Triglyceride-glucose index is associated with myocardial ischemia and poor prognosis in patients with ischemia and no obstructive coronary artery disease.

BACKGROUND: Ischemia and no obstructive coronary artery disease (INOCA) is increasingly recognized and associated with poor outcomes. The triglyceride-glucose (TyG) index is a reliable alternative measure of insulin resistance significantly linked to cardiovascular disease and adverse prognosis. We investigated the association between the TyG index and myocardial ischemia and the prognosis in INOCA patients. METHODS: INOCA patients who underwent both coronary angiography and myocardial perfusion imaging (MPI) were included consecutively. All participants were divided into three groups according to TyG tertiles (T1, T2, and T3). Abnormal MPI for myocardial ischemia in individual coronary territories was defined as summed stress score (SSS) ≥ 4 and summed difference score (SDS) ≥ 2. SSS refers to the sum of all defects in the stress images, and SDS is the difference of the sum of all defects between the rest images and stress images. All patients were followed up for major adverse cardiac events (MACE). RESULTS: Among 332 INOCA patients, 113 (34.0%) had abnormal MPI. Patients with higher TyG index had a higher rate of abnormal MPI (25.5% vs. 32.4% vs. 44.1%; p = 0.012). Multivariate logistic analysis showed that a high TyG index was significantly correlated with abnormal MPI in INOCA patients (OR, 1.901; 95% CI, 1.045-3.458; P = 0.035). During the median 35 months of follow-up, 83 (25%) MACE were recorded, and a higher incidence of MACE was observed in the T3 group (T3 vs. T2 vs. T1: 36.9% vs. 21.6% vs. 16.4%, respectively; p = 0.001). In multivariate Cox regression analysis, the T3 group was significantly associated with the risk of MACE compared to the T1 group (HR, 2.338; 95% CI 1.253-4.364, P = 0.008). CONCLUSION: This study indicates for the first time that the TyG index is significantly associated with myocardial ischemia and poor prognosis among INOCA patients.

Is systemic inflammation a missing link between cardiometabolic index with mortality? Evidence from a large population-based study.

BACKGROUND: This study sought to elucidate the associations of cardiometabolic index (CMI), as a metabolism-related index, with all-cause and cardiovascular mortality among the older population. Utilizing data from the National Health and Nutrition Examination Survey (NHANES), we further explored the potential mediating effect of inflammation within these associations. METHODS: A cohort of 3029 participants aged over 65 years old, spanning six NHANES cycles from 2005 to 2016, was enrolled and assessed. The primary endpoints of the study included all-cause mortality and cardiovascular mortality utilizing data from National Center for Health Statistics (NCHS). Cox regression model and subgroup analysis were conducted to assess the associations of CMI with all-cause and cardiovascular mortality. The mediating effect of inflammation-related indicators including leukocyte, neutrophil, lymphocyte, systemic immune-inflammation index (SII), neutrophil to lymphocyte ratio (NLR) were evaluated to investigate the potential mechanism of the associations between CMI and mortality through mediation package in R 4.2.2. RESULTS: The mean CMI among the enrolled participants was 0.74±0.66, with an average age of 73.28±5.50 years. After an average follow-up period of 89.20 months, there were 1,015 instances of all-cause deaths and 348 cardiovascular deaths documented. In the multivariable-adjusted model, CMI was positively related to all-cause mortality (Hazard Ratio (HR)=1.11, 95% CI=1.01-1.21). Mediation analysis indicated that leukocytes and neutrophils mediated 6.6% and 13.9% of the association of CMI with all-cause mortality. CONCLUSION: Elevated CMI is positively associated with all-cause mortality in the older adults. The association appeared to be partially mediated through inflammatory pathways, indicating that CMI may serve as a valuable indicator for poor prognosis among the older population.

Studying the Effect of the Host Genetic Background of Juvenile Polyposis Development Using Collaborative Cross and Smad4 Knock-Out Mouse Models.

