Statistical Assessment Research Articles

Exploration of vitamin D hydroxy metabolites C3 epimers in cardiovascular patients: comparative cross-sectional study

Abstract Background Research on vitamin D deficiency has recently surged in popularity. This issue has been acknowledged as a widespread problem, often called a "pandemic", and approximately 90% of the Polish population suffers from vitamin D deficiency. The 3-epi-25(OH)D2 and 3-epi-25(OH)D3 metabolites are stereoisomers of 25(OH)D2 and 25(OH)D3 metabolites, and they may be accidentally measured when determining 25(OH)D levels and result in overestimating metabolite concentrations. Purpose Our study aims to identify vitamin D hydroxy metabolites (25-hydroxyvitamin D2, 25-hydroxyvitamin D3, and their epimers 3-epi-25-hydroxyvitamin D2 and 3-epi-25-hydroxyvitamin D3) in patients with cardiovascular disease and healthy volunteers. To our knowledge, no similar studies have been conducted on this topic. Method We included 27 adult patients with venous thrombosis (fourteen males and thirteen females, aged 64.11±14.84 years) and 35 healthy volunteers (thirty-three females and two males, aged 36.37±12.29 years). We used our validated UPLC-MS/MS method to measure the concentrations of 25(OH)D2, 25(OH)D3, 3-epi-25(OH)D2, and 3-epi-25(OH)D3. Statistica 13.3 with Plus Kit 3.0 was used for the statistical assessment. Normal variables were represented as mean and standard deviation, and non-normal variables as the median and interquartile range. A P-value < 0.05 was considered statistically significant for all tests. Results Patients had significantly lower levels of epi-25(OH)D2 than the healthy control group (0.6 [0.4] ng/mL vs. 2.2 [1.3-4.3] ng/mL, p = 0.004). Similarly, they exhibited significantly lower levels of %epi-25(OH)D2 (8.6 [6-22.3] % vs. 39.4 [18.5] %, p = 0.035). Females had higher levels of 25(OH)D3 than males (26.5 [16.2-37.9] ng/mL vs. 18.8 [7.5] ng/mL, p = 0.04). They also exhibited higher levels of total 25(OH)D3 (30.3 [15.6] ng/mL vs. 19.4 [7.8] ng/mL, p = 0.016). Higher age (OR 1.12, 95% CI 1.07 to 1.18), being male (OR 17.77, 95% CI 3.54 to 89.3), and lower % 3-epi-25(OH)D2 (OR 0.92, 95% CI 0.84 to 0.998) were univariate predictors for patients with venous thrombosis. Conclusion: Demographic factors within a given population may affect the 25(OH)D3 concentration. The results indicate that vitamin D epimeric metabolites, particularly epi-25(OH)D2, and their percentage were different in patients compared to healthy volunteers. Additional studies involving a larger population are necessary to fully comprehend the relationship between these vitamin D epimeric metabolites and cardiovascular health

Subphenotypes of adult-onset diabetes: Data-driven clustering in the population-based KORA cohort.

A data-driven cluster analysis in a cohort of European individuals with type 2 diabetes (T2D) has previously identified four subgroups based on clinical characteristics. In the current study, we performed a comprehensive statistical assessment to (1) replicate the above-mentioned original clusters; (2) derive de novo T2D subphenotypes in the Kooperative Gesundheitsforschung in der Region Augsburg (KORA) cohort and (3) describe underlying genetic risk and diabetes complications. We used data from n = 301 individuals with T2D from KORA FF4 study (Southern Germany). Original cluster replication was assessed forcing k = 4 clusters using three different hyperparameter combinations. De novo clusters were derived by open k-means analysis. Stability of de novo clusters was assessed by assignment congruence over different variable sets and Jaccard indices. Distribution of polygenic risk scores and diabetes complications in the respective clusters were described as an indication of underlying heterogeneity. Original clusters did not replicate well, indicated by substantially different assignment frequencies and cluster characteristics between the original and current sample. De novo clustering using k = 3 clusters and including high sensitivity C-reactive protein in the variable set showed high stability (all Jaccard indices >0.75). The three de novo clusters (n = 96, n = 172, n = 33, respectively) adequately captured heterogeneity within the sample and showed different distributions of polygenic risk scores and diabetes complications, that is, cluster 1 was characterized by insulin resistance with high neuropathy prevalence, cluster 2 was defined as age-related diabetes and cluster 3 showed highest risk of genetic and obesity-related diabetes. T2D subphenotyping based on its sample's own clinical characteristics leads to stable categorization and adequately reflects T2D heterogeneity.

