bluuebunny/crossref_metadata_2025 huggingface dataset:
Characterization of Potting Epoxy Resins Performance Parameters Based on a Viscoelastic Constitutive Model
Authors: Yang Lin , Ding Anxin , Xu Mi , Li Yuefang , Zhao Xianhang , Peng Jingxuan , Li Xiang
Published: March 2024

To describe the evolution of residual stresses in epoxy resin during the curing process, a more detailed characterization of its viscoelastic properties is necessary. In this study, we have devised a simplified apparatus for assessing the viscoelastic properties of epoxy resin. This apparatus employs a confining cylinder to restrict the circumferential and radial deformations of the material. Following the application of load by the testing machine, the epoxy resin sample gradually reduces the gap between its surface and the inner wall of the confining cylinder, ultimately achieving full contact and establishing a continuous interface. By recording the circumferential stress–strain on the outer surface of the confining cylinder, we can deduce the variations in material bulk and shear moduli with time. This characterization spans eight temperature points surrounding the glass transition temperature, revealing the bulk and shear relaxation moduli of the epoxy resin. Throughout the experiments, the epoxy resin’s viscoelastic response demonstrated a pronounced time-temperature dependency. Below the glass transition temperature, the stress relaxation response progressively accelerated with increasing temperature, while beyond the glass transition temperature, the stress relaxation time underwent a substantial reduction. By applying the time-temperature superposition principle, it is possible to construct the relaxation master curves for the bulk and shear moduli of the epoxy resin. By fitting the data, we can obtain expressions for the constitutive model describing the viscoelastic behavior of the epoxy resin. In order to validate the reliability of the test results, a uniaxial tensile relaxation test was conducted on the epoxy resin casting body. The results show good agreement between the obtained uniaxial relaxation modulus curves and those derived from the bulk and shear relaxation modulus equations, confirming the validity of both the device design and the testing methodology.
Soft Sensor Modeling Method Considering Higher-Order Moments of Prediction Residuals
Authors: Ma Fangyuan , Ji Cheng , Wang Jingde , Sun Wei , Palazoglu Ahmet
Published: March 2024

Traditional data-driven soft sensor methods can be regarded as an optimization process to minimize the predicted error. When applying the mean squared error as the objective function, the model tends to be trained to minimize the global errors of overall data samples. However, there are deviations in data from practical operation, in which the model performance in the estimation of the local variations in the target parameter worsens. This work presents a solution to this challenge by considering higher-order moments of prediction residuals, which enables the evaluation of deviations of the residual distribution from the normal distribution. By embedding constraints on the distribution of residuals into the objective function, the model tends to converge to the state where both stationary and deviation data can be accurately predicted. Data from the Tennessee Eastman process and an industrial cracking furnace are considered to validate the performance of the proposed modeling method.
Performance of Mg/Al and Zn/Al Hydroxide Double Lamellar-Bentonite for Removal of Anionic Azo Dye from Aqueous Solution
Authors: Bouhent Mohammed Mustapha , Bentaleb Kahina , Al-Ameri Abdulrahman , Maschke Ulrich
Published: March 2024

This paper presents the preparation and characterization of bentonite coated with hydroxide double lamellar Mg/Al-bentonite and Zn/Al-bentonite as a potential adsorbent material. The coating process involved co-precipitation of mixed metal nitrate solution (Mg-Al) or (Zn-Al), followed by immersion of bentonite (B-Na+) dispersion. The structures and morphologies of the coated bentonites were characterized using XRD, FTIR, BET, and SEM analysis. The results of the BET analysis indicate that Mg/Al-bentonite and Zn/Al-bentonite have larger surface areas and pore volumes compared to bentonite alone. Specifically, the surface area of Mg/Al-bentonite is 209.25 m2/g with a pore volume of 0.423 cm3/g, while Zn/Al-bentonite has a surface area of 175.95 m2/g and a pore volume of 0.313 cm3/g. In contrast, the surface area and pore volume of bentonite alone are 110.43 m2/g and 0.132 cm3/g, respectively. The Mg/Al-bentonite reaches 85% uptake within 3 h (equivalent to 724.20 mg/g at 25 °C and pH 7), achieving rapid equilibrium. In contrast, the Zn/Al-bentonite achieves a maximum adsorption of 74% within 5 h under identical pH and temperature conditions, corresponding to 650.34 mg/g. The error function values, including the correlation coefficient R2, chi-square test χ2, and residual sum of squares RSS, were calculated to evaluate both kinetic and isotherm models. The kinetic adsorption data agreed well with a pseudo-second-order model. The adsorption process followed the Sips isotherm model, and the monolayer adsorption capacity of Mg/Al-bent and Zn/Al-bent composites was 872.41 (R2 = 0.974) and 678.45 mg/g (R2 = 0.983), respectively. The thermodynamic analysis of the adsorption process revealed that it occurred spontaneously with an endothermic characteristic. The parameters ΔS, ΔH, and ΔG were used to determine this.
Calculation Method of Support Load Zoning and Mechanism of Mine Pressure Behavior in Upward Mining Face across Half of the Goaf along the Panel Direction
Authors: Zhang Yujiang , Ma Fudong , Feng Guorui , Zhang Shuai , Li Jie , Wang Qian , Zhang Xianfeng , Li Shule , Chen Yexing
Published: March 2024

