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Background: Mutations in the RCC1 and BTB domain-containing protein 1 (RCBTB1) gene have been implicated in a rare form of retinal dystrophy. Herein, we report the clinical features of a 45-year-ol...

Acoustic-graphene-plasmons (AGPs) are highly confined electromagnetic modes, which carry extreme momentum and low loss in the Mid-infrared (MIR) to Terahertz (THz) spectra. They are therefore enablers of extremely strong light-matter interactions at these long wavelengths. However, owing to their large momentum they are also challenging to excite and detect. Here, we demonstrate a new way to excite AGPs that are confined to nanometric-scale cavities directly from the far-field, via localized graphene-plasmon-magnetic-resonators (GPMRs). This approach enables the efficient excitation of single AGP cavities, which are able to confine MIR light to record-breaking ultra-small mode-volumes, which are over a billion times smaller than their free-space volume.

Acoustic-graphene-plasmons (AGPs) are highly confined electromagnetic modes, which carry extreme momentum and low loss in the Mid-infrared (MIR) to Terahertz (THz) spectra. In this work [1], we demonstrate a new way to excite AGPs from the far-field, which are confined to nanometric-scale cavities, via localized graphene-plasmon-magnetic-resonators (GPMRs). This approach enables the efficient excitation of single AGP cavities, which are able to confine MIR light to record-breaking ultra-small mode-volumes that are ∼5·1010 times smaller than their free-space volume.

The potential association between coal-burning arsenic exposure and type 2 diabetes (T2D) was examined through a case control study, conducted in coal-burning arsenic poisoning areas in the Guizhou Province. This study included patients diagnosed with type 2 diabetes. Control subjects without type 2 diabetes were recruited randomly after gender and age 1:1 matching. All subjects completed questionnaire surveys and underwent physical examination and whole blood arsenic level testing. The whole blood arsenic level was associated with a significant increase in the risk of type 2 diabetes (75th versus 25th, adjusted OR = 1.76, 95% CI: 1.03-3.01). However, a nonlinear relationship was observed between the blood arsenic level and type 2 diabetes. The risk of type 2 diabetes increased with blood arsenic levels above 3.69 μg/L (Log As ≥0.57). The subgroup analysis revealed that blood arsenic levels were associated with significantly increased risk of type 2 diabetes in people who ever smoked (P .05), particularly those who smoked ≥15 years (adjusted OR = 3.15, 95% CI: 1.9-7.28). Therefore, prolonged arsenic exposure, even at a low level, is associated with a higher prevalence of type 2 diabetes in a nonlinear pattern. Blood arsenic levels less than 3.69 μg/L may be considered safe with respect to the risk of T2D. However, smoking, particularly smoking ≥15 years, may be associated with the development of diabetes in patients with arsenic exposure.

In order to adapt to the current trend of higher education popularization and the need of mathematics teaching in the Internet Age, this paper combines the mobile terminal of Internet technology with the traditional higher mathematics classroom teaching and explores the hybrid teaching mode based on the support of Internet class. The purpose is to fully give play to the teacher’s guiding role in guiding, inspiring, and monitoring the teaching process and mobilize the students’ enthusiasm and creativity in the learning process.

We propose and experimentally demonstrate a polarization-selective waveguide hologram at optical wavelengths, based on an all-dielectric metamaterial multilayer system. We show that two spatially separated or overlapped holographic images can be produced with two orthogonally polarized beams, incorporated into a binary computer generated hologram (CGH). These two images can be combined into a single 3D stereoscopic image observable using linearly or circularly polarized glasses. The two polarized beams can also be utilized to construct radially and azimuthally polarized "vortex" beams. The fundamental and first higher-order TM and TE modes of an optical waveguide are used to guide the two polarization states with distinct propagation constants. The two guided waves act as spatially distinct reference waves such that the integrated, on-chip hologram can distinguish the two and provide two independent images corresponding to the two polarizations. Polarization selective waveguide holograms can be used in a diverse set of applications, from chip-scale displays and augmented reality (AR) to optical trapping.

