This paper presents a simple yet effective supervised deep hash approach that constructs binary hash codes from labeled data for large-scale image search. We assume that the semantic labels are ...governed by several latent attributes with each attribute on or off, and classification relies on these attributes. Based on this assumption, our approach, dubbed supervised semantics-preserving deep hashing (SSDH), constructs hash functions as a latent layer in a deep network and the binary codes are learned by minimizing an objective function defined over classification error and other desirable hash codes properties. With this design, SSDH has a nice characteristic that classification and retrieval are unified in a single learning model. Moreover, SSDH performs joint learning of image representations, hash codes, and classification in a point-wised manner, and thus is scalable to large-scale datasets. SSDH is simple and can be realized by a slight enhancement of an existing deep architecture for classification; yet it is effective and outperforms other hashing approaches on several benchmarks and large datasets. Compared with state-of-the-art approaches, SSDH achieves higher retrieval accuracy, while the classification performance is not sacrificed.
Polarimetric synthetic aperture radar (PolSAR) image classification is an important application. Advanced deep learning techniques represented by deep convolutional neural network (CNN) have been ...utilized to enhance the classification performance. One current challenge is how to adapt deep CNN classifier for PolSAR classification with limited training samples, while keeping good generalization performance. This letter attempts to contribute to this problem. The core idea is to incorporate expert knowledge of target scattering mechanism interpretation and polarimetric feature mining to assist deep CNN classifier training and improve the final classification performance. A polarimetric-feature-driven deep CNN classification scheme is established. Both classical roll-invariant polarimetric features and hidden polarimetric features in the rotation domain are used to drive the proposed deep CNN model. Comparison studies validate the efficiency and superiority of the proposal. For the benchmark AIRSAR data, the proposed method achieves the state-of-the-art classification accuracy. Meanwhile, the convergence speed from the proposed polarimetric-feature-driven CNN approach is about 2.3 times faster than the normal CNN method. For multitemporal UAVSAR data sets, the proposed scheme achieves comparably high classification accuracy as the normal CNN method for train-used temporal data, while for train-not-used data it obtains an average of 4.86% higher overall accuracy than the normal CNN method. Furthermore, the proposed strategy can also produce very promising classification accuracy even with very limited training samples.
Reduction of the 17,18‐double bond in the D‐ring during chlorophyll biosynthesis is catalyzed by the rare, naturally occurring photoenzyme protochlorophyllide oxidoreductase (POR). A conserved ...tyrosine residue has been suggested to donate a proton to C18 of the substrate in the past decades. Taylor and colleagues scrutinized the model with a powerful tool that utilized a modified genetic code to introduce fluorinated tyrosine analogues into POR. The presented results show that the suggested catalytically critical tyrosine is unlikely to participate in the reaction chemistry but is required for substrate binding, and instead, a cysteine residue preceding the lid helix is proposed to have the role of proton donor.
Reduction of the 17,18‐double bond in the D‐ring during chlorophyll biosynthesis is catalyzed by the rare, naturally occurring photoenzyme protochlorophyllide oxidoreductase. Previously, a conserved tyrosine residue had been suggested to donate a proton to C18 of the substrate. Aoife Taylor and colleagues show that the suggested tyrosine is unlikely to participate in the reaction chemistry but is required for substrate binding, and instead, a cysteine residue preceding the lid helix is proposed to be the proton donor.
Single-cell RNA sequencing can reveal the transcriptional state of cells, yet provides little insight into the upstream regulatory landscape associated with open or accessible chromatin regions. ...Joint profiling of accessible chromatin and RNA within the same cells would permit direct matching of transcriptional regulation to its outputs. Here, we describe droplet-based single-nucleus chromatin accessibility and mRNA expression sequencing (SNARE-seq), a method that can link a cell's transcriptome with its accessible chromatin for sequencing at scale. Specifically, accessible sites are captured by Tn5 transposase in permeabilized nuclei to permit, within many droplets in parallel, DNA barcode tagging together with the mRNA molecules from the same cells. To demonstrate the utility of SNARE-seq, we generated joint profiles of 5,081 and 10,309 cells from neonatal and adult mouse cerebral cortices, respectively. We reconstructed the transcriptome and epigenetic landscapes of major and rare cell types, uncovered lineage-specific accessible sites, especially for low-abundance cells, and connected the dynamics of promoter accessibility with transcription level during neurogenesis.
