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Background: The International Society of Blood Transfusion has documented 30 distinct blood group systems; the ABO and Rh systems are regarded as the most important blood group systems. Determining the ABO-Rh (D) blood group is vital in clinical settings to prevent the possibility of incompatibility and Rhesus D alloimmunization. Objective: This study aimed to provide information on the distribution of blood groups and Rh factor among Bowen University Teaching Hospital School of Nursing students with the view of educating students about the risks of rhesus incompatibility. Material and Methods: retrospective cross-sectional study which reviewed the preschool entry medical records of Nursing students of Bowen University Teaching Hospital Ogbomoso from 2019-2022. The data were systematically collated, analyzed and used to generate frequency tables. Results: a total of 216 records were reviewed. The majority were females (84.3%), less than or equal to 18 years (48.6%) and with blood group O (44.4%) and rhesus positivity (94.0%). None from the male gender had an AB blood group. Prevalence of Rh(D) positive was higher among females (85.3%) while Rh(D) negative was higher among males (14.7%). There was a significant association between gender and Rhesus factor. Conclusion: the findings from this study shows that blood group O and Rh(D) positive had the highest prevalence while the blood group AB and Rh(D) negative had the lowest prevalence. Therefore, effort should be made to educate the few who could suffer adverse events from Rhesus incompatibility.

Background: Anxiety and depression are common mental disorders that are not only on the increase, but their comorbidity accounts for greater severity, chronicity, functional limitations and significant impairment of physical health. Objective: The objective of this study is to determine the prevalence of comorbid anxiety and depression (CAD) among patients attending the General Outpatient Clinic, which could help increase the index of suspicion of these disorders and subsequently improve overall patient care. Methods: A hospital-based cross-sectional study was carried out at the General Outpatient Clinic of Bowen University Teaching Hospital, Ogbomoso, between August and November 2021. Using a systematic sampling technique, 222 respondents were recruited. CAD was evaluated using the Generalized Anxiety Disorder Scale and Patient Health Questionnaire. SPSS version 26 was used for data analysis. Frequency and percentages were calculated, and Chi-square was used to test for significant association with a p-value set at

Background: The advent of antiretroviral therapy (ART) in controlling Human Immunodeficiency Virus (HIV) disease has been quite effective in ensuring that infected people can enjoy healthy, long, and productive lives. Medication adherence is an essential part of patient care, especially among patients with HIV, as it greatly determines the effectiveness of treatment. Few studies have explored factors influencing medication adherence and treatment satisfaction among adults, with little focus on adolescents. Objectives: To assess medication adherence, treatment satisfaction and factors influencing adherence to ART medication among adolescents living with HIV in Lagos, Nigeria. Methods: This descriptive, cross-sectional study was conducted among diagnosed and registered adolescents aged 10-19 years living with HIV and receiving treatment at eight selected antiretroviral centres in Lagos state, Nigeria. A total of 203 adolescents were recruited in stages, and data were collected using an interviewer-administered semi-structured questionnaire. Results: There was a low level of adherence as only 59/203 (29.1%) of the respondents adhered to ART. Depression, perceived stigma, being away from home, side effects of drugs, pill burden, and forgetfulness were some factors identified as barriers to adherence. The respondents were most satisfied with the effectiveness of the medication and least satisfied with the side effects. Conclusions: Medication adherence among adolescents was relatively low; the level of satisfaction with ART medication is an entity that significantly impacts adherence.

Blended learning strategy is an education strategy that involves multiple teaching methods to help students learn more effectively, it combines a mix of face-to-face classroom instruction and online instructional approaches. Despite the importance of blended learning strategy, it has not been fully adopted by university lecturers. Hence, this study investigated Lectures’ Perception on the use of Blended Learning Strategy in University of Ilorin Nigeria. This study adopted a descriptive research design of the survey type, and employed four sectioned researcher-designed questionnaires to elicit information from the respondents.150 lecturers across seven faculties in University of Ilorin were randomly sampled for the study. Both descriptive and inferential statistics were employed to answer and test the formulated hypothesis at 0.05 level of significance. The findings of this study were: (i) The lecturers’ perception on the usefulness of blended learning strategy for instruction in University of Ilorin is positive (3.49>2.44); (ii) The lecturers’ perception on the ease of use of blended learning strategy for instruction in University of Ilorin is positive (3.35>2.44); (iii) The lecturers are facing challenges in using blended learning strategy for instruction (3.20>2.44); (iv) There was no significance difference on lecturers’ perceived usefulness of blending learning strategy based on the area of specialization (p=.060>0.05); (v) There was significance difference on lecturers’ perceived ease of use of blending learning strategy based on the area of specialization (p=.049 0.05). Based on the findings of the study, it was revealed that blended learning is an effective strategy for quality teaching and learning. Though there are challenges affecting the proper implementation of this strategy. The study therefore recommended that seminar and workshop should be organized for lecturers to further their knowledge on the uses of blended learning strategy for instruction.

