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21 pages, 1996 KiB

Open AccessArticle

Evaluating V2X-Based Vehicle Control under Unreliable Network Conditions, Focusing on Safety Risk

by Roland Nagy, Árpád Török and Zsombor Pethő

Appl. Sci. 2024, 14(13), 5661; https://doi.org/10.3390/app14135661 (registering DOI) - 28 Jun 2024

Viewed by 89

Abstract

With the emergence of Vehicle-to-Everything (V2X) systems, it is important to investigate how deteriorating network parameters affect vehicle functionality based on wireless communication. It is important to determine how we can prevent the performance degradation of these functions and ensure safety on the roads. This paper examines the potential for enhancing the performance of a connected vehicle function by considering network parameters in the control algorithm. In order to achieve this, a safety indicator was incorporated into the control algorithm, which takes into account both vehicle dynamics and network parameters. Following an assessment of the proposed control method, it was determined that it is a suitable approach for enhancing the performance of the vehicle function. Full article

(This article belongs to the Special Issue Applications of Big Data in Public Transportation Systems)

26 pages, 4072 KiB

Open AccessArticle

On the Detection of Vulnerable Road Users—Simulating Limits of an FMCW Radar

by Fatih Yüksekkaya, Norman Franchi and Maximilian Lübke

Electronics 2024, 13(13), 2547; https://doi.org/10.3390/electronics13132547 (registering DOI) - 28 Jun 2024

Viewed by 90

Abstract

The complexity of urban traffic environments poses unique challenges for automotive radar sensors. Limited range and Doppler resolution hinder the ability to distinguish closely spaced objects and detect vulnerable road users, particularly pedestrians. Therefore, it is important to know the limits of FMCW radars. To assess these limitations, the WinProp channel simulator is used to model and simulate traffic scenarios regarding the detection of the range, velocity, and SNR of targets. To validate WinProp as a simulation tool for traffic scenarios, a real traffic scenario is configured and the simulation results compared to the measurement results in order to demonstrate the suitability of WinProp for simulating traffic scenarios and evaluating radar detection performance. The close agreement between the simulation and measurement results provides validation for WinProp’s accuracy in modeling detections and signal processing within traffic scenarios. To showcase the limitations of FMCW radars, two scenarios with challenging detection conditions are simulated: an occluded pedestrian between parked vehicles and a densely populated road. A monostatic setup with a single patch antenna and a 16 × 16 patch antenna array is evaluated, using chirp bandwidths of 1 GHz and 4 GHz. The simulations have shown that although it is feasible to detect an occluded pedestrian by multipath propagation, there is still a need in improving the detection performance when there is no multipath from an occluded pedestrian. Furthermore, the results indicate that higher bandwidth improves target separation but is insufficient for occluded pedestrian detection without multipath. However, with some targets, even the range resolution at 4 GHz was not sufficient, which required a separation in the Doppler dimension, emphasizing the need for overall resolution improvement of FMCW radars. Future work should focus on developing more complex road user models and simulating a broader range of scenarios to comprehensively evaluate radar performance in road traffic environments. Full article

(This article belongs to the Special Issue Advances in Vehicular Ad Hoc Networks (VANETs))

17 pages, 2890 KiB

Open AccessFeature PaperArticle

Intraspecific Chemical Variability and Antioxidant Capacity of Siparuna guianensis Aubl. Essential Oil from Brazil

by Daniel B. Santos, Raphael O. de Figueiredo, Rosa Helena V. Mourão, Willian N. Setzer, Joyce Kelly R. da Silva and Pablo Luis B. Figueiredo

Horticulturae 2024, 10(7), 690; https://doi.org/10.3390/horticulturae10070690 (registering DOI) - 28 Jun 2024

