Circulation and Climate Variability in the Czech Republic between 1961 and 2020: A Comparison of Changes for Two “Normal” Periods

Thirty-year periods are treated in climatology as spans with relatively representative and stable climatic patterns, which can be used for calculating climate normals. Annual and seasonal series of circulation types were used to compare two 30-year sub-periods, 1961–1990 and 1991–2020, the second one being strongly influenced by recent global warming. This analysis was conducted according to the objective classification of circulation types and the climatic characteristics of sunshine duration, temperature, humidity, precipitation, and wind speed as calculated for the territory of the Czech Republic during the 1961–2020 period. For both sub-periods, their statistical characteristics were calculated, and the statistical significance of differences between them was evaluated. There was a statistically significant increase in the annual frequencies of anticyclonic circulation types and a significant decrease in cyclonic circulation types during 1991–2020 compared with 1961–1990. Generally, in both 30-year periods, significant differences in means, variability, characteristics of distribution, density functions, and linear trends appear for all climatic variables analysed except precipitation. This indicates that the recent 30-year “normal” period of 1991–2020, known to be influenced more by recent climate change, is by its climatic characteristics unrepresentative of the stable climatic patterns of previous 30-year periods.

Transcriptomic Fingerprint of Bacterial Infection in Lower Extremity Ulcers

Clinicians and researchers utilize subjective classification systems based on clinical parameters to stratify lower extremity ulcer infections for treatment and research. This study compared clinical infection classifications (mild to severe) of lower extremity ulcers (n = 44) with transcriptomic profiles and direct measurement of bacterial RNA signatures by RNA-sequencing. Samples demonstrating similar transcriptomes were clustered and characterized by transcriptomic fingerprint. Clinical infection severity did not explain the major sources of variability among the samples and samples with the same clinical classification demonstrated high inter-sample variability. High proportions of bacterial RNA, however, resulted in a strong effect on transcription and increased expression of genes associated with immune response and inflammation. K-means clustering identified two clusters of samples, one of which contained all of the samples with high levels of bacterial RNA. A support vector classifier identified a fingerprint of 20 genes, including immune-associated genes such as CXCL8, GADD45B, and HILPDA, which accurately identified samples with signs of infection via cross-validation. This suggests that stratification of infection states based on a transcriptomic fingerprint may be a useful tool for studying host-bacterial interactions in these ulcers, as well as an objective classification method to identify the severity of infection.

Thermal regions in Sri Lanka

The need for an objective classification of the thermal regions of Sri Lanka is emphasised. A brief account of the thermal climate of Sri Lanka is given. Regionalization based on thermal factors has been attempted quantitatively using factor, cluster and discriminant analysis. Three groups of cluster have been selected and mapped. The results are interpreted and related to the known thermal patterns of Sri Lanka.

Grasslands of Navarre (Spain), focusing on the Festuco-Brometea: classification, hierarchical expert system and characterisation

