Assumption Of Homogeneity Research Articles

Statistical method accounts for microscopic electric field distortions around neurons when simulating activation thresholds.

Notwithstanding advances in computational models of neuromodulation, there are mismatches between simulated and experimental activation thresholds. Transcranial Magnetic Stimulation (TMS) of the primary motor cortex generates motor evoked potentials (MEPs). At the threshold of MEP generation, whole-head models predict macroscopic (at millimeter scale) electric fields (50-70 V/m) which are considerably below conventionally simulated cortical neuron thresholds (200-300 V/m). We hypothesize that this apparent contradiction is in part a consequence of electrical field warping by brain microstructure. Classical neuronal models ignore the physical presence of neighboring neurons and microstructure and assume that the macroscopic field directly acts on the neurons. In previous work, we performed advanced numerical calculations considering realistic microscopic compartments (e.g., cells, blood vessels), resulting in locally inhomogeneous (micrometer scale) electric field and altered neuronal activation thresholds. Here we combine detailed neural threshold simulations under homogeneous field assumptions with microscopic field calculations, leveraging a novel statistical approach. We show that, provided brain-region specific microstructure metrics, a single statistically derived scaling factor between microscopic and macroscopic electric fields can be applied in predicting neuronal thresholds. For the cortical sample considered, the statistical methods match TMS experimental thresholds. Our approach can be broadly applied to neuromodulation models, where fully coupled microstructure scale simulations may not be practical.

Religious savior-centered psychotherapy for depression: a focus on women’s well-being

ABSTRACT This study explores the effectiveness of Religious Savior-Centered Psychotherapy (RSCP) in treating depression in religious women. RSCP is a therapeutic approach that integrates Islamic teachings, particularly the concept of a Savior, with cognitive and behavioral strategies to address mental health challenges. Unlike traditional therapy models, RSCP emphasizes spiritual healing by fostering a strong connection to faith and a hopeful outlook for the future. The study aims to assess RSCP’s impact on depression in women by aligning with Islamic teachings and emphasizing positive future expectations. A pretest-posttest design with a two-month follow-up was employed to evaluate the effects of RSCP. The study included 70 women aged 18–60 from five counseling clinics in Tehran, all diagnosed with mild to moderate depression, and having expressed a belief in a Savior. MANCOVA was used to analyze the data, ensuring assumptions of normality and homogeneity of variances were met. MANCOVA results indicated a significant linear correlation between the treatment and depression levels (p < .05), with a large effect size (partial η2 = .61 for posttest and .54 for follow-up). Initial findings suggest RSCP’s potential benefit on mental well-being. RSCP has the potential to be integrated into existing mental health frameworks as a culturally sensitive option, particularly for Muslim women seeking faith-based approaches to mental health care. Future research with larger samples, randomized controlled trials, and longitudinal studies is needed to explore the effectiveness of this new positive psychotherapy approach.

The model of the local Universe in the framework of the second-order perturbation theory

Abstract Recently, we constructed the specific solution to the second-order cosmological perturbation theory, around any Friedmann–Lema\^itre–Robertson–Walker (FLRW) background filled with dust matter and a positive cosmological constant. In this paper, we use the {\it Cosmicflows-4} (CF4) sample of galaxies from the Extragalactic Distance Database to constrain this metric tensor. We obtain an approximation to the local matter distribution and geometry. We numerically solve for null geodesics for randomly distributed mock sources and compare this model with the Lema\^itre-Hubble constant inferred from the observations under the assumption of perfect isotropy and homogeneity. We conclude on effects of realistic inhomogeneities on the luminosity distance in the context of the Hubble tension and discuss limitations of our approach.

Water compression induced ionic negative differential resistance in nanopores.

The mass transport behavior through nanoscale channels, greatly influenced by the structures and dynamics of nanoconfined water, plays an essential role in many biophysical processes. However, the dynamics of nanoconfined water under an external field and its effects are still not fully understood. Here, on the basis of molecular dynamics simulations, we theoretically show that the ionic current of [Bmim][PF6] through narrow pores in graphene membrane exhibits an ionic negative differential resistance effect-the ionic current decreases as the voltage increases over a certain threshold. This effect arises from the violation of traditional fluid dynamics as the assumption of continuity and homogeneity of fluids is no longer effective in ultrathin nanopores. The gradient of electric field around the atomic-thin layer produces a strong gradient force on the polarized water inside the nanopore. This dielectrophoretically compressed water leads to a hydrostatic force that repels ions from entering the nanopore. Our findings may advance the understanding of hydrostatic mechanism, which governs ion transport through nanopores.

