Heavy flavour jet substructure

We present a comprehensive study of energy correlation functions and jet angu- larities for heavy-flavour QCD jets. In particular, we discuss the possibility of using these observables to expose the dead cone effect, i.e. the suppression of collinear QCD radiation around massive quarks, and to investigate the sensitivity of different observable definitions to the presence of quark masses. Our calculations are presented as all-order resummed predictions at next-to-leading-logarithmic accuracy, matched to (partial) fixed-order results to obtain a better description of the transition around the dead cone threshold. We also compare our analytic results with Pythia, Herwig and Sherpa Monte Carlo predictions to estimate the impact of non-perturbative contributions such as hadronisation, underlying events and B-hadron decays

Prognostic Impact of IMDC Category Shift From Baseline to Nivolumab Initiation in Metastatic Renal Cell Carcinoma: A Sub-Analysis of the MEET-URO 15 Study

Introduction: The International Metastatic Renal Cell Carcinoma Database Consortium (IMDC) score is the most important prognostic score to stratify patients with metastatic renal cell carcinoma (mRCC), helping to guide treatment choice in first line. We hypothesized that IMDC change may also exert a prognostic role in subsequent lines of mRCC therapy. Methods: Meet-URO 15 is a multicenter Italian study of patients with mRCC receiving nivolumab as a second or subsequent line of therapy. This posthoc analysis aimed to evaluate the overall survival (OS) and progression-free survival (PFS) from nivolumab start as primary endpoints, overall response rate (ORR) and disease-control rate (DCR) as secondary endpoints, according to the change in the IMDC category from the first-line setting (baseline) to nivolumab start. Patients with available prognostic IMDC category information at baseline and before nivolumab were included. Results: 492 patients were included in the analysis. At baseline, 165 (33.5%), 287 (58.3%), and 40 patients (8.2%) had favorable, intermediate, and poor IMDC categories, respectively. Before nivolumab, 364 patients (73.9%) remained in the same prognostic category as at baseline, 27 (5.5%) improved, and 101 (20.5%) deteriorated. Significantly longer mPFS (P =.01) and mOS (P <.01) were reached by patients with a stable favorable group compared to those worsening to intermediate/poor. A longer mOS was also achieved from intermediate/poor patients who improved their IMDC category before nivolumab compared to those remaining stable/worsening (P <.01 and P =.04, respectively). Maintaining IMDC category stability from baseline to nivolumab determined a more consistent DCR in favorable patients (P =.03). Overall, patients who improved their IMDC risk score reached better survival outcomes than those who remained stable/deteriorated. Conclusions: In our sub-analysis, the shift in the IMDC risk category appears to be a helpful prognostic tool for assessing the outcomes of patients with mRCC treated with ≥2nd line nivolumab

Probabilistic Fusion Framework Combining CNNs and Graphical Models for Multiresolution Satellite and UAV Image Classification

Image classification - or semantic segmentation - from input multiresolution imagery is a demanding task. In particular, when dealing with images of the same scene collected at the same time by very different acquisition systems, for example multispectral sensors onboard satellites and unmanned aerial vehicles (UAVs), the difference between the involved spatial resolutions can be very large and multiresolution information fusion is particularly challenging. This work proposes two novel multiresolution fusion approaches, based on deep convolutional networks, Bayesian modeling, and probabilistic graphical models, addressing the challenging case of input imagery with very diverse spatial resolutions. The first method aims to fuse the multimodal multiresolution imagery via a posterior probability decision fusion framework, after computing posteriors on the multiresolution data separately through deep neural networks or decision tree ensembles. The optimization of the parameters of the model is fully automated by also developing an approximate formulation of the expectation maximization (EM) algorithm. The second method aims to perform the fusion of the multimodal multiresolution information through a pyramidal tree structure, where the imagery can be inserted, modeled, and analyzed at its native resolutions. The application is to the semantic segmentation of areas affected by wildfires for burnt area mapping and management. The experimental validation is conducted with UAV and satellite data of the area of Marseille, France. The code is available at https://github.com/Ayana-Inria/BAS_UAV_satellite_fusion

