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Abstract Introduction The use of anti-retroviral therapy (ART) has made HIV a manageable condition, but there are risks associated with medications like reverse transcriptase inhibitors (RTIs) and integrase strand transfer inhibitors (INSTIs), such as liver and renal toxicity. It is essential to understand these risks for effective treatment and case management. Investigating liver toxicity related to RTIs and INSTIs in Nigeria is crucial for optimizing HIV treatment. This study aimed to assess the impact of tenofovir lamivudine dolutegravir (TLD) on the liver function of HIV patients at Nigerian Navy Hospital (NNH)-Warri. Methods The liver function of 170 participants was assessed, with 120 on ART and the remainder being HIV-negative attendees at NNH-Warri. The study used a cross-sectional design and selected participants through random sampling. We collected data using a semi-structured questionnaire. Blood samples were taken through venipuncture and stored at – 20 °C before analysis. Ethical approval was obtained, and data analysis was conducted using SPSS Statistical Software Version 23, with significance set at p

Abstract In this study, task space tracking control of robot manipulators driven by brushless DC (BLDC) motors is considered. Dynamics of actuators are taken into account and the entire electromechanical system (i.e. kinematic, dynamic, and electrical models) is assumed to include parametric/structured uncertainties. A novel adaptive controller is designed and the stability of the closed loop system is ensured via novel Lyapunov type tools. To demonstrate performance and applicability of the proposed method, a simulation study is conducted using the model of a two degree of freedom, planar robotic manipulator driven by BLDC motors.

In modern physics, relativity is primarily understood through the framework of Einstein’s theory. According to the special theory of relativity (STR), Galilean relativity serves as a very accurate approximation at low velocities, where ‘relativistic effects’ can be neglected. However, at high velocities, these effects become significant and are accurately described by STR. This paper challenges this understanding, arguing that the opposite is true. In Galilean relativity, the relativity of time is substantial and cannot be ignored. Thus, relative time is more negligible in STR than in Galilean relativity. By comparing Galilean relativity and STR through physical, mathematical, and specific examples, two conclusions are drawn: first, the current categorization of relativity theories based on velocity magnitude is artificial and inaccurate; second, the relativity of time can be ignored in special relativity, while it remains significant and cannot be overlooked in Galilean relativity.

In this study, an assessment of Radon concentration in some selected water sources from Kiyawa town, Kiyawa local Government area, Jigawa state, Nigeria was conducted. The results obtained show that the concentrations of Radon in the water samples ranged from 32.152 to 43.891 Bq/L, with mean values of 37.78 Bq/L and 35.13 Bq/L for well and borehole water respectively. These results were compared with the world average Maximum Contaminant Level (MCL) of 10 Bq/L set by the World Health Organization (WHO), and it was observed that 60% of the recorded Radon concentrations, alongside the mean values for both water types, exceeded the WHO's recommended MCL of 10 Bq/L, as well as the MCL of 11.1 Bq/L set by the United States Environmental Protection Agency (USEPA) in 1991. However, all mean values were below the recommended action level of 100 Bq/L set by the European Commission (2001/928/Euratom) for public water supplies, and WHO in 2008. Also, all the mean values of the annual effective doses exceeded the recommended level of 0.1 mSv/year set by the WHO. Consequently, it is recommended that the inhabitants of Kiyawa town boil their water, regardless of its source, before drinking to reduce Radon concentrations in the water.

Abstract Background Preeclampsia, a complex hypertensive disorder unique to pregnancy, significantly impacts maternal and fetal health worldwide, with a prevalence of 2–8%. This condition results from a complex interplay of genetic, environmental, and immunological factors. Aim and objectives This study aims to investigate the genetic predispositions to preeclampsia, focusing on specific gene polymorphisms among pregnant women at Central Hospital Auchi, Nigeria. Materials and methods We examined the endothelial nitric oxide synthase (eNOS), vascular endothelial growth factor (VEGF), angiotensin-converting enzyme (ACE), and tumor necrosis factor-alpha (TNF-α) genes in 200 pregnant women, equally divided between preeclamptic patients and normotensive controls. Results The eNOS G894T polymorphism was significantly associated with preeclampsia, with the T allele nearly doubling the risk. The VEGF C936T polymorphism's T allele also indicated a higher risk. The D allele in the ACE gene's insertion/deletion (I/D) polymorphism significantly increased the risk, as did the A allele in the TNF-α G308A polymorphism. Conclusions These findings highlight the importance of genetic factors in preeclampsia and suggest that genetic screening could improve risk stratification and early detection. Future research should integrate genetic, epigenetic, and environmental data to understand preeclampsia's multifaceted nature and develop targeted therapies. This study underscores the potential of personalized medicine in managing and reducing the risks associated with preeclampsia.

Analyzing secondary structures (SSs) during earthquakes is vital due to their vulnerability and potential impact on building functionality and occupant safety. Understanding the seismic performance of SSs requires analyzing the Floor Response Spectra (FRS). This research investigates how the dynamic interaction between the primary structure (PS) and SSs affects the FRS under near-field (NF) and far-field (FF) earthquake conditions. Both the elastic PS and SS are modeled as single-degree-of-freedom (SDOF) systems. The governing equations of motion of the PS and SS are derived and numerically solved using the RK4 method. The study examines the influence of the PS vibration period (Tp), tuning ratio (Tr), mass ratio , and SS damping ratio on FRS. Twenty horizontal ground motion excitations were selected for the study. Time-history analysis results indicate that the dynamic interaction is negligible at a lower mass ratio . For values of 0.01, 0.1, and 0.5, the peak acceleration response of the SS under near-field (NF) excitation decreased by 15.7%, 68.3%, and 79.1%, respectively, and by 15.2%, 68.9%, and 78.8% under far-field (FF) excitation, compared to the uncoupled case. The spectral acceleration response of the SS is significantly influenced by dynamic interaction within dynamic interaction has no effect on FRS across all considered values. Parametric analysis showed that NF earthquakes induce larger FRS peaks compared to FF events. In conclusion, a comparison between simulated FRS and those predicted by Eurocode 8 shows discrepancies, with the code-based formulation often either underestimating or overestimating the FRS magnitude.

Abstract Systemic amyloidosis involves the deposition of misfolded proteins in organs/tissues, leading to progressive organ dysfunction and failure. Congo red is the gold-standard chemical stain for visualizing amyloid deposits in tissue, showing birefringence under polarization microscopy. However, Congo red staining is tedious and costly to perform, and prone to false diagnoses due to variations in amyloid amount, staining quality and manual examination of tissue under a polarization microscope. We report virtual birefringence imaging and virtual Congo red staining of label-free human tissue to show that a single neural network can transform autofluorescence images of label-free tissue into brightfield and polarized microscopy images, matching their histochemically stained versions. Blind testing with quantitative metrics and pathologist evaluations on cardiac tissue showed that our virtually stained polarization and brightfield images highlight amyloid patterns in a consistent manner, mitigating challenges due to variations in chemical staining quality and manual imaging processes in the clinical workflow.

This research aimed to determine the impact of the mechanical densifying process of wood material on the varnish surface adhesion strength. Specimens from black pine (Pinus nigra) and Uludag fir (Abies bornmuelleriana Mattf.) were subjected to densification in a hydraulic press at 140 °C to the extent of 25% and 50% in the radial direction. While densification increased the surface adhesion strength of the varnish layer in black pine, the value decreased in fir. Regarding the interaction between densification ratio, surface treatment, and wood type, the highest surface adhesion strength of the varnish layer was found in black pine + unsanded surface + 25% densification, and the lowest was in Uludag fir + unsanded surface + 50% densification. It can be stated that the densification process creates high adhesion values for the polyurethane varnish in the black pine wood type. The sanding process has an intensifying effect on these values, and the products that were obtained from the polyurethane varnished samples do not require sanding. Considering these situations can provide significant advantages in projects with wood materials subjected to the densification process.

