Glucose-6-Phosphate Dehydrogenase (G-6-PD) deficiency is the most important disorder of the pentose phosphate pathway in erythrocyte metabolism resulting in decreased activity of the enzyme. G-6-PD deficiency has been reported to be common in populations living in malaria endemic areas. Certain drugs that are used in the treatment of malaria and other conditions are known to induce hemolysis in G-6-PD deficient individuals. This study was carried out to determine the prevalence of G-6-PD deficiency in individuals with malaria infection. One hundred subjects were recruited in the study with 50 individuals positive for malaria infection as test subjects and 50 negatives for malaria infection serving as controls. A G-6-PD deficiency prevalence of 14% was found in the study, 86% of the G-6-PD deficient individuals were from the control group while 14% were from the malaria positive group. A significant difference (p≤0.01) in G-6-PD deficiency was found between the malaria group and the control group. Among the G-6-PD deficient individuals 93% were males. There was a significant (p≤0.05) difference in Packed Cell Volume and hemoglobin levels between the G-6-PD deficient group and the G-6-PD normal group. The lower prevalence of G-6-PD deficiency among the malaria group compared to the control group validates studies linking G-6-PD deficiency with malaria. Also, the higher prevalence seen in control group and males, suggests that gender plays an important role in this enzyme deficiency hence the need for G-6-PD screening in our community given the overuse of agents that may predispose a G-6-PD deficient individual to oxidative stress which could cause some hematological complications such as hemolytic anemia.

Background: Havan Yagya is a traditional Vedic fumigation practice involving the combustion of medicinal herbs, wood, and clarified butter (ghee) in a consecrated fire. Ethnopharmacological evidence and emerging scientific literature suggest that the smoke generated during Havan possesses significant antimicrobial properties. Objective: The present preliminary study aimed to evaluate the effect of Havan Yagya on the observable microbial load settling from indoor room air using the passive settle plate method, and to quantify the percentage reduction in colony-forming units (CFU) at 30 minutes and 24 hours post-Havan. Methods: Sterile culture-media plates were exposed in a controlled indoor room environment before and after Havan under identical conditions. Plates were incubated aerobically at 37°C and visible colonies were enumerated. Results: A baseline average of 11.0 CFU/plate was recorded before Havan. At 30 minutes post-Havan, the average count decreased to 1.0 CFU/plate, representing a 90.90% reduction. At 24 hours post-Havan, the average count was 5.5 CFU/plate, corresponding to a 50% reduction from baseline. Conclusion: These findings indicate that Havan Yagya produces a marked short-term reduction in airborne microbial settling, with a sustained partial effect persisting for at least 24 hours. The results are consistent with published literature on medicinal smoke and traditional fumigation practices. Larger controlled trials are warranted to validate and extend these preliminary observations.

Valorization of silica-bearing plant residues offers a route for converting low-value biomass into functional inorganic materials. This study investigated silica recovery from Bambusa vulgaris leaves using a multistage process comprising hydrochloric-acid leaching, hydrogen-peroxide pretreatment, calcination, alkaline extraction, acid precipitation, washing, and drying. Freshly collected leaves were washed and oven-dried, after which a 50.044 g powder batch was leached with 1 M HCl at 80°C for 1 h. The recovered dry mass after leaching was 31.8 g. A 3.0 g acid-leached sub-batch was then treated with 1 mL of 30% H2O2 in 20 mL distilled water at 60°C for 1 h and dried to 1.942 g before calcination at 650°C for 3 h. A representative gravimetric mass balance showed that approximately 100 g of dry leaf powder produced 20 g of calcined ash and approximately 10 g of dried silica-based powder, corresponding to a 20% ash yield, a 10% recovered-product yield on a dry-leaf basis, and a 50% ash-to-product recovery. The calcined material was subjected to alkaline extraction with 2 M NaOH at 90°C for 1 h, and the resulting sodium-silicate-containing filtrate was acidified with HCl to approximately pH 3. The formed gel was washed and dried at 100°C for 12 h to obtain a white silica-based powder. FTIR analysis over 4000-400 cm-1 showed a broad O-H band centered at 3398 cm-1, a prominent Si-O-Si asymmetric stretching band at 1062 cm-1, a Si-O-related band near 800 cm-1, and a broad Si-O-Si bending region at approximately 470-425 cm-1. These features are consistent with hydrated, silanol-containing silica and with the broad spectral profile commonly reported for biogenic amorphous silica. However, FTIR alone cannot establish crystallographic phase or quantitative purity. The study therefore demonstrates a feasible H2O2-assisted extraction route with competitive gravimetric recovery, while identifying XRD, XRF/EDX, replicated yield measurements, and a matched no-H2O2 control as essential next-stage analyses.

