This study investigates the impact of agricultural investment policy—represented by agricultural loans and investment allocations—on rice crop production in Iraq over the period 2003–2023, employing the Autoregressive Distributed Lag (ARDL) model. Using time-series econometric analysis, the study confirms a short-term positive and statistically significant effect of financial support on rice output, while revealing statistically insignificant long-term effects. The presence of a cointegration relationship suggests long-term equilibrium between agricultural policy variables and rice production. However, the absence of causality in the Yamamoto-Toda test implies that structural and institutional inefficiencies may dilute the long-term impact of financial interventions. Practical implications of the study lie in guiding policymakers toward optimizing short-term agricultural investment strategies while simultaneously reforming institutional frameworks to enhance long-run outcomes. Emphasis is placed on the effective deployment of resources, improved monitoring mechanisms, and fostering innovation in agricultural practices. The results also underscore the importance of aligning credit mechanisms with production cycles to maximize returns. From a social perspective, the research highlights agriculture’s critical role in enhancing food security and rural employment. It addresses the economic disparities caused by inefficient resource allocation and advocates for policies that promote Development of the agricultural sector, particularly in post-conflict regions like Iraq. The unique contribution of this study lies in its comprehensive econometric approach contextualized within Iraq’s fragile economic structure. It provides a data-driven framework for understanding how targeted financial mechanisms can enhance agricultural productivity, offering insight for emerging economies aiming to balance investment efficiency with Economic development. Keywords: Agricultural Sector, Agricultural Investment, Rice Crops.
The study tagged ( the intellectual implications of the realistic Fine works of art) is a scientific effort to detect modest intellectual and artistic dimensions of the artwork realistic plastic , through some selected artistic productions of the painted work of art of the Iranian artist Ayman al - Maliki , with the result that the researcher collects materials to serve the scientific research topic which comes in three chapters.
First chapter included the general framework of the research (the promise of the research problem and its significance, objectives and limits and some of the terms contained therein).
Second chapter of this research was specified to the theoretical framework which included some of the topics that are dire
In the modern world, wind turbine (WT) has become the largest source of renewable energy. The horizontal-axis wind turbine (HAWT) has higher efficiency than the vertical-axis wind turbine (VAWT). The blade pitch angle (BPA) of WT is controlled to increase output power generation over the rated wind speed. This paper proposes an accurate controller for BPA in a 500-kw HAWT. Three types of controllers have been applied and compared to find the best controller: PID controller (PIDC), fuzzy logic type-2 controller (T2FLC), and hybrid type-2 fuzzy-PID controller (T2FPIDC). This paper has been used Mamdani and Sugeno fuzzy inference systems (FIS) to find the best inference system for WT controllers. Furthermore, genetic algorithm (GA) and particl
... Show MoreWireless sensor applications are susceptible to energy constraints. Most of the energy is consumed in communication between wireless nodes. Clustering and data aggregation are the two widely used strategies for reducing energy usage and increasing the lifetime of wireless sensor networks. In target tracking applications, large amount of redundant data is produced regularly. Hence, deployment of effective data aggregation schemes is vital to eliminate data redundancy. This work aims to conduct a comparative study of various research approaches that employ clustering techniques for efficiently aggregating data in target tracking applications as selection of an appropriate clustering algorithm may reflect positive results in the data aggregati
... Show MoreProblem Statement: Despite the critical role of arm movement in freestyle swimming, many learners— specially female students at Baghdad University's College of Physical Education and Sport Sciences— face difficulties executing the pushing phase of the stroke correctly. This phase essential for generating propulsion and maintaining body coordination in water. Traditional teaching methods lack immediate feedback on the quality and force of arm movements, impeding effective motor learning and coordination. Approach: the researchers developed a custom-made device designed to measure the pressure force exerted by the palms during freestyle swimming. The device features pressure sensors attached both hands, a processor that analyzes the colle
... Show MoreBackground: Interleukin-6 (IL-6) is a cytokine that has several functions, including stimulating growth and inhibiting cell death. It has the potential to operate as a biomarker for the accurate prediction of disease severity and activity, platelets-rich plasma was used in the treatment of oral lichen planus and can change the salivary IL-6 level.
Objectives: To study the clinical outcome of intralesional platelets-rich plasma in patients with oral lichen planus and to measure salivary IL-6 levels before and after the treatment with platelets-rich plasma were the aims of this study.
Subjects and Methods: In this clinical trial, for each patient a standardi
... Show MoreWithin the framework of big data, energy issues are highly significant. Despite the significance of energy, theoretical studies focusing primarily on the issue of energy within big data analytics in relation to computational intelligent algorithms are scarce. The purpose of this study is to explore the theoretical aspects of energy issues in big data analytics in relation to computational intelligent algorithms since this is critical in exploring the emperica aspects of big data. In this chapter, we present a theoretical study of energy issues related to applications of computational intelligent algorithms in big data analytics. This work highlights that big data analytics using computational intelligent algorithms generates a very high amo
... Show MoreThis article deals with the approximate algorithm for two dimensional multi-space fractional bioheat equations (M-SFBHE). The application of the collection method will be expanding for presenting a numerical technique for solving M-SFBHE based on “shifted Jacobi-Gauss-Labatto polynomials” (SJ-GL-Ps) in the matrix form. The Caputo formula has been utilized to approximate the fractional derivative and to demonstrate its usefulness and accuracy, the proposed methodology was applied in two examples. The numerical results revealed that the used approach is very effective and gives high accuracy and good convergence.