbol domain. This design enhances spectral efficiency while preserving the diversity advantages of coordinate interleaving. Furthermore, a rotated multi-mode constellation construction method based on inter-constellation minimum product distance is developed to improve mode separability. By exploiting the equivalent real-valued orthogonal structure introduced by coordinate interleaving, low-complexity maximum likelihood (ML) and three-stage Max-Log detectors are constructed. Simulation results demonstrate that the proposed low-complexity detectors achieve near-ML detection performance. Additionally, at a spectral efficiency of 1.25 bps/Hz, MRIM-CI-OFDM achieves approximately 3 dB SNR gain over the coordinate-interleaved/repeated-index benchmarks and more than 5 dB gain over conventional OFDM-IM. Full article

Tanner quasi-cyclic low-density parity-check (QC-LDPC) codes form an important family of structured LDPC codes with favorable girth properties. This paper studies the girth of Tanner $(2, L)$-regular QC-LDPC codes (referred to as Tanner QC-LDPC cycle codes) for arbitrary integers $L>2$ and develops a novel algebraic number theoretic method to determine the girth for all sufficiently large primes p with $p\equiv 1\left(\mathrm{mod}2L\right)$. We first analyze the case $L=3$ and prove that the girth is 12 for every prime $p\equiv 1\left(\mathrm{mod}6\right)$ through exhaustive resultant computations. We then extend the method to arbitrary L and obtain a clear classification: when L is even, the girth is exactly 8 for all admissible primes; when L is odd, the girth attains the maximum value 12 for all sufficiently large admissible primes. The proof transforms cycle existence conditions into polynomial equations and applies resultant theory. This approach converts the infinite task of checking all primes into a finite set of algebraic checks. Numerical simulations show that the Tanner $(2, 5)$-regular non-binary code over $\mathrm{GF}\left(64\right)$ achieves a coding gain of approximately $0.2$ dB over the 5G LDPC code of equivalent binary length. Full article

Early-Warning Radar (EWR) is an advanced detection system capable of monitoring aerial targets over long distances with high precision, providing critical information support for defense security. However, EWR faces challenges such as a limited number of pulses, low coherent integration gain, small target Radar Cross Section (RCS), and complex clutter and electromagnetic interference environments. Conventional Constant False Alarm Rate (CFAR) detection algorithms struggle to effectively detect weak targets while maintaining an acceptable false alarm rate. To address these issues, this paper introduces a deep learning approach. A high target-clutter/interference/noise discriminative feature spectrum is obtained through phase difference transformation, upon which a dual-branch collaborative architecture network is constructed. In this architecture, the main network focuses on extracting spatiotemporal amplitude–phase characteristics, while the auxiliary branch implicitly mines the target’s physical boundary features from frequency-domain echoes. Through a self-attention mechanism, the features from both branches are semantically aligned and fused. This method significantly enhances the weak target detection capability of EWR under the constraint of a controlled false alarm rate. Test results show that under the false alarm rate ranging from ${10}^{-3}$ to ${10}^{-4}$, the SNR gain of the proposed algorithm is about 2∼5 dB, which is equivalent to increasing the radar detection range by 10∼30%. Full article

Wheeled inverted-pendulum robots with movable upper structures and variable payloads exhibit configuration-dependent equilibrium drift and payload-dependent dynamic variation, which complicate balancing control. This paper proposes a gain-scheduled controller–observer framework for payload-adaptive balancing of such a robot. First, the multi-body system is reduced to a control-oriented equivalent inverted-pendulum model through center-of-mass lumping, from which a parameter-varying linearized model is established. On this basis, an H∞ state-feedback controller with input constraints is synthesized in a linear matrix inequality (LMI) framework, and an augmented-state observer is designed to estimate the residual equilibrium offset induced by payload variation. To improve robustness over the operating range, the frozen-point design is extended to a sampled-model multi-model synthesis framework, and gain scheduling is implemented with respect to the measurable arm angle. Nonlinear Simscape simulations show that the proposed method can recover balance at representative fixed operating points, compensate effectively for load-induced equilibrium drifts, and preserve stable balancing performance under slow arm-angle variation. Quantitative comparisons with an LQR baseline further support the effectiveness of the proposed framework for payload-adaptive balancing control. Full article