The 1515 mining face in Yongming Coal Mine was upward mined across half of the goaf along the panel direction. In this paper, the methods of field measurement, theoretical analysis, and numerical simulation were used to study the overlying rock fracture structure, support load characteristics, and the mechanism of mine pressure behavior across half of the goaf. The results indicate that the support load of the 1515 upward mining face across half of the goaf along the panel direction exhibits distinct zoning characteristics. The maximum support load is 1.37 times the minimum support load. The development height of the roof separation in the up-mining area is 1.74 times that in the entity coal area, at 9.1 m and 5.22 m respectively. The height of separation and hanging roof length increase and decrease, respectively, along the initial rock fracture area, tensile fracture area, structural fracture area, and compacted fracture area. Based on the definition of the variation coefficient “m” for immediate roof height and hanging roof coefficient “n”, a partitioned method for calculating support loads in the upward mining face across half of the goaf was proposed. Finally, the key parameter values for support loads in each zoning were provided and validated.
Energy Efficiency in Heat Pumps and Solar Collectors: Case of Slovakia
Authors: Kuzevic Stefan , Tausova Marcela , Culkova Katarina , Domaracka Lucia , Shyp Danylo
Published: March 2024

Sustainable energy presently represents the energy of the future, which should be based on the application respecting the importance of energy priorities, increasing regional self-sufficiency, regional control of energy, and regulation of resource use. In the area of energy supply, the use of RES has been increasingly popular, mainly due to the instability in the energy market and the political situation worldwide. Paper’s ambition is to evaluate the efficiency of the selected RES use in the specific conditions of Slovakia, with the aim to achieve the EU targets. This is important due to the increasing use of RES in Slovakia. The objective of this paper is achieved through an analysis of the energy profit of the RES system, comparing the costs of the proposed solutions. The evaluation is carried out by calculating the energy and economic efficiency of three possible buildings used in the research. Using the data obtained, the results show the most suitable alternative for each building. The resulting findings provide a valuable insight for governments in identifying the best projects for RES use. The result will be methodology creation as a base for local administration and communities to elaborate plans with a goal to extend RES use.
Time-Specific Thresholds for Batch Process Monitoring: A Study Based on Two-Dimensional Conditional Variational Auto-Encoder
Authors: Zhu Jinlin , Liu Zhong , Lou Xuyang , Gao Furong , Zhang Zheng
Published: March 2024

This paper studies the use of varying threshold in the statistical process control (SPC) of batch processes. The motivation is driven by how when multiple phases are implicated in each repetition, the distributions of the features behind vary with phases or even the time; thus, it is inconsistent to uniformly bound them by an invariant threshold. In this paper, we paved a new path for learning and monitoring batch processes based on an efficient framework integrating a model termed conditional dynamic variational auto-encoder (CDVAE). Phase indicators are first used to split the data and are then separated, serving as an extra input for the model in order to alleviate the learning complexity. Dissimilar to the routine using features across all timescales, only features relevant to local timestamps are aggregated for threshold calculation, producing a varying threshold that is more specific for the process variations occurring among the timeline. Leveraged upon this idea, a fault detection panel is devised, and a deep reconstruction-based contribution diagram is illustrated for locating the faulty variables. Finally, the comparative results from two case studies highlight the superiority in both detection accuracy and diagnostic performance.
The Optimization of Nickel-Rich Cathode-Material Production on a Pilot Plant Scale
Authors: Purwanto Agus , Ikhsanudin Muhammad Nur , Asri Putri Putih Puspa , Giasari Afifah Salma , Hakam Miftakhul , Yudha Cornelius Satria , Widiyandari Hendri , Dyartanti Endah Retno , Jumari Arif , Nur Adrian
Published: March 2024

Lithium-ion batteries (LIBs) remain the cornerstone of EV technology due to their exceptional energy density. The selection of cathode materials is a decisive factor in LIB technology, profoundly influencing performance, energy density, and lifespan. Among these materials, nickel-rich NCM cathodes have gained significant attention due to their high specific capacity and cost-effectiveness, making them a preferred choice for EV energy storage. However, the transition from the laboratory-scale to industrial-scale production of NMC-811 cathode material presents challenges, particularly in optimizing the oxidation process of Ni2+ ions. This paper addresses the challenges of transitioning NMC-811 cathode material production from a lab scale to a pilot scale, with its high nickel content requiring specialized oxidation processes. The important point emphasized in this transition process is how to produce cathode materials on a pilot scale, but show results equivalent to the laboratory scale. Several optimization variations are carried out, namely, the optimization of the heating rate and the calcination and sintering temperatures, as well as oxygen variations. These two aspects are important for large-scale production. This paper discusses strategies for successful pilot-scale production, laying the foundation for industrial-scale manufacturing. Additionally, NMC-811 cathodes are incorporated into 18650 cylindrical cells, advancing the adoption of high-performance cathode materials.
Numerical Study of Cavitation Characteristics through Butterfly Valve under Different Regulation Conditions
Authors: Zhang Guang , Hu Runhua , Yin Dapeng , Chen Desheng , Zhou Haolin , Lin Zhe
Published: March 2024

