bluuebunny/crossref_metadata_2025 huggingface dataset:
Methods to Calibrate a Digital Colour Camera as a Multispectral Imaging Sensor in Low Light Conditions
Authors: Simoneau Alexandre , Aubé Martin
Published: July 2023

High-sensitivity multispectral imaging sensors for scientific use are expensive and consequently not available to scientific teams with limited financial resources. Such sensors are used in applications such as nighttime remote sensing, astronomy, and night time studies in general. In this paper, we present a method aiming to transform non-scientific multispectral imaging sensors into science-friendly ones. The method consists in developing a calibration procedure applied to digital colour cameras not initially designed for scientific purposes. One of our targets for this project was that the procedure would not require any complex or costly equipment. The development of this project was motivated by a need to analyze airborne and spaceborne pictures of the earth surface at night, as a way to determine the optical properties (e.g., light flux, spectrum type and angular emission function) of artificial light sources. This kind of information is an essential part of the input data for radiative transfer models used to simulate light pollution and its effect on the natural environment. Examples of applications of the calibration method are given for that specific field.
Refraction Correction for Spectrally Derived Bathymetry Using UAS Imagery
Authors: Lambert Selina E. , Parrish Christopher E.
Published: July 2023

Spectrally derived bathymetry (SDB) algorithms are rapidly gaining in acceptance and widespread use for nearshore bathymetric mapping. In the past, refraction correction could generally be ignored in SDB, due to the relatively small fields of view (FOVs) of satellite sensors, and the fact that such corrections were typically small in relation to the uncertainties in the output bathymetry. However, the validity of ignoring refraction correction in SDB is now called into question, due to the ever-improving accuracies of SDB, the desire to use the data in nautical charting workflows, and the application of SDB algorithms to airborne cameras with wide FOVs. This study tests the hypothesis that refraction correction leads to a statistically significant improvement in the accuracy of SDB using uncrewed aircraft system (UAS) imagery. A straightforward procedure for SDB refraction correction, implemented as a modification to the well-known Stumpf algorithm, is presented and applied to imagery collected from a commercially available UAS in two study sites in the Florida Keys, U.S.A. The results show that the refraction correction produces a statistically significant improvement in accuracy, with a reduction in bias of 46–75%, a reduction in RMSE of 3–11 cm, and error distributions closer to Gaussian.
Novel Method for Determining the Height of the Stable Boundary Layer under Low-Level Jet by Judging the Shape of the Wind Velocity Variance Profile
Authors: Xian Jinhong , Zhang Ning , Lu Chao , Yang Honglong , Qiu Zongxu
Published: July 2023

The height of the stable boundary layer is a key parameter in atmospheric transmission and diffusion, air quality, emergency response, wind energy, and numerical weather prediction models. Existing methods mainly determine the stable boundary layer height via a threshold or minimum value of the wind speed variance under a low-level jet. Based on multi-meteorological element data from a meteorological gradient observation tower, this paper revealed the limitations of existing methods from the perspective of dynamic and thermal effects. In this paper, it is demonstrated that there were four types of shapes of the wind speed variance profile under the low-level jet and a method for using the shape of the variance profile to retrieve the height of the stable boundary layer was proposed. This method distinguished different types of wind speed variance profiles and solved the problems of the misjudgment and omissions (about 34%) present in existing methods. Our experiment showed that the average absolute error of the proposed method was less than 18 m and the average relative error was less than 9%. The results showed that the proposed inversion method was extended to all kinds of wind field detection equipment for inversion of the stable boundary layer height and has very high universality.
Evolution Patterns of Cooling Island Effect in Blue–Green Space under Different Shared Socioeconomic Pathways Scenarios
Authors: Pan Ziwu , Xie Zunyi , Ding Na , Liang Qiushuang , Li Jianguo , Pan Yu , Qin Fen
Published: July 2023

Blue–green space refers to blue space (rivers and lakes) and green space (lawns and trees), which have the cooling island effect and are increasingly acknowledged as a potential and effective way to help alleviate the urban heat island effect. Scientific and flexible blue–green space planning is required, especially for medium- and large-scale urban agglomerations in the face of climate change. However, the temporal evolution and spatial patterns of the cooling island effect in the blue–green space under different future scenarios of climate change have not been fully investigated. This would impede long-term urban strategies for climate change adaptation and resilience. Here we studied the relationship between future climate change and blue–green spatial layout with Weather Research and Forecasting (WRF), based on the numerical simulation data of 15 global climate models under different extreme Shared Socioeconomic Pathway (SSP) scenarios. As a result, future changes in urban cooling island (UCI) magnitudes were estimated between historical (2015–2020) and future timelines: 2030s (2021–2040), 2050s (2041–2060), 2070s (2061–2080), and 2090s (2081–2100). Our results showed different land use types in blue and green space across the study area were predicted to present various changes in the next 80 years, with forest, grassland, and arable land experiencing the most significant land use transfer. The future UCI intensity of cities under SPP5-8.5 (12) was found to be lower than that under SPP2-4.5 (15), indicating that cities may be expected to experience decreases in UCI magnitudes in the future under SSP5-8.5. When there is no expansion of urban development land, we found that the conversion of different land use types into blue and green space leads to little change in future UCI intensity. While the area growth of forests and water bodies is proportional to the increase in UCI, the increase of farmland was observed to have the most significant impact on reducing the amplitude of urban UCI. Given that Huai’an City, Yancheng City, and Yangzhou City have abundant blue–green space, the urban cooling island effect was projected to be more significant than that of other cities in the study area under different SSP scenarios. The simulation results of the WRF model indicate that optimizing the layout of urban blue–green space plays an important role in modulating the urban thermal environment.
Correlation Matrix-Based Fusion of Hyperspectral and Multispectral Images
Authors: Lin Hong , Li Jun , Peng Yuanxi , Zhou Tong , Long Jian , Gui Jialin
Published: July 2023

