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Summary: Background: Children in low and middle-income countries remain vulnerable following hospital-discharge. We estimated the incidence and correlates of hospital readmission among young children admitted to nine hospitals in sub-Saharan Africa and South Asia. Methods: This was a secondary analysis of the CHAIN Network prospective cohort enrolled between 20th November 2016 and 31st January 2019. Children aged 2–23 months were eligible for enrolment, if admitted for an acute illness to one of the study hospitals. Exclusions were requiring immediate resuscitation, inability to tolerate oral feeds in their normal state of health, had suspected terminal illness, suspected chromosomal abnormality, trauma, admission for surgery, or their parent/caregiver was unwilling to participate and attend follow-up visits. Data from children discharged alive from the index admission were analysed for hospital readmission within 180-days from discharge. We examined ratios of readmission to post-discharge mortality rates. Using models with death as the competing event, we evaluated demographic, nutritional, clinical, and socioeconomic associations with readmission. Findings: Of 2874 children (1239 (43%) girls, median (IQR) age 10.8 (6.8–15.6) months), 655 readmission episodes occurred among 506 (18%) children (198 (39%) girls): 391 (14%) with one, and 115 (4%) with multiple readmissions, with a rate of: 41.0 (95% CI 38.0–44.3) readmissions/1000 child-months. Median time to readmission was 42 (IQR 15–93) days. 460/655 (70%) and 195/655 (30%) readmissions occurred at index study hospital and non-study hospitals respectively. One-third (N = 213/655, 33%) of readmissions occurred within 30 days of index discharge. Sites with fewest readmissions had the highest post-discharge mortality. Most readmissions to study hospitals (371/450, 81%) were for the same illness as the index admission. Age, prior hospitalisation, chronic conditions, illness severity, and maternal mental health score, but not sex, nutritional status, or physical access to healthcare, were associated with readmission. Interpretation: Readmissions may be appropriate and necessary to reduce post-discharge mortality in high mortality settings. Social and financial support, training on recognition of serious illness for caregivers, and improving discharge procedures, continuity of care and facilitation of readmission need to be tested in intervention studies. We propose the ratio of readmission to post-discharge mortality rates as a marker of overall post-discharge access and care. Funding: The Bill & Melinda Gates Foundation (OPP1131320).

Renewable energy penetrated distribution systems (REPDS) are the upcoming form of conventional distribution systems due to environmental benefits and power quality concerns. However, islanding detection is a challenging problem associated with these REPDSs. In this paper, the Particle filter (PF) is utilized to detect the islanding events in modern REPDS by utilizing a voltage signal at the point of common coupling (PCC). Initially, the PF is implemented on voltage signature at PCC for state estimation of fundamental and non-fundamental components. Then, the Particle filter estimated residuals (PFER) and non-fundamental $3^{\mathrm {rd}}$ harmonic component (NFTHC) indices are computed. The estimated PFER & NFTHC indices are matched with the pre-specified threshold setting to recognize the islanding conditions. Then, the tripping decision is taken by OR-operation of both the estimated PFER & NFTHC. The suggested method is competent in detecting islanding events in both balanced as well as unbalanced load/generation events. Moreover, the suggested method is also capable of discriminating islanding conditions from non-islanding events. Extensive simulation on MATLAB/Simulink-based IEEE 13-bus test bed and UL-1741 test bed are accomplished to authenticate the usefulness of the suggested scheme. The results illustrate that the suggested method performs well with 99% accuracy, low computational latency, and very low non-detection zone (NDZ). Furthermore, the time of action of the presented scheme is less than 2 milliseconds (m sec) deprived of any false operation.

An improved ripple correlation control (iRCC) algorithm is proposed to enable conventional ripple correlation control (cRCC) to track maximum power under uniform and partial shading condition (PSC). The proposed iRCC has two parts; the first part detects the global maximum power point (GMPP) under PSC, the second part executes the ripple correlation control to operate the photovoltaic (PV) array at GMPP. The proposed iRCC stays with the second part under uniform irradiation condition and moves to the GMPP only when it detects a dynamic change in weather condition. The proposed iRCC is validated through simulation in Matlab and by hardware prototype. The performance improvement is verified in contrast with the conventional RCC method. The results showcase that the proposed iRCC algorithm accurately tracks the GMPP compared to the conventional RCC method. Consequently, the proposed iRCC method, under partial shading condition 1 (PSC-1), produce 131 % more output power compared with the cRCC method. For PSC-2, the shading resulted in power peaks such that the proposed iRCC power yield is almost equal to the cRCC method. This suggests that the proposed iRCC method can outperform the cRCC method depending on the shading pattern.

