The purpose of this paper is to investigate the mediating role of online learning motivation (OLM) in the COVID‐19 pandemic situation in Bangladesh by observing and comparing direct lectures (DL), ...instructor–learner interaction (ILI), learner–learner interaction (LLI), and internet self‐efficacy (ISE) as predictors of OLM and online learning satisfaction (OLS). Data were collected from 442 undergraduate and graduate students from more than 35 universities in Bangladesh. To test the hypotheses, the PLS‐SEM approach was applied using SmartPLS 3.0. The study shows a significant mediating role of OLM between the independent variables and learning satisfaction. In addition, DL, ILI, and ISE are shown to be significant predictors of student satisfaction. The findings have a number of valuable implications for education policy makers, universities, instructors, and students. Moreover, the study suggests some new research perspectives to overcome the limitations of this research and to gain precise knowledge on students' learning motivation and satisfaction regarding other online classes for different categories of students (e.g., high school and college, professional, and PhD).
Lay Description
What is already known about this topic
Previous studies have been designed to show direct lectures, interactions, and internet self‐efficacy as predictors of student satisfaction in pre‐ COVID‐19 situations.
Most of the previous scholarly articles found a mixed result; whether a positive or negative relationship between predictors and the dependent variable.
What this paper adds
This study is the first study to explore the mediating effect of online learning motivation on student's satisfaction during the COVID‐19 pandemic from the perspective of a developing country.
It concluded, among othe things, that more attention should be paid to students' and instructors' trainings for online learning.
Implications for practice and/or policy
Developing countries are implementing online education for the first time, so this study contributes to policymakers, faculties, and universities to design appropriate instruction methods, interactions, course, and curriculum design to cope up with the new normal.
This study will contribute concern policymakers to initiate and design necessary training and development programmes to enhance online learning skills and better learning experiences/satisfaction in this pandemic situation.
Alpha-cellulose extracted from corn husks was used as the raw material for the production of food-grade carboxymethyl cellulose (CMC). Preparation of CMC from husk cellulose was carried out by an ...etherification process, using sodium hydroxide and monochloroacetic acid (MCA), with ethanol as the supporting medium. Characterizations of CMC were carried out by analyzing the spectra of FTIR, XRD patterns and SEM photomicrographs. Degree of substitution (DS) was determined with respect to particle size using chemical methods. Solubility, molecular weight and DS of CMC increased with decreased cellulose particle sizes. Microbiological testing of the prepared CMC was done by the pour plate method. Concentrations of heavy metals such as arsenic, lead, cadmium and mercury in the purified CMC were measured by Atomic Absorption Spectroscopy technique and found to be within the WHO/FAO recommended value. A comparative study with CMC available in the international market was conducted. The purity of the prepared CMC was higher, at 99.99% well above the purity of 99.5% for standard CMC. High purity CMC showed a yield 2.4g/g with DS 2.41, water holding capacity 5.11g/g, oil holding capacity 1.59g/g. The obtained product is well suited for pharmaceutical and food additives.
The latest SARS COV2 coronavirus contributes to a pandemic of millions of COVID-19. As there is no defensive immunity in humans and a virus can overcome inborn immune reaction, it can propagate ...unhindered, mostly in tissues contaminated. No unique therapies for COVID-19 contaminated patients are available at this time. The insights learned from previous respiratory viral infection control have given guidance into COVID- 19 therapy. Several complementary treatments have been tentatively introduced in hospital environments such as immune-modulators, antiviral, convalescent plasma transfusions and natural products. In COVID-19 patients, some of these therapies have provided substantial curative benefits. Moreover, numerous studies and clinical trials are being carried out in order to determine the efficacy of current pharmaceutical and natural products to establish possible therapeutic strategies for producing novel COVID-19 medicines. We summarized and defined the modes of mechanism, protection and efficacy on the existing therapeutic strategies for diseases linked to COVID-19 infection.
