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Article: An Assessment of the Suitability of Sentinel-2 Data for Identifying Burn Severity in Areas of Low Vegetation

Luo, Huifen / Wu, Junlin

Journal of the Indian Society of Remote Sensing. 2022 June, v. 50, no. 6

2022

Abstract: Forest fires result in a range of adverse Earth's eco-environment and economic impacts. It is crucial to timely and accurately assess the severity of a forest fire, because burn severity is the factor for post-fire vegetation recovery. On the 7th July ... ...

Abstract	Forest fires result in a range of adverse Earth's eco-environment and economic impacts. It is crucial to timely and accurately assess the severity of a forest fire, because burn severity is the factor for post-fire vegetation recovery. On the 7th July 2015, a forest fire occurred in western Spain, Comunidad Valenciana, near the villages of Montán and Caudiel. The fire mainly affected low vegetation types such as scrublands and herbs. This study intended to evaluate the use of Sentinel-2 data for identifying burn severity within areas covered by low vegetation, with the single band, spectral index, and differential spectral index Sentinel-2 data assessed. The results confirmed that the use of near-infrared and short-wave infrared ranges of Sentinel-2 data was suitable for identifying burned and unburned areas of low vegetation. The use of the normalized difference vegetation index performed best in distinguishing between areas of highly and moderately damaged vegetation, whereas the use of the normalized burn ratio (NBR) and NBR2 performed best for distinguishing between areas of completely destroyed and moderately damaged vegetation. These preliminary research results indicated that Sentinel-2 data are useful for forest fire monitoring in areas with low vegetation.
Keywords	burn severity ; forest fires ; forests ; normalized difference vegetation index ; shrublands ; Spain
Language	English
Dates of publication	2022-06
Size	p. 1135-1144.
Publishing place	Springer India
Document type	Article
ZDB-ID	2439566-3
ISSN	0974-3006 ; 0255-660X
ISSN (online)	0974-3006
ISSN	0255-660X
DOI	10.1007/s12524-022-01518-7
Database	NAL-Catalogue (AGRICOLA)

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Article: Effects of urban growth on the land surface temperature: a case study in Taiyuan, China

Luo, Huifen / Wu, Junlin

Environment, development and sustainability. 2021 July, v. 23, no. 7

2021

Abstract: In the present study, Landsat series remote sensing image are utilized to investigate the spatial and temporal changes of the urban heat island (UHI) in the Taiyuan city from 1990, 2004 and 2014. The main influencing factors of the UHI are analyzed in ... ...

Abstract	In the present study, Landsat series remote sensing image are utilized to investigate the spatial and temporal changes of the urban heat island (UHI) in the Taiyuan city from 1990, 2004 and 2014. The main influencing factors of the UHI are analyzed in this regard. The single window algorithm is adopted to invert the land surface temperature (LST) from the thermal infrared data and analyze the spatiotemporal pattern of the LST in the studied area. Then, the urban thermal field variance index (UTFVI), normalized difference vegetation index (NDVI) and biophysical composition index (BCI) are calculated in accordance with the LST. Moreover, the degree of impervious surface of the study area is divided according to the BCI value. By analyzing the correlation between the LST, NDVI and the BCI, the influences of two major factors, green space and impervious surface, on urban heat islands are discussed. It is found that the average surface temperature of the Taiyuan city has increased by 5.17 °C during the past 24 years from 1990 to 2014, while the impervious surface area has increased by 223.53 km², which is 1.179 times of that in 1990. There is a statistical correlation between the LST and the data of the NDVI and impervious surface, which shows that the reduction in green space and the increase in impervious surface in the city have a significant impact on the urban heat island effect. As the largest city in Shanxi province, there is an increasing demand in Taiyuan city for constructing lands during the urbanization process, which has led to a remarkable decrease in the green space and an increase in impervious surfaces. Therefore, the LST in Taiyuan city has been affected by the rapid urbanization. Furthermore, UTFVI indicates that the overall ecological environment of the Taiyuan city has deteriorated and the area of high temperature in the city has increased significantly. Results of the present study may provide a scientific basis for government departments to formulate urban planning and environmental protection policies. The present study may help the government to expand urban green spaces in the right places, control the expansion of the impervious surface of the city, alleviate the UHI effect and maintain the sustainable development of the Taiyuan city.
Keywords	Landsat ; algorithms ; case studies ; environment ; environmental protection ; green infrastructure ; heat island ; surface area ; surface temperature ; sustainable development ; urbanization ; variance ; China
Language	English
Dates of publication	2021-07
Size	p. 10787-10813.
Publishing place	Springer Netherlands
Document type	Article
ZDB-ID	1438730-x
ISSN	1387-585X
ISSN	1387-585X
DOI	10.1007/s10668-020-01087-0
Database	NAL-Catalogue (AGRICOLA)

