http://192.64.112.23:8080/xmlui/handle/311/77 2025-12-01T07:14:42Z 2025-12-01T07:14:42Z Mashayekhi, Bita Mohammed, Yousif http://192.64.112.23:8080/xmlui/handle/311/94 2025-02-21T19:28:39Z 2025-01-01T00:00:00Z

Perceived Internal Audit Quality and External Auditors’ Attributes in Iranian and Iraqi Banks Mashayekhi, Bita; Mohammed, Yousif The significance of internal auditing and its quality cannot be overstated, making it essential to investigate the factors influencing this quality. This study, employing a cross-sectional analysis, aims to assess how the characteristics of external auditors affect the perceived quality of internal audits in Iranian and Iraqi banks. In 2024, data regarding the attributes of external auditors and the perceived quality of internal audits were collected through a questionnaire distributed to external auditors from various banks in Iran and Iraq. The data analysis was conducted using Partial Least Squares Structural Equation Modeling (PLS-SEM). The study reveals a positive relationship between external auditors’ competence and independence and the perceived quality of internal audits, while it shows a negative impact of external audit methodologies on this perceived quality. These findings highlight the importance of external auditors’ independence as a key determinant of perceived internal audit quality.

2025-01-01T00:00:00Z J. Jalil, Parwin M. Mhamedsharif, Renjbar H. Shnawa, Bushra M. Hamad, Samir Aspoukeh, Peyman H. Ahmed, Mukhtar http://192.64.112.23:8080/xmlui/handle/311/93 2025-02-21T19:23:26Z 2025-01-01T00:00:00Z

Comparative assessment of Anti‑inflammatory and catalytic properties of chemically synthesised and green‑synthesised silver nanoparticles from Ziziphus spina‑christi leaf extract J. Jalil, Parwin; M. Mhamedsharif, Renjbar; H. Shnawa, Bushra; M. Hamad, Samir; Aspoukeh, Peyman; H. Ahmed, Mukhtar Background Green synthesis is chosen for its environmental friendliness, as it eliminates the need for toxic chemicals by using natural compounds as reducing and stabilising agents. This research investigates the synthesis of silver nanoparticles (Ag-NPs) through green methods, utilising Ziziphus spina-christi leaf extract, and compares them with commercially avail- able silver nanoparticles. Aim The study compares the structural, morphological, physicochemical, toxicity, anti-inflammatory, and catalytic proper- ties of green-synthesized Ag-NPs (GS-Ag-NPs) with commercial Ag-NPs (CS-Ag-NPs). Methods Various techniques, including UV–Vis spectroscopy, Fourier transform infrared spectroscopy, Scanning electron microscopy, X-ray diffraction, transmission electron microscopy, dynamic light scattering, energy-dispersive X-ray spec- troscopy, zeta potential analysis, and thermal gravimetric analysis were employed to characterise the synthesised Ag-NPs. In vitro toxicity assessments, anti-inflammatory activity assays, and catalytic activity studies were conducted to evaluate the biocompatibility, anti-inflammatory, and catalytic properties of the synthesised Ag-NPs. Results The results indicate that GS-Ag-NPs exhibit a more uniform size distribution (20.23 nm) and spherical morphology than commercial Ag-NPs, which have a larger size (38.2 nm). In vitro toxicity assessments show that GS-Ag-NPs are more biocompatible, with minimal haemolysis (3.2 ± 0.1%) compared to commercial Ag-NPs (19 ± 0.48%). Additionally, GS- Ag-NPs demonstrate enhanced anti-inflammatory activity (19.04%) and slightly higher catalytic activity in dye degradation processes at lower dye concentrations. Conclusion This comparative analysis highlights the advantages of green synthesis methods in producing biocompatible, stable, and functionally superior Ag-NPs. The findings suggest the potential of GS-Ag-NPs for applications in various fields, including biomedicine, catalysis, and environmental remediation

