bluuebunny/crossref_metadata_2025 huggingface dataset:
Sweet Cherry Plants Prioritize Their Response to Cope with Summer Drought, Overshadowing the Defense Response to Pseudomonas syringae pv. syringae
Authors: Villalobos-González Luis , Carreras Claudia , Beltrán María Francisca , Figueroa Franco , Rubilar-Hernández Carlos , Opazo Ismael , Toro Guillermo , Salvatierra Ariel , Sagredo Boris , Pizarro Lorena , Fiore Nicola , Pinto Manuel , Arbona Vicent , Gómez-Cadenas Aurelio , Pimentel Paula
Published: June 2024

Disease severity and drought due to climate change present significant challenges to orchard productivity. This study examines the effects of spring inoculation with Pseudomonas syringae pv. syringae (Pss) on sweet cherry plants, cvs. Bing and Santina with varying defense responses, assessing plant growth, physiological variables (water potential, gas exchange, and plant hydraulic conductance), and the levels of abscisic acid (ABA) and salicylic acid (SA) under two summer irrigation levels. Pss inoculation elicited a more pronounced response in ‘Santina’ compared to ‘Bing’ at 14 days post-inoculation (dpi), and those plants inoculated with Pss exhibited a slower leaf growth and reduced transpiration compared to control plants during 60 dpi. During differential irrigations, leaf area was reduced 14% and 44% in Pss inoculated plants of ‘Bing’ and ‘Santina’ respectively, under well-watered (WW) conditions, without changes in plant water status or gas exchange. Conversely, water-deficit (WD) conditions led to gas exchange limitations and a 43% decrease in plant biomass compared to that under WW conditions, with no differences between inoculation treatments. ABA levels were lower under WW than under WD at 90 dpi, while SA levels were significantly higher in Pss-inoculated plants under WW conditions. These findings underscore the influence on plant growth during summer in sweet cherry cultivars that showed a differential response to Pss inoculations and how the relationship between ABA and SA changes in plant drought level responses.
Selection of Stable Reference Genes for QRT-PCR in Tree Peony ‘Doulv’ and Functional Analysis of PsCUC3
Authors: Zhou Shuang , Ma Chao , Zhou Wenbin , Gao Shuangcheng , Hou Dianyun , Guo Lili , Shi Guoan
Published: June 2024

(1) Background: Tree peonies display extensive cultivar diversity due to widespread hybridization, resulting in a complex genetic architecture. This complexity complicates the selection of universal reference genes across different cultivars for qRT-PCR analyses. Paeonia suffruticosa ‘Doulv’, notable for its unique green blooms in China, exhibits chlorosis post-flowering and features petaloid stamens and pistils. (2) Methods: Based on published literature and RNA-seq data from ‘Doulv’, nine candidate reference genes—ACT (Actin), TUB (β-Tubulin), UBC (Ubiquitin Conjugating Enzyme), UBQ (Ubiquitin), UPL (Ubiquitin Protein Ligase), PP2A (Protein Phosphatase 2A), PP2C (Protein Phosphatase 2C), MBF1A (Multiprotein Bridging Factor 1A), and GAPDH (Glyceraldehyde-3-Phosphate Dehydrogenase)—were selected. Their expression stability was assessed across various tissues and developmental stages of ‘Doulv’ flowers using qRT-PCR, with evaluations conducted via GeNorm_v3.5, NormFinder_v20, and BestKeeper_v1.0. Gene cloning and expression analyses of PsCUC3, including its subcellular localization, were performed. (3) Results: GAPDH and ACT were identified as the most stable reference genes in petaloid stamens across various developmental stages of ‘Doulv’, whereas UBC and MBF1A were optimal across different tissues. Notably, specific conserved amino acids in PsCUC3 from ‘Doulv’ diverged from those in NAM/CUC3 proteins of other species, impacting its protein structure. PsCUC3 expression analysis revealed no correlation with chlorophyll content in petaloid stamens but an association with petaloid organ development. Furthermore, PsCUC3 was predominantly localized in the nucleus. (4) Conclusions: This study comprehensively evaluated suitable reference genes using GeNorm_v3.5, NormFinder_v20, and BestKeeper_v1.0 software, establishing a robust qRT-PCR detection system for ‘Doulv’ peony. These results provide a solid experimental foundation for further research on ‘Doulv’ peony. Building on this experimental foundation, the functional analysis of the PsCUC3 gene was conducted. The findings suggest a potential association between the PsCUC3 gene and floral morphology alterations in ‘Doulv’, identifying PsCUC3 as crucial for understanding the molecular mechanisms influencing floral structure in tree peonies.
Harnessing Walnut-Based Zinc Oxide Nanoparticles: A Sustainable Approach to Combat the Disease Complex of Meloidogyne arenaria and Macrophomina phaseolina in Cowpea
Authors: Hussain Mir , Parveen Ghazala , Bhat Aashaq , Reshi Zubair , Ataya Farid , Handoo Zaffar
Published: June 2024