Phosphorus (P) is an essential macronutrient for plant growth, development and production. However, little is known about the effects of P deficiency on nutrient absorption, photosynthetic apparatus ...performance and antioxidant metabolism in citrus. Seedlings of 'sour pummelo' (Citrus grandis) were irrigated with a nutrient solution containing 0.2 mM (Control) or 0 mM (P deficiency) KH2PO4 until saturated every other day for 16 weeks. P deficiency significantly decreased the dry weight (DW) of leaves and stems, and increased the root/shoot ratio in C. grandis but did not affect the DW of roots. The decreased DW of leaves and stems might be induced by the decreased chlorophyll (Chl) contents and CO2 assimilation in P deficient seedlings. P deficiency heterogeneously affected the nutrient contents of leaves, stems and roots. The analysis of Chl a fluorescence transients showed that P deficiency impaired electron transport from the donor side of photosystem II (PSII) to the end acceptor side of PSI, which showed a greater impact on the performance of the donor side of PSII than that of the acceptor side of PSII and photosystem I (PSI). P deficiency increased the contents of ascorbate (ASC), H2O2 and malondialdehyde (MDA) as well as the activities of superoxide dismutase (SOD), catalase (CAT), ascorbate peroxidase (APX), dehydroascorbate reductase (DHAR) and glutathione reductase (GR) in leaves. In contrast, P deficiency increased the ASC content, reduced the glutathione (GSH) content and the activities of SOD, CAT, APX and monodehydroascorbate reductase (MDHAR), but did not increase H2O2 production, anthocyanins and MDA content in roots. Taking these results together, we conclude that P deficiency affects nutrient absorption and lowers photosynthetic performance, leading to ROS production, which might be a crucial cause of the inhibited growth of C. grandis.
Tin‐based compounds have received much attention as anode materials for lithium/sodium ion batteries owing to their high theoretical capacity. However, the huge volume change usually leads to the ...pulverization of electrode, giving rise to a poor cycle performance, which have severely hampered their practical application. Herein, highly durable yolk–shell SnSe2 nanospheres (SnSe2@SeC) are prepared by a multistep templating method, with an in situ gas‐phase selenization of the SnO2@C hollow nanospheres. During this process, Se can be doped into the carbon shell with a tunable amount and form SeC bonds. Density functional theory calculation results reveal that the SeC bonding can enhance the charge transfer properties as well as the binding interaction between the SnSe2 core and the carbon shell, favoring an improved rate performance and a superior cyclability. As expected, the sample delivers reversible capacities of 441 and 406 mAh g−1 after 2000 cycles at 2 and 5 A g−1, respectively, as the anode material for a sodium‐ion battery. Such performances are significantly better than the control sample without the SeC bonding and also other metal selenide‐based anodes, evidently showing the advantage of Se doping in the carbon shell.
Yolk–shell SnSe2@C nanospheres with SeC bonds in the carbon shell are synthesized by selenization of the SnO2@C precursor. Density functional theory calculation results reveal that the SeC bonding can enhance the charge transfer properties and the binding energy between the SnSe2 core and the carbon shell, leading to greatly improved high‐rate performance and cycling stability for a sodium‐ion battery.