The fusion of the hyperspectral image (HSI) and the multispectral image (MSI) is commonly employed to obtain a high spatial resolution hyperspectral image (HR-HSI); however, existing methods often involve complex feature extraction and optimization steps, resulting in time-consuming fusion processes. Additionally, these methods typically require parameter adjustments for different datasets. Still, reliable references for parameter adjustment are often unavailable in practical scenarios, leading to subpar fusion results compared to simulated scenarios. To address these challenges, this paper proposes a fusion method based on a correlation matrix. Firstly, we assume the existence of a correlation matrix that effectively correlates the spectral and spatial information of HSI and MSI, enabling fast fusion. Subsequently, we derive a correlation matrix that satisfies the given assumption by deducing the generative relationship among HR-HSI, HSI, and MSI. Finally, we optimize the fused result using the Sylvester equation. We tested our proposed method on two simulated datasets and one real dataset. Experimental results demonstrate that our method outperforms existing state-of-the-art methods. Particularly, in terms of fusion time, our method achieves fusion in less than 0.1 seconds in some cases. This method provides a practical and feasible solution for the fusion of hyperspectral and multispectral images, overcoming the challenges of complex fusion processes and parameter adjustment while ensuring a quick fusion process.
Attention-Enhanced Generative Adversarial Network for Hyperspectral Imagery Spatial Super-Resolution
Authors: Wang Baorui , Zhang Yifan , Feng Yan , Xie Bobo , Mei Shaohui
Published: July 2023

Hyperspectral imagery (HSI) with high spectral resolution contributes to better material discrimination, while the spatial resolution limited by the sensor technique prevents it from accurately distinguishing and analyzing targets. Though generative adversarial network-based HSI super-resolution methods have achieved remarkable progress, the problems of treating vital and unessential features equally in feature expression and training instability still exist. To address these issues, an attention-enhanced generative adversarial network (AEGAN) for HSI spatial super-resolution is proposed, which elaborately designs the enhanced spatial attention module (ESAM) and refined spectral attention module (RSAM) in the attention-enhanced generator. Specifically, the devised ESAM equipped with residual spatial attention blocks (RSABs) facilitates the generator that is more focused on the spatial parts of HSI that are difficult to produce and recover, and RSAM with spectral attention refines spectral interdependencies and guarantees the spectral consistency at the respective pixel positions. Additionally, an especial U-Net discriminator with spectral normalization is enclosed to pay more attention to the detailed informations of HSI and yield to stabilize the training. For producing more realistic and detailed super-resolved HSIs, an attention-enhanced generative loss is constructed to train and constrain the AEGAN model and investigate the high correlation of spatial context and spectral information in HSI. Moreover, to better simulate the complicated and authentic degradation, pseudo-real data are also generated with a high-order degradation model to train the overall network. Experiments on three benchmark HSI datasets illustrate the superior performance of the proposed AEGAN method in HSI spatial super-resolution over the compared methods.
Isolating the Source Region of Infrasound Travel Time Variability Using Acoustic Sensors on High-Altitude Balloons
Authors: Silber Elizabeth A. , Bowman Daniel C.
Published: July 2023

High-altitude balloons carrying infrasound sensor payloads can be leveraged toward monitoring efforts to provide some advantages over other sensing modalities. On 10 July 2020, three sets of controlled surface explosions generated infrasound waves detected by a high-altitude floating sensor. One of the signal arrivals, detected when the balloon was in the acoustic shadow zone, could not be predicted via propagation modeling using a model atmosphere. Considering that the balloon’s horizontal motion showed direct evidence of gravity waves, we examined their role in infrasound propagation. Implementation of gravity wave perturbations to the wind field explained the signal detection and aided in correctly predicting infrasound travel times. Our results show that the impact of gravity waves is negligible below 20 km altitude; however, their effect is important above that height. The results presented here demonstrate the utility of balloon-borne acoustic sensing toward constraining the source region of variability, as well as the relevance of complexities surrounding infrasound wave propagation at short ranges for elevated sensing platforms.
MASA-SegNet: A Semantic Segmentation Network for PolSAR Images
Authors: Sun Jun , Yang Shiqi , Gao Xuesong , Ou Dinghua , Tian Zhaonan , Wu Jing , Wang Mantao
Published: July 2023

