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User-centric (UC) distributed massive multiple-input multiple-output (D-mMIMO), also known as cell-free mMIMO, is a pivotal technology for enabling future mobile communication systems. While UC D-mMIMO intrinsically follows a distributed architecture, its processing can be implemented in a distributed or centralized fashion. This paper proposes a comprehensive cost assessment methodology for UC D-mMIMO, capturing its total cost of ownership and factoring in the deployment configuration, processing implementation, computational demands, and fronthaul signaling. The methodology considers two transmission reception point (TRP) deployment strategies. The first focuses only on supporting user equipment (UE) demands, while the other fulfills these requirements and also actively strives to provide a fairer service among UEs. The proposed methodology is then used to perform a techno-economic assessment of the feasibility of centralized versus distributed processing functional splits while varying key costs and TRP capabilities, like antenna and served UE count. Results suggest that with the TRP deployment that only supports the required UE rate, distributed processing is usually the most feasible option for UE demands of up to 50 Mbps, and centralized processing is more cost-effective in other cases. Additionally, when considering the actively fairer TRP deployment, centralized processing becomes cheaper for any UE demands.

Type 1 diabetes (T1D) presents a persistent medical challenge, demanding innovative strategies for sustained glycemic control and enhanced patient well-being. Beta cells are specialized cells in the pancreas that produce insulin, a hormone that regulates blood sugar levels. When beta cells are damaged or destroyed, insulin production decreases, which leads to T1D. Allo Beta Cell Transplantation has emerged as a promising therapeutic avenue, with the goal of reinstating glucose regulation and insulin production in T1D patients. However, the path to success in this approach is fraught with complex immunological hurdles that demand rigorous exploration and resolution for enduring therapeutic efficacy. This exploration focuses on the distinct immunological characteristics inherent to Allo Beta Cell Transplantation. An understanding of these unique challenges is pivotal for the development of effective therapeutic interventions. The critical role of glucose regulation and insulin in immune activation is emphasized, with an emphasis on the intricate interplay between beta cells and immune cells. The transplantation site, particularly the liver, is examined in depth, highlighting its relevance in the context of complex immunological issues. Scrutiny extends to recipient and donor matching, including the utilization of multiple islet donors, while also considering the potential risk of autoimmune recurrence. Moreover, unanswered questions and persistent gaps in knowledge within the field are identified. These include the absence of robust evidence supporting immunosuppression treatments, the need for reliable methods to assess rejection and treatment protocols, the lack of validated biomarkers for monitoring beta cell loss, and the imperative need for improved beta cell imaging techniques. In addition, attention is drawn to emerging directions and transformative strategies in the field. This encompasses alternative immunosuppressive regimens and calcineurin-free immunoprotocols, as well as a reevaluation of induction therapy and recipient preconditioning methods. Innovative approaches targeting autoimmune recurrence, such as CAR Tregs and TCR Tregs, are explored, along with the potential of stem stealth cells, tissue engineering, and encapsulation to overcome the risk of graft rejection. In summary, this review provides a comprehensive overview of the inherent immunological obstacles associated with Allo Beta Cell Transplantation. It offers valuable insights into emerging strategies and directions that hold great promise for advancing the field and ultimately improving outcomes for individuals living with diabetes.

AimIn a recent randomized, multicenter trial (NCT02814838) a short-term anti-inflammatory treatment with ladarixin (LDX; an inhibitor of the CXCR1/2 chemokine receptors) did not show benefit on preserving residual beta cell function in new-onset type 1 diabetes. We present a post hoc analysis of trial patients in the predefined subgroup analysis developed according to baseline daily insulin requirement (DIR) tertiles.MethodA double-blind, randomized (2:1), placebo-controlled study was conducted in 45 men and 31 women (aged 18–46 years) within 100 days of the first insulin administration. Patients received LDX (400 mg twice daily) for three cycles of 14 days on/14 days off, or placebo. The primary endpoint was the area under the curve for C-peptide [AUC (0–120 min)] in response to a 2-h mixed meal tolerance test (MMTT) at week 13 ± 1. Seventy-five patients completed the week 13 MMTT and were divided into three groups according to the DIR tertiles: lower, ≤ 0.23U/kg/die (n = 25); middle, 0.24–0.40 U/kg/die (n = 24); upper, ≥ 0.41 U/kg/die (n = 26).ResultsWhen considering the patients in the upper tertile (HIGH-DIR), C-peptide AUC (0–120 min) at 13 weeks was higher in the LDX group (n = 16) than in the placebo (n = 10) group [difference: 0.72 nmol/L (95% CI 0.9–1.34), p = 0.027]. This difference reduced over time (0.71 nmol/L at 26 weeks, p = 0.04; 0.42 nmol/L at 52 weeks, p = 0.29), while it has never been significant at any time in patients in the lower and/or middle tertile (LOW-DIR). We characterized at baseline the HIGH-DIR and found that endo-metabolic (HOMA-B, adiponectin, and glucagon-to-C-peptide ratio) and immunologic (chemokine (C-C motif) ligand 2 (CCL2)/monocyte chemoattractant protein 1 (MCP1) and Vascular Endothelial Growth Factor (VEGF)) features distinguished this group from LOW-DIR.ConclusionWhile LDX did not prevent the progressive loss of beta-cell function in the majority of treated subjects, the post hoc analysis suggests that it could work in subjects with HIGH-DIR at baseline. As we found differences in endo-metabolic and immunologic parameters within this subgroup, this generates the hypothesis that the interactions between host factors and drug action can contribute to its efficacy. Further research is needed to evaluate this hypothesis.

