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.
Wireless Body Area Sensor Networks (WBASNs) have garnered significant attention due to the implementation of self-automaton and modern technologies. Within the healthcare WBASN, certain sensed data hold greater significance than others in light of their critical aspect. Such vital data must be given within a specified time frame. Data loss and delay could not be tolerated in such types of systems. Intelligent algorithms are distinguished by their superior ability to interact with various data systems. Machine learning methods can analyze the gathered data and uncover previously unknown patterns and information. These approaches can also diagnose and notify critical conditions in patients under monitoring. This study implements two s
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In this paper, we investigate the automatic recognition of emotion in text. We perform experiments with a new method of classification based on the PPM character-based text compression scheme. These experiments involve both coarse-grained classification (whether a text is emotional or not) and also fine-grained classification such as recognising Ekman’s six basic emotions (Anger, Disgust, Fear, Happiness, Sadness, Surprise). Experimental results with three datasets show that the new method significantly outperforms the traditional word-based text classification methods. The results show that the PPM compression based classification method is able to distinguish between emotional and nonemotional text with high accuracy, between texts invo
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Type 1 diabetes (T1D) is an autoimmune disease with chronic nature resulting from a combination of both factors genetic and environmental. The genetic contributors of T1D among Iraqis are unexplored enough. The study aimed to shed a light on the contribution between genetic variation of interleukin2 (IL2) gene to T1D as a risk influencer in a sample of Iraqi patients. The association between IL2−330 polymorphism (rs2069762) was investigated in 322 Iraqis (78 T1D patients and 244 volunteers as controls). Genotyping for the haplotypes using polymerase chain reaction test – specific sequence primer (PCR-SSP) for (GG, GT, and TT) genotypes corresponding to (G and T) alleles were performed. A significant association revealed a decreased freq
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This study was conducted with the aim to extract and purify a polyphenolic compound “ Resveratrol†from the skin of black grapes Vitis vinifera cultivated in Iraq. The purified resveratrol is obtained after ethanolic extraction with 80% v/v solution for fresh grape skin, followed by acid hydrolysis with 10% HCl solution then the aglycon moiety was taken with organic solvent
( chloroform). Using silica gel G60 packed glass column chromatography with mobile phase benzene: methanol: acetic acid 20:4:1 a
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Many therapeutic methods used to encourage reparative processes of cartilage and accelerate their healing such as drugs, magneto-laser and so on. Twenty four adult New Zealand rabbits used in this study. They were divided in to two groups; control and treaded with He –Ne laser. A square skin flap done on the medial aspect of both auricles followed by pealing a square piece of cartilage from the auricle then the flaps sutured .The site of the operation in the rabbits of the treated group were irradiated with He –Ne laser 5mw power for seven days began after the operation directly. 3 rabbits from each group used for collection of specimens for histopathological examination at the 1, 2, 4 & 6 weeks post the operation. Significant
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Abstract Background: Augmentation cystoplasty is one of the surgical procedure for treatment of spastic neurogenic bladder that has a significant improvement in the cystometric parameters. Aim of study: The aim of this study is to describe cystometric findings pre and post augmentation cystoplasty in patients with spastic neurogenic bladder. Patients and methods: A prospective study including patients aged 6-18years with neurogenic bladder operated on for augmentation cystoplasty surgery with ilium segments due to a neurogenic bladder from the years 2020–2024. A urodynamic study was conducted before and 3 months after the surgical procedure. Non-probabilistic sample of consecutive cases. Descriptive statistics were presented using fre
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