Isolation, Characterization, and Identification of Biological Control Agent for Potato Soft Rot in Bangladesh

A total of 91 isolates of probable antagonistic bacteria of potato soft rot bacterium Erwinia carotovora subsp. carotovora (Ecc) were extracted from rhizospheres and endophytes of various crop plants, different soil varieties, and atmospheres in the potato farming areas of Bangladesh. Antibacterial activity of the isolated probable antagonistic bacteria was tested in vitro against the previously identified most common and most virulent soft rot causing bacterial strain Ecc P-138. Only two isolates E-45 and E-65 significantly inhibited the in vitro growth of Ecc P-138. Physiological, biochemical, and carbon source utilization tests identified isolate E-65 as a member of the genus Bacillus and the isolate E-45 as Lactobacillus sp. The stronger antagonistic activity against Ecc P-138 was found in E-65 in vitro screening and storage potatoes. E-65 reduced the soft rot infection to 22-week storage potatoes of different varieties by 32.5–62.5% in model experiment, demonstrating its strong potential to be used as an effective biological control agent for the major pectolytic bacteria Ecc. The highest (62.5%) antagonistic effect of E-65 was observed in the Granola and the lowest (32.7%) of that was found in the Cardinal varieties of the Bangladeshi potatoes. The findings suggest that isolate E-65 could be exploited as a biocontrol agent for potato tubers

Genetic improvement of Purslane (Portulaca oleracea L.) and its future prospects

Common purslane (Portulaca oleracea), also known as pigweed, fatweed, pusle, and little hogweed, is an annual succulent herb in the family Portulacaceae that is found in most corners of the globe. From the ancient ages purslane has been treated as a major weed of vegetables as well as other crops. However, worldwide researchers and nutritionists have studied this plant as a potential vegetable crop for humans as well as animals. Purslane is a nutritious vegetable with high antioxidant properties and recently has been recognized as the richest source of α-linolenic acid, essential omega-3 and 6 fatty acids, ascorbic acid, glutathione, α-tocopherol and β-carotene. The lack of vegetable sources of ω-3 fatty acids has resulted in a growing level of attention to introduce purslane as a new cultivated vegetable. In the rapid-revolutionizing worldwide atmosphere, the ability to produce improved planting material appropriate to diverse and varying rising conditions is a supreme precedence. Though various published reports on morphological, physiological, nutritional and medicinal aspects of purslane are available, research on the genetic improvement of this promising vegetable crop are scant. Now it is necessary to conduct research for the genetic improvement of this plant. Genetic improvement of purslane is also a real scientific challenge. Scientific modernization of conventional breeding with the advent of advance biotechnological and molecular approaches such as tissue culture, protoplast fusion, genetic transformation, somatic hybridization, marker-assisted selection, qualitative trait locus mapping, genomics, informatics and various statistical representation have opened up new opportunities of revising the relationship between genetic diversity, agronomic performance and response to breeding for varietal improvement. This review is an attempt to amalgamate the assorted scientific information on purslane propagation, cultivation, varietal improvement, nutrient analyses, medicinal uses and to describe prospective research especially for genetic improvement of this crop

Modelling and simulation of 1.2 MWp tenaga suria brunei photovoltaic power plant

The energy demand in Brunei Darussalam will increase in near future. The renewable energy is one of the alternative energy sources that could satisfy the increasing energy demands. Brunei Darussalam depends heavily on fossil fuel to generate its electricity needs. Fossil fuels are depleted and the main source of pollution. Photovoltaic (PV) systems generate electricity directly from the sunlight without any emission of global warming gases, and the fuel is free. In order to optimize the performance of PV systems their operation should be well understood. In this paper, we present the modelling of a real 1.2 MWp photovoltaic system. The PV power plant is tied to the grid. The PV array, the DC/DC converter and the DC/AC inverter are modelled and implemented in Matlab/Simulink. The controller of the gridconnected inverter is modelled to achieve constant voltage, constant frequency and to be synchronized with the grid. The system is simulated under Brunei weather conditions and the results are acceptable

A Novel Non-Invasive Estimation of Respiration Rate from Motion Corrupted Photoplethysmograph Signal Using Machine Learning Model

