Clinicoprognostic implications of increased serum levels of vascular endothelial growth factor and basic fibroblastic growth factor in early B-cell chronic lymphocytic leukaemia

To assess the relative merit of increased serum levels of vascular endothelial growth factor and basic fibroblastic growth factor in predicting the risk of disease progression of patients with early B-cell chronic lymphocytic leukaemia we analyzed 81 Binet stage A patients whose sera were taken at the time of diagnosis and evaluated for the presence of vascular endothelial growth factor and basic fibroblast growth factor using an enzyme-linked immunosorbent assay. Serum levels of vascular endothelial growth factor positively correlated with Rai sub-stages (P=0.03), peripheral blood lymphocytosis (P=0.03), bone marrow histology (P=0.04) and β2-microglobulin (β2-m) (P=0.006). When dealing with basic fibroblast growth factor only a correlation with Rai sub-stages (P=0.02) could be found. Different cut-offs set on the basis of a stratification in quartiles, failed to demonstrate any correlation between serum levels of basic fibroblast growth factor and disease progression. In contrast, patients with increased serum levels of vascular endothelial growth factor (above median value, 203 pg ml−1) had a three times increased risk of disease progression, although, in multivariate analysis only Rai sub-stages (P=0.0001) and lymphocyte doubling time (P=0.002) retained their prognostic significance. Low levels of vascular endothelial growth factor were indicative of good clinical outcome in the subgroup of patients with either low (P=0.02) or high (P=0.03) β2-m concentration. Finally, the highest prognostic power was obtained when serum vascular endothelial growth factor and β2-m were examined in combination. Median of progression-free survival of patients who had both serum vascular endothelial growth factor and β2-m higher than median value was only 13 months, in contrast median progression-free survival of patients with one marker increased (i.e. above the 50th percentile) was 40 months. Patients with both markers below the median experienced the best clinical outcome (median progression-free survival not reached at 40 months). In conclusion, serum levels of either vascular endothelial growth factor or basic fibroblast growth factor are high in patients with early chronic lymphocytic leukaemia, however, only vascular endothelial growth factor predicts behaviour of disease and helps to refine the prognosis of stage A patients

Supply lead time uncertainty in a Sustainable Order Quantity inventory model

Transport plays a key role in inventory management since it affects logistic costs as well as environmental performance of the supply chain. Expected value and variability of supply lead time depend on the transportation means adopted, and influence the optimal values of order quantity, reorder level, and safety stock to be adopted. Fast transportation means allow reducing expected value of the lead time; they are characterized by the highest costs of externalities (i.e. air pollutant emission, noise, congestion, accidents). On the contrary, slow transportation means require high inventory level due to large order quantity; in this case costs of externalities tend to decrease. The Sustainable Order Quantity (SOQ) [1] allows identifying optimal order quantity, reorder level, safety stock as well as transportation means which minimize the sum of the logistic and environmental costs in case of stochastic variability of product demand. In this paper, the authors propose a new SOQ analytical model considering stochastic variability of supply lead time (LT). A solution procedure is suggested for solving the proposed model. The approach is applied to a real industrial case study in order to evaluate the benefits of applying it if compared with the traditional one

Minimum Emissions Configuration of a Green Energy–Steel System: An Analytical Model

The need to significantly reduce emissions from the steelmaking sector requires effective and ready-to-use technical solutions. With this aim, different decarbonization strategies have been investigated by both researchers and practitioners. To this concern, the most promising pathway is represented by the replacement of natural gas with pure hydrogen in the direct reduced iron (DRI) production process to feed an electric arc furnace (EAF). This solution allows to significantly reduce direct emissions of carbon dioxide from the DRI process but requires a significant amount of electricity to power electrolyzers adopted to produce hydrogen. The adoption of renewable electricity sources (green hydrogen) would reduce emissions by 95–100% compared to the blast furnace–basic oxygen furnace (BF–BOF) route. In this work, an analytical model for the identification of the minimum emission configuration of a green energy–steel system consisting of a secondary route supported by a DRI production process and a renewable energy conversion system is proposed. In the model, both technological features of the hydrogen steel plant and renewable energy production potential of the site where it is to be located are considered. Compared to previous studies, the novelty of this work consists of the joint modeling of a renewable energy system and a steel plant. This allows to optimize the overall system from an environmental point of view, considering the availability of green hydrogen as an inherent part of the model. Numerical experiments proved the effectiveness of the model proposed in evaluating the suitability of using green hydrogen in the steelmaking process. Depending on the characteristics of the site and the renewable energy conversion system adopted, decreases in emissions ranging from 60% to 91%, compared to the BF–BOF route, were observed for the green energy–steel system considered It was found that the environmental benefit of using hydrogen in the secondary route is strictly related to the national energy mix and to the electrolyzers’ technology. Depending on the reference context, it was found that there exists a maximum value of the emission factor from the national electricity grid below which is environmentally convenient to produce DRI by using only hydrogen. It was moreover found that the lower the electricity consumption of the electrolyzer, the higher the value assumed by the emission factor from the electricity grid, which makes the use of hydrogen convenient