Butterfly valves are widely used in the pipeline transportation industry due to their safety and reliability, as well as their low manufacturing and operation costs. Cavitation is a common phenomenon in the butterfly valve that can lead to serious damage to a valve’s components. Therefore, it is important to investigate the generation and evolution of cavitation in butterfly valves. In this study, LES and the Zwart model were used as the turbulence and cavitation models, respectively, to simulate cavitation through a butterfly valve. The influence of the valve opening degree and inlet flow velocity on dynamic cavitation through the butterfly valve were studied. Furthermore, the cavitated flow field was examined, along with the performance coefficients of the butterfly valve. With the increase in the incoming flow velocity, the high-speed jet zone over a large-range and low-pressure zone appeared inside the downstream of butterfly valve, which affected its stability and the cavitation generation through the valve. Furthermore, the flow coefficient decreased with the increase in vapor volume. In addition, the results indicated that cavitation was more easily induced for smaller valve opening degrees, and the interaction between cavitation and solid walls was stronger. Due to the existence of cavitation, the flow characteristics of butterfly valves are seriously affected.
Differential Analysis of Pomelo Peel Fermentation by Cordyceps militaris Based on Untargeted Metabolomics
Authors: Xiang Yannan , Tian Siyi , Luo Xinyu , Cai Chenggang , Du Yaowen , Yang Hailong , Gao Haiyan
Published: March 2024

The content of differentially abundant metabolites in the fermentation broth of grapefruit peels fermented by Cordyceps militaris at different fermentation times was analyzed via LC–MS/MS. Small molecule metabolites and differential metabolic pathways were analyzed via multivariate analysis and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment. A total of 423 metabolites were identified at 0, 2, 6, and 10 days after fermentation. Among them, 169 metabolites showed differential abundance, with significant differences observed between the fermentation liquids of every two experimental groups, and the metabolite composition in the fermentation liquid changed over the fermentation time. In summary, the upregulation and downregulation of metabolites in cancer metabolic pathways collectively promote the remodeling of cancer cell metabolism, facilitating increased glycolysis, alterations in TCA cycle flux, and enhanced biosynthesis of the macromolecules required for rapid proliferation and survival. This study provides new perspectives on the development of high-value-added agricultural and forestry byproducts and the development and research of functional foods.
Estimating Lung Volume Capacity from X-ray Images Using Deep Learning
Authors: Ghimire Samip , Subedi Santosh
Published: March 2024

Estimating lung volume capacity is crucial in clinical medicine, especially in disease diagnostics. However, the existing estimation methods are complex and expensive, which require experts to handle and consequently are more error-prone and time-consuming. Thus, developing an automatic measurement system without a human operator that is less prone to human error and, thus, more accurate has always been a prerequisite. The limitation of radiation dose and various medical conditions in technologies like computed tomography was also the primary concern in the past. Although qualitative prediction of lung volume may be a trivial task, designing clinically relevant and automated methods that effectively incorporate imaging data is a challenging problem. This paper proposes a novel multi-tasking-based automatic lung volume estimation method using deep learning that jointly learns segmentation and regression of volume estimation. The two networks, namely, segmentation and regression networks, are sequentially operated with some shared layers. The segmentation network segments the X-ray images, whose output is regressed by the regression network to determine the final lung volume. Besides, the dataset used in the proposed method is collected from three different secondary sources. The experimental results show that the proposed multi-tasking approach performs better than the individual networks. Further analysis of the multi-tasking approach with two different networks, namely, UNet and HRNet, shows that the network with HRNet performs better than the network with UNet with less volume estimation mean square error of 0.0010.
The Double Identities of the Shaman and the Dualistic Attitudes of the State: An Exploration of Contemporary Organizational Shamanism in Northeast China
Authors: Qu Feng
Published: March 2024

This paper presents a case study of the first shamanic organization in China and argues that organizational shamanism in Northeast China is characterized by the double identities of the shaman and the dualistic attitudes of the national authorities. The analyses in this paper reveal how the shamanic organization created a modernized and globalized space for traditional shamans and specialists to connect with the outside world, enabling them to gain empowerment, legitimacy, and agency. Chinese authorities hold dualistic attitudes towards shamanism: the positive attitude of seeing shamanism as part of cultural heritage has always been coupled with the negative attitude of seeing shamanism as superstition. The studies in this paper demonstrate that organizational shamanism in Northeast China has played a crucial role in negotiating with political authorities and linking local traditions with global discourse. In this sense, the traditional eco-cosmological way of maintaining relationships with natural forces and nonhuman beings has been irrevocably transformed into a cosmopolitical form for the shaman, where the animistic world engages with the outside world, global currency, and political forces.
Institutions and Countercultures: Christianity’s Impact on South Korean Modernization
Authors: Kim Andrew Eungi , Connolly Daniel
Published: March 2024

