Prevalence and risk factors of childhood anemia in Nepal: A multilevel analysis

Introduction Anemia is a common problem in children particularly in developing countries and taking steps to tackle it is one of the major public health challenges for Nepal. The objective of this study is to investigate the prevalence of individual, household and community level determinants of childhood anemia in Nepal. Methods Data was taken from a nationally representative sample of 1,942 Nepalese children aged from 6–59 months. The Chi-square test was used to determine the bivariate relationship between the selected variables and childhood anemia and a multilevel logistic regression model with a random intercept at household and community level was used to identify important determinants of this kind of anemia. Results The results showed that 52.6% (95% CI: 49.8%-55.4%) of the children were anemic while 26.6% (95% CI: 24.0%-29.3%) of them were moderate to severe. The prevalence of overall anemia was higher among children aged less than 11 months as well as in underweight children, children of underweight, anemic and uneducated mothers and those in the terrain ecological regions. Multivariable analysis showed that children aged less than 11 months, who were underweight and had anemic mothers were more likely to have moderate or severe anemia. Children in the hilly ecological region were less likely to have it compared to mountain and terrain ecological regions. Children in middle-class families and children of mothers who completed secondary education were more likely to have anemia. Conclusion Nepal is facing a serious public health problem due to the high prevalence of childhood anemia. This adverse situation occurs due to socio-demographic and geographical factors such as age, malnutrition status, mother’s anemia status, socio-economic status and regional variations. Prevention of childhood anemia should be given top priority in Nepal and should be considered as a major public health intervention

Evaluation of low-head drip systems for vegetable farming in Bangladesh

Bangladesh is in the phase of introducing drip irrigation (DI) system in the country. Several types of drip emitters are now becoming available in the market although their performance indices are yet to be matched for local farming practices. This study reports the results of a series of experiments carried out to quantify the hydraulic performances indices of two different types of emitters available in Bangladeshi marketplace. One of the emitters, E1 was designed and manufactured locally, while the other, E2 was imported and highly priced. Followed by the hydraulic experiment, these emitters were also employed in comparative field experiments for tomato and brinjal production at two separate locations in the country. Irrigation schedules were designed based on the local evapotranspiration regime. During the study, both the emitter types exhibited non pressure compensating features as their flow rate increased with pressure. Interestingly, both types of emitters gave a persistent trend of flow rate along the laterals. Standard uniformity indices for DI systems were also calculated, and the DI systems were categorized (good to excellent) based on the established guidelines for microirrigation. Very good performance indices were obtained at 3 m head for emitter E1, and at 2.5 m head for emitter E2. The results of the field experiments also showed that yield, water saving and water productivity of drip irrigated tomato was increased by 12%, 49.48% and 49% respectively when compared with furrow irrigation that is considered as a farmer practice. Similar results were also obtained for brinjal fields irrigated under DI systems. These experiments showed promising comparative benefits of drip technology for vegetable cultivation in water scarce coastal areas of Bangladesh.

Artificial Intelligence and Bio-Inspired Soft Computing-Based Maximum Power Plant Tracking for a Solar Photovoltaic System under Non-Uniform Solar Irradiance Shading Conditions - A Review

Substantial progress in solar photovoltaic (SPV) dissemination in grid-connected and standalone power generation systems has been witnessed during the last two decades. However, weather intermittency has a non-linear characteristic impact on solar photovoltaic output, which can cause considerable loss in the system's overall output. To overcome these inevitable losses and optimize the SPV output, maximum power point tracking (MPPT) is mounted in the middle of the power electronics converters and SPV to achieve the maximum output with better precision from the SPV system under intermittent weather conditions. As MPPT is considered an essential part of the SPV system, up to now, many researchers have developed numerous MPPT techniques, each with unique features. A Google Scholar survey from 2015 - 2021 was performed to scrutinize the number of published review papers in this area. An online search established that on different MPPT techniques, overall, 100 review articles were published; out of these 100, seven reviews on conventional MPPT techniques under shading or partial shading and only four under non-uniform solar irradiance are published. Unfortunately, no dedicated review article has explicitly focused on soft computing MPPT (SC-MPPT) techniques. Therefore, a comprehensive review of articles on SC-MPPT techniques is desirable, in which almost all the familiar SC-MPPT techniques have to be summarized in one piece. This review article concentrates explicitly on soft computing-based MPPT techniques under non-uniform irradiance conditions along with their operating principles, block/flow diagram. It will not only be helpful for academics and researchers to provide a future direction in SC-MPPT optimization research, but also help the field engineers to select the appropriate SC-MPPT for SPV according to system design and environmental conditions

