Search Results (238)

Background: Scleral fixation of intraocular lenses (IOLs) is a valuable option in cases of aphakia or inadequate capsular support, yet conventional sutured and sutureless approaches can pose technical challenges and complication risks. The needle-guided scleral fixation technique offers a simplified, single-suture solution that enhances safety and reproducibility. Methods: In this retrospective interventional case series, 30 eyes with insufficient capsular support underwent IOL implantation using Meduri’s needle-guided single-suture technique at the G. Martino University Hospital, Messina. The surgical method employs a 24-gauge needle to guide a double-armed 10-0 polypropylene suture through the sclera for precise IOL anchorage, minimizing vitreous manipulation. Outcomes were assessed over 24 months, including best-corrected visual acuity (BCVA), IOL centration, intraocular pressure (IOP), and postoperative complications. Results: Mean BCVA improved from X to Y LogMAR at two years (p < 0.05). All IOLs remained well-centered without tilt or decentration. Mild conjunctival hyperemia occurred in 70% of cases, resolving spontaneously. No suture erosion, vitreous hemorrhage, or retinal detachment was observed. Conclusions: The needle-guided single-suture technique provides a stable, efficient, and reproducible method for posterior chamber IOL fixation in aphakic eyes lacking capsular support. Its minimal learning curve and reduced surgical complexity make it an attractive alternative to both traditional sutured and modern sutureless methods, particularly in centers without vitreoretinal expertise. Full article

Home energy management systems have emerged as a crucial solution for enhancing energy efficiency, reducing carbon emissions, and facilitating the integration of renewable energy sources into homes. To fully realize their potential, these systems’ performance must be optimized, which involves addressing multiple objectives, such as minimizing costs and environmental impact. The Pareto frontier is a tool widely adopted in multi-objective optimization within home energy management systems’ operation, where a range of optimal solutions are produced. This study uses the Pareto curve to optimize the operational performance of home energy management systems, considering the state health of the battery to determine the best answer among the optimal solutions in the curve. The main reason for considering the state of health is the effects of the battery’s operation on the performance of energy systems, especially for long-term optimization outcomes. In this study, the performance of the battery is measured through a physical model named PyBaMM that is tuned based on swarm intelligence techniques, including the Whale Optimization Algorithm, Grey Wolf Optimization, Particle Swarm Optimization, and the Gravitational Search Algorithm. The proposed framework automatically identifies the optimal solution out of the ones in the Pareto curve by comparing the performance of the battery through the tuned physical model. The effectiveness of the proposed algorithm is demonstrated for a home, including four distinct energy carriers along with a 12 V 128 Ah LFP chemistry Li-ion battery module, where the overall cost and carbon emissions are the metrics for comparisons. Implementation results show that tuning the physical model based on the Whale Optimization Algorithm reaches the highest accuracy compared to the other methods. Moreover, considering the state of health of the battery as the selecting criterion will improve home energy management systems’ performance, particularly in long-term operation models, because it guarantees a longer battery lifespan. Full article

The hydraulic transportation technology of piped vehicles is a new type of pipeline transportation mode. A concentric annular turbulent flow with different boundaries is formed between the barrel of the piped vehicle and the pipe wall. The study on the annular turbulent flow can provide basic support for the application and promotion of this technology. Therefore, in this paper, the PIV technique was utilized to experimentally investigate the statistical characteristics of the annular turbulent flow in a fully developed smooth concentric annular pipe. The results showed that the position of the maximum velocity in the annular turbulent flow was not at the center but biased towards the barrel wall. Moreover, the smaller the radius ratio, the more it shifted towards the barrel wall. The position of the maximum velocity was independent of the Reynolds number and was a univariate function of the radius ratio; it was obtained by fitting experimental data that $r_{mt}^{*}={\displaystyle \frac{k^{0.349}}{1+k^{0.349}}}$. The resistance coefficient of annular turbulence was independent of the radius ratio and was a univariate function of the Reynolds number; it was obtained by fitting experimental data that $\lambda ={\displaystyle \frac{0.3183}{{R{e}_a}^{0.2487}}}$. The shear stress on the barrel wall was greater than that on the pipe wall in annular turbulent flow. Moreover, as the radius ratio increased, the shear stress on the barrel wall decreased, while that on the pipe wall increased. The velocity distribution in annular turbulent flow was divided into an inner region and an outer region. In the inner region, the $u_c^{+}-y_c^{+}$ curves were greatly affected by the Reynolds number, and the average gradient increased with the increase in the Reynolds number, while in the outer region, the average gradient of the $u_p^{+}-y_p^{+}$ curves decreased with the increase in the Reynolds number. The velocity distribution in annular turbulent flow cannot be expressed by a unified relationship. However, at high Reynolds numbers, there existed a region where the velocity distribution satisfied the logarithmic law in the outer region, and the slope of the logarithmic region was greater than that in circular pipe flow and parallel-plate flow. Full article

