Hierarchical Dendrogram Research Articles

Evaluation of oral and dermal health risk exposures of contaminants in groundwater resources for nine age groups in two densely populated districts, Nigeria

Human health and the sustainability of the socioeconomic system are directly related to water quality. As anthropogenic activity becomes more intense, pollutants, particularly potentially harmful elements (PHEs), penetrate water systems and degrade water quality. The purpose of this study was to evaluate the safety of using groundwater for domestic and drinking purposes through oral and dermal exposure routes, as well as the potential health risks posed to humans in the Nnewi and Awka regions of Nigeria. The research involved the application of a combination of the National Sanitation Foundation Water Quality Index (NSFWQI), HERisk code, and hierarchical dendrograms. Additionally, we utilized the regulatory guidelines established by the World Health Organization and the Standard Organization of Nigeria to compare the elemental compositions of the samples. The physicochemical parameters and NSFWQI evaluation revealed that the majority of the samples were PHE-polluted. Based on the HERisk code, it was discovered that in both the Nnewi and Awka regions, risk levels are higher for people aged 1 to <11 and >65 than for people aged 16 to <65. Overall, it was shown that all age categories appeared to be more vulnerable to risks due to the consumption than absorption of PHEs, with Cd > Pb > Cu > Fe for Nnewi and Pb > Cd > Cu > Fe for water samples from Awka. Summarily, groups of middle age are less susceptible to possible health issues than children and elderly individuals. Hierarchical dendrograms and correlation analysis showed the spatio-temporal implications of the drinking groundwater quality and human health risks in the area. This research could help local government agencies make informed decisions on how to effectively safeguard the groundwater environment while also utilizing the groundwater resources sustainably.

A multi-model study for understanding the contamination mechanisms, toxicity and health risks of hardness, sulfate, and nitrate in natural water resources.

Several water quality contaminants have attracted the attention of numerous researchers globally, in recent times. Although the toxicity and health risk assessments of sulfate and water hardness have not received obvious attention, nitrate contamination has gained peculiar research interest globally. In the present paper, multiple data-driven indexical, graphical, and soft computational models were integrated for a detailed assessment and predictive modeling of the contamination mechanisms, toxicity, and human health risks of natural waters in Southeast Nigeria. Majority of the tested physicochemical parameters were within their satisfactory limits for drinking and other purposes. However, total hardness (TH), SO4, and NO3 were above stipulated limits in some locations. A nitrate health risk assessment revealed that certain areas present a chronic health risk to children, females, and males due to water intake. However, the dermal absorption route was found to have negligible health risks. SO4 in some locations was above the 100mg/L Nigerian limit; thus, heightening the potentialhealth effects due to intake of the contaminatedwater resources. Most samples had low TH values, which exposes users to health defects. There are mixed contamination mechanisms in the area, according to graphical plots, R-mode hierarchical dendrogram, factor analysis, and stoichiometry. However, geogenic mechanisms predominate over human-related mechanisms. Based on the results, a composite diagrammatic model was developed. Furthermore, predictive radial basis function (RBF) and multiple linear regression (MLR) models accurately predicted the TH, SO4, and NO3, with the RBF outperforming the MLR models. Insights from the RBF and MLR models were useful in validating the results of the hierarchical dendrogram, factor, stoichiometric, and graphical analyses.

Comparison of antimicrobial resistance among Salmonella enterica serovars isolated from Canadian turkey flocks, 2013 to 2021