Research on Statistical Assessment Methods of Stock Investment Value-Taking Education Industry as Example

Abstract: This paper selects the financial statement data of 18 listed companies in the field of education and selects 9 financial indicators from the four aspects of solvency, profitability, development ability and operation ability that can reflect the comprehensive strength of listed companies. Finally, the stocks of 18 listed companies were divided into three categories: high-value stocks, potential stocks and low-value stocks according to the comprehensive strength of the companies. The results show that: (1) From the comparison between the rankings of the selected 18 stocks combined with the traditional methods by combining principal component analysis and entropy weight method, it can be seen that for the comprehensive multi-index evaluation analysis in the past five years, the ranking agreement between the two methods can reach 80% or more. Due to the unstable fluctuations of the stock market, the consistency between the analysis results and investment recommendations obtained in this paper and the actual investment situation of the stock market can also exceed 60%. (2) From the results of cluster analysis, Chuanzhi Education, Entrepreneurship Dark Horse, Guoxin Culture, China Hi-Tech and Action Education are all high-value stocks in the education category, while Meijim, Qinshang Co., Ltd., and Kaiwen Education are potential education stocks.

Differences in elemental abundances between CI chondrites and the solar photosphere

AbstractCI chondrites have been a proxy for the solar system since the mid‐20th century. The photospheric and CI chondrite abundances (P and CI, respectively) show a strong correlation. CI as a proxy is also justified by the (i) smoothness of their abundances plotted as a function of odd mass number and (ii) agreement within the error of P as determined spectroscopically. But our statistical assessment of spectroscopic studies and solar wind from the Genesis mission indicates that the small, ~10%–30%, differences (residuals) between CI and P depend on the 50% condensation temperature (Tc50). So, if CI is to be used as a proxy for P, Cosmochemists may want to add a correction to individual elements. Our work is consistent with two published hypotheses: that (i) residuals are linear with Tc50 and (ii) that elements having Tc50 > 1343 K are depleted relative to those with 495 K < Tc50 < 1343 K in CI. We discuss other interpretations which are also feasible. Understanding these small differences of the CI and P for different elements and their variation with Tc50 can help constrain future models of solar system formation and the history of CI chondrites.

