Simple Parameters Research Articles

Uncertain least square support vector regression with imprecise observations

In this study, an innovative approach that combines least square support vector regression (LSSVR) with uncertainty theory to enhance its performance in dealing with low-quality or imprecise data from real-world be proposed. The resulting model, called uncertain least square support vector regression (ULSSVR), incorporates chance constraints and simplified parameter selection, which are critical to handle imprecise observations. A numerical algorithm called the conjugate residual method (CR) is introduced to reduce the computational complexity of the model solution. The experimental results using both small and medium-sized datasets demonstrate the superior performance of ULSSVR in terms of prediction accuracy and generalization ability compared to other models such as uncertain support vector regression (USVR), uncertain linear lodel, uncertain polynomial model, and uncertain growth models. ULSSVR not only improves prediction accuracy by at least 28.49% but also demonstrates faster computational speed. Overall, ULSSVR presents a promising solution for data science and internet applications where dealing with imprecise and low-quality data is a common challenge.

The impact of gestational weeks of Coronavirus disease 2019 (COVID-19) infection on perinatal outcomes

BackgroundTo evaluate the relationship between coronavirus disease 2019 (COVID-19) infection at different time points during pregnancy and perinatal outcomes.MethodsThis retrospective study included 611 women who hospitalized for delivery between December 7 and April 30, 2023. Based on the different pregnancy weeks infected with COVID-19, the participants were divided into four groups: Group 1 (14–27+6 weeks gestation), Group 2 (28–36+6 weeks gestation), Group 3 (37–39+6 weeks gestation), and Group 4 (≥ 40 weeks gestation). Data including maternal demographic characteristics, clinical profiles, and perinatal outcomes were analyzed.ResultsThere were no significant differences in maternal demographic characteristics among the four groups (P > 0.05). Compared to Groups 3 and 4, a higher rate of fever was noted in Groups 1 and 2 (P < 0.05). The frequency of preeclampsia and gestational diabetes mellitus showed a decreasing trend as pregnancy progressing (P < 0.05). Preterm delivery and neonatal intensive care unit admission were more frequently observed in Groups 1 and 2 than in Groups 3 and 4 (P < 0.05). Multivariate logistic regression analysis demonstrated that the timing of gestation in which COVID-19 was infected was not associated with preterm delivery and neonatal intensive care unit admission (P > 0.05), whereas gestational age at COVID-19 infection was negatively associated with the occurrence of preeclampsia and gestational diabetes mellitus (P < 0.05).ConclusionsGestational age at COVID-19 infection is a simple parameter that predicts adverse perinatal outcomes to aid clinicians in determining to provide early enhanced prenatal care and increased monitoring to reduce maternal complications.

Analysis of Cesarean Section Causes Using Robson’s Ten Group Classification System in Selected Hospitals Affiliated to Shiraz University of Medical Sciences: A Cross-sectional Study

Background: Robson’s Ten Group Classification System (RTGCS) is widely used to evaluate, monitor, and compare cesarean delivery (CD) rates within and between delivery service centers. This study aimed to investigate the causes of CD in Shiraz teaching hospitals using RTGCS. Materials and Methods: A cross-sectional study on 1787 pregnant women who underwent CD in selected teaching hospitals in Shiraz, Iran, was selected via convenience sampling within 3 months. The data collection tool was a demographic, midwifery, and fertility information questionnaire completed through interviews and medical records. Subjects’ classification was performed based on midwifery concepts and parameters described in RTGCS. The Robson's 10-group classification is based on simple obstetrical parameters (parity, previous CS, gestational age, onset of labour, fetal presentation, and number of fetuses). Data were analyzed using SPSS software and descriptive tests were used to describe the data. Results: Of the 1787 subjects, 455 (25.5%) had planned CS and 1332 (74.5%) had emergency CS. The most common causes of CD were previous CD (58.6%) and fetal distress (27.6%). Overall, 823 (46.1%) had fetal and placental causes, 1268 (71%) had uterine causes, and 78 (4.4%) had maternal causes. Conclusion: The biggest factors that played a role in the CD rate in the present study were termed multipara women with a history of previous CD. The CD rate and the overall size of this group are still increasing, and as a result, women with a history of a previous CD must be motivated more effectively to have a vaginal birth after cesarean delivery (VBAC).