In recent years, there has been a surge in the global digitization of corporate processes and concepts such as digital technology development which is growing at such a quick pace that the construction industry is struggling to catch up with latest developments. A formidable digital technology, artificial intelligence (AI), is recognized as an essential element within the paradigm of digital transformation, having been widely adopted across different industries. Also, AI is anticipated to open a slew of new possibilities for how construction projects are designed and built. To obtain a better knowledge of the trend and trajectory of research concerning AI technology application in the construction industry, this research presents an exhaustive systematic review of seventy articles toward AI applicability to the entire lifecycle of the construction value chain identified via the guidelines outlined by the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA). The review’s findings show foremostly that AI technologies are mostly used in facility management, creating a huge opportunity for the industry to profit by allowing facility managers to take proactive action. Secondly, it shows the potential for design expansion as a key benefit according to most of the selected literature. Finally, it found data augmentation as one of the quickest prospects for technical improvement. This knowledge will assist construction companies across the world in recognizing the efficiency and productivity advantages that AI technologies can provide while helping them make smarter technology investment decisions.

Relevance. The load on a reinforced concrete slab with high strength lightweight aggregate concrete leads to increased brittleness and contributes to large deflection or flexure of slabs. The addition of fibers to the concrete mix can improve its mechanical properties including flexure, deformation, toughness, ductility, and cracks. The aims of this work are to investigate the flexure and ductility of lightweight expanded clay concrete slabs reinforced with basalt fiber polymers, and to check the effects of basalt fiber mesh on the ductility and flexure. Methods. The ductility and flexural/deflection tests were done on nine engineered cementitious composite (expanded clay concrete) slabs with dimensions length 1500 mm, width 500 mm, thickness 65 mm. These nine slabs are divided in three reinforcement methods types: three lightweight expanded clay concrete slab reinforced with basalt rebars 10 mm (first slab type); three lightweight expanded clay concrete slab reinforced with basalt rebars 10 mm plus dispersed chopped basalt fiber plus basalt fiber polymer (mesh) of cells 2525 mm (second slab type); three lightweight expanded clay concrete slab reinforced with basalt rebars 10 mm plus dispersed basalt fiber of length 20 mm, diameter 15 m (third slab type). The results obtained showed physical deflection of the three types of slab with cracks. The maximum flexural load for first slab type is 16.2 KN with 8,075 mm deflection, second slab type is 24.7 KN with 17,26 mm deflection and third slab type 3 is 32 KN with 15,29 mm deflection. The ductility of the concrete slab improved with the addition of dispersed chopped basalt fiber and basalt mesh.

This study assesses the impact of academic self-efficacy on the academic performance of university science students in Katsina State, Nigeria. One research question and three null hypotheses were formulated. A descriptive survey research design was adopted where 320 randomly selected students from mathematics, physics, chemistry, and biology departments in the four universities in the state were selected. Academic Self-Efficacy Scale and students CGPA record was used as data collection tools which were analyzed using frequency count, percentage, Pearson Product Moment Correlation, Linear Regression, and ANOVA. The result of the study revealed that the majority of the students have either moderate or high academic self-efficacy, but belong to either a third class and/or lower second class degrees. A weak significant positive correlation existed between students’ academic self-efficacy and performance (r = 0.12; p0.05). The researchers recommend that school counselors should improve students’ academic self-efficacy to enhance students’ academic performance.

