Controlling the electronic properties of van der Waals heterostructures by applying electrostatic design

Van der Waals heterostructures based on the heteroassembly of 2D materials represent a recently developed class of materials with promising properties especially for optoelectronic applications. The alignment of electronic energy bands between consecutive layers of these heterostructures crucially determines their functionality. In the present paper, relying on dispersion-corrected density-functional theory calculations, we present electrostatic design as a promising tool for manipulating this band alignment. The latter is achieved by inserting a layer of aligned polar molecules between consecutive transition-metal dichalcogenide (TMD) sheets. As a consequence, collective electrostatic effects induce a shift of as much as 0.3 eV in the band edges of successive TMD layers. Building on that, the proposed approach can be used to design electronically more complex systems, like quantum cascades or quantum wells, or to change the type of band lineup between type II and type I

Lack of Association of Type 2 Diabetes Susceptibility Genotypes and Body Weight on the Development of Islet Autoimmunity and Type 1 Diabetes

AIM: To investigate whether type 2 diabetes susceptibility genes and body weight influence the development of islet autoantibodies and the rate of progression to type 1 diabetes. METHODS: Genotyping for single nucleotide polymorphisms (SNP) of the type 2 diabetes susceptibility genes CDKAL1, CDKN2A/2B, FTO, HHEX-IDE, HMGA2, IGF2BP2, KCNJ11, KCNQ1, MTNR1B, PPARG, SLC30A8 and TCF7L2 was obtained in 1350 children from parents with type 1 diabetes participating in the BABYDIAB study. Children were prospectively followed from birth for islet autoantibodies and type 1 diabetes. Data on weight and height were obtained at 9 months, 2, 5, 8, 11, and 14 years of age. RESULTS: None of type 2 diabetes risk alleles at the CDKAL1, CDKN2A/2B, FTO, HHEX-IDE, HMGA2, IGF2BP2, KCNJ11, KCNQ1, MTNR1B, PPARG and SLC30A8 loci were associated with the development of islet autoantibodies or diabetes. The type 2 diabetes susceptible genotype of TCF7L2 was associated with a lower risk of islet autoantibodies (7% vs. 12% by age of 10 years, P = 0.015, P(corrected) = 0.18). Overweight children at seroconversion did not progress to diabetes faster than non-overweight children (HR: 1.08; 95% CI: 0.48-2.45, P>0.05). CONCLUSIONS: These findings do not support an association of type 2 diabetes risk factors with islet autoimmunity or acceleration of diabetes in children with a family history of type 1 diabetes

New changing look case in NGC 1566

We present a study of optical, UV and X-ray light curves of the nearby changing look active galactic nucleus in the galaxy NGC 1566 obtained with the Neil Gehrels Swift Observatory and the MASTER Global Robotic Network over the period 2007-2018. We also report on our optical spectroscopy at the South African Astronomical Observatory with the 1.9-m telescope on the night 2018 August 2-3. A substantial increase in X-ray flux by 1.5 orders of magnitude was observed following the brightening in the UV and optical bands during the last year. After a maximum was reached at the beginning of 2018 July the fluxes in all bands decreased with some fluctuations. The amplitude of the flux variability is strongest in the X-ray band and decreases with increasing wavelength. Low-resolution spectra reveal a dramatic strengthening of the broad emission as well as high-ionization [Fe X] 6374 angstrom lines. These lines were not detected so strongly in the past published spectra. The change in the type of the optical spectrum was accompanied by a significant change in the X-ray spectrum. All these facts confirm NGC 1566 to be a changing look Seyfert galaxy

Erratum to: Binding Energy and Spin-Orbit Splitting of a Hydrogenic Donor Impurity in AlGaN/GaN Triangle-Shaped Potential Quantum Well

In the framework of effective-mass envelope function theory, including the effect of Rashba spin-orbit coupling, the binding energyEband spin-orbit split energy Г of the ground state of a hydrogenic donor impurity in AlGaN/GaN triangle-shaped potential heterointerface are calculated. We find that with the electric field of the heterojunction increasing, (1) the effective width of quantum well decreases and (2) the binding energy increases monotonously, and in the mean time, (3) the spin-orbit split energy Г decreases drastically. (4) The maximum of Г is 1.22 meV when the electric field of heterointerface is 1 MV/cm

