A comprehensive quantification of global forest fragmentation is urgently required to guide forest protection, restoration and reforestation policies. Previous efforts focused on the static ...distribution patterns of forest remnants, potentially neglecting dynamic changes in forest landscapes. Here, we map global distribution of forest fragments and their temporal changes between 2000 and 2020. We find that forest landscapes in the tropics were relatively intact, yet these areas experienced the most severe fragmentation over the past two decades. In contrast, 75.1% of the world's forests experienced a decrease in fragmentation, and forest fragmentation in most fragmented temperate and subtropical regions, mainly in northern Eurasia and South China, declined between 2000 and 2020. We also identify eight modes of fragmentation that indicate different recovery or degradation states. Our findings underscore the need to curb deforestation and increase connectivity among forest fragments, especially in tropical areas.
Cross-camera label estimation from a set of unlabeled training data is an extremely important component in the unsupervised person re-identification (re-ID) systems. With the estimated labels, the ...existing advanced supervised learning methods can be leveraged to learn discriminative re-ID models. In this paper, we utilize the graph matching technique for accurate label estimation due to its advantages in optimal global matching and intra-camera relationship mining. However, the graph structure constructed with non-learned similarity measurement cannot handle the large cross-camera variations, which leads to noisy and inaccurate label outputs. This paper designs a dynamic graph matching (DGM) framework, which improves the label estimation process by iteratively refining the graph structure with better similarity measurement learned from the intermediate estimated labels. In addition, we design a positive re-weighting strategy to refine the intermediate labels, which enhances the robustness against inaccurate matching output and noisy initial training data. To fully utilize the abundant video information and reduce false matchings, a co-matching strategy is further incorporated into the framework. Comprehensive experiments conducted on three video benchmarks demonstrate that DGM outperforms the state-of-the-art unsupervised re-ID methods and yields the competitive performance to fully supervised upper bounds.
Stability analysis is an important research direction in evolutionary game theory. Evolutionarily stable states have a close relationship with Nash equilibria of repeated games, which are ...characterized by the folk theorem. When applying the folk theorem, one needs to compute the minimax profile of the game in order to find Nash equilibria. Computing the minimax profile is an NP-hard problem. In this paper, we investigate a new methodology to compute evolutionary stable states based on the level-k equilibrium, a new refinement of Nash equilibrium in repeated games. A level-k equilibrium is implemented by a group of players who adopt reactive strategies and who have no incentive to deviate from their strategies simultaneously. Computing the level-k equilibria is tractable because the minimax payoffs and strategies are not needed. As an application, this paper develops a tractable algorithm to compute the evolutionarily stable states and the Pareto front of n-player symmetric games. Three games, including the iterated prisoner's dilemma, are analyzed by means of the proposed methodology.
The SARS-CoV-2 Omicron variant exhibits striking immune evasion and is spreading rapidly worldwide. Understanding the structural basis of the high transmissibility and enhanced immune evasion of ...Omicron is of high importance. Here, using cryo-electron microscopy, we present both the closed and the open states of the Omicron spike (S) protein, which appear more compact than the counterparts of the G614 strain
, potentially related to enhanced inter-protomer and S1-S2 interactions induced by Omicron residue substitution. The closed state showing dominant population may indicate a conformational masking mechanism for the immune evasion of Omicron. Moreover, we captured three states for the Omicron S-ACE2 complex, revealing that the substitutions on the Omicron RBM result in new salt bridges and hydrogen bonds, more favourable electrostatic surface properties, and an overall strengthened S-ACE2 interaction, in line with the observed higher ACE2 affinity of Omicron S than of G614. Furthermore, we determined the structures of Omicron S in complex with the Fab of S3H3, an antibody that is able to cross-neutralize major variants of concern including Omicron, elucidating the structural basis for S3H3-mediated broad-spectrum neutralization. Our findings shed light on the receptor engagement and antibody neutralization or evasion of Omicron and may also inform the design of broadly effective vaccines against SARS-CoV-2.
To deal with a series of settlement problems such as the insufficient security for the user’s transaction, the complex process of settlement and the difficulty in data analysis within the sharing ...mode of the electric vehicles’ private piles, this paper proposed a new settlement mode for the shared private piles of electric vehicles. This mode took the shared charging network of the vehicle networking and the pile networking as the background, built a decentralized energy block chain, optimized the structure of the settlement mode by using distributed ledger technology, and used the intelligent contract algorithm to improve the settlement efficiency of charging orders. At the same time, this mode considered the transaction records and subsequent data analysis in its design, and used the evidence-storage and traceability technology to facilitate the integration of charging information data and to realize the configuration optimization of charging network.