The use of Aspilia africana as a nonconventional feedstuff to reduce the cost of feed has not been fully explored in poultry production. Therefore, an experiment was conducted on one hundred and ninety-two (192) twelve weeks old birds to determine the effect of Aspilia africana leaf meal (ALM) diet on the performance, egg quality and faecal microbial load. The birds were divided into four groups, each consisting of forty-eight birds. After a two-week acclimatisation, experimental diets that consisted of 0% (Diet 1), 10% (Diet 2), 20% (Diet 3) and 30% (Diet 4) ALM substitution of soybean were fed to the birds. Data on growth performance were collected in the first phase, whereas egg quality, laying performance and faecal count was examined in phase two of the experiment. The data collected were subjected to one-way analysis of variance and significant means were separated via Duncan Multiple Range Test (DMRT). The obtained results identified best (p < 0.05) outcome for growth performance and faecal bacterial load at 30% ALM inclusion in the diet. ALM offered at 20% was optimal for overall egg quality, though egg weight at first lay was superior in pullets fed 10% ALM diet. When consumer attraction to yolk colour is the criterion for purchase, preference for eggs from birds supplied 30% dietary ALM is expected.

Objectives Evidence-based guidelines recommend physiotherapy for respiratory treatment and physical rehabilitation of patients with COVID-19. It is unclear to what extent physiotherapy services are used in the front-line management of COVID-19 in Nigeria. This study aimed to explore the experiences of front-line physiotherapists managing patients with COVID-19 in Nigeria.Design Qualitative interview-based study.Setting ICU and hospital COVID-19 wards, COVID-isolation and treatment centres in Nigeria, between August 2020 and January 2021.Participants Eight out of 20 physiotherapists managing patients with COVID-19 in the front line were recruited using purposive and snowball sampling.Methods Qualitative in-depth semistructured telephone interviews of all consenting physiotherapists managing patients with COVID-19 in the front line in Nigeria were conducted and transcribed verbatim. Transcripts were thematically analysed.Results Eight front-line physiotherapists (three neurological physiotherapists, two orthopaedic physiotherapists, one cardiopulmonary physiotherapist, one sports physiotherapist and one rotational physiotherapist) provided consent and data for this study. Four themes and 13 subthemes were generated illustrating discriminatory experiences of front-line physiotherapists, particularly from COVID-19 team leads; lack of multidisciplinary teamwork within COVID-19 teams; wide ranging stigmatisation from extended family members, colleagues, friends and the general public; material and psychosocial personal losses; lack of system support and suboptimal utilisation of physiotherapy in the management of COVID-19 in Nigeria. Personal agency, sense of professionalism, previous experience managing highly infectious diseases and being a cardiopulmonary physiotherapist were the factors that made the front-line physiotherapists to become involved in managing patients with COVID-19. However, discriminatory experiences made some of these physiotherapists to stop being involved in the management of patients with COVID-19 in the front line. Most front-line physiotherapists were not cardiopulmonary physiotherapists which may have influenced their level of expertise, multidisciplinary involvement and patient outcomes.Conclusions There is suboptimal involvement and support for physiotherapists, particularly cardiopulmonary physiotherapists treating patients with COVID-19 in the front line in Nigeria.

Antimicrobial resistance presents a significant health care crisis. The mutation F98Y in Staphylococcus aureus dihydrofolate reductase (SaDHFR) confers resistance to the clinically important antifolate trimethoprim (TMP). Propargyl-linked antifolates (PLAs), next generation DHFR inhibitors, are much more resilient than TMP against this F98Y variant, yet this F98Y substitution still reduces efficacy of these agents. Surprisingly, differences in the enantiomeric configuration at the stereogenic center of PLAs influence the isomeric state of the NADPH cofactor. To understand the molecular basis of F98Y-mediated resistance and how PLAs' inhibition drives NADPH isomeric states, we used protein design algorithms in the osprey protein design software suite to analyze a comprehensive suite of structural, biophysical, biochemical, and computational data. Here, we present a model showing how F98Y SaDHFR exploits a different anomeric configuration of NADPH to evade certain PLAs' inhibition, while other PLAs remain unaffected by this resistance mechanism.

