Re-measurement and influencing factors of agricultural eco-efficiency under the 'dual carbon' target in China.

Given that agriculture is both a carbon source and sink, the sustainability goals of carbon peaking and neutrality place high demands on the green and low-carbon agricultural development in China, and the exploration of a realistic path for a sustainable agricultural development is urgently needed. Under the above 'dual carbon' target, this study focused on the key issue of how to improve China's agricultural eco-efficiency (AEE) and constructed an innovative AEE indicator system that can reflect carbon constraint and coordinated agricultural economic development, resource use and ecological environment. The super-efficient slack-based measured Data Envelopment Analysis (SBM-DEA) method, which considers undesirable outputs, was applied to re-measure the AEE of 30 provinces and cities in China from 2001 to 2020, and its spatial and temporal evolution was analysed in conjunction with kernel density estimation. The Tobit regression model was used to explore various influencing factors by region. The results show that the AEE re-measurements, which take into account the 'dual carbon' requirement, are significantly better than the traditional AEE. From 2001 to 2020, China had an overall V-shaped fluctuation curve AEE, with a small decline and several inter-annual fluctuations, and exhibited a large potential to rise. China's AEE showed a spatially uneven regional development at different stages of distribution and evident multi-polar differentiation. Inter-provincial differences were observed in China's AEE, and the vicious circle of low-level green and low-carbon agricultural development was difficult to break. Urbanisation had a significant positive effect on national and eastern AEE but a significant negative effect on central AEE. The agricultural carbon offset rate had a significant effect on AEE nationally and in the three regions. Thus, the introduction of 'dual carbon' target effectively drove the development of AEE. Agricultural industry structure inhibited the improvement of AEE nationally and in the western region. Agricultural economic development hindered the national AEE improvement but promoted that of the central region, where China showed an environment Kuznets curve. Hopefully, this study can provide data support and theoretical reference for the green and low-carbon agricultural development and help achieve the 'dual carbon' target.

Proximity labeling reveals OTUD3 as a DNA-binding deubiquitinase of cGAS.

Cyclic GMP-AMP synthase (cGAS), as the major DNA sensor, initiates DNA-stimulated innate immune responses and is essential for a healthy immune system. Although some regulators of cGAS have been reported, it still remains largely unclear how cGAS is precisely and dynamically regulated and how many potential regulators govern cGAS. Here we carry out proximity labeling of cGAS with TurboID in cells and identify a number of potential cGAS-interacting or -adjacent proteins. Deubiquitinase OTUD3, one candidate identified in cytosolic cGAS-DNA complex, is further validated to not only stabilize cGAS but also enhance cGAS enzymatic activity, which eventually promotes anti-DNA virus immune response. We show that OTUD3 can directly bind DNA and is recruited to the cytosolic DNA complex, increasing its association with cGAS. Our findings reveal OTUD3 as a versatile cGAS regulator and find one more layer of regulatory mechanism in DNA-stimulated innate immune responses.

DeepMIH: Deep Invertible Network for Multiple Image Hiding.

Multiple image hiding aims to hide multiple secret images into a single cover image, and then recover all secret images perfectly. Such high-capacity hiding may easily lead to contour shadows or color distortion, which makes multiple image hiding a very challenging task. In this paper, we propose a novel multiple image hiding framework based on invertible neural network, namely DeepMIH. Specifically, we develop an invertible hiding neural network (IHNN) to innovatively model the image concealing and revealing as its forward and backward processes, making them fully coupled and reversible. The IHNN is highly flexible, which can be cascaded as many times as required to achieve the hiding of multiple images. To enhance the invisibility, we design an importance map (IM) module to guide the current image hiding based on the previous image hiding results. In addition, we find that the image hidden in the high-frequency sub-bands tends to achieve better hiding performance, and thus propose a low-frequency wavelet loss to constrain that no secret information is hidden in the low-frequency sub-bands. Experimental results show that our DeepMIH significantly outperforms other state-of-the-art methods, in terms of hiding invisibility, security and recovery accuracy on a variety of datasets.

