Technical note: Intercomparison of three AATSR Level 2 (L2) AOD products over China

One of four main focus areas of the PEEX initiative is to establish and sustain long-term, continuous, and comprehensive ground-based, airborne, and seaborne observation infrastructure together with satellite data. The Advanced Along-Track Scanning Radiometer (AATSR) aboard ENVISAT is used to observe the Earth in dual view. The AATSR data can be used to retrieve aerosol optical depth (AOD) over both land and ocean, which is an important parameter in the characterization of aerosol properties. In recent years, aerosol retrieval algorithms have been developed both over land and ocean, taking advantage of the features of dual view, which can help eliminate the contribution of Earth's surface to top-of-atmosphere (TOA) reflectance. The Aerosol_cci project, as a part of the Climate Change Initiative (CCI), provides users with three AOD retrieval algorithms for AATSR data, including the Swansea algorithm (SU), the ATSR-2ATSR dual-view aerosol retrieval algorithm (ADV), and the Oxford-RAL Retrieval of Aerosol and Cloud algorithm (ORAC). The validation team of the Aerosol-CCI project has validated AOD (both Level 2 and Level 3 products) and AE (Ångström Exponent) (Level 2 product only) against the AERONET data in a round-robin evaluation using the validation tool of the AeroCOM (Aerosol Comparison between Observations and Models) project. For the purpose of evaluating different performances of these three algorithms in calculating AODs over mainland China, we introduce ground-based data from CARSNET (China Aerosol Remote Sensing Network), which was designed for aerosol observations in China. Because China is vast in territory and has great differences in terms of land surfaces, the combination of the AERONET and CARSNET data can validate the L2 AOD products more comprehensively. The validation results show different performances of these products in 2007, 2008, and 2010. The SU algorithm performs very well over sites with different surface conditions in mainland China from March to October, but it slightly underestimates AOD over barren or sparsely vegetated surfaces in western China, with mean bias error (MBE) ranging from 0.05 to 0.10. The ADV product has the same precision with a low root mean square error (RMSE) smaller than 0.2 over most sites and the same error distribution as the SU product. The main limits of the ADV algorithm are underestimation and applicability; underestimation is particularly obvious over the sites of Datong, Lanzhou, and Urumchi, where the dominant land cover is grassland, with an MBE larger than 0.2, and the main aerosol sources are coal combustion and dust. The ORAC algorithm has the ability to retrieve AOD at different ranges, including high AOD (larger than 1.0); however, the stability deceases significantly with increasing AOD, especially when AOD > 1.0. In addition, the ORAC product is consistent with the CARSNET product in winter (December, January, and February), whereas other validation results lack matches during winter

Dust aerosol optical depth retrieval and dust storm detection for Xinjiang Region using Indian National Satellite Observations

The Xinjiang Uyghur Autonomous Region (Xinjiang) is located near the western border of China. Xinjiang has a high frequency of dust storms, especially in late winter and early spring. Geostationary satellite remote sensing offers an ideal way to monitor the regional distribution and intensity of dust storms, which can impact the regional climate. In this study observations from the Indian National Satellite (INSAT) 3D are used for dust storm detection in Xinjiang because of the frequent 30-min observations with six bands. An analysis of the optical properties of dust and its quantitative relationship with dust storms in Xinjiang is presented for dust events in April 2014. The Aerosol Optical Depth (AOD) derived using six predefined aerosol types shows great potential to identify dust events. Cross validation between INSAT-3D retrieved AOD and MODIS AOD shows a high coefficient of determination (R2 = 0.92). Ground validation using AERONET (Aerosol Robotic Network) AOD also shows a good correlation with R2 of 0.77. We combined the apparent reflectance (top-of-atmospheric reflectance) of visible and shortwave infrared bands, brightness temperature of infrared bands and retrieved AOD into a new Enhanced Dust Index (EDI). EDI reveals not only dust extent but also the intensity. EDI performed very well in measuring the intensity of dust storms between 22 and 24 April 2014. A visual comparison between EDI and Feng Yun-2E (FY-2E) Infrared Difference Dust Index (IDDI) also shows a high level of similarity. A good linear correlation (R2 of 0.78) between EDI and visibility on the ground demonstrates good performance of EDI in estimating dust intensity. A simple threshold method was found to have a good performance in delineating the extent of the dust plumes but inadequate for providing information on dust plume intensity

Bio-inspired plasmonic nanoarchitectured hybrid system towards enhanced far red-to-near infrared solar photocatalysis

