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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]

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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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.

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]

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]

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 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.

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.

Background: Variety characterization is the foremost important step that should be done by breeders to classify a variety into distinct groups. A significant technique for locating and assessing several genotypes for the registration, protection and production of seeds of superior quality is the Distinctness, Uniformity and Stability (DUS) characterization. Consequently, the current investigation aimed to use DUS descriptors to describe and assess the variance present in mungbean genotypes. Methods: One hundred forty-two mungbean genotypes were examined using 21 agro-morphological qualitative DUS descriptors in a randomized block design with two replications across two seasons, kharif 2021 and kharif 2022. Result: In the twenty-one DUS traits that were examined, four characters' plant growth habit, leaf shape, leaf size and seed size exhibited trimorphic variance. Three characters (plant habit, stem pubescence and pod pubescence) were found to be identical among all genotypes while fourteen characters displayed dimorphic variance. All of the mungbean genotypes displayed a significant degree of variance for all DUS characteristics. Based on the UPGMA method of clustering, the dendrogram classified all the one hundred forty-two genotypes into three major clusters. The presence of variation among the genotypes under study was demonstrated by the further classification of these primary clusters into five sub-clusters. The majority of the genotypes were found in cluster II (121 genotypes), which was followed by cluster I (18 genotypes) and cluster III (3 genotypes). [ABSTRACT FROM AUTHOR]

• 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]

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.

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.

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.

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]

• Characteristic elements of papyrus fragments removed from ancient cartonnage. • The difference in the elemental compositions of papyrus from cartonnage through three age groups during Ptolemaic Period. • The composition of the preparation layer of cartonnage remained on papyrus fragments. • Dendrogram helps in dating papyrus. Papyrus was used as a writing support from 2500 BC to the 11th century AD to record and transfer information both in Egypt (where it has predominantly survived) and the wider Mediterranean and Near Eastern world. During the Ptolemaic and early Roman periods in Egypt (c. 322 BC-14 AD), discarded written papyri were recycled and widely used as a support to make cartonnage, which was a glued encasement to protect mummified bodies. This research investigates the elemental characteristics of papyri known or believed to have come from cartonnage, in order to understand how that usage might have changed the elemental compositions of those papyri. In this research, the elemental compositions of ink, no-ink and "white" areas (where observed) were characterised using X-ray fluorescence spectrometry in twenty papyri. Inked areas have significantly greater concentrations of lead than areas of papyri with no ink, and X-ray diffractometry revealed that calcite (CaCO 3) formed the white compound of the preparation layer of the cartonnage. Changes in ink composition may have the potential to be used as a technique for dating papyri. [Display omitted] [ABSTRACT FROM AUTHOR]

Context: Preservation of genetic diversity of species is a pressing issue; in particular, the preservation of the gene pool of many rare and endangered plants is a priority. Species of the genus Crambe (family Brassicaceae) have potential in agriculture and bioremediation. Aims: This study aims to assess the genetic diversity and DNA fingerprint of five rare species of the genus Crambe , and to develop the concept of a genetic passport for rare plants. Methods: DNA fingerprinting was conducted via the inter simple sequence repeat (ISSR) method, using six ISSR primers. Hierarchical cluster analysis of the species was performed. Key results: In total, 145 polymorphic loci were detected. The studied species formed two different clusters on genetic dendrogram analysis. The first cluster comprised two species, Crambe steveniana and C. tataria from a single subsection (Tatariae), forming a common clade. They were the most genetically close species with genetic similarity of 0.8431. The remaining three species (C. cordifolia , C. maritima , C. pinnatifida), from another subsection of Crambe , formed nodes from the general clade. Conclusions: The findings allow plants to be genetically certified using our methods and informative ISSR primers for rare plants. We were able to propose a genetic formula identifying a species and present an example of a genetic passport for rare plants. The genetic structure of C. pinnatifida was investigated for the first time. Implications: The present findings contribute to the systematics and critical investigation of rare plant species with genetic resource potential. A genetic passport could be used in the protection of copyright of agricultural varieties. We assessed the genetic diversity and DNA fingerprint of five rare species of the Brassicaceae genus Crambe , using six inter simple sequence repeat primers. The species could be clustered into two groups according to subsection of Crambe. The results demonstrate that the methods allow rare plants to be genetically certified. [ABSTRACT FROM AUTHOR]