Comparing continuum and direct fiber models of soft tissues: An ocular biomechanics example reveals that continuum models may artificially disrupt the strains at both the tissue and fiber levels

Collagen fibers are the main load-bearing component of soft tissues but difficult to incorporate into models. Whilst simplified homogenization models suffice for some applications, a thorough mechanistic understanding requires accurate prediction of fiber behavior, including both detailed fiber-level strains and long-distance transmission. Our goal was to compare the performance of a continuum model of the optic nerve head (ONH) built using conventional techniques with a fiber model we recently introduced which explicitly incorporates the complex 3D organization and interaction of collagen fiber bundles [1]. To ensure a fair comparison, we constructed the continuum model with identical geometrical, structural, and boundary specifications as for the fiber model. We found that: 1) although both models accurately matched the intraocular pressure (IOP)-induced globally averaged displacement responses observed in experiments, they diverged significantly in their ability to replicate specific 3D tissue-level strain patterns. Notably, the fiber model faithfully replicated the experimentally observed depth-dependent variability of radial strain, the ring-like pattern of meridional strain, and the radial pattern of circumferential strain, whereas the continuum model failed to do so; 2) the continuum model disrupted the strain transmission along each fiber, a feature captured well by the fiber model. These results demonstrate limitations of the conventional continuum models that rely on homogenization and affine deformation assumptions, which render them incapable of capturing some complex tissue-level and fiber-level deformations. Our results show that the strengths of explicit fiber modeling help capture intricate ONH biomechanics. They potentially also help modeling other fibrous tissues. Statement of SignificanceUnderstanding the mechanics of fibrous tissues is crucial for advancing knowledge of various diseases. This study uses the ONH as a test case to compare conventional continuum models with fiber models that explicitly account for the complex fiber structure. We found that the fiber model captured better the biomechanical behaviors at both the tissue level and the fiber level. The insights gained from this study demonstrate the significant potential of fiber models to advance our understanding of not only glaucoma pathophysiology but also other conditions involving fibrous soft tissues. This can contribute to the development of therapeutic strategies across a wide range of applications.

Sustainable leadership among financial managers in Spain: A gender issue

Finance plays a key role in supporting sustainable companies, thereby contributing, and supporting the transition towards a low carbon and circular economy. At the strategic level, finance can aid companies make decisions regarding the trade-offs between their sustainable goals. Therefore, key players in this respect are finance managers who need to take decisions regarding the latter. This study analyzed the level of sustainable leadership among financial managers in Spain. A total of 131 senior financial managers (106 men and 25 women), from various sectors in Spanish companies (a multi-sector study), responded to two scales: the Honeybee Sustainable Leadership Scale (focusing on stakeholder orientation and a vision of social and shared leadership) and the Locust Leadership Scale (primarily centered on achieving short-term profits at any cost). A descriptive analysis of the sample was conducted. The t-test was applied for comparing means and the Mann-Whitney U test statistical technique was used under conditions where the assumptions of normality and homogeneity of variance were violated. In the hypothesis testing, a significance level of p&lt;0.05 was employed. The main finding was that female financial managers scored significantly higher on the Honeybee Leadership Scale compared to their male counterparts, signifying that female presence is key to sustainable leadership. Therefore, including women in higher corporate-level positions would contribute to a more sustainable approach in management. Furthermore, it was also found that the organizations in which the financial managers worked tended to undertake a hybrid approach to sustainable leadership. Most companies undertook a hybrid perspective incorporating elements of both diametrically opposed bee and locust leadership philosophies.

A non-homogeneous alternating renewal process model for interval censoring

Abstract Previous approaches to modelling interval-censored data have often relied on assumptions of homogeneity in the sense that the censoring mechanism, the underlying distribution of occurrence times, or both, are assumed to be time-invariant. In this work, we introduce a model which allows for non-homogeneous behaviour in both cases. In particular, we outline a censoring mechanism based on a non-homogeneous alternating renewal process in which interval generation is assumed to be time-dependent, and we propose a Markov point process model for the underlying occurrence time distribution. We prove the existence of this process and derive the conditional distribution of the occurrence times given the intervals. We provide a framework within which the process can be accurately modelled, and subsequently compare our model to the homogeneous approach through a number of illustrative examples.

