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Pterocarpus santalinus L.f. is an endangered tree species that is cherished worldwide for its valuable deep red-colored heartwood, which has multiple uses. This species exhibits a wide range of medicinal properties and offers immense potential for the discovery of bioactive compounds of pharmacological importance. The overharvesting of this species for heartwood has led to a gradual decline in its natural populations, thereby depleting its genetic resources and contributing to the loss of genetic diversity. Therefore, it is essential to assess genetic diversity, as such information allows for the effective conservation and utilization of genetic resources. In the present study, the genetic diversity and population structure among 40 germplasm accessions originating from 8 populations of P. santalinus were analyzed using six cross-species simple sequence repeats (SSR), 20 each of inter simple sequence repeats (ISSR) and random amplified polymorphic DNA (RAPD) markers. SSR markers revealed higher polymorphism (100 %), followed by ISSRs (82.81 %) and RAPDs (67.50 %), across all the accessions. The mean values of the polymorphic information content (PIC), effective multiplex ratio (EMR), and marker index (MI) were higher for SSRs (0.84, 9.17, and 7.7), followed by ISSRs (0.262, 4.474, and 1.251) and RAPDs (0.204, 3.268 and 0.970, respectively), indicating the superiority of SSRs in detecting polymorphisms in red sanders. Similarly, the estimates of Nei's gene diversity (H) and Shannon's information index (I) varied across the studied accessions, with the highest values for SSRs (H = 0.528, I = 0.923), followed by ISSRs (H = 0.287, I = 0.428) and RAPDs (H = 0.206, I = 0.307). However, the genetic statistic (Gst) or fixation statistic (Fst) and gene flow (Nm) values were higher for RAPDs (0.455 and 0.598) and ISSRs (0.446 and 0.620) than for SSRs (0.383 and 0.489, respectively), indicating significant genetic differentiation of the populations and moderate gene flow among the populations. Analysis of molecular variance (AMOVA) with SSR, ISSR, and RAPD markers revealed that a greater proportion of genetic variation resided within populations (74 %, 69 %, and 66 %, respectively) than among populations (26 %, 31 %, and 34 %, respectively). Hierarchical clustering on the basis of RAPDs grouped most of the accessions according to the population of origin; however, this clustering was different for the ISSR and SSR markers. STRUCTURE analysis divided the accessions into four, two, and three groups with SSR, ISSR, and RAPD markers, respectively, with admixtures detected in all the groups pointing toward shared genetic lineages and diverse genetic ancestry among the accessions of different populations. Overall, the populations of Gumudipoondi of Tamil Nadu and K.V. Bhavi of Andhra Pradesh were genetically more diverse than other populations, as revealed by genetic diversity estimates obtained with SSR and ISSR marker systems; therefore, the accessions of these populations must be prioritized for conservation and utilization in breeding programs for genetic improvement. [Display omitted] • Genetic diversity was assessed among 40 accessions of P. santalinus using 6 cross-species SSR, 20 each of ISSR and RAPD primers. • Cross-species SSRs were more efficient in detecting genetic diversity in the studied populations than ISSRs and RAPDs. • The populations of Gumidipoondi of Tamil Nadu (GTN) and K.V. Bhavi of Andhra Pradesh (KAP) exhibited higher genetic diversity than other populations according to SSR and ISSR marker analysis. • Analysis of molecular variance with SSR, ISSR and RAPD markers showed that genetic variations within populations (74 %, 69 % and 66 %) were greater than among populations (26 %, 31 % and 34 %). • STRUCTURE analysis using SSR, ISSR and RAPD markers divided the populations into four, two and three genetic groups, respectively, with admixtures detected in all genetic groups. [ABSTRACT FROM AUTHOR]

This paper presents a significant advancement in information security risk assessment by introducing a flexible and comprehensive model. The research integrates established standards, expert knowledge, machine learning, and ontological modeling to create a multifaceted approach for understanding and managing information security risks. The combination of standards and expert insights forms a robust foundation, ensuring a holistic grasp of the intricate risk landscape. The use of cluster analysis, specifically applying k-means on information security standards, expands the data-driven approach, uncovering patterns not discernible through traditional methods. The integration of machine learning algorithms in the creation of information security risk dendrogram demonstrates effective computational techniques for enhanced risk discovery. The introduction of a heat map as a visualization tool adds innovation, facilitating an intuitive understanding of risk interconnections and prioritization for decision makers. Additionally, a thesaurus optimizes risk descriptions, ensuring comprehensiveness and relevance despite evolving terminologies in the dynamic field of information security. The development of an ontological model for structured risk classification is a significant stride forward, offering an effective means of categorizing information security risks based on ontological relationships. These collective innovations enhance understanding and management of information security risks, paving the way for more effective approaches in the ever-evolving technological landscape. [ABSTRACT FROM AUTHOR]

Carbapenem-Resistant Acinetobacter baumannii (CRAB) outbreak in intensive care units (ICUs) is a significant problem for healthcare facilities. In this study, we aimed to investigate the occurrence of CRAB isolates among ICU-admitted patients during the three waves of the COVID-19 pandemic in Iran using Multiple-Locus Variable Number Tandem-Repeat Analysis (MLVA). We obtained 50 (A) baumannii isolates from tracheal aspirate and blood culture samples. In the disc diffusion method, all isolates were cefotaxime, ceftriaxone, and cefepime-resistant, while 98% (49/50) of isolates were resistant to piperacillin, piperacillin-tazobactam, ceftazidime, and ciprofloxacin. Levofloxacin and tobramycin resistance was found in 76% (38/50) of isolates. In the microbroth dilution test all isolates were resistant to imipenem, 98% (49/50) to meropenem, 68% (34/50) to colistin, and 20% (10/50) to polymyxin (B) Based on the PCR findings, all isolates harbored blaOXA−40, ISAba-1, and int-2 genes. There were no isolates found that have the blaOXA−58, blaOXA−143, blaVEB−1, blaVIM, and int-3 genes. Among Extended-spectrum beta-lactamases (ESBL) genes, blaCTX−M, blaTEM, blaSHV, blaGES, and blaPER−1 have a prevalence of 42% (21/50), 84% (42/50), 58% (29/50), 78% (39/50), and 54% (27/50), respectively. 74% (37/50) of the isolates had the blaOXA−23 gene, while all of the isolates carried the blaOXA−40 gene. Among MBL genes, blaIPM, blaGIM, blaSIM, and blaNDM−1 have a prevalence of 20% (10/50), 8% (4/50), 22% (11/50), and 60% (30/50), respectively. The prevalence of int-1 was documented as 74% (37/50). Accordingly, all isolates were identified as CRAB. The co-existence of blaOXA−23/int-2 and blaOXA−23/isaba-1 was 74% (37/50). The co-existence of blaNDM−1/ISAba-1 was observed in 30 (60%) isolates. Using an 80% similarity threshold on the dendrogram constructed through MLVA typing, all isolates were grouped into two clusters: cluster A with 9 isolates from wave 3, and cluster B with 41 isolates from waves 3, 4, and 5. Our study confirms a clonal transmission of CRAB during the study period and suggests using molecular typing methods like MLVA in healthcare settings to identify dominant clones, antibiotic resistance patterns, and transmission routes. This will help to better manage the emergence and spread of antibiotic-resistant strains in future outbreaks. [ABSTRACT FROM AUTHOR]

