University of Thi-Qar

Hendi S.H., Taher H.B., Hussein K.Q.

AbstractSurveillance video processing requires high efficiency, given its large datasets, demands significant resources for timely and effective analysis. This study aims to enhance surveillance systems by developing an automated method for extracting key events from outdoor surveillance videos. The proposed model comprises four phases: preprocessing and feature extraction, training and testing, and validation. Before utilizing a convolution neural networks approach to extract features from videos, the videos are pre-processed. Events classification uses gated recurrent units. In validation, motions and objects are extraction then feature extraction. Results show satisfactory performance, achieving 79% accuracy in events classification, highlighting the effectiveness of the methodology in identifying significant outdoor events.

Altimemy M., Caspar J., Shkarah A., Oztekin A.

Due to the increasing global power demand, hydropower plants face the challenge of operating at flow rates far from their best efficiency point to comply with the electrical grid. Consequently, turbine units experience unstable high swirling flows under different load conditions, reducing the life of system components. Understanding the mechanisms behind the onset and sustenance of these instabilities in the swirling flow leaving the turbine runner is crucial for improving turbine performance. To achieve this, large eddy simulations were conducted to characterize the unsteady flow inside an industrial-sized Francis turbine. The turbine was studied under a wide range of flow rates, 100%, 80%, 60%, 40%, and 120% of the design flow rate. A high swirl velocity was introduced as the flow rate deviated from 100% load, causing significant changes in the flow structure. An organized structure of vortex filaments in a helical pattern is seen inside the draft tube at 80% and 60% load, and the 40% load case showed an unorganized collection of small-scale vortices. A straight vortex cavity is seen in the draft tube center at 120% excess load. At the best design point, the magnitude of the swirl velocity was 0.1 times the tip speed. However, as the flow rate dropped to 40% of the design flow rate, the magnitude increased to 0.4 times the tip speed near the wall. In addition, the 40% load case had the highest magnitude of pressure fluctuations, over 25 times the peak design case near the runner. This showed that a very unsteady flow field could damage the system or cause unstable operation at ultra-low partial loads. Generated power dropped dramatically as the flow rate decreased, and more noise was present in the power signal.

Al-Abbasi M.A., Fadhil Z., Mahmood S.S., Al-Mashhadani M.H., Jawad S.F., Alhuwaymil Z., Alshareef S.A., Alyami M.S.

A simple, fast, and accurate indirect spectroscopic method has been developed to determine remdesivir (Rem) by the dye bleaching method in an aqueous medium. This method for determining remdesivir involves proposed two steps. First, metanil yellow dye is bleached in acidic media using KBr and KBrO3, which breaks the azo group and reduces it to primary amine groups, turning the dye from yellow-orange to colorless. Second, remdesivir is added to the colorless solution, a reaction likely occurs between remdesivir and any remaining bromine or other oxidation products. The purple color could be due to the formation of a complex between remdesivir and an intermediate oxidation product. Then, the remaining-colored dye (purple) absorption is measured at a wavelength of 526 nm following Beer’s law limitation 2–28 µg.mL− 1. The product remains stable for 60 min, with detection and quantification limits (LOQ) of 0.0181 and 0.0549 µg.mL− 1, respectively. The molar absorption coefficient is 51340.668 and 3325.076 L mol− 1.cm− 1 while the Sandell sensitivity is 0.0117 and 0.1316 µg.cm− 2. The method was successfully applied to estimate the pharmaceutical preparation COVIFOR™ (Injection 100 mg). The relative deviation value was not more than 0.6182%, and the recall rate was 99.4610%, indicating the proposed method’s success in estimating remdesivir and the possibility of its practical use in estimating the drug in pharmaceutical preparations.

Du H., Tan M.L., Xia L., Tew Y.L., Yaseen Z.M.

ABSTRACT Solar radiation modification (SRM) has been discussed as a potential strategy to rapidly mitigate global warming by reflecting more sunlight into space. However, its impact on tropical hydrological cycles remains underexplored. This study investigates the potential impacts of SRM on streamflow of the Kelantan River Basin (KRB) by incorporating climate projections from the Geoengineering Model Intercomparison Project Phase 6 (GeoMIP6) into the Soil and Water Assessment Tool plus (SWAT+) model. The findings reveal that UKESM1-0-LL and MPI-ESM1-2-LR exhibit greater uncertainty in representing the climate of the KRB compared to CNRM-ESM2-1 and IPSL-CM6A-LR. Maximum and minimum temperatures under SSP5-8.5 are projected to increase by up to 3.52 °C by the end of the 21st century, while these increases could be limited to between 1.72 and 2.33 °C under SRM scenarios, corresponding to 1.96 to 2.22 °C under SSP2-4.5. The multi-model ensemble mean projected an inverse V-shaped trend in annual precipitation, with a peak in the mid-21st century before declining, except for G6sulfur, which exhibits a steady decrease. Increases in monthly precipitation during the 2045–2064 period may intensify flooding in the KRB. Meanwhile, decreases in streamflow during dry months are projected for the periods 2045–2064 and 2065–2085 under G6sulfur, particularly in the middle and upper basins.