Background: Inadvertent medication administration errors and secondary contamination during pediatric pharmaceutical preparation represent critical global patient safety threats. Direct bedside observation provides an authentic clinical audit of actual nursing practice compared with self-reported survey methods. Objective: To investigate pediatric nurses' real-world clinical adherence to basic infection prevention protocols and safe medication storage and handling regulations across public referral hospitals. Methods: A multicenter cross-sectional observational audit was conducted across pediatric departments in four governmental hospitals: Shandi Teaching Hospital, Al-Mak Nimr Teaching Hospital, Hosh Bannaga Hospital, and Al-Misktab Hospital. A total-coverage sample of 130 frontline bedside pediatric nurses was directly observed during routine medication rounds using an expert-validated clinical checklist comprising 11 basic infection control items and 3 medication storage parameters. Bivariate associations between nursing characteristics and clinical adherence were evaluated using Chi-square tests with statistical significance defined at p ≤ 0.05. Results: Direct clinical audits identified widespread compliance gaps across frontline pediatric units. Procedural hand hygiene was correctly performed in only 50.0% of encounters before and after drug handling, and in 53.8% upon direct patient contact. Strict aseptic injection preparation technique was observed in 46.2% of participants. Serious vulnerabilities were noted in parenteral device handling: only 40.0% segregated multi-dose vials within centralized clean medication stations, and dedicated single-patient insulin pen usage was restricted to 40.0%. Compliant pharmaceutical storage aligned with manufacturer temperature and light recommendations was observed in 46.2% of nurses. Bivariate analysis revealed that bachelor's degree qualification and extended clinical experience were significantly associated with higher clinical compliance (p < 0.05). Conclusion: Routine nursing compliance with basic infection control and safe medication handling remains critically compromised in public pediatric inpatient settings. Hospital administrations must establish centralized aseptic preparation stations, institute strict patient-specific device labeling policies, and sustain regular observational audits.

Prestressed High-Strength Concrete (PHC) piles have recently been utilized in Saudi Arabia for the Ras Al-Khair Steel Plate Manufacturing Project due to their high structural capacity, durability, and rapid installation. This study evaluates the performance of PHC piles installed using two construction methods: dynamic driving and hydraulic static pressing. The performance of the installation methods was assessed based on the results of axial compression load tests, with a maximum allowable settlement of 25 mm under the highest test load. The static pressing method results on a lower average settlement and narrower range of settlement readings for the tested piles, which suggest that it is more reliable than dynamic driving method.

Unknown project risks play a critical role in the successful execution of projects. These risks may originate from internal or external sources and can present opportunities, threats, or neutral outcomes. The objective of this paper is to examine unknown project risks that may affect project outcomes. It discusses the challenges associated with identifying unknown risks and highlights the role of project managers and risk management teams in managing these risks and their potential impacts as well as in transforming unknown risks into known and manageable risks through structured risk identification, investigations and continuous monitoring. Effective identification and management of unknown risks enhance project decision-making, reduce uncertainties, and increase the likelihood of project success. This paper also presents a case study on the implementation of new technologies in Saudi Aramco. The study examines the challenges encountered during implementation and demonstrates how thorough investigations and clarification of identified uncertainties, known and unknown risks contributed to the successful implementation and adoption of these technologies within the company.