This paper characterizes the Single Event Effect (SEE) sensitivities of the Serializer/Deserializer (SerDes) module on the advanced 28 nm Xilinx Kintex-7 Field Programmable Gate Array (FPGA). A systematical SEE measurement method is proposed and implemented to evaluate the SEE sensitivity of the SerDes circuits. In our experiments, an extremely low Single Event Upset (SEU) Linear Energy Transfer (LET) threshold of the SerDes circuits was investigated, and both the recoverable and unrecoverable Single Event Functional Interrupts (SEFIs) were clearly distinguished and classified. In the experiments, it was found that the SEUs and recoverable SEFIs of the TX and RX in the same channel were closely related due to their shared clock and control circuits. Based on this detailed survey, a further discussion of the mechanisms of the SEU, recoverable SEFI, and unrecoverable SEFI is also provided. The SEE sensitivity of the high-speed SerDes circuits presented in this paper will promote the effective utilization of error mitigation strategies in order to control the risks of applications in radiation environments.

Light switchable materials are essential to optoelectronic applications in photovoltaics, memories, sensors, and communications. Natural switchable materials suffer from weak absorption and slow response times, preventing their use in low-power, ultrafast applications. Integrating light switchable materials with metasurface perfect absorbers offers an innovative route to achieving desirable features for nanophotonic devices, such as directional emission, low-power and broadband operation, high radiative quantum efficiency, and large spontaneous emission rates. Here we show an enhanced two-photon photochromism based on a metasurface perfect absorber: film-coupled colloidal silver nanocubes. The photochromic molecules, spiropyrans, are sandwiched between the silver nanocubes and the gold substrate. With nearly 100% absorption and an accompanying large field enhancement in the molecular junction, the transformation of spiropyrans to merocyanines is observed under excitation with 792 nm laser light. Fluorescence lifetime measurements on the merocyanine form reveal that large Purcell enhancement in the film-coupled nanocubes leads to large enhancements of the spontaneous emission rate and a high quantum efficiency. An averaged incident power as low as 10 μW is enough to initiate the two-photon isomerization of spiropyran in the film-coupled nanocubes, and a power of 100nW is able to excite the merocyanines to emit fluorescence. The power consumption is orders of magnitude lower than bare spiropyran thin films on silicon and gold, which is highly desirable for the writing and reading processes relevant to optical data storage. By sweeping the plasmonic resonance of the film-coupled nanocubes, wavelength specificity is demonstrated, which opens up new possibilities for minimizing the cross talk between adjacent bits in nanophotonic devices.

During the past decades, major advances have been made in both the generation and detection of infrared light; however, its efficient wavefront manipulation and information processing still encounter great challenges. Efficient and fast optoelectronic modulators and spatial light modulators are required for mid-infrared imaging, sensing, security screening, communication and navigation, to name a few. However, their development remains elusive, and prevailing methods reported so far have suffered from drawbacks that significantly limit their practical applications. In this study, by leveraging graphene and metasurfaces, we demonstrate a high-performance free-space mid-infrared modulator operating at gigahertz speeds, low gate voltage and room temperature. We further pixelate the hybrid graphene metasurface to form a prototype spatial light modulator for high frame rate single-pixel imaging, suggesting orders of magnitude improvement over conventional liquid crystal or micromirror-based spatial light modulators. This work opens up the possibility of exploring wavefront engineering for infrared technologies for which fast temporal and spatial modulations are indispensable., Metamaterials: mid-infrared modulator Ultrafast modulators and spatial light modulators (SLMs) for mid-infrared light have been realized by the use of an electrically-tunable graphene on a silicon-integrated metasurface. The modulators designed and built by Beibei Zeng and coworkers from Los Alamos National Laboratory, Duke University and Arizona State University in the US offer a depth of modulation of 90% and a modulation speed exceeding 1 GHz. The modulator consists of a sandwich structure consisting of an array of gold nanoantennas, a layer of graphene, atop a thin dielectric film of Al2O3, an amorphous-Si layer and a rear reflector made of gold. The structure also features gate and drain electrodes to electrically tune the device. When constructed into a 6x6 pixel array the modulators allow the realization of a SLM for proof-of-principle high frame rate single-pixel imaging in the mid-IR.