Semantic segmentation of Polarimetric SAR (PolSAR) images is an important research topic in remote sensing. Many deep neural network-based semantic segmentation methods have been applied to PolSAR image segmentation tasks. However, a lack of effective means to deal with the similarity of object features and speckle noise in PolSAR images exists. Thisstudy aims to improve the discriminative capability of neural networks for various intensities of backscattering coefficients while reducing the effects of noise in PolSAR semantic segmentation tasks. Firstly, we propose pre-processing methods for PolSAR image data, which consist of the fusion of multi-source data and false color mapping. Then, we propose a Multi-axis Sequence Attention Segmentation Network (MASA-SegNet) for semantic segmentation of PolSAR data, which is an encoder–decoder framework. Specifically, within the encoder, a feature extractor is designed and implemented by stacking Multi-axis Sequence Attention blocks to efficiently extract PolSAR features at multiple scales while mitigating inter-class similarities and intra-class differences from speckle noise. Moreover, the process of serialized residual connection design enables the propagation of spatial information throughout the network, thereby improving the overall spatial awareness of MASA-SegNet. Within the decoder, it is used to accomplish the semantic segmentation task. The superiority of this algorithm for semantic segmentation will be explored through feature visualization. The experiments show that our proposed spatial sequence attention mechanism can effectively extract features and reduce noise interference and is thus able to obtain the best results on two large-scale public datasets (the AIR-POlSAR-Seg and FUSAR-Map datasets).
Revealing the Land Subsidence Deceleration in Beijing (China) by Gaofen-3 Time Series Interferometry
Authors: Han Yakun , Li Tao , Dai Keren , Lu Zhong , Yuan Xinzhe , Shi Xianlin , Liu Chen , Wen Ningling , Zhang Xi
Published: July 2023

Revealing the land subsidence in Beijing, China, induced by the massive groundwater extraction in the past three decades, is important to mitigate the hazards and protect the residences and infrastructure. Many SAR (Synthetic Aperture Radar) datasets have been successfully applied to reveal the land subsidence over Beijing in previous research, while few works were achieved on land subsidence revealed by time-series InSAR (Interferometric Synthetic Aperture Radar) with Gaofen-3 SAR images. In this study, we successfully perform the time-series InSAR analysis with Gaofen-3 SAR images to extract the land subsidence in Beijing from 2020 to 2021. The Sentinel-1 SAR images were used to assess the accuracy of Gaofen-3 images. The subsidence scale and extent are consistent in detected major subsidence bowls between the two datasets. The spatial–temporal evolution and the deceleration of Beijing land subsidence were revealed by comparing with the Sentinel-1 results from 2017 to 2020. Moreover, we evaluated the interferometric performance of Gaofen-3 satellite SAR imagery and analyzed the main factors that mostly influence the coherence and quality of interferograms. Our results proved that the long perpendicular baselines decrease the coherence seriously over the study area, and the artifacts induced by inaccurate orbit information reduce the quality of the Gaofen-3 interferograms. Refining and removing the two main artifacts could improve the quality of interferograms formed by Gaofen-3 SAR images.
A Probabilistic Approach to Mapping the Contribution of Individual Riverine Discharges into Liverpool Bay Using Distance Accumulation Cost Methods on Satellite Derived Ocean-Colour Data
Authors: Heal Richard , Fronkova Lenka , Silva Tiago , Collingridge Kate , Harrod Richard , Greenwood Naomi , Devlin Michelle J.
Published: July 2023

Assessments of the water quality in coastal zones often rely on indirect indicators from contributing river inputs and the neighbouring ocean. Using a novel combination of distance accumulation cost methods and an ocean-colour product derived from SENTINEL-3 data, we developed a probabilistic method for the assessment of dissolved inorganic nitrogen (DIN) in Liverpool Bay (UK) for the period from 2017 to 2020. Using our approach, we showed the annual and monthly likelihood of DIN exposure from its 12 major contributory rivers. Furthermore, we generated monthly risk maps showing the probability of DIN exposure from all rivers, which revealed a seasonal variation of extent and location around the bay. The highest likelihood of high DIN exposure throughout the year was in the estuarine regions of the Dee, Mersey, and Ribble, along with near-shore areas along the north Wales coast and around the mouth of the rivers Mersey and Ribble. There were seasonal changes in the risk of DIN exposure, and this risk remained high all year for the Mersey and Dee estuary regions. In contrast, for the mouth and near the coastal areas of the Ribble, the DIN exposure decreased in spring, remained low during the summer and early autumn, before displaying an increase during winter. Our approach offers the ability to assess the water quality within coastal zones without the need of complex hydrodynamic models, whilst still having the potential to apportion nutrient exposure to specific riverine inputs. This information can help to prioritise how direct mitigation strategies can be applied to specific river catchments, focusing the limited resources for coastal zone and river basin management.
The Effect of Grain Size on Hyperspectral Polarization Data of Particulate Material
Authors: Golding Rachel M. , Lapszynski Christopher S. , Bachmann Charles M. , Lee Chris H.
Published: July 2023

