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The main potential benefits of rainwater harvesting, namely water saving and storm water management, are easily evaluable at a building scale when well-known behavioral models are used. However, the evaluation is often more complex at an urban scale, due to a lack of building characteristics and demographic data. In the present paper, we propose a method, which is based on the representative building concept that can be used to quantify the potential benefits of rainwater harvesting at different scales, that is, from the building scale to the district and city scales. Particular attention has been paid to the sizing of the system so that it can be used for different rainwater collection purposes. The method has been applied to the city of Turin (Italy) considering different scenarios: 1) domestic use (e.g., toilet flushing and the washing machine), where buildings are independent of each other, and 2) two public uses (the irrigation of public green areas and street washing), for which we have hypothesized that the rainwater collection takes place at a district scale. The non-potable water saving for domestic use varies across the city from 29% to 62%, according to the characteristics of the buildings, while the reduction of the flow peak conveyed to the sewerage system, during extreme storms, is quite constant (in the 57–67% range). Irrigation and street washing require a lower amount of water, thus about 80% of water can be saved, but the retention efficiency is low, and a slight reduction in the flow peaks can be expected. The aim of the methodology presented in this work is to provide a suitable decision-making tool for policy makers and urban planners to evaluate the capability and efficiency of rainwater harvesting systems for buildings, districts, and cities.

The main potential benefits of rainwater harvesting, namely water saving and storm water management, are easily evaluable at a building scale when well-known behavioral models are used. However, the evaluation is often more complex at an urban scale, due to a lack of building characteristics and demographic data. In the present paper, we propose a method, which is based on the representative building concept that can be used to quantify the potential benefits of rainwater harvesting at different scales, that is, from the building scale to the district and city scales. Particular attention has been paid to the sizing of the system so that it can be used for different rainwater collection purposes. The method has been applied to the city of Turin (Italy) considering different scenarios: 1) domestic use (e.g., toilet flushing and the washing machine), where buildings are independent of each other, and 2) two public uses (the irrigation of public green areas and street washing), for which we have hypothesized that the rainwater collection takes place at a district scale. The non-potable water saving for domestic use varies across the city from 29% to 62%, according to the characteristics of the buildings, while the reduction of the flow peak conveyed to the sewerage system, during extreme storms, is quite constant (in the 57–67% range). Irrigation and street washing require a lower amount of water, thus about 80% of water can be saved, but the retention efficiency is low, and a slight reduction in the flow peaks can be expected. The aim of the methodology presented in this work is to provide a suitable decision-making tool for policy makers and urban planners to evaluate the capability and efficiency of rainwater harvesting systems for buildings, districts, and cities.

Background/Objectives: Lung cancer is the leading cause of cancer-related deaths worldwide. Non-Small-Cell Lung Cancer (NSCLC) accounts for 80–90% of all lung cancers. Antibody-Drug Conjugates (ADCs) represent an expanding targeted therapy option for the treatment of NSCLC. The aim is to perform a systematic literature review to evaluate the efficacy and safety profiles of ADCs currently undergoing clinical trials for the treatment of NSCLC. Methods: The study adhered to the Preferred Reporting Items for Systematic reviews and Meta-Analyses (PRISMA) statement. Literature searches were conducted in PubMed, ClinicalTrial.gov and Web of Science databases, covering the period from 2014 to 2024. Only randomized and non-randomized phase II-IV clinical trials focusing on ADC-based therapies for adult patients affected by NSCLC were selected. The Revised Cochrane Risk-of-Bias Tool for Randomized Trials (RoB 2.0) and the Risk of Bias in Non-randomized Studies of Interventions (ROBINS-I) were used to evaluate the overall risk of bias in the included randomized and non-randomized studies, respectively. While GRADE (Grading of Recommendations, Assessment, Development and Evaluations) methodology was used to assess the certainty of the evidence. Efficacy endpoints were categorized based on primary outcomes while safety was assessed through the frequency and severity of Treatment-Emergent Adverse Events (TEAEs), and a qualitative summary of the findings was conducted. Results: A total of seven studies, including three randomized, three non-randomized, and one without specific allocation, were included, comprising 1287 patients, with 693 (54%) men, and an average age of 63 years old. Two studies were deemed to have a low risk of bias, while six had a moderate risk or some concerns. Five ADCs were evaluated: trastuzumab deruxtecan (T-DXd), trastuzumab emtansine (T-DM1), telisotuzumab vedotin, patritumab deruxtecan, and datopotamab deruxtecan (Dato-DXd). T-DXd demonstrated superior efficacy in HER2-overexpressing and HER2-mutant NSCLC, with an ORR of 52.9% and 49.0%, respectively. However, HER2-mutant patients exhibited a longer median DOR (16.8 vs. 6.2 months) but a higher incidence of grade ≥ 3 TEAEs (38.6% vs. 22%). T-DM1 showed modest efficacy, with an ORR of 20% in HER2-overexpressing NSCLC and 6.7% in HER2-mutant patients. Dato-DXd demonstrated improved ORR (26.4% vs. 12.8%) and PFS (4.4 vs. 3.7 months) compared to docetaxel. Patritumab deruxtecan achieved an ORR of 39% in EGFR-mutant NSCLC, while telisotuzumab vedotin exhibited limited activity in c-MET-positive NSCLC (ORR 9%, median DOR 7.5 months). Frequency and severity of TEAEs varied across ADCs, with ILD being a major concern, highlighting the need for strict patient monitoring and early intervention to mitigate severe adverse events. Conclusions: ADCs represent a promising advancement in NSCLC treatment, offering targeted therapeutic options beyond conventional chemotherapy and immunotherapy. T-DXd has emerged as the most effective ADC for HER2-mutant NSCLC with manageable safety profile, whereas Dato-DXd provides a viable alternative for TROP2-expressing tumors. While ADCs offer significant clinical benefits, careful patient selection and proactive management of adverse events remain crucial. Ongoing and future trials will further refine the role of ADCs in personalized NSCLC treatment, potentially expanding their tumor-agnostic use to broader patient populations.