The relationship between modernization and religion is contested, with the literature differing in how and in what ways religion helps or hinders countries’ social, economic, and political development. This paper draws upon the history of Christianity in South Korea to critically explore the links between religion and modernization. It makes two arguments. First, discussions of the link between religion and modernization frequently employ static definitions of religion, but Christianity is characterized by oscillations between worldly (institutionalizing) and unworldly (countercultural) impulses that theoretically make very different contributions to social, economic, and political development. Second, in the case of South Korea, it is shown that both impulses have made vital contributions to the country’s modernization at different times. This suggests that the dynamic tug-of-war between the institutional and countercultural facets of Korean Christianity, although problematic for individual believers and religious leaders, helped it become an important contributor to the country’s success story. However, this paper concludes on a cautionary note by warning that extreme instances of these impulses have caused cleavages between Christianity and the Korean state and society and could undermine its future contributions. This suggests that diversity and toleration—a hallmark of Korean Christianity—will continue to be the best pathway forward.
The Efforts of Government-Driven Reform of Both State and Personal Rites in Early Chosŏn: A Historical Shift from Spiritual Efficacy to Meritorious Practice
Authors: Chongsŏk Ch’oe
Published: March 2024

In the fifteenth century, the government of Chosŏn, Korea, influenced by the new religious understandings from early Ming China, strived to reform state and personal rites by eliminating elements of spiritual efficacy to align with contemporary religious perspectives. This series of ritual reforms mirrored various Ming policies that, despite being appealing theoretically, struggled with implementation due to a mismatch with local and personal realities. This suggests that Chosŏn’s government-led reforms, diverging from traditional beliefs, faced similar challenges in Korea, leading to various problems. This study delves into the ritual transformations prompted by the reforms in the early Chosŏn era. It highlights the government’s partial success in reforming state rites by removing elements of spiritual efficacy despite potential hindrances and deviations from traditional practices. However, this study also notes the failure of reforms concerning personal rites, which did not yield significant results. It reflects on the complexities and implications of these reforms, considering the socio-religious context of the time and the influence of contemporary Ming China.
Rebooting Ecumenism, the Theological Equivalent of the Climate Crisis: The Role of Urgency and Accountability on the Road to Ecclesial Interdependence
Authors: Herescu Dragos
Published: March 2024

This article puts forward the argument for the acute and urgent need to move from ecclesial self-sufficiency to ecclesial interdependency in the ecumenical process. The difficulties in ecumenical cooperation mirror those in the climate crisis, as despite a global crisis of relevance for Christianity and for the ecumenical movement, individual Churches, much like individual states, fail to work together effectively as they negotiate their own internal challenges. Not dissimilar to the ecological climate breakdown, what we understand as the history-bound reality of the Church will not be safeguarded and will not be made relevant in today’s globalised, pluralistic, interconnected, and dominantly secular, in many contexts, world, except by concerted action from all Churches.
Polarized Light Pollution of Fixed-Tilt Photovoltaic Solar Panels Measured by Drone-Polarimetry and Its Visual-Ecological Importance
Authors: Takács Péter , Száz Dénes , Bernáth Balázs , Pomozi István , Horváth Gábor
Published: March 2024

Specific polarized light pollution (PLP) means the adverse influences of strongly and horizontally polarized light reflected from smooth and dark artificial surfaces on polarotactic water-seeking aquatic insects. Typical PLP sources are photovoltaic panels. Using drone-based imaging polarimetry, in a solar panel farm, we measured the reflection-polarization patterns of fixed-tilt photovoltaic panels from the viewpoint of flying polarotactic aquatic insects, which are the most endangered targets and potential victims of such panels. We found that the temporal changes in PLP were complementary for the two orthogonal viewing directions relative to the panel rows. The estimated magnitude plp of the polarized light pollution of solar panels viewed parallel to the panel rows was the highest (primary peak plp = 49–58% after sunrise and secondary peak plp = 35–48% prior to sunset) at low solar elevations, after sunrise and at or prior to sunset, when many aquatic insect species fly and seek water bodies. On the other hand, the PLP of solar panels viewed perpendicular to the panel rows was the highest (plp = 29–35%) at the largest solar elevations, near noon, when numerous flying aquatic insect species also seek water. Solar panel farms near wetlands can, therefore, be dangerous for these insects.
A Novel Transformer Network with a CNN-Enhanced Cross-Attention Mechanism for Hyperspectral Image Classification
Authors: Wang Xinyu , Sun Le , Lu Chuhan , Li Baozhu
Published: March 2024