Polarization provides useful quantitative information about scattering surfaces. In hyperspectral remote sensing of natural surfaces composed of granular materials, there are relatively few studies of polarization. Most earlier remote sensing studies of polarization have been based on multi-spectral data, and the majority focused on the negative branch of polarization, which typically appears at phase angles less than 20 degrees, using models with limited accuracy. Models of the positive branch have also shown limitations, particularly at longer phase angles. We review these earlier studies by Hapke and Shkuratov and present the results of our laboratory study using hyperspectral polarization imagery of particulate surfaces. Although the linear polarization ratio is typically a nonlinear function of phase angle, our results show that in an approximately linear region of the polarization curve, there is a correlation between the slope of the linear polarization ratio and the average grain size.
Mapping Irish Water Bodies: Comparison of Platforms, Indices and Water Body Type
Authors: Zhao Minyan , O’Loughlin Fiachra
Published: July 2023

Accurate monitoring of water bodies is essential for the management and regulation of water resources. Traditional methods for measuring water quality are always time-consuming and expensive; furthermore, it can be very difficult capture the full spatiotemporal variations across regions. Many studies have shown the possibility of remote-sensing-based water monitoring work in many areas, especially for water quality monitoring. However, the use of optical remotely sensed imagery depends on several factors, including weather, quality of images and the size of water bodies. Hence, in this study, the feasibility of optical remote sensing for water quality monitoring in the Republic of Ireland was investigated. To assess the value of remote sensing for water quality monitoring, it is critical to know how well water bodies and the existing in situ monitoring stations are mapped. In this study, two satellite platforms (Sentinel-2 MSI and Landsat-8 OLI) and four indices for separating water and land pixel (Normalized Difference Vegetation Index—NDVI; Normalized Difference Water Index—NDWI; Modified Normalized Difference Water Index—MNDWI; and Automated Water Extraction Index—AWEI) have been used to create water masks for two scenarios. In the first scenario (Scenario 1), we included all pixels classified as water, while for the second scenario (Scenario 2) accounts for potential land contamination and only used water pixels that were completed surround by other water pixels. The water masks for the different scenarios and combinations of platforms and indices were then compared with the existing water quality monitoring station and to the shapefile of the river network, lakes and coastal and transitional water bodies. We found that both platforms had potential for water quality monitoring in the Republic of Ireland, with Sentinel-2 outperforming Landsat due to its finer spatial resolution. Overall, Sentinel-2 was able to map ~25% of the existing monitoring station, while Landsat-8 could only map ~21%. These percentages were heavily impacted by the large number of river monitoring stations that were difficult to map with either satellite due to their location on smaller rivers. Our results showed the importance of testing several indices. No index performed the best across the different platforms. AWEInsh (Automated Water Extraction Index—no shadow) and Sentinel-2 outperformed all other combinations and was able to map over 80% of the area of all non-river water bodies across the Republic of Ireland. While MNDWI was the best index for Landsat-8, it was the worst performer for Sentinel-2. This study showed that optical remote sensing has potential for water monitoring in the Republic of Ireland, especially for larger rivers, lakes and transitional and coastal water bodies.
A High-Performance Thin-Film Sensor in 6G for Remote Sensing of the Sea Surface
Authors: Song Qi , Xu Xiaoguang , Zi Jianchen , Wang Jiatong , Peng Zhongze , Zhang Bingyuan , Zhang Min
Published: July 2023

Functional devices in the THz band will provide a highly important technical guarantee for the promotion and application of 6G technology. We sought to design a high-performance sensor with a large area, high responsiveness, and low equivalent noise power, which is stable at room temperature for long periods and still usable under high humidity; it is suitable for the environment of marine remote sensing technology and has the potential for mass production. We prepared a Te film with high stability and studied its crystallization method by comparing the sensing and detection effects of THz waves at different annealing temperatures. It is proposed that the best crystallization and detection effect is achieved by annealing at 100 °C for 60 min, with a sensitivity of up to 19.8 A/W and an equivalent noise power (NEP) of 2.8 pW Hz−1/2. The effective detection area of the detector can reach the centimeter level, and this level is maintained for more than 2 months in a humid environment at 30 °C with 70–80% humidity and without encapsulation. Considering its advantages of stability, detection performance, large effective area, and easy mass preparation, our Te thin film is an ideal sensor for 6G ocean remote sensing technology.
A Dual Load-Modulated Doherty Power Amplifier Design Method for Improving Power Back-Off Efficiency
Authors: Jin Yi , Dai Zhijiang , Ran Xiongbo , Xu Changzhi , Li Mingyu
Published: July 2023

