Search Results (25,278)

Background/Objectives: Routine postoperative ICU admission following brain tumor surgery may not benefit selected patients. The objective of this study was to develop a risk prediction instrument for early (within 24 h) postoperative adverse events using machine learning techniques. Methods: Retrospective cohort of 1000 consecutive adult patients undergoing elective brain tumor resection. Nine events/interventions (CPR, reintubation, return to OR, mechanical ventilation, vasopressors, impaired consciousness, intracranial hypertension, swallowing disorders, and death) were chosen as target variables. Potential prognostic features (n = 27) from five categories were chosen and a gradient boosting algorithm (XGBoost) was trained and cross-validated in a 5 × 5 fashion. Prognostic performance, potential clinical impact, and relative feature importance were analyzed. Results: Adverse events requiring ICU intervention occurred in 9.2% of cases. Other events not requiring ICU treatment were more frequent (35% of cases). The boosted decision trees yielded a cross-validated ROC-AUC of 0.81 ± 0.02 (mean ± CI95) when using pre- and post-op data. Using only pre-op data (scheduling decisions), ROC-AUC was 0.76 ± 0.02. PR-AUC was 0.38 ± 0.04 and 0.27 ± 0.03 for pre- and post-op data, respectively, compared to a baseline value (random classifier) of 0.092. Targeting a NPV of at least 95% would require ICU admission in just 15% (pre- and post-op data) or 30% (only pre-op data) of cases when using the prediction algorithm. Conclusions: Adoption of a risk prediction instrument based on boosted trees can support decision-makers to optimize ICU resource utilization while maintaining adequate patient safety. This may lead to a relevant reduction in ICU admissions for surveillance purposes. Full article

In various applications, observed variables are missing some information that was intended to be collected. The estimations of both loading and path coefficients could be biased when ignoring the missing data. Inverse probability weighting (IPW) is one of the well-known methods helping to reduce bias in regressions, while belonging to a promising but new category in structural equation models. The paper proposes both parametric and nonparametric IPW estimation methods for dynamic structural equation models, in which both loading and path coefficients are developed into functions of a random variable and of the quantile level. To improve the computational efficiency, modified parametric IPW and modified nonparametric IPW are developed through reducing inverse probability computations but making fuller use of completely observed information. All the above IPW estimation methods are compared to existing complete case analysis through simulation investigations. Finally, the paper illustrates the proposed model and estimation methods by an empirical study on digital new-quality productivity. Full article

In this research, the objective was to optimize the drying process of Astragalus by investigating the effects of microwave vacuum drying parameters, including temperature (30, 35, 40, 45, and 50 °C) and slice thickness (2, 3, 4, 5, and 6 mm). In addition, utilizing COMSOL 6.0 finite element analysis software, we delved into the distribution of heat and moisture during the drying process. The results revealed that drying temperature played a significantly greater role than slice thickness in determining the drying dynamics. The thermal and mass transfer mechanism indicated that the whole drying process conforms to the microwave radiation mechanism and the basic principle of electromagnetic heating. In the case of low temperatures and thinner slice sizes, the more polysaccharide content was retained; The total phenol content peaked when the slice thickness was 5 mm; The increase of slice thickness was not conducive to the retention of total flavonoids content. The potent antioxidant capacity was detected at a temperature of 40 °C, with slice thickness having a negligible effect on this capacity; Low temperatures were beneficial for the preservation of active ingredients. Compared with the scanning electron microscope, the structure appeared more uniform at a temperature of 50 °C. Based on the analysis of the kinetic characteristics of microwave vacuum drying of Astragalus and the quality achieved under various drying conditions, the results of the study can provide valuable guidance for controlling the quality of microwave vacuum drying of Astragalus under different drying requirements. Full article

In the context of the electricity sector’s liberalization and deregulation, the accurate forecasting of electricity prices has emerged as a crucial strategy for market participants and operators to minimize costs and maximize profits. However, their effectiveness is hampered by the variable temporal characteristics of real-time electricity prices and a wide array of influencing factors. These challenges hinder a single model’s ability to discern the regularity, thereby compromising forecast precision. This study introduces a novel hybrid system to enhance forecast accuracy. Firstly, by employing an advanced decomposition technique, this methodology identifies different variation features within the electricity price series, thus bolstering feature extraction efficiency. Secondly, the incorporation of a novel multi-objective intelligent optimization algorithm, which utilizes two objective functions to constrain estimation errors, facilitates the optimal integration of multiple deep learning models. The case study uses electricity market data from Australia and Singapore to validate the effectiveness of the algorithm. The forecast results indicate that the hybrid short-term electricity price forecasting system proposed in this paper exhibits higher prediction accuracy compared to traditional single-model predictions, with MAE values of 7.3363 and 4.2784, respectively. Full article

