The traditional oil supply chain suffers from various shortcomings regarding crude oil extraction, processing, distribution, environmental pollution and traceability. It offers only forward flow of products with limitations in quality inspection, fraudulent information and monopolistic behavior of supply chain entities. Inclusion of counterfeiting products and opaqueness of the system urge renovation in this sector. Technological advancement can now reshape the infrastructure of the supply chain for the future. Here, a conceptual framework utilizing blockchain and smart contract to monitor the overall oil supply chain is suggested. Blockchain is a used to monitor and support the security building of a decentralized type supply chain. The Internet of Things (IoT) sensors open a broader window to track the process and attributes in real time. A methodology to support reverse traceability for each participant of the supply chain is constructed. Implementation of smart contracts is also shown with detailed analysis. The challenges of implementing such a system are further described and our framework's adaptability in the real world is validated. The paper concludes with future research scope to mitigate the restrictions of data management and maintenance with advanced working prototypes and agile systems achieving greater traceability and transparency. INTRODUCTIONSupply chain management (SCM) in the oil industry holds great importance for its expansion and global market. The value of oil has a significant impact on the world economy. In general, SCM can be coined as the flow of ingredients from production to consumer. It includes several phases from supplying raw materials to end customer including manufacturer, distributor, retailer. For the oil supply chain, these entities are an industry or a company. Moreover, it is a global process as the crude oil is extracted from one place, processed and refined at another, and distributed worldwide. The traditional oil supply chain serves general purposes but cannot comply fully. There are certain limitations in tracking, monitoring, and giving the end customer power to reverse track. It generally goes with the forward flows, that is, the raw materials' flow to final products [1,2]. However, it is equally important to support the reverse flow of product information for any customer. Blockchain and smart contracts, along with Internet of Things (IoT) devices, can change the traditional supply chain for This is an open access article under the terms of the Creative Commons Attribution License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.
Background. Most maternal deaths occur during childbirth and after childbirth. This study was aimed at determining the trends of health facilities during delivery in Bangladesh, as well as their influencing factors. Methods. This study used secondary data from three Bangladesh Multiple Indicator Cluster Surveys (MICSs) in 2006, 2012–13, and 2019. The study’s target sample was those women who gave birth in the last two years of the survey. A two-level logistic regression was applied to determine the effects on health facility delivery separately in these two survey points (MICSs 2012–13 and 2019). Results. The results show that the delivery of health facilities has increased by almost 37.4% in Bangladesh, from 16% in 2006 to 53.4% in 2019. The results of two-level logistic regression show that the total variation in health facility delivery across the community has decreased over recent years. After adding community variables, various individual-level factors such as women with secondary education ( OR = 0.55 in 2012-13 vs. OR =0.60 in 2019), women from middle wealth status ( OR = 0.49 in 2012-13 vs. OR = 0.65 in 2019), religion, and child ever born showed a strong relationship with health facility delivery in both survey years. At the community level, residents showed significant association only in the 2012-13 survey and indicated a 43% ( OR = 1.43 for 2012-13) greater availability of health facilities in urban residences than in rural residences. Using media showed a highly significant connection with health facility delivery in both years as well as an increasing trend over the years in Bangladesh ( OR = 1.19 in 2012-13 vs. OR = 1.38 in 2019). However, division, prenatal care, and skilled services all contribute greatly to increasing the delivery of health facilities in Bangladesh. Conclusions. The results of this study suggest that policymakers need to pay attention to individual and community-level factors, especially women’s education, poverty reduction, and adequate prenatal care provided by well-trained caregivers.
This study focuses on determining the kinetic parameters of pyrolysis and gasification of manure‐derived hydrochar. Hydrochar was first pyrolyzed in Thermogravimetric analyzer at heating rates of 5, 10, and 20°C min−1 with N2 and gasified afterwards with CO2 at 800, 900, and 1000°C for 30, 60, and 90 min. Morphology of the pyrolysis and gasified chars were analyzed with FT‐IR and scanning electron microscope (SEM). Kissinger's method was used to evaluate kinetic parameters for pyrolysis, while Arrhenius method was implemented to evaluate gasification kinetic parameters. Activation energy for pyrolysis and gasification were 211.5 ± 7.7 kJ mol−1 and 270 ± 20 kJ mol−1, respectively. FT‐IR analysis revealed that ‐OH and aliphatic C‐H groups were significantly reduced compare to raw hydrochar during gasification. A decrease of particle size and an increase of amorphous region were observed in SEM analysis, while energy‐dispersive x‐ray spectroscopy analysis revealed an increase in oxygen and carbon contents in gasified char. © 2018 American Institute of Chemical Engineers Environ Prog, 38: 154–162, 2019
Introduction: The coronavirus disease 2019 (COVID-19) has become a public health concern, and behavioral adjustments will minimize its spread worldwide by 80%. The main purpose of this research was to examine the factors associated with concerns about COVID-19 and the future direction of the COVID-19 scenario of Bangladesh. Methods: The binary logistic regression model was performed to assess the impact of COVID-19 concern in Bangladesh. Based on data obtained through online surveys in November 2020 and to predict the next 40 days daily confirmed and deaths of COVID-19 in Bangladesh by applying the Autoregressive Integrated Moving Average (ARIMA) model. Results: The study enrolled 400 respondents, with 253 (63.2%) were male, and 147 (36.8%) were female. The mean age of respondents was 25.13 ± 5.74 years old. Almost 70% of them were found to be concerned about the COVID-19 pandemic. The result showed that respondents’ education level, knowledge regarding COVID-19 transmits, households with aged people, seasonal flu and HD/respiratory problems, and materials used while sneezing/coughing significantly influenced COVID-19 concerns. The analysis predicted that confirmed cases would gradually decrease for the ARIMA model while death cases will be constant for the next 40 days in Bangladesh. Conclusion: The current study suggested that knowledge about COVID-19 spread and education played a vital role in the decline of COVID-19 concerned. A particular program should focus on creating an awareness of the disadvantages of concerns about the COVID-19 pandemic by augmenting knowledge about COVID-19 spread, enhancing Education in Bangladesh.
Tilapia Lake Virus (TiLV) is a disease that affects tilapia fish, causing a high rate of sudden death at any stage of their growth. Unfortunately, there are currently no effective antiviral drugs or vaccines to control the progression of this disease. Researchers have discovered that the CRM1 protein plays a critical function in the development and spreading of animal viruses. By inhibiting CRM1, the virus's spread in commercial fish farms can be suppressed. With this in mind, this study intended to identify potential antiviral drugs from two different tropical mangrove plants from tropical regions: Heritiera fomes and Ceriops candolleana. To identify promising compounds that target the CRM1 protein, a computer-aided drug discovery approach is employed containing molecular docking, ADME (absorption, distribution, metabolism and excretion) analysis, toxicity assessment as well as molecular dynamics (MD) simulation. To estimate binding affinities of all phytochemicals, molecular docking is used and the top three candidate compounds with the highest docking scores were selected, which are CID107876 (-8.3), CID12795736 (-8.2), and CID12303662 (-7.9). We also evaluated the ADME and toxicity properties of these compounds. Finally, molecular dynamics simulation was conducted to analyze the stability of the protein-ligand complex structures and confirm the suitability of these compounds. The computational study demonstrated that the phytochemicals found in H. fomes and C. candolleana could potentially serve as important inhibitors of TiLV, offering practical utility. However, further in vivo investigations are necessary to investigate the effectiveness of these compounds as antiviral drugs against the virus TiLV.
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