AC microgrids (ACMGs) represent a promising evolution of traditional distribution systems, driven by environmental advantages and concerns over power quality. However, detecting islanding events within ACMGs poses a significant challenge. In this study, we propose the utilization of the Cubature Kalman Filtering Algorithm (CKFA) to address this challenge by leveraging voltage signals at the point of common coupling (PCC). Initially, CKFA is applied to voltage signatures to compute Voltage Residuals (VR) and Voltage Harmonic Signatures (VHS) through state estimation. These estimated VR and VHS indices are then compared against pre-defined threshold settings to identify islanding states. Subsequently, a tripping decision is made based on the OR operation of both estimated VR and VHS. The proposed method demonstrates efficacy in detecting islanding occurrences under both balanced and unbalanced load/generation conditions and effectively discriminating between islanding and non-islanding conditions. Extensive simulations conducted on MATLAB/Simulink-based IEEE 13-bus test bed and UL-1741 test bed validate the effectiveness of the presented scheme. Results signify a high accuracy rate of 99.9%, tied with low computational complexity and the smallest non-detection zone (NDZ). Additionally, the time of operation for the suggested scheme is less than 1 millisecond, without any false operations, emphasizing its effectiveness in practical application.

Summary: Background: Growth faltering is well-recognized during acute childhood illness and growth acceleration during convalescence, with or without nutritional therapy, may occur. However, there are limited recent data on growth after hospitalization in low- and middle-income countries. Methods: We evaluated growth following hospitalization among children aged 2–23 months in sub-Saharan Africa and South Asia. Between November 2016 and January 2019, children were recruited at hospital admission and classified as: not-wasted (NW), moderately-wasted (MW), severely-wasted (SW), or having nutritional oedema (NO). We describe earlier (discharge to 45-days) and later (45- to 180-days) changes in length-for-age [LAZ], weight-for-age [WAZ], mid-upper arm circumference [MUACZ], weight-for-length [WLZ] z-scores, and clinical, nutritional, and socioeconomic correlates. Findings: We included 2472 children who survived to 180-days post-discharge: NW, 960 (39%); MW, 572 (23%); SW, 682 (28%); and NO, 258 (10%). During 180-days, LAZ decreased in NW (−0.27 [−0.36, −0.19]) and MW (−0.23 [−0.34, −0.11]). However, all groups increased WAZ (NW, 0.21 [95% CI: 0.11, 0.32]; MW, 0.57 [0.44, 0.71]; SW, 1.0 [0.88, 1.1] and NO, 1.3 [1.1, 1.5]) with greatest gains in the first 45-days. Of children underweight (

Objectives This study evaluated the prevalence and correlates of guideline non-adherence for common childhood illnesses in low-resource settings.Design and setting We used secondary cross-sectional data from eight healthcare facilities in six Asian and African countries.Participants A total of 2796 children aged 2–23 months hospitalised between November 2016 and January 2019 with pneumonia, diarrhoea or severe malnutrition (SM) and without HIV infection were included in this study.Primary outcome measures We identified children treated with full, partial or non-adherent initial inpatient care according to site-specific standard-of-care guidelines for pneumonia, diarrhoea and SM within the first 24 hours of admission. Correlates of guideline non-adherence were identified using generalised estimating equations.Results Fully adherent care was delivered to 32% of children admitted with diarrhoea, 34% of children with pneumonia and 28% of children with SM when a strict definition of adherence was applied. Non-adherence to recommendations was most common for oxygen and antibiotics for pneumonia; fluid, zinc and antibiotics for diarrhoea; and vitamin A and zinc for SM. Non-adherence varied by site. Pneumonia guideline non-adherence was more likely among patients with severe disease (OR 1.82; 95% CI 1.38, 2.34) compared with non-severe disease. Diarrhoea guideline non-adherence was more likely among lower asset quintile groups (OR 1.16; 95% CI 1.01, 1.35), older children (OR 1.10; 95% CI 1.06, 1.13) and children presenting with wasting (OR 6.44; 95% CI 4.33, 9.57) compared with those with higher assets, younger age and not wasted.Conclusions Non-adherence to paediatric guidelines was common and associated with older age, disease severity, and comorbidities, and lower household economic status. These findings highlight opportunities to improve guidelines by adding clarity to specific recommendations.