Status of the Cryogenic Anti-Coincidence Detector (CryoAC) for the Athena X-Ray Integral Field Unit (X-IFU)

The Cryogenic Anti-Coincidence detector (CryoAC) is a critical component of the Athena X-ray Integral Field Unit (X-IFU), in order to fully exploit the instrument performance in the pursuit of high-resolution X-ray spectroscopy with Transition Edge Sensor (TES) detectors.Athena will be the upcoming large X-ray observatory by the European Space Agency (ESA) spanning the energy range of 0.2 to 12 keV. Recently, the mission has successfully undergone a redefinition process to align with new parameters set by ESA, and the launch is now scheduled for the mid-2030s. The X-ray Integral Field Unit (X-IFU) represents one of the two instrumental components within the payload, functioning as a cryogenic spectrometer with a spectral resolution of about 4 eV at 7 keV. In this configuration, the CryoAC serves to mitigate the impact of cosmic ray-induced events on the spectrometer TES detectors, which compromises the sensitivity of X-ray measurements. The detector aims to identify and veto non-X-ray events, allowing measurement of faint or distant X-ray sources that will be submerged by background events.In particular, we will present the design and first experimental results of a new CryoAC sample, namely DM#144, developed on the basis of the experience gained with the last CryoAC prototypes. It is a possible candidate for the CryoAC DM1.1, the model to be tested in the future X-IFU FPA Demontration Model 1.1 campaign.Our goal is to provide a comprehensive overview of the current status of the CryoAC for the Athena X-IFU TES detector, offering valuable insights into the ongoing development an design changes of the detector

Optimised scheduling of a cogenerative subnetwork based on a micro gas turbine and thermal storage with the addition of an innovative solar assisted heat pump and Ni-Zn battery

The Innovative Energy Systems (IES) laboratory at the University of Genoa features a plant configuration comprising a micro gas turbine, latent heat thermal energy storage, an innovative heat pump system connected to solar façade panels, and a NiZn battery. This study presents the optimization of four distinct sub-plant configurations, focusing on their economic and environmental performance across different seasons (January, April, July, and October) under two market scenarios (no selling price or selling price equal to buying price). A genetic algorithm-based tool is developed for the optimized energy scheduling of these configurations, taking into account the operational characteristics of programmable, non-programmable energy sources and energy storage devices. The analysis highlighted that when the selling price is equal to zero, the system is optimised to improve sell-consumption. The addition of the battery or the heat pump to the system always leads to reduction of operational costs compared to the baseline case with only the micro gas turbine and thermal energy storage. Notably, the heat pump alone provides greater cost benefits than the battery, although the combined use of both systems yields the highest cost reductions ranging, depending on the month, up to − 16.9% in the “no sell” scenario and up to − 12.3% when selling and buying prices are equal. Regarding the CO2 emissions, both components lead to an emission reduction in the “no sell” scenario while only the HP guarantees an emission reduction during the “equal to buy” scenario, in both cases up to − 20.5% less. This analysis highlights the economic and environmental advantages of integrating NiZn battery storage and a solar-assisted heat pump into the energy system, demonstrating cost savings and emission reductions across various market conditions and seasonal demands

Winding Test Results of an Innovative Technique for Block Coil Curved Dipoles in the Development of a Gantry for Hadron-Therapy

The Superconducting Ion Gantry (SIG) project is the INFN (Istituto Nazionale di Fisica Nucleare) participation in the EuroSIG collaboration between INFN, CNAO, CERN and MedAustron. The EuroSIG main focus is on the exploration of new concepts and the prototype development of superconducting magnets used in hadron-therapy treatments. More specifically, in the SIG project, we are studying the most critical aspects of a 430 MeV/u superconducting carbon-ion gantry and particular attention is given to the design of 45-degree cosθ dipoles and the construction and testing of a 30-degree demonstrator. Although the baseline of the project is centered on cosθ-type magnets, we are working on an alternative strategy to mitigate the risk of failure in the construction of the demonstrator. This is a block coil type solution to avoid, with a simpler geometry, the difficulties of winding a curved cosθ dipole with significantly small curvature radius. In this context, an innovative winding technique was developed and tests have been conducted to confirm its feasibility. This contribution presents the results obtained from the winding tests in order to show the effectiveness of the method adopted to wind this type of coils and highlight possible improvements. In addition, an electromagnetic design concept for curved block coil dipoles has been developed, with the intention of proposing an optimized solution for the geometry of the coils, along with the method they can be wound

