Work Fluctuations in Ergotropic Heat Engines.

We study the work fluctuations in ergotropic heat engines, namely two-stroke quantum Otto engines where the work stroke is designed to extract the ergotropy (the maximum amount of work by a cyclic unitary evolution) from a couple of quantum systems at canonical equilibrium at two different temperatures, whereas the heat stroke thermalizes back the systems to their respective reservoirs. We provide an exhaustive study for the case of two qutrits whose energy levels are equally spaced at two different frequencies by deriving the complete work statistics. By varying the values of temperatures and frequencies, only three kinds of optimal unitary strokes are found: the swap operator U1, an idle swap U2 (where one of the qutrits is regarded as an effective qubit), and a non-trivial permutation of energy eigenstates U3, which indeed corresponds to the composition of the two previous unitaries, namely U3=U2U1.

Laser scanner and UAV digital photogrammetry as support tools for cosmic-ray muon radiography applications: an archaeological case study from Italy.

The use of light detection and ranging technologies, i.e. terrestrial laser scanner (TLS), airborne laser scanner (ALS) and mobile laser scanner (MLS), together with the unmanned aerial vehicles digital photogrammetry (UAV-DP) and satellite data are proving to be fundamental tools to carry out reliable muographic measurement campaigns.

How big is Big Data? A comprehensive survey of data production, storage, and streaming in science and industry.

The contemporary surge in data production is fueled by diverse factors, with contributions from numerous stakeholders across various sectors. Comparing the volumes at play among different big data entities is challenging due to the scarcity of publicly available data. This survey aims to offer a comprehensive perspective on the orders of magnitude involved in yearly data generation by some public and private leading organizations, using an array of online sources for estimation.

Tissue Equivalent Curved Organic X-ray Detectors Utilizing High Atomic Number Polythiophene Analogues.

Organic semiconductors are a promising material candidate for X-ray detection. However, the low atomic number (Z) of organic semiconductors leads to poor X-ray absorption thus restricting their performance. Herein, the authors propose a new strategy for achieving high-sensitivity performance for X-ray detectors based on organic semiconductors modified with high -Z heteroatoms.

Machine learning approaches in microbiome research: challenges and best practices.

Microbiome data predictive analysis within a machine learning (ML) workflow presents numerous domain-specific challenges involving preprocessing, feature selection, predictive modeling, performance estimation, model interpretation, and the extraction of biological information from the results. To assist decision-making, we offer a set of recommendations on algorithm selection, pipeline creation and evaluation, stemming from the COST Action ML4Microbiome. We compared the suggested approaches on a multi-cohort shotgun metagenomics dataset of colorectal cancer patients, focusing on their performance in disease diagnosis and biomarker discovery.

Gadolinium-Doped Carbon Nanodots as Potential Anticancer Tools for Multimodal Image-Guided Photothermal Therapy and Tumor Monitoring.

This study focuses on the synthesis and characterization of gadolinium-doped carbon nanodots (CDs-Gd) and their potential applications in multimodal imaging and precision cancer therapy. CDs-Gd were synthesized through a solvothermal decomposition method combining citric acid, GdCl, and urea. The incorporation of Gd ions within the carbonaceous structure resulted in stable CDs-Gd with a peculiar architecture that retained optical and paramagnetic properties.

3-APTES on Dendritic Fibrous Mesoporous Silica Nanoparticles for the pH-Controlled Release of Corrosion Inhibitors.

Mesoporous silica nanoparticles (MSNPs) are currently used in different fields like catalysis, nanomedicine, and conservation science, taking advantage of their high surface area. Here, we synthesized and functionalized mesoporous dendritic fibrous nanoparticles to realize a smart delivery system of protective agents for metals. Different MSNPs were obtained via the microemulsion method followed by a hydrothermal or refluxing treatment at different w/o ratios, times, and temperatures.

Multiple neuron clusters on Micro-Electrode Arrays as an in vitro model of brain network.

Understanding the brain functioning is essential for governing brain processes with the aim of managing pathological network dysfunctions. Due to the morphological and biochemical complexity of the central nervous system, the development of general models with predictive power must start from in vitro brain network engineering. In the present work, we realized a micro-electrode array (MEA)-based in vitro brain network and studied its emerging dynamical properties.

Quantitative T1 mapping detects blood-brain barrier breakdown in apparently non-enhancing multiple sclerosis lesions.

