scholarly journals Sewage Systems Surveillance for SARS-CoV-2: Identification of Knowledge Gaps, Emerging Threats, and Future Research Needs

Pathogens ◽  
2021 ◽  
Vol 10 (8) ◽  
pp. 946
Author(s):  
Fatemeh Amereh ◽  
Masoud Negahban-Azar ◽  
Siavash Isazadeh ◽  
Hossein Dabiri ◽  
Najmeh Masihi ◽  
...  
Keyword(s):  
Estimation Method ◽  
Research Direction ◽  
High Rate ◽  
Management Tool ◽  
Future Research ◽  
Sources Of Information ◽  
New Paradigm ◽  
Management Tools ◽  
Novel Coronavirus ◽  
Sampling Procedures

The etiological agent for novel coronavirus (COVID-19, Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2), not only affects the human respiratory system, but also the gastrointestinal tract resulting in gastrointestinal manifestations. The high rate of asymptomatic infected individuals has challenged the estimation of infection spread based on patients’ surveillance, and thus alternative approaches such as wastewater-based epidemiology (WBE) have been proposed. Accordingly, the number of publications on this topic has increased substantially. Thus, this systematic review aimed at providing state-of-the-knowledge on the occurrence and existing methods for sampling procedures, detection/quantification of SARS-CoV-2 in sewage samples, as well as anticipating challenges and providing future research direction to improve the current scientific knowledge. Articles were collected from three scientific databases. Only studies reporting measurements of virus in stool, urine, and wastewater samples were included. Results showed that improving the scientific community’s understanding in these avenues is essential if we are to develop appropriate policy and management tools to address this pandemic pointing particularly towards WBE as a new paradigm in public health. It was also evident that standardized protocols are needed to ensure reproducibility and comparability of outcomes. Areas that require the most improvements are sampling procedures, concentration/enrichment, detection, and quantification of virus in wastewater, as well as positive controls. Results also showed that selecting the most accurate population estimation method for wastewater-based epidemiology studies is still a challenge. While the number of people infected in an area could be approximately estimated based on quantities of virus found in wastewater, these estimates should be cross-checked by other sources of information to draw a more comprehensive conclusion. Finally, wastewater surveillance can be useful as an early warning tool, a management tool, and/or a way for investigating vaccination efficacy and spread of new variants.

The value of nest boxes in the research and management of Australian hollow-using arboreal marsupials

2006 ◽  
Vol 33 (3) ◽  
pp. 161 ◽  
Author(s):  
Georgia L. Beyer ◽  
Ross L. Goldingay
Keyword(s):  
Management Tool ◽  
Future Research ◽  
Species Introduction ◽  
Management Tools ◽  
Nest Box ◽  
Survey Techniques ◽  
Nest Boxes ◽  
Arboreal Marsupials ◽  
Cercartetus Nanus ◽  
Key Aspects

Nest boxes have been recognised as research and management tools for arboreal marsupials in Australia for over 20 years. We review the published literature with the aim of describing the scope of studies conducted in Australia thus far and providing guidance to future research. We recognise three types of application in research: (1) detection of species, (2) study of a species’ ecology, and (3) investigation of box designs preferred by different species. Several species of arboreal marsupial may be detected more readily in nest boxes than by conventional survey techniques, allowing description of key aspects of their ecology; e.g. feathertail glider (Acrobates pygmaeus), eastern pygmy possum (Cercartetus nanus) and brush-tailed phascogale (Phascogale tapoatafa). Identifying the most favoured nest-box design for any species has implications for detection and management uses of nest boxes. More research is needed but preliminary findings suggest that species prefer narrow entrance holes, while height of the nest box above 3 m may be inconsequential. We recognise three types of management application: (1) species introduction, (2) support of populations of endangered species, and (3) strategic placement such as to enhance habitat connectivity. Currently there have been few attempts to use nest boxes to manage arboreal marsupials but further research is needed to realise their potential as a management tool.

scholarly journals Determinants of Academic Staff Turnover Intention in case of Bonga University

2020 ◽  
Vol 8 (1) ◽  
pp. 1-4
Author(s):  
Biniam Getnet ◽  
Amanuel Shibiru
Keyword(s):  
Turnover Intention ◽  
Academic Staff ◽  
Research Direction ◽  
Sampling Procedure ◽  
External Factors ◽  
High Rate ◽  
Primary Data ◽  
Future Research ◽  
Staff Turnover ◽  
Staff Retention

In Academic Staff retention is one of the challenges facing several University in both the developed and developing countries of the world. The purpose of this study is to investigate the determinants of Academic Staff Turnover Intention in case of Bonga University. The study measured determinants and its relation with Turnover intention in the Bonga University. The sample consisted of 157 respondents’ selected based on random sampling procedure. Primary data were collected by using 5-point Likert scale questionnaire. The result of the study showed that determinants; External factors have strong influence on Academic Staff Turnover Intention and weak impact with personal and Internal factors to Turnover Intention at Bonga University. The correlation results indicate that there is a positive correlation between the determinants and Turnover Intention. The results of the regression test showed that External factors have significant on Turnover intention. Thus, the determinants affect turnover intention that have not improve in order to maximizing academic programs and working conditions, working with city administration in order to facilitate better living and recreation centres, solving house problem staff and facilitating good education for children. The prevalence of academic staff intending to leave was found to be moderate and as a result, Before the intention is going to high rate take action in order to fill gaps of external factors the result presented and there should be staff retention mechanisms in place to improve the work environment and remuneration methods to retain senior and skilled academicians. Generally, based on the above findings the researchers were forward the possible recommendation and future research direction.