Recently, with the remarkable advancements of deep learning in the field of image processing, convolutional neural networks (CNNs) have garnered widespread attention from researchers in the domain of hyperspectral image (HSI) classification. Moreover, due to the high performance demonstrated by the transformer architecture in classification tasks, there has been a proliferation of neural networks combining CNNs and transformers for HSI classification. However, the majority of the current methods focus on extracting spatial–spectral features from the HSI data of a single size for a pixel, overlooking the rich multi-scale feature information inherent to the data. To address this problem, we designed a novel transformer network with a CNN-enhanced cross-attention (TNCCA) mechanism for HSI classification. It is a dual-branch network that utilizes different scales of HSI input data to extract shallow spatial–spectral features using a multi-scale 3D and 2D hybrid convolutional neural network. After converting the feature maps into tokens, a series of 2D convolutions and dilated convolutions are employed to generate two sets of Q (queries), K (keys), and V (values) at different scales in a cross-attention module. This transformer with CNN-enhanced cross-attention explores multi-scale CNN-enhanced features and fuses them from both branches. Experimental evaluations conducted on three widely used hyperspectral image (HSI) datasets, under the constraint of limited sample size, demonstrate excellent classification performance of the proposed network.
Inland Water Level Monitoring from Satellite Observations: A Scoping Review of Current Advances and Future Opportunities
Authors: Kossieris Stylianos , Tsiakos Valantis , Tsimiklis Georgios , Amditis Angelos
Published: March 2024

Inland water level and its dynamics are key components in the global water cycle and land surface hydrology, significantly influencing climate variability and water resource management. Satellite observations, in particular altimetry missions, provide inland water level time series for nearly three decades. Space-based remote sensing is regarded as a cost-effective technique that provides measurements of global coverage and homogeneous accuracy in contrast to in-situ sensors. The advent of Open-Loop Tracking Command (OLTC), and Synthetic Aperture Radar (SAR) mode strengthened the use of altimetry missions for inland water level monitoring. However, it is still very challenging to obtain accurate measurements of water level over narrow rivers and small lakes. This scoping systematic literature review summarizes and disseminates the research findings, highlights major results, and presents the limitations regarding inland water level monitoring from satellite observations between 2018 and 2022. Following the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guideline and through a double screening process, 48 scientific publications were selected meeting the eligibility criteria. To summarize the achievements of the previous 5 years, we present fundamental statistical results of the publications, such as the annual number of publications, scientific journals, keywords, and study regions per continent and type of inland water body. Also, publications associated with specific satellite missions were analyzed. The findings show that Sentinel-3 is the dominant satellite mission, while the ICESat-2 laser altimetry mission has exhibited a high growth trend. Furthermore, publications including radar altimetry missions were charted based on the retracking algorithms, presenting the novel and improved methods of the last five years. Moreover, this review confirms that there is a lack of research on the collaboration of altimetry data with machine learning techniques.
Spatio-Temporal Changes and Driving Forces Analysis of Urban Open Spaces in Shanghai between 1980 and 2020: An Integrated Geospatial Approach
Authors: Zhu Yaoyao , Ling Gabriel Hoh Teck
Published: March 2024

Although there is extensive research demonstrating the significant loss and fragmentation of urban spaces caused by rapid urbanization, to date, no empirical research in Shanghai has investigated the spatiotemporal dynamics of urban open spaces using a comprehensive set of integrated geospatial techniques based on long-sequence time series. Based on the Google Earth Engine (GEE) platform and using the Random Forest (RF) classifier, multiple techniques, namely landscape metrics, trend analysis, open space ratio, transition matrix, Normalized Difference Vegetation Index (NDVI), and fractal dimension analysis, were applied to analyze the Landsat satellite data. Next, Geographic Detector (GeoDetector) methods were used to investigate the driving forces of such spatial variations. The results showed that (1) the RF classification algorithm, supported by the GEE, can accurately and quickly obtain a research object dataset, and that calculating the optimal spatial grain size for open space pattern was 70 m; (2) open spaces exhibited declining and contracting trends; and open spaces in the city experienced a decline from 91.83% in 1980 to 69.63% in 2020. Meanwhile, the degree of open spaces in each district increased to different extents, whilst connectivity markedly decreased. Furthermore, the open space of city center districts showed the lowest rate of decrease, with open space patterns fragmenting due to encroaching urbanization; (3) the contribution of socioeconomic factors to the spatial–temporal changes in open space continually has increased over the past 40 years, and were also higher than natural geographic factors to some extent. Apart from offering policy insights guiding the future spatial planning and development of the city, this paper has contributions from both methodological and empirical perspectives. Based on integrated remote sensing and geographic information science (GIS) techniques, this paper provides updated evidence and a clearer understanding of the spatiotemporal variations in urban spaces and their influencing mechanisms in Shanghai.
Rock Glacier Inventory of the Southwestern Pamirs Supported by InSAR Kinematics
Authors: Ma Qiqi , Oguchi Takashi
Published: March 2024