Background/Objectives: Although upper extremity dexterity problems are frequently reported in people with Parkinson’s disease (PwPD), valid and reliable scales for assessing upper extremity function and dexterity are limited. The objective of this study was to investigate the reliability and validity of the Action Research Arm Test (ARAT) and the Jebsen–Taylor Hand Function Test (JTHFT) in PwPD. Methods: Seventy PwPD and thirty HC were recruited. The test–retest reliability was evaluated by determining the intraclass correlation coefficient (ICC). MDC₉₅ was calculated by using ICC results. The concurrent validities of JTHFT and ARAT were determined by investigating their relationship with the Nine-Hole Peg Test (9-HPT), Hoehn and Yahr scale (H & Y), Unified Parkinson’s Disease Rating Scale (UPDRS), and motor symptoms (UPDRS-III). The cut-off times that best discriminated between PwPD and HC were investigated by plotting receiver operating characteristic (ROC) curves. Results: The ARAT and JTHFT showed excellent test–retest reliability (ICC = 0.937 to 0.995). The MDC₉₅ values for the ARAT were 0.38 for the dominant hand and 0.58 for the non-dominant hand. MDC₉₅ values for the JTHFT subtests and total scores ranged from 0.38 to 4.71. The ARAT, JTHFT subtests, and total scores demonstrated a fair-to-strong correlation with other outcomes (p < 0.05). The cut-off times that best differentiated JTHFT subtests and total scores ranged from 3.56 to 64.23. Conclusions: The JTHFT is a reliable and valid measurement tool for the assessment of manual dexterity in PwPD, while the ARAT is a reliable assessment tool in PwPD but does not have discriminant validity. Full article

Objectives: Previously, we identified four open-angle glaucoma (OAG)-associated autoantibodies (anti-ETNK1, anti-VMAC, anti-NEXN, and anti-SUN1) using proteome-wide autoantibody screening by wet protein arrays. The objective of this exploratory study was to evaluate the diagnostic performance of these four glaucoma-associated autoantibodies using automated machine learning. Methods: Plasma samples from 119 patients with OAG and 35 patients with cataracts as controls were enrolled for the study. All machine-learning analyses were performed in Python 3.9.16 (GCC 11.2.0) using scikit-learn 1.2.2 and PyCaret 3.0.1. Variables included plasma levels of the autoantibodies, age, sex, and intra-ocular pressure (IOP). Probability calibration (Platt/sigmoid and isotonic) was assessed with reliability curves and Brier scores. Model explainability was examined with permutation importance, SHAP values, and an ablation analysis removing one autoantibody at a time. Results: The tuned random forest achieved an out-of-fold (OOF) area under the receiver-operating characteristic curve (ROC–AUC) of 0.852 (±0.040), an average precision (AP) of 0.950, and an F1 score of 0.865. Isotonic mapping improved agreement between predicted and empirical probabilities. Among these four autoantibodies, VMAC was the most important factor for the model’s prediction. Conclusions: A machine learning model using four autoantibodies from blood samples showed potential for diagnosing OAG. Full article

To ensure the safety of supercritical CO₂ pipelines and address the limitations of full-scale fracture tests, such as high risk and substantial investment, software for evaluating the crack arrest toughness of CO₂ pipelines containing impurities was developed based on the Battelle Two-Curve Model (BTCM) in this study. The software is programmed in Python (v.3.12.4), with a graphical user interface (GUI) built using PyQt6 (v.6.10.0) and a three-tier architecture design. It integrates the resistance curve model and the decompression wave model. To determine the thermodynamic state of the fluid, a large property database covering pure components and various mixtures is embedded, incorporating state equations such as PR, HEOS, and GERG-2008. The software can generate pressure drop curves, decompression curves, and resistance curves. The pressure plateau can be quickly identified by examining the pressure drop curve. Whether the pipeline can achieve self-crack arrest can be rapidly judged by comparing the positional relationships between the decompression curve and the resistance curve. To verify the accuracy of the software’s calculation results, comparisons were conducted with previous decompression wave experimental data, full-scale burst test data of a CO₂ pipeline, and the international HLP model. The calculation error of the software is within 10%. The development and application of this software provide a convenient, efficient, and accurate practical tool for the calculation of crack arrest toughness and crack arrest evaluation of supercritical CO₂ pipelines. Full article