The article aimed to formulate an MLX binary ethosome hydrogel for topical delivery to escalate MLX solubility, facilitate dermal permeation, avoid systemic adverse events, and compare the permeation flux and efficacy with the classical type. MLX ethosomes were prepared using the hot method according to the Box–Behnken experimental design. The formulation was implemented according to 16 design formulas with four center points. Independent variables were (soya lecithin, ethanol, and propylene glycol concentrations) and dependent variables (vesicle size, dispersity index, encapsulation efficiency, and zeta potential). The design suggested the optimized formula (MLX–Ethos–OF) with the highest desirability to perform the best responses formulated and validated. It demonstrates a 169 nm vesicle size, 0.2 dispersity index, 83.1 EE%, and −42.76 mV good zeta potential. MLX–Ethos–OF shows an amorphous form in PXRD and a high in vitro drug release of >90% over 7 h by diffusion and erosion mechanism. MLX–Ethos–OF hyaluronic acid hydrogel was fabricated and assessed. It shows an elegant physical appearance, shear thinning system rheological behavior, good spreadability, and skin-applicable pH value. The ex vivo permeation profile shows a flux rate of 70.45 μg/cm2/h over 12 h. The in vivo anti-inflammatory effect was 53.2% ± 1.3 over 5 h. compared with a 10.42 flux rate and 43% inflammatory inhibition of the classical ethosomal type. The conclusion is that binary ethosome is highly efficient for MLX local delivery rather than classical type.

Among healthcare workers, nurses are considered the core of healthcare auth–info services in healthcare facilities because of their responsibilities and duties toward patients. All healthcare professionals, especially nurses, must be completely knowledgeable about the hazards of ionizing radiation, and the most effective radiation protection techniques. This study assessed the attitude and awareness toward radiation protection among final-year nursing students in the Fatima College of Health Sciences (FCHS) campuses. An online cross-sectional survey was conducted between March and April 2022. A total of 200 out of 224 female participants ranging from 18 to 30 years old agreed to participate in the study. The highest percentage of final-year nursing students did not attend any radiation protection course (52%). The results of the last section of the survey indicate a lack of awareness of basic radiation protection knowledge among final-year nursing students in FCHS campuses (less than 80%). The results showed a lack of knowledge and poor attitude toward radiation hazards and radiation protection from final-year nursing students in the FCHS. Formal education about basic radiation and radiation is recommended in the nursing program for safe clinical practice.

Introduction. We aimed to determine the burden of respiratory disease by examining clinical profiles and associated predictors of morbidity and mortality of patients admitted to a Pediatric Intensive Care Unit (PICU) in Pakistan, a resource limited country. We also stratified the respiratory diseases as defined by the Pediatric Advanced Life Support (PALS) Classification. Methods. A retrospective study was conducted on children aged 1 month to 18 years who were diagnosed with respiratory illness at the PICU in a tertiary hospital in Karachi, Pakistan. Demographics, essential clinical details including immunization status, and the outcome in terms of mortality or survival were recorded. Predictors of mortality and morbidity including prolonged intubation and mechanical ventilation in the PICU were analyzed using the chi-square test or Fischer’s exact test as appropriate. Results. 279 (63.8% male; median age 9 months, IQR 4–36 months) patients were evaluated of which 44.2% were malnourished and 23.3% were incompletely immunized. The median length of stay in the PICU was 3 days (IQR 2–5 days). Pneumonia was the principal diagnosis in 170 patients (62%) and accounted for most deaths. 76/279 (27.2%) were ventilated, and 67/279(24.0%) needed inotropic support. A high Pediatric Risk of Mortality (PRISM) III score, pneumothorax, and lower airway disease were significantly associated with ventilation support. The mortality rate of patients was 14.3%. Predictors of mortality were a high PRISM III score (OR 1.179; 95% CI 1.024–1.358, P=0.022) and a positive blood culture (OR 4.305; 95% CI 1.062-17.448, P=0.041). Conclusion. Pneumonia is a significant contributor of respiratory diseases in the PICU in Pakistan and is the leading cause of morbidity and mortality. A high PRISM III score, pneumothorax, and lower airway disease were predictors for ventilation support. A high PRISM III score and a positive blood culture were predictors of patient mortality in our study.