Diagnostic Approaches of Palatogingival Groove: A Systematic Review

Palatogingival Grooves (PGG) constitute developmental anatomical irregularities primarily situated along the palatal aspects of the roots of maxillary incisors. Literature is sparse on diagnostic approaches of PGG. Our study aimed to alleviate clinicians the process of recognizing anomaly. Systematic electronic searches of scientific literature without publication date or language restriction were undertaken in 2023.11.03 research was conducted in PubMed, Willey Online Library, Science Direct and Medline Ovid. Using specific keywords 54 articles with 67 cases were included in our study according to inclusion and exclusion criteria. Pre-made Cochrane data extraction templates were used for frequency evaluation, nonparametric Spearman’s, Kendall rank correlation coefficients, Mann-Whitney U Test and Odds ratio was assessed by statistic to evaluate significant correlations. Most quantitively expressed symptoms of PGG included increased tooth mobility, appearance of purulent discharge, sinus tract and periodontal pocket with an average mean of 9,14 ± 2,30 mm along with painful vertical per-cussion. However, statistical assessment showed inverse correlation between in-creased mobility and painful percussion. Furthermore, quantitively, deeper perio-dontal pockets were accompanied by more prominent gingival alterations, however only one opposing significant correlation was noted between the depth of per-iodontal pocket and existence of additional root. Frequency evaluation revealed that IPR was the main diagnostic tool used in majority of cases. Deeper periodontal pocket was assessed by conjunction of two or three tools. CBCT was used most with deeper periodontal pocket averaging 9,75 ± 1,02 mm. In conclusion, quantita-tive data suggest that periodontal pockets averaging 9,14 ± 2,30 mm, I or II-degree mobility, painful percussion and purulent discharge are the main PGG characteristics, with sparce significant correlations between them. IPR was noted as the main roentgenological modality as should be used firstly when suspecting PGG, yet both quantitative and statistical data suggest that CBCT is ought to be used to alleviate the assessment.

Analysis of long-term MSW settlement based on field data measured at two closed landfills

Waste settlement characteristics vary depending on waste composition, physical properties, waste management operations, and time. In this study, the post-closure waste settlement behavior was analyzed using field data measured at two closed municipal solid waste landfills in Korea, for 23 and 5 years after landfill closure. The long-term waste settlement data was analyzed to derive a time-varying long-term compression ratio (CLT) that was consistent with modeled biodegradation processes. A statistical assessment of the field data was conducted to examine the relationship between CLT and several factors that may affect the observed settlements. The CLT of Landfill #1 and #2 was found to vary between the two landfills that had differences in the percentage of organic matter (B0), total unit weight (γwaste), and moisture content (w) due to changes in waste management policies.

Statistical assessment for reusing permeate from dewatering water treatment sludge process: more sustainability in environmental sanitation.

Sludge from water treatment plants (WTPs) is usually processed by physicochemical clarification followed by thickening, which results in the production of an effluent from dewatering/drying sludge processes that can potentially impact the environment. This paper assessed the viability of employing sludge dewatering water from a water treatment sludge plant (WTSP) in São Paulo State, Brazil, for reuse purposes. Water quality variables were monitored in the effluent and receiving stream. The data were analyzed by paired samples Student t-test (parametric significance test), paired samples Wilcoxon signed rank test (non-parametric significance test), and principal component analysis (multivariate analysis). Despite the distribution of data, typically not Gaussian, both Student and Wilcoxon methods agreed in 9 out of 10 studied parameters regarding the influence of WTSP discharge on waterbody; only for total manganese the Wilcoxon approach provided better fit than Student. Principal component analysis helped to evince correlations among all variables. Results provided useful information for understanding the vocation of WTSP effluent for reuse. For direct non-potable reuse, recirculating the final effluent back to the WTP for two months saved 92,000 m3 of water, the volume of drinking water demanded by the city (n = 292,000 inhabitants) in approximately 30h.

An Effective DNA Methylation Biomarker Screening Mechanism for Amyotrophic Lateral Sclerosis (ALS) Based on Comorbidities and Gene Function Analysis.

This study used epigenomic methylation differential expression analysis to identify primary biomarkers in patients with amyotrophic lateral sclerosis (ALS). We combined electronic medical record datasets from MIMIC-IV (United States) and NHIRD (Taiwan) to explore ALS comorbidities in depth and discover any comorbidity-related biomarkers. We also applied word2vec to these two clinical diagnostic medical databases to measure similarities between ALS and other similar diseases and evaluated the statistical assessment of the odds ratio to discover significant comorbidities for ALS subjects. Important and representative DNA methylation biomarker candidates could be effectively selected by cross-comparing similar diseases to ALS, comorbidity-related genes, and differentially expressed methylation loci for ALS subjects. The screened epigenomic and comorbidity-related biomarkers were clustered based on their genetic functions. The candidate DNA methylation biomarkers associated with ALS were comprehensively discovered. Gene ontology annotations were then applied to analyze and cluster the candidate biomarkers into three different groups based on gene function annotations. The results showed that a potential testing kit for ALS detection can be composed of SOD3, CACNA1H, and ERBB4 for effective early screening of ALS using blood samples. By developing an effective DNA methylation biomarker screening mechanism, early detection and prophylactic treatment of high-risk ALS patients can be achieved.