Pomegranate (Punica granatum L.) is an ancient edible fruit crop well recognized for its immense nutraceutical and medicinal properties. Precise morphological characterization of wild, exotic and commercial (cultivar) varieties and understanding the molecular variability in perennial crops like pomegranate is essential for developing varietal DNA fingerprints, identifying true-to-type of genotypes, to avoid duplication and overcome the problem of clonal admixture. It has become a challenge to identify varieties based solely on observable phenotypic traits due to dynamic environmental factors that influence physical traits and increasing number of varieties. Hence, the implementation of stable molecular markers is the best complementary biotechnological tool, which fulfil the above requirements. In our first objective, we identified 24 polymorphic SSR markers out of 40. These SSRs screened on 13 different varieties of pomegranate. The PIC value ranged from 0.13 to 0.37 (mean 0.25) and heterozygosity percent ranged from 0.14% to 0.50% (mean 0.35%). Highest PIC value and heterozygosity observed in PgSSR78 marker. Similarity coefficient matrix showed the genetic distance between the twenty-four varieties, ranged from 0.58 to 0.99. Maximum similarity was observed between Alah and Khandari. Minimum similarity was found between IC318743 and 1185 followed by Maha and 1185. PgSSR16, PgSSR23, PgSSR49, PgSSR60, PgSSR32, PgSSR40, PgSSR78 markers were found with high PIC value and heterozygosity and these primers could be useful for pomegranate cultivar identification. From this study, microsatellite markers have proven to be very useful marker for developing varietal identification marker at early growth stage due to its high polymorphism, abundance, multi-allelic and co-dominant inheritance. [ABSTRACT FROM AUTHOR]

This is aimed at assessing the effect of the analysed physico-chemical, microbial parameters and heavy metals on run-off in selected routes at Nsukka Urban. The major roads selected included campus gate (CG), Ikenga road (IR), Enugu road (ER) and Ikpa/Orba road (IKPR); with university market road serving as control location (C). Four run-off samples were collected from each of the selected roads; in October 2020. The heavy metals were analysed using the Atomic Absorption Spectrophotometer (AAS); other parameters were analysed using standard methods. The results revealed that the analysed metals concentrations ranges from (in ppm): Cd (0.00–0.09), As (0.23–1.58 mg/L), Fe (6.48–79.72), Hg (.00–3.00), Pb (0.25–0.75), Ni (0.21–0.92), Mn (0.10–0.21), and Cr (0.67– 01.33) indicating increase in the concentration of samples as against control showing anthropogenic influences. The results also unravelled that metal concentrations are above the permissible standards for potable water. Coliform ranged (0.00–1736.00 cfu/mL), Turbidity (22.50–52.80 NTU) and Organic matter (55–130 mg/l). All other parameters like pH, EC, K+, Mg2+, and Na+ are all within the permissible limit of WHO. Multivariate and Sorensen analyses were also employed to separate chemical variables into components which gave a clue to the different sources of contaminants within an area, based on the indicator parameter associations. This analysis unravels anthropogenic contamination from domestic solid and sewage wastes on the quality of surface run-off and should be mitigated. [ABSTRACT FROM AUTHOR]

The study focused on isolating indigenous Qatari lactic acid bacteria (LAB) from various challenged date palm tree leaf silages to construct a comprehensive strain collection, useful to study the diversity of these strains following their adaptation to the uncommon silage. Matrix-assisted laser desorption ionization-time of flight mass spectrometry (MALDI–TOF MS) was employed for strain identification and differentiation. The diversity of LAB populations and strains was assessed through principal component analysis (PCA) and dendrogram analyses. A total of 88 LAB isolates were obtained from silages of fresh palm leaves, silage of mixed leaves and dairy feed, along with fresh palm tree leaves, and dairy feed, adapted to local harsh environments. These isolates were categorized according to the new classification of 2020, belonging to genera of Pediococcus, Lactiplantibacillus plantarum, Lacticaseibacillus paracasei, Companilactobacillus farciminis, Limosilactobacillus oris, Limosilactobacillus vaginalis, Lactiplantibacillus pentosus and Lactobacillus johnsonii. Pediococcus was the most prevalent genus, falling mostly within the species Pediococcus lolii. MALDI–TOF MS protein profiles, PCA, and dendrogram analyses successfully grouped the LAB isolates into five distinctive clusters based on the protein's similarities. The high diversity of the indigenous LAB in spontaneous palm leaf silages demonstrated their adaptation and mutualistic interactions, forming robust consortia that ensure the quality of the silage. The straightforward, quick, and accurate identification of LAB in this silage using MALDI–TOF MS presents a valuable approach for formulating LAB consortia for silaging harsh agricultural by-products.

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.

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.

