bluuebunny/crossref_metadata_2025 huggingface dataset:
The Characterization of the Vertical Distribution of Surface Soil Moisture Using ISMN Multilayer In Situ Data and Their Comparison with SMOS and SMAP Soil Moisture Products
Authors: Yang Na , Xiang Feng , Zhang Hengjie
Published: August 2023

In this paper, we investigated the vertical distribution characteristics of surface soil moisture based on ISMN (International Soil Moisture Network) multilayer in situ data (5, 10, and 20 cm; 2, 4, and 8 in) and performed comparisons between the in situ data and four microwave satellite remote sensing products (SMOS L2, SMOS-IC, SMAP L2, and SMAP L4). The results showed that the mean soil moisture difference between layers can be −0.042~−0.024 (for the centimeter group)/−0.067~−0.044 (for the inch group) m3/m3 in negative terms and 0.020~0.028 (for the centimeter group)/0.036~0.040 (for the inch group) m3/m3 in positive terms. The surface soil moisture was found to have very significant stratification characteristics, and the interlayer difference was close to or beyond the SMOS and SMAP 0.04 m3/m3 nominal retrieval accuracy. Comparisons revealed that the satellite retrievals had a higher correlation with the field measurements of 5 cm/2 in, and SMAP L4 had the smallest difference with the in situ data. The mean difference caused by using 10 cm/4 in and 20 cm/8 in in situ data instead of the 5 cm/2 in data could be about −0.019~−0.018/−0.18~−0.015 m3/m3 and −0.026~−0.023/−0.043~−0.039 m3/m3, respectively, meaning that there would be a potential depth mismatch in the data validation.
Evaluation of Atmospheric Phase Correction Performance in 79 GHz Ground-Based Radar Interferometry: A Comparison with 17 GHz Ground-Based SAR Data
Authors: Izumi Yuta , Sato Motoyuki
Published: August 2023

Ground-based radar interferometry is capable of measuring target displacement to sub-mm accuracy. W-band ground-based radar has recently been investigated as a potential application for structural health monitoring. On the other hand, the application of W-band ground-based radar for natural slope monitoring is considered in this study due to its advantages in portability and recent cost-effective solutions. In radar interferometry, atmospheric phase screen (APS) is the most relevant phase disturbance that should be corrected for accurate displacement measurement. However, the APS effects in W-band radar interferometry have rarely been discussed. In this context, we study and evaluate the impacts of APS and its potential correction methods for 79 GHz ground-based radar interferometry using multiple-input and multiple-output (MIMO) radar. This paper presents an experimental investigation of a 79 GHz radar system using two types of field experiments conducted in an open flat field and a quarry site. In addition to the W-band radar system, a Ku-band (17 GHz) ground-based synthetic aperture radar (GB-SAR) system was jointly tested to compare different operating frequency bands. The result confirmed the accurate displacement estimation capability of the 79 GHz radar with an appropriate APS correction.
Color-Coated Steel Sheet Roof Building Extraction from External Environment of High-Speed Rail Based on High-Resolution Remote Sensing Images
Authors: Li Yingjie , Jin Weiqi , Qiu Su , Zuo Dongsheng , Liu Jun
Published: August 2023

The identification of color-coated steel sheet (CCSS) roof buildings in the external environment is of great significance for the operational security of high-speed rail systems. While high-resolution remote sensing images offer an efficient approach to identify CCSS roof buildings, achieving accurate extraction is challenging due to the complex background in remote sensing images and the extensive scale range of CCSS roof buildings. This research introduces the deformation-aware feature enhancement and alignment network (DFEANet) to address these challenges. DFEANet adaptively adjusts the receptive field to effectively separate the foreground and background facilitated by the deformation-aware feature enhancement module (DFEM). Additionally, feature alignment and gated fusion module (FAGM) is proposed to refine boundaries and preserve structural details, which can ameliorate the misalignment between adjacent features and suppress redundant information during the fusion process. Experimental results on remote sensing images along the Beijing–Zhangjiakou high-speed railway demonstrate the effectiveness of DFEANet. Ablation studies further underscore the enhancement in extraction accuracy due to the proposed modules. Overall, the DFEANet was verified as capable of assisting in the external environment security of high-speed rails.
Analysis of the Correlation between Frontal Alpha Asymmetry of Electroencephalography and Short-Term Subjective Well-Being Changes
Authors: Wutzl Betty , Leibnitz Kenji , Kominami Daichi , Ohsita Yuichi , Kaihotsu Michiko , Murata Masayuki
Published: August 2023

Subjective well-being (SWB) describes how well people experience and evaluate their current condition. Previous studies with electroencephalography (EEG) have shown that SWB can be related to frontal alpha asymmetry (FAA). While those studies only considered a single SWB score for each experimental session, our goal is to investigate such a correlation for individuals with a possibly different SWB every 60 or 30 s. Therefore, we conducted two experiments with 30 participants each. We used different temperature and humidity settings and asked the participants to periodically rate their SWB. We computed the FAA from EEG over different time intervals and associated the given SWB, leading to pairs of (FAA, SWB) values. After correcting the imbalance in the data with the Synthetic Minority Over-sampling Technique (SMOTE), we performed a linear regression and found a positive linear correlation between FAA and SWB. We also studied the best time interval sizes for determining FAA around each SWB score. We found that using an interval of 10 s before recording the SWB score yields the best results.
Crop Mapping Based on Sentinel-2 Images Using Semantic Segmentation Model of Attention Mechanism
Authors: Gao Meixiang , Lu Tingyu , Wang Lei
Published: August 2023

