Kolmogorov-Smirnov Research Articles

Construction 4.0: enhancing sustainable construction practices by evaluating digital twin barriers in the Nigerian AEC industry

PurposeThe architecture, engineering and construction (AEC) industry is currently undergoing a paradigm shift as it integrates innovations such as digital twins (DT) in its activities. As a result, this study aims to ascertain the barriers affecting the implementation of digital twin (DT) technology in Nigeria’s AEC sector.Design/methodology/approachThe study employed a quantitative approach using a questionnaire distributed via Google Forms, yielding 120 valid responses from built environment professionals in Nigeria. The data were subjected to statistical tests such as the Kolmogorov–Smirnov test, Cronbach’s alpha, descriptive statistics and the Kruskal–Wallis test. Hypotheses were validated through partial least squares structural equation modelling (PLS-SEM).FindingsThe study revealed that out of the 43 identified barriers, inadequate system integration, challenges in guaranteeing interoperability, university education on the subject is deficient, and new system compatibility with legacy systems are the main barriers to implementing DT for sustainable construction practices in the AEC Industry of Nigeria.Research limitations/implicationsThe study was conducted in Nigeria with a focus on the Federal Capital Territory. The study identified the barriers of DT in the construction sector.Practical implicationsThis study developed and assessed a theoretical framework, examining the relationships between variables. The findings have important implications for the construction industry, offering opportunities to improve construction processes. Furthermore, the study will help improve sustainable practices within the built environment.Originality/valueThe study categorised the barriers of DT into the following: system integration; security-related; performance-related; organizational-related; data quality issues and environmental related issues.

Пилотное исследование самооценки педагогами-психологами условий и дефицитов своей профессиональной деятельности в инклюзивной школе

<p>The purpose of the pilot study was to identify problems, deficits and conditions for ensuring the readiness of educational psychologists for effective professional activities in psychological support of students with special educational needs and normatively developing children in an inclusive school. The research methods were self-assessment tools for readiness and ability for psychological and pedagogical support in inclusive education, developed on the basis of competency-based and activity-based approaches, which included 4 questionnaires: attitude towards inclusion, intention to implement inclusive practices, reflection of difficulties and self-efficacy in implementing inclusive practitioner The total sample size was 89 respondents, who were educational psychologists from inclusive schools with higher education from 5 regions of the Russian Federation. Responses to the questionnaire were collected remotely through the ‘Anketolog’ system. Descriptive statistics for the questionnaires (M±SD) were performed, the distribution of answers to the questionnaires was checked for normality using the Kolmogorov-Smirnov test and correlation analysis was carried out using Spearman. Based on the average scores for the answers, the rating of answers on the “Effectiveness” and “Difficulties” questionnaires was determined. Analysis of the results of responses to the statements of the questionnaires showed a moderate positive correlation between all questionnaires, except for the Difficulties Questionnaire, where there was a negative correlation, which corresponds to the results of previously conducted studies on similar questionnaires. Almost all respondents have a positive attitude towards inclusion and a positive self-assessment of their readiness and ability to implement psychological and pedagogical support for students with special educational needs. The attitude of educational psychologists to the difficulties of implementing inclusion in school, expressed by a value of 2.714, corresponds to the prevailing choice of answers on a Likert scale between “Undecided” (3 points) and “Rather disagree” (2 points), which mainly reflects respondents’ disagreement with the presence of difficulties in their work, including disagreement with the lack of support from school administrators. Thus, in conditions of support from schools, educational psychologists show a positive attitude towards inclusion and evaluate their effectiveness in supporting students at a high level.</p>

Effects of Different Crystallization Protocols on Marginal Gap of Lithium Disilicate Single Crowns: SEM Analysis