Abstract. Enhancement of okra fruit production requires identification of genotypes with promising seed yield attributes, thus multivariate techniques were employed to reveal genetic and morphological attributes of sixteen diverse okra lines during wet and dry seasons in 2019 at Teaching and Research Farm, College of Agriculture, Osun State University, Ejigbo Campus. Seeds were sown in single-row plots of 5 m long, spaced 0.70 m apart and 0.50 m within on sandy loam soil in a randomized complete block design. The dry season crop was supported by the application of 12 mm water weekly. Data collected on growth and seed traits were subjected to the General Linear Model (GLM), principal component analysis (PCA), and cluster analysis using the Statistical Analysis System (SAS, 2018). The petiole color was scored according to IPGRI (1991) square root transformed prior to the analysis. Results showed highly significant lines, season, and their interactions for almost all traits. Four PCAs accounted for 85.77% and the first two PCA captured 51% of the total variations. Both PCA and cluster analysis grouped the lines into four and revealed the potentials of SAHARI F1, NGB01197, and LD-88 for high seed yield. It is concluded that these lines can be incorporated into okra yield improvement program.

Power systems need reactive power support to withstand voltage instability issues. The Volt Ampere reactive (VAr) resources are to be optimally determined for location and size. Generally, candidate locations are determined based on the ranking of buses according to sensitivity indices, and the Trajectory Sensitivity Index (TSI) is the most widely used sensitivity index. However, the locations identified by ranking the buses at the system level using the TSI method do not guarantee an optimal VAr solution. The recent methods based on dividing the power system into zones address the issue of optimality. The prevailing zoning methods are based on the computation of the electrical distance between buses and do not address the zoning scenario where the electrical distance between the buses is indeterminable. This paper introduces a new multistage algorithm for grouping the buses into zones even when the electrical distance is indeterminable. The new proposed strategy encompasses applying proposed analytical and parametric techniques after the standard clustering steps. A new index, namely the Bilateral Sensitivity Index (BSI), is introduced to quantify the proximity of buses. The TSI-based zonal level ranking of buses is introduced. The proposed strategy demonstrates that when TSI is employed to rank the buses at the zonal level rather than at the system level, it helps towards an optimal VAr solution. The new multistage clustering strategy is integrated into the generalized Dynamic Voltage Stability Analysis (DVSA) framework for optimal VAr determination and applied to study the voltage collapse phenomenon on a practical 24-bus system in the southern part of India. The results demonstrate the proposed approach’s efficacy in mitigating voltage instability issues through optimal VAr support.

The results of long-term geochemical studies of the content of metals: aluminum, mercury, chromium, manganese, iron, zinc, cobalt, nickel and vanadium are presented, as well as the total concentration of these metals and sulfur in oils from 36 deposits of the main oil and gas-bearing region of Ukraine – the Dnipro-Donetsk Basin. The purpose of the research was to develop a classification of oil deposits on the example of the Dnipro-Donetsk basin based on geochemical studies of metal content and their cluster analysis, which can be used as the strictest criterion for dividing them into two fundamentally different groups – deposits formed mainly by oils of biogenic origin and deposits that contain oil of essentially abiogenic generation. According to the results of the cluster analysis, natural classifications of these deposits were developed for the first time according to the listed indicators and the V/Ni ratio, which are presented in the work in the form of dendrograms. It is shown that according to the results of the cluster analysis, the sample mean values of the analyzed indicators, which differ significantly between individual deposits or groups of deposits in the established series, can be interpreted in the terminology of qualitative assessment as: abnormally low; low; below average; average; above average; high; abnormally high. The analysis of the research results and their interpretation in the genetic sense with comparison with three different geochemical criteria of the relationship of the origin of oil to abiogenic or biogenic sources of petrogenesis according to the existing ideas made it possible to establish, firstly, the deposits that, according to each of these ideas, belong to those formed mainly by abiogenic matter, second, to establish and analyze coincidences and differences in the list of these deposits. It is substantiated that the comparative analysis of the results of the clustering of the considered deposits by the content of such abiogenic elements as Al and Hg in the oils according to the results of their clustering by the concentrations of V, Cr and Co shows that the totality of the deposits belonging to the clusters with high and abnormally high content of V, Cr and Co differs from the list of deposits with high and abnormally high concentrations of Al and Hg only in the absence of the Yuryivskyi deposit, and they completely coincide with each other.Thus, high and abnormally high contents of V, Cr and Co in the oils of the studied fields, based on the logic of previous studies, can be used as a stricter criterion for dividing them into two fundamentally different groups – fields formed mainly by oils of biogenic origin and fields containing oil significantly abiogenic generation. In this regard, according to the previously established laws, it makes sense to consider as a criterion the selection of deposits with oil of essentially abiogenic origin besidesto the concentrations of V, Cr and Co, also ratios of Co/Ni and Cr/Ni.

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. [ABSTRACT FROM AUTHOR]