MIND: Multi-Task Incremental Network Distillation

The recent surge of pervasive devices that generate dynamic data streams has underscored the necessity for learning systems to adapt continually to data distributional shifts. To tackle this challenge, the research community has put forth a spectrum of methodologies, including the demanding pursuit of class-incremental learning without replay data. In this study, we present MIND, a parameter isolation method that aims to significantly enhance the performance of replay-free solutions and achieve state-of-the-art results on several widely studied datasets. Our approach introduces two main contributions: two alternative distillation procedures that significantly improve the efficiency of MIND increasing the accumulated knowledge of each sub-network, and the optimization of the BachNorm layers across tasks inside the sub-networks. Overall, MIND outperforms all the state-of-the-art methods for rehearsal-free Class-Incremental learning (with an increment in classification accuracy of approx. +6% on CIFAR-100/10 and +10% on TinyImageNet/10) reaching up to approx. +40% accuracy in Domain-Incremental scenarios. Moreover, we ablated each contribution to demonstrate its impact on performance improvement. Our results showcase the superior performance of MIND indicating its potential for addressing the challenges posed by Class-incremental and Domain-Incremental learning in resource-constrained environments.Comment: Accepted at the 38th AAAI Conference on Artificial Intelligenc

Comparison between hospitalized patients affected or not by COVID-19 (RESILIENCY study)

Dear Editor, in the recent report of Munblit and coworkers [1], authors observed that the combination of clinical features was sufficient to diagnose COVID-19 indicating that laboratory testing is not critical in real-life clinical practice. To date, all patients admitted to Emergency Department with acute respiratory failure and/or fever should be considered as a suspected SARS-CoV-2 infection [2-3], and an early recognition of etiology and the prompt therapeutic management are crucial to improve survival [4-5]. From March to July 2020, we performed a prospective, multicenter study (RESILIENCY study). During the study period, all patients hospitalized for suspected or confirmed COVID-19 were prospectively recruited in 3 large hospitals in Rome, Italy. All patients with suspected SARS-CoV-2 infection, admitted to the hospital in case of fever and/or hypoxemic respiratory failure (PaO2 <60 mmHg at rest in ambient air) or of exacerbation of underlying diseases or severe symptoms not manageable outside the hospital, were evaluated according to a predefined protocol (see Figure 1). Overall, 653 patients were included in the study: 309 (47.3%) patients with confirmed COVID-19 and 344 (52.7%) without COVID-19, hospitalized for other causes. Baseline characteristics and outcomes of the study population showed that the main causes of hospitalization among patients without COVID-19 were: acute heart failure (47%), bacterial pneumonia (38.5%), and pulmonary embolism (9.2%). Overall, 67 (21.7%) patients of COVID-19 group and 45 (13.1%) hospitalized for other causes were admitted to intensive care unit; 30-day mortality was observed in 59 (19%) patients of COVID-19 group and 62 (18%) of non-COVID-19 group. The multivariate analysis about risk factors for COVID-19 etiology at time of hospitalization showed that dry cough (OR 3.76, CI 95% 1.98-7.92, P<0.001), duration of fever>3 days (OR 5.21, CI 95% 2.34-9.21, P<0.001), lymphocytopenia (OR 1.98, CI 95% Downloaded from https://academic.oup.com/cid/advance-article/doi/10.1093/cid/ciaa1745/5989494 by Sapienza Università di Roma user on 01 December 2020 Accepted Manuscript 3 1.27-4.22, P=0.002) and PaO2/FiO2 ratio<250 (OR 4.98, CI 95% 2.22-9.71, P<0.001) were independently associated with COVID-19 etiology, while procalcitonin value>1 ng/ mL (OR 0.21, CI 95% 0.08-0.82, p<0.001), and lactate>2 mmol/L (OR 0.41, CI 95% 0.15-0.77, p<0.001) were associated with non-COVID-19 etiology. Finally, analysis about predictors of 30-day mortality showed that age (per-year increase OR 1.33; CI 95% 1.11-2.10; p<0.001), cardiovascular disease (OR 4.58; CI 95% 2.07-8.25; p<0.001), and ICU admission (OR 2.1; CI 95% 1.48-4.4; p<0.001) were independently associated with all-cause 30-day mortality, while the use of low-molecularweight heparin (OR 0.22, CI 95% 0.03-0.45, p=0.002) was associated with survival. The findings of the present study can be summarized as follows:1) the prompt identification of specific clinical characteristics (like dry cough or duration of fever>3 days), and laboratory findings (like lymphocytopenia, PaO2/FiO2 ratio<250, procalcitonin value>1 ng/ mL, and lactate>2 mmol/L) can help physicians to distinguish rapidly between COVID19 or other etiologies [6]; 2) the application of a standard approach to management of patients with acute respiratory failure and/or fever associated with the knowledge of clinical and laboratory characteristics of COVID-19 can early drive physicians to therapeutic choices; and 3) age, cardiovascular disease, and ICU admission show an independent association with all-cause 30-day mortality [7], while the use of low-molecular-weight heparin was associated with survival [8]. In conclusion, COVID-19 syndrome is characterized by a heterogeneous clinical, laboratoristic, and radiological presentation, especially at its onset [9]. However, the application of a standard approach to management of patients with acute respiratory failure and/or fever and the knowledge of clinical and laboratory characteristics of COVID-19 can early drive therapeutic choic