Juvenile polyposis syndrome (JPS) is a rare autosomal dominant disorder characterized by multiple juvenile polyps in the gastrointestinal tract, often associated with mutations in genes such as Smad4 and BMPR1A. This study explores the impact of Smad4 knock-out on the development of intestinal polyps using collaborative cross (CC) mice, a genetically diverse model. Our results reveal a significant increase in intestinal polyps in Smad4 knock-out mice across the entire population, emphasizing the broad influence of Smad4 on polyposis. Sex-specific analyses demonstrate higher polyp counts in knock-out males and females compared to their WT counterparts, with distinct correlation patterns. Line-specific effects highlight the nuanced response to Smad4 knock-out, underscoring the importance of genetic variability. Multimorbidity heat maps offer insights into complex relationships between polyp counts, locations, and sizes. Heritability analysis reveals a significant genetic basis for polyp counts and sizes, while machine learning models, including k-nearest neighbors and linear regression, identify key predictors, enhancing our understanding of juvenile polyposis genetics. Overall, this study provides new information on understanding the intricate genetic interplay in the context of Smad4 knock-out, offering valuable insights that could inform the identification of potential therapeutic targets for juvenile polyposis and related diseases.

Physicomechanical, Wettability, Corrosion, Thermal, and Microstructural Morphology Characteristics of Carbonized and Uncarbonized Bagasse Ash Waste-Reinforced Al-0.45Mg-0.35Fe-0.25Si-Based Composites: Fabrications and Characterizations.

An effort was being made to incorporate waste bagasse ash (WBA) both in carbonized and uncarbonized form into the formulation of Al6063 matrix-based metal matrix composites (MMC's) by partially substituting ceramic particles for them. In the process of developing composites, comparative research on carbonized WBA and uncarbonized bagasse powder was carried out in the role of reinforcement. Microstructure investigations revealed that carbonized WBA particles were properly distributed throughout the aluminum-base metal matrix alloy. They also had the appropriate level of wettability. The reinforcement of carbonized WBA particles in AA6063-based matrix material had a maximum tensile strength of 110 MPa and a maximal hardness of 39 BHN when 3.75 wt % of the particles were used. The deterioration in tensile strength (6.25 wt % of WBA) and the appearance of porosity and blowholes can be enumerated by tensile fractography-based scanning electron microscopy (SEM) analysis. The reinforcement of carbonized WBA particles in AA6063-based matrix material was found to have a maximal percent elongation of 14.42% and the highest fracture toughness of 15 Joules when 1.25 wt % of the particles were employed. For AA6063/3.75 wt % carbonized WBA-based MMC's, the minimum percent porosity was determined to be 5.83, and the minimum thermal expansion was found to be 45 mm3. As the percentage of reinforcement in bagasse-reinforced composites increases, the density of the material, the amount of corrosion loss, and the cost all decrease gradually. The AA6063 matrix, with a composition of 3.75 wt % carbonized WBA-based MMC's, had satisfactory specific strength and corrosion loss. The AA6063 alloy composite's microstructure analysis revealed that carbonized WBA enhanced the material's mechanical characteristics, contributing to its excellent mechanical capabilities. The results of the corrosion test showed that carbonized WBA-reinforced composites exhibited reduced weight loss due to corrosion, whereas uncarbonized bagasse powder was an inappropriate reinforcement. The SEM analysis of AA6063 alloy/3.75 wt % carbonized WBA ash reinforcement-based MMC's exposed to a 3.5 wt % NaCl solution has exhibited the development of corrosion pits as a result of localized attack by the corrosive environment. The thermal expansion test showed that the composite with uncarbonized bagasse powder as reinforcement have a high shrinkage rate in comparison with the composite with 3.75 wt %. The composite's mechanical characteristics and thermal stability were enhanced by the presence of hard phases like SiO2, Al2O3, Fe2O3, CaO, and MgO, as revealed by X-ray diffraction analysis. This made it suitable for use in a variety of applications.

