Theory and Application of No-Till Reseeding Technology in Degraded Grasslands in China

Grasslands occupy nearly 400 million hectares in China, accounting for about 40.7% of the total land area, provide multiple ecological and economic benefits. However, due to over-grazing and over-cultivation, more than 90% grasslands in China are threatened by degradation that has caused significant negative impact on biodiversity and ecosystem functioning, such as biodiversity losses, decreased productivity, increased soil erosion etc. Thus, restoration of degraded grassland is urgent for sustainable grassland management in China. No-till reseeding has been found to be an effective way for grassland vegetation regeneration with improved productivity and increased plant diversity via reseeding suitable species with minimum disturbance for the soil. Here, we present a conceptual framework integrating plant-soil feedback theory and subclimax management model. We show that field experiments with reseeding legumes into the degraded grasslands can restore forage production and plant diversity in degraded grassland. We also applied the no-till reseeding technology in degraded grasslands in China, such as Shanxi, Gansu, Qinghai and found that reseeding leguminous and gramineous forages are effective in improving productivity and nutritional quality of degraded grassland in China. Overall, no-till reseeding is an effective way in restoring degraded grassland and could play an important role for sustainable grassland management in China

Cicatricial Alopecia

Cicatricial alopecia represents a group of disorders sharing a final pathway of destruction followed by replacement with fibrous tissue of the hair follicle unit. Cicatricial alopecia is classified into two categories, namely primary cicatricial alopecia, in which the hair follicle is the sole target of a progressive inflammatory process in a group of diverse skin or systemic diseases, and secondary cicatricial alopecia, referring to the hair follicle destruction as a result of a nonspecific disruption of the dermis. Permanent hair loss may also occur in the late phases of some nonscarring alopecias that are called “biphasic alopecias.” Based on the pathological characteristics, the lesions of primary cicatricial alopecia are divided into lymphocyte-predominant subgroup, neutrophil-predominant subgroup, or mixed subgroup. In principle, the primary goal of the treatment aims to attenuate the progression of the inflammatory and the scarring processes at the earliest phase of the disease. In clinical practice, the lymphocyte-predominant lesions are treated with immunosuppressive agents, whereas the neutrophil-predominant lesions are treated with antimicrobials or dapsone. As the efficacy of medication treatment against the cicatricial alopecia varies significantly, autologous hair transplantation is recommended to patients who have a relatively stable primary or a secondary cicatricial alopecia

Assessing environmental fate of β-HCH in Asian soil and association with environmental factors

Chinese Gridded Pesticide Emission and Residue Model was applied to simulate long-term environmental fate of beta-HCH in Asia spanning 1948-2009. The model captured well the spatiotemporal variation of beta-HCH soil concentrations across the model domain. beta-HCH use in different areas within the model domain was simulated respectively to assess the influence of the different sources of beta-HCH on its environment fate. A mass center of soil residue (MCSR) was introduced and used to explore environmental factors contributing to the spatiotemporal variation of beta-HCH soil residue. Results demonstrate that the primary emission dominates beta-HCH soil residues during the use of this pesticide. After phase-out of the pesticide in 1999, the change in beta-HCH soil residues has been associated with the Asian summer monsoon, featured by northward displacement of the MCSR. The displacement from several major sources in China and northeastern Asia shows a downward trend at a 95% confidence level, largely caused by environmental degradation and northward delivery of beta-HCH under cold condition in northern area. The MCSRs away from the India and southern and southeastern Asia sources show a rapid northward displacement at a 99% confidence level, featuring the cold trapping effect of the Tibetan Plateau.Chinese Gridded Pesticide Emission and Residue Model was applied to simulate long-term environmental fate of beta-HCH in Asia spanning 1948-2009. The model captured well the spatiotemporal variation of beta-HCH soil concentrations across the model domain. beta-HCH use in different areas within the model domain was simulated respectively to assess the influence of the different sources of beta-HCH on its environment fate. A mass center of soil residue (MCSR) was introduced and used to explore environmental factors contributing to the spatiotemporal variation of beta-HCH soil residue. Results demonstrate that the primary emission dominates beta-HCH soil residues during the use of this pesticide. After phase-out of the pesticide in 1999, the change in beta-HCH soil residues has been associated with the Asian summer monsoon, featured by northward displacement of the MCSR. The displacement from several major sources in China and northeastern Asia shows a downward trend at a 95% confidence level, largely caused by environmental degradation and northward delivery of beta-HCH under cold condition in northern area. The MCSRs away from the India and southern and southeastern Asia sources show a rapid northward displacement at a 99% confidence level, featuring the cold trapping effect of the Tibetan Plateau

MEA-Defender: A Robust Watermark against Model Extraction Attack

Recently, numerous highly-valuable Deep Neural Networks (DNNs) have been trained using deep learning algorithms. To protect the Intellectual Property (IP) of the original owners over such DNN models, backdoor-based watermarks have been extensively studied. However, most of such watermarks fail upon model extraction attack, which utilizes input samples to query the target model and obtains the corresponding outputs, thus training a substitute model using such input-output pairs. In this paper, we propose a novel watermark to protect IP of DNN models against model extraction, named MEA-Defender. In particular, we obtain the watermark by combining two samples from two source classes in the input domain and design a watermark loss function that makes the output domain of the watermark within that of the main task samples. Since both the input domain and the output domain of our watermark are indispensable parts of those of the main task samples, the watermark will be extracted into the stolen model along with the main task during model extraction. We conduct extensive experiments on four model extraction attacks, using five datasets and six models trained based on supervised learning and self-supervised learning algorithms. The experimental results demonstrate that MEA-Defender is highly robust against different model extraction attacks, and various watermark removal/detection approaches.Comment: To Appear in IEEE Symposium on Security and Privacy 2024 (IEEE S&P 2024), MAY 20-23, 2024, SAN FRANCISCO, CA, US

