Array of Josephson junctions with a non-sinusoidal current-phase relation as a model of the resistive transition of unconventional superconductors

An array of resistively and capacitively shunted Josephson junctions with nonsinusoidal current-phase relation is considered for modelling the transition in high-T$_c$ superconductors. The emergence of higher harmonics, besides the simple sinusoid $I_{c}\sin\phi$, is expected for dominant \emph{d}-wave symmetry of the Cooper pairs, random distribution of potential drops, dirty grains, or nonstationary conditions. We show that additional cosine and sine terms act respectively by modulating the global resistance and by changing the Josephson coupling of the mixed superconductive-normal states. First, the approach is applied to simulate the transition in disordered granular superconductors with the weak-links characterized by nonsinusoidal current-phase relation. In granular superconductors, the emergence of higher-order harmonics affects the slope of the transition. Then, arrays of intrinsic Josephson junctions, naturally formed by the CuO$_2$ planes in cuprates, are considered. The critical temperature suppression, observed at values of hole doping close to $p=1/8$, is investigated. Such suppression, related to the sign change and modulation of the Josephson coupling across the array, is quantified in terms of the intensities of the first and second sinusoids of the current-phase relation. Applications are envisaged for the design and control of quantum devices based on stacks of intrinsic Josephson junctions.Comment: Added: comparison with experiments; reference

Job Insecurity and Job Performance: A Serial Mediated Relationship and the Buffering Effect of Organizational Justice

The study aimed to extend the current knowledge of the relationship between job insecurity and performance. In line with traditional stress theories, work-family and burnout were hypothesized as serial mediators of the negative link between job insecurity and job performance. Also, the current study hypothesized that the association between job insecurity and the mediators [i.e., Work-family conflict (WFC) and burnout] could be buffered by perceived organizational justice among employees. Therefore, we empirically tested a moderated serial mediation model. Participants were 370 employees of an Italian multiservice social cooperative. Data were collected using a self-report questionnaire in the aftermath of the COVID-19 pandemic outbreak. The obtained results indicated that WFC and burnout mediated the association between job insecurity and job performance. Furthermore, perceived organizational justice buffered the relationship between job insecurity and WFC. Concerning job burnout, the association with job insecurity was moderated only among employees perceiving medium and high levels of organizational justice. The moderated serial mediation index provided support to the role of organizational justice in decreasing the association between job insecurity and job performance. This study delves deeper into the variables explaining the relationship between job insecurity and job performance by testing a serial process mechanism that involved WFC and burnout. Additionally, the obtained results provide suggestions to organizations and managers regarding the protective role of organizational justice to sustain employees\u2019 mental health and performance. Practical implications at the organizational and managerial level are provided, along with a focus on the actual impact of the pandemic

Resistive transition in granular disordered high Tc superconductors: a numerical study

The resistive transition of granular high-Tc superconductors, characterized by either weak (YBCO-like) or strong (MgB2-like) links, occurs through a series of avalanche-type current-density rearrangements. These rearrangements correspond to the creation of resistive layers, crossing the whole specimen approximately orthogonal to the current-density direction, due to the simultaneous transition of a large number of weak links or grains. The present work shows that exact solution of the Kirchhoff equations for strongly and weakly linked networks of nonlinear resistors, with Josephson-junction characteristics, yield the subsequent formation of resistive layers within the superconductive matrix as temperature increases. Furthermore, the voltage noise observed at the transition is related to the resistive layer formation process. The noise intensity is estimated from the superposition of voltage drop elementary events related to the subsequent resistive layers. At the end of the transition, the layers mix up, the step amplitude decreases, and the resistance curve smooths. This results in the suppression of noise, as experimentally found. Remarkably, a scaling law for the noise intensity with the network size is argued. It allows us to extend the results to networks with arbitrary size and, thus, to real specimen

A Grid platform for the European Civil Protection e-Infrastructure: the Forest Fires use scenario