PSIX-8 A multistrain probiotic modifies fecal microbial populations of healthy adult cats

Abstract Probiotics can modulate the intestinal microbiota and benefit the host’s health, whereas environmental stressors can negatively impact the composition of the intestinal microbiota. Lactic acid bacteria (LAB), most commonly Lactobacillus and Bifidobacterium species, are well-known organisms with probiotic potential. The objective of this study was to determine the impact on the fecal microbial population of healthy Cats, after ingestion of a probiotic blend of Lactobacillus acidophilus-286, Bifidobacterium animalis subs. Lactis-689, and Enterococcus faecium-202. Thirty adult cats (15 male, 15 female; mean BW=3.39 kg; mean age=3.3 y) were enrolled in this placebo-controlled and blinded study. After a 7-d washout period, cats were allocated into two groups similar in terms of body weight, age, and sex. Cats were fed a complete dry extruded diet and at time 0 h on d-0 received orally 4 g of a placebo paste or probiotic paste corresponding to the target dose of 4x107 total CFU. Administration of the placebo or probiotic was repeated 12 h and 24 h after the first dose. Afterward, fecal scores were evaluated daily for 7 days. Fresh fecal samples were collected on days 0, 3, and 7 for microbial enumerations and fecal metabolite measurements. Fecal microbial count data did not conform to the assumptions of normality and homogeneity of variances, consequently, non-parametric tests were performed for comparisons. Fecal scores, dry matter, and metabolites were not different between groups. Fecal counts of Lactobacillus spp., Bifidobacterium spp., and Enterococcus spp. were greater on both d-3 and d-7 (P &amp;lt; 0.01) in cats that consumed probiotics. Fecal counts of both Escherichia coli and Clostridium perfringens were fewer (P &amp;lt; 0.05) in cats that consumed probiotics. In conclusion, the consumption by cats on d-0 of a probiotic blend of Lactobacillus acidophilus-286, Bifidobacterium animalis subs. Lactis-689, and Enterococcus faecium-202 modified the intestinal microbiota up to 7 days after consumption, as evidenced by the increase of lactic acid bacteria and the decrease of Escherichia coli and Clostridium perfringens in feces.

PSIX-7 A multi-strain probiotic modifies fecal microbial populations of healthy adult dogs

Abstract Probiotics can modulate the intestinal microbiota and benefit the health of the host, whereas environmental stressors can negatively impact the composition of the intestinal microbiota. Lactic acid bacteria (LAB), most commonly Lactobacillus and Bifidobacterium species, are well-known organisms with probiotic potential. The objective of this study was to determine the impact on the fecal microbial population of healthy dogs, after ingestion of a probiotic blend of Lactobacillus acidophilus-286, Bifidobacterium animalis subs. Lactis-689, and Enterococcus faecium-202. Adult dogs [n = 30; 15 male, 15 female; mean body weight (BW) = 14.7 kg; mean age = 3.3 yr) were enrolled in this placebo-controlled and blinded study. After a 7-d washout period, dogs were allocated into two groups similar in terms of breed, BW, age, and sex. Dogs were fed a complete dry extruded diet and at time 0 h on d 0 received orally 4 g of a placebo paste or probiotic paste corresponding to the target dose of 4x107 total CFU. Administration of the placebo or probiotic was repeated 12 h and 24 h after the first dose. Afterward, fecal scores were evaluated daily for 7 d. Fresh fecal samples were collected on d 0, 3, and 7 for microbial enumerations and fecal metabolite measurements. Fecal microbial count data did not conform to the assumptions of normality and homogeneity of variances, consequently, non-parametric tests were performed for comparisons. Fecal scores, dry matter, and metabolites were not different between groups. Fecal counts of Lactobacillus spp., Bifidobacterium spp., and Enterococcus spp. were greater on both d 3 and d 7 (P &amp;lt; 0.01) in dogs that consumed probiotics. Fecal counts of both Escherichia coli and Clostridium perfringens were fewer (P &amp;lt; 0.01) in dogs that consumed probiotics. In conclusion, the consumption by dogs on d 0 of a probiotic blend of Lactobacillus acidophilus-286, Bifidobacterium animalis subs. Lactis-689, and Enterococcus faecium-202 modified the intestinal microbiota up to 7 d after consumption, as evidenced by the increase of lactic acid bacteria and the decrease of Escherichia coli and Clostridium perfringens in feces.