Correlation of simple hematological parameters with disease activity and damage indices among Egyptian patients with systemic lupus erythematosus

ObjectiveTo evaluate the correlation of different hematological parameters in lupus patients with SLE disease activity index (SLEDAI), the Systemic Lupus International Collaboration Clinics/American College of Rheumatology Damage Index (SLICC/ACR DI), and some laboratory data related to kidney functions in active patients with nephritis. Material and methods80 inactive SLE patients (SLEDAI score<10 points), and 80 active patients (SLEDAI≥10 points) were enrolled in this study. All patients underwent full medical history taking, clinical evaluation including calculation of SLEDAI and SLICC/ACR DI scores, and laboratory investigations including complete blood count. The two groups were compared regarding different disease parameters. Correlations of some hematological parameters with SLEDAI, SLICC/ACR DI scores and some laboratory data related to kidney function in patients with nephritis were made. ResultsThe active group showed statistically significantly higher mean NLR (P=0.000), NC3R (P=0.000), MLR (P=0.000), PLR (P=0.000), and RDW (P=0.001), and statistically significantly lower mean MPV (P=0.002). The mean MLR (P=0.018) and PLR (P=0.005) were statistically significantly higher in the active patients with nephritis. For both groups, there were no significant correlations between studied parameters and SLEDAI or SLICC/ACR DI, except with NC3R values in the active group which were associated with SLEDAI (r=.221, P=0.049). ConclusionThe hematological parameters in SLE have promising potential clinical application as a novel activity marker, especially in patients with nephritis.

Changing the first screening parameters for patients and their derivatives in Phase II–III clinical studies

Actuality. The search for parameters of clinical trials (CT) associated with the recruitment of patients is primarily associated with the search for parameters that can predict the recruitment — predictors of patient recruitment, since patient recruitment is an important and one of the most complex processes in clinical trials, the success of which depends on the entire study. The authors propose to use the parameters of the recruitment of patients assumed by the center, the number of exclusion criteria according to the protocol, and other simple methods that allow predicting the upcoming recruitment; however, the proposed approaches are unclaimed. The parameter of success in enrolling patients in the previous 10 or more studies proposed by the authors obviously has its drawbacks because clinical centers that did not participate in 10 successful studies are automatically excluded. However, the search for a simple parameter to predict upcoming recruitment continues; for example, the time of the first screening has its own predictor potential. We investigated changes in this parameter and its derivatives during the recruitment of patients to selected international multicenter clinical trials (IMCTs). Materials and methods. A retrospective analysis of 4 IMCTs of II–III phases was performed on the recruitment of patients and changes in the time parameters of the first screening and its derivatives. Aim. Consider changes in the time parameter of the first screening and its derivatives during patient recruitment. Statistical analysis. Descriptive statistics with typing. Results. The change in the time parameter of the first screening during the recruitment of patients for CT was considered. The time of the first screening varies depending on the type of clinical center and the experience of the principal investigator. Discussion. According to the literature, a change in the time parameter of the first screening may indicate the success of the recruitment of patients in the center. Conclusion. The changes in the time of the screening set studied by us will allow us to apply the obtained values in clinical trials.