Introduction: Leaving hospital care prematurely could threaten the healthy survival of and expose children to a risk of harmful alternatives. It is also a concern and a challenge to healthcare providers and the health system. A better understanding of itscharacteristic could help mitigate the impact on children. Objective: To determine the prevalence, types of, and reasons for premature hospital discharge amongst children. Methods: We carried out a threeyear retrospective review of case notes of children who were taken away from hospital admission by their parents/caregivers before they were due for discharge. Socio-demographic, clinical and discharge information were collected and data was entered into Microsoft® Excel® for Mac 2011 (Version 14.1.0), cleaned and analysed. Results were presented as percentages, statistical means and standard deviations, tables and charts. Results: There were 56 cases of premature discharge out of 2858 admissions, giving a prevalence of 2.0%. Under-five children constituted 65.4%, with a male: female ratio of 2.3:1. Thirty-one (55.3%) children were absconded with while 25 (44.7%) were taken away by caregivers against medical advice. The commonest diagnoses were protein-energy malnutritionand pneumonia and majority were from poor socio-economic family background. The commonest reasons for discharge AMA were unaffordable costs and perception of improvement of child’s medical condition. Conclusion: Socio-economic factors were significant determinants of utilization of in-patient hospital services for the children studied. There is a need for provision of affordable health care as well as efficient discharge policy to protect children from potential risksassociated with premature hospital discharge.

Toxoplasma gondii, a ubiquitous zoonotic parasite infecting warm-blooded animals, poses a significant health threat to workers with occupational animal exposure (WOEA) due to their frequent contact with potential reservoirs. Existing data on T. gondii seroprevalence in the WOEA exhibits substantial global variation. This systematic review and meta-analysis, adhering to PRISMA guidelines, aimed to quantify the global seroprevalence of T. gondii infection among WOEA over the past five decades (1972–2023). We identified 66 eligible studies through a comprehensive search strategy encompassing English publications, with a total sample size of 15,279. A random-effects model with the Freeman-Tukey transformation in STATA v16.0 accounted for the high heterogeneity observed. We estimated the pooled global seroprevalence of T. gondii infection in WOEA at 41% (95% CI: 36–47%). Subgroup analyses revealed significant variations by gender: males (63%) vs. females (37%) (p

Klebsiella pneumoniae is an opportunistic Gram-negative bacterium in the Enterobacteriaceae family associated with a wide range of diseases, such as pneumonia, bloodstream infections, meningitis and urinary tract infections. Infections caused by drug-resistant strains of Klebsiella pneumoniae pose a significant threat to the effectiveness of conventional antibiotics. Hence, this has led to the need to explore alternative antimicrobial therapies, especially natural products derived from plant sources. This study assessed the phytochemical composition and antibacterial properties and performed a molecular docking analysis of Henna leaves (Lawsonia inermis L.) extracts on strains of Klebsiella pneumoniae. Crude ethanol and methanol extracts of L. inermis L. were prepared at different concentrations (25, 50, 75 and 100 mg/mL) and tested on extended spectrum beta-lactamases (ESBLs)-producing strains of Klebsiella pneumoniae. Phytocompounds were identified using gas chromatography–mass spectrometry (GC-MS) and further subjected to virtual ligands screening with DataWarrior (v05.02.01) and a molecular docking analysis using AutoDock4.2 (v4.2.6). The active compounds of L. inermis L. were determined by the docking analysis, including phytochemical, physicochemical, pharmacokinetics and docking score. The GC-MS analysis identified 27 phytoconstituents, including ethyl acetate, sclareol, 2-[1,2-dihydroxyethyl]-9-[β-d-ribofuranosyl] hypoxanthine, α-bisabolol and 2-Isopropyl-5-methylcyclohexyl 3-(1-(4-chlorophenyl)-3-oxobutyl)-coumarin-4-yl carbonate. The 27 compounds were then screened for their physicochemical and pharmacokinetic properties. The results revealed that the methanol extracts at 100 mg/mL showed significantly higher (p < 0.05) zones of inhibition (13.7 ± 1.2 mm), while the ethanol extracts at 50 mg/mL were significantly lower (6.3 ± 0.6 mm) compared to all the other treatments. The docking analysis revealed that out of the 27 compounds identified, only twelve (12) compounds have a drug-likeness activity. The 12 compounds were further subjected to docking analysis to determine the binding energies with the CTX-M protein of Klebsiella pneumoniae. Only one compound [CID_440869; (2-[1,2-dihydroxyethyl]-9-[β-d-ribofuranosyl] hypoxanthine)] had the best binding energy of −9.76 kcal/mol; hence, it can be considered a potentially suitable treatment for infections caused by ESBLs-producing strains of Klebsiella pneumoniae. This study has demonstrated that L. inermis L. extracts have antibacterial effects. Further research could explore the potential antimicrobial applications of L. inermis L. extracts to many bacterial strains.

Background: Antiretroviral therapy (ART) has transformed HIV management, but concerns regarding liver toxicity persist, particularly with the use of reverse transcriptase inhibitors (RTIs) and integrase strand transfer inhibitors (INSTIs). This study aims to assess the impact of tenofovir/lamivudine/dolutegravir (TLD) therapy on liver function in HIV-positive individuals at a military hospital in southern Nigeria. Methods: We conducted a cross-sectional study involving 170 participants: 120 HIV-positive individuals on TLD and 50 HIV-negative controls, matched for age, sex, socioeconomic status, and ethnicity. Data were collected through questionnaires and blood sampling. Plasma levels of liver function markers, including alanine aminotransferase (ALT), aspartate aminotransferase (AST), glutathione S-transferases (GSTs), total protein (TP), and albumin (Alb), were analyzed using relevant biochemical methods. We conducted a statistical analysis using SPSS version 23, with significance set at p < 0.05. Results: Significant differences were observed in AST, TP, Alb, and GST levels between HIV-positive individuals on TLD and HIV-negative controls. HIV-positive subjects exhibited lower AST and Alb levels but higher TP and GST levels. Further analysis revealed correlations between age, gender, and liver enzymes, highlighting the complex interplay between HIV, liver function, and treatment outcomes. Conclusion: The results suggested that decreased AST levels may indicate a protective effect of TLD on liver integrity, while ALT activity showed minimal impact. Changes in TP, Alb, and GST levels emphasize the importance of monitoring hepatic function and detoxification pathways in HIV-positive individuals on TLD therapy.

In this brief paper 34 earrings are presented, all of which are curated in the Archaeological Museum of İznik in south-western Marmara region of Turkey. They are significant, as very few items of jewellery from Bithynia have been published.

Abstract Background The decision-to-delivery interval (DDI) for a caesarean section is among the factors that reflect the quality of care a pregnant woman receives and the impact on maternal and foetal outcomes and should not exceed 30 min especially for Category 1 National Institute for Health and Care Excellence (NICE) guidelines. Herein, we evaluated the effect of decision-to-delivery interval on the maternal and perinatal outcomes among emergency caesarean deliveries at a secondary health facility in north-central Nigeria. Methods We conducted a four-year retrospective descriptive analysis of all emergency caesarean sections at a secondary health facility in north-central Nigeria. We included pregnant mothers who had emergency caesarean delivery at the study site from February 10, 2017, to February 9, 2021. Results Out of 582 who underwent an emergency caesarean section, 550 (94.5%) had a delayed decision-to-delivery interval. The factors associated with delayed decision-to-delivery interval included educational levels (both parents), maternal occupation, and booking status. The delayed decision-to-delivery interval was associated with an increase in perinatal deaths with an odds ratio (OR) of 6.9 (95% CI, 3.166 to 15.040), and increased odds of Special Care Baby Unit (SCBU) admissions (OR 9.8, 95% CI 2.417 to 39.333). Among the maternal outcomes, delayed decision-to-delivery interval was associated with increased odds of sepsis (OR 4.2, 95% CI 1.960 to 8.933), hypotension (OR 3.8, 95% 1.626 TO 9.035), and cardiac arrest (OR 19.5, 95% CI 4.634 to 82.059). Conclusion This study shows a very low optimum DDI, which was associated with educational levels, maternal occupation, and booking status. The delayed DDI increased the odds of perinatal deaths, SCBU admission, and maternal-related complications.