In this paper, the load modulation process of a Doherty power amplifier (DPA) is analyzed to address the issue of why designed DPAs have a very low efficiency in the back-off state in some cases. A general formula of the real load modulation process is also given for analyzing the load modulation of a peak PA matching network. This provides a new perspective for improving the back-off efficiency of a DPA. To improve the power back-off efficiency of a DPA, a dual load-modulated DPA (D-DPA) design method is proposed. The core principle of the proposed design method is to control the load modulation process from the carrier PA to the peaking PA based on the design method of the traditional two-way DPA. The efficiency of the peaking PA in the back-off region is enhanced, thereby improving the efficiency in the entire back-off region of the DPA. Based on the proposed design method, a D-DPA operating at 2 GHz is designed and fabricated. The test results show that the saturated output power and gain are 43.7 dBm and 9.7 dB, respectively, while the efficiency at 6 dB output power back-off is 59.2%. The designed D-DPA eliminates the efficiency pit of the traditional two-way DPA in the output power back-off region.
Insights into Ionic Liquids for Flame Retardant: A Study Based on Bibliometric Mapping
Authors: Pan Kai , Liu Hui , Wang Zhijun , Ji Wenjing , Wang Jianhai , Huang Rui , Wei Ze , Ye Dong , Xu Chang , Wang Haining
Published: July 2023

Fire is a typical disaster in the processing industry. Ionic liquids, as a type of green flame retardant, play an important role in process safety. In order to grasp the current research status, hotspots, and frontiers in the field of ionic liquids in flame retardancy, the bibliometric mapping method is applied to study the relevant literature in Web of Science datasets from 2000–2022 in this paper. The results show that the research on ionic liquids in flame retardancy is multidisciplinary and involves some disciplines such as energy science, material science, and environmental protection. Journal of Power Sources, Polymer Degradation and Stability, ACS Applied Materials and Interfaces, and Chemical Engineering Journal are the core journals in the field. The results of keyword co-occurrence indicate that the hotspots of research can be divided into five components: the improvement and application of pure ionic liquids electrolytes, the research of gel polymer electrolytes, applying ionic liquids to enhance the polymer materials’ flame retardancy properties, utilizing ionic liquids and inorganic materials to synergize flame retardant polymers, and using ionic liquids flame retardant to improve material’s multiple properties. The burst terms and time zone diagram’s results point out the combination of computational quantum chemistry to study the flame retardancy mechanism of ionic liquids, the study of fluorinated electrolytes, ionic liquids for smoke suppression, phosphorus-containing ionic liquids for flame retardant, and machine learning-assisted design of ILs flame retardants are the research frontiers and future research trends.
The Effects of New Urbanization Pilot City Policies on Urban Innovation: Evidence from China
Authors: Li Shengsheng , Wang Yuanyuan , Dincer Hasan , Yuksel Serhat , Yu Dongyao
Published: July 2023

The new urbanization city pilot policy is China’s most recent policy on urban urbanization. This paper uses new urbanization pilot policies as a quasi-natural experiment to empirically test the impact of new urbanization pilot policies on urban innovation through the difference-in-differences (DID) method using panel data from 199 cities in China from 2011 to 2019. The results show that: (1) The new urbanization city pilot policy has significantly enhanced urban innovation. (2) The theoretical mechanism test shows that the pilot policy of new urbanization promotes urban innovation through the level of human capital. (3) The results of the heterogeneity analysis show that the new urbanization pilot policies have obvious city-level heterogeneity and regional heterogeneity on the improvement of urban innovation levels. The impact effect of new urbanization pilot policies is higher in first-tier and second-tier cities than in fourth-tier and fifth-tier cities; the effect of new urbanization pilot policies is higher in western regions than in eastern and middle regions.
The Innovation-Based Human Development Index Using PROMETHEE II: The Context of G8 Countries
Authors: Tunsi Weam , Alidrisi Hisham
Published: July 2023

The current Human Development Index (HDI) has a promising potential to consider further dimensions, the technological dimensions in specific, in order to absorb various innovational aspects whenever human development is to be benchmarked among countries. Hence, the innovation-based HDI was developed herein using one of the well-known Multi-Criteria Decision Making (MCDM) techniques: the Preference Ranking Organization Method for Enrichment of Evaluations II (PROMETHEE II) considering a mixture of technological criteria, including the Global Innovation Index (GII) itself. The G8 countries, as leading countries worldwide, were investigated in this regard in order to attain such a benchmarking attempt. The model was formulated using seven criteria selected from the World Bank (WB) Open Data (such as High-technology exports as a percentage of manufactured exports, Research and development (R&D) expenditure as a percentage of GDP, and Trademark applications, …, etc.) along with the GII, for the purpose of conducting an MCDM-based evaluation model for the G8 countries. The results of the developed index affirm that the ranking of the G8 countries has distinctly been changed as a consequence of considering technological and innovational aspects, compared to the original HDI (i.e., USA +4—from 5th to 1st; Canada −4, from 2nd to 6th). By utilizing MCDM methods (including PROMETHEE II), this paper also affirms that an infinite number of indexes can be developed in the future by employing a huge number of WB indicators with respect to various MCDM approaches. Hence, international communities are in need of setting up commonly accepted guidelines in order to facilitate having a unified prioritization (i.e., unified preference) regarding the potential criteria and/or indicators to be considered globally for better sustainable development.
A Survey of the Role of Charity Societies in Recycling Clothing Waste and the Extent of Their Societal Impact in Saudi Arabia
Authors: Bin Hamdan Najla Ibrahim
Published: July 2023