Objective: In everyday dentistry, lithium disilicate is a valid option for single-fix partial dentures, and this material crystallization process is available with two protocols: long and short. This study’s aim was to assess the effects of these two different crystallization protocols, long and short, on the marginal gap of lithium disilicate single crowns. Methods: A total of 24 abutment plastic teeth were scanned using an intra-oral scanner. For each plastic tooth, an identical pair of lithium disilicate crowns was milled (a total of 48 crowns) by a four-axis machine. Each paired sample was categorized into two groups: long crystallization (24 crowns) and short crystallization (24 crowns). To assess precision, each unit’s marginal gap (including abutments and crowns) was meticulously measured at four specified regions using a scanning electron microscope. A Kolmogorov–Smirnov test performed on the study variables indicated a normal distribution (p > 0.05), and it was followed by independent t-tests (α = 0.05). Results: For the long crystallization group, the mean total marginal gap values were 42.91 ± 9.67 μm, and for the short crystallization group, the values were 43.25 ± 8.14 μm, with no significant difference between the groups (p = 0.894). In addition, no significant differences were found between the groups regarding the mean marginal gap measurements for all four surfaces (distal (p = 0.310), mesial (p = 0.732), palatal (p = 0.655), and buccal (p = 0.535)). Conclusions: Both the long and short crystallization methods used for lithium disilicate single crowns demonstrated marginal gap values of less than 120 μm, which are within the clinically acceptable range, with no significant differences across any parameters between the two groups. Regarding the marginal gap value, it is recommended to use the short crystallization protocol as it is more time-efficient.

The Effect of Acupressure on Pain Associated with Chest Tube Removal in Patients with Chest Trauma

Background: Inserting a chest tube is a life-saving procedure for patients with chest trauma, but it is often associated with significant pain. To alleviate this discomfort, non-pharmacological methods such as acupressure can be employed. Therefore, this study aimed to determine the effect of acupressure on pain during chest tube removal in patients with thoracic trauma. Methods: This quasi-experimental study involved the selection of 204 patients with chest tubes following chest trauma in Zahedan in 2022. The through patients were selected purposefully and Non-random allocation divided into two intervention and control groups of 102 people. The intervention group received acupressure treatment, while the control group did not. Pain levels of the patients were measured using a pain intensity scale on both the day of chest tube insertion and the day of removal. The data were analyzed using statistical test such as independent-t, paired-t and chi-square statistical tests within the SPSS 26 software. Results: The normality of the main variable was assessed using the Kolmogorov-Smirnov (KS) test. The significance level for the pain variable was found to be less than 0.05 (P<0.001), indicating a non-normal distribution. Therefore, the Mann-Whitney U test was utilized for data analysis. The results of the Mann-Whitney test revealed that before the intervention, the mean pain scores were 9.46±0.69 in the intervention group and 9.47±0.65 in the control group. After the intervention, the mean pain scores were 7.11±0.98 in the intervention group and 9.39±0.90 in the control group. Based on the Mann-Whitney U value obtained from the comparison of the two groups before and after the intervention, it can be concluded that the intervention had a significant effect on reducing pain (Table 2). Conclusion: The insertion and removal of chest tube after trauma can be an extremely painful experiences for individuals. Considering the crucial role of nurses, non-pharmacological methods such as acupressure can be used to alleviate their pain. Acupressure is a cost-effective, accessible, and readily available approach that can be utilized in this context.

Graph-Variational Convolutional Autoencoder-Based Fault Detection and Diagnosis for Photovoltaic Arrays

Solar energy is a critical renewable energy source, with solar arrays or photovoltaic systems widely used to convert solar energy into electrical energy. However, solar array systems can develop faults and may exhibit poor performance. Diagnosing and resolving faults within these systems promptly is crucial to ensure reliability and efficiency in energy generation. Autoencoders and their variants have gained popularity in recent studies for detecting and diagnosing faults in solar arrays. However, traditional autoencoder models often struggle to capture the spatial and temporal relationships present in photovoltaic sensor data. This paper introduces a deep learning model that combines a graph convolutional network with a variational autoencoder to diagnose faults in solar arrays. The graph convolutional network effectively learns from spatial and temporal sensor data, significantly improving fault detection performance. We evaluated the proposed deep learning model on a recently published solar array dataset for an integrated power probability table mode. The experimental results show that the model achieves a fault detection rate exceeding 95% and outperforms the conventional autoencoder models. We also identified faulty components by analyzing the model’s reconstruction error for each feature, and we validated the analysis through the Kolmogorov–Smirnov test and noise injection techniques.

Improvement of contact lens-associated dry eye disease with the use of hydrogen peroxide.