The structural heterogeneities of fruits and vegetables intensify the complexity to comprehend the interrelated physicochemical changes that occur during drying. Shrinkage of food materials during ...drying is a common physical phenomenon which affects the textural quality and taste of the dried product. The shrinkage of food material depends on many factors including material characteristics, microstructure, mechanical properties, and process conditions. Understanding the effect of these influencing factors on deformation of fruits and vegetables during drying is crucial to obtain better‐quality product. The majority of the previous studies regarding shrinkage are either experimental or empirical; however, such studies cannot provide a realistic understanding of the physical phenomena behind the material shrinkage. In contrast, theoretical modeling can provide better insights into the shrinkage that accompanies simultaneous heat and mass transfer during drying. However, limited studies have been conducted on the theoretical modeling of shrinkage of fruits and vegetables. Therefore, the main aim of this paper is to critically review the existing theoretical shrinkage models and present a framework for a theoretical model for the shrinkage mechanism. This paper also describes the effect of different drying conditions on material shrinkage. Discussions on how the diverse characteristics of fruits and vegetables affect shrinkage propagation is presented. Moreover, a comprehensive review of formulation techniques of shrinking models and their results are also presented. Finally, the challenges in developing a physics‐based shrinkage model are discussed.
Smart electric vehicles (EVs) are attractive because of their clean, zero-emission, low impact on the environment whilst providing a safer and smoother riding experience. To provide the latter, ...driving control requires appropriate systems and algorithms to optimize smart vehicle performance, maximize vehicle stability and protection, minimize accident probability, heighten driving comfort, and optimize transportation costs. Despite advancements in these areas, the realization of optimal smart EVs still requires considerable effort. This paper reviews driving control systems and algorithms for smart EVs, including the advanced driving assistant system, implementation of sensors, vehicle dynamics, and control algorithms. The major contribution of this review is to identify promising work to assist researchers with the most advanced trends in this area for prospective regulations.
The intention of this paper is to investigate the mediating role of work engagement between the four dimensions of organizational justice (OJ) and organizational citizenship behavior (OCB) ...dimensions. The current literature appears to have overlooked the mediating role of work engagement (WE) in the link between justice and organizational citizenship behavior (OCB) in higher education institutions (HEIs). As a result, it appears to be one of the primary studies of its kind to investigate the relationship between OJ dimensions (i.e., procedural, distributive, informational, and interpersonal justice) and OCB dimensions (i.e., OCBI and OCBO) through WE. Data were collected from 121 faculty members from ten private universities operating in Bangladesh. The PLS-SEM was employed to investigate hypotheses. The investigation found OJ is positively connected to WE. Besides, WE is significantly related to OCB. Moreover, WE mediated the relationship between OJ dimensions and OCB dimensions, except for the relationship between PJ and OCB dimensions. The study provides necessary guidelines for the organizations regarding how they might improve citizenship behavior by ensuring justice and engagement in the workplace. Therefore, the application of the findings might ensure better employee outcomes and organizational productivity.
Procedural justice; Organizational citizenship behavior; Informational justice; Work engagement; Interactional justice; University faculty.
Parkinson's Disease (PD), known as Parkinsonism, is a neurodegenerative disease that mainly affects the elderly and is characterized by an extensive and progressive loss of dopaminergic neurons in ...the Substantia Nigra pars compacta (SNpc). Owing to genetic, environmental, and lifestyle changes, the incidence of PD has recently risen among adults. The most widely used PD treatment strategies include the use of dopamine agonists, anticholinergics, and enzyme inhibitors. The aquatic flora and fauna have become the emerging source of novel, structurally diverse bioactive compounds and, at present, the researchers concentrate their efforts on isolating, characterizing, and identifying many secondary metabolites of different nature to treat various disorders, including, neuroprotective marine natural products (MNPs). The bioactive peptides, tannins, carotenoids, alkaloids, polyunsaturated fatty acids (PUFA), and sulfated polysaccharides from the MNP's and their synthetic derivatives have demonstrated important neuroprotective activity in preclinical studies through multiple mechanisms. An extensive literature survey was carried out, and published articles from PubMed, Scifinder, Google Scholar, Web of Science, and Scopus were carefully reviewed to compile information on the MNPs to treat PD. This current review focus on neuroprotective MNPs and their probable biological pathways to treat PD based on their structure and bioactivities reported from 1990 to 2020.
