bluuebunny/crossref_metadata_2025 huggingface dataset:
Estimation and Evaluation of 15 Minute, 40 Meter Surface Upward Longwave Radiation Downscaled from the Geostationary FY-4B AGRI
Authors: Zheng Limeng , Cao Biao , Na Qiang , Qin Boxiong , Bai Junhua , Du Yongming , Li Hua , Bian Zunjian , Xiao Qing , Liu Qinhuo
Published: March 2024

Surface upward longwave radiation (SULR) is one of the four components of surface net radiation. Geostationary satellites can provide high temporal but coarse spatial resolution SULR products. Downscaling coarse SULR to a higher resolution is important for fine-scale thermal condition monitoring. Statistical regression downscaling is widely used due to its simplicity and is built on the assumption that the thermal parameter like land surface temperature (LST) or SULR has a relationship with the related surface factors like the normalized difference vegetation index (NDVI), and the relationship remains unchanged in any scales. In this study, to establish the relationship between SULR and the related surface factors, we chose the multiple linear regression (MLR) model and five surface factors (i.e., the modified normalized difference water index (MNDWI), normalized difference built-up and soil index (NDBSI), NDVI, normalized moisture difference index (NMDI), and urban index (UI)) to drive the downscaling process. Additionally, a step-by-step downscaling strategy was applied to reach the 100-fold increase in spatial resolution, transitioning the estimated SULR from 4 km of the advanced geostationary radiation imager (AGRI) onboard FengYun-4B (FY-4B) satellite to 40 m of the visual and infrared multispectral imager (VIMI) in infrared spectrum onboard GaoFen5-02 (GF5-02). Finally, we evaluated the downscaling results by comparing the downscaled SULR values with the in situ measured SULR and GF5-02-calculated SULR, and the root mean square errors (RMSEs) were 19.70 W/m2 and 24.86 W/m2, respectively. Throughout this MLR-based step-by-step downscaling method (high-frequency data from FY-4B and high spatial resolution data from GF5-02), high spatiotemporal SULR (15 min temporal resolution, 40 m spatial resolution) were successfully generated instead of coarse spatial resolution ones from the FY-4B satellite or a coarse temporal resolution one from the GF5-02 satellite, relieving the above-mentioned conflict to some extent.
Quantifying Seagrass Density Using Sentinel-2 Data and Machine Learning
Authors: Meister Martin , Qu John J.
Published: March 2024

Seagrasses, rooted aquatic plants growing completely underwater, are extremely important for the coastal ecosystem. They are an important component of the total carbon burial in the ocean, they provide food, shelter, and nursery to many aquatic organisms in coastal ecosystems, and they improve water quality. Due to human activity, seagrass coverage has been rapidly declining, and there is an urgent need to monitor seagrasses consistently. Seagrass coverage has been closely monitored in the Chesapeake Bay since 1970 using air photos and ground samples. These efforts are costly and time-consuming. Many studies have used remote sensing data to identify seagrass bed outlines, but few have mapped seagrass bed density. This study used Sentinel-2 satellite data and machine learning in Google Earth Engine and the Chesapeake Bay Program field data to map seagrass density. We used seagrass density data from the Chincoteague and Sinepuxent Bay to train machine learning algorithms and evaluate their accuracies. Out of the four machine learning models tested (Naive Bayes (NB), Classification and Regression Trees (CART), Support Vector Machine (SVM), and Random Forest (RF)), the RF model outperformed the other three models with overall accuracies of 0.874 and Kappa coefficients of 0.777. The SVM and CART models performed similarly and NB performed the poorest. We tested two different approaches to assess the models’ accuracy. When we used all the available ground samples to train the models, whereby our analysis showed that model performance was associated with seagrass density class, and that higher seagrass density classes had better consumer accuracy, producer accuracy, and F1 scores. However, the association of model performance with seagrass density class disappeared when using the same training data size for each class. Very sparse and dense seagrass classes had replacedhigherbetter accuracies than the sparse and moderate seagrass density classes. This finding suggests that training data impacts machine learning model performance. The uneven training data size for different classes can result in biased assessment results. Selecting proper training data and machine learning models are equally important when using machine learning and remote sensing data to map seagrass density. In summary, this study demonstrates the potential to map seagrass density using satellite data.
Multimodal Features Alignment for Vision–Language Object Tracking
Authors: Ye Ping , Xiao Gang , Liu Jun
Published: March 2024