scholarly journals A systematic and network-based analysis of data-driven quality management in supply chains and proposed future research directions

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Rohit Agrawal ◽  
Vishal Ashok Wankhede ◽  
Anil Kumar ◽  
Sunil Luthra
Keyword(s):  
Network Analysis ◽  
Quality Management ◽  
Supply Chains ◽  
Research Direction ◽  
Strategic Decision ◽  
Data Driven ◽  
Future Research ◽  
Management Tools ◽  
Content Type ◽  
Future Research Directions

PurposeThis work aims to review past and present articles about data-driven quality management (DDQM) in supply chains (SCs). The motive behind the review is to identify associated literature gaps and to provide a future research direction in the field of DDQM in SCs.Design/methodology/approachA systematic literature review was done in the field of DDQM in SCs. SCOPUS database was chosen to collect articles in the selected field and then an SLR methodology has been followed to review the selected articles. The bibliometric and network analysis has also been conducted to analyze the contributions of various authors, countries and institutions in the field of DDQM in SCs. Network analysis was done by using VOS viewer package to analyze collaboration among researchers.FindingsThe findings of the study reveal that the adoption of data-driven technologies and quality management tools can help in strategic decision making. The usage of data-driven technologies such as artificial intelligence and machine learning can significantly enhance the performance of SC operations and network.Originality/valueThe paper discusses the importance of data-driven techniques enabling quality in SC management systems. The linkage between the data-driven techniques and quality management for improving the SC performance was also elaborated in the presented study.

scholarly journals Adoption of Contract Farming and Precautionary Savings to Manage the Catastrophic Risk of Maize Farming: Evidence from Bangladesh

2018 ◽  
Vol 11 (1) ◽  
pp. 29 ◽  
Author(s):  
K Adnan ◽  
Liu Ying ◽  
Swati Sarker ◽  
Muhammad Hafeez ◽  
Amar Razzaq ◽  
...  
Keyword(s):  
Risk Management ◽  
Management Tool ◽  
Precautionary Savings ◽  
Multinomial Probit ◽  
Contract Farming ◽  
Management Tools ◽  
Factors Affecting ◽  
Crop Type ◽  
Major Factors ◽  
Sampling Procedures

Agricultural production faces several types of risk, and risk management tools vary by place, season, and crop type. Most farmers use multiple risk-minimizing tools to reduce the effects of various hazards. However, previous research has overlooked the potential connections between different risk management tool utilization decisions. This study examines farmers’ decisions of adopting risk management tools (contract farming and precautionary savings) and investigates the impacts of various factors on farmers’ risk management decisions by using bivariate and multinomial probit models. The study was carried out in four different agro-ecological regions of Bangladesh with 350 farmers chosen through multistage stratified random sampling procedures. The findings revealed that the farmers’ decisions towards adopting risk management tools are correlated, and the adoption of one risk management tool may induce farmers to adopt other risk management tools at that time. Moreover, the results revealed that age, education, income, and land ownership are the major factors affecting the adoption of risk management tools, and most farmers are risk-averse in nature. Both models provide interpretation and information for the development of a better understanding of the current situation of rural farm households, which may serve as a platform for policymakers who are anticipating appropriate risk management tools for the farmers.

ECONOMIC GROWTH ANALYSIS: A STUDY ON MALAYSIAN MARKET

2019 ◽  
Vol 8 (2) ◽  
Author(s):  
Suhaily Maizan Abdul Manaf ◽  
Shuhada Mohamed Hamidi ◽  
Nur Shafini Mohd Said ◽  
Siti Rapidah Omar Ali ◽  
Nur Dalila Adenan
Keyword(s):  
Economic Growth ◽  
Foreign Direct Investment ◽  
Direct Investment ◽  
Inflation Rate ◽  
Government Expenditure ◽  
Correlation Method ◽  
Research Direction ◽  
Least Square ◽  
Future Research ◽  
Internal And External Factors

Economic performance of a country is mostly determined by the growth and any other internal and external factors. In this study, researchers purposely focused on Malaysian market by examining the relationship between export, inflation rate, government expenditure and foreign direct investment towards economic growth in Malaysia by applying the yearly data of 47 years from 1970 to 2016 using descriptive statistics, regression model and correlation method analysis. By applying Ordinary Least Square (OLS) method, the result suggests that export, government expenditure and foreign direct investment are positively and significantly correlated with the economic growth. However, inflation rate has negative and insignificant relationship with the economic growth. The outcome of the study is suggested to be useful in providing the future research direction towards the economic growth in Malaysia. Keywords: economic growth; export; inflation rate; government expenditure

