Deterministic optical polarisation in nitride quantum dots at thermoelectrically cooled temperatures.

We report the successful realisation of intrinsic optical polarisation control by growth, in solid-state quantum dots in the thermoelectrically cooled temperature regime (≥200 K), using a non-polar InGaN system. With statistically significant experimental data from cryogenic to high temperatures, we show that the average polarisation degree of such a system remains constant at around 0.90, below 100 K, and decreases very slowly at higher temperatures until reaching 0.77 at 200 K, with an unchanged polarisation axis determined by the material crystallography. A combination of Fermi-Dirac statistics and k·p theory with consideration of quantum dot anisotropy allows us to elucidate the origin of the robust, almost temperature-insensitive polarisation properties of this system from a fundamental perspective, producing results in very good agreement with the experimental findings. This work demonstrates that optical polarisation control can be achieved in solid-state quantum dots at thermoelectrically cooled temperatures, thereby opening the possibility of polarisation-based quantum dot applications in on-chip conditions

Fuzzy Bayesian inference for mapping vague and place-based regions: a case study of sectarian territory

The problem of mapping regions with socially-derived boundaries has been a topic of discussion in the GIS literature for many years. Fuzzy approaches have frequently been suggested as solutions, but none have been adopted. This is likely due to difficulties associated with determining suitable membership functions, which are often as arbitrary as the crisp boundaries that they seek to replace. This paper presents a novel approach to fuzzy geographical modelling that replaces the membership function with a possibility distribution that is estimated using Bayesian inference. In this method, data from multiple sources are combined to estimate the degree to which a given location is a member of a given set and the level of uncertainty associated with that estimate. The Fuzzy Bayesian Inference approach is demonstrated through a case study in which census data are combined with perceptual and behavioural evidence to model the territory of two segregated groups (Catholics and Protestants) in Belfast, Northern Ireland, UK. This novel method provides a robust empirical basis for the use of fuzzy models in GIS, and therefore has applications for mapping a range of socially-derived and otherwise vague boundaries

Constant photocurrent method to probe the sub-bandgap absorption in wide bandgap semiconductor films : the case of α-Ga2O3

The optical absorption coefficient is one of the fundamental properties of semiconductors and is critical to the development of optical devices. Herein, a revival of the constant photocurrent method is presented to measure sub-bandgap absorption in wide bandgap semiconductor films. The method involves maintaining a constant photocurrent by continually adjusting the impinging photon flux across the energy spectrum. Under such conditions, the reciprocal of the photon flux for uniformly absorbed light is proportional to the absorption coefficient. This method is applied to α-Ga 2O 3 and reveals that it can access the absorption coefficient from 1 × 10 5 cm −1 at the band edge (5.3 eV) to 0.8 cm −1 close to mid-bandgap (2.7 eV). Changes in the steepness of the absorption curve in the sub-bandgap region are in excellent agreement with defect states of α-Ga 2O 3 reported by deep level transient spectroscopy, indicating that the technique shows promise as a probe of energetically distributed defect states in thin film wide bandgap semiconductors

Case-finding for common mental disorders of anxiety and depression in primary care: an external validation of routinely collected data

Background The robustness of epidemiological research using routinely collected primary care electronic data to support policy and practice for common mental disorders (CMD) anxiety and depression would be greatly enhanced by appropriate validation of diagnostic codes and algorithms for data extraction. We aimed to create a robust research platform for CMD using population-based, routinely collected primary care electronic data. Methods We developed a set of Read code lists (diagnosis, symptoms, treatments) for the identification of anxiety and depression in the General Practice Database (GPD) within the Secure Anonymised Information Linkage Databank at Swansea University, and assessed 12 algorithms for Read codes to define cases according to various criteria. Annual incidence rates were calculated per 1000 person years at risk (PYAR) to assess recording practice for these CMD between January 1st 2000 and December 31st 2009. We anonymously linked the 2799 MHI-5 Caerphilly Health and Social Needs Survey (CHSNS) respondents aged 18 to 74 years to their routinely collected GP data in SAIL. We estimated the sensitivity, specificity and positive predictive value of the various algorithms using the MHI-5 as the gold standard. Results The incidence of combined depression/anxiety diagnoses remained stable over the ten-year period in a population of over 500,000 but symptoms increased from 6.5 to 20.7 per 1000 PYAR. A ‘historical’ GP diagnosis for depression/anxiety currently treated plus a current diagnosis (treated or untreated) resulted in a specificity of 0.96, sensitivity 0.29 and PPV 0.76. Adding current symptom codes improved sensitivity (0.32) with a marginal effect on specificity (0.95) and PPV (0.74). Conclusions We have developed an algorithm with a high specificity and PPV of detecting cases of anxiety and depression from routine GP data that incorporates symptom codes to reflect GP coding behaviour. We have demonstrated that using diagnosis and current treatment alone to identify cases for depression and anxiety using routinely collected primary care data will miss a number of true cases given changes in GP recording behaviour. The Read code lists plus the developed algorithms will be applicable to other routinely collected primary care datasets, creating a platform for future e-cohort research into these conditions. Keyword

