A nonparametric empirical Bayes approach to covariance matrix estimation

We propose an empirical Bayes method to estimate high-dimensional covariance matrices. Our procedure centers on vectorizing the covariance matrix and treating matrix estimation as a vector estimation problem. Drawing from the compound decision theory literature, we introduce a new class of decision rules that generalizes several existing procedures. We then use a nonparametric empirical Bayes g-modeling approach to estimate the oracle optimal rule in that class. This allows us to let the data itself determine how best to shrink the estimator, rather than shrinking in a pre-determined direction such as toward a diagonal matrix. Simulation results and a gene expression network analysis shows that our approach can outperform a number of state-of-the-art proposals in a wide range of settings, sometimes substantially.Comment: 20 pages, 4 figure

Hepatitis B and Hepatitis C Seroprevalence in Children Receiving Antiretroviral Therapy for Human Immunodeficiency Virus-1 Infection in China, 2005–2009

Coinfection of hepatitis B virus (HBV) or hepatitis C virus (HCV) may compromise pediatric antiretroviral therapy (ART) in China. In this study, we evaluated the seroprevalence of HBV and HCV in children receiving ART and associated factors

A deep learning-based approach for automated yellow rust disease detection from high resolution hyperspectral UAV images

Yellow rust in winter wheat is a widespread and serious fungal disease, resulting in significant yield losses globally. Effective monitoring and accurate detection of yellow rust are crucial to ensure stable and reliable wheat production and food security. The existing standard methods often rely on manual inspection of disease symptoms in a small crop area by agronomists or trained surveyors. This is costly, time consuming and prone to error due to the subjectivity of surveyors. Recent advances in Unmanned Aerial Vehicles (UAVs) mounted with hyperspectral image sensors have the potential to address these issues with low cost and high efficiency. This work proposed a new deep convolutional neural network (DCNN) based approach for automated crop disease detection using very high spatial resolution hyperspectral images captured with UAVs. The proposed model introduced multiple Inception-Resnet layers for feature extraction and was optimized to establish the most suitable depth and width of the network. Benefiting from the ability of convolution layers to handle three-dimensional data, the model used both spatial and spectral information for yellow rust detection. The model was calibrated with hyperspectral imagery collected by UAVs in five different dates across a whole crop cycle over a well-controlled field experiment with healthy and rust infected wheat plots. Its performance was compared across sampling dates and with random forest, a representative of traditional classification methods in which only spectral information was used. It was found that the method has high performance across all the growing cycle, particularly at late stages of the disease spread. The overall accuracy of the proposed model (0.85) was higher than that of the random forest classifier (0.77). These results showed that combining both spectral and spatial information is a suitable approach to improving the accuracy of crop disease detection with high resolution UAV hyperspectral images

Beyond Pasteur’s Quadrant Model: A New Dynamic Model of Basic Research and its Implementation

Basic research inspired by national interest is critical for the promotion of China’s innovation capacity and global competitiveness in science and technology; it is also a major driving force for disruptive technologies. Therefore, the concept and development law of basic research inspired by national interest should be well studied to guide the development of basic research. In this study, we review the connotation and application of the linear model of innovation proposed by Vannevar Bush and the Pasteur’s quadrant model proposed by Donald Stokes. Based on these models, we introduce basicness and useness dimensions along with a time dimension and develop a new three-dimensional dynamic model of basic research. The development of intense lasers fits this new model well and clearly demonstrates the spiral upward interactions among basic research, applied research, and technology development inspired by national interest. On the basis of this new model of basic research development, we emphasize the importance of falsifiability and research integrity, and the decisive role of basic research on the key technologies. Besides, the subjective misguidance of researches inspired by national interest should be avoided

Study on the Strength Performance of Recycled Aggregate Concrete with Different Ages under Direct Shearing

In order to study the mechanical properties of recycled aggregate concrete (RAC) at different ages, 264 standard cubes were designed to test its direct shear strength and cube compressive strength while considering the parameters of age and recycled aggregate replacement ratio. The failure pattern and load–displacement curve of specimens at direct shearing were obtained; the direct shear strength and residual shear strength were extracted from the load–displacement curves. Experimental results indicate that the influence of the replacement ratio for the front and side cracks of RAC is insignificant, with the former being straight and the latter relatively convoluted. At the age of three days, the damaged interface between aggregate and mortar is almost completely responsible for concrete failure; in addition to the damage of coarse aggregates, aggregate failure is also an important factor in concrete failure at other ages. The load–displacement curve of RAC at direct shearing can be divided into elasticity, elastoplasticity, plasticity, and stabilization stages. The brittleness of concrete decreases with its age, which is reflected in the gradual shortening of the elastoplastic stage. At 28 days of age, the peak direct shear force increases with the replacement ratio, while the trend is opposite at ages of 3 days, 7 days, and 14 days, respectively. The residual strength of RAC decreases inversely to the replacement ratio, with the rate of decline growing over time. A two-parameter RAC direct shear strength calculation formula was established based on the analysis of age and replacement rate to peak shear force of RAC. The relationship between cube compressive strength and direct shear strength of recycled concrete at various ages was investigated

Impact of Diets on Response to Immune Checkpoint Inhibitors (ICIs) Therapy against Tumors