Abdulaali H.S., Usman I.M., Alawi M., Alqawzai S.

This study examines the impact of Indoor Environmental Quality (IEQ) on guest comfort and satisfaction in former Green Building Index (GBI)-certified green hotels in Malaysia’s historic cities, including Kuala Lumpur, Melaka, and Penang. With many hotels moving away from certification, it highlights the need to maintain high environmental and comfort standards. The research evaluates IEQ performance, suggests additional parameters, and explores how comfort mediates the relationship between IEQ and satisfaction. Eight hypotheses were tested, focusing on indoor air quality (IAQ), thermal comfort, lighting, acoustics, visual comfort, building features, decoration, and indoor greenery. A survey of 700 hotel guests resulted in 384 valid responses, confirming that IEQ significantly influences comfort and satisfaction. Among the factors, acoustic/noise (Beta = 0.305), IAQ (Beta = 0.221), and building characteristics (Beta = 0.167) were the most impactful, followed by thermal comfort, lighting, decoration, visual comfort, and indoor greenery. Regression analysis showed a strong link between guest comfort and satisfaction, with comfort as a key mediator. Challenges included noise, thermal discomfort, and lighting problems. The study emphasizes the importance of air quality, thermal comfort, and noise management while balancing aesthetic elements like greenery and decoration to improve guest experiences. It offers valuable insights for hotel operators, advancing sustainable practices and guest satisfaction in green-certified hotels.

Benhamida O., Dahmani Z., Ibrahim R.W.

The aim of this work is to study two classes of stochastic fractional differential equations via the application of the method of upper and lower solutions combined with the Arzela-Ascoli theorem. We begin by proving an auxiliary result for the integral representation of an Airy-type stochastic problem. The specific symmetry features of an Airy-type stochastic problem depend on the form of the stochastic differential equations (SDE) and the relevant coefficients, it is vital to note. To comprehend each issue’s unique symmetries and their effects, a thorough investigation is necessary. Then, we prove an existence result for extremal solutions for the same problem. Another class of stochastic equations of higher-order type is also studied. We also present some examples to show the validity of the obtained results. At the end, a conclusion follows.

Rosmadi H.S., Ahmed M.F., Radwan N., Mokhtar M.B., Lim C.K., Halder B., Scholz M., Alshehri F., Pande C.B.

Flood disasters are common events in Malaysia, particularly during the monsoon seasons. Hence, disaster management in Malaysia is based on the framework following “Directive 20” by the National Security Council (MKN). This study gathered qualitative information in Shah Alam Municipality through informal interviews with 20 informants following the quadruple-helix multi-stakeholders model in 2023 for flood disaster management (FDM). Thematic analysis of the qualitative information was conducted following the four main priority of action themes of the Sendai Framework for United Nations Disaster Risk Reduction (2015–2030) using the Taguette software. This study found coordination and inter-agency data sharing are two major issues in Shah Alam that require immediate attention for FDM. Thus, this study suggests improving district-level flood management guidelines, especially the involvement of the National Disaster Management Agency (NADMA). The NADMA should have a close look at the flood management plan, which acts as Malaysia’s main disaster management coordinator, as they are usually the first agency on the scene when a disaster occurs. Hence, to prevent and lessen flood disaster impact, disaster risk preparedness and individual management through customized training are crucial in combining non-structural and structural measures for FDM.

Mallah S.H., Waheeb A.S., Hassan A.U., Awad M.A., Jalfan A.R., Elnaggar A.Y., El Azab I.H., Mahmoud M.H.