Zinc oxide nanoparticles (ZnO NPs) exhibit diverse applications, including antimicrobial, UV-blocking, and catalytic properties, due to their unique structure and properties. This study focused on the characterization of zinc oxide nanoparticles (ZnO NPs) synthesized from Juglans regia leaves and their application in mitigating the impact of simultaneous infection by Meloidogyne arenaria (root-knot nematode) and Macrophomina phaseolina (root-rot fungus) in cowpea plants. The characterization of ZnO NPs was carried out through various analytical techniques, including UV–visible spectrophotometry, Powder-XRD analysis, FT-IR spectroscopy, and SEM-EDX analysis. The study confirmed the successful synthesis of ZnO NPs with a hexagonal wurtzite structure and exceptional purity. Under in vitro conditions, ZnO NPs exhibited significant nematicidal and antifungal activities. The mortality of M. arenaria juveniles increased with rising ZnO NP concentrations, and a similar trend was observed in the inhibition of M. phaseolina mycelial growth. SEM studies revealed physical damage to nematodes and structural distortions in fungal hyphae due to ZnO NP treatment. In infected cowpea plants, ZnO NPs significantly improved plant growth parameters, including plant length, fresh mass, and dry mass, especially at higher concentrations. Leghemoglobin content and the number of root nodules also increased after ZnO NP treatment. Additionally, ZnO NPs reduced gall formation and egg mass production by M. arenaria nematodes and effectively inhibited the growth of M. phaseolina in the roots. Furthermore, histochemical analyses demonstrated a reduction in oxidative stress, as indicated by decreased levels of reactive oxygen species (ROS) and lipid peroxidation in ZnO NP-treated plants. These findings highlight the potential of green-synthesized ZnO NPs as an eco-friendly and effective solution to manage disease complex in cowpea caused by simultaneous nematode and fungal infections.
The Influence of Climate Change on the Distribution of Hibiscus mutabilis in China: MaxEnt Model-Based Prediction
Authors: Zhang Lu , Jiang Beibei , Meng Yu , Jia Yin , Xu Qian , Pan Yuanzhi
Published: June 2024

Our study utilized 374 geographical distribution records of H. mutabilis and 19 bioclimatic factors, employing the MaxEnt model and the Geographic Information System (ArcGIS). The key environmental variables influencing the suitable distribution areas of H. mutabilis were analyzed through the comprehensive contribution rate, permutation importance, and Pearson correlation coefficient. Based on this analysis, the contemporary and future suitable distribution areas and their extents were predicted. The results indicate that the key limiting factor affecting the suitable distribution areas of H. mutabilis is the precipitation of the driest month (bio14), with secondary factors being annual precipitation (bio12), annual mean temperature (bio1), and annual temperature range (bio7). Under contemporary climate conditions, the total suitable area for H. mutabilis is approximately 2,076,600 km2, primarily concentrated in the tropical and subtropical regions of southeastern China. Under low-to-medium-emission scenarios (SSP1-2.6, SSP2-4.5), the total suitable area of H. mutabilis shows a trend of first decreasing and then increasing compared to the current scenario. In contrast, under high-emission scenarios (SSP5-8.5), it exhibits a trend of first increasing and then decreasing. The spatial pattern changes indicate that the retention rate of suitable areas for H. mutabilis ranges from 95.28% to 99.28%, with the distribution centers primarily located in Hunan and Guizhou provinces, showing an overall migration trend towards the west and north. These findings suggest that H. mutabilis possesses a certain level of adaptability to climate change. However, it is crucial to consider regional drought and sudden drought events in practical cultivation and introduction processes. The results of our study provide a scientific basis for the rational cultivation management, conservation, and utilization of germplasm resources of H. mutabilis.
Chitosan Hemostatic Dressings: Properties and Surgical Applications
Authors: Cassano Roberta , Perri Paolo , Scarcello Edoardo , Piro Paolo , Sole Roberta , Curcio Federica , Trombino Sonia
Published: June 2024

Wounds caused by trauma and/or surgery represent a significant challenge in contemporary medical practice, requiring innovative approaches to promote optimal healing and reduce the risk of bleeding and complications resulting from it. In this context, chitosan, a natural polysaccharide derived from chitin, represents an ideal material for the study and application of medical devices, in the form of dressings, in wound management for pre- and/or post-operative wounds due to its ability to induce hemostasis and its high biocompatibility with biological tissues. The aim of this work was to discuss the structural characteristics, properties and application of chitosan-based hemostatic dressings in hemostatic processes resulting from pre- or post-surgical approaches.
A High Andean Hydrocolloid Extracted by Microatomization: Preliminary Optimization in Aqueous Stability
Authors: Choque-Quispe Yudith , Choque-Quispe David , Ligarda-Samanez Carlos A. , Solano-Reynoso Aydeé M. , Froehner Sandro , Ramos-Pacheco Betsy S. , Carhuarupay-Molleda Yakov Felipe , Sumarriva-Bustinza Liliana Asunción
Published: June 2024