Using remote sensing images to identify crop plots and estimate crop planting area is an important part of agricultural remote sensing monitoring. High-resolution remote sensing images can provide rich information regarding texture, tone, shape, and spectrum of ground objects. With the advancement of sensor and information technologies, it is now possible to categorize crops with pinpoint accuracy. This study defines crop mapping as a semantic segmentation problem; therefore, a deep learning method is proposed to identify the distribution of corn and soybean using the differences in the spatial and spectral features of crops. The study area is located in the southwest of the Great Lakes in the United States, where corn and soybean cultivation is concentrated. The proposed attention mechanism deep learning model, A2SegNet, was trained and evaluated using three years of Sentinel-2 data, collected between 2019 and 2021. The experimental results show that this method is able to fully extract the spatial and spectral characteristics of crops, and its classification effect is significantly better than that of the baseline method, and it has better classification performance than other deep learning models. We cross verified the trained model on the test sets of different years through transfer learning in both spatiotemporal and spatial dimensions. Proving the effectiveness of the attention mechanism in the process of knowledge transfer, A2SegNet showed better adaptability.
Frequency-Selective Surface-Based MIMO Antenna Array for 5G Millimeter-Wave Applications
Authors: Ud Din Iftikhar , Alibakhshikenari Mohammad , Virdee Bal S. , Jayanthi Renu Karthick Rajaguru , Ullah Sadiq , Khan Salahuddin , See Chan Hwang , Golunski Lukasz , Koziel Slawomir
Published: August 2023

In this paper, a radiating element consisting of a modified circular patch is proposed for MIMO arrays for 5G millimeter-wave applications. The radiating elements in the proposed 2 × 2 MIMO antenna array are orthogonally configured relative to each other to mitigate mutual coupling that would otherwise degrade the performance of the MIMO system. The MIMO array was fabricated on Rogers RT/Duroid high-frequency substrate with a dielectric constant of 2.2, a thickness of 0.8 mm, and a loss tangent of 0.0009. The individual antenna in the array has a measured impedance bandwidth of 1.6 GHz from 27.25 to 28.85 GHz for S11 ≤ −10 dB, and the MIMO array has a gain of 7.2 dBi at 28 GHz with inter radiator isolation greater than 26 dB. The gain of the MIMO array was increased by introducing frequency-selective surface (FSS) consisting of 7 × 7 array of unit cells comprising rectangular C-shaped resonators, with one embedded inside the other with a central crisscross slotted patch. With the FSS, the gain of the MIMO array increased to 8.6 dBi at 28 GHz. The radiation from the array is directional and perpendicular to the plain of the MIMO array. Owing to the low coupling between the radiating elements in the MIMO array, its Envelope Correlation Coefficient (ECC) is less than 0.002, and its diversity gain (DG) is better than 9.99 dB in the 5G operating band centered at 28 GHz between 26.5 GHz and 29.5 GHz.
Railway Track Fault Detection Using Selective MFCC Features from Acoustic Data
Authors: Rustam Furqan , Ishaq Abid , Hashmi Muhammad Shadab Alam , Siddiqui Hafeez Ur Rehman , López Luis Alonso Dzul , Galán Juan Castanedo , Ashraf Imran
Published: August 2023

Railway track faults may lead to railway accidents and cause human and financial loss. Spatial, temporal, and weather elements, and wear and tear, lead to ballast, loose nuts, misalignment, and cracks leading to accidents. Manual inspection of such defects is time-consuming and prone to errors. Automatic inspection provides a fast, reliable, and unbiased solution. However, highly accurate fault detection is challenging due to the lack of public datasets, noisy data, inefficient models, etc. To obtain better performance, this study presents a novel approach that relies on mel frequency cepstral coefficient features from acoustic data. The primary objective of this study is to increase fault detection performance. As well as designing an ensemble model, we utilize selective features using chi-square(chi2) that have high importance with respect to the target class. Extensive experiments were carried out to analyze the efficiency of the proposed approach. The experimental results suggest that using 60 features, 40 original features, and 20 chi2 features produces optimal results both regarding accuracy and computational complexity. A mean accuracy score of 0.99 was obtained using the proposed approach with machine learning models using the collected data. Moreover, this performance was significantly better than that of existing approaches; however, the performance of models may vary in real-world settings.
Label-Free DNA Detection Using Etched Tilted Bragg Fiber Grating-Based Biosensor
Authors: Noman Abdullah Al , Dash Jitendra Narayan , Maruf Md Abdullah Al , Xin Cheng , Tam Hwa-Yam , Yu Changyuan
Published: August 2023