Objective: We aimed to compare the clinical utility and diagnostic accuracy of the ADNEX model, ROMA score, RMI I, and RMI IV, as well as two serum markers (CA125 and HE4) in preoperative discrimination between benign and malignant adnexal masses (AMs). Methods: We conducted a retrospective study extracting all consecutive patients with AMs seen at our Institution between January 2015 and December 2020. Accuracy metrics included sensitivity (SE), specificity (SP), and area under the receiver operating characteristic curve (AUC), and their 95% confidence intervals (CI) were calculated for basic discrimination between AMs. Model performance was evaluated in terms of discrimination ability and clinical utility (net benefit, NB). Results: A total of 581 women were included; 481 (82.8%) had a benign ovarian tumor and 100 (17.2%) had a malignant tumor. The SE and SP of CA125, HE4, ROMA score, RMI I, RMI IV, and ADNEX model were 0.60 (0.54–0.66) and 0.80 (0.76–0.83); 0.39 (0.30–0.49) and 0.96 (0.94–0.98); 0.59 (0.50–0.68) and 0.92 (0.88–0.95); 0.56 (0.46–0.65) and 0.98 (0.96–0.99); 0.54 (0.44–0.63) and 0.96 (0.94–0.98); 0.82 (0.73–0.88) and 0.91 (0.89–0.94), respectively. The overall AUC was 0.76 (0.74–0.79) for CA125, 0.81 (0.78–0.83) for HE4, 0.82 (0.80–0.85) for ROMA, 0.86 (0.84–0.88) for RMI I, 0.83 (0.81–0.86) for RMI IV, and 0.92 (0.90–0.94) for ADNEX. The NB for ADNEX was higher than other biomarkers and models across all decision thresholds between 5% and 50%. Conclusions: The ADNEX model showed a better discrimination ability and clinical utility when differentiating malignant from benign Ams, compared to CA125, HE4, ROMA score, RMI I, and RMI IV.

Objectives: To analyze the role of PCI variation (Δ-PCI) before and after neoadjuvant chemotherapy (NACT) in an interval cytoreductive surgery (ICS) setting with the aim to propose a scoring model for predicting both complete cytoreduction and histopathologic response. Methods: A total of 50 consecutive patients who underwent ICS at our institution were prospectively collected between January-2020 and December-2023. PCI was assessed at exploratory surgery and at ICS. The clinical and histopathological response to NACT was determined by Δ-PCI and CRS. A cut-off value for Δ-PCI, to predict complete cytoreduction, histopathological response, and both together, was identified using a receiver operating characteristic (ROC) curve. The Kaplan–Meier test was used to define disease-free survival (DFS) based on the Δ-PCI cut-off value. Results: Complete cytoreduction was achieved in 82% of patients, with a median Δ-PCI score at ICS of 12 (range 7–29). The remaining 18% had a median Δ-PCI score at IDS of 8 (range 4–11). The best predictor of complete cytoreduction, histopathologic response CRS 3, and both was the Δ-PCI score, with an area under the curve (AUC) of 0.85 (0.73–0.96), 0.98 (0.94–1.00) and 0.88 (0.75–0.96), respectively; ROC curve analysis determined a Δ-PCI cut-off of 8, 17 and 15, respectively. Δ-PCI ≥ 15 as a predictor for both complete cytoreduction and histopathologic response CRS 3 with a median DFS of 26 months for Δ-PCI ≥ 15 versus 12 months for Δ-PCI < 15 (p = 0.02). Conclusions: Δ-PCI (cut-off ≥ 15) is a predictive model for complete cytoreduction, histological response CRS 3, and improved DFS.