We analyzed literature data on the composition of 479 glasses used to stabilize radioactive wastes, covering a wide range and including 51 oxides and few fluorides. The most common glass constituents included SiO2, B2O3, Na2O, and Fe2O3 in varying amounts, with a predominance of borosilicate glasses. Seven families of waste radioactive glasses were observed, including borosilicates, silicates, boroaluminosilicates, iron phosphates, aluminosilicates, sodium iron phosphates, and boroaluminates. These data were used to estimate an average composition associated with a sodium borosilicate glass. Multivariate exploratory methods were used to analyze and classify the compositions of the waste radioactive glasses using multidimensional scaling and hierarchical clustering. Four main clusters were observed, the largest with 417 glasses, mainly silicates, borosilicates, aluminosilicates, and boroaluminosilicates. The results of this work have shown that it is possible to map radioactive waste glasses according to their composition, promoting a road map for future applications with specific properties. [ABSTRACT FROM AUTHOR]

Background: Candida auris is an opportunistic pathogen that has become widespread in recent years and shows resistance to multiple drugs. The aim of our study was to determine the antifungal susceptibilities of C. auris isolates, to perform a dendrogram from the mass spectra of strains obtained from matrix-assisted laser desorption ionization-time of flight mass spectrometry in order to evaluate the proteomic similarities of the strains and determine the geographical clade of C. auris strains in this study by the help of Multiplex RT-PCR. Methods: The samples yielded 58 C. auris isolates. MALDI TOF MS (BioMerieux, France) was used for identification of the isolates and Sensititre Yeast One (Thermoscientific) system was used for antifungal susceptibility testing. Dendrograms of strain's spectra were generated by using the RUO/Saramis (BioMerieux, France) database and evaluated through hierarchical clustering analysis. The selected nine strains were examined at the clade level by using Multiplex RT-PCR. Results The susceptibility profile of the strains revealed resistance to Fluconazole in 84% (MICs = 32) and resistance to Amphotericin B in 60% (MIC = 2). All strains were found to be sensitive to Anidulafungin and Micafungin. The dendrogram of the main spectra of C. auris isolates showed a similarity range of 35 - 100%. The nine strains studied were identified as clade 1 (South Asian). Conclusions: It was determined that C. auris strains were members of geographical clade 1, and the Amphotericin B resistance was found to be higher than expected. This situation poses a threat to critically ill patients. [ABSTRACT FROM AUTHOR]

Genetic similarity determines the extent to which two genotypes share common genetic material. It can be measured in various ways, such as by comparing DNA sequences, proteins, or other genetic markers. The significance of genetic similarity is multifaceted and encompasses various fields, including evolutionary biology, medicine, forensic science, animal and plant breeding, and anthropology. Genetic similarity is an important concept with wide application across different scientific disciplines. The research material included 21 rapeseed genotypes (ten interspecific Brassicaceae hybrids of F2 generation and 11 of their parental forms) and 146 alleles obtained using 21 ISSR molecular markers. In the presented study, six measures for calculating genetic similarity were compared: Euclidean, Jaccard, Kulczyński, Sokal and Michener, Nei, and Rogers. Genetic similarity values were estimated between all pairs of examined genotypes using the six measures proposed above. For each genetic similarity measure, the average, minimum, maximum values, and coefficient of variation were calculated. Correlation coefficients between the genetic similarity values obtained from each measure were determined. The obtained genetic similarity coefficients were used for the hierarchical clustering of objects using the unweighted pair group method with an arithmetic mean. A multiple regression model was written for each method, where the independent variables were the remaining methods. For each model, the coefficient of multiple determination was calculated. Genetic similarity values ranged from 0.486 to 0.993 (for the Euclidean method), from 0.157 to 0.986 (for the Jaccard method), from 0.275 to 0.993 (for the Kulczyński method), from 0.272 to 0.993 (for the Nei method), from 0.801 to 1.000 (for the Rogers method) and from 0.486 to 0.993 (for the Sokal and Michener method). The results indicate that the research material was divided into two identical groups using any of the proposed methods despite differences in the values of genetic similarity coefficients. Two of the presented measures of genetic similarity (the Sokal and Michener method and the Euclidean method) were the same. [ABSTRACT FROM AUTHOR]