Exploring Microstructural, Interfacial, Mechanical, and Wear Properties of AlSi7Mg0.3 Composites with TiMOVWCr High-Entropy Alloy Powder.

This study explored the impact of varying weight percentages of TiMoVWCr high-entropy alloy (HEA) powder addition on A356 composites produced using friction stir processing (FSP). Unlike previous research that often focused on singular aspects, such as mechanical properties, or microstructural analysis, this investigation systematically examined the multifaceted performance of A356 composites by comprehensively assessing the microstructure, interfacial bonding strength, mechanical properties, and wear behavior. The study identified a uniform distribution of TiMoVWCr HEA powder in the composition A356/2%Ti2%Mo2%V2%W2%Cr, highlighting the effectiveness of the FSP technique in achieving homogeneous dispersion. Strong bonding between the reinforcement and matrix material was observed in the same composition, indicating favorable interfacial characteristics. Mechanical properties, including tensile strength and hardness, were evaluated for various compositions, demonstrating significant improvements across the board. The addition of 2%Ti2%Mo2%V2%W2%Cr powder enhanced the tensile strength by 36.39%, while hardness improved by 62.71%. Similarly, wear resistance showed notable enhancements ranging from 35.56 to 48.89% for different compositions. Microstructural analysis revealed approximately 1640.59 grains per square inch for the A356/2%Ti2%Mo2%V2%W2%Cr processed composite at 500 magnifications. In reinforcing Al composites with Ti, Mo, V, W, and Cr high-entropy alloy (HEA) particles, each element imparted distinct benefits. Titanium (Ti) enhanced strength and wear resistance, molybdenum (Mo) contributed to improved hardness, vanadium (V) promoted hardenability, tungsten (W) enhanced wear resistance, and chromium (Cr) provided wear resistance and hardness. Anticipating the potential applications of the developed composite, the study suggests its suitability for the aerospace sector, particularly in casting lightweight yet high-strength parts such as aircraft components, engine components, and structural components, underlining the significance of the investigated TiMoVWCr HEA powder-modified A356 composites.

Silver nanoparticles biosynthesis using mixture of Lactobacillus sp. and Bacillus sp. growth and their antibacterial activity.

The biosynthesis of nanoparticles offers numerous advantages, including ease of production, cost-effectiveness, and environmental friendliness. In our research, we focused on the bioformation of silver nanoparticles (AgNPs) using a combination of Lactobacillus sp. and Bacillus sp. growth. These AgNPs were then evaluated for their biological activities against multidrug-resistant bacteria. Our study involved the isolation of Bacillus sp. from soil samples and Lactobacillus sp. from raw milk in Dhamar Governorate, Yemen. The synthesized AgNPs were characterized using various techniques such as UV-visible spectroscopy, X-ray diffraction (XRD), Fourier-transform infrared spectroscopy (FTIR), and transmission electron microscopy (TEM). The antibacterial properties of the AgNPs were assessed using the modified Kirby Bauer disk diffusion method against multidrug-resistant strains of Staphylococcus aureus and Pseudomonas aeruginosa. Our results demonstrated that the use of a bacterial mixture for biosynthesis led to faster and more effective production of AgNPs compared to using a single bacterium. The UV-visible spectra showed characteristic peaks indicative of silver nanoparticles, while XRD analysis confirmed the crystalline nature of the synthesized particles. FTIR results suggested the presence of capping proteins that contribute to the synthesis and stability of AgNPs. Furthermore, TEM images revealed the size and morphology of the AgNPs, which exhibited spherical shapes with sizes ranging from 4.65 to 22.8 nm. Notably, the antibacterial activity of the AgNPs was found to be more pronounced against Staphylococcus aureus than Pseudomonas aeruginosa, indicating the potential of these nanoparticles as effective antimicrobial agents. Overall, our study highlights the promising antibacterial properties of AgNPs synthesized by a mixture of Lactobacillus sp. and Bacillus sp. growth. Further research is warranted to explore the potential of utilizing different bacterial combinations for enhanced nanoparticle synthesis.

