Cloud computing technology has been studied in the context of industry 4.0 as a tool applied to manufacturing services and resources. Such concept is widely known as Cloud Manufacturing. This paper aims at mapping the current state of academic researches on this field, promoting the understanding of trends, references and practical applications in real-life conditions. A bibliometric analysis was conducted using two different databases -Scopus and Web of Sciences -and VOSviewer's text mining tools and techniques. From a sample of 1,420 papers, this study identified the countries which had the largest volume of publications, the main journals related to the subject, the most influent articles, and four clusters by keywords occurrences: (i) "Optimization of manufacturing processes", (ii) "Collaborative networks of manufacturing resources and services", (iii) "Industry 4.0 and cloud computing systems", and (iv) "Data reliability and cyber-security". Finally, this work selected and analyzed the 159 articles with applied case studies, in order to stratify and to understand the most common approaches within the four pre-established categories. This article can contribute to researchers and developers searching for successful practical applications in digitalization of manufacturing chains, as well as to those who are looking for gaps in the still unexplored fields of Cloud Manufacturing. Both the assessment and the categorization of the case studies about Cloud Manufacturing is a differential in this article.

Background Although it is generally accepted that physical activity and flares of low back pain (LBP) are related, evidence for the directionality of this association is mixed. The Flares of Low back pain with Activity Research Study (FLAReS) takes a novel approach to distinguish the short-term effects of specific physical activities on LBP flares from the cumulative effects of such activities, by conducting a longitudinal case-crossover study nested within a cohort study. The first aim is to estimate the short-term effects (≤ 24 h) of specific physical activities on LBP flares among Veterans in primary care in the Veterans Affairs healthcare system. The second aim is to estimate the cumulative effects of specific activities on LBP-related functional limitations at 1-year follow-up. Methods Up to 550 adults of working age (18—65 years) seen for LBP in primary care complete up to 36 “Scheduled” surveys over 1-year follow-up, and also complete unscheduled “Flare Window” surveys after the onset of new flares. Each survey asks about current flares and other factors associated with LBP. Surveys also inquire about activity exposures over the 24 h, and 2 h, prior to the time of survey completion (during non-flare periods) or prior to the time of flare onset (during flares). Other questions evaluate the number, intensity, duration, and/or other characteristics of activity exposures. Other exposures include factors related to mood, lifestyle, exercise, concurrent treatments, and injuries. Some participants wear actigraphy devices for weeks 1–4 of the study. The first aim will examine associations between 10 specific activity categories and participant-reported flares over 1-year follow-up. The second aim will examine associations between the frequency of exposure to 10 activity categories over weeks 1–4 of follow-up and long-term functional limitations at 12 months. All analyses will use a biopsychosocial framework accounting for potential confounders and effect modifiers. Discussion FLAReS will provide empirically derived estimates of both the short-term and cumulative effects of specific physical activities for Veterans with LBP, helping to better understand the role of physical activities in those with LBP. Trial Registration ClinicalTrials.gov NCT04828330, registered April 2, 2021.

Cloud computing technology has been studied in the context of industry 4.0 as a tool applied to manufacturing services and resources. Such concept is widely known as Cloud Manufacturing. This paper aims at mapping the current state of academic researches on this field, promoting the understanding of trends, references and practical applications in real-life conditions. A bibliometric analysis was conducted using two different databases – Scopus and Web of Sciences – and VOSviewer’s text mining tools and techniques. From a sample of 1,420 papers, this study identified the countries which had the largest volume of publications, the main journals related to the subject, the most influent articles, and four clusters by keywords occurrences: (i) “Optimization of manufacturing processes”, (ii) “Collaborative networks of manufacturing resources and services”, (iii) “Industry 4.0 and cloud computing systems”, and (iv) “Data reliability and cyber-security”. Finally, this work selected and analyzed the 159 articles with applied case studies, in order to stratify and to understand the most common approaches within the four pre-established categories. This article can contribute to researchers and developers searching for successful practical applications in digitalization of manufacturing chains, as well as to those who are looking for gaps in the still unexplored fields of Cloud Manufacturing. Both the assessment and the categorization of the case studies about Cloud Manufacturing are the differentials in this article.

Cloud computing technology has been studied in the context of industry 4.0 as a tool applied to manufacturing services and resources. Such concept is widely known as Cloud Manufacturing. This paper aims at mapping the current state of academic researches on this field, promoting the understanding of trends, references and practical applications in real-life conditions. A bibliometric analysis was conducted using two different databases – Scopus and Web of Sciences – and VOSviewer’s text mining tools and techniques. From a sample of 1,420 papers, this study identified the countries which had the largest volume of publications, the main journals related to the subject, the most influent articles, and four clusters by keywords occurrences: (i) “Optimization of manufacturing processes”, (ii) “Collaborative networks of manufacturing resources and services”, (iii) “Industry 4.0 and cloud computing systems”, and (iv) “Data reliability and cyber-security”. Finally, this work selected and analyzed the 159 articles with applied case studies, in order to stratify and to understand the most common approaches within the four pre-established categories. This article can contribute to researchers and developers searching for successful practical applications in digitalization of manufacturing chains, as well as to those who are looking for gaps in the still unexplored fields of Cloud Manufacturing. Both the assessment and the categorization of the case studies about Cloud Manufacturing is a differential in this article.