Tripartite quantum state mapping and discontinuous entanglement transfer in a cavity QED open system

We describe the transfer of quantum information and entanglement from three flying (radiation) to three localized (atomic) qubits via cavity modes resonantly coupled to the atoms, in the presence of a common reservoir. Upon addressing the full dynamics of the resulting nine-qubit open system, we find that once the cavities are fed, fidelity and transferred entanglement are optimal, while their peak values exponentially decrease due to dissipative processes. The external radiation is then turned off and quantum correlations oscillate between atomic and cavity qubits. For a class of mixtures of W and GHZ input states we deal with a discontinuous exchange of entanglement among the subsystems, facing the still open problem of entanglement sudden death and birth in a multipartite system.Comment: 7 pages, 6 figures, 2 table

Improving the entanglement transfer from continuous variable systems to localized qubits using non Gaussian states

We investigate the entanglement transfer from a bipartite continuous-variable (CV) system to a pair of localized qubits assuming that each CV mode couples to one qubit via the off-resonance Jaynes-Cummings interaction with different interaction times for the two subsystems. First, we consider the case of the CV system prepared in a Bell-like superposition and investigate the conditions for maximum entanglement transfer. Then we analyze the general case of two-mode CV states that can be represented by a Schmidt decomposition in the Fock number basis. This class includes both Gaussian and non Gaussian CV states, as for example twin-beam (TWB) and pair-coherent (TMC, also known as two-mode-coher ent) states respectively. Under resonance conditions, equal interaction times for both qubits and different initial preparations, we find that the entanglement transfer is more efficient for TMC than for TWB states. In the perspective of applications such as in cavity QED or with superconducting qubits, we analyze in details the effects of off-resonance interactions (detuning) and different interaction times for the two qubits, and discuss conditions to preserve the entanglement transfer.Comment: revised version, 11 pages, 7 figures (few of them low-res

Stigma and discrimination (Sad) at the time of the sars-cov-2 pandemic

Infectious disease control is a crucial public health issue. Although it is important to urgently perform public health measures in order to reduce the risk of spread, it could end up stigmatizing entire groups of people rather than offering control measures based on sound scientific principles. This “us” versus “them” dynamic is common in stigmatization, in general, and indicates a way in which disease stigma can be viewed as a proxy for other types of fears, especially xenophobia and general fear of outsiders. The pandemic risk associated with SARS-CoV-2 infection led us to consider, among other related issues, how stigma and discrimination remain serious barriers to care for people suspected of being infected, even more if they are assisting professions, such as health workers, employed in emergency response. The purpose of this review is to evaluate and promote the importance of psychological aspects of the stigma and social discrimination (SAD) in pandemic realities and, more specifically, nowadays, in the context of SARS-CoV-2/COVID-19. Just as it happened with HIV, HCV, tuberculosis, and Zika, stigma and discrimination undermine the social fabric compromising the ethics and principles of civilization to which each individual in entitled. Recognizing disease stigma history can give us insight into how, exactly, stigmatizing attitudes are formed, and how they are disbanded. Instead of simply blaming the ignorance of people espousing stigmatizing attitudes about certain diseases, we should try to understand precisely how these attitudes are formed so that we can intervene in their dissemination. We should also look at history to see what sorts of interventions against stigma may have worked in the past. Ongoing research into stigma should evaluate what has worked in the past, as above-mentioned, providing us with some clues as to what might work in the current pandemic emergency, to reduce devastating discrimination that keeps people from getting the care they need. We propose a systematic and historical review, in order to create a scientific and solid base for the following SAD analysis. The aim is to propose a coping strategy to face stigma and discrimination (SAD) related to SARS-CoV-2/COVID-19 pandemic outbreak, borrowing coping strategy tools and solutions from other common contagious diseases. Furthermore, our study observes how knowledge, education level, and socioeconomic status (SES) can influence perception of SARS-CoV-2/ COVID-19 risk in a digital world, based on previous research, best practices, and evidence-based research

Application of selection hyper-heuristics to the simultaneous optimisation of turbines and cabling within an offshore windfarm

Global warming has focused attention on how the world produces the energy required to power the planet. It has driven a major need to move away from using fossil fuels for energy production toward cleaner and more sustainable methods of producing renewable energy. The development of offshore windfarms, which harness the power of the wind, is seen as a viable approach to creating renewable energy but they can be difficult to design efficiently. The complexity of their design can benefit significantly from the use of computational optimisation. The windfarm optimisation problem typically consists of two smaller optimisation problems: turbine placement and cable routing, which are generally solved separately. This paper aims to utilise selection hyper-heuristics to optimise both turbine placement and cable routing simultaneously within one optimisation problem. This paper identifies and confirms the feasibility of using selection hyper-heuristics within windfarm optimisation to consider both cabling and turbine positioning within the same single optimisation problem. Key results could not identify a conclusive advantage to combining this into one optimisation problem as opposed to considering both as two sequential optimisation problems.</p