Abstract Carbapenem-Resistant Acinetobacter baumannii (CRAB) outbreak in intensive care units (ICUs) is a significant problem for healthcare facilities. In this study, we aimed to investigate the occurrence of CRAB isolates among ICU-admitted patients during the three waves of the COVID-19 pandemic in Iran using Multiple-Locus Variable Number Tandem-Repeat Analysis (MLVA). We obtained 50 (A) baumannii isolates from tracheal aspirate and blood culture samples. In the disc diffusion method, all isolates were cefotaxime, ceftriaxone, and cefepime-resistant, while 98% (49/50) of isolates were resistant to piperacillin, piperacillin-tazobactam, ceftazidime, and ciprofloxacin. Levofloxacin and tobramycin resistance was found in 76% (38/50) of isolates. In the microbroth dilution test all isolates were resistant to imipenem, 98% (49/50) to meropenem, 68% (34/50) to colistin, and 20% (10/50) to polymyxin (B) Based on the PCR findings, all isolates harbored bla OXA−40 , ISAba-1, and int-2 genes. There were no isolates found that have the bla OXA−58 , bla OXA−143 , bla VEB−1 , bla VIM , and int-3 genes. Among Extended-spectrum beta-lactamases (ESBL) genes, bla CTX−M , bla TEM , bla SHV , bla GES , and bla PER−1 have a prevalence of 42% (21/50), 84% (42/50), 58% (29/50), 78% (39/50), and 54% (27/50), respectively. 74% (37/50) of the isolates had the bla OXA−23 gene, while all of the isolates carried the bla OXA−40 gene. Among MBL genes, bla IPM , bla GIM , bla SIM , and bla NDM−1 have a prevalence of 20% (10/50), 8% (4/50), 22% (11/50), and 60% (30/50), respectively. The prevalence of int-1 was documented as 74% (37/50). Accordingly, all isolates were identified as CRAB. The co-existence of bla OXA−23 /int-2 and bla OXA−23 /isaba-1 was 74% (37/50). The co-existence of bla NDM−1 /ISAba-1 was observed in 30 (60%) isolates. Using an 80% similarity threshold on the dendrogram constructed through MLVA typing, all isolates were grouped into two clusters: cluster A with 9 isolates from wave 3, and cluster B with 41 isolates from waves 3, 4, and 5. Our study confirms a clonal transmission of CRAB during the study period and suggests using molecular typing methods like MLVA in healthcare settings to identify dominant clones, antibiotic resistance patterns, and transmission routes. This will help to better manage the emergence and spread of antibiotic-resistant strains in future outbreaks.

Maize (Zea mays L.) is the third most important cereal crop in the world because of its nutritional value and industrial benefits. Molecular markers are used mainly by the breeders to study the genetic variability of genotypes and its application in the breeding process. Two types of molecular markers, 10 random amplified polymorphic DNA (RAPD) primers and 10 start codon target (SCoT) primers, were assayed to determine the genetic diversity of 25 Slovak maize lines and 25 maize cultivars. A high level of polymorphism was found with both RAPD and SCoT markers, which was confirmed by high average polymorphism information content (PIC) values using both techniques. The efficiency of individual marker techniques in the detection of genotype diversity can be compared by calculating the marker index (MI), detecting diversity index (DDI), discriminating power, resolving power (RP) and other indices. A higher MI (11.788), DDI (2.358) and RP (53.08) value was achieved by the SCoT technique compared to the RAPD method. Three joint dendrograms and PCoA plots constructed based on RAPD, SCoT and both methods combined confirmed the unambiguous separation of maize lines and cultivars from each other. The results obtained from the RAPD and SCoT analysis can be used for the selection of potentially suitable biological sources for further marker-assisted breeding. [ABSTRACT FROM AUTHOR]

Diversity information mining about a crop for different attributes is an essential step for effective breeding programs. The present investigation evaluates the quantum of genetic variability and determines the relationship among the important agro-economic traits based on two years of phenotypic data of 210 accessions of linseed. The traits, capsule weight per plant, capsule per plant, husk weight per plant, and seed weight per plant exhibited comparatively higher genetic coefficient of variation (GCV) and phenotypic coefficient of variation (PCV). In contrast, oil content and seed per capsule exhibited a lower value. The high magnitude of broad sense heritability was observed for all traits except seeds per capsule and husk weight per plant. The trait, capsules per plant, plant height, and days to 50% flowering showed high genetic advance coupled with high heritability. Hierarchical cluster analysis grouped 210 accessions into six distinct clusters. Out of 210, 144 (68.57%) accessions were grouped into three clusters (I, II, and III), in which cluster-III was the largest, containing 64 accessions followed by cluster II and cluster-I. The highest inter-cluster distance was observed between clusters-I and V (127.85), while the lowest was between clusters-II and IV (27.09). The positive correlation of capsule weight per plant with the seed weight per plant and a negative correlation with the days to 50% flowering indicates that high yielding linseed varieties with early flowering/maturity could be developed through direct and indirect selection. Further, seed yield and oil content could be enhanced together as indicated by ghe positive association among these two important traits. In this study, high yielding accessions with moderate to high oil content such as GP36, GP31, GP14, GP54, GP26, GP24, GP34, GP21, GP37 and GP27 and early flowering (less than 70 days) accessions such as GP2, GP26, GP27, CG33, CG44, CG42, CG132, and CG31 identified as potential genetic materials that could be exploited for developing early maturing varieties with high yield. In addition, information’s on various genetic parameters will help breeders to devise suitable breeding methodology for linseed genetic improvement for targeted traits.

Common and tartary buckwheat are important cultivated species of the genus Fagopyrum. Genetic polymorphism of thirty-five genotypes of common buckwheat (Fagopyrum esculentum Moench) and tartary buckwheat (Fagopyrum tataricum Gaertn.) was analyzed using 10 random amplified polymorphic DNA (RAPD) primers. A total of 119 DNA fragments were amplified using ten RAPD primers with an average of 11.9 fragments per primer. The number of amplified fragments ranged from 6 (OPB-08) to 16 (SIGMA-D-01). PIC values ranged from 0.782 (OPC-08) to 0.919 (SIGMA-D-01) with an average of 0.871 per primer. The marker index (10.364) and diversity detecting index (2.961) were high and presented the utility of used marker technique. To evaluate the genetic relationships among buckwheat genotypes a phylogenetic tree based on UPGMA algorithm was constructed. The genotypes of common and tartary buckwheat were separated independently into cluster I and II. Cluster I separated 14 genotypes of tartary buckwheat into two subclusters (Ia, Ib). Genotype 903016, which originated in Pakistan, was separated individually into the subcluster Ia. Cluster II included genotypes of common buckwheat and was further subdivided into subcluster IIa and IIb. Two genotypes of subcluster IIb (Bamby and Hruszowska) were genetically the closest. Bamby and Hruszowska reflected the maximum similarity value (0.605) according to Jaccard's coefficient of similarity. Based on the presented data it is suggested that the RAPD technique is suitable for differentiation among genotypes of common and tartary buckwheat. RAPD primers have proven to be reliable and useful method for studying genetic variability of buckwheat genotypes. [ABSTRACT FROM AUTHOR]