The emergence of antimicrobial resistance (AMR) in Salmonella from turkeys has raised a food safety concern in Canada as certain serovars have been implicated in human salmonellosis outbreaks in recent years. While several studies evaluated AMR in broiler chickens in Canada, there are limited studies that assess AMR in turkey flocks. This study analyzed data collected between 2013 and 2021 by the Canadian Integrated Program for Antimicrobial Resistance Surveillance (CIPARS) farm turkey surveillance program to determine the prevalence of AMR and differences in resistance patterns among Salmonella serovars recovered from turkey flocks. Salmonella isolates were tested for susceptibility to 14 antimicrobials using a microbroth dilution method. Hierarchical clustering dendrograms were constructed to compare the individual AMR status of Salmonella serovars. Differences in the probability of resistance between Salmonella serovars were determined using generalized estimating equation logistic regression models to account for farm-level clustering. Of the 1,367 Salmonella isolates detected, 55.3% were resistant to at least one antimicrobial and 25.3% were multidrug resistant (MDR) (resistant to ≥3 antimicrobial classes). The Salmonella isolates exhibited high resistance to tetracycline (43.3%), streptomycin (47.2%), and sulfisoxazole (29.1%). The 3 most frequently occurring serovars were S. Uganda (22.9%), S. Hadar (13.5%), and S. Reading (12.0%). Streptomycin-sulfisoxazole-tetracycline (n=204) was the most frequent MDR pattern identified. Heatmaps showed that S. Reading exhibited coresistance to the quinolone class antimicrobials, ciprofloxacin, and nalidixic acid; S. Heidelberg to gentamicin and sulfisoxazole; and S. Agona to ampicillin and ceftriaxone. Salmonella Hadar isolates had higher odds of resistance to tetracycline (OR: 152.1, 95% CI: 70.6-327.4) while the probability of being resistant to gentamicin and ampicillin was significantly higher in S. Senftenberg than in all the other serovars. Moreover, S. Uganda had the highest odds of being MDR (OR: 4.7, 95% CI: 3.7-6.1). The high resistance observed warrants a reassessment of the drivers for AMR, including AMU strategies and other production factors. Differences in AMR patterns highlight the need to implement serovar-specific mitigation strategies.

Self-care from the perspective by female sex workers to prevent and face the SARS-CoV-2 pandemic.

The objective was to identify the meanings attributed to self-care and its relationship with the actions taken by female sex workers in preventing and coping with COVID-19. Qualitative study supported by the Self-Care Nursing theory. An in-depth interview was carried out with 30 female sex workers from the Alto Sertão Produtivo Baiano. The IRAMUTEQ software was used to analyze the speeches, with the Descending Hierarchical Classification dendrogram. Four classes were observed, revealing the meanings attributed to self-care: the idea that self-care promotes quality of life and well-being; money as a facilitating instrument for self-care actions, both in preventing COVID-19 and in coping with difficulties; in addition to the notion that self-care contributes to the care of those around them. It is concluded that the female sex workers demonstrated to understand the concept of self-care in association with the notion of precaution, while prevention is carried out through the recommendations made by competent bodies. Furthermore, a self-care deficit was noticed due to the conditions present in the sexual service and the difficulties imposed by the pandemic.

Autocuidado na perspectiva de trabalhadoras sexuais para prevenção e enfrentamento à pandemia do SARS-CoV-2

Abstract The objective was to identify the meanings attributed to self-care and its relationship with the actions taken by female sex workers in preventing and coping with COVID-19. Qualitative study supported by the Self-Care Nursing theory. An in-depth interview was carried out with 30 female sex workers from the Alto Sertão Produtivo Baiano. The IRAMUTEQ software was used to analyze the speeches, with the Descending Hierarchical Classification dendrogram. Four classes were observed, revealing the meanings attributed to self-care: the idea that self-care promotes quality of life and well-being; money as a facilitating instrument for self-care actions, both in preventing COVID-19 and in coping with difficulties; in addition to the notion that self-care contributes to the care of those around them. It is concluded that the female sex workers demonstrated to understand the concept of self-care in association with the notion of precaution, while prevention is carried out through the recommendations made by competent bodies. Furthermore, a self-care deficit was noticed due to the conditions present in the sexual service and the difficulties imposed by the pandemic.

Development of a method for automatic construction of hierarchical structures of several collections of texts in the formalization of linguistic expert information

The paper discusses methods of forming special models for the representation of various sets of knowledge in various information systems. The work is devoted to the application of distributive semantics in the identification of significant combinations in one subject area (PRO) within the framework of the formalization of linguistic expert information (LEI). The paper applies an approach to the formalization of LEI based on a set of analytical methods, where linear algebra is used as models. This approach makes it possible to initialize the procedure for the automatic formation of hierarchical LEI architectures or dendrograms when identifying significant combinations of titles of several collections of texts. The scientific novelty lies in the proposed analytical approach using distributive semantics in identifying significant combinations of titles of several collections of texts, which allows for the analysis and processing of linguistic expert information. The paper aims to create conditions for the formalization of the LEI by applying distributive semantics when identifying significant combinations of titles of several collections. The ontology constructed in this work complements the search structure within the framework of the considered PRO and can be supplemented and developed in the future.