Multiwaves, breathers, lump and other solutions for the Heimburg model in biomembranes and nerves.

In this manuscript, a mathematical model known as the Heimburg model is investigated analytically to get the soliton solutions. Both biomembranes and nerves can be studied using this model. The cell membrane's lipid bilayer is regarded by the model as a substance that experiences phase transitions. It implies that the membrane responds to electrical disruptions in a nonlinear way. The importance of ionic conductance in nerve impulse propagation is shown by Heimburg's model. The dynamics of the electromechanical pulse in a nerve are analytically investigated using the Hirota Bilinear method. The various types of solitons are investigates, such as homoclinic breather waves, interaction via double exponents, lump waves, multi-wave, mixed type solutions, and periodic cross kink solutions. The electromechanical pulse's ensuing three-dimensional and contour shapes offer crucial insight into how nerves function and may one day be used in medicine and the biological sciences. Our grasp of soliton dynamics is improved by this research, which also opens up new directions for biomedical investigation and medical developments. A few 3D and contour profiles have also been created for new solutions, and interaction behaviors have also been shown.

Physicomechanical, morphological and tribo-deformation characteristics of lightweight WC/AZ31B Mg-matrix biocomposites for hip joint applications.

Exploring high strength materials with a higher concentration of reinforcements in the alloy proves to be a challenging task. This research has explored magnesium-based composites (AZ31B alloy) with tungsten carbide reinforcements, enhancing strength for medical joint replacements via league championship optimisation. The primary objective is to enhance medical joint replacement biomaterials employing magnesium-based composites, emphasising the AZ31B alloy with tungsten carbide reinforcements. The stir casting method is utilised in the manufacture of magnesium matrix composites (MMCs), including varied percentages of tungsten carbide (WC). The mechanical characteristics, such as micro-hardness, tensile strength, and yield strength, have been assessed and compared with computational simulations. The wear studies have been carried out to analyse the tribological behaviour of the composites. Additionally, this study investigates the prediction of stress and the distribution of forces inside bone and joint structures, therefore offering significant contributions to the field of biomedical research. This research contemplates the use of magnesium-based MMCs for the discovery of biomaterials suitable for medical joint replacement. The study focuses on the magnesium alloy AZ31B, with particles ranging in size from 40 to 60 microns used as the matrix material. Moreover, the outcomes have revealed that when combined with MMCs based on AZ31B-magnesium matrix, the WC particle emerges as highly effective reinforcements for the fabrication of lightweight, high-strength biomedical composites. This study uses the league championship optimisation (LCO) approach to identify critical variables impacting the synthesis of Mg MMCs from an AZ31B-based magnesium alloy. The scanning electron microscopy (SEM) images are meticulously analysed to depict the dispersion of WC particulates and the interface among the magnesium (Mg) matrix and WC reinforcement. The SEM analysis has explored the mechanisms underlying particle pull-out, the characteristics of inter-particle zones, and the influence of the AZ31B matrix on the enhancement of the mechanical characteristics of the composites. The application of finite element analysis (FEA) is being used in order to make predictions regarding the distribution of stress and the interactions of forces within the model of the hip joint. This study has compared the physico-mechanical and tribological characteristics of WC to distinct combinations of 0%, 5%, 10% and 15%, and its impact on the performance improvements. SEM analysis has confirmed the findings' improved strength and hardness, particularly when 10%-15% of WC was incorporated. Following the incorporation of 10% of WC particles within Mg-alloy matrix, the outcomes of the study has exhibited enhanced strength and hardness, which furthermore has been evident by utilising SEM analysis. Using ANSYS, structural deformation and stress levels are predicted, along with strength characteristics such as additional hardness of 71 HRC, tensile strength of 140-150 MPa, and yield strength closer to 100-110 MPa. The simulations yield significant insights into the behaviour of the joint under various loading conditions, thus enhancing the study's significance in biomedical environments.

