Modeling Friction Losses in the Water-Assisted Pipeline Transportation of Heavy Oil

In the lubricated pipe flow (LPF) of heavy oils, a water annulus acts as a lubricant and separates the viscous oil from the pipe wall. The steady state position of the annular water layer is in the high shear region. Significantly, lower pumping energy input is required than if the viscous oil was transported alone. An important challenge to the general application of LPF technology is the lack of a reliable model to predict frictional pressure losses. Although a number of models have been proposed to date, most of these models are highly system specific. Developing a reliable model to predict pressure losses in LPF is an open challenge to the research community. The current chapter introduces the concept of water lubrication in transporting heavy oils and discusses the methodologies available for modeling the pressure drops. It also includes brief descriptions of most important pressure loss models, their limitations, and the scope of future works

AnoMalNet: Outlier Detection based Malaria Cell Image Classification Method Leveraging Deep Autoencoder

Class imbalance is a pervasive issue in the field of disease classification from medical images. It is necessary to balance out the class distribution while training a model for decent results. However, in the case of rare medical diseases, images from affected patients are much harder to come by compared to images from non-affected patients, resulting in unwanted class imbalance. Various processes of tackling class imbalance issues have been explored so far, each having its fair share of drawbacks. In this research, we propose an outlier detection based binary medical image classification technique which can handle even the most extreme case of class imbalance. We have utilized a dataset of malaria parasitized and uninfected cells. An autoencoder model titled AnoMalNet is trained with only the uninfected cell images at the beginning and then used to classify both the affected and non-affected cell images by thresholding a loss value. We have achieved an accuracy, precision, recall, and F1 score of 98.49%, 97.07%, 100%, and 98.52% respectively, performing better than large deep learning models and other published works. As our proposed approach can provide competitive results without needing the disease-positive samples during training, it should prove to be useful in binary disease classification on imbalanced datasets

Computational fluid dynamics study of yield power law drilling fluid flow through smooth-walled fractures.

Presence of natural fractures in sub-surface makes an oil well drilling operation very challenging. As one of the major functions of drilling mud is to maintain bottomhole pressure inside a wellbore to avoid any invasion of unwanted high-pressure influx (oil/gas/water), drilling a well through these fractures can cause severe mud loss into the formation and subsequent danger of compromising the wellbore pressure integrity. The aim of this paper is to carry out a Computational Fluid Dynamics (CFD) study of drilling fluid flow through natural fractures to improve comprehensive understanding of the flow in fractured media. The study was carried out by creating a three-dimensional steady-state CFD model using ANSYS (Fluent). For simplicity and validation purpose, the model defines fracture as an empty space between two circular disks. Moreover, it is considered that single-phase fluid is flowing through fractures. By solving the flow equations in the model, correlations to determine the fracture width and invasion radius have been developed for specific mud rheological properties. Prior to onset of drilling and at the end of lost circulation, similar correlations can be developed by knowing rheological properties of drilling fluid which will be very much helpful to take an instantaneous action during lost circulation, i.e., determining lost circulation material particle size and also be useful in the well development stage to determine the damaged area to be treated

SURVIVAL ASSESSMENT OF PATHOGENIC BACTERIA WITH ANTIBIOTIC RESISTANCE TRAITS FROM FRESH SUMMER ROYAL GRAPE : IN VITRO MICROBIAL CHALLENGE TEST

Table grape act as a popular and mouthwatering fruit supplement over the world. Unhygienic handling of these fruits can possess a diverse threat to public health safety. Moreover, the fruit juice can serve as a nutrient for bacterial growth as well if kept in an unsanitary condition. For this purpose, five imported grape samples (Red Globe, Perlette, Calmeria, Princess and Summer Royal) were tested to assess the presence of pathogenic bacteria and drug-resistant pattern of the isolates. The total bacterial count (TBC) and total fungal count (TFC) showed the presence large amount of bacterial (ranged from 4.4 x 10(4) to 8.1 x 10(7)) and fungal population on the grapes samples, especially on the skin part of the fruits. Several pathogenic isolates, Escherichia coli, Staphylococcus spp., and Pseudomonas spp. were isolated from tested grape samples. However, the presence of Salmonella spp., Shigella spp., Vibrio spp. and Klebsiella spp. were not found from any of the samples. The concerning part of the present study was drug-resistant bacterial strains isolated from supplied Fresh Summer Royal Grape. The most of the isolated bacterial spp. were resistant to all most all of the commonly used antibiotics such as ampicillin (10 mu g), trimethoprim/sulfamethoxazole (25 mu g), tetracycline (30 mu g), ceftriaxone (30 mu g), imipenem (10 mu g), chloramphenicol (30 mu g), azithromycin (15 mu g), novobiocin (30 mu g), vancomycin (30 mu g), penicillin G (10 mu g), ciprofloxacin (5 mu g), neomycin (30 mu g), levofloxacin (5 mu g), kanamycin (30 mu g) and cefiximycin (5 mu g). No grape samples showed any kind of antimicrobial activity against both pathogenic and non-pathogenic bacteria. The survival pattern of inoculated bacterial samples in the grape sample showed a slight decrease in growth in the course of time.Peer reviewe

Bioethanol and biodiesel blended fuels — Feasibility analysis of biofuel feedstocks in Bangladesh

