Genetic Diversity Associated with Eco-geographical Parameters, Morphological Characteristics and Soil Analyzes of Common Vetch (Vicia sativa L.) in Algeria

Background: In the present study, we have set a goal, to study the genetic variability and phylogenetic affinities of 26 spontaneous Vicia sativa L. accessions collected in Algeria, as part of the recovery and enhancement of the local genetic heritage and its integration into the breeding and varietal creation programs. Methods: Morphological traits, performance parameters and phenological stages of each accession were tracked during an experimental test in pots under greenhouse conditions from December 29, 2019 to June 1, 2020. An eco-geographical characterization of samples was also carried out through geographical coordinates. On the other side and for the first time in Algeria, soil analyses of each site were undertaken. Result: The phylogenetic study of accessions confirm the taxonomic complexity of the group V. sativa L. According to the principal component analyses and kruskal-Wallis test, the most segregating variables with the highest values and the largest K variance ratios are most of the attributes associated with the flower, pod and seed. The association of the two dissimilarity matrix carried out by a Mantel test between the morphological and eco-geographic parameters showed a significant effect with a p value = 0.004 at the threshold of alpha=0.05 and a correlation coefficient r (AB) = 0.156.

The rumen liquid metatranscriptome of post-weaned dairy calves differed by pre-weaning ruminal administration of differentially-enriched, rumen-derived inocula

Background Targeted modification of the dairy calf ruminal microbiome has been attempted through rumen fluid inoculation to alter productive phenotypes later in life. However, sustainable effects of the early life interventions have not been well studied, particularly on the metabolically active rumen microbiota and its functions. This study investigated the sustained effects of adult-derived rumen fluid inoculations in pre-weaning dairy calves on the active ruminal microbiome of post-weaned dairy calves analyzed via RNA-sequencing. Results Two different adult-derived microbial inocula (bacterial- or protozoal-enriched rumen fluid; BE or PE, respectively) were administered in pre-weaned calves (3–6 weeks) followed by analyzing active rumen microbiome of post-weaned calves (9 weeks). The shared bacterial community at the genus level of 16S amplicon-seq and RNA-seq datasets was significantly different (P = 0.024), 21 out of 31 shared major bacterial genera differed in their relative abundance between the two analytic pipelines. No significant differences were found in any of the prokaryotic alpha- and beta-diversity measurements (P > 0.05), except the archaeota that differed for BE based on the Bray–Curtis dissimilarity matrix (P = 0.009). Even though the relative abundances of potentially transferred microbial and functional features from the inocula were minor, differentially abundant prokaryotic genera significantly correlated to various fermentation and animal measurements including butyrate proportion, body weight, and papillae length and counts. The overall microbial functions were affected quantitatively by BE and qualitatively by PE (P < 0.05), and this might be supported by the individual KEGG module and CAZymes profile differences. Exclusive networks between major active microbial (bacterial and archaeal genera) and functional features (KEGG modules) were determined which were differed by microbial inoculations. Conclusions This study demonstrated that actively transcribed microbial and functional features showed reliable connections with different fermentations and animal development responses through adult rumen fluid inoculations compared to our previous 16S amplicon sequencing results. Exclusive microbial and functional networks of the active rumen microbiome of dairy calves created by BE and PE might also be responsible for the different ruminal and animal characteristics. Further understanding of the other parts of the gastrointestinal tract (e.g., abomasum, omasum, and small intestine) using metatranscriptomics will be necessary to elucidate undetermined biological factors affected by microbial inoculations.

Semantic Based Weighted Web Session Clustering Using Adapted K-Means and Hierarchical Agglomerative Algorithms

The WWW has a big number of pages and URLs that supply the user with a great amount of content. In an intensifying epoch of information, analysing users browsing behaviour is a significant affair. Web usage mining techniques are applied to the web server log to analyse the user behaviour. Identification of user sessions is one of the key and demanding tasks in the pre-processing stage of web usage mining. This paper emphasizes on two important fallouts with the approaches used in the existing session identification methods such as Time based and Referrer based sessionization. The first is dealing with comparing of current request’s referrer field with the URL of previous request. The second is dealing with session creation, new sessions are created or comes in to one session due to threshold value of page stay time and session time. So, authors developed enhanced semantic distance based session identification algorithm that tackles above mentioned issues of traditional session identification methods. The enhanced semantic based method has an accuracy of 84 percent, which is higher than the Time based and Time-Referrer based session identification approaches. The authors also used adapted K-Means and Hierarchical Agglomerative clustering algorithms to improve the prediction of user browsing patterns. Clusters were found using a weighted dissimilarity matrix, which is calculated using two key parameters: page weight and session weight. The Dunn Index and Davies-Bouldin Index are then used to evaluate the clusters. Experimental results shows that more pure and accurate session clusters are formed when adapted clustering algorithms are applied on the weighted sessions rather than the session obtained from traditional sessionization algorithms. Accuracy of the semantic session cluster is higher compared with the cluster of sessions obtained using traditional sessionization.

