Hasil untuk "Environmental protection"

Mingqiao Mo, Yunlong Tan, Hao Zhang et al.

Large language models (LLMs) have achieved remarkable progress in code generation, yet their potential for software protection remains largely untapped. Reverse engineering continues to threaten software security, while traditional virtual machine protection (VMP) relies on rigid, rule-based transformations that are costly to design and vulnerable to automated analysis. In this work, we present the first protection-aware framework that learns robust representations of VMP-protected code. Our approach builds large-scale paired datasets of source code and normalized VM implementations, and introduces hierarchical dependency modeling at intra-, preceding-, and inter-instruction levels. We jointly optimize language modeling with functionality-aware and protection-aware contrastive objectives to capture both semantic equivalence and protection strength. To further assess resilience, we propose a protection effectiveness optimization task that quantifies and ranks different VM variants derived from the same source. Coupled with a two-stage continual pre-training and fine-tuning pipeline, our method enables models to generate, compare, and reason over protected code. Extensive experiments show that our framework significantly improves robustness across diverse protection levels, opening a new research direction for learning-based software defense. In this work, we present ShieldedCode, the first protection-aware framework that learns robust representations of VMP-protected code. Our method achieves 26.95% Pass@1 on L0 VM code generation compared to 22.58% for GPT-4o., and improves binary similarity detection Recall@1 by 10% over state of art methods like jTrans.

Daniel Straub, Wolfgang Betz, Mara Ruf et al.

Information value, a measure for decision sensitivity, can provide essential information in engineering and environmental assessments. It quantifies the potential for improved decision-making when reducing uncertainty in specific inputs. By contrast to other sensitivity measures, it admits not only a relative ranking of input factors but also an absolute interpretation through statements like ''Eliminating the uncertainty in factor $A$ has an expected value of $5000$ Euro''. In this paper, we present a comprehensive overview of the information value by presenting the theory and methods in view of their application to engineering and environmental assessments. We show how one should differentiate between aleatory and epistemic uncertainty in the analysis. Furthermore, we introduce the evaluation of the information value in applications where the decision is described by a continuous parameter. The paper concludes with two real-life applications of the information value to highlight its power in supporting decision-making in engineering and environmental applications.

Kaixin Shen, Ruijie Quan, Jiaxu Miao et al.

The rapid advancement of image editing techniques has raised concerns about their misuse for generating Not-Safe-for-Work (NSFW) content. This necessitates a targeted protection mechanism that blocks malicious edits while preserving normal editability. However, existing protection methods fail to achieve this balance, as they indiscriminately disrupt all edits while still allowing some harmful content to be generated. To address this, we propose TarPro, a targeted protection framework that prevents malicious edits while maintaining benign modifications. TarPro achieves this through a semantic-aware constraint that only disrupts malicious content and a lightweight perturbation generator that produces a more stable, imperceptible, and robust perturbation for image protection. Extensive experiments demonstrate that TarPro surpasses existing methods, achieving a high protection efficacy while ensuring minimal impact on normal edits. Our results highlight TarPro as a practical solution for secure and controlled image editing.

Chao Zhang, Yulin Lu

Since the Industrial Revolution, the world economy has experienced rapid development, and China's economy has also achieved an unprecedented takeoff in the past. Behind the economic growth, population surge, and continuous improvement of people's living standards lies the enormous consumption of fossil energy and environmental pollution. This kind of pollution has caused irreparable damage to the world. The most concerned environmental issue globally at present is the global warming caused by carbon dioxide emissions. China is in a stage of rapid development, and as the largest developing country, China's development path has a significant impact on global climate change. At the same time, the global community also puts pressure on China to limit carbon dioxide emissions. To address energy shortages and environmental issues, countries around the world have introduced corresponding energy and environmental regulations. Due to different culture and government systems, the effects of energy and environmental regulations in various countries are also different. Therefore, it is still necessary to discuss China's energy and environmental regulations.This paper uses data from prefecture-level cities between 2003 and 2008 to discuss the impact of the "Eleventh Five-Year Plan" environmental regulations on urbanization rates. It first provides a theoretical analysis of the relationship between environmental regulation and urbanization, finding that environmental regulation can influence urban population mobility through both crowding-in and crowding-out effects.

