Addition of Ginseng (Withania Somnifera) To the Diet and Its Effect on Productive Performance for Broilers Raised with Two Different Densities: إضافة الجينسنغ (Withania somnifera) إلى العليقة وتأثيره في الأداء الإنتاجي لفروج اللحم المربى بكثافتين مختلفتين

The study was conducted to find out the effect of adding ginseng root powder (Withania somnifera) at (0, 1.5 and 3.0) g/kg under two densities of breeding (12 and 17) birds/m2 on performance, economic indicators. Chicks were raised from the age 1 day-42 and distributed to the treatments at the second week in T1:12 bird\m2 +0%, T2:12 bird\m2 +1.5%,T3:12 bird\m2 +0.3%,T4:17bird\m2+0%,T5:17bird\m2+ 1.5%,T6:17 bird \m2 +0.3%.The statistical analysis showed that there was no significant difference in density in body weight, weight gain, relative growth, feed conversion factor, production index, production coefficient,while the density was 12 birds/ m2 superior in consumption The feed density of 17 birds/m2 gave a higher productivity in kg/m2 compared to 12 birds/m2. The addition of ginseng did not affect the weight gain, relative growth, conversion factor, index, production coefficient, productivity yield in kg/m2, while there was a superiority of adding (1.5 and 3.0) g of ginseng compared with no addition in live body weight and in Feed consumption and production factor and in the effect of the interaction there were no significant differences in the weight gain, growth, feed consumption, evidence and production factor, while we note that the interaction(12 birds/ m2+1.5 gm ginseng) gave the highest body weight and a significant improvement in the feed conversion factor for the addition of (1.5 and 3.0) gm under the influence of breeding density 17 birds/m2 and the productivity yield exceeded kg/m2.

On the Theory of Elasticity of Microinhomogeneous Media with Account for Stochastic Changes in the Connectivity of Constituent Components

The paper proposes a mathematical model aimed at calculating the effective elastic moduli of a micro-inhomogeneous two-component isotropic composite material, which components are connected randomly depending on the level of their relative volumetric contents. A stochastic equation is formulated for the connectivity parameter of the constituent components, according to which, with an increase in the volumetric content of the filler, individual inclusions build the structures of the matrix mixture in the form of interpenetrating frameworks, and then turn into a new binding matrix with individual inclusions from the material of the rest of the old matrix. The algorithm for the numerical solution of this stochastic differential equation is constructed in accordance with the Euler-Maruyama method. For each implementation of this algorithm, the corresponding stochastic trajectories are constructed for the random connectivity function of the constituent components of the composite material. A variant of the method aimed at calculating the mathematical expectation of a random connectivity function of the constituent components has been developed and the corresponding differential equation has been obtained for it. It is shown that the numerical solution of this equation and the average value of the production factor function calculated for all realizations of stochastic trajectories give close numerical values. New macroscopic constitutive relations are found for microinhomogeneous materials with a variable microstructure and their effective elastic moduli are calculated. It is noted that the formulas for these effective elastic moduli generalize the known results for isotropic composite materials. The values of the effective elastic moduli, constructed according to the expressions obtained in the paper, lie within the Khashin-Shtrikman range for the lower and upper bounds of the effective elastic moduli of the composite materials. The numerical analysis of the developed models showed a good agreement with the known experimental data.

New coronavirus infection as an occupational disease: complex expert cases

Introduction. The professional activity of medical workers (MW) is in close contact with daily contact with various factors of the production environment: physical, chemical, biological, and labor processes. Until 2020, tuberculosis and viral hepatitis prevailed in the structure of occupational diseases (OD) of the medical workers in the Russian Federation. According to the State report "On the state of sanitary and epidemiological welfare of the population in the Russian Federation in 2020," the first ranking the second place in the structure of occupational diseases, depending on the impact of harmful production factor took the illnesses associated with the action of biological factors - 20,19%, while the main reason for the growth in the incidence of healthcare workers in coronavirus infection COVID-19 (further COVID-19). The study aims were to identify problematic aspects in the establishment of the COVID-19 work from MW. Materials and methods. We have given descriptions of clinical cases, as well as a retrospective analysis of issues of OD according to the patient registers of the following medical institutions: the Center of Occupational Pathology of Sechenov University, the Republican Center of Occupational Pathology of the Ministry of Health, Republic of Tatarstan, the Regional Center of Occupational Pathology of the Samara Region. Results. In 2020, COVID-19 was the most common OD with fatal outcomes and complications in healthcare workers. Today, difficulties in determining the connection of COVID-19 with the profession arise when assessing the epidemiological history, the consequences after a coronavirus infection, and the formulation of the diagnosis. Conclusions. For a qualitative examination of the connection of COVID-19 with the profession, it is necessary to develop a list of clinical conditions with the definition of the timing of complications.