Utilizing sine trigonometric q-spherical fuzzy rough aggregation operators for group decision-making and their role in digital transformation.

q-spherical fuzzy rough set (q-SFRS) is also one of the fundamental concepts for addressing more uncertainties in decision problems than the existing structures of fuzzy sets, and thus its implementation was more substantial. The well-known sine trigonometric function maintains the periodicity and symmetry of the origin in nature and thus satisfies the expectations of the experts over the multi-parameters. Taking this feature and the significance of the q-SFRSs into consideration, the main objective of the article is to describe some reliable sine trigonometric laws for SFSs. Associated with these laws, we develop new average and geometric aggregation operators to aggregate the q-spherical fuzzy rough numbers. Then, we presented a group decision-making strategy to address the multi-attribute group decision-making problem using the developed aggregation operators. To verify the value of the defined operators, a MAGDM strategy is provided along with applications for selecting a Cloud Service Provider and a Digital Transformation Vendor for digital transformation. Moreover, a comparative study is also performed to present the effectiveness of the developed approach.

Assessing indoor positioning system: A q-spherical fuzzy rough TOPSIS analysis.

This study investigates advanced data collection methodologies and their implications for understanding employee and customer behavior within specific locations. Employing a comprehensive multi-criteria decision-making framework, we evaluate various technologies based on four distinct criteria and four technological alternatives. To identify the most effective technological solution, we employ the q-spherical fuzzy rough TOPSIS method, integrating three key parameters: lower set approximation, upper set approximation, and parameter q (where q ≥ 1). Our novel approach combines the TOPSIS method with q-spherical fuzzy rough set theory, providing deeper insights into data-driven decision-making processes in corporate environments. By comparing our proposed framework with existing multi-criteria decision-making methodologies, we demonstrate its strength and competitiveness. This research contributes to enhancing decision-making capabilities in corporate settings and beyond.

Prognostic impact of coronary microvascular dysfunction in patients with atrial fibrillation.

BACKGROUND: Coronary microvascular dysfunction (CMD) is frequently observed in atrial fibrillation (AF), the most commonly sustained arrhythmia. Nevertheless, an in-depth prognostic significance of CMD in AF is lacking. We aimed to provide insight into the predictive impact of CMD assessed by a novel non-invasive coronary angiography-derived index of microcirculatory resistance (caIMR) for major adverse events (MACE) in AF patients. METHOD: This study included patients with AF who underwent invasive coronary angiography due to suspected cardiac ischemia and did not exhibit obstructive epicardial coronary artery disease (≤50 % stenosis). The caIMR was prospectively evaluated, and the optimal cutoff value for predicting MACE was determined through ROC analysis. RESULT: A total of 463 patients with AF were enrolled. During a median of 33 months of follow-up, 111 (23.97 %) patients had MACE endpoints. The best caIMR cutoff value was 39.28. In patients with MACE, both the mean caIMR and the prevalence of elevated caIMR (caIMR>39.28) were significantly higher compared to those without MACE. An elevated caIMR was linked to a higher risk of MACE (log-rank P < 0.001) and emerged as an independent predictor of clinical outcomes (HR: 4.029; 95 % CI: 2.529-6.418; P < 0.001). In addition, the risk of MACE was higher in high caIMR patients with non-paroxysmal AF (log-rank P < 0.001) and no catheter ablation (log-rank P < 0.001). CONCLUSION: Elevated caIMR is common and showed a vital independent prognostic significance in AF patients. In addition to well-known risk factors, assessment of microvascular function can be a feasible approach for early prevention and a therapeutic target in AF patients.

A novel approach towards web browser using the concept of a complex spherical fuzzy soft information.