The Growth Effect of State Capacity Revisited

AbstractI provide new empirical estimates of the effect of state capacity on economic development across countries over the period 1960–2022. Specifically, I construct a comprehensive state capacity index based on six different dimensions of effective state institutions available in the Varieties of Democracy (V‐Dem) dataset. Then, I estimate heterogeneous parameter models under a common factor framework. My empirical strategy explicitly allows the growth effect of state capacity to differ across countries and accounts for unobserved common factors. My preferred estimates indicate that a one‐standard‐deviation increase in my V‐Dem‐based state capacity index predicts a rise in income per person by roughly 6%–7%. The magnitude of such impact equates to less than half of that implied by conventional estimates obtained under highly restrictive assumptions of slope homogeneity and cross‐sectional independence. Furthermore, I provide partial evidence suggesting that worldwide heterogeneity in the economic importance of state capacity is deeply rooted in prehistorically determined population diversity, state history, long‐term relatedness between countries, and interpersonal trust.

Comparing continuum and direct fiber models of soft tissues. An ocular biomechanics example reveals that continuum models may artificially disrupt the strains at both the tissue and fiber levels.

Collagen fibers are the main load-bearing component of soft tissues but difficult to incorporate into models. Whilst simplified homogenization models suffice for some applications, a thorough mechanistic understanding requires accurate prediction of fiber behavior, including both detailed fiber-level strains and long-distance transmission. Our goal was to compare the performance of a continuum model of the optic nerve head (ONH) built using conventional techniques with a fiber model we recently introduced which explicitly incorporates the complex 3D organization and interaction of collagen fiber bundles [1]. To ensure a fair comparison, we constructed the continuum model with identical geometrical, structural, and boundary specifications as for the fiber model. We found that: 1) although both models accurately matched the intraocular pressure (IOP)-induced globally averaged displacement responses observed in experiments, they diverged significantly in their ability to replicate specific 3D tissue-level strain patterns. Notably, the fiber model faithfully replicated the experimentally observed depth-dependent variability of radial strain, the ring-like pattern of meridional strain, and the radial pattern of circumferential strain, whereas the continuum model failed to do so; 2) the continuum model disrupted the strain transmission along each fiber, a feature captured well by the fiber model. These results demonstrate limitations of the conventional continuum models that rely on homogenization and affine deformation assumptions, which render them incapable of capturing some complex tissue-level and fiber-level deformations. Our results show that the strengths of explicit fiber modeling help capture intricate ONH biomechanics. They potentially also help modeling other fibrous tissues.

Correlation between microstructural inhomogeneity and architectural design in additively manufactured NiTi shape memory alloys

ABSTRACT Additively manufactured Nitinol (NiTi) architectured materials, designed with unit cell architectures, hold promise for customisable applications. However, the common assumption of homogeneity in modeling and additive manufacturing of these architectured materials needs further investigation because geometric-dependent melt pool behaviour results in inhomogeneous microstructure and thermomechanical properties. This study shows that property inhomogeneity at the mesoscale is one reason for pseudo-linear response and partial superelasticity of the fabricated NiTi body-centered cubic (BCC) architectured materials. We modeled using a phenomenological constitutive relation and additively manufactured NiTi architectured materials with varying relative densities. These fabricated samples showed distinct microstructural textures and compositions that affected their local recoverability. The edge effects and laser turn regions were identified as the causes underlying the observed microstructural inhomogeneity. The dimensionless Fourier number is used to describe the transition of printing modes. This study provides valuable information on rigorous experimental/computational consistency in future work.

The role of posted speed limit on pedestrian and bicycle injury severities: An investigation into systematic and unobserved heterogeneities