Although rock glaciers (RGs) are prevalent in the southwestern Pamirs, systematic studies on them are scarce. This article introduces the first inventory of RGs in the southwestern Pamirs, situated at the western edge of the High Mountain Asia region. The inventory, established through a combination of Google Earth optical imagery and Interferometric Synthetic Aperture Radar (InSAR) techniques, encompasses details on the locations, geomorphological parameters, and kinematic attributes of RGs. A total of 275 RGs were cataloged in an area of 55.52 km2 from 3620 to 5210 m in altitude. Our inventory shows that most RGs in this region are talus-connected (213 landforms), with the highest frequency facing northeast (23%). The distribution of RGs thins from west to east and is more abundant in higher altitudes. The Shakhdara range to the south hosts a denser and more active population of RGs than the Shughnon range to the north, highlighting the influence of topography and precipitation. Overall, RGs in the southwestern Pamirs exhibit high activity levels, with active RGs predominating (58%). A comparison between active and transitional RGs showed no significant differences in elevation, temperature, and slope. Glacier-connected and glacier forefield-connected RGs demonstrated higher line-of-sight (LOS) velocities than talus-connected and debris-mantled slope-connected RGs, underscoring the significant impact of precipitation and meltwater on their activity.
Identification of Precursors in InSAR Time Series Using Functional Data Analysis Post-Processing: Demonstration on Mud Volcano Eruptions
Authors: Fontana Matteo , Bernardi Mara Sabina , Cigna Francesca , Tapete Deodato , Menafoglio Alessandra , Vantini Simone
Published: March 2024

One of the most promising applications of satellite data is providing users in charge of land and emergency management with information and data to support decision making for geohazard mapping, monitoring and early warning. In this work, we consider ground displacement data obtained via interferometric processing of satellite radar imagery, and we provide a novel post-processing approach based on a Functional Data Analysis paradigm capable of detecting precursors in displacement time series. The proposed approach appropriately accounts for the spatial and temporal dependencies of the data and does not require prior assumptions on the deformation trend. As an illustrative case, we apply the developed method to the identification of precursors to a mud volcano eruption in the Santa Barbara village in Sicily, southern Italy, showing the advantages of using a Functional Data Analysis framework for anticipating the warning signal. Indeed, the proposed approach is able to detect precursors of the paroxysmal event in the time series of the locations close to the eruption vent and provides a warning signal months before a scalar approach would. The method presented can potentially be applied to a wide range of geological events, thus representing a valuable and far-reaching monitoring tool.
Mapping Dissolved Organic Carbon and Organic Iron by Comparing Deep Learning and Linear Regression Techniques Using Sentinel-2 and WorldView-2 Imagery (Byers Peninsula, Maritime Antarctica)
Authors: Fernández Susana del Carmen , Muñiz Rubén , Peón Juanjo , Rodríguez-Cielos Ricardo , Ruíz Jesús , Calleja Javier F.
Published: March 2024

Byers Peninsula is considered one of the largest ice-free areas in maritime Antarctica. Since 2006, the Spanish Polar Program has taken part in a large number of environmental studies involving the effects of climate change on biological life cycles, limnology, and microbiology. Soils from maritime Antarctica are generally weakly developed and have chemical, physical, and morphological characteristics that are strongly influenced by the parent material. However, biological activity during the short Antarctic summer promotes intense transference of nutrients and organic matter in areas occupied by different species of birds and marine mammals. Mapping and monitoring those areas that are highly occupied by various species could be very useful to create models prepared from satellite images of the edaphic properties. In this approach, deep learning and linear regression models of the soil properties and spectral indexes, which were considered as explicative variables, were used. We trained the models on soil properties closely related to biological activity such as dissolved organic carbon (DOC) and the iron fraction associated with the organic matter (Fe). We tested the best approach to model the spatial distribution of DOC, Fe, and pH by training the linear regression and deep learning models on Sentinel-2 and WorldView-2 images. The most robust models, the pH model built with the deep learning approach on Sentinel images (MAE of 0.51, RMSE of 0.70, and R2 with a residual of −0.49), the DOC model built with linear regression on Sentinel images (MAE of 189.39, RMSE of 342.23, and R2 with a residual of 0.0), and the organic Fe model built with deep learning (MAE of 116.20, RMSE of 209.93, and R2 of −0.05), were used to track possible areas with ornithogenic soils, as well as areas of Byers Peninsula that could be supporting the highest biological development.
Review of GNSS-R Technology for Soil Moisture Inversion
Authors: Yang Changzhi , Mao Kebiao , Guo Zhonghua , Shi Jiancheng , Bateni Sayed M. , Yuan Zijin
Published: March 2024