Statistical assessment of Indian classical music’s role in diabetes, thyroid, hypertension management

Statistical assessment of Indian classical music’s role in diabetes, thyroid, hypertension management

Statistical assessment of the inner shape of a channel based on laser speckle contrast imaging

In this work, we employed laser speckle contrast imaging coupled with the analysis of several statistical moments on the recorded images to recognize the shape of an object through the analysis of the pattern of a flow around it. We postulated that a flow through different geometries would generate a unique flow structure and thus the mathematical analysis of the differences can be utilized to detect and recognize various shape geometries. To this aim, the flow of scattered liquid that had passed through objects of different shapes was illuminated by a laser beam and the diffused speckle image was recorded by a camera. In the computer, the captured speckle image was first converted to a flow image and then mathematically analyzed to recognize the shape of the objects. Three out of the eight statistical metrics were found to be the best candidates for the recognition of shapes, thus proving our hypothesis.

Characteristics of gait function in hemiparetic patients with subacute period of ischemic stroke: a single-center retrospective study

BACKGROUND: Gait disorders are common among 80% of stroke patients. Its consequences include increased risk of falls and functional limitations, which can significantly reduce the quality of life. AIM: To investigate the functional profile of hemiparesis resulting from subacute ischemic stroke. MATERIALS AND METHODS: This observational, retrospective, one-stage, single-center study analyzed primary biomechanical gait parameters in 31 patients and 34 healthy controls. Spatial, temporal, kinematic, and electromyographic characteristics were recorded. A statistical assessment and inter-group and intra-group comparison of the collected data were performed to identify the pathognomonic features of hemiplegic gait in patients with subacute stroke. RESULTS: Changes in gait biomechanics typical for hemiparetic patients who have suffered from ischemic stroke were described: slight asymmetry of step cycle, normal duration of support period on the paretic side, significant increase in duration of support period on the healthy side, and shortening of single support period on the paretic side. Additionally, the asymmetry of the walking function was characterized by changes in reciprocity, that is, a harmonious sequence of step cycles. The function of the hip and knee joints was reduced and altered, and the amplitude of the ankle joint was increased. Decrease and change in the bioelectric activity profile of muscles were detected. Moreover, the quadriceps femoris function was least affected. CONCLUSION: The main changes in walking function are characterized by an asymmetry of spatiotemporal parameters, a decrease in movement amplitudes of the hip and knee joints on the paretic side, an increase in ankle joint amplitude, a decrease in the bioelectric activity of muscles, and a shift in the phases of their activity. The results contribute to a better understanding of the mechanisms behind hemiplegic gait and provide a valuable tool for developing more personalized and targeted rehabilitation plans for patients suffering from hemiparesis as a result of subacute ischemic stroke.

