This paper empirically examines whether integrating entrepreneurial abilities with the theory of perceived behaviour positively influences Sustainable-Development-Goal-8-driven sustainable entrepreneurial intentions (SDG-8 SEIs). The data used in this study were gathered from 540 students from top-ranked Indian engineering colleges that offer entrepreneurship courses and have access to company incubators. According to the theory of planned behaviour (TPB), perceived behavioural control, subjective norms, and entrepreneurial drive are the three elements of perceived entrepreneurial behaviour. The TPB’s dimensions in this study have entrepreneurial competencies as their antecedents. Cognitive competency, risk propensity, and social competency and resilience are antecedents of the TPB’s dimensions. One entrepreneurial viewpoint uses sustainable UNDP-SDG-8 as a metric for assessing intentions; its objectives are the promotion of inclusive and sustainable economic growth, full and productive employment, and decent work for all. This study used partial least squares structural equation modelling (PLS-SEM). According to the findings, engineering students in India are more likely to have entrepreneurial-focused intentions based on sustainability if they adhere to the TPB’s dimensions along with additional constructs. Using an expanded TPB model, we show that the TPB has learnable and stimulating antecedents, with these having a positive effect on SDG-8 SEIs, thus extending entrepreneurial activity in India. Policymakers, universities, and students will find these results very intriguing. The TPB’s dimensions and three additional dimensions are proposed as antecedents in a new conceptual model aimed at sustainable entrepreneurship in this study. Full article

Background/Objectives: A superinfection occurs when a new, secondary organism colonizes an existing infection. Spine infections are associated with high patient morbidity and sometimes require multiple irrigations and debridements (I&Ds). When multiple I&Ds are required, the risk of complications increases. The purpose of this study was to report our experience with spine superinfections and determine which patients are typically affected. Methods: A retrospective case series of spine superinfections and a retrospective case–control analysis were conducted. Data were collected manually from electronic medical records. Spine I&Ds were identified. Groups were created for patients who had multiple I&Ds for (1) a recurrence of the same causative organism or (2) a superinfection with a novel organism. Preoperative demographic, clinical, and microbiologic data were compared between these two outcomes. A case series of superinfections with descriptive data was constructed. Lastly, two illustrative cases were provided in a narrative format. Results: A total of 92 patients were included in this analysis. Superinfections occurred after 6 out of the 92 (7%) initial I&Ds and were responsible for 6 out of the 24 (25%) repeat I&Ds. The preoperative erythrocyte sedimentation rate (ESR) and C-reactive protein (CRP) of the patients with a superinfection were significantly lower than those in the control group (p = 0.022 and p = 0.032). Otherwise, the observed differences in the preoperative variables were not statistically different. In the six cases of superinfection, the presence of high-risk comorbidities, a history of substance abuse, or a lack of social support were commonly observed. The superinfecting organisms included Candida, Pseudomonas, Serratia, Klebsiella, Enterobacter, and Staphylococcus species. Conclusions: Superinfections are a devastating complication requiring reoperation after initial spine I&D. Awareness of the possibility of superinfection and common patient archetypes can be helpful for clinicians and care teams. Future work is needed to examine how to identify, help predict, and prevent spine superinfections. Full article

Photosynthesis, as the primary source of energy for all life forms, plays a crucial role in maintaining the global balance of energy, entropy, and enthalpy in living organisms. Among its various building blocks, photosystem I (PSI) is responsible for light-driven electron transfer, crucial for generating cellular reducing power. PSI acts as a light-driven plastocyanin-ferredoxin oxidoreductase and is situated in the thylakoid membranes of cyanobacteria and the chloroplasts of eukaryotic photosynthetic organisms. Comprehending the structure and function of the photosynthetic machinery is essential for understanding its mode of action. New insights are offered into the structure and function of PSI and its associated light-harvesting proteins, with a specific focus on the remarkable structural conservation of the core complex and high plasticity of the peripheral light-harvesting complexes. Full article