Aims: To clarify the syntaxonomic position of the grasslands in Navarre, with special focus on the dry grasslands, and to characterise the resulting syntaxonomic units in terms of diagnostic species and ecological conditions. Study area: Navarre (northern Spain). Methods: We sampled 119 plots of 10 m2 following the standardised EDGG methodology and analysed them together with 839 plots of similar size recorded in the 1990. For the classification, we used the modified TWINSPAN algorithm, complemented by the determination of diagnostic species with phi coefficients of association, which led to the creation of an expert system. We conducted these steps in a hierarchical manner for each syntaxonomic rank. We visualised the position of the syntaxa along environmental gradients by means of NMDS. Species richness, and structural and ecological characteristics of the syntaxa were compared by ANOVAs. Results: We could clearly identify five phytosociological classes: Lygeo-Stipetea, Festuco-Brometea, Molinio-Arrhenatheretea, Nardetea strictae, and Elyno-Seslerietea. Within the Festuco-Brometea a xeric and a meso-xeric order could be distinguished, with two alliances each, and eight associations in total: Thymelaeo-Aphyllanthetum, Jurineo-Festucetum, Helianthemo-Koelerietum, Prunello-Plantaginetum, Carduncello-Brachypodietum, Helictotricho-Seslerietum, Calamintho-Seselietum and Carici-Teucrietum.Conclusions: The combination of numerical methods allowed a consistent and more objective classification of grassland types in Navarre than previous approaches. At the association level, we could largely reproduce the units previously described with traditional phytosociological methods. By contrast, at higher syntaxonomic level, our analyses suggest significant modifications. Most importantly, a major part of the units traditionally included in the Festuco-Ononidetea seem to fall within the Festuco-Brometea. We could show that bryophytes and lichens are core elements of these grasslands and particularly the Mediterranean ones of Lygeo-Stipetea, both in terms of biodiversity and of diagnostic species. We conclude that the combination of our different numerical methods is promising for deriving more objective and reproducible delimitations of syntaxa in a hierarchical manner. Taxonomic references: Euro+Med (2006–2021) for vascular plants, Hodges et al. (2020) for bryophytes and The British Lichen Society (2021) for lichens, except for Endocarpon loscosii, Heppia lutosa, Psora saviczii and P. vallesiaca, which follow Nimis and Martellos (2021), and Buellia zoharyi, Fulgensia poeltii, Lichenochora clauzadei and Toninia massata, which follow Llimona et al. (2001). Syntaxonomic reference: Mucina et al. (2016), except for those syntaxa specifically treated here and given with authorities. Abbreviations: ANOVA = analysis of variance; EDGG = Eurasian Dry Grassland Group; NMDS: non-metric multidimensional scaling; TWINSPAN = Two-Way Indicator Species Analysis.

Clasificación espacial del suelo urbano por el valor especulativo del suelo e imágenes MSI satelitales usando K-MEANS, Huancayo, Perú

The city of Huancayo, like other intermediate cities in Latin America, faces problems of poorly planned land-use changes and a rapid dynamic of the urban land market. The scarce and outdated information on the urban territory impedes the adequate classification of urban areas, limiting the form of its intervention. The purpose of this research was the adoption of unassisted and mixed methods for the spatial classification of urban areas, considering the speculative land value, the proportion of urbanized land, and other geospatial variables. Among the data collection media, Multi-Spectral Imagery (MSI) from the Sentinel-2 satellite, the primary road system, and a sample of direct observation points, were used. The processed data were incorporated into georeferenced maps, to which urban limits and official slopes were added. During data processing, the K-Means algorithm was used, together with other machine learning and assisted judgment methods. As a result, an objective classification of urban areas was obtained, which differs from the existing planning.

Precipitation in the Czech Republic in Light of Subjective and Objective Classifications of Circulation Types

Many studies in Europe have investigated the relationship between climatological variables and circulation patterns expressed by various classifications of circulation types. This study provides new insights based on an analysis of precipitation in the western (Bohemia—BOH) and eastern (Moravia and Silesia—M&S) parts of the Czech Republic with respect to the subjective classification of the Czech Hydrometeorological Institute and objective classification based on the flow strength, flow direction, and vorticity during the 1961–2020 period. Circulation types are investigated in regard to their contributions to the total precipitation, mean daily precipitation totals, and precipitation probability (daily totals ≥ 1.0 mm). Types with a westerly airflow and a trough over Central Europe exhibit the highest proportions in precipitation totals. Types with a cyclone over Central Europe, especially combined with a northwestern (BOH) or northeastern (M&S) airflow, result in the highest daily mean totals and precipitation probability. Types with a southwestern airflow transport more precipitation to BOH, while those with a northeastern airflow transport more precipitation to M&S, with a slight seasonal shift in the gradient axis between winter and summer. Circulation types under both classifications are examined from the perspective of their precipitation representation in BOH and M&S and the differences between these two regions. In addition, the suitability of both classifications for precipitation analysis is investigated.

Machine Learning application for selecting efficient Loan Applicants in Private Banks of Bangladesh

Machine Learning Applications have been well accepted for various financial processes throughout the world. Supervised Learning processes for objective classification by Naïve Bayes classifiers have been supporting many definitive segregation processes. Various banks in Bangladesh have found challenging moments to identify financially and ethically qualified loan applicants. In this research process, we have confirmed the safe applicant’s list using definitive variable measures through identifiable questions. Our research process has successfully segregated the given applicants using Naïve Bayes classifier with the proof of lowering loan default rate from an average of 23.26%% to 11.76% and development of financial ratios as performance indicators of these banks through various financial ratios as indicators of these banks.