Viewed by 67

Abstract

Siparuna guianensis Aubl. is an essential-oil-producing plant with diverse ethnopharmacological uses and bioactive potential. This study aims to evaluate the intraspecific variation in the yield, chemical composition, and antioxidant capacity of S. guianensis essential oil (EO). The specimens (SG-1 to SG-6) were collected in June, five in the district of Outeiro and one in the Salvaterra municipality (Brazil). EOs were obtained by hydrodistillation. The chemical compositions were analyzed by gas chromatography coupled to a mass spectrometer (GC-MS). The DPPH radical scavenging tests and inhibition of β-carotene oxidation by linoleic acid were carried out to evaluate the antioxidant capacity of EOs. Principal components analyses were performed to verify the interrelationships between the studied specimens’ oil yields, chemical composition, and antioxidant capacity. Regarding chemical constituents, all studied samples showed the occurrence of spathulenol with an average concentration of 25.6 ± 15.6%. The samples that presented the highest amounts of this constituent were SG-5 (43.3%) and SG-1 (41.8%); the spathulenol amounts in other samples were 33.2% (SG-4); 13.8% (SG-2); 11.5% (SG-6) and 9.8% (SG-3). Moreover, there was no significant variability in yield and antioxidant capacity using DPPH and β-carotene/linoleic acid; both tests found insignificant values. This species presents a notable intraspecific chemical variability. Despite notable antitumor activities, the plant presents intraspecific chemical variability in composition, which suggests new studies to evaluate the impacts on bioactive compounds. Full article

(This article belongs to the Special Issue Medicinal and Aromatic Plants: Isolation, Characterization and Biological Activities)

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24 pages, 1027 KiB

Open AccessArticle

An Advanced Lung Carcinoma Prediction and Risk Screening Model Using Transfer Learning

by Isha Bhatia, Aarti, Syed Immamul Ansarullah, Farhan Amin and Amerah Alabrah

Diagnostics 2024, 14(13), 1378; https://doi.org/10.3390/diagnostics14131378 (registering DOI) - 28 Jun 2024

Viewed by 58

Abstract

Lung cancer, also known as lung carcinoma, has a high death rate, but an early diagnosis can substantially reduce this risk. In the current era, prediction models face challenges such as low accuracy, excessive noise, and low contrast. To resolve these problems, an advanced lung carcinoma prediction and risk screening model using transfer learning is proposed. Our proposed model initially preprocesses lung computed tomography images for noise removal, contrast stretching, convex hull lung region extraction, and edge enhancement. The next phase segments the preprocessed images using the modified Bates distribution coati optimization (B-RGS) algorithm to extract key features. The PResNet classifier then categorizes the cancer as normal or abnormal. For abnormal cases, further risk screening determines whether the risk is low or high. Experimental results depict that our proposed model performs at levels similar to other state-of-the-art models, achieving enhanced accuracy, precision, and recall rates of 98.21%, 98.71%, and 97.46%, respectively. These results validate the efficiency and effectiveness of our suggested methodology in early lung carcinoma prediction and risk assessment. Full article

(This article belongs to the Special Issue Artificial Intelligence in Cancers—2nd Edition)

31 pages, 932 KiB

Open AccessArticle

Feasibility of Natural Fibre Usage for Wind Turbine Blade Components: A Structural and Environmental Assessment

by Kyle Pender, Konstantinos Bacharoudis, Filippo Romoli, Peter Greaves and Jonathan Fuller

Sustainability 2024, 16(13), 5533; https://doi.org/10.3390/su16135533 (registering DOI) - 28 Jun 2024

Viewed by 92

Abstract

There are two key areas of development across wind turbine blade lifecycles with the potential to reduce the impact of wind energy generation: (1) deploying lower-impact materials in blade structures and (2) developing low-impact blade recycling solution(s). This work evaluates the feasibility of using natural fibres to replace traditional glass and carbon fibres within state-of-the-art offshore blades. The structural design of blades was performed using Aeroelastic Turbine Optimisation Methods and lifecycle assessment was conducted to evaluate the environmental impact of designs. This enabled the matching of blade designs with preferred waste treatment strategies for the lowest impact across the blade lifecycle. Flax and hemp fibres were the most promising solutions; however, they should be restricted to use in stiffness-driven, bi-axial plies. It was found that flax, hemp, and basalt deployment could reduce Cradle-to-Gate Global Warming Potential (GWP) by around 6%, 7%, and 8%, respectively. Cement kiln co-processing and mechanical recycling strategies were found to significantly reduce Cradle-to-Grave GWP and should be the prioritised strategies for scrap blades. Irrespective of design, carbon fibre production was found to be the largest contributor to the blade GWP. Lower-impact alternatives to current carbon fibre production could therefore provide a significant reduction in wind energy impact and should be a priority for wind decarbonisation. Full article

(This article belongs to the Special Issue Current Advances in Offshore Wind Energy for Sustainability)