Spectral Clustering of Mixed-Type Data

Cluster analysis seeks to assign objects with similar characteristics into groups called clusters so that objects within a group are similar to each other and dissimilar to objects in other groups. Spectral clustering has been shown to perform well in different scenarios on continuous data: it can detect convex and non-convex clusters, and can detect overlapping clusters. However, the constraint on continuous data can be limiting in real applications where data are often of mixed-type, i.e., data that contains both continuous and categorical features. This paper looks at extending spectral clustering to mixed-type data. The new method replaces the Euclidean-based similarity distance used in conventional spectral clustering with different dissimilarity measures for continuous and categorical variables. A global dissimilarity measure is than computed using a weighted sum, and a Gaussian kernel is used to convert the dissimilarity matrix into a similarity matrix. The new method includes an automatic tuning of the variable weight and kernel parameter. The performance of spectral clustering in different scenarios is compared with that of two state-of-the-art mixed-type data clustering methods, k-prototypes and KAMILA, using several simulated and real data sets.

Genomics Reveal Admixture and Unexpected Patterns of Diversity in a Parapatric Pair of Butterflies

We studied the evolutionary relationship of two widely distributed parapatric butterfly species, Melitaea athalia and Melitaea celadussa, using the ddRAD sequencing approach, as well as genital morphology and mtDNA data. M. athalia was retrieved as paraphyletic with respect to M. celadussa. Several cases of mito-nuclear discordance and morpho-genetic mismatch were found in the contact zone. A strongly diverged and marginally sympatric clade of M. athalia from the Balkans was revealed. An in-depth analysis of genomic structure detected high levels of admixture between M. athalia and M. celadussa at the contact zone, though not reaching the Balkan clade. The demographic modelling of populations supported the intermediate genetic make-up of European M. athalia populations with regards to M. celadussa and the Balkan clade. However, the dissimilarity matrix of genotype data (PCoA) suggested the Balkan lineage having a genetic component that is unrelated to the athalia-celadussa group. Although narrowly sympatric, almost no signs of gene flow were found between the main M. athalia group and the Balkan clade. We propose two possible scenarios on the historical evolution of our model taxa and the role of the last glacial maximum in shaping their current distribution. Finally, we discuss the complexities regarding the taxonomic delimitation of parapatric taxa.

Comparative Assessment of Hierarchical Clustering Methods for Grouping in Singular Spectrum Analysis

Singular spectrum analysis (SSA) is a popular filtering and forecasting method that is used in a wide range of fields such as time series analysis and signal processing. A commonly used approach to identify the meaningful components of a time series in the grouping step of SSA is the utilization of the visual information of eigentriples. Another supplementary approach is that of employing an algorithm that performs clustering based on the dissimilarity matrix defined by weighted correlation between the components of a time series. The SSA literature search revealed that no investigation has compared the various clustering methods. The aim of this paper was to compare the effectiveness of different hierarchical clustering linkages to identify the appropriate groups in the grouping step of SSA. The comparison was performed based on the corrected Rand (CR) index as a comparison criterion that utilizes various simulated series. It was also demonstrated via two real-world time series how one can proceed, step-by-step, to conduct grouping in SSA using a hierarchical clustering method. This paper is supplemented with accompanying R codes.

Essential oils of Eplingiella fruticosa populations: chemical, antioxidant, and cytotoxic analyses

This study investigates the variations in the chemical profiles and biological activities (antioxidant and cytotoxic) of Eplingiella fruticosa from the state of Sergipe, an endemic species from the Northeast region of Brazil. The essential oils were extracted from six populations by hydrodistillation and analyzed by GC/MS-FID. Cluster analysis was performed with the data of the constituents of the essential oils, and then a dissimilarity matrix, based on Euclidean distances, and a dendrogram, through the Ward clustering method, were constructed. The antioxidant activity of the essential oils was tested by different assays (DPPH, ABTS, β-carotene, and FRAP), and cytotoxic activity was tested by the SRB assay. The compounds found in greater amounts were α-pinene, β-pinene, 1,8-cineole, camphor, borneol, δ-elemene, α-cubebene, α-ylangene, (E)-caryophyllene, germacrene D, bicyclogermacrene, trans-calamenene, spathulenol, caryophyllene oxide, and viridiflorol. These compounds defined the formation of two groups. The first group was composed of the populations of São Cristóvão, Itaporanga, Japaratuba, and Malhada dos Bois municipalities and was characterized by the presence of the monoterpene camphor (8.39-11.27%) as the compound of greatest concentration in relation to the other municipal areas. The second group was composed of the populations of Moita Bonita and Pirambu municipalities and was characterized by the major presence of the sesquiterpene bicyclogermacrene (7.45% and 10.98%). The plants exhibited weak effects in terms of antioxidant activity; however, the essential oil showed significant toxicity for the lines A549 (51.00% cell viability) in the population of Japaratuba, and B16F10 (64.94% cell viability) in Malhada dos Bois. The observations of this study may open a way to optimize the use of the E. fruticosa populations in relation to their cytotoxic properties.