Relation of Serum Bilirubin in Physiological Range with Spot Urine Albumin to Creatinine Ratio and eGFR Among Diabetic Patients with or without Nephropathy

Recent studies have suggested a potential role of bilirubin as an antioxidant to protect diabetic patients from hyperglycemia-induced oxidative stress thereby preventing diabetic complications. Diabetic nephropathy is a serious microvascular complication which is determined by increased urinary albumin to creatinine ratio and reduced eGFR. The present work aimed to study the relation of the simple biochemical parameter of serum bilirubin level with the estimated glomerular filtration rate (eGFR) and spot urine albumin to creatinine ratio in diabetic patients with or without nephropathy. This cross sectional study was done in the department of Biochemistry and Molecular Biology, Bangladesh Institute of Research and Rehabilitation in Diabetes, Endocrine and Metabolic Disorders (BIRDEM) Academy from July 2017 to June 2018. We have taken 63 diabetic patients without nephropathy and 63 diabetic patients with nephropathy.Data about clinical and biochemical parameters (blood pressure, BMI, fasting serum glucose, estimated GFR, serum bilirubin and spot urine ACR etc.) were measured by appropriate methods. We used student’s t test and Pearson’s correlation coefficient to detect the relationship of serum bilirubin with other variables All statistical tests were considered at 5% level of significance. We found diabetic patients with nephropathy have significantly lower serum bilirubin (p&lt;0.001) than diabetic patients without nephropathy (0.46±0.18 and 0.64± 0.21 mg/d respectively). Pearson’s correlation test showed that serum bilirubin positively correlated with eGFR (r=0.312, p=0.013) in diabetic patients with nephropathy. This study concluded that low serum bilirubin level is associated with eGFR in diabetic patients with nephropathy.&#x0D; Bangladesh J Med Biochem 2019; 12(2): 16-22

The use of simple structural parameters of energetic metal-organic frameworks to assess their density

A new method is presented for accurately estimating the density (D) of energetic material-organic frameworks (EMOFs), which has vital role in determining their performance. The experimental density data for 124 EMOFs, which are composed of five or six-membered heterocyclic rings, has been used to develop and analyze the model. The model is constructed based on simple structural parameters and can be easily applied to EMOFs with complex compositions and structures. The performance of the new model in estimating density has been compared to the Dalirandeh et al. model. The values of statistical factors comprising mean absolute error (MAE), maximum absolute error (AEmax), root mean square error (RMSE), mean absolute percent error (MAPE), and coefficient of determination (R2) for Dalirandeh et al./new model are 0.09/0.07, 0.33/0.23, 0.12/0.10, 4.21/3.50, and 0.94/0.96, respectively. Statistical validations and applicability domain (AD) assessments have confirmed that the new model provides high accuracy, precision, reliability, and goodness-of-fit.

Septic cardiomyopathy-diagnosis and estimation of disease severity

The relevance of septic cardiomyopathy is frequently underestimated due to the complexity of the pattern of cardiac injury and the corresponding difficulties in quantifying the degree of functional impairment. Account of the methods for diagnosis and severity classification of septic cardiomyopathy. Literature review and analysis of the main findings. Septic cardiomyopathy is characterized by both systolic and diastolic impairment of not only the left, but also the right ventricle, as well as by sinus-tachycardiomyopathy (≥ 90-95beats/min) of variable degree. Sepsis-related organ failure assessment (SOFA) score, left ventricular ejection fraction (LVEF), ECG and cardiac biomarkers do not help in grading severity of septic cardiomyopathy. For that purpose either asophisticated echocardiography diagnosis is mandatory, or the measurement of those global heart function parameters which take into account the dependency of cardiac output on afterload, in view of the pronounced vasodilatation in sepsis and septic shock, is needed. Asuitable parameter on the basis of cardiac output measurement is afterload-related cardiac performance (ACP), which gives the percentage of cardiac output in aseptic patient related to the cardiac output ahealthy heart pumps when challenged by afall in systemic vascular resistance to the same extent. The calculation of ACP shows that at least one in two septic patients suffers from impaired heart function and that mortality increases as severity increases. Simple parameters like LVEF are not apt for diagnosis nor for disease severity classification of septic cardiomyopathy. For that purpose either sophisticated echocardiography techniques or load-independent parameters-best validated-ACP measurements are appropriate.