Community assembly and co-occurrence network complexity of pelagic ciliates in response to environmental heterogeneity affected by sea ice melting in the Ross Sea, Antarctica.

In the Southern Ocean, the living environment of organisms has changed due to the dramatic increase in melting sea ice and the loss of glaciers, which have consequently caused substantial changes in biodiversity. Samples of pelagic ciliates from 13 sites were collected as bioindicators to demonstrate the relationship between spatial distribution patterns and environmental heterogeneity affected by sea ice melting and to reveal the community assembly mechanisms in the Ross Sea. Univariate analyses and multivariate analyses were effective tools demonstrating clear spatial patterns and providing a sufficient explanation to interpret strong correlations between pelagic ciliate communities and environmental variations, especially the distribution pattern of nutrients and Chl a. Moreover, environmental heterogeneity might affect the co-occurrence network complexity of ciliate communities. Furthermore, our results also indicated that stochastic processes play a significant role in the community assembly of pelagic ciliates. This study examined the controlling mechanisms of environmental heterogeneity affected by sea ice melting on pelagic ciliate communities and provided explanations for the community assembly of pelagic ciliates in polar marine ecosystems.

Vapor construction and modification of stem cell-laden multicomponent scaffolds for regenerative therapeutics.

Tissue engineering based on the combined use of isolated cells, scaffolds, and growth factors is widely used; however, the manufacture of cell-preloaded scaffolds faces challenges. Herein, we fabricated a multicomponent scaffold with multiple component accommodations, including bioactive molecules (BMs), such as fibroblast growth factor-2 (FGF-2) and l-ascorbic acid 2-phosphate (A2-P), and living cells of human adipose-derived stem cells (hASCs), within one scaffold construct. We report an innovative fabrication process based on vapor-phased construction using iced templates for vapor sublimation. Simultaneously, the vaporized water molecules were replaced by vapor deposition of poly-p-xylylene (PPX, USP Class VI, highly compatible polymer, FDA-approved records), forming a three-dimensional and porous scaffold matrix. More importantly, a multicomponent modification was achieved based on using nonvolatile solutes, including bioactive molecules of FGF-2 and A2-P, and living cells of hASCs, to prepare iced templates for sublimation. Additionally, the fabrication and construction resulted in a multicomponent scaffold product comprising the devised molecules, cells, and vapor-polymerized poly-p-xylylene as the scaffold matrix. The clean and dry fabrication process did not require catalysts, initiators or plasticizers, and potentially harmful solvents, and the scaffold products were produced in simple steps within hours of the processing time. Cell viability analysis showed a high survival rate (approximately 86.4%) for the accommodated hASCs in the fabricated scaffold product, and a surprising multilineage differentiation potential of hASCs was highly upregulated because of synergistic guidance by the same accommodated FGF-2 and A2-P components. Proliferation and self-renewal activities were also demonstrated with enhancement of the multicomponent scaffold product. Finally, in vivo calvarial defect studies further revealed that the constructed scaffolds provided blood vessels to grow into the bone defect areas with enhancement, and the induced conduction of osteoblast growth also promoted bone healing toward osseointegration. The reported scaffold construction technology represents a prospective tissue engineering scaffold product to enable accommodable and customizable versatility to control the distribution and composition of loading delicate BMs and living hASCs in one scaffold construct and demonstrates unlimited applications in tissue engineering repair and regenerative medicine applications.

Hierarchical Bayesian LSTM for Head Trajectory Prediction on Omnidirectional Images.