22 pages, 3612 KiB

Open AccessCommunication

Sustainability Activities in a Hard-to-Abate Industry—A Real-Life Example

by Ragnhild Dragøy, Lena Burri, Pål Skogrand, Thomas Røkke, Viktor Ananiev and Stig Grafsrønningen

Sustainability 2024, 16(13), 5532; https://doi.org/10.3390/su16135532 (registering DOI) - 28 Jun 2024

Viewed by 99

Abstract

Marine sources of omega-3, proteins, and other nutrients are in increasing demand, while supply is struggling to meet this demand increase. A key focus for meeting the need for marine ingredients for human and animal nutrition is ensuring sustainable sourcing for both the oceans as well as other production types. Aker BioMarine is harvesting and producing marine ingredients from krill and this communication is intended to showcase how the harvesting and production of such ingredients are performed in a sustainable way. This communication is written to describe the krill fisheries’ management, to provide demonstration cases from CO₂ hot spotting, and show how results from these are used to target GHG emission reduction. The initiatives that are taken to ensure sustainable fishing and production, as well as examples of short- and long-term actions to reduce and minimize the impact of all activities, are provided. Full article

(This article belongs to the Special Issue Marine Biotechnology for Sustainability of Ecologically Significant Resources)

15 pages, 1293 KiB

Open AccessArticle

Hydraulic Conductivity Estimation: Comparison of Empirical Formulas Based on New Laboratory Experiments

by Mohammad Reza Goodarzi, Majid Vazirian and Majid Niazkar

Water 2024, 16(13), 1854; https://doi.org/10.3390/w16131854 (registering DOI) - 28 Jun 2024

Viewed by 104

Abstract

Hydraulic conductivity (K) is one of the most important characteristics of soils in terms of groundwater movement and the formation of aquifers. Generally, it indicates the ease of infiltration and penetration of water in the soil. It depends on various factors, including fluid viscosity, pore size, grain size, porosity ratio, mineral grain roughness, and soil saturation level. Each of the empirical formulas used to calculate K includes one or more of the influencing parameters. In this study, pumping tests from an aquifer were performed by using a hydrology apparatus. Laboratory experiments were conducted on six types of soil with different grain sizes, ranging from fine sand to coarse sand, to obtain K. The experimental-based K values were compared with that of empirical formulas. The results demonstrate that Breyer and Hazen (modified) formulas adequately fit the laboratory values. The novelty of the present study is the comparison of the experimental formulas in completely similar conditions of the same sample, such as porosity, viscosity, and grain size, using the pumping test in a laboratory method, and the results show that the Hazen and the Breyer formulas provide the best results. The findings of this work will help in better development of groundwater resources and aquifer studies. Full article

17 pages, 2054 KiB

Open AccessArticle

Synthesis and In Silico Analysis of New Polyheterocyclic Molecules Derived from [1,4]-Benzoxazin-3-one and Their Inhibitory Effect against Pancreatic α-Amylase and Intestinal α-Glucosidase

by Mohamed Ellouz, Aziz Ihammi, Abdellah Baraich, Ayoub Farihi, Darifa Addichi, Saliha Loughmari, Nada Kheira Sebbar, Mohamed Bouhrim, Ramzi A. Mothana, Omar M. Noman, Bruno Eto, Fatiha Chigr and Mohammed Chigr

Molecules 2024, 29(13), 3086; https://doi.org/10.3390/molecules29133086 (registering DOI) - 28 Jun 2024

Viewed by 81

Abstract

This study focuses on synthesizing a new series of isoxazolinyl-1,2,3-triazolyl-[1,4]-benzoxazin-3-one derivatives 5a–5o. The synthesis method involves a double 1,3-dipolar cycloaddition reaction following a “click chemistry” approach, starting from the respective [1,4]-benzoxazin-3-ones. Additionally, the study aims to evaluate the antidiabetic potential of these newly synthesized compounds through in silico methods. This synthesis approach allows for the combination of three heterocyclic components: [1,4]-benzoxazin-3-one, 1,2,3-triazole, and isoxazoline, known for their diverse biological activities. The synthesis procedure involved a two-step process. Firstly, a 1,3-dipolar cycloaddition reaction was performed involving the propargylic moiety linked to the [1,4]-benzoxazin-3-one and the allylic azide. Secondly, a second cycloaddition reaction was conducted using the product from the first step, containing the allylic part and an oxime. The synthesized compounds were thoroughly characterized using spectroscopic methods, including ¹H NMR, ¹³C NMR, DEPT-135, and IR. This molecular docking method revealed a promising antidiabetic potential of the synthesized compounds, particularly against two key diabetes-related enzymes: pancreatic α-amylase, with the two synthetic molecules 5a and 5o showing the highest affinity values of 9.2 and 9.1 kcal/mol, respectively, and intestinal α-glucosidase, with the two synthetic molecules 5n and 5e showing the highest affinity values of −9.9 and −9.6 kcal/mol, respectively. Indeed, the synthesized compounds have shown significant potential as antidiabetic agents, as indicated by molecular docking studies against the enzymes α-amylase and α-glucosidase. Additionally, ADME analyses have revealed that all the synthetic compounds examined in our study demonstrate high intestinal absorption, meet Lipinski’s criteria, and fall within the required range for oral bioavailability, indicating their potential suitability for oral drug development. Full article