Background. Kho-Kho is a high intensity, intermittent pursuit sport in which explosive acceleration, rapid change of direction, and lower limb power are widely assumed to underpin competitive success. Whether these generic attributes actually discriminate between ability strata within an already selected squad remains empirically unresolved, and female players at the state tier are largely absent from the peer reviewed record. Purpose. To compare speed, agility, and leg explosive strength among high, medium, and low ability state level female Kho-Kho players. Methods. Sixty-seven female state level players (18–23 years) were purposively sampled from Purba Medinipur, North 24 Parganas, South Kolkata, and Hooghly districts, West Bengal, and classified into three ability groups. Speed was assessed by the 50-yard dash, agility by the 4 × 10 yard shuttle run, and leg explosive strength by the standing broad jump. Data were analysed by descriptive statistics and one way ANOVA (α = 0.05) using IBM SPSS Statistics 26. Results. No significant differences emerged for speed, F(2, 64) = 1.06, p = 0.352, η² = 0.03; agility, F(2, 64) = 0.197, p = 0.822; or leg explosive strength, F(2, 64) = 0.744, p = 0.479. Descriptively the high ability group was fastest (8.01 ± 0.552 s), jumped furthest (1.84 ± 0.165 m), and showed markedly lower variability. Conclusion. These components function as a performance threshold rather than a discriminator at state level; selection should additionally assess reactive agility, technical skill, and tactical decision making.

Transportation infrastructure is critical to economic transformation and sustainable development in emerging African economies, yet inadequate financing continues to constrain the development and efficiency of transport systems. This study examines the effect of transportation infrastructure financing on sustainable development, using economic growth as the principal indicator, with particular attention to public-private partnerships (PPPs), public investment, infrastructure bonds, concessional loans, and sovereign funds. The study adopted a quantitative survey design and analysed 2,836 valid responses obtained from transportation and logistics organisations. Least square regression was employed to examine the relationships between the financing mechanisms and sustainable development, while logistic regression was used as a robustness check. The results reveal positive and statistically significant relationships across all five financing mechanisms. Infrastructure bonds recorded the strongest estimated relationship (3.231), followed by public investment (2.841), sovereign funds (2.767), PPPs (2.764), and concessional loans (2.667), all significant at the 1% level. The robustness analysis further supports the consistency of the findings. The study concludes that diversified and effectively managed transportation infrastructure financing can contribute significantly to sustainable development in emerging African economies. It recommends stronger institutional capacity, improved governance, and strategic diversification of public and private financing sources.

Traditional Institutions (TIs) in Kamporijo Circle of Kamle District, Arunachal Pradesh are fundamental to the governance, culture and livelihood of indigenous communities, especially the Nyishi people. In terms of economy, Traditional Institutions play an important role in facilitating dispute resolutions, resource management and the sustenance of livelihoods. Traditional Institutions promote traditional land-use systems including jhum cultivation and the simultaneous use of community forests according to principles of reciprocity and balance in nature. Objective: The study aims to examine the role and functions of Traditional Institutions (TIs) in Kamporijo Circle of Kamle District of Arunachal Pradesh. Research Methodology: The study utilises a qualitative analytical research design to characterize the role and functions of Traditional Institutions (TIs) in Kamle district of Arunachal Pradesh. Adopting qualitative protocol allows for a more comprehensive and situated understanding of TIs within local cultural implications. Results and Discussions: The conceptual framework provides insight into how traditional institutions operate within the context of Nyishi tribal society in Kamporijo and explains the role of these institutions within the framework of greater socio-cultural issues, rather than viewing them in isolation. It bridges between indigenous knowledge systems and modern institutional frameworks, thus providing a culturally grounded approach to studying development, governance, and social transformation in tribal areas of Arunachal Pradesh. Conclusion: Their main functions as dispute resolution, the gatekeeper of customary land rights, and moral arbiter are legitimised by social consent and the familiarity of the villagers. TIs operate as harmonising conflict resolution mechanisms, emphasising reconciliation, restorative justice, conventional significance and a legitimate basis to redress grievances that preserve community harmony.