In recent years, the latest maintenance modelling techniques that adopt the data-based method, such as machine learning (ML), have brought about a broad range of useful applications. One of the major challenges in the automotive industry is the early detection of component failure for quick response, proper action, and minimizing maintenance costs. A vital component of an automobile system is an air pressure system (APS). Failure of APS without adequate and quick responses may lead to high maintenance costs, loss of lives, and component damages. This paper addresses classification problem where we detect whether a fault does or does not belong to APS. If a failure occurs in APS, it is classified as positive class; otherwise, it is classified as negative class. Hence, in this paper, we propose broad embedded logistic regression (BELR). The proposed BELR is applied to predict APS failure. It combines a broad learning system (BLS) and logistic regression (LogR) classifier as a fusion model. The proposed approach capitalizes on the strength of BLS and LogR for a better APS failure prediction. Additionally, we employ the BLS’s feature-mapped nodes for extracting features from the input data. Additionally, we use the enhancement nodes of the BLS to enhance the features from feature-mapped nodes. Hence, we have features that can assist LogR for better classification performances, even when the data is skewed to the positive class or negative class. Furthermore, to prevent the curse of dimensionality, a common problem with high-dimensional data sets, we utilize principal component analysis (PCA) to reduce the data dimension. We validate the proposed BELR using the APS data set and compare the results with the other robust machine learning classifiers. The commonly used evaluation metrics, namely Recall, Precision, an F1-score, to evaluate the model performance. From the results, we validate that performance of the proposed BELR.

Given the deluge of technology flowing into African countries from the global north, it is not a hyperbole to make a point that developed nations are better equipped to practically integrate Smart Technologies supporting Artificial Intelligence (STAI) into higher education teaching methodologies. However, conversations regarding the application of AI in higher education have been spurred by attempts at its practical implementation in developing countries such as Lesotho, Rwanda, and Nigeria. Furthermore, a dearth of literature exists regarding STAI in higher education within the contexts of higher education in Lesotho, Rwanda, and Nigeria. This dearth points to a necessity for research to be conducted to include the three countries' higher education contexts in order for researchers to be able to comprehend the perspectives of educators in these countries on their use of STAI in teaching and learning, as well as to identify the challenges associated with integrating STAI into higher education instructional practices. This study examines these three countries as case studies to gain insights into the perspectives of these educators on smart technologies which support AI in their higher education sectors. Vygotsky's (1978) emphasis on 'cultural tools' and social interaction remains crucial in the knowledge-building process, and his social constructivist learning theory underpins the study. An online, semi-structured questionnaire was designed to address the question: What are e the viewpoints of a sampled group of higher education educators from Rwanda, Nigeria and Lesotho on Smart Technologies which support AI in Higher Education? The findings revealed participant from these countries to possess varied technological knowledge of the use of STAI to facilitate content comprehension and achievement of their teaching objectives. However, we argue in this paper that the participating educators' varied understandings of the use of STAI in higher education needs to expand and to be swiftly accommodated if the three countries are to be on par with developed countries.

Past research identified various psychosocial indicators of college students' academic success. Using the affordance ecology framework, the present study explored the complex relations among different psychosocial indicators with a Bayesian Gaussian Graphical Model approach. Specifically, this study aims to uncover the general patterns of the psychosocial indicators, central variables, and the network centrality indices (network betweenness, closeness, and strength). The final sample consisted of 997 college students. Results showed that after accounting for the complex covariances of all indicators, sense of belonging, having the highest strength, was one of the most central factors in the network of psychosocial indicators and demonstrated a strong direct link to the rest of the psychosocial indicators. Variables relating to the family background and socioeconomic status, including perceived parental support, perceived family social status, and perceived personal financial situation, demonstrated high betweenness and closeness in the network. Implications for higher education research on the psychosocial experiences of students were discussed.

The rapid expansion of the knowledge society, due mainly to the ubiquity and access of information and communication technology (ICT), places a professional demand on teachers to acquire relevant knowledge to make use of technology in their classrooms. Thus, for teachers to effectively integrate ICT into their teaching repertoire, they must transform their pedagogical practices. In this regard, the quality of pre-service and in-service training is pivotal in preparing teachers for effective technology integration. Utilising a case study approach and Activity Theory principles as a theoretical lens, this study set out to explore the influence of ICT as a tool of instruction on the classroom practice of in-service teachers in Rwanda. Qualitative methods were employed to capture data through interviews, observations, and document analysis. Data was analysed using content analysis to understand in-service teachers' constructions about learning through ICT and how it influenced their classroom practice. The investigation of the influence of ICT as an instructional tool to in-service teachers yielded unique patterns of their ICT learning-teaching experiences. The findings were two-fold. First, the ICT learning experiences of the in-service teachers changed their perspective towards teaching and learning with ICT in their own classrooms. Second, the teacher participants vicariously mirrored their lecturers' use of ICT in their own classroom practice. This unintended experience created affordances for the in-service teacher trainees to not only learn 'about' ICT, but significantly 'how to teach' pedagogically with ICT. It is crucial for teacher trainees to experience the same type of learning environments they are expected to create in their own classrooms.