How preferences shape the welfare and employment effects of trade

We set up a trade model with two countries, two sectors, and one production factor, which features a home-market effect due to the existence of trade costs. We consider search frictions and firm-level wage bargaining in the sector producing differentiated goods and a perfectly competitive labor market in the sector producing a homogeneous good. Consumers have price-independent generalized-linear preferences over the two types of goods, covering homothetic and quasi-homothetic preferences as two limiting cases. Due to the specific functional forms of indirect utility, homothetic preferences lead to risk aversion, while quasi-homothetic preferences lead to risk neutrality in our model. We show that trade between two countries that differ in their population size leads to an expansion of the differentiated goods sector and a contraction of the homogeneous good sector in the larger economy. This induces the larger country to net-export differentiated goods at the cost of a higher economy-wide rate of unemployment in the open economy (with the effects reversed for the smaller country). The welfare effects of trade depend on the preference structure. Looking at the two limiting cases, we show that the larger country is likely to benefit from trade if preferences are homothetic, whereas losses from trade are possible if preferences are quasi-homothetic. The opposite is true in the smaller country. This reveals an important role of preferences for the welfare effects of trade in the presence of labor market imperfection, a result we further elaborate on by considering more general preferences as well as differences of countries in their per-capita income levels.

Market Power in Agricultural Land Markets: Concepts and Empirical Challenges

This paper provides review about challenges and opportunities to assess and quantify market power in agricultural land markets. Measuring land market power is challenging because the characteristics of this production factor hinder the direct application of familiar concepts from commodity markets. Immobility, fixed availability, and large heterogeneity of land and potential users contradict assumptions of fictitious point market for homogeneous goods. Moreover, the use of concentration indicators for policy assessments is hampered by two problems. First, defining the relevant regional size of the market is challenging and concentration indicators are not robust with regard to market size and number of actors. Second, high concentration of land ownership or land operation may point at potential market power, but it may also be the result of an efficient allocation of land due to structural change in agriculture. The aforementioned challenges are illustrated with a case study for the Federal State of Brandenburg in Germany. Using available data for land sales, a regression analysis reveals a negative relationship between land use concentration and farmland prices. This result can be interpreted as an indication of market power on the buyer side in agricultural land markets. However, it is hardly possible to translate this finding into recommendations for land market regulations because the evaluation of the potential misuse of dominant positions in land markets requires a case-specific analysis. Providing evidence for the exertion of market power in land markets is extremely complex and deserves further attention from researchers and politicians.

Artificial Intelligence and Economic Growth: A Theoretical Framework

The growing adoption of Artificial Intelligence (AI) has sparked ubiquitous concerns worldwide. Artificial intelligence can affect economic growth and employment. The influence is assumed to be substantial because the adoption of AI technology may lead to increased productivity, lower wages, prices, and labor substitution. Artificial intelligence can affect global economic growth with its widespread adoption and diffusion. We mathematically examined the effects of AI on economic growth, reiterating how AI is unique as a production factor. The models show that AI capital lowers capital prices, increases wages, and augments productivity. Besides, AI capital positively affects the labor share and vice versa, provided that AI and labor are complementary. We improved a task-based model to show AI raises both labor share and wages by generating new tasks. We also present the potential policy implications of AI adoption. We conclude AI can contribute to economic growth. Labor-abundant countries should adopt labor-augmenting technology, while countries with an aging population can adopt capital-augmenting technology. However, caution should be exercised in ensuring that the models are leveraged optimally.