7637 Characteristics of Thyroid Nodules Among Adolescents and Adults in Medina, Saudi Arabia

Abstract Disclosure: R. Alradadi: None. M. Sindi: None. O. Alrehaili: None. S. Alanazi: None. S. Alahmadi: None. F. Mansuri: None. A. Zain: None. Background: Thyroid Nodules are common clinical finding, with a prevalence of about 20% in young adults and around 70% in the elderly population. A significant increase in the incidence rate of Thyroid Cancer in our population has been noted, over the past 30 years. The aim of the study is to define the characteristics of Thyroid Nodules in adolescents and adults in our region compared to what published worldwide. Method: A retrospective chart review, conducted at our Health Institution. The study included adolescents and adult who had Thyroid Nodules and was seen in the outpatient endocrine clinic in the period between 2018 and 2022, using non-probability consecutive sampling. Patient medical records provided demographic, medical, and laboratory data, and the analysis employed SPSS for statistical assessment​​. Data collection conducted from October through December of 2023 Result: Out of the total sample of 552 patients, there were 84.8% females. More than half of the patients (55.9%) were between 36-55 years of age. 57.4% of patients were overweight or obese. 56.4% presented with goiter. FT3, FT4 and TSH levels were normal among 88.4%, 78% and 83.3% respectively. Anti TPO antibodies were reported in 14.2% as compared to thyroglobulin antibodies in 2.2%.Follicular neoplasm/suspected neoplasm was detected among 8.15% of the sample. Papillary thyroid carcinoma [27/41] was the most frequent finding with positive FNA. Multiple nodules were more prevalent 38.8% as compared to solitary nodules in 34.1%. The right sided nodules were mostly solid 49.2% while hypervascularity was noted in 9.1% and51.4% were of more than 1.5cm. In contrast, left lobe nodule 37% were found to be solid and 6.2% showed hypervascularity and size was more than 1.5cm in 45% of the left nodules Conclusion: The vast majority of adults and adolescents with thyroid nodule were female as expected based on what reported from previous studies. Preexisting Thyroid Diseases present in only small number of patients 15.4 %. Anti-TPO antibody was more predominant than Thyroglobulin Antibody. Follicular neoplasm/suspected neoplasm was detected among 8.15% of the sample. Papillary thyroid carcinoma was the most frequent finding among the positive FNA results. Presentation: 6/3/2024

Predictive modeling of sustainable recycled materials for stone column construction

Climate change due to carbon dioxide emissions is one of the most significant global challenges. Sustainable recycled materials are recognized as a critical factor in mitigating climate change, representing a fundamental strategy for reducing gas emissions and preserving the environment. Promising sustainable recycled materials in construction, such as crushed asphalt, crushed concrete, crushed ceramic, and treated concrete offer numerous advantages, including reduced carbon dioxide (CO2)\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$${\ ext{(CO}}_{2} )$$\\end{document} emissions, cost-effectiveness, increased strength, and enhanced mechanical properties. In this study, various machine learning techniques, including the support vector machine (SVM), multiple linear regression (MLR), gaussian process regression (GPR), and artificial neural network (ANN), are used to assess the effectiveness of sustainable recycled materials within stone columns. The MLR model was specifically utilized to predict the ultimate stress equation for these materials within stone columns. Forty-five constructed samples were used in developing the models. The effectiveness of each model was evaluated using various statistical assessment measures, including mean absolute error (MAE), absolute fraction of variation (R2\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$${\ ext{R}}^{2}$$\\end{document}), and root mean square error (RMSE). The predictive model’s performance was validated using the k-fold cross-validation method. The ANN model with an R2\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$${\ ext{R}}^{2}$$\\end{document} value of 0.962 and an RMSE value of 7.268 kPa, performed better compared to GPR, SVM and MLR models. In summary, the results of the study indicate that the MLR model, utilizing the identified input parameters, can accurately predict the ultimate stress for different sustainable recycled materials. Implementing such technologies within the construction sector can expedite and reduce the cost of assessing material characteristics and the influence of input parameters.

Assessment, analysis and optimization for high temperature sliding wear process parameter with additive built nickel base superalloy