Background: Sickle cell anaemia has been associated with oxidative stress. Total Antioxidant Capacity (TAC), Total Oxidant Status (TOS) and Oxidative Stress Index (OSI) are cumulative markers of oxidative stress. Objective:To evaluate the serum levels of oxidative stress markers in children with sickle cell anaemia (SCA) and determine the relationship between these markers and disease severity. Method: One hundred and fifty-six children, comprising 78 with SCA, aged 1 - 15 years and 78 age- and sex-matched Haemoglobin AA controls were studied. Serum TOS, OSI, and TAC were determined using ELISA kits. The severity of the SCA was determined using clinical and laboratory parameters. Result: Children with SCA had lower mean serum TAC (0.83±0.31UAE) than controls (1.19±0.24UAE)with p

White matter hyperintensities of presumed vascular origin (WMH) are associated with cognitive impairment and are a key imaging marker in evaluating brain health. However, WMH volume alone does not fully account for the extent of cognitive deficits and the mechanisms linking WMH to these deficits remain unclear. Lesion network mapping (LNM) enables us to infer if brain networks are connected to lesions and could be a promising technique for enhancing our understanding of the role of WMH in cognitive disorders. Our study employed LNM to test the following hypotheses: (i) LNM-informed markers surpass WMH volumes in predicting cognitive performance; and (ii) WMH contributing to cognitive impairment map to specific brain networks. We analysed cross-sectional data of 3485 patients from 10 memory clinic cohorts within the Meta VCI Map Consortium, using harmonized test results in four cognitive domains and WMH segmentations. WMH segmentations were registered to a standard space and mapped onto existing normative structural and functional brain connectome data. We employed LNM to quantify WMH connectivity to 480 atlas-based grey and white matter regions of interest (ROI), resulting in ROI-level structural and functional LNM scores. We compared the capacity of total and regional WMH volumes and LNM scores in predicting cognitive function using ridge regression models in a nested cross-validation. LNM scores predicted performance in three cognitive domains (attention/executive function, information processing speed, and verbal memory) significantly better than WMH volumes. LNM scores did not improve prediction for language functions. ROI-level analysis revealed that higher LNM scores, representing greater connectivity to WMH, in grey and white matter regions of the dorsal and ventral attention networks were associated with lower cognitive performance. Measures of WMH-related brain network connectivity significantly improve the prediction of current cognitive performance in memory clinic patients compared to WMH volume as a traditional imaging marker of cerebrovascular disease. This highlights the crucial role of network integrity, particularly in attention-related brain regions, improving our understanding of vascular contributions to cognitive impairment. Moving forward, refining WMH information with connectivity data could contribute to patient-tailored therapeutic interventions and facilitate the identification of subgroups at risk of cognitive disorders.

The purpose of this research was to demonstrate the proximate analysis of poultry-mix made using maize bran as a basis. Red beans, soya beans, and benny beans were the three samples utilised in this study. This work investigates the appropriate poultry mix for birds breed for meat and egg. Thirty grammes of proteinous feedstock were weighed and homogeneously combined with 70 grammes of maize bran. The following was revealed in a proximate analysis of the feeds: moisture ranged from 1.18% to 1.54%, unrefined lipids 0.99–3.08%, total carbohydrate 57% to 72%, ash content 38.48% to 38.92%, unrefined protein 18.38% to 22.53% and unrefined fiber 2.0% to 4.65% respectively for broilers and layers. In terms of nutritional concentrations, all feed samples showed a substantial variation. Based on the findings of the study, it can be stated that Soya bean-maize bran is an excellent poultry-mix formulation that has deep well-disposed benefits and meets nearly all nutritional needs for meat and egg-producing birds.