Daniele Canavese, Leonardo Regano, Bjorn De Sutter et al.

This paper introduces a novel approach for the automated selection of software protections to mitigate MATE risks against critical assets within software applications. We formalize the key elements involved in protection decision-making - including code artifacts, assets, security requirements, attacks, and software protections - and frame the protection process through a game-theoretic model. In this model, a defender strategically applies protections to various code artifacts of a target application, anticipating repeated attack attempts by adversaries against the confidentiality and integrity of the application's assets. The selection of the optimal defense maximizes resistance to attacks while ensuring the application remains usable by constraining the overhead introduced by protections. The game is solved through a heuristic based on a mini-max depth-first exploration strategy, augmented with dynamic programming optimizations for improved efficiency. Central to our formulation is the introduction of the Software Protection Index, an original contribution that extends existing notions of potency and resilience by evaluating protection effectiveness against attack paths using software metrics and expert assessments. We validate our approach through a proof-of-concept implementation and expert evaluations, demonstrating that automated software protection is a practical and effective solution for risk mitigation in software.

I. M. Siruk

Purpose. To analyze the environmental problems of the Zdovbytsia United Territorial Community (Rivne region, Ukraine) and to propose practical solutions for their resolution in the context of sustainable development. Methods. Analytical approach, statistical, sociological, systematic analysis. Results. It was found that the most pressing environmental issues of the community include air pollution from vehicles and industrial enterprises, unauthorized landfills, insufficient modern waste disposal sites, deterioration of surface and groundwater quality, dust pollution from mineral extraction activities, and degradation of green spaces. A low level of environmental awareness among residents was identified, leading to weak support for environmental initiatives. Based on the analysis, the following solutions were proposed: implementation of separate collection and recycling systems for waste; establishment of official waste reception points; modernization of wastewater treatment facilities; enhancement of environmental monitoring of air and water resources; restoration of green zones; introduction of environmental education programs for students and adults; and encouragement of businesses to adopt environmentally friendly technologies. Conclusions. Effective resolution of the environmental problems in the Zdovbytsia community is possible through the combination of administrative, educational, and economic measures, as well as active cooperation between local authorities, the public, and the business sector. It is essential to ensure a systematic approach to environmental policy planning aimed at creating a safe, healthy, and comfortable living environment.

Octavio Aburto-Oropeza, Valentina Platzgummer, Erica M. Ferrer et al.

Mechanisms for marine ecological protection and recovery, including area-based conservation tools like ‘Marine Protected Areas’ (MPAs) are necessary tools to reach the Aichi Target or the forthcoming 30x30 target set by the Kunming-Montreal Biodiversity Framework. However, full ecosystem recovery takes years to manifest and the idea that MPA protection alone will foster human well-being is frequently contradicted by socio-economic evidence. Therefore, a new framework for marine area-based conservation and ecosystem restoration that reconciles the discrepancies between ecological recovery and socio-economic growth timelines is needed to effectively meet global biodiversity conservation targets. We introduce the concept of ‘Marine Prosperity Areas,’ (MPpA) an area-based conservation tool that prioritizes human prosperity as opposed to passively relying on ecosystem recovery to catalyze social change and economic growth. This concept leverages a suite of tried-and-true community-based intervention and investment strategies to strengthen and expand access to environmental science, social goods and services, and the financial perks of the blue economy. This data-driven framework may be of interest to stakeholders who support traditional area-based conservation models, but also to those who have been historically opposed to MPAs or have been excluded from past conservation processes.

Ying Li, Jing Jia, Runze Lu et al.