A label-free-based fiber optic biosensor based on etched tilted Bragg fiber grating (TFBG) is proposed and practically demonstrated. Conventional phase mask technic has been utilized to inscribe tilted fiber Bragg grating with a tilt angle of 10°, while the etching has been accomplished with hydrofluoric acid. A composite of polyethylenimine (PEI)/poly(acrylic acid) (PAA) has been thermally deposited on the etched TFBG, followed by immobilization of probe DNA (pDNA) on this deposited layer. The hybridization of pDNA with the complementary DNA (cDNA) has been monitored using wavelength-dependent interrogation. The reproducibility of the probes has been demonstrated by fabricating three identical probes and their response has been investigated for cDNA concentration ranging from 0 μM to 3 μM. The maximum sensitivity has been found to be 320 pm/μM, with the detection limit being 0.65 μM. Furthermore, the response of the probes towards non-cDNA has also been investigated in order to establish its specificity.
Power Transformers OLTC Condition Monitoring Based on Feature Extraction from Vibro-Acoustic Signals: Main Peaks and Euclidean Distance
Authors: Dabaghi-Zarandi Fataneh , Behjat Vahid , Gauvin Michel , Picher Patrick , Ezzaidi Hassan , Fofana Issouf
Published: August 2023

The detection of On-Load Tap-Changer (OLTC) faults at an early stage plays a significant role in the maintenance of power transformers, which is the most strategic component of the power network substations. Among the OLTC fault detection methods, vibro-acoustic signal analysis is known as a performant approach with the ability to detect many faults of different types. Extracting the characteristic features from the measured vibro-acoustic signal envelopes is a promising approach to precisely diagnose OLTC faults. The present research work is focused on developing a methodology to detect, locate, and track changes in on-line monitored vibro-acoustic signal envelopes based on the main peaks extraction and Euclidean distance analysis. OLTC monitoring systems have been installed on power transformers in services which allowed the recording of a rich dataset of vibro-acoustic signal envelopes in real time. The proposed approach was applied on six different datasets and a detailed analysis is reported. The results demonstrate the capability of the proposed approach in recognizing, following, and localizing the faults that cause changes in the vibro-acoustic signal envelopes over time.
Shot Boundary Detection with 3D Depthwise Convolutions and Visual Attention
Authors: Esteve Brotons Miguel Jose , Lucendo Francisco Javier , Javier Rodriguez-Juan , Garcia-Rodriguez Jose
Published: August 2023

Shot boundary detection is the process of identifying and locating the boundaries between individual shots in a video sequence. A shot is a continuous sequence of frames that are captured by a single camera, without any cuts or edits. Recent investigations have shown the effectiveness of the use of 3D convolutional networks to solve this task due to its high capacity to extract spatiotemporal features of the video and determine in which frame a transition or shot change occurs. When this task is used as part of a scene segmentation use case with the aim of improving the experience of viewing content from streaming platforms, the speed of segmentation is very important for live and near-live use cases such as start-over. The problem with models based on 3D convolutions is the large number of parameters that they entail. Standard 3D convolutions impose much higher CPU and memory requirements than do the same 2D operations. In this paper, we rely on depthwise separable convolutions to address the problem but with a scheme that significantly reduces the number of parameters. To compensate for the slight loss of performance, we analyze and propose the use of visual self-attention as a mechanism of improvement.
A Novel Decoupled Feature Pyramid Networks for Multi-Target Ship Detection
Authors: Xue Wentao , He Maozheng , Zhang Yincheng , Ye Hui
Published: August 2023

The efficiency and accuracy of ship detection is of great significance to ship safety, harbor management, and ocean surveillance in coastal harbors. The main limitations of current ship detection methods lie in the complexity of application scenarios, the difficulty in diverse scales object detection, and the low efficiency of network training. In order to solve these problems, a novel multi-target ship detection method based on a decoupled feature pyramid algorithm (DFPN) is proposed in this paper. First, a feature decoupling module is introduced to separate ship contour features and position features from the multi-scale fused features, to overcome the problem of similar features in multi-target ships. Second, a feature pyramid structure combined with a gating attention module is constructed to improve the feature resolution of small ships by enhancing contour features and spatial semantic information. Finally, a feature pyramid-based multi-feature fusion algorithm is proposed to improve the adaptability of the network to changes in ship scale according to the contextual relationship of ship features. Experiments on the multi-target ship detection dataset showed that the proposed method increased by 6.3% mAP and 20 FPS higher than YOLOv4, 7.6% mAP and 36 FPS higher than Faster-R-CNN, 5% mAP and 36 FPS higher than Mask-R-CNN, and 4.1% mAP and 35 FPS higher than DetectoRS. The results demonstrate that the DFPN can detect multi-target ships in different scenes with high accuracy and a fast detection speed.
Performance Analysis of IRS-Assisted THz Communication Systems over α-μ Fading Channels with Pointing Errors
Authors: Alvi Sajid Hussain , Ali Bakhtiar , Mirza Jawad , Javed Muhammad Awais , Fida Adnan , Lee Byung Moo , Bashir Tariq
Published: August 2023

