bluuebunny/crossref_metadata_2025 huggingface dataset:
GRB7 Plays a Vital Role in Promoting the Progression and Mediating Immune Evasion of Ovarian Cancer
Authors: Wen Liang , Hu Wei , Hou Sen , Luo Ce , Jin Yiteng , Zeng Zexian , Zhang Zhe , Meng Yuanguang
Published: August 2024

Background: Despite breakthroughs in treatment, ovarian cancer (OC) remains one of the most lethal gynecological malignancies, with an increasing age-standardized mortality rate. This underscores an urgent need for novel biomarkers and therapeutic targets. Although growth factor receptor-bound protein 7 (GRB7) is implicated in cell signaling and tumorigenesis, its expression pattern and clinical implications in OC remain poorly characterized. Methods: To systematically investigate GRB7’s expression in OC, our study utilized extensive datasets from TCGA, GTEx, CCLE, and GEO. The prognostic significance of GRB7 was evaluated by means of Kaplan–Meier and Cox regression analyses. Using a correlation analysis and gene set enrichment analysis, relationships between GRB7’s expression and gene networks, immune cell infiltration and immunotherapy response were investigated. In vitro experiments were conducted to confirm GRB7’s function in the biology of OC. Results: Compared to normal tissues, OC tissues exhibited a substantial upregulation of GRB7. Reduced overall survival, disease-specific survival, and disease-free interval were all connected with high GRB7 mRNA levels. The network study demonstrated that GRB7 is involved in pathways relevant to the course of OC and has a positive connection with several key driver genes. Notably, GRB7’s expression was linked to the infiltration of M2 macrophage and altered response to immunotherapy. Data from single-cell RNA sequencing data across multiple cancer types indicated GRB7’s predominant expression in malignant cells. Moreover, OC cells with GRB7 deletion showed decreased proliferation and migration, as well as increased susceptibility to T cell-mediated cytotoxicity. Conclusion: With respect to OC, our results validated GRB7 as a viable prognostic biomarker and a promising therapeutic target, providing information about its function in tumorigenesis and immune modulation. GRB7’s preferential expression in malignant cells highlights its significance in the biology of cancer and bolsters the possibility that it could be useful in enhancing the effectiveness of immunotherapy.
Effect of Burned Multi-Crop Ashes on Faba Bean-Development Parameters
Authors: Petlickaitė Rita , Romaneckas Kęstutis , Sinkevičienė Aušra , Praspaliauskas Marius , Jasinskas Algirdas
Published: August 2024

The use of burned plant biomass ashes could help not only with respect to utilizing combustion residues, but also with respect to optimizing the nutrition of cultivated agricultural plants without harming the environment. With this aim, a pot experiment of the effects of multi-crop biomass ash on faba bean seedlings was carried out in the Academy of Agriculture of the Vytautas Magnus University (VMU). Four ash fertilization rates were tested: 1. unfertilized (N0, comparative-control treatment); 2. fertilized at a low rate (N1, 200 kg ha−1); 3. fertilized at an average rate (N2, 1000 kg ha−1); 4. fertilized at a high rate (N3, 2000 kg ha−1). Final observations showed that ash fertilization significantly increases the height of faba bean sprouts by 21–38%, the length of the roots by 10–20% and the chlorophyll concentration in the leaves by 17%. The average green biomass of faba bean sprouts consistently increased with increasing fertilization rate, from 56% to 209%. Dried biomass increased by 160–220%. With increasing ash fertilization rate, the percentage of dry matter in the roots decreased by 10–50%. We recommend fertilizing faba bean with medium (1000 kg ha−1) and high (2000 kg ha−1) ash rates, as these rates led to the largest plants with the highest productivity potential.
On the Trail of Morphological Traits: Morphometry Helps to Clarify Morphological Variation in Section Viperella (Sisyrinchium)
Authors: Dani Julia Gabriele , Inácio Camila Dellanhese , Souza-Chies Tatiana T.
Published: August 2024