When viewing omnidirectional images (ODIs), viewers can access different viewports via head movement (HM), which sequentially forms head trajectories in spatial-temporal domain. Thus, head trajectories play a key role in modeling human attention on ODIs. In this paper, we establish a large-scale dataset collecting 21,600 head trajectories on 1,080 ODIs. By mining our dataset, we find two important factors influencing head trajectories, i.e., temporal dependency and subject-specific variance. Accordingly, we propose a novel approach integrating hierarchical Bayesian inference into long short-term memory (LSTM) network for head trajectory prediction on ODIs, which is called HiBayes-LSTM. In HiBayes-LSTM, we develop a mechanism of Future Intention Estimation (FIE), which captures the temporal correlations from previous, current and estimated future information, for predicting viewport transition. Additionally, a training scheme called Hierarchical Bayesian inference (HBI) is developed for modeling inter-subject uncertainty in HiBayes-LSTM. For HBI, we introduce a joint Gaussian distribution in a hierarchy, to approximate the posterior distribution over network weights. By sampling subject-specific weights from the approximated posterior distribution, our HiBayes-LSTM approach can yield diverse viewport transition among different subjects and obtain multiple head trajectories. Extensive experiments validate that our HiBayes-LSTM approach significantly outperforms 9 state-of-the-art approaches for trajectory prediction on ODIs, and then it is successfully applied to predict saliency on ODIs.

A photoaffinity labeling strategy identified EF1A1 as a binding protein of cyclic dinucleotide 2'3'-cGAMP.

2'3'-cyclic GMP-AMP (2'3'-cGAMP), generated by cyclic GMP-AMP synthase (cGAS) under activation by cytosolic DNA, has a vital role in innate immune response via its receptor protein stimulator of interferon genes (STING) to fight viral infections and tumors. In order to have a complete understanding of biological functions of 2'3'-cGAMP, it is important to find out whether 2'3'-cGAMP has other unrevealed binding proteins present in mammalian cells and executes unknown functions. Here we report the 2'3'-cGAMP-based photoaffinity probes that capture and isolate 2'3'-cGAMP-binding proteins. These probes enable the identification of some potential 2'3'-cGAMP-binding proteins from HeLa cells. EF1A1, an essential protein regulating protein synthesis, is further validated to associate with 2'3'-cGAMP in vitro and in cells to impede protein synthesis. Thus, our studies provide a powerful approach to enable identification of the 2'3'-cGAMP interactome, discover unknown functions of 2'3'-cGAMP, and understand its physiological/pathological roles in tumor immunity and immune-related diseases.

Vapor-phased fabrication and modulation of cell-laden scaffolding materials.

Bottom-up approaches using building blocks of modules to fabricate scaffolds for tissue engineering applications have enabled the fabrication of structurally complex and multifunctional materials allowing for physical and chemical flexibility to better mimic the native extracellular matrix. Here we report a vapor-phased fabrication process for constructing three-dimensional modulated scaffold materials via simple steps based on controlling mass transport of vapor sublimation and deposition. We demonstrate the fabrication of scaffolds comprised of multiple biomolecules and living cells with built-in boundaries separating the distinct compartments containing defined biological configurations and functions. We show that the fabricated scaffolds have mass production potential. We demonstrate overall >80% cell viability of encapsulated cells and that modulated scaffolds exhibit enhanced cell proliferation, osteogenesis, and neurogenesis, which can be assembled into various geometric configurations. We perform cell co-culture experiments to show independent osteogenesis and angiogenesis activities from separate compartments in one scaffold construct.

MFQE 2.0: A New Approach for Multi-Frame Quality Enhancement on Compressed Video.

The past few years have witnessed great success in applying deep learning to enhance the quality of compressed image/video. The existing approaches mainly focus on enhancing the quality of a single frame, not considering the similarity between consecutive frames. Since heavy fluctuation exists across compressed video frames as investigated in this paper, frame similarity can be utilized for quality enhancement of low-quality frames given their neighboring high-quality frames. This task is Multi-Frame Quality Enhancement (MFQE). Accordingly, this paper proposes an MFQE approach for compressed video, as the first attempt in this direction. In our approach, we first develop a Bidirectional Long Short-Term Memory (BiLSTM) based detector to locate Peak Quality Frames (PQFs) in compressed video. Then, a novel Multi-Frame Convolutional Neural Network (MF-CNN) is designed to enhance the quality of compressed video, in which the non-PQF and its nearest two PQFs are the input. In MF-CNN, motion between the non-PQF and PQFs is compensated by a motion compensation subnet. Subsequently, a quality enhancement subnet fuses the non-PQF and compensated PQFs, and then reduces the compression artifacts of the non-PQF. Also, PQF quality is enhanced in the same way. Finally, experiments validate the effectiveness and generalization ability of our MFQE approach in advancing the state-of-the-art quality enhancement of compressed video.