(This article belongs to the Special Issue Advances in Synthesis and Biological Activity of Novel Derivatives Based on Five-Membered Heterocyclic Scaffolds and Their Intermediates—Second Edition)

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12 pages, 6301 KiB

Open AccessArticle

A Study on the Evaluation of Thermal Insulation Performance of Cellulose-Based Silica Aerogel Composite Building Materials

by Jeo Hwang, Yoonmi Kim, Jooyoung Park and Dongho Rie

Polymers 2024, 16(13), 1848; https://doi.org/10.3390/polym16131848 (registering DOI) - 28 Jun 2024

Viewed by 111

Abstract

Buildings utilize both inorganic and organic insulation materials to conserve energy and prevent heat loss. However, while exhibiting excellent thermal insulation performance, organic insulation materials increase the risk of fire due to the emission of intense heat and toxic smoke in the event of a fire. Conversely, inorganic insulation materials are characterized by a lower thermal insulation performance, leading to an increase in the weight of the building with extensive use. Therefore, the necessity for research into new insulation materials that address the drawbacks of existing ones, including reducing weight, enhancing fire resistance, and improving thermal insulation performance, has been recognized. This study focuses on evaluating the enhancement of the thermal insulation performance using novel building materials compared to conventional ones. The research methodology involved the incorporation of porous aerogel powders into paper-based cellulose insulation to improve its insulating properties. Samples were prepared in standard 100 × 100 mm² panel forms. Two control groups were utilized: a pure control group, where specimens were fabricated using 100% recycled cardboard for packaging, and a mixed control group, where specimens were produced using a mixture ratio of 30 wt% ceramic binder and 40 wt% expandable graphite. Experimental group specimens were prepared by increasing the aerogel content from 200 to 1000 mL under each condition of the control groups (pure and mixed) after mixing. The thermal insulation performance of the specimens was evaluated in terms of thermal conductivity and thermal diffusivity according to ISO 22007-2 (for solids, paste, and powders). Through this study, it was found that the thermal insulation performances of the pure control and experimental groups improved by 16.66%, while the mixed control and experimental groups demonstrated a 17.06% enhancement in thermal insulation performance with the addition of aerogel. Full article

(This article belongs to the Special Issue Recent Developments in Wood Polymer Composites)

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37 pages, 720 KiB

Open AccessArticle

A Survey of Computationally Efficient Graph Neural Networks for Reconfigurable Systems

by Habib Taha Kose, Jose Nunez-Yanez, Robert Piechocki and James Pope

Information 2024, 15(7), 377; https://doi.org/10.3390/info15070377 (registering DOI) - 28 Jun 2024

Viewed by 92

Abstract

Graph neural networks (GNNs) are powerful models capable of managing intricate connections in non-Euclidean data, such as social networks, physical systems, chemical structures, and communication networks. Despite their effectiveness, the large-scale and complex nature of graph data demand substantial computational resources and high performance during both training and inference stages, presenting significant challenges, particularly in the context of embedded systems. Recent studies on GNNs have investigated both software and hardware solutions to enhance computational efficiency. Earlier studies on deep neural networks (DNNs) have indicated that methods like reconfigurable hardware and quantization are beneficial in addressing these issues. Unlike DNN research, studies on efficient computational methods for GNNs are less developed and require more exploration. This survey reviews the latest developments in quantization and FPGA-based acceleration for GNNs, showcasing the capabilities of reconfigurable systems (often FPGAs) to offer customized solutions in environments marked by significant sparsity and the necessity for dynamic load management. It also emphasizes the role of quantization in reducing both computational and memory demands through the use of fixed-point arithmetic and streamlined vector formats. This paper concentrates on low-power, resource-limited devices over general hardware accelerators and reviews research applicable to embedded systems. Additionally, it provides a detailed discussion of potential research gaps, foundational knowledge, obstacles, and prospective future directions. Full article