COVID-19-related mental health effects in the workplace: A narrative review

The Coronavirus Disease 2019 (COVID-19) pandemic has deeply altered social and working environments in several ways. Social distancing policies, mandatory lockdowns, isolation periods, and anxiety of getting sick, along with the suspension of productive activity, loss of income, and fear of the future, jointly influence the mental health of citizens and workers. Workplace aspects can play a crucial role on moderating or worsening mental health of people facing this pandemic scenario. The purpose of this literature review is to deepen the psychological aspects linked to workplace factors, following the epidemic rise of COVID-19, in order to address upcoming psychological critical issues in the workplaces. We performed a literature search using Google Scholar, PubMed, and Scopus, selecting papers focusing on workers' psychological problems that can be related to the workplace during the pandemic. Thirty-five articles were included. Mental issues related to the health emergency, such as anxiety, depression, post-traumatic stress disorder (PTSD), and sleep disorders are more likely to affect healthcare workers, especially those on the frontline, migrant workers, and workers in contact with the public. Job insecurity, long periods of isolation, and uncertainty of the future worsen the psychological condition, especially in younger people and in those with a higher educational background. Multiple organizational and work-related interventions can mitigate this scenario, such as the improvement of workplace infrastructures, the adoption of correct and shared anti-contagion measures, including regular personal protective equipment (PPE) supply, and the implementation of resilience training programs. This review sets the basis for a better understanding of the psychological conditions of workers during the pandemic, integrating individual and social perspectives, and providing insight into possible individual, social, and occupational approaches to this "psychological pandemic"

A learning-based algorithm to quickly compute good primal solutions for Stochastic Integer Programs

We propose a novel approach using supervised learning to obtain near-optimal primal solutions for two-stage stochastic integer programming (2SIP) problems with constraints in the first and second stages. The goal of the algorithm is to predict a "representative scenario" (RS) for the problem such that, deterministically solving the 2SIP with the random realization equal to the RS, gives a near-optimal solution to the original 2SIP. Predicting an RS, instead of directly predicting a solution ensures first-stage feasibility of the solution. If the problem is known to have complete recourse, second-stage feasibility is also guaranteed. For computational testing, we learn to find an RS for a two-stage stochastic facility location problem with integer variables and linear constraints in both stages and consistently provide near-optimal solutions. Our computing times are very competitive with those of general-purpose integer programming solvers to achieve a similar solution quality

Tripartite entanglement transfer from flying modes to localized qubits

We investigate the process of entanglement transfer from a three-mode quantized field to a system of three spatially separated qubits each one made of a two-level atom resonantly coupled to a cavity mode. The optimal conditions for entanglement transfer, evaluated by atomic tripartite negativity, are derived for radiation prepared in qubit-like and Gaussian entangled states in terms of field parameters, atom-cavity interaction time, cavity mirror losses, and atomic preparation. For qubit-like states we found that for negligible cavity losses some states may completely transfer their entanglement to the atoms and/or be exactly mapped to the atomic state, whereas for Gaussian states we found a range of field parameters to obtain a large entanglement transfer. The purity of the three-qubit states and the entanglement of two-qubit subsystems are also discussed in some details.Comment: 12 pages, 12 fig

Transcriptional activation of the miR-17-92 cluster is involved in the growth-promoting effects of MYB in human Ph-positive leukemia cells.

MicroRNAs, non-coding regulators of gene expression, are likely to function as important downstream effectors of many transcription factors including MYB. Optimal levels of MYB are required for transformation/maintenance of BCR-ABL-expressing cells. We investigated whether MYB silencing modulates microRNA expression in Philadelphia-positive (Ph+) leukemia cells and if MYB-regulated microRNAs are important for the MYB addiction of these cells. Thirty-five microRNAs were modulated by MYB silencing in lymphoid and erythromyeloid chronic myeloid leukemia-blast crisis BV173 and K562 cells; 15 of these were concordantly modulated in both lines. We focused on the miR-17-92 cluster because of its oncogenic role in tumors and found that: i) it is a direct MYB target; ii) it partially rescued the impaired proliferation and enhanced apoptosis of MYB-silenced BV173 cells. Moreover, we identified FRZB, a Wnt/β-catenin pathway inhibitor, as a novel target of the miR-17-92 cluster. High expression of MYB in blast cells from 2 Ph+leukemia patients correlated positively with the miR-17-92 cluster and inversely with FRZB. This expression pattern was also observed in a microarray dataset of 122 Ph+acute lymphoblastic leukemias. In vivo experiments in NOD scid gamma mice injected with BV173 cells confirmed that FRZB functions as a Wnt/β-catenin inhibitor even as they failed to demonstrate that this pathway is important for BV173-dependent leukemogenesis. These studies illustrate the global effects of MYB expression on the microRNAs profile of Ph+cells and supports the concept that the MYB addiction of these cells is, in part, caused by modulation of microRNA-regulated pathways affecting cell proliferation and survival. Copyright© 2019 Ferrata Storti Foundation

Incorporating Stakeholders’ priorities and preferences in 4D trajectory optimization

A key feature of trajectory based operations (TBO) -- a new concept developed to modernize the air traffic system -- is the inclusion of preferences and priorities of the air traffic management (ATM) stakeholders. In this paper, we present a new mathematical model to optimize flights' 4D-trajectories. This is a multi-objective binary integer programming (IP) model, which assigns a 4D-trajectory to each flight, while explicitly modeling priorities and highlighting the trade off involved with the Airspace Users (AUs) preferences. The scope of the model (to be used at pre-tactical level) is the computation of optimal 4D pre-departure trajectory for each flight to be shared or negotiated with other stakeholders and subsequently managed throughout the flight. These trajectories are obtained by minimising the deviation (delay and re-routing) from the original preferred 4D-trajectories as well as minimizing the air navigation service (ANS) charges subject to the constraints of the system. Computational results for the model are presented, which show that the proposed model has the ability to identify trade-offs between the objectives of the stakeholders of the ATM system under the TBO concept. This can therefore provide the ATM stakeholders with useful decision tools to choose a trajectory for each flight