Respiratory ailments such as asthma, chronic obstructive pulmonary disease (COPD), pneumonia, and lung cancer are life-Threatening. Respiration rate (RR) is a vital indicator of the wellness of a patient. Continuous monitoring of RR can provide early indication and thereby save lives. However, a real-Time continuous RR monitoring facility is only available at the intensive care unit (ICU) due to the size and cost of the equipment. Recent researches have proposed Photoplethysmogram (PPG) and/ Electrocardiogram (ECG) signals for RR estimation however, the usage of ECG is limited due to the unavailability of it in wearable devices. Due to the advent of wearable smartwatches with built-in PPG sensors, it is now being considered for continuous monitoring of RR. This paper describes a novel approach for RR estimation using motion artifact correction and machine learning (ML) models with the PPG signal features. Feature selection algorithms were used to reduce computational complexity and the chance of overfitting. The best ML model and the best feature selection algorithm combination were fine-Tuned to optimize its performance using hyperparameter optimization. Gaussian Process Regression (GPR) with Fit a Gaussian process regression model (Fitrgp) feature selection algorithm outperformed all other combinations and exhibits a root mean squared error (RMSE), mean absolute error (MAE), and two-standard deviation (2SD) of 2.63, 1.97, and 5.25 breaths per minute, respectively. Patients would be able to track RR at a lower cost and with less inconvenience if RR can be extracted efficiently and reliably from the PPG signal. 2013 IEEE.Corresponding authors: Muhammad E. H. Chowdhury ([email protected]), Mamun Bin Ibne Reaz ([email protected]), and Md. Shafayet Hossain ([email protected]) This work was supported in part by the Qatar National Research under Grant NPRP12S-0227-190164, and in part by the International Research Collaboration Co-Fund (IRCC) through Qatar University under Grant IRCC-2021-001. The statements made herein are solely the responsibility of the authors.Scopu

Tetraplex PCR assay involving double gene-sites discriminates beef and buffalo in Malaysian meat curry and burger products

Replacement of beef by buffalo and vice versa is frequent in global markets, but their authentication is challenging in processed foods due to the fragmentation of most biomarkers including DNA. The shortening of target sequences through use of two target sites might ameliorate assay reliability because it is highly unlikely that both targets will be lost during food processing. For the first time, we report a tetraplex polymerase chain reaction (PCR) assay targeting two different DNA regions in beef (106 and 120-bp) and buffalo (90 and 138-bp) mitochondrial genes to discriminate beef and buffalo in processed foods. All targets were stable under boiling, autoclaving and microwave cooking conditions. A survey in Malaysian markets revealed 71% beef curries contained buffalo but there was no buffalo in beef burgers. The assay detected down to 0.01 ng DNA and 1% meat in admixed and burger products

Modelling and simulation of 1.2 MWpTenaga suria brunei photovoltaic power plant

The energy demand in Brunei Darussalam will increase in near future. The renewable energy is one of the alternative energy sources that could satisfy the increasing energy demands. Brunei Darussalam depends heavily on fossil fuel to generate its electricity needs. Fossil fuels are depleted and the main source of pollution. Photovoltaic (PV) systems generate electricity directly from the sunlight without any emission of global warming gases, and the fuel is free. In order to optimize the performance of PV systems their operation should be well understood. In this paper, we present the modelling of a real 1.2 MWp photovoltaic system. The PV power plant is tied to the grid. The PV array, the DC/DC converter and the DC/AC inverter are modelled and implemented in Matlab/Simulink. The controller of the grid-connected inverter is modelled to achieve constant voltage, constant frequency and to be synchronized with the grid. The system is simulated under Brunei weather conditions and the results are acceptable. © 2019 Mattingley Publishing. All rights reserved

Mapping local patterns of childhood overweight and wasting in low- and middle-income countries between 2000 and 2017

A double burden of malnutrition occurs when individuals, household members or communities experience both undernutrition and overweight. Here, we show geospatial estimates of overweight and wasting prevalence among children under 5 years of age in 105 low- and middle-income countries (LMICs) from 2000 to 2017 and aggregate these to policy-relevant administrative units. Wasting decreased overall across LMICs between 2000 and 2017, from 8.4% (62.3 (55.1–70.8) million) to 6.4% (58.3 (47.6–70.7) million), but is predicted to remain above the World Health Organization’s Global Nutrition Target of <5% in over half of LMICs by 2025. Prevalence of overweight increased from 5.2% (30 (22.8–38.5) million) in 2000 to 6.0% (55.5 (44.8–67.9) million) children aged under 5 years in 2017. Areas most affected by double burden of malnutrition were located in Indonesia, Thailand, southeastern China, Botswana, Cameroon and central Nigeria. Our estimates provide a new perspective to researchers, policy makers and public health agencies in their efforts to address this global childhood syndemic