During the full cycle of the emergency management, Civil Protection operative procedures involve many actors belonging to several institutions playing different roles. In this context the sharing of information is a vital requirement to make correct and effective decisions. Therefore a European-wide technological infrastructure providing a distributed and coordinated access to different kinds of resources (data, information, services, expertise, etc.) could enhance existing Civil Protection applications and even enable new ones. In the recent years Grid technologies have reached a mature state providing a platform for secure and coordinated resource sharing between the participants in the so-called Virtual Organizations. Moreover the Earth and Space Sciences Informatics provide the conceptual tools for modelling the geospatial information shared in Civil Protection applications during its entire life cycle. Therefore a European Civil Protection e-infrastructure could be based on a Grid platform enhanced with Earth Sciences specific services. However Civil Protection applications stress the requirements of Earth Sciences research applications, for example in terms of real-time support. Therefore a set of high-level services specifically tailored for such applications must be built on top of the Grid platform. As a result of a requirement analysis, the FP6 project CYCLOPS has proposed an architectural framework for the future European Civil Protection e-Infrastructure. In this architecture a layer of high-level services tailored to Civil Protection applications is built on top of the EGEE Grid middleware. This architectural approach has been tested implementing a prototype of a grid-enabled RISICO, the application for wild fire risk assessment used by the Italian Civil Protection

Virtual biopsy in prostate cancer: can machine learning distinguish low and high aggressive tumors on MRI?

In the last decades, MRI was proven a useful tool for the diagnosis and characterization of Prostate Cancer (PCa). In the literature, many studies focused on characterizing PCa aggressiveness, but a few have distinguished between low-aggressive (Gleason Grade Group (GG) =3) PCas based on biparametric MRI (bpMRI). In this study, 108 PCas were collected from two different centers and were divided into training, testing, and validation set. From Apparent Diffusion Coefficient (ADC) map and T2-Weighted Image (T2WI), we extracted texture features, both 3D and 2D, and we implemented three different methods of Feature Selection (FS): Minimum Redundance Maximum Relevance (MRMR), Affinity Propagation (AP), and Genetic Algorithm (GA). From the resulting subsets of predictors, we trained Support Vector Machine (SVM), Decision Tree, and Ensemble Learning classifiers on the training set, and we evaluated their prediction ability on the testing set. Then, for each FS method, we chose the best classifier, based on both training and testing performances, and we further assessed their generalization capability on the validation set. Between the three best models, a Decision Tree was trained using only two features extracted from the ADC map and selected by MRMR, achieving, on the validation set, an Area Under the ROC (AUC) equal to 81%, with sensitivity and specificity of 77% and 93%, respectively.Clinical Relevance- Our best model demonstrated to be able to distinguish low-aggressive from high-aggressive PCas with high accuracy. Potentially, this approach could help clinician to noninvasively distinguish between PCas that might need active treatment and those that could potentially benefit from active surveillance, avoiding biopsy-related complications

Advanced e-Infrastructures for civil protection applications : the CYCLOPS project

During the full cycle of the emergency management, Civil Protection operative procedures involve many actors belonging to several institutions (civil protection agencies, public administrations, research centers, etc.) playing different roles (decision-makers, data and service providers, emergency squads, etc.). In this context the sharing of information is a vital requirement to make correct and effective decisions. Therefore a European-wide technologi- cal infrastructure providing a distributed and coordinated access to different kinds of resources (data, information, services, expertise, etc.) could enhance existing Civil Protection applications and even enable new ones. Such European Civil Protection e-Infrastructure should be designed taking into account the specific requirements of Civil Protection applications and the state-of-the-art in the scientific and technological disciplines which could make the emergency management more effective. In the recent years Grid technologies have reached a mature state providing a platform for secure and coordinated resource sharing between the participants collected in the so-called Virtual Organizations. Moreover the Earth and Space Sciences Informatics provide the conceptual tools for modeling the geospatial information shared in Civil Protection applications during its entire lifecycle. Therefore a European Civil Protection e-infrastructure might be based on a Grid platform enhanced with Earth Sciences services. In the context of the 6th Framework Programme the EU co-funded Project CYCLOPS (CYber-infrastructure for CiviL protection Operative ProcedureS), ended in December 2008, has addressed the problem of defining the re- quirements and identifying the research strategies and innovation guidelines towards an advanced e-Infrastructure for Civil Protection. Starting from the requirement analysis CYCLOPS has proposed an architectural framework for a European Civil Protection e-Infrastructure. This architectural framework has been evaluated through the development of prototypes of two operative applications used by the Italian Civil Protection for Wild Fires Risk Assessment (RISICO) and by the French Civil Protection for Flash Flood Risk Management (SPC-GD). The results of these studies and proof-of-concepts have been used as the basis for the definition of research and innovation strategies aiming to the detailed design and implementation of the infrastructure. In particular the main research themes and topics to be addressed have been identified and detailed. Finally the obstacles to the innovation required for the adoption of this infrastructure and possible strategies to overcome them have been discussed