We study the angle-dependent optical reflectance spectrum of a metasurface consisting of a periodic array of film-coupled plasmonic nanopatch particles. The nanopatch metasurface exhibits a strong, angle-independent absorption resonance at a wavelength defined by the nanopatch geometry and relative density. When the nanopatches are arranged in a regular lattice, a second, sharp absorption dip is present that varies strongly as a function of the incidence angle. This second resonance is a collective effect involving the excitation of surface plasmon modes and relates to a Wood’s anomaly. Using an analytical model, we compute the surface modes of the structure and confirm details about the various mechanisms that contribute to the reflection spectra. The measured reflectance spectra are in excellent agreement with both analytical calculations and full-wave numerical simulations.

LED is a new generation of solid cold light source, LED packaging technology is the decision key to enter the field of general lighting one of the key technologies. With LED brightness and luminous efficiency continues to improve, it will also be more and more challenging. On the one hand, the package must have the largest LED light extraction rate, so that light losses to a minimum. On the other hand, the package must have the best thermal performance LED, if the cooling efficiency, LED brightness will decrease, and also shorten the LED life, solve the heat problem has become a power type LED applications Prerequisite. Through thermal simulation software Solidworks, this article did a simulation on some typical LED package materials, and then considered a various factors based on the simulation results, the right requirements of high-power light-emitting materials were founded, so that high-power LED lighting devices get popularity.

Building properties on a map can be represented by multiple building characterization factors. In this paper, using principal component analysis method, we analyzed multiple factors characterizing buildings. Also, through dimensionality reduction transformation into a small amount of comprehensive factors, this paper proposed simplified expression of building properties, to better meet the need of map generalization for buildings.

Various examples of out-of-plane multicolor waveguide holography systems, methods of manufacture, and methods of use are described herein. In some examples, a multicolor waveguide holography system includes a planar waveguide to convey optical radiation between a grating coupler and a metasurface hologram. The grating coupler may be configured to couple out-of-plane optical radiation of three different color incident at three different angles into the planar waveguide. The combined multicolor optical radiation may be conveyed by the waveguide to the metasurface hologram. The metasurface hologram may diffractively decouple the three colors of optical radiation for off-plane propagation to form a multicolor holographic image in free space.

Hyperspectral remote sensing image (HSI) consists of hundreds of bands that contain rich space, radiation and spectral information. The high-dimensional data can also lead to the course of dimensionality problem making it difficult to be used effectively. In this paper, we proposed a manifold learning algorithm to reduce the dimensionality for HSI data. For high dimensional datasets with continuous variables, it is often the case that the data points are arranged along with low dimensional structures, named manifolds, in the high dimensional space. Manifold learning aims to identifying those special low dimensional structures for subsequent usage such as classification or regression. However, many manifold learning algorithms perform an eigenvector analysis on a data similarity matrix whose size is N∗N, where N is the number of data points. The memory complexity of the analysis is at least O(N2) that is not feasible for a regular computer to compute or storage for very large datasets. To solve this problem, we used statistical sampling methods to sample a subset of data points as landmarks. A skeleton of the manifold was then identified based on the landmarks. The remaining data points were then inserted into the skeleton by Locally Linear Embedding (LLE). We tested our algorithm on AVIRIS Salinas-A data set. The experimental results showed that the HSI dataset could be reduced to a lower-dimensional space for land use classification with good performance, and the main structure was preserved well.

High-dimensional data such as hyperspectral images contain abundant information of surface radiation. But the massive redundant information makes it complex to be utilized conveniently. To solve this problem, a manifold learning dimensionality reduction framework for hyperspectral image is proposed. Firstly, statistical sampling methods were used to sample a subset of data points as landmarks. A skeleton of the manifold was then identified basing on the landmarks. The remaining data points were then inserted into the skeleton by Locally Linear Embedding algorithm. At last, original data sets and data sets reduced with different manifold learning approaches were classified by KNN classifier to evaluate the performance of the proposed framework. The framework was tested on AVIRIS Salinas-A dataset. The experimental results showed that the tradeoff of accuracy with different landmarks is of great significant. Insufficient landmarks lead to low accuracy and excess landmarks may spend a considerable amount of time.