Measuring universal health coverage based on an index of effective coverage of health services in 204 countries and territories, 1990–2019 : A systematic analysis for the Global Burden of Disease Study 2019

Background Achieving universal health coverage (UHC) involves all people receiving the health services they need, of high quality, without experiencing financial hardship. Making progress towards UHC is a policy priority for both countries and global institutions, as highlighted by the agenda of the UN Sustainable Development Goals (SDGs) and WHO's Thirteenth General Programme of Work (GPW13). Measuring effective coverage at the health-system level is important for understanding whether health services are aligned with countries' health profiles and are of sufficient quality to produce health gains for populations of all ages. Methods Based on the Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2019, we assessed UHC effective coverage for 204 countries and territories from 1990 to 2019. Drawing from a measurement framework developed through WHO's GPW13 consultation, we mapped 23 effective coverage indicators to a matrix representing health service types (eg, promotion, prevention, and treatment) and five population-age groups spanning from reproductive and newborn to older adults (≥65 years). Effective coverage indicators were based on intervention coverage or outcome-based measures such as mortality-to-incidence ratios to approximate access to quality care; outcome-based measures were transformed to values on a scale of 0–100 based on the 2·5th and 97·5th percentile of location-year values. We constructed the UHC effective coverage index by weighting each effective coverage indicator relative to its associated potential health gains, as measured by disability-adjusted life-years for each location-year and population-age group. For three tests of validity (content, known-groups, and convergent), UHC effective coverage index performance was generally better than that of other UHC service coverage indices from WHO (ie, the current metric for SDG indicator 3.8.1 on UHC service coverage), the World Bank, and GBD 2017. We quantified frontiers of UHC effective coverage performance on the basis of pooled health spending per capita, representing UHC effective coverage index levels achieved in 2019 relative to country-level government health spending, prepaid private expenditures, and development assistance for health. To assess current trajectories towards the GPW13 UHC billion target—1 billion more people benefiting from UHC by 2023—we estimated additional population equivalents with UHC effective coverage from 2018 to 2023. Findings Globally, performance on the UHC effective coverage index improved from 45·8 (95% uncertainty interval 44·2–47·5) in 1990 to 60·3 (58·7–61·9) in 2019, yet country-level UHC effective coverage in 2019 still spanned from 95 or higher in Japan and Iceland to lower than 25 in Somalia and the Central African Republic. Since 2010, sub-Saharan Africa showed accelerated gains on the UHC effective coverage index (at an average increase of 2·6% [1·9–3·3] per year up to 2019); by contrast, most other GBD super-regions had slowed rates of progress in 2010–2019 relative to 1990–2010. Many countries showed lagging performance on effective coverage indicators for non-communicable diseases relative to those for communicable diseases and maternal and child health, despite non-communicable diseases accounting for a greater proportion of potential health gains in 2019, suggesting that many health systems are not keeping pace with the rising non-communicable disease burden and associated population health needs. In 2019, the UHC effective coverage index was associated with pooled health spending per capita (r=0·79), although countries across the development spectrum had much lower UHC effective coverage than is potentially achievable relative to their health spending. Under maximum efficiency of translating health spending into UHC effective coverage performance, countries would need to reach $1398 pooled health spending per capita (US$ adjusted for purchasing power parity) in order to achieve 80 on the UHC effective coverage index. From 2018 to 2023, an estimated 388·9 million (358·6–421·3) more population equivalents would have UHC effective coverage, falling well short of the GPW13 target of 1 billion more people benefiting from UHC during this time. Current projections point to an estimated 3·1 billion (3·0–3·2) population equivalents still lacking UHC effective coverage in 2023, with nearly a third (968·1 million [903·5–1040·3]) residing in south Asia. Interpretation The present study demonstrates the utility of measuring effective coverage and its role in supporting improved health outcomes for all people—the ultimate goal of UHC and its achievement. Global ambitions to accelerate progress on UHC service coverage are increasingly unlikely unless concerted action on non-communicable diseases occurs and countries can better translate health spending into improved performance. Focusing on effective coverage and accounting for the world's evolving health needs lays the groundwork for better understanding how close—or how far—all populations are in benefiting from UHC