Vision–language tracking presents a crucial challenge in multimodal object tracking. Integrating language features and visual features can enhance target localization and improve the stability and accuracy of the tracking process. However, most existing fusion models in vision–language trackers simply concatenate visual and linguistic features without considering their semantic relationships. Such methods fail to distinguish the target’s appearance features from the background, particularly when the target changes dramatically. To address these limitations, we introduce an innovative technique known as multimodal features alignment (MFA) for vision–language tracking. In contrast to basic concatenation methods, our approach employs a factorized bilinear pooling method that conducts squeezing and expanding operations to create a unified feature representation from visual and linguistic features. Moreover, we integrate the co-attention mechanism twice to derive varied weights for the search region, ensuring that higher weights are placed on the aligned visual and linguistic features. Subsequently, the fused feature map with diverse distributed weights serves as the search region during the tracking phase, facilitating anchor-free grounding to predict the target’s location. Extensive experiments are conducted on multiple public datasets, and our proposed tracker obtains a success score of 0.654/0.553/0.447 and a precision score of 0.872/0.556/0.513 on OTB-LANG/LaSOT/TNL2K. These results are satisfying compared with those of recent state-of-the-art vision–language trackers.
Historical Marine Cold Spells in the South China Sea: Characteristics and Trends
Authors: Li Chunhui , Sun Wenjin , Ji Jinlin , Zhu Yuxin
Published: March 2024

Marine cold spells (MCSs) are extreme ocean temperature events impacting marine organisms, yet their characteristics and trends in the South China Sea (SCS) historical period remain unclear. This study systematically analyzes sea surface temperature (SST) and MCSs in the SCS using satellite observation data (OISSTv2.1) from 1982 to 2022. The climatological mean SST ranges from 22 °C near the Taiwan Strait to 29 °C near the Nansha Islands, showing notable variations. Annual SST anomalies demonstrate a heterogeneous spatial trend of approximately 0.21 ± 0.16 °C/decade (p < 0.01) across the SCS, indicating an increase in SST over time. MCS analysis uncovers spatial non-uniformity in frequency, with higher values near the Beibu Gulf and Hainan Island, and longer durations in the northeastern coastal areas. Statistical analysis indicates normal distributions for frequency and duration trends but skewness for intensity and cumulative intensity, reflecting extreme values. Winter months exhibit larger MCS occurrence areas and higher mean intensities, illustrating seasonal variability. Anticipated changes will significantly impact the ecological structure and functioning of the SCS.
Dynamical Model of Rotation and Orbital Coupling for Deimos
Authors: Huang Kai , Zhang Lijun , Yang Yongzhang , Ye Mao , Li Yuqiang
Published: March 2024

This paper introduces a novel dynamical model, building upon the existing dynamical model for Deimos in the current numerical ephemerides, which only encompasses the simple libration effects of Deimos. The study comprehensively incorporates the rotational dynamics of Deimos influenced by the torque exerted by the major celestial bodies (Mars, the Sun) in the solar system within the inertial space. Consequently, a full dynamical model is formulated to account for the complete coupling between the rotation and orbit of Deimos. Simultaneously, employing precision orbit determination methods used for artificial satellites, we develop an adjustment model for fitting data to the complete model. The 12-order Adams–Bashforth–Moulton (ABM) integration algorithm is employed to synchronously integrate the 12 state variables of the full model to obtain the orbit of Deimos.The difference in the orbits obtained by integrating the full model over a period of 10 years and those obtained by the simplified model is at the order of 10 km. After precise orbit determination, this difference decreases to below 100 m, so numerical simulation results indicate that the full dynamical model and adjustment model are stable and reliable. Simultaneously, the integration of the Deimos third-order gravity field in the full model over a 10-year period induces only meter-level positional changes. This suggests that when constructing the complete model, the utilization of a second-order gravity field alone is sufficient. Compared to the simple model, the polar axis of Deimos in the inertial space exhibits a more complex oscillation in the full model. Additionally, the full model calculates that the minimum moment of inertia principal axis of Phobos has an amplitude of approximately 0.5 degrees in the longitude direction and does not exceed 2 degrees in the latitude direction. This work further advances the current dynamical model for Deimos and establishes the foundational model for the generation of a new set of precise numerical ephemerides for Deimos.
Species Abundance Modelling of Arctic-Boreal Zone Ducks Informed by Satellite Remote Sensing
Authors: Merchant Michael Allan , Battaglia Michael J. , French Nancy , Smith Kevin , Singer Howard V. , Armstrong Llwellyn , Harriman Vanessa B. , Slattery Stuart
Published: March 2024

The Arctic-Boreal zone (ABZ) covers over 26 million km2 and is home to numerous duck species; however, understanding the spatiotemporal distribution of their populations across this vast landscape is challenging, in part due to extent and data scarcity. Species abundance models for ducks in the ABZ commonly use static (time invariant) habitat covariates to inform predictions, such as wetland type and extent maps. For the first time in this region, we developed species abundance models using high-resolution, time-varying wetland inundation data produced using satellite remote sensing methods. This data captured metrics of surface water extent and inundated vegetation in the Peace Athabasca Delta, Canada, which is within the NASA Arctic Boreal Vulnerability Experiment core domain. We used generalized additive mixed models to demonstrate the improved predictive value of this novel data set over time-invariant data. Our findings highlight both the potential complementarity and efficacy of dynamic wetland inundation information for improving estimation of duck abundance and distribution at high latitudes. Further, these data can be an asset to spatial targeting of biodiversity conservation efforts and developing model-based metrics of their success under rapidly changing climatic conditions.
Modelling Asphalt Overlay As-Built Roughness Based on Profile Transformation—Case for Paver Using Automatic Levelling System
Authors: Díaz-Torrealba Rodrigo , Marcobal José Ramón , Gallego Juan
Published: March 2024

