Search Results (55)

This paper presents a calibration technique for the Intelligent Driver Model (IDM), a car-following model that considers the physical interpretation of each parameter. Using an instrumented vehicle, trajectory data were gathered for a group of Portuguese drivers. The data included various basic scenarios, such as unrestricted acceleration and deceleration maneuvers, as well as following other cars in steady-state conditions. The calibration process involved two steps. In the first step, specific parameters that have clear physical interpretations were manually adjusted to accurately reproduce the speed patterns of basic driving scenarios. In the second step, the obtained results were used to establish the limits of values for a simultaneous calibration procedure. The results demonstrate that the calibration procedure enables precise replication of the actual trajectories. Nevertheless, the model validation results indicate that calibrating without limitations on the parameter search space produces estimates with greater explanatory capability, contradicting previous research and supporting the need for additional analyses. Full article

Climate change-induced heavy rainfall during summer months can further increase suspended solid loads in rivers, elevating turbidity. Such elevated turbidity can compromise fish gill tissue integrity and impair oxygen uptake, potentially leading to fatal impacts in aquatic ecosystems. Therefore, this study aims to examine fish migratory behaviors and physiological responses to varying turbidity levels through experimental trials to generate baseline data for assessing fish habitat suitability. The experimental design comprised two primary components: an investigation of turbidity avoidance behaviors and an analysis of habitat compatibility through extended exposure to turbid conditions. This study focused on dominant freshwater fish species native to South Korea, Zacco platypus, Pseudopungtungia nigra, and Zacco koreanus. Fish condition in response to turbidity was monitored over a 15-day period, during which locomotor activity and water quality parameters were recorded. In the control group tank with no turbidity, all species exhibited unrestricted swimming patterns without depth preference. However, in moderate and high turbidity treatments, all demonstrated preferential utilization of middle- and lower-depth strata. In addition, the highest number of fish mortality occurred in high-turbidity zones because of respiratory impediments from elevated suspended solid concentrations. These findings provide valuable insights into fish mobility and habitat utilization patterns in rivers experiencing sudden turbidity events, such as those associated with weir operations. Full article

Fused deposition modeling (FDM), as one of the most widespread and cost-effective additive manufacturing (AM) technologies, faces ongoing challenges in improving the dimensional accuracy and mechanical properties of complex shapes. The repeated heating and cooling of thermoplastic filaments make the FDM parts prone to accumulating warping deformation, which is difficult to predict due to the specificity of material deposition toolpaths. In this study, a path-based discrete modeling and process simulation method was developed for the FDM process. Based on process parameters and material deposition toolpaths, the finite element (FE) model was reconstructed using the discrete modeling method. Then, the birth–death element method (BDEM) was employed to simulate the FDM process and solve the thermo-mechanical coupling field in ANSYS 2022 R1. The corresponding computing programs were compiled in C++. The effectiveness of the proposed method was verified by three numerical examples using ABS material. According to the results, the simulated deformations show strong agreement with the deformations of real FDM parts. The findings of this study are applicable to other mainstream AM processes and are unrestricted by any complex geometries. Full article