The modern technology is the practical application of scientific knowledge, whether in industry or daily life, for goals or purposes. More quickly than any other technological advancement in human history, digital technologies have advanced. The technology sector is expanding and provides both new educational opportunities and innovative, exciting products. Right now, one of the most widely used and fascinating technologies is the web browser. This article introduced the novel concepts of complex spherical fuzzy soft relations (CSFSRs) by using the Cartesian Product (CP) of two complex spherical fuzzy soft sets (CSFSSs). Additionally, examples are used to clarify various types of relations. Because it discusses all levels of membership, abstinence, and non-membership with multidimensional variables, the CSFSRs have a detailed structure. The CSFSR-based modelling tools developed in this research, which primarily rely on the score function, can be used to choose the best Web browser. The transaction could be as easy as users sharing records via a functional web browser. Finally, the advantages of this suggested structure are illustrated by contrasting it with alternative structures.

Role of dietary fiber and lifestyle modification in gut health and sleep quality.

Dietary fiber has an immense role in the gut microbiome by modulating juvenile growth, immune system maturation, glucose, and lipid metabolism. Lifestyle changes might disrupt gut microbiota symbiosis, leading to various chronic diseases with underlying inflammatory conditions, obesity, and its associated pathologies. An interventional study of 16 weeks examined the impact of psyllium husk fiber with and without lifestyle modification on gut health and sleep quality in people with central obesity (men = 60 and women = 60), those aged from 40 to 60 years, those having WC ≥ 90 cm (men) and WC ≥ 80 cm (women), and no history of any chronic disease or regular medication. The participants were subgrouped into three intervention groups, namely, the psyllium husk fiber (PSH) group, the lifestyle modification (LSM) group, and the LSM&PSH group and control group with equal gender bifurcation (men = 15 and women = 15). A 24-h dietary recall, gastrointestinal tract (GIT) symptoms, and sleep quality analysis data were collected on validated questionnaires. The analyses of variance and covariance were used for baseline and post-intervention, respectively. Student's t-test was applied for pre- and post-intervention changes on the variable of interest. The intervention effect on GIT health was highly significant (P < 0.001). The mean GIT scores of the LSM, PSH, and LSM&PSH groups were 2.99 ± 0.14, 2.49 ± 0.14, and 2.71 ± 0.14, respectively, compared to the mean GIT scores of the control group. No significant (P = 0.205) effect of either intervention was observed on sleep quality. The study concluded that psyllium husk fiber significantly improved the GIT symptoms, while no significant effect of the intervention was observed on sleep quality analysis.

Fabrication and Characterization of Montmorillonite Clay/Agar-Based Magnetic Composite and Its Biological and Electrical Conductivity Evaluation.

Montmorillonite clay and agar are naturally occurring materials of significant importance in designing biocompatible materials tailored for applications in biotechnology and medicine. The introduction of magnetic properties has the potential to significantly boost their characteristics and expand their applications. In this study, we have successfully synthesized highly intercalated magnetic composites, incorporating magnetic iron oxide nanoparticles (MNPs), montmorillonite clay (MMT), and agar (AG), through a thermo-physicomechanical method. Three samples of MMT-AG with 2, 1.5, and 0.5% MNPs and three sample composites of MNPs-AG with 2, 1, and 0.5% MMT clay are prepared. The synthesized composites were characterized by SEM, XRD, TGA, DTA, and FTIR. SEM analysis revealed a uniform dispersion of MNPs and MMT in the composite. The XRD pattern confirmed the presence of MNPs in the composite site. The TGA and DTA results demonstrated improved thermal stability due to the MNP incorporation. FTIR spectra showed all of the constituents of agar, MNPs, and MMT clay. The swelling ratio was observed to range from 835% to 1739%. The swelling study indicated an increased hydrophobicity with the addition of MNPs to the composite. Antibacterial activities revealed a significant inhibition of Escherichia coli (E. coli) growth by ranging from 10 to 19 nm in the composite. The composite also exhibited a considerable antioxidant action, with IC50 values of 7.96, 46.55, and 57.58 µg/mL, and electrical properties just like conductors.

Aldosterone Effect on Cardiac Structure and Function.

