The article represents the results of studying the spatial-dynamic factors and revealing the regularities of the global spread of Lumpy skin disease in cattle. The developed risk analysis and epizootological forecast provides the keeping up with a multi-year trend for the growth of epizootic tension in this disease for the period up to 2030. The highest probability of disease registration from 0.6 to 1.0 is predicted for the tropical agroecosystems of the African continent (enzootic zone) in 2018-2030. There is a real risk of disease in neighboring countries of Eurasia with the probability is less than 0.4. In the Russian Federation, outbreaks can occur in all federal districts of the country, but the highest probability of its occurrence is possible in agroecosystems of the subtropics of the North Caucasus and Southern Federal Districts of the country
In the article, on a small numerical example, we consider the similarity and difference of symptoms and syndromes according to their diagnostic meaning, i.e. according to the information they contain about the belonging of conditionals of animals to different nosological images. This problem can be solved for veterinary with the use of a new method of agglomerative cognitive clustering, implemented in Automated System-Cognitive analysis (ASC-analysis). This method of clustering differs from the known traditional methods in: a) in this method, the parameters of the generalized image of the cluster are calculated not as averages from the original objects (symptoms) or their center of gravity, but are determined using the same basic cognitive operation of ASC-analysis, which is used to form generalized images of the classes based on examples of objects and which really correctly provides a generalization; b) the similarity criterion is not the Euclidean distance or its variants, but the integral criterion of non-metric nature: "the total amount of information", the application of which is theoretically correct and gives good results in unortonormated spaces, which are usually found in practice; c) cluster analysis is carried out not on the basis of initial variables, frequency matrices or matrix of similarity (differences), depending on the units of measurement on the axes (measurement scales), but in cognitive space, in which one unit of measurement is used for all axes: the amount of information, and therefore the results of clustering do not depend on the initial units of measurement of features of objects. All this allows us to get the results of clustering, understandable to specialists and amenable to meaningful interpretation, well-consistent with the experts ' assessments, their experience and intuitive expectations, which is often a problem for classical clustering methods
Antibacterial chemotherapeutic drugs, which include antibiotics and synthetic antimicrobial agents, are widely used in veterinary medicine for the prevention and treatment of diseases caused by microorganisms. Antibacterial agents can be classified by type of action and chemical structure. It is also known that when several drugs are used in combination with each other, they interact within the body with each other, which can lead to strengthening or weakening of their action. For these reasons, it is of scientific and practical interest to develop a classification of antibiotics by their characteristics and principle of action (task 1), as well as by mutual compatibility (task 2). The article solves these problems using a new method of agglomerative cognitive clustering, implemented in automated system-cognitive analysis (ASK-analysis). This method of clustering has a number of advantages over the known traditional methods of clustering. These advantages allow us to obtain clustering results that are understandable to specialists and amenable to meaningful interpretation, which are well consistent with the experts ' assessments, their experience and intuitive expectations, which is often a problem for classical clustering methods. The article provides detailed numerical examples of solving two problems. The universal automated system called "Eidos", which is a tool of ASK-analysis, is in full open access on the author's website: http://lc.kubagro.ru/aidos/_Aidos-X.htm. Numerical examples of solving veterinary problems with the use of artificial intelligence technologies are placed as cloud Eidos-applications and are available to everyone
Coloring the plumage of chickens is a complex genetically determined sign. The study of the interactions of the main genes of chicken pigmentation was started by A.S. Serebrovsky. The most complete information on the genes of coloring plumage of chickens and down of chickens is given by Z.M. Kogan, indicating the clutch groups and the arrangement of these genes on the chromosome map. In the 1990s, the interaction of color genes, pen pattern and modifier genes affecting the intensity of the main color and pattern of the pen was described in detail. It was found that in pigs the pigmentation is regulated by the MC1-R melanocortin receptor associated with the locus E. Due to molecular studies, loci of dominant white color (I), recessive white color (c / c), striped pen pattern (B) adherent to the floor , and spotted spot locus (mo). The final phenotype depends not only on individual genes, but also on their interactions and the genetic environment as a whole. The same genes can produce different patterns and shades of the main plumage, and different genes determine the same phenotypes. Despite the fact that there was significant progress in determining the molecular causes of the appearance of a particular type of color in chickens, much remains to be learned