Soil moisture (SM) is an important parameter in water cycle research. Rapid and accurate monitoring of SM is critical for hydrological and agricultural applications, such as flood detection and drought characterization. The Global Navigation Satellite System (GNSS) uses L-band microwave signals as carriers, which are particularly sensitive to SM and suitable for monitoring it. In recent years, with the development of Global Navigation Satellite System–Reflectometry (GNSS-R) technology and data analysis methods, many studies have been conducted on GNSS-R SM monitoring, which has further enriched the research content. However, current GNSS-R SM inversion methods mainly rely on auxiliary data to reduce the impact of non-target parameters on the accuracy of inversion results, which limits the practical application and widespread promotion of GNSS-R SM monitoring. In order to promote further development in GNSS-R SM inversion research, this paper aims to comprehensively review the current status and principles of GNSS-R SM inversion methods. It also aims to identify the problems and future research directions of existing research, providing a reference for researchers. Firstly, it introduces the characteristics, usage scenarios, and research status of different GNSS-R SM observation platforms. Then, it explains the mechanisms and modeling methods of various GNSS-R SM inversion research methods. Finally, it highlights the shortcomings of existing research and proposes future research directions, including the introduction of transfer learning (TL), construction of small models based on spatiotemporal analysis and spatial feature fusion, and further promoting downscaling research.
HP3D-V2V: High-Precision 3D Object Detection Vehicle-to-Vehicle Cooperative Perception Algorithm
Authors: Chen Hongmei , Wang Haifeng , Liu Zilong , Gu Dongbing , Ye Wen
Published: March 2024

Cooperative perception in the field of connected autonomous vehicles (CAVs) aims to overcome the inherent limitations of single-vehicle perception systems, including long-range occlusion, low resolution, and susceptibility to weather interference. In this regard, we propose a high-precision 3D object detection V2V cooperative perception algorithm. The algorithm utilizes a voxel grid-based statistical filter to effectively denoise point cloud data to obtain clean and reliable data. In addition, we design a feature extraction network based on the fusion of voxels and PointPillars and encode it to generate BEV features, which solves the spatial feature interaction problem lacking in the PointPillars approach and enhances the semantic information of the extracted features. A maximum pooling technique is used to reduce the dimensionality and generate pseudoimages, thereby skipping complex 3D convolutional computation. To facilitate effective feature fusion, we design a feature level-based crossvehicle feature fusion module. Experimental validation is conducted using the OPV2V dataset to assess vehicle coperception performance and compare it with existing mainstream coperception algorithms. Ablation experiments are also carried out to confirm the contributions of this approach. Experimental results show that our architecture achieves lightweighting with a higher average precision (AP) than other existing models.
Detection and Comparison of Volatile Organic Compounds in Four Varieties of Hawthorn Using HS-GC-IMS
Authors: Zhu Lijun , Ou Feilin , Xiang Yun , Wang Bin , Mao Yingchao , Zhu Lingfeng , Zhang Qun , Lei Chang
Published: March 2024

Hawthorn is a type of natural food with significant medicinal and nutritional properties; it has been listed in the “Both Food and Drug” list by the Chinese Ministry of Health Item List since 1997. However, hawthorn varieties have complex origins, and there are significant differences in the content, type, and medicinal efficacy of the chemically active ingredients in different varieties of hawthorn. This leads to the phenomenon of mixed varieties and substandard products being passed off as high-quality. In this work, by using headspace gas chromatography–ion mobility spectrometry (HS-GC-IMS), we identified and analyzed volatile organic compounds (VOCs) in four varieties of hawthorn, establishing their characteristic fingerprints. As a result, a total of 153 peaks were detected, and 139 VOCs were also identified. As shown by the fingerprint profiles, the different hawthorn samples contained different VOCs. Meanwhile, by using principal component analysis (PCA), Euclidean distance, and partial least-squares discriminant analysis (PLS-DA), the relationship between the VOCs found in the different varieties of hawthorn was revealed. This study developed a simple, fast, accurate, and sensitive method for identifying, tracking, and evaluating hawthorn varieties.
Alleviating Salt Stress in Tomatoes through Seed Priming with Polyethylene Glycol and Sodium Chloride Combination
Authors: Habibi Nasratullah , Terada Naoki , Sanada Atsushi , Koshio Kaihei
Published: March 2024