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Article ; Online: A Smart DNA Hydrogel Enables Synergistic Immunotherapy and Photodynamic Therapy of Melanoma.

Yang, Sen / Wu, Junlin / Wang, Zhongyu / Cheng, Yu / Zhang, Rui / Yao, Chi / Yang, Dayong

Angewandte Chemie (International ed. in English)

2024 Volume 63, Issue 14, Page(s) e202319073

Abstract: Immunotherapy faces insufficient immune activation and limited immune effectiveness. Herein, we report a smart DNA hydrogel that enables the release of multivalent functional units at the tumor site to enhance the efficacy of immunotherapy. The smart DNA ...

Abstract	Immunotherapy faces insufficient immune activation and limited immune effectiveness. Herein, we report a smart DNA hydrogel that enables the release of multivalent functional units at the tumor site to enhance the efficacy of immunotherapy. The smart DNA hydrogel was assembled from two types of ultra-long DNA chains synthesized via rolling circle amplification. One DNA chain contained immune adjuvant CpG oligonucleotides and polyaptamers for loading natural killer cell-derived exosomes; the other chain contained multivalent G-quadruplex for loading photodynamic agents. DNA chains formed DNA hydrogel through base-pairing. HhaI restriction endonuclease sites were designed between functional units. Upon stimuli in the tumor sites, the hydrogel was effectively cleaved by the released HhaI and disassembled into functional units. Natural killer cell-derived exosomes played an anti-tumor role, and the CpG oligonucleotide activated antigen-presenting cells to enhance the immunotherapy. Besides the tumor-killing effect of photodynamic therapy, the generated cellular debris acted as an immune antigen to further enhance the immunotherapeutic effect. In a mouse melanoma orthotopic model, the smart DNA hydrogel as a localized therapeutic agent, achieved a remarkable tumor suppression rate of 91.2 %. The smart DNA hydrogel exhibited enhanced efficacy of synergistic immunotherapy and photodynamic therapy, expanding the application of DNA materials in biomedicine.
MeSH term(s)	Animals ; Mice ; Melanoma/drug therapy ; Hydrogels ; Photochemotherapy ; DNA ; Immunotherapy ; Disease Models, Animal ; Cell Line, Tumor
Chemical Substances	Hydrogels ; DNA (9007-49-2)
Language	English
Publishing date	2024-02-29
Publishing country	Germany
Document type	Journal Article
ZDB-ID	2011836-3
ISSN	1521-3773 ; 1433-7851
ISSN (online)	1521-3773
ISSN	1433-7851
DOI	10.1002/anie.202319073
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Book ; Online: Robust Deep Reinforcement Learning through Bootstrapped Opportunistic Curriculum

Wu, Junlin / Vorobeychik, Yevgeniy

2022

Abstract: Despite considerable advances in deep reinforcement learning, it has been shown to be highly vulnerable to adversarial perturbations to state observations. Recent efforts that have attempted to improve adversarial robustness of reinforcement learning can ...