The posted speed limit, as a proxy of actual speed, is one of the most fundamental predictors of active travelers’ (pedestrian and bicyclist) injury outcomes when involved in crashes with motor vehicles. Although earlier studies predominantly considered posted speed limit as an exogenous variable and provided highly insightful findings, majorities of them assume the effects of active traveler behavior to remain the same across different posted speed limits, which in turn neglect the heterogeneity in active traveler behaviors on high-speed roads vs. low-speed roads. This study proposes to develop a latent segmentation-based active traveler injury severity model to relax the homogeneity assumption of the posted speed limit by active traveler behavior. Specifically, this study proposes to estimate a latent segmentation-based correlated random parameters generalized ordered logit model to examine active travel injury severity mechanisms. The proposed model accommodates systematic heterogeneity in the effects of posted speed limit, crash year and active traveler group by using a piecewise linear function in injury severity component of the latent segment model. The model is demonstrated by using active traveler crash data from Queensland, Australia, for the years 2015 through 2019. To demonstrate the implications of the estimated models, a number of hypothetical scenario analyses are performed with a specific focus on active traveler behavior and reduction in posted speed limits. The outcomes from the hypothetical scenario analysis highlighted that a 76 % (73 %) reduction in active traveler fatalities can be achieved by converting 50–60 km/hr roadways to 10–40 km/hr roadways in the urban areas (rural areas) of Queensland. The outcomes of the study will allow us to identify effective speed management strategies while targeting those with high-risk behavior.

Dynamics of a single cavitation bubble near a cylindrical blind hole

Cavitation bubble dynamics, such as microjets and moving shock waves, are strongly influenced by their surroundings. We investigated the complex bubble behavior during the growth and collapse stages near a blind hole. The simultaneous study, which is a combination of experiment and numerical methods, was performed. The single bubble was induced by a laser focus beam near a blind hole in the cuvette and measured by a high-speed camera with an image processing method. Numerical predictions were conducted for a detailed further investigation of the pressure and velocity fields near and inside the bubble. A fully compressible two-phase Navier-Stokes solver based on the homogeneous flow assumption was used. Both experimental and numerical results showed good agreement with each other. Strong deformation of the bottom bubble surface evolution was observed at low standoffs above the hole entrance. An extremely high-velocity microjet with a mushroom cap-shaped bubble was predicted under high standoffs below the hole entrance. Secondary cavitation in the blind hole was observed experimentally, and we discussed the low-pressure region caused by the interaction among the shock wave, bubble, and blind hole. Consequently, the tendencies of maximum microjet velocity and time-dependent surface pressure in the collapse phase are suggested.

Living the liquid life: Gender, precarity, and journalism in the post-#metoo era

Abstract Despite a long-standing trend of increasing women in the profession, masculine norms and gender inequality persist in media work. During the #metoo movement, Swedish journalists launched the #deadline campaign, shedding light on the connection between gender and worsening working conditions. Increasing demands for flexibility have institutionalised temporary contracts, eroded job security, and expanded job precarity, with women and young journalists disproportionately affected. In this article, we explore gendered journalistic precarity and systemic inequalities, challenging the assumption of professional homogeneity in the field of journalism. We conducted 23 interviews with Swedish journalists on temporary contracts, applying a feminist analysis to understand how power dynamics affect their experiences. Five years post #metoo, gender issues have faded from professional discourse. However, the interviews reveal continued gender discrimination and harassment, exacerbated by factors such as age, class, and position in the labour market.

Numerical analysis of ultrasound-mediated microbubble interactions in vascular systems: Effects on shear stress and vessel mechanics

The present study concerns the numerical modeling of microbubble oscillation within an elastic microvessel, aiming to enhance the safety and efficacy of ultrasound-mediated drug delivery and diagnostic imaging. The success of such applications depends on a thorough understanding of microbubble–vessel interactions. Despite some progress, the critical impact of the stabilizing shell around gas core has remained underexplored. To address this, we developed a novel numerical approach that models the stabilizing shell. Additionally, there is novelty in modeling consequent vascular deformation in response to complicated spatiotemporal microbubble oscillations. The novel approach was implemented for shear stress evaluation as a critical factor in vascular permeability. Finally, our unique approach offered novel insights into microbubble–vessel interactions under diverse acoustic conditions. Results indicated substantial impact of shell properties and acoustic parameters on induced shear stress. With a fourfold increase in acoustic pressure amplitude, 15.6-fold and sixfold increases were observed in maximum shear stress at 1 and 3 MHz, respectively. Also, the peak shear stress could reach up to 15.6 kPa for a shell elasticity of 0.2 N/m at 2.5 MHz. Furthermore, decreasing microvessel/bubble size ratio from 3 to 1.5 increased maximum shear stress from 5.1 to 24.3 kPa. These findings are crucial for optimizing ultrasound parameters in clinical applications, potentially improving treatment outcomes while minimizing risk of vessel damage. However, while our model demonstrated high fidelity in reproducing experimental observations, it is limited by assumptions of vessel geometry and homogeneity of vessel properties. Future work can improve our findings through in vitro experimental measurements.