لقد نزل القرآن الكريم في فترة ازدهرت فيها الفنون الأدبية. لقد ترك القرآنُ مخاطبِيه عاجزين ليس فقط من حيث أساليب البلاغية، بل من حيث محتواه أيضاً. كما يتضمن محتواه نقل الحقائق العلمية التي تم اكتشافها بعد قرون في العملية التاريخية، ومع تطور العلم عبر التاريخ أصبح من الواضح مدى تطابق المعلومات التي يقدمها القرآن الكريم مع الواقع العلمي .أظهرت التطورات الحديثة أن القرآن، خاصةً بإعجازه، يظل معجزة تتجدد في كل العصور، وليس مقتصراً على عصر النبوة، بل يمتد تأثيره إلى يوم القيامة. القرآن الكريم يحتوي على العديد من الأمثلة على الإعجاز العلمي، مثل ذكر نظام المجموعة الشمسية وخلق الإنسان من نطفة، ووصف مراحل نموه الجنيني، وكل ذلك تم اكتشافه بواسطة العلم الحديث. يتفق المسلمون على أن القرآن الكريم يمثل معجزة في أسلوبه اللغوي وفي بلاغته. سوف يتضح لنا في مقالتنا أن الإعجاز العلمي والبلاغي في القرآن حقيقة واضحة. توصلت الدراسة إلى عدة نتائج، أهمها: يقدم القرآن الكريم دلائل علمية تم تأكيدها من خلال تطور الأبحاث العلمية، مما يثبت أن القرآن الكريم كتاب الله تعالى، وأن محمداً صلى الله عليه وسلم هو رسول الله. يتضمن القرآن الكريم العديد من المعلومات العلمية الدقيقة التي لم تكن معروفة للبشر في عصر نزوله، ويتميز ببلاغة رائعة، لا يمكن أن تكون من تأليف بشري على الإطلاق.

Abstract Introduction Secondary peritonitis is the second leading cause of sepsis worldwide. Drug resistance to peritoneal cavity bacterial infection remains a public health threat, especially in resource-limited settings in Africa, including Uganda. This study aimed to determine the antibacterial susceptibility patterns and factors associated with secondary peritonitis among patients with acute abdomen who underwent surgery at a Regional Referral Hospital in Uganda. Methods This was a cross-sectional study conducted at Hoima Regional Referral Hospital (HRRH) that enrolled 126 patients with acute abdomen. Clinical samples were aseptically collected at laparotomy from patients with secondary peritonitis for culture and sensitivity using standard Microbiological methods. Binary logistic regression was used to identify factors associated with secondary peritonitis among patients with acute abdomen. Results The majority of the patients were males (61.9%) with a mean age of 37.9(SD ± 21.8). Secondary peritonitis was found in 57(45.2%) of the patients. Gram-negative bacteria were the most commonly isolated organisms with Escherichia coli (35.8%) and Klebsiella spp (17.0%) predominating. Imipenem 88.8%(8/9), Amikacin 88.8%(8/9), Ciprofloxacin 44.4%(4/9) and Gentamicin 44.4%(4/9) demonstrated sensitivity to the different isolated organisms at varying degrees. Being a male (AOR = 3.658; 95% CI = 1.570–8.519, p = 0.003) and presenting 3 days after onset of symptoms (AOR = 2.957; 95% CI = 1.232–7.099, p = 0.015) were independently associated with secondary peritonitis. Conclusion Imipenem, Amikacin, Ciprofloxacin, and Gentamicin should be considered for empirical therapy in cases of secondary peritonitis. Patients, more especially males with abdominal pain should be encouraged to present early to the hospital to minimize progression to secondary peritonitis.

Dextrocardia with situs inversus are rare congenital anomalies which can be asymptomatic and compatible with normal life. They are characterized by mirror images of all intra-thoracic and intra-abdominal viscera. Our aim is to report an incidental finding of dextrocardia with situs inversus in a neonate with neonatal sepsis. A day-old male term neonate presented with features of infection. Physical examination revealed cardiac apex on the 4th right intercostal space, along the mid-clavicular line. Chest radiograph and abdominal ultrasound confirmed the diagnosis of dextrocardia with situs inversus. Bilateral cervical ribs were also seen on chest radiograph. He was managed with antibiotics and discharged. Newborn babies should have a thorough physical examination after delivery before discharge to enable early diagnosis of congenital anomalies for appropriate referral.

Abstract Machine learning, a subset of artificial intelligence, has experienced rapid advancements and applications across various domains. In education, its integration holds great potential to revolutionize teaching, learning, and educational outcomes. Despite the growing interest, there needs to be more comprehensive bibliometric analyses that track the trajectory of machine learning’s integration into educational research. This study addresses this gap by providing a nuanced perspective derived from bibliometric insights. Using a dataset from 1986 to 2022, consisting of 449 documents from 145 sources retrieved from the Web of Science (WoS), the research employs network analysis to unveil collaborative clusters and identify influential authors. A temporal analysis of annual research output sheds light on evolving trends, while a thematic content analysis explores prevalent research themes through keyword frequency. The findings reveal that co-authorship network analysis exposes distinct clusters and influential figures shaping the landscape of machine learning in educational research. Scientific production over time reveals a significant surge in research output, indicating the field’s maturation. The co-occurrence analysis emphasizes a collective focus on student-centric outcomes and technology integration, with terms like “online” and “analytics” prevailing. This study provides a nuanced understanding of the collaborative and thematic fabric characterizing machine learning in educational research. The implications derived from the findings guide strategic collaborations, emphasizing the importance of cross-disciplinary engagement. Recommendations include investing in technological infrastructure and prioritizing student-centric research. The study contributes foundational insights to inform future endeavors in this ever-evolving field.

Assessment for Learning (AfL) plays a crucial role in the effective teaching and learning of Geography, offering educators a means to enhance student achievement. Through ongoing evaluations involving verbal and written exercises, AfL not only readies students for summative Assessment of Learning (AoL) but also supports them in grasping complex Geography concepts, features, and processes, as evidenced by examination performance. Over the last five years, as indicated by the Examinations Council of Lesotho, persistent challenges have emerged in this regard, potentially stemming from inadequacies in assessment strategies. This study delves into the perceptions of Geography teachers concerning Assessment for Learning. Employing a qualitative approach, the research utilizes non-participatory observations and in-depth interviews to collect data. The study is grounded in Gregory's Theory of Perception and Keeping Learning on Track Theory of Action, offering theoretical frameworks for analysis. The findings reveal that teachers face obstacles when implementing Assessment for Learning, including time constraints and issues related to classroom overcrowding. Notably, a significant insight is the lack of both Assessment knowledge and Pedagogical Content Knowledge among teachers. As a resolution, it is recommended that comprehensive assessment training be provided for both pre-service and in-service teachers, addressing these identified gaps.

Abstract In the rapidly evolving landscape of education, Artificial Intelligence (AI) has emerged as a transformative tool with the potential to revolutionize teaching and learning processes. However, the successful integration of AI in education depends on the trust and acceptance of teachers. This study addresses a significant gap in research by investigating the trust dynamics of 677 in-service Science, Technology, Engineering, Arts, and Mathematics (STEAM) teachers in Nigeria towards AI-based educational technologies. Employing structural equation modelling for data analysis, our findings reveal that anxiety, preferred methods to increase trust, and perceived benefits significantly influence teachers' trust in AI-based edtech. Notably, the lack of human characteristics in AI does not impact trust among STEAM teachers. Additionally, our study reports a significant gender moderation effect on STEAM teachers' trust in AI. These insights are valuable for educational policymakers and stakeholders aiming to create an inclusive, AI-enriched instructional environment. The results underscore the importance of continuous professional development programs for STEAM teachers, emphasizing hands-on experiences to build and sustain confidence in integrating AI tools effectively, thus fostering trust in the transformative potentials of AI in STEAM education.