For most landslides, several destabilising processes act simultaneously, leading to relative sliding along the soil or rock mass surface over time. A number of machine learning approaches have been proposed recently for accurate relative and cumulative landside displacement prediction, but researchers have limited their studies to only a few indicators of displacement. Determining which influencing factors are the most important in predicting different stages of failure is an ongoing challenge due to the many influencing factors and their inter-relationships. In this study, we take a data-driven approach to explore correlations between various influencing factors triggering slope movement to perform dimensionality reduction, then feature selection and extraction to identify which measured factors have the strongest influence in predicting slope movements via a supervised regression approach. Further, through hierarchical clustering of the aforementioned selected features, we identify distinct types of displacement. By selecting only the most effective measurands, this in turn informs the subset of sensors needed for deployment on slopes prone to failure to predict imminent failures. Visualisation of the important features garnered from correlation analysis and feature selection in relation to displacement show that no one feature can be effectively used in isolation to predict and characterise types of displacement. In particular, analysis of 18 different sensors on the active and heavily instrumented Hollin Hill Landslide Observatory in the north west UK, which is several hundred metres wide and extends two hundred metres downslope, indicates that precipitation, atmospheric pressure and soil moisture should be considered jointly to provide accurate landslide prediction. Additionally, we show that the above features from Random Forest-embedded feature selection and Variational Inflation Factor features (Soil heat flux, Net radiation, Wind Speed and Precipitation) are effective in characterising intermittent and explosive displacement. [ABSTRACT FROM AUTHOR]

Diversity information mining about a crop for different attributes is an essential step for effective breeding programs. The present investigation evaluates the quantum of genetic variability and determines the relationship among the important agro-economic traits based on two years of phenotypic data of 210 accessions of linseed. The traits, capsule weight per plant, capsule per plant, husk weight per plant, and seed weight per plant exhibited comparatively higher genetic coefficient of variation (GCV) and phenotypic coefficient of variation (PCV). In contrast, oil content and seed per capsule exhibited a lower value. The high magnitude of broad sense heritability was observed for all traits except seeds per capsule and husk weight per plant. The trait, capsules per plant, plant height, and days to 50% flowering showed high genetic advance coupled with high heritability. Hierarchical cluster analysis grouped 210 accessions into six distinct clusters. Out of 210, 144 (68.57%) accessions were grouped into three clusters (I, II, and III), in which cluster-III was the largest, containing 64 accessions followed by cluster II and cluster-I. The highest inter-cluster distance was observed between clusters-I and V (127.85), while the lowest was between clusters-II and IV (27.09). The positive correlation of capsule weight per plant with the seed weight per plant and a negative correlation with the days to 50% flowering indicates that high yielding linseed varieties with early flowering/maturity could be developed through direct and indirect selection. Further, seed yield and oil content could be enhanced together as indicated by ghe positive association among these two important traits. In this study, high yielding accessions with moderate to high oil content such as GP36, GP31, GP14, GP54, GP26, GP24, GP34, GP21, GP37 and GP27 and early flowering (less than 70 days) accessions such as GP2, GP26, GP27, CG33, CG44, CG42, CG132, and CG31 identified as potential genetic materials that could be exploited for developing early maturing varieties with high yield. In addition, information's on various genetic parameters will help breeders to devise suitable breeding methodology for linseed genetic improvement for targeted traits. [ABSTRACT FROM AUTHOR]

Mediterranean olive cultivars (Olea europaea), including the historic cultivar 'Mehras,' were analyzed using ISSR to identify and study the genetic relationships among them. Three ISSR primers (UBC-807, ISSR 810, ISSR 825) generated 784 data entries (221 for present and 563 for absent bands), which were analyzed using SPSS and Structure software. Results showed that fragment size ranged between 250 to 1700 bp. The similarity among the fourteen cultivars ranged from 10% between cultivars 'Nabali Muhasan' and 'Arbosana' up to 59% between genotypes 'Qaisi' and 'Kafari Baladi.' When primers were evaluated for their discriminating power, it was found that all of them had a value equal to 1. Moreover, the primer PIC values were 0.29, 0.31, and 0.31 for ISSR 807, ISSR 810, and ISSR 825, respectively. The constructed dendrogram showed four main clades, while Nabali Muhasan did not cluster with any. The first clade clustered included five cultivars. The second clade included four cultivars. Both the third and fourth clades included two cultivars each. The genome structure confirms the dendrogram tree. [ABSTRACT FROM AUTHOR]

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Identification of orchid species is important in orchid conservation. Diversity in orchids can be studied from morphological and anatomical aspects. Observation of morphological characters is easier because it can be done on all plant parts, including stems, flowers, leaves, roots, seeds, and fruit. This research was conducted to study the morphological diversity quantitatively between hybrid Phalaenopsis orchid varieties. The research aims to identify the morphological characteristics of 15 hybrid genotype/accession of Phalaenopsis orchids, followed by descriptor for ornamental orchid plants. Observation variables, including 19 quantitative parameters from leaf characterization and flower characterization. Data analysis was performed using the NTYSYS (Numerical Taxonomy and Multivariate Analysis System) version 2.02i to determine genetic distance; Grouping (cluster) using the UPGMA (Unpair Group of Mean Arithmetic) method. The results of the grouping dendrogram showed that based on the quantitative morphological characters of 15 species of Phalaenopsis hybrid orchids, there were three major groups at 0.92 Dist, namely group I consist of 8 hybrid Phalaenopsis orchids, group II consisted of 6 hybrid Phalaenopsis orchids, and group III only had the P. Shu Long Beauty orchid. P. Shu Long Beauty had the greatest diversity of 1.44 Dist with the other 14 accessions. Taisuko kaaladian "v3" and Dtps. Fullers C-Plus 3790 has a diversity of 0.07. Whereas Dtps. Fullers Sunset has a diversity of 0.90 with the accessions Taisuko kaaladian" v3", Dtps. Fullers C-Plus 3790, P. Red Shoe Ox1408, and P. Ox Black Face Ox1647. [ABSTRACT FROM AUTHOR]

The aim of this article is to study the degradation of a composite material under static pressure. The high pressure condition is similar to the one encountered inside hydrogen tanks. Damage modeling was used to evaluate the behavior of hydrogen tanks to high pressure. A practical approach, coupling a finite element method (FEM) simulation and machine learning (ML) algorithm, is suggested. The representative volume element (RVE) was used in association with a choice of a behavior law and a damage law as an input data. Algorithms for ML classification such as K‐nearest neighbors (k‐NN) and a special k‐NN with a dynamic time warping metric were used. The hierarchical clustering through dendrograms visualizations allowed to exhibit the impact of composite parameters in relation to fiber, matrix properties and fiber volume fraction on the strain degradation under external static pressure. Continuing this, the optimum RVE which shows a low degradation value will be exhibited. [ABSTRACT FROM AUTHOR]