The as-built roughness, or smoothness obtained during pavement construction, plays an important role in road engineering since it serves as an indicator for both the level of service provided to users and the overall standard of construction quality. Being able to predict as-built roughness is therefore important for supporting pavement design and management decision making. An as-built IRI prediction model for asphalt overlays based on profile transformation was proposed in a previous study. The model, used as basis for this work, was developed for the case of wheeled pavers without automatic screed levelling. This study presents further development of the base prediction model, including the use of an automatic screed control system through a long-distance averaging mobile reference. Formulation of linear systems that constitute the model are presented for the case of a wheeled paver using contactless acoustic sensors set-up over a floating levelling beam attached to the paver. To calibrate the model, longitudinal profile data from the Long-Term Pavement Performance SPS-5 experiment was used, obtaining a mean error of 0.17 m/km for the predicted IRI. The results obtained demonstrate the potential of the proposed approach as a modelling alternative.
Design and Implementation of C-Band Large-Power Planar Butler Matrix in SRS
Authors: Li Jinfeng , Yan Liping , Liu Changjun , Bai He , Cui Wanzhao
Published: March 2024

In satellite remote sensing (SRS), there is a demand for large-power microwave components. A Butler matrix is essential to a transmitting antenna array in SRS. This article illustrates the electrical and mechanical design, simulation, and test results of a large-power planar beamforming network for SRS at C-band. It is a 4 × 4 Butler matrix based on square coaxial lines. Short-ended stubs are used in the Butler matrix to broaden its bandwidth by 10%, support inner conductors, and enhance heat transfer in vacuum environments. The simulation results are consistent with the measured results. The reflection coefficient is less than −18 dB, and the isolation is more than 23 dB from 3.8 GHz to 4.2 GHz. The insertion losses are less than 0.6 dB, and the phase errors are better than ±6°. The measured peak microwave power of the proposed Butler matrix is 9 kW. Its size is 440 × 400 × 40 mm3. The proposed Butler matrix beamforming network can be applied to SRS systems.
Fine-Grained Permeable Surface Mapping through Parallel U-Net
Authors: Ogilvie Nathaniel , Zhang Xiaohan , Kochenour Cale , Wshah Safwan
Published: March 2024

Permeable surface mapping, which mainly is the identification of surface materials that will percolate, is essential for various environmental and civil engineering applications, such as urban planning, stormwater management, and groundwater modeling. Traditionally, this task involves labor-intensive manual classification, but deep learning offers an efficient alternative. Although several studies have tackled aerial image segmentation, the challenges in permeable surface mapping arid environments remain largely unexplored because of the difficulties in distinguishing pixel values of the input data and due to the unbalanced distribution of its classes. To address these issues, this research introduces a novel approach using a parallel U-Net model for the fine-grained semantic segmentation of permeable surfaces. The process involves binary classification to distinguish between entirely and partially permeable surfaces, followed by fine-grained classification into four distinct permeability levels. Results show that this novel method enhances accuracy, particularly when working with small, unbalanced datasets dominated by a single category. Furthermore, the proposed model is capable of generalizing across different geographical domains. Domain adaptation is explored to transfer knowledge from one location to another, addressing the challenges posed by varying environmental characteristics. Experiments demonstrate that the parallel U-Net model outperforms the baseline methods when applied across domains. To support this research and inspire future research, a novel permeable surface dataset is introduced, with pixel-wise fine-grained labeling for five distinct permeable surface classes. In summary, in this work, we offer a novel solution to permeable surface mapping, extend the boundaries of arid environment mapping, introduce a large-scale permeable surface dataset, and explore cross-area applications of the proposed model. The three contributions are enhancing the efficiency and accuracy of permeable surface mapping while progressing in this field.
High-Density Glass Scintillators for Proton Radiography—Relative Luminosity, Proton Response, and Spatial Resolution
Authors: Stolen Ethan , Fullarton Ryan , Hein Rain , Conner Robin L. , Jacobsohn Luiz G. , Collins-Fekete Charles-Antoine , Beddar Sam , Akgun Ugur , Robertson Daniel
Published: March 2024

