scholarly journals THE SELECTION OF DIFFERENT TYPES OF STONE FRUIT CROPS FOR CLONAL ROOTSTOCKS WITH EASY ROOTING OF LIGNIFIED CUTTINGS

2018 ◽  
Vol 55 ◽  
pp. 221-225
Author(s):  
V. G. Eremin ◽  
◽  
E. A. Smirnova ◽  
Author(s):  
N. Triapitsyna ◽  
K. Udovychenko ◽  
S. Vasyuta

The results are the work during 2004—2018 years in Ukraine on the selection of material of stone fruits crops, which satisfies the requirements of the normative international documents for the creation of a prebasic clones collection. Analyzed state of plant material certification of these cultures.


2020 ◽  
Vol 4 (64) ◽  
pp. 128-142 ◽  
Author(s):  
Anna Pavlovna Kuznetsova ◽  
◽  
Anna Igorevna Drygina ◽  
Alexandr Mikhailovich Fedorenko ◽  
Marina Vitalievna Maslova ◽  
...  

2021 ◽  
Vol 3 (69) ◽  
pp. 44-53
Author(s):  
Anna Pavlovna Kuznetsova ◽  
◽  
Mariya Sergeyevna Lenivtseva ◽  

Author(s):  
Gennadiy V. Eremin ◽  
Vladimir N. Podorozhniy ◽  
Oksana V. Eremina

Abstract On the basis of diversity of wild types of the genus Prunus L. (P. cerasifera, P. armeniaca, P. persica, P. fruticosa, P. lannesiana, P. maackii, P. tomentosa, P. pumila, and P. incana) in the collection of the Krymsk Experiment Breeding Station, highly adaptive, medium or weak vigour clonal rootstocks for stone fruit crops with good compatibility with grafted cultivars were selected: for plum, apricot and peach - Kuban 86, VVA-1, Evrika 99, Zarevo (Glow), Alab 1, Speaker, Best, VSV-1; and for sweet cherries and sour cherries - L-2, LC-52, VSL-1, VSL-2, and RVL-9. Part of the rootstocks were tested and successfully used in different parts of Russia and some near and far countries. The applied integration of tissue culture in vitro in the selection process at the station considerably promoted the rapid introduction of new rootstocks into world production. Technologies were developed for microclonal reproduction, and green and woody cuttings. The revealed light rooting of woody cuttings of stocks Kuban 86, Evrika 99, Zarevo, Best, VSL-1, RVL-9 (50-80%) allowed to develop technology for growing of young plants on these rootstocks directly in the first field of the nursery.


2021 ◽  
Vol 13 (4) ◽  
pp. 2146
Author(s):  
Anik Gupta ◽  
Carlos J. Slebi-Acevedo ◽  
Esther Lizasoain-Arteaga ◽  
Jorge Rodriguez-Hernandez ◽  
Daniel Castro-Fresno

Porous asphalt (PA) mixtures are more environmentally friendly but have lower durability than dense-graded mixtures. Additives can be incorporated into PA mixtures to enhance their mechanical strength; however, they may compromise the hydraulic characteristics, increase the total cost of pavement, and negatively affect the environment. In this paper, PA mixtures were produced with 5 different types of additives including 4 fibers and 1 filler. Their performances were compared with the reference mixtures containing virgin bitumen and polymer-modified bitumen. The performance of all mixes was assessed using: mechanical, hydraulic, economic, and environmental indicators. Then, the Delphi method was applied to compute the relative weights for the parameters in multi-criteria decision-making methods. Evaluation based on distance from average solution (EDAS), technique for order of the preference by similarity to ideal solution (TOPSIS), and weighted aggregated sum product assessment (WASPAS) were employed to rank the additives. According to the results obtained, aramid pulp displayed comparable and, for some parameters such as abrasion resistance, even better performance than polymer-modified bitumen, whereas cellulose fiber demonstrated the best performance regarding sustainability, due to economic and environmental benefits.