Background: Palliative surgery for the treatment of functionally univentricular heart malformations consists of a staged approach to separation of the pulmonary and systemic circulation, including the creation of a superior cavopulmonary connection. Literature on the superior cavopulmonary connection in porcine models lacks information on details of the procedure as well as data on its acute hemodynamic effects. In preliminary experiments, we were unable to reproduce an already published porcine model. Therefore, we used a conduit extension and cardiopulmonary bypass in order to achieve hemodynamic stability and still employ the commonly used straight downward pathway for the superior caval vein onto the right pulmonary artery, as in the human clinical setting. This model of a univentricular circulation utilising the superior cavopulmonary anastomosis is intended to be applied in the setting of unilateral diaphragmatic palsy. Hence, we aim to investigate the effect of unilateral diaphragmatic pacing in a reproducible model of univentricular physiology. Methods: Therefore, we constructed an anastomosis between the superior caval vein and the right pulmonary artery (RPA) in 14 pigs on cardiopulmonary bypass using a 12 mm expanded polytetrafluorethylene interposition graft. Six pigs received a bidirectional cavopulmonary connection with unrestricted atrial septal communication (BDCPC), while eight pigs received a unidirectional cavopulmonary connection (UDCPC) to the excluded RPA. Results: The BDCPC resulted in an impaired cardiopulmonary state (cardiac output dropped from 3.15 ± 0.21 to 2.17 ± 0.19 L/min; p < 0.01), mean arterial pressure plummeted (from 80.8 ± 3.7 to 49.3 ± 7.3 mmHg; p = 0.02), arterial lactate concentration rose (from 0.82 ± 0.09 to 4.36 ± 0.96 mmol/L; p = 0.01), arterial oxygen saturation dropped (from 95.8 ± 1.1 to 60.9 ± 10.4%; p < 0.01), and right ventricular function deteriorated (tricuspid annular plane systolic excursion decreased from 12 ± 0.7 to 5 ± 0.7 mm; p < 0.01). In contrast, in the UDCPC group, the cardiopulmonary parameters indicated a stable condition. Conclusions: Consequently, a UDCPC is a more suitable acute model in pigs for a univentricular circulation. The model’s reproducibility may aid in future research on partial cavopulmonary connection. Full article

This experiment aimed to evaluate the impact of various feed additive-treated silage corn straw on the growth performance, blood parameters, nutrient apparent digestibility, and rumen fermentation in Simmental cattle. Eighteen healthy Simmental bulls (275.64 ± 15.27 kg) were randomly assigned to three groups, each consisting of six bulls: a control group (CON) receiving a basal diet, an experimental group, (OS) wherein 20% of the rice straw in the control group’s diet was substituted with silage corn straw treated with organic acid, and another experimental group (MS) wherein 20% of the rice straw was replaced with silage corn straw mixed with corn flour, lactic acid bacteria, and organic acid. All cattle were fed at 08:30 and 16:30, twice each day, with unrestricted access to water throughout the study. The results indicated that silage had no effect on the growth and serum biochemical indexes of beef cattle among all groups. However, other parameters, mainly rumen fermentation parameters, nutrient digestibility, and rumen microorganisms, were affected by the silage. The MS group significantly increased the concentration of microbial protein (MCP) in the rumen of cattle compared to the CON group. The OS and MS groups had a similar apparent digestibility of ether extract and acid detergent fiber (ADF), but a higher digestibility of dry matter (DM) (p = 0.001) and crude protein (CP) (p < 0.001) compared to the CON group. The rumen bacterial community of the MS group had a lower abundance of Proteobacteria than the CON group (p = 0.016). The abundance of Firmicutes in the MS group was not significantly different from the CON group, but there was an increasing trend compared with the OS group (p = 0.054). A Spearman correlation analysis showed that the apparent digestibility of NDF and CP was negatively correlated with Succinivibrionaceae UCG-002 (r = −0.552, p = 0.018; r = −0.668, p = 0.002), Succinimonas (r = −0.774, p < 0.001; r = −0.513, p = 0.029), and Ruminobacter (r = −0.583, p = 0.011; r = −0.618, p = 0.006). The apparent digestibility of DM exhibited a negative correlation with Succinivibrionaceae UCG-002 (r = −0.538, p = 0.021) and Succinimonas (r = −0.642, p = 0.004). Overall, corn straw silage with mixed additives has more feeding value, which can improve rumen fermentation and regulate the rumen bacterial community. Straw silage can change the rumen microbial community structure to improve the apparent digestibility of nutrients. Full article

