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Cardiac amyloidosis (CA) is an increasingly recognized cause of restrictive cardiomyopathy in which extracellular amyloid deposition leads to progressive structural and functional impairment. Beyond myocardial infiltration, growing evidence highlights the central role of autonomic nervous system dysfunction (ANS) —particularly the vagal nerve involvement—as a contributor to orthostatic intolerance, syncope, exercise limitation, arrhythmias, and reduced quality of life. Emerging data suggest that autonomic impairment may precede overt cardiac manifestations, offering a potential window for earlier recognition. This narrative review summarizes current knowledge on the mechanisms and clinical relevance of autonomic dysfunction in CA, emphasizing the novelty of the “vagal link” as a unifying framework connecting with a specific focus on the vagus nerve (VN) and its complex interplay with cardiac structure and function. We further discuss diagnostic approaches and the potential role of autonomic assessment in early detection, risk stratification, and personalized treatment strategies. A clearer understanding of vagal dysfunction may provide new insights into disease progression and identify opportunities for therapeutic innovation.

Green buildings have recently become a key aspect of the construction field and bring along a renovation of the whole industry chain. Such changes introduce new challenges for all subjects involved, and designers are also affected by such issues, especially for the development of projects based on international green building standards. Within this scope, project management plays a key role in the optimization of the design phase. This research analyzes the design process of international projects from the project management perspective through a multiple case study approach, considering the sustainability-related tasks that negatively affect the project design development under two types of contractual approaches: Design-Build and Design-Bid-Build. It aims to identify whether the Design-Build or Design-Bid-Build process is the best solution for developing green building projects. Two case studies in Italy and two case studies in Spain are analyzed, and the effects of the project management issues are evaluated under three different points of view: Time, cost, and level of sustainability of the building. A poorly planned process for the achievement of the various green building features of the project can impact the project schedule and the budget, whereas, a poorly managed project could also negatively impact its green building features. Finally, this research also highlights the positive relationship between process integration and green building design development.

Question: Using a Lean approach to classify issues, or wastes, experienced during the different design processes, what sustainability-related activities affect the project design development stage. Purpose: The objective of this paper is to create a new lean-based approach to analyze the design process and quantify the negative effect of detected project-management issues on the project’s main resources, categorized through three different variables: costs, time and sustainability. Research Method: The research makes full use of a Lean approach intended as a standardized method to identify project wastes, classify the issues experienced during the different design processes and ultimately propose possible solutions for process optimization. The Lean approach was used as the basis to study four case studies wherein real projects were developed in different European countries under the LEED and BREEAM reference standards. The projects were analyzed against a set of guidelines developed by the Researchers with the aim of avoiding the replication of such issues in future projects. The analysis took into consideration all sustainability-related activities that affected the project design development. Findings: By identifying and estimating the effects of each issue on the project variables, researchers could rank their negative impact on the project budget, schedule and level of sustainability. The ranking allowed isolating which issues, or categories of issues, had the worst impact on the overall project from both qualitative and quantitative points of view. These research goals were achieved through the implementation of the Lean method and philosophy. Limitations: Among the main challenges related to time-variance analysis. Estimating the delay of single activities impact was sometimes difficult and ambiguous because it relied on other activities for which dependency could not be calculated. Limitations related to cost-variance analysis involved indirect costs that were difficult to estimate because they were neither related to any written document nor any formal activity or event of the project. The present research takes into consideration only four case-study projects and therefore the related conclusions cannot be generalized for all building projects. Implications: Applying the ranking of the issues identifies to a real project development with limited resources, it would be possible to highlight which problems should be addressed first in order to avoid, or at least limit, their negative impact on the project establishing a set of guidelines for future projects. Value for authors: This study sets the basis for several other research studies in relationship with green-building developments and lean approach. Keywords: Lean Construction, Lean Thinking, Design, Green-Building; Development, Sustainability; Project Management; Waste Paper type: Full paper.

Building systems account for 71% of energy used in buildings (USGBC). Researchers have explored solutions for reducing energy use in buildings. One way to minimize energy use is by reducing cooling loads through use of shading devices. This research explored the impact of fixed shading device geometry on energy. The research examined the role of shading device geometry including projection, width and height above window in reducing energy use. Researchers used Carrier HAP software, applied to a case study project in Northern Italy to conduct energy analyses. Researchers developed a single space model studying 376 shading device geometries on four different window configurations. A total of 1504 simulations were run in order to select an optimum for the case study. The optimum shading device was applied to a whole building analysis to determine impact on an entire building against a baseline case without shading devices. In order to help test the results researchers ran simulations in three additional locations including Spain, Italy and Germany. The study showed that fixed shading devices have a positive impact on improving building energy performance, particularly on reducing cooling loads. Negative impacts that shading devices may have on energy use in heating months can be more than offset by cooling season savings. Effectiveness of shading devices is closely related to window configuration and building thermal mass. Recommendations are made regarding use and geometry of shading devices.