Aqueous suspensions rely on electrostatic interactions among suspended solids, posing a significant challenge to maintaining stability during storage, particularly in the food and pharmaceutical industries, where synthetic stabilizers are commonly employed. However, there is a growing interest in exploring new materials derived from natural and environmentally friendly sources. This study aimed to optimize the stability parameters of a novel Altoandino Nostoc Sphaericum hydrocolloid (NSH) extracted via micro atomization. Suspensions were prepared by varying the pH, gelatinization temperature and NSH dosage using a 23 factorial arrangement, resulting in eight treatments stored under non-controlled conditions for 20 days. Stability was assessed through turbidity, sedimentation (as sediment transmittance), ζ potential, particle size, color and UV-Vis scanning. Optimization of parameters was conducted using empirical equations, with evaluation based on the correlation coefficient (R2), average relative error (ARE) and X2. The suspensions exhibited high stability throughout the storage period, with optimized control parameters identified at a pH of 4.5, gelatinization temperature of 84.55 °C and NSH dosage of 0.08 g/L. Simulated values included turbidity (99.00%), sedimentation (72.34%), ζ potential (−25.64 mV), particle size (300.00 nm) and color index (−2.00), with simulated results aligning with practical application. These findings suggest the potential use of NSH as a substitute for commercial hydrocolloids, albeit with consideration for color limitations that require further investigation.
All-Cellulose Nanofiber-Based Sustainable Triboelectric Nanogenerators for Enhanced Energy Harvesting
Authors: Cao Mengyao , Chen Yanglei , Sha Jie , Xu Yanglei , Chen Sheng , Xu Feng
Published: June 2024

Triboelectric nanogenerators (TENGs) show promising potential in energy harvesting and sensing for various electronic devices in multiple fields. However, the majority of materials currently utilized in TENGs are unrenewable, undegradable, and necessitate complex preparation processes, resulting in restricted performance and durability for practical applications. Here, we propose a strategy that combines straightforward chemical modification and electrospinning techniques to construct all-cellulose nanofiber-based TENGs with substantial power output. By using cellulose acetate (CA) as the raw material, the prepared cellulose membranes (CMs) and fluorinated cellulose membranes (FCMs) with different functional groups and hydrophobic properties are applied as the tribopositive and tribonegative friction layers of FCM/CM-based triboelectric nanogenerators (FC-TENGs), respectively. This approach modulates the microstructure and triboelectric polarity of the friction materials in FC-TENGs, thus enhancing their triboelectric charge densities and contact areas. As a result, the assembled FC-TENGs demonstrate enhanced output performance (94 V, 8.5 µA, and 0.15 W/m2) and exceptional durability in 15,000 cycles. The prepared FC-TENGs with efficient energy harvesting capabilities can be implemented in practical applications to power various electronic devices. Our work strengthens the viability of cellulose-based TENGs for sustainable development and provides novel perspectives on the cost-effective and valuable utilization of cellulose in the future.
Research on Occupational Risk Assessment for Welder Occupation in Romania
Authors: Pirvu Valentin , Rontescu Corneliu , Bogatu Ana-Maria , Cicic Dumitru-Titi , Burlacu Adrian , Ionescu Nadia
Published: June 2024

The ever-increasing needs of the working population have led to the development of various branches of industry, an increase in the number of employees, and a rise in the number of work-related accidents. The welder occupation is one of the most sought after occupations in Europe, according to the EURopean Employment Services (EURES) statistics. Taking into account the work system in which welders conduct their activity (uncomfortable working positions, splashes, high temperatures, mechanical factors, gases and fumes, magnetic fields due to electric current), the paper presents the risk factors identified for the welder occupation, based on the occupational injury and illness risk assessments. Following the analysis of 25 risk assessments, carried out by the assessment team that must include qualified evaluators, process specialists, the workers’ representative, occupational health and safety responsible at various industrial economic agents, a total of 70 main risk factors of occupational accidents and diseases were identified for the welder occupation. Risk factors were classified according to four main work components: worker, workload, work environment, and means of production. To reflect the importance of the identified risk factor, the number of organizations that considered that the risk was likely to occur but also the possibility that the risk was above the acceptable limit, calculated using the National Institute for Research and Development for Labor Protection “Alexandru Darabont” (INCDPM) method, a method often used in Romania, was identified from the analyzed assessments. Finally, a prevention and protection plan was drawn up with regard to the risks identified for the welder occupation, the final aim of which was to respectively reduce the probability of occurrence with the severity of the risks identified.
Intelligent Monitoring Model for Lost Circulation Based on Unsupervised Time Series Autoencoder
Authors: Wu Liwei , Wang Xiaopeng , Zhang Ziyue , Zhu Guowei , Zhang Qilong , Dong Pinghua , Wang Jiangtao , Zhu Zhaopeng
Published: June 2024

Lost circulation, a common risk during the drilling process, significantly impacts drilling safety and efficiency. The presence of data noise and temporal evolution characteristics pose significant challenges to the accurate monitoring of lost circulation. Traditional supervised intelligent monitoring methods rely on large amounts of labeled data, which often do not consider temporal fluctuations in data, leading to insufficient accuracy and transferability. To address these issues, this paper proposes an unsupervised time series autoencoder (BiLSTM-AE) intelligent monitoring model for lost circulation, aiming to overcome the limitations of supervised algorithms. The BiLSTM-AE model employs BiLSTM for both the encoder and decoder, enabling it to comprehensively capture the temporal features and dynamic changes in the data. It learns the patterns of normal data sequences, thereby automatically identifying anomalous risk data points that deviate from the normal patterns during testing. Results show that the proposed model can efficiently identify and monitor lost circulation risks, achieving an accuracy of 92.51%, a missed alarm rate of 6.87%, and a false alarm rate of 7.71% on the test set. Compared to other models, the BiLSTM-AE model has higher accuracy and better timeliness, which is of great significance for improving drilling efficiency and ensuring drilling safety.
Nuclear Magnetic Resonance Logging-Based Permeability Classification Modeling for Tight Sandstone Reservoirs
Authors: Liang Zhongkui , Li Xueying , Sun Aiyan , Hou Fang , Zhai Zhiwei , Sui Qiang
Published: June 2024

