University of Human Development

Introduction: Autoimmune thyroid disease (AITD) is a T-cell mediated disorder characterized by the presence of thyroid autoantibodies, particularly thyroid peroxidase antibodies (TPO-Ab), which serve as specific biomarkers of thyroid autoimmunity. The relationship between TPO-Ab and thyroid hormones is influenced by several confounding factors, potentially leading to inconsistent findings across studies. Methods: This cross-sectional study investigated 47 patients with AITD (35 women, 12 men; mean age 40 years) receiving levothyroxine (LT4) therapy, all with serum TPO-Ab ≥16 IU/mL. Anthropometric, glycemic, and lipid indices were measured alongside thyroid function tests, and correlations were assessed using zero-order and partial correlation analyses. Results: A significant positive correlation was found between TPO-Ab and thyroid-stimulating hormone (TSH) (r = 0.510, p < 0.001). Adjusting for age, body mass index (BMI), fasting glucose, HbA1c, and LDL-c reduced this correlation, while controlling for triglycerides (TG) and HDL-c increased it. Similar trends were observed between TPO-Ab and free thyroid hormones. Multivariate regression showed that 29.1 % of TPO-Ab variability was explained by the tested covariates, highlighting the interplay between metabolic and immunological factors. The influence of lipid parameters suggests that lipid metabolism may directly modulate autoimmunity and thyroid function. Moreover, the use of exogenous LT4, known to lower TG and HDL-c, further complicates the interpretation of antibody-hormone interactions. Conclusion: In conclusion, applying partial correlation analysis provides a more accurate assessment of the link between TPO-Ab and thyroid hormones compared to simple correlations, and supports the need for controlling metabolic and demographic covariates in both clinical practice and research to avoid misleading associations in autoimmune thyroid disease.

    يُعالج التفكير الطوباوي في العمارة غالبًا كفكرة مكانية واحدة، مما يقلل من تعقيده إلى تشكيلات شكلية أو مادية فقط. تتحدى هذا البحث هذا المنظور المختزل من خلال اقتراح إطار متعدد الأبعاد يفسر الطوبيا عبر أربع عدسات مترابطة — المكان، الوقت، الشخصية، والموضوع. بدلاً من العمل كفئات معزولة، تعمل هذه الأبعاد في وقت واحد وبشكل علاقاتي، مشكِّلةً الطريقة التي يتم بها تخيل الطوبيا المعمارية وتمثيلها وتجسيدها. وتطور الدراسة هذا الإطار ذو الأربع عدسات من خلال تركيب نظري لتاريخ العمارة ونظرية المدن والدراسات الطوباوية النقدية، موضحةً كيف يؤثر كل بعد على الآخر ويعتمد عليه: المكان يرسخ المعنى السياقي؛ الوقت يؤطر الاستمرارية والتغيير؛ الشخصية تفسر القيم والهوية الإنسانية؛ والموضوع يكشف عن التجليات المادية والرمزية. باستخدام هذا الإطار كأداة تشخيصية تفسيرية، يقوم البحث بتحليل رؤى معمارية مختارة لتوضيح كيف يمتد التفكير الطوباوي متعدد الأبعاد إلى ما هو أبعد من المثالية الشكلية نحو قراءات أكثر ثراءً اجتماعيًا وثقافيًا وزمنيًا. تُظهر النتائج أن المفاهيم الطوباوية في العمارة تكتسب التماسك فقط عندما يُفهم أن هذه الأبعاد الأربعة تُنتج بشكل مشترك وليس بصورة هرمية أو متسلسلة. تكمن مساهمة البحث في تقديم أداة تحليلية شاملة توسع الخطاب المعماري المعاصر بما يتجاوز الحتمية المكانية. من خلال تسليط الضوء على التفاعل العلاقاتي بين المكان والزمان والشخصية والموضوع، يدعم الإطار نهجًا أكثر أخلاقية وشمولية وتنوعًا لمعالجة التحديات الحضرية الحديثة. تدعو هذه النظرة متعددة الأبعاد المعماريين والمخططين والنظريين إلى إعادة النظر في الطوبيا، ليس كخطة ثابتة، بل كعدسة متطورة لتخيل بيئات مبنية أكثر عدلاً.