Economic and environmental savings from upgraded biogas applications

The directive 2009/28 CE state a mandatory 10% minimum target to be achieved by all member states for the share of biofuels in transport petrol and diesel consumption by 2020. In the Directive, the advantage, in terms of greenhouse gas (GHG) saving, of agricultural manure and municipal organic waste treatments for biogas production is highlighted. Key biogas applications are identified in both direct energy conversion (combined heat and power-CHP) and in its use as biomethane (biogas upgrading). In the attempt to achieve EU targets, Italian incentive policies are moving from generation-based incentive (GBI) towards premium for reducing GHG emissions from power plant. In this context, the evaluation of biogas applications feasibility, from both an economic and an environmental point of view, is required. In this paper economic and environmental savings obtainable from both direct biogas application (CHP) and upgraded biogas applications (in-grid feeding or traditional petroleum based fuel replacement) are compared. Municipal organic wastes as substrate for biogas production have been considered. Economic and environmental performances of different scenarios are evaluated. Scenarios differ for biogas treatments and final applications. In all scenarios, emission savings have been calculated by means of an LCA approach. In case of CHP application, GHG emissions are compared with those corresponding to the national fuel mix used to generate electricity. In case of in-grid feeding of upgraded biogas (biomethane), GHG from biomethane production are compared with emissions from extraction, production and transportation of natural gas. Concerning fuel replacement application, Well To Tank (WTT) and Tank to Wheels (TTW) approaches are implemented in order to evaluate the Well To Wheels (WTW) environmental performance of the scenario considered. The purpose of this research is twofold: on one hand, to compare benefits in terms of GHG and local (NOx, PM, CO) emissions achievable of biogas/biomethane applications; on the other hand, to identify effective incentive policies allowing to give economic feasibility to biogas/biomethane applications

External Costs Evaluation for Sustainable Logistics

Transport is responsible for around a quarter of EU greenhouse gas emissions (EU, 2011). In a sustainable perspective, all external costs caused by freight transport have to be considered in the supply chain management. Traditional models, however, minimize logistics costs neglecting externalities. In this paper, the authors propose a Sustainable Order Quantity (SOQ) model allowing to identify (in case of a deterministic product demand) the optimal order size and the optimal means of transport which minimize logistic costs (holding, ordering, and transport), as well as external costs of transport. The 'loss factor' parameter is adopted to classify means of transport. External costs evaluation proposed is the result of a critical analysis of the most important researches on this issue. The lot size and the transport means selection are jointly solved by means of the SOQ model of (Digiesi et al., 2012a) in the hypothesis of a complete internalization of all external costs caused by freight transport. In the attempt to reduce the environmental costs of transport, EU public decision makers recognized the need to charge external costs according to a "user pays" and "polluter pays" principle to drive towards sustainable choices. In order to achieve EU targets, more severe public regulations will be adopted in the near future in EU Countries. The model proposed could help supply chain managers in identifying optimal strategies compliant with public regulations adopted. In order to evaluate the effectiveness of this strategy the analytical model proposed has been tested on a real case study

Potential environmental savings in new vehicles distribution

Environmental impacts of the road vehicles manufacturing and usage have been widely studied but very limited considerations have been made about the new vehicles distribution from the assembly plants to the final users. In this paper a methodology is proposed in order to evaluate the external costs of new passenger cars distribution and to estimate the achievable reduction that could be obtained by adopting different transportation modes. Starting from the location of the assembly plants and the models of passenger cars produced in 2013 in Europe, the external costs associated to the flows from the assembly plants to the selected European countries are evaluated. Potential environmental savings are estimated and discussed

A Stochastic-Based Model to Assess the Variability of Task Completion Times of Differently Aged and Experienced Workers Subject to Fatigue

In current industrial scenarios, the new paradigm of Industry 5.0 (I5.0) is gaining interest: considering the Industry 4.0 paradigm as a base, I5.0 is aimed at reaching a more sustainable, human-centric, and resilient industry. Under the I5.0 human-centric perspective, behavioural issues assume high criticality, thus requiring a more reliable prediction of operators’ performances. In manual assembly lines, operators’ performances are characterized by a stochastic behaviour over time. System’s and operator’s features cause the variability of task completion time: the former is related to properties of the work environment (e.g., ergonomics, cycle time), the latter is related to the intrinsic stochastic behaviour of operators. Furthermore, workers’ features and their different attitudes to becoming fatigued, influence performance variability. In this context, the authors propose a new stochastic model that expresses the variability of execution times of operators involved in manual assembly lines by considering their differences in age, experience, and fatigue state. The novelty of the proposed model relies on considering the stochastic behaviour of workers influenced by age, experience as well as fatigue. The effectiveness of the proposed model is tested through numerical experiments of a job rotation scheduling problem to maximize productivity with proper worker-workstation assignments

Minimizing Carbon-footprint of Municipal Waste Integrated Management Systems

Sustainability in urban development, economic growth and human well-being are critical issues faced all over the world. In the last decade urban planning and management had accomplished, or will do it, innovations in order to meet the challenges posed by sustainable development. Reduction of 20% of GHG emission, the achievement of 20% energy demand by renewable energy together with an increase of 20% of energy efficiency are targets foreseen by EU. In this scenario a strategic role is played by municipal waste integrated management system (MWIMS). The matter is becoming increasingly important as a results of the growth of urbanization rate: the raising complexity of a MWIMS relies on the high number of design and management variables and relationships pertaining to collection, treatments and disposal phases. Waste management practices can sway greenhouse gas emission by affecting energy consumption, methane generation, carbon sequestration and non-energy related manufacturing emission. In this context, a sustainable waste management system allows a reduction of negative impacts on environment. The purpose of such a study is to propose a decision-making framework aiming to minimize the carbon footprint of a MWIMS. The model goes beyond the existing technical and organizational solutions outlining the different options in a much broader view concerning both waste collection and treatments. A mixed integer linear programming model , has been applied to a full case study concerning Bari. The study is carried out within the research project RES NOVAE (Reti, Edifici, Strade ‐ Nuovi Obiettivi Virtuosi per l’Ambiente e l’Energia). The strength of the framework results in supporting public decision-making, a complex process due to the number of decision variables and their implications on economic performance. Results exhibit the effectiveness of the model also in pointing out opportunities non yet evaluated