New progress in LURR-integrating with the dimensional method

The evolution laws of LURR (Loading-Unloading Response Ratio) before strong earthquakes, especially the peak point of LURR, are described in this paper. The results of four methods (experimental, numerical simulation, seismic data analysis and with damage mechanics analysis) lead to a consistent conclusion-the evolution laws of LURR before strong earthquakes are that, at the early stage of the seismic cycle, LURR will fluctuate around 1 and in the late stage, it rises swiftly and to its peak point. At some time after this peak point, a catastrophic event or events occur. These do not occur at the peak point, but lag behind. The lag time which is denoted by T (2) depends on the magnitude M of the upcoming earthquake among other factors. In order to consider the influence of geophysical parameters in a specific region such as E (a) and J ((t)), where is the shear strain rate of tectonic loading in situ, E (a) is the sum of radiated energy of all earthquake occurring in a specific region measured during a long time duration (110 years in this paper) divided by the area of the region and the time duration, and J ((t)) is a parameter denoting the LURR anomaly area weighted with Y (the value of LURR) and represents the expanse and degree of the seismogenic zone. The dimensional analysis method has been used to reveal the relation between M, T (2) and other parameters in situ for more reliable earthquake prediction

Synthetically Supervised Feature Learning for Scene Text Recognition

We address the problem of image feature learning for scene text recognition. The image features in the state-of-the-art methods are learned from large-scale synthetic image datasets. However, most meth- ods only rely on outputs of the synthetic data generation process, namely realistically looking images, and completely ignore the rest of the process. We propose to leverage the parameters that lead to the output images to improve image feature learning. Specifically, for every image out of the data generation process, we obtain the associated parameters and render another “clean” image that is free of select distortion factors that are ap- plied to the output image. Because of the absence of distortion factors, the clean image tends to be easier to recognize than the original image which can serve as supervision. We design a multi-task network with an encoder-discriminator-generator architecture to guide the feature of the original image toward that of the clean image. The experiments show that our method significantly outperforms the state-of-the-art methods on standard scene text recognition benchmarks in the lexicon-free cate- gory. Furthermore, we show that without explicit handling, our method works on challenging cases where input images contain severe geometric distortion, such as text on a curved path

Nox4 reprograms cardiac substrate metabolism via protein O-GlcNAcylation to enhance stress adaptation.

Cardiac hypertrophic remodeling during chronic hemodynamic stress is associated with a switch in preferred energy substrate from fatty acids to glucose, usually considered to be energetically favorable. The mechanistic interrelationship between altered energy metabolism, remodeling, and function remains unclear. The ROS-generating NADPH oxidase-4 (Nox4) is upregulated in the overloaded heart, where it ameliorates adverse remodeling. Here, we show that Nox4 redirects glucose metabolism away from oxidation but increases fatty acid oxidation, thereby maintaining cardiac energetics during acute or chronic stresses. The changes in glucose and fatty acid metabolism are interlinked via a Nox4-ATF4-dependent increase in the hexosamine biosynthetic pathway, which mediates the attachment of O-linked N-acetylglucosamine (O-GlcNAcylation) to the fatty acid transporter CD36 and enhances fatty acid utilization. These data uncover a potentially novel redox pathway that regulates protein O-GlcNAcylation and reprograms cardiac substrate metabolism to favorably modify adaptation to chronic stress. Our results also suggest that increased fatty acid oxidation in the chronically stressed heart may be beneficial

Ultrathin 2 nm gold as ideal impedance-matched absorber for infrared light

Thermal detectors are a cornerstone of infrared (IR) and terahertz (THz) technology due to their broad spectral range. These detectors call for suitable broad spectral absorbers with minimalthermal mass. Often this is realized by plasmonic absorbers, which ensure a high absorptivity butonly for a narrow spectral band. Alternativly, a common approach is based on impedance-matching the sheet resistance of a thin metallic film to half the free-space impedance. Thereby, it is possible to achieve a wavelength-independent absorptivity of up to 50 %, depending on the dielectric properties of the underlying substrate. However, existing absorber films typicallyrequire a thickness of the order of tens of nanometers, such as titanium nitride (14 nm), whichcan significantly deteriorate the response of a thermal transducers. Here, we present the application of ultrathin gold (2 nm) on top of a 1.2 nm copper oxide seed layer as an effective IR absorber. An almost wavelength-independent and long-time stable absorptivity of 47(3) %, ranging from 2 $\mu$m to 20 $\mu$m, could be obtained and is further discussed. The presented gold thin-film represents analmost ideal impedance-matched IR absorber that allows a significant improvement of state-of-the-art thermal detector technology