Measurement of hadronic event shapes in high-p T multijet final states at √s = 13 TeV with the ATLAS detector

A measurement of event-shape variables in proton-proton collisions at large momentum transfer is presented using data collected at s = 13 TeV with the ATLAS detector at the Large Hadron Collider. Six event-shape variables calculated using hadronic jets are studied in inclusive multijet events using data corresponding to an integrated luminosity of 139 fb−1. Measurements are performed in bins of jet multiplicity and in different ranges of the scalar sum of the transverse momenta of the two leading jets, reaching scales beyond 2 TeV. These measurements are compared with predictions from Monte Carlo event generators containing leading-order or next-to-leading order matrix elements matched to parton showers simulated to leading-logarithm accuracy. At low jet multiplicities, shape discrepancies between the measurements and the Monte Carlo predictions are observed. At high jet multiplicities, the shapes are better described but discrepancies in the normalisation are observed. [Figure not available: see fulltext.

Two-particle azimuthal correlations in photonuclear ultraperipheral Pb+Pb collisions at 5.02 TeV with ATLAS

Two-particle long-range azimuthal correlations are measured in photonuclear collisions using 1.7 nb − 1 of 5.02 TeV Pb + Pb collision data collected by the ATLAS experiment at the CERN Large Hadron Collider. Candidate events are selected using a dedicated high-multiplicity photonuclear event trigger, a combination of information from the zero-degree calorimeters and forward calorimeters, and from pseudorapidity gaps constructed using calorimeter energy clusters and charged-particle tracks. Distributions of event properties are compared between data and Monte Carlo simulations of photonuclear processes. Two-particle correlation functions are formed using charged-particle tracks in the selected events, and a template-fitting method is employed to subtract the nonflow contribution to the correlation. Significant nonzero values of the second- and third-order flow coefficients are observed and presented as a function of charged-particle multiplicity and transverse momentum. The results are compared with flow coefficients obtained in proton-proton and proton-lead collisions in similar multiplicity ranges, and with theoretical expectations. The unique initial conditions present in this measurement provide a new way to probe the origin of the collective signatures previously observed only in hadronic collisions

Measurements of inclusive and differential cross-sections of combined t t ¯ γ and tWγ production in the eμ channel at 13 TeV with the ATLAS detector

Abstract: Inclusive and differential cross-sections for the production of top quarks in association with a photon are measured with proton-proton collision data corresponding to an integrated luminosity of 139 fb−1. The data were collected by the ATLAS detector at the LHC during Run 2 between 2015 and 2018 at a centre-of-mass energy of 13 TeV. The measurements are performed in a fiducial volume defined at parton level. Events with exactly one photon, one electron and one muon of opposite sign, and at least two jets, of which at least one is b-tagged, are selected. The fiducial cross-section is measured to be 39.6−2.3+2.7 fb. Differential cross-sections as functions of several observables are compared with state-of-the-art Monte Carlo simulations and next-to-leading-order theoretical calculations. These include cross-sections as functions of photon kinematic variables, angular variables related to the photon and the leptons, and angular separations between the two leptons in the event. All measurements are in agreement with the predictions from the Standard Model