Abstract Superalloys are highly demanding alloy for high temperature application. The conventional production process and metallurgical sustainability of the superalloy against the applications is the preamble of the existing research. Based on the review it is clear to say that the development of nickel base superalloy with advanced technique without compensating the quality is open for research. The nickel base superalloy is developed through additive manufacturing process following a metal laser sintering technique. The developed alloy is used to perform high temperature sliding wear analysis with the different input process conditions. Applied load, sliding duration and the working temperature are the defined process environment for the investigation. The process conditions are designed with twenty-seven set of experimental trials for statistical analysis and process assessment. The responses on surface roughness and the material loss with respect to the input process parameters are technically assessed and justifications made with the electron microscopic images. The surface topography has influenced due to applied load and the sliding duration. Applied load has influenced the contact area prone with severe wear and the ridges are notice from the microscopic analysis. The statistical analysis has proved that the influence of temperature is less and negotiable compared to the load and time factor. From the optimization process, the optimal parameter for the experimental design is 10 N, 100 °C and 30 min is the ultimate condition to produce best results from the high temperature sliding wear analysis.

Evaluation of the Buffer Capacity of Soils for Copper and Statistical Assessment of the Contributions of Its Components

Evaluation of the Buffer Capacity of Soils for Copper and Statistical Assessment of the Contributions of Its Components

Supermassive black hole formation via collisions in black hole clusters

More than 300 supermassive black holes have been detected at redshifts larger than six, and they are abundant in the centers of local galaxies. Their formation mechanisms, however, are still rather unconstrained. A possible origin of these supermassive black holes could be mergers in dense black hole clusters, forming as a result of mass segregation within nuclear star clusters at the center of galaxies. In this study, we present the first systematic investigation of the evolution of such black hole clusters in which the effect of an external potential is taken into account. Such a potential could be the result of gas inflows into the central region; for example, as a result of galaxy mergers. We show here that the efficiency of the formation of a massive central object is mostly regulated by the ratio of cluster velocity dispersion divided by the speed of light, potentially reaching efficiencies of 0.05–0.08 in realistic systems. Our results show that this scenario is potentially feasible and may provide black hole seeds of at least 103 M⊙. We conclude that the formation of seed black holes via this channel should be taken into account in statistical assessments of the black hole population.

Lip and incisor changes in patients with different ethnicities treated with extraction versus nonextraction: A cone-beam computed tomography study

This study used cone-beam computed tomography (CBCT) via voxel-based superimposition to evaluate lip and incisor changes after orthodontic treatment with four premolar extractions (Ext) versus nonextraction (Non-Ext) among African American (AA) and White (W) patients. A total of 240 CBCTs of 120 adolescent orthodontic patients with Class I skeletal/dental relationships were included. Patients were initially divided according to treatment, and then each group was subdivided according to patients' ethnicity (Ext/W = 30, Ext/AA = 30, Non-Ext/W = 30, and Non-Ext/AA = 30). CBCTs were imported into Invivo6 for voxel-based superimposition. Lip and incisor measurements were recorded. Independent t tests and two-way ANOVA were used for statistical assessment. The Non-Ext/W group had a greater increase in all outcome variables compared with the Non-Ext/AA group, with a significant change in volume and position of upper (UL) and lower lips (LL), inclination of upper (U1) and lower incisors (L1), and position of U1. The Ext/AA group had a greater decrease in all measured outcomes compared with the Ext/W group, with significant change in inclination of U1 and L1, and position and volume of LL. W patients had more crowding than AA patients in both treatment approaches. Retraction ratios of 6.5:1 and 2.1:1 were recorded between the U1 and UL positions, and L1 and LL positions, respectively. There were no direct interaction effects between ethnicity and treatment, nor were there any significant effects of ethnicity after controlling for the covariates. Ethnicity alone has no impact on incisor and lip position after treatment. However, ethnicity in the form of initial presentation of malocclusion can have a significant influence.