The article analyzes the total cost of ownership (TCO) of 5G fronthauling solutions based on analog and digital radio-over-fiber (RoF) architectures in cloud radio access networks (C-RANs). The capital and operational expenditures (CAPEX, OPEX) are assessed, for a 10-year period, considering three different RoF techniques: intermediate frequency analog RoF (IF-A-RoF), digital signal processing (DSP) assisted analog RoF (DSP-A-RoF), and digital RoF (D-RoF) based on the common public radio interface (CPRI) specifications. The greenfield deployment scenario under exam includes both fiber trenching (FT) and fiber leasing (FL) options. The TCO is assessed while varying (i) the number of aggregated subcarriers, (ii) the number of three-sector antennas located at the base station, and (iii) the mean fiber-hop length. The comparison highlights the significance that subcarrier aggregation has on the cost efficiency of the analog RoF solutions. In addition, the analysis details the contribution of each cost category to the overall CAPEX and OPEX values. The obtained results indicate that subcarrier aggregation via DSP results in high cost efficiency for a mobile fronthaul network, while a CPRI-based architecture together with FL brings the highest OPEX value.

Computational fluid dynamics (CFD) is currently used in the environmental field to simulate flow and dispersion of pollutants around buildings. However, the closure assumptions of the turbulence usually employed in CFD codes are not always physically based and adequate for all the flow regimes relating to practical applications. The starting point of this work is the performance assessment of the V2F (i.e., v2¯ − f) model implemented in Ansys Fluent for simulating the flow field in an idealized array of two-dimensional canyons. The V2F model has been used in the past to predict low-speed and wall-bounded flows, but it has never been used to simulate airflows in urban street canyons. The numerical results are validated against experimental data collected in the water channel and compared with other turbulence models incorporated in Ansys Fluent (i.e., variations of both k-ε and k-ω models and the Reynolds stress model). The results show that the V2F model provides the best prediction of the flow field for two flow regimes commonly found in urban canopies. The V2F model is also employed to quantify the air-exchange rate (ACH) for a series of two-dimensional building arrangements, such as step-up and step-down configurations, having different aspect ratios and relative heights of the buildings. The results show a clear dependence of the ACH on the latter two parameters and highlight the role played by the turbulence in the exchange of air mass, particularly important for the step-down configurations, when the ventilation associated with the mean flow is generally poor.

All over the world, the rapid urbanization process is challenging the sustainable development of our cities. In 2015, the United Nation highlighted in Goal 11 of the SDGs (Sustainable Development Goals) the importance to “Make cities inclusive, safe, resilient and sustainable”. In order to monitor progress regarding SDG 11, there is a need for proper indicators, representing different aspects of city conditions, obviously including the Land Cover (LC) changes and the urban climate with its most distinct feature, the Urban Heat Island (UHI). One of the aspects of UHI is the Surface Urban Heat Island (SUHI), which has been investigated through airborne and satellite remote sensing over many years. The purpose of this work is to show the present potential of Google Earth Engine (GEE) to process the huge and continuously increasing free satellite Earth Observation (EO) Big Data for long-term and wide spatio-temporal monitoring of SUHI and its connection with LC changes. A large-scale spatio-temporal procedure was implemented under GEE, also benefiting from the already established Climate Engine (CE) tool to extract the Land Surface Temperature (LST) from Landsat imagery and the simple indicator Detrended Rate Matrix was introduced to globally represent the net effect of LC changes on SUHI. The implemented procedure was successfully applied to six metropolitan areas in the U.S., and a general increasing of SUHI due to urban growth was clearly highlighted. As a matter of fact, GEE indeed allowed us to process more than 6000 Landsat images acquired over the period 1992–2011, performing a long-term and wide spatio-temporal study on SUHI vs. LC change monitoring. The present feasibility of the proposed procedure and the encouraging obtained results, although preliminary and requiring further investigations (calibration problems related to LST determination from Landsat imagery were evidenced), pave the way for a possible global service on SUHI monitoring, able to supply valuable indications to address an increasingly sustainable urban planning of our cities.

This study presents 1D analytical solutions for the ensemble variance of reactive scalars in one-dimensional turbulent flows, in case of stationary conditions, homogeneous mean scalar gradient and turbulence, Dirichlet boundary conditions, and first order kinetics reactions. Simplified solutions and sensitivity analysis are also discussed. These solutions represent both analytical tools for preliminary estimations of the concentration variance and upwind spatial reconstruction schemes for CFD (Computational Fluid Dynamics)—RANS (Reynolds-Averaged Navier-Stokes) codes, which estimate the turbulent fluctuations of reactive scalars.