Abstract Autologous administration of attenuated Theileria parva-infected cells induces immunity to T. parva in cattle. The mechanism of attenuation, however, is largely unknown. Here, we used RNA sequencing of pathogenic and attenuated T. parva-infected T-cells to elucidate the transcriptional changes underpinning attenuation. We observed differential expression of several host genes, including TRAIL, PD-1, TGF-β and granzymes that are known to regulate inflammation and proliferation of infected cells. Importantly, many genes linked with the attenuation of the related T. annulata-infected cells were not dysregulated in this study. Furthermore, known T. parva antigens were not dysregulated in attenuated relative to pathogenic cells, indicating that attenuation is not due to enhanced immunogenicity. Overall this study suggests that attenuation is driven by a decrease in proliferation and restoration of the inflammatory profile of T. parva-infected cells. Additionally, it provides a foundation for future mechanistic studies of the attenuation phenotype in Theileria-infected cells.

The COVID-19 pandemic has had a significant impact on high-stakes testing, including the National Benchmark Tests in South Africa. Current linear testing formats have been criticized for their limitations, leading to a shift towards Computerized Adaptive Testing [CAT]. Assessments with CAT are more precise and take less time. Evaluation of CAT programs requires simulation studies. To assess the feasibility of implementing CAT in NBTs, SimulCAT, a simulation tool, was utilized. The SimulCAT simulation involved creating 10,000 examinees with a normal distribution characterized by a mean of 0 and a standard deviation of 1. A pool of 500 test items was employed, and specific parameters were established for the item selection algorithm, CAT administration rules, item exposure control, and termination criteria. The termination criteria required a standard error of less than 0.35 to ensure accurate abilities estimation. The findings from the simulation study demonstrated that fixed-length tests provided higher testing precision without any systematic error, as indicated by measurement statistics like CBIAS, CMAE, and CRMSE. However, fixed-length tests exhibited a higher item exposure rate, which could be mitigated by selecting items with fewer dependencies on specific item parameters (a-parameters). On the other hand, variable-length tests demonstrated increased redundancy. Based on these results, CAT is recommended as an alternative approach for conducting NBTs due to its capability to accurately measure individual abilities and reduce the testing duration. For high-stakes assessments like the NBTs, fixed-length tests are preferred as they offer superior testing precision while minimizing item exposure rates.

Bu çalışma, asit yağmurlarının açık hava şartlarındaki ağaç malzemelerde kullanılan verniklerin bazı renk değerine etkilerini belirlemek amacıyla yapılmıştır. Bu maksatla açık hava şartlarında sık kullanılan sapsız meşe (Qııercııs petrae Liebl) ve sarıçamdan (Pinus sylevestrıs Lipsky.) hazırlanan örnekler, ASTM-D-30232’ e göre sentetik ve su bazlı vernik ile verniklendikten sonra yüzeyler farklı konsantrasyon ve miktarlarda sülfürik ve nitrik asit çözeltisi etkilerine maruz bırakılmıştır. Örneklerin renk değişimi ASTM-D 2244’e göre belirlenmiştir. Sonuç olarak, kırmızı renk değeri, tekli etkileşimde, en yüksek meşe (10,68), sentetik vernik (11,99), %5N (14,01) ve 120 g/m2 (10,36), en düşük sarıçam (8,935), su bazlı vernik (7,63), % 3S’de (9,293), 150 ve 180 g/m2 de yaklaşık eşit, çoklu etkileşimde en yüksek M+Sn+I+%5N’de (17,49), en düşük Sç+Sb+I+%3S’de (6,408) çıkmıştır. Sarı renk değeri tekli etkileşimde en yüksek sarıçam (56,61), sentetik vernik (35,16), %5 Nitrik asit (34,41) ve 120 g/m2 (30,13)’de, en düşük meşede (51,97), su bazlı vernik (24,02), %5S (29,18) ve 150 ve 180 g/m2, çoklu etkileşimde en yüksek Sç+Sn+I+%3N (46,08)’de, en düşük M+Sb+III+%5S (22,34)’de ölçülmüştür. Buna göre, asit yağmurlarının yoğun olduğu bölgelerde dış mekânlarda kullanılacak ahşap malzemelerde bu çalışmada bulunan değerlerin renk bakımından dikkate alınması, malzemenin uzun yıllar kullanımı açısından yarar sağlayabilir. Özellikle renk değişiminin az olması beklenen alanlarda su bazlı vernik ve sarıçam kullanılması önerilebilir. Diğer faktörlerden elde edilen sonuçların uygulamalarda dikkate alınması avantaj sağlayabilir.

Abstract The increasing prevalence of Fourth Industrial Revolution (4IR) technologies has led to a surge in the popularity of AI application tools, particularly chatbots, in various fields, including education. This research explores the factors influencing undergraduate students' inclination to embrace AI application tools, specifically chatbots, for educational purposes. Using an expanded diffusion theory of innovation framework, the study investigates the relationship between relative advantages, compatibility, trialability, perceived trust, perceived usefulness, perceived ease of use, and behavioral intention. Using a 7-point scale, a questionnaire was given to 842 undergraduate students to collect data. The analysis, conducted using SmartPLS 4.0.9.2 software with a covariance-based structural equation model, produced significant findings. The study confirms hypotheses related to the relative advantages, compatibility, trialability, perceived usefulness, and perceived trust associated with chatbots. Notably, students who perceive the benefits of chatbots show a strong intention to use them for academic purposes. The perception of compatibility between students and chatbots positively influences adoption intention, highlighting the importance of compatibility. Additionally, students who have the opportunity to trial chatbots are more likely to use them, emphasizing the significance of trialability. Interestingly, the study did not establish direct relationships between perceived usefulness, perceived ease of use, and behavioral intention. This suggests the presence of other influential factors or dynamics in the adoption of chatbots for educational purposes. These findings offer practical insights for students and contribute to the theoretical understanding of the diffusion theory of innovation. Future research can further explore these insights to unravel the complexities of chatbot adoption and facilitate the broader adoption of AI tools in educational settings.

Potato has been determined as the food of future on global extent. Within this study factors affecting potato consumption were evaluated in the scope of domestic market. The main reasons behind the choice of potato consumption were its reference as future’s product as well as today’s, and the possibility to consume potato both as fresh and processed forms. In order to underline the detailed reasons, 3.072 consumers were surveyed between August and September 2020. Due to the findings, factors affecting potato consumption in the domestic market were detected as consumer awareness, consumer value and consumer convenience. These factors reflect the health awareness developed among the society within the pandemic process. This finding put forward that there is a need for public promotion of potato with reference to its food content and positive health impact. On the other hand, due to partial and complete shut-down implementations processed potato consumption has reduced and home-made fresh potato consumption has risen. This has been acknowledged as a social progress with respect to direction to healthy consumption. A declination in potato consumption was detected among two-thirds of the households due to rising prices. These findings indicated factors that affect purchases or consumption of a specific product or services under normal and extraordinary conditions need to be known. This is important for sustainability of social health and quantitative and qualitative estimation and management of both national and international market demand.

AbstractThis study addresses the challenge of teaching genetics effectively to high school students, a topic known to be particularly challenging. Leveraging the growing importance of artificial intelligence (AI) in education, the research explores the perspectives, attitudes, and behavioral intentions of pre-service teachers regarding the integration of AI-based applications in high school genetics education. As these pre-service teachers, commonly denoted as digital natives, are expected to seamlessly integrate technology into their future classrooms in our technology-dependent society, understanding their viewpoints is crucial. The research involved 90 teacher candidates specializing in biology from Nigerian higher education institutions. Employing the Theory of Planned Behavior, survey responses were analyzed using structural equation modeling and independent sample t-test methods. The results indicate that perceived usefulness and subjective norms are significant predictors of AI use, with subjective norms strongly influencing pre-service teachers’ behavioral intentions. Notably, perceived behavioral control does not significantly predict intentions, paralleling the observation that perceive usefulness does not guarantee AI adoption. Gender differentially affects subjective norms, particularly among female pre-service teachers, while no significant gender differences are observed in other variables, suggesting comparable attitudes. The study underscores the pivotal role of attitudes and social norms in shaping pre-service teachers’ decisions regarding AI technology integration. Detailed discussions on implications, limitations, and potential future research directions are also discussed.