Clothing waste is one of the key wastes that societies discard in general, the Saudi society in particular. This increases environmental and visual pollution if necessary measures are not taken to reduce these pollutants. In turn, many charity societies that specialize in collecting clothing waste in Saudi Arabia have taken advantage of this waste by recycling it and thus achieving clothing sustainability, which, in turn, maintains environmental balance, especially since we are a clothing-consumer society. Recently, the researcher noticed the spread of many clothing containers for collecting used clothes by charity societies all over residential neighborhoods in the central, western, eastern and northern regions; this study focuses on the fate of those used clothes that are disposed of and placed in the containers designated for them. But, has this initiative of charity societies achieved the public benefit of society by sustaining these wastes? The study includes three hypotheses, and to verify them, we conduct variance tests, and Scheffe tests for multiple comparisons, as well as (T) tests. The study reaches the conclusion that there are statistically significant differences between the average scores of the sample members in how charity societies benefit from clothing waste according to the study variables, where the (F) value is (46.369), which is a statistically significant value at a level of (0.01). There are also statistically significant differences between the average scores of the sample members in the methods of classifying and sorting clothing waste to achieve its sustainability according to the study variables, where the (F) value is (15.212), which is a statistically significant value at the level of (0.01). There are statistically significant differences between the average scores of the sample members in the societal impact of charity societies to achieve clothing sustainability according to the study variables, where the (T) value is (8.403), which is a statistically significant value at the level of significance (0.01).
Sustainable Management of High-Impact Non-Native Molluscs and Their Potential Commercial Importance in the Eastern Adriatic Sea
Authors: Jelić Mrčelić Gorana , Nerlović Vedrana , Doğan Alper
Published: July 2023

Molluscs, especially bivalves, play an important role in food production and are the dominant group in mariculture worldwide. They are also an important component of the marine ecosystem, influencing the food web and nutrient cycling, as well as creating and modifying habitats. In the Mediterranean Sea, about 578 non-native species have been reported, including 230 taxa of non-native mollusc species. In most regional European seas, including the Mediterranean, the socioeconomic impacts of high-impact mollusc species have generally been poorly studied, and only a few well-documented cases have been reported. The present study collects scientific information on non-native molluscs in Croatian waters that are classified as high impact according to the European Alien Species Information Network EASIN: one Gastropoda—Rapana venosa—and seven Bivalvia species—Anadara kagoshimensis, Anadara transversa, Arcuatula senhousia, Brachidontes pharaonis, Magallana gigas, Pinctada radiata, and Ruditapes philippinarum. This study aims to fill the gap in the literature on high-impact non-native molluscs in the eastern Adriatic Sea through reviewing the literature on examples from other European seas, focusing on the possibility of commercialization and sustainable management of high-impact non-native molluscs. The invasion of non-native molluscs must be managed appropriately, especially if commercialisation is chosen as a management strategy. Additional management measures must be selected and objectively evaluated, taking into account the specificities, location and feasibility of the proposed measures. The study could help researchers, decision-makers, and the public to address the problems with high-impact species in the Adriatic countries, but also in other regions where the monitoring of high-impact non-native species is still inadequate. In addition to Croatia, the monitoring and management of these species is also important for other countries in the eastern Adriatic: Slovenia, Montenegro and Albania.
Improving Railway Alignment Selection in Mountainous Areas with Complex Vegetation: A Multisource Data Landslide Identification Approach for Assisted Decision-Making Research
Authors: Qian Jin , Li Lei , Wu Sitong , Liu Jinting , Zhang Yu
Published: July 2023

In order to provide important assistance for the scientific and effective route selection of future planned railways in the research area and to quickly and accurately identify the distribution range of landslides, thereby proactively mitigating the impact of geological hazards on railways under earthquake conditions, this study aims to shift the risk threshold for geological hazards and provide a scientific basis for the accurate planning and route selection of railways in mountainous areas. Jiuzhaigou was selected as the research area and postearthquake surface deformation information in the study area was obtained through Sentinel-1 satellite radar data. Based on Sentinel-2 optical remote sensing imagery, the changes in vegetation indices in the study area before and after the earthquake were analyzed in depth. The concept of vegetation index difference was proposed as a characteristic parameter for landslide information interpretation and a method combining surface deformation information was developed for landslide information interpretation. According to this method, the study area experienced a deformation subsidence of up to 14.93 cm under the influence of the earthquake, with some areas experiencing an uplift of approximately 6.0 cm. The vegetation index difference in the research area ranged from −1.83502 to 1.45366. The total number of landslides extracted is 12.034 km2 and 164 landslide points are marked, with an overall recognition accuracy of 92.6% and a Kappa coefficient of 0.876. The research results provide new research ideas for landslide information interpretation and can be used to assist in the decision-making of mountain railroad alignment options.
A Value Chain Analysis of Cauliflower and Tomato in Bangladesh
Authors: Sharma Dabasis , Alam Mohammad Jahangir , Begum Ismat Ara , Ding Shijun , McKenzie Andrew M.
Published: July 2023