The dropout rate of contact lens users has not decreased significantly over the years. Despite continuous improvements in contact lens (CL) designs, materials and surface treatments, the number of CL users who drop out remains similar to the number of new CL users. The aim of this study is to analyse the improvement in contact lens-associated dry eye disease (CLADE), quantified with the OSDI questionnaire when changing maintenance system solution from multipurpose solution to hydrogen peroxide. This study included contact lens users for over a year as the multipurpose solution for the maintenance system, suffering from CLADE, and those who scored over 13 in the ocular surface disease index questionnaire, and did not manifest any clinical signs over 3 in the EFRON scale. The non-parametric data distribution was verified with the Kolmogorov-Smirnov test and Wilcoxon signed-rank test, which was used to compare the visual acuity (VA), OSDI score and bulbar redness (EFRON scale) of the follow-up visit against the baseline value. Thirty-eight patients were included. Analysing the clinical parameters between the initial and final visit after one month of hydrogen peroxide use, a statistically significant improvement was found in the VA, bulbar hyperemia, OSDI scale and their subscales of the total sample (P<0.04). This study is intended as a first step towards a standardised protocol of actions to improve CLADE in an attempt to reduce contact lens dropout using OSDI as a tool for detection.

Predicting Diameter Distributions in Mixed Forests in Southern Mexico

Understanding the diameter structure of a stand is crucial for making informed decisions regarding silviculture and forest management. This is achieved by collecting forest inventory data and applying them to probability density functions. The objective of this study was to identify the optimal probability density function for describing the diameter distribution in a mixed temperate forest in Oaxaca, Mexico. Circular sampling plots of 1000 m² were established, and the diameter at breast height (DBH) and total height of 16,863 trees of the 25 most important timber species were measured. Four probability density functions (Weibull 2P, Log-Normal, Log-Logistic, and Burr) were fitted by using maximum likelihood approach for different silvicultural treatments. The predictive ability of the functions was evaluated using bias, root mean square error, Kolmogorov-Smirnov statistic and graphical analyses. In terms of accuracy and parsimony, the Burr function demonstrated the best performance, followed by the Log-Normal and Log-Logistic functions. Consequently, the Burr function is recommended for modeling the diameter distribution of stands under different treatments in the study site.

Modified Half-Cauchy Chen (MHCC) Distribution with Applications to Lifetime Dataset

In this article, we have recommended an innovative versatile distribution called Modified Half-Cauchy Chen distribution by modifying half-Cauchy Chen distribution. The recommended distribution's various properties are derived and analyzed. The recommended distribution's parameters are ascertained by applying the maximum likelihood estimation (MLE) approach. Furthermore, the performance of the Modified Half-Cauchy Chen distribution is compared against other distributions using various statistical measures. These measures consist of the Corrected Akaike Information Criterion (CAIC), the Kolmogorov-Smirnov (K-S) test, the Bayesian Information Criterion (BIC), and the Akaike Information Criterion (AIC). The results consistently demonstrate the superior fit of the Modified Half-Cauchy Chen distribution to the data. The goodness-of-fit analysis is carried out on a real data set in order to evaluate the innovative distribution's applicability. The Modified half-Cauchy Chen distribution is shown to perform better than a few other known distributions. R programming software is used to help with every computation.

The Influence Of Spiritual Emotional Freedom Technique On Cortisol Levels in Ischaemic Stroke Patients

Background: Ischaemic stroke patients experience an increase in cortisol of 38% over 90 days. The spiritual emotional freedom technique (SEFT) provides manual stimulation of acupuncture points, which makes the muscles feel relaxed so that they can control cortisol. This study set out to assess how SEFT affected the cortisol levels in patients who had suffered an ischaemic stroke. Methods: A control group and pre- and post-test measures were part of the quasi-experimental research design. There were seventy-one patients in the research population of the study. The sample was measured using the Slovin formula, and the sampling strategy used was purposeful sampling. Over the course of three months, the intervention group had 12 sessions of SEFT once a week, whereas the control group received regular spiritual treatment from RSUD Dr. Moewardi Surakarta, an outpatient nurse. The ELISA method was used to measure cortisol levels. The Kolmogorov-Smirnov test was used to assess normality, and the Levene test was used to test for homogeneity in bivariate data. The Mann-Whitney method was used to analyze the data. Results: The mean cortisol before intervention was 119.63, and the mean cortisol after intervention was 99.23. SEFT affects cortisol levels in patients who have had an ischaemic stroke, according to a statistically significant (p&lt;0.05) p-value of zero. Conclusion: Patients with ischaemic stroke experienced a significant drop in cortisol levels after using the SEFT. Furthermore, it is necessary to study the dominant factors that influence the cortisol hormone and the need for a multi-religious approach in an effort to develop spiritual-based interventions.