Electricity price forecasting has been a topic of significant interest since the deregulation of electricity markets worldwide. The New Zealand electricity market is run primarily on renewable fuels, and so weather metrics have a significant impact on electricity price and volatility. In this paper, we employ a mixed-frequency vector autoregression (MF-VAR) framework where we propose a VAR specification to the reverse unrestricted mixed-data sampling (RU-MIDAS) model, called RU-MIDAS-VAR, to provide point forecasts of half-hourly electricity prices using several weather variables and electricity demand. A key focus of this study is the use of variational Bayes as an estimation technique and its comparison with other well-known Bayesian estimation methods. We separate forecasts for peak and off-peak periods in a day since we are primarily concerned with forecasts for peak periods. Our forecasts, which include peak and off-peak data, show that weather variables and demand as regressors can replicate some key characteristics of electricity prices. We also find the MF-VAR and RU-MIDAS-VAR models achieve similar forecast results. Using the LASSO, adaptive LASSO, and random subspace regression as dimension-reduction and variable selection methods helps to improve forecasts where random subspace methods perform well for large parameter sets while the LASSO significantly improves our forecasting results in all scenarios. Full article

The purpose of this paper is to discuss the problem of estimation and testing the equality of two autoregressive parameters of two first-order autoregressive processes $\mathit{AR}\left(1\right)$, where for each process, the observations are made at different time points. The primary interest is to propose the testing procedures for the homogeneity of autocorrelation parameters ${\rho }_1$ and ${\rho }_2$. Furthermore, we are interested in estimating ${\rho }_1$ under uncertain and weak prior information about the possible equality of ${\rho }_1$ and ${\rho }_2$, though we may not have full confidence in the tenacity of this information. A large sample test for the homogeneity of the parameters is developed. Pooled “P” (or restricted estimator) and preliminary test “PT” estimators are proposed, and their properties are investigated and compared with the unrestricted estimator “UE” of ${\rho }_1$. Full article

Several wireless communication technologies, including Wireless Sensor Networks (WSNs), are essential for Internet of Things (IoT) applications. WSNs employ a layered framework to govern data exchanges between sender and recipient, which facilitates the establishment of rules and standards. However, in this conventional framework, network data sharing is limited to directly stacked layers, allowing manufacturers to develop proprietary protocols while impeding WSN optimization, such as energy consumption minimization, due to non-directly stacked layer effects on network performance. A Cross-Layer (CL) framework addresses implementation, modeling, and design challenges in IoT systems by allowing unrestricted data and parameter sharing between non-stacked layers. This holistic approach captures system dynamics, enabling network design optimization to address IoT network challenges. This paper introduces a novel CL modeling methodology for wireless communication systems, which is applied in two case studies to develop models for estimating energy consumption metrics, including node and network lifetime. Each case study validates the resulting model through experimental tests, demonstrating high accuracy with less than 3% error. Full article

The paper presents the application of a new bio-inspired metaheuristic optimization algorithm. The popularity and usability of different swarm-based metaheuristic algorithms are undeniable. The majority of known algorithms mimic the hunting behavior of animals. However, the current approach does not satisfy the full bio-diversity inspiration among different organisms. Thus, the Birch-inspired Optimization Algorithm (BiOA) is proposed as a powerful and efficient tool based on the pioneering behavior of one of the most common tree species. Birch trees are known for their superiority over other species in overgrowing and spreading across unrestricted terrains. The proposed two-step algorithm reproduces both the seed transport and plant development. A detailed description and the mathematical model of the algorithm are given. The discussion and examination of the influence of the parameters on efficiency are also provided in detail. In order to demonstrate the effectiveness of the proposed algorithm, its application to selecting the parameters of the control structure of a drive system with an elastic connection is shown. A structure with a PI controller and two additional feedbacks on the torque and speed difference between the drive motor and the working machine was selected. A system with rated and variable parameters is considered. The theoretical considerations and the simulation study were verified on a laboratory stand. Full article