Fermentation of pumpkin puree and mature coconut water using water kefir grains is a potential method for producing a novel functional non-dairy-based probiotic drink. In the present study, response surface methodology based on Box–Behnken design (RSM-BBD) was used to optimise fermentation temperature and substrates’ concentrations. The optimised fermentation temperature, pumpkin puree, and brown sugar concentrations of pumpkin-based mature coconut water kefir beverage (PWKC) were 27 °C, 20%, and 10% w/v, respectively. The optimised PWKC (PWKC_opt) obtained an overall acceptability (OA) score of 4.03, with a desirable Lactobacillus count (6.41 Log CFU/mL), 0.68% v/v lactic acid content, 31% of water kefir grains’ biomass growth rate, and fermentation time (to reach pH 4.5) of 4.5 h. The optimized beverage, PWKC_opt, contained 3.26% proteins, 2.75% dietary fibre, 2186.33 mg/L of potassium, 180.67 mg/L phosphorus, and 137.33 mg/L calcium and had a total phenolic content of 89.93 mg GAE/100 mL, flavonoid content of 49.94 mg QE/100 mL, and carotenoid content of 33.24 mg/100 mL, with antioxidant activity (FRAP: 169.17 mM Fe(II)/100 mL, IC₅₀ value of DPPH free radicals scavenging activity: 27.17 mg/mL). Water kefir microorganisms in PWKC_opt remained stable for at least 56 days at 4 °C. Therefore, PWKC_opt might potentially serve as a value-added product, offering a basis for sustainable development within both the coconut and pumpkin industries. Full article

With the rapid development of artificial intelligence technology, data-driven advanced models have provided new ideas and means for airfoil aerodynamic optimization. As the advanced models update and iterate, many useful explorations and attempts have been made by researchers on the integrated application of artificial intelligence and airfoil aerodynamic optimization. In this paper, many critical aerodynamic optimization steps where data-driven advanced models are employed are reviewed. These steps include geometric parameterization, aerodynamic solving and performance evaluation, and model optimization. In this way, the improvements in the airfoil aerodynamic optimization area led by data-driven advanced models are introduced. These improvements involve more accurate global description of airfoil, faster prediction of aerodynamic performance, and more intelligent optimization modeling. Finally, the challenges and prospect of applying data-driven advanced models to aerodynamic optimization are discussed. Full article

This paper investigated the integration of LiDAR technology in cut-to-length (CTL) harvesting machines to enhance tree selection accuracy and efficiency. In the evolution of CTL forest machines towards improving operational efficiency and operator conditions, challenges persist in manual tree selection during thinning operations, especially under unmarked conditions and complex environments. These can be improved due to advances in technology. We studied the potential of LiDAR systems in assisting harvester operators, aiming to mitigate workload, reduce decision errors, and optimize the harvesting workflow. We used both synthetic and real-world 3D point cloud data sets for tree stem defect analysis. The former was crafted using a 3D modelling engine, while the latter originated from forest observations using 3D LiDAR on a CTL harvester. Both data sets contained instances of tree stem defects that should be detected. We demonstrated the potential of LiDAR technology: The analysis of synthetic data yielded a Root Mean Square Error (RMSE) of 0.00229 meters (m) and an RMSE percentage of 0.77%, demonstrating high detection accuracy. The real-world data also showed high accuracy, with an RMSE of 0.000767 m and an RMSE percentage of 1.39%. Given these results, we recommend using on-board LiDAR sensor technologies for collecting and analyzing data on tree/forest quality in real-time. This will help overcome existing barriers and drive forest operations toward enhanced efficiency and sustainability. Full article