Emergent competition shapes top-down versus bottom-up control in multi-trophic ecosystems.

Ecosystems are commonly organized into trophic levels-organisms that occupy the same level in a food chain (e.g., plants, herbivores, carnivores). A fundamental question in theoretical ecology is how the interplay between trophic structure, diversity, and competition shapes the properties of ecosystems. To address this problem, we analyze a generalized Consumer Resource Model with three trophic levels using the zero-temperature cavity method and numerical simulations. We derive the corresponding mean-field cavity equations and show that intra-trophic diversity gives rise to an effective "emergent competition" term between species within a trophic level due to feedbacks mediated by other trophic levels. This emergent competition gives rise to a crossover from a regime of top-down control (populations are limited by predators) to a regime of bottom-up control (populations are limited by primary producers) and is captured by a simple order parameter related to the ratio of surviving species in different trophic levels. We show that our theoretical results agree with empirical observations, suggesting that the theoretical approach outlined here can be used to understand complex ecosystems with multiple trophic levels.

Association of cardiometabolic and triglyceride-glucose index with left ventricular diastolic function in asymptomatic individuals

Background and aimsObesity and insulin resistance are associated with left ventricular diastolic dysfunction (LVDD) and increased risk of heart failure. Cardiometabolic index (CMI) and triglyceride glucose (TyG) are new indexes to assess visceral obesity and insulin resistance, respectively. The study aimed to investigate the clinical usefulness of these indexes for identifying LVDD individuals. Methods and resultsOverall, 1898 asymptomatic individuals were included in this cross-sectional study. Participants underwent anthropometrics, serum biochemical evaluation, and echocardiography. Multiple linear regression analysis revealed that both indexes were independent determinants of diastolic parameters among females; while for males, CMI and TyG were not associated with A velocity. In the multivariate logistic analysis, the proportion of LVDD in the third and fourth quartiles of CMI remained significantly greater than that in the lowest quartile in females (Q3 vs. Q1: odds ratio (OR) = 2.032, 95% confidence interval (CI): 1.181–3.496; Q4 vs. Q1: OR = 2.393, 95% CI: 1.347–4.249); while in males, the incidence of LVDD was significantly greater only in the fourth quartile. For TyG, the presence of LVDD in the fourth quartile was significantly greater in both genders. The discriminant values between the CMI (AUC: 0.704, 95% CI: 0.668–0.739) and TyG (AUC: 0.717, 95% CI: 0.682–0.752) were similar in females. Both indexes performed better in females than in males to identify LVDD. ConclusionThe CMI and TyG might both serve as effective tools to identify LVDD in routine health check-ups in primary care, mainly in females. With simpler parameters, the CMI could be utilized in medically resource-limited areas.

Geometric parameters that affect the behavior of logic-gated CAR T cells.

Clinical applications of CAR-T cells are limited by the scarcity of tumor-specific targets and are often afflicted with the same on-target/off-tumor toxicities that plague other cancer treatments. A new promising strategy to enforce tumor selectivity is the use of logic-gated, two-receptor systems. One well-described application is termed Tmod™, which originally utilized a blocking inhibitory receptor directed towards HLA-I target antigens to create a protective NOT gate. Here we show that the function of Tmod blockers targeting non-HLA-I antigens is dependent on the height of the blocker antigen and is generally compatible with small, membrane-proximal targets. We compensate for this apparent limitation by incorporating modular hinge units to artificially extend or retract the ligand-binding domains relative to the effector cell surface, thereby modulating Tmod activator and blocker function. By accounting for structural differences between activator and blocker targets, we developed a set of simple geometric parameters for Tmod receptor design that enables targeting of blocker antigens beyond HLA-I, thereby broadening the applications of logic-gated cell therapies.