(This article belongs to the Special Issue Artificial Intelligence on the Edge)

18 pages, 10562 KiB

Open AccessArticle

Motor PHM on Edge Computing with Anomaly Detection and Fault Severity Estimation through Compressed Data Using PCA and Autoencoder

by Jong Hyun Choi, Sung Kyu Jang, Woon Hyung Cho, Seokbae Moon and Hyeongkeun Kim

Mach. Learn. Knowl. Extr. 2024, 6(3), 1466-1483; https://doi.org/10.3390/make6030069 (registering DOI) - 28 Jun 2024

Viewed by 98

Abstract

The motor is essential for manufacturing industries, but wear can cause unexpected failure. Predictive and health management (PHM) for motors is critical in manufacturing sites. In particular, data-driven PHM using deep learning methods has gained popularity because it reduces the need for domain expertise. However, the massive amount of data poses challenges to traditional cloud-based PHM, making edge computing a promising solution. This study proposes a novel approach to motor PHM in edge devices. Our approach integrates principal component analysis (PCA) and an autoencoder (AE) encoder achieving effective data compression while preserving fault detection and severity estimation integrity. The compressed data is visualized using t-SNE, and its ability to retain information is assessed through clustering performance metrics. The proposed method is tested on a custom-made experimental platform dataset, demonstrating robustness across various fault scenarios and providing valuable insights for practical applications in manufacturing. Full article

(This article belongs to the Section Data)

26 pages, 6002 KiB

Open AccessArticle

Multi-Objective Optimization in Support of Life-Cycle Cost-Performance-Based Design of Reinforced Concrete Structures

by Ali Sabbaghzade Feriz, Hesam Varaee and Mohammad Reza Ghasemi

Mathematics 2024, 12(13), 2008; https://doi.org/10.3390/math12132008 (registering DOI) - 28 Jun 2024

Viewed by 100

Abstract

Surveys on the optimum seismic design of structures reveal that many investigations focus on minimizing initial costs while satisfying performance constraints. Although reducing initial costs while complying with earthquake design codes significantly ensures occupant safety, it may still cause considerable economic losses and fatalities. Therefore, calculating potential earthquake damages over the structure’s lifetime is essential from an optimal Life-Cycle Cost (LCC) design perspective. LCC analysis evaluates economic feasibility, including construction, operation, occupancy, maintenance, and end-of-life costs. The population-based, meta-heuristic Ideal Gas Molecular Movement (IGMM) algorithm has proven effective in solving highly nonlinear mono- and multi-objective engineering problems. This paper investigates the LCC-based mono- and multi-objective optimum design of a 3D four-story concrete building structure using the Endurance Time (ET) method, which is employed for its efficiency in estimating structural responses under varying seismic hazard levels. The novelty of this work lies in integrating the ET method with the IGMM algorithm to comprehensively address both economic and performance criteria in seismic design. The results indicate that the proposed technique significantly reduces minor injury costs, rental costs, and income costs by 22%, 16%, and 16%, respectively, achieving a total reduction of 10% in all structural Life-Cycle Costs, which is considered significant. Full article

(This article belongs to the Special Issue Advances in Evolutionary Computation and Applications)

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13 pages, 7761 KiB

Open AccessArticle

Numerical Simulation for the Desired Compatibility between the Inside Slopes of Open Irrigation Canals, and the Used Type of Wing Walls for the Most Efficient Performance of Water Structures

by Mohamed A. Ashour, Haitham M. Abueleyon, M. Khairy Ali, Abdallah A. Abdou and Tarek S. Abu-Zaid

Limnol. Rev. 2024, 24(3), 192-204; https://doi.org/10.3390/limnolrev24030011 - 28 Jun 2024

