Measuring and Analyzing the Impact of Investment Spending on Achieving Growth for the Real Iraqi GDP

The study aim to measurement Investment spending in economic activity Via its effect on the production of sectors of the national economy, and due to the fact that investment spending is linked to public revenues, especially petroleum, because of the economy’s direction, its direction has made investment spending allocations fluctuate with the fluctuation of these revenues and then Its weak impact on the real output in Iraq and then a weakness in achieving the real economic growth aims that are expected from this spending, as the research reached a significant weakness in the impact of investment spending on the real output with and without petroleum, as the increases did not match The big investment spending with real output growth with and without petroleum. which indicates weak efficiency and performance of the national economy in achieving the required real economic growth and a lot of use of the policy of transfer between expenditures as well as the lack of a long and short-term balance relationship between investment spending and real output with and without petroleum.

Managing of Unassigned Mass Spectrometric Data by Neural Network for Cancer Phenotypes Classification

Mass spectrometric profiling provides information on the protein and metabolic composition of biological samples. However, the weak efficiency of computational algorithms in correlating tandem spectra to molecular components (proteins and metabolites) dramatically limits the use of “omics” profiling for the classification of nosologies. The development of machine learning methods for the intelligent analysis of raw mass spectrometric (HPLC-MS/MS) measurements without involving the stages of preprocessing and data identification seems promising. In our study, we tested the application of neural networks of two types, a 1D residual convolutional neural network (CNN) and a 3D CNN, for the classification of three cancers by analyzing metabolomic-proteomic HPLC-MS/MS data. In this work, we showed that both neural networks could classify the phenotypes of gender-mixed oncology, kidney cancer, gender-specific oncology, ovarian cancer, and the phenotype of a healthy person by analyzing ‘omics’ data in ‘mgf’ data format. The created models effectively recognized oncopathologies with a model accuracy of 0.95. Information was obtained on the remoteness of the studied phenotypes. The closest in the experiment were ovarian cancer, kidney cancer, and prostate cancer/kidney cancer. In contrast, the healthy phenotype was the most distant from cancer phenotypes and ovarian and prostate cancers. The neural network makes it possible to not only classify the studied phenotypes, but also to determine their similarity (distance matrix), thus overcoming algorithmic barriers in identifying HPLC-MS/MS spectra. Neural networks are versatile and can be applied to standard experimental data formats obtained using different analytical platforms.

Comparing the Influence of Synthetic jets on Cooling the Angled Plates Versus Vertical and Horizontal Plates

Synthetic jets besides being used in heat transfer, have also been used to control turbulence and flow separation. In the previous decade, research on the applications of a synthetic jet has indicated that by using these types of jets, flow separation can be reduced or even stopped altogether. In addition, these jets have been utilized in unmanned aerial vehicles (UAVs) (to control separation on airfoils) and flight control. In this study, the jet is located perpendicular to the flat plane with fixed heat flux and the effect of some geometric parameters including the ratio of the distance between the jet and the impact plane to the nozzle width, the ratio of the impact plane length to the jet nozzle width, the ratio of synthetic jet width to width of the nozzle, the ratio of the hole height to the nozzle width, the angle of the impact plate as well as the diaphragm characteristics such as amplitude and frequency of the jet diaphragm in heat transfer were evaluated numerically by using OpenFOAM open-source software. The findings indicate that synthetic jets have very weak efficiency for cooling vertical panels. However, they are extremely effective on angled plates. Synthetic jets have more influence on angled planes than horizontal planes.

Issuing opportunities of the Kazakhstan stock market: unrealized gains

The Kazakhstani economy has a significant emission potential. The study reveals the issues of the restraining influence on the development of Kazakhstani companies' emission activity. Among them are the role of bank lending in financing the national economy; government discouragement of economic development; weak efficiency of administrative and tax preferences for issuers. An important factor is the doubt of Kazakhstani companies on their capital fair evaluation in the market. In particular, the study noted that over the past five years, there has been a stable trend towards a decrease in bank lending as for large, the same is for small and medium-sized businesses. Basing on the continuing low number of new registrations of prospectuses for the issue of shares, there arises an issue of finding ways to meet the needs of business entities in financing. The findings from the analysis of sources of financing the State programs in the Republic of Kazakhstan showed the amount of possible funding from the stock market instruments. The study of data over the past few years made it possible to conclude that the methods and ways of using funds allocated under these state programs actually discourage business and local governments to use the emission potential that Kazakhstani market participants currently have. Administrative and tax preferences that operate in Kazakhstan for domestic participants in the stock market are either mainly aimed at investors or rather incomprehensible and imperceptible for potential issuers. Uncertainty in achieving the planned funding levels and in a fair assessment of the company's capital cost, basing on the above factors identified as a result of the study, is the main constraining reason for the low emission activity of Kazakhstani stock market participants.

An Exploration of Seaweed Polysaccharides Stimulating Denitrifying Bacteria for Safer Nitrate Removal

Excessive use of nitrogen fertilizer in intensively managed agriculture has resulted in abundant accumulation of nitrate in soil, which limits agriculture sustainability. How to reduce nitrate content is the key to alleviate secondary soil salinization. However, the microorganisms used in soil remediation cause some problems such as weak efficiency and short survival time. In this study, seaweed polysaccharides were used as stimulant to promote the rapid growth and safer nitrate removal of denitrifying bacteria. Firstly, the growth rate and NO3−-N removal capacity of three kinds of denitrifying bacteria, Bacillus subtilis (BS), Pseudomonas stutzeri (PS) and Pseudomonas putida (PP), were compared. The results showed that Bacillus subtilis (BS) had a faster growth rate and stronger nitrate removal ability. We then studied the effects of Enteromorpha linza polysaccharides (EP), carrageenan (CA), and sodium alginate (AL) on growth and denitrification performance of Bacillus subtilis (BS). The results showed that seaweed polysaccharides obviously promoted the growth of Bacillus subtilis (BS), and accelerated the reduction of NO3−-N. More importantly, the increased NH4+-N content could avoid excessive loss of nitrogen, and less NO2−-N accumulation could avoid toxic effects on plants. This new strategy of using denitrifying bacteria for safely remediating secondary soil salinization has a great significance.