The Upper Paleozoic tight sandstone reservoirs on the eastern margin of the Ordos Basin exhibit strong heterogeneity and complex pore structures, leading to poor correlation between porosity and permeability and insufficient accuracy in permeability calculations to meet the requirements of reservoir fine evaluation. Therefore, a new method for high-precision permeability calculation based on flow zone index (FZI) reservoir classification is proposed. This method determines the number of reservoir classifications based on the characteristics of the FZI normal probability distribution plot and establishes FZI division criteria for reservoir types. Classified reservoirs exhibit similar flow characteristics, significantly improving the correlation between permeability and porosity. Based on nuclear magnetic resonance (NMR) combined with mercury injection capillary pressure (MICP) experiments, a modeling method for calculating the flow zone index based on the geometric mean of NMR T2 is proposed. This method realizes continuous calculation of FZI based on NMR logging, reservoir classification, and permeability for the entire wellbore, thereby constructing a new permeability prediction method for tight sandstone reservoirs based on NMR logging and FZI classification. Actual application results demonstrate that the permeability calculated using NMR logging is in high agreement with the permeability analyzed from core data, with an average relative error of 45.8%, proving the effectiveness of the proposed method in this study.
Parametric Design of an Advanced Multi-Axial Energy-Storing-and-Releasing Ankle–Foot Prosthesis
Authors: Leopaldi Marco , Brugo Tommaso Maria , Tabucol Johnnidel , Zucchelli Andrea
Published: June 2024

The ankle joint is pivotal in prosthetic feet, especially in Energy-Storing-and-Releasing feet, favoured by individuals with moderate to high mobility (K3/K4) due to their energy efficiency and simple construction. ESR feet, mainly designed for sagittal-plane motion, often exhibit high stiffness in other planes, leading to difficulties in adapting to varied ground conditions, potentially causing discomfort or pain. This study aims to present a systematic methodology for modifying the ankle joint’s stiffness properties across its three motion planes, tailored to individual user preferences, and to decouple the sagittal-plane behaviour from the frontal and transverse ones. To integrate the multi-axial ankle inside the MyFlex-η, the designing of experiments using finite element analysis was conducted to explore the impact of geometric parameters on the joint’s properties with respect to design constraints and to reach the defined stiffness targets on the three ankle’s motion planes. A prototype of the multi-axial ankle joint was then manufactured and tested under FEA-derived load conditions to validate the final configuration chosen. Composite elastic elements and complementary parts of the MyFlex-η, incorporating the multi-axial ankle joint, were developed, and the prosthesis was biomechanically tested according to lower limb prosthesis ISO standards and guidelines from literature and the American Orthotic and Prosthetic Association (AOPA). Experimental tests showed strong alignment with numerical predictions. Moreover, implementing the multi-axial ankle significantly increased frontal-plane compliance by 414% with respect to the same prosthesis with only one degree of freedom on the sagittal plane without affecting the main plane of locomotion performance.
Dynamics of Digital Media Use in Religious Communities—A Theoretical Model
Authors: Müller Julia , Friemel Thomas N.
Published: June 2024

Mediatization and digitalization are trends that are increasingly affecting religious communities and their communicative practices. While many aspects of these developments have been described theoretically and empirically, little is known about the dynamic interplay between digital media use, an individual’s religious meaning system, and the relationships within a religious community. Building on the theory of the mediatization of religion, the functionalist perspective of religion, media selection, and co-orientation research, we propose a dynamic model of digital media use in religious communities. Hereby, the religious functions of meaning-making and social connection are considered important drivers for how individuals engage with others. Additionally, theories on media selection help our understanding of the acceptance and domestication of new technologies, as well as selective exposure to specific content. In combination, the model links the individuals with the social context of their religious communities and vice versa. Furthermore, the theoretical model helps to combine and systematize empirical research from different disciplines that are relevant to understanding today’s digital religious media use. We therefore conclude with a discussion of the benefits of the model for future theoretical developments and empirical research in the field of digital religion and beyond.
Petition, Prostration, and Tears: Painting and Prayer in Roman Catacombs
Authors: Kinney Dale
Published: June 2024

This article examines the evidence for performative prayer in early Roman catacomb painting from the perspective of an art historian. Praying (orant) figures are a dominant theme of third-century painting. Although the orant pose is generally regarded as symbolic, strong evidence connects at least one of the figures with the intercessory prayers offered by the order of widows. Following the “Constantinian turn” in the fourth century, a different form of performative prayer prevailed at the tombs of martyrs, with worshippers lying in prostration (proskynesis) pouring out copious tears. Two much-discussed poems by Prudentius (Peristephanon IX and XI) describe this form of prayer in conjunction with paintings of the gruesome martyrdoms of St. Cassian of Imola and St. Hippolytus. Arguments that the paintings inspired the weeping are incompatible with the nature of catacomb painting at the time, and with testimonies to the power of the tomb itself to compel such displays. The more fruitful suggestion that the ekphrasis in Peristephanon XI reflects a painting of the death of the mythical Hippolytus leads to a grove in the Temple of Diana at Nemi and the legend that the hero was resurrected by Aesculapius.
Bidirectional Feature Fusion and Enhanced Alignment Based Multimodal Semantic Segmentation for Remote Sensing Images
Authors: Liu Qianqian , Wang Xili
Published: June 2024