The effectiveness of android-based application for adolescents in estimating food portion size

Gadgets are now an important part of daily activities, including among adolescents. This technology allows effective information sharing, making it an alternative to nutrition education. Nutrition education regarding portion size is expected to change adolescents’ feeding behavior. The use of conventional media such as food models and leaflets (paperbased media) suffer from many weaknesses in terms of size, weight, price and practicality. This study compared the effects of an android-based application “GIZIKU (My Nutrition)” to the one on the food model and leaflet on adolescents’ ability to estimate the portion. There were 64 adolescents with normal body-mass index from 5 junior high schools who participated in this intervention. Their skills in estimating the portion size (in portion estimation ratio/PER) were measured two months after being given the education using the application and food model. The Kolmogorov-Smirnov test was then applied to compare the two groups. In general, no difference was found in the portion estimation ratio between the groups (p = 0.83). Most of the respondents (75.3%) showed a tendency to overestimate the portion size of food served to them. The absence of a gap between the groups indicated that the use of “The GIZIKU” application (and may apply to other electronic-based delivery modes) can be a feasible alternative for more effective, affordable and practical nutrition education.

A Dynamic Algorithm for Measuring Pedestrian Congestion and Safety in Urban Alleyways

This study presents an algorithm for measuring Pedestrian Congestion and Safety on alleyways, wherein pedestrians and vehicles share limited space, making traditional pedestrian density metrics inadequate. The primary objective is to provide a more accurate assessment of congestion and safety in these shared spaces by incorporating both pedestrian and vehicle interactions, unlike traditional methods that focus solely on pedestrians, regardless of road type. Pedestrian Congestion was calculated using Time to Collision (TTC)-based safety occupation areas, while Pedestrian Safety was assessed by accounting for both physical and psychological safety through proxemics, which measures personal space violations. The algorithm dynamically adapts to changing vehicle and pedestrian movements, providing a more accurate assessment of congestion compared to existing methods. Statistical validation through t-tests and K-S (Kolmogorov–Smirnov) tests confirmed significant differences between the proposed method and traditional pedestrian density metrics, while Bland–Altman analysis demonstrated agreement between the two methods. The experimental results reveal that Pedestrian Congestion and Safety varied with time and location, capturing the spatio-temporal characteristics of alleyways. Visual comparisons of Pedestrian Congestion, Safety, and Density further validated that the proposed algorithm provides a more accurate reflection of real-world conditions compared to traditional pedestrian density metrics. These findings highlight the algorithm’s ability to measure real-time changes in congestion and safety, incorporate psychological discomfort into safety calculations, and offer a comprehensive analysis by considering both pedestrian and vehicle interactions.

Knowledge and Attitude of Emergency department Nurses about Care of Self-Harming Adolescents and Related Factors: A Cross Sectional Study

Introduction: Self-harm is a hidden health issue and an emergency priority that is relatively common among adolescents. The standard level of service management for self-harming patients is directly related to the knowledge and attitude of nurses when providing care to self-harming patients. Objective: This study aimed to determine the knowledge and attitude of nurses regarding the care of self-harming adolescents and related factors among emergency nurses. Methods: This analytical cross-sectional study involved 208 nurses with over 6 months of work experience in the emergency departments of educational hospital in Rasht, Iran. The nurses were included through census sampling. The data collection tool was a three-part questionnaire including demographic information, the Attitudes Towards Deliberate Self-Harm Questionnaire (ADSHQ), and knowledge. Data were analyzed using the Kolmogorov-Smirnov and Shapiro-Wilk tests, multiple linear regression, the Friedman test, and Spearman’s correlation coefficient. Results: Based on results the mean age of the participants was 34.8 ± 7.8 years and the majority of them (90.9%) were female and had bachelor’s degree (88.5%). The mean score of nurses’ knowledge was 0.67 ± 0.12. Nurses’ attitudes were positively evaluated with a mean score of 3.59 ± 0.28. Additionally, the attitude score had a positive correlation with the knowledge (r=0.252,p=0.001,). The knowledge score was significantly associated with nurses’ marital status (P= 0.042) and experience in caring for self-harming adolescents (P=0.016), Based on findings of multiple linear regression analysis, attitude score was significantly associated with nurses’ age (β=0.184, 95% CI; 0.061- 0.323, p=0.004) and experience in caring for self-harming adolescents (β=2.495% CI; 0.340 - 4.595, , p=0.023). Conclusion: Based on results, it is recommended to employ more experienced nurses in emergency departments to deal with these adolescents. Furthermore, it is necessary to develop orientation and retraining programs to familiarize nurses and strengthen positive attitudes, focusing on increasing empathy and self-confidence for effective care.