MULTIVARIATE STATISTICAL ANALYSIS FOR ASSESSMENT OF THE RELATIONSHIPS BETWEEN BONE DENSITY, BIOGENIC ELEMENTS CONTENT, AND THE LEVEL OF OXIDATIVE STRESS IN OSTEOPOROTIC WOMEN

The aim of the present study is to reveal hidden relationships between bone density, biogenic elements content, and the level of oxidative stress of female patients with osteoporosis and osteopenia. Additionally, specific links between the patients are sought in order to interpret different similarity patterns of objects (patients) helping to a better understanding of the significance of the clinical variables for each identified similarity pattern. Material and Methods: The input dataset consisting of 59 objects (patients) and 11 experimentally determined variables (clinical parameters) was subject to intelligent data analysis including cluster analysis (hierarchical and non-hierarchical mode) and factor analysis. Results and Discussion: In the hierarchical dendrogram for clustering of 11 variables are formed 3 major clusters. We could assume that three factors (impact) are linked to the structure of the data set: descriptors responsible for osteoporosis diagnosis; descriptors (essential elements) related to osteoporosis status; descriptors related to the "overall health status impact”. The patients are clustered in 3 clusters corresponding to 3 different levels of health status (improving, worsening and intermediate) by K-means clustering. The specific descriptors are defined for each identified cluster. Factor analysis shows that 3 latent factors explain nearly 70 % of the total variance of the system ˗ each of them with respective clinical meaning. A relationship is proven between T-score, diagnosis, and antioxidant activity by a 3D plot of factor loadings. Conclusion: The multivariate statistical data interpretation for patients with osteoporosis problems reveals hidden relationships between specific similarity clusters among all patients or between the clinical parameters experimentally measured. It helps to better distinguish the variations between the specific groups and to determine the indicators for the variability. All this helps for more individual approachesto medical treatment.

Changes on mutant pot chrysanthemums (Dendranthema × grandiflora Tzelev.)

Chrysanthemum (Dendranthema x grandiflora Tzvelev) is one of the most important ornamental plants in the world that has the richest mutant varieties with numerous colors. The objective of this study is to determine the effective mutagen dose (EMD50) for creating variations by gamma irradiation. It is aimed to get a mutagenesis protocol that could develop new mutants in pot chrysanthemums. To determine the EMD50, rooted cuttings of brownish-red color ‘Brandevil’ variety were irradiated by gamma radiation at 0, 10, 20, 30, 40, 50 Gray (Gy) doses. According to the shoot lengths, EMD50 was calculated as 27 Gy. The mutation frequency was calculated as 4.8%. Some changes were observed for flower numbers per plant, plant heights and widths, shapes and colors of both flowers and leaves. The color changes varied from brownish-red to yellow and orange. Two different colors appeared in the same pot at some genotypes as well as form changes of flowers. The similarity of the mutants was determined by the hierarchical cluster dendrogram involving five groups. Various colors were obtained for leaves and flowers. Remarkable mutations of the selected mutants were multiplied by tissue culture.

Start codon-targeted marker evaluation of genetic relationship and population structure in southern Nigerian fluted pumpkin (Telfairia occidentalis Hook F.) collection

