Role of Strain-Induced Microscale Compositional Pulling on Optical Properties of High Al Content AlGaN Quantum Wells for Deep-Ultraviolet LED

A systematic study was carried out for strain-induced microscale compositional pulling effect on the structural and optical properties of high Al content AlGaN multiple quantum wells (MQWs). Investigations reveal that a large tensile strain is introduced during the epitaxial growth of AlGaN MQWs, due to the grain boundary formation, coalescence and growth. The presence of this tensile strain results in the microscale inhomogeneous compositional pulling and Ga segregation, which is further confirmed by the lower formation enthalpy of Ga atom than Al atom on AlGaN slab using first principle simulations. The strain-induced microscale compositional pulling leads to an asymmetrical feature of emission spectra and local variation in emission energy of AlGaN MQWs. Because of a stronger three-dimensional carrier localization, the area of Ga segregation shows a higher emission efficiency compared with the intrinsic area of MQWs, which is benefit for fabricating efficient AlGaN-based deep-ultraviolet light-emitting diode.

2D Wavelet Tree Ordering Based Localized Total Variation Model for Efficient Image Restoration

The degraded image during the process of image analysis needs more number of iterations to restore it. These iterations take long waiting time and slow scanning, resulting in inefficient image restoration. A few numbers of measurements are enough to recuperate an image with good condition. Due to tree sparsity, a 2D wavelet tree reduces the number of coefficients and iterations to restore the degraded image. All the wavelet coefficients are extracted with overlaps as low and high sub-band space and ordered them such that they are decomposed in the tree ordering structured path. Some articles have addressed the problems with tree sparsity and total variation (TV), but few authors endorsed the benefits of tree sparsity. In this paper, a spatial variation regularization algorithm based on tree order is implemented to change the window size and variation estimators to reduce the loss of image information and to solve the problem of image smoothing operation. The acceptance rate of the tree-structured path relies on local variation estimators to regularize the performance parameters and update them to restore the image. For this, the Localized Total Variation (LTV) method is proposed and implemented on a 2D wavelet tree ordering structured path based on the proposed image smooth adjustment scheme. In the end, a reliable reordering algorithm proposed to reorder the set of pixels and to increase the reliability of the restored image. Simulation results clearly show that the proposed method improved the performance compared to existing methods of image restoration.

Refugees, expellees and immigrants: comparing migrant reception policies and practices in post-war Bristol, Dortmund and Malmö

The vital role that cities play in the governance of migration is increasingly recognized, yet migration scholars still perceive this ‘local turn’ as a recent phenomenon. This article presents a cross-country and cross-city comparative analysis of three mid-size European cities during the post-war period: Bristol, Dortmund and Malmö. It analyses administrative cultures and local policy arenas, exposing the complexity of local migration policy-making and the crucial importance of historical perspectives. It reveals the inherent local variation in policies and practices, and argues that traditional national-level studies do not fully capture how urban actors responded to migration.

Detection and categorization of severe cardiac disorders based solely on pulse interval measurements

Cardiac disorders are common conditions associated with a high mortality rate. Due to their potential for causing serious symptoms, it is desirable to constantly monitor cardiac status using an accessible device such as a smartwatch. While electrocardiograms (ECGs) can make the detailed diagnosis of cardiac disorders, the examination is typically performed only once a year for each individual during health checkups, and it requires expert medical practitioners to make comprehensive judgments. Here we describe a newly developed automated system for alerting individuals about cardiac disorders solely based on pulse interval measurements. For this purpose, we examined two metrics of heart rate variability (HRV) and analyzed 1-day ECG recordings of more than 1,000 subjects in total. We found that a newly introduced metric of local variation was more efficient than conventional HRV metrics for detecting premature contraction, and furthermore, that a suitable combination of the old and new metrics resulted in much superior detectability particularly for atrial fibrillation, which requires more attention. Even with a 1-minute recording of pulse intervals, our new detection system had a diagnostic performance even better than that of the conventional analysis method applied to a 1-day recording.

Spatial variation of geometry, binding, and electronic properties in the moiré superstructure of MoS2 on Au(111)

The lattice mismatch between a monolayer of MoS2 and its Au(111) substrate induces a moiré superstructure. The local variation of the registry between sulfur and gold atoms at the interface leads to a periodic pattern of strongly and weakly interacting regions. In consequence, also the electronic bands show a spatial variation. We use scanning tunneling microscopy and spectroscopy (STM/STS), x-ray photoelectron spectroscopy (XPS) and x-ray standing wave (XSW) for a determination of the geometric and electronic structure. The experimental results are corroborated by density functional theory (DFT). We obtain the geometric structure of the supercell with high precision, identify the fraction of interfacial atoms that are strongly interacting with the substrate, and analyze the variation of the electronic structure in dependence of the location within the moiré unit cell and the nature of the band.

Quaternionic Kähler Metrics Associated to Special Kähler Manifolds with Mutually Local Variations of BPS Structures

We construct a quaternionic Kähler manifold from a conical special Kähler manifold with a certain type of mutually local variation of BPS structures. We give global and local explicit formulas for the quaternionic Kähler metric and specify under which conditions it is positive-definite. Locally, the metric is a deformation of the 1-loop corrected Ferrara–Sabharwal metric obtained via the supergravity c-map. The type of quaternionic Kähler metrics we obtain is related to work in the physics literature by S. Alexandrov and S. Banerjee, where they discuss the hypermultiplet moduli space metric of type IIA string theory, with mutually local D-instanton corrections.

A Node Placement Algorithm Utilizing Mobile Nodes in WSN and IoT Networks

The operation of the Internet of Things (IoT) networks and Wireless Sensor Networks (WSN) is often disrupted by a number of problems, such as path disconnections, network segmentation, node faults, and security attacks. A method that gains momentum in resolving some of those issues is the use of mobile nodes or nodes deployed by mobile robots. The use of mobile elements essentially increases the resources and the capacity of the network. In this work, we present a Node Placement Algorithm with two variations, which utilizes mobile nodes for the creation of alternative paths from source to sink. The first variation employs mobile nodes that create locally-significant alternative paths leading to the sink. The second variation employs mobile nodes that create completely individual (disjoint) paths to the sink. We then extend the local variation of the algorithm by also accounting for the energy levels of the nodes as a contributing factor regarding the creation of alternative paths. We offer both a high-level description of the concept and also detailed algorithmic solutions. The evaluation of the solutions was performed in a case study of resolving congestion in the network. Results have shown that the proposed algorithms can significantly contribute to the alleviation of the problem of congestion in IoT and WSNs and can easily be used for other types of network problems.