The experience of development banks has led to the conclusion that they directly affect economic growth: projects implementation ensures production of goods and services, creates new workplaces. The growth of gross domestic product is not always inclusive and does not guarantee equal accessibility of all segments of the population to economic opportunities, education, health care, etc. on a constant basis. The Asian Development Bank (hereinafter referred to as the Bank) purposefully influences inclusive economic growth (hereinafter referred to as IEG) in the countries of the Asia-Pacific (hereinafter referred to as APAC) with the help of its own IEG model and allows assessing public administration, economic growth, social support, using 35 indicators, which contributes to reduction of poverty and inequality. For each country the Bank develops its own strategy of cooperation. The authors conducted a hier-archical clustering of the APAC countries based on the values of 24 IEG indicators of the Bank (for two datasets). The APAC countries in each cluster are characterised by approximately the same general level of IEG. The clustering model provides an opportunity to plan projects and assess their influence on IEG, excludes disadvantages of the so-called composite indices that could describe the IEG of a country or region with one value, compensates potential inaccuracies of the basic data.

One of the most important functions of forests is their capacity to store carbon, which varies according to floristic composition, age, and tree density. To provide information that is useful for the carbon inventories, the construction of growth curves for dominant strata within the study area was set as the objective of this work. With data from the National Forest and Soil Inventory 2005-2009 were calculated the IVI by conglomerate and from a dendrogram performed with cluster analysis, using the Ward's linkage method, dominant strata were formed. A growth curve per community was constructed based on the maximum yields per hectare recorded in the forestry management plans, the percentage increases were attributed to volume per species at different ages, which was obtained by ICA through trunk analysis. Five dominant strata were formed; Pinus oocarpa (21.08 % to 54.38 %), Pinus douglasiana (41.45 % to 89.83 %), Pinus devoniana (27.53 % to 63.88 %), Pinus leiophylla (27.53 % to 89.03 %) and Quercus spp. (36.05 % to 93.26 %). The maximum yields for the stands within the study area were 329.98 m3 ha-1, 330.71 m3 ha-1, 171.35 m3 ha-1, 185.22 % and 127. 46 m3 ha-1, respectively. The Pinus oocarpa and Pinus douglasiana dominant strata are had the highest percentage increases in the region due to their historical foment. [ABSTRACT FROM AUTHOR]

Endophytic microorganisms are those that inhabit the interior of plant tissues and organs without causing damage to the plant, triggering a mutualistic interaction. These endophytes are known to produce compounds with various applications in the areas of biotechnology, pharmaceutical industry and agriculture; therefore, molecular methods are used to investigate the phylogeny of these organisms. The Brazilian Cerrado is the second largest biome in Brazil and is considered a hotspot, with a high diversity of endemic fauna and flora. The objective of this work was to analyze, through in silico analysis, the phylogeny of cultivable endophytic fungi isolated from plants found in the Brazilian Cerrado biome. A search was carried out for articles that worked with endophytes in the period between 2012 and 2022. The dendrogram was generated using the Neighbor-joining method based on the ITS1-5.8S-ITS2 conserved region obtained by GenBank codes of isolated endophytes. The genera Xylaria, Diaporthe, and Colletotrichum were isolated in more than three plants in the seven articles found. Most of the articles found related to the biodiversity of endophytic fungi from the Brazilian Cerrado aim at the bioprospecting of bioactive compounds, through culture-dependent methods; as such, a part of endophytic diversity may be lost due to the inability of certain endophytes to grow in artificial media. In silico analysis can assist in the investigation of phylogenetic relationships between endophytic fungi and has the potential to guide future work aimed at prospecting for bioactive compounds, phylogenetic identification, or biodiversity of this group of endophytes. [ABSTRACT FROM AUTHOR]

Clustering is a well-known and studied problem, one of its variants, called contiguity-constrained clustering, accepts as a second input a graph used to encode prior information about cluster structure by means of contiguity constraints i.e. clusters must form connected subgraphs of this graph. This paper discusses the interest of such a setting and proposes a new way to formalise it in a Bayesian setting, using results on spanning trees to compute exactly a posteriori probabilities of candidate partitions. An algorithmic solution is then investigated to find a maximum a posteriori partition and extract a Bayesian dendrogram from it. The interest of this last tool, which is reminiscent of the classical output of a simple hierarchical clustering algorithm, is analysed. Finally, the proposed approach is demonstrated with experiments on simulated data and real applications. A reference implementation of this work is available in the R package gtclust that accompanies the paper. [ABSTRACT FROM AUTHOR]

The production and consumption of vegetables, such as tomatoes, have been growing in recent years, due to the combination of several factors, such as market demand, investment in research, education and awareness about health benefits, as well as government incentives and improvements in cultivation technology. The combination of these factors results in an increasing demand for products that offer health benefits, such as tomatoes rich in antioxidants, which help combat free radicals in cells. To maintain most of the nutritional and sensory properties characteristic of the fresh product, it is important to identify the parameters that will help in maintenance. Thus, the study aims to characterize the influence of different packages and storage times with the variables of tomato. The experiment examined the storage of two tomato derivatives (atomized tomato and chips) using various packaging types and storage durations. It utilized a factorial design (2 × 4) with an extra control treatment, comprising 3 replications. Packaging options included low-density polyethylene plastic bags and laminated plastic bags with aluminum foil, while storage durations ranged from 10 to 40 days. Parameters related to color (°Hue and chroma), flavor (pH, titratable acidity, soluble solids, and maturation index), and bioactive compounds (lycopene and β-carotene) of two tomato derivatives (atomized tomato and chips) were analyzed. After the analyzes, it was observed that the transparent package was the one that allowed the best conservation among the studied variables of the atomized tomato derivative, the same happened for the laminated packaging for the derivative chips. Regarding storage time, 20 days showed the best results regarding the conservation of flavor and bioactive compounds.