Solar conversion to fuels or to electricity in semiconductors using far red-to-near infrared (NIR) light, which accounts for about 40% of solar energy, is highly significant. One main challenge is the development of novel strategies for activity promotion and new basic mechanisms for NIR response. Mother Nature has evolved to smartly capture far red-to-NIR light via their intelligent systems due to unique micro/nanoarchitectures, thus motivating us for biomimetic design. Here we report the first demonstration of a new strategy, based on adopting nature’s far red-to-NIR responsive architectures for an efficient bio-inspired photocatalytic system. The system is constructed by controlled assembly of light-harvesting plasmonic nanoantennas onto a typical photocatalytic unit with butterfly wings’ 3D micro/nanoarchitectures. Experiments and finite-difference time-domain (FDTD) simulations demonstrate the structural effects on obvious far red-to-NIR photocatalysis enhancement, which originates from (1) Enhancing far red-to-NIR (700~1200 nm) harvesting, up to 25%. (2) Enhancing electric-field amplitude of localized surface plasmon (LSPs) to more than 3.5 times than that of the non-structured one, which promotes the rate of electron-hole pair formation, thus substantially reinforcing photocatalysis. This proof-of-concept study provides a new methodology for NIR photocatalysis and would potentially guide future conceptually new NIR responsive system designs

The Changing Landscape for Stroke\ua0Prevention in AF: Findings From the GLORIA-AF Registry Phase 2

Background GLORIA-AF (Global Registry on Long-Term Oral Antithrombotic Treatment in Patients with Atrial Fibrillation) is a prospective, global registry program describing antithrombotic treatment patterns in patients with newly diagnosed nonvalvular atrial fibrillation at risk of stroke. Phase 2 began when dabigatran, the first non\u2013vitamin K antagonist oral anticoagulant (NOAC), became available. Objectives This study sought to describe phase 2 baseline data and compare these with the pre-NOAC era collected during phase 1. Methods During phase 2, 15,641 consenting patients were enrolled (November 2011 to December 2014); 15,092 were eligible. This pre-specified cross-sectional analysis describes eligible patients\u2019 baseline characteristics. Atrial fibrillation disease characteristics, medical outcomes, and concomitant diseases and medications were collected. Data were analyzed using descriptive statistics. Results Of the total patients, 45.5% were female; median age was 71 (interquartile range: 64, 78) years. Patients were from Europe (47.1%), North America (22.5%), Asia (20.3%), Latin America (6.0%), and the Middle East/Africa (4.0%). Most had high stroke risk (CHA2DS2-VASc [Congestive heart failure, Hypertension, Age  6575 years, Diabetes mellitus, previous Stroke, Vascular disease, Age 65 to 74 years, Sex category] score  652; 86.1%); 13.9% had moderate risk (CHA2DS2-VASc = 1). Overall, 79.9% received oral anticoagulants, of whom 47.6% received NOAC and 32.3% vitamin K antagonists (VKA); 12.1% received antiplatelet agents; 7.8% received no antithrombotic treatment. For comparison, the proportion of phase 1 patients (of N = 1,063 all eligible) prescribed VKA was 32.8%, acetylsalicylic acid 41.7%, and no therapy 20.2%. In Europe in phase 2, treatment with NOAC was more common than VKA (52.3% and 37.8%, respectively); 6.0% of patients received antiplatelet treatment; and 3.8% received no antithrombotic treatment. In North America, 52.1%, 26.2%, and 14.0% of patients received NOAC, VKA, and antiplatelet drugs, respectively; 7.5% received no antithrombotic treatment. NOAC use was less common in Asia (27.7%), where 27.5% of patients received VKA, 25.0% antiplatelet drugs, and 19.8% no antithrombotic treatment. Conclusions The baseline data from GLORIA-AF phase 2 demonstrate that in newly diagnosed nonvalvular atrial fibrillation patients, NOAC have been highly adopted into practice, becoming more frequently prescribed than VKA in Europe and North America. Worldwide, however, a large proportion of patients remain undertreated, particularly in Asia and North America. (Global Registry on Long-Term Oral Antithrombotic Treatment in Patients With Atrial Fibrillation [GLORIA-AF]; NCT01468701

Segmentation Method of Cerebral Aneurysms Based on Entropy Selection Strategy

The segmentation of cerebral aneurysms is a challenging task because of their similar imaging features to blood vessels and the great imbalance between the foreground and background. However, the existing 2D segmentation methods do not make full use of 3D information and ignore the influence of global features. In this study, we propose an automatic solution for the segmentation of cerebral aneurysms. The proposed method relies on the 2D U-Net as the backbone and adds a Transformer block to capture remote information. Additionally, through the new entropy selection strategy, the network pays more attention to the indistinguishable blood vessels and aneurysms, so as to reduce the influence of class imbalance. In order to introduce global features, three continuous patches are taken as inputs, and a segmentation map corresponding to the central patch is generated. In the inference phase, using the proposed recombination strategy, the segmentation map was generated, and we verified the proposed method on the CADA dataset. We achieved a Dice coefficient (DSC) of 0.944, an IOU score of 0.941, recall of 0.946, an F2 score of 0.942, a mAP of 0.896 and a Hausdorff distance of 3.12 mm

Longgitudinal splitting versus sequential unzipping of thick-walled carbon nanotubes: Towards controllable systhesis of high-quality graphitic nanoribbons