In this paper, we analyze the performance of an intelligent reflecting surface (IRS)-aided terahertz (THz) wireless communication system with pointing errors. Specifically, we derive closed-form analytical expressions for the upper bounded ergodic capacity and approximate expression of the outage probability. We adopt an α-μ fading channel model for our analysis that is experimentally demonstrated to be a good fit for THz small-scale fading statistics, especially in indoor communication scenarios. In the proposed analysis, the statistical distribution of the α-μ fading channel is used to derive analytical expressions for the ergodic capacity and outage probability. Our proposed analysis considers not only the IRS reflected channels, but also the direct channel between the communication nodes. The results of the derived analytical expressions are validated through Monte Carlo simulations. Through simulations, it has been noticed that pointing errors degrade the performance of the IRS-assisted THz wireless communication system which can be compensated by deploying an IRS having a large number of reflecting elements.
Triangle-Mesh-Rasterization-Projection (TMRP): An Algorithm to Project a Point Cloud onto a Consistent, Dense and Accurate 2D Raster Image
Authors: Junger Christina , Buch Benjamin , Notni Gunther
Published: August 2023

The projection of a point cloud onto a 2D camera image is relevant in the case of various image analysis and enhancement tasks, e.g., (i) in multimodal image processing for data fusion, (ii) in robotic applications and in scene analysis, and (iii) for deep neural networks to generate real datasets with ground truth. The challenges of the current single-shot projection methods, such as simple state-of-the-art projection, conventional, polygon, and deep learning-based upsampling methods or closed source SDK functions of low-cost depth cameras, have been identified. We developed a new way to project point clouds onto a dense, accurate 2D raster image, called Triangle-Mesh-Rasterization-Projection (TMRP). The only gaps that the 2D image still contains with our method are valid gaps that result from the physical limits of the capturing cameras. Dense accuracy is achieved by simultaneously using the 2D neighborhood information (rx,ry) of the 3D coordinates in addition to the points P(X,Y,V). In this way, a fast triangulation interpolation can be performed. The interpolation weights are determined using sub-triangles. Compared to single-shot methods, our algorithm is able to solve the following challenges. This means that: (1) no false gaps or false neighborhoods are generated, (2) the density is XYZ independent, and (3) ambiguities are eliminated. Our TMRP method is also open source, freely available on GitHub, and can be applied to almost any sensor or modality. We also demonstrate the usefulness of our method with four use cases by using the KITTI-2012 dataset or sensors with different modalities. Our goal is to improve recognition tasks and processing optimization in the perception of transparent objects for robotic manufacturing processes.
Green Cities: Utopia or Reality? Evidence from Zurich, Switzerland
Authors: Perić Ana , Jiang Yingying , Menz Sacha , Ricci Liana
Published: August 2023

There is an overall scientific consensus that green spaces positively affect urban dwellers’ health and well-being. However, there is a gap between knowledge and policy objectives, and their translation into effective interventions to unleash the benefits of green spaces. Examining such ‘implementation gap’ in Zurich is relevant due to the integration of the ‘green urban agenda’ in various Swiss policies. The research narrows its focus to district 9, including the Altstetten and Albisrieden neighborhoods, which contain diverse green spaces despite ongoing densification. The study further explores four green space clusters and their 400-m catchment areas within the district. The research applies a mixed-method approach at three analytical levels: (1) identification of the critical tenets associated with the ‘green urban agenda’ through a review of multi-scale national policies, (2) assessment of green spaces’ provision, types, size, and mutual connectivity in Zurich’s district 9 based on online available quantitative data and on-site observation, and (3) identification of the dominant activities in four green space clusters through on-site observation. Through critical mutual examination of the identified ‘green urban agenda’ principles in the national policies and green space attributes, the findings reveal the extent of the convergence or divergence between policy trends and their implementation in practice.
Unveiling High-Tech Metals in Roasted Pyrite Wastes from the Iberian Pyrite Belt, SW Spain
Authors: Yesares Lola , González-Jiménez José María , Jiménez-Cantizano Francisco Abel , González-Pérez Igor , Caro-Moreno David , Sánchez Isabel María
Published: August 2023

The Iberian Pyrite Belt (IPB), in the southwestern Iberian Peninsula, is a large metallogenic province exploited since ancient times. As a result of historical and current mining activity, a vast volume of metallic mineral waste, mainly derived from the processing of pyrite, is still in situ and polluting the environment. A specific mine waste residuum locally known in the area as “morrongos”, which was produced during pyrite roasting mainly in the 19th century, is evaluated here in order to unravel untapped resources of high-tech metals commonly used in high-tech devices. Applying a combination of whole-rock geochemical (ICP-AES, ICPMS, FA-AAS) and single-grain mineralogical techniques (EPMA, LA-ICP-MS, FESEM, and FIB-HRTEM) on the “morrongos”, we unhide the still-present remarkable concentrations of Au, Ag, Pb, Zn, and Cu in them. The mineralogical expressions for these economic metals include oxides (hematite, magnetite, and hercynite), arsenates, sulfates of the jarosite group, native metals, and, to a lesser extent, relictic sulfides. This first-ever estimation of these economic metals in this type of residue allows their revalorization, highlighting them as suitable sources for the exploitation and recovery of metals necessary for the clean energy transition.
Quantitative Distribution and Contamination Risk Assessment of Cu and Zn in Municipal Sewage Sludge
Authors: Jakubus Monika
Published: August 2023