SSL-WM: A Black-Box Watermarking Approach for Encoders Pre-trained by Self-supervised Learning

Recent years have witnessed significant success in Self-Supervised Learning (SSL), which facilitates various downstream tasks. However, attackers may steal such SSL models and commercialize them for profit, making it crucial to protect their Intellectual Property (IP). Most existing IP protection solutions are designed for supervised learning models and cannot be used directly since they require that the models' downstream tasks and target labels be known and available during watermark embedding, which is not always possible in the domain of SSL. To address such a problem especially when downstream tasks are diverse and unknown during watermark embedding, we propose a novel black-box watermarking solution, named SSL-WM, for protecting the ownership of SSL models. SSL-WM maps watermarked inputs by the watermarked encoders into an invariant representation space, which causes any downstream classifiers to produce expected behavior, thus allowing the detection of embedded watermarks. We evaluate SSL-WM on numerous tasks, such as Computer Vision (CV) and Natural Language Processing (NLP), using different SSL models, including contrastive-based and generative-based. Experimental results demonstrate that SSL-WM can effectively verify the ownership of stolen SSL models in various downstream tasks. Furthermore, SSL-WM is robust against model fine-tuning and pruning attacks. Lastly, SSL-WM can also evade detection from evaluated watermark detection approaches, demonstrating its promising application in protecting the IP of SSL models

Multiattribute Decision Making Based on Entropy under Interval-Valued Intuitionistic Fuzzy Environment

Multiattribute decision making (MADM) is one of the central problems in artificial intelligence, specifically in management fields. In most cases, this problem arises from uncertainty both in the data derived from the decision maker and the actions performed in the environment. Fuzzy set and high-order fuzzy sets were proven to be effective approaches in solving decision-making problems with uncertainty. Therefore, in this paper, we investigate the MADM problem with completely unknown attribute weights in the framework of interval-valued intuitionistic fuzzy (IVIF) set (IVIFS). We first propose a new definition of IVIF entropy and some calculation methods for IVIF entropy. Furthermore, we propose an entropy-based decision-making method to solve IVIF MADM problems with completely unknown attribute weights. Particular emphasis is put on assessing the attribute weights based on IVIF entropy. Instead of the traditional methods, which use divergence among attributes or the probabilistic discrimination of attributes to obtain attribute weights, we utilize the IVIF entropy to assess the attribute weights based on the credibility of the decisionmaking matrix for solving the problem. Finally, a supplier selection example is given to demonstrate the feasibility and validity of the proposed MADM method

Sources and preservation of organic matter in soils of the wetlands in the Liaohe (Liao River) Delta, North China

Total organic carbon, total nitrogen, delta C-13(org), delta N-15, and aliphatic and polyaromatic hydrocarbons of fifty-five soil samples collected from the coastal wetlands of the Liaohe Delta were measured, in order to determine the sources and possible preservation of organic matter (OM). The delta(15)(N) and delta C-13(org) values in the samples ranged from 3.0 parts per thousand to 9.4 parts per thousand and from -30.4 parts per thousand to -20.3 parts per thousand, respectively, implying that the OM in the soils is predominantly derived from C-3 plant. The long-chain n-alkanes had a strong odd-over-even carbon number predominance, suggesting a significant contribution from waxes of higher plants. The ubiquitous presence of unresolved complex mixture, alkylated polycylic aromatic hydrocarbons and typical biomarkers of petroleum hydrocarbons (pristane, phytane, hopanes and steranes) indicates that there is a contribution of petroleum hydrocarbons to the organic carbon pool in the wetland soils. P. australis-vegetated wetlands have strong potentials for the preservation of organic carbon in the wetlands. (C) 2013 Elsevier Ltd. All rights reserved.Total organic carbon, total nitrogen, delta C-13(org), delta N-15, and aliphatic and polyaromatic hydrocarbons of fifty-five soil samples collected from the coastal wetlands of the Liaohe Delta were measured, in order to determine the sources and possible preservation of organic matter (OM). The delta(15)(N) and delta C-13(org) values in the samples ranged from 3.0 parts per thousand to 9.4 parts per thousand and from -30.4 parts per thousand to -20.3 parts per thousand, respectively, implying that the OM in the soils is predominantly derived from C-3 plant. The long-chain n-alkanes had a strong odd-over-even carbon number predominance, suggesting a significant contribution from waxes of higher plants. The ubiquitous presence of unresolved complex mixture, alkylated polycylic aromatic hydrocarbons and typical biomarkers of petroleum hydrocarbons (pristane, phytane, hopanes and steranes) indicates that there is a contribution of petroleum hydrocarbons to the organic carbon pool in the wetland soils. P. australis-vegetated wetlands have strong potentials for the preservation of organic carbon in the wetlands. (C) 2013 Elsevier Ltd. All rights reserved