This article briefly discusses a new innovation (brought to a level that ensures its practical use) method of artificial intelligence: automated system-cognitive analysis (ASC-analysis) and its programmatic toolkit which is called intellectual system "Eidos". A detailed numerical example of the solution demonstrating the technology of creating a veterinary diagnostic test of gastrointestinal diseases of horses is given. As the source data, we use data from the UCI repository, kindly given by Mary McLeish and Matt Cecile (Department of computer science of University of Guelph, Ontario, Canada N1G 2W1, with the support of a sponsor: Will Taylor. The developed test is used to solve the problems of diagnosis, decision support and examining the simulated subject area by studying its model. The results of the study can be used by anyone, due to the fact that Eidos the universal automated system, which is a tool of ask-analysis, is in full open free access on the author's website at: http://lc.kubagro.ru/aidos/_Aidos-X.htm, and numerical examples of solving veterinary problems with the use of artificial intelligence technologies are placed as a cloud Eidos-application 129
In the diagnosis of subclinical, serous and catarral mastitis of cows a wide range of microorganisms has been isolated, including the genera Streptococcus (Str. disgalactiae, Str. agalactiae, Str. pyogenes), Staphylococcus (St. aureus, St. epidermidis) и E. coli. When treating cows with mastitis with argovit, the average duration of treatment for animals was2.9 +0.1, 3.3 + 0.3, 4.1 +0,2 days, which is 1.6, 1.9, 1.8 times less compared with the drug spectromast in the control group. The effect of argovit containing silver nanoparticles on antibiotic sensitivity in selected microflora in the treatment of subclinical, serous and catarrhal mastitis of cows was studied. Studies conducted to determine the antibiotic sensitivity of isolated microorganisms after the treatment of mastitis of cows showed the dependence of the results, both on the drug used and on the clinical form of the disease. It has been established that the use of spectromast causes a pronounced decrease in19 (76%) preparations with subclinical, 24 (96%) serous and 23 (92%) catarrhal mastitis. It was also noted that with the development of the pathological process, an increase in the appearance of previously absent resistance to antibacterial drugs was observed with subclinical6 (24%), serous 7 (28%), catarrhal 8 (32%) mastitis of the cows. While using argovit, an increase in antibiotic sensitivity to 21 drugs (84%) in subclinical, 24(96%) in serous and 23 (92%) catarrhal mastitis was revealed. In the treatment of subclinical mastitis in the experimental group, a slight decrease was observed for 4 (16%) drugs
Meat Academy website http://meatinfo.ru has a comparative table of breeds of cattle on 8 indicators, from which 2 are text and 6 are numerical http://meatinfo.ru/info/show?id=197. It is a natural question for business executives, which of these breeds are similar throughout the system of indicators characterizing them, and which ones differ and to what extent. There is also the question of which indicators are similar and different in meaning and by how much. This article is devoted to the solution of these problems. The results of the study can be used by anyone, due to the fact that Eidos the universal automated system, which is a tool of ask-analysis, is in full open free access on the author's website at: http://lc.kubagro.ru/aidos/_Aidos-X.htm, and numerical examples of solving the mentioned problems with the use of artificial intelligence technologies are placed as a cloud Eidos-application #131
The researchers obtained data on the morphological, biochemical and trace element composition of the blood of bull-calves of Hereford breed of different sizes. In this regard, scientists and business executives have three natural questions: 1) whether it is possible to predict the size and thus the meat productivity of bulls using these blood indicators; what are the strength and direction of the influence of certain values of blood indicators on the size and weight of bulls; what blood indicators are similar in meaning, and what are different and how much (to what extent). The article is devoted to the reasoned answers to these questions by applying modern methods of mathematical and numerical modeling to solve the corresponding problems. The results of the study can be used by anyone, due to the fact that Eidos the universal automated system, which is a tool of ask-analysis, is in full open free access on the author's website at: http://lc.kubagro.ru/aidos/_Aidos-X.htm, and numerical examples of solving the mentioned problems with the use of artificial intelligence technologies are placed as a cloud Eidos-application #133