Background: Headaches frequently affect nursing students, fueled by intense academic demands and psychological stress. Among these, migraine—a severe form of headache characterized by pulsatile pain, nausea, and light or sound sensitivity—poses a notable public health concern, particularly for university populations vulnerable to stress‑related triggers. This study aimed to assess the prevalence, clinical features, and daily impact of migraine among nursing students at the University of Sulaimani. Methods: A quantitative design, cross-sectional descriptive study was conducted among all stages of nursing students to assess prevalence, clinical features, and impact of migraine on daily functioning among nursing students at the University of Sulaimani from the period of 5th November 2023 to 15th June 2024 by using a standard tool based on the ICHD-3 criteria. Content validity was confirmed by five experts, and reliability was verified using split-half and Cronbach’s alpha (r = 0.83).Data were analyzed using SPSS version 24 with results presented as frequencies and percentages. Out of 109 students reporting headaches, only 48 (44%) had migraine headaches. Results: 109 students 54.1% female and 45.9% were male experienced headaches. Out of these 109 students 48 (44.0%), 58.3% female and 41.7% male of them had migraine according to the International Classification of Headache Disorders, 3rd edition criteria tool for migraine. The most frequently cited trigger was too little sleep (77.1%), and the leading self‑care strategy was lying down or sleeping during attacks (82.6%). Unilateral head pain was the predominant symptom (68.8%), followed by phonophobia (56.9%) and pulsating quality (45.9%). Functionally, 62.4% missed 1–3 university days in the past three months due to headache, and 57.8% reported reduced study or work productivity on 1–3 days. Conclusion: Headache is highly prevalent among nursing students, with nearly half of those affected meeting the criteria for migraine, and women disproportionately represented. Common triggers such as inadequate sleep and the widespread reliance on rest‑based relief strategies emphasize key areas for targeted support. Migraines clearly impair academic performance especially study and work productivity and daily functioning.

Periodontal disease (PD) and cognitive disorders (CDs) are common in older people, and these variables appear to be linked. The aim of this article was to assess this association using an umbrella meta-analysis. PubMed and MEDLINE were searched for records until June 2025. The groups were compared using odds ratio (OR) and relative risk (RR). A total of 20 meta-analyses were included. Individuals with PD and its consequences had higher chances of having/developing all-type CDs: periodontitis (OR = 1.65, 95% CI: 1.37-1.97, p = < 0.0001), tooth loss (OR = 1.51, 95% CI: 1.32-1.71, p = < 0.0001). The risk was much higher for patients with severe periodontitis: (OR = 2.69, 95% CI: 2.26-3.20, p = < 0.0001). Pooled analysis for cohort studies was (RR = 1.26, 95% CI: 1.20-1.32, p = < 0.0001). PD is associated with CDs with low to moderate certainty of evidence measured by GRADE.

Fiber-reinforced polymer (FRP) bars are gaining prominence in civil infrastructure due to their high strength-to-weight ratio, corrosion resistance, and low thermal conductivity. The bond strength (BS) between FRP bars and concrete, which is influenced by surface treatments like sand-coating or ribbing, plays a critical role in ensuring structural performance and durability. This study aims to predict the bond strength of different FRP bar types and surface characteristics in concrete using machine learning models. A total of 416 datasets from standard pull-out tests were collected and statistically analyzed, considering variables such as bar type, surface treatment, concrete compressive strength, bar diameter, bonded length, concrete cover, and FRP bar tensile properties. Two machine learning models, Artificial Neural Networks (ANN) and Extreme Gradient Boosting (XGBoost) were developed for bond strength prediction. Model performance was evaluated using Root Mean Squared Error (RMSE), Correlation Coefficient (R), and Scatter Index (SI). XGBoost demonstrated superior performance with lower RMSE and SI, and higher R values in 5-fold cross-validation. Sensitivity analysis identified concrete compressive strength as the most significant input in bond strength prediction. Additionally, main effect plots and Analysis of Variance (ANOVA) tests were conducted to further investigate the relationships between variables. These findings contribute to a more accurate understanding of FRP bar-concrete interactions, facilitating the optimization of structural design.

The advent of e-marketing has transformed the business landscape, offering small and medium enterprises (SMEs) a powerful tool for growth, particularly in emerging economies like the Kurdistan Region of Iraq. In Erbil city, SMEs face the dual challenge of leveraging digital tools for competitiveness while operating within a unique socio-economic context. This study aims to investigate the impact of electronic marketing on business growth in small and medium enterprises (SMEs) in Erbil city. To achieve this end, the researchers utilize analytical descriptive approaches. Using a quantitative case study methodology, data were collected through a pre-tested, structured questionnaire distributed to 85 e-marketing group leaders in Erbil City. A total of 79 valid responses were obtained for statistical analysis. The study yielded multiple conclusions, indicating a substantial and positive correlation between the adoption of e-marketing mixes and business growth, illustrating that the proficient utilization of digital marketing tools enhances revenue growth, market expansion, and customer engagement. The research presented a set of recommendations; the most important thing is that small and medium-sized firms ought to aggressively employ social media marketing to promote brand awareness and foster client involvement, while collaborating with local influencers can bolster brand recognition and broaden reach in the Kurdistan market.