AbstractThis paper reviews the application of artificial intelligence (AI)-based models in modeling vehicular road traffic noise. A computerized search method was used to conduct the literature search. Fifty published articles from 2007 to 2023 were reviewed regarding observation time, input data, countries where studies were performed, and modeling techniques. Sixty-three percent of the studies used an observation period of 60 min, and 29% used 15 min. All the reviewed papers considered traffic flow as the major input parameter, followed by average speed, with 95% of the researchers using it as an input parameter. It was found that using AI-based models for traffic noise prediction was popular in countries with no established empirical models. The primary input parameters for the AI-based models are traffic volume and speed. Traffic volume is used either as total traffic volume or classified into sub-categories, and each category is used as an independent input parameter. Although AI-based models have demonstrated reliable performance regarding prediction error and goodness of fit, the accuracy of the AI-based models’ performance should be compared with the results of the empirical models in countries with established models, such as the UK (CoRTN) and the USA (FHWA).

Abstract The acceptance of nanoparticle technology in the quest for cancer treatment is due to its many potentials and possibilities of filling in the gaps in the limitations of the current treatment modalities. Insights into the possibilities of getting even more from this technology, as well as the synergistic properties of photothermal therapy (PTT) and photodynamic therapy (PDT)—the use of reactive oxygen species (ROS)—can also be exploited in the ablation of prostate cancer tumors. Therefore, the combination of gold and selenium photoactive nanoparticles as platforms for drug delivery via PTT/PDT in prostate cancer therapy, with a specific emphasis on the 'micro-carrier' based approach, was discussed and explored in this review under relevant subtopics ranging from understanding the complex chemistry and biology of the pharmacologically active Se/Au-containing agents to giving a thorough knowledge of these therapeutic agents' potential as a targeted and successful treatment strategy for prostate cancer by investigating the complex mechanisms behind their delivery, activation, and synergistic effects. Furthermore, this article presents a comprehensive overview of the current research environment, problems encountered, and future perspectives in the continuous war against prostate cancer.

Myocarditis is a cardiovascular disease characterised by inflammation of the heart muscle which can lead to heart failure. There is heterogeneity in the mode of presentation, underlying aetiologies, and clinical outcome with impact on a wide range of age groups which lead to diagnostic challenges. Cardiovascular magnetic resonance (CMR) is the preferred imaging modality in the diagnostic work-up of those with acute myocarditis. There is a need for systematic analytical approaches to improve diagnosis. Artificial intelligence (AI) and machine learning (ML) are increasingly used in CMR and has been shown to match human diagnostic performance in multiple disease categories. In this review article, we will describe the role of CMR in the diagnosis of acute myocarditis followed by a literature review on the applications of AI and ML to diagnose acute myocarditis. Only a few papers were identified with limitations in cases and control size and a lack of detail regarding cohort characteristics in addition to the absence of relevant cardiovascular disease controls. Furthermore, often CMR datasets did not include contemporary tissue characterisation parameters such as T1 and T2 mapping techniques, which are central to the diagnosis of acute myocarditis. Future work may include the use of explainability tools to enhance our confidence and understanding of the machine learning models with large, better characterised cohorts and clinical context improving the diagnosis of acute myocarditis.

Empirical evidence proves that agricultural research and development expenditure, and researchers attract high returns though the investments have long gestation periods. Nonetheless, Sub-Saharan Africa invests meagerly in agricultural research and development, and researchers. This study explores the impacts of agricultural research and development expenditures, and researchers on food security in the region and across the sub-regions. The study applies Bootstrapped linear squared dummy variable due to its capacity to handle heterogeneity and missing observations and two-step system generalized method of moments techniques to analyze the data on 24 sub-Saharan African countries over the period 2000–2016. Data on measures of food security, food production per capita, and food price index are obtained from Food and Agriculture Organization stat, data on population growth is sourced from World Development Indicators, and data on investments in agricultural innovations are extracted from International Food Policy Research Institute. Our findings show that investments in agricultural innovation substantially increase food security through food productivity growth. The full-time equivalent of agricultural researchers’ hours is more impactful on food security than agricultural research and development spending. The findings also reveal that the investments are more effective in enhancing food security in Eastern, Southern, and Western African sub-regions while they instead exacerbate the problem of food insecurity in Central Africa. The policy implications are that adequate resources should be channeled into proper agricultural research and development to introduce new crop varieties or significantly improved crops, etc. Moreover, there should be coordination between large and small countries in investments in order for the countries to benefit from the economies of scale.

Este trabajo presenta un enfoque para resolver el Problema del Viajante Múltiple (mTSP) mediante la integración de algoritmos metaheurísticos (MHs) con técnicas de aprendizaje automático (ML). En particular, se desarrolló el algoritmo de Optimización Discreta de Halcones de Harris (DHHO) para manejar la naturaleza discreta del mTSP, ya que el algoritmo original de Optimización de Halcones de Harris (HHO) fue diseñado para problemas continuos. El algoritmo DHHO, mejorado con mecanismos de aprendizaje basados en SARSA para la inicialización de soluciones y ajuste de parámetros, mejora significativamente la eficiencia de las soluciones del mTSP. Al aprovechar la adaptabilidad del ML dentro del robusto marco de MH, este estudio ofrece una nueva perspectiva sobre los problemas de optimización combinatoria, superando las mejores soluciones conocidas (BKS) en varias instancias del mTSP. Los resultados se probaron utilizando instancias de referencia de TSPLIB, incluyendo Att48, Berlin52, Bier127, Pr76 y Rat99, para dos, tres y cuatro vendedores, logrando resultados óptimos en 12 de las 15 instancias. El rendimiento del DHHO se validó por la calidad de las soluciones y la consistencia a lo largo de múltiples ejecuciones, obteniendo resultados óptimos en 5 de 5 instancias para dos vendedores, 3 de 5 para tres vendedores y 4 de 5 para cuatro vendedores. La validación estadística mediante la prueba de rango con signo de Wilcoxon confirmó la significancia de estas mejoras (p < 0.05). Este trabajo destaca el impacto de integrar MHs y ML, contribuyendo de manera sustancial a la literatura actual.

IntroductionSub-Saharan Africa (SSA) is plagued by myriads of diseases, mostly infectious; but cancer disease burden is rising among non-communicable diseases. Nigeria has a high burden of cancer, however its remote underserved culturally-conserved populations have been understudied, a gap this study sought to fill.MethodsThis was a cross-sectional multi-institutional descriptive study of histologically diagnosed cancers over a four-year period (January 2019-December 2022) archived in the Departments of Pathology and Cancer Registries of six tertiary hospitals in the northeast of Nigeria. Data obtained included age at diagnosis, gender, tumor site and available cancer care infrastructure. Population data of the study region and its demographics was obtained from the National Population Commission and used to calculate incident rates for the population studied.ResultsA total of 4,681 incident cancer cases from 2,770 females and 1,911 males were identified. The median age at diagnosis for females was 45 years (range 1–95yrs), and 56 years (range 1–99yrs) for males. Observed age-specific incidence rates (ASR) increased steadily for both genders reaching peaks in the age group 80 years and above with the highest ASR seen among males (321/100,000 persons) compared to females (215.5/100,000 persons). Breast, cervical, prostatic, colorectal and skin cancers were the five most common incident cancers. In females, breast, cervical, skin, ovarian and colorectal cancers were the top five malignancies; while prostate, haematolymphoid, skin, colorectal and urinary bladder cancers predominated in men.ConclusionRemote SSA communities are witnessing rising cancer disease burden. Proactive control programs inclusive of advocacy, vaccination, screening, and improved diagnostics are needed.