Autocorrelation maps for optimal setting in cardiac resynchronization therapy

Background and ObjectivePatients with chronic heart failure are treated with implanted devices artificially stimulating the ventricular myocardium to support the ventricular activation propagation dynamics. The criterion for stimulation/pacing timing is a shortening of the QRS duration in the ECG signal. The study suggests additional ECG parameters that could be helpful in cardiac resynchronization therapy (CRT) device pacing settings. MethodsThis issue was approached by computing and evaluating autocorrelation maps derived from body surface potential maps during the QRS complex. The autocorrelation maps were calculated from the body surface potential maps of seventeen patients, fourteen of whom were diagnosed with the left bundle branch block (LBBB) and three with the right bundle branch block (RBBB). Eleven of the LBBB patients were responders, and all three RBBB patients and three LBBB patient were non-responders. The body surface potential maps were measured during their spontaneous heart rhythm and optimal CRT setting. The patients’ autocorrelation maps were compared with the autocorrelation maps of a control group of 33 healthy persons using two-sample Kolmogorov-Smirnov and Wilcoxon rank-sum statistical tests. ResultsThe autocorrelation maps from spontaneous rhythm were significantly different (p < 0.00008) in healthy and LBBB groups, which was shown on 19 parameters extracted from the autocorrelation maps by both the statistical tests of equality. In the optimal CRT setting in the LBBB responders, four of the studied parameters (Shannon entropy of the histogram of the autocorrelation map's values, and mean, standard deviation, and geometrical mean of the autocorrelation map's positive values) were not significantly different from the parameters of the healthy subjects (p > 0.19). ConclusionsSelected parameters of autocorrelation maps can be used as additional parameters for optimal CRT pacing settings, leading to patients’ positive responses to the treatment.

Perbandingan Hasil Pemeriksaan Asam Urat Metode Point of Care Testing (POCT) dengan Metode Fotometrik

The techniques used in laboratory examinations are crucial for diagnosing illnesses, including figuring out how much uric acid is in the body. The photometric technique and the Point Of Care Testing (POCT) approach are two of them. The aim of this research is to examine the findings of uric acid level examinations in persons between the ages of 20 and 40 in families and communities in Ciparay District, Bandung Regency, using POCT and photometric techniques. This is a cross-sectional research that employs a sequential random sample approach on 30 populations for sampling. A normality test utilizing the Paired Sample T-Test and the One-Sample Kolmogorov-Smirnov Test was used to analyze the data. The analysis's findings revealed that the uric acid level determined by the photometric technique was 4,920±1,480, whereas the average and standard deviation for the POCT method was 5,266±1,439. This indicates that the two approaches' average uric acid levels differ from one another. With a p-value of 0.045, the paired T-test demonstrated a significant difference between the photometric and POCT methods.

The Lyα Dependence on Nebular Properties from the HETDEX and MOSDEF Surveys

Investigating the impact of galaxy properties on emergent Lyα emission is crucial for reionization studies, given the sensitivity of Lyα to neutral hydrogen. This study presents an analysis of the physical characteristics of 155 star-forming galaxies, 29 with Lyα detected, and 126 with Lyα not detected with Lyα EW < 20 Å, at z = 1.9–3.5, drawn from the MOSFIRE Deep Evolution Field survey, that have overlapping observations from the Hobby–Eberly Telescope Dark Energy Experiment survey. To unravel the interstellar medium (ISM) conditions in our sample, we developed a custom nebular line modeling algorithm based on the MAPPINGS V photoionization model grid and the emcee framework. Combining nebular-based ISM properties with photometry-based global properties, constrained via Bagpipes, we explore distinctions in the stellar and gas properties between Lyα-detected and Lyα-nondetected galaxies. Our analysis reveals statistically significant differences between the two samples in terms of stellar mass and dust attenuation (A V ) at >2σ significance, as determined via a Kolmogorov–Smirnov test. Moreover, there are weaker (≲1σ significance) indications that the ionization parameter and metallicity differ between the two samples. Our results demonstrate that the escape fraction of Lyα ( fescLyα ) is inversely correlated with stellar mass, star formation rate, and dust attenuation, while it is positively correlated with the ionization parameter, with significance levels exceeding 2σ. Our findings suggest that the interstellar environments of Lyα-detected galaxies, characterized by low mass, low dust, low gas-phase metallicity, and high ionization parameters, play a pivotal role in promoting the escape of Lyα radiation.