Research on the Impact of Environmental Regulations on Industrial Green Total Factor Productivity: Perspectives on the Changes in the Allocation Ratio of Factors among Different Industries

This paper constructs a two-sector manufacturer model of endogenous technological progress. We analyze the impact of environmental regulations on the factor input and output of different industries. Then, we reveal the intermediary role of inter-industry factor allocation in the impact of environmental regulations on industrial green total factor productivity (GTFP). Finally, the paper uses panel data from 30 provinces in China’s industry from 2000 to 2017 to conduct empirical tests. We can draw the following conclusions: (1) The relative magnitude of the output compensation of the production department and the innovation compensation of the R&D department could change the impact of environmental regulations on the input and output of inter-industry factors, and the comprehensive effects of both input and output will affect the level of GTFP. (2) The curve of the direct impact of environmental regulations on GTFP is in an inverted “U” shape. However, the production factor allocation ratio can “reverse” the inhibitory effect of high-intensity regulations on GTFP. (3) The capital factor has a greater impact on the regulatory effect, but the labor factor has a more lasting impact on the regulatory effect. High-strength environmental regulations can enhance manufacturers’ preference for human capital. Therefore, formulating environmental regulatory policies oriented to improve the ratio of factor allocation, mixing different types of regulatory policies, and increasing investment in human capital are all conducive to accelerating the transformation and upgrading of China’s industrial structure and achieving high-quality development of the industrial economy.

Cloud–edge cooperation for meteorological radar big data: a review of data quality control

With the rapid development of information technology construction, increasing specialized data in the field of informatization have become a hot spot for research. Among them, meteorological data, as one of the foundations and core contents of meteorological informatization, is the key production factor of meteorology in the era of digital economy as well as the basis of meteorological services for people and decision-making services. However, the existing centralized cloud computing service model is unable to satisfy the performance demand of low latency, high reliability and high bandwidth for weather data quality control. In addition, strong convective weather is characterized by rapid development, small convective scale and short life cycle, making the complexity of real-time weather data quality control increased to provide timely strong convective weather monitoring services. In order to solve the above problems, this paper proposed the cloud–edge cooperation approach, whose core idea is to effectively combine the advantages of edge computing and cloud computing by taking full advantage of the computing resources distributed at the edge to provide service environment for users to satisfy the real-time demand. The powerful computing and storage resources of the cloud data center are utilized to provide users with massive computing services to fulfill the intensive computing demands.

Comparative analysis production of fruit and sunti acid using the Hayami method

Agroindustry sector has a role important to improve the economic society level of Aceh, Indonesian. The opportunities in business to develop agroindustry from Averrhoa bilimbi L. was a relative major potential included the fruit candy and sunti acid. This study aims to calculated added value of fruit candy and sunti acid using the hayami method. The result was obtained primary and secondary data. The primary data were obtained directly results of interviews with business actors using questionnaires. Furthermore, the secondary data were obtained from literature review studies. The data was collected using the observation, interviews, and documentation. The average added value obtained by fruit candy of each kilogram was found the output value in Rp.150,000 Whereas, the sunti acid was a lower value in Rp. 65,000 This means that a kilogram was used can provide added value of Rp. 11,250 from fruit candy and Rp. 15,625 from sunti acid. The added value ratio was used to quantify the advancement achieved for productivity from A. bilimbi in agroindustry to involve the additional value from local products. Then, the highest profit until 60% in sunti acid product, and 44.44% in fruit candy. The retribution for the owner of the production factor was found the value the entrepreneur profit to 9.76% (Rp. 51,250/kg) for fruit candy and 26.37% (Rp.35,625/kg) for sunti acid. The descriptive data analysis method was expected to suggest the development of agroindustry based on the local commodity product, mainly the fruit candy and sunti acid to supported the food security.

Technical Efficiency Analysis of shallot Farming in Bima Regency- NTB Province Using the Cobb-Douglas Stochastic Frontier Production Function

Bima Regency is the center for the development and production of the largest shallot commodity in NTB Province. However, the productivity of shallots in Bima Regency still needs to be increased in order to achieve maximum production. The purpose of this study is to analyze the factors that influence shallot farming and to analyze the technical efficiency of farmers in conducting shallot farming. Bima Regency is the research area determined by purposive sampling because it is the center of shallot development in NTB Province. The research data was taken by conducting interviews with 35 respondents who were determined by proportional sampling. Then the data obtained were analyzed using the Cobb Douglas Stochastic Frontier production function approach using the Frontier 4.1 software program. Based on the results of the analysis, it was found that the production factor of the number of seeds, urea fertilizer and labor had a significant effect on the production of shallots at the alpha level of 5 percent while pesticides and KCL fertilizers had a significant effect on the production of shallots at the alpha level of 15 percent. The level of technical efficiency of onion farming in Bima Regency is classified as efficient because it has a value of 0.9569. Farmers can still improve efficiency in onion farming by optimizing the use of superior seeds, labor, balanced fertilizer application, and increasing farmers' skills in adopting innovation and using onion cultivation technology.