95 research outputs found

    Machine learning of microscopic structure-dynamics relationships in complex molecular systems

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    In many complex molecular systems, the macroscopic ensemble's properties are controlled by microscopic dynamic events (or fluctuations) that are often difficult to detect via pattern-recognition approaches. Discovering the relationships between local structural environments and the dynamical events originating from them would allow unveiling microscopic level structure-dynamics relationships fundamental to understand the macroscopic behavior of complex systems. Here we show that, by coupling advanced structural (e.g., Smooth Overlap of Atomic Positions, SOAP) with local dynamical descriptors (e.g., Local Environment and Neighbor Shuffling, LENS) in a unique dataset, it is possible to improve both individual SOAP- and LENS-based analyses, obtaining a more complete characterization of the system under study. As representative examples, we use various molecular systems with diverse internal structural dynamics. On the one hand, we demonstrate how the combination of structural and dynamical descriptors facilitates decoupling relevant dynamical fluctuations from noise, overcoming the intrinsic limits of the individual analyses. Furthermore, machine learning approaches also allow extracting from such combined structural/dynamical dataset useful microscopic-level relationships, relating key local dynamical events (e.g., LENS fluctuations) occurring in the systems to the local structural (SOAP) environments they originate from. Given its abstract nature, we believe that such an approach will be useful in revealing hidden microscopic structure-dynamics relationships fundamental to rationalize the behavior of a variety of complex systems, not necessarily limited to the atomistic and molecular scales

    Clinical Care Conditions and Needs of Palliative Care Patients from Five Italian Regions: Preliminary Data of the DEMETRA Project

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    In order to plan the right palliative care for patients and their families, it is essential to have detailed information about patients' needs. To gain insight into these needs, we analyzed five Italian local palliative care networks and assessed the clinical care conditions of patients facing the complexities of advanced and chronic disease. A longitudinal, observational, noninterventional study was carried out in five Italian regions from May 2017 to November 2018. Patients who accessed the palliative care networks were monitored for 12 months. Sociodemographic, clinical, and symptom information was collected with several tools, including the Necesidades Paliativas CCOMS-ICO (NECPAL) tool, the Edmonton Symptom Assessment System (ESAS), and interRAI Palliative Care (interRAI-PC). There were 1013 patients in the study. The majority (51.7%) were recruited at home palliative care units. Cancer was the most frequent diagnosis (85.4%), and most patients had at least one comorbidity (58.8%). Cancer patients reported emotional stress with severe symptoms (38.7% vs. 24.3% in noncancer patients; p = 0.001) and were less likely to have clinical frailty (13.3% vs. 43.9%; p < 0.001). Our study confirms that many patients face the last few months of life with comorbidities or extreme frailty. This study contributes to increasing the general knowledge on palliative care needs in a high-income country

    Half-integer Shapiro steps in highly transmissive InSb nanoflag Josephson junctions

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    We investigate a ballistic InSb nanoflag-based Josephson junction with Nb superconducting contacts. The high transparency of the superconductor-semiconductor interfaces enables the exploration of quantum transport with parallel short and long conducting channels. Under microwave irradiation, we observe half-integer Shapiro steps that are robust to temperature, suggesting their possible non-equilibrium origin. Our results demonstrate the potential of ballistic InSb nanoflags Josephson junctions as a valuable platform for understanding the physics of hybrid devices and investigating their non-equilibrium dynamics.Comment: 37 pages, 14 figure

    The Diverticular Disease Registry (DDR Trial) by the Advanced International Mini-Invasive Surgery Academy Clinical Research Network: Protocol for a Multicenter, Prospective Observational Study

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    Diverticular disease is an increasingly common issue, with a variety of clinical presentations and treatment options. However, very few prospective cohort studies explore outcomes between the different presentations and treatments. The Diverticular Disease Registry (DDR Trial) is a multicenter, prospective, observational cohort study on behalf of the Advanced International Mini-Invasive Surgery (AIMS) academy clinical research network. The DDR Trial aims to investigate the short-term postoperative and long-term quality of life outcomes in patients undergoing surgery or medical treatments for diverticular disease. DDR Trial is open to participation by all tertiary-care hospitals. DDR Trial has been registered at ClinicalTriats.gou (NCT 04907383). Data collection will be recorded on Research Electronic Data Capture (REDCap) starting on June 1 , 2021 and will end after 5 years of recruitment. All adult patients with imaging-proven colonic diverticular disease (i.e., symptomatic colonic diverticulosis including diverticular bleeding, diverticulitis, and Symptomatic Uncomplicated Diverticular Disease) will be included. The primary outcome of DDR Trial is quality of life assessment at 12-month according to the Gastrointestinal Quality of Life Index (GIQLI). The secondary outcome is 30-day postoperative outcomes according to the Clavien-Dindo classification. DDR Trial will significantly advance in identifying the optimal care for patients with diverticular disease by exploring outcomes of different presentations and treatments