Immunotherapy has revolutionized the established therapeutics against tumors. As the major immunotherapy approach, immune checkpoint inhibitors (ICIs) achieved remarkable success in the treatment of malignancies. However, the clinical gains are far from universal and durable, because of the primary and secondary resistance of tumors to the therapy, or side effects induced by ICIs. There is an urgent need to find safe combinatorial strategies that enhance the response of ICIs for tumor treatment. Diets have an excellent safety profile and have been shown to play pleiotropic roles in tumor prevention, growth, invasion, and metastasis. Accumulating evidence suggests that dietary regimens bolster not only the tolerability but also the efficacy of tumor immunotherapy. In this review, we discussed the mechanisms by which tumor cells evade immune surveillance, focusing on describing the intrinsic and extrinsic mechanisms of resistance to ICIs. We also summarized the impacts of different diets and/or nutrients on the response to ICIs therapy. Combinatory treatments of ICIs therapy with optimized diet regimens own great potential to enhance the efficacy and durable response of ICIs against tumors, which should be routinely considered in clinical settings

Modeling the Potential Distribution of Three Taxa of <i>Akebia</i> Decne. under Climate Change Scenarios in China

Akebia trifoliata (Thunb.) Koidz., Akebia trifoliata subsp. australis (Diels) T. Shimizu and Akebia quinata (Houtt.) Decne. are the source plants of the traditional Chinese medicines AKEBIAE CAULIS and AKEBIAE FRUCTUS, and have high pharmaceutical value. However, the resource reserve of these plants has dramatically declined due to habitat destruction, which has seriously affected their adequate supply and sustainable utilization. A poor knowledge of the potential distribution of these medicinal materials would seriously constrain the protective exploitation of wild resources and the establishment of new cultivations. In this study, based on the scenarios of SSP1-2.6, SSP2-4.5, SSP3-7.0 and SSP5-8.5, the maximum entropy model was used to predict the potential distribution of these three Akebia taxa under current and future (2030s, 2050s, 2070s and 2090s) climate conditions. Our findings showed that the potentially suitable areas of these three Akebia taxa were mainly distributed in China at 101.8–121.9° E and 23.5–34.6° N. Temperature played a more significant role than precipitation in affecting the distribution. The dominant bioclimatic variable that affected the distribution of A. trifoliata and A. quinata in China was the minimum temperature of the coldest month (BIO06). For A. trifoliata subsp. australis, the mean diurnal range (BIO02) was the dominant variable influencing its distribution. Compared with current conditions, the moderate- and high-suitability areas of these three Akebia taxa were predicted to shrink towards the core areas, while the low-suitability areas were all observed to increase from the 2030s to the 2090s. With the increase in radiative forcing of SSP, the low-impact areas of these three Akebia taxa showed a decreasing trend as a whole. Our results illustrate the impact of climate change on the distribution of Akebia, and would provide references for the sustainable utilization of Akebia’s resources

The Spatial and Temporal Distribution Patterns of XCH₄ in China: New Observations from TROPOMI

Methane is the second most important greenhouse gas after carbon dioxide. The intensity and distribution of methane source/sink in China are unknown. We collected the column-averaged dry air mixing ratio of CH4 (abbreviated as XCH4 hereafter) from TROPOMI for the period from 2018 to 2021, to study spatial distribution and temporal change of atmospheric CH4 concentration, providing clues and foundations for understanding the source/sink in China. It was found that the distribution of XCH4 is roughly high in the East, low in the West, high in the South and low in the North. Additionally, an evidently positive linear relationship between XCH4 and population density was witnessed, suggesting anthropogenic emissions may account for a large portion of total methane emissions. XCH4 exhibits evident seasonal characteristics, with the peak in summer and trough in winter, regardless of the different regions. Moreover, we used XCH4 anomalies to identify the emission sources and found its great potential in the detection of methane emission from mining plants, landfill, rice fields and even geological fracture zones

Platinum decorated hierarchical porous structures composed of ultrathin titanium nitride nanoflakes for efficient methanol oxidation reaction

Alloying Pt electrocatalysts with the second transition metal (e. g., Fe, Co, Ni and Cu) is an effective strategy to boost the methanol oxidation reaction (MOR) and simultaneously reduce the catalyst cost for the direct methanol fuel cells. However, the durability issues caused by the leaching of the transition metals for prolonged time and carbon corrosion hinder the practical applications of the Pt alloys. Herein, for the first time, a facile and robust strategy is developed to synthesize titanium nitride and copper doped titanium nitride with porous and hierarchical tubular structures (labeled as TiN NFs and Ti0.9Cu0.1N NFs, respectively). When used as the Pt support, both of Pt/TiN NFs and Pt/Ti0.9Cu0.1N NFs exhibit much enhanced activity and durability compared with the commercial Pt/C catalyst. The experimental data confirms that the leaching of the transition metal can be significantly impeded by this strategy while their advantageous properties that favors MOR activity for the Pt based catalysts are maintained. This work opens a new path for maximizing the MOR activity and stability by introducing porous binary transition metal nitride as the Pt support, which integrates the advantages of high stability, co-catalysis and doping effects. (c) 2018 Elsevier Ltd. All rights reserved