Objectives: The disruption of the blood-brain barrier (BBB) is a key and early feature in the pathogenesis of demyelinating multiple sclerosis (MS) lesions and has been neuropathologically demonstrated in both active and chronic plaques. The local overt BBB disruption in acute demyelinating lesions is captured as signal hyperintensity in post-contrast T1-weighted images because of the contrast-related shortening of the T1 relaxation time. On the contrary, the subtle BBB disruption in chronic lesions is not visible at conventional radiological evaluation but it might be of clinical relevance.

Monte Carlo Simulations Corroborate PET-Measured Discrepancies in Activity Assessments of Commercial Y Vials.

In a recent multicenter study, discrepancies between PET/CT-measured activity and vendor-calibrated activity for Y glass and resin microspheres were found. In the present work, the origin of these discrepancies was investigated by Monte Carlo (MC) simulations. Three vial configurations, containing Y-chloride, Y-labeled glass microspheres, and Y-labeled resin microspheres, were modeled with GAMOS, and the electric signal generated in an activity meter was simulated.

Updating Y Voxel S-Values including internal Bremsstrahlung: Monte Carlo study and development of an analytical model.

Purpose: Internal Bremsstrahlung (IB) is a process accompanying β-decay but neglected in Voxel S-Values (VSVs) calculation. Aims of this work were to calculate, through Monte Carlo (MC) simulation, updated Y-VSVs including IB, and to develop an analytical model to evaluate Y-VSVs for any voxel size of practical interest.

Methods: GATE (Geant4 Application for Tomographic Emission) was employed for simulating voxelized geometries of soft tissue, with voxels sides l ranging from 2 to 6 mm, in steps of 0.

Secondary Structures of MERS-CoV, SARS-CoV, and SARS-CoV-2 Spike Proteins Revealed by Infrared Vibrational Spectroscopy.

All coronaviruses are characterized by spike glycoproteins whose S1 subunits contain the receptor binding domain (RBD). The RBD anchors the virus to the host cellular membrane to regulate the virus transmissibility and infectious process. Although the protein/receptor interaction mainly depends on the spike's conformation, particularly on its S1 unit, their secondary structures are poorly known.

TRAX-CHEMxt: Towards the Homogeneous Chemical Stage of Radiation Damage.

The indirect effect of radiation plays an important role in radio-induced biological damages. Monte Carlo codes have been widely used in recent years to study the chemical evolution of particle tracks. However, due to the large computational efforts required, their applicability is typically limited to simulations in pure water targets and to temporal scales up to the µs.

Cryomilling of Isotope-Enriched Ti Powders for HIVIPP Deposition to Manufacture Targets for Nuclear Cross Section Measurement.

The realization of isotopically enriched Ti targets for nuclear cross-section measurements requires particular attention, from the starting material preparation up to the deposition technique. In this work, a cryomilling process was developed and optimized, aimed at reducing the size of Ti metal sponge as provided by the supplier (size up to 3 mm), to the optimal size of 10 µm, to fit the High Energy Vibrational Powder Plating technique used for target manufacturing. The optimization of the cryomilling protocol and the HIVIPP deposition using Ti material was thus performed.

Survey on the interest and commitment of AIFM members to scientific activities (SicAS) - The initiative of the FutuRuS working group.

Purpose: The "FutuRuS" working group of the Italian Association of Medical Physics and Health Physics (AIFM) designed a survey (SicAS) to get feedback from its members regarding their interests and their experience in taking part in scientific activities and events, with the objective of focusing future efforts of the AIFM towards increasing the scientific activity of the medical physics expert (MPE).

Methods: SicAS was sent out in March 2022 to all AIFM members by newsletter and official communication. SicAS was structured into three sections: personal information and institution of affiliation information, involvement in scientific activities, interest in and commitment to scientific activities.

First Results on Zinc Oxide Thick Film Deposition by Inverted Magnetron Sputtering for Cyclotron Solid Targets Production.

The magnetron sputtering technique has been investigated in recent years with ever-growing interest as a verifiable solid target manufacturing technology aimed at the production of medical radionuclides by using low-energy cyclotron accelerators. However, the possible loss of high-cost materials prevents access to work with isotopically enriched metals. The need for expensive materials for the supply of the growing demand for theranostic radionuclides makes the material-saving approach and recovery essential for the radiopharmaceutical field.

Quality assessment, variability and reproducibility of anatomical measurements derived from T1-weighted brain imaging: The RIN-Neuroimaging Network case study.