LURR's Twenty Years and Its Perspective

Seismogenic process is a nonlinear and irreversible one, so that the response to loading of a seismogenic zone is different from the unloading one. This difference reflects quantitatively the process of an earthquake preparation. A physics-based new parameter-Load/Unload Response Ratio (LURR) was proposed to measure quantitatively the proximity to a strong earthquake and then used to be an earthquake predictor. In the present paper, a brief history of LURR is recalled; inspection of real earthquake cases, numerical simulations and laboratory studies of LURR, prediction efforts in terms of LURR, probability problem of LURR and its prospect are also expatiated

Role of Temperature in the Growth of Silver Nanoparticles Through a Synergetic Reduction Approach

This study presents the role of reaction temperature in the formation and growth of silver nanoparticles through a synergetic reduction approach using two or three reducing agents simultaneously. By this approach, the shape-/size-controlled silver nanoparticles (plates and spheres) can be generated under mild conditions. It was found that the reaction temperature could play a key role in particle growth and shape/size control, especially for silver nanoplates. These nanoplates could exhibit an intensive surface plasmon resonance in the wavelength range of 700–1,400 nm in the UV–vis spectrum depending upon their shapes and sizes, which make them useful for optical applications, such as optical probes, ionic sensing, and biochemical sensors. A detailed analysis conducted in this study clearly shows that the reaction temperature can greatly influence reaction rate, and hence the particle characteristics. The findings would be useful for optimization of experimental parameters for shape-controlled synthesis of other metallic nanoparticles (e.g., Au, Cu, Pt, and Pd) with desirable functional properties

Medical physics aspects of cancer care in the Asia Pacific region

Medical physics plays an essential role in modern medicine. This is particularly evident in cancer care where medical physicists are involved in radiotherapy treatment planning and quality assurance as well as in imaging and radiation protection. Due to the large variety of tasks and interests, medical physics is often subdivided into specialties such as radiology, nuclear medicine and radiation oncology medical physics. However, even within their specialty, the role of radiation oncology medical physicists (ROMPs) is diverse and varies between different societies. Therefore, a questionnaire was sent to leading medical physicists in most countries/areas in the Asia/Pacific region to determine the education, role and status of medical physicists

A pivotal role for starch in the reconfiguration of 14C-partitioning and allocation in Arabidopsis thaliana under short-term abiotic stress.

Plant carbon status is optimized for normal growth but is affected by abiotic stress. Here, we used 14C-labeling to provide the first holistic picture of carbon use changes during short-term osmotic, salinity, and cold stress in Arabidopsis thaliana. This could inform on the early mechanisms plants use to survive adverse environment, which is important for efficient agricultural production. We found that carbon allocation from source to sinks, and partitioning into major metabolite pools in the source leaf, sink leaves and roots showed both conserved and divergent responses to the stresses examined. Carbohydrates changed under all abiotic stresses applied; plants re-partitioned 14C to maintain sugar levels under stress, primarily by reducing 14C into the storage compounds in the source leaf, and decreasing 14C into the pools used for growth processes in the roots. Salinity and cold increased 14C-flux into protein, but as the stress progressed, protein degradation increased to produce amino acids, presumably for osmoprotection. Our work also emphasized that stress regulated the carbon channeled into starch, and its metabolic turnover. These stress-induced changes in starch metabolism and sugar export in the source were partly accompanied by transcriptional alteration in the T6P/SnRK1 regulatory pathway that are normally activated by carbon starvation