Seismic characterization and modelling of the gas hydrate system in the northern Bay of Bengal, offshore Bangladesh

The offshore Bangladesh includes the northern Bengal fan, where sediment supply from the Ganges and Brahmaputra rivers has resulted in the accumulation of up to 20 km of shallow-marine, fluvio-deltaic and slope sediments that have accumulated during rapid tectonic subsidence since the late Miocene. The high sedimentation rates, along with high organic matter content, make this area favorable for the formation of natural gas from both microbial and thermogenic sources. Here we use multichannel seismic reflection profiles and modelling of the gas hydrate stability zone (GHSZ) to present the first evidence for the occurrence of natural gas hydrate in the offshore Bangladesh. First, we analyze the sediments of the shelf and slope areas, which are characterized by downslope sediment transport features and by the presence, in places, of faults/fractures as well as widely distributed amplitude anomalies and seismic facies that we relate to the presence of gas. A high-amplitude reversed polarity reflection of variable continuity that mimics the seafloor and cross-cut stratigraphy is interpreted as a Bottom Simulating Reflector (BSR). The BSR is observed in several areas that are predominantly located in the E-SE of the study area, in water depths of 1300–1900 m and at depths below seafloor of 250–440 m. Sediments above BSR locations generally show higher seismic interval velocities reaching values of ∼1920–1940 m/s, which are consistent with the presence of gas hydrate in shallow marine sediments. Furthermore, the BSR lies at approximately the same depth as the theoretical base of the gas (methane) hydrate stability zone (BGHSZ), calculated assuming a 3.5 % wt pore water salinity and using existing geothermal gradient and seafloor temperature data from the study region. However, in places, the BSR lies deeper or shallower than the base of the modelled BGHSZ. These discrepancies include areas where faults/fractures and seismic evidence linked to fluid flow from deeper reservoirs reach the GHSZ disrupting its stratigraphic continuity. At these locations, we suggest that faults/fractures act as fluid migration pathways causing localized heat-flow perturbations and/or changes in the hydrate-forming gas composition both likely affecting the depth of the GHSZ. Our results provide the first evidence of the gas hydrate potential in the offshore Bangladesh and should drive future research and data acquisition aiming to understand the composition, saturation and thickness of the gas hydrate-bearing sediments in this region

A Diamond Shaped Multilevel Inverter With Dual Mode of Operation

This study presents a novel multilevel inverter structure that can operate in both switched capacitor and asymmetric DC source modes. In the first mode, it can produce seven-level output voltage employing two switched capacitors and one single DC supply. The five-level output voltage is produced while operating the second mode. The voltage ratio between the input and output voltage for the capacitor mode is 1:3 (triple voltage gain). During the first mode, the capacitor of the inverter is self -balanced whereas the inverter can produce higher voltage output in the DC source mode. The proposed inverter reduces the total standing voltage in both modes of operations as it can generate the output voltage without requiring any additional H-bridge circuit. The feasibility and predominate features of the proposed inverter have been established by comparing with existing topologies in terms of power components count. Results obtained from this study are validated using simulation employing sinusoidal pulse width modulation (SPWM). A hardware prototype has also been developed for further validation

Android malware classification using optimum feature selection and ensemble machine learning

The majority of smartphones on the market run on the Android operating system. Security has been a core concern with this platform since it allows users to install apps from unknown sources. With thousands of apps being produced and launched daily, malware detection using Machine Learning (ML) has attracted significant attention compared to traditional detection techniques. Despite academic and commercial efforts, developing an efficient and reliable method for classifying malware remains challenging. As a result, several datasets for malware analysis have been generated and made available during the past ten years. These datasets may contain static features, such as API calls, intents, and permissions, or dynamic features, like logcat errors, shared memory, and system calls. Dynamic analysis is more resilient when it comes to code obfuscation. Though binary classification and multi-classification have been carried out in recent studies, the latter provides valuable insight into the nature of malware. Because each malware variant operates differently, identifying its category might help prevent it. Using the well-known ensemble ML approach called weighted voting, this study performed dynamic feature analysis for multi-classification. Random Forest, K-nearest Neighbors, Multi-Level Perceptrons, Decision Trees, Support Vector Machines, and Logistic Regression are all studied in this ensemble model. We used a recent dataset named CCCS-CIC-AndMal-2020, which contains an extensive collection of Android applications and malware samples. A well-researched data preparation phase followed by weighted voting based on R2 scores of the ML classifiers presents an accuracy of 95.0% even after excluding 60.2% features, outperforming all recent studies

Prevalence and risk factors of childhood anemia in Nepal: A multilevel analysis.