Analysis of Labor Absorption in the Dodol Industry in Suranadi Village, Narmada District, West Lombok Regency

This research aims to analyze the application of labor in the dodol industry in Suranadi Village, Narmada District, West Lombok Regency. Data comes from 13 respondents who are owners of the dodol industry with the data collection method used is the census method and questionnaire distribution techniques as data collection tools. The analytical instrument employed is multiple linear regression, accompanied by the classical assumption tests, which encompass three evaluations: the normality test, multicollinearity test, and heteroscedasticity test, as well as the statistical assessment known as the simultaneous test (F test). partial test (t-test) and coefficient of determination. The research results show that the production value and capital wage variables have a significant value of 0.000 <0 05, which means they are simultaneous. has a significant influence on labor absorption. Individually, the wage variable has a significant value of 0.043 < 0.05. the production value variable is 0.040 < .05, and the capital variable is 0.043 < 0.05, which means that partially the wages, production value and capital variables have a significant influence on the application of labor force.

Statistical assessment of direct investment (equity capital instruments) in the economy of the Dnipropetrovsk area

Introduction. The statistics above prove that the Dnipropetrovsk area in terms of the volume of attracted foreign direct investment is confidently ranked 1st among the regions of Ukraine in 2024. The purpose of the paper is to build a model of statistical assessment of direct investment (tools of participation in capital) in the economy of Dnipropetrovsk area. Results. The shortcomings that create significant problems of formation of information and analytical support of existing models of analysis of investment cooperation between countries are identified. Adaptive forecasting based on the method of exponential smoothing. The essence of this method is that each element (level) of the time row is smoothed with a weighted average, and its weight decreases as the end of the row is removed. The forecast of direct investment (instruments of participation in capital) of EU countries in the economy of Dnipropetrovsk area by 2028 was built. Based on statistical analysis for the period 2015-2023. The forecast of direct investment (instruments of participation in capital, by types of economic activity) of EU countries in the economy of Dnipropetrovsk area by 2028. On the basis of statistical analysis for the period 2021-2023. It is emphasized that in 2021. Three industries (education (P); art, sports, entertainment and rest (R); providing other services (S)) are not made public in order to ensure compliance with the requirements of the Law of Ukraine "On Official Statistics" on the confidentiality of statistical information. Conclusion. According to the analysis, six key consequences and risks of war in Ukraine are separated when attracting foreign direct investment. As a prospect of further research in the subject area is to build a gravitational model of direct investment relationship between the economy of Dnipropetrovsk area and EU countries, for example by the following factors: GDP per capita of the country; geographical distance between Ukraine and donor countries; The population of the country. This will identify problematic issues in forming a foreign investment stimulating policy. The possibility of constructing a gravity model of foreign direct investment for Dnipropetrovsk area has been grown.

Stacked generalization ensemble learning strategy for multivariate prediction of delamination and maximum thrust force in composite drilling

The complexity of drilling carbon fiber reinforced polymers (CFRP) requires accurate predictive models. This study addresses the challenge using an ensemble machine learning (ML) approach with stacked generalization. The model captures the relationships between key input variables—such as graphene nanoplatelet (GNP) content, ultrasonic assistance, tool type, stacking sequence, and feed rate—and output parameters, specifically thrust force and delamination. A nested feature scoring (NFS) method was employed for importance analysis, revealing tooling type and feed rate as key features for minimizing delamination and reducing thrust force, respectively. The machinability results revealed that ultrasonic drilling lowered thrust force by improving chip evacuation and reducing fiber breakage. HSS tools with cobalt content, alongside symmetrical stacking sequence, helped to further minimize both thrust force and delamination. However, the inclusion of GNPs led to an increase in thrust force and delamination, attributed to the increased strength of the CFRP/GNP composite. The process involved meticulous training, resulting in four optimal-fit models serving as inputs for the stacked meta-model. Iterative enhancements fortified the ensemble robustness, with fine-tuning of hyperparameters through Bayesian optimization. The ensemble superiority over individual models manifested in a remarkable reduction of mean absolute error (MAE) and root mean squared error (RMSE) by up to 97% and 124% for delamination, and 205% and 154% for thrust force, compared to the best base learner. Visual and statistical assessments effectively illuminated the intricate interactions between variables in the drilling process. The methodology resulted in a highly adaptable predictive model with applications across diverse manufacturing contexts.