    The consolidated European synthesis of CO2 emissions and removals for the European Union and United Kingdom:1990-2020

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    Quantification of land surface-atmosphere fluxes of carbon dioxide (CO2) and their trends and uncertainties is essential for monitoring progress of the EU27+UK bloc as it strives to meet ambitious targets determined by both international agreements and internal regulation. This study provides a consolidated synthesis of fossil sources (CO2 fossil) and natural (including formally managed ecosystems) sources and sinks over land (CO2 land) using bottom-up (BU) and top-down (TD) approaches for the European Union and United Kingdom (EU27+UK), updating earlier syntheses (Petrescu et al., 2020, 2021). Given the wide scope of the work and the variety of approaches involved, this study aims to answer essential questions identified in the previous syntheses and understand the differences between datasets, particularly for poorly characterized fluxes from managed and unmanaged ecosystems. The work integrates updated emission inventory data, process-based model results, data-driven categorical model results, and inverse modeling estimates, extending the previous period 1990-2018 to the year 2020 to the extent possible. BU and TD products are compared with the European national greenhouse gas inventory (NGHGI) reported by parties including the year 2019 under the United Nations Framework Convention on Climate Change (UNFCCC). The uncertainties of the EU27+UK NGHGI were evaluated using the standard deviation reported by the EU member states following the guidelines of the Intergovernmental Panel on Climate Change (IPCC) and harmonized by gap-filling procedures. Variation in estimates produced with other methods, such as atmospheric inversion models (TD) or spatially disaggregated inventory datasets (BU), originate from within-model uncertainty related to parameterization as well as structural differences between models. By comparing the NGHGI with other approaches, key sources of differences between estimates arise primarily in activities. System boundaries and emission categories create differences in CO2 fossil datasets, while different land use definitions for reporting emissions from land use, land use change, and forestry (LULUCF) activities result in differences for CO2 land. The latter has important consequences for atmospheric inversions, leading to inversions reporting stronger sinks in vegetation and soils than are reported by the NGHGI. For CO2 fossil emissions, after harmonizing estimates based on common activities and selecting the most recent year available for all datasets, the UNFCCC NGHGI for the EU27+UK accounts for 926g±g13gTggCgyr-1, while eight other BU sources report a mean value of 948 [937,961]gTggCgyr-1 (25th, 75th percentiles). The sole top-down inversion of fossil emissions currently available accounts for 875gTggC in this same year, a value outside the uncertainty of both the NGHGI and bottom-up ensemble estimates and for which uncertainty estimates are not currently available. For the net CO2 land fluxes, during the most recent 5-year period including the NGHGI estimates, the NGHGI accounted for -91g±g32gTggCgyr-1, while six other BU approaches reported a mean sink of -62 [-117,-49]gTggCgyr-1, and a 15-member ensemble of dynamic global vegetation models (DGVMs) reported -69 [-152,-5]gTggCgyr-1. The 5-year mean of three TD regional ensembles combined with one non-ensemble inversion of -73gTggCgyr-1 has a slightly smaller spread (0th-100th percentiles of [-135,+45]gTggCgyr-1), and it was calculated after removing net land-atmosphere CO2 fluxes caused by lateral transport of carbon (crop trade, wood trade, river transport, and net uptake from inland water bodies), resulting in increased agreement with the NGHGI and bottom-up approaches. Results at the category level (Forest Land, Cropland, Grassland) generally show good agreement between the NGHGI and category-specific models, but results for DGVMs are mixed. Overall, for both CO2 fossil and net CO2 land fluxes, we find that current independent approaches are consistent with the NGHGI at the scale of the EU27+UK. We conclude that CO2 emissions from fossil sources have decreased over the past 30 years in the EU27+UK, while land fluxes are relatively stable: positive or negative trends larger (smaller) than 0.07 (-0.61)gTggCgyr-2 can be ruled out for the NGHGI. In addition, a gap on the order of 1000gTggCgyr-1 between CO2 fossil emissions and net CO2 uptake by the land exists regardless of the type of approach (NGHGI, TD, BU), falling well outside all available estimates of uncertainties. However, uncertainties in top-down approaches to estimate CO2 fossil emissions remain uncharacterized and are likely substantial, in addition to known uncertainties in top-down estimates of the land fluxes. The data used to plot the figures are available at 10.5281/zenodo.8148461 (McGrath et al., 2023).</p
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