IntroductionAnemia is a common problem in children particularly in developing countries and taking steps to tackle it is one of the major public health challenges for Nepal. The objective of this study is to investigate the prevalence of individual, household and community level determinants of childhood anemia in Nepal.MethodsData was taken from a nationally representative sample of 1,942 Nepalese children aged from 6-59 months. The Chi-square test was used to determine the bivariate relationship between the selected variables and childhood anemia and a multilevel logistic regression model with a random intercept at household and community level was used to identify important determinants of this kind of anemia.ResultsThe results showed that 52.6% (95% CI: 49.8%-55.4%) of the children were anemic while 26.6% (95% CI: 24.0%-29.3%) of them were moderate to severe. The prevalence of overall anemia was higher among children aged less than 11 months as well as in underweight children, children of underweight, anemic and uneducated mothers and those in the terrain ecological regions. Multivariable analysis showed that children aged less than 11 months, who were underweight and had anemic mothers were more likely to have moderate or severe anemia. Children in the hilly ecological region were less likely to have it compared to mountain and terrain ecological regions. Children in middle-class families and children of mothers who completed secondary education were more likely to have anemia.ConclusionNepal is facing a serious public health problem due to the high prevalence of childhood anemia. This adverse situation occurs due to socio-demographic and geographical factors such as age, malnutrition status, mother's anemia status, socio-economic status and regional variations. Prevention of childhood anemia should be given top priority in Nepal and should be considered as a major public health intervention

CTC together with Shh and Nrf2 are prospective diagnostic markers for HNSCC

Abstract Background The lack of appropriate prognostic biomarkers remains a significant obstacle in the early detection of Head and Neck Squamous Cell Carcinoma (HNSCC), a cancer type with a high mortality rate. Despite considerable advancements in treatment, the success in diagnosing HNSCC at an early stage still needs to be improved. Nuclear factor erythroid 2-related factor 2 (Nrf2) and Sonic Hedgehog (Shh) are overexpressed in various cancers, including HNSCC, and have recently been proposed as possible therapeutic targets for HNSCC. Circulating Tumor Cell (CTC) is a novel concept used for the early detection of cancers, and studies have suggested that a higher CTC count is associated with the aggressiveness of HNSCC and poor survival rates. Therefore, we aimed to establish molecular markers for the early diagnosis of HNSCC considering Shh/Nrf2 overexpression in the background. In addition, the relation between Shh/Nrf2 and CTCs is still unexplored in HNSCC patients. Methods In the present study, we selected a cohort of 151 HNSCC patients and categorized them as CTC positive or negative based on the presence or absence of CTCs in their peripheral blood. Data on demographic and clinicopathological features with the survival of the patients were analyzed to select the patient cohort to study Shh/Nrf2 expression. Shh and Nrf2 expression was measured by qRT-PCR. Results Considering significant demographic [smoking, betel leaf (p-value < 0.0001)] and clinicopathological risk factors [RBC count (p < 0.05), Platelet count (p < 0.05), Neutrophil count (p < 0.005), MCV (p < 0.0001), NLR (p < 0.05), MLR (p < 0.05)], patients who tested positive for CTC also exhibited significant overexpression of Shh/Nrf2 in both blood and tissue compared to CTC-negative patients. A strong association exists between CTCs and tumor grade. Following chemotherapy (a combination of Cisplatin, 5FU, and Paclitaxel), the frequency of CTCs was significantly decreased in patients with HNSCC who had tested positive for CTCs. The Kaplan–Meier plot illustrated that a higher number of CTCs is associated with poorer overall survival (OS) in patients with HNSCC. Conclusions Detecting CTCs, and higher expression of Shh and Nrf2 in HNSCC patients’ blood, can be a promising tool for diagnosing and prognosticating HNSCC