The integration between the building information modeling (BIM) methodology and the building energy simulation (BES) can contribute to a thermo-energetic analysis since the model generated and fed into BIM is exported to simulation software. This integration, also called interoperability, is satisfactory when the information flow is carried out without the loss of essential information. Several studies point out interoperability flaws between the methodologies; however, most of them occur in low-geometry-complexity models during quantitative experiments. The purpose of this research was to analyze the BIM/BES integration based on a quantitative and interpretative interoperability analysis of two buildings with complex geometries located on the UFU Campus (library and Building 5T) in Uberlândia, Brazil. To accomplish this, two geometries of each building were modeled, detailed, and simplified to analyze the data import, workflow, and model correction in the BES software. In the case of the library, the integration of Revit with DesignBuilder and IES-VE was analyzed, and in Block 5T, Revit was used with DesignBuilder and eQUEST. The BES software that presented the best integration with Revit for complex geometries was DesignBuilder, with the best performance being in the interpretative criteria. It was concluded that the simplification of complex geometries is essential for better data transfers. To determine the BES software that has better integration with BIM, a comprehensive evaluation is necessary, considering not only data transfers but also ease of working within BES software, the possibility of corrections in these, as well as the availability of tutorials and developer support. Full article

Interior permanent magnet synchronous machines (IPMSMs) driven with a square-wave control (i.e., six-step, block, or 120${}^{\circ }$ control), known commonly as brushless direct current (BLDC) drives, are used widely due to their high power density and control simplicity. The advance firing (AF) angle is employed to achieve improved operation characteristics of the drive. The AF angle is, in general, applied to compensate for the commutation effects. In the case of an IPMSM, the AF angle can also be adjusted to exploit reluctance torque. In this paper, a detailed study was performed to understand its effect on the drive’s performance in regard to reluctance torque. Furthermore, a multi-objective optimization of the machine’s cross-section using neural network models was conducted to enhance performance at a constant AF angle. The reference and improved machine designs were evaluated in a system-level simulation, where the impact was considered of the commutation of currents. A significant improvement in the machine performance was achieved after optimizing the geometry and implementing a fixed AF angle of ${10}^{\circ }$. Full article

Industry 4.0 is an industrial paradigm that is causing changes in form and substance in factories, companies and businesses around the world and is impacting work and education in general. In fact, the disruptive technologies that frame the Fourth Industrial Revolution have the potential to improve and optimize manufacturing processes and the entire value chain, which could lead to an exponential evolution in the production and distribution of goods and services. All these changes imply that the fields of engineering knowledge must be oriented towards the concept of Industry 4.0, for example, Mechanical Engineering. The development of various physical assets that are used by cyber-physical systems and digital twins is based on mechanics. However, the specialized literature on Industry 4.0 says little about the importance of mechanics in the new industrial era, and more importance is placed on the evolution of Information and Communication Technologies and artificial intelligence. This article presents a frame of reference for the importance of Mechanical Engineering in Industry 4.0 and proposes an extension to the concept of Mechanics 4.0, recently defined as the relationship between mechanics and artificial intelligence. To analyze Mechanical Engineering in Industry 4.0, the criteria of the four driving forces that defined mechanics in the Third Industrial Revolution were used. An analysis of Mechanical Engineering Education in Industry 4.0 is presented, and the concept of Mechanical Engineering 4.0 Education is improved. Finally, the importance of making changes to the educational models of engineering education is described. Full article