In this study, an approach to design new fluorescent organic polymers based on benzodithiophene (BDT) chromophores are presented by utilizing machine learning (ML) techniques. For this, the BDT chromophores, from the literature, along with their corresponding λe. by using Rapid Discovery Kit (RDKit), their molecular descriptors are designed to employ ML models for predicting their λmax and λe properties. Among the evaluated models, Linear Regression, Random Forest and Decision Tree models demonstrate the best performance, achieving R² values between 0.96 and 0.98. Their analysis of SHapley Additive exPlanations (SHAP) values reveals that the Labute Accessible Surface Area (ASA) and the number of Rotatable Bonds can be the most influential features to impact their performance. Leveraging these insights, their 5,000 new polymers are designed with their predicted λe extending up to 987 nm. Their highest Synthetic Accessibility Likelihood Index (SALI) scores for the top 1,000 polymers reaches up to 3.21 to indicate their accessibility for synthesis. This work not only advances the understanding of BDT -based materials but can also provide a framework for designing of new fluorescent polymers.

Miniandi N.D., Jamal M.H., Muhammad M.K., Sharrar L., Shahid S.

This study presents a novel machine learning-based approach by integrating urban land surface indices, including the Normalized Difference Vegetation Index (NDVI), Normalized Difference Built-up Index (NDBI), Urban Index (UI), Normalized Difference Water Index (NDWI), and Albedo, derived from high-resolution Landsat 8 data, to quantitatively assess the effectiveness of Urban Heat Island (UHI) mitigation strategies for Kuala Lumpur. Nonparametric correlation analysis was used to select the most suitable land features for developing Machine Learning (ML) models and predicting Land Surface Temperature (LST). The results showed that Kuala Lumpur’s LST had risen to 2.2 °C between 2013 and 2023, driven by urban development and the resulting UHI effect. Comparative analysis of the ML models revealed that the random forest (RF) model best estimated LST, with a Kling-Gupta Efficiency (KGE) of 0.68 and a spatial bias of ± 1.6 °C. Application of the RF model showed that an improvement in NDVI by 25% can cause a drop in LST ranging from − 1.4 to 0.1 °C, while a 25% increase in albedo can decrease the LST by -1.2 to 0.1 °C. The reduction in LST is highest in areas with high LST, indicating the possibility of mitigating the extreme UHI effect by enhancing albedo and NDVI. This study offers a data-driven alternative to costly numerical simulations, making it one of the first applications of ML for UHI modeling in a tropical megacity like Kuala Lumpur.

Hamed M.M., Ali Z., Nashwan M.S., Shahid S.

ABSTRACTThis study aims to project extreme temperatures and the population exposed to them in the MENA region for two Shared Socioeconomic Pathways (SSP1‐1.9 and 1‐2.6), representative Paris climate agreement goals of 1.5°C and 2.0°C temperature rise limits, respectively, for two future periods, near (2020–2059) and far (2060–2099). The daily maximum (Tmax) and minimum (Tmin) temperature of global climate models (GCMs) of the coupled model intercomparison project phase 6 (CMIP6) were used to estimate eight temperature indices, while the population distribution for the historical and future periods was used to assess the changes in the population exposed to temperature extremes. Eastern regions faced the highest increase of warm spells, up to 100 days more in SSP1‐2.6, while cold spells decreased the most in Egypt and Sudan by up to 24 days in the same scenario. The southern region faced the highest increase in summer days, with population exposure up to 25 million person‐day by 2099. The extremes in temperature would mainly affect the populations of Mauritania, Algeria, Morocco, Saudi Arabia, Iraq, UAE, and Qatar. For a temperature rise of 2.0°C, the percentage of the population exposed to the extremes expressed by duration will increase by between 2.7% and 18.5% by 2059 and by between 8.9% and 77.8% by 2099, indicating a significant increase in the population exposed to the hot extreme for only 0.5°C rising temperature. However, the changes will be more remarkable for the cold and hot extremes.

Mohammed A.G., Al Waeli D.K.