Abstract Background Cluster heatmaps are widely used in biology and other fields to uncover clustering patterns in data matrices. Most cluster heatmap packages provide utility functions to divide the dendrograms at a certain level to obtain clusters, but it is often difficult to locate the appropriate cut in the dendrogram to obtain the clusters seen in the heatmap or computed by a statistical method. Multiple cuts are required if the clusters locate at different levels in the dendrogram. Results We developed DendroX, a web app that provides interactive visualization of a dendrogram where users can divide the dendrogram at any level and in any number of clusters and pass the labels of the identified clusters for functional analysis. Helper functions are provided to extract linkage matrices from cluster heatmap objects in R or Python to serve as input to the app. A graphic user interface was also developed to help prepare input files for DendroX from data matrices stored in delimited text files. The app is scalable and has been tested on dendrograms with tens of thousands of leaf nodes. As a case study, we clustered the gene expression signatures of 297 bioactive chemical compounds in the LINCS L1000 dataset and visualized them in DendroX. Seventeen biologically meaningful clusters were identified based on the structure of the dendrogram and the expression patterns in the heatmap. We found that one of the clusters consisting of mostly naturally occurring compounds is not previously reported and has its members sharing broad anticancer, anti-inflammatory and antioxidant activities. Conclusions DendroX solves the problem of matching visually and computationally determined clusters in a cluster heatmap and helps users navigate among different parts of a dendrogram. The identification of a cluster of naturally occurring compounds with shared bioactivities implicates a convergence of biological effects through divergent mechanisms.

This paper presents a significant advancement in information security risk assessment by introducing a flexible and comprehensive model. The research integrates established standards, expert knowledge, machine learning, and ontological modeling to create a multifaceted approach for understanding and managing information security risks. The combination of standards and expert insights forms a robust foundation, ensuring a holistic grasp of the intricate risk landscape. The use of cluster analysis, specifically applying k-means on information security standards, expands the data-driven approach, uncovering patterns not discernible through traditional methods. The integration of machine learning algorithms in the creation of information security risk dendrogram demonstrates effective computational techniques for enhanced risk discovery. The introduction of a heat map as a visualization tool adds innovation, facilitating an intuitive understanding of risk interconnections and prioritization for decision makers. Additionally, a thesaurus optimizes risk descriptions, ensuring comprehensiveness and relevance despite evolving terminologies in the dynamic field of information security. The development of an ontological model for structured risk classification is a significant stride forward, offering an effective means of categorizing information security risks based on ontological relationships. These collective innovations enhance understanding and management of information security risks, paving the way for more effective approaches in the ever-evolving technological landscape.

• Genome sequencing of Primula denticulata at 15X coverage. • 31,584 microsatellite loci were identified, 100 primer pairs were synthesized and tested. Out of these, 64 microsatellite loci were polymorphic. • Cross-species transferability of polymorphic loci was tested in 14 different Primula species. • UPGMA dendrogram showed the phylogenetic relationship among species. • Study aids fast plant diversity assessment for climate vulnerability and conservation. The genus Primula (Primulaceae) harbours habitat-sensitive species. It is a valuable tool for monitoring and assessing the overall state of the ecosystem as it can serve as a reliable indicator of ecological health. Primula denticulata Sm. is one of the most prevalent Primrose species found in the Indian Himalayan region with a wide extent of distribution from 1500 m to 3500 m altitude. Considering the ecological importance of Primulas, it is imperative to develop microsatellite markers to study genetic variability which can offer valuable insights into the adaptive strategies of the plants in response to changing environmental conditions. In this study, we sequenced the P. denticulata genome by utilizing Illumina paired-end sequencing technology at ∼15X coverage. 27,196 sequences harbouring 31,584 microsatellite loci were identified. 100 primer pairs were synthesized and tested for amplification. Impressively, 84 of these primers exhibited robust amplification, and 64 of these displayed polymorphism. Primer pairs from trinucleotide motifs were identified as more polymorphic. To assess the broader applicability of these primers, we also tested cross-species transferability on 14 different Primula species representing different sections of the genus that were collected from different parts of Himalaya. Notably, one SSR locus, Next Generation Sequencing Primula_5 (NGSPr_5) was able to produce bands in all the species showing 100 % transferability. Primula atrodentata showed a maximum (88.23 %) while P. glabra exhibited minimum (19.60 %) cross-transferability. The UPGMA dendrogram clustered different sections of sub-genus Aleuritia , and species from subgenera Sphondylia and Auganthus separately into two major groups. The groupings are in accordance with the known relationship between the different species from the genus. [ABSTRACT FROM AUTHOR]

The pH values of soil samples collected from the topsoil to a depth of 50cm range from 5.78 to 6.64, with an average of 6.284, indicating slightly acidic soil. Water samples near auto-mechanic workshops fall below NSDWQ and WHO standards. Soil heavy metal levels mostly meet ACV and Dutch guidelines, except for Iron (Fe), Copper (Cu), Zinc (Zn), Cadmium (Cd), and Chromium (Cr). Soil contamination analysis shows a high to extreme degree of contamination, likely from the auto-mechanic workshop. Positive correlations between metal pairs suggest a common source and transport to the soil. Principal Component Analysis (PCA) of soil samples reveals Cu, Zn, Fe, Ni, and Pb as dominant metals, while Ni-Cr shows negative correlations with others. In water samples, Cu, Cd, and Co dominate, indicating a different contamination source. Soil and water samples generally meet NSDWQ and WHO standards, but Total Dissolved Solids (TDS), Electrical Conductivity (EC), and Salinity exceed these standards. Understanding these findings is crucial for managing and mitigating contamination risks near auto-mechanic workshops. [ABSTRACT FROM AUTHOR]

Microsatellites were used to evaluate and compare the lineage relationships and genetic diversity of two improved cultivars of corn (Zea mays L.), seven modern native races, and eight archaeological Chimú samples (1.100-1.500 AD) of the North Peruvian coast. Electrophoresis was required to remove the PCR inhibitors from ancient DNA. Eight STR primer pairs generated amplicons from the genome of modern corn, but only five amplified ancient corn DNA. To establish the lineage relationships among samples, the coefficient of similarity of Jaccard and the technique of analysis of conglomerate with binding average were used. Thus, the pattern of genealogical and genetic relationships of the genotypes were determined. Seven out of the eight pairs of SSR primers revealed polymorphism, being 2.47 (range 2-6) the average of polymorphic alleles. The total alleles tested were 23, with 97 polymorphic bands for the modern corn, yet being monomorphic for the Chimú corn, generating an average of genetic similarity of 0.44 and 1, respectively. These results suggest the existence of inbreeding in some populations of Chimú corn of the north coast of Peru 500 to 900 years ago. Modern races exhibited higher polymorphism, due to hybridization and better assisted selection, in agreement with cytogenetic data. [ABSTRACT FROM AUTHOR]