Proton radiography is a promising development in proton therapy, and researchers are currently exploring optimal detector materials to construct proton radiography detector arrays. High-density glass scintillators may improve integrating-mode proton radiography detectors by increasing spatial resolution and decreasing detector thickness. We evaluated several new scintillators, activated with europium or terbium, with proton response measurements and Monte Carlo simulations, characterizing relative luminosity, ionization quenching, and proton radiograph spatial resolution. We applied a correction based on Birks’s analytical model for ionization quenching. The data demonstrate increased relative luminosity with increased activation element concentration, and higher relative luminosity for samples activated with europium. An increased glass density enables more compact detector geometries and higher spatial resolution. These findings suggest that a tungsten and gadolinium oxide-based glass activated with 4% europium is an ideal scintillator for testing in a full-size proton radiography detector.
Ultrasonic Through-Metal Communication Based on Deep-Learning-Assisted Echo Cancellation
Authors: Zhang Jinya , Jiang Min , Zhang Jingyi , Gu Mengchen , Cao Ziping
Published: March 2024

Ultrasound is extremely efficient for wireless signal transmission through metal barriers due to no limit of the Faraday shielding effect. Echoing in the ultrasonic channel is one of the most challenging obstacles to performing high-quality communication, which is generally coped with by using a channel equalizer or pre-distorting filter. In this study, a deep learning algorithm called a dual-path recurrent neural network (DPRNN) was investigated for echo cancellation in an ultrasonic through-metal communication system. The actual system was constructed based on the combination of software and hardware, consisting of a pair of ultrasonic transducers, an FPGA module, some lab-made circuits, etc. The approach of DPRNN echo cancellation was applied to signals with a different signal-to-noise ratio (SNR) at a 2 Mbps transmission rate, achieving higher than 20 dB SNR improvement for all situations. Furthermore, this approach was successfully used for image transmission through a 50 mm thick aluminum plate, exhibiting a 24.8 dB peak-signal-to-noise ratio (PSNR) and a about 95% structural similarity index measure (SSIM). Additionally, compared with three other echo cancellation methods—LMS, RLS and PNLMS—DPRNN has demonstrated higher efficiency. All those results firmly validate that the DPRNN algorithm is a powerful tool to conduct echo cancellation and enhance the performance of ultrasonic through-metal transmission.
Migration through Resolution Cell Correction and Sparse Aperture ISAR Imaging for Maneuvering Target Based on Whale Optimization Algorithm—Fast Iterative Shrinkage Thresholding Algorithm
Authors: Guo Xinrong , Liu Fengkai , Huang Darong
Published: March 2024

Targets faced by inverse synthetic aperture radar (ISAR) are often non-cooperative, with target maneuvering being the main manifestation of this non-cooperation. Maneuvers cause ISAR imaging results to be severely defocused, which can create huge difficulties in target identification. In addition, as the ISAR bandwidth continues to increase, the impact of migration through resolution cells (MTRC) on imaging results becomes more significant. Target non-cooperation may also result in sparse aperture, leading to the failure of traditional ISAR imaging algorithms. Therefore, this paper proposes an algorithm to realize MTRC correction and sparse aperture ISAR imaging for maneuvering targets simultaneously named whale optimization algorithm–fast iterative shrinkage thresholding algorithm (WOA-FISTA). In this algorithm, FISTA is used to perform MTRC correction and sparse aperture ISAR imaging efficiently and WOA is adopted to estimate the rotational parameter to eliminate the effects of maneuvering on imaging results. Experimental results based on simulation and measured datasets prove that the proposed algorithm implements sparse aperture ISAR imaging and MTRC correction for maneuvering targets simultaneously. The proposed algorithm achieves better results than traditional algorithms under different signal-to-noise ratio conditions.
Sybil Attacks Detection and Traceability Mechanism Based on Beacon Packets in Connected Automobile Vehicles
Authors: Zhu Yaling , Zeng Jia , Weng Fangchen , Han Dan , Yang Yiyu , Li Xiaoqi , Zhang Yuqing
Published: March 2024

Connected Automobile Vehicles (CAVs) enable cooperative driving and traffic management by sharing traffic information between them and other vehicles and infrastructures. However, malicious vehicles create Sybil vehicles by forging multiple identities and sharing false location information with CAVs, misleading their decisions and behaviors. The existing work on defending against Sybil attacks has almost exclusively focused on detecting Sybil vehicles, ignoring the traceability of malicious vehicles. As a result, they cannot fundamentally alleviate Sybil attacks. In this work, we focus on tracking the attack source of malicious vehicles by using a novel detection mechanism that relies on vehicle broadcast beacon packets. Firstly, the roadside units (RSUs) randomly instruct vehicles to perform customized key broadcasting and listening within communication range. This allows the vehicle to prove its physical presence by broadcasting. Then, RSU analyzes the beacon packets listened to by the vehicle and constructs a neighbor graph between the vehicles based on the customized particular fields in the beacon packets. Finally, the vehicle’s credibility is determined by calculating the edge success probability of vehicles in the neighbor graph, ultimately achieving the detection of Sybil vehicles and tracing malicious vehicles. The experimental results demonstrate that our scheme achieves the real-time detection and tracking of Sybil vehicles, with precision and recall rates of 98.53% and 95.93%, respectively, solving the challenge of existing detection schemes failing to combat Sybil attacks from the root.
Detection and Evaluation for High-Quality Cardiopulmonary Resuscitation Based on a Three-Dimensional Motion Capture System: A Feasibility Study
Authors: Tang Xingyi , Wang Yan , Ma Haoming , Wang Aoqi , Zhou You , Li Sijia , Pei Runyuan , Cui Hongzhen , Peng Yunfeng , Piao Meihua
Published: March 2024