Abstract	Despite considerable advances in deep reinforcement learning, it has been shown to be highly vulnerable to adversarial perturbations to state observations. Recent efforts that have attempted to improve adversarial robustness of reinforcement learning can nevertheless tolerate only very small perturbations, and remain fragile as perturbation size increases. We propose Bootstrapped Opportunistic Adversarial Curriculum Learning (BCL), a novel flexible adversarial curriculum learning framework for robust reinforcement learning. Our framework combines two ideas: conservatively bootstrapping each curriculum phase with highest quality solutions obtained from multiple runs of the previous phase, and opportunistically skipping forward in the curriculum. In our experiments we show that the proposed BCL framework enables dramatic improvements in robustness of learned policies to adversarial perturbations. The greatest improvement is for Pong, where our framework yields robustness to perturbations of up to 25/255; in contrast, the best existing approach can only tolerate adversarial noise up to 5/255. Our code is available at: https://github.com/jlwu002/BCL. Comment: ICML 2022
Keywords	Computer Science - Machine Learning
Subject code	006 ; 629
Publishing date	2022-06-20
Publishing country	us
Document type	Book ; Online
Database	BASE - Bielefeld Academic Search Engine (life sciences selection)

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Article ; Online: Efficacy of continuous positive airway pressure on TNF-α in obstructive sleep apnea patients: A meta-analysis.

Luo, Yong / Zhang, Fa-Rong / Wu, Jun-Lin / Jiang, Xi-Jiao

PloS one

2023 Volume 18, Issue 3, Page(s) e0282172

Abstract: Background: Tumor necrosis factor-α (TNF-α) is an important mediator of the immune response. At present, the improvement of TNF-α after continuous positive airway pressure (CPAP) treatment of obstructive sleep apnea-hypopnea syndrome (OSAHS) is still ... ...

Abstract	Background: Tumor necrosis factor-α (TNF-α) is an important mediator of the immune response. At present, the improvement of TNF-α after continuous positive airway pressure (CPAP) treatment of obstructive sleep apnea-hypopnea syndrome (OSAHS) is still controversial. Methods: We conducted a systematic review of the present evidence based on a meta-analysis to elucidate the effects of TNF-α on OSAHS after CPAP treatment. Results: To measure TNF-α, ten studies used enzyme-linked immunosorbent assay (ELISA), and one used radioimmunoassay. The forest plot outcome indicated that CPAP therapy would lower the TNF-α levels in OSAHS patients, with a weighted mean difference (WMD) of 1.08 (95% CI: 0.62-1.55; P < 0.001) based on the REM since there is highly significant heterogeneity (I2 = 90%) among the studies. Therefore, we used the subgroup and sensitivity analyses to investigate the source of heterogeneity. The findings of the sensitivity analysis revealed that the pooled WMD ranged from 0.91 (95% CI: 0.52-1.31; P < 0.001) to 1.18 (95% CI: 0.74-1.63; P < 0.001). The findings were not influenced by any single study. Notably, there was homogeneity in the Asia subgroup and publication year: 2019, implying that these subgroups could be the source of heterogeneity. Conclusion: Our meta-analysis recommends that CPAP therapy will decrease the TNF-α level in OSAHS patients, but more related research should be conducted.
MeSH term(s)	Humans ; Tumor Necrosis Factor-alpha ; Continuous Positive Airway Pressure ; Sleep Apnea, Obstructive/therapy ; Syndrome ; Enzyme-Linked Immunosorbent Assay
Chemical Substances	Tumor Necrosis Factor-alpha
Language	English
Publishing date	2023-03-23
Publishing country	United States
Document type	Systematic Review ; Meta-Analysis ; Journal Article
ZDB-ID	2267670-3
ISSN	1932-6203 ; 1932-6203
ISSN (online)	1932-6203
ISSN	1932-6203
DOI	10.1371/journal.pone.0282172
Database	MEDical Literature Analysis and Retrieval System OnLINE

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Article ; Online: Fructus mori polysaccharide alleviates diabetic symptoms by regulating intestinal microbiota and intestinal barrier against TLR4/NF-κB pathway.