Synergistically Enhanced Wound Healing of a Vapor-Constructed Porous Scaffold.

In this study, a porous, three-dimensional material of parylene (poly-p-xylylene) incorporating keratin was fabricated. As an FDA-approved material, parylene is highly stable and biocompatible. Keratin is an abundant natural material that can enhance cell adhesion and wound healing. A unique vapor deposition construction technique dispersed keratin homogenously in the parylene system. Instead of using a conventional template, a sublimating template was applied. This composite porous scaffold was investigated mechanically and biologically. In addition, human adipose stem cells were cultured on the scaffold. The synergistic functions, including biocompatibility, permeability, cell adhesion, and stem cell differentiation, were investigated. A mouse excisional wound-healing model further verified that using the porous composite scaffold with stem cells accelerated the wound healing process, supporting its in vivo efficacy. The positive results demonstrated that this material has the potential to serve as a wound repair platform.

Parylene-Based Porous Scaffold with Functionalized Encapsulation of Platelet-Rich Plasma and Living Stem Cells for Tissue Engineering Applications.

A scaffold was fabricated to synergistically encapsulate living human adipose-derived stem cells (hASCs) and platelet-rich plasma (PRP) based on a vapor-phase sublimation and deposition process. During the process, ice templates were prepared using sterile water as the solvent and were used to accommodate the sensitive living cells and PRP molecules. Under controlled processing conditions, the ice templates underwent vapor sublimation to evaporate water molecules, while at the same time, vapor-phase deposition of poly-p-xylylene (Parylene, USP Class VI highly biocompatible) occurred to replace the templates, and the final construction yielded a scaffold with Parylene as the matrix, with simultaneously encapsulated living hASCs and PRP molecules. Evaluation of the fabricated synergistic scaffold for the proliferation activities toward the encapsulated hASCs indicated significant augmentation of cell proliferation contributed by the PRP ingredients. In addition, osteogenic activity in the early stage by alkaline phosphatase expression and later stage with calcium mineralization indicated significant enhancement toward osteogenetic differentiation of the encapsulated hASCs, which were guided by the PRP molecules. By contrast, examinations of adipogenic activity by lipid droplet formation revealed an inhibition of adipogenesis with decreased intracellular lipid accumulation, and a statistically significant downregulation of adipogenic differentiation was postulated for the scaffold products when compared to the osteogenetic results and the control experiments. The reported fabrication method featured a clean and simple process to construct scaffolds that combined delicate living hASCs and PRP molecules inside the structure. The resultant synergistic scaffold and the selected commercially available hASCs and PRP are emerging as tissue engineering tools that provide multifunctionality for tissue repair and regeneration.

A Deep Learning Approach for Multi-Frame In-Loop Filter of HEVC.