Improved agricultural value chains linking rural and urban areas can provide opportunities to initiate development interventions. This paper was aimed at mapping the value chain of cauliflower and tomato along with the identification of internal and external governance structures throughout the chain. Data were collected from 100 farmers and 60 traders, selected through the application of simple random and purposive sampling, respectively. Value chain mapping techniques and marketing margins were used for evaluating the economic performance of each actor. To uncover the farmers’ perceptions of internal and external governance structures, the Likert scaling technique was utilized, which was checked by applying the Mann–Whitney U test. Eleven marketing channels were ascertained for cauliflower and tomato, whereas wholesalers contributed the largest share of gross (32.28% for cauliflower and 31.96% for tomato) and net (57.41% for cauliflower and 48.09% for tomato) marketing margins. The highest return on investment was obtained by Aratdars. The lowest amount of cauliflower (1.51%) and tomato (1.30%) were responsible for direct marketing. The benefit–cost ratio was found to be 1.30 and 1.25, respectively, for cauliflower and tomato. This paper revealed considerable differences among NATP and non-NATP farmers with regard to internal and external governance practices. Despite both groups reporting good internal governance practices from their own perspectives, the negative attitude of NATP and non-NATP farmers toward the existence of good external governance practices created a matter of deep concern. To ensure the farmers’ benefits, good governance practices must be implemented throughout the value chain.
Emergency Decision Making for Electric Power Personal Accidents Based on Ontology and Case-Based Reasoning
Authors: Hao Xiaolong , Cao Cen , Yu Sheng , Sun Xiaohu , Feng Min , Luo Wang , Xu Zhiqiang , Xiao Hui
Published: July 2023

Improvements in the emergency response efficiency and management level of power construction sites are conducive to reducing the construction safety risk of power infrastructure projects and then achieving the sustainability of construction site safety. Therefore, this paper proposes an emergency decision-making method for electric power personal accidents, which applies ontology and case-based reasoning to electric power emergency decision making. Firstly, ontology technology is used to structurally represent power accident case knowledge and clarify concepts and their relationships. Then, a power accident knowledge ontology hierarchy is designed, and a powerful personal accident case library is established. Secondly, by calculating cases’ conceptual similarity, attribute similarity, and structural similarity, a global power accident case similarity calculation method is proposed, and case matching is performed based on the calculation results to achieve case knowledge retrieval and reuse. Finally, the results of the example-based study show that the method effectively achieves the accurate retrieval of electric power accident cases, improves the efficiency of the emergency decision response to electric power construction site accidents, and then provides support for emergency decision making for electric power construction site accidents.
Characteristics of Humic Acids in Drained Floodplain Soils in Temperate Climates: A Spectroscopic Study
Authors: Kawałko Dorota , Jamroz Elżbieta , Jerzykiewicz Maria , Ćwieląg-Piasecka Irmina
Published: July 2023

This study aims to assess the characteristics of humic acids (HAs) in floodplain soils. HAs were isolated from the Fluvisols located out of the embankment in the riparian forest (unflooded riparian forest) and within the embankment (inter-embankment), in the area periodically flooded. HAs from these soils were examined for quantity, structure, and humification degree using extraction methods as well as elemental analysis, UV-Vis, FTIR, EPR, and 1HNMR spectroscopies. In the soils after drainage, a significant decrease in HAs has been observed compared to the periodically flooded areas. Obtained results showed that organic matter from periodically flooded soils is more humified and contains HAs with a more aromatic, lignin-like structure compared to the humus matter from unflooded Fluvisols. Humic acids from periodically flooded soil contained a lower amount of C and H compared to those isolated from unflooded soils located out of the embankment, which resulted in a less aliphatic or more aromatic character of their molecules. A higher H/C ratio of HAs from the Fluvisols after drainage exhibits more condensed aromatic ring or substituted ring structures in the molecules. Soils with organic matter with a higher humification index contained HAs with lower radical concentration values in comparison to soils with less humified organic matter. Results obtained show that in flooded areas with periodically reductive conditions, humic acids do not lose as many -OCH3 groups as in better oxidized soils and therefore exhibit a lignin-like aromatic structure. It has been proven that the formation and dynamics of HA transformation may vary due to the water regime in soils.
Improvement of Agricultural Supply Quality in China: Evidence from Jiangsu Province
Authors: Zhou Rongrong , Liu Hanzhou , Zhang Qian , Wang Wei , Mao Jian , Wang Xuerong , Tang Decai
Published: July 2023