2021 ◽  
Vol 11 (11) ◽  
pp. 5235
Author(s):  
Nikita Andriyanov

The article is devoted to the study of convolutional neural network inference in the task of image processing under the influence of visual attacks. Attacks of four different types were considered: simple, involving the addition of white Gaussian noise, impulse action on one pixel of an image, and attacks that change brightness values within a rectangular area. MNIST and Kaggle dogs vs. cats datasets were chosen. Recognition characteristics were obtained for the accuracy, depending on the number of images subjected to attacks and the types of attacks used in the training. The study was based on well-known convolutional neural network architectures used in pattern recognition tasks, such as VGG-16 and Inception_v3. The dependencies of the recognition accuracy on the parameters of visual attacks were obtained. Original methods were proposed to prevent visual attacks. Such methods are based on the selection of “incomprehensible” classes for the recognizer, and their subsequent correction based on neural network inference with reduced image sizes. As a result of applying these methods, gains in the accuracy metric by a factor of 1.3 were obtained after iteration by discarding incomprehensible images, and reducing the amount of uncertainty by 4–5% after iteration by applying the integration of the results of image analyses in reduced dimensions.


2021 ◽  
pp. 1-21
Author(s):  
Muhammad Shabir ◽  
Rimsha Mushtaq ◽  
Munazza Naz

In this paper, we focus on two main objectives. Firstly, we define some binary and unary operations on N-soft sets and study their algebraic properties. In unary operations, three different types of complements are studied. We prove De Morgan’s laws concerning top complements and for bottom complements for N-soft sets where N is fixed and provide a counterexample to show that De Morgan’s laws do not hold if we take different N. Then, we study different collections of N-soft sets which become idempotent commutative monoids and consequently show, that, these monoids give rise to hemirings of N-soft sets. Some of these hemirings are turned out as lattices. Finally, we show that the collection of all N-soft sets with full parameter set E and collection of all N-soft sets with parameter subset A are Stone Algebras. The second objective is to integrate the well-known technique of TOPSIS and N-soft set-based mathematical models from the real world. We discuss a hybrid model of multi-criteria decision-making combining the TOPSIS and N-soft sets and present an algorithm with implementation on the selection of the best model of laptop.


2021 ◽  
Vol 13 (5) ◽  
pp. 956
Author(s):  
Florian Mouret ◽  
Mohanad Albughdadi ◽  
Sylvie Duthoit ◽  
Denis Kouamé ◽  
Guillaume Rieu ◽  
...  

This paper studies the detection of anomalous crop development at the parcel-level based on an unsupervised outlier detection technique. The experimental validation is conducted on rapeseed and wheat parcels located in Beauce (France). The proposed methodology consists of four sequential steps: (1) preprocessing of synthetic aperture radar (SAR) and multispectral images acquired using Sentinel-1 and Sentinel-2 satellites, (2) extraction of SAR and multispectral pixel-level features, (3) computation of parcel-level features using zonal statistics and (4) outlier detection. The different types of anomalies that can affect the studied crops are analyzed and described. The different factors that can influence the outlier detection results are investigated with a particular attention devoted to the synergy between Sentinel-1 and Sentinel-2 data. Overall, the best performance is obtained when using jointly a selection of Sentinel-1 and Sentinel-2 features with the isolation forest algorithm. The selected features are co-polarized (VV) and cross-polarized (VH) backscattering coefficients for Sentinel-1 and five Vegetation Indexes for Sentinel-2 (among us, the Normalized Difference Vegetation Index and two variants of the Normalized Difference Water). When using these features with an outlier ratio of 10%, the percentage of detected true positives (i.e., crop anomalies) is equal to 94.1% for rapeseed parcels and 95.5% for wheat parcels.


2021 ◽  
Vol 6 (1) ◽  
Author(s):  
Kangkang Zha ◽  
Xu Li ◽  
Zhen Yang ◽  
Guangzhao Tian ◽  
Zhiqiang Sun ◽  
...  

AbstractArticular cartilage is susceptible to damage but hard to self-repair due to its avascular nature. Traditional treatment methods are not able to produce satisfactory effects. Mesenchymal stem cells (MSCs) have shown great promise in cartilage repair. However, the therapeutic effect of MSCs is often unstable partly due to their heterogeneity. Understanding the heterogeneity of MSCs and the potential of different types of MSCs for cartilage regeneration will facilitate the selection of superior MSCs for treating cartilage damage. This review provides an overview of the heterogeneity of MSCs at the donor, tissue source and cell immunophenotype levels, including their cytological properties, such as their ability for proliferation, chondrogenic differentiation and immunoregulation, as well as their current applications in cartilage regeneration. This information will improve the precision of MSC-based therapeutic strategies, thus maximizing the efficiency of articular cartilage repair.


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