Tomato cultivation grapples with salt stress, disrupting growth parameters and physiological processes. High salinity levels induce osmotic stress, impacting cellular integrity and hindering metabolic activities. Salt accumulation at the root zone alters key physiological attributes, compromising overall harvestable output. Seed priming emerges as a potential solution to enhance plant resilience. A research gap exists in understanding the combined influence of polyethylene glycol and sodium chloride as seed priming agents under salt stress conditions. The study occurred in the Greenhouse of Laboratory Horticultural Science at Tokyo University of Agriculture. Micro Tom seeds underwent a factorial randomized design, involving five salinity and four priming treatments. Replicated ten times, totaling 200 plants, seed priming used polyethylene glycol, inducing salinity stress with sodium chloride. Meticulous measurements of growth parameters, photosynthetic traits, yield attributes, and electrolyte leakage were conducted. Statistical analyses discerned treatment effects at a 5% significance level. Seed priming, especially with ‘PEG plus NaCl’, effectively mitigated salt stress effects on tomato plants. Under severe salt stress, primed plants exhibited increased plant height, trusses, leaves, and leaf area. Photosynthetic efficiency and yield attributes demonstrated significant improvements with seed priming. Electrolyte leakage, indicative of leaf damage, was notably reduced by seed priming treatments, with ‘PEG plus NaCl’ exhibiting the highest efficacy. These results offer valuable guidance for optimizing agricultural practices in saline environments, contributing to sustainable strategies for food security amidst escalating environmental challenges.
Categorization of the Potential Impact of Italian Quarries on Water Resources through a Multi-Criteria Decision Aiding-Based Model
Authors: Paoletti Matteo , Piscopo Vincenzo , Sbarbati Chiara , Scarelli Antonino
Published: March 2024

Quarrying has great importance for economic development and, at the same time, can have several adverse environmental impacts; specifically, it may have a significant influence on water resources. There are approximately 4000 quarries in Italy, and knowledge of their potential impact on water resources is limited. To this end, a procedure for categorizing Italian quarries was devised by combining the methods of Geographic Information Systems and Multi-Criteria Decision Aiding, selecting the potentially impactful criteria, and parametrizing the latter through the available databases. Using the ELECTRE models (ELECTRE TRI and ELECTRE III), the impact category of each quarry was assessed separately for surface water and groundwater and then the overall impact on water resources was assessed. The simulations were carried out by varying the weights of the various selected criteria, which allowed the grouping of Italian quarries into five categories with increasing potential impact on water resources. The ranking of quarries falling into the two highest-impact categories was further refined using ascending and descending distillations. The categorization can be interpreted as a first national assessment of the sustainability of quarrying activities with reference to water resources. The methodological approach of the study proved to be appropriate for the quarry-sorting and -ranking processes, lending itself to the introduction of other criteria and weights, including those arising from the participation of different stakeholders.
Do Economic and Social Satisfaction Matter Equally in Sustainable Business? Hotel Membership Types and Sales Promotions
Authors: Wen Tianhao , Ha Hong-Youl
Published: March 2024

Customer responses to economic and social satisfaction are important in business-to-business transactions; however, these responses can vary when customer segments and sales promotions are combined. This study investigates the roles of two satisfaction types by demonstrating three-way interactions with two moderators: memberships and promotion levels. Using survey data on paid hotel memberships in Korea, this study focuses on the moderated moderation effects of hotel membership type and sales promotions. The authors find that sales promotions positively affect members’ behavioral intentions when they are economically or socially satisfied, regardless of the membership type. In particular, when social satisfaction is positive, the impact of sales promotions on paid membership renewal intentions increases dramatically regardless of the membership type. Meanwhile, lower-tiered members respond more positively to price discounts, increasing their paid membership renewal intentions. In contrast, premium members prefer coupons over price discounts. However, the slope of customer responses is steeper for social satisfaction than economic satisfaction, highlighting that the impact of sales promotions differs by membership type.
The Spatiotemporal Impact of Digital Economy on High-Quality Agricultural Development: Evidence from China
Authors: Li Qi , Liu Zhijiao
Published: March 2024

China’s high-quality economic development is strongly supported by the high-quality development of agriculture, and the digital economy has emerged as a key driver for promoting shared prosperity and high-quality economic development. Against this backdrop, investigating the connection between high-quality agricultural development and the digital economy holds significant importance. This study utilized the entropy-weighted TOPSIS model to evaluate comprehensive evaluation indicators of the two according to panel data from 30 provinces in China between 2011 and 2021. Subsequently, GIS spatial analysis and exploratory spatial data analysis (ESDA) were employed to investigate the spatiotemporal evolution features and spatial correlations. Finally, the spatiotemporal geographically weighted regression (GTWR) model was constructed to examine the spatiotemporal impact of the digital economy on the advancement of high-quality agricultural growth. The results indicate that: (1) from 2011 to 2021, China’s high-quality agricultural development and digital economy both demonstrated a general increasing trend. In terms of spatial distribution, there were significant spatial variations, with a general trend of “Southeast is higher, whereas the Northwest is lower”. The regions with significant value were primarily clustered in the coastal areas in the east and several provincial capitals. (2) Both of the two exhibited significant global spatial self-correlation, and there were also significant spatiotemporal clustering effects in high-quality agricultural growth, gradually forming a high-value cluster centered around Shanghai and a low-value cluster centered around western provinces. (3) The digital economy positively influences the enhancement of high-quality agricultural development, demonstrating notable spatial and temporal heterogeneity. In contrast to the southeastern areas, the influence is more pronounced in the northern and central-western areas.