The need to improve bioethanol yield from elephant grass has made the optimization of the pretreatment process inevitable. This work studied and determined the optimal alkaline concentration for the pretreatment of elephant grass with sodium hydroxide (NaOH) and hot water under the specified conditions. The pretreatment was performed at different concentrations of sodium hydroxide for a period of 1:30 hr. at 97.5oC. Scanning Electron Microscope (SEM) and Fourier Transform Infrared Spectroscopy (FTIR) were used to determine the effects of the pretreatment on the morphology and structure of the elephant grass. The grass hydrolysate was subjected to simultaneous saccharification and fermentation using cellulase enzyme and bakers’ yeast. Optimum pretreatment condition was obtained by using 0.25 M NaOH, which yielded 6.778g/L reducing sugar. Bioethanol yield was found to be 8.84% of the available sugar. The SEM and FTIR analysis showed that NaOH pretreatment under the determined optimum conditions successfully disintegrated the recalcitrant structure of elephant grass. Hence, NaOH pretreatment at the concentration of 0.25 M exposed to hot water for 1:30 hr. at 97.5oC is a promising condition for bioethanol production from elephant grass.

This study proposes an interoperable Management Information System (MIS) that integrates real-time payment intelligence, merchandise planning, and distributed workforce coordination within a unified enterprise information architecture. The proposed framework addresses fragmentation across payment, retail, inventory, and workforce systems through System, Process, and Experience APIs, supported by Apache Kafka and Apache Flink for real-time event processing. Synthetic financial, retail, and workforce datasets are used to evaluate payment-event processing, fraud aware demand signals, inventory decisions, workforce allocation, operational reliability, and governance. A multi-objective planning model considers processing latency, inventory exposure, workforce imbalance, and operational risk. The experimental results indicate that the proposed MIS achieved 86 ms decision latency, compared with 420 ms for event-driven processing and 1,850 ms for batch coordination. Timely payment event processing reached 97%, inventory response reached 91%, and workforce task response reached 88%. The findings indicate that payment activity can serve as a real-time operational signal for merchandise and workforce decisions when supported by governed interoperability, event processing, and audit controls. The study provides an architecture and evaluation framework for integrated decision intelligence across distributed enterprise operations.

The removal of synthetic dyes such as Methylene Blue from aqueous effluents is a critical environmental challenge. This study investigates the efficacy of activated Carbon derived from Pterocarpus santalinoides Fruit as a low-cost and renewable adsorbent of Methylene Blue dye. The Pterocarpus santalinoides activated carbon was analyzed using scanning electron microscopy and Fourier transform infra-red spectroscopy. The Box-Behnken design of response surface methodology (RSM) method was adopted to optimize the adsorption process variables such as contact time (20 – 100 min), adsorbent dose (0.1 – 0.5 g), initial dye concentration (10 – 50 mg/l), and temperature (30 – 60 ℃). The characterization result revealed the good adsorptive properties of the Pterocarpus santalinoides activated carbon. The ANOVA result indicates that quadratic model was reliable for predicting methylene blue removal with R2 of 0.9267 and 0.9618 for adsorption capacity. The optimum condition for the maximum removal efficiency of 95.90 % and adsorption capacity of 5.70 mg/g were achieved at contact time (56.33 min), adsorbent dose (0.43 g), MB concentration (36.26 mg/l) and temperature (55.91 ℃). Both Henry and Langmuir isotherms were well fitted to the adsorption data. The adsorption kinetics was best described by the Psuedo–second order model indicating a chemisorption-dominated process. Equilibrium Isotherm data showed a high correlation with the Langmuir model suggesting a monolayer adsorption on a homogeneous surface. This study successfully demonstrated the efficiency of Box Behnken Design of Response Surface Methodology (BBD – RSM) as a powerful tool for modeling and optimizing the adsorption process, providing a clear path-way for maximizing the efficiency of Pterocarpus santalinoides based activated Carbon for dye wastewater treatment and environmental remediation.