AbstractFluted pumpkin (Telfairia occidentalis Hook F.) is an underutilized indigenous leafy vegetable with enormous prospects for food security in sub-Saharan Africa. However, relatively little is known about genetic relationships and population structure in the species. In this study, 32 landraces of fluted pumpkin collected across three southern geographical regions in Nigeria were assessed for genetic diversity and population structure using 8 start codon-targeted (SCoT) makers. The polymorphic information content of the SCoT markers ranged from 0.48 in SCoT36 to 0.94 in SCoT28, with an average of 0.77. Hierarchical cluster dendrogram based on Ward's method and principal component analysis grouped the landraces into four clusters without affiliation to provenance. Overall, the mean values of the population genetic diversity parameters – Nei's gene diversity (H) and Shannon's information index (I) showed values of 0.28 ± 0.01 and 0.43 ± 0.02, respectively, implying a narrow genetic base for the landraces. The result was further corroborated by a very close Nei's genetic distance and identity among populations of the landraces. Furthermore, the south-west population exhibited the higher genetic diversity (H = 0.31 ± 0.02 and I = 0.45 ± 0.03). Population structure analysis inferred three subpopulations for the accessions with varying degrees of allelic admixture. An analysis of molecular variance revealed that almost all the genetic variation occurred within (99%) than between (1%) populations. The findings shed light on the genetic diversity of southern Nigerian fluted pumpkin and have significant implications for the characterisation, conservation, exploitation and improvement of the species.

Influence of urbanisation on phytodiversity and some soil properties in riverine wetlands of Bamenda municipality, Cameroon

In urban areas, human activities result in the discharge of a variety of chemical substances into the environment. This affects soil quality, plant species diversity and human security. To suggest appropriate management strategies that ensure soil quality and human security amid urbanization, this study assessed the relationship between macrophyte diversity and some soil characteristics of wetlands that are adjacent to urban, peri-urban and rural areas in Bamenda Municipality, Cameroon. Plant communities were sampled for species composition and relative abundance, using the Braun-banquet method. Species richness was evaluated using Simpson’s diversity index. Twenty-one soil samples (0–25 cm depth) were randomly collected within the wetlands and analyzed for their physicochemical characteristics using standard methods. The hierarchical cluster analysis (HCA) was used to group the wetlands under managing units. The dominant species ranked in order of abundance in the rural wetland were Raphia farinifera > Ludwigia hexandra > Coix spp. > Leersia hexandra > Ehchinochloa paramidelis. The Peri-urban wetland dominant species stood at Commelina bengalensis > Leersia hexandra > Cyperus distance > Ehchinochloa pyramidalis. In the Urban segment, Pennisetum purpureum > Echinochloa pyramidalis > Tithonia diversifolia > Leersia hexandra were the abundant species. The Simpson index of diversity was 0.94 for the urban and 0.96 for the peri-urban and rural sites respectively. The soils were slightly acidic with pH KCl ranging from 4.87 to 5.41. From the coefficient of variability classes, Sand, pH-H2O, pH-KCl, and Na consistently varied slightly across the three sites. Two significant clusters (management units) representing a combination of urban, and peri-urban/rural were formed from the hierarchical dendrograms. The Mann–Whitney U test revealed a significant (P < 0.05) lower exchange acidity in the rural than the urban sites indicating contamination of the urban site, reducing its macrophyte diversity. Intensification and extension of urbanisation are gradually reducing the macrophyte diversity and also contaminating the soils of the wetlands of the Bamenda municipality in Cameroon, warranting monitoring. The chemical composition of soils in the urban cluster needs early remediation by encouraging the planting and monitoring of certain plants that can already take up the elements.

Volatile Profiling of Magnolia champaca Accessions by Gas Chromatography Mass Spectrometry Coupled with Chemometrics.

Magnolia champaca (L.) Baill. ex Pierre of family Magnoliaceae, is a perennial tree with aromatic, ethnobotanical, and medicinal uses. The M. champaca leaf is reported to have a myriad of therapeutic activities, however, there are limited reports available on the chemical composition of the leaf essential oil of M. champaca. The present study explored the variation in the yield and chemical composition of leaf essential oil isolated from 52 accessions of M. champaca. Through hydrodistillation, essential oil yield was obtained, varied in the range of 0.06 ± 0.003% and 0.31 ± 0.015% (v/w) on a fresh weight basis. GC-MS analysis identified a total of 65 phytoconstituents accounting for 90.23 to 98.90% of the total oil. Sesquiterpene hydrocarbons (52.83 to 65.63%) constituted the major fraction followed by sesquiterpene alcohols (14.71 to 22.45%). The essential oils were found to be rich in β-elemene (6.64 to 38.80%), γ-muurolene (4.63 to 22.50%), and β-caryophyllene (1.10 to 20.74%). Chemometrics analyses such as PCA, PLS-DA, sPLS-DA, and cluster analyses such as hierarchical clustering, i.e., dendrogram and partitional clustering, i.e., K-means classified the essential oils of M. champaca populations into three different chemotypes: chemotype I (β-elemene), chemotype II (γ-muurolene) and chemotype III (β-caryophyllene). The chemical polymorphism analyzed in the studied populations would facilitate the selection of chemotypes with specific compounds. The chemotypes identified in the M. champaca populations could be developed as promising bio-resources for conservation and pharmaceutical application and further improvement of the taxa.