<h4>Background</h4>Qingdao, a historically high-risk area for hemorrhagic fever with renal syndrome (HFRS) in China, is undergoing agricultural mechanization and urbanization. However, the specific risk factors for HFRS in this context remain unclear. This study sought to determine the risk factors for HFRS in Qingdao.<h4>Methods</h4>Community-based, 1:2 case-control study. Each case was matched with two healthy neighborhood controls based on biological sex, age, and the same neighborhood or village. Univariate and multivariate conditional logistic regression analyses were performed. Furthermore, stratified analyses were performed to explore risk factor heterogeneity between the peak season for Hantaan virus (HTNV) type HFRS (October-January) and other months.<h4>Results</h4>93 cases (73.2%, 93/127) reported from January 2022 to September 2023 and 186 controls completed this questionnaire. Farmers accounted for the highest proportion (68.8%, 64/93). In multivariate logistic regression analysis, there were three significant risk factors for HFRS: piles of firewood and/or grain in residential yards (odds ratio [OR]=3.75, 95% CI: 2.14-6.55), mite and/or flea bites (OR=1.83, 95% CI: 1.06-3.18) and contacting with rats and/or their excreta (OR=1.73, 95% CI: 1.09-2.74); three variables represented significant protective factors for HFRS: frequency of sun exposure for quilts and bedding (OR=0.41, 95% CI: 0.19-0.90), rodent control measures at home (OR=0.50, 95% CI: 0.30-0.81) and knowing the main sources of HFRS transmission (OR=0.58, 95% CI: 0.36-0.90). Stratified analysis revealed that the influence of these factors varied by season, with rodent contact and control measures being particularly salient during the HTNV peak season.<h4>Conclusion</h4>This study provides the first comprehensive evidence of risk and protective factors for HFRS in Qingdao, highlighting the role of rodent control, promoting comprehensive health education, environmental management, and personal protection. However, the results should be interpreted considering the study's limitations, including a 73.2% response rate and the potential for recall bias.

Jingkao Tan, Na Li, Qulan Zhou et al.

Obtaining an accurate temperature distribution in furnaces for industrial combustion devices is critical. Acoustic pyrometry (AP) is a promising methodology for high-quality temperature field reconstruction, which is widely used in the monitoring of atmosphere, room, and furnace. However, due to the harsh working environment and the engineering limitations, the number of installed acoustic transducers is restricted, which in turn results in sparse valid data and an ill-posed AP problem. We used multiple means of improvement to improve the reconstruction performance of AP in a gradual and systematic manner. The fast finite-difference shooting method, the adaptive grid evolution strategy (AGES) and the radial basis function approximation with polynomial reproduction (RBFPR) were proposed and integrated into the sequential process optimization approach we concluded to systematically improve the reconstruction performance over the initial algorithm. In this approach, we optimized the parameters used for the reconstruction sequentially, analyzed the effectiveness of various means of improvement, finalized and validated an algorithm that takes into account universality and precision. Qualitative and quantitative analyses of the simulation and experimental results show the validity of the finalized algorithm and the sequential process optimization approach, demonstrating its significance for furnace temperature field measurement, combustion control, and environmental protection.

Wenkai LIU, Dan OUYANG, Yangli XU et al.