Chen, Xiaoxia / Wu, Junlin / Fu, Xiong / Wang, Pingping / Chen, Chun

International journal of biological macromolecules

2023 Volume 249, Page(s) 126038

Abstract: Fructus mori polysaccharide (FMP) has a variety of biological activities. In this study, the results showed that FMP alleviated hyperglycemia, insulin resistance, hyperlipidemia, endotoxemia, and high metabolic inflammation levels in type 2 diabetic ( ... ...

Abstract	Fructus mori polysaccharide (FMP) has a variety of biological activities. In this study, the results showed that FMP alleviated hyperglycemia, insulin resistance, hyperlipidemia, endotoxemia, and high metabolic inflammation levels in type 2 diabetic (T2DM) mice. Next, it was found that the above beneficial effects of FMP on diabetic mice were significantly attenuated after antibiotics eliminated intestinal microbiota (IM) of mice. In addition, FMP suppressed intestinal inflammation and oxidative stress levels by inhibiting the activation of the TLR4/MyD88/NF-κB pathway, and indirectly upregulated the expression of the tight junction proteins Claudin-1, Occludin, and Zonula occlusionn-1 (ZO-1) to repair the intestinal barrier. Interestingly, the protective effect of FMP on the intestinal barrier was also attributed to its regulation of IM. The 16S rRNA and Spearman correlation analysis showed that FMP could repair the intestinal barrier to improve T2DM by remodeling specific IM, especially by significantly inhibiting 93.66 % of endotoxin-producing Shigella and promoting the proliferation of probiotic Allobaculum and Bifidobacterium by 16.31 % and 19.07 %, respectively. This study provided a theoretical support for the application of FMP as a novel probiotic in functional foods for diabetes.
MeSH term(s)	Mice ; Animals ; NF-kappa B/metabolism ; Toll-Like Receptor 4/metabolism ; Diabetes Mellitus, Experimental/drug therapy ; Gastrointestinal Microbiome ; RNA, Ribosomal, 16S ; Polysaccharides/pharmacology ; Polysaccharides/therapeutic use ; Inflammation ; Diabetes Mellitus, Type 2/drug therapy
Chemical Substances	NF-kappa B ; Toll-Like Receptor 4 ; RNA, Ribosomal, 16S ; Polysaccharides
Language	English
Publishing date	2023-07-27
Publishing country	Netherlands
Document type	Journal Article
ZDB-ID	282732-3
ISSN	1879-0003 ; 0141-8130
ISSN (online)	1879-0003
ISSN	0141-8130
DOI	10.1016/j.ijbiomac.2023.126038
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Book ; Online: Exact Verification of ReLU Neural Control Barrier Functions

Zhang, Hongchao / Wu, Junlin / Vorobeychik, Yevgeniy / Clark, Andrew

2023

Abstract: Control Barrier Functions (CBFs) are a popular approach for safe control of nonlinear systems. In CBF-based control, the desired safety properties of the system are mapped to nonnegativity of a CBF, and the control input is chosen to ensure that the CBF ... ...