2025-01-01T00:00:00Z Laith Ali, Aenas Kareem Mahmood, Bahroz Obaid Kareem, Rebaz Ates, Tankut A. Barzinjy, Azeez Bulut, Niyazi Keser, Serhat Kaygili, Omer http://192.64.112.23:8080/xmlui/handle/311/92 2025-02-21T19:18:12Z 2025-01-01T00:00:00Z

Experimental and theoretical analysis of bismuth Co-doped erbium- based hydroxyapatites Laith Ali, Aenas; Kareem Mahmood, Bahroz; Obaid Kareem, Rebaz; Ates, Tankut; A. Barzinjy, Azeez; Bulut, Niyazi; Keser, Serhat; Kaygili, Omer This study explores the impact of bismuth (Bi) and erbium (Er) co-doping on the structural, morphological, and electronic properties of hydroxyapatites (HAp). Bi/Er co-doped HAp samples at varying concentrations were synthesized through a wet chemical process and characterized using X-ray diffraction (XRD), Fourier transform infrared (FTIR) spectroscopy, and scanning electron microscopy (SEM). Additionally, density functional theory (DFT) was employed to analyze band structure (BS), energy gap (Eg), density of states (DOS), and linear attenuation coefficient (LAC). Results revealed a sys- tematic decrease in the energy gap from 4.0340 eV to 3.9222 eV with increasing Bi content, highlighting a reduced band gap energy trend as the Bi and Er concentrations increase. Higher Bi concentration also influenced the DOS and BS, and reduced crystallite size (D) across samples. Among them, the 0.26Bi-0.39Er-HAp sample exhibited the lowest crystallinity (76.56%) and smallest crystallite size (27.84 nm). This study provides valuable insights into how co-doping affects HAp properties, with potential implications for biomedical and environmental applications

2025-01-01T00:00:00Z Muhealddin Awlla, Kozhin Veisi, Hadi Abas Abdullah, Abdulhady http://192.64.112.23:8080/xmlui/handle/311/91 2025-02-21T19:12:05Z 2025-01-01T00:00:00Z

Sentiment analysis in low‑resource contexts: BERT’s impact on Central Kurdish Muhealddin Awlla, Kozhin; Veisi, Hadi; Abas Abdullah, Abdulhady This paper enhances the study of sentiment analysis for the Central Kurdish lan- guage by integrating the Bidirectional Encoder Representations from Transformers (BERT) into Natural Language Processing techniques. Kurdish is a low-resourced language, having a high level of linguistic diversity with minimal computational resources, making sentiment analysis somewhat challenging. Earlier, this was done using a traditional word embedding model, such as Word2Vec, but with the emer- gence of new language models, specifically BERT, there is hope for improvements. The better word embedding capabilities of BERT lend to this study, aiding in the capturing of the nuanced semantic pool and the contextual intricacies of the lan- guage under study, the Kurdish language, thus setting a new benchmark for senti- ment analysis in low-resource languages. The steps include collecting and normal- izing a large corpus of Kurdish texts, pretraining BERT with a special tokenizer for Kurdish, and developing different models for sentiment analysis including Bidi- rectional Long Short-Term Memory (BiLSTM), Multi-Layer Perceptron (MLP), and finetuning the BERT classifier. The proposed approach consists of 3 classes: positive, negative, and neutral sentiment analysis using a sentiment embedding of BERT in four different configurations. The accuracy of the best-performing clas- sifier, BiLSTM, is 74.09%. For the BERT with an MLP classifier model, the maxi- mum accuracy achieved is 73.96%, while the fine-tuned BERT model tops the oth- ers with 75.37% accuracy. Additionally, the fine-tuned BERT model demonstrates a vast improvement when focused on two 2-class sentiment analyses positive and negative with an accuracy of 86.31%. The study makes a comprehensive compari- son, highlighting BERT’s superiority over the traditional ones based on accuracy and semantic understanding. It is motivated because several results are obtained that the proposed BERT-based models outperform Word2Vec models conventionally used here by a remarkable accuracy gain in most sentiment analysis tasks

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