Bone cancer and its related chronic pain are huge clinical problems since the available drugs are often ineffective or cannot be used long term due to a broad range of side effects. The mechanisms, mediators and targets need to be identified to determine potential novel therapies. Here, we characterize a mouse bone cancer model induced by intratibial injection of K7M2 osteosarcoma cells using an integrative approach and investigate the role of capsaicin-sensitive peptidergic sensory nerves. The mechanical pain threshold was assessed by dynamic plantar aesthesiometry, limb loading by dynamic weight bearing, spontaneous pain-related behaviors via observation, knee diameter with a digital caliper, and structural changes by micro-CT and glia cell activation by immunohistochemistry in BALB/c mice of both sexes. Capsaicin-sensitive peptidergic sensory neurons were defunctionalized by systemic pretreatment with a high dose of the transient receptor potential vanilloid 1 (TRPV1) agonist resiniferatoxin (RTX). During the 14- and 28-day experiments, weight bearing on the affected limb and the paw mechanonociceptive thresholds significantly decreased, demonstrating secondary mechanical hyperalgesia. Signs of spontaneous pain and osteoplastic bone remodeling were detected both in male and female mice without any sex differences. Microglia activation was shown by the increased ionized calcium-binding adapter molecule 1 (Iba1) immunopositivity on day 14 and astrocyte activation by the enhanced glial fibrillary acidic protein (GFAP)-positive cell density on day 28 in the ipsilateral spinal dorsal horn. Interestingly, defunctionalization of the capsaicin-sensitive afferents representing approximately 2/3 of the nociceptive fibers did not alter any functional parameters. Here, we provide the first complex functional and morphological characterization of the K7M2 mouse osteosarcoma model. Bone-cancer-related chronic pain and hyperalgesia are likely to be mediated by central sensitization involving neuroinflammation via glial cell activation in the spinal dorsal horn, but not the capsaicin-sensitive sensory neuronal system. Full article

In this study, a set of accurate dispersive nonlinear wave equations is established, using the wave velocity and free surface elevation as variables. These equations improve upon previous equations in which the velocity potential is used as a variable by considering the rotational wave motion and by adding a second-order bottom slope term that applies to general situations, allowing the equations to consider the influence of rapidly changing, horizontal, two-dimensional bottom topographies. The problem of the inaccuracy of the integral calculations used in previous equations in nearshore areas is solved by approximating the integral calculations into differential calculations, and a set of coupled wave equations is established by keeping the free surface elevation and the horizontal velocity constant, thus allowing the calculation of nearshore wave-generated currents. The benefits of the current model are confirmed through comparisons with corresponding laboratory experimental findings and are illustrated through a comparison with the numerical outcomes of other pertinent models. Full article

The finite element numerical simulation results of deep pit deformation are greatly influenced by soil layer parameters, which are crucial in determining the accuracy of deformation prediction results. This study employs the orthogonal experimental design to determine the combinations of various soil layer parameters in deep pits. Displacement values at specific measurement points were calculated using PLAXIS 3D under these varying parameter combinations to generate training samples. The nonlinear mapping ability of the Back Propagation (BP) neural network and Particle Swarm Optimization (PSO) were used for sample global optimization. Combining these with actual onsite measurements, we inversely calculate soil layer parameter values to update the input parameters for PLAXIS 3D. This allows us to conduct dynamic deformation prediction studies throughout the entire excavation process of deep pits. The results indicate that the use of the PSO-BP neural network for inverting soil layer parameters effectively enhances the convergence speed of the BP neural network model and avoids the issue of easily falling into local optimal solutions. The use of PLAXIS 3D to simulate the excavation process of the pit accurately reflects the dynamic changes in the displacement of the retaining structure, and the numerical simulation results show good agreement with the measured values. By updating the model parameters in real-time and calculating the pile displacement under different working conditions, the absolute errors between the measured and simulated values of pile top vertical displacement and pile body maximum horizontal displacement can be effectively reduced. This suggests that inverting soil layer parameters using measured values from working conditions is a feasible method for dynamically predicting the excavation process of the pit. The research results have some reference value for the selection of soil layer parameters in similar areas. Full article

Background: Human-Machine Interaction (HMI) has been an important field of research in recent years, since machines will continue to be embedded in many human actvities in several contexts, such as industry and healthcare. Monitoring in an ecological mannerthe cognitive workload (CW) of users, who interact with machines, is crucial to assess their level of engagement in activities and the required effort, with the goal of preventing stressful circumstances. This study provides a comprehensive analysis of the assessment of CW using wearable sensors in HMI. Methods: this narrative review explores several techniques and procedures for collecting physiological data through wearable sensors with the possibility to integrate these multiple physiological signals, providing a multimodal monitoring of the individuals’CW. Finally, it focuses on the impact of artificial intelligence methods in the physiological signals data analysis to provide models of the CW to be exploited in HMI. Results: the review provided a comprehensive evaluation of the wearables, physiological signals, and methods of data analysis for CW evaluation in HMI. Conclusion: the literature highlighted the feasibility of employing wearable sensors to collect physiological signals for an ecological CW monitoring in HMI scenarios. However, challenges remain in standardizing these measures across different populations and contexts. Full article