Background: Dual antiplatelet therapy (DAPT), combining aspirin with a P2Y12 receptor inhibitor (P2Y12i), remains central to the management of acute myocardial infarction (MI), especially in patients undergoing percutaneous coronary intervention (PCI). However, the pharmacodynamic response to antiplatelet therapy may vary with body composition. This study investigates the association between body mass index (BMI) and clinical outcomes in MI patients treated with PCI and DAPT. Methods: This retrospective cohort study analyzed data from 52,119 MI patients treated with coronary stenting from 2014 to 2021, sourced from the Hungarian Myocardial Infarction Registry. Patients were stratified into clopidogrel-based (n = 44,480) and potent P2Y12i-based (prasugrel or ticagrelor; n = 7639) DAPT cohorts. Clinical outcomes—including 12-month mortality and ischemic events—were assessed across BMI categories. Kaplan–Meier analysis and LASSO Cox regression identified predictors of mortality, while decision curve analysis (DCA) evaluated the net clinical benefit of potent P2Y12i across BMI strata. Results: Univariate and multivariate Cox regression analyses identified BMI and potent P2Y12i treatment as significant predictors of 365-day mortality, with higher BMI associated with lower observed rates of mortality, major adverse cardiovascular events (MACEs), and stroke. However, higher BMI was also associated with an increased risk of repeat revascularization and PCI. This study found that the protective effect of potent P2Y12i treatment was consistent across different BMI categories. Conclusions: In patients with MI undergoing PCI, elevated BMI was paradoxically associated with more favorable short-term outcomes, including reduced mortality. Potent P2Y12i therapy demonstrated a consistent benefit across BMI categories, supporting its broad application irrespective of body mass. Full article

The process of X-ray diffraction on the X-112° Y-cut of a LiTaO₃ crystal excited by surface acoustic waves (SAW) with a wavelength of $\mathrm{Ʌ}=4$ μm was studied at a synchrotron radiation source in a scheme of a double-crystal X-ray diffractometer. The sinusoidal acoustic modulation of the crystal lattice leads to the appearance of diffraction satellites on the rocking curve; the number and intensity of satellites depend on the amplitude of the SAW. Analysis of X-ray diffraction spectra allowed us to determine the velocity ($V_{SAW}=3300$ m/s) and amplitudes of the SAW. For the first time experimental investigations have demonstrated the presence of the power flow angle in the X-112° Y-cut of a LiTaO₃ crystal, i.e., a situation where the direction of acoustic energy propagation ($PFV$) does not coincide with the direction of the SAW wave vector $K_{SAW}$. The measured power flow angle was $PFA=0.41°$. This $PFA$ value is important for designing acoustoelectronic devices in order to reduce acoustic signal losses. Full article

The design of offshore monopile foundations typically follows an iterative process aimed at optimizing key geometric parameters—namely, pile diameter, wall thickness, and embedded length. Among these, selecting an appropriate embedded length is a critical step in geotechnical design, as it must satisfy both stability and serviceability requirements. The critical pile length is defined as the embedment depth beyond which additional penetration yields no significant improvement in lateral capacity and at which the pile reaches its critical lateral capacity. From a design standpoint, extending the pile beyond this length offers no further gain in resistance, rendering such an approach both inefficient and uneconomical. To evaluate and characterize the critical length of offshore monopile foundations, three-dimensional finite element (3D FE) analyses were performed on laterally loaded monopiles using the NGI-ADP constitutive model. The analyses considered a wide range of pile geometries, load eccentricities, and soil properties. This study first investigate how geotechnical parameters affect lateral response, then characterizes the critical lateral capacity ($H_{crit}$) and critical pile length ($L_{crit}$) based on the analyzed cases. Finally, an empirical equation was developed to estimate the critical embedment depth of monopiles in clay. Results indicate that higher undrained shear strength ($S_u$) or lower ultimate plastic shear strain (${\gamma }_f$) considerably reduce the critical pile length, whereas it is increased with greater pile head rotation. The normalized critical length is largely independent of pile diameter and load eccentricity. These insights provide practical guidance for geotechnical design by offering an efficient method to estimate critical pile length, supporting informed decisions on the required embedment depth. Full article