The post-maximum behaviour of the changing-look Seyfert galaxy NGC 1566

We present results of the long-term multiwavelength study of optical, UV, and X-ray variability of the nearby changing-look (CL) Seyfert NGC 1566 observed with the Swift Observatory and the MASTER Global Robotic Network from 2007 to 2019. We started spectral observations with South African Astronomical Observatory 1.9-m telescope soon after the brightening was discovered in July 2018 and present here the data for the interval between 2018 August and 2019 September. This paper concentrates on the remarkable post-maximum behaviour after 2018 July when all bands decreased with some fluctuations. We observed three significant re-brightenings in the post-maximum period during 2018 November 17-2019 January 10, 2019 April 29-2019 June 19, and 2019 July 27-2019 August 6. An X-ray flux minimum occurred in 2019 March. The UV minimum occurred about 3 months later. It was accompanied by a decrease of the L-UV/LX-ray ratio. New post-maximum spectra covering (2018 November 31-2019 September 23) show dramatic changes compared to 2018 August 2, with fading of the broad lines and [Fe X] lambda 6374 until 2019 March. These lines became somewhat brighter in 2019 August-September. Effectively, two CL states were observed for this object: changing to type 1.2 and then returning to the low state as a type 1.8 Sy. We suggest that the changes are due mostly to fluctuations in the energy generation. The estimated Eddington ratios are about 0.055 per cent for minimum in 2014 and 2.8 per cent for maximum in 2018

What is the clinical relevance of different lung compartments?

The lung consists of at least seven compartments with relevance to immune reactions. Compartment 1 - the bronchoalveolar lavage (BAL), which represents the cells of the bronchoalveolar space: From a diagnostic point of view the bronchoalveolar space is the most important because it is easily accessible in laboratory animals, as well as in patients, using BAL. Although this technique has been used for several decades it is still unclear to what extent the BAL represents changes in other lung compartments. Compartment 2 - bronchus-associated lymphoid tissue (BALT): In the healthy, BALT can be found only in childhood. The role of BALT in the development of the mucosal immunity of the pulmonary surfaces has not yet been resolved. However, it might be an important tool for inhalative vaccination strategies. Compartment 3 - conducting airway mucosa: A third compartment is the bronchial epithelium and the submucosa, which both contain a distinct pool of leukocytes (e.g. intraepithelial lymphocytes, IEL). This again is also accessible via bronchoscopy. Compartment 4 - draining lymph nodes/Compartment 5 - lung parenchyma: Transbronchial biopsies are more difficult to perform but provide access to two additional compartments - lymph nodes with the draining lymphatics and lung parenchyma, which roughly means "interstitial" lung tissue. Compartment 6 - the intravascular leukocyte pool: The intravascular compartment lies between the systemic circulation and inflamed lung compartments. Compartment 7 - periarterial space: Finally, there is a unique, lung-specific space around the pulmonary arteries which contains blood and lymph capillaries. There are indications that this "periarterial space" may be involved in the pulmonary host defense

Human-computer collaboration for skin cancer recognition

The rapid increase in telemedicine coupled with recent advances in diagnostic artificial intelligence (AI) create the imperative to consider the opportunities and risks of inserting AI-based support into new paradigms of care. Here we build on recent achievements in the accuracy of image-based AI for skin cancer diagnosis to address the effects of varied representations of AI-based support across different levels of clinical expertise and multiple clinical workflows. We find that good quality AI-based support of clinical decision-making improves diagnostic accuracy over that of either AI or physicians alone, and that the least experienced clinicians gain the most from AI-based support. We further find that AI-based multiclass probabilities outperformed content-based image retrieval (CBIR) representations of AI in the mobile technology environment, and AI-based support had utility in simulations of second opinions and of telemedicine triage. In addition to demonstrating the potential benefits associated with good quality AI in the hands of non-expert clinicians, we find that faulty AI can mislead the entire spectrum of clinicians, including experts. Lastly, we show that insights derived from AI class-activation maps can inform improvements in human diagnosis. Together, our approach and findings offer a framework for future studies across the spectrum of image-based diagnostics to improve human-computer collaboration in clinical practice

A Profile Likelihood Analysis of the Constrained MSSM with Genetic Algorithms

The Constrained Minimal Supersymmetric Standard Model (CMSSM) is one of the simplest and most widely-studied supersymmetric extensions to the standard model of particle physics. Nevertheless, current data do not sufficiently constrain the model parameters in a way completely independent of priors, statistical measures and scanning techniques. We present a new technique for scanning supersymmetric parameter spaces, optimised for frequentist profile likelihood analyses and based on Genetic Algorithms. We apply this technique to the CMSSM, taking into account existing collider and cosmological data in our global fit. We compare our method to the MultiNest algorithm, an efficient Bayesian technique, paying particular attention to the best-fit points and implications for particle masses at the LHC and dark matter searches. Our global best-fit point lies in the focus point region. We find many high-likelihood points in both the stau co-annihilation and focus point regions, including a previously neglected section of the co-annihilation region at large m_0. We show that there are many high-likelihood points in the CMSSM parameter space commonly missed by existing scanning techniques, especially at high masses. This has a significant influence on the derived confidence regions for parameters and observables, and can dramatically change the entire statistical inference of such scans.Comment: 47 pages, 8 figures; Fig. 8, Table 7 and more discussions added to Sec. 3.4.2 in response to referee's comments; accepted for publication in JHE