Adaptation and innovation are extremely important to the manufacturing industry. This development should lead to sustainable manufacturing using new technologies. To promote sustainability, smart production requires global perspectives of smart production application technology. In this regard, thanks to intensive research efforts in the field of artificial intelligence (AI), a number of AI-based techniques, such as machine learning, have already been established in the industry to achieve sustainable manufacturing. Thus, the aim of the present research was to analyze, systematically, the scientific literature relating to the application of artificial intelligence and machine learning (ML) in industry. In fact, with the introduction of the Industry 4.0, artificial intelligence and machine learning are considered the driving force of smart factory revolution. The purpose of this review was to classify the literature, including publication year, authors, scientific sector, country, institution, and keywords. The analysis was done using the Web of Science and SCOPUS database. Furthermore, UCINET and NVivo 12 software were used to complete them. A literature review on ML and AI empirical studies published in the last century was carried out to highlight the evolution of the topic before and after Industry 4.0 introduction, from 1999 to now. Eighty-two articles were reviewed and classified. A first interesting result is the greater number of works published by the USA and the increasing interest after the birth of Industry 4.0.

Blockchain is a disruptive technology that is revolutionizing information technology and represents a change of cultural paradigm for the way in which information is shared. Companies are rushing to understand how they can use blockchain distributed ledger technology to innovate processes, products and transactions. In a globalized world where environmental sustainability is a critical success factor, what is the role of the blockchain? By using a systematic review approach and the Preferred Reporting Items for Systematic Review and Meta‐Analyses (PRISMA) protocol, this study attempts to identify whether and how blockchain technology is considered able to affect environmental sustainability. Findings from 195 studies from 2015 to 2020 were analysed after the search protocol was applied. The results indicate that blockchain technology could contribute to environmentally sustainable development goals (SDGs) from different points of view, such as supporting the realization of a sustainable supply chain, improving energy efficiency and promoting the creation of secure and reliable smart cities. Furthermore, the investigation highlights the sectors where to focus research investments, providing a way to reward sustainable behaviour and increasing environmental sustainability. On the other hand, blockchain has no negligible negative effects on the environment that need to be considered before adoption.

Cancer radiotherapy (RT) may induce what is referred to as the “abscopal effect,” a regression of non-irradiated metastatic lesions distant from the primary tumor site directly subject to irradiati...

Concrete production causes significant environmental damage during its entire life cycle due to the large consumption of natural aggregate. The aim of this research was to use the Life Cycle Assessment (LCA) methodology to conduct a comparative analysis of four different concrete mixtures, i.e., construction and demolition waste (CDW), incinerator ashes, marble sludge, and blast furnace slag. The LCA study was implemented in the Campania Region of Italy. The main contribution of the study was that it proposed the use of “green” recycled aggregates in concrete production in order to assess the reduction of potential adverse impacts, from both environmental and energy perspectives. SimaPro^© software was used to conduct the analysis. The main results of the research showed that the recycled aggregates that were analyzed were preferable to traditional concrete. In particular, the recycled aggregate that had the least adverse impact on the environment was blast furnace waste.

Purpose: It is well known that hepatocellular carcinoma (HCC) is an arginine auxotroph due to argininosuccinate synthetase I deficiency. This study's purpose was to evaluate the effects of pegylated arginine deiminase (ADI) in terms of toxicity, tumor response, α-fetoprotein (AFP) levels, and serum arginine levels. Patients and Methods: Eighty patients were randomly assigned to receive either 80 IU/m² or 160 IU/m² of ADI weekly for up to 6 months. Adverse events, serum arginine, AFP levels, and antibody production against ADI were measured on a regular basis. In addition, disease response and time to progression according to the Response Evaluation Criteria in Solid Tumors (RECIST) and survival rates were evaluated. Results: Four patients were excluded from the survival analysis because they developed exclusion criteria after randomization, but before first treatment. The number of patients in the two cohorts were similar (n = 37 in the low-dose cohort, n = 39 in the high-dose cohort). Mean (±SE) survival for all subjects was 15.8 months (474 days ± 39 days) from time of diagnosis of unresectable disease. Arginine levels remained below baseline for 50 days while antibodies against ADI reached a plateau at approximately the same time. There were no deaths attributed to ADI treatment. Only two patients were withdrawn for immunogenic-related adverse events. Grade 2, 3, or 4 toxicities were recorded in 92, 19, and 0 patients, respectively. Conclusion: Pegylated ADI is a promising drug that capitalizes on a significant enzymatic deficiency in HCC. It is safe, well tolerated, and may benefit patients with unresectable HCC.