Rosin is an abundantly available natural product. In this paper, for the first time, a rosin derivative is employed as the main monomer for preparation of epoxy vitrimers to improve the mechanical ...properties of vitrimers. Novel epoxy vitrimer networks with dynamic reversible covalent boronic ester bonds are constructed by a reaction between thiols in 2,2'-(1,4-phenylene)-bis (4-mercaptan-1,3,2-dioxaborolane) (BDB) as a curing agent and epoxy groups in the rosin derivative. The rosin-based epoxy vitrimer networks are fully characterized by Fourier transform infrared spectroscopy (FTIR), an equilibrium swelling experiment, and dynamic mechanical analysis (DMA). The obtained rosin-based epoxy vitrimers possess superior thermostability and good mechanical properties. Due to transesterification of boronic ester bonds, rosin epoxy vitrimer network topologies can be altered, giving welding, recycle, self-healing, and shape memory abilities to the fabricated polymer. Besides, the effects of treating time and temperature on welding capability is investigated, and it is found that the welding efficiency of the 20% C-FPAE sample is >93% after treatment for 12 h at 160 °C. Moreover, through a hot press, the pulverized samples of 20% C-FPAE can be reshaped several times and most mechanical properties are restored after reprocessing at 200 °C for 60 min. Finally, chemical degradation is researched for the rosin-based epoxy vitrimers.
This paper addresses a new person reidentification problem without label information of persons under nonoverlapping target cameras. Given the matched (positive) and unmatched (negative) image pairs ...from source domain cameras, as well as unmatched (negative) and unlabeled image pairs from target domain cameras, we propose an adaptive ranking support vector machines (AdaRSVMs) method for reidentification under target domain cameras without person labels. To overcome the problems introduced due to the absence of matched (positive) image pairs in the target domain, we relax the discriminative constraint to a necessary condition only relying on the positive mean in the target domain. To estimate the target positive mean, we make use of all the available data from source and target domains as well as constraints in person reidentification. Inspired by adaptive learning methods, a new discriminative model with high confidence in target positive mean and low confidence in target negative image pairs is developed by refining the distance model learnt from the source domain. Experimental results show that the proposed AdaRSVM outperforms existing supervised or unsupervised, learning or non-learning reidentification methods without using label information in target cameras. Moreover, our method achieves better reidentification performance than existing domain adaptation methods derived under equal conditional probability assumption.
•A modified meta-frontier non-radial directional distance function approach is used.•The technology heterogeneity among port enterprises is considered.•We measure the static CO2 emission performance ...(CEP) of ports during 2013 to 2018.•The dynamic changes in CEP and the underlying driving forces are also analysed.•The influencing factors of static and dynamic CEP are examined.
The rapid development of China’s port industry has led to serious CO2 emission problems. In this study, using the panel data of 16 port enterprises in China during 2013–2018, we first classified port enterprises into two groups based on the criterion of size and complexity. Then, we use a modified non-radial directional distance function in the meta-frontier framework to evaluate the port CEP and its dynamic changes as well as driving forces. The results show that the CEP of the whole is poor over the sample period on the basis of meta-frontier. Both groups performed well in CEP with respect to their specific group frontiers. Driving forces of the growth of CEP differ among port groups and individual port. Additionally, the effect of environmental regulation on CEP is positive, while the effect of openness on the growth of CEP is negative.
Abstract
Non-invasive assessment of the risk of lymph node metastasis (LNM) in patients with papillary thyroid carcinoma (PTC) is of great value for the treatment option selection. The purpose of ...this paper is to develop a transfer learning radiomics (TLR) model for preoperative prediction of LNM in PTC patients in a multicenter, cross-machine, multi-operator scenario. Here we report the TLR model produces a stable LNM prediction. In the experiments of cross-validation and independent testing of the main cohort according to diagnostic time, machine, and operator, the TLR achieves an average area under the curve (AUC) of 0.90. In the other two independent cohorts, TLR also achieves 0.93 AUC, and this performance is statistically better than the other three methods according to Delong test. Decision curve analysis also proves that the TLR model brings more benefit to PTC patients than other methods.
This letter proposes an augmented scheme of LT codes to improve the decoding success rate. The method involves substituting the 1‐s in full‐degree columns of the generator matrix of conventional LT ...codes with binary extension field elements and simultaneously increasing the ratio of full‐degree columns in the ideal soliton distribution. For non‐full‐degree columns, we retain the nonzero elements as 1‐s in the conventional LT codes generator matrix to preserve computational efficiency. Compared to conventional LT codes, the proposed method enhances the linear independence of the generator matrix, leading to a higher decoding success rate with minimal data packets. Experimental results demonstrate the effectiveness of the method at improving the performance of LT codes, with close to 100% decoding success rate achieved with around 5% data redundancy.
An augmented scheme of LT codes is proposed to improve the decoding success rate. The method involves substituting the 1 in full‐degree columns of the generator matrix of conventional LT codes with binary extension field elements and simultaneously increasing the ratio of full‐degree columns in the ideal soliton distribution, which allows for higher decoding success rates with a reduced amount of encoded data. Experimental results demonstrate the effectiveness of the method at improving the performance of LT codes, and this approach holds significant value in various applications of LT codes.
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