As a pivotal node in both urban and rural power grids, the box-type substation not only serves the functions of power conversion and distribution but also need to provide structural support and environmental adaptability. However, deficiencies in strength, stiffness, or vibration characteristics may lead to vibration and noise issues, and extreme environmental changes can pose risks of structural damage. This study aims to verify and optimize the seismic resistance and environmental adaptability of box-type substations through finite element simulation methods. Using SOLIDWORKS, a three-dimensional model of the box-type substation was constructed, and static and dynamic analyses were conducted using Ansys Workbench to comprehensively evaluate the dynamic response of the box-type substation under wind, snow loads, and seismic action. Through iterative simulations and a comparison of multiple design solutions, the structural optimization of the substation was achieved. The optimized structure balances strength and stiffness, significantly reducing the weight of the substation body, with the wall thickness reduced by 60%. Additionally, the phenomenon of stress concentration on the side walls was eliminated, ensuring that the equivalent stress is below the material yield strength. This research provides methods and empirical results for enhancing the performance and reliability of box-type substations under seismic conditions, confirming the feasibility of a lightweight design, while ensuring structural safety. Full article

Often in the forensic context, child victims and witnesses are interviewed several times, exposing them to suggestive questions and social pressures. The present study had the main purpose of verifying the effect of coping strategies on the levels of immediate suggestibility and on the Resistant Behavioral Responses (RBRs) of children subjected to repeated suggestive interviews. A sample of 90 children, aged between 11 and 14, were administered the two parallel Gudjonsson Suggestibility Scales (GSS2 and GSS1) a few months apart and the Coping Inventory for Stressful Situations (CISS) to detect their coping strategies. The results showed that the avoidance coping increased suggestive vulnerability and reduced resistant responses. Task-oriented coping favored responses with greater source monitoring, which allow for the rejection of misleading information. Coping strategies did not show direct effects on the management of the socioemotional aspects involved in the suggestive interaction. After the negative feedback that invites children to be more accurate, a smaller effect of the avoidance strategy was recorded, indicating how actively requesting greater source monitoring can lead children to better recognize misleading information. Full article

This article explores the use of olive pit powder (OPP) as a promising resource for enhancing the thermal insulation properties of epoxy mortars. A comprehensive analysis of the chemical and physical characteristics of OPP was conducted, employing analytical techniques including scanning electron microscopy (SEM), thermogravimetric analysis and emitted gas analysis (TG-MS-EGA), and proximal analysis. Experimental samples of epoxy grout were prepared by using different proportions of a conventional inorganic filler, quartz powder, and OPP within an epoxy mortar matrix. As the percentage of OPP in the formulation increased, the microstructure of the samples gradually became more porous and less compact. Consequently, there was a decrease in density with the increase in OPP content. The 28-day compressive strength decreased from 46 MPa to 12.8 MPa, respectively, in the samples containing only quartz (Sample E) and only OPP (Sample A) as a filler. Similarly, flexural strength decreased from 35.2 to 5.3 MPa. The thermal conductivity decreased from 0.3 W/mK in Sample E to 0.11 in Sample A. Therefore, increasing the %wt of OPP improved insulating properties while reducing the mechanical resistance values. This study highlights the potential of OPP as an environmentally friendly and thermally efficient filler for epoxy mortars, thereby promoting sustainable construction practices. Full article