Effect of Ti, Bi, W, Zn, and Pb nanoparticles on the radiation shielding properties in transparent medium: a Monte Carlo study

Recently, researchers have tried to examine novel materials to enhance radiation shielding in hospitals and medical centers as a replacement for regular shielding materials such as lead and concrete. To assess the impact of new radiation shield materials, this study is devoted to the examining the silicon shields as well as silica and tellurium glasses containing nanoparticles and micro-particles. For this purpose, using Monte Carlo code MCNPX, the role of Ti, Bi, W, Zn, and Pb particles in silicon shields, also tellurium and silica glasses incorporating Bi2O3, ZnO, TiO2, WO3, and PbO particles in nanometer and micrometer scales with proportions of 10%, 15%, 20%, 25%, 30%, 35%, 40%, and 45% are examined. The MCNP results demonstrate a strong agreement with the XCOM data, with a relative difference less than 2.11% across all samples. The Kolmogorov-Smirnov (K-S) test has been conducted to evaluate the consistency between the simulated data and the XCOM data, with the maximum vertical deviation (Dmax) less than 0.01%. The results show the improvement of radiation protection characteristics following the particle size reduction from micrometers to nanometers in all shields. Moreover, it was observed that increasing the proportion of nanoparticles in the shields enhances the protective properties. As a result, the shields containing the smallest size and accommodating the highest number of particles exhibit the best radiation shielding properties. Finally, the tellurium glasses doped with 45% nanoparticles of WO3 demonstrated the best shielding properties.

Fitting Probability Distributions and Statistical Trend Analysis of Rainfall of Agro-climatic Zone of West Bengal

This research aimed to identify the most appropriate probability distribution for modeling average monthly rainfall in the agro-climatic zones of West Bengal and to detect any trends in this data. The study utilized historical rainfall data spanning 51 years (1970-2020) obtained from the IMD in Pune. To determine the best-fitting distribution and assess trends, 23 different probability distributions were employed, with the Mann-Kendall test and Sen’s slope estimator used for trend analysis. Goodness-of-fit tests, including the Kolmogorov-Smirnov, Anderson-Darling, and Chi-square tests, were employed to determine the most suitable distribution. The findings indicated that the Generalized Extreme Value, Gamma, and Lognormal (3-parameter) distributions were the best fits for two specific districts. The monthly rainfall distributions can be effectively used for predicting future monthly rainfall events in the region. The Mann-Kendall test revealed an increasing trend in rainfall for Kalimpong and Nadia Districts and a decreasing trend for Malda District.

The effects of European mistletoe (Viscum album L.) on urban tree health

Background. Urban forests play a crucial role in making the urban environment and provide for sustainable development of urban areas. At the same time, urban habitats are stressful for trees therefore the latter become more susceptive to a range of disturbances, in particular to biotic agents such as the European mistletoe. The paper aims to evaluate the detrimental impacts of this hemiparasitic plant on urban trees. Materials and Methods. The study was conducted in an urban watershed of central and northwestern parts of the city of Kharkiv, Ukraine. Urban tree health survey took place in different stand types along 4 transects of the total length of 6.54 km. Totally, 956 individual trees were surveyed during the vegetation season of 2019. The health status of individual trees was assessed applying the 7-grade scale after O. D. Maslov, modified by the Ukrainian Forestry Research Institute. The mistletoe presence on individual trees was quantified using a semi-logarithmic index. The statistical analysis of the data collected involved the comparison of two empirical distributions, the normality test of the initial data, and the determination of the relationship between two independent samples. Results and Discussion. The analysis of the collected data revealed that the studied trees divided into two groups – “non-infested” and “mistletoe-infested” – grew in quite similar conditions and showed quite similar distribution by stand types, classes of soil conditions and age classes. We found differences in the mean health status between non-infested (transient from “weakened” to “dry-top”), and mistletoe-infested trees (“dry-top”): the tree health index of 2.43±0.03 for the former vs. 2.98±0.08 for the latter. Empirical distributions of the number of trees by the tree health classes in both groups were different too (the Kolmogorov–Smirnov criterion λ = 3.14 at Р &gt;0.999). We found a significant positive correlation between both mistletoe abundance and the age of individual infested trees (Spearman’s R = 0.36 at Р &gt;0.999), as well as the health index of individual infested trees (Spearman’s R = 0.23 at Р &gt;0.95). Conclusions. The study has proven a negative effect of mistletoe’s infestation on the tree crown foliage assessed with the tree health index. Such an effect increases with the age of infested trees. The findings of this study suggest that in urban forests the mistletoe acts as a trigger towards acceleration of tree stand health deterioration.

