Search

The building sector has a significant impact on the environment due to its unproductive and technologically outdated practices. Although digital tools have emerged as potential solutions, current building practices often lack automation and efficiency. Throughout history, several self-supporting techniques, i.e., construction methods dedicated to the building of shells that do not need support during the construction works, have been developed. These techniques allow for reducing waste and minimizing construction costs. Combining self-supporting techniques and digital tools could aid the development of contemporary, highly sustainable, and efficient building practices that permit the use of alternative and sustainable materials. Building on this, the research conducted defines an approach for evaluating the balanced state of masonry structures during construction works and built using robotic technologies. The approach considers the factors that govern the stability under construction derived through studying self-supporting building techniques. The proposed approach assesses the structural state under construction, evaluating the need for temporary supports. An example of a masonry arch is provided to emphasize the importance of construction factors in sustainable building practices. Then the method is applied to a real case study. Overall, integrating self-supporting techniques with digital tools has the potential to revolutionize the building sector, and create highly sustainable and efficient practices.

Since the beginning of the COVID-19 pandemic, the impact of superinfections in intensive care units (ICUs) has progressively increased, especially carbapenem-resistant Acinetobacter baumannii (CR-Ab). This observational, multicenter, retrospective study was designed to investigate the characteristics of COVID-19 ICU patients developing CR-Ab colonization/infection during an ICU stay and evaluate mortality risk factors in a regional ICU network. A total of 913 COVID-19 patients were admitted to the participating ICUs; 19% became positive for CR-Ab, either colonization or infection (n = 176). The ICU mortality rate in CR-Ab patients was 64.7%. On average, patients developed colonization or infection within 10 ± 8.4 days from ICU admission. Scores of SAPS II and SOFA were significantly higher in the deceased patients (43.8 ± 13.5, p = 0.006 and 9.5 ± 3.6, p < 0.001, respectively). The mortality rate was significantly higher in patients with extracorporeal membrane oxygenation (12; 7%, p = 0.03), septic shock (61; 35%, p < 0.001), and in elders (66 ± 10, p < 0.001). Among the 176 patients, 129 (73%) had invasive infection with CR-Ab: 105 (60.7%) Ventilator-Associated Pneumonia (VAP), and 46 (26.6%) Bloodstream Infections (BSIs). In 22 cases (6.5%), VAP was associated with concomitant BSI. Colonization was reported in 165 patients (93.7%). Mortality was significantly higher in patients with VAP (p = 0.009). Colonized patients who did not develop invasive infections had a higher survival rate (p < 0.001). Being colonized by CR-Ab was associated with a higher risk of developing invasive infections (p < 0.001). In a multivariate analysis, risk factors significantly associated with mortality were age (OR = 1.070; 95% CI (1.028–1.115) p = 0.001) and CR-Ab colonization (OR = 5.463 IC95% 1.572–18.988, p = 0.008). Constant infection-control measures are necessary to stop the spread of A. baumannii in the hospital environment, especially at this time of the SARS-CoV-2 pandemic, with active surveillance cultures and the efficient performance of a multidisciplinary team.

The containment of unwanted electromagnetic radiation and interference is a relevant topic for the system design of any electrical system, and even more for data centers. In this context, the racks hosting piles of servers are one of the main sources of electromagnetic noise. Such unwanted radiation can couple and interact with other computing machines, but also with sensitive electronic devices needed for the management and/or maintenance of the center. The aim of this work is to show how the proper stack-up of the trays in the rack gives rise to a decrease in the unwanted physical electromagnetic radiation. Based on the application of the spherical wave expansion technique, a multi-objective genetic algorithm is developed to evaluate the optimal set of rack configurations that allows for a reduction of the external radiated field. The algorithm and the implemented constraints are described, and the results are discussed.

(1) Methods for checking the condition of monumental masonry structures can still be considered understudied. Among the different approaches available in the literature, the graphical ones have a special role, due to their simplicity and effectiveness. (2) In this work, a 2D method (Thrust Line Analysis (TLA)), the Modified Thrust Line Method (MTLM), and the 3D Membrane Equilibrium Analysis (MEA) method are compared. All methods have the same starting concept: no tensile strength, no sliding between the stone blocks, infinite compressive strength. (3) The methods are compared in terms of stress distribution (for the same—or similar—thrust line), and in terms of the Geometrical Safety Factor ensured. (4) The work shows that these theories, if properly conveyed in a scientific methodology (as many authors are doing currently and have done in the past) demonstrate the effectiveness and the advantages of graphical methods for simple structures.

An iterative optimization for decoupling capacitor placement on a power delivery network (PDN) is presented based on Genetic Algorithm (GA) and Artificial Neural Network (ANN). The ANN is first trained by an appropriate set of results obtained by a commercial simulator. Once the ANN is ready, it is used within an iterative GA process to place a minimum number of decoupling capacitors for minimizing the differences between the input impedance at one or more location, and the required target impedance. The combined GA&ndash, ANN process is shown to effectively provide results consistent with those obtained by a longer optimization based on commercial simulators. With the new approach the accuracy of the results remains at the same level, but the computational time is reduced by at least 30 times. Two test cases have been considered for validating the proposed approach, with the second one also being compared by experimental measurements.

Decoupling capacitors are fundamental keys for the reduction of transient noise in power delivery networks, their arrangement and values are crucial for reaching this goal. This work deals with the optimization of the decoupling capacitors of a power delivery network by using a nature-inspired algorithm. In particular, the capacitance value and the location of three decoupling capacitors are optimized in order to obtain an input impedance below a specific mask, by using a nature-inspired algorithm, the genetic one, in combination with two electromagnetic solvers used to compute the objective function. An experimental board is designed and manufactured, measurements are performed to validate the numerical results.