Abstract	Control Barrier Functions (CBFs) are a popular approach for safe control of nonlinear systems. In CBF-based control, the desired safety properties of the system are mapped to nonnegativity of a CBF, and the control input is chosen to ensure that the CBF remains nonnegative for all time. Recently, machine learning methods that represent CBFs as neural networks (neural control barrier functions, or NCBFs) have shown great promise due to the universal representability of neural networks. However, verifying that a learned CBF guarantees safety remains a challenging research problem. This paper presents novel exact conditions and algorithms for verifying safety of feedforward NCBFs with ReLU activation functions. The key challenge in doing so is that, due to the piecewise linearity of the ReLU function, the NCBF will be nondifferentiable at certain points, thus invalidating traditional safety verification methods that assume a smooth barrier function. We resolve this issue by leveraging a generalization of Nagumo's theorem for proving invariance of sets with nonsmooth boundaries to derive necessary and sufficient conditions for safety. Based on this condition, we propose an algorithm for safety verification of NCBFs that first decomposes the NCBF into piecewise linear segments and then solves a nonlinear program to verify safety of each segment as well as the intersections of the linear segments. We mitigate the complexity by only considering the boundary of the safe region and by pruning the segments with Interval Bound Propagation (IBP) and linear relaxation. We evaluate our approach through numerical studies with comparison to state-of-the-art SMT-based methods. Our code is available at https://github.com/HongchaoZhang-HZ/exactverif-reluncbf-nips23.
Keywords	Computer Science - Machine Learning
Subject code	600
Publishing date	2023-10-13
Publishing country	us
Document type	Book ; Online
Database	BASE - Bielefeld Academic Search Engine (life sciences selection)

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Book ; Online: Neural Lyapunov Control for Discrete-Time Systems

Wu, Junlin / Clark, Andrew / Kantaros, Yiannis / Vorobeychik, Yevgeniy

2023

Abstract: While ensuring stability for linear systems is well understood, it remains a major challenge for nonlinear systems. A general approach in such cases is to compute a combination of a Lyapunov function and an associated control policy. However, finding ... ...

Abstract	While ensuring stability for linear systems is well understood, it remains a major challenge for nonlinear systems. A general approach in such cases is to compute a combination of a Lyapunov function and an associated control policy. However, finding Lyapunov functions for general nonlinear systems is a challenging task. To address this challenge, several methods have been proposed that represent Lyapunov functions using neural networks. However, such approaches either focus on continuous-time systems, or highly restricted classes of nonlinear dynamics. We propose the first approach for learning neural Lyapunov control in a broad class of discrete-time systems. Three key ingredients enable us to effectively learn provably stable control policies. The first is a novel mixed-integer linear programming approach for verifying the discrete-time Lyapunov stability conditions, leveraging the particular structure of these conditions. The second is a novel approach for computing verified sublevel sets. The third is a heuristic gradient-based method for quickly finding counterexamples to significantly speed up Lyapunov function learning. Our experiments on four standard benchmarks demonstrate that our approach significantly outperforms state-of-the-art baselines. For example, on the path tracking benchmark, we outperform recent neural Lyapunov control baselines by an order of magnitude in both running time and the size of the region of attraction, and on two of the four benchmarks (cartpole and PVTOL), ours is the first automated approach to return a provably stable controller. Our code is available at: https://github.com/jlwu002/nlc_discrete. Comment: NeurIPS 2023
Keywords	Computer Science - Machine Learning ; Electrical Engineering and Systems Science - Systems and Control
Subject code	515
Publishing date	2023-05-10
Publishing country	us
Document type	Book ; Online
Database	BASE - Bielefeld Academic Search Engine (life sciences selection)

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Article ; Online: Peer victimization and non-suicidal self-injury among high school students: the mediating role of social anxiety, mobile phone addiction, and sex differences.

Long, Qianmei / Huang, Bin / Tang, Yiyu / Wu, Junlin / Yu, Jia / Qiu, Junlin / Huang, Yanqing / Huang, Guoping

BMC psychiatry

2024 Volume 24, Issue 1, Page(s) 25

Abstract: Background: Peer victimization (PV) is one of the major causes of non-suicidal self-injury. Non-suicidal self-injury (NSSI), peer victimization, social anxiety, and mobile phone addiction are significantly related; however, the interaction mechanism and ...