Flowfield analysis of a linear clustered plug nozzle with round-to-square modules

The plug nozzle is one of the advanced expansion devices proposed to improve the overall performance of launcher liquid rocket engines. The present work investigates the three-dimensional flow field generated on this kind of nozzle by partitioning the primary nozzle into modules. A linear plug nozzle has been designed together with modules having two different geometries: a rectangular cross section and round-to-square module. Numerical simulations have been carried out considering the case where all modules of the primary nozzle are active and the case where one module is turned off. The solutions are compared and specific three-dimensional flow structures taking place inside the modules and on the plug are identified. The relationship between these structures and the skin friction distribution within the module and along the plug surface is investigated. Finally, the effect on performance of these three-dimensional flow features is emphasized. (c) 2006 Elsevier Masson SAS. All rights reserved

MIND: Multi-Task Incremental Network Distillation

The recent surge of pervasive devices that generate dynamic data streams has underscored the necessity for learning systems to adapt continually to data distributional shifts. To tackle this challenge, the research community has put forth a spectrum of methodologies, including the demanding pursuit of class-incremental learning without replay data. In this study, we present MIND, a parameter isolation method that aims to significantly enhance the performance of replay-free solutions and achieve state-of-the-art results on several widely studied datasets. Our approach introduces two main contributions: two alternative distillation procedures that significantly improve the efficiency of MIND increasing the accumulated knowledge of each sub-network, and the optimization of the BachNorm layers across tasks inside the sub-networks. Overall, MIND outperforms all the state-of-the-art methods for rehearsal-free Class-Incremental learning (with an increment in classification accuracy of approx. +6% on CIFAR-100/10 and +10% on TinyImageNet/10) reaching up to approx. +40% accuracy in Domain-Incremental scenarios. Moreover, we ablated each contribution to demonstrate its impact on performance improvement. Our results showcase the superior performance of MIND indicating its potential for addressing the challenges posed by Class-incremental and Domain-Incremental learning in resource-constrained environments

Analysis of Three-dimensional Flow Generated by a Linear Aerospike

Linear aerospike nozzles are envisaged as a possible means to improve launcher engine performance. One of the most interesting properties of these nozzles is the possibility of a good integration with the vehicle. To improve the knowledge of the flow-field and performance of aerospike nozzles, they are studied numerically, with particular attention to the differences between the basic two-dimensional nozzle, usually considered in the design phase, and the more realistic three-dimensional nozzle. The study considers also the effect of flight condition, which cannot be neglected because of the characteristic external expansion of aerospike nozzles

Total quality service in digital era

Purpose – Total quality management is a valuable approach to continuously improve the quality of organizations; however, scholars debate its applicability to services, which require specific best practices that are different from those related to manufacturing. Moreover, digitization is pervading all kinds of services, but little has been written about total quality service practices in digital-based companies. For this purpose, the authors provide a holistic model of total quality service that reflects the peculiarities of such companies, guided by the question: how do total quality service practices change in digital-based service organizations? Design/methodology/approach – The authors conduct an illustrative case study on Healthware Group, a global integrated digital health organization, to evaluate theoretical assumptions about total quality service practices in the digital environment. Findings – The findings allow to validate the model provided. In addition, the study enables them to observe the changes the authors are witnessing in service provision in the digital era and the consequent transformation of best practices. To be accurate, the authors cannot refer to a full transformation in digital-based companies but rather to the enrichment and extension of TQS practices. The best illustration of these conclusions has been summarized in a set of propositions corresponding to seven of the key levers of a TQS model. Originality/value – The paper represents the first attempt to discuss the relationship between total quality service and digitalization, offering a set of propositions for academics and insights for practitioners. The model can be used as a tool to visualize the different levers that successful implementation of TQS in digital-based services companies can rely on