One of the methods of managing sewage sludge (SS) is its soil application. This possibility is promoted by the chemical composition rich in organic matter and nutrients. However, heavy metal contents in SS must meet respective permissible limits. Among the heavy metals in SS, Cu and Zn are found in the largest amount; thus, this study focuses on these elements. The main aim of the study is to investigate the quantitative distribution of metals in sequentially separated fractions of sewage sludge. Additionally, the potential risk of environmental contamination with heavy metals was assessed in the case of SS application for agricultural purposes. The relevant analyses were conducted on four different examples of municipal SS. Based on the total amounts as well as those determined in the SS fractions, the following indices were calculated: Igeo (geoaccumulation index), ICF, (individual contamination factor), and RAC (risk assessment code). The use of data from the sequential analysis as well as the calculated indices made it possible to assess the usefulness of SS in practice in terms of potential introduction of Cu and Zn into the environment with the sludge dose. It was found that total Cu (Cutot) and Zn (Zntot) did not exceed the permissible limits binding within respective Polish and international regulations. Regardless of the years of study and the analyzed SS, Cutot ranged from 260.9 to 393.5 mg·kg−1, and Zntot from 475.5 to 1153.1 mg·kg−1. The amounts of Cu and Zn were predominantly reducible (bound to iron and manganese hydroxides, Fr. II) and oxidizable complexes (bound to organic matter and sulfides, Fr. III). The average amounts of Cu in Fr. II ranged from 149.4 to 172.4 mg·kg−1, while those of Zn in Fr. II ranged from 370.9 to 754.6 mg·kg−1. Cu amounts in Fr. III were from 160.9 to 183 mg·kg−1 and Zn amounts in Fr. III were from 104.9 to 171.9 mg·kg−1. Total content of metals as well as TOC values strongly determined the quantitative level of both elements in the SS fractions. Generally, with the increase in the total amount of metals, their levels in the sludge fractions increased. In turn, the increase in TOC resulted in a decrease in the amounts of Cu and Zn in the sludge fractions. Calculated Igeo and ICF ratios showed high and very high SS contamination with Cu and Zn. Igeo values for Cu, regardless of the year of study and sludge sample, that ranged from 4.62 to 5.43 and for Zn from 3.41 to 4.86. At the same time, the ICF values for Cu ranged from 8.59–23.04, and for Zn 15.42–44.47. The RAC values indicated a low (Cu) and medium (Zn) risk of using SS in terms of the potential metal availability in the environment. The RAC values ranged from 1.46 to 4.40% for Cu and from 9.63 to 23.13% for Zn.
A Circular Economy Approach in the Development of Superabsorbent Polymeric Matrices: Evaluation of the Mineral Retention
Authors: Álvarez-Castillo Estefanía , Oliveira Sonia , Bengoechea Carlos , Sousa Isabel , Raymundo Anabela , Guerrero Antonio
Published: August 2023

This manuscript focuses on the production of polymeric matrices enriched in minerals and antioxidant compounds. The biopolymers employed are obtained from different by-products of the agro-food industry (porcine plasma protein, pea protein concentrate and soy protein isolate), which helps to revalorize them. Two different manufacturing techniques are employed to produce these matrices: 3D-printing and injection molding. Bioactivity was enhanced through immersion of the samples in magnesium glutamate and iron lactate solutions. To incorporate these minerals and bioactive compounds into the matrices, two additional stages are required: (1) an immersion stage in a mineral/bioactive containing solution, which allows simultaneous removal of the glycerol employed as plasticizer and entrapment of the minerals and bioactive compounds; and (2) a subsequent freeze-drying stage. Matrices produced through these manufacturing processes were assessed through water uptake capacity, mineral analysis, bioactivity and color measurements. The studied matrices have great potential in the food industry, as the threshold for claiming a significant mineral content was reached after the immersion stage. The presence of bioactive compounds could avoid the degradation of these matrices when food processing includes stages at relatively high temperatures.
The Role of Agroforestry in Poverty Alleviation: A Case Study from Nujiang Prefecture, Southwestern China
Authors: Dou Yaquan , Li Ya , Li Ming , Chen Xingliang , Zhao Xiaodi
Published: August 2023