Which came first, the chicken or the egg? That is not a pun, joking or irrelevant question. Two hypotheses have tried to answer it. The first, and accepted for years, proposes that the evolutionary process went from oviparity, through an Embryonic Retention (ER) phase, to viviparity. In other words, the simpler egg came first, which hatched into the more complex chicken. That is known as the terrestrial model. Indeed, fishes typically lay eggs, albeit some sharks are viviparous. Even some living (extant) mammals are oviparous, (monotremes like platypus and echidnas). But new evidence has challenged such traditional view, proposing that it was the other way round. Thus, first came the chicken, which eventually laid the egg. That is the Extended Embryo-Retention (EER) model. In the first evolutionary step of this scenario, ancient reptiles, birds and mammals gave birth to offspring. Subsequently, some of them developed oviparity. Indeed, several archaeological and phylogenetic discoveries have shown that first, during the ER period, thin layers of tissues (extraembryonic membranes) evolved for a better development of the embryo, given rise to the amniotes. It is known that living reptiles (like crocodiles and turtles) and birds typically show non-EER oviparity. But curiously, most lizards, snakes and mammals exhibit oviparity with EER or viviparity. While the debate continues, both archaeology and molecular biology will contribute to clarify this interesting topic. [ABSTRACT FROM AUTHOR]

Which came first, the chicken or the egg? That is not a pun, joking or irrelevant question. Two hypotheses have tried to answer it. The first, and accepted for years, proposes that the evolutionary process went from oviparity, through an Embryonic Retention (ER) phase, to viviparity. In other words, the simpler egg came first, which hatched into the more complex chicken. That is known as the terrestrial model. Indeed, fishes typically lay eggs, albeit some sharks are viviparous. Even some living (extant) mammals are oviparous, (monotremes like platypus and echidnas). But new evidence has challenged such traditional view, proposing that it was the other way round. Thus, first came the chicken, which eventually laid the egg. That is the Extended Embryo-Retention (EER) model. In the first evolutionary step of this scenario, ancient reptiles, birds and mammals gave birth to offspring. Subsequently, some of them developed oviparity. Indeed, several archaeological and phylogenetic discoveries have shown that first, during the ER period, thin layers of tissues (extraembryonic membranes) evolved for a better development of the embryo, given rise to the amniotes. It is known that living reptiles (like crocodiles and turtles) and birds typically show non-EER oviparity. But curiously, most lizards, snakes and mammals exhibit oviparity with EER or viviparity. While the debate continues, both archaeology and molecular biology will contribute to clarify this interesting topic. [ABSTRACT FROM AUTHOR]

Microsatellites were used to evaluate and compare the lineage relationships and genetic diversity of two improved cultivars of corn (Zea mays L.), seven modern native races, and eight archaeological Chimú samples (1.100-1.500 AD) of the North Peruvian coast. Electrophoresis was required to remove the PCR inhibitors from ancient DNA. Eight STR primer pairs generated amplicons from the genome of modern corn, but only five amplified ancient corn DNA. To establish the lineage relationships among samples, the coefficient of similarity of Jaccard and the technique of analysis of conglomerate with binding average were used. Thus, the pattern of genealogical and genetic relationships of the genotypes were determined. Seven out of the eight pairs of SSR primers revealed polymorphism, being 2.47 (range 2-6) the average of polymorphic alleles. The total alleles tested were 23, with 97 polymorphic bands for the modern corn, yet being monomorphic for the Chimú corn, generating an average of genetic similarity of 0.44 and 1, respectively. These results suggest the existence of inbreeding in some populations of Chimú corn of the north coast of Peru 500 to 900 years ago. Modern races exhibited higher polymorphism, due to hybridization and better assisted selection, in agreement with cytogenetic data. [ABSTRACT FROM AUTHOR]

This research focused on analyzing the biometric, colorimetric and morphological characteristics of thirty seeds, covering legumes, cereals and oilseeds. Thirteen legumes, fourteen cereals and three oilseeds were collected from three different locations. The methodology used was descriptive, applying multivariate multiple factorial and cluster analysis. The results showed variability between biometric, chromatic and morphological characteristics among the seeds. Predominant shapes include circular, oval, oblong, less frequently kidney and lanceolate. Significant differences in biometric parameters stand out, evidencing similarities in colorimetric parameters. Specifically, Pallar and Bean exhibited greater equatorial dimensions, length, weight, 100 g weight, area and perimeter, While peanut and Chickpea presented greater thickness. In terms of colorimetry - luminosity, Pallar, Yellow corn and Tarwi presented higher values unlike Black lentils, Purple corn and Black beans, being less luminous. Multivariate tests revealed the formation of four groups based on the parameters studied. This study provides valuable information about the different seeds, establishing a basis for their propagation and improvement in the Peruvian context.

Introduction. Up-to-date data and full characterization of circulating ASFV isolates play a crucial role in virus eradication and control in endemic regions and countries. The aim of the study was to evaluate and characterize the molecular and biological properties of the ASFV isolate ASF/Tatarstan 20/WB-12276, conduct phylogenetic analysis, and compare the results with isolates circulating in Europe and Asia. Materials and methods. For bioassay, eight heads of the Large White pigs weighing 1520 kg/head were used. Detection of specific anti-ASFV antibodies by ELISA and immunoperoxidase method. Detection of ASFV genome was performed by qPCR. Isolation of ASF/Tatarstan 20/WB-12276 and determination of titer were performed in pig spleen cell culture. Sequencing was carried out by the Sanger method. Results. The virus was characterized as highly virulent and capable of causing acute to subacute forms of ASF. Phylogenetic analysis revealed substitutions in the genome of the ASF/Tatarstan 20/WB-12276 isolate (IGR/I73R-I329L and I267L markers) that supported the clustering of the studied variant with isolates prevalent in most of Europe and Asia. Conclusion. For the first time, the molecular and biological properties of the ASF/Tatarstan 20/WB-12276 virus isolate taken from a wild boar shot on the territory of the Republic of Tatarstan were studied and analyzed.

