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

\u201cWoulda, coulda, shoulda\u201d. Workers\u2019 proactivity in the association between emotional demands and mental health

The present study aimed to explore the mediating role of hostile customer relations in the association between emotional dissonance and workers\u2019 mental health. Moreover, the moderating role of proactive personality as a buffer against hostile customer relations was assessed. Emotional demands become crucial within professions that involve a direct relationship with clients and, if poorly managed, can negatively affect workers\u2019 health and performance. Accordingly, data were collected on a sample of n = 918 mass-retail employees working for one of the leading Italian supermarket companies. Most participants were women (62.7%) with a mean age = 40.38 (SD = 7.68). The results of a moderated mediation analysis revealed that emotional dissonance was related to more hostile customer relations that, in turn, were associated with higher rates of mental health symptoms. Proactive personality emerged as a protecting factor that prevented the onset of conflicts with clients, particularly among workers experiencing high levels of emotional dissonance. The identification of resources enabling management of emotional demands could suggest suitable adaptive strategies for customer-facing roles, thus preventing the occurrence of adverse mental health symptoms

Health, Stress and Technologies : Integrating Technology Acceptance and Health Belief Models for Smartphone-Based Stress Intervention

Work-related stress significantly jeopardizes employees’ physical and mental health due to the considerable time they spend at work. Smartphone-based interventions provide a promising solution, eliminating traditional face-to-face interventions’ barriers. However, the elements that influence workers’ intentions to use this still remain unexplored. This study explores the link between health belief model (HBM) and technology acceptance model (TAM) factors. In this study, 336 Italian workers (64% female) answered an online questionnaire. We employed a structural equation model (SEM) to analyze the data. The results unveiled an indirect relationship: individuals perceiving health risks were more inclined to use stress-management apps, mediated by perceived utility (PU). This study underscores the significant potential of integrating the HBM with the TAM in predicting users’ preparedness for smartphone-based health interventions. These findings not only hold substantial value but also illuminate a path forward for professionals and organizations, offering insights to tailor and optimize smartphone tools for stress management and the promotion of workplace well-being. Ultimately, this research paves the way for the cultivation of healthier work environments, marking a noteworthy contribution to the field

Transient Effects of Self-adjustment of Pressure Reducing Valves

AbstractPressure control strategy through Pressure Reducing Valves (PRV) has been deeply investigated as management strategy, aimed at water leakages reduction avoiding very expensive pipe replacement programs. On the contrary, few experimental data are available in literature, with regard to PRV transient behavior in terms of its response to incoming pressure waves, as well as the time required for achieving the pressure set point. In this paper, the results of some experimental tests are presented. The PRV is installed in a single high density polyethylene pipe and transients are generated by operating the downstream end valve. Two types of tests are considered: a partial valve closure and opening simulating a water demand decrease and increase, respectively. The analysis of the experimental pressure traces points out the valuable effects of the PRV on transient characteristics with respect to the case of a partially closed in-line valve with a constant opening degree

Depression of early phase of HTLV-I infection in vitro mediated by human beta-interferon.

Natural human interferon beta (beta-IFN) was tested during the early phase of in vitro infection with HTLV-I virus of human cord blood mononuclear cells (CBL), to evaluate whether its antiviral and immunomodulating effects might prevent spreading of infection in the host. beta-IFN was found to reduce HTLV-I transmission and integration in CBL cultures. Moreover, beta-IFN had no effect in preventing virus transmission and integration in K562 and a very limited effect in HL60 and Molt-4 human tumour lines, suggesting a cell-type specific mode of action. beta-IFN induced a 'priming' response on CBL, since overnight pretreatment of recipient cells or one single treatment at the onset of the coculture were almost equally effective in protecting against HTLV-I infection. During the early days post infection (p.i.), IFN-treated CBL showed a pattern of phenotypic markers that was closer to that of non-infected CBL. In contrast, untreated CBL exposed to HTLV-I showed a percent increase of Tac+, M3+ and Leu 11+ subpopulations. Cell-mediated immune responses of CBL were depressed after coculturing with HTLV-I producer MT-2 cells. beta-IFN was able to boost the cell-mediated cytotoxicity of fresh and infected CBL against both K562 and MT-2 target cells. Leukocyte blastogenesis in mixed lymphocyte/tumour cell cultures, evaluated in terms of 3H-thymidine incorporation during the first week p.i., was also enhanced by IFN when macrophages and lymphocytes were reconstituted at an optimal 1:20 ratio. It is conceivable that this overall enhancement of the immune response induced by beta-IFN could contribute to reduce HTLV-I infection in vitro

Radiomics to predict response to neoadjuvant chemotherapy in rectal cancer: influence of simultaneous feature selection and classifier optimization

