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Background/Objectives: Carbapenem-resistant Klebsiella pneumoniae (CRKP) is of great concern because of the difficulties encountered in the management of infections it may cause. This study aims to identify possible difficulties in the management of K. pneumoniae infections in the current context of antibiotic resistance, particularly regarding carbapenem resistance. Methods: This is a retrospective, cross-sectional study that analyses epidemiological, clinical and bacteriological features identified in all patients with CRKP infections/colonization admitted during 2024 in an infectious diseases hospital. Results: Carbapenemase-producing K. pneumoniae isolates were co-harboring NDM+OXA-48 in 55.2% of cases. NDM+OXA-48-producing K. pneumoniae (116 isolates, 55.2%) was correlated with high resistance to aztreonam (100%, p = 0.01), ceftazidime–avibactam (100%, p < 0.01), trimethoprim–sulfamethoxazole (99.1%, p < 0.01), gentamycin (94.8%, p < 0.01), amikacin (93.8%, p < 0.01), colistin (79.8%, p < 0.01). OXA-48-producing K. pneumoniae (29 isolates, 13.8%) was correlated with lower resistance to ceftazidime–avibactam (11.5%, p < 0.01), amikacin (48.1%, p < 0.01), colistin (51.7%, p = 0.01), and gentamycin (65.5%, p < 0.01). We found in vitro synergistic effects of ceftazidime/avibactam + aztreonam for 32/32 CRKP isolates and of colistin + tigecycline for 12/14 CRKP isolates. Higher recurrence of CRKP infections was recorded in patients with urinary tract conditions (RR = 11.58, 95%CI: 1.58–81.91) and upper urinary tract devices (RR = 3.53, 95% CI: 1.72–7.22). In this study, adequate antibiotic treatment, compared to excessive antibiotic treatment in CRKP infections, was associated with shorter treatment duration (p = 0.02) and shorter length of hospitalization (p = 0.04). Conclusions: In our study, CRKP is frequently coharboring NDM+OXA-48, having limited treatment options. Implementing new treatment strategies, testing antibiotic synergies for older antibiotics in order to identify alternative treatment options and avoiding unnecessary carbapenem consumption are essential for decreasing the burden of CRKP infections.

Background: The antimicrobial resistance (AMR) of Klebsiella pneumoniae recorded a steep upward trend over the last two decades, among which carbapenem-resistant Klebsiella pneumoniae (CRKP) is one of the most concerning strains considering the development and spread of AMR. The aim of this study was to analyze the evolution of AMR for Klebsiella pneumoniae and to describe the risk factors of AMR for Klebsiella pneumoniae, including the COVID-19 pandemic. Methods: We conducted a retrospective study on Klebsiella pneumoniae non-duplicative isolates collected from patients admitted to a tertiary hospital in Bucharest, Romania, from January 2019 to December 2021. We evaluated AMR changes by comparing resistance between 2019 and the mean of 2020–2021. Results: The rates of AMR increased for third-generation cephalosporins, carbapenems, aminoglycosides, fluoroquinolones, and colistin and decreased for trimethoprim/sulfamethoxazole (TMP/SMX), 45.7% in 2019 vs. 28.3% in 2021. A longer length of hospital stay (ꭓ2 = 49.68, p < 0.01); recent antibiotic consumption, RR = 1.38, 95% CI [1.21, 1.57]; and recent contact with hospital settings, RR = 1.54, 95% CI [1.32, 1.8] were risk factors for multidrug-resistant (MDR) Klebsiella pneumoniae. Conclusions: The AMR of Klebsiella pneumoniae increased during 2020–2021 for most of the potential active antibiotics; only TMP/SMX resistance decreased, and it may represent a treatment option for CRKP or MDR Klebsiella pneumoniae infections. Decreasing the excessive use of antibiotics and the implementation of prevention and control measures in healthcare settings are mandatory for avoiding further increases in the AMR rate of Klebsiella pneumoniae.

Lately, the logistics sector has seen accelerated development, which has led to general economic growth, but, at the same time, it has caused considerable environmental damage due to the excessive consumption and emissions that are currently affecting society at large. Since logistics activities are considered some of the most polluting economic activities, this present article aims to present the advantages of implementing the green logistics concept. To this purpose, the activity of a logistics centre in Romania was analysed, with a focus on the greenhouse gases (GHGs) produced as a consequence of this economic activity, and its carbon footprint was calculated according to the GHG Protocol. Although this global standard is based on an integrated approach to how GHG emissions are calculated, there is limited evidence about its degree of implementation by companies. The results of the analysis revealed that the consumption of energy and fuel by the logistics sector has a significant impact on the environment. This impact is maintained, albeit at a smaller scale, even if the technology is replaced and the equipment used by companies to carry out their activities is increasingly performant.