This paper presents initial findings from aeroelastic studies conducted on a wing-propeller model, aimed at evaluating the impact of aerodynamic interactions on wing flutter mechanisms and overall aeroelastic performance. The flutter onset is assessed using a frequency-domain method. Mid-fidelity tools based on the time-domain approach are then exploited to account for the complex aerodynamic interaction between the propeller and the wing. Specifically, the open-source software DUST and MBDyn are leveraged for this purpose. The investigation covers both windmilling and thrusting conditions. During the trim process, adjustments to the collective pitch of the blades are made to ensure consistency across operational points. Time histories are then analyzed to pinpoint flutter onset, and corresponding frequencies and damping ratios are identified. The results reveal a marginal destabilizing effect of aerodynamic interaction on flutter speed, approximately 5%. Notably, the thrusting condition demonstrates a greater destabilizing influence compared to the windmilling case. These comprehensive findings enhance the understanding of the aerodynamic behavior of such systems and offer valuable insights for early design predictions and the development of streamlined models for future endeavors. Full article

Active power dispatch of new energy refers to an effective method of ensuring the stable operation and optimal economic benefits of new energy power systems through scientific and rational planning and control of active power output from new energy generation. However, as the proportion of new energy increases, the system’s voltage support capacity decreases, leading to potential voltage collapse and oscillation issues. The Multiple Renewable Energy Station Short-Circuit Ratio (MRSCR) is a critical indicator of the system’s voltage support capacity for power systems with high new energy penetration. This study aims to introduce MRSCR constraints into the active power dispatch to guarantee sufficient grid integration strength and stable operation. The MRSCR constraints are approximated using the least squares fitting method. Additionally, this study compares the economic benefits and margin of the indicators between wind and thermal power active scheduling models with and without considering MRSCR. Case studies show that the active scheduling model considering MRSCR constraints improves the MRSCR margin with minimal loss of economic benefits. Full article

Hepatitis E virus (HEV) is a leading cause of acute viral hepatitis worldwide, primarily transmitted through contaminated water and food. In patients with chronic liver disease (CLD), HEV infection might worsen the prognosis. This study aimed to evaluate the cost-effectiveness of hepatitis E vaccination strategies in CLD patients. A decision tree–Markov cohort model was used to assess the cost-effectiveness of universal-vaccination, vaccination-following-screening, and no-vaccination strategies in 100,000 CLD patients over their lifetimes, simulating cohorts aged ≥16 years, ≥40 years, and ≥60 years, based on the licensed vaccination ages and typical ages of CLD onset, from a societal perspective. Model parameters were retrieved and estimated from previous publications and government data. The outcomes included HEV-related cases, costs, and the incremental cost-effectiveness ratio (ICER). Compared to no-vaccination, universal-vaccination reduced HEV-related cases by 32.8% to 39.6%, while vaccination-following-screening reduced them by 38.1% to 49.3%. Furthermore, universal-vaccination showed ICERs of USD 6898.33, USD 6638.91, and USD 6582.69 per quality-adjusted life year (QALY) for cohorts aged ≥16, ≥40, and ≥60 years, respectively. Moreover, the vaccination-following-screening strategy significantly enhanced cost-effectiveness, with ICERs decreasing to USD 6201.55, USD 5199.46, and USD 4919.87 per QALY for the cohorts. Additionally, one-way sensitivity analysis identified the discount rate and utility for CLD patients as the key factors influencing ICER. Probabilistic sensitivity analysis indicated the vaccination-following-screening strategy was cost-effective with probabilities of 92.50%, 95.70%, and 95.90% for each cohort. Hepatitis E vaccination in CLD patients costs less than GDP per capita for each QALY gained in China. The vaccination-following-screening strategy may be the optimal option, especially in those over 60 years. Full article

The objective of this retrospective study was to compare the dento-alveolar effects of two different expansion protocols, Invisalign First (IF) and Leaf Expander (LE), in patients in mixed dentition with transversal upper maxillary deficiency. Materials and Methods: 30 patients were treated with IF, whereas 38 patients were treated with LE. For each sample 3D digital cast models were analyzed pre and post expansion and transversal diameter of the upper arch, molar rotation and inclination and arch perimeter were measured. Results: LE resulted in a more significant expansion of the molar width and the arch perimeter, with less effect on the expansion of deciduous canines and deciduous molars. IF allowed a more effective molar derotation, but with a greater buccal tipping movement than LE, which determines a more bodily movement of the molars: the expansion determined by IF seems to be more dental than skeletal. Conclusions: IF is a good alternative to LE in case of limited transversal maxillary contraction, particularly when there is a significant mesio-rotation of the first upper molars. Full article