BACKGROUND: Cardiac remodelling could be a key mechanism in aldosteronemediated cardiovascular morbidity and mortality. Experimental and clinical evidence has demonstrated that aldosterone causes cardiac structural remodelling and dysfunction by its profibrotic and pro-hypertrophic effects, which result mainly from the direct effects on myocardial collagen deposition, inflammation, and oxidative stress. Clinical studies have investigated the aldosterone effects on the heart in different clinical conditions, including general population, essential hypertension, primary aldosteronism, heart failure, and atrial fibrillation. Robust findings indicate that aldosterone or the activation of the cardiac mineralocorticoid receptor can cause damage to myocardial tissue by mechanisms independent of the blood pressure, leading to tissue hypertrophy, fibrosis, and dysfunction. CONCLUSION: Aldosterone-mediated cardiovascular morbidity and mortality mainly result from cardiac structural and functional alterations. In different clinical settings, aldosterone can induce cardiac structural remodelling and dysfunction via several pathological mechanisms, including cardiac fibrosis, inflammation, and oxidative stress. Aldosterone antagonists could effectively decrease or reverse the detrimental aldosterone-mediated changes in the heart.

Global dynamics and computational modeling approach for analyzing and controlling of alcohol addiction using a novel fractional and fractal-fractional modeling approach.

In recent years, alcohol addiction has become a major public health concern and a global threat due to its potential negative health and social impacts. Beyond the health consequences, the detrimental consumption of alcohol results in substantial social and economic burdens on both individuals and society as a whole. Therefore, a proper understanding and effective control of the spread of alcohol addictive behavior has become an appealing global issue to be solved. In this study, we develop a new mathematical model of alcohol addiction with treatment class. We analyze the dynamics of the alcohol addiction model for the first time using advanced operators known as fractal-fractional operators, which incorporate two distinct fractal and fractional orders with the well-known Caputo derivative based on power law kernels. The existence and uniqueness of the newly developed fractal-fractional alcohol addiction model are shown using the Picard-Lindelöf and fixed point theories. Initially, a comprehensive qualitative analysis of the alcohol addiction fractional model is presented. The possible equilibria of the model and the threshold parameter called the reproduction number are evaluated theoretically and numerically. The boundedness and biologically feasible region for the model are derived. To assess the stability of the proposed model, the Ulam-Hyers coupled with the Ulam-Hyers-Rassias stability criteria are employed. Moreover, utilizing effecting numerical schemes, the models are solved numerically and a detailed simulation and discussion are presented. The model global dynamics are shown graphically for various values of fractional and fractal dimensions. The present study aims to provide valuable insights for the understanding the dynamics and control of alcohol addiction within a community.

The correlation of atherogenic index of plasma with non-obstructive CAD and unfavorable prognosis among patients diagnosed with MINOCA.

BACKGROUND: The atherogenic index of plasma (AIP) is linked to lipid metabolism and has shown considerable prognostic value in cardiovascular disorders. However, its role in myocardial infarction with non-obstructive coronary arteries (MINOCA) has not been investigated. We assessed the relationship between AIP, the severity of coronary stenosis, and prognosis in MINOCA. METHODS: We included consecutive patients who were diagnosed with MINOCA. AIP was calculated using the base 10 logarithm of the ratio between the levels of TG and HDL-C. The patients were divided into four groups based on their AIP quartiles: Q1 (AIP<-0.145), Q2 (AIP≥-0.145and≤0.049), Q3 (AIP>0.049and≤0.253), and Q4 (AIP>0.253). All patients underwent follow-up for MACE. RESULTS: The final analysis included 421 patients, with 188 having normal coronaries (0 stenosis) and 233 exhibiting non-obstructive coronary artery disease (CAD) (<50 % stenosis). In the multivariate logistic analysis, highest AIP (Q4) group was significantly associated with increased risk of non-obstructive CAD in MINOCA (OR,1.994;95 % CI:1.075-3.698; P = 0.029). During the follow-up period, MACE occurred in 22.8 % of MINOCA patients. Q4 group exhibited a significantly higher rate of MACE (P = 0.021). Furthermore, when both AIP and coronary stenosis status were considered, the results revealed individuals in the Q4 group with non-obstructive CAD had the highest risk of MACE (log-rank P = 0.027). The adjusted Cox analysis indicated that the Q4 group was associated with a 2.052-fold increase in the HR of MACE. CONCLUSION: AIP exhibits a notable association with the incidence of MACE in MINOCA patients and serves as a substantial marker for non-obstructive CAD in this patient group.

