The spatial localization of charge carriers to promote the formation of bound excitons and concomitantly enhance radiative recombination has long been a goal for luminescent semiconductors. ...Zero‐dimensional materials structurally impose carrier localization and result in the formation of localized Frenkel excitons. Now the fully inorganic, perovskite‐derived zero‐dimensional SnII material Cs4SnBr6 is presented that exhibits room‐temperature broad‐band photoluminescence centered at 540 nm with a quantum yield (QY) of 15±5 %. A series of analogous compositions following the general formula Cs4−xAxSn(Br1−yIy)6 (A=Rb, K; x≤1, y≤1) can be prepared. The emission of these materials ranges from 500 nm to 620 nm with the possibility to compositionally tune the Stokes shift and the self‐trapped exciton emission bands.
Fully inorganic, perovskite‐derived zero‐dimensional Cs4SnBr6 exhibits room‐temperature broad‐band photoluminescence from self‐trapped excitons, centered at 540 nm with a quantum yield of 15±5 % (298 K; near 100 % at 200 K), and a large Stokes shift of ca.1.2 eV. A compositional series, Cs4−xAxSn(Br1−yIy)6 (A=Rb, K; x≤1, y≤1), was obtained wherein the emission peak ranges from 500 nm to 620 nm.
This paper presents a density- and grid- based (DGB) clustering method for categorizing data with arbitrary shapes and noise. As most of the conventional clustering approaches work only with ...round-shaped clusters, other methods are needed to be explored to proceed classification of clusters with arbitrary shapes. Clustering approach by fast search and find of density peaks and density-based spatial clustering of applications with noise, and so many other methods are reported to be capable of completing this task but are limited by their computation time of mutual distances between points or patterns. Without the calculation of mutual distances, this paper presents an alternative method to fulfill clustering of data with any shape and noise even faster and with more efficiency. It was successfully verified in clustering industrial data (e.g., DNA microarray data) and several benchmark datasets with different kinds of noise. It turned out that the proposed DGB clustering method is more efficient and faster in clustering datasets with any shape than the conventional methods.
Because of their excellent scheduling capabilities, artificial neural networks (ANNs) are becoming popular in short-term electric power system forecasting, which is essential for ensuring both ...efficient and reliable operations and full exploitation of electrical energy trading as well. For such a reason, this paper investigates the effectiveness of some of the newest designed algorithms in machine learning to train typical radial basis function (RBF) networks for 24-h electric load forecasting: support vector regression (SVR), extreme learning machines (ELMs), decay RBF neural networks (DRNNs), improves second order, and error correction, drawing some conclusions useful for practical implementations.
Difficult experiments in training neural networks often fail to converge due to what is known as the flat-spot problem, where the gradient of hidden neurons in the network diminishes in value, ...rending the weight update process ineffective. Whereas a first-order algorithm can address this issue by learning parameters to normalize neuron activations, the second-order algorithms cannot afford additional parameters given that they include a large Jacobian matrix calculation. This paper proposes Levenberg-Marquardt with weight compression (LM-WC), which combats the flat-spot problem by compressing neuron weights to push neuron activation out of the saturated region and close to the linear region. The presented algorithm requires no additional learned parameters and contains an adaptable compression parameter, which is adjusted to avoid training failure and increase the probability of neural network convergence. Several experiments are presented and discussed to demonstrate the success of LM-WC against standard LM and LM with random restarts on benchmark data sets for varying network architectures. Our results suggest that the LM-WC algorithm can improve training success by 10 times or more compared with other methods.
Bats possess extraordinary adaptations, including flight, echolocation, extreme longevity and unique immunity. High-quality genomes are crucial for understanding the molecular basis and evolution of ...these traits. Here we incorporated long-read sequencing and state-of-the-art scaffolding protocols
to generate, to our knowledge, the first reference-quality genomes of six bat species (Rhinolophus ferrumequinum, Rousettus aegyptiacus, Phyllostomus discolor, Myotis myotis, Pipistrellus kuhlii and Molossus molossus). We integrated gene projections from our 'Tool to infer Orthologs from Genome Alignments' (TOGA) software with de novo and homology gene predictions as well as short- and long-read transcriptomics to generate highly complete gene annotations. To resolve the phylogenetic position of bats within Laurasiatheria, we applied several phylogenetic methods to comprehensive sets of orthologous protein-coding and noncoding regions of the genome, and identified a basal origin for bats within Scrotifera. Our genome-wide screens revealed positive selection on hearing-related genes in the ancestral branch of bats, which is indicative of laryngeal echolocation being an ancestral trait in this clade. We found selection and loss of immunity-related genes (including pro-inflammatory NF-κB regulators) and expansions of anti-viral APOBEC3 genes, which highlights molecular mechanisms that may contribute to the exceptional immunity of bats. Genomic integrations of diverse viruses provide a genomic record of historical tolerance to viral infection in bats. Finally, we found and experimentally validated bat-specific variation in microRNAs, which may regulate bat-specific gene-expression programs. Our reference-quality bat genomes provide the resources required to uncover and validate the genomic basis of adaptations of bats, and stimulate new avenues of research that are directly relevant to human health and disease
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Phase competition underlies many remarkable and technologically important phenomena in transition metal oxides. Vanadium dioxide (VO2) exhibits a first-order metal-insulator transition (MIT) near ...room temperature, where conductivity is suppressed and the lattice changes from tetragonal to monoclinic on cooling. Ongoing attempts to explain this coupled structural and electronic transition begin with two alternative starting points: a Peierls MIT driven by instabilities in electron-lattice dynamics and a Mott MIT where strong electron-electron correlations drive charge localization. A key missing piece of the VO2 puzzle is the role of lattice vibrations. Moreover, a comprehensive thermodynamic treatment must integrate both entropic and energetic aspects of the transition. Here we report that the entropy driving the MIT in VO2 is dominated by strongly anharmonic phonons rather than electronic contributions, and provide a direct determination of phonon dispersions. Our ab initio calculations identify softer bonding in the tetragonal phase, relative to the monoclinic phase, as the origin of the large vibrational entropy stabilizing the metallic rutile phase. They further reveal how a balance between higher entropy in the metal and orbital-driven lower energy in the insulator fully describes the thermodynamic forces controlling the MIT. Our study illustrates the critical role of anharmonic lattice dynamics in metal oxide phase competition, and provides guidance for the predictive design of new materials.