A visible colorimetric sensor array based on chemo-responsive dyes and chemometric algorithms for real-time potato quality monitoring systems

The colorimetric sensor array real-time monitoring system with multivariate analysis was established for discrimination of potato varieties with different types and degrees of corruption. The characteristic volatile compounds of fresh, dry rot and soft rot potatoes was identified by Gas Chromatography-Mass Spectrometry and the 3 × 4 array was fabricated to capture the characteristics volatile compounds. The sensor array system produced a visible color difference map upon its exposure to volatile compounds of potato. Discrimination of potatoes with the same types or different degrees of corruption was subsequently achieved using principal component analysis and hierarchical clustering analysis dendrogram. The k-nearest neighbor algorithm for potato classification provided the best results with 100 % discrimination on both the calibration and prediction sets. The linear discriminant analysis model achieved a 99.76 % calibration set and a 99.31 % prediction set for potato grading. An online warning device based on array was devised to realize unmanned monitoring for potato quality.

Incorporation of information entropy theory, artificial neural network, and soft computing models in the development of integrated industrial water quality index.

Keeping purpose and targeted end-users in perspective, several water quality indices have been developed over the past decades to summarily convey water quality information to decision-makers and the general public. Industrial water quality is often analyzed based on the corrosion and scaling potentials (CSPs) of water. The commonly used CSP index parameters are chloride-sulfate mass ratio, Langelier index, Larson-Skold index, aggressive index, Ryznar stability index, and Puckorius scaling index. Simultaneous application of these index parameters often classifies a sample into multiple water quality categories, thereby introducing bias in assessment anddecision-making. No previous numerical model integrated the CSP indices to provide a single, composite index value for a more unbiased interpretation of industrial water quality. Therefore, this paper proposes an integrated industrial water quality index (IIWQI) that integrates the six CSP index parameters for direct and concise assessment of industrial water resources. To achieve its aim, this research incorporated information entropy theory and soft computing techniques. The developed IIWQI was applied to water samples from southeastern Nigeria. Different classification groups were observed based on the six CSP indices. However, the IIWQI summarized the classifications of the water samples into three categories: Class 1 (28.57%, slight-medium corrosivity, significant scaling potential); Class 2 (46.43%, medium-high corrosivity, no scaling); and Class 3 (25.00%, high-very high corrosion, no scaling). Correlation analysis revealed the relationships between the physicochemical variables, CSP index parameters, IIWQI, and the entropy-based variability of the IIWQI. The spatiotemporal water quality groups were revealed by Q-mode hierarchical dendrograms. Multiple linear regression and two multilayer perceptron neural networks accurately predicted the IIWQI. The findings of this paper could help in better evaluation, interpretation, and management of industrial water quality.

Health risk assessment of pesticide residue in freshly harvested Vigna subterranea (Bambara nut) in Nsukka South Eastern Nigeria.

Two species of freshly harvested Bambara nut were analyzed for organophosphate and organochlorine pesticide residue using GC-FID and GC-ECD. The risk associated with the consumption of the Bambara nut was evaluated using the health risk index (HRI) and the probable cancer risk (PCR). A maximum of thirteen (13) organochlorines and eight (8) organophosphate pesticides were determined from both species respectively. The results revealed that almost all the quantified pesticides exceeded their respective FAO maximum residue levels (MRLs). The health risk index (HRI) values of the organochlorines and organophosphates were below 1 in adults indicating little or no risk to adults. While the HRI of the organophosphates and a few values in the organochlorines were above 1 in children indicating that organophosphate pesticides in the freshly harvested white and mixed Bambara nut could pose a great health risk to children within these areas. The Hierarchical Cluster Dendrogram indicated similar sources of the assessed organochlorine and organophosphate pesticides.