This paper proposes a methodological framework for linking standardized carbon footprint reporting with structured decision support in logistics. The approach integrates the GHG Protocol framework and the ISO 14064 standard in order to formalize emissions inventories, reporting requirements, and verification constraints into a coherent, transparent, and auditable analytical structure. While existing standards provide robust guidance for the quantification and reporting of greenhouse gas emissions, their systematic integration into decision support representations remains limited. The main contribution of the paper consists of the formal operationalization of carbon accounting processes into decision variables, constraints, and performance indicators that preserve traceability, transparency, and compatibility with external verification requirements. A simplified linear programming formulation is employed as a standard-driven decision support abstraction, illustrating how emissions-related data derived from standardized reporting can be consistently translated into operational constraints and analytical indicators. The mathematical formulation is not intended to replace detailed logistics optimization models, but to demonstrate the methodological linkage between emissions reporting, verification requirements, and structured decision-oriented analysis. The proposed framework is illustrated through a logistics hub case study using average emission factors and estimated consumption data. The numerical results serve an illustrative purpose and highlight the functioning of the framework, rather than providing fully calibrated operational solutions. The methodology is designed to be reproducible and auditable and may be extended to other industrial sectors, as well as to more advanced modeling settings incorporating dynamic or stochastic elements.

Background: Integrating Radio Frequency Identification (RFID) technology into storage areas within the wiring harness manufacturing industry enables real-time component traceability and supports the implementation of fully automated inventory processes. While RFID systems provide continuous data regarding component type, quantity, and location, periodic inventory validation is still required to verify and correct records in the warehouse management system. Methods: This study examines the feasibility of passive ultra-high-frequency (UHF) RFID technology for automatic inventory management in a components warehouse. It also reviews relevant scientific literature on autonomous RFID signal measurement and Synthetic Aperture Radar (SAR)-based localization methods, which are subsequently adapted for inventory applications. An experimental setup is developed to characterize the reading field, hysteresis effects, and the influence of distance and tag orientation on detection performance. Results: The findings indicate that RFID-based automatic inventory is achievable with high accuracy and stability, especially when tag trajectories correspond to areas of high detection probability and antenna polarization is optimally configured. Conclusions: The proposed RFID-based system can be implemented with minimal hardware changes and low investment, thereby improving stock accuracy, traceability, and operational efficiency in automotive component logistics.

This paper presents a compelling argument for optimizing the logistics flow of wiring harnesses within the automotive industry to address the rising production demands of vehicle manufacturers. It introduces an innovative assembly line structure specifically designed to boost efficiency and enhance responsiveness to client needs. Drawing from data gathered from an actual assembly line dedicated to producing engine harnesses for K9K engines, this study offers a practical and impactful foundation for its proposed optimization strategies. The new assembly structure effectively merges the benefits of a dynamic line—which emphasizes efficient space utilization and flexibility—with the strengths of a rotary line, particularly in light of the increasing complexity associated with harness production. The paper features a mathematical model that calculates cycle times for workstations within this new system architecture, optimizing the entire production process. Moreover, it illustrates how advanced modeling, simulation, and optimization techniques using WITNESS Horizon Version Release 25.0 can identify necessary adjustments for achieving optimal assembly line balance. Additionally, this research addresses pressing environmental concerns by proposing a robust recycling strategy for the scrap produced during wiring harness manufacturing. By advocating for sustainable practices and responsible waste management, the study highlights the importance of minimizing the ecological footprint of the automotive manufacturing process. In summary, this research provides essential insights and practical solutions for optimizing wiring harness logistics flow in the automotive industry. By implementing these strategies, manufacturers can significantly enhance their production capacity, improve operational efficiency, and maintain competitiveness in an ever-evolving market landscape.

Industrial development has implicitly led to the development of new systems that increase the ability to provide services and products in real time. Autonomous mobile robots are considered some of the most important tools that can help both industry and society. These robots offer a certain autonomy that makes them indispensable in industrial activities. However, some elements of these robots are not yet very well outlined, such as their construction, their lifetime and energy consumption, and the environmental impact of their activity. Within the context of European regulations (here, we focus on the Green Deal and the growth in greenhouse gas emissions), any industrial activity must be analyzed and optimized so that it is efficient and does not significantly impact the environment. The added value of this paper is its examination of the activities carried out by mobile robots and the impact of their electronic components on the environment. The proposed analysis employs, as a central point, an analysis of mobile robots from the point of view of their electronic components and the impact of their activity on the environment in terms of energy consumption, as evaluated by calculating the emission of greenhouse gases (GHGs). The way in which the activity of a robot impacts the environment was established throughout the economic flow, as well as by providing possible methods of reducing this impact by optimizing the robot’s activity. The environmental impact of a mobile robot, in regard to its electronic components, will also be analyzed when the period of operation is completed.

