Background: Diabetic cheiroarthropathy is a term derived from the Greek word “cheiros” meaning “of the hand”, It is characterized by stiff hands with distinctively thick, tight, and waxy skin, especially on the dorsal aspects of the hands. It is part of long term complication of diabetes and many suggest it is associated with microvascular complication. The aim of the study was to determine the prevalence of diabetic cheiroarthropathy in Iraqi patients with diabetes, and to study its association with diabetic retinopathy and glycemic control. Material and Methods: A cross-sectional study in which 110 diabetic patients and 110 non-diabetic healthy people who accepted to take part in the study were randomly recruited. 45 of the diabetic patients have Type 1 diabetes mellitus, and the other 65 have Type II diabetes mellitus. All diabetic patients and non-diabetic controls were examined for the presence of cheiroarthropathy, It’s association with sex, age of onset and duration of diabetes was recorded, the diabetic patients were also examined by an ophthalmologist for the evidence of diabetic retinopathy. Results: The total prevalence of cheiroarthropathy in all studied diabetic patients was 55.5%, while the prevalence in the control group was 4.5%. The cheiroarthropathy was more sever in Type 1 diabetes compared with Type 1I diabetes. Longer disease duration in both types of diabetes was associated with increased incidence of cheiroarthropathy, Diabetic retinopathy was higher in frequency in patients with cheiroarthropathy than in those without. Conclusions: The prevalence of diabetic cheiroarthropathy is high and nearly equal in both types of diabetes, but more sever in type 1 diabetes mellitus, it was associated with the duration of diabetes in both types and with the presence of diabetic retinopathy for only type1 diabetes mellitus.
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Reliable estimation of critical parameters such as hydrocarbon pore volume, water saturation, and recovery factor are essential for accurate reserve assessment. The inherent uncertainties associated with these parameters encompass a reasonable range of estimated recoverable volumes for single accumulations or projects. Incorporating this uncertainty range allows for a comprehensive understanding of potential outcomes and associated risks. In this study, we focus on the oil field located in the northern part of Iraq and employ a Monte Carlo based petrophysical uncertainty modeling approach. This method systematically considers various sources of error and utilizes effective interpretation techniques. Leveraging the current state of a
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Detection of early clinical keratoconus (KCN) is a challenging task, even for expert clinicians. In this study, we propose a deep learning (DL) model to address this challenge. We first used Xception and InceptionResNetV2 DL architectures to extract features from three different corneal maps collected from 1371 eyes examined in an eye clinic in Egypt. We then fused features using Xception and InceptionResNetV2 to detect subclinical forms of KCN more accurately and robustly. We obtained an area under the receiver operating characteristic curves (AUC) of 0.99 and an accuracy range of 97–100% to distinguish normal eyes from eyes with subclinical and established KCN. We further validated the model based on an independent dataset with
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Stylistics represents a modern approach in understanding the literary text through the linguistic patterns that form it. The distinctive phenomena that the text includes constitute special features in it. As well as exploring its aesthetic aspects through description and analysis at the same time. The close link between stylistics and linguistics made stylistics occupy a prominent place in modern literary criticism.
In this regard, we do not want to dwell on the different directions of stylistics. Rather, we will prolong the discussion in the study of the style as a (deviation. Aversion) from the original. Because this trend plays on the chord of the paradox between the surface structure and the deep structure, especially when the sur
Micro-perforated panel (MPP) absorber is increasingly gaining popularity as an alternative sound absorber in buildings compared to the well-known synthetic porous materials. A single MPP has a typical feature of a Helmholtz resonator with a high amplitude of absorption but a narrow absorption frequency bandwidth. To improve the bandwidth, a single MPP can be cascaded with another single MPP to form a double-layer MPP. This paper proposes the introduction of inhomogeneous perforation in the double-layer MPP system (DL-iMPP) to enhance the absorption bandwidth of a double-layer MPP. Mathematical models are proposed using the equivalent electrical circuit model and are validated with experiments with good agreement. It is revealed that the DL-
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Increasing hydrocarbon recovery from tight reservoirs is an essential goal of oil industry in the recent years. Building real dynamic simulation models and selecting and designing suitable development strategies for such reservoirs need basically to construct accurate structural static model construction. The uncertainties in building 3-D reservoir models are a real challenge for such micro to nano pore scale structure. Based on data from 24 wells distributed throughout the Sadi tight formation. An application of building a 3-D static model for a tight limestone oil reservoir in Iraq is presented in this study. The most common uncertainties confronted while building the model were illustrated. Such as accurate estimations of cut-off permeab
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The study explored applications of artificial intelligence and its dialectical relationship with international human rights law of individuals, which requires assessing the effects of this technology on human rights and freedoms. The problem of privacy of humanity, as AI technologies can control human rights and freedoms, while monitoring potential violations in this context. The study use of documentary research and qualitative lens to analyze the data. In conclusion, unawareness of the use of AI may impose significant hurdles on future generations and may infringe on human rights across all sectors of society. The government should mandate obligations for artificial intelligence businesses concerning education, health, human right
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