Initiatives for the collection of harmonized MRI datasets are growing continuously, opening questions on the reliability of results obtained in multi-site contexts. Here we present the assessment of the brain anatomical variability of MRI-derived measurements obtained from T1-weighted images, acquired according to the Standard Operating Procedures, promoted by the RIN-Neuroimaging Network. A multicentric dataset composed of 77 brain T1w acquisitions of young healthy volunteers (mean age = 29.

Internal Bremsstrahlung, the missing process in beta decay Monte Carlo simulation: The relevance in P Dose-Point-Kernel estimation.

Purpose: In nuclear medicine, Dose Point Kernels (DPKs), representing the energy deposited all around a point isotropic source, are extensively used for dosimetry and are usually obtained by Monte Carlo (MC) simulations. For beta-decaying nuclides, DPK is usually estimated neglecting Internal Bremsstrahlung (IB) emission, a process always accompanying the beta decay and consisting in the emission of photons having a continuous spectral distribution. This work aims to study the significance of IB emission for DPK estimation in the case of P and provide DPK values corrected for the IB photon contribution.

Quantification of pulmonary involvement in COVID-19 pneumonia: an upgrade of the software for lung CT segmentation.

Computed tomography (CT) scans are used to evaluate the severity of lung involvement in patients affected by COVID-19 pneumonia. Here, we present an improved version of the automatic segmentation software ( 2), which implements a cascade of three deep neural networks (DNNs) to segment the lungs and the lung lesions associated with COVID-19 pneumonia. The first network (BB-net) defines a bounding box enclosing the lungs, the second one (U-net ) outputs the mask of the lungs, and the final one (U-net ) generates the mask of the COVID-19 lesions.

LIDAL, a Time-of-Flight Radiation Detector for the International Space Station: Description and Ground Calibration.

LIDAL (Light Ion Detector for ALTEA, Anomalous Long-Term Effects on Astronauts) is a radiation detector designed to measure the flux, the energy spectra and, for the first time, the time-of-flight of ions in a space habitat. It features a combination of striped silicon sensors for the measurement of deposited energy (using the ALTEA device, which operated from 2006 to 2012 in the International Space Station) and fast scintillators for the time-of-flight measurement. LIDAL was tested and calibrated using the proton beam line at TIFPA (Trento Institute for Fundamental Physics Application) and the carbon beam line at CNAO (National Center for Oncology Hadron-therapy) in 2019.

High-Throughput Microscopy Analysis of Mitochondrial Membrane Potential in 2D and 3D Models.

Recent proteomic, metabolomic, and transcriptomic studies have highlighted a connection between changes in mitochondria physiology and cellular pathophysiological mechanisms. Secondary assays to assess the function of these organelles appear fundamental to validate these -omics findings. Although mitochondrial membrane potential is widely recognized as an indicator of mitochondrial activity, high-content imaging-based approaches coupled to multiparametric to measure it have not been established yet.

: a new crystallographic machine learning platform for crystal system determination.

Determination of the crystal system and space group is the first step of crystal structure analysis. Often this turns out to be a bottleneck in the material characterization workflow for polycrystalline compounds, thus requiring manual interventions. This work proposes a new machine-learning (ML)-based web platform, (Crystallography MachinE LeArning), for crystal systems classification.

A multicenter evaluation of a deep learning software (LungQuant) for lung parenchyma characterization in COVID-19 pneumonia.

Background: The role of computed tomography (CT) in the diagnosis and characterization of coronavirus disease 2019 (COVID-19) pneumonia has been widely recognized. We evaluated the performance of a software for quantitative analysis of chest CT, the LungQuant system, by comparing its results with independent visual evaluations by a group of 14 clinical experts. The aim of this work is to evaluate the ability of the automated tool to extract quantitative information from lung CT, relevant for the design of a diagnosis support model.

Proton boron capture therapy (PBCT) induces cell death and mitophagy in a heterotopic glioblastoma model.

Despite aggressive therapeutic regimens, glioblastoma (GBM) represents a deadly brain tumor with significant aggressiveness, radioresistance and chemoresistance, leading to dismal prognosis. Hypoxic microenvironment, which characterizes GBM, is associated with reduced therapeutic effectiveness. Moreover, current irradiation approaches are limited by uncertain tumor delineation and severe side effects that comprehensively lead to unsuccessful treatment and to a worsening of the quality of life of GBM patients.