Promoting the reform of the agricultural supply side and its quality improvement are crucial for realizing agricultural modernization. This paper tests the varied trajectory of agricultural total factor productivity (ATFP) in Jiangsu Province over the past 21 years. The paper used the three-stage DEA empirical analysis method—Stochastic Frontier Approach (SFA), to address the uncertainty in the development of the agricultural industry. The paper introduces environmental variables such as urbanization level, import and export trade, financial support for agriculture, and transportation convenience. The research results show that: (1) the ATFP growth in Jiangsu Province presents a fluctuating trend; (2) The further sub-index research of ATFP in Jiangsu Province shows that the average rate of growth for agricultural technology efficiency (AEC) in Jiangsu is negative, indicating that the input cost of agricultural factors in Jiangsu increases and marginal efficiency decreases; (3) The empirical analysis of ATFP growth by region shows that there are still large differences in agricultural economic development level, the level of modern agricultural technology and ATFP in the southern, the central and the northern parts of Jiangsu. (4) Stage III: DEA empirical results showed that improving urbanization level, net export trade, and transportation convenience is conducive to improving agricultural production efficiency; financial support for agriculture is weakly conducive to improving agricultural production efficiency. On this basis, the paper puts forward countermeasures and suggestions to promote agricultural structural reform.
Insect Production for Animal Feed: A Multiple Case Study in Brazil
Authors: Gomes Jaqueline Geisa Cunha , Okano Marcelo Tsuguio , Ursini Edson Luiz , Santos Henry de Castro Lobo dos
Published: July 2023

The production of insects as a sustainable protein source represents an innovation for animal feed. The objective of this research is to analyze the value chain of the use of edible insects in animal feed in Brazil through the framework of SWOT, the business model sustainable canvas, and a multiple case study, highlighting the sustainability characteristics. A qualitative approach of the descriptive exploratory type was used, and the multiple case study identified the actors in the chain and how value is generated. The young age of the sector explains the characteristics observed in the Brazilian chain, such as a large development deficit in terms of financing, technology and the qualification of human resources; a disorganized supply chain and supplier structure; and efforts undertaken by regulatory agencies to promote the development of regulations relating to the production and use of insects in animal feed, which, in turn, will lead those wishing to participate in this innovative venture into research and development in the area. Brazil’s edible insect supply chain can become a more significant aspect of sustainable agriculture by closing nutrient and energy loops, promoting food security and minimizing climate change and biodiversity losses, all of which are associated with the achievement of the Sustainable Development Goals.
Essential Oil Volatiles as Sustainable Antagonists for the Root-Knot Nematode Meloidogyne ethiopica
Authors: Faria Jorge M. S. , Rusinque Leidy , Cavaco Tomás , Nunes João C. , Inácio Maria L.
Published: July 2023

Climate change is prompting a shift of tropical pests to locations with a previously lower probability of invasion. This is the case for root-knot nematodes, Meloidogyne sp., particularly of the tropical group. Among them, M. ethiopica is now considered a threat to European food security. The development of novel sustainable nematicides can be based on in vitro bioassays of highly active phytochemicals, e.g., volatiles from essential oils. However, a steady supply of nematodes is often very difficult and dependent on environmental conditions. In the present study, an in vitro co-culture system of M. ethiopica parasitizing hairy roots of Solanum lycopersicum was established, for the first time, to easily obtain populations of second-stage juveniles (J2). These were then used to screen the nematicidal activity of 10 volatile compounds characteristic of essential oils. Finally, information on the most successful compounds was reviewed to predict their environmental dispersion and ecotoxicological hazards. The M. ethiopica population obtained from the co-culture was morphologically similar to reported populations in natural conditions and could be accurately used in direct-contact bioassays. The aldehydes citral and citronellal induced complete mortality of the tested J2, at 1 mg/mL, while compounds from other chemical groups were not as successful. In comparison to commonly used commercial nematicides, citral and citronellal were less likely to accumulate in the water environmental compartment and have lower reported toxicities compared to aquatic organisms and to mammals. Overall, in vitro co-cultures showed the potential to expedite the screening and discovery of bioactive compounds as a contribution to the development of sustainable biopesticides, as well as to lower the impacts of modern farming on agroecosystems.
Digital Literacy, Farmers’ Income Increase and Rural Internal Income Gap
Authors: Liu Bo , Zhou Jing
Published: July 2023

The digital economy has promoted the income growth of rural residents in China, but it has also widened the income gap within rural areas. The excessive income gap will lead to the uneven distribution of social resources and the decline of efficiency, thus threatening the sustainable development of the rural economy. This study utilizes the ‘Circumstances-Efforts’ analytical framework, the skill-biased technology change theory, and data from the China Family Panel Studies (CFPS) in 2018 to examine the impact of digital literacy on income growth among rural residents and the resulting income gap within rural areas. The findings indicate that digital literacy positively contributes to the income growth of rural residents. Moreover, the mechanism analysis reveals that improved access to digital devices and more effective information play a significant role in enhancing the income of rural residents. Furthermore, the analysis of income structures demonstrates that digital literacy has a greater impact on increasing wage income and agricultural income for both high-income and low-income rural residents. However, it is important to note that digital literacy also contributes to the widening income gap within rural areas, particularly impacting high-income rural residents.