Decoherence of Einstein-Podolsky-Rosen steering

We consider two systems A and B that share Einstein-Podolsky-Rosen (EPR) steering correlations and study how these correlations will decay, when each of the systems are independently coupled to a reservoir. EPR steering is a directional form of entanglement, and the measure of steering can change depending on whether the system A is steered by B, or vice versa. First, we examine the decay of the steering correlations of the two-mode squeezed state. We find that if the system B is coupled to a reservoir, then the decoherence of the steering of A by B is particularly marked, to the extent that there is a sudden death of steering after a finite time. We find a different directional effect, if the reservoirs are thermally excited. Second, we study the decoherence of the steering of a Schr\"odinger cat state, modeled as the entangled state of a spin and harmonic oscillator, when the macroscopic system (the cat) is coupled to a reservoir

Retrovirology: 3 at age 2

Retrovirology announces new editorial board members and reprises progress over the first two years of publishing

Overcoming data scarcity of Twitter: using tweets as bootstrap with application to autism-related topic content analysis

Notwithstanding recent work which has demonstrated the potential of using Twitter messages for content-specific data mining and analysis, the depth of such analysis is inherently limited by the scarcity of data imposed by the 140 character tweet limit. In this paper we describe a novel approach for targeted knowledge exploration which uses tweet content analysis as a preliminary step. This step is used to bootstrap more sophisticated data collection from directly related but much richer content sources. In particular we demonstrate that valuable information can be collected by following URLs included in tweets. We automatically extract content from the corresponding web pages and treating each web page as a document linked to the original tweet show how a temporal topic model based on a hierarchical Dirichlet process can be used to track the evolution of a complex topic structure of a Twitter community. Using autism-related tweets we demonstrate that our method is capable of capturing a much more meaningful picture of information exchange than user-chosen hashtags.Comment: IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining, 201

Bowel ischaemia in COVID-19 infection: a scoping review protocol

Introduction: COVID-19 disease was declared as a pandemic by WHO since March 2020 and can have a myriad of clinical presentations affecting various organ systems. Patients with COVID-19 are known to have an increased risk of thromboembolism, including cardiovascular, pulmonary and cerebral ischaemic events. However, an increasing number of case studies have reported that COVID-19 infection is also associated with gastrointestinal ischaemia. This scoping review aims to collate the current evidence of COVID-19-related gastrointestinal ischaemia and raise awareness among healthcare professionals of this lesser known, but serious, non-pulmonary complication of COVID-19 infection. Methods: The proposed scoping review will be conducted as per the Arksey and O’Malley methodological framework (2005) the Joanna Briggs Institute methodology for scoping reviews. A systematic search will be undertaken on different databases including EMBASE, PubMed and MEDLINE. Two independent reviewers will screen titles, abstracts and full-text articles according to the inclusion criteria and extract relevant data from the included articles. Results will be presented in a tabular form with a narrative discussion. Ethics and dissemination: Ethical approval will not be required for this scoping review. This scoping review will provide an extensive overview of the association between COVID-19 infection and bowel ischaemia. Further ethical and methodological challenges will also be discussed in our findings to define a new research agenda. Findings will be disseminated through peer-reviewed publications and presentations at both national and international conferences

Predictive biometrics: A review and analysis of predicting personal characteristics from biometric data

Interest in the exploitation of soft biometrics information has continued to develop over the last decade or so. In comparison with traditional biometrics, which focuses principally on person identification, the idea of soft biometrics processing is to study the utilisation of more general information regarding a system user, which is not necessarily unique. There are increasing indications that this type of data will have great value in providing complementary information for user authentication. However, the authors have also seen a growing interest in broadening the predictive capabilities of biometric data, encompassing both easily definable characteristics such as subject age and, most recently, `higher level' characteristics such as emotional or mental states. This study will present a selective review of the predictive capabilities, in the widest sense, of biometric data processing, providing an analysis of the key issues still adequately to be addressed if this concept of predictive biometrics is to be fully exploited in the future

Enhanced Power Conversion Efficiency via Hybrid Ligand Exchange Treatment of p-Type PbS Quantum Dots.

PbS quantum dot solar cells (QDSCs) have emerged as a promising low-cost, solution-processable solar energy harvesting device and demonstrated good air stability and potential for large-scale commercial implementation. PbS QDSCs achieved a record certified efficiency of 12% in 2018 by utilizing an n+-n-p device structure. However, the p-type layer has generally suffered from low carrier mobility due to the organic ligand 1,2-ethanedithiol (EDT) that is used to modify the quantum dot (QD) surface. The low carrier mobility of EDT naturally limits the device thickness as the carrier diffusion length is limited by the low mobility. Herein, we improve the properties of the p-type layer through a two-step hybrid organic ligand treatment. By treating the p-type layer with two types of ligands, 3-mercaptopropionic acid (MPA) and EDT, the PbS QD surface was passivated by a combination of the two ligands, resulting in an overall improvement in open-circuit voltage, fill factor, and current density, leading to an improvement in the cell efficiency from 7.0 to 10.4% for the champion device. This achievement was a result of the improved QD passivation and a reduction in the interdot distance, improving charge transport through the p-type PbS quantum dot film

How Robust are the Estimated Effects of Nonpharmaceutical Interventions against COVID-19?

To what extent are effectiveness estimates of nonpharmaceutical interventions (NPIs) against COVID-19 influenced by the assumptions our models make? To answer this question, we investigate 2 state-of-the-art NPI effectiveness models and propose 6 variants that make different structural assumptions. In particular, we investigate how well NPI effectiveness estimates generalise to unseen countries, and their sensitivity to unobserved factors. Models which account for noise in disease transmission compare favourably. We further evaluate how robust estimates are to different choices of epidemiological parameters and data. Focusing on models that assume transmission noise, we find that previously published results are robust across these choices and across different models. Finally, we mathematically ground the interpretation of NPI effectiveness estimates when certain common assumptions do not hold