Sisyrinchium, a large genus of the Iridaceae family, is divided into ten sections and defined by genetic, morphological and phylogenetic traits. The section Viperella, though monophyletic, encounters taxonomic hurdles, particularly within the Sisyrinchium palmifolium L. and Sisyrinchium vaginatum Spreng complexes, resulting in numerous misidentifications. The taxonomic confusion in the group may stem from various factors, emphasizing extensive morphological variations, leading to overlapping characteristics. We used morphometric approaches to better characterize the species belonging to two complexes, assess their variation and identify diagnostic traits for taxonomy enhancement. We assessed 16 quantitative traits for the S. palmifolium complex and 15 for the S. vaginatum complex, totaling 652 specimens recorded across 15 herbaria covering the entire species’ distribution area. In the S. vaginatum complex, 66.5% of the variations were accounted for in the first two axes, while in the S. palmifolium complex, the first two axes explained 55.3%. Our findings revealed that both complexes exhibited many morphological variations, leading to a characteristic overlap. These characteristics may have arisen due to recent diversifications of the group and niche overlaps. Additionally, we identified some morphological characteristics that are useful for distinguishing species. Finally, we compiled a section gathering all useful characteristics for species delimitation within the group, aiming to facilitate non-experts in deciphering this species complex.
Assessment of Fatty Acid and Oxylipin Profile of Resprouting Olive Trees Positive to Xylella fastidiosa subsp. pauca in Salento (Apulia, Italy)
Authors: Scala Valeria , Scortichini Marco , Marini Federico , La Montagna Dario , Beccaccioli Marzia , Micalizzi Kristina , Cacciotti Andrea , Pucci Nicoletta , Tatulli Giuseppe , Fiorani Riccardo , Loreti Stefania , Reverberi Massimo
Published: August 2024

Xylella fastidiosa subsp. pauca ST53 (XFP), the causal agent of olive quick decline syndrome (OQDS), was thoroughly investigated after a 2013 outbreak in the Salento region of Southern Italy. Some trees from Ogliarola Salentina and Cellina di Nardò, susceptible cultivars in the Gallipoli area, the first XFP infection hotspot in Italy, have resprouted crowns and are starting to flower and yield fruits. Satellite imagery and Normalized Difference Vegetation Index analyses revealed a significant improvement in vegetation health and productivity from 2018 to 2022 of these trees. Lipid molecules have long been recognized as plant defense modulators, and recently, we investigated their role in XFP-positive hosts and in XFP-resistant as well as in XFP-susceptible cultivars of olive trees. Here, we present a case study regarding 36 olive trees (12 XFP-positive resprouting, 12 XFP-positive OQDS-symptomatic, and 12 XFP-negative trees) harvested in 2022 within the area where XFP struck first, killing millions of trees in a decade. These trees were analyzed for some free fatty acid, oxylipin, and plant hormones, in particular jasmonic and salicylic acid, by targeted LC-MS/MS. Multivariate analysis revealed that lipid markers of resistance (e.g., 13-HpOTrE), along with jasmonic and salicylic acid, were accumulated differently in the XFP-positive resprouting trees from both cultivars with respect to XFP-positive OQDS symptomatic and XFP-negative trees, suggesting a correlation of lipid metabolism with the resprouting, which can be an indication of the resiliency of these trees to OQDS. This is the first report concerning the resprouting of OQDS-infected olive trees in the Salento area.
Multiscale Modeling of Vinyl-Addition Polynorbornenes: The Effect of Stereochemistry
Authors: Shahidi Nobahar , Laub Jeffrey A. , Vogiatzis Konstantinos D. , Doxastakis Manolis
Published: August 2024

Vinyl-addition polynorbornenes are candidates for designing high-performance polymers due to unique characteristics, which include a high glass transition temperature associated with a rigid backbone. Recent studies have established that the processability and properties of these polymers can be fine-tuned by using targeted substitutions. However, synthesis with different catalysts results in materials with distinct properties, potentially due to the presence of various stereoisomers that are difficult to quantify experimentally. Herein, we develop all-atom models of polynorbornene oligomers based on classical force fields and density functional theory. To establish the relationship between chemical architecture, chain conformations, and melt structure, we perform detailed molecular dynamics simulations with the fine-tuned atomistic force field and propose simpler coarse-grained descriptions to address the high molecular weight limit. All-atom simulations of oligomers suggest high glass transition temperatures in the range of 550–600 K. In the melt state (800 K), meso chains form highly rigid extended coils (C∞≈11) with amorphous structural characteristics similar to the X-ray diffraction data observed in the literature. In contrast, simulations with racemo chains predict highly helical tubular chain conformations that could promote assembly into crystalline structures.
Effect of Partial Elimination of Mitochondrial DNA on Genome-Wide Identified AOX Gene Family in Chlamydomonas reinhardtii
Authors: Khan Asadullah , Jihong Zuo , Luo Haolin , Raza Ali , Hussain Quaid , Hu Zhangli
Published: August 2024