The beginning of the COVID-19 pandemic was marked by a sharp decline in syphilis infections in many countries worldwide, including Greece. However, a resurgence of positive cases started to appear in the second half of 2020. The aim of this study was to explore the impact of the pandemic on the incidence of new syphilis infections and reinfections and analyze the sociodemographic characteristics associated with recurrent episodes. We analyzed medical records from a 14-month period after the beginning of the pandemic and compared them with the respective period before the start of the pandemic. Our participants consisted mainly of men, with a median age of 43 years, homosexual orientation, and higher education. During COVID-19, more HIV patients presented for syphilis testing (38.0% vs. 34.6%, p = 0.025). Overall, we observed almost a two-fold increase in positive syphilis cases during COVID-19 (21.1% vs. 12.4%, p < 0.001), with new infections rising from 8.4% to 13.2% and reinfections from 4.0% to 7.9%. Multivariable logistic regression analysis revealed that the COVID-19 pandemic, among different parameters (such as age, gender, sexual orientation, HIV status, and educational level), was the only factor associated with higher positive syphilis rates (OR 1.47, 95% CI: 1.07–2.01, p = 0.003). Our results highlight the need to ensure enhanced prevention and undisrupted healthcare services, with a focus on future pandemics. Full article

Integration of heat pumps combined with thermal energy storage provides a key pathway to decarbonizing the energy supply in the industry when the processes are not operated continuously. Yet, this integration of such novel systems introduces control challenges due to added dependencies between different process streams. This work investigates the control problem of heat pumps coupled to stratified thermal energy storage that is integrated into non-continuous industrial processes. A two-layer control strategy is proposed, where, in the higher level, a model predictive controller is developed for energy management using a linear model of the non-linear process. The resulting optimization problem is a mixed integer quadratic program. The low-level control layer is defined with standard industry controllers. The overall system is tested using a dynamic simulation model for the entire process, demonstrating its performance in three different cases. The control strategy optimizes heat recovery while ensuring system operability. The study demonstrates successful disturbance rejection and cold starts, wherein 100% of the targeted heat recovery can be confirmed under nominal conditions. Further evaluation in laboratory or field trials is recommended, and alternative, yet-to-be-defined, control concepts may be compared to the proposed approach. Full article

The utilization of micro-sample testing has demonstrated its effectiveness in conducting quantitative research on mechanical properties, damage evolutions and fracture features. For in-service equipment, millimicron sampling allows for non-destructive testing and analysis of mechanical performance evolution during operation. This paper presents a comparative study of the miniature uniaxial tensile test (MUTT) and small punch test (SPT) by experimental and finite element methods. As a comparison, the standard conventional-size tensile tests were also carried out. Detailed analyses of the elastoplastic behaviors and damage evolutions of MUTT and SPT were presented, followed by an application case illustrating the characterization of hydrogen embrittlement sensitivity based on MUTT and SPT. An inverse finite element modeling method of load–displacement curve reproduction was used to calibrate the variations of damage parameters of hydrogen-charged MUTT and SPT specimens. Hydrogen embrittlement (HE) indexes were determined by using different calculation methods. The results reveal that the HE sensitivity estimated by MUTT is higher than that measured by SPT, which is related to the different deformation processes and strain rates of the two testing methods. Full article

Agricultural phosphorus (P) loss constitutes a significant factor in agricultural non-point source pollution (ANSP). Due to the widespread occurrence and complexity of ANSP, emphasis on risk prevention and control is preferable to retroactive treatment, to reduce costs. Effective risk identification is an issue that needs to be addressed urgently. Henan Province, a typical intensive agricultural region in China, was used as a case study to develop a straightforward and precise model for assessing the risk of P loss. Total phosphorus (TP) emission intensity at the county level in Henan Province was estimated based on planting, livestock and poultry breeding, and rural domestic activities. Subsequently, influential factors were selected to determine the extent of P loss in rivers. Finally, the model was validated using water quality data. The results indicate that (1) TP emission and rainfall are the primary contributors to the risk of P loss, whereas vegetation coverage has negligible effects. (2) The primary sources of TP emission, in descending order of magnitude, are livestock and poultry breeding, rural domestic activities, and planting. Livestock and poultry breeding represents the largest proportion at approximately 50%. (3) High-risk areas for P loss are concentrated in the plains of the central, eastern, and northern Henan Province, while low-risk areas are mainly located in the western mountainous and hilly regions. (4) The model exhibits high accuracy with a determination coefficient (R²) of 0.81 when compared to surface water quality monitoring data. This study provides a new framework for assessing the risk of P loss in intensive agricultural settings. Full article

