Future Trends
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2022 ◽  
Vol 157 ◽  
pp. 112045
Antônio Djalma Nunes Ferraz Junior ◽  
Claudia Etchebehere ◽  
Danilo Perecin ◽  
Suani Teixeira ◽  
Jeremy Woods

2022 ◽  
Vol 205 ◽  
pp. 107765
Mahdi Debouza ◽  
Ahmed Al-Durra ◽  
Tarek H.M. EL-Fouly ◽  
Hatem H. Zeineldin

2022 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Syed Abdul Rehman Khan ◽  
Adeel Syed Ali Shah ◽  
Zhang Yu ◽  
Muhammad Tanveer

Purpose The circular economy (CE) is an evolving subject transitioning from conceptualization to empirical testing. Over the past decade, researchers have done an exhaustive study to understand the concept of CE and its realized values both financially and environmentally on organizations that have traditional business models based on linear consumption. For understanding the transitional phenomena completely, the paper aims to review the current and emerging research trends in CE to ascertain future direction. Design/methodology/approach The research was conducted on 91 articles published in the study area during the past decade (2016–2021) in renowned peer-reviewed journals. The criteria set to review literature are based on the following assortment: CE drivers, CE barriers, definitions by different authors, yearly distribution of the publication, research publisher and journals, google citation and methodology used in the selected research articles. Findings The study suggests that researchers from the selected years are keen to understand the transition and its critical factors by bringing forward frameworks and incorporating CE with digital technologies. The digital technology implied are Industrial Technology (IR) 4.0, Big Data, Internet of Things (IoT), Artificial Intelligence, Blockchain and Data Analytics to increase organizational and environmental performance. CE researchers need to use empirical testing in different sectors to understand and bring forward more improvised business models and practices according to the dynamics of the industry. Originality/value The literature review suggests gaps exist to integrate the micro, meso and macro levels to get CE implementation's system-wide benefits. The study has also identified that many CE frameworks available in the literature for implementation must be empirically tested to yield performance results.

2022 ◽  
Vol 2022 ◽  
pp. 1-14
Muhammad Farooq ◽  
Aman Ullah Khan ◽  
Hosny El-Adawy ◽  
Katja Mertens-Scholz ◽  
Iahtasham Khan ◽  

Q fever is a worldwide distributed zoonosis caused by Coxiella burnetii, a Gram-negative bacterium. Despite existence of large amount of research data on the developments related to Q fever, no bibliometric analysis of this subject is available to our knowledge. Bibliometric studies are an essential resource to track scholarly trends and research output in a subject. This study is aimed at reporting a bibliometric analysis of publications related to Q fever (2,840 articles published in the period 1990-2019) retrieved from Science Citation Index Expanded, an online database of Clarivate Analytics Web of Science Core Collection. Data was retrieved using keywords “Q fever” or “Coxiella burnetii” in title, abstract, and author keywords to describe important research indicators such as the kind and language of articles, the most important publications, research journals and categories, authors, institutions, and the countries having the most significant contribution to this subject. Finally, the emerging areas in field of diagnosis, host range, and clinical presentation were identified. Word cluster analysis of research related to Q fever revealed that major focus of research has been on zoonosis, seroprevalence, laboratory diagnosis (mainly using ELISA and PCR), clinical manifestations (abortion and endocarditis), vectors (ticks), and hosts (sheep, goat, and cattle). This bibliometric study is intended to visualize the existing research landscape and future trends in Q fever to assist in future knowledge exchange and research collaborations.

Kennedy Borle ◽  
Nicola Kopac ◽  
Nick Dragojlovic ◽  
Elisabet Rodriguez Llorian ◽  
Jan M. Friedman ◽  

Hiroyuki Noda

Aiming to identify the potentially reduced malaria cases by stagnation of international traffic after the COVID-19 pandemic, a longitudinal analysis of malaria cases as well as entries of Japanese and foreigners was conducted using data from 5 April 1999 to 30 September 2021 in Japan. Multivariable risk ratios were calculated with the Poison regression model as a predictive model of malaria cases by the number of entries for Japanese and foreigners. A generalized regression model was used to examine an association of time trend with entries for Japanese and foreigners using data before 2019, to estimate the potentially reduced number of entries after 2020. The potentially reduced number of malaria cases was estimated by the potentially reduced number of entries for Japanese and foreigners after 2020 using a multivariable Poison regression model. The multivariable risk ratio (95% confidence intervals) of malaria case numbers per 100,000 persons increment of entries per day was 3.41 (1.50–7.77) for Japanese and 1.47 (0.92–2.35) for foreigners. During 2020, a potential reduction of 28 (95% confidence limit: 22–34) malaria cases was estimated, which accounted for 58% (52–63%) of malaria cases in Japan. These finding suggest that the stagnation of international traffic during the COVID-19 pandemic reduced the number of malaria cases in Japan. This model may be helpful for countries without indigenous malaria to predict future trends of imported malaria cases.

Energies ◽  
2022 ◽  
Vol 15 (2) ◽  
pp. 513
Kexue Zhang ◽  
Lei Kang ◽  
Xuexi Chen ◽  
Manchao He ◽  
Chun Zhu ◽  

Intelligent unmanned mining is a key process in coal mine production, which has direct impact on the production safety, coal output, economic benefits and social benefits of coal mine enterprises. With the rapid development and popularization of 5G+ intelligent mines and coal mine intelligent equipment in China, the intelligentization of intelligent unmanned mining has become an important research topic. Especially with the promulgation of some Chinese policies and regulations, intelligent unmanned mining technology has become one of the key technologies of coal mine production. To understand the connotation, status quo and development trends of intelligent unmanned mining, this paper takes the relationship between key technologies and engineering application of intelligent unmanned mining in China as the perspective. It is proposed that the intelligent unmanned mining technology is in the whole process of working face mining. A research structure of unmanned follow-up operation and safe patrol is changing to the mode of intelligent adaptive mining, followed by the basic concepts and characteristics of intelligent unmanned mining. Relevant researches that maybe beneficial to the proposed research content are reviewed in four layers, which include basic theory, key technology, mining mode, and overall design system theory and technology. Finally, the current intelligent unmanned mining mode and future trends in this field in China are summarized.

Dr. Nael Sayedahmed ◽  

In the past few years a shift is seen in the use of Corporate Social Responsibility (CSR) to a Human Social Responsibility (HSR) approach. This is based on the idea that a business has its employees as a resource and not just a beneficiary of the CSR practices of this business, and that employees are the sustained element of CSR as they can impact its objectives and scope with ease due to interaction with management and community at the same time. This research reviews literature related to both areas and the reasons such shift is seen in different business industries, and how HSR is handled by employees at different levels of the organization, as well as the limitations related to HSR.

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