To investigate the effect of the combination of pectinase and neutral protease on the extraction rate of polysaccharides and the hypolipidemic activity of polysaccharide products from Sargassum fusiforme, the preparation of Sargassum fusiforme polysaccharides (SFP) was optimaized by response surface methodology. The polysaccharide products were separated and purified by a purification instrument, of which the physicochemical properties were analysed by scanning electron microscope, Fourier transform infrared spectroscopy and high performance liquid chromatography. Finally, the hypolipidemic ability of SFP was evaluated in vitro using bile acid salt binding capacity and pancreatic lipase activity inhibition assays as well as in vivo by constructing an in vivo zebrafish hyperlipidemia model, respectively. Results showed that the optimal conditions for SFP preparation with the combined enzymatic method were determined: 4:1 ratio of pectinase to neutral protease, pH5.5, temperature 50 ℃, enzyme addition rate of 2%, and a solvent-to-material ratio of 25:1. Four SFP fractions were obtained by isolation and purification, among which SFP-4 was identified to effectively bind bile salts (EC50=0.3524 mg/mL) and inhibit pancreatic lipase activity (IC50=0.3568 mg/mL), with the best lipid-lowering activity. Further investigation of the physicochemical properties of SFP-4 revealed that it was composed of seven monosaccharides, including fucose, galactose, and glucuronic acid, and was characterized by a pore structure and the structure of sulfate polysaccharides. At a concentration of 500 μg/mL, lipid accumulation was significantly reduced in zebrafish (P<0.01), with the expression of fatty acid synthesis-related genes (mttp, pparg, and fasn) downregulated, while lipolysis-related genes (pparab and acaca) were upregulated. A comparable lipid-lowering effect to simvastatin was observed. In conclusion, the combined enzyme method could effectively improve the yield of SFP, and the polysaccharide products were demonstrated to possess significant hypolipidemic activity. This study provides a theoretical support for the development and utilization of the hypolipidemic function of Sargassum fusiforme polysaccharides.

Yu Huang, Liang Guo, Wanqian Guo et al.

In the field of environmental science, it is crucial to have robust evaluation metrics for large language models to ensure their efficacy and accuracy. We propose EnviroExam, a comprehensive evaluation method designed to assess the knowledge of large language models in the field of environmental science. EnviroExam is based on the curricula of top international universities, covering undergraduate, master's, and doctoral courses, and includes 936 questions across 42 core courses. By conducting 0-shot and 5-shot tests on 31 open-source large language models, EnviroExam reveals the performance differences among these models in the domain of environmental science and provides detailed evaluation standards. The results show that 61.3% of the models passed the 5-shot tests, while 48.39% passed the 0-shot tests. By introducing the coefficient of variation as an indicator, we evaluate the performance of mainstream open-source large language models in environmental science from multiple perspectives, providing effective criteria for selecting and fine-tuning language models in this field. Future research will involve constructing more domain-specific test sets using specialized environmental science textbooks to further enhance the accuracy and specificity of the evaluation.

Guanlin Li, Shuai Yang, Jie Zhang et al.

With the development of generative models, the quality of generated content keeps increasing. Recently, open-source models have made it surprisingly easy to manipulate and edit photos and videos, with just a few simple prompts. While these cutting-edge technologies have gained popularity, they have also given rise to concerns regarding the privacy and portrait rights of individuals. Malicious users can exploit these tools for deceptive or illegal purposes. Although some previous works focus on protecting photos against generative models, we find there are still gaps between protecting videos and images in the aspects of efficiency and effectiveness. Therefore, we introduce our protection method, PRIME, to significantly reduce the time cost and improve the protection performance. Moreover, to evaluate our proposed protection method, we consider both objective metrics and human subjective metrics. Our evaluation results indicate that PRIME only costs 8.3% GPU hours of the cost of the previous state-of-the-art method and achieves better protection results on both human evaluation and objective metrics. Code can be found in https://github.com/GuanlinLee/prime.

Keivan Navaie

As 6G evolves into an AI-native technology, the integration of artificial intelligence (AI) and Generative AI into cellular communication systems presents unparalleled opportunities for enhancing connectivity, network optimization, and personalized services. However, these advancements also introduce significant data protection challenges, as AI models increasingly depend on vast amounts of personal data for training and decision-making. In this context, ensuring compliance with stringent data protection regulations, such as the General Data Protection Regulation (GDPR), becomes critical for the design and operational integrity of 6G networks. These regulations shape key system architecture aspects, including transparency, accountability, fairness, bias mitigation, and data security. This paper identifies and examines the primary data protection risks associated with AI-driven 6G networks, focusing on the complex data flows and processing activities throughout the 6G lifecycle. By exploring these risks, we provide a comprehensive analysis of the potential privacy implications and propose effective mitigation strategies. Our findings stress the necessity of embedding privacy-by-design and privacy-by-default principles in the development of 6G standards to ensure both regulatory compliance and the protection of individual rights.