Abstract The successful implementation of sustainability in construction projects increases in urgency when considered against the specific economic, social and environmental pressure of particular regions. Kurdistan Region in Iraq faces major barriers in pursuing sustainable development because of its expanding infrastructure needs. The fuzzy analytic hierarchy process (FAHP) serves as the research method to find out and rank sustainability issues across regional construction projects. The implementation of expert opinions along with linguistic variables within fuzzy AHP improves uncertain decision-making processes to deliver enhanced evaluation of essential challenges. The main purpose of the study is to identify and assess a crucial sustainability’s challenges by ranking them based on their significant. The challenges have been categorized into six main categories: organization and managerial, cultural and human attitudes, technical, financial, governmental and regulatory and technological barriers. Among the others, governmental and regulatory occupied the first place with 0.319 normalized weight. While organization and managerial and cultural and human attitudes weighted 0.256 and 0.167 respectively as second and third significant barriers among main challenges groups. Ineffective government policies on green construction ranked the first barrier among the sub-main challenges that construction project faced in Kurdistan Region. On the other hand, Communication of clean technology advantages to home buyers is ranked the less significant barrier among the others. The result provides valuable insights for policymakers, project manager and stakeholders offering a structured approach to address sustainability concerns and improving construction practices.

ABSTRACTBackgroundDental caries and iron deficiency anemia (IDA) are prevalent especially in developing children. There seems to be an association between these two variables.ObjectiveTo evaluate this association among children and adolescents using a systematic review and umbrella meta‐analysis technique.MethodsThe PRISMA reference databases like PubMed, Scopus, Web of Science and Google Scholar were searched for all records published before January 2025. Meta‐analyses that evaluated the association among < 18‐year‐olds were included. Parameters like odds ratio (OR) and mean difference (MD) with the 95% confidence interval (CI) were used to compare between the groups. I² and Cochran's Q (χ²) tests were used for measuring heterogeneity, whereas Egger's test was utilised to measure publication bias. A Measurement Tool to Assess systematic Reviews (AMSTAR 2) was used to assess the quality of the meta‐analyses. The degree of certainty of the outcomes was evaluated using the Grading of Recommendations Assessment, Development and Evaluation (GRADE) tool.ResultsA total of five meta‐analyses were included. Children with IDA were significantly over three times more likely to have dental caries than children without anemia (OR = 3.64, 95% CI: 2.45 to 5.40, p < 0.0001. Heterogeneity: I² = 80%, p = 0.007. Publication bias: p = 0.14. GRADE: Moderate). The pooled analysis for serum ferritin showed a tendency toward lower ferritin level in children with caries; but without statistical significance (MD = −3.96, 95% CI: −8.48 to 0.57, p = 0.087. Heterogeneity: I² = 66.3%, p = 0.031. Publication bias: p = 0.003. GRADE: Very low). Children with dental caries had lower haemoglobin levels, but the finding was not significant with high level of heterogeneity and publication bias (MD = −2.20 g/dL, 95% CI: −4.59 to 0.19, p = 0.071. Heterogeneity: 80.%, p = 0.006. Publication bias: p = 0.005. GRADE: Very low). Children with caries had lower MCV, but this result was non‐significant with evidence of heterogeneity and publication bias (MD = −1.96 fL, 95% CI: −4.02 to 0.10, p = 0.062. Heterogeneity: I² = 57.2%, p = 0.096. Publication bias: p = 0.041. GRADE: Very low).ConclusionDental caries was more prevalent among anemic children compared to non‐anemic ones with a low level of certainty.

Nowadays, real-world optimization problems are becoming increasingly complex tasks, prompting the development of nature-inspired algorithms that mimic biological phenomena to improve search performance and solution quality. The Mud Ring Algorithm (MRA), inspired by the cooperative hunting behavior of bottlenose dolphins, has shown promise but remains sensitive to parameter settings, especially when balancing exploration and exploitation. To address these limitations, this paper proposes the Enhanced Mud Ring Algorithm (EMRA), which introduces a novel mechanism to more effectively manage the exploration-exploitation tradeoff. This modification allows the algorithm to escape local minima and explore the solution space more effectively. Numerical experiments on some standard benchmark functions as well as the difficult Congress on Evolutionary Computation 2019 benchmark suite show that EMRA outperforms the original MRA in terms of accuracy performance and computational cost, especially when dealing with high-dimension and multi-peak functions. In addition, EMRA was used in three complex engineering optimization problem designs (welded beam, pressure vessel, and tension spring), and the results were found to be more accurate and reliable than MRA. These results validate the strength and applicability of EMRA as a general optimization tool to tackle complex problems from many different disciplines, including real-world problems requiring the exhaustive exploration of multiple options. In summary, this study shows that EMRA is an effective extension of metaheuristic optimization that is applicable in real-world problems.