Business analytics in industry 4.0: a systematic review

Recently, the term “Industry 4.0” has emerged to characterize several Information Technology and Communication (ICT) adoptions in production processes (e.g., Internet-of-Things, implementation of digital production support information technologies). Business Analytics is often used within the Industry 4.0, thus incorporating its data intelligence (e.g., statistical analysis, predictive modelling, optimization) expert system component. In this paper, we perform a Systematic Literature Review (SLR) on the usage of Business Analytics within the Industry 4.0 concept, covering a selection of 169 papers obtained from six major scientific publication sources from 2010 to March 2020. The selected papers were first classified in three major types, namely, Practical Application, Reviews and Framework Proposal. Then, we analysed with more detail the practical application studies which were further divided into three main categories of the Gartner analytical maturity model, Descriptive Analytics, Predictive Analytics and Prescriptive Analytics. In particular, we characterized the distinct analytics studies in terms of the industry application and data context used, impact (in terms of their Technology Readiness Level) and selected data modelling method. Our SLR analysis provides a mapping of how data-based Industry 4.0 expert systems are currently used, disclosing also research gaps and future research opportunities.The work of P. Cortez was supported by FCT - Fundação para a Ciência e Tecnologia within the R&D Units Project Scope: UIDB/00319/2020. We would like to thank to the three anonymous reviewers for their helpful suggestions

Chromosomal aberrations detected by comparative genomic hybridization technique (CGH) in invasive ductal carcinoma of breast

Background: Nonlethal genetic damage is the basis for carcinogenesis. As various gene aberrations accumulate, malignant tumors are formed, regardless of whether the genetic damage is subtle or large enough to be distinguished in a karyotype. The study of chromosomal changes in tumor cells is important in the identification of oncogenes and tumor suppressor genes by molecular cloning of genes in the vicinity of chromosomal aberrations. Furthermore, some specific aberrations can be of great diagnostic and prognostic value. Comparative genomic hybridization (CGH) is used to screen the entire genome for the detection and/or location chromosomal copy number changes.Methods: In this study, frozen sections of 20 primary breast tumors diagnosed as invasive ductal carcinoma from the Cancer Institute of Imam Khomeini Hospital, Tehran, Iran, were studied by CGH to detect chromosomal aberrations. We compared histopathological and immunohistochemical findings.Results: Hybridization in four of the cases was not optimal for CGH analysis and they were excluded from the study. DNA copy number changes were detected in 12 (75%) of the remaining 16 cases. Twenty-one instances of chromosomal aberrations were detected in total, including: +1q, +17q, +8q, +20q, -13q, -11q, -22q, -1p, -16q, -8p. The most frequent were +1q, +17q, +8q, -13q, similar to other studies. In three cases, we detected -13q, which is associated with axillary lymph node metastasis and was reported in one previous study. The mean numbers of chromosomal aberrations per tumor in metastatic and nonmetastatic tumors was 1.5 and 1, respectively. No other association between detected chromosomal aberrations and histopathological and immunohistochemical findings were seen.Conclusion: Since intermediately to widely invasive carcinomas are more likely to have chromosomal aberrations, CGH can be a valuable prognostic tool. Furthermore, CGH can be used to detect targeting molecules within novel amplifications which holds the potential for a new therapeutic approach for intractable cancer."n&nbsp