Contactless transmission of mechanical power, which is characteristic of coaxial magnetic gears (CMGs), offers significant advantages over conventional mechanical gears, in particular, reduced maintenance frequency and inherent overload protection. At the same time, there is a lack of design methodologies for this type of gear based on the analysis and systematization of experience gained from already implemented designs. This paper presents a method for determining the maximum magnetic torques of CMGs on the basis of an equivalent magnetic-circuit model. The error associated with the proposed methodology does not exceed ±15%, which enables the influence of geometric parameters and the magnetic properties of materials on the key performance indicators of the gear to be assessed already at the preliminary design stage. A mathematical model of CMG dynamics was also developed, based on a quasi-stationary two-dimensional approximation of the magnetic field, accounting for the geometry of the magnetic circuit, the spatial distribution of the magnetic vector potential, and magnetic-circuit saturation. The proposed mathematical model was verified using the results of physical experiments. The discrepancy between the calculated and experimental values of the torque on the low-speed shaft in the steady state does not exceed 5.5%. Based on the optimization procedure, the dependence of the maximum linear torque density on the outer diameter of the CMG, the number of poles of the high-speed rotor, and the transmission ratio was determined. It was shown that, as the number of poles increases, the linear torque density also increases and, for example, for diameters of approximately 800 mm, it may exceed 100 N·m/m. Full article

SAR interferometry (InSAR) provides a framework for extracting high-resolution topographic information and detecting surface deformation. By analyzing the phase difference between radar acquisitions obtained at different times, one can characterize landscape geometry and surface changes. However, inherent phase noise often compromises the reliability of the resulting interferometric products. Consequently, there is a sustained need for spatial filtering techniques that suppress noise while preserving structural integrity and resolution. This work addresses the challenge of filtering the unwrapped phase, a process traditionally reliant on accurate coherence images to identify reliable pixels. We evaluate three statistically based spatial filters for phase noise reduction. The Enhanced Lee filter, which utilizes spatial adaptation and a physically grounded probability model, serves as the baseline for comparison. We examine the Gierull model, which improves computational efficiency by restricting the parameter space. To further reduce execution time, we propose and evaluate two empirical alternatives: the truncated wrapped normal (TcN) and the truncated wrapped Cauchy (TcC) distributions. Results indicate that these empirical models significantly reduce computational demand without degrading the quality of the filtered phase. We assess performance using a simulated dataset for objective validation alongside InSAR imagery of La Cumbre volcano, Los Alamos, and Robledo volcano. While the proposed models demonstrate significant gains in computational efficiency compared to current methods, we identify numerical integration as a primary bottleneck in the filtering process; this challenge warrants further investigation. Our results indicate that empirical statistical models provide a viable path for accelerated InSAR processing with accuracy equivalent to traditional, computationally intensive approaches. Full article

Background: The recombinant zoster vaccine (RZV) has been shown to reduce the risk of dementia and delay cognitive decline. However, economic evaluations in populations with mild cognitive impairment (MCI), particularly those incorporating cognitive outcomes, remain unavailable. This study evaluated the cost-effectiveness of RZV vaccination at age 50 among Chinese adults with MCI. Methods: A decision tree–Markov model was developed from a societal perspective to assess the lifetime cost-effectiveness of RZV (Shingrix, GSK) in a cohort of 1 million immunocompetent Chinese adults with MCI receiving vaccination at the age of 50. The primary outcome was the incremental cost-effectiveness ratio (ICER), while secondary outcomes included cases averted and the number needed to vaccinate (NNV) to prevent one case of herpes zoster (HZ), postherpetic neuralgia (PHN), and dementia. A willingness-to-pay (WTP) threshold equivalent to the 2024 Chinese gross domestic product (GDP) per capita (13,121 USD) was applied. Sensitivity analyses were conducted to test the robustness of the results. Results: Over a lifetime horizon, RZV vaccination was estimated to avert 54.64% of HZ cases, 97.58% of PHN cases, and 12.28% of dementia cases compared with no vaccination, resulting in an additional 2.23 million quality-adjusted life years (QALYs) gained. The ICER was 4216.99 USD/QALY, remaining well below the WTP threshold. The corresponding NNVs were 6.25 for HZ, 24.03 for PHN, and 280.82 for dementia progression. Conclusions: RZV vaccination is cost-effective for Chinese adults aged 50 years with MCI, providing substantial health gains through reductions in both HZ burden and dementia progression. Full article