Viewed by 164

Abstract

The design of water structures is crucial for efficient hydraulic performance. Open irrigation canals are designed with specific inside slopes to ensure maximum stability, while the wing walls of water structures constructed across the canal are designed to maximize hydraulic performance. Therefore, ensuring compatibility between the canal inside slopes and the wing wall types used on both the upstream and downstream sides is of great importance for achieving optimum hydraulic performance. However, our literature review indicates that this necessary compatibility between the canal inside slope and the wing wall type has not been adequately researched and studied. This present study aims to numerically investigate the relationship between open canals inside slopes and wing wall types, as well as examine the impact of using different wing wall types with varying canals inside slopes on hydraulic performance efficiency. Four canal inside slope ratios (Z) (H: V = 2:1, 1.5:1, 1:1, and 0.75:1) are simulated using the HEC-RAS program, along with two types of water structure wing walls (box and broken). The HEC-RAS numerical model provides accurate and reliable estimations of the hydraulic characteristics of flowing water through the structure, and the results are verified using previous experimental measurements available in the literature. The variation (ε%) between the measured and computed results is consistent for estimating specific energy, velocity, heading (afflux), and water depths. The simulation results demonstrate that changing the canal inside slope (Z) from 0.75:1 to 2:1 results in a relative increase of approximately 27.84% in heading up and 15.06% in velocity. Additionally, the broken wing wall proves to be more effective than the box type. The study confirms that the optimal configuration for the most efficient performance of water structures involves utilizing broken-type wing walls on the upstream side, along with a 1H:1V canal inside slope. This configuration reduces the relative velocity and relative heading by approximately 12% and 20%, respectively, which is considered highly favorable. Full article

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11 pages, 5571 KiB

Open AccessArticle

Quantum Graphene Asymmetric Devices for Harvesting Electromagnetic Energy

by Mircea Dragoman, Adrian Dinescu, Martino Aldrigo and Daniela Dragoman

Nanomaterials 2024, 14(13), 1114; https://doi.org/10.3390/nano14131114 (registering DOI) - 28 Jun 2024

Viewed by 106

Abstract

We present here the fabrication at the wafer level and the electrical performance of two types of graphene diodes: ballistic trapezoidal-shaped graphene diodes and lateral tunneling graphene diodes. In the case of the ballistic trapezoidal-shaped graphene diode, we observe a large DC current of 200 µA at a DC bias voltage of ±2 V and a large voltage responsivity of 2000 v/w, while in the case of the lateral tunneling graphene diodes, we obtain a DC current of 1.5 mA at a DC bias voltage of ±2 V, with a voltage responsivity of 3000 v/w. An extended analysis of the defects produced during the fabrication process and their influences on the graphene diode performance is also presented. Full article

(This article belongs to the Special Issue Harvesting Electromagnetic Fields with Nanomaterials from Microwaves to Ultraviolet)

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28 pages, 2881 KiB

Open AccessArticle

Trends in Corporate Environmental Compliance Research: A Bibliometric Analysis (2004–2024)

by Tiancheng Chi and Zheng Yang

Sustainability 2024, 16(13), 5527; https://doi.org/10.3390/su16135527 (registering DOI) - 28 Jun 2024

Viewed by 122

Abstract

Against the backdrop of the global energy crisis and climate change, corporate environmental compliance has emerged as a key aspect of environmental regulation and a focal point of academic interest. It plays a crucial role in alleviating regulatory pressure, enabling green innovations, enhancing performance, and fostering sustainable development. Despite extensive research in the field, comprehensive reviews and bibliometric analyses remain scarce. To address this gap, this study meticulously analyzed 851 papers indexed in the WoS’s SSCI and SCI from 2004 to 2024. Using visualization tools like VOSviewer and CiteSpace, it conducted a multidimensional bibliometric analysis and systematic review, identifying core authors such as Aseem, Ntim, and Zeng, high-productivity countries including China, the USA, and the UK, and key journals like the Journal of Cleaner Production and Sustainability. Keyword co-occurrence and cluster analysis revealed central research themes of environmental information disclosure, innovation, and environmental management systems. Burst analysis highlighted emerging hot topics, notably ecological and green innovation, and the interplay between Total Factor Productivity and environmental regulations. Additionally, we identified several critical gaps in the field. For instance, research on corporate environmental governance mechanisms in the context of digital transformation remains insufficient. Furthermore, the effectiveness of multi-stakeholder collaborative governance frameworks requires ongoing investigation. Therefore, we encourage future researchers to focus on the following topics: digitization and environmental compliance, multi-stakeholder participation mechanisms, cost–benefit analysis of corporate environmental compliance, and the impact of political and regulatory environments on corporate environmental compliance. Full article

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