Background/Objectives: Neuroblastoma is a pediatric embryonal tumor of the autonomic nervous system, characterized by high heterogeneity. Recent research has explored the therapeutic potential of retinoic acid and selenium derivatives as antiproliferative agents. This study aims to assess the antiproliferative effects of sodium selenite and retinoic acid, as well as the conventional chemotherapeutic agents, cyclophosphamide and cisplatin, using the SH-SY5Y neuroblastoma cell line. Methods: Cells were treated with the compounds at concentrations ranging from 0 to 1000 µM for 72 h. The following assays were performed: cell viability, clonogenic assay, cell migration, cell cycle analysis, and gene expression (BCL2 and BAX). Data were analyzed using the Kruskal–Wallis test followed by Dunn’s or the Mann–Whitney test (p < 0.05). IC₅₀ values were obtained from dose–response curves. Results: Sodium selenite (100–1000 µM) significantly reduced cell viability by more than 50% (IC₅₀: 166 µM at 72 h). Retinoic acid (300 µM) reduced viability by 65% (IC₅₀: 198 µM at 72 h), and cisplatin (10 µM) reduced viability by 79% (IC₅₀: 3.4 µM at 72 h). All compounds significantly decreased colony formation. Sodium selenite and retinoic acid induced arrest in the G0/G1 phase of the cell cycle. Gene expression analysis revealed downregulation of the BCL2 gene by all compounds and upregulation of BAX only by sodium selenite at IC₅₀ concentration. Conclusions: Sodium selenite and retinoic acid showed antiproliferative effects on neuroblastoma cells, suggesting their potential as adjuvant therapeutic agents. To reach this goal, we suggest further investigation of their mechanisms of action and evaluation of the combined strategies. Full article

Background: The pathological response to neoadjuvant chemotherapy (NAC) is an established predictor of long-term outcomes in breast cancer. However, conventional binary assessment based solely on pathological complete response (pCR) fails to capture prognostic heterogeneity across molecular subtypes. This study aimed to develop an interpretable deep learning model that integrates multiple clinical and pathological variables to predict both recurrence and metastasis development following NAC treatment. Methods: We conducted a retrospective analysis of 832 breast cancer patients who received NAC between 2013 and 2022. The analysis incorporated five key variables: tumor size changes, nodal status, Ki-67 index, Miller–Payne grade, and molecular subtype. A Multi-Layer Perceptron (MLP) model was implemented on the PyTorch platform and systematically benchmarked against SVM, Random Forest, and XGBoost models using five-fold cross-validation. Model performance was assessed by calculating the area under the curve (AUC), accuracy, precision, recall, and F1-score, and by analyzing confusion matrices. Results: The MLP model achieved AUC values of 0.86 (95% CI: 0.82–0.93) for HER2-positive cases, 0.82 (95% CI: 0.70–0.92) for triple-negative cases, and 0.76 (95% CI: 0.66–0.82) for HR+/HER2-negative cases. SHAP analysis identified post-NAC tumor size, Ki-67 index, and Miller–Payne grade as the most influential predictors. Notably, patients who achieved pCR still had a 12% risk of developing recurrence, highlighting the necessity for ongoing risk assessment beyond binary response evaluation. Conclusions: The proposed deep learning system provides precise and interpretable risk assessment for NAC patients, facilitating individualized treatment approaches and post-treatment monitoring plans. Full article

While methods like cyclic triaxial testing and p-y model updating theory exist in geotechnical and offshore wind engineering, they have not been systematically applied to solve the specific deformation problems of offshore PV piles. This study investigates a specific offshore photovoltaic (PV) project in Qinhuangdao City, Hebei Province. Initially, field tests of horizontal static load on steel pipe pile foundations were conducted. A finite element model (FEM) of single piles was subsequently developed and validated. Further analysis examined the failure modes, initial stiffness, and ultimate resistance of offshore PV single piles in sandy soil foundations under varying pile diameters and embedment depths. The hyperbolic p-y curve model was modified by incorporating pile diameter size effects and embedment depth considerations. Key findings reveal the following: (1) The predominant failure mechanism of fixed offshore PV monopiles manifests as wedge-shaped failure in shallow soil layers. (2) Conventional API specifications and standard hyperbolic models demonstrate significant deviations in predicting p-y (horizontal soil resistance-pile displacement) curves, whereas the modified hyperbolic model shows good agreement with field measurements and numerical simulations. This research provides critical data support and methodological references for calculating the horizontal bearing capacity of offshore PV steel pipe pile foundations. Full article

