Is digital twin technology supporting safety management? A bibliometric and systematic review

In the Industry 4.0 era, digital tools applied to production and manufacturing activities represent a challenge for companies. Digital Twin (DT) technology is based on the integration of different “traditional” tools, such as simulation modeling and sensors, and is aimed at increasing process performance. In DTs, simulation modeling allows for the building of a digital copy of real processes, which is dynamically updated through data derived from smart objects based on sensor technologies. The use of DT within manufacturing activities is constantly increasing, as DTs are being applied in different areas, from the design phase to the operational ones. This study aims to analyze existing fields of applications of DTs for supporting safety management processes in order to evaluate the current state of the art. A bibliometric review was carried out through VOSviewer to evaluate studies and applications of DTs in the engineering and computer science areas and to identify research clusters and future trends. Next, a bibliometric and systematic review was carried out to deepen the relation between the DT approach and safety issues. The findings highlight that in recent years, DT applications have been tested and developed to support operators during normal and emergency conditions and to enhance their abilities to control safety levels

IoT technologies for wine supply chain traceability: Potential application in the Southern Apulia Region (Italy)

The high value and volume of Italian wine production determines a strong stimulus for counterfeiting, which generates negative consequences for grape growers, winemakers and consumers. In this context, IoT technologies and the blockchain can serve as tools to ensure traceability, transparency and efficiency along the whole wine supply chain. Using primary data collected through interviews to the main grape growers and wineries involved in the wine supply chain in the Southern Apulia Region and secondary data, acquired from previous scientific literature, the study proposes a framework for the traceability and efficiency of the wine supply chain based on a combination of blockchain, Radio-Frequency Identification (RFID) and Near Field Communication (NFC) tags, Serial Shipping Container Codes (SSCC) and Quick Response (QR) codes. The developed framework allows for the systematic storage of information about commodities and processes throughout the supply chain, from grape growers to wine consumption and packaging disposal and/or reuse (forward and reverse flows). In addition, it ensures the transparency, safety, and security of all processes involved within the wine supply chain, serving as a quality information management tool. The information collected along the wine supply chain is entered into the management system by farmers, winemakers and bottlers and is accessible to all of them, while the distributors, consumers and the bottle reverse logistics operators, can only consult all of the information stored on the blockchain in order to know the origin, the quality, the processing and the authenticity of wines, without being able to enter data and/or modify the existent information

Modelling forage yield and water productivity of continuous crop sequences in the Argentinian Pampas

In recent years, the use of forage crop sequences (FCS) has been increased as a main component into the animal rations of the Argentinian pasture-based livestock systems. However, it is unclear how year-by-year rainfall variability and interactions with soil properties affect FCS dry matter (DM) yield in these environments. Biophysical crop models, such as Agricultural Production Systems Simulator (APSIM), are tools that enable the evaluation of crop yield variability across a wide of environments. The objective of this study was to evaluate the APSIM ability to predict forage DM yield and water productivity (WP) of multiple continuous FCS. Thirteen continuous FCS, including winter and summer crops, were simulated by APSIM during two/three growing seasons in five locations across the Argentinian Pampas. Our modelling approach was based on the simulation of multiple continuous FCS, in which crop DM yields depend on the performance of the previous crop in the same sequence and the final soil variables of the previous crop are the initial conditions for the next crop. Overall, APSIM was able to accurately simulate FCS DM yield (0.93 and 3.2 Mg ha−1 for concordance correlation coefficient [CCC] and root mean square error [RMSE] respectively). On the other hand, the model predictions were better for annual (CCC = 0.94; RMSE = 0.4 g m−2 mm−1) than for seasonal WP (CCC = 0.71; RMSE = 1.9 g m−2 mm−1), i.e. at the crop level. The model performance to predict WP was associated with better estimations of the soil water dynamics over the long-term, i.e. at the FCS level, rather than the short-term, i.e. at the crop level. The ability of APSIM to predict WP decreased as seasonal WP values increased, i.e. for low water inputs. For seasonal water inputs, <200 mm, the model tended to under-predict WP, which was directly associated with crop DM yield under-predictions for frequently harvested crops. Even though APSIM showed some weaknesses in predicting seasonal DM yield and WP, i.e. at the crop level, it appears as a potential tool for further research on complementary forage crops based on multiple continuous FCS in the Argentinian livestock systems