WATER QUALITY PARAMETERS FOR POLLUTION SOURCE IDENTIFICATION IN WARWADE DAM WATER, DUTSE, JIGAWA STATE, NIGERIA: STATISTICAL AND SPATIOTEMPORAL EVALUATION

This study looked at the diminishing water quality of Warwade Dam, which is one of Dutse's largest dams. Statistical methodologies such as descriptive statistics, principal component analysis (PCA), regression analysis, correlation analysis, and cluster analysis were used to examine selected water quality characteristics. pH, conductivity, TDS, temperature, and DO captured the highest variability (98.94%) in the data set, according to the PCA scree plot. Ca and Mg were the most variable from the PCA scree plot among the metals studied (99.96 percent). The correlational analysis revealed that the characteristics differed in terms of spatio-temporal and/or limnological aspects. Variables within a cluster are relatively similar, whereas variables outside a cluster are very dissimilar, according to cluster analysis employing hierarchical dendrogram to establish linkages, relationships, and differences among parameters. The validation test was passed by 67 percent of the parameters in the general linear regression model (very strong fit at P value 0.05). The PCA scree plot of 99.39 percent variability revealed that the dam concentrations of nitrate, nitrite, and chloride were identical

PCR Analysis for Genetic Distances of Two Charybdis Crab Populations.

Genomic DNA (gDNA) set apart from two populations of Korean Charybdis crab (Charybdis japonica) was augmented by PCR experiments. The five oligonucleotides primers (ONT-primers) were spent to yield the number of unique loci shared to each crab population (ULSECP) and number of loci shared by the two crab populations (LSTCP). 305 fragments (FRAGs) were identified in the Charybdis crab population A (CCPA), and 344 in the Charybdis crab population B (CCPB): 44 number of ULSECP (14.43%) in the CCPA and 110 (31.98%) in the CCPB. 44 number of LSTCP, with an average of 8.8 per primer, were detected in the two crab populations. The bandsharing (BS) value between entity's no. 01 and no. 10 was the lowest (0.371) between the two CCPs. The average bandsharing (ABS) values of individuals in the CCPA (0.575±0.014) were lesser than in those originated from the CCPB (0.705±0.011) (p < 0.05). The polar hierarchical dendrogram (PHD) achieved by the five ONT-primers denotes three genetic clusters (GCs): cluster I (CHARYBCRAB 01, 04, 05, 06, and 08), cluster II (CHARYBCRAB 02, 03, 07, 09, 10, and 11) and cluster III (CHARYBCRAB 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, and 22). The shortest genetic distance (GD) displaying significant molecular difference (MD) was between individuals CHARYBCRAB no. 18 and CHARYBCRAB no. 17 (0.055).

Comparative study of volatile composition of major Northern Highbush blueberry (Vaccinium corymbosum) varieties

Blueberries originated from North America and the predominant cultivated species are Vaccinium corymbosum (Northern and Southern Highbush), Vaccinium ashei (Southern Rabbiteye), and Vaccinium angustifolium (Lowbush). Consumer’s demand for high-quality blueberry fruits has driven the interest to better understand the flavor chemistry of blueberry. Forty-five previously identified aroma contributing compounds were further investigated in 11 blueberry varieties, including some developing types. Based on odor activity value, branch-chain esters, terpenes, and aldehydes could be the primary aroma contributors to all 11 blueberry varieties. A heatmap with hierarchical clustering dendrogram showed that the three varieties ORUS 235-4, ORUS 235-3, and ORUS-10-1 were close together with a high level of branch-chain esters and, in turn, close to ‘Draper’ and ‘Duke’. However, they differed from the other varieties, including ‘Aurora’, ‘Bluecrop’, ‘Elliott’, ‘Legacy’, ‘Liberty,’ and ORUS-202-2. One-way ANOVA analysis demonstrated that terpenoids varied the most among varieties. Also, the Pearson correlation showed terpenoids, except eucalyptol, exhibited a strong positive correlation, especially between linalool and α-terpineol. Enantiomer analysis revealed S-(+)-linalool was dominant in all blueberries, whereas the S-(−)-α-terpineol was slightly higher than R-(+)-α-terpineol. This study provided a detailed volatile composition database for unraveling the complex genetics of the various blueberry flavor aspects to assist the breeding purposes of new blueberry crops.