A hyperactive tumour microenvironment (TME) drives unrestricted cancer cell survival, drug resistance, and metastasis in ovarian carcinoma (OC). However, therapeutic targets within the TME for OC remain elusive, and efficient methods to quantify TME activity are still limited. Herein, we employed an integrated bioinformatics approach to determine which immune-related genes (IRGs) modulate the TME and further assess their potential theragnostic (therapeutic + diagnostic) significance in OC progression. Using a robust approach, we developed a predictive risk model to retrospectively examine the clinicopathological parameters of OC patients from The Cancer Genome Atlas (TCGA) database. The validity of the prognostic model was confirmed with data from the International Cancer Genome Consortium (ICGC) cohort. Our approach identified nine IRGs, AKT2, FGF7, FOS, IL27RA, LRP1, OBP2A, PAEP, PDGFRA, and PI3, that form a prognostic model in OC progression, distinguishing patients with significantly better clinical outcomes in the low-risk group. We validated this model as an independent prognostic indicator and demonstrated enhanced prognostic significance when used alongside clinical nomograms for accurate prediction. Elevated LRP1 expression, which indicates poor prognosis in bladder cancer (BLCA), OC, low-grade gliomas (LGG), and glioblastoma (GBM), was also associated with immune infiltration in several other cancers. Significant correlations with immune checkpoint genes (ICGs) highlight the potential importance of LRP1 as a biomarker and therapeutic target. Furthermore, gene set enrichment analysis highlighted LRP1’s involvement in metabolism-related pathways, supporting its prognostic and therapeutic relevance also in BLCA, OC, low-grade gliomas (LGG), GBM, kidney cancer, OC, BLCA, kidney renal clear cell carcinoma (KIRC), stomach adenocarcinoma (STAD), and stomach and oesophageal carcinoma (STES). Our study has generated a novel signature of nine IRGs within the TME across cancers, that could serve as potential prognostic predictors and provide a valuable resource to improve the prognosis of OC. Full article

Aiming at the high accuracy and high robustness position control of servo pump control in the pitch system of a wind turbine generator, this paper proposes an active disturbance rejection controller (ADRC). The ADRC considers pitch angular velocity and acceleration limits. According to the kinematics principle of the pump-controlled pitch system, the relationship between the pitch angular velocity and acceleration limit and the displacement of the hydraulic cylinder is established. Through the method of theoretical analysis, the nonlinear relationship expression between pitch angle and hydraulic cylinder displacement is obtained, and the linearization of pitch angular velocity control is realized; the formula for b₀ (the estimated value of the input gain of the system) of the pump-controlled pitch system is obtained by the method of modeling and analysis, b₀ is the key parameter for the design of the ADRC; the stability of the controller parameters is proved through the stability analysis and simulation analysis, and the design of the self-immobilizing controller with pitch angular velocity and acceleration limitation is the completed ADRC design. Finally, a joint simulation platform of AMESim and MATLAB as well as a physical experiment platform of electro-hydraulic servo pump-controlled pitch control is constructed, and the effectiveness of the proposed control method is verified through simulation and experiment. The results show that compared with the unrestricted ADRC and PID, the velocity-acceleration-limited ADRC can effectively improve the control effect of the angular velocity and acceleration of the paddle, smooth the startup process, improve the safety of the system, and have better position control accuracy and anti-jamming ability. Full article

A collection of metabolic disorders and neurodegenerative diseases linked to oxidative stress and neuroinflammation frequently affect postmenopausal women or estrogen deprivation. Recent research has focused on alternative therapies that can enhance these women’s quality of life. This study set out to investigate the effects of physical exercise (EX) and intermittent fasting (IF) on oxidants/antioxidants, inflammatory cytokines, neurotransmitters, and brain-derived neurotrophic factor (BDNF) in the cortex of rats. Additionally, it sought to assess the response to oxidative stress and neuroinflammation in the brains of rats following ovariectomy (OVX) and the potential mechanisms of these interventions. Fifty female rats were divided into one of the following groups 30 days after bilateral OVX: Control, OVX, OVX + EX, OVX + IF, and OVX + EX + IF groups. The rats in the Control and OVX groups continued their normal activities and had unrestricted access to food and water, but the rats in the OVX + EX and OVX + EX + IF groups had a 4-week treadmill training program, and the rats in the OXV + IF and OVX + EX + IF groups fasted for 13 h each day. The rats were killed, the cerebral cortex was taken, tissue homogenates were created, and various parameters were estimated using these homogenates. The results show that ovariectomized rats had decreased levels of neurotransmitters (DA, NE, and SE), acetylcholinesterase, brain GSH (glutathione), SOD (superoxide dismutase), catalase, GPx (glutathione peroxidase), and TAC (total antioxidant capacity), as well as elevated levels of proinflammatory cytokines and mediators (TNF-α, IL-1β, Cox-2). While ovariectomy-induced declines in neurotransmitters, enzymatic and nonenzymatic molecules, neuroinflammation, and oxidative brain damage were considerably mitigated and prevented by treadmill exercise and intermittent fasting, BDNF was significantly increased. These results suggest that ovariectomy can impair rat neuronal function and regular treadmill exercise and intermittent fasting seem to protect against ovariectomy-induced neuronal impairment through the inhibition of oxidative stress and neuroinflammation and increased BDNF levels in the brain cortex. However, combining regular exercise and intermittent fasting did not provide additional benefits compared to either treatment alone. Full article