The growing availability of patient data from several clinical settings, fueled by advanced analysis systems and new diagnostics, presents a unique opportunity. These data can be used to understand disease progression and predict future outcomes. However, analysing this vast amount of data requires collaboration between physicians and experts from diverse fields like mathematics and engineering. Mathematical models play a crucial role in interpreting patient data and enable in-silico simulations for diagnosis and treatment. To facilitate the creation and sharing of such models, the CNR-IASI BioMatLab group developed the \"Gemini\" (MoSpec/Autocoder) system, a framework allowing researchers with basic mathematical knowledge to quickly and correctly translate biological problems into Ordinary Differential Equations models. The system facilitates the development and computation of mathematical models for the interpretation of medical and biological phenomena, also using data from the clinical setting or laboratory experiments for parameter estimation. Gemini automatically generates code in multiple languages (C++, Matlab, R, and Julia) and automatically creates documentation, including code, figures, and visualizations. This user-friendly approach promotes model sharing and collaboration among researchers, besides vastly increasing group productivity.

Ionizing radiations are responsible for bond scission, radical formation, and oxidative degradation of polymer matrices. This study focuses on the effects of gamma irradiation on solid propellant binders, targeting a comprehensive chemical and mechanical characterization of different formulations. Samples were produced either by conventional methods based on hydroxyl-terminated polybutadiene and standard polyaddition reaction using isocyanates, or innovative approaches involving UV-driven radical curing. The samples were irradiated for comparison and to study their evolution as a function of three absorbed doses (25, 45, 130 kGy) for preliminary characterization studies, using a 60-Co gamma source. Samples were irradiated in air at uncontrolled room temperature. The coupling of spectroscopy techniques (Fourier transform infrared—FTIR, Raman and electron paramagnetic resonance—EPR) and dynamic mechanical analysis (DMA) highlighted the key role of antioxidant agents in tailoring mechanical changes in the binder phase. The absence of antioxidants enhances radical formation, oxidation, and cross-linking. These processes lead to progressively increased rigidity and reduced flexibility as a function of the absorbed dose. Complex interactions between photocured components largely influence radical stabilization and material degradation. These findings provide valuable insights for designing novel radiation-resistant binders, enabling the development of solid propellants tailored for reliable, long-term permanence in space, and advancing the knowledge on the applicability of 3D-printed propellants.

Several fields such as particle physics, space exploration, and high-energy physics, use Commercial Off-The-Shelf (COTS) electronic components in a high-radiation operative environment. These operating conditions can cause significant damage to electronic circuits, affecting their operational features and thus the reliability of the entire facility. Qualifying and characterizing these components against radiation is essential to ensure their proper functioning in harsh conditions. This study investigates the effect of stress-testing electronic components used in high-radiation environments with various types of radiation sources. The components were exposed to gamma rays, laser-driven protons, conventionally accelerated protons, and neutrons, analyzing the devices parameters after different irradiation conditions. The results indicate significant degradation in electrical performance due to radiation-induced defects and significant variations of the effects at same dose delivery. We show that laser-driven proton irradiation achieves equivalent stress-testing with doses two orders of magnitude lower and much quicker than other radiation sources, demonstrating a much higher stress-testing efficiency.

Glioblastoma is the most aggressive and treatment-resistant form of primary brain tumors, characterized by rapid invasion and a poor prognosis. Its complex behavior continues to challenge both clinical interventions and research efforts. Mathematical modeling provides a valuable approach to unraveling a tumor’s spatiotemporal dynamics and supporting the development of more effective therapies. In this study, we built on the existing literature by refining and adapting mathematical models to better capture glioblastoma infiltration, using a partial differential equation (PDE) framework to simulate how cancer cell density evolves across both time and space. In particular, the role of cell diffusion and growth in tumor progression and their limitations due to cell crowding and competition were investigated. Experimental data of glioblastoma taken from the literature were exploited for the identification of the model parameters. The improved data reproduction when the limitations of cell diffusion and growth were taken into account proves the relevant impact of the considered mechanisms on the spread of the tumor population, which underscores the potential of the proposed framework.

Hashimoto’s thyroiditis (HT) is a prevalent autoimmune disorder marked by chronic inflammation of the thyroid gland, predominantly affecting children and adolescents. In a previous study, we developed a “maximal” mathematical model of thyroid physiology to simulate the complex interactions within the thyroid gland. The present research introduces an enhanced version of the “maximal” model, integrating the pathophysiological impacts of HT. It specifically models the adverse effects of thyroid peroxidase (TPO) and thyroglobulin (Tg) antibodies (TPOAb and TgAb) on TPO, Tg, sodium iodide symporter (NIS), albeit indirectly, and thyroid volume. Additionally, we present a new “minimal” model offering a streamlined interpretation of thyroid physiology and pathophysiology, designed for faster computational analysis while maintaining essential physiological interactions. Both models were fitted against longitudinal clinical data from patients with HT, assessing the concentrations of Thyroid Stimulating Hormone (TSH), Thyroxine (T4), and thyroid volume over 36 months, in both untreated patients and those receiving levothyroxine (LT4) treatment. The adaptation of the models to data shows that both of them accurately reproduce the available observed clinical outcomes, with the “maximal” model providing more detailed physiological insights but requiring extensive data and longer computation times. In contrast, the “minimal” model, despite exhibiting less realistic TSH oscillations, offers rapid parameter estimation and may be more feasible in clinical settings. These models hold significant potential as tools for detailed study and management of HT, enabling simulations of disease progression and therapeutic responses, thus paving the way for personalized treatment strategies.