A novel unmanned aerial vehicle path planning approach: sand cat optimization algorithm incorporating learned behaviour

Unmanned aerial vehicle (UAV) path planning plays an important role in UAV flight, and an effective algorithm is needed to realize UAV path planning. The sand cat algorithm is characterized by simple parameter setting and easy implementation. However, the convergence speed is slow, easy to fall into the local optimum. In order to solve these problems, a novel sand cat algorithm incorporating learning behaviors (LSCSO) is proposed. LSCSO is inspired by the life habits and learning ability of sand cats and incorporates a new position update strategy into the basic Sand Cat Optimization Algorithm, which maintains the diversity of the population and improves the convergence ability during the optimization process. Finally, LSCSO is applied to the challenging UAV 3D path planning with cubic B-spline interpolation to generate a smooth path, and the proposed algorithm is compared with a variety of other competing algorithms. The experimental results show that LSCSO has excellent optimization-seeking ability and plans a safe and feasible path with minimal cost consideration among all the compared algorithms.

The relationship between mid-upper arm circumference and blood pressure in Walter Sisulu University community.

Prevalence of hypertension is increasing to higher levels in South Africa. Anthropometric measures for obesity are well known to predict the development of hypertension. However, the relationship between mid-upper arm circumference (MUAC) and blood pressure (BP) is scant in South African communities such as universities. Therefore, this study was aimed at investigating the correlation between MUAC and BP among the community of Walter Sisulu University (WSU). A total of 230 participants from WSU (students and staff members), 113 females and 117 males aged ≥ 18 years participated in this cross-sectional study. MUAC, systolic BP (SBP) and diastolic BP (DBP) were measured using standard procedures. In a Pearson's correlation analysis, MUAC was positively correlated with SBP and DBP in both women (SBP; r = 0.53, P< 0.001; DBP; r = 0.45 P < 0.001) and men (SBP; r = 0.29 P = 0.001; DBP; r = 0.25 P = 0.007). Furthermore, in the multivariable-adjusted regression analysis, MUAC was positively associated with SBP in women only (adjusted R2 = 0.489, β = 0.29 (95% CI = 0.16; 2.08)), P =0.023) after adjusted for age, body fat percentage, waist-to-height ratio, smoking and alcohol. MUAC is positively correlated with BP in women, not in men of WSU community. MUAC, as a simple and low-cost quantifiable parameter, could be employed as a risk indicator in the early detection and prevention of cardiovascular diseases (CVDs) in women.

Free Energy Barriers for Passive Drug Transport through the Mycobacterium tuberculosis Outer Membrane: A Molecular Dynamics Study.

The emergence of multi-drug-resistant tuberculosis strains poses a significant challenge to modern medicine. The development of new antituberculosis drugs is hindered by the low permeability of many active compounds through the extremely strong bacterial cell wall of mycobacteria. In order to estimate the ability of potential antimycobacterial agents to diffuse through the outer mycolate membrane, the free energy profiles, the corresponding activation barriers, and possible permeability modes of passive transport for a series of known antibiotics, modern antituberculosis drugs, and prospective active drug-like molecules were determined using molecular dynamics simulations with the all-atom force field and potential of mean-force calculations. The membranes of different chemical and conformational compositions, density, thickness, and ionization states were examined. The typical activation barriers for the low-mass molecules penetrating through the most realistic membrane model were 6-13 kcal/mol for isoniazid, pyrazinamide, and etambutol, and 19 and 25 kcal/mol for bedaquilin and rifampicin. The barriers for the ionized molecules are usually in the range of 37-63 kcal/mol. The linear regression models were derived from the obtained data, allowing one to estimate the permeability barriers from simple physicochemical parameters of the diffusing molecules, notably lipophilicity and molecular polarizability.