Artificial intelligence has become increasingly embedded in the practices through which human beings acquire, organize, evaluate, communicate, and act upon information. The philosophical problem raised by this development is therefore not exhausted by the familiar observation that artificial intelligence sometimes produces false information. More fundamental is the question of whether systems that generate apparently knowledgeable discourse can participate appropriately in epistemic practices when they do not possess the kinds of beliefs, experiences, intentions, understanding, or testimonial commitments ordinarily associated with human knowers. This paper develops the concept of epistemic impropriety as a normative framework for examining that problem. Epistemic impropriety is distinguished from epistemic error and epistemic harm: an error concerns falsity or inadequate justification; a harm concerns damage suffered in one's capacity as a knower; impropriety concerns the violation or distortion of norms governing responsible inquiry, testimony, justification, interpretation, authority, and epistemic agency. The paper argues that the central epistemic danger of generative artificial intelligence lies in the possibility that linguistic plausibility may acquire the social authority normally associated with justified knowledge. This danger manifests itself in hallucination, the manufacture of apparent understanding, the illusion of comprehensiveness, the substitution of plausibility for justification, algorithmic opacity, automation bias, synthetic testimony, epistemic injustice, hermeneutical exclusion, epistemic infantilization, and the gradual displacement of human intellectual agency. At the same time, the paper rejects the simplistic conclusion that artificial intelligence is epistemically worthless. AI may function as an epistemic technology, a cognitive aid, and a participant in distributed practices of inquiry without thereby becoming an autonomous knower or epistemic authority in the full human sense. The appropriate philosophical response is consequently neither technological rejection nor uncritical enthusiasm, but the cultivation of a critical human–AI epistemic relationship governed by provenance, transparency, evidential calibration, contestability, pluralism, human judgment, and responsibility. The ultimate question is not merely whether artificial intelligence can generate answers, but whether its participation enables human beings to become better knowers.

This paper presents the findings of a research on an artificial intelligence-based hybrid Support Vector Machine–Bat Optimization Algorithm (SVM-BOA) model developed for spectrum sensing in the Ultra High Frequency (UHF) television band (470 – 694 MHz). The main objective is to enhance detection accuracy, probability of detection, probability of false alarm, and computational efficiency for efficient spectrum utilization. Experimental spectrum measurements were conducted across Kano, Kaduna, and the Federal Capital Territory (FCT), Abuja, Nigeria, to assess the level of spectrum occupancy and identify available Television White Space (TVWS) channels. Relevant signal features, including received signal power level, noise power level, and frequency, were extracted from the field data collected and used to train and test the proposed model. The model was developed and implemented in MATLAB computing environment. The new model was validated using test data for classification of channel status as either free or occupied. The developed model achieved a detection accuracy of 97.67% at a threshold of −99.5dB, based on metric from confusion matrix, outperforming baseline SVM (78.57%) and other benchmark optimization-based SVM models, including Grid Search SVM (92.86%), Random Search SVM (89.29%), Genetic Algorithm SVM (92.86%), and Particle Swarm Optimization SVM (92.78%). It also attained a probability of detection (Pd) of 1.00 (100%) and a probability of false alarm (Pfa) of 0.1053 (10.53%), which satisfies the sensing performance requirements of the Institute of Electrical and Electronics (IEEE 802.22) standards under low-signal conditions. These findings suggest that the hybrid SVM-BOA approach will offer superior classification accuracy and computational efficiency relative to conventional techniques and comparable hybrid models, signifying a strong potential for the improvement of spectrum utilization in next-generation cognitive radio networks.

The Magnus expansion is attractive for periodically driven quantum systems because every finite truncation exponentiates an anti-Hermitian generator and therefore preserves unitarity. Its practical failure in interacting fermionic systems is nevertheless subtle: a low-order approximation may remain unitary while becoming progressively less accurate as additional terms are retained. We establish order-resolved breakdown signatures for a half-filled, periodically driven one-dimensional Fermi-Hubbard chain. The one-period propagator is computed numerically exactly in the fixed-particle sector and compared with Magnus approximants through fourth order. Failure is defined operationally by a successive-order error ratio (rₙ=εₙ/εₙ₋₁≥ 1), not by an unsupported claim of divergence of the infinite series. Across a raw (9×29) interaction-frequency grid ((U/J=0…,8), (ω/J=2…,16)), at least one added order loses improvement at 36.40% of the 261 sampled points. The smallest sampled frequency above which all retained orders improve throughout the remaining high-frequency tail rises from (ω/J=2.5) at (U=0) to (11.5) at (U/J=8). At (U/J=4), the highest (r₄=1) crossing occurs at (ω/J=7.719), followed by a monotone sampled tail from (ω/J=8). High-frequency error exponents approach the expected omitted-order scaling. A norm-based convergence certificate is consistently more conservative than the observed finite-order boundary. These results show that Magnus breakdown in the Hubbard model is order dependent, interaction shifted, and detectable before unitarity is lost.