Nivedita Singh, Yejin Do, Yongsang Yu. Imane Fouad et al.

Despite stringent data protection regulations such as the General Data Protection Regulation (GDPR), the California Consumer Privacy Act (CCPA), and other country-specific regulations, many websites continue to use cookies to track user activities. Recent studies have revealed several data protection violations, resulting in significant penalties, especially for multinational corporations. Motivated by the question of why these data protection violations continue to occur despite strong data protection regulations, we examined 360 popular e-commerce websites in multiple countries to analyze whether they comply with regulations to protect user privacy from a cookie perspective.

Xiaoxuan Bai, Peng Li, Weiqing Zhou et al.

High-temporal resolution and timely emission estimates are essential for developing refined air quality management policies. Considering the advantages of extensive coverage, high reliability, and near real-time capabilities, in this work, electric power big data (EPBD) was first employed to obtain accurate hourly resolved facility-level air pollutant emissions information from the cement industries in Tangshan City, China. Then, the simulation optimization was elucidated by coupling the data with the weather research and forecasting (WRF)-community multiscale air quality (CMAQ) model. Simulation results based on estimated emissions effectively captured the hourly variation, with the NMB within ±50% for NO₂ and PM_2.5 and R greater than 0.6 for SO₂. Hourly PM_2.5 emissions from clinker production enterprises exhibited a relatively smooth pattern, whereas those from separate cement grinding stations displayed a distinct diurnal variation. Despite the remaining underestimation and/or overestimation of the simulation concentration, the emission inventory based on EPBD demonstrates an enhancement in simulation results, with RMSE, NMB, and NME decreasing by 9.6%, 15.8%, and 11.2%, respectively. Thus, the exploitation of the vast application potential of EPBD in the field of environmental protection could help to support the precise prevention and control of air pollution, with the possibility of the early achievement of carbon peaking and carbon neutrality targets in China and other developing countries.

Sindhura Gupta, Susovan Mukhopadhyay, Ambarnath Banerji et al.

The popularity of low-voltage ac distribution networks is increasing day by day. However, an efficient protection scheme for low-voltage ac distribution systems is still challenging. This paper introduces a protection scheme suitable for low-voltage grid connected and islanded ac microgrid based on local measurements in order to locate, identify and isolate faults. Here current decomposition method is specifically incorporated to accomplish fault type identification. MATLAB/SIMULINK platform is chosen to examine the performance of the proposed scheme both in grid connected and islanded low-voltage ac microgrid. The feasibility of the protection scheme is extensively investigated by simulating all types of faults with substantial variations like different fault location, different fault resistances etc. The test results ensure that the proposed protection scheme is sufficiently reliable and faster for providing complete protection in low-voltage ac microgrid.

Loes van Bemmel, Zhuoran Liu, Nik Vaessen et al.

Recent research has proposed approaches that modify speech to defend against gender inference attacks. The goal of these protection algorithms is to control the availability of information about a speaker's gender, a privacy-sensitive attribute. Currently, the common practice for developing and testing gender protection algorithms is "neural-on-neural", i.e., perturbations are generated and tested with a neural network. In this paper, we propose to go beyond this practice to strengthen the study of gender protection. First, we demonstrate the importance of testing gender inference attacks that are based on speech features historically developed by speech scientists, alongside the conventionally used neural classifiers. Next, we argue that researchers should use speech features to gain insight into how protective modifications change the speech signal. Finally, we point out that gender-protection algorithms should be compared with novel "vocal adversaries", human-executed voice adaptations, in order to improve interpretability and enable before-the-mic protection.