High-quality cardiopulmonary resuscitation (CPR) and training are important for successful revival during out-of-hospital cardiac arrest (OHCA). However, existing training faces challenges in quantifying each aspect. This study aimed to explore the possibility of using a three-dimensional motion capture system to accurately and effectively assess CPR operations, particularly about the non-quantified arm postures, and analyze the relationship among them to guide students to improve their performance. We used a motion capture system (Mars series, Nokov, China) to collect compression data about five cycles, recording dynamic data of each marker point in three-dimensional space following time and calculating depth and arm angles. Most unstably deviated to some extent from the standard, especially for the untrained students. Five data sets for each parameter per individual all revealed statistically significant differences (p < 0.05). The correlation between Angle 1′ and Angle 2′ for trained (rs = 0.203, p < 0.05) and untrained students (rs = −0.581, p < 0.01) showed a difference. Their performance still needed improvement. When conducting assessments, we should focus on not only the overall performance but also each compression. This study provides a new perspective for quantifying compression parameters, and future efforts should continue to incorporate new parameters and analyze the relationship among them.
Position Checking-Based Sampling Approach Combined with Attraction Point Local Optimization for Safe Flight of UAVs
Authors: Zhu Hai , Li Baoquan , Tong Ruiyang , Yin Haolin , Zhu Canlin
Published: March 2024

Trading off the allocation of limited computational resources between front-end path generation and back-end trajectory optimization plays a key role in improving the efficiency of unmanned aerial vehicle (UAV) motion planning. In this paper, a sampling-based kinodynamic planning method that can reduce the computational cost as well as the risks of UAV flight is proposed. Firstly, an initial trajectory connecting the start and end points without considering obstacles is generated. Then, a spherical space is constructed around the topological vertices of the environment, based on the intersections of the trajectory with the obstacles. Next, some unnecessary sampling points, as well as node rewiring, are discarded by the designed position-checking strategy to minimize the computational cost and reduce the risks of UAV flight. Finally, in order to make the planning framework adaptable to complex scenarios, the strategies for selecting different attraction points according to the environment are designed, which further ensures the safe flight of the UAV while improving the success rate of the front-end trajectory. Simulations and real-world experiment comparisons are conducted on a vision-based platform to verify the performance of the proposed method.
Counteracting Bleeding in Centrifugal Partition Chromatography: Redosing of the Stationary Phase
Authors: Buthmann Felix , Hohlmann Jan , Volpert Sophia , Neuwald Mareen , Hamza Djamal , Schembecker Gerhard
Published: March 2024

Centrifugal Partition Chromatography is a type of Liquid-Liquid Chromatography that offers several advantages compared to Liquid Chromatography. Two immiscible liquids are utilized, and one phase has to be immobilized to implement chromatographic separation. This is performed with the help of centrifugal force. As this immobilization is not ideal, the stationary phase continuously leaks out of the apparatus (so-called bleeding). We measured the stationary phase’s loss precisely and implemented a controller to compensate for it during operation. This innovative mode of operation is called redosing of the stationary phase and prolongs the experimental runtime significantly. In a first step, we implemented an open-loop controller, which was capable of counteracting bleeding but could not dial to a given setpoint precisely. Therefore, a closed-loop controller with a moving frame shifting factor was programmed. This controller reached and maintained setpoints with high accuracy. The last experimental step was to check for boundaries of this new degree of freedom. In addition, we highlighted the accompanying hydrodynamics during redosing with the help of Computational Fluid Dynamics. We were able to show the influence of different volumes of the redosed stationary phase on the flow regime.
Population Aging and Decline Will Happen Sooner Than We Think
Authors: Guillemot Jonathan R. , Zhang Xue , Warner Mildred E.
Published: March 2024

The United Nations’ 2022 World Population Prospects suggests the global population will reach 10 billion people in 2058 and will peak in 2086. Aggregated data do not account for regional and age-group realities, which draw a more pressing picture. We analyze the World Population Prospects 2022 data according to age groups and regions and show that population peaks are going to occur sooner in some regions of the world than others, and the working-age population will peak on average 10 to 20 years before the overall population peaks. Africa is the only world region expected to continue to experience significant population growth. The population will be increasingly made up of larger proportions of older ages than younger, thereby shifting the dependency ratio. Reflections on the implications of an aging and shrinking population on policy regarding fertility, aging, migration, urban planning and economic development are needed. The challenge is not to be left for future generations to face; it is happening tomorrow.
Coupling and Coordination Relationship of Economic–Social–Natural Composite Ecosystem in Central Yunnan Urban Agglomeration
Authors: Yang Anran , Zhao Junsan , Lin Yilin , Chen Guoping
Published: March 2024