MRI-based radiomics to predict response in locally advanced rectal cancer: comparison of manual and automatic segmentation on external validation in a multicentre study

BACKGROUND: Pathological complete response after neoadjuvant chemoradiotherapy in locally advanced rectal cancer (LARC) is achieved in 15–30% of cases. Our aim was to implement and externally validate a magnetic resonance imaging (MRI)-based radiomics pipeline to predict response to treatment and to investigate the impact of manual and automatic segmentations on the radiomics models. METHODS: Ninety-five patients with stage II/III LARC who underwent multiparametric MRI before chemoradiotherapy and surgical treatment were enrolled from three institutions. Patients were classified as responders if tumour regression grade was 1 or 2 and nonresponders otherwise. Sixty-seven patients composed the construction dataset, while 28 the external validation. Tumour volumes were manually and automatically segmented using a U-net algorithm. Three approaches for feature selection were tested and combined with four machine learning classifiers. RESULTS: Using manual segmentation, the best result reached an accuracy of 68% on the validation set, with sensitivity 60%, specificity 77%, negative predictive value (NPV) 63%, and positive predictive value (PPV) 75%. The automatic segmentation achieved an accuracy of 75% on the validation set, with sensitivity 80%, specificity 69%, and both NPV and PPV 75%. Sensitivity and NPV on the validation set were significantly higher (p = 0.047) for the automatic versus manual segmentation. CONCLUSION: Our study showed that radiomics models can pave the way to help clinicians in the prediction of tumour response to chemoradiotherapy of LARC and to personalise per-patient treatment. The results from the external validation dataset are promising for further research into radiomics approaches using both manual and automatic segmentations. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s41747-022-00272-2

MRI-based radiomics to predict response in locally advanced rectal cancer: comparison of manual and automatic segmentation on external validation in a multicentre study

Background: Pathological complete response after neoadjuvant chemoradiotherapy in locally advanced rectal cancer (LARC) is achieved in 15–30% of cases. Our aim was to implement and externally validate a magnetic resonance imaging (MRI)-based radiomics pipeline to predict response to treatment and to investigate the impact of manual and automatic segmentations on the radiomics models. Methods: Ninety-five patients with stage II/III LARC who underwent multiparametric MRI before chemoradiotherapy and surgical treatment were enrolled from three institutions. Patients were classified as responders if tumour regression grade was 1 or 2 and nonresponders otherwise. Sixty-seven patients composed the construction dataset, while 28 the external validation. Tumour volumes were manually and automatically segmented using a U-net algorithm. Three approaches for feature selection were tested and combined with four machine learning classifiers. Results: Using manual segmentation, the best result reached an accuracy of 68% on the validation set, with sensitivity 60%, specificity 77%, negative predictive value (NPV) 63%, and positive predictive value (PPV) 75%. The automatic segmentation achieved an accuracy of 75% on the validation set, with sensitivity 80%, specificity 69%, and both NPV and PPV 75%. Sensitivity and NPV on the validation set were significantly higher (p = 0.047) for the automatic versus manual segmentation. Conclusion: Our study showed that radiomics models can pave the way to help clinicians in the prediction of tumour response to chemoradiotherapy of LARC and to personalise per-patient treatment. The results from the external validation dataset are promising for further research into radiomics approaches using both manual and automatic segmentations

Heart Failure With Mid-range or Recovered Ejection Fraction: Differential Determinants of Transition

The recent definition of an intermediate clinical phenotype of heart failure (HF) based on an ejection fraction (EF) of between 40% and 49%, namely HF with mid-range EF (HFmrEF), has fuelled investigations into the clinical profile and prognosis of this patient group. HFmrEF shares common clinical features with other HF phenotypes, such as a high prevalence of ischaemic aetiology, as in HF with reduced EF (HFrEF), or hypertension and diabetes, as in HF with preserved EF (HFpEF), and benefits from the cornerstone drugs indicated for HFrEF. Among the HF phenotypes, HFmrEF is characterised by the highest rate of transition to either recovery or worsening of the severe systolic dysfunction profile that is the target of disease-modifying therapies, with opposite prognostic implications. This article focuses on the epidemiology, clinical characteristics and therapeutic approaches for HFmrEF, and discusses the major determinants of transition to HFpEF or HFrEF