Predicting concrete’s compressive strength (CS) is a crucial and challenging task in civil engineering as it directly impacts the longevity and structural integrity of infrastructure initiatives. Precise estimation of the water–cement ratio (W/C) is essential for guaranteeing the structural integrity of structures since it is a critical parameter that greatly affects concrete’s CS. This study carries out an extensive investigation of the prediction of the W/C of concrete, utilizing the enormous potential of machine learning, including the backpropagation neural network (BPNN), bilayer neural network, boosted tree algorithm, bagged tree algorithm (BGTA), and support vector regression (SVR), using 108 datasets. We integrate artificial intelligence models with traditional engineering techniques to develop a reliable, precise, and efficient forecasting system. The study input includes curing days (D), fiber (F), cement (C), fine and coarse aggregate (FA and CA), density (Den), CS, water (W), and W/C as the output variables. The result shows that, in comparison to the other models, BGTA-M3 achieved the best performance evaluation criterion. In the calibration and verification phases, NSE, PCC, R, and WI = 1 and MAPE = 0.00, respectively. BPNN-M3 had an MAPE of 0.0004 in the verification phase. The study uses SHapley Additive exPlanations (SHAP), an explainable artificial intelligence (AI) technique, to improve decision-making in complex systems, with cement “C” significantly contributing to higher predictions in SVR-M2. Future studies should expand the dataset to include information from diverse geographic areas, environmental conditions, and concrete mixes to enhance the applicability and dependability of the models.

Research has confirmed that people’s attitudes towards starting their own business may be influenced by their education, age, gender and prior entrepreneurial experiences. To support the employability and economic success of tourism graduates, this study, conducted in the South African context, aimed to explore the predictors of tourism students’ interest and motivation towards starting their tourism-related businesses after graduation. A survey questionnaire was employed to gather information from 154 randomly selected tourism students at a comprehensive university in South Africa. The first phase of data analyses dealt with the assessment of the measurement model, while the second phase tested the structural model using the partial least square-structural equation modelling (PLS-SEM) method implemented on SmartPLS software. The results indicate that certain student profile characteristics (such as age, gender, completing entrepreneurship module, self-assurance and satisfaction level) had significant effects on entrepreneurial desirability and feasibility (DF), entrepreneurial attributes (EA) and entrepreneurship education (EE). Further, the results reveal that EE did not differ by age, EA did not vary by gender and DF was not influenced by tourism students’ self-assurance (SA). The study suggests that the institution under investigation uses appropriate experiential pedagogical approaches to provide tourism students with the ‘know-how’ and other necessary ‘hands-on skills’ to improve their capacity to launch new businesses. Contribution: This article is important for higher education in general, particularly in sub-Saharan Africa, because it not only contributes to the literature on entrepreneurship but equally helps higher education institutions to integrate tourism entrepreneurship modules into their curricula.

In the context of global integration and increasing reliance on Artificial Intelligence (AI) in education, evaluating the AI literacy of pre-service teachers is crucial. As future architects of educational systems, pre-service teachers must not only possess pedagogical expertise but also a strong foundation in AI literacy. This quantitative study examines AI literacy among 529 pre-service teachers in a Nigerian university, utilizing structural equation modeling (SEM) for comprehensive analysis. The research explores various dimensions of AI literacy, revealing that a profound understanding of AI significantly predicts positive outcomes in AI use, detection, ethics, creation, and problem-solving. However, no correlation exists between AI knowledge and emotion regulation or the assumption that active AI use enhances AI detection capabilities. The study identifies a trade-off between AI application and creation, emphasizing the ethical considerations intertwined with emotional and persuasive facets of AI use. It also supports the link between AI creation and problem-solving, emphasizing the foundational role of AI knowledge in shaping diverse aspects of AI literacy among pre-service teachers. The findings offer valuable insights for educators, administrators, policymakers, and researchers aiming to enhance AI literacy in pre-service teacher education programs.

This study investigates the acceptance and utilization of artificial intelligence (AI) among in-service teachers in Lesotho, focusing on the mediating role of school support and resources (SSR). In Lesotho's educational landscape, which is characterized by a growing interest in technology integration, this study fills an essential gap in the existing literature by exploring in-service teachers' perspectives on AI adoption and the mediating influence of SSR. Using the Unified Theory of Acceptance and Use of Technology (UTAUT) as the theoretical framework, the study adopts a cross-sectional design, collecting data from a sample of 315 in-service teachers through online surveys. The data was analyzed using maximum likelihood estimation. The results reveal a substantial positive relationship between perceived usefulness, perceived ease of use, and a positive attitude towards AI, with SSR playing a pivotal role as a complementary mediator in these connections. However, the study identifies a non-significant relationship between technical proficiency and behavioral intention, suggesting a need for further investigation into the technical skills essential for effective AI integration. The results highlight the critical role of SSR in shaping in-service teachers' intentions to use AI in their teaching practices. As a result, the study recommends tailored continuous professional development programs and collaborative learning communities to enhance teachers' skills. Additionally, it emphasizes the importance of advocating for policies that support AI integration in education and underscores the ethical considerations related to AI use. We discuss the implications of our results concerning integrating AI into teachers' teaching practices in schools and outline future directions.

The cement industry contributes about 7–8 % of the global CO2 emissions. Therefore, to reduce the embodied CO2 emission from cement, its usage in concrete needs to be reduced. Agricultural waste from date palm trees is one of the major waste materials in middle east countries like Saudi Arabia. In this study, the date palm waste was processed to date palm ash (DPA) and used as supplementary cementitious material (SCM) in concrete to reduce the embodied CO2 emissions. Due to the weak pozzolanic reaction of the DPA, it was blended with eggshell powder (ESP) owing to its high calcium oxide content. Cement was replaced with DPA at 0 %, 10 %, 20 %, 30 % and 40 % by weight. ESP was added in proportions of 0 %, 1 %, 2 %, 3 % and 4 % by mass of binder. Response surface methodology (RSM) was used to carryout experimental design and sustainability analysis. The findings showed that using either DPA as SCM or blends of DPA and ESP as binder materials significantly reduced embodied CO2 emissions and cost, enhanced eco-strength efficiency of the concrete. The mathematical models developed for predicting the embodied CO2 and cost of the concrete were higher significant with very good accuracy. From the optimization results, an eco-sustainable concrete in terms of lower cost and embodied CO2 was achieved by blending 21.3 % DPA as SCM and 2.3 % ESP by mass of binder in the concrete.DPA can be considered an environmentally sustainable and cost-effective SCM, and its performance was significantly enhanced when blended with ESP.

There is a need for teachers who are prepared to teach Artificial Intelligence (AI) across the K-12 learning contexts. Owing to the dearth of teacher education programmes on AI, it is helpful to explore factors to be considered in designing an effective AI programme for future teachers. We posit that understanding how to encourage pre-service teachers to learn AI is thus critical for practitioners and policymakers while designing effective instructional AI teacher education programmes. This exploratory study examined the perceptions of pre-service teachers and their behavioral intention to learn AI, by identifying factors that might affect learning and promoting AI in teacher preparation programmes. This study proposed a research model supported by the theory of planned behavior and expanded with other constructs. The factors that were examined include basic knowledge of AI, subjective norm, AI for social good, perceived self-efficacy, self-transcendent goals, personal relevance, AI anxiety, behavioral intention to learn AI, and actual learning of AI. Using a duly validated questionnaire, we surveyed 796 pre-service teachers in Nigerian Universities. Through structural equation modeling approach analyses, our proposed model explains about 79% of the variance in pre-service teachers' intention to learn AI. Basic knowledge and subjective norm were found to be the most important determinant in pre-service teachers’ intention to learn AI. All our hypotheses were supported except for self-efficacy and personal relevance, personal relevance and social good, and behavioral intention and actual learning behavior. The findings provide practitioners, researchers, and policymakers with valuable information to consider in designing effective AI teacher education programmes.