We investigate the dynamics of a non-interacting spin system, undergoing coherent Rabi oscillations, in the presence of stochastic resetting. We show that resetting generally induces long-range quantum and classical correlations both in the emergent dissipative dynamics and in the non-equilibrium stationary state. Moreover, for the case of conditional reset protocols -- where the system is reinitialized to a state dependent on the outcome of a preceding measurement -- we show that, in the thermodynamic limit, the spin system can feature collective behavior which results in a phenomenology reminiscent of that occurring in non-equilibrium phase transitions. The discussed reset protocols can be implemented on quantum simulators and quantum devices that permit fast measurement and readout of macroscopic observables, such as the magnetisation. Our approach does not require the control of coherent interactions and may therefore highlight a route towards a simple and robust creation of quantum correlations and collective non-equilibrium states, with potential applications in quantum enhanced metrology and sensing.

We consider closed quantum many-body systems subject to stochastic resetting. This means that their unitary time evolution is interrupted by resets at randomly selected times. When a reset takes place the system is reinitialized to a state chosen from a set of reset states conditionally on the outcome of a measurement taken immediately before resetting. We construct analytically the resulting non-equilibrium stationary state, thereby establishing an explicit connection between quantum quenches in closed systems and the emergent open system dynamics induced by stochastic resetting. We discuss as an application the paradigmatic transverse-field quantum Ising chain. We show that signatures of its ground-state quantum phase transition are visible in the steady state of the reset dynamics as a sharp crossover. Our findings show that a controlled stochastic resetting dynamics allows to design non-equilibrium stationary states of quantum many-body systems, where uncontrolled dissipation and heating can be prevented. These states can thus be created on demand and exploited, e.g., as a resource for quantum enhanced sensing on quantum simulator platforms.

Spin-boson models can describe a variety of physical systems, such as atoms in a cavity or vibrating ion chains. In equilibrium these systems often feature a radical change in their behavior when switching from weak to strong spin-boson interaction. This usually manifests in a transition from a \"dark\" to a \"superradiant\" phase. However, understanding the out-of-equilibrium physics of these models is extremely challenging, and even more so for strong spin-boson coupling. Here we show that non-equilibrium strongly interacting spin-boson systems can mimic some fundamental properties of an associative memory - a system which permits the recognition of patterns, such as letters of an alphabet. Patterns are encoded in the couplings between spins and bosons, and we discuss the dynamics of the spins from the perspective of pattern retrieval in associative memory models. We identify two phases, a \"paramagnetic\" and a \"ferromagnetic\" one, and a crossover behavior between these regimes. The \"ferromagnetic\" phase is reminiscent of pattern retrieval. We highlight similarities and differences with the thermal dynamics of a Hopfield associative memory and show that indeed elements of \"machine learning behavior\" emerge in strongly coupled spin-boson systems.

Spin-boson Hamiltonians are an effective description for numerous quantum many-body systems such as atoms coupled to cavity modes, quantum electrodynamics in circuits and trapped ion systems. While reaching the limit of strong coupling is possible in current experiments, the understanding of the physics in this parameter regime remains a challenge, especially when disorder and dissipation are taken into account. Here we investigate a regime where the many-body spin dynamics can be related to a Ising energy function defined in terms of the spin-boson couplings. While in the coherent weak coupling regime it is known that an effective description in terms of spin Hamiltonian is possible, we show that a similar viewpoint can be adopted in the presence of dissipation and strong couplings. The resulting many-body dynamics features approximately thermal regimes, separated by out-of-equilibrium ones in which detailed balance is broken. Moreover, we show that under appropriately chosen conditions one can even achieve cooling of the spin degrees of freedom. This points towards the possibility of using strongly coupled dissipative spin-boson systems for engineering complex energy landscapes together with an appropriate cooling dynamics.

Incoherent stochastic processes added to unitary dynamics are typically deemed detrimental since they are expected to diminish quantum features such as superposition and entanglement. Instead of exhibiting energy-conserving persistent coherent motion, the dynamics of such open systems feature, in most cases, a steady state, which is approached in the long-time limit from all initial conditions. This can, in fact, be advantageous as it offers a mechanism for the creation of robust quantum correlations on demand without the need for fine-tuning. Here, we show this for a system consisting of two coherently coupled bosonic modes, which is a paradigmatic scenario for the realization of quantum resources such as squeezed entangled states. Rather counterintuitively, the mere addition of incoherent hopping, which results in a statistical coupling between the bosonic modes, leads to steady states with robust quantum entanglement and enables the emergence of persistent coherent non-stationary behavior.