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In cases of brain tumors, some brain cells experience abnormal and rapid growth, leading to the development of tumors. Brain tumors represent a significant source of illness affecting the brain. Magnetic Resonance Imaging (MRI) stands as a well-established and coherent diagnostic method for brain cancer detection. However, the resulting MRI scans produce a vast number of images, which require thorough examination by radiologists. Manual assessment of these images consumes considerable time and may result in inaccuracies in cancer detection. Recently, deep learning has emerged as a reliable tool for decision-making tasks across various domains, including finance, medicine, cybersecurity, agriculture, and forensics. In the context of brain cancer diagnosis, Deep Learning and Machine Learning algorithms applied to MRI data enable rapid prognosis. However, achieving higher accuracy is crucial for providing appropriate treatment to patients and facilitating prompt decision-making by radiologists. To address this, we propose the use of Convolutional Neural Networks (CNN) for brain tumor detection. Our approach utilizes a dataset consisting of two classes: three representing different tumor types and one representing non-tumor samples. We present a model that leverages pre-trained CNNs to categorize brain cancer cases. Additionally, data augmentation techniques are employed to augment the dataset size. The effectiveness of our proposed CNN model is evaluated through various metrics, including validation loss, confusion matrix, and overall loss. The proposed approach employing ResNet50 and EfficientNet demonstrated higher levels of accuracy, precision, and recall in detecting brain tumors., Competing Interests: The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (© 2024 The Author(s).)

Multipliers are essential components within digital signal processing, arithmetic operations, and various computational tasks, making their design and optimization crucial for improving the efficiency and performance of integrated circuits. Among multiplier architectures, Vedic multipliers stand out due to their inherent efficiency and speed, derived from ancient Indian mathematical principles. This study presents a comprehensive analysis and comparison of 4-bit Vedic multiplier designs utilizing Gate Diffusion Input (GDI), Complementary Metal-Oxide-Semiconductor (CMOS), and Transmission Gate (TG) technologies, utilizing different adder architectures such as Ripple Carry Adder (RCA), and Carry Lookahead Adder (CLA), Carry Skip Adder (CSA). The objective is to explore the performance, area, and power consumption characteristics of these multipliers across different technologies and adder implementations. Each multiplier architecture is meticulously designed and optimized to leverage the unique features of the respective technology while adhering to the principles of Vedic mathematics. The designs are evaluated based on parameters such as transistor count, delay, power dissipation, and area. The results demonstrate the effectiveness of GDI technology in terms of in tems of delay, area, power and PDP when compared with other technologies. The 4-bit Vedic multiplier has been designed using 32 nm technology within Tanner EDA software tools., Competing Interests: The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (© 2024 The Author(s).)

Background: Bangladesh has achieved remarkable progress in reducing maternal mortality, yet postpartum deaths remain a significant issue. Emphasis on quality postnatal care (qPNC) is crucial, as increased coverage alone has not sufficiently reduced maternal morbidity and mortality., Methods: This study included data from the Bangladesh Maternal Mortality Survey of 32,106 mothers who delivered within three years prior to the survey. Descriptive statistics were used to report coverage and components of postnatal care stratified by covariates. Log-linear regression models were used to assess the determinants of quality postnatal care among facility and home births., Results: From 2010 to 2016, postnatal care coverage within 48 h of delivery by a qualified provider rose from 23% to 47%. Of the births, 94% were facility births that received timely PNC, contrasted with only 6% for home births. Despite the increased coverage, quality of care remained as low as 1% for home births and 13% for facility births. Key factors affecting qPNC utilization included socio-demographic factors, pregnancy complications, type of birth attendant, delivery method, and financial readiness., Conclusion: Importantly, deliveries assisted by skilled birth attendants correlated with higher quality postnatal care. This study reveals a significant gap between the coverage and quality of postnatal care in rural Bangladesh, especially for home births. It underscores the need for targeted interventions to enhance qPNC.