Genetics of wild and mass-reared populations of a generalist aphid parasitoid and improvement of biological control

Due to their ability to parasitize various insect species, generalist parasitoids are widely used as biological control agents. They can be mass-reared and released in agroecosystems to control several pest species in various crops. However, the existence of genetic differentiation among populations of generalist parasitoid species is increasingly recognized and this can be associated with an adaptation to local conditions or to a reduced range of host species. Moreover, constraints of mass-rearing conditions can alter genetic variation within parasitoid populations released. These features could be associated with a reduced efficiency of the control of targeted pest species. Here, we focused on strawberry greenhouses where the control of aphids with the generalist parasitoid Aphidius ervi appears to be inefficient. We investigated whether this inefficiency may have both genetic and ecological bases comparing wild and commercial populations of A. ervi. We used two complementary genetic approaches: one based on the mitochondrial marker COI and one based on microsatellite markers. COI analysis showed a genetic differentiation within the A. ervi species, but the structure was neither associated with the commercial/wild status nor with host species factors. On the other hand, using microsatellite markers, we showed a genetic differentiation between commercial and wild A. ervi populations associated with a loss of genetic diversity within the mass-reared populations. Our ecological genetics study may potentially explain the weak efficiency of biological control of aphids in protected strawberry crops and enable to provide some insights to improve biological control.

Innovation management in the oil and gas sector of the Republic of Kazakhstan: problems and ways of solution

The purpose of the study is to analyze the current state and problems of innovation management in the economy of the Republic of Kazakhstan, in general, and in the oil-extracting sector, in particular. To solve the goals and objectives of the research, the following scientific methods were used: a set of systemic, logical and statistical methods, analysis of the results of the country’s innovative development. Used materials of state statistics bodies, data from the literature of Kazakhstani economic science. The analysis was carried out on the basis of studying information from open sources. Based on the use of the above methods, conclusions are formulated about the current state and problems of innovation management in the oil-extracting sector of the Republic of Kazakhstan. The results of the study are the provisions on the problems in the effectiveness of innovation management in the oil and gas industry. The conclusion is made about the insufficient level of innovative planning and management in comparison with world standards, despite the introduction of a number of government measures. The special importance of the problem under consideration is reflected, since the oil and gas sector today forms the basis of the Kazakhstani economy, forming the financial basis of the country’s state budget and having the opportunity to implement large-scale innovative projects. Attention is focused on the issue of a gradual departure from the raw material orientation and the transition to a state with a developed innovative economy. The contradictions between the growth of investment in industry and the weak efficiency of the implementation of innovative approaches in management are shown. The idea of developing and implementing a model for improving the management of innovative activities of companies in the oil and gas industry of Kazakhstan at the state level is proposed.

ECONOMETRICS OF NATIONAL SECURITY AND DEFENSE OF UKRAINE

The article provides the importance of Ukraine's economic development to ensure national security, highlights the main internal and external threats to Ukraine's national security, such as: hybrid economic war, the "needle" of loans from the International Monetary Fund, communal tariffs, opening the gas market in Ukraine, inefficient introduction of the circulation of domestic agricultural lands and insufficient use of the capabilities of the country's economy. The cyclical nature of economic development is practically proved by distinguishing four phases of economic development of the studied countries for the last ten years, weak efficiency of economic policy of Ukraine and possible applied mechanisms of economic growth. An econometric analysis of GDP of Ukraine and countries that occupy the largest share in Ukrainian imports of goods, the budget of Ukraine and the budget of the Ministry of Defense of Ukraine using the method of least squares and even linear regressions, calculated the intensity of changes in Ukraine's economic processes. The model of gross domestic product of Ukraine depending on the gross domestic product of China, Poland, Russia, Turkey, Germany, Italy, Belarus, the United States and France (nine-factor model), as well as the model of Ukraine's defense budget depending on the domestic gross domestic product product, budget expenditures, taxes, minimum and average wages and inflation (seven-factor model). On the example of the Ministry of Defense of Ukraine as a public sector institution, the registration algorithm for economic (additional) activities by military units and the distribution of revenues to increase the special fund of the state budget of Ukraine and create recovery of the country economy in general.

Detecting congestion in DEA by solving one model

Presence of input congestion is one of the key issues that results in lower efficiency and performance in Decision Making Units (DMUs). So, determination of congestion is of prime importance, and removing it improves performance of DMUs. One of the most appropriate methods for detecting congestion is Data Envelopment Analysis (DEA). Since the output of inefficient units can be increased by keeping the input constant through projecting on the weak efficiency frontier, it is unnecessary to determine the congested inefficient DMUs. Therefore, in this case we solely determine congested vertex units. Towards this aim, only one LP model in DEA is proposed and the status of congestion (strong congestion and weak congestion) obtained. In our method, a vertex unit under evaluation is eliminated from the production technology, and then, if there exists an activity that belongs to the production technology with lower inputs and higher outputs compared with omitted unit, we say vertex unit evidences congestion. One of the features of our model is that by solving only one LP model and with easier and fewer calculations compared to other methods, congested units can be identified. Data set obtained from Japanese chain stores for a period of 27 years is used to demonstrate the applicability of the proposed model and the results are compared with some previous methods.