Image–text multimodal deep semantic segmentation leverages the fusion and alignment of image and text information and provides more prior knowledge for segmentation tasks. It is worth exploring image–text multimodal semantic segmentation for remote sensing images. In this paper, we propose a bidirectional feature fusion and enhanced alignment-based multimodal semantic segmentation model (BEMSeg) for remote sensing images. Specifically, BEMSeg first extracts image and text features by image and text encoders, respectively, and then the features are provided for fusion and alignment to obtain complementary multimodal feature representation. Secondly, a bidirectional feature fusion module is proposed, which employs self-attention and cross-attention to adaptively fuse image and text features of different modalities, thus reducing the differences between multimodal features. For multimodal feature alignment, the similarity between the image pixel features and text features is computed to obtain a pixel–text score map. Thirdly, we propose a category-based pixel-level contrastive learning on the score map to reduce the differences among the same category’s pixels and increase the differences among the different categories’ pixels, thereby enhancing the alignment effect. Additionally, a positive and negative sample selection strategy based on different images is explored during contrastive learning. Averaging pixel values across different training images for each category to set positive and negative samples compares global pixel information while also limiting sample quantity and reducing computational costs. Finally, the fused image features and aligned pixel–text score map are concatenated and fed into the decoder to predict the segmentation results. Experimental results on the ISPRS Potsdam, Vaihingen, and LoveDA datasets demonstrate that BEMSeg is superior to comparison methods on the Potsdam and Vaihingen datasets, with improvements in mIoU ranging from 0.57% to 5.59% and 0.48% to 6.15%, and compared with Transformer-based methods, BEMSeg also performs competitively on LoveDA dataset with improvements in mIoU ranging from 0.37% to 7.14%.
Wide Dynamic Range, High Uniformity Spectral Irradiance Source for Calibration of Scientific-Grade, Large-Size Space Detectors
Authors: Kong Deyao , Yuan Yinlin , Li Haitao , Zhai Wenchao , Zheng Xiaobing
Published: June 2024

In order to meet the high uniformity calibration requirements for scientific-grade, large-size space detectors used in the CHES Extrasolar Planet Exploration Mission, this paper presents the design of a wide dynamic range, high uniformity spectral irradiance source (WHUIS). Utilizing a cascade integrating sphere design, and optimizing the overlapping area radiant flux adjustment structure and illumination light path, we achieve a wide dynamic range and high uniformity irradiance output. We established an irradiance transmission model based on the new assumption and analyzed the influence of factors such as illumination distance, stray light, and non-uniform radiance on the uniformity of irradiance output. The model is then validated by building experimental equipment. The findings show that in a circular area of 40 mm, the irradiance uniformity of our light source system exceeds 99.9%, and constant color temperature is adjustable within six orders of magnitude, consistent with the uniformity level predicted by the model.
Discrimination of Fe-Ni-Laterites from Bauxites Using a Novel Support Vector Machines-Based Methodology on Sentinel-2 Data
Authors: Anifadi Alexandra , Sykioti Olga , Koutroumbas Konstantinos , Vassilakis Emmanuel , Vasilatos Charalampos , Georgiou Emil
Published: June 2024

Currently, the global shift towards green energy is at the forefront of efforts introducing a new era, thus rendering exploration for critical raw materials essential. To this purpose, the utilization of advanced machine learning methods in remote sensing has emerged as a rapid and cost-effective approach. This study proposes a new methodology, utilizing Sentinel-2 satellite data, to distinguish ferronickel (Fe-Ni-) laterite from bauxite across pre-mining, mining, and post-mining occurrences worldwide. Both ores contain mineral raw materials such as nickel, iron, cobalt, and alumina and their discrimination is generally macroscopically challenging, especially when their locations are often in geographical proximity. The proposed method is based on Support Vector Machines (SVM) classification using spectral signatures of known Fe-Ni-laterite and bauxite-bearing pixels in Greece, Cuba, and Jamaica. The highest classification accuracies are obtained by combining b12 with b6 or b7 spectral bands. Comparisons with specific ore mineralogies show that b6 and b7 are strongly linked to the ferric phase, while b12 is mainly associated with the argillic mineralogies, the latter probably being the key discriminating factor between the two ores. From laboratory chemical analyses, we also establish that b12 and b6 or b7 are strongly associated with Al2O3 and Fe2O3 content correspondingly. The proposed method is accurate, it has reduced prospection costs, and it can facilitate the initial screening of broad areas by automatically characterizing whether an ore is bauxite or Fe-Ni-laterite. This underscores the methodology’s significance in ore differentiation and exploration within the context of green energy endeavors.
RETRACTED: Zhang et al. Geometric Construction of Video Stereo Grid Space. Remote Sens. 2022, 14, 2356
Authors: Zhang Huangchuang , Shi Ruoping , Li Ge
Published: June 2024