Background: The DNA mismatch repair (MMR) is the biological pathway that plays a key role in maintaining genomic stability during DNA replication and recombination. The value of MMR pathway is under investigation in pediatrics' solid tumors. Aims: In this research work, we investigated the proteins involved in the oncogenesis of pediatric solid neoplasms and detect these proteins in a representative cohort sample of Saudi pediatric cases under the bioinformatic networking technique. We also described the MLH1, BRAF, p53, proliferating cell nuclear antigen, and PMS2 along with MSH2-MSH6 antibodies to be a diagnostic immunohistochemistry (IHC) panel for identifying MMR mutations. This research will open the new doors for advanced research on proteins involved in the oncogenesis of pediatric solid neoplasms. The hypotheses were tested on a sample of solid malignancies and IHC results were reported. Material and Methods: The study was conducted in different institutions in Saudi Arabia. The inclusion criteria required enrolling biopsies of solid neoplasms or resected solid malignant neoplasms presented to the laboratories in the participating institutions of all pediatric patients (aging from 0 to 14 years). The specimens were examined microscopically utilizing Hematoxylin and Eosin stain as well as the utilization of MMR proteins immunohistochemistry (IHC), and PNCA. Results: The qualitative assessment showed that IHC diagnosis yielded positive results with ≥80% of positive cells (intact) for MMR proteins (MSH2, MSH6, PMS2, and MLH1). The PCNA protein was absent only in vaginal germ cell tumor and metastatic medulloblastoma. Conclusion: In our sample, we have found that there is an intact MMR proteins expression. Also, the IHC technique presents accuracy and ability as a diagnostic technique for identifying the different types of pediatric cancers. The MMR protein panel accompanied with PCNA panels holds additional value, as it helps reduce dependency solely on MMR protein expressions.

Abstract Background Traditional risk scores for recurrent atrial fibrillation (AF) following catheter ablation utilize readily available clinical and echocardiographic variables and yet have limited discriminatory capacity. Use of data from cardiac imaging and deep learning may help improve accuracy and prediction of recurrent AF after ablation. Methods We evaluated patients with symptomatic, drug‐refractory AF undergoing catheter ablation. All patients underwent pre‐ablation cardiac computed tomography (cCT). LAVi was computed using a deep‐learning algorithm. In a two‐step analysis, random survival forest (RSF) was used to generate prognostic models with variables of highest importance, followed by Cox proportional hazard regression analysis of the selected variables. Events of interest included early and late recurrence. Results Among 653 patients undergoing AF ablation, the most important factors associated with late recurrence by RSF analysis at 24 (+/−18) months follow‐up included LAVi and early recurrence. In total, 5 covariates were identified as independent predictors of late recurrence: LAVi (HR per mL/m2 1.01 [1.01–1.02]; p 66.7 mL/m2 and early recurrence had the highest risk of late recurrence risk compared with those with LAVi

Öz Amaç: Uzmanlık eğitimi almak isteyen diş hekimlerinin, Diş Hekimliği Uzmanlık Eğitimi Giriş Sınavı’na (DUS) girmeleri gerekmektedir. Çıkmış soruların konu dağılımları hakkında bilgi edinmek, sınava hazırlanan adaylar için faydalı olmaktadır. Literatür incelendiğinde bu konuda herhangi bir araştırmaya rastlanılmamıştır. Bu çalışma, son 10 yıldaki DUS Restoratif Diş Tedavisi sorularının retrospektif olarak incelenmesini amaçlamaktadır. Gereç ve Yöntemler: Çalışma için gerekli etik kurul izni alınmıştır. Çalışmaya, son 10 yılda sorulmuş olan 130 adet DUS Restoratif Diş Tedavisi sorusu dahil edilmiştir. Konu başlıkları Ölçme, Seçme ve Yerleştirme Merkezi’nin (ÖSYM) referans kitap olarak gösterdiği kaynaklar doğrultusunda hazırlanmıştır. Soruların konulara ve yıllara göre dağılımları incelenmiştir. Ayrıca, soruların dağılımları yüzde olarak hesaplanmıştır. Bulgular: Elde edilen veriler doğrultusunda; en fazla diş çürükleri (n:16) konusundan, en az ise dişlerin gelişim bozuklukları (n:2) ve restoratif diş hekimliğinde hasta muayenesi (n:2) konularından soru sorulduğu belirlenmiştir. Diş çürükleri konusunda en fazla soru (n:4) 2013 yılı ilkbahar döneminde sorulmuştur. Ayrıca bazı konulardan da hiç soru sorulmadığı tespit edilmiştir. Sonuç: Elde edilen sonuçlar, yıllara göre konu dağılımlarında düzensizliklerin olduğunu ortaya koymaktadır. Bazı konulardan en az iki sene de bir soru sorulduğu, bazı konulardan ise hiç soru sorulmadığı saptanmıştır. Çalışma sonuçlarının, sınava hazırlık sürecinde yararlı olacağını düşünmekteyiz. Anahtar Kelimeler: Diş hekimliğinde uzmanlık sınavı, Konu dağılımı, Restoratif diş tedavisi.

Background: It has been known for centuries that plants and plant-derived chemicals are useful in treating diseases, with Aloe vera being one of the biologically active plants. A significant role is played by the C-reactive protein (CRP) in many inflammatory conditions, while leukocytes play an integral role in the response of the immune system to infectious diseases. Objectives: This study explored the potential anti-inflammatory effects of Aloe vera methanolic extract on the total white blood cell (TWBC) count and CRP levels in Wistar rats received formalin. Methods: A total of 25 Wistar rats were divided into five groups (A to E), with group A serving as the control and the other groups receiving formalin to induce inflammation, followed by increasing doses of Aloe vera extract. The CRP level was measured using an enzyme-linked immunosorbent assay (ELISA) kit, and the TWBC count was determined using a Sysmex haematology autoanalyzer. Results: Research findings showed that 200 mg of Aloe vera methanolic extract effectively reduced the CRP level (0.056±0.0027) (P=0.04), while 600 mg of the extract significantly increased the TWBC count (13.920±4.757) (P=0.03). Conclusion: These findings suggest that Aloe vera extract may be an effective natural supplement for improving the immune system function and reducing inflammation in the body. However, further research is needed to fully understand the underlying mechanisms for these effects and to determine the optimal doses and potential side effects.

Çalışmamız kapsamında, eklemleri fırçasız doğru akım (DA) motorları kullanılarak sürülen ve hem dinamik hem de kinematik modelinde parametrik belirsizlikler içeren robot kolları için, eyleyici dinamikleri denetleyici tasarımına dahil edilerek uyarlamalı görev uzayı takip denetleyicisi tasarımı gerçekleştirilmiştir. Denetleyici tasarımının doğrudan görev uzayında gerçekleştirilmesi sayesinde pozisyon seviyesinde ters kinematiğin hesaplanmasına ihtiyaç duyulmamaktadır. Geliştirilen tam durum geri beslemeli ve ivme ölçümlerine ihtiyaç duymayan denetleyici yapısı için Lyapunov tabanlı kararlılık analizi gerçekleştirilmiştir. Kararlılık analizinin sonucuna göre robot kolunun hem dinamik hem de kinematik modelindeki parametrik belirsizliklere rağmen görev uzayı takip hatasının asimptotik kararlılığı ve denetleyici girişleri de dahil olmak üzere sistemde kullanılan tüm işaretlerin sınırlılığı garanti edilmiştir. Ek olarak önerilen yöntemin performansını ve uygulanabilirliğini göstermek amacıyla düzlemde çalışan, iki serbestlik dereceli ve eklemleri fırçasız DA motorları ile sürülen robot kolunun dinamik modeli kullanılarak benzetim çalışması gerçekleştirilmiştir.