Hyperspectral remote sensing image (HSI) consists of hundreds of bands that contain rich space, radiation and spectral information. The high-dimensional data can also lead to the curse of dimensionality problem making it difficult to be used effectively. In this paper, we proposed a manifold learning algorithm to reduce the dimensionality for HSI data. For high dimensional datasets with continuous variables, it is often the case that the data points are arranged along with low dimensional structures, named manifolds, in the high dimensional space. Manifold learning aims to identifying those special low dimensional structures for subsequent usage such as classification or regression. However, many manifold learning algorithms perform an eigenvector analysis on a data similarity matrix whose size is N×N, where N is the number of data points. The memory complexity of the analysis is at least O(N2) that is not feasible for a regular computer to compute or storage for very large datasets. To solve this problem, we used statistical sampling methods to sample a subset of data points as landmarks. A skeleton of the manifold was then identified based on the landmarks. The remaining data points were then inserted into the skeleton by Locally Linear Embedding (LLE). We tested our algorithm on AVIRIS Salinas-A data set. The experimental results showed that the HSI dataset could be reduced to a lower-dimensional space for land use classification with good performance, and the main structure was preserved well.

Background: Breast cancer is one of the most common malignancies with increasing incidences every year and a leading cause of death among women. Although early stage breast cancer can be effectively treated, there are limited numbers of treatment options available for patients with advanced and metastatic disease. The novel breast cancer associated antigen NY-BR-1 was identified by SEREX analysis and is expressed in the majority (>70%) of breast tumors as well as metastases, in normal breast tissue, in testis and occasionally in prostate tissue. The biological function and regulation of NY-BR-1 is up to date unknown. Methods: We performed an in silico analysis on the genetic variations of the NY-BR-1 gene using data available in public SNP databases and the tools SIFT, Polyphen and Provean to find possible functional SNPs. Additionally, we considered the allele frequency of the found damaging SNPs and also analyzed data from an in-house sequencing project of 55 breast cancer samples for recurring SNPs, recorded in dbSNP. Results: Over 2800 SNPs are recorded in the dbSNP and NHLBI ESP databases for the NY-BR-1 gene. Of these, 65 (2.07%) are synonymous SNPs, 191 (6.09%) are non-synoymous SNPs, and 2430 (77.48%) are noncoding intronic SNPs. As a result, 69 non-synoymous SNPs were predicted to be damaging by at least two, and 16 SNPs were predicted as damaging by all three of the used tools. The SNPs rs200639888, rs367841401 and rs377750885 were categorized as highly damaging by all three tools. Eight damaging SNPs are located in the ankyrin repeat domain (ANK), a domain known for its frequent involvement in protein-protein interactions. No distinctive features could be observed in the allele frequency of the analyzed SNPs. Conclusion: Considering these results we expect to gain more insights into the variations of the NY-BR-1 gene and their possible impact on giving rise to splice variants and therefore influence the function of NY-BR-1 in healthy tissue as well as in breast cancer.

As social network is becoming widely used, the problem of protection of user's privacy has caused heated debate. It is necessary to let users know who would propagate or leak their personal information, and we define those people as vulnerable friends. Most existing approaches are either personal information based or users' influence based. In this paper, we aim to mine the vulnerable information behind, and thus better identify vulnerable friends. In this paper, we present a Fuzzy Analytical Hierarchy Process (FAHP) based method by fusing users' influence consideration. Apparently, multiple factors (e.g., gender, birthday, hometown, mobile phone, high school, college etc.) may affect propagation of privacy information. Therefore, we first present the calculation of users' influence. Second, we adopt FAHP to analysis users' information and consider their probability of propagating other people's information. At last, we use Coefficient of Variation combine those factors. A thorough experimental comparison, based on the data which regards to Facebook, illustrates advantage of our scheme over other algorithms.

The light distribution simulation of LED is very important before the production. it is necessary to do meaningful light distribution simulation before the production of LED. At present, in the market, there are very few companies which can produce LED chips, because of less investment, low threshold into line, most of the companies are doing package and application of LED, it is needed to do the design of LED light distribution. In this paper the MFC simulation program by MATLAB program can run in every operating system. Moreover, the design of the program is of high practicability. The research on problems of LED light distribution will bring meaningful and valuable reference and guidance for some enterprises.