In 2019–2020, Bangladesh imported 5.2 million metric tonnes of petroleum products, worth 2.5 billion USD, and 50% of the imports were consumed by the transportation sector. Having limited natural oil reserves and being heavily dependent on oil imports, the country is vulnerable to shocks in the international oil market, which can jeopardize its consistent economic growth. The Government announced a 5% blending of bioethanol with gasoline in 2017, with broken rice, maize, and molasses as the feedstocks, but sourcing biofuel from food crops can hamper the country's food security. This study explores second and third generation feedstocks e.g., organic plants, seeds, agricultural residues, and waste animal fat or skin that can be collected and processed for the extraction of biofuels. Technical potential of biofuel from the feedstocks is analysed which shows that Bangladesh has a potential to extract 44.4 million metric tonnes of bioethanol in a year from agricultural residues with rice residue having the highest potential (71%). Ground nut and rubber seeds can be major feedstocks for biodiesel production having a potential of 61,000 and 42,000 metric tonnes per year, respectively. Waste chicken skin can be another promising feedstock for the extraction of biodiesel. Biofuels extracted from these non-edible feedstocks and blended with existing transport fuels can lessen Bangladesh's import bills through a sustainable, environmentally friendly manner

Relation of radial artery occlusion after trans-radial percutaneous coronary intervention with the duration of hemostatic compression

Background: Trans-radial percutaneous coronary intervention (PCI) in cardiac procedures accesses coronary arteries through the wrist's radial artery. Post-PCI, hemostatic compression on the radial artery prevents bleeding and aids healing. Radial artery occlusion (RAO), a possible complication, involves blockage of the radial artery. This study aimed to assess the relationship between radial artery occlusion after trans-radial percutaneous coronary intervention with the duration of hemostatic compression. Methods: This prospective observational study was conducted in the Department of Cardiology, National Institute of Cardiovascular Diseases (NICVD), Dhaka, Bangladesh, spanning from September 2018 to August 2019. The study enrolled 140 patients who underwent percutaneous coronary intervention (PCI) through the trans-radial approach (TRA), randomly assigned to two groups: Group I (2-hour hemostatic compression after PCI) and Group II (6-hour hemostatic compression post-procedure). Data analysis was performed using SPSS version 23.0. Results: In this study, early radial artery occlusion was observed in 4.3% of patients in group I and 12.8% in group II (P=0.04), while late radial artery occlusion occurred in 2.8% of patients in group I and 11.4% in group II, with a statistically significant difference (P=0.04). Multivariate logistic regression analysis identified a 6-hour hemostatic compression duration (P=0.01), post-procedural nitroglycerine use (P=0.03), and procedure time (P=0.03) as predictors of radial artery occlusion. Conclusions: Reduced hemostatic compression duration is linked to a decreased occurrence of both early and late radial artery occlusion following trans-radial intervention

Multidrug Resistance in Cancer: Understanding Molecular Mechanisms, Immunoprevention and Therapeutic Approaches

Cancer is one of the leading causes of death worldwide. Several treatments are available for cancer treatment, but many treatment methods are ineffective against multidrug-resistant cancer. Multidrug resistance (MDR) represents a major obstacle to effective therapeutic interventions against cancer. This review describes the known MDR mechanisms in cancer cells and discusses ongoing laboratory approaches and novel therapeutic strategies that aim to inhibit, circumvent, or reverse MDR development in various cancer types. In this review, we discuss both intrinsic and acquired drug resistance, in addition to highlighting hypoxia- and autophagy-mediated drug resistance mechanisms. Several factors, including individual genetic differences, such as mutations, altered epigenetics, enhanced drug efflux, cell death inhibition, and various other molecular and cellular mechanisms, are responsible for the development of resistance against anticancer agents. Drug resistance can also depend on cellular autophagic and hypoxic status. The expression of drug-resistant genes and the regulatory mechanisms that determine drug resistance are also discussed. Methods to circumvent MDR, including immunoprevention, the use of microparticles and nanomedicine might result in better strategies for fighting cancer

SARS-CoV-2 and Rohingya Refugee Camp, Bangladesh: Uncertainty and How the Government Took Over the Situation

Background: Bangladesh hosts more than 800,000 Rohingya refugees from Myanmar. The low health immunity, lifestyle, access to good healthcare services, and social-security cause this population to be at risk of far more direct effects of COVID-19 than the host population. Therefore, evidence-based forecasting of the COVID-19 burden is vital in this regard. In this study, we aimed to forecast the COVID-19 obligation among the Rohingya refugees of Bangladesh to keep up with the disease outbreak’s pace, health needs, and disaster preparedness. Methodology and Findings: To estimate the possible consequences of COVID-19 in the Rohingya camps of Bangladesh, we used a modified Susceptible-Exposed-Infectious-Recovered (SEIR) transmission model. All of the values of different parameters used in this model were from the Bangladesh Government’s database and the relevant emerging literature. We addressed two different scenarios, i.e., the best-fitting model and the good-fitting model with unique consequences of COVID-19. Our best fitting model suggests that there will be reasonable control over the transmission of the COVID-19 disease. At the end of December 2020, there will be only 169 confirmed COVID-19 cases in the Rohingya refugee camps. The average basic reproduction number (R0 role= presentation \u3eR0) has been estimated to be 0.7563. Conclusions: Our analysis suggests that, due to the extensive precautions from the Bangladesh government and other humanitarian organizations, the coronavirus disease will be under control if the maintenance continues like this. However, detailed and pragmatic preparedness should be adopted for the worst scenario