Application of shock index-based classification in hypovolemic shock due to obstetric hemorrhage and its comparison with conventional vital sign for prediction of adverse maternal outcome

Background: At least, 358,000 women worldwide die annually from pregnancy and childbirth-related problems. Obstetric hemorrhage is the single most significant cause of maternal mortality worldwide accounting for 25–30% of all maternal deaths. Aims and Objectives: The objective of the study is to see the usefulness/importance of shock index (SI) in obstetric hemorrhage (antepartum and post-partum hemorrhage) and to compare the performance of SI with conventional vital signs for prediction of maternal outcome. Materials and Methods: The descriptive study was conducted in 100 cases of hemorrhagic shock patients admitted in obstetrics and gynecology at Baba Raghav Das Medical College, Gorakhpur, between June 2020 and May 2021, on 100 subjects. Results: In our study, there were 100 patients. Patients with SI 0.6 to &lt;1 were included in Group I which comprises 26% patients in which 57.69% patients required only intravenous (IV) fluid, while 30.77% patients needed blood transfusion. Patients with SI&gt;1 were included in Group II which comprises 74% patients in which all patients required initial resuscitation with IV fluid and then blood transfusion, 21.62% patients require inotropic support, and 9.46% patients needed fresh frozen plasma transfusion. Maternal outcome in Group I patients is that only 15.38% patients required emergency lower segment cesarean section (LSCS). While in Group II, 28.95% patients required emergency LSCS, 5.26% patients required intensive care unit (ICU) admission for ventilator support, 3.95% went for cesarean hysterectomy, while 2.63% patients landed in end organ failure and expired. Conclusion: All patients with obstetric hemorrhage with SI&gt;1 should receive immediate intervention such as blood transfusion need of ICU or surgical intervention. This is higher than the upper limit of normality in non-pregnant population. In low-resource settings, this simple parameter could improve outcomes because it has a significant ability to predict adverse maternal outcomes of hemorrhage.

Machine learning prediction of in-hospital recurrent infarction and cardiac death in patients with myocardial infarction

Background and aimThe aim of the study is to identify statistical patterns in patients with myocardial infarction (MI) during hospitalization that allow predicting the development of acute conditions (recurrent myocardial infarction, cardiac death). MethodsWe identified 3471 episodes of patients treated with a diagnosis acute MI in Almazov National Medical Research Centre. For modelling we selected episodes with acute MI with cardiac surgery operations. Classical machine learning models were chosen as forecasting models: decision trees and ensembles based on them, logistic regression and support vector machine. ResultsThe important signs for predicting recurrent MI were the minimum values of hemoglobin, the echocardiography parameters end systolic volume and pulmonary regurgitation, and the minimum value of leukocyte level. Predictors of lethal outcome during hospitalization were advanced age, high values of leukocytes, low values of hemoglobin, high values of alanine aminotransferase. ConclusionThe obtained results make it possible to predict the development of a lethal outcome and re-infarction based on simple parameters that are easily available in clinical practice.

Efeitos globais de segunda ordem em estruturas de concreto armado: critério simplificado com base no método de Galerkin

Abstract Global second order effects in reinforced concrete buildings can be estimated using numerical or simplified methods, such as the γz coefficient, presented in the Brazilian standard. This paper proposes a new simplified parameter, which is deduced by the Galerkin’s Method by Weighted Residuals. In order to evaluate the accuracy of the proposed methodology, 42 planar frames (21 framed system structures and 21 dual system structures) were analysed in terms of internal forces and displacements. Such results were compared to those obtained by the γz coefficient and to the reference results obtained throughout a geometric nonlinear elastic finite element program. The precision of the results was defined by statistical analyses, which showed that the results using the proposed parameter were closer to the reference ones, even in the recommended range for using the γz coefficient.