Exploring the spatio-temporal differentiation characteristics and coupling coordination relationship of the composite ecosystem of urban agglomerations is of great significance for promoting the synergistic sustainable development and integration construction of urban agglomerations. This paper is based on LUCC (Land Use and Land Cover Change) data, a DEM (Digital Elevation Model), and temperature, precipitation, and other multi-source data, using the central Yunnan urban agglomeration as an example and constructing a multi-dimensional evaluation index system highlighting development quality and efficiency. The entropy weight method was first used to determine the comprehensive weights to evaluate the regional economic and social development level. Then, the InVEST (Integrated Valuation of Ecosystem Services and Trade-offs) model was used to quantitatively calculate and analyze the spatial and temporal evolution characteristics of the four key ecosystem services, evaluating the spatio-temporal evolution characteristics of the natural subsystem. The coupling coordination model was used to quantitatively analyze the evolution of the coupling coordination of the composite ecosystems in the central Yunnan urban agglomeration during the period of 2010–2020, and to reveal its development law. The results show the following: ➀ During the study period, the socio-economic subsystems in the central Yunnan urban agglomeration demonstrated an outward radiative growth from Kunming City, marked by underdeveloped sub-centers and prevalent low-level areas. ② Trends in ecosystem services varied, with water and soil conservation showing fluctuating increases, carbon sequestration remaining stable, and habitat quality declining. The critically important integrated ecosystem services zone of the natural subsystem is mainly located in the northeastern region and southwestern edge of the study area. ③ In 2020, the coupling coordination degree of the composite ecosystem was 0.9492. This showed that economic, social, and ecological subsystems are highly coupled, with consistent overall development trends and strong interactions. ④ The increase in the degree of harmonization amounted to 7.82%, with lagging subsystems varying in the degree of harmonization in subregions. This study can provide a scientific foundation for the development of policies for the Central Yunnan urban agglomeration, promoting regional sustainable development and optimizing the spatial pattern of the national territory.
Analysis of the Dynamic Evolution Game of Government, Enterprise and the Public to Control Industrial Pollution
Authors: Yu Na , Lu Meilin
Published: March 2024

This paper proposes a two-party evolutionary game model of government and enterprise to solve the dilemma of industrial pollution control and explore the mode of government and enterprise collaborative governance. The local equilibrium points of the game model in four cases are calculated and analyzed, and the results show that government power alone cannot help enterprises achieve an ideal level of pollution reduction, and it is necessary to introduce public power for supervision. Based on the above, a tripartite evolutionary game model comprising the government, the public, and the enterprise is proposed. When the costs and benefits of the tripartite game players meet certain conditions, the system will evolve to a state of equilibrium (0,1,1). Following the current situation of economic development in China, the parameters of the two-party and tripartite evolutionary game are assigned, and the operating path and system’s evolution trajectory of the two-party and tripartite industrial pollution control are simulated by Matlab R2016a software. It is indicated that whether the government participates in supervision or not, an enterprise will actively control pollution under strong public supervision, which can provide feasible suggestions for the selection of industrial pollution control policies.
Innovations in Agricultural Bio-Inputs: Commercial Products Developed in Argentina and Brazil
Authors: da Silva Medina Gabriel , Rotondo Rosana , Rodríguez Gustavo Rubén
Published: March 2024

Innovations in agricultural bio-inputs can lead to sustainable alternatives to replace synthetic fertilizers and pesticides. However, there is no clear understanding of what technologies can become available to farmers as commercial products, particularly in developing countries. This study summarizes the innovations used in commercial products in Argentina and Brazil based on the countries’ official data and on in-depth surveys conducted with 14 bio-input private companies. The results reveal ongoing development efforts to improve traditional products, such as inoculants that help plants fix nitrogen. There is also progress in mastering the formulation of new bio-inputs, such as bio-fertilizers that promote plant growth and bio-pesticides for pest control. Lastly, the next generation of bio-inputs composed of phytovaccines promises to help prepare plants’ immune systems against the attack of pathogenic fungi and bacteria, while bio-herbicides can potentially reduce the use of synthetic herbicides to prepare fields for harvest. Domestic companies based in Argentina and Brazil play an important role in these innovations that can underpin bio-economy growth in developing countries.
Experts’ Perspectives on Inclusive Governance for Protecting Hot Spring Landscapes in China: Barriers and Implications
Authors: Li Yue , Abu Bakar Nor Azlina , Ismail Nor Atiah , Mohd Ariffin Noor Fazamimah , Mundher Riyadh
Published: March 2024