Due to their potential to reduce greenhouse gas emissions, light-frame timber buildings (LFTBs) are widely used in seismically active regions. However, their construction in these areas remains limited, primarily due to the high costs associated with continuous anchor tie systems (ATSs), which are required to withstand significant seismic forces. To address this challenge, frictional seismic isolation offers an alternative by enhancing seismic protection. Although frictional base isolation is an effective mitigation strategy, its performance can be compromised by extreme ground motions that induce large lateral displacements, resulting in impacts between the sliders and the perimeter protection ring. The effects of these internal lateral impacts on base-isolated LFTBs remain largely unexplored. To fill this knowledge gap, this study evaluates the collapse capacity of a set of base-isolated LFTBs representative of Chilean real estate developments. Nonlinear numerical models were developed in the OpenSeesPy platform to capture the nonlinear behavior of the superstructure, including the impact effects within the frictional isolation system. Incremental dynamic analyses following the FEMA P695 methodology were performed using subduction ground motions. Collapse margin ratios (CMRs) and fragility curves were derived to quantify seismic performance. Results indicate that frictional base-isolated LFTBs can achieve acceptable collapse safety without ATS, even with compact-size bearings. Code-conforming archetypes achieved CMRs ranging from 1.24 to 1.55, indicating sufficient safety margins. These findings support the cost-effective implementation of frictional base isolation in mid-rise timber construction for high-seismic regions. Full article

This study investigates the development of axial force in micro anti-slide piles under soil movement during slope stabilization. Axial force arises from two primary mechanisms: axial soil displacement ($z_{\mathrm{s}}$) and pile kinematics. The former plays a dominant role, producing either tensile or compressive axial force depending on the direction of $z_{\mathrm{s}}$, while the kinematically induced component remains consistently tensile. A sliding angle of $\alpha =5°$ represents an approximate transition point where these two effects balance each other. Furthermore, the two mechanisms exhibit distinct mobilization behaviors: $z_{\mathrm{s}}$-induced axial force mobilizes earlier than both bending moment and shear force, whereas kinematically induced axial force mobilizes significantly later. The study reveals two distinct pile–soil interaction mechanisms depending on proximity to the slip surface: away from the slip surface, axial soil resistance is governed by rigid cross-section translation, whereas near the slip surface, rotation-dominated displacement accompanied by soil–pile separation introduces significant complexity in predicting both the magnitude and direction of axial friction. A hyperbolic formulation was adopted to model both the lateral soil resistance relative to lateral pile–soil displacement (p-y behavior) and the axial frictional resistance relative to axial pile–soil displacement (t-z behavior). Soil resistance equations were derived to explicitly incorporate the effects of cross-sectional rotation and pile–soil separation. A novel beam-spring finite element method (BSFEM) that incorporates both geometric and material nonlinearities of the pile behavior was developed, using a soil displacement-driven solution algorithm. Validation against both numerical simulations and field monitoring data from an engineering application demonstrates the model’s effectiveness in capturing the distribution and evolution of axial deformation and axial force in micropiles under varying soil movement conditions. Full article

Integral abutment bridges (IABs) are increasingly adopted in transportation infrastructure due to their durability, reduced maintenance needs, and cost-effectiveness compared to conventional bridges. However, their reliable performance under live loads is strongly influenced by the nonlinear soil–structure interaction (SSI) at the pile–abutment joint, which remains challenging to quantify using conventional analysis methods. This study develops simplified spring-based models to capture the SSI behavior of pile–abutment joints in short-span IABs. Predictive equations for joint rotation, deflection, moment, and shear are formulated using Linear Regression (LR) and Response Surface Methodology (RSM). Unlike prior studies relying solely on FEM or traditional p–y curves, the novelty of this work lies in deriving regression-based spring constants calibrated against FEM analyses, which can be directly implemented in standard structural software. This approach significantly reduces computational demands while maintaining predictive accuracy, enabling efficient assessment of pile contributions and global bridge response. Validation against finite element method (FEM) results confirms the reliability of the simplified models, with RSM outperforming LR in representing nonlinear parameter interactions. Full article