Renewable energy sources are critical to the global effort to achieve carbon neutrality. Alongside hydropower, wind and nuclear plants, the photovoltaic (PV) systems developed greatly, with new PV technologies emerging in recent years. Although the conversion efficiencies are improving and the materials used have a lower impact on the environment, the feasibility of these technologies is required to be assessed. This paper proposes a levelized cost of energy (LCOE) model to assess the feasibility of five PV technologies: high-efficiency silicon heterojunction cells (HJT), N-type monocrystalline silicon cells (N-type), P-type passivated emitter and rear contact cells (PERC), N-type tunnel oxide passivated contact cells (TOPCon) and bifacial TOPCon. The LCOE considers capital investment, government incentives, operation and maintenance costs, residual value of PV modules and total energy output during the PV system’s life span. To determine the influence of PV system’s capacity over the LCOE values, three systems are analyzed for each technology: 3 kW, 5 kW and 7 kW. The results show that the largest PV systems have the lowest LCOE values, ranging from 2.39 c€/kWh (TOPCon) to 2.92 c€/kWh (HJT) when incentives are accessed, and ranging from 6.05 c€/kWh (TOPCon) to 6.51 c€/kWh (HJT) without subsidies. The 3 kW and 5 kW PV systems have higher LCOE values due to lower energy output during lifetime.

In today’s rapidly evolving information technology sectors, agile methodologies have been employed by software development organizations to facilitate the large-scale, efficient, and swift development of digital products. Notably, it is a widely accepted principle that an increase in project delivery predictability results from more effective portfolio management. Despite the abundant resources within software engineering that address project management and agile development performance, the measurement of portfolio delivery performance integrating sustainability principles is under-researched. This paper aims to underline a solution to bridge this gap by proposing a data-driven scoring model explicitly designed for software firms to integrate sustainability metrics into their project and portfolio performance assessment. The model is primarily aimed at monitoring and enhancing delivery performance while also reinforcing the sustainability of the software development lifecycle. A thorough literature review was conducted to discern gaps in existing practices, followed by development of a scoring model melded with delivery and sustainability metrics seamlessly. Validated through a case study, the findings reveal that the model influences the performance and sustainability dynamics within software development entities. The insights gained from this study underscore the pivotal role of a harmonized delivery and sustainability metrics system in enhancing the sustainability and efficiency of software development undertakings.

The flexible packaging industry has registered a significant growth over the last years, especially due to rising demand from healthcare, automotive, construction, food, beverage, and retail industries. It is essential for the production plants to regularly assess their ability to achieve performance target objectives and, at the same time, to compare their performance with that of factories from the same industry. By combining qualitative and quantitative research, this study proposes a set of thirty-two key performance indicators (KPIs), grouped into six activity areas, believed to be adequate to the flexible packaging industry, for assessing the operational performance. The analytical hierarchy process (AHP) method was employed to obtain the weights of the KPIs and to select the best manufacturing facility from a leading flexible packaging company in line with the opinions of experts that activate in this field. The results indicated that the main aspects considered by experts for assessing manufacturing plants operational performance were financial issues followed by production, customers contentment, quality, employee satisfaction and environmental protection. The proposed practical framework for assessing the operational performance along with the detailed information obtained in the paper are expected to represent important benchmarks for stakeholders involved in the decision-making process for flexible packaging industry.

Nowadays, as the technology behind solar photovoltaic systems has been significantly improved, along with a significant decrease in costs, grid-connected photovoltaic systems are becoming an important option to reach a low-carbon energy transition. The high cost of electricity consumed at the Technical University of Cluj-Napoca represented a good reason for the university to increase its energy efficiency by adopting and increasing energy consumption from renewable energy sources. This paper assesses the technical, economic, and environmental feasibility of deploying four photovoltaic systems at the aforementioned university situated in the Northwestern part of Romania, according to the Romanian renewable energy legislation. PVSOL software has been used to estimate the performance of photovoltaic installations. The results indicated that the most viable distributed generation system is the one with a capacity of 100 kW, meeting approximately 23 percent of university electricity needs, and at the same time, reducing carbon dioxide emissions by approximately 460 tons. A sensitivity analysis has been performed to evaluate the effect of several critical parameters on the PV system’s economic feasibility. The results provide valuable decision-making information regarding the buildings’ solar potential for other universities, supporting the transition to solar energy.

Increasing electric vehicle (EV) adoption raises concerns about EV waste management and the impact on the environment. To improve energy efficiency and exploit their remaining usable capacity, the retired batteries may be repurposed in second-life applications. This paper predicts the usable second-life capacity of retired EV batteries, considering the European Union (EU) regulation regarding the mandatory recycled critical material quotas in newly manufactured batteries from 2031 onwards. Based on political influences and the market’s capacity to return to pre-pandemic values, four scenarios are proposed regarding future EV sales in the EU market. The algorithm implemented in Matlab R2025a indicates the batteries that must be recycled to meet the mandatory targets and the ones that can be repurposed as battery energy storage systems. Historical data and future predictions are used to determine the number of EV batteries sold, lifetime, the market’s chemistry share and the usable capacity for second life. The annual mandatory recycled critical material content is compared to the available recyclable mass from both retired batteries in the current year and those that are already active in their second life. The economic analysis reveals the scenario with the highest total revenue, including the cascade benefits and recycling value.

The pandemic caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection is one of the world’s most disruptive health crises. The presence of diabetes plays an important role in the severity of the infection, and a rise in newly diagnosed diabetes cases has been identified. The aim of this retrospective study was to determine the incidence of new-onset diabetes (NOD) and predictive factors with their cut-off values for patients hospitalized with COVID-19. All patients (n = 219) hospitalized for COVID-19 during three consecutive months were included. NOD was diagnosed in 26.48% of patients. The severity of the infection, hospital admission values for fasting plasma glucose, lactate dehydrogenase (LDH), PaO2/FiO2 ratio, the peak values for leucocytes, neutrophils, C-reactive protein, triglycerides, and the need for care in the intensive care unit were predictors for the occurrence of NOD in univariate analysis, while only LDH level remained a significant predictor in the multivariable analysis. In conclusion, the results of the study showed a high incidence of NOD in patients hospitalized with COVID-19 and identified LDH levels at hospital admission as a significant predictor of NOD during SARS-CoV-2 infection. However, the persistence of NOD after the COVID-19 infection is not known, therefore, the results must be interpreted with caution.