For most landslides, several destabilising processes act simultaneously, leading to relative sliding along the soil or rock mass surface over time. A number of machine learning approaches have been proposed recently for accurate relative and cumulative landside displacement prediction, but researchers have limited their studies to only a few indicators of displacement. Determining which influencing factors are the most important in predicting different stages of failure is an ongoing challenge due to the many influencing factors and their inter-relationships. In this study, we take a data-driven approach to explore correlations between various influencing factors triggering slope movement to perform dimensionality reduction, then feature selection and extraction to identify which measured factors have the strongest influence in predicting slope movements via a supervised regression approach. Further, through hierarchical clustering of the aforementioned selected features, we identify distinct types of displacement. By selecting only the most effective measurands, this in turn informs the subset of sensors needed for deployment on slopes prone to failure to predict imminent failures. Visualisation of the important features garnered from correlation analysis and feature selection in relation to displacement show that no one feature can be effectively used in isolation to predict and characterise types of displacement. In particular, analysis of 18 different sensors on the active and heavily instrumented Hollin Hill Landslide Observatory in the north west UK, which is several hundred metres wide and extends two hundred metres downslope, indicates that precipitation, atmospheric pressure and soil moisture should be considered jointly to provide accurate landslide prediction. Additionally, we show that the above features from Random Forest-embedded feature selection and Variational Inflation Factor features (Soil heat flux, Net radiation, Wind Speed and Precipitation) are effective in characterising intermittent and explosive displacement.

Arsenic is naturally found in the rocks of the Pleistocene and Holocene ages in the groundwater aquifer media. The district Ballia has many reports which are focused on arsenic contamination in its different blocks. This article is devoted to a thorough study of hydrogeochemical characteristics and the source of origin of arsenic in the groundwater system of the Ballia district. The relationship between this hydrogeologically present arsenic and various cations and anions including some physicochemical parameters are discussed here. These observations have been done using ICP MS and ion chromatographic techniques. The relationship study has been done by using a correlation matrix which is further proven by the dendrogram. Different types of loading plots of various principal components have also been studied with the help of principal component analysis. The nature and quality of groundwater are studied with the help of a piper plot. This research article is a complete and detailed study of the nature of groundwater in district Ballia. It also enlightens the source of arsenic contamination in the study area. HIGHLIGHTS The sampling area is 16 blocks of district Ballia, U.P. India.; The physicochemical studies have been done by ICP MS and ion chromatograph.; The quality of the groundwater samples was examined with the help of a piper plot.; The water sample shows various positive correlations with different ions which are found in it.; The relationship of As with other ions could be helping in its removal.;

Background: Healthcare-associated infections appear in a patient receiving medical attention at a hospital or other healthcare facility and develops infections that weren't present when they were admitted. One of the most important organisms causing infections acquired in hospitals is Staphylococcus aureus (S. aureus). For many bacterial species, Random Amplified Polymorphic DNA (RAPD) is a low-cost but effective typing technique. Objectives: To determine the genotypic polymorphism, the level of genetic relatedness, and the antimicrobial sensitivity and resistance among various S. aureus isolates. Methods: The following tests were performed on 50 samples that were obtained using strict aseptic precautions: sample culture, isolate identification using colony morphology, Gram stained film, biochemical responses, and antibiotic susceptibility testing. After RAPD-PCR, Syngene gene tool software was used to analyse the fingerprint pattern. Results: The most prevalent isolated organism was S. aureus. as it represented (70%) of isolated pathogens. Vancomycin and linezolid were effective against S. aureus isolates. The isolates of S. aureus were more common in nasal swab (42.9%) followed by wound (28.5%) then urine &endotracheal aspirate (14.3%). Patterns of RAPD-PCR of S.aureus isolates generated with primer GEN1-50-01 (5’GTGCAATGAG-3’) resulting in several polymorphic bands and a dendrogram was created. Conclusions: S. aureus is an important cause of HCAI, Health care workers represent an important source of HCAI, RAPD –PCR technique was an easy and rapid one to perform with a good discriminatory power in typing (fingerprinting) of Staphylococcus aureus.

Coffee is a perennial plant planted on Bangka Island by farmers. Exploration of coffee plants was carried out to see several developed varieties that could be grown on Bangka Island. This study aims to determine the diverse morphological character, phenetic relationship, and variability of folk coffee plants in Bangka. This research was conducted in October 2021-April 2022 in Bangka, Central Bangka and South Bangka. This research was conducted using explorative and descriptive methods. Sampling is carried out randomly to determine the sampling location and data collection. The data from quantitative research were analyzed using variability, while phenetic relationships were analyzed using the UPGMA method (uneweighted pair group method with arithmetic mean) with the NTSYS-pc application (numerical taxonomy software and multivariate analysis system). The results of the analysis of phenetic relationships of qualitative characters resulted in a degree of similarity of coefficients at 53% within coffee of melabun, kota kapur, puput and paku. Analysis of quantitative and combined character phenetic relationships between coffee and puput resulted in a degree of co-efficiency similarity at 25% and 42%. The variability of quantitative character analysis is widespread on plant height and number of flowers per node.

The Ann Arbor system is disadvantaged in utilizing information from additional prognostic factors. In this study, we applied the Ensemble Algorithm for Clustering Cancer Data (EACCD) to create a prognostic system for lymphoma that integrates additional prognostic factors. Hodgkin and non-Hodgkin lymphoma survival data were extracted from the Surveillance, Epidemiology, and End Results Program of the National Cancer Institute and divided into the training set (131,725 cases) and the validation set (15,683 cases). Five prognostic factors were studied: Ann Arbor stage, type, site, age, and sex. EACCD was applied to the training set to produce a prognostic system, called an EACCD system, for convenience. The EACCD system stratified patients into eight prognostic groups with well-separated survival curves. These eight prognostic groups had significantly higher accuracies in survival prediction than the 24 Ann Arbor substages. A higher-risk group in the EACCD system roughly corresponds to a higher Ann Arbor substage. The proposed system shows a good performance in risk stratification and survival prediction on both the training and the validation sets. The EACCD system expands the traditional Ann Arbor staging system by leveraging additional prognostic information and is expected to advance treatment management for lymphoma patients.