Purpose – The literature about the dynamics of Muslims' awareness and perception of waqf has been generally scarce,especially in Nigeria. As renewed efforts are emerging to develop a new waqf regime in the country, this study examines this aspect in Gombe metropolis, Nigeria, with a view to identifying the key factors shaping people's perception and awareness towards waqf. Design/methodology/approach – To achieve the objective of this study, primary data were collected through a survey among 494 business owners in the Gombe metropolis. The data were then analysed using probit and Tobit regression models. Findings – The study found that altruistic behaviour, religiosity level, educational level and young age are among the factors that determine people's perception and awareness towards donating to waqf among business owners in Gombe. Altruism and young age embolden businesspersons to recognise the effectiveness of waqf institutions in solving socioeconomic challenges. Practical implications – The findings of this study imply that waqf has huge potential in the study area and that with well-structured, organized waqf education programmes within the business community using diverse avenues, a robust waqf sector can be developed. Originality/value – As far as the study area and the entire Nigerian Islamic economics and finance landscape is concerned, the study has explored a novel research area. Given the infant stage of empirical studies on waqf in Nigeria, there are virtually no previous attempts to examine the awareness and perception of businesspersons towards waqf; variables that are key to the development of an effective sector.

AbstractCamel brucellosis is a major public health concern in Sudan; however, there is no overall estimation of the prevalence of camel brucellosis in Sudan. Following the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines, this study aimed to perform a meta-analysis of 30 eligible studies published before December 31, 2022, with a total of 70059 dromedary camels, to estimate the pooled prevalence of camel brucellosis and its risk factors in Sudan. The random effect model was used for the final analysis due to the significantly high heterogeneity among the included studies, and the results showed that the overall pooled prevalence of camel brucellosis was 17%, with a confidence interval (CI) of 12%–21%. The prevalence was higher in males than females (54% vs. 46%) and in adults than youngling (77% vs. 23%). The prevalence also varied by region, with central and northern Sudan having the highest prevalence (24%), compared to other regions of Sudan. Moreover, the prevalence of camel brucellosis appeared to be decreasing over time. The current study concluded that camel brucellosis infection is still endemic in many areas of Sudan, with the disease being especially prevalent in central and northern Sudan. Thus, this study provides valuable information for the prevention and control of camel brucellosis in Sudan. However, the significant heterogeneity among the included studies should be taken into account when interpreting these results. Finally, to provide adequate information, research must be updated, and more research must be conducted in many regions of Sudan.

Mohamed Adam,1 Mustafa J Musa,2 Saleh M Al-Qahtani,3 Magbool Alelyani,1 Alamin Musa,1 Maisa Elzaki,4 Amel FH Alzain,4 Sarra Ali,5 Afaf Medani,1 Emadeldedin Mohamed Mukhtar,1 Awadia Gareeballah4 1Department of Radiological Sciences, College of Applied Medical Sciences, King Khalid University, Abha, Asir, Saudi Arabia; 2Department of Applied Radiologic Science, University of Jeddah, Kingdom of Saudi Arabia (KSA), Jeddah, Saudi Arabia; 3Department of Child Health, College of Medicine, King Khalid University, Abha, Asir, Saudi Arabia; 4Department of Diagnostic Radiology Technology, College of Applied Medical Sciences, Taibah University, Al-Madianah Al-Munawwarrah, Saudi Arabia; 5Department of Diagnostic Radiography Technology, College of Applied Medical Sciences, Jazan University, Jazan, Saudi ArabiaCorrespondence: Mohamed Adam, Department of Radiological Sciences, College of Applied Medical Sciences, King Khalid University, Abha, Asir, Saudi Arabia, Email o_maurie2006@yahoo.com; madam@kku.edu.saBackground: Abdominal organ sonography is a crucial part of the workup for treating sickle cell disease (SCD) patients.Objective: The main objective of this study was to evaluate the abdominal organs in SCD patients using ultrasonography.Methodology: A non-interventional descriptive cross-sectional study was carried out in Asir region Saudi Arabia from April 2019 to July 2020. The study was conducted in 78 patients with sickle cell disease (SCD). Data were gathered using a data collection sheet included demographic information, clinical information including medication types, and complications linked to SCD. Furthermore, the study evaluated abdominal ultrasound findings pertaining to the liver, gall bladder, spleen, and kidneys. The data were analyzed using Statistical Package for Social Sciences (SPSS).Results: More than half of the study participants 43 (55.1%) were females. About 53.8% of the study participants received blood transfusions, and (11.5%) receive extra-vaccine. Concerning ultrasound findings, hepatomegaly was found in seventeen (21.8%), focal liver lesions in four (5.1%), gallstones in five (6.4%), splenomegaly in fifteen (19.3%), and the presence of splenic focal lesions was found in seven (9.0%). The most frequent complication associated with SCD was osteomyelitis sepsis in six cases (7.7%). The study revealed a significant correlation between the type of crisis and type of medication used and the size of the spleen (P-value < 0.01), and no notable correlation was found between the types of crises and the size of the liver (P-value > 0.05).Conclusion: Abdominal sonography in SCD patients revealed a wide range of alterations in the liver, gallbladder, and spleen. The most frequently observed complications in SCD were hepatomegaly, splenomegaly, localized lesions in both organs, and the presence of gallstones.Keywords: sickle cell disease, ultrasonography, abdominal organ, echo-texture

Key Clinical Message Ankylosing spondylitis (AS) presents with renal failure and proteinuria in a minority of cases, usually due to secondary amyloidosis or IgA nephropathy. While focal segmental glomerulosclerosis (FSGS) is less common, it should still be in the differential regardless of the patient's clinical profile.

The designed and synthesized multifunctional properties of bis-hydrazono[1,3,4]thiadiazoles became important for developing an efficient medication for Alzheimer’s disease. Thiadiazoles were characterized and studied towards this target as an acetylcholinesterase inhibitor (ChEIs). In this study, one-pot synthetic strategy was applied for the synthesis of bis-hydrazono[1,3,4]thiadiazole series from 2,2′-(1,2-diphenylethane-1,2-diylidene)bis(hydrazine-1-carbodithioic acid) and hydrazonoyl chlorides. The greener pastures, in silico, an environmentally-friendly and free computer-aided method, bioactivity studies of the bis-hydrazono[1,3,4]thiadiazoles 4a-h exhibited various possible interesting inhibitory activities against AChE showing similar behaviour to the approved drugs, Donepezil, Galantamine and Rivastigmine. For a fair comparison, the superpositions of 4a-h, and Donepezil, Galantamine and Rivastigmine docked together into the functional domain (binding pocket) of 1EVE to reveal interesting different molecular laydowns of the compounds. On the other side, the display of the molecules before and after docking was discussed. The binding affinity slightly differs between Donepezil, Galantamine, Rivastigmine, and the ligands 4a-h. The range of the recorded binding affinity for 4a-h is from (−9.4 to −8.4 kcal/mol−1), whereas the binding affinity for Donepezil, Galantamine and Rivastigmine is (−11.1, −9.8 and −8.0 kcal/mol−1 respectively), which is higher than all the prepared ligands.Furthermore, the binding amino acids also varied among the studied compounds in this study. Phe290, Phe330, Phe331, Trp279, Tyr70, Tyr121 and Tyr334 are the common amino acids binding with the FDA-approved AChE inhibitors for treating AD, Donepezil, Galantamine and Rivastigmine and ligands. Notably, the number of hydrophobic and hydrogen interactions studied between the ligands 4a-h and the Donepezil, Galantamine and Rivastigmine drugs were compared as a preliminary indicator towards a successful inhibitor. The comparative study in this research work aims to rank our compounds with respect to the approved medications. This is a friendly environmental preliminary helpful indication before leaping into time and energy-consuming experimental work. Organ toxicological endpoints and toxicity-predicted activity were obtained using the ProTox-II web server for both the approved medication and ligands. Later, in-vitro acetylcholinesterase inhibition assays were conducted to assess the efficacy of bis-hydrazono[1,3,4]thiadiazoles 4a-h as inhibitors of acetylcholinesterase (AChE) in comparison to Donepezil. Results indicated promising inhibition activities for example 4 h, 4 g and 4d to the testing drug Donepezil for breaking down the neurotransmitter acetylcholine.