Despite significant efforts to develop ways to produce customized carbon-based nanostructures, facile synthesis of mass graphene/graphitic nanoribbons (GNRs) without losing the intrinsic sp2-structure and properties remains challenging. Here we report that bulk of multi-layered graphitic nanoribbons can be prepared by gas-phase oxidative splitting of multi-walled carbon nanotubes (MWCNTs) using HNO3 vapor. The longitudinal splitting behavior of MWCNTs is substantially dependent on three key factors: the utilization of gaseous oxidant, the use of highly-crystallined carbon nanotubes with larger diameter, and the associated high-pressure conditions. Moreover, this splitting process is evidenced to be edge-selective and nonaggressive as opposed to traditional wet chemical oxidation, for which the obtained GNRs show minimized oxidation level, highly intact crystalline and robust electrical conductance. This study suggests a simple yet effective strategy for producing mass high-quality GNRs

Two-dimensional nanosheets by rapid and efficient microwave exfoliation of layered materials

Layered materials beyond graphene have generated renewed interests in numerous fields. Liquid-phase exfoliation methods face essential challenges in their universal application toward various two-dimensional materials (2DMs), short processing time, high yield, chemical stability, ultrathin thickness, and large lateral size of the nanosheets. To date, few reported methods are satisfactory in these requirements. We develop a general microwave-assisted, rapid (30 min), efficient (up to 50% yield), and potentially scalable approach to exfoliate 2DMs into mono- and few-layer nanosheets of superior chemical stability and large lateral size. 2DMs including h-BN, g-C3N4, BP, TMDs (MoS2, WS2, MoSe2), Zn2(bim)4, and Ti3C2Tx are tested for exfoliation in different fluid media including organic solvents and PF6–-containing ionic liquids (ILs). The nanosheets (e.g., BP) are surprisingly stable, probably attributed to solvation shells preventing the exfoliated sheets from reacting with water and oxygen. Theoretical simulations reveal that the dielectric constant of the fluid medium is a key factor determining the exfoliation efficiency. The preferred fluid media should be strongly polar (e.g., organic solvents with a high dielectric constant), which indicates materials’ ability to store electromagnetic energy via polarization. Finally, we demonstrate the 3D printing of nanosheet-based hybrids for potential applications. This general strategy paves a new promising pathway for the efficient liquid exfoliation of various 2DMs

Accelerating Deep Neural Networks by Combining Block-Circulant Matrices and Low-Precision Weights

As a key ingredient of deep neural networks (DNNs), fully-connected (FC) layers are widely used in various artificial intelligence applications. However, there are many parameters in FC layers, so the efficient process of FC layers is restricted by memory bandwidth. In this paper, we propose a compression approach combining block-circulant matrix-based weight representation and power-of-two quantization. Applying block-circulant matrices in FC layers can reduce the storage complexity from O ( k 2 ) to O ( k ) . By quantizing the weights into integer powers of two, the multiplications in the reference can be replaced by shift and add operations. The memory usages of models for MNIST, CIFAR-10 and ImageNet can be compressed by 171 × , 2731 × and 128 × with minimal accuracy loss, respectively. A configurable parallel hardware architecture is then proposed for processing the compressed FC layers efficiently. Without multipliers, a block matrix-vector multiplication module (B-MV) is used as the computing kernel. The architecture is flexible to support FC layers of various compression ratios with small footprint. Simultaneously, the memory access can be significantly reduced by using the configurable architecture. Measurement results show that the accelerator has a processing power of 409.6 GOPS, and achieves 5.3 TOPS/W energy efficiency at 800 MHz

Generalized 3D Printing of Graphene-Based Mixed-Dimensional Hybrid Aerogels

Graphene-based mixed-dimensional materials hybridization is important for a myriad of applications. However, conventional manufacturing techniques face critical challenges in producing arbitrary geometries with programmable features, continuous interior networks, and multimaterials homogeneity. Here we propose a generalized three-dimensional (3D) printing methodology for graphene aerogels and graphene-based mixed-dimensional (2D + <i>n</i>D, where <i>n</i> is 0, 1, or 2) hybrid aerogels with complex architectures, by the development of hybrid inks and printing schemes to enable mix-dimensional hybrids printability, overcoming the limitations of multicomponents inhomogeneity and harsh post-treatments for additives removal. Importantly, nonplanar designed geometries are also demonstrated by shape-conformable printing on curved surfaces. We further demonstrate the 3D-printed hybrid aerogels as ultrathick electrodes in a symmetric compression tolerant microsupercapacitor, exhibiting quasi-proportionally enhanced areal capacitances at high levels of mass loading. The excellent performance is attributed to the sufficient ion- and electron-transport paths provided by the 3D-printed highly interconnected networks. The encouraging finding indicates tremendous potentials for practical energy storage applications. As a proof of concept, this general strategy provides avenues for various next-generation complex-shaped hybrid architectures from microscale to macroscale, for example, seawater desalination devices, electromagnetic shielding systems, and so forth