An efficient intrusion detection model based on convolutional spiking neural network.

Many intrusion detection techniques have been developed to ensure that the target system can function properly under the established rules. With the booming Internet of Things (IoT) applications, the resource-constrained nature of its devices makes it urgent to explore lightweight and high-performance intrusion detection models. Recent years have seen a particularly active application of deep learning (DL) techniques. The spiking neural network (SNN), a type of artificial intelligence that is associated with sparse computations and inherent temporal dynamics, has been viewed as a potential candidate for the next generation of DL. It should be noted, however, that current research into SNNs has largely focused on scenarios where limited computational resources and insufficient power sources are not considered. Consequently, even state-of-the-art SNN solutions tend to be inefficient. In this paper, a lightweight and effective detection model is proposed. With the help of rational algorithm design, the model integrates the advantages of SNNs as well as convolutional neural networks (CNNs). In addition to reducing resource usage, it maintains a high level of classification accuracy. The proposed model was evaluated against some current state-of-the-art models using a comprehensive set of metrics. Based on the experimental results, the model demonstrated improved adaptability to environments with limited computational resources and energy sources.

Improved exponential type mean estimators for non-response case using two concomitant variables in simple random sampling.

This paper addresses new exponential estimators for population mean in case of non-response on both the study and the concomitant variables using simple random sampling. The expressions for theoretical bias and mean square error of new estimators are derived up to first-order approximation and comparisons are made with the existing estimators. The proposed estimators are observed more efficient as compared to the considered estimators in the literature. For instance, the classical [4] unbiased estimator, the estimator of [9], and other existing estimators under the explained conditions. The theoretical results are supported numerically by using real-life data sets, under the criteria of bias, mean square error, percent relative efficiency and mathematical conditions. It is also clear from the numerical results that the suggested exponential estimators performed better than the estimators in the literature.

The Complexity of Skeletal Transverse Dimension: From Diagnosis, Management, and Treatment Strategies to the Application of Collaborative Cross (CC) Mouse Model.

This study investigates the significance of skeletal transverse dimension (STD) in orthodontic therapy and its impact on occlusal relationships. The primary goal is to enhance understanding and promote the integration of transverse skeletal diagnostics into routine orthodontic assessments. To achieve this aim, the study employs a comprehensive approach, utilizing model analysis, clinical assessments, radiographic measurements, and occlusograms. The initial step involves a meticulous assessment of deficiencies in the maxilla, mainly focusing on transverse dimension issues. Various successful diagnostic methods are employed to ascertain the type and presence of these deficiencies. Furthermore, the study compares surgically assisted maxillary expansion (SARME) and orthopedic maxillary expansion (OME) in addressing skeletal transverse issues. Stability assessments and efficacy analyses are conducted to provide valuable insights into the superiority of SARME over OME. The findings reveal that proper evaluation of STD is crucial in orthodontic diagnosis, as overlooking transverse dimension issues can lead to complications such as increased masticatory muscle activity, occlusal interferences, and an elevated risk of gingival recession. Surgically assisted maxillary expansion emerges as a more stable solution than orthopedic methods. In conclusion, incorporating skeletal transverse diagnostics into routine orthodontic assessments is imperative for achieving optimal occlusal relationships and minimizing negative consequences on dentition, periodontium, and joints. The study emphasizes the significance of accurate three-dimensional assessments and recommends the consideration of SARME over OME for addressing skeletal transverse deficiencies. Finally, the Collaborative Cross (CC) mouse model is also a novel mouse model for studying complex traits. Exploring the Collaborative Cross mouse model opens avenues for future research, promising further insights into transverse skeletal issues in orthodontics.