Fleshy fruit texture is a critically important quality characteristic of ripe fruit. Softening is an irreversible process which operates in most fleshy fruits during ripening which, together with ...changes in color and taste, contributes to improvements in mouthfeel and general attractiveness. Softening results mainly from the expression of genes encoding enzymes responsible for cell wall modifications but starch degradation and high levels of flavonoids can also contribute to texture change. Some fleshy fruit undergo lignification during development and post‐harvest, which negatively affects eating quality. Excessive softening can also lead to physical damage and infection, particularly during transport and storage which causes severe supply chain losses. Many transcription factors (TFs) that regulate fruit texture by controlling the expression of genes involved in cell wall and starch metabolism have been characterized. Some TFs directly regulate cell wall targets, while others act as part of a broader regulatory program governing several aspects of the ripening process. In this review, we focus on advances in our understanding of the transcriptional regulatory mechanisms governing fruit textural change during fruit development, ripening and post‐harvest. Potential targets for breeding and future research directions for the control of texture and quality improvement are discussed.
This review focuses on advances in our understanding of the transcriptional regulatory mechanisms governing changes in fruit texture (e.g. softening and lignification) during fruit development, ripening, and postharvest. Potential targets for breeding and future research directions for the control of texture and quality improvement are discussed.
In this paper, we propose and numerically solve a model considering confined flow in fractured porous media coupled with free flow in conduits. Such a situation arises, for example, for fluid flows ...in fractured vuggy carbonate reservoirs and caves/conduits, where a matrix and fractures are the main spaces for fluid storage and flow. The flow in caves and conduits is governed by the Stokes equation; the flow in fractured porous media, which consists of both a matrix and fractures, is described by a coupled Darcy–Darcy (bulk–fracture) model. Then, the two models are coupled through suitable (physically consistent) interface conditions on the interface between fractured porous media and caves/conduits, playing a key role in a physically faithful simulation that achieves high accuracy. The construction of all the interface conditions of the coupled model is based on the fundamental properties of the traditional bulk–fracture model and the well-known Stokes–Darcy model. The weak formulation is derived for the proposed model, and the well-posedness of the model is theoretically analyzed. We also propose a polyhedral discontinuous Galerkin finite element approximation for the Stokes flow in conduits and Darcy flow in the porous matrix, which is coupled with a conforming finite element scheme for the flow in the fracture. Optimal error estimates in a suitable energy norm are obtained. Two-dimensional numerical experiments are conducted to validate the proposed model and to demonstrate the features of both the model and the numerical method, such as the optimal convergence rate of the numerical solution; the detail flow characteristics around fractures, the matrix, and conduits; and the applicability to real-world problems.
The development of new electrode materials for lithium‐ion batteries (LIBs) has always been a focal area of materials science, as the current technology may not be able to meet the high energy ...demands for electronic devices with better performance. Among all the metal oxides, tin dioxide (SnO2) is regarded as a promising candidate to serve as the anode material for LIBs due to its high theoretical capacity. Here, a thorough survey is provided of the synthesis of SnO2‐based nanomaterials with various structures and chemical compositions, and their application as negative electrodes for LIBs. It covers SnO2 with different morphologies ranging from 1D nanorods/nanowires/nanotubes, to 2D nanosheets, to 3D hollow nanostructures. Nanocomposites consisting of SnO2 and different carbonaceous supports, e.g., amorphous carbon, carbon nanotubes, graphene, are also investigated. The use of Sn‐based nanomaterials as the anode material for LIBs will be briefly discussed as well. The aim of this review is to provide an in‐depth and rational understanding such that the electrochemical properties of SnO2‐based anodes can be effectively enhanced by making proper nanostructures with optimized chemical composition. By focusing on SnO2, the hope is that such concepts and strategies can be extended to other potential metal oxides, such as titanium dioxide or iron oxides, thus shedding some light on the future development of high‐performance metal‐oxide based negative electrodes for LIBs.
Tin dioxide (SnO2) is an attractive candidate as a high‐capacity anode material for lithium‐ion batteries. In this review, a comprehensive discussion is provided about the synthesis of both phase‐pure SnO2 and SnO2‐based nanocomposites with different nanostructures ranging from 1D nanorods, to 2D nanosheets, to 3D hollow structures, and their application in high‐performance lithium‐ion batteries is discussed.
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