Global burden of 369 diseases and injuries in 204 countries and territories, 1990–2019: a systematic analysis for the Global Burden of Disease Study 2019

Background: In an era of shifting global agendas and expanded emphasis on non-communicable diseases and injuries along with communicable diseases, sound evidence on trends by cause at the national level is essential. The Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) provides a systematic scientific assessment of published, publicly available, and contributed data on incidence, prevalence, and mortality for a mutually exclusive and collectively exhaustive list of diseases and injuries. Methods: GBD estimates incidence, prevalence, mortality, years of life lost (YLLs), years lived with disability (YLDs), and disability-adjusted life-years (DALYs) due to 369 diseases and injuries, for two sexes, and for 204 countries and territories. Input data were extracted from censuses, household surveys, civil registration and vital statistics, disease registries, health service use, air pollution monitors, satellite imaging, disease notifications, and other sources. Cause-specific death rates and cause fractions were calculated using the Cause of Death Ensemble model and spatiotemporal Gaussian process regression. Cause-specific deaths were adjusted to match the total all-cause deaths calculated as part of the GBD population, fertility, and mortality estimates. Deaths were multiplied by standard life expectancy at each age to calculate YLLs. A Bayesian meta-regression modelling tool, DisMod-MR 2.1, was used to ensure consistency between incidence, prevalence, remission, excess mortality, and cause-specific mortality for most causes. Prevalence estimates were multiplied by disability weights for mutually exclusive sequelae of diseases and injuries to calculate YLDs. We considered results in the context of the Socio-demographic Index (SDI), a composite indicator of income per capita, years of schooling, and fertility rate in females younger than 25 years. Uncertainty intervals (UIs) were generated for every metric using the 25th and 975th ordered 1000 draw values of the posterior distribution. Findings: Global health has steadily improved over the past 30 years as measured by age-standardised DALY rates. After taking into account population growth and ageing, the absolute number of DALYs has remained stable. Since 2010, the pace of decline in global age-standardised DALY rates has accelerated in age groups younger than 50 years compared with the 1990–2010 time period, with the greatest annualised rate of decline occurring in the 0–9-year age group. Six infectious diseases were among the top ten causes of DALYs in children younger than 10 years in 2019: lower respiratory infections (ranked second), diarrhoeal diseases (third), malaria (fifth), meningitis (sixth), whooping cough (ninth), and sexually transmitted infections (which, in this age group, is fully accounted for by congenital syphilis; ranked tenth). In adolescents aged 10–24 years, three injury causes were among the top causes of DALYs: road injuries (ranked first), self-harm (third), and interpersonal violence (fifth). Five of the causes that were in the top ten for ages 10–24 years were also in the top ten in the 25–49-year age group: road injuries (ranked first), HIV/AIDS (second), low back pain (fourth), headache disorders (fifth), and depressive disorders (sixth). In 2019, ischaemic heart disease and stroke were the top-ranked causes of DALYs in both the 50–74-year and 75-years-and-older age groups. Since 1990, there has been a marked shift towards a greater proportion of burden due to YLDs from non-communicable diseases and injuries. In 2019, there were 11 countries where non-communicable disease and injury YLDs constituted more than half of all disease burden. Decreases in age-standardised DALY rates have accelerated over the past decade in countries at the lower end of the SDI range, while improvements have started to stagnate or even reverse in countries with higher SDI. Interpretation: As disability becomes an increasingly large component of disease burden and a larger component of health expenditure, greater research and developm nt investment is needed to identify new, more effective intervention strategies. With a rapidly ageing global population, the demands on health services to deal with disabling outcomes, which increase with age, will require policy makers to anticipate these changes. The mix of universal and more geographically specific influences on health reinforces the need for regular reporting on population health in detail and by underlying cause to help decision makers to identify success stories of disease control to emulate, as well as opportunities to improve. Funding: Bill & Melinda Gates Foundation. © 2020 The Author(s). Published by Elsevier Ltd. This is an Open Access article under the CC BY 4.0 licens