Construction of E-commerce Personalized Information Recommendation System in the Era of Big Data

With the continuous expansion of the scale of e-commerce, personalized recommendation technology has been widely used. However, the traditional recommendation system has been unable to meet the current needs of data processing, and good big data processing ability has become the basic requirement of the new personalized recommendation system. In addition, traditional recommendation systems are often limited to tangible goods recommendation, and pay less attention to e-commerce logistics service recommendation. In this paper, through the in-depth study of information personalized recommendation service in e-commerce environment, combined with the application background of big data: Taking the user dissimilarity matrix as the recommendation model, we propose IU usercf and UDB slope one recommendation algorithm. The two algorithms based on incremental update recommendation model have good scalability, can effectively deal with big data, and have high prediction accuracy. The proposed algorithm is applied to the actual system, taking e-commerce logistics service as the recommendation object and iu-usercf as the recommendation algorithm, the personalized recommendation system for e-commerce logistics service is constructed. The e-commerce logistics service recommendation system explores the application practice of recommendation algorithm under big data, and enriches the application scenarios of personalized recommendation technology.

Genetic Diversity And Population Structure of Indian Mustard (Brassica Juncea) Based On Morphological and Molecular Markers

Rapeseed-mustard is one of the most important oilseed crops and providing a major source of edible oil in the world besides having other economic importance like leafy vegetables, ornamentals, and hedge crops. However, the genetic diversity present in the Brassica gene pool has not been investigated in detail. To address this problem, a study was conducted on 76 genotypes of B. juncea including cultivars, exotic lines, registered genetic stocks, advanced breeding lines, and germplasm lines. The genetic diversity was analyzed with the help of 50 polymorphic SSR and EST-SSR markers. For these genotype-marker combinations, a total of 126 alleles were amplified. Using molecular and phenotypic data, the dendrogram was constructed based on Jaccard’s similarity coefficient and Manhattan dissimilarity coefficient and linkage algorithm UPGMA. All the genotypes were grouped into 5 clusters based on their dissimilarity matrix. Population structure analysis grouped the genotypes in 8 clusters and various degrees of admixture was also observed. The grouping of genotypes appears effective as per their pedigree. The marker data was found more accurate to characterize the diversity and study the population structure than the quantitative trait data. The results of the present investigation will provide useful information for the identification of important alleles for future studies and pave the way to enhance genetic gains in Indian mustard.

Social entrenchment influences the amount of areal borrowing in contact languages

Aims and objectives: Social factors in language contact are not well understood. This study seeks to establish and explain the role of social entrenchment in the evolution of contact languages. It also aims to contribute to a broader perspective on areality that can account for social and linguistic factors in contact outcomes involving all languages present in multilingual ecologies, including contact languages. Methodology: The copula system was singled out for a detailed analysis. A corpus of primary data of the three African English-lexifier contact languages, Pichi, Cameroon Pidgin, and Ghanaian Pidgin, their ancestor Krio, and of their African adstrates (Bube, Mokpe, Akan) and European superstrates (Spanish, English) was investigated and compared. Data and analysis: Relevant features were selected for a dissimilarity matrix. A quantitative analysis was done with SplitsTree4. The resulting distance matrix and phylogenetic network were investigated for signals of genealogical transmission and areal diffusion and interpreted on their social background. Findings/conclusions: The copula systems of the three contact languages carry a genealogical signal of their ancestor Krio as well as an areal signal from the adstrates and superstrates spoken in their respective ecologies. The amount of areal borrowing increases in the order Pichi < Cameroon Pidgin < Ghanaian Pidgin, reflective of the depth of social entrenchment of each variety from left to right. Originality: Previous studies do not describe the copula systems of the English-lexifier contact languages of Africa and the Caribbean at a similar level of granularity and mostly focus on their emergence during creolization. This study attempts to explain their subsequent areal differentiation and links it to differences in social ecologies. Significance/implications: Areal borrowing can lead to significant departures from genealogically inherited structures within a short time if social entrenchment is shallow. Conversely, even languages of wider communication can remain remarkably stable if social entrenchment is deep.