Background: Neonatal mortality remains unacceptably high in many countries. WHO recommends that all newborns be assessed during the postnatal period and should seek prompt medical care if there is any danger sign. However, in many developing countries, only a small proportion of women receive postnatal care. Also, the quality of care in public health facilities is sub-optimal., Methods: We designed an intervention package that included community health worker-assisted pregnancy and birth surveillance, post-natal visits to assess newborns on the first, third, seventh and twenty-eighth days of birth, referral for facility-based care, and establishing a newborn stabilization unit at the first level referral health facility. We did a quasi-experimental, propensity-score matched, controlled study in the Sylhet region of Bangladesh. We used a cross-sectional survey method at baseline and endline to measure the effect of our intervention. We considered two indicators for the primary outcome-(a) all-cause neonatal mortality rate and (b) case fatality of severe illness. Secondary outcomes were the proportion of neonates with signs and symptoms of severe illness who sought care in a hospital or a medically qualified provider., Results: Our sample size was 9,940 live births (4,257 at baseline, 5,683 at end line). Our intervention was significantly associated with a 39% reduction (aRR = 0.61, 95% CI: 0.40-0.93; p = 0.046) in the risk of neonatal mortality and 45% reduction (aRR = 0.55, 95% CI: 0.35-0.86; p = 0.001) in the risk of case fatality of severe illness among newborns in rural Bangladesh. The intervention significantly increased the care-seeking for severe illness at the first-level referral facility (DID 36.6%; 95% CI % 27.98 to 45.22; p<0.001)., Interpretation: Our integrated community-facility interventions model resulted in early identification of severely sick neonates, early care seeking and improved treatment. The interventions led to a significant reduction in all-cause neonatal mortality and case fatality from severe illness., Competing Interests: The authors have declared that no competing interest exists., (Copyright: © 2023 Huda et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.)

Background: Neonatal deaths contribute to nearly half (47%) of under-five mortality globally and 67% in Bangladesh. Despite high neonatal mortality, care-seeking from qualified providers for newborn danger signs remains low. Identification of direct and indirect factors and their pathways affecting care-seeking will help to design a well-targeted intervention. This study assessed the direct, indirect, and total effect of the predictive factors on neonatal care-seeking in Bangladesh., Materials and Methods: This was a cross-sectional baseline household survey conducted in 14 districts of Bangladesh in 2019 with 17,251 recently delivered women (RDW) with a live birth outcome in the preceding 15 months. We used a two-stage stratified cluster sampling process to select the samples from 14 districts. We investigated the inter-relationship of maternal background characteristics, maternal health utilizations, child/neonate factors, health service delivery-related factors and newborn danger sign knowledge with newborn care-seeking practices and estimated the direct, indirect, and total effects using Generalized Structural Equation Modeling (GSEM) and mediation analysis. p -value = 0.05 was considered statistically significant. The result of the mediation analysis was reported in Log Odds (LOD). The positive LOD (LOD > 0) implies a positive association., Results: Half of the mothers (50.8%) reported a neonatal illness and among them, only 36.5% mothers of sick neonates sought care from qualified providers. Our mediation analysis showed that maternal health utilization factors, i.e., 4 + antenatal care visits (ANC) from a qualified provider (LOD: 0.63, 95% CI: 0.49, 0.78), facility delivery (LOD: 0.74, 95% CI: 0.30, 1.17) and postnatal care (PNC) from a qualified provider (LOD: 0.50, 95% CI: 0.21, 0.78) showed the highest total effect over other factors domains, and therefore, were the most important modifiable predictors for qualified neonatal care-seeking. Other important factors that directly and/or indirectly increased the chance of newborn care-seeking from qualified providers were household wealth (LOD: 0.86, 95% CI: 0.70, 1.02), maternal education (LOD: 0.48, 95% CI: 0.32, 0.63), distance to nearest health facility (LOD: 0.20, 95% CI: 0.10, 0.30), community health worker's (CHWs) home visits during ANC (LOD: 0.24, 95% CI: 0.13, 0.36), neonatal danger sign counseling after delivery (LOD: 0.20, 95% CI: 0.06, 0.34) and women's knowledge of neonatal danger signs (LOD: 0.37, 95% CI: 0.09, 0.64)., Conclusion: The inter-relationship and highest summative effect of ANC, facility delivery, and PNC on newborn care-seeking suggested the maternal care continuum altogether from ANC to facility delivery and PNC to improve care-seeking for the sick newborn. Additionally, referral training for unqualified providers, targeted intervention for poorer households, increasing CHWs home visits and neonatal danger sign counseling at the facility and community should also be considered., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (© 2023 Azad, Billah, Bhui, Ali, Herrera, Graft-Johnson, Garg, Priyanka, Zubair, Rokonuzzaman, Rahman, Meena and Arifeen.)

