ARO-THE SCIENTIFIC JOURNAL OF KOYA UNIVERSITY

Predictive Logistic Models for Off-Street Parking Policy

2025-02-04T19:55:49+00:00

The land in city centers is typically used for commercial and industrial purposes, leading to increased traffic congestion. To promote more efficient, sustainable, and accessible land use in city centers, it is necessary to manage incoming traffic flow and travel demands effectively. This can be achieved by implementing appropriate parking policies, which should be predicted carefully to avoid adverse effects on human and economic activities. A case study is conducted in Duhok city, Iraq, aims to estimate the potential responses of city center travelers to reasonable off-street parking restriction policies. Real data were gathered through interviews with a quantitative sample of drivers to assess their reactions to two policies: increasing parking fees and reducing available parking spaces. The study examines central parkers’ socio-demographic and travel characteristics, including origin, trip purpose, timing, parking duration, search time, payment, income, age, and car occupancy. The study presents the results of two binary logistic models used to estimate the probability of implementing new parking policies to alleviate traffic congestion and improve movement. The findings suggest that travelers are more inclined to change their mode of transportation or travel time of day rather than altering their destination or canceling their trip. The findings contribute to the ongoing discourse on sustainable urban development and offer practical solutions for addressing the complex challenges associated with traffic volume and movement control in developing cities. This study aims to contribute to the growing body of knowledge on sustainable urban transportation planning and offer practical recommendations for transportation authorities.

Extraction of Nickel Oxide from Spent Catalyst for Environmentally Safe Disposal

2025-02-04T19:57:16+00:00

Molecular sieves are used in various industries, especially petroleum and gas processing plants, as catalysts. These materials are in contact with crude oil products. After several operational years, these materials’ activities were reduced to a nonfeasible level called spent molecular sieve. Tens of tons are disposed of annually from oil and gas companies in Iraq. The paper aims to determine the kinds and amounts of toxic materials carried by the nickel oxide sulfur bed spent catalyst and then submit the suitable treatment methods, such as leaching by water, base solution, and acid solution. Aradioactive test was first done to ensure the material was free from the radioactivity array. The material was tested for nickel oxide concentration after each step of treatment. It was found that the leaching by water reduces the content by 4.5% during 24 h of leaching and 15.5% after 7 days. The leaching by alkaline sodium hydroxide 10% concentration solution reduces the content by 7% during 24 h and 14.3% after 7 days. The 10% hydrochloric acid concentration solution leaching reduces the nickel content by 10.8 during 24 h and 65.7 after 7 days. Leaching by acid solution is more efficient in the extraction of nickel oxide. The treatment method novelty is to be carried out at reasonable temperatures with high metal extraction efficiency. The research results achieved this goal of attaining extraction at an easily achievable temperature of 70°C with a relatively good extraction rate higher than 65%.

Dual-Band Power Divider with Wide Suppression Band

2025-02-06T11:27:16+00:00

In this paper, a planar dual-band Wilkinson power divider (DWPD) with a triangular-shaped resonator is designed. This work stands out from existing designs by addressing key limitations in conventional power dividers, i.e., physical size, harmonic suppression, and insertion loss. The proposed triangular shaped resonator has a compact size of 9.9 mm × 3.4 mm (0.26 λg × 0.09 λg ), where λg is electrical wavelength at 5.9 GHz, and provides a wide suppression band from 7.1 GHz to 20.6 GHz with a 20 dB attenuation level. In the proposed DWPD structure, two triangular shaped resonators are used in two branches. It works at 3.6 GHz and 5.5 GHz with <0.1 dB insertion loss at both operating bands. The input and output return losses and ports isolation parameters at both bands are better than 20 dB, which show good performance of the divider at operating bands. Besides the acceptable performance, the proposed DWPD provides a wide suppression band from 6.8 GHz to 20.5 GHz with more than 20dB attenuation level. In the divider design, the neural network is employed to model a triangular-shaped resonator. The proposed neural network has two outputs (S11 and S21), and two hidden layers with eight neurons at each layer. The weights of each neuron are obtained using particle swarm optimization algorithms. The proposed neural network model has accurate results, and the mean relative error of the train and test data for both outputs is <0.1 , which validates the accurate results of the proposed model.

The Role of Immune Defense in Serratia marcescens Nosocomial Infections

2025-02-04T19:35:24+00:00

Developing resistance mechanisms leads to various nosocomial infections caused by opportunistic bacteria. Serratia marcescens are well known to be opportunistic and are equipped with an armory of virulence factors against host immune response. The study aims to detect the immune defense in patients infected with multidrug-resistant S. marcescens. The study includes 132 clinical samples, including burn, wound, otitis media, and urinary tract infection (UTI) at several hospitals in Baghdad, Iraq. All isolates are identified by cultivation on MacConkey agar, nutrient agar, and blood agar, followed by biochemical tests and assessment with the VITEK 2 compact system. The isolates are tested for antibiotic susceptibility tests, interleukin-12 (IL12) levels, neutrophil ability to phagocytosis, and complement C3 and C4 levels. Out of 120 positive cultures, six isolates are identified as S. marcescens. The urine samples are the most isolated source and a higher level of antibiotic resistance was noticed in ampicillin and cefotaxime (100%), whereas a lower level is in imipenem. Stimulation (p ꞊ 0.005) provided a significant increase in IL-12 production. The infection with the S. marcescens stimulated the neutrophil’s phagocytosis process compared with the control. The interplay role of virulence factors in S. marcescens influences its pathogenesis, antibiotic resistance, and immune response, particularly involving neutrophils and IL-12. Understanding these interactions is crucial for developing effective therapeutic strategies.