# Background Antibody-based serological tests which target households and communities can estimate the true extent of infection in a population. It minimizes the biases of facility-based selective testing and generates scientific data on disease transmission through household asymptomatic cases. The objective of this study was to determine the seroprevalence and trend of SARS-CoV-2 in a densely populated urban community of Karachi. # Methods Three serial cross-sectional surveys were conducted in November 2020, February 2021, and December 2021 in Karachi's District East. Households were selected to provide serum samples for Elecsys® immunoassay for the detection of SARS-CoV-2 antibodies. All household members were eligible to participate regardless of age and infection status. Bayesian regression was used to adjust for assay performance and estimate seroprevalence. # Results We enrolled 1506 participants from 501 households. In November 2020, adjusted seroprevalence was estimated as 24.0% (95% confidence interval, CI=18.0-31.0), compared to 53.9% (95% CI=45.5-63.2) in February. In December 2021, it increased to 84.9% (95% CI=78.5-92.3). The conditional risk of infection was 41% (95% CI=29.9-51.6), 56.7% (95% CI=50.4--62.6) and 77.8% (95% CI=73.0-81.7) in surveys 4, 5, and 6 respectively. Only 18.7% of participants who had reactive antibodies for COVID-19 were symptomatic. # Conclusions An increase in seroprevalence estimates in Karachi's District East was observed over time. Community-based seroprevalence studies help to estimate the true proportion of the population that has been infected and predicts the spread of the disease in similar settings.

A bond-additive connectivity index, named as the Mostar index, is used to measure the amount of peripheral edges of a simple connected graph, where a peripheral edge in a graph is an edge whose one end vertex has more number of vertices closer as compared to the other end vertex. In this study, we count the contribution of peripheral edges in commuting, non-commuting, and non-conjugate graphs associated to the dihedral and semi-dihedral groups. In fact, we compute the Mostar index of these graphs.

Summary: Background: A better understanding of which children are likely to die during acute illness will help clinicians and policy makers target resources at the most vulnerable children. We used machine learning to characterise mortality in the 30-days following admission and the 180-days after discharge from nine hospitals in low and middle-income countries (LMIC). Methods: A cohort of 3101 children aged 2–24 months were recruited at admission to hospital for any acute illness in Bangladesh (Dhaka and Matlab Hospitals), Pakistan (Civil Hospital Karachi), Kenya (Kilifi, Mbagathi, and Migori Hospitals), Uganda (Mulago Hospital), Malawi (Queen Elizabeth Central Hospital), and Burkina Faso (Banfora Hospital) from November 2016 to January 2019. To record mortality, children were observed during their hospitalisation and for 180 days post-discharge. Extreme gradient boosted models of death within 30 days of admission and mortality in the 180 days following discharge were built. Clusters of mortality sharing similar characteristics were identified from the models using Shapley additive values with spectral clustering. Findings: Anthropometric and laboratory parameters were the most influential predictors of both 30-day and post-discharge mortality. No WHO/IMCI syndromes were among the 25 most influential mortality predictors of mortality. For 30-day mortality, two lower-risk clusters (N = 1915, 61%) included children with higher-than-average anthropometry (1% died, 95% CI: 0–2), and children without signs of severe illness (3% died, 95% CI: 2–4%). The two highest risk 30-day mortality clusters (N = 118, 4%) were characterised by high urea and creatinine (70% died, 95% CI: 62–82%); and nutritional oedema with low platelets and reduced consciousness (97% died, 95% CI: 92–100%). For post-discharge mortality risk, two low-risk clusters (N = 1753, 61%) were defined by higher-than-average anthropometry (0% died, 95% CI: 0–1%), and gastroenteritis with lower-than-average anthropometry and without major laboratory abnormalities (0% died, 95% CI: 0–1%). Two highest risk post-discharge clusters (N = 267, 9%) included children leaving against medical advice (30% died, 95% CI: 25–37%), and severely-low anthropometry with signs of illness at discharge (46% died, 95% CI: 34–62%). Interpretation: WHO clinical syndromes are not sufficient at predicting risk. Integrating basic laboratory features such as urea, creatinine, red blood cell, lymphocyte and platelet counts into guidelines may strengthen efforts to identify high-risk children during paediatric hospitalisations. Funding: Bill & Melinda Gates Foundation OPP1131320.