Ad astra per aspera (Through Hardships to the Stars): Lessons Learned from the First National Virtual APDS Meeting, 2020

This article is made available for unrestricted research re-use and secondary analysis in any form or by any means with acknowledgement of the original source. These permissions are granted for the duration of the World Health Organization (WHO) declaration of COVID-19 as a global pandemic.Objective After COVID-19 rendered in-person meetings for national societies impossible in the spring of 2020, the leadership of the Association of Program Directors in Surgery (APDS) innovated via a virtual format in order to hold its national meeting. Design APDS leadership pre-emptively considered factors that would be important to attendees including cost, value, time, professional commitments, education, sharing of relevant and current information, and networking. Setting The meeting was conducted using a variety of virtual formats including a web portal for entry, pre-ecorded poster and oral presentations on the APDS website, interactive panels via a web conferencing platform, and livestreaming. Participants There were 298 registrants for the national meeting of the APDS, and 59 participants in the New Program Directors Workshop. The registrants and participants comprised medical students, residents, associate program directors, program directors, and others involved in surgical education nationally. Results There was no significant difference detected for high levels of participant satisfaction between 2019 and 2020 for the following items: overall program rating, topics and content meeting stated objectives, relevant content to educational needs, educational format conducive to learning, and agreement that the program will improve competence, performance, communication skills, patient outcomes, or processes of care/healthcare system performance. Conclusions A virtual format for a national society meeting can provide education, engagement, and community, and the lessons learned by the APDS in the process can be used by other societies for utilization and further improvement

Inter-MAR Association Contributes to Transcriptionally Active Looping Events in Human β-globin Gene Cluster

Matrix attachment regions (MARs) are important in chromatin organization and gene regulation. Although it is known that there are a number of MAR elements in the β-globin gene cluster, it is unclear that how these MAR elements are involved in regulating β-globin genes expression. Here, we report the identification of a new MAR element at the LCR(locus control region) of human β-globin gene cluster and the detection of the inter-MAR association within the β-globin gene cluster. Also, we demonstrate that SATB1, a protein factor that has been implicated in the formation of network like higher order chromatin structures at some gene loci, takes part in β-globin specific inter-MAR association through binding the specific MARs. Knocking down of SATB1 obviously reduces the binding of SATB1 to the MARs and diminishes the frequency of the inter-MAR association. As a result, the ACH establishment and the α-like globin genes and β-like globin genes expressions are affected either. In summary, our results suggest that SATB1 is a regulatory factor of hemoglobin genes, especially the early differentiation genes at least through affecting the higher order chromatin structure

Whole-genome sequencing reveals host factors underlying critical COVID-19

Critical COVID-19 is caused by immune-mediated inflammatory lung injury. Host genetic variation influences the development of illness requiring critical care1 or hospitalization2–4 after infection with SARS-CoV-2. The GenOMICC (Genetics of Mortality in Critical Care) study enables the comparison of genomes from individuals who are critically ill with those of population controls to find underlying disease mechanisms. Here we use whole-genome sequencing in 7,491 critically ill individuals compared with 48,400 controls to discover and replicate 23 independent variants that significantly predispose to critical COVID-19. We identify 16 new independent associations, including variants within genes that are involved in interferon signalling (IL10RB and PLSCR1), leucocyte differentiation (BCL11A) and blood-type antigen secretor status (FUT2). Using transcriptome-wide association and colocalization to infer the effect of gene expression on disease severity, we find evidence that implicates multiple genes—including reduced expression of a membrane flippase (ATP11A), and increased expression of a mucin (MUC1)—in critical disease. Mendelian randomization provides evidence in support of causal roles for myeloid cell adhesion molecules (SELE, ICAM5 and CD209) and the coagulation factor F8, all of which are potentially druggable targets. Our results are broadly consistent with a multi-component model of COVID-19 pathophysiology, in which at least two distinct mechanisms can predispose to life-threatening disease: failure to control viral replication; or an enhanced tendency towards pulmonary inflammation and intravascular coagulation. We show that comparison between cases of critical illness and population controls is highly efficient for the detection of therapeutically relevant mechanisms of disease