Hot spring landscapes offer enticing development prospects for investors in China. However, due to mounting economic pressures and a lack of coordination among various authorities, inclusive governance has proven ineffective in overseeing development projects centered around hot spring landscapes. Consequently, this manuscript delves into the potential for implementing inclusive governance strategies to safeguard hot spring landscapes in China. This study selected Linyi City as its study site due to its location above a fault zone, which has resulted in the presence of numerous hot springs. Additionally, it has been officially classified as a ‘hot spring city in China’ by the Chinese Ministry of Land and Resources. This study employed a semi-structured expert interview to investigate the barriers that stand in the way of applying inclusive governance to hot spring landscapes. Moreover, the interview investigates the implications of the lack of utilization of inclusive governance strategies for hot spring landscapes. The analysis of the results indicates that experts believed that the current protection policies were ineffective due to the existence of a multitude of barriers, such as the existence of deficiencies in the current policies, the multiplicity of management authorities, differences in visions in decision-making, limited public participation, a lack of awareness and trust from the public, a lack of balance in development approaches, and a limited role of science and technology. This resulted in a lack of proper communication and delegation of responsibilities with regard to inclusive governance strategies for protecting hot spring landscapes. Furthermore, the analysis unveiled diverse implications arising from the non-application of inclusive governance strategies, encompassing aspects such as tourism, economics, environment, sociocultural, and sustainability.
Aspects Regarding of Passive Filters Sustainability for Non-Linear Single-Phase Consumers
Authors: Diniș Corina Maria , Popa Gabriel Nicolae , Cunțan Corina Daniela , Iagăr Angela
Published: March 2024

The efficient use of electrical energy (an important component of sustainability) has become increasingly important for electrical consumers (industrial and non-industrial) as we face the challenges of climate change and the need to protect the environment. This theme is essential for guaranteeing a secure and sustainable future for both present and future generations. The power quality and the efficiency of electrical energy are connected to each other. Some power quality problems are caused by natural and unpredictable events, but many disturbances affecting power quality are caused by suppliers and consumers. One of the most important parameters in power engineering is the power factor, which indicates the degree of efficient use of electrical energy. Harmonics is the most important dynamic component of power quality, which affects the operation of electrical equipment and, at the same time, reduces the power factor. Harmonic sources in power systems are generally associated with nonlinear loads. To analyze the operating of passive filters (series L, shunt LC, T type LCL), two groups of experiments (relevant consumers were chosen for the industry as well as from the household sector) were carried out with single-phase nonlinear consumers: in the first group of experiments, a variable-frequency drive is used to supply a three-phase induction motor with variable load; in the second group of experiments, compact fluorescent lamps and LED lamps were used. Following the experiments, it was found that the difficulty of calibrating coils (to size a filter), especially the coils with a core, and the change in electrical properties over time for capacitors. For a certain type of consumer, the improvement of the current waveform depends on the type of filter used, the possibility of improving the power factor (to use electrical energy efficiently), and the role of the source impedance, which is particularly important to improve the efficiency of passive filters. Through the appropriate choice of the passive filter, a decrease in the deforming regime is obtained, with a slight decrease in the active power, and by increasing the power factor, a decrease in the losses of electrical energy from the electrical networks is obtained, with direct implications for the emission of greenhouse gases.
Sharing Is Caring: Exploring Distributed Solar Photovoltaics and Local Electricity Consumption through a Renewable Energy Community
Authors: Ferreira Evandro , Sequeira Miguel Macias , Gouveia João Pedro
Published: March 2024

Renewable Energy Communities (REC) can play a crucial role in enhancing citizen participation in the energy transition. Current European Union legislation enshrines energy communities and mandates Member States to encourage these organizations, promoting adequate conditions for their establishment. Nevertheless, uptake has been slow, and more research is needed to optimize the associated energy sharing. Using a Portuguese case study (REC Telheiras, Lisbon), this research aims to match local generation through four photovoltaic systems (totalizing 156.5 kWp of installed capacity) with household electricity consumption while cross evaluating the Portuguese legislation for energy sharing. The latter aim compares two scenarios: (a) current legislation (generated energy must be locally self-consumed before shared) and (b) equal share for members with a fixed coefficient. The evaluation is performed according to two indexes of self-consumption (SCI) and self-sufficiency (SSI), related to the simulation of four photovoltaic systems in public buildings, their associated consumption profiles, and an average household consumption profile of community members. The results show that, while maximizing self-consumption for the same values of generation and consumption, the number of participants is considerably lower for Scenario A (SCI = 100% is achieved with at least 491 residential members in Scenario A and 583 in Scenario B), implying that legislative changes enabling energy communities to better tailor sharing schemes may be necessary for them to become more attractive. The methods and results of this research can also be applied to other types of facilities, e.g., industrial and commercial consumers, if they are members of a REC and have smart meters in their installations.
Examining the Quadratic Impact of Sovereign Environmental, Social, and Governance Practices on Firms’ Profitability: New Insights from the Financial Industry in Gulf Cooperation Council Countries
Authors: Athari Seyed Alireza , Saliba Chafic , Abboud Elsa , El-Bayaa Nourhan
Published: March 2024