Gene Polymorphism of Antigen B Subunit 2 and Pathogenesis of Cystic Echinococcosis in Murine Model

2025-02-07T00:33:26+00:00

A complex genetic diversity among the causative agent, Echinococcus granulosus, is documented. Antigen B (AgB) is a major antigenic fraction of hydatid fluid and hydatid cyst tissues. This study aims to investigate the role of antigen B subunit 2 (AgB2) gene polymorphism in the pathogenesis of cystic echinococcosis (CE) in murine model. Ovine liver hydatid cysts are obtained from Erbil Slaughterhouse. Protoscoleces from each isolate are separated into two batches. First preserved at −20°C for molecular analysis whereas the second is used for experimental infection in mice. Parasite DNA was extracted, and AgB2 genome was amplified and sequenced. The sequencing profile of six of the isolates (1, 2, 3, 5, 8, and 11) revealed a 100% analogy with AgB2 gene of E. granulosus genotype G2. Minor sequence polymorphisms, 1.67%, are observed in one of the isolates, whereas remarkable DNA sequence polymorphisms are noticed in three of the isolates. The polymerase chain reaction (PCR) products sequencing profiles revealed 100% polymorphisms in four of the isolates in comparison with the source gene (AY569356.1), instead, those isolates reveal various degrees of analogy, 80.33%, 80.87–89.05%, and 89.36% to G1, G3, and G6, respectively. Polymorphic sequencing profile of the PCR-amplified product (250 bp) of E. granulosus clone EgB2G2v13 AgB2 gene (Accession no.: AY569356.1) has no significant impact on the pathogenicity of the CE in murine model. To upgrade the diagnostic sensitivity rates of the
immunological techniques, a mixture of native hydatid antigens containing AgB is recommended to be used in the ser-diagnosis of this infection.

Computational Study of Some Urolithin Derivatives-based Biomass Corrosion Inhibitors on the Fe (110), Cu(111) and Al(111) Surface

2025-02-07T00:33:25+00:00

Corrosion poses a significant economic and environmental burden, highlighting the need for sustainable corrosion inhibitors. This study investigates the potential of urolithin derivatives (UroE, UroM5, UroM6, and UroM7) as eco-friendly corrosion inhibitors for Fe(110), Cu(111), and Al(111) surfaces. The research uses Density Functional Theory (DFT) calculations and Monte Carlo (MC) simulations to compute quantum chemical parameters, Fukui function, and noncovalent interactions. The results show that compounds with strong hydrogen bonding interactions form more robust bonds with the metal surface, potentially leading to enhanced corrosion protection. UroM5 demonstrates superior stability and lower reactivity due to its high band gap energy. MC simulations reveal that the adsorption energies of urolithin derivatives on metal surfaces follow a trend: UroM5 > UroM6 > UroE > UroM7, suggesting a stronger binding affinity for these metals. Thermal characteristics, particularly Gibbs free energy, were also investigated. The results suggest that a temperature increase from 825 to 1000 K may induce a transition from physisorption to chemisorption for all chemicals on the metal surface. These comprehensive analyses provide valuable insights into the mechanism and efficiency of urolithin derivatives as corrosion inhibitors, paving the way for the development of novel and eco-friendly anti-corrosion materials.

A Comprehensive Review of Facial Beauty Prediction Using Multi-task Learning and Facial Attributes

2025-02-04T19:55:35+00:00

Beauty multi-task prediction from facial attributes is a multidisciplinary challenge at the intersection of computer vision, machine learning, and psychology. Despite the centrality of beauty in human perception, its subjective nature—shaped by individual, social, and cultural influences—complicates its computational modeling. This review addresses the pressing need to develop robust and fair predictive models for facial beauty assessments by leveraging deep learning techniques. Using facial attributes such as symmetry, skin complexion, and hairstyle, we explore how these features influence perceptions of attractiveness. The study adopts advanced computational methodologies, including convolutional neural networks and multi-task learning frameworks, to capture nuanced facial cues. A comprehensive analysis of publicly available datasets reveals critical gaps in diversity, biases, and ground truth annotation for training effective models. We further examine the methodological challenges in defining and measuring beauty, such as data imbalances and algorithmic fairness. By synthesizing insights from psychology and machine learning, this work highlights the potential of interdisciplinary approaches to enhance the reliability and inclusivity of automated beauty prediction systems.