According to the guidelines, patients with locally advanced colorectal cancer undergo neoadjuvant chemotherapy. However, response to therapy is reached only up to 30% of cases. Therefore, it would be important to predict response to therapy before treatment. In this study, we demonstrated that the simultaneous optimization of feature subset and classifier parameters on different imaging datasets (T2w, DWI and PET) could improve classification performance. On a dataset of 51 patients (21 responders, 30 non responders), we obtained an accuracy of 90%, 84% and 76% using three optimized SVM classifiers fed with selected features from PET, T2w and ADC images, respectively

Federated data bases for the development of an operational monitoring and forecasting system of the ocean: the THREDDS Dataset Merger

During the last decade, operational monitoring and forecasting systems have been developed in all the European seas. The exchange of data and products and the development of services for a wide community of users pose some fundamental issues, whose solution has become a priority in integrated and GMES referring projects, such as the MERSEA European project. These projects aim to develop a European system for operational monitoring and forecasting on global and regional scales of ocean physics, bio-chemistry and ecosystems. GMES system and its operational projects need to federate resources and expertise coming from diverse organizations working on different Earth Sciences fields (e.g. satellite data processing, in situ observing systems, data management, ocean and ecosystem modeling, etc.). Therefore, it is required a Marine Information Management (MIM) system capable of facilitating the regular real-time exchange of high quality information, data and products. Moreover, MIM system must provide appropriate information for a wide range of external users both in real-time and delayed mode. </p><p style=&quot;line-height: 20px;&quot;> In this paper an architecture based on the OPeNDAP/THREDDS technology is proposed as a solution for these operational systems. In this context, a catalog merging solution is introduced for the MIM system, which results in the design and development of the THREDDS Dataset Merger (TDM): a set of services meant to merge THREDDS Dataset Inventory Catalogs, so to achieve a unique catalog service for a whole database federation. TDM service merges distributed and autonomous THREDDS catalogs in order to work out a virtual merged catalog. The TDM service was extended in order to provide automatic catalogs synchronization. This service allows extending the pull-based TDM paradigm to support push-based applications. Some security issues are also considered

Deep learning to segment liver metastases on CT images: Impact on a radiomics method to predict response to chemotherapy

Predicting response to neo-adjuvant chemotherapy of liver metastases (mts) using CT images is of key importance to provide personalized treatments. However, manual segmentation of mts should be avoid to develop methods that could be integrated into the clinical practice. The aim of this study is to evaluate if and how much automatic segmentation can affect a radiomics-based method to predict response to neoadjuvant chemotherapy of individual liver mts. To this scope, we developed an automatic deep learning method to segment liver mts, based on the U-net architecture, and we compared the classification results of a classifier fed with manual and automatic masks. In the validation set composed of 39 liver mts, the automatic deeplearning algorithm was able to detect 82% of mts, with a median precision of 67%. Using manual and automatic masks, we obtained the same classification in 19/32 mts. In case of mts with largest diameter > 20 mm, the precision of the segmentation does not impact the classification results and we obtained the same classification with both masks. Conversely, with smaller mts, we showed that a Dice coefficient of at least 0.5 should be obtained to extract the same information from the two segmentations. This are very important results in the perspective of using radiomics-based approach to predict response to therapy into clinical practice. Indeed, either precisely manually segment all lesions or refine them after automatic segmentation is a time-consuming task that cannot be performed on a daily basis

Lattice calculation of the DsD_{s} meson radiative form factors over the full kinematical range

We compute the structure-dependent axial and vector form factors for the radiative leptonic decays $D_s\to \ell\nu_\ell\gamma$, where $\ell$ is a charged lepton, as functions of the energy of the photon in the rest frame of the $D_s$ meson. The computation is performed using gauge-field configurations with 2+1+1 sea-quark flavours generated by the European Twisted Mass Collaboration and the results have been extrapolated to the continuum limit. For the vector form factor we observe a very significant partial cancellation between the contributions from the emission of the photon from the strange quark and that from the charm quark. The results for the form factors are used to test the reliability of various Anz\"atze based on single-pole dominance and its extensions, and we present a simple parametrization of the form factors which fits our data very well and which can be used in future phenomenological analyses. Using the form factors we compute the differential decay rate and the branching ratio for the process $D_s\to e\nu_e\gamma$ as a function of the lower cut-off on the photon energy. With a cut-off of 10 MeV for example, we find a branching ratio of Br$(E_\gamma>10\,\mathrm{MeV})=4.4(3)\times 10^{-6}$ which, unlike some model calculations, is consistent with the upper bound from the BESIII experiment Br$(E_\gamma>10\,\mathrm{MeV})<1.3\times 10^{-4}$ at 90% confidence level. Even for photon energies as low as 10 MeV, the decay $D_s\to e\nu_e\gamma$ is dominated by the structure-dependent contribution to the amplitude (unlike the decays with $\ell=\mu$ or $\tau$), confirming its value in searches for hypothetical new physics as well as in determining the Cabibbo-Kobayashi-Maskawa (CKM) parameters at $O(\alpha_\mathrm{em})$, where $\alpha_{\mathrm{em}}$ is the fine-structure constant.Comment: 31 pages, 14 figure