The Remote Sensing Editorial Office retracts the article “Geometric Construction of Video Stereo Grid Space” [...]
Evaluation of Rayleigh-Corrected Reflectance on Remote Detection of Algal Blooms in Optically Complex Coasts of East China Sea
Authors: Zhang Chengxin , Tao Bangyi , Li Yunzhou , Ai Libo , Zhu Yixian , Liang Liansong , Huang Haiqing , Li Changpeng
Published: June 2024

This study used GOCI-II data to systematically evaluate the feasibility of Rayleigh-corrected reflectance (Rrc) to detect algal blooms in the complex optical environment of the East China Sea (ECS). Based on long-term in situ remote sensing reflectance (Rrs), Rrc spectra demonstrated the similar capability of reflecting the water condition under various atmospheric conditions, and the baseline indices (BLIs) derived from Rrc and Rrs showed good consistency (R2 > 0.98). The effectiveness of five Rrc-based BLIs (SS490, CI, DI, FLH, and MCI) for algal bloom detection was assessed, among which SS490 and MCI showed better performances. A synthetic bloom detection algorithm based on the BLIs of Rrc was then developed to avoid the impact of turbid water. The validation of the BLI algorithm was carried out based on the in situ algal abundance data from 2021 to 2023. Specifically, SS490 showed the best bloom detection result (F-measure coefficient, FM = 0.97), followed by MCI (FM = 0.88). Since the 709 nm bands used in MCI were missing in many ocean color satellites, the SS490 algorithm was more useful in application. Compared to Rrs based bloom detection algorithms, synthetical Rrc BLI proposed in this paper provides more effective observation results and even better algal bloom detection performance. In conclusion, the study confirmed the feasibility of utilizing Rrc for algal bloom detection in the coastal areas of the ECS, and recognized the satisfactory performance of synthetical SS490 by comparing with the other BLIs.
Regional Landslide Susceptibility Assessment and Model Adaptability Research
Authors: Zhang Zhiqiang , Sun Jichao
Published: June 2024

Landslide susceptibility denotes the likelihood of a disaster event under specific conditions. The assessment of landslide susceptibility has transitioned from qualitative to quantitative methods. With the integration of information technology in geological hazard analysis, a range of quantitative models for assessing landslide susceptibility has emerged and is now widely used. To compare and evaluate the accuracy of these models, this study focuses on Xupu County in Hunan Province, applying several models, including the CF model, FR model, CF-LR coupled model, FR-LR coupled model, SVM model, and RF model, to assess regional landslide susceptibility. ROC curves are used to evaluate the reliability of the model’s predictions. The evaluation results reveal that the CF model (AUC = 0.756), FR model (AUC = 0.764), CF-LR model (AUC = 0.776), FR-LR model (AUC = 0.781), SVM model (AUC = 0.814), and RF model (AUC = 0.912) all have AUC values within the range of 0.7–0.9, indicating that the overall accuracy of the models is good and can provide a reference for landslide susceptibility zoning in the study area. Among these, the Random Forest model demonstrates the best accuracy for landslide susceptibility zoning in the study area. By extracting the extremely high susceptibility zones from the landslide susceptibility zonings obtained by six models, a comparative analysis of model adaptability was conducted. The results indicate that the Random Forest model has the best adaptability under specific conditions in Xupu County.
Interferometric Calibration Model for the LuTan-1 Mission: Enhancing Digital Elevation Model Accuracy
Authors: Mou Jingwen , Wang Yu , Hong Jun , Wang Yachao , Wang Aichun , Sun Shiyu , Liu Guikun
Published: June 2024

The LuTan-1 (LT-1) mission, China’s first civilian bistatic spaceborne Synthetic Aperture Radar (SAR) mission, comprises two L-band SAR satellites. These satellites operate in bistatic InSAR strip map mode, maintaining a formation flight with an adjustable baseline to generate global digital elevation models (DEMs) with high accuracy and spatial resolution. This research introduces a dedicated interferometric calibration model for LT-1, tackling the unique challenges of the bistatic system, such as interferometric parameter coupling and the π-ambiguity problem caused by synchronization phase errors. This study validates the model using SAR images from LT-1 and Xinjiang corner reflector data, achieving interferometric phase accuracy better than 0.1 rad and baseline accuracy better than 2 mm, thereby producing high-precision DEMs with a height accuracy meeting the 5 m requirement.
Matching Spring Phenology Indicators in Ground Observations and Remote-Sensing Metrics
Authors: Xu Junfeng , Wu Ting , Peng Dailiang , Fu Xuewei , Yan Kai , Lou Zihang , Zhang Xiaoyang
Published: June 2024