Agroforestry has gained increasing attention as a sustainable land use mode to ensure food security, mitigate global climate change, and improve farmers’ livelihoods. Likewise, agroforestry plays a key role in alleviating poverty, mitigating climate change and achieving the Sustainable Development Goals (SDGs) in China. Lanxangia tsaoko, as a typical agroforestry species in Nujiang Prefecture, plays a vital role in improving farmers’ livelihoods. After years of development, the Lanxangia tsaoko industry (LTI) in Nujiang Prefecture has made remarkable achievements and accumulated useful experiences. Taking the development of LTI as an example, this paper analyzes the impact of agroforestry on farmers’ livelihoods and its mechanism through field survey and theoretical deduction. First, by investigating the willingness of households to choose LTI, we found that most farmers have a positive attitude toward LTI, and they actively participate in cooperative organizations. Then, by analyzing the development stage and mode of LTI in Nujiang Prefecture, we found that the industry has made significant progress under the external and internal effects. We also found that the mechanism by which agroforestry affects farmers’ livelihoods is a process in which various stakeholders, including government, enterprises, farmers, etc., participate in industrial development with their production components and advantages. Although agroforestry is an effective way to improve farmers’ livelihoods and promote sustainable agricultural development, it is also necessary to pay attention to risk prevention. This paper discusses the role of agroforestry in farmers’ livelihoods, which provides a reference for lower-income forest areas.
The Classification Impact of Different Types of Environmental Regulation on Chinese Provincial Carbon Emission Efficiency
Authors: Ye Feifei , You Rongyan , Lu Haitian , Han Sirui , Yang Long-Hao
Published: August 2023

The evaluation of inter-provincial carbon emission efficiency and the analysis of its influencing factors hold great practical significance for reducing carbon emissions and promoting sustainable development in ecological management. To address the shortcomings of existing research in the classification evaluation of carbon emission efficiency and account for the impacts of different environmental regulatory policies on carbon emissions, this paper aims to examine the impact of formal and informal environmental regulations on carbon emission efficiency. This is accomplished by utilizing a combination of the data envelopment analysis (DEA) model, entropy weighting, and k-means cluster analysis methods. The fixed-effects model is also applied to examine the influences of different factors on carbon emission efficiency under different categories. To conduct the case studies, carbon emission management data from 30 provinces in China are collected, and the results show the following: (1) Formal environmental regulations exhibit a “U-shaped” relationship with carbon emission efficiency, whereas informal environmental regulations have an “inverted U-shaped” relationship with carbon emission efficiency. (2) Under the cluster analysis of carbon emission efficiency, formal environmental regulations are found to have a stronger incentive effect on inter-provincial carbon efficiency compared to informal environmental regulations. This study carries significant theoretical and practical implications for China’s timely attainment of its double-carbon target.
A Comprehensive Evaluation of Vehicle Intelligent Barrier Avoidance Function under Special Roads Based on G1-CRITIC
Authors: Zhang Xuewen , Zhan Qi , Zhou Wei , Liu Zhichao
Published: August 2023

As one of the core functions of the autonomous driving of vehicles under special roads, the intelligent barrier avoidance function plays an important role in improving traffic efficiency and ensuring driving safety. Scientific, reasonable, and comprehensive evaluation methods can provide the basis for intelligent vehicles before their use. The comprehensive evaluation index system is constructed for the avoidance ability and avoidance mode of intelligent vehicles against different barriers. The weights of qualitative indicators that are difficult to quantify are determined based on the order relation analysis (G1) method, and the weights of quantitative indicators are determined based on the CRITIC (criteria importance though intercriteria correlation) method. The overall system is comprehensively and quantitatively evaluated through the grey correlation degree method. The correctness of the evaluation method is verified via testing. According to the comprehensive evaluation method studied, the comprehensive evaluation result of the test vehicle is obtained. The intelligent barrier avoidance function of negative barriers is superior to that of positive barriers. The integrated evaluation method can obtain evaluation results of vehicle performance in different test scenarios.
Optimal Green Input Level for a Capital-Constrained Supply Chain Considering Disruption Risk
Authors: Cheng Junheng , Hong Weiyi , Cheng Jingya
Published: August 2023

Under increasingly stringent environmental regulations, inadequate green input levels from manufacturers may lead to substandard emissions and production shutdown, which further results in the disruption risk of the supply chain. This work investigates a green supply chain (GSC) consisting of one environmentally regulated manufacturer and one capital-constrained retailer who faces stochastic market demand. The manufacturer needs to make decisions on the green input level, which is related to the investment cost as well as supply disruption risk. The retailer has to determine product order quantities and financing decisions. We derive the operational equilibriums for the GSC system under three scenarios: no financing, trade credit financing (TCF), and bank credit financing (BCF), and recommend the optimal financial selection for the retailer via the comparison of three financial modes. The analytical and numerical results reveal that the manufacturer should improve the green input level within the financial capability to enhance the sustainable operation level of the supply chain. In addition, we find that the capital-constrained retailer will choose financing, since either BCF or TCF will result in a higher profit than no financing. Moreover, we obtain the threshold of green input level, with which we can decide whether to choose TCF or BCF under the given corresponding parameters.
Optimal Energy Consumption Path Planning for Unmanned Aerial Vehicles Based on Improved Particle Swarm Optimization
Authors: Na Yiwei , Li Yulong , Chen Danqiang , Yao Yongming , Li Tianyu , Liu Huiying , Wang Kuankuan
Published: August 2023