An extensive study on the in-loop filter has been proposed for a high efficiency video coding (HEVC) standard to reduce compression artifacts, thus improving coding efficiency. However, in the existing approaches, the in-loop filter is always applied to each single frame, without exploiting the content correlation among multiple frames. In this paper, we propose a multi-frame in-loop filter (MIF) for HEVC, which enhances the visual quality of each encoded frame by leveraging its adjacent frames. Specifically, we first construct a large-scale database containing encoded frames and their corresponding raw frames of a variety of content, which can be used to learn the in-loop filter in HEVC. Furthermore, we find that there usually exist a number of reference frames of higher quality and of similar content for an encoded frame. Accordingly, a reference frame selector (RFS) is designed to identify these frames. Then, a deep neural network for MIF (known as MIF-Net) is developed to enhance the quality of each encoded frame by utilizing the spatial information of this frame and the temporal information of its neighboring higher-quality frames. The MIF-Net is built on the recently developed DenseNet, benefiting from its improved generalization capacity and computational efficiency. In addition, a novel block-adaptive convolutional layer is designed and applied in the MIF-Net, for handling the artifacts influenced by coding tree unit (CTU) structure in HEVC. Extensive experiments show that our MIF approach achieves on average 11.621% saving of the Bjøntegaard delta bit-rate (BD-BR) on the standard test set, significantly outperforming the standard in-loop filter in HEVC and other state-of-the-art approaches.

Nucleophilic Substitution of gem-Difluoroalkenes with TMSNu Promoted by Catalytic Amounts of Cs2CO3.

The efficient and practical nucleophilic cyanation and trifluoromethylation with appropriate trimethylsilyl nucleophiles were developed. Catalytic amounts of cheap and nontoxic Cs2CO3 were used to maintain a sufficiently high concentration of nucleophilic anion (CN- or CF3-) which could begin the catalytic cycle. The present methodologies provide diverse functionalized monofluoroalkenes bearing a cyano and trifluoromethyl group with excellent to moderate stereoselectivities.

Characterization of Mechanical Stability and Immunological Compatibility for Functionalized Modification Interfaces.

Surface modification layers are performed on the surfaces of biomaterials and have exhibited promise for decoupling original surface properties from bulk materials and enabling customized and advanced functional properties. The physical stability and the biological compatibility of these modified layers are equally important to ensure minimized delamination, debris, leaching of molecules, and other problems that are related to the failure of the modification layers and thus can provide a long-term success for the uses of these modified layers. A proven surface modification tool of the functionalized poly-para-xylylene (PPX) system was used as an example, and in addition to the demonstration of their chemical conjugation capabilities and the functional properties that have been well-documented, in the present report, we additionally devised the characterization protocols to examine stability properties, including thermostability and adhesive strength, as well as the biocompatibility, including cell viability and the immunological responses, for the modified PPX layers. The results suggested a durable coating stability for PPXs and firmly attached biomolecules under these stability and compatibility tests. The durable and stable modification layers accompanied by the native properties of the PPXs showed high cell viability against fibroblast cells and macrophages (MΦs), and the resulting immunological activities created by the MΦs exhibited excellent compatibility with non-activated immunological responses and no indication of inflammation.

Clickable and Photo-Erasable Surface Functionalities by Using Vapor-Deposited Polymer Coatings.

A prospective design for interface properties is enabled to perform precise functionalization, erasure capability for existing properties, reactivation of surface functionality to a second divergent property. A vapor-deposited, 2-nitro-5-(prop-2-yn-1-yloxy)methylbenzyl carbamate-functionalized poly-para-xylylene coating is synthesized in this study to realize such tasks by offering the accessibility of the azide/alkyne click reaction, an integrated photochemical decomposition/cleavage moiety, and the reactivation sites of amines behind the cleavage that allow the installation of a second surface function. With the benefits from the mild processing conditions used for the coatings and the rapid response of the photochemical reaction, the creation of sophisticated interface properties and localized chemical compositions was elegantly demonstrated with a hybrid functionality including a confined hydrophlic/hydrophobic wetting property and/or a cell adherent/repellent platform on such a coating surface.

Defined cell adhesion for silicon-based implant materials by using vapor-deposited functional coatings.