In an attempt to reutilize marble waste, a new approach is presented in the current study to promote its use in the field of shielding against ionizing radiation. In this study, we aimed to develop a novel and sustainable/eco-friendly lead-free radiation shielding material by improving artificial marble (AM) produced from marble waste combined with polyester by reinforcing it with bismuth oxide (Bi₂O₃) nanoparticles. Six samples of AM samples doped with different concentrations ($0\%$,$5\%$,$10\%$,$15\%$, $20\%$, and $25\%$) of Bi₂O₃ nanoparticles were prepared. The linear attenuation coefficient ($LAC$) values were measured experimentally through the narrow beam method at different energies $(0.0595 \mathrm{M}\mathrm{e}\mathrm{V}$, $0.6617 \mathrm{M}\mathrm{e}\mathrm{V}$, $1.1730 \mathrm{M}\mathrm{e}\mathrm{V}$, and $1.330 \mathrm{M}\mathrm{e}\mathrm{V}$) for all samples with various concentrations of Bi₂O₃. Radiological shielding parameters such as half value layer ($HVL$), tenth-value layer ($TVL$), and radiation shielding efficiency ($RSE$) were estimated and compared for all the different samples. The results prove that increasing the concentration of Bi₂O₃ leads to the enhancement of the radiation shielding properties of the AM as a shielding material. It was observed that as the energy increases, the efficiency of the samples falls. High energy dependence was found when calculating the $HVL$ and $TVL$ values of the samples, which increased with increases in the energy of the incident photons. A comparison between the sample with the most efficient gamma radiation attenuation capability (AM-$25\%$), concrete, and lead was conducted, and a discussion regarding their radiation shielding properties is presented herein. The results show that the AM-$25\%$ sample is superior to the ordinary concrete over all the studied energy ranges, as evidenced by its significantly lower $HVLs$. On the contrary, lead is superior to the AM-$25\%$ sample over all the studied energy ranges owing to its unbeatable density as a shielding material. Overall, this new type of artificial marble has the potential to be used as a radiation shielding material at low- to medium-gamma energy regions, specifically in medical imaging and radiation therapy. Full article

Human Immunodeficiency Virus (HIV) is a stigmatizing disease that disproportionately affects African Americans and Latinos among people living with HIV (PLWH). Researchers are increasingly utilizing artificial intelligence (AI) to analyze large amounts of data such as social media data and electronic health records (EHR) for various HIV-related tasks, from prevention and surveillance to treatment and counseling. This paper explores the ethical considerations surrounding the use of AI for HIV with a focus on acceptability, trust, fairness, and transparency. To improve acceptability and trust towards AI systems for HIV, informed consent and a Federated Learning (FL) approach are suggested. In regard to unfairness, stakeholders should be wary of AI systems for HIV further stigmatizing or even being used as grounds to criminalize PLWH. To prevent criminalization, in particular, the application of differential privacy on HIV data generated by data linkage should be studied. Participatory design is crucial in designing the AI systems for HIV to be more transparent and inclusive. To this end, the formation of a data ethics committee and the construction of relevant frameworks and principles may need to be concurrently implemented. Lastly, the question of whether the amount of transparency beyond a certain threshold may overwhelm patients, thereby unexpectedly triggering negative consequences, is posed. Full article

Clinicians often use endoscopic ultrasonography to survey pancreatic tumors. When endoscopists conduct this examination and find the tumor to be unresectable, a fine-needle biopsy is subsequently performed for tissue confirmation. However, if the tumor is deemed resectable, the necessity of a pre-operative fine-needle biopsy remains debatable. Therefore, we performed a retrospective analysis of a single-center cohort of patients with pancreatic tumors who underwent an endoscopic ultrasound-guided fine-needle biopsy or aspiration (EUS-FNB or FNA) between 2020 and 2022. This study focused on patients diagnosed with resectable malignant pancreatic tumors. The exclusion criteria included individuals diagnosed with benign pancreatic lesions and those with unresectable tumors. A total of 68 patients were enrolled in this study. Histological examination revealed that pancreatic adenocarcinoma was the predominant type of tumor (n = 42, 61.8%), followed by neuroendocrine tumors (n = 22, 32.3%), and metastasis (n = 4, 5.9%). Notably, 17 patients had a history of other cancers, with 23.5% being diagnosed with a metastatic tumor rather than primary pancreatic cancer. Therefore, EUS-FNA/FNB is crucial in patients with a resectable pancreatic tumor and a history of cancer to differentiate between a primary and a metastatic tumor. Full article