The present study particularly aims to probe the quadratic effects of the combined and individual sovereign environmental, social, and governance (ESG) activities on the banking sector’s profitability. Furthermore, we attempt to shed light on the channels through which sovereign ESG practices impact the banking sector’s profitability. Unlike the vast majority of prior works that investigated the sustainability practice–firms’ profitability nexus from the firm level, this study originally probes this relationship from the country level by considering the sovereign ESG sustainability activities. To attain this purpose, we focus on banking sectors operating in Gulf Cooperation Council (GCC) economies and employ the panel-fixed effects and panel-corrected standard errors approaches between 2000 and 2022. Remarkably, the findings uncover that the nexus between combined sovereign ESG and profitability is a non-linear and inversed U-shape (concave), implying that investing in sovereign ESG enhances the banking sector’s profitability. However, after exceeding an inflection point (0.349), its effect turns out to be negative and it develops into activities of destruction. Furthermore, the findings underscore that the association between individual sovereign environmental responsibility and the banking sector’s profitability is a non-linear U-shape (convex), while an inversed U-shaped (concave) nexus is uncovered for the individual sovereign social and governance activities. Moreover, the significant non-linear inverted U-shape for the combined sovereign ESG–stability nexus corroborates that financial stability is a channel through which sovereign ESG significantly impacts profitability.
Energy Performance Analysis of the Renovation Process in an Italian Cultural Heritage Building
Authors: Ziozas Nikolaos , Kitsopoulou Angeliki , Bellos Evangelos , Iliadis Petros , Gonidaki Dimitra , Angelakoglou Komninos , Nikolopoulos Nikolaos , Ricciuti Silvia , Viesi Diego
Published: March 2024

Renovating buildings with cultural heritage significance is an important step toward achieving sustainability in our cities. The benefits are not only energy-related but also encompass social aspects that make these renovations a high apriority. The present work investigates the renovation process of a cultural heritage building in the Municipality of Trento in Italy, specifically focusing on achieving energy savings and renewable energy integration by implementing various renovation actions. These renovation actions include improvements to the building envelope, such as roof insulation and window replacements. Additionally, the renovation actions for active systems involve the installation of a ground-source heat pump for heating/cooling coupled with a borehole thermal energy storage system, which is an innovative technology for the renovation of cultural heritage buildings. The electrical systems of the building are upgraded through the addition of standard rooftop photovoltaics, innovative building-integrated photovoltaics (shingles), and the installation of an LED lighting system. The baseline and the renovation scenarios are studied using the dynamic simulation tool INTEMA.building, written in the programming language Modelica. This tool simulates both the building envelope and the energy systems with a high level of detail, using advanced control systems and adjustable time steps. According to the simulation analysis, the primary energy demand is reduced by 30.49%, the final energy demand by 36.74%, and the net electricity demand by 8.72%. Results from this study can be useful to interested stakeholders (e.g., building owners, architects, construction companies, public agents, and urban planners) dealing with the renovation of cultural heritage and protected buildings. Also, the results can be exploited for estimating energy savings by applying advanced renovation strategies for cultural heritage buildings.
Multi-Attribute Decision-Making Method in Preventive Maintenance of Asphalt Pavement Based on Optimized Triangular Fuzzy Number
Authors: Xu Xunqian , Wang Siwen , Kang Fengyi , Li Shue , Li Qi , Wu Tao
Published: March 2024

By choosing the right pavement maintenance plan, we can reduce resource utilization, reduce environmental pollution, and extend road life, which is important for improving social sustainability. At present, the selection of road maintenance programs mostly adopts multiple attribute decision-making (MADA), in particular, the analytic hierarchy process (AHP) is often used. However, this method needs to use expert scoring data, which leads to strong subjectivity and poor reliability. Therefore, it reduces the science of road maintenance scheme selection. In order to reduce the subjectivity of the score and obtain a more suitable road maintenance scheme, this paper applies a multi-criteria decision-making method that characterizes attribute information by triangular fuzzy numbers (TFN) in the discrete decision space. Firstly, we invite experts to score the importance of the selection of pavement preventive maintenance technical solutions with respect to the indicators affecting the selection of solutions. Secondly, the two indicators of similarity and reliability are used to quantitatively evaluate the indicators and programs, respectively. Finally, we compare the weighted programs according to the overall possibility degree of each program. In actual cases, the overall possibility degree of each scheme obtained by this method is 1.0002–0.0477, and the optimal solution is fog sealing technology. The decision-making model applied in this paper can be considered in multiple dimensions, which can scientifically reduce the subjectivity of expert scoring. The best maintenance plan can also be quickly obtained through the simple calculation method in this paper.