Medullary carcinomas of the nonampullary small intestine: association with coeliac disease, mismatch repair deficiency, PD‐L1 expression, and favourable prognosis

Aim: Gastrointestinal medullary carcinoma is a rare histologic subtype of adenocarcinoma. As nonampullary small bowel medullary carcinomas (SB-MCs) are poorly characterized, we aimed to analyse their clinicopathologic and immunohistochemical features and to compare them with nonmedullary small bowel adenocarcinomas (NM-SBAs). Methods and Results: Surgically resected SBAs collected through the Small Bowel Cancer Italian Consortium were classified as SB-MCs (carcinomas with ≥50% of tumour fulfilling the typical histologic criteria of MC) or NM-SBAs. Immunohistochemistry for cytokeratin (CK)7, CK20, CDX2, programmed death-ligand 1 (PD-L1) and mismatch repair proteins was performed in both SB-MCs and NM-SBAs. SB-MCs were also tested for CK8/18, synaptophysin, SMARCB1, SMARCA2, SMARCA4, and ARID1A and for Epstein–Barr virus (EBV)-encoded RNAs by in-situ hybridization. MLH1 promoter methylation status was evaluated in MLH1-deficient cases. Eleven SB-MCs and 149 NM-SBAs were identified. One (9%) SB-MC was EBV-positive, while 10 (91%) harboured mismatch repair deficiency (dMMR). MLH1 promoter hypermethylation was found in all eight dMMR SB-MCs tested. Switch/sucrose nonfermentable deficiency was seen in two (18%) SB-MCs, both with isolated loss of ARID1A. Compared with NM-SBAs, SB-MCs exhibited an association with coeliac disease (P < 0.001), higher rates of dMMR (P < 0.001), and PD-L1 positivity by both tumour proportion score and combined positive score (P < 0.001 for both), and a lower rate of CK20 expression (P = 0.024). Survival analysis revealed a better prognosis of SB-MC patients compared to NM-SBA cases (P = 0.02). Conclusion: SB-MCs represent a distinct histologic subtype, with peculiar features compared to NM-SBAs, including association with coeliac disease, dMMR, PD-L1 expression, and better prognosis

Hydrophobic iron oxide nanoparticles: Controlled synthesis and phase transfer via flash nanoprecipitation

Iron oxide nanoparticles (IONPs) synthesized via thermal decomposition find diverse applications in biomedicine owing to precise control of their physico-chemical properties. However, use in such applications requires phase transfer from organic solvent to water, which remains a bottleneck. Through the thermal decomposition of iron oleate (FeOl), we systematically investigate the impact of synthesis conditions such as oleic acid (OA) amount, temperature increase rate, dwell time, and solvent on the size, magnetic saturation, and crystallinity of IONPs. Solvent choice significantly influences these properties, manipulating which, synthesis of monodisperse IONPs within a tunable size range (10-30 nm) and magnetic properties (75 to 42 Am(2)Kg-(1)) is obtained. To enable phase transfer of IONPs, we employ flash nanoprecipitation (FNP) for the first time as a method for scalable and precise size control, demonstrating its potential over conventional methods. Poly(lactic-co-glycolic acid) (PLGA)-coated IONPs with hydrodynamic diameter (H-d) in the range of 250 nm, high colloidal stability and high IONPs loadings up to 43% were obtained, such physicochemical properties being tuned exclusively by the size and hydrophobicity of starting IONPs. They showed no discernible cytotoxicity in human dermal fibroblasts, highlighting the applicability of FNP as a novel method for the functionalization of hydrophobic IONPs for biomedicine