Enhanced Conditional GAN for High-Quality Synthetic Tabular Data Generation in Mobile-Based Cardiovascular Healthcare.

The generation of synthetic tabular data has emerged as a critical task in various fields, particularly in healthcare, where data privacy concerns limit the availability of real datasets for research and analysis. This paper presents an enhanced Conditional Generative Adversarial Network (GAN) architecture designed for generating high-quality synthetic tabular data, with a focus on cardiovascular disease datasets that encompass mixed data types and complex feature relationships. The proposed architecture employs specialized sub-networks to process continuous and categorical variables separately, leveraging metadata such as Gaussian Mixture Model (GMM) parameters for continuous attributes and embedding layers for categorical features. By integrating these specialized pathways, the generator produces synthetic samples that closely mimic the statistical properties of the real data. Comprehensive experiments were conducted to compare the proposed architecture with two established models: Conditional Tabular GAN (CTGAN) and Tabular Variational AutoEncoder (TVAE). The evaluation utilized metrics such as the Kolmogorov-Smirnov (KS) test for continuous variables, the Jaccard coefficient for categorical variables, and pairwise correlation analyses. Results indicate that the proposed approach attains a mean KS statistic of 0.3900, demonstrating strong overall performance that outperforms CTGAN (0.4803) and is comparable to TVAE (0.3858). Notably, our approach shows lowest KS statistics for key continuous features, such as total cholesterol (KS = 0.0779), weight (KS = 0.0861), and diastolic blood pressure (KS = 0.0957), indicating its effectiveness in closely replicating real data distributions. Additionally, it achieved a Jaccard coefficient of 1.00 for eight out of eleven categorical variables, effectively preserving categorical distributions. These findings indicate that the proposed architecture captures both distributions and dependencies, providing a robust solution in supporting mobile personalized cardiovascular disease prevention systems.

Assessing the Suitability of Probability Distribution Models for Streamflow Analysis in Peninsular Malaysia

Streamflow analysis is indeed a need for Malaysia which always threaten by extreme streamflow events including flooding. However, the determination of the most suitable probability distribution for streamflow analysis has been the major concern and received considerable critical attention recently. The purpose of this study is to analyse the performances of several distributions in fitting the streamflow data collected form 11 streamflow stations in Peninsular Malaysia. and select the best performed distribution eventually. Normal, Generalized Extreme Value (GEV), three-parameter Gamma (G3), two-parameter Gamma (G2), three-parameter Weibull (W3), two-parameter Weibull (W2), three-parameter Log-Normal (LN3) and two-parameter Log-Normal (LN2) were used in this study to fit the maximum, minimum, and mean streamflow with monthly and seasonal time scales by using Easyfit software. The performances of distributions were evaluated through constructing Probability-Probability (P-P) Plot, Cumulative Distribution Function (CDF) and conducting goodness-of-fit tests including Chi-square () Test, Anderson-Darling (AD) Test and Kolmogorov-Smirnov (KS) Test. All the results were tabulated for comparison and the most suitable probability distribution was selected. Overall, the results indicated that the GEV distribution was the best fit distribution for most of the stations and most of the data series or time scales, while the LN3 distribution appeared to be the second-best distribution. These findings add to a growing body of literature on the selection of probability distribution especially for the streamflow analysis in Peninsular Malaysia. Besides, these findings provide significant information and practical knowledge in supporting the future development of streamflow-related plans or management including the flood and drought mitigation plans.