In mobile ad hoc networks (MANETs), geographical routing provides a robust and scalable solution for the randomly distributed and unrestricted movement of nodes. Each node broadcasts beacon packets periodically to exchange its position with neighboring nodes. However, reliable beacons can negatively affect routing performance in dynamic environments, particularly when there is a sudden and rapid change in the nodes’ mobility. Therefore, this paper suggests an improved Greedy Perimeter Stateless Routing Protocol, namely AFB-GPSR, to reduce routing overhead and increase network reliability by maintaining correct route selection. To this end, an adaptive beaconing strategy based on a fuzzy logic scheme (AFB) is utilized to choose more optimal routes for data forwarding. Instead of constant periodic beaconing, the AFB strategy can dynamically adjust beacon interval time with the variation of three network parameters: node speed, one-hop neighbors’ density, and link quality of nodes. The routing evaluation of the proposed protocol is carried out using OMNeT++ simulation experiments. The results show that the AFB strategy within the GPSR protocol can effectively reduce the routing overhead and improve the packet-delivery ratio, throughput, average end-to-end delay, and normalized routing load as compared to traditional routing protocols (AODV and GPSR with fixed beaconing). An enhancement of the packet-delivery ratio of up to 14% is achieved, and the routing cost is reduced by 35%. Moreover, the AFB-GPSR protocol exhibits good performance versus the state-of-the-art protocols in MANET. Full article

The first case of virtual polymerization based on the concept of digital twins (DTs) is presented. The free-radical polymerization of vinyl monomers is considered to be a chain reaction consisting of a set of elementary ones. Those three types, related to the polymerization initiation and propagation as well as to the termination of polymer chain growth, are discussed. Special sets of DTs, whose total number approaches 60, distinguish each reaction type. The calculations are carried out using a semi-empirical version of the unrestricted Hartree–Fock approximation. The main energy and spin-density parameters of the ground state of the DTs are determined. The barrier profiles of two pairs of DTs are calculated, based on which two Evans–Polanyi–Semenov relations, attributed to elementary reactions of type (1) and (2), are constructed. These provide a quite reliable evaluation of the activation energy for the initiation and propagation of the free-radical polymerization of vinyl monomers in all the cases. The decisive role of spins in the formation of the elementary reaction transition states is established. Full article

Deep lifelong learning models can learn new information continuously while minimizing the impact on previously acquired knowledge, and thus adapt to changing data. However, existing optimization approaches for deep lifelong learning cannot simultaneously satisfy the following conditions: unrestricted learning of new data, no use of old data, and no increase in model parameters. To address this problem, a deep lifelong learning optimization algorithm based on dense region fusion (DLLO-DRF) is proposed. This algorithm first obtains models for each stage of lifelong learning, and divides the model parameters for each stage into multiple regions based on the parameter values. Then, based on the dispersion of the parameter distribution, dense regions are dynamically obtained from the divided regions, and the parameters of the dense regions are averaged and fused to optimize the model. Finally, extensive experiments are conducted on the self-labeled transmission line defect dataset, and the results show that DLLO-DRF has the best performance among various comparative algorithms. Full article