In order to enhance the energy efficiency of unmanned aerial vehicles (UAVs) during flight operations in mountainous terrain, this research paper proposes an improved particle swarm optimization (PSO) algorithm-based optimal energy path planning method, which effectively reduces the non-essential energy consumption of UAV during the flight operations through a reasonable path planning method. First, this research designs a 3D path planning method based on the PSO optimization algorithm with the goal of achieving optimal energy consumption during UAV flight operations. Then, to overcome the limitations of the classical PSO algorithm, such as poor global search capability and susceptibility to local optimality, a parameter adaptive method based on deep deterministic policy gradient (DDPG) is introduced. This parameter adaptive method dynamically adjusts the main parameters of the PSO algorithm by monitoring the state of the particle swarm solution set. Finally, the improved PSO algorithm based on parameter adaptive improvement is applied to path planning in mountainous terrain environments, and an optimal energy-consuming path-planning algorithm for UAVs based on the improved PSO algorithm is proposed. Simulation results show that the path-planning algorithm proposed in this research effectively reduces non-essential energy consumption during UAV flight operations, especially in more complex terrain scenarios.
Spatio-Temporal Evolution of Ecological Sensitivity in the Desert of China from 1981 to 2022
Authors: Song Chunwei , Teni Geer , Du Huishi
Published: August 2023

The northern desert of China plays an important strategic role in land resource security and national economic development. Research on the spatio-temporal changes of ecological sensitivity can provide a scientific reference for desert management and ecological restoration in arid and semi-arid areas in northern China. This paper takes the northern desert of China as the research area, uses the spatial distance model to build a comprehensive ecological sensitivity evaluation index system, and discusses the spatio-temporal evolution characteristics of ecological sensitivity in the area from 1981 to 2022. The results show the following: (1) The land use types in the northern desert of China are mainly sandy land, grassland and other lands. The changing areas of grassland and other lands are 74,353.14 km2 and 50,807.97 km2, which is an important factor affecting the ecological sensitivity in the northern desert of China. (2) Five aspects, including terrain, climate, hydrology, soil and vegetation, influence and restrict each other, and jointly create the background conditions for the distribution and change of ecological sensitivity in the northern desert of China. Climate and terrain are the most important influencing factors affecting the ecological sensitivity of northern desert of China. Vegetation is the most active and basic factor affecting the ecological sensitivity of northern desert of China. Hydrology and soil have a certain limiting effect on the ecological sensitivity of northern desert of China. (3) The spatial heterogeneity of ecological sensitivity in the northern desert of China is significant, showing the characteristics of high volatility in the west, low volatility in the central region and low volatility in the east. (4) For nearly 42 years, ecological sensitivity of the northern desert of China shows first increasing and then decreasing characteristics. The area of the fluctuation reduction zone accounts for 26.34% of the total research area, of which the area of extreme sensitivity and mild sensitivity varies by 11.84% and 65.28%, respectively. (5) The spatial aggregation characteristics of ecological sensitivity have changed significantly, and the area of high–high and low–low agglomeration areas has also been decreasing, indicating that the environment is obviously improving. In the future, we should pay attention to the efficient use of natural resources in the northern desert of China and strengthen the protection of all kinds of land to achieve the sustainable development of the regional environment.
Evaluation Model of Urban Resilience in the Face of Public Health Emergencies: A Case Study of Xi’an
Authors: Liu Yifan , Li Xunchang , Yang Wei , Xu Rui , Qi Yuang
Published: August 2023

In recent years, there have been frequent outbreaks of public health emergencies worldwide, especially resulting from the COVID-19 pandemic, which has seriously affected social and economic development and people’s production and life. In order to avoid or minimize the harm caused by these emergencies to society and the public, this article constructs a resilience indicator system for urban emergency response capabilities based on resistance, adaptation, and recovery. We establish a dynamic model of urban emergency response resilience, select the infectious disease dynamics method as the index weight calculation method, analyze the correlations among various indicators and parameters of the urban emergency response resilience system, and conduct sensitivity analysis on the model parameters to determine the importance sequence of each model parameter. Combined with the fuzzy hierarchy analysis method, we evaluate the model and use the 2021 year-end epidemic in Xi’an as an example to evaluate the urban emergency response resilience level using the evaluation model. According to the maximum membership degree principle, the results show that the emergency resilience levels of Xi’an were “moderately strong”, “moderately strong”, and “strong” in the first, second, and third stages of the epidemic, respectively. The results demonstrate that the method proposed in this article can objectively reflect the current level of urban emergency resilience and provide some references and guidance for improving the resilience of urban emergency response to public health emergencies.
Implementing the Integrated Social Sustainability Assessment to Norway: A Citizen-Centric and Expert-Weighted Approach
Authors: Akbarinejad Tahmineh , Salaj Alenka Temeljotov , Johansen Agnar
Published: August 2023