This work is a continuation of the author's series of works on cognitive veterinary medicine. The present period is characterized by the appearance of huge volumes of texts in different languages in the open access, generated by people. Currently, these texts are accumulated in various electronic libraries and bibliographic databases (WoS, Scopus, RSCI, etc.), as well as on the Internet on various sites. All these texts have specific authors, dates and can belong simultaneously to many non-alternative categories and genres, in particular: educational; scientific; artistic; political; news; chats; forums and many others. The solution of the generalized problem of attribution of texts is of great scientific and practical interest, i.e. studying these texts, which would reveal their probable authors, date of creation, the ownership of these texts to the above generalized categories or genres, and might evaluate the similarities - differences of authors and texts according to their content, highlight key words etc. To solve all these problems it seems necessary to form the generalized linguistic images of texts into groups (classes), i.e. to form semantic kernels of classes. A special case of this problem is the creation of the semantic kernel in various scientific specialties of the HAC of the Russian Federation and the automatic classification of scientific texts in the areas of science. Traditionally, this task is solved by dissertation councils, i.e. experts, on the basis of expert assessments, i.e. in an informal way, on the basis of experience, intuition and professional competence. However, the traditional approach has a number of serious drawbacks that impose significant limitations on the quality and volume of analysis. Currently, there are all grounds to consider these restrictions as unacceptable, because they can be overcome. Thus, there is a problem, the solutions of which are the subject of consideration in this article. Therefore, the efforts of researchers and developers to overcome them are relevant. Therefore, the aim of the work is to develop an automated technology (method and tools), as well as methods of their application for the formation of the semantic core of veterinary medicine by automated system-cognitive analysis of passports of scientific specialties of the HAC of the Russian Federation and automatic classification of texts in the areas of science. A detailed numerical example of solving the problem on real data has been given as well
14 January 2019 at the website of the higher attestation Commission of the Russian Federation http://vak.ed.gov.ru/87 the information appeared: "About refining of scientific specialties and their respective fields of science where publications are included in the List of peer-reviewed scientific publications, where basic scientific results of dissertations on competition of a scientific degree of candidate of Sciences, on competition of a scientific degree of the doctor of Sciences must be published ". It is reported that according to the recommendation of the HAC for other publications included in the List of groups of scientific specialties, the work on refining scientific specialties and branches of science will be continued in 2019. This work is a continuation of the author's series of works on cognitive linguistics. It offers innovative intelligent technology to automate the solution of the problem formulated by the higher attestation Commission of the Russian Federation above. With the use of the automated system-cognitive analysis (ASC-analysis) and its programmatic toolkit which is intellectual system called "Eidos" directly on the basis of official texts of passports of scientific specialties of the higher attestation Commission of the Russian Federation, there were established their semantic kernels, and then, implemented the automatic classification of scientific texts (articles, monographs, textbooks, etc.) on the specialties and groups of specialties of the higher attestation Commission of the Russian Federation. Traditionally, this task is solved by dissertation councils, as well as editorial boards of scientific publications, i.e. by experts, on the basis of expert assessments, in an informal way, on the basis of experience, intuition and professional competence. However, the traditional approach has a number of serious drawbacks that impose significant limitations on the quality and volume of analysis. Therefore, the efforts of researchers and developers to overcome these limitations are relevant. Currently, there are all grounds to consider these restrictions as unacceptable, because they are not only necessary, but also quite possible to overcome. Thus, there is a problem, the solution of which is the subject of consideration in this article. A detailed numerical example of solving the problem on real data is given as well