Background: Skin-to-skin contact (SSC) practice improves newborn survival and child development through preventing hypothermia in newborns, improving early initiation of breastfeeding practice, and strengthening mother-child bonding. Despite having numerous benefits, it is one of the least practiced interventions in low and middle-income countries (1 to 74%). In Bangladesh, the prevalence of SSC was 26% in 2014. In this study, we aimed to estimate the prevalence of SSC in the study districts and identify factors that facilitate or inhibit SSC practice so that context-specific recommendations can be made to advance the use of this intervention., Methods: We used baseline household survey data of USAID's MaMoni MNCSP project conducted in 10 districts of Bangladesh in 2019. Our analysis included 13,695 recently delivered women (RDW) with a live birth outcome. Our primary outcome was the mother's reported practice of SSC. We examined various antepartum, intrapartum, newborn, and sociodemographic factors associated with SSC using a multivariable generalized linear model. Our findings were reported using adjusted Prevalence Risk Ratios (aPRRs) and 95% Confidence Intervals (CIs)., Results: Overall, 28% of RDW reported practicing SSC across the 10 surveyed districts. Our multivariable analysis showed that public facility delivery (aPRR 2.01; 95%CI: 1.80, 2.26), private facility delivery (aPRR 1.23; 95%CI: 1.06, 1.42) and ≥ 4 antenatal care (ANC) visits at least one from a medically trained provider (MTP) (aPRR 1.17; 95%CI: 1.03, 1.26) had a significant positive association with SSC practice. Caesarean section (aPRR 0.64; 95%CI: 0.56, 0.73) had a significant negative association with SSC practice compared to vaginal births. We also found a significant positive association of SSC practice with mothers' who perceived the birth size of their baby to be small, mothers with a higher education level (≥10 years), and mothers from households in the highest wealth quintile., Conclusions: The prevalence of SSC is very low in the surveyed districts of Bangladesh. Considering the factors associated with SSC, relevant stakeholders need to increase their efforts on improving ANC and facility delivery coverages as well as improving SSC practice in the facilities especially after caesarean deliveries. Countries with a high burden of home deliveries, also need to emphasize community-based interventions and increasing coverage of skilled birth attendance for improving this life-saving intervention., (© 2021. The Author(s).)

Study Objective: To evaluate the competency of trained health workers in detecting and managing hypertensive disorders of pregnancy during routine antenatal check-ups (ANCs) at primary care facilities in Bangladesh., Study Design and Settings: Cross-sectional study; conducted in 26 primary care facilities., Outcome Measures: Accurate diagnosis of the hypertensive disorders of pregnancy., Method: In total 1560 ANC consultations provided by primary health workers, known as Family Welfare Visitors (FWVs), were observed using a structured checklist between October 2017 and February 2018. All consultations were reassessed by study physicians for validation., Result: Of the 'true' cases of gestational hypertension (n=32), pre-eclampsia (n=29) and severe pre-eclampsia (n=16), only 3%, 7% and 25%, respectively, were correctly diagnosed by FWVs. Per cent agreement for the diagnosed cases of any hypertensive disorders of pregnancy was 9% and kappa statistics was 0.50 (p value 0.0125). For identification of any hypertensive disorders by FWVs, sensitivity and positive predictive values were 14% and 50%, respectively. There was a moderate positive correlation between the blood pressure measurements taken by FWVs and study physicians. Only 27% of those who had 'some protein' in urine were correctly identified by FWVs. Women diagnosed with any of the hypertensive disorders of pregnancy by FWVs were more likely to be counselled on at least one danger sign of pre-eclampsia (severe headache, blurring of vision and upper abdominal pain) than those without any such diagnosis (41% vs 19%, p value 0.008). All four cases of severe pre-eclampsia diagnosed by FWVs were given a loading dose of intramuscular magnesium sulphate and three among them were referred to a higher facility., Conclusion: The FWVs should be appropriately trained on risk assessment of pregnant women with particular emphasis on accurately assessing the diagnostic criteria of hypertensive disorders of pregnancy and its management., Competing Interests: Competing interests: None declared., (© Author(s) (or their employer(s)) 2021. Re-use permitted under CC BY-NC. No commercial re-use. See rights and permissions. Published by BMJ.)