Efficacy assessment in crop protection: a tutorial on the use of Abbott’s formula

In 1925, the American entomologist Walter Sidney Abbott proposed an equation for assessing efficacy, and it is still widely used today for analysing controlled experiments in crop protection and phytomedicine. Typically, this equation is applied to each experimental unit and the efficacy estimates thus obtained are then used in analysis of variance and least squares regression procedures. However, particularly regarding the common assumptions of homogeneity of variance and normality, this approach is often inaccurate. In this tutorial paper, we therefore revisit Abbott’s equation and outline an alternative route to analysis via generalized linear mixed models that can satisfactorily deal with these distributional issues. Nine examples from entomology, weed science and phytopathology, each with a different focus and methodological peculiarity, are used to illustrate the framework.

Multi-view heterogeneous graph learning with compressed hypergraph neural networks

Multi-view learning is an emerging field of multi-modal fusion, which involves representing a single instance using multiple heterogeneous features to improve compatibility prediction. However, existing graph-based multi-view learning approaches are implemented on homogeneous assumptions and pairwise relationships, which may not adequately capture the complex interactions among real-world instances. In this paper, we design a compressed hypergraph neural network from the perspective of multi-view heterogeneous graph learning. This approach effectively captures rich multi-view heterogeneous semantic information, incorporating a hypergraph structure that simultaneously enables the exploration of higher-order correlations between samples in multi-view scenarios. Specifically, we introduce efficient hypergraph convolutional networks based on an explainable regularizer-centered optimization framework. Additionally, a low-rank approximation is adopted as hypergraphs to reformat the initial complex multi-view heterogeneous graph. Extensive experiments compared with several advanced node classification methods and multi-view classification methods have demonstrated the feasibility and effectiveness of the proposed method.

Modelling of JP-8 distributed combustion using a HyChem mechanism under gas turbine conditions

The critical advantages of liquid fuels in aviation over alternative energy carriers imply their dominance in the upcoming decades. The Mixture Temperature Controlled (MTC) combustion concept allows spatially homogeneous, efficient burning (distributed combustion) with low pollutant emission. MTC combustion of jet fuel JP-8 was investigated in an atmospheric burner, and the measured pollutant concentrations in the flue gas were reproduced using the Hybrid Chemistry (HyChem) approach employing Perfectly Stirred Reactor simulations. Using this robust approach comes with losing spatiotemporal characteristics if the mixture homogeneity assumption is globally valid. The effect of residence time and pressure under typical gas turbine operating conditions was investigated. Stable combustion was present above 3 ms residence time at pressures up the 60 bar, which was the upper limit of the investigated regime, while the lower residence time limit of stable combustion was 0.3 ms. The residence time interval of stable operation could be extended by applying flue gas recirculation. NO emission can be reduced by increasing the operating pressure, while the N2O production is dominant only up to 20 bar and in the 10–100 ms residence time range. CO emission vanishes above 10 ms residence time. Ultra-low emission operation requires >20 bar pressure and 10 ms residence time with distributed combustion, requiring larger combustion chambers for future jet engines.

Cardiomyopathy Classification System

Cardiomyopathy encompasses various types and refers to a condition affecting the heart muscle, which impairs the organ's normal pumping function. When diagnosing cardiomyopathy, it is crucial to identify the specific type of the disease. This paper outlines the benefits and implications of a new classification system for cardiomyopathy, highlighting its potential to improve diagnosis and treatment, as well as its impact on research and clinical trials. The methodology section details the research design, data collection methods, and sample selection process. The data analysis section explains the techniques used for data processing and statistical analysis. Finally, the evaluation and validation section describes the expert review process and the testing andvalidation methods applied. This research adopts an interpretive paradigm, which emphasizes the importance of individual experience in understanding social realities. The statistical analysis assessed the diagnostic capability of genetic testing across genders using ROC curves, revealing strong performance for both males (AUC=.856, p &lt; .001) and females (AUC=.835, p &lt; .001), surpassing pure chance. A one-way ANOVA test was conducted to examine age differences among four genetic patient groups. The assumption of homogeneity of variance was satisfied, as indicated by Levene's test for equality of variances, F(3,156) = 1.277, p &gt; .05. Significant age differences were found among the groups, F(3,156) = 5.537, p &lt; .005. An evidence-based classification system would enhance diagnostic accuracy, treatment efficacy, and research quality, thereby improving outcomes for patients with cardiomyopathy.