Background: The keratorefractive lenticule extraction (KLEx) procedure has gained popularity because of its safety and effectiveness; however, its predictability remains variable, as it may be over- or under-corrected. This study aimed to evaluate visual and refractive outcomes following the utilisation of VISULYZE-generated nomograms (Carl Zeiss Meditec AG, Jena, Germany) and OcuLign cyclotorsion alignment tools (Carl Zeiss Meditec AG, Jena, Germany). Methods: This retrospective consecutive cohort study included patients undergoing KLEx, grouped into four sequential treatment phases: PRE-NOMOGRAM, NOMOGRAM, OCULIGN & NOMOGRAM, and OCULIGN. Results: A total of 688 patients (1264 eyes) were included. The OCULIGN group showed numerically higher efficacy, with 83.0% achieving post-operative (PO) uncorrected distance visual acuity (UDVA) 20/20 or better, with no loss of corrected distance visual acuity (CDVA) lines, and 67.0% gaining one line. Predictability and accuracy were high across groups, with the OCULIGN group demonstrating a strong correlation between attempted and achieved spherical equivalent (R² = 0.9908), and 95.5% of eyes within ±0.50 D. Early PO outcomes suggested minimal refractive shift at one month. The NOMOGRAM group demonstrated numerically improved astigmatism correction (100.0% within ≤0.50 D), while the OCULIGN & NOMOGRAM group showed high precision in axis alignment. However, baseline imbalances were present, and between-group differences were relatively small. Conclusions: The use of OcuLign cyclotorsion alignment and VISULYZE-generated nomograms was associated with favourable visual and refractive outcomes following KLEx. However, given the retrospective, sequential design, imbalanced baseline, and limited follow-up duration, these findings should be interpreted cautiously. Further prospective, randomised studies with longer follow-up are required to confirm these observations. Full article

Background/Objectives: This study aimed to compare AI-generated educational material with faculty-authored content in Dental Prostheses Technology, evaluating perceived clarity, accuracy, structure, usefulness, and overall instructional quality across different age and professional groups. Methods: An analytical cross-sectional study was conducted using two versions of the first three chapters of a prosthodontics textbook: the original faculty-authored text and a reformulated version generated by ChatGPT 5.2 (OpenAI). Images were removed and formatting standardized to ensure a text-only comparison. An anonymized online questionnaire based on a five-point Likert scale assessed clarity, accuracy, readability, usefulness and structure. To reduce potential bias, participants were unaware of the authorship of the evaluated materials (human-authored vs. AI-generated). A total of 130 participants independently reviewed both documents. Data were analyzed using Wilcoxon signed-rank, Mann–Whitney U, and Friedman tests. Results: Both materials received favorable evaluations across all dimensions. The AI-generated version demonstrated a statistically significant advantage in clarity (Z = −2.107, p = 0.035; r = 0.19), while no significant differences were observed for structure, accuracy, readability, or usefulness. Generational differences emerged: younger participants valued improved clarity but reported reduced usefulness, mid-career participants showed the greatest improvement in perceived accuracy, and senior professionals reported substantial gains in usefulness and readability. Conclusions: AI-generated educational material demonstrates pedagogical equivalence to faculty-authored content, with clarity representing its principal advantage. Large language models may serve as effective complementary tools in dental education, particularly for restructuring complex content. Full article