Association testing for binary trees-A Markov branching process approach.

We propose a new approach to test associations between binary trees and covariates. In this approach, binary‐tree structured data are treated as sample paths of binary fission Markov branching processes (bMBP). We propose a generalized linear regression model and developed inference procedures for association testing, including variable selection and estimation of covariate effects. Simulation studies show that these procedures are able to accurately identify covariates that are associated with the binary tree structure by impacting the rate parameter of the bMBP. The problem of association testing on binary trees is motivated by modeling hierarchical clustering dendrograms of pixel intensities in biomedical images. By using semi‐synthetic data generated from a real brain‐tumor image, our simulation studies show that the bMBP model is able to capture the characteristics of dendrogram trees in brain‐tumor images. Our final analysis of the glioblastoma multiforme brain‐tumor data from The Cancer Imaging Archive identified multiple clinical and genetic variables that are potentially associated with brain‐tumor heterogeneity.

Assessment of PTEs in water resources by integrating HHRISK code, water quality indices, multivariate statistics, and ANNs

The use of contaminated water for drinking and sanitary purposes can be detrimental to human health. In this article, the Human Health Risk (HHRISK) code was applied, alongside the modified heavy metal index (MHMI), synthetic pollution index (SPI), and entropy-weighted water quality index (EWQI), to investigate the pollution status, ingestion, and dermal health risks of potentially toxic elements (PTEs) (Fe, Zn, Mn, Pb, Cr, and Ni) in water resources from the Umunya area, Nigeria. Physicochemical measurements followed standard methods. Results of the MHMI, SPI, and EWQI revealed that about 60% of the water samples had low pollution and were considered suitable for human consumption, while 40% were unsuitable. Further, cumulative non-carcinogenic health risk scores indicated that 60% of the water samples pose low-medium risks while 40% pose high risks to child and adult populations. Contrarily, results of cumulative carcinogenic health risk showed that 6.67% of the samples expose water users to low risks, whereas 93.33% expose them to high risks. Although there are agreements between the results for both adult and child populations (regarding non-carcinogenic and carcinogenic risks), it is worth highlighting that the risk scores for children were higher. Therefore, children in the study area are more vulnerable to both carcinogenic and non-carcinogenic health risks. Also, it was revealed that the risk due to ingestion was higher than that due to dermal contact. Linear regression analysis showed strong agreement between the indexical models and the cumulative health risks. While artificial neural networks and multiple linear regression models accurately predicted the water quality indices, hierarchical dendrograms efficiently classed the water samples into various spatiotemporal water quality groups.

Seed Germination and Seedling Growth of Robinia pseudoacacia Depending on the Origin of Different Geographic Provenances

Black locust (Robinia pseudoacacia) is recognised as a forest species of interest due to its multiple uses. The management of forest genetic resources and their efficient conservation suffer from variations in traits and start with seed germination. The aim of the current study was to investigate the germination of seeds obtained from plus trees selected in eight Romanian provenances, as well as to investigate the influence of the origin upon plants’ growth and development. Two experiments were undertaken to test seed germination: one treatment involved water-soaked seeds and heat/cold treatment, while the other treatment was based on sulphuric acid, at different concentrations (50, 70, 90%). The results were correlated with the morphological analysis of the seeds. Satu-Mare had the lowest germination rate within both treatments. Sulphuric acid did not improve seed germination as much as the heat treatment. The highest germination rate occurred for the water and temperature treatment on seeds from Bihor provenance (68.2%). The most distant provenance was Bihor, in inverse correlation with Bistrița Năsăud and grouped separately within the hierarchical dendrogram of cluster analysis based on the analysed parameters of the provenances investigated. The results demonstrated that the genotypes and environmental heterogeneity of the seed origin within the provenances may finally result in different performances.