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.
Activated carbon (AC) is a highly important adsorbent material, as it is a solid form of pure carbon that boasts a porous structure and a large surface area, making it effective for capturing pollutants. Thanks to its exceptional features, AC is widely used for purifying water that is contaminated with odors and removing dyes in a cost-effective manner. A variety of carbonic materials have been employed to prepare AC, and this study aimed to evaluate the suitability of utilizing waste mango and avocado seeds for this purpose, followed by testing their efficacy in removing dye from aqueous solutions. The results indicate that using waste mango and avocado as AC is technically feasible, achieving dye removal percentages of 98% and 93%,
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RA Ali, LK Abood, Int J Sci Res, 2017 - Cited by 2
Abstract
The vegetative filter strips (VFS) are a useful tool used for reducing the movement of sediment and pesticide in therivers. The filter strip’s soil can help in reducing the runoff volume by infiltration. However, the characteristics of VFS (i.e., length) are not recently identified depending on the estimation of VFS modeling performance. The aim of this research is to study these characteristics and determine acorrelation between filter strip length and percent reduction (trapping efficiency) for sediment, water, and pesticide. Two proposed pesticides(one has organic carbon sorption coefficient, Koc, of 147 L/kg which is more moveable than XXXX, and another one
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Document source identification in printer forensics involves determining the origin of a printed document based on characteristics such as the printer model, serial number, defects, or unique printing artifacts. This process is crucial in forensic investigations, particularly in cases involving counterfeit documents or unauthorized printing. However, consistent pattern identification across various printer types remains challenging, especially when efforts are made to alter printer-generated artifacts. Machine learning models are often used in these tasks, but selecting discriminative features while minimizing noise is essential. Traditional KNN classifiers require a careful selection of distance metrics to capture relevant printing
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Jurisprudential disagreements are a significant source of a vast jurisprudential wealth. Among the manifestations of these disagreements are scholarly critiques raised by some scholars against others, claiming their divergence from the legal evidence or established principles for deducing legal rulings. One such critique is presented by the narrator scholar Abu Bakr Ibn Abi Shaybah, may Allah have mercy on him, directed towards Abu Hanifah al-Nu‘man, may Allah have mercy on him. In his compilation, Ibn Abi Shaybah cited numerous hadiths and traditions that he considered conflicting with the judgments as perceived by Imam Abu Hanifah, may Allah have mercy on him. These issues cover various branches of jurisprudence, including worship, sale
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