The effect of triaxiality on the evolution of damage in Al-2024 aluminum cylindrical specimens is studied in this work. Uncoupled and coupled damage models, all of them explicitly dependent on triaxiality, are assessed and compared. These models are characterized by tensile tests on cylindrical specimens without notches, to obtain the material parameters for each model. The capability of each model to predict fracture when different positive triaxial conditions evolve is then evaluated through tensile tests on notched cylindrical specimens. In particular, the damage index, evaluated at the fracture strain level, is compared with the experimental results validating the models. Moreover, the triaxiality evolution in the different specimens is studied in order to assess its effect on damage, demonstrating that the fracture strain decreases at greater triaxiality values. Observations through scanning electron microscopy confirm this pattern; i.e., an increase in triaxiality reveals a shift in the fracture mechanism from a more ductile condition in the original specimens to a more brittle one as the notch radius decreases. In addition, bilinear damage evolution is proposed to describe the physical behavior of the material when the Lemaitre coupled model is considered. In such a case, special attention must be devoted to the material characterization since coupling between hardening material parameters and damage affects the results. Full article

Background/Objectives: Detailed morphometric analysis of an aneurysm and the related vascular bifurcation are critical factors when determining rupture risk and planning treatment for unruptured intracranial aneurysms (UIAs). The standard visualization of digital subtraction angiography (DSA) and its 3D reconstruction on a 2D monitor provide precise measurements but are subject to variability based on the rater. Visualization using virtual (VR) and augmented reality platforms can overcome those limitations. It is, however, unclear whether accurate measurements of the aneurysm and adjacent arterial branches can be obtained on VR models. This study aimed to assess interrater reliability and compare measurements between 3D VR, standard 2D DSA, and 3D DSA reconstructions, evaluating the reliability and accuracy of 3D VR as a measurement tool. Methods: A pool of five neurosurgeons performed three individual analyses on each of the ten UIA cases, measuring them in completely immersed 3D VR and the standard on-screen format (2D DSA and 3D reconstruction). This resulted in three independent measurements per modality for each case. Interrater reliability of measurements and morphology characterization, comparative differences, measurement duration, and VR user experience were assessed. Results: Interrater reliability for 3D VR measurements was significantly higher than for 3D DSA measurements (3D VR mean intraclass correlation coefficient [ICC]: 0.69 ± 0.22 vs. 3D DSA mean ICC: 0.36 ± 0.37, p = 0.042). No significant difference was observed between 3D VR and 2D DSA (3D VR mean ICC: 0.69 ± 0.22 vs. 2D DSA mean ICC: 0.43 ± 0.31, p = 0.12). A linear mixed-effects model showed no effect of 3D VR and 3D DSA (95% CI = −0.26–0.28, p = 0.96) or 3D VR and 2D DSA (95% CI = −0.02–0.53, p = 0.066) on absolute measurements of the aneurysm in the anteroposterior, mediolateral, and craniocaudal dimensions. Conclusions: 3D VR technology allows for reproducible, accurate, and reliable measurements comparable to measurements performed on a 2D screen. It may also potentially improve precision for measurements of non-planar aneurysm dimensions. Full article

Optimizing energy consumption is an important aspect of industrial competitiveness, as it directly impacts operational efficiency, cost reduction, and sustainability goals. In this context, anomaly detection (AD) becomes a valuable methodology, as it supports maintenance activities in the manufacturing sector, allowing for early intervention to prevent energy waste and maintain optimal performance. Here, an AD-based method is proposed and studied to support energy-saving predictive maintenance of production lines using time series acquired directly from the field. This paper proposes a deep echo state network (DeepESN)-based method for anomaly detection by analyzing energy consumption data sets from production lines. Compared with traditional prediction methods, such as recurrent neural networks with long short-term memory (LSTM), although both models show similar time series trends, the DeepESN-based method studied here appears to have some advantages, such as timelier error detection and higher prediction accuracy. In addition, the DeepESN-based method has been shown to be more accurate in predicting the occurrence of failure. The proposed solution has been extensively tested in a real-world pilot case consisting of an automated metal filter production line equipped with industrial smart meters to acquire energy data during production phases; the time series, composed of 88 variables associated with energy parameters, was then processed using the techniques introduced earlier. The results show that our method enables earlier error detection and achieves higher prediction accuracy when running on an edge device. Full article