Soy protein supplementation does not cause lymphocytopenia in postmenopausal women

BACKGROUND: The health benefits of soy isoflavones have been widely investigated; however, there are some concerns as to whether soy isoflavones, similar to ipriflavone, a synthetic isoflavone, cause lymphocytopenia in postmenopausal women. Hence, the purpose of this study was to investigate the extent to which 12-month supplementation of 25 g soy protein containing 60 mg isoflavones alters lymphocyte counts or other hematological parameters in postmenopausal women who were not on hormone replacement therapy. METHODS: Eighty-seven postmenopausal women were randomly assigned to receive either soy protein or an equivalent amount of control protein devoid of isoflavones. Fasting venous blood was collected at baseline and at the end of twelve month study period for complete blood count analyses. RESULTS: Between the two treatment groups, the percent changes in hematological parameters, including lymphocytes, were not different. While women consuming the soy supplement had an increase in mean corpuscular hemoglobin concentration (MCHC) and red cell distribution width index (RDW; a marker of reticulocytes), women consuming the control diet had higher percentage of only MCHC. CONCLUSION: Overall, the results of the present study indicate that consumption of 25 g soy protein containing 60 mg isoflavones daily for one year does not cause lymphocytopenia

A comprehensive fracture prevention strategy in older adults: The European union geriatric medicine society (EUGMS) statement

Prevention of fragility fractures in older people has become a public health priority, although the most appropriate and cost-effective strategy remains unclear. In the present statement, the Interest group on falls and fracture prevention of the European union geriatric medicine society (EUGMS), in collaboration with the International association of gerontology and geriatrics for the European region (IAGG-ER), the European union of medical specialists (EUMS), the Fragility fracture network (FFN), the International osteoporosis foundation (IOF) – European society for clinical and economic aspects of osteoporosis and osteoarthritis (ECCEO), outlines its views on the main points in the current debate in relation to the primary and secondary prevention of falls, the diagnosis and treatment of bone fragility, and the place of combined falls and fracture liaison services for fracture prevention in older people

A classification proposal of digital twin applications in the safety domain

The increasing diffusion of digitalization in industry and society is forcing the adopting of tools based on new enabling technologies. This phenomenon is clearly observable in the manufacturing sector, where, due to the diffusion of Industry 4.0 paradigm, physical processes are integrating effectively with digital ones. One recent innovative technology is the Digital Twin (DT), where digital models and physical ones communicate – by sharing data as well as information – usually in a bidirectional way. As recent studies have analyzed the current level of adoption of DT technologies in the manufacturing sector, less effort has been focused on evaluating applications in the safety domain. Theoretically, the DT inherent capability of acquiring data from the physical world - usually developed in real time – together with the potentiality of reliable data processing could support a more effective diffusion of dynamic risk assessment models as well as real time alert management systems for improving safety. Otherwise, the actual capability of real applications highly depends on the level of complexity of the specific DT. The aim of the study is to provide a methodology to assess current application of DT technologies; the framework has been developed in the safety domain aiming to point out to researchers as well as technicians in a clear way the capabilities of a specific DT application. The framework has been adopted for analyzing current applications of DT in the scientific literature aiming to propose a theoretical validation. The application has outlined that, although the number of DT applications in the safety field is not so large, the current tools developed are characterized by a high level of complexity thus providing higher reliability to support the specific safety problem in analysis. Further developments will be oriented towards developing a quantitative assessment framework to integrate the proposed tool

Adoption of precision farming tools: The case of italian farmers

The process of adopting innovation, especially with regard to precision farming (PF), is inherently complex and social, and influenced by producers, change agents, social norms and organizational pressure. An empirical analysis was conducted among Italian farmers to measure the drivers and clarify “bottlenecks” in the adoption of agricultural innovation. The purpose of this study was to analyze the socio-structural and complexity factors that affect the probability to adopt innovations and the determinants that drive an individual’s decisions. Preliminary results found high levels of adoption among younger farmers, those that had a high level of education, those with high intensity of information, with large farm sizes, and high labor intensity. A logit model was used to understand the role played by labor intensity and perceived in the adoption process. In light of the Common Agricultural Policy Reform post 2020, the findings suggest relevant policy implications, such as the need to increase awareness of PF tools and foster dissemination of information aimed at reducing the degree of perceived complexity