Accurate monitoring of leaf phenology, from individual trees to entire ecosystems, is vital for understanding and modeling forest carbon and water cycles, as well as assessing climate change impact. However, the accuracy of many remote-sensing phenological products remains difficult to directly corroborate using ground-based monitoring, owing to variations in the observed indicators and the scales used. This limitation hampers the practical implementation of remote-sensing phenological metrics. In our study, the start of growing season (SOS) from 2016 to 2021 was estimated for the continental USA using Sentinel-2 images. The results were then matched with several ground-based spring vegetation phenology metrics obtained by the USA National Phenology Network (USA-NPN). In this study, we focused on the relationships between the leaf-unfolding degree (LUD), the SOS, and the factors that drive these measures. Our results revealed that: (1) the ground-based leaves and increasing leaf size stages were significantly correlated with the SOS; (2) with the closest match being observed for a leaf spread of 13%; (2) the relationship between the SOS and LUD varied according to the species and ecoregion, and the pre-season cumulative radiation was found to be the main factor affecting the degree of matching between the ground observations and the metrics derived from the Sentinel-2 data. Our investigations provide a ground-based spring phenology metric that can be used to verify or evaluate remote-sensing spring phenology products and will help to improve the accuracy of remote-sensing phenology metrics.
International Counter-Trafficking: A Zero-Sum Game?—Introduction to the Special Issue
Authors: Clemente Mara
Published: June 2024

“Human trafficking” is widely described as a matter of concern [...]
Multifeature-Based Variational Mode Decomposition–Temporal Convolutional Network–Long Short-Term Memory for Short-Term Forecasting of the Load of Port Power Systems
Authors: Chen Guang , Ma Xiaofeng , Wei Lin
Published: June 2024

Accurate short-term forecasting of power load is essential for the reliable operation of the comprehensive energy systems of ports and for effectively reducing energy consumption. Owing to the complexity of port systems, traditional load forecasting methods often struggle to capture the non-linearity and multifactorial interactions within the factors creating power load. To address these challenges, this study combines variational mode decomposition (VMD), temporal convolutional network (TCN), and long short-term memory (LSTM) network to develop a multi-feature-based VMD-TCN-LSTM model for the short-term forecasting of the power load of ports. VMD is first used to decompose the power load series of ports into multiple, relatively stable components to mitigate volatility. Furthermore, meteorological and temporal features are introduced into the TCN-LSTM model, which combines the temporal feature extraction capability of the TCN and the long term-dependent learning capability of the LSTM. Comparative analyses with other common forecasting models using the observed power load data from a coastal port in China demonstrate that the proposed forecasting model achieves a higher prediction accuracy, with an R-squared value of 0.94, mean squared error of 3.59 MW, and a mean absolute percentage error of 2.36%.
A Comprehensive Experimental Study on the Physical Performance and Durability of Bamboo Bio-Concrete
Authors: Andreola Vanessa M. , da Gloria M’hamed Y. R. , Pepe Marco , Toledo Filho Romildo D.
Published: June 2024

In recent decades, the building sector has been moving toward promoting renewable raw materials to reduce greenhouse gas emissions associated with construction materials. One of the most valuable alternatives is the use of large-volume fractions of vegetable aggregates, leading to the development of bio-based cement mixture. A review of the recent scientific literature has shown that traditional design rules cannot be applied to bio-based cement mixtures. In this context, this study summarizes the results of a comprehensive experimental campaign aimed at unveiling the influence of bamboo particles on the physical properties and durability indicators of Bamboo Bio-Concrete (BBC) designed by applying a recent methodology proposed by the authors. The mixtures were produced using bamboo particles at a volumetric fraction of 45% and 50%. Fundamental properties such as density, thermal conductivity, capillary water absorption, and drying shrinkage were measured. The results obtained herein highlight the lightweight (density lower than 786 kg/m3) and insulating properties (thermal conductivity within 0.32 to 0.52 W/mK) of the BBC. The capillary absorption ranged between 2.40 and 2.83 g/cm2, whereas the drying shrinkage ranged between 2500 and 5000 µε. These properties indicate the feasibility of using this material in various applications in the construction sector.
Study on Sustainable Lightweight Design of Airport Waiting Chair Frame Structure Based on ANSYS Workbench
Authors: Zhang Xiaoying , Xu Wei , Li Rongrong , Zhou Jichun , Luo Zhongyu
Published: June 2024

The airport waiting chair frames, as an important part of the overall seating, must be designed to provide comfort, safety, and aesthetic appeal. While the airport furniture industry has made progress in terms of sustainability, more efforts are needed to improve material selection, manufacturing processes, and supply chain management to support the development of sustainable furniture. This study proposes innovative ideas for the lightweight design of the frame, based on the limitations of the existing design. Firstly, structural innovations are discussed, non-traditional mesh panels and curved rounded designs are discussed, and non-introduced mesh panels and curved designs are used to enhance the strength and stability of airport waiting chairs and enhance their overall performance. Secondly, innovations in lightweighting have focused on adjusting the thickness dimensions to enhance comfort, material utilization, and sustainability as well as to achieve a lightweight and thin appearance effect. In order to determine the optimal ranges of values for the thickness of the seat surface support strip (P5), the thickness of the backrest strip (P3), and the thickness of the seat panel (P1), nine groups of chairs with different frame sizes were tested using an orthogonal experimental method. Based on the experimental results for size and topology optimization, NX2312 software modeling will be imported into ANSYS Workbench for static analysis. Using the optimized results, the use of 2.842 kg of steel was successfully reduced by 34.8% to ensure the seat’s stability. This provides a reference and idea for the digital and standardized innovative design of airport waiting chair furniture structure in the future. Through digital design and lightweight optimization, material savings and effective use of resources can be achieved, promoting the goal of sustainable development.
Integrated Ozonation and Photocatalysis to Remove Pollutants for Reuse of Rainwater
Authors: Marszałek Anna , Affek Katarzyna , Załęska-Radziwiłł Monika , Dudziak Mariusz
Published: June 2024