Abstract Introduction X-linked hypophosphatemic rickets (XLH) is a rare genetic disorder characterized by phosphate wasting, leading to rickets in children and osteomalacia in adults. We present the case of a 21-year-old male diagnosed with XLH, highlighting the clinical features, diagnostic approach, and management strategies employed. XLH is the most common form of heritable rickets, caused by mutations in the PHEX gene. It manifests as rickets in children and osteomalacia in adults, accompanied by bone pain, muscle weakness, and skeletal deformities. We discuss a case emphasizing the importance of early diagnosis and comprehensive management. Clinical Case Mr. AH, a 21-year-old single, non-smoking male, presented with bowing of the legs and was found to have elevated urine phosphate levels. Laboratory tests revealed a calcium level of 9.3 mg/dL, phosphate level of 2.19 mg/dL, parathyroid hormone (PTH) level of 20.98 pg/mL, and vitamin D was not evaluated at the time of presentation. His stature was notably short for his age, with a height of 130 cm and a weight of 50 kg. Blood pressure was recorded at 130/70 mmHg. The patient's clinical presentation, alongside laboratory findings indicative of hypophosphatemia, elevated urine phosphate, and an inappropriately normal PTH level, led to the diagnosis of XLH. The diagnosis was further supported by the characteristic skeletal deformities observed. Initially, the patient was managed with phosphate supplements and active vitamin D analogs. Specifically, he was prescribed Zoledronic acid (Zometa) 4mg injection, One Alpha (alfacalcidol) 0.25 mcg tab leo minepharma 2x2, and Diabase tab (calcitriol) 50000 IU weekly. This treatment regimen aimed to correct the hypophosphatemia, improve bone mineralization, and ameliorate the clinical symptoms. Managing XLH necessitates a multidisciplinary approach, focusing on correcting phosphate levels, supplementing vitamin D, and addressing skeletal deformities. Zoledronic acid, an antiresorptive agent, along with phosphate and vitamin D supplementation, can effectively manage these aspects. However, monitoring for complications such as nephrocalcinosis is crucial. Conclusion This case underscores the complexities of diagnosing and managing XLH. Early intervention and a tailored therapeutic strategy are pivotal in improving patient outcomes, highlighting the necessity for awareness and understanding of this rare condition among clinicians.

Mohammed A.G., Al Waeli D.K.

Abstract Clinical Case A 21 year old single male presented with growth failure, delayed puberty, and significant liver enlargement attributed to glycogen deposition, a rare complication observed in some children and young adults with Type 1 Diabetes Mellitus (T1DM), irrespective of glycemic control. In his initial visit (Sep 5, 2020):Height: 144 cm, Weight: 40 kg. The patient’s uncontrolled diabetes and growth failure were notable. In the follow-up visits (Oct 4, 2020 - May 20, 2024), the patient exhibited fluctuating glycemic control (HbA1c ranging from 9.7% to 12.0%), variably elevated liver enzymes (ALT and AST), and concerning lipid profiles, with triglycerides peaking at 905 mg/dL. Growth parameters remained below the expected range for age and sex, indicating persistent growth failure. Laboratory tests highlighted uncontrolled diabetes, hypertriglyceridemia, and liver enzyme elevation. Endocrinological assessments revealed low testosterone levels with slightly altered FSH and LH, pointing to a hypogonadotropic pattern. The persistent high HbA1c levels (>10%) indicated poor glycemic control, complicating the patient’s liver condition and growth failure. The treatment regimen focused on intensive insulin therapy to manage diabetes, using combinations of NovoRapid, Tresiba, Ryzodec (aspart+degludec), and Apidra (Glulisine insulin). Lipid profile management included Lipanthyl (Fenofibrate) and Crestor (Rosuvastatin). Nutritional support was indicated with Nutrigen syrup aiming to address growth failure and possible micronutrient deficiencies. Despite the comprehensive management approach, challenges in achieving optimal glycemic control were apparent with the latest HbA1c at 9.7%. However, some improvement in liver enzymes and lipid profile was noted. Growth failure and delayed puberty remain significant concerns requiring ongoing multidisciplinary care. Conclusion This case underscores the complexity of managing rare complications of T1DM like extensive liver enlargement due to glycogen deposition, in conjunction with growth failure and delayed puberty. It highlights the necessity of an integrated therapeutic strategy focusing not only on glycemic control but also on the management of associated metabolic derangements and hormonal imbalances. Further research into targeted treatments for such rare complications is warranted. Managing patients with T1DM who develop rare complications such as extensive liver enlargement, growth failure, and delayed puberty is challenging. A holistic and tailored approach is essential for improving patient outcomes, underlining the crucial role of continuous monitoring, adjustment of therapeutic strategies, and multidisciplinary care.

Al Waeli D.K., Mohammed A.G., Albaghdadi F.A.