The K* algorithm provably approximates partition functions for a set of states (e.g., protein, ligand, and protein-ligand complex) to a user-specified accuracy ε. Often, reaching an ε-approximation for a particular set of partition functions takes a prohibitive amount of time and space. To alleviate some of this cost, we introduce two new algorithms into the osprey suite for protein design: fries, a Fast Removal of Inadequately Energied Sequences, and EWAK*, an Energy Window Approximation to K*. fries pre-processes the sequence space to limit a design to only the most stable, energetically favorable sequence possibilities. EWAK* then takes this pruned sequence space as input and, using a user-specified energy window, calculates K* scores using the lowest energy conformations. We expect fries/EWAK* to be most useful in cases where there are many unstable sequences in the design sequence space and when users are satisfied with enumerating the low-energy ensemble of conformations. In combination, these algorithms provably retain calculational accuracy while limiting the input sequence space and the conformations included in each partition function calculation to only the most energetically favorable, effectively reducing runtime while still enriching for desirable sequences. This combined approach led to significant speed-ups compared to the previous state-of-the-art multi-sequence algorithm, BBK*, while maintaining its efficiency and accuracy, which we show across 40 different protein systems and a total of 2,826 protein design problems. Additionally, as a proof of concept, we used these new algorithms to redesign the protein-protein interface (PPI) of the c-Raf-RBD:KRas complex. The Ras-binding domain of the protein kinase c-Raf (c-Raf-RBD) is the tightest known binder of KRas, a protein implicated in difficult-to-treat cancers. fries/EWAK* accurately retrospectively predicted the effect of 41 different sets of mutations in the PPI of the c-Raf-RBD:KRas complex. Notably, these mutations include mutations whose effect had previously been incorrectly predicted using other computational methods. Next, we used fries/EWAK* for prospective design and discovered a novel point mutation that improves binding of c-Raf-RBD to KRas in its active, GTP-bound state (KRasGTP). We combined this new mutation with two previously reported mutations (which were highly-ranked by osprey) to create a new variant of c-Raf-RBD, c-Raf-RBD(RKY). fries/EWAK* in osprey computationally predicted that this new variant binds even more tightly than the previous best-binding variant, c-Raf-RBD(RK). We measured the binding affinity of c-Raf-RBD(RKY) using a bio-layer interferometry (BLI) assay, and found that this new variant exhibits single-digit nanomolar affinity for KRasGTP, confirming the computational predictions made with fries/EWAK*. This new variant binds roughly five times more tightly than the previous best known binder and roughly 36 times more tightly than the design starting point (wild-type c-Raf-RBD). This study steps through the advancement and development of computational protein design by presenting theory, new algorithms, accurate retrospective designs, new prospective designs, and biochemical validation.

Book review of “The Global Education Guidebook: Humanizing K-12 Classrooms Worldwide Through Equitable Partnerships.” By J.D. Klein. Bloomington: Solution Tree, 2017. ISBN: 978-1943874637 The Global Education Guidebook is a compendium of guidance, resources, learning approaches, and frameworks that teachers or global education practitioners can employ in building equitable learning partnerships to help learners develop humanized consciousness of the world and their roles as social actors in it.

Information on the presence of antibiotics is sparse for all types of water in Africa, including groundwater, surface water, effluent of wastewater treatment plants (WWTPs) and municipal potable water. With the relatively high sales of different antibiotics to treat infectious diseases in the human population of Africa, the residual of the antibiotics is bound to be released through excretion via urine or fecal matter in parallel to the high sales. This article reviews the published analysis on the occurrence of antibiotics in the environment particularly in the aquatic environment in some countries in Africa. In general, sulfamethoxazole was the most commonly detected in Africa surface water (with eight reports from four countries) at a concentration range of 0.00027 – 39 μgL-1. Wastewater analysis is believed to give an early warning for preventing epidemics. Thus, we discuss the associated level of antibiotic resistance to some prevalent diseases in Africa whose aetiological agents can develop antibiotic resistance due to exposure to antibiotic residue in water. This is important because of rising population of immuno-deficient African residents ravaged by HIV/AIDS, poor nutrition and less efficient sanitation systems.