Using Chlamydomonas as a model organism, we attempted to eliminate mitochondrial DNA (mtDNA) similar to rho0 or rho− cells (completely or partially mtDNA-eliminated cells) in yeast. We successfully generated partially mtDNA-eliminated cells named as crm- cells, causing the inactivation of mitochondrial activity. We used three different chemicals to eliminate mtDNA including acriflavine (AF), ethidium bromide (EB) and dideoxycytidine (ddC) which prevents replication, inhibits POLG (DNA polymerase gamma) and terminates the mtDNA chain, respectively. The qPCR method was used to detect the mtDNA copy number and the selected rrnL6 gene for the detection of mitochondria, as well as the selected Chlamydomonas CC-124 strain. A reduction in the mitochondrial copy number led to a higher expression of AOX1, UCP1, PGRL1 and ICL1, which indicates the disturbance of the mitochondria–chloroplast ATP and NADPH balance. We selected AOX genes to further study this family and carried out a genome-wide search to identify AOX genes in green algae (C. reinhardtii). Our results revealed that C. reinhardtii contains four AOX genes, i.e., CrAOX1, CrAOX2, CrAOX3 and CrAOX4, which are distributed on Chr 3, Chr7 and Chr9. All CrAOX genes were predicted to localize in mitochondria using bioinformatics tools. Phylogenetic analysis suggests that these CrAOXs are subdivided into four groups and genes existing in the same group could perform identical functions. Collinearity analysis describes the strong evolutionary relationships of AOXs between the unicellular green algae Chlamydomonas reinhardtii and the multicellular green algae Volvox carteri. GO (gene ontology) annotation analysis predicted that CrAOXs played an integral part in carrying out alternate oxidative and respirative activities. Three putative miRNAs, cre-miR1162-3p, cre-miR1171 and cre-miR914, targeting the CrAOX2 gene were identified. Our studies have laid a foundation for the further use of partially mtDNA-eliminated cells and elucidating the functional characteristics of the AOX gene family.
Multiapproach Design Methodology of a Downscaled Wet Scrubber to Study the Collection of Submicronic Particles from Waste Incineration Flue Gas
Authors: Hoyos Angela , Joubert Aurélie , Bouhanguel Ala , Henry Marc , Durécu Sylvain , Le Coq Laurence
Published: August 2024

Wet scrubbers are traditionally used as dedusting systems in waste incineration plants for wet flue gas treatment. Although these devices are not particularly performant at capturing submicron particles, which are associated with health and environmental hazards, their collection efficiency can be improved by optimizing operating conditions. This study presents the design methodology of a downscaled wet scrubber, constructed and implemented at a municipal waste incineration plant to be fed with real fumes, and to study its efficiency towards the removal of submicronic particles. The downscaled scrubber was designed to operate with flue gas at 200 °C, high humidity (1% RH), and an average total particle concentration of 200 mg/Nm3. A criterion of geometric, aerodynamic, and residence time similarities to an existing industrial scrubber was targeted. The height of the device was selected by matching the theoretical fractional particle collection efficiencies of the industrial and downscaled scrubbers. Featuring a cylindrical shape, the downscaled scrubber has a diameter of 0.3 m and a height of 2.5 m. It operates in co-current with water injected through four spray levels. Computational fluid dynamics simulations were conducted to analyze the gas flow structure within the device, and the results were validated by hot wire anemometer velocity measurements.
Applicability of a Fractal Model for Sandstone Pore-Fracture Structure Heterogeneity by Using High-Pressure Mercury Intrusion Tests
Authors: Zou Shuangying , Sun Mingyuan , Chen Yongmei , Li Qinglin , Chang Xiangchun , Zhang Junjian , Ren Guangying
Published: August 2024

Pore structure heterogeneity affects the porosity and permeability variation of tight sandstone, thereby restricting sandstone gas production. In total, 11 sandstone samples were taken as a target in the northwest margin of the Junggar Basin. Then, scanning electron microscope and high-pressure mercury injection tests are used to study the distribution of a pore and fracture system in the target sandstone. On this basis, single and multifractal models are used to quantitatively characterize the heterogeneity of pore structure, and the applicability of the classification model in characterizing the heterogeneity of the pore-fracture structure is explored. The results are as follows. (1) The target samples are divided into two types, with the mercury removal efficiency of type A samples ranging from 44.6 to 51.8%, pore size mainly distributed between 100 and 1000 nm, and pore volume percentage ranging from 43 to 69%. The mercury removal efficiency of type B samples ranges from 14 to 28%, and pore diameter distribution is relatively uniform. (2) Different fractal models represent different physical meanings. The calculation results of sponge and thermodynamic fractal models indicate that the heterogeneity of pore structure distribution in the type B sample is significantly stronger than that in type A, which is inconsistent with the conclusions of the Sierpinski model. This is because the aforementioned two models characterize the complexity of pore surface area, while the Sierpinski model characterizes the roughness of pore volume. The comparison shows that there is a significant correlation between the thermal dimensionality value DT and the volume percentage of macropores and mesopores. Therefore, the thermodynamic model can better quantitatively characterize the heterogeneity of macropore and mesoporous pore distribution. (3) The results indicate that higher pore volume range is mainly influenced by mesopores and macropores. From the relationship curve between mercury removal efficiency and single fractal dimension, it can be seen that mercury removal efficiency is greatly affected by distribution heterogeneity of the lower value area of pore volume, and it has no obvious relationship with distribution heterogeneity in the lower value area of the pore volume.
Radioiodinated Anastrozole and Epirubicin for HER2-Targeted Cancer Therapy: Molecular Docking and Dynamics Insights with Implications for Nuclear Imaging
Authors: Binmujlli Mazen Abdulrahman
Published: August 2024