To achieve sustainability, more economic and environmental initiatives, projects, and policies must have a positive impact on society, advance social justice, and enhance the general well-being of people and communities. This study proposes a quantitative and qualitative framework to assess social sustainability in different urban regions. A multi-category approach is used to determine what categories and indicators of social sustainability city governments and academia should consider to ensure that their policies and projects align with community values. The next step involves assessing residents’ satisfaction through citizen participation. This framework, entitled the “Integrated Social Sustainability Assessment (ISSA)”, was applied in three zones of the Furuset area in Oslo. The results of the three diagrams show how community strengths and weaknesses can be identified, allowing projects to be prioritized in a way that benefits citizens in the long term and provides a comparative score. This framework provides policymakers with useful tools and guidelines for creating policies and projects that are sustainable, equitable, and capable of meeting the needs of their communities in a measurable manner.
A Study on the Impact of Fiscal Decentralization on Regional Green Development: A Perspective Based on the Emphasis on Sports
Authors: Liu Jianan , Dai Ni , Sui Yuan , Yaqoubi Asmatullah
Published: August 2023

From the perspective of institutional economics, we investigate the impact of fiscal decentralization on regional green development in China and its transmission mechanism through influencing sports fiscal expenditures on regional green development. Based on panel data of Chinese provincial regions from 2006 to 2017 in China, we use fixed effects models, two-stage least squares, and mediating effects models to find that fiscal decentralization accelerates regional green sustainability. Fiscal decentralization can enhance the government’s emphasis on sports and promote the smart and intelligent development of the sports and health industry, thus contributing to the improvement of green and sustainable development. There is regional heterogeneity in the effect of the governmental emphasis on sports, and the mediating effect of the degree of emphasis on sports is more obvious in the eastern region. We verify the possibility that the government can accelerate economic green sustainability by raising the importance of the sports and health industry development and promoting the intelligent infrastructure of sports and enrich the theoretical study of the ecological effect of fiscal decentralization from the perspective of sports economic development.
Innovation-Led Environmental Sustainability in Vietnam—Towards a Green Future
Authors: Li Qianyi , Qamruzzaman Md
Published: August 2023

The motivation of the study is to assess the role of education, technological innovation, financial innovation, and clean energy consumption trade openness on environmental sustainability in Vietnam. The study implemented symmetric and asymmetric frameworks to document explanatory variables’ coefficients on ES. Study findings suggest that education, innovation, and clean energy prompt environmental sustainability by lowering the carbon emission and ecological imbalance in the long and short run. Regarding the asymmetric assessment, the standard Wald test confirmed the asymmetric association in the long run and short run. For directional causality, the study implemented the TY–Fourier causality test. It revealed bidirectional causality between technological innovation and environmental sustainability. In contrast, unidirectional causality ran from education to ES and FDI to ES. Policy recommendations have been derived from the empirical findings of both symmetric and asymmetric investigations. These recommendations highlight the importance of prioritizing investments in education and technological innovation to enhance environmental sustainability. Moreover, promoting clean energy technologies and encouraging financial innovations can serve as additional catalysts for advancing sustainable practices. The implications of the policy as mentioned above offers valuable insights for policymakers and stakeholders in their endeavor to develop strategies to achieve environmental sustainability in Vietnam. While the findings contribute to our understanding of the determinants of ES in Vietnam, it is important to note that the study’s scope is limited to the examined determinants. Other factors not included in the study may also have a significant role.
Development of Alternative Protein Sources in Terms of a Sustainable System
Authors: Sobczak Paweł , Grochowicz Józef , Łusiak Patrycja , Żukiewicz-Sobczak Wioletta
Published: August 2023

Epidemiological studies of the population, changing dietary trends and climate change are the main factors influencing consumer choices. Although food overproduction and overconsumption are observed in the world, the proper nutrition of the population poses a problem. Despite satisfying bodily needs in terms of energy requirements, it is becoming increasingly difficult to balance diets with essential ingredients, such as protein. Traditional sources of proteins, due to changing dietary trends, are no longer attractive to consumers. Hence, global research is shifting towards alternative sources of protein. Therefore, this study aims to identify alternative sources of food protein from the perspective of the transformation of the food market. Scientific research, using innovative technologies, is targeting the previously underestimated sources of alternative raw materials and products, whose biological activity often astonishes the researchers themselves.
Loose Belt Fault Detection and Virtual Flow Meter Development Using Identified Data-driven Energy Model for Fan Systems
Authors: Wang Gang , Wang Junke , Tiamiyu Nurayn , Wang Zufen , Song Li
Published: August 2023

An energy model that correlates fan airflow, head, speed, and system power input is essential to detect device faults and optimize control strategies in fan systems. Since the application of variable-frequency drives (VFDs) makes the motor-efficiency data published by manufacturers inapplicable for VFD–motor–fan systems, the fan efficiency and drive (belt–motor–VFD) efficiency must be identified for each individual system to obtain accurate energy models. The objectives of this paper are to identify an energy model of existing VFD–motor–fan systems using available experimental data and demonstrate its applications in loose belt fault detection and virtual airflow meter development for optimal control. First, an approach is developed to identify the fan head, fan efficiency, and drive-efficiency curves using available fan head, speed, and system power input as well as temporarily measured airflow rate without measuring shaft power. Then, the energy model is identified for an existing VFD–motor–fan system. Finally, the identified model is applied to detect the slipped belt faults and develop the virtual airflow meter. The experiment results reveal that the developed approach can effectively obtain the energy model of VFD–motor–fan systems and the model can be applied to effectively detect slipped belt faults and accurately calculate the fan airflow rate.