Mechanism analysis and optimal design of sound-absorbing metastructure constructed by slit-embedded Helmholtz resonators

&lt;sec&gt;Low-frequency noise has always been a thorny problem in the field of noise control. In recent years, the development of sound-absorbing metastructures has provided new ideas for controlling low-frequency noise. In this work, we propose a low-frequency sound-absorbing metastructure constructed by Helmholtz resonators with embedded slit. Analytical and numerical models are established to analyze the sound absorption performance and mechanism of the proposed sound-absorbing metastructure, and optimization design is conducted to achieve low-frequency wideband absorption performance. The analytical modeling method and the performance of the proposed sound-absorbing metastructure are also experimentally verified. The main conclusions are summarized as follows.&lt;/sec&gt;&lt;sec&gt;1) By using transfer matrix method and finite element method, analytical and numerical models for calculating sound absorption coefficient are established. It is shown that analytical predictions are in good agreement with numerical calculations. It is demonstrated that a typical design of a 30-mm-thick single-cell metastructure can achieve a sound absorption coefficient of 0.88 at 404 Hz. Typical designs of two-cell parallel structure and the four-cell parallel structure (both with a thickness of 50 mm) can achieve two and four nearly perfect low-frequency sound absorption peaks in a frequency band of 200–400 Hz, respectively.&lt;/sec&gt;&lt;sec&gt;2) The low-frequency sound absorption mechanisms of the proposed metastructures are explained from four aspects: simplified equivalent model parameters, normalized acoustic impedance, complex-plane zero/pole distribution, and sound pressure cloud image and particle velocity field distribution. It is demonstrated that the main sound absorption mechanism is related to the thermal viscous loss of sound waves, caused by the inner wall of embedded slit.&lt;/sec&gt;&lt;sec&gt;3) The design for broadband low-frequency absorption performance is optimized by using differential evolution optimization algorithm. An optimized parallel-multi-cell coupled metastructure with multiple perfect sound absorption peaks below 500 Hz is realized. For a thickness of 90 mm, the sound absorption coefficient curve of an optimized metastructure exhibits 8 almost perfect sound absorption peaks and an average sound absorption coefficient of 0.86 in a frequency range of 170－380 Hz.&lt;/sec&gt;&lt;sec&gt;4) Experimental samples are fabricated to test sound absorption. Experimental results are basically consistent with the analytical predictions. The results from analytical model, numerical calculations and experimental measurements are mutually verified.&lt;/sec&gt;&lt;sec&gt;In summary, the sound-absorbing metastructures with a thickness of sub-wavelength, proposed in this work, exhibit outstanding sound absorption performance at low frequencies. We demonstrate that they are suitable for low frequency broadband sound absorption below 500 Hz. Owing to their thin thickness and relatively simple construction, they have broad application prospects in practical noise control engineering.&lt;/sec&gt;

Review on li-ion battery model used in electrical vehicle

In recent years, battery models have become increasingly crucial, particularly with the surge in electric vehicle usage within the transportation sector. Accurate models are essential for assessing battery performance and devising effective battery management systems. Various modeling approaches exist in literature, each carrying its own set of advantages and drawbacks. Typically, more intricate models offer precise results but demand greater computational resources and entail time-consuming, costly laboratory tests for parameter determination. Hence, for first stage assessments and battery managing system designs, models employing simpler parameter documentation procedures are the most viable and suitable options. The presence of a precise battery model within a simulation platform holds immense significance in crafting efficient battery-powered systems. Absolutely! The lithium-ion battery model is a standout option owing to its potential as an energy storage system, particularly for renewable technology applications. This is largely due to its remarkable power compactness and energy storage capabilities.

Designing size-controlled air cavities to reduce iron losses of 3D printed ferromagnetic parts: Modelling and experimental results

We studied the effect of cavity insertion to reduce iron losses into Fe-2.6wt.%Si ferromagnetic components fabricated by Laser Powder Bed Fusion (L-PBF) 3D printing process. Finite Element Method (FEM) simulation was used to understand the impact of various cavity configurations on eddy current losses and to identify design guidelines. Results highlight the dependence of losses on eddy current path length, which can be expressed by simple geometrical design parameters. Finally, L-PBF samples were magnetically characterized up to 500 Hz. A good correspondence between experimental data and modelling results is observed. A torus designed with six external cavities allowed the reduction of the losses by 60 % compared to a bulk specimen (0.5 T; 500 Hz).