Abstract Introduction Pituitary gland hyperplasia (PGH) due to primary hypothyroidism (PH) still underdiagnosed. It is reversible with proper thyroxine therapy. Unfortunately, patients may be referred to unnecessary pituitary surgery without thyroid function test (TFT) assessment. We present a case of a 13 years old female scheduled for pituitary surgery for macro adenoma diagnosed by PMRI but fortunately, endocrine assessment revealed intense PH, proper treatment produced dramatic resolution in PGH. Increase number of Pituitary gland (PG) cells causes PGH leads to abnormally enlarged PG on pituitary MRI (PMRI) (1). There is hypercellularity, polymorphism with large acini and intact reticulum (2). Firstly described at 1851 in cretins (3). It could be physiological in pregnancy or pathological due to primary hypothyroidism (PH), primary hypoadrenalism or primary gonadal insufficiency (4). Typical PMRI showed diffuse, regular, isointense enlargement of PG with homogenous uptake of gadolinium (5). Clinical Case We present a 13 years old female scheduled for PG surgery due to large mass, fortunately referred for endocrinological evaluation which showed very high TSH and low free T4 with normal other endocrine & vision assessment. Diagnosis of PH established and thyroxine therapy started with monitoring response to treatment by TSH and repeat the PMRI after 7 months which showed dramatic reduction in PG size and TSH normalized. At presentation TSH was > 100 mIU/L (0.27-4.2), while Free T4 was 0.08 ng/dL (0.93-1.70 ng/dL). Thyroxine 50 mcg had been started and increased gradually according to TSH level every 6 weeks. After 7months, TSH level became 3 mIU/L and new PMRI showed significant reduction in size of PG. Low thyroid hormones caused thyrotrophic hyperactivity resulting in PGH (6). Although thyrotrophs form 5-10% of anterior PG, trans conversion of somatotrophs to thyrotrophs with multiplication of thyrotrophs increase cells producing TSH (7). Hyperprolactinemia may occur in about 75% of cases and features of hypothyroidism are usual presentations in children and young patients rather than features due to sellar expansion (8). Thyroxine treatment reduces size of the PG in 85% of cases of PGH (9). Surgery may be indicated to decompress the optic chiasma or to confirm diagnosis when size not reduced or worsened with treatment (10). Although it is difficult to differentiate between tumor and PGH, prominent midline with smooth outlines suggests PGH (11). In PGH, there is a uniform hyperplasia causing homogenous enlargement on unenhanced T1,T2 images and post contrast there is an equal enhancement of hyperplastic PG (12). Biochemical, clinical and radiological follow up is indicated to check response and pick up early complications (13). Conclusion Prolonged, intense PH one of causes of PGH and should be kept in mind in every case of homogenously enlarged PG necessitating thyroid function and other pituitary hormones assessment before surgery.Figure 1:MRI picture before and after thyroxine therapyDramatic reduction in the size of pituitary gland after 7 month treatment with thyroxine.

Abdulmahdi M.A., Al-Khursan A.H.

Abstract This work studies the generation of the orbital angular momentum (OAM) beam in the double quantum dot-metal nanoparticle (DQD-MNP) system under the application of the OAM beam. First, an analytical model is derived to attain the relations of probe and generated fields as a distance function in the DQD-MNP system under OAM applied field and spontaneously generated coherence (SGC) components. The calculation here is of material property; it differs from others by calculating energy states of the DQDs and the computation of the transition momenta between quantum dot (QD)-QD and QD-wetting layer (WL) transitions. The orthogonalized plane wave (OPW) calculates QD-WL transitions and their momenta. The momentum calculation is essential to specify the Rabi frequency of the input field. Such characteristics are not used in earlier models. The results show that SGC is vital in increasing the generated field. The signal field generated in the DQD-MNP system doubles that from the DQD system alone. So, the DQD-MNP system is preferred to the DQD system. The generated field in the DQD-MNP for the strong coupling DQD-MNP system is higher than that for the weak coupling. Increasing the distance separating the DQD-MNP reduces the generated field. Higher OAM number reduce the generated field at a long distance in the device. The model is then extended to study the effect of incoherent pumping ( $$\:{R}_{inc}$$ ) and the relations are modified to cover this part. The results show that $$\:{R}_{inc}$$ reduces the generated field. While the results that compare the weak and strong coupling appear for the first, others compare well to the literature.

Alkhuwaylidee A.R., Gatea A.K., Alomari M.F.

The research aims to address the importance of the smart teaching system to guide and assist university students. By improving their learning experience. This system helps solve several problems related to the limited resources of universities and students, language barriers, and cultural differences. Uses technology to provide individual feedback, adaptive learning methods, and data analytics to improve student performance. Key features of the Smart Tutoring system include an easy-to-use interface, adaptive learning methods, and data analytics to monitor student achievement, identify areas for improvement, and help deliver personalized interventions. The system increases student engagement and motivation, improving the learning experience and promoting active participation in education.