Co-Enzyme Q10 to Treat Neurological Disorders: Basic Mechanisms, Clinical Outcomes, and Future Research Direction

2013 ◽  
Vol 12 (5) ◽  
pp. 641-664 ◽  
Author(s):  
Mohamed Salama ◽  
Ti-Fei Yuan ◽  
Sergio Machado ◽  
Eric Murillo-Rodriguez ◽  
Jose Vega ◽  
...  
Keyword(s):  
Clinical Outcomes ◽  
Neurological Disorders ◽  
Research Direction ◽  
Future Research ◽  
Future Research Direction

Novel Coronavirus Disease (COVID-19): A Narrative Review Based on Current Status

2020 ◽  
Vol 18 ◽  
Author(s):  
Rina Das ◽  
Dinesh Kumar Mehta ◽  
Meenakshi Dhanawat
Keyword(s):  
Severe Acute Respiratory Syndrome ◽  
Clinical Symptoms ◽  
Virus Disease ◽  
Relevant Literature ◽  
World Health ◽  
Current Status ◽  
Future Research ◽  
Treatment And Prevention ◽  
First Case ◽  
Novel Coronavirus

Abstract:: A novel virus, severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), appeared and expanded globally by the end of year in 2019 from Wuhan, China, causing severe acute respiratory syndrome. During its initial stage, the disease was called the novel coronavirus (2019-nCoV). It was named COVID-19 by the World Health Organization (WHO) on 11 February 2020. The WHO declared worldwide the SARS-CoV-2 virus a pandemic on March 2020. On 30 January 2020 the first case of Corona Virus Disease 2019 (COVID-19) was reported in India. Now in current situation the virus is floating in almost every part of the province and rest of the globe. -: On the basis of novel published evidences, we efficiently summarized the reported work with reference to COVID-19 epidemiology, pathogen, clinical symptoms, treatment and prevention. Using several worldwide electronic scientific databases such as Pubmed, Medline, Embase, Science direct, Scopus, etc were utilized for extensive investigation of relevant literature. -: This review is written in the hope of encouraging the people successfully with the key learning points from the underway efforts to perceive and manage SARS-CoV-2, suggesting sailent points for expanding future research.

scholarly journals Structural and Functional Remodeling of Mitochondria in Cardiac Diseases

2021 ◽  
Vol 22 (8) ◽  
pp. 4167
Author(s):  
Xiaonan Sun ◽  
Jalen Alford ◽  
Hongyu Qiu
Keyword(s):  
Regulatory Network ◽  
Molecular Basis ◽  
Therapeutic Potential ◽  
Research Direction ◽  
Future Research ◽  
Cardiac Diseases ◽  
Functional Remodeling ◽  
Underlying Mechanisms ◽  
Mitochondrial Remodeling ◽  
Normal Cellular Function

Mitochondria undergo structural and functional remodeling to meet the cell demand in response to the intracellular and extracellular stimulations, playing an essential role in maintaining normal cellular function. Merging evidence demonstrated that dysregulation of mitochondrial remodeling is a fundamental driving force of complex human diseases, highlighting its crucial pathophysiological roles and therapeutic potential. In this review, we outlined the progress of the molecular basis of mitochondrial structural and functional remodeling and their regulatory network. In particular, we summarized the latest evidence of the fundamental association of impaired mitochondrial remodeling in developing diverse cardiac diseases and the underlying mechanisms. We also explored the therapeutic potential related to mitochondrial remodeling and future research direction. This updated information would improve our knowledge of mitochondrial biology and cardiac diseases’ pathogenesis, which would inspire new potential strategies for treating these diseases by targeting mitochondria remodeling.

scholarly journals Federated Quantum Machine Learning

Entropy ◽  
2021 ◽  
Vol 23 (4) ◽  
pp. 460
Author(s):  
Samuel Yen-Chi Chen ◽  
Shinjae Yoo
Keyword(s):  
Machine Learning ◽  
Data Privacy ◽  
Research Direction ◽  
Future Research ◽  
Quantum Computers ◽  
Training Time ◽  
Quantum Neural Network ◽  
Distributed Training ◽  
Machine Learning Model ◽  
Quantum Machine Learning

Distributed training across several quantum computers could significantly improve the training time and if we could share the learned model, not the data, it could potentially improve the data privacy as the training would happen where the data is located. One of the potential schemes to achieve this property is the federated learning (FL), which consists of several clients or local nodes learning on their own data and a central node to aggregate the models collected from those local nodes. However, to the best of our knowledge, no work has been done in quantum machine learning (QML) in federation setting yet. In this work, we present the federated training on hybrid quantum-classical machine learning models although our framework could be generalized to pure quantum machine learning model. Specifically, we consider the quantum neural network (QNN) coupled with classical pre-trained convolutional model. Our distributed federated learning scheme demonstrated almost the same level of trained model accuracies and yet significantly faster distributed training. It demonstrates a promising future research direction for scaling and privacy aspects.

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