Air pollution is an important issue, especially in megacities across the world. There are emission sources within and also in the regions around these cities, which cause fluctuations in air quality ...based on prevailing meteorological conditions. Short term air quality forecasting is used not to just possibly mitigate forthcoming high air pollution episodes, but also to plan for reduced exposures of residents. In this study, a model using Artificial Neural Networks (ANN) has been developed to forecast pollutant concentration of PM10, PM2.5, NO2, and O3 for the current day and subsequent 4 days in a highly polluted region (32 different locations in Delhi). The model has been trained using meteorological parameters and hourly pollution concentration data for the year 2018 and then used for generating air quality forecasts in real-time. It has also been equipped with Real Time Correction (RTC), to improve the quality of the forecasts by dynamically adjusting the forecasts based on the model performance during the past few days. The model without RTC performs decently, but with RTC the errors are further reduced in forecasted values. The utility of the model has been demonstrated in real-time and model validations were performed for the whole year of 2018 and also independently for 2019. The model shows very good performance for all the pollutants on several evaluation metrics. Coefficient of correlations for various pollutants varies from 0.79–0.88 to 0.49–0.68 between the Day0 to Day4 forecasts. Lowest deterioration of performance was observed for ozone over the four days of forecasts. Use of RTC further improves the model performance for all pollutants.
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•ANN model developed to forecast pollutants in highly polluted region for next 4 days.•Significant improvement in model performance trained with Real Time Correction (RTC).•80% percentile values satisfactorily predicted; extreme high values under-predicted•Ozone predictions are better than for PM.
Aloe vera
is one of the oldest medicinal plants in human history. It exhibits 200 or more different biologically-active substances and has attracted many researchers into its potential applications. ...Researchers have also noted that
Aloe vera
has fewer adverse effects on human health than other alternative herbal medicines.
Aloe vera
leaves contain acemannan which is the key functional component. Acemannan is a long-chain polymer consisting of randomly acetylated linear
d
-mannopyranosyl units and has immune modulation, antibacterial, antifungal and antitumor properties. Due to this functional attribute,
the Aloe vera
plant is known as a “healing plant”. Researchers claim that
Aloe vera
treatment can speed wound healing, offer UV protection, and has anti-oxidant and anti-microbial properties. Historically,
Aloe vera
has been used for a variety of medicinal purposes.
Aloe vera
contains a moisturizing agent for which it is used in cosmetics. Aloe gel is also used in computer memory hardware to reduce electronic waste. Recently
Aloe vera
are extensively used to prepare the different types textile composite which are involved in the field of wound healing, tissue engineering, medical textile, health care textiles, curative garments, cosmetotextiles, UV protective textiles, wearable electronic textiles and so on.
Aloe vera
is used in pre-treatment and printing due to its succulent enzymatic and gummy characteristics.
Aloe
gel also contains a salty substance that allows its use in natural, eco-friendly dyeing. This review considers the many actual and potential applications of
Aloe vera
based textile composite materials for therapeutic and other purposes.
Graphic Abstract
Pay inequity seems to be a major concern at private universities in developing countries. Therefore, this study, drawing on equity and relative deprivation theories, aims to investigate the role of ...pay equity in shaping the organizational commitment of university faculty members in Bangladesh. It used the convenience sampling method with a structured questionnaire. Participants in the study were 254 full-time faculty members, including lecturers, assistant professors, associate professors, and professors from private universities in Bangladesh. A t-test comparing different categories of faculty members showed no noteworthy distinctions between their responses regarding pay equity and organizational commitment. Then, the study employed variance-based structural equation modeling (PLS-SEM) to analyze the data and validate the research model. According to the findings, internal pay equity positively and significantly affects affective (β = 0.327, p < 0.05) and normative commitment (β = 0.579, p < 0.05). Moreover, external pay equity is significantly associated with affective (β = 0.488, p < 0.05) and continuance commitment (β = 0.492, p < 0.05). However, the impact of internal pay equity on continuance commitment (β = 0.150, p = 0.165) was insignificant. Similarly, the relationship between external pay equity and normative commitment (β = 0.170, p = 0.263) was also insignificant. The findings indicate that higher education institutions can stimulate the organizational commitment of academics by promoting pay equity.
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