The field of implantable electronics relies on using silicon materials due to the merits of a well-established fabrication process and favorable properties; of particular interest is the surface modification of such materials. In the present study, we introduce a surface modification technique based on coatings of functionalized Parylene on silicon substrates, where the modified layers provide a defined cell adhesion capability for the resultant silicon materials/devices. Functionalization of Parylene was achieved during a one-step chemical vapor deposition (CVD) polymerization process, forming NHS ester-functionalized Parylene, and subsequent RGD attachment was enabled via a conjugation reaction between the NHS ester and amine groups. The modification procedures additionally provided a clean and gentle approach to avoid thermal excursions, intense irradiation, chemicals, or solvents that might damage delicate structures or sensitive molecules on the devices. The modification layers exhibited excellent mechanical strength on the substrate, meeting the high standards of the American Society for Testing and Materials (ASTM), and the resultant cell adherence property was verified by a centrifugation assay and the analysis of attached cell morphologies; the results collectively demonstrated robust and sustainable modification layers of the NHS ester-functionalized Parylene and confirmed that the cell-adherence property imparted by using this facile modification technique was effective. The modification technology is expected to benefit the design of prospective interface properties for silicon-based devices and related industrial products.

Synthesis of ß-Alkyl 2-Hydroxychalcones by Rhodium-Catalyzed Coupling of N-Phenoxyacetamides and Nonterminal Propargyl Alcohols.

An efficient rhodium-catalyzed coupling of N-phenoxyacetamides and nonterminal propargyl alcohols has been developed. A series of ß-Alkyl 2-hydroxychalcones bearing diverse functional groups were obtained with excellent regio- and stereoselectivity, and the desired chalcones could then be converted to triazole and chromene smoothly.

Reducing Complexity of HEVC: A Deep Learning Approach.

High Efficiency Video Coding (HEVC) significantly reduces bit-rates over the preceding H.264 standard but at the expense of extremely high encoding complexity. In HEVC, the quad-tree partition of coding unit (CU) consumes a large proportion of the HEVC encoding complexity, due to the brute-force search for rate-distortion optimization (RDO). Therefore, this paper proposes a deep learning approach to predict the CU partition for reducing the HEVC complexity at both intra-and inter-modes, which is based on convolutional neural network (CNN) and long-and short-term memory (LSTM) network. First, we establish a large-scale database including substantial CU partition data for HEVC intra-and inter-modes. This enables deep learning on the CU partition. Second, we represent the CU partition of an entire coding tree unit (CTU) in the form of a hierarchical CU partition map (HCPM). Then, we propose an early-terminated hierarchical CNN (ETH-CNN) for learning to predict the HCPM. Consequently, the encoding complexity of intra-mode HEVC can be drastically reduced by replacing the brute-force search with ETH-CNN to decide the CU partition. Third, an early-terminated hierarchical LSTM (ETH-LSTM) is proposed to learn the temporal correlation of the CU partition. Then, we combine ETH-LSTM and ETH-CNN to predict the CU partition for reducing the HEVC complexity at inter-mode. Finally, experimental results show that our approach outperforms other state-of-the-art approaches in reducing the HEVC complexity at both intra-and inter-modes.

Vapor sublimation and deposition to build porous particles and composites.

The vapor deposition of polymers on regular stationary substrates is widely known to form uniform thin films. Here we report porous polymer particles with sizes controllable down to the nanometer scale can be produced using a fabrication process based on chemical vapor deposition (CVD) on a dynamic substrate, i.e., sublimating ice particles. The results indicate that the vapor deposition of a polymer is directed by the sublimation process; instead of forming a thin film polymer, the deposited polymers replicated the size and shape of the ice particle. Defined size and porosity of the polymer particles are controllable with respect to varying the processing time. Extendable applications are shown to install multiple functional sites on the particles in one step and to localize metals/oxides forming composite particles. In addition, one fabrication cycle requires approximately 60 min to complete, and potential scaling up the production of the porous particles is manageable.

Surface modification: activation and deactivation of osteogenic differentiation based on detachable growth factor protein.

An advanced material interface is modified by using a substrate-independent coating of detachable poly-para-xylylene, enabling dynamical control of the immobilization and detachment of biomolecules, and a previously installed biological function is deactivated or tuned with reduced activity. The induction of osteogenesis activity, and subsequent deactivation of such osteogenesis activity, is demonstrated.