Background and Objectives: The ki67 nuclear protein is a tool for diagnosis and prognosis in oncology that is used to evaluate cell proliferation. Differentiated thyroid carcinoma is usually a slow-growing neoplasm, the most common type being the papillary form. Some clinical and pathological aspects may predict aggressive behaviour. There are reported cases of recurrence without clinico-pathological findings of aggressiveness. To obtain better predictions of the disease outcome in thyroid carcinoma, many immunohistochemical markers have been studied. The aim of this narrative literature review is to identify the benefits that ki67 may add to the management of patients with differentiated thyroid carcinoma, according to the latest evidence. Materials and Methods: We performed a search on the PubMed and Google Scholar databases using controlled vocabulary and keywords to find the most suitable published articles. A total number of sixty-eight items were identified, and five other articles were selected from other sources. After refining the selection, the inclusion criteria and exclusion criteria were applied, and a total number of twenty-nine articles were included in this literature review. Results and Discussion: The studies consist of retrospective studies (89.66%), case reports (6.9%) and literature reviews (3.45%), evaluating the role, implications and other parameters of ki67 as a diagnostic and/or prognostic tool. The statistical correlations between ki67 and other features were systematized as qualitative results of this review in order to improve the treatment strategies presented in the included articles. Conclusions: The included studies present converging data regarding most of the aspects concerning ki67. The ki67 proliferation index is a diagnostic/prognostic tool of interest in differentiated thyroid carcinoma and a good predictor of disease-free survival, disease recurrence and metastatic development. Prospective studies on large cohorts may add value for ki67 as a specific tool in the management strategy of differentiated thyroid carcinoma. Full article

Hemodialysis (HD) is a life-sustaining membrane-based therapy that is essential for managing kidney failure. However, it can have significant physical and psychological effects on patients due to chronic or acute consequences related to membrane bioincompatibility. End-stage renal disease (ESRD) patients on hemodialysis have a high incidence of psychiatric illness, particularly depression and anxiety disorders, and poor quality of life has been observed. Dialysis can also lead to physical symptoms of its own, such as fatigue, loss of appetite, anemia, low blood pressure, and fluid overload, in addition to the symptoms associated with kidney failure. Therefore, this critical review aims to comprehensively understand the impact of dialysis membrane bioincompatibility and the use of varying molecular weight cut-off membranes on the physical and psychological symptoms experienced by dialysis patients. We analyzed the latest research on the correlation between major inflammatory biomarkers released in patients’ blood due to membrane incompatibility, as well as the critical influence of low levels of hemoglobin and vital proteins such as human serum albumin due to the use of high-cut-off membranes and correlated these factors with the physical and psychological symptoms experienced by dialysis patients. Furthermore, our study aims to provide valuable insights into the impact of dialysis on critical symptoms, higher hospitalization rates, and the quality of life of First Nations, as well as child and youth dialysis patients, in addition to diabetic dialysis patients. Our goal is to identify potential interventions aiming to optimize the dialysis membrane and minimize its negative effects on patients, ultimately improving their well-being and long-term outcomes. Full article

The lateral stability control of vehicles is one of the most crucial aspects of vehicle safety. This article introduces a coordinated-control strategy designed to enhance the handling stability of distributed-drive electric vehicles. The upper controller uses active front steering and direct yaw moment-control controllers designed based on sliding-mode control theory. The lower controller optimally allocates control inputs to the upper controller, considering factors such as load transfer and tire load rate. It divides the stability region by relying on the phase plane and develops a coordinated-control strategy based on the degree of deviation of the vehicle state from the stability region. The results of the simulation experiments demonstrate that the proposed control strategy effectively improves handling stability under extreme working conditions. Full article