A new type of composite wall system incorporating phase change materials (PCMs) was proposed and its potential for air conditioning/heating energy savings in continental temperate climate was ...evaluated. The novelty of the wall system consists of the fact that two PCM wallboards, impregnated with different PCMs are used. The structure of the new wall system is that of a three-layer sandwich-type insulating panel with outer layers consisting of PCM wallboards and middle layer conventional thermal insulation. The PCM wallboard layers have different functions: the external layer has a higher value of the PCM melting point and it is active during hot season and the internal layer with a PCM melting point near set point temperature for heating is active during cold season. A year-round simulation of a room built using the new wall system was carried out and the effect of PCM presence into the structure of the wall system was assessed. It was found that the new wall system contributes to annual energy savings and reduces the peak value of the cooling/heating loads. The melting point values for the two PCMs resulting in the highest value of the energy savings were identified.
The stability properties of the Hill equation are discussed, especially those of the Mathieu equation that characterize ion motion in electrodynamic traps. The solutions of the Mathieu-Hill equation ...for a trapped ion are characterized by employing the Floquet theory and Hill’s method solution, which yields an infinite system of linear and homogeneous equations whose coefficients are recursively determined. Stability is discussed for parameters a and q that are real. Characteristic curves are introduced naturally by the Sturm–Liouville problem for the well-known even and odd Mathieu equations cem(z,q) and sem(z,q). In the case of a Paul trap, the stable solution corresponds to a superposition of harmonic motions. The maximum amplitude of stable oscillations for ideal conditions (taken into consideration) is derived. We illustrate the stability diagram for a combined (Paul and Penning) trap and represent the frontiers of the stability domains for both axial and radial motion, where the former is described by the canonical Mathieu equation. Anharmonic corrections for nonlinear Paul traps are discussed within the frame of perturbation theory, while the frontiers of the modified stability domains are determined as a function of the chosen perturbation parameter and we demonstrate they are shifted towards negative values of the a parameter. The applications of the results include but are not restricted to 2D and 3D ion traps used for different applications such as mass spectrometry (including nanoparticles), high resolution atomic spectroscopy and quantum engineering applications, among which we mention optical atomic clocks and quantum frequency metrology.
ABSTRACT
Cosmological models and their corresponding parameters are widely debated because of the current discrepancy between the results of the Hubble constant, H0, obtained by SNe Ia, and the ...Planck data from the cosmic microwave background radiation. Thus, considering high redshift probes like gamma-ray bursts (GRBs) is a necessary step. However, using GRB correlations between their physical features to infer cosmological parameters is difficult because GRB luminosities span several orders of magnitude. In our work, we use a three-dimensional relation between the peak prompt luminosity, the rest-frame time at the end of the X-ray plateau, and its corresponding luminosity in X-rays: the so-called 3D Dainotti fundamental plane relation. We correct this relation by considering the selection and evolutionary effects with a reliable statistical method, obtaining a lower central value for the intrinsic scatter, σint = 0.18 ± 0.07 (47.1 per cent) compared to previous results, when we adopt a particular set of GRBs with well-defined morphological features, called the platinum sample. We have used the GRB fundamental plane relation alone with both Gaussian and uniform priors on cosmological parameters and in combination with SNe Ia and BAO measurements to infer cosmological parameters like H0, the matter density in the universe (ΩM), and the dark energy parameter w for a wCDM model. Our results are consistent with the parameters given by the Lambda cold dark matter model but with the advantage of using cosmological probes detected up to z = 5, much larger than the one observed for the furthest SNe Ia.
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