Rainwater is susceptible to pollutants such as sulphur dioxide, nitrogen oxides, heavy metals, and particles, posing challenges to water quality protection and soil degradation, impacting ecosystems and agriculture. The study focuses on the effectiveness of combined ozonation and photocatalysis in improving physicochemical parameters and reducing toxic substances. Integrated analyses, including ecotoxicological assessments, evaluate the impact of treatment on actual rainwater samples. The results indicate significant reductions in color, heavy metals, and organic pollutants after treatment. Microbiological analyses reveal the inactivation of E. coli, which is crucial for safe water reuse. Ecotoxicity studies show no toxicity to crustaceans, but slight toxicity to algae and bioluminescence bacteria in post-treatment samples. Genotoxicity assessments indicate that there is no detectable DNA damage. Overall, the study highlights the complex nature of rainwater pollution and the efficacy of photocatalytic ozonation in reducing contaminants, underscoring the need for more research to ensure sustainable water resource management.
Improving Quality of Work for Positive Health: Interaction of Sustainable Development Goal (SDG) 8 and SDG 3 from the Sustainable HRM Perspective
Authors: Mariappanadar Sugumar
Published: June 2024

Evidence indicates that harmful work practices such as long working hours in high-income countries kill more people than road accidents (International Labour Organisation, 2021). The Global Reporting Initiatives (GRIs) for Sustainability—Occupational Health and Safety (OHS) 403 standards (2018)—include ‘work-related leading indicators’, but currently, a limited understanding of these exists to prevent an increase in deaths due to work-related non-communicable diseases. The health harm of work construct, which is different from work stress, is a recent development in the sustainable HRM literature explaining employees’ perception of the restrictions imposed by work practices on achieving positive health. To promote health and well-being for all in the employment stage of life (SDG 3), this study aims to establish the health harm of work that is caused by work intensification as work-related leading indicators of adverse/decent working conditions (SDG 8). A total of 605 white-collar full-time employees completed work intensification, the health harm of work, and mental well-being questionnaires, and self-reported on health risk factors and chronic health conditions. Structural equation modelling was used to analyse the mediational research model of the dynamic transitionary effect of work intensification on employee health and well-being through the health harm of work. The findings indicate that work intensification improves employee mental well-being (SDG 3), but the mediation transitionary effect of the health harm of work highlights that mental well-being is reduced when work intensification (SDG 8) started increasing the health harm of work among individuals. The health harm of work from the sustainable HRM perspective is found to be effective work-practice related leading indicators of health and well-being in the working population. Research and practical implications to develop a business-health agenda of shared values are discussed.
From Bibliometric Analysis to Experimental Validation: Bibliometric and Literature Review of Four Cementing Agents in Soil Stabilization with Experimental Focus on Xanthan Gum
Authors: Baldovino Jair de Jesús Arrieta , Palma Calabokis Oriana , Saba Manuel
Published: June 2024

This article focuses on the search for efficient solutions to enhance the mechanical strength of geomaterials, especially soils, with crucial applications in civil engineering. Four promising materials are explored as soil improvement agents: natural latex (rubber trees), lignosulfonate (paper industry byproduct), xanthan gum (bacterial fermentation), and eggshell lime. While other sustainable options exist, these four were chosen for their distinct characteristics and potential for further study. Natural latex, derived from rubber trees, demonstrates exceptional potential for strengthening the mechanical resistance of soils, offering a path to effective stabilization without compromising environmental sustainability. Lignosulfonate, a paper industry byproduct, emerges as an alternative that can significantly enhance the load-bearing capacity of soils, boosting its applicability in civil engineering projects. Xanthan gum, produced through bacterial fermentation, possesses unique properties that increase soil cohesion and strength, making it a valuable option for geotechnical applications. Finally, despite potential challenges, eggshell lime shows promising potential in enhancing the mechanical resistance of soils. This study highlights the importance of evaluating and comparing these agents in terms of their effectiveness in improving the mechanical strength of soils in civil engineering applications. In the literature review, the impact of stabilizer addition (%) was examined for the four cementing agents studied, along with its influence on key soil properties like optimum moisture content (OMC, %), maximum dry density (MDD, gm/cc), California bearing ratio (CBR, %), uniaxial compressive strength (UCS) at 28 days (MPa), and the change in UCS (ΔUCS, %) among other physicochemical parameters. Appropriate selection of these materials can lead to developing more robust and sustainable geomaterials, promoting significant advancements in geotechnical engineering and civil construction practices. To evaluate their effectiveness, the efficiency of one of them was assessed experimentally. Xanthan gum (XG) was selected to biopolymerize clay soil. Specimens were prepared for strength and stiffness tests, including unconfined compression, scanning electron microscopy (SEM), and ultrasonic wave analysis. The impact of stabilizer concentration was examined (e.g., 1%, 3%, 5% xanthan gum) to assess how dosage affects the soil–stabilizer mixture. The results showed that the rubber increases the unconfined compression and stiffness of the soil, controlled by the XG’s porosity/volumetric quantity ratio. The research demonstrates the potential of XG, but a broader analysis of all four materials with the outlined testing methods paves the way for future advancements in geotechnical engineering.