Abstract	Background: Peer victimization (PV) is one of the major causes of non-suicidal self-injury. Non-suicidal self-injury (NSSI), peer victimization, social anxiety, and mobile phone addiction are significantly related; however, the interaction mechanism and effect of sex differences remain to be determined. Objective: Herein, we investigated the relationship between peer victimization and NSSI among Chinese high school students. We also explored the chain mediating roles of social anxiety and mobile phone addiction and the regulatory role of sex. The findings of this study provide insights for theoretical interventions based on internal mechanisms. Method: A self-reported survey of 14,666 high school students from Sichuan County was conducted using a peer victimization scale, NSSI scale, social anxiety scale, and mobile phone addiction scale. A self-administered questionnaire was used to capture sociodemographic information. Results: Peer victimization, social anxiety, and mobile phone addiction were positively correlated with NSSI. Peer victimization had significant direct predictive effects on NSSI (95% CI: 0.341, 0.385) and significant indirect predictive effects on NSSI through social anxiety (95% CI: 0.008, 0.019) or mobile phone addiction (95% CI: 0.036, 0.053). Peer victimization had significant indirect predictive effects on NSSI through social anxiety as well as mobile phone addiction (95% CI: 0.009, 0.014). The first stage (predicting the effect of peer victimization on NSSI) and the third stage (predicting the effect of mobile phone addiction on NSSI) were both moderated by sex. Conclusions: Peer victimization could directly predict NSSI and indirectly predict NSSI through social anxiety and mobile phone addiction. Thus, social anxiety and mobile phone addiction exhibited chain mediating effects between peer victimization and NSSI in high school students; moreover, sex might be involved in the regulation of the mediation process.
MeSH term(s)	Humans ; Male ; Female ; Sex Characteristics ; Self-Injurious Behavior ; Technology Addiction ; Students ; Crime Victims ; Anxiety
Language	English
Publishing date	2024-01-04
Publishing country	England
Document type	Journal Article ; Research Support, Non-U.S. Gov't
ZDB-ID	2050438-X
ISSN	1471-244X ; 1471-244X
ISSN (online)	1471-244X
ISSN	1471-244X
DOI	10.1186/s12888-024-05495-8
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Book ; Online: On the Exploitability of Reinforcement Learning with Human Feedback for Large Language Models

Wang, Jiongxiao / Wu, Junlin / Chen, Muhao / Vorobeychik, Yevgeniy / Xiao, Chaowei

2023

Abstract: Reinforcement Learning with Human Feedback (RLHF) is a methodology designed to align Large Language Models (LLMs) with human preferences, playing an important role in LLMs alignment. Despite its advantages, RLHF relies on human annotators to rank the ... ...

Abstract	Reinforcement Learning with Human Feedback (RLHF) is a methodology designed to align Large Language Models (LLMs) with human preferences, playing an important role in LLMs alignment. Despite its advantages, RLHF relies on human annotators to rank the text, which can introduce potential security vulnerabilities if any adversarial annotator (i.e., attackers) manipulates the ranking score by up-ranking any malicious text to steer the LLM adversarially. To assess the red-teaming of RLHF against human preference data poisoning, we propose RankPoison, a poisoning attack method on candidates' selection of preference rank flipping to reach certain malicious behaviors (e.g., generating longer sequences, which can increase the computational cost). With poisoned dataset generated by RankPoison, we can perform poisoning attacks on LLMs to generate longer tokens without hurting the original safety alignment performance. Moreover, applying RankPoison, we also successfully implement a backdoor attack where LLMs can generate longer answers under questions with the trigger word. Our findings highlight critical security challenges in RLHF, underscoring the necessity for more robust alignment methods for LLMs.
Keywords	Computer Science - Artificial Intelligence ; Computer Science - Computation and Language ; Computer Science - Cryptography and Security ; Computer Science - Human-Computer Interaction
Subject code	004
Publishing date	2023-11-16
Publishing country	us
Document type	Book ; Online
Database	BASE - Bielefeld Academic Search Engine (life sciences selection)

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