Assessment of the anthropogenic transformation of post-forest vegetation in the village of Guzeripl and its environs (the Republic of Adygea, the Western Caucasus) based on the composition and structure of complexes of dominant species

Definition of the ceno-flora or regional flora in the cenosis, the proportion of species resistant or non-resistant to impacts has become widespread among the methods of indicating disturbances in vegetation cover.However, such studies, if they are conducted on a large spatial scale, require significant time and do not imply spatial detailing of the results. It is suggested that for several reasons it would be useful to use dominant species to solve this problem. The goal of the research is to demonstrate the possibilities of one of the variants of this approach using the example of vegetation of a small settlement (the mountain village of Guzeripl). It consists in studying the composition (level of synanthropization) and structure of species complexes that dominate communities in relatively large visually homogeneous areas of the terrain (0.15–0.2 ha). The results have shown that, on average, the highest level of synanthropization (transformation) is characteristic of dominant complexes of young fallow lands, a lower level of wastelands and roadsides, and a significantly lower level of old fallow lands and hayfields. In general, communities with a moderate degree of disturbance predominate in the study area. The results also indicate that the impact of anthropogenic factors on areas of vegetation leads to changes not only in the composition of dominant complexes, but also in their structure, the parameters of which can be considered as an additional tool for indicating anthropogenic disturbances

Depth distribution of absorbed dose on the external surface of Cosmos 1887 biosatellite

Significant absorbed dose levels exceeding 1.0 Gy day(exp -1) have been measured on the external surface of the Cosmos 1887 biosatellite as functions of depth in stacks of thin thermoluminescent detectors (TLD's) made in U.S.S.R. and U.S.A. The dose was found to decrease rapidly with increasing absorber thickness, thereby indicating the presence of intensive fluxes of low-energy particles. Comparison between the U.S.S.R. and U.S.A. results and calculations based on the Vette Model environment are in satisfactory agreement. The major contribution to the dose under thin shielding thickness is shown to be from electrons. The fraction of the dose due to protons and heavier charged particles increases with shielding thickness

Radiobiological experiments with plant seeds aboard the biosatellite Cosmos 1887

The effects of spaceflight factors on the seeds of Arabidopsis thaliana and Crepis capillaris were studied. The seeds were located inside the satellite in an open space, protected with aluminum foil and also exposed without the foil cover. When the seeds were in open space without any protection, their viability was found to be suppressed; the survival rate and fertility of plants grown from these seeds were also diminished. An increase in the frequency of chromosome aberrations (CA) and in the number of multiple injuries was registered in this case. Experiments with the aluminum foil shielding showed a decrease in the suppression of the seeds' viability, but mutational changes were found to be even more increased, while the survival rate and fertility of the plants decreased. An increase in the thickness of shielding resulted in a decrease in the effects up to the level of the control, except for the effects connected with CA and fertility of the plants. Analysis of the results shows that these impairments can be ascribed to the action of single heavy charged particles (HCP). The seeds can thus be regarded as an integral biological 'dosimeter' which allows estimation of the total effects of radiation, ecological and biological factors

Potential of machine learning methods in operational risk stratification in patients with coronary artery disease scheduled for coronary bypass surgery

Aim. To develop and evaluate the effectiveness of models for predicting mortality after coronary bypass surgery, obtained using machine learning analysis of preoperative data.Material and methods. As part of a cohort study, a retrospective prediction of in-hospital mortality after coronary artery bypass grafting (CABG) was performed in 2182 patients with stable coronary artery disease. Patients were divided into 2 following samples: learning (80%, n=1745) and training (20%, n=437). The initial ratio of surviving (n=2153) and deceased (n=29) patients in the total sample indicated a pronounced class imbalance, and therefore the resampling method was used in the training sample. Five machine learning (ML) algorithms were used to build predictive risk models: Logistic regression, Random Forrest, CatBoost, LightGBM, XGBoost. For each of these algorithms, cross-validation and hyperparameter search were performed on the training sample. As a result, five predictive models with the best parameters were obtained. The resulting predictive models were applied to the learning sample, after which their performance was compared in order to determine the most effective model.Results. Predictive models implemented on ensemble classifiers (CatBoost, LightGBM, XGBoost) showed better results compared to models based on logistic regression and random forest. The best quality metrics were obtained for CatBoost and LightGBM based models (Precision — 0,667, Recall — 0,333, F1-score — 0,444, ROC AUC — 0,666 for both models). There were following common high-ranking parameters for deciding on the outcome for both models: creatinine and blood glucose levels, left ventricular ejection fraction, age, critical stenosis (>70%) of carotid arteries and main lower limb arteries.Conclusion. Ensemble machine learning methods demonstrate higher predictive power compared to traditional methods such as logistic regression. The prognostic models obtained in the study for preoperative prediction of in-hospital mortality in patients referred for CABG can serve as a basis for developing systems to support medical decision-making in patients with coronary artery disease

The composition, species richness and species pool size of mono- and oligodominant forest stands of the Western Caucasus

There is an opinion that the pressure of competition in the plant communities of stable and productive habitats leads to the decrease in evenness of structure of species abundance and species richness up to the monopolization of plots by the most successful competitor (Huston, 1979; Bengtsson et al., 1994). Hence, between the species richness of phytocoenoses and relative density of individuals of dominant species (RDD), negative dependence should be observed. However, according to another view, the number of species and structure of their abundance are determined by the different processes. The number of species is determined by the species pool size and the rate of species immigration, while the abundance structure — by the competition (Stirling, Wilsey, 2001; Ma, 2005; Wilsey, Stirling, 2007). In particular, in some communities a decrease of RDD leads to an increase in abundance of subdominant species and to oligodominant structure. These changes in relative abundance could occur without changes in species richness. Therefore these variables could be weakly related (Ma, 2005; Wilsey, Stirling, 2007; Munson, Lauenroth, 2009). However, it is unclear how widely these scenarios are realized in the plant cover. The aim of our study was to examine the relationship between RDD, the dominance structure as a whole (mono- or oligodominant), the species richness and the size of the species pool in the forest stands of the Western Caucasus.</jats:p