Objectives: The aims of this study were to evaluate the efficacy of a five-bundle intervention and to decrease the number of cases in which only one set of blood cultures is collected prior to starting antimicrobials. Methods: The study group consisted of the two hospital wards that have the highest collection rate (120 blood cultures/1000 patient days and 121.4 blood cultures/1000 patient days, respectively), and the control group consisted of the other three adult wards. The collection protocol was changed, and a bundle of five measures was introduced: one-on-one discussions with the nurses, 2% chlorhexidine in 70% alcohol for disinfection, ensuring the use of sterile gloves, sterile wipes, a checklist for the materials needed, and a copy of the collection protocol. The impact of these changes was followed over a 5-month period. Results: Prior to the intervention, the contamination rate was higher in the control group (6.5%) versus the study group (4%), p = 0.00578. The before–after analysis revealed a significantly reduced contamination rate in the control group (4.6% vs. 6.5% p = 0.0099), but it was above the one obtained in the study group (3.1% vs. 4%, p = 0.1635). The number of infectious episodes in which one blood culture set was collected decreased significantly in the study group (77/311 vs. 139/456, p = 0.041). Conclusions: The intervention decreased the contamination rate and the number of infectious episodes in which one blood culture set is collected.

This paper presents a logistic flow of assembling automotive rear axles. The product is presented in detail starting from the detailed research and analysis of relevant documentation about its functionality, including the manufacturing logistic flow diagram and the required equipment for the product manufacturing and assembly. This study is focused on optimizing the logistic flow for the manufacturing and assembly of automotive rear axles using WITNESS Horizon for system modeling and simulation in order to conduct system diagnostics, identify problems, and find solutions that will facilitate the optimization process. The study included a comprehensive assessment of the logistic flow, highlighting the performance of the equipment involved and identifying potential bottlenecks. Using the results obtained after the simulations, the Simplex linear mathematical method was applied to maximize production efficiency and profitability, considering the suppliers’ capacity constraints and the components’ delivery requirements. The results demonstrated a significantly optimized rear-axle production process, with increased profitability and improved productivity by eliminating identified bottlenecks. This research contributes to a deeper understanding of the complexities within the automotive industry and provides a solid foundation for continuously improving manufacturing and assembly processes.

Background: although the prevalence of bacterial co-infections for COVID-19 patients is very low, most patients receive empirical antimicrobial therapy. Furthermore, broad spectrum antibiotics are preferred to narrow spectrum antibiotics. Methods: in order to estimate the excess of antibiotic prescriptions for patients with COVID-19, and to identify the factors that were correlated with the unjustified antibiotic usage, we conducted an observational (cohort) prospective study in patients hospitalized with COVID-19 at the National Institute for Infectious Diseases “Prof. Dr. Matei Bals”, Bucharest, on an infectious disease ward, from November 2021 to January 2022. To evaluate the prevalence of bacterial co-infection in these patients, all positive microbiology results and concomitant suspected or confirmed bacterial co-infections, as documented by the treating doctor, were recorded. The patients were grouped in two categories: patients who received antibiotics and those who did not receive antibiotics, justified or not. Results: from the 205 patients enrolled in the study, 83 (40.4%) received antibiotics prior to being admitted to the hospital. 84 patients (41.0%) received antibiotics during their hospitalization; however, only 32 patients (15.6%) had signs and symptoms suggestive of an infection, 19 (9.3%) presented pulmonary consolidation on the computed tomography (CT) scan, 20 (9.7%) patients had leukocytosis, 29 (14.1%) had an increased procalcitonin level and only 22 (10.7%) patients had positive microbiological tests. It was observed that patients treated with antibiotics were older [70 (54–76) vs. 65 (52.5–71.5), p = 0.023, r = 0.159], had a higher Charlson index [4 (2–5) vs. 2 (1–4), p = 0.007, r = 0.189], had a severe/critical COVID-19 disease more frequently [61 (72.6%) vs. 38 (31.4%), p < 0.001, df = 3, X2 = 39.563] and required more oxygen [3 (0–6) vs. 0 (0–2), p < 0.001, r = 0.328]. Conclusion: empirical antibiotic treatment recommendation should be reserved for COVID-19 patients that also had other clinical or paraclinical changes, which suggest a bacterial infection. Further research is needed to better identify patients with bacterial co-infection that should receive antibiotic treatment.