This study evaluates radioiodinated anastrozole ([125I]anastrozole) and epirubicin ([125I]epirubicin) for HER2-targeted cancer therapy, utilizing radiopharmaceutical therapy (RPT) for personalized treatment of HER2-positive cancers. Through molecular docking and dynamics simulations (200 ns), it investigates these compounds’ binding affinities and mechanisms to the HER2 receptor compared to lapatinib, a known HER2 inhibitor. Molecular docking studies identified [125I]epirubicin with the highest ΔGbind (−10.92 kcal/mol) compared to lapatinib (−10.65 kcal/mol) and [125I]anastrozole (−9.65 kcal/mol). However, these differences were not statistically significant. Further molecular dynamics (MD) simulations are required to better understand the implications of these findings on the therapeutic potential of the compounds. MD simulations affirmed a stable interaction with the HER2 receptor, indicated by an average RMSD of 4.51 Å for [125I]epirubicin. RMSF analysis pointed to significant flexibility at key receptor regions, enhancing the inhibitory action against HER2. The [125I]epirubicin complex maintained an average of four H-bonds, indicating strong and stable interactions. The average Rg values for [125I]anastrozole and [125I]epirubicin complexes suggest a modest increase in structural flexibility without compromising protein compactness, reflecting their potential to induce necessary conformational changes in the HER2 receptor function. These analyses reveal enhanced flexibility and specific receptor region interactions, suggesting adaptability in binding, which could augment the inhibitory action against HER2. MM-PBSA calculations indicate the potential of these radioiodinated compounds as HER2 inhibitors. Notably, [125I]epirubicin exhibited a free binding energy of −65.81 ± 0.12 kJ/mol, which is comparable to lapatinib at −64.05 ± 0.11 kJ/mol and more favorable than [125I]anastrozole at −57.18 ± 0.12 kJ/mol. The results suggest electrostatic interactions as a major contributor to the binding affinity. The computational analysis underscores that [125I]anastrozole and [125I]epirubicin may have a promising role as HER2 inhibitors, especially [125I]epirubicin due to its high binding affinity and dynamic receptor interactions. These findings, supported by molecular docking scores and MM-PBSA binding energies, advocate for their potential superior inhibitory capability against the HER2 receptor. To validate these computational predictions and evaluate the therapeutic potential of these compounds for HER2-targeted cancer therapy, it is essential to conduct empirical validation through both in vitro and in vivo studies.
Using Phosphogypsum as a Source of Calcium Sulfate When Synthesizing Calcium Molybdate Nanoparticles
Authors: Belaoufi Youssef , Bensemlali Meryem , Hatimi Badreddine , Mortadi Halima , Labjar Najoua , Nunzi Jean-Michel , El Idrissi Mohammed , Aarfane Abdellatif , Bakasse Mina , Nasrellah Hamid
Published: August 2024

Calcium molybdate (CaMoO4) is of significant interest due to its unique properties and numerous industrial applications, such as catalysis, electrochemistry, and optoelectronics. In this study, we developed an economical and environmentally friendly method to synthesize calcium molybdate from Moroccan phosphogypsum (PG) industrial waste and sodium molybdate, all at room temperature. Comprehensive analysis through X-ray diffraction (XRD), Fourier transform infrared spectroscopy (FT-IR), Raman vibrational spectroscopy, and scanning electron microscopy (SEM) revealed the high purity of the synthesized calcium molybdate, with particle sizes of only 12 nm. Additionally, optical characteristics were studied using ultraviolet-visible spectroscopy (UV-vis), which showed an optical band gap of Egap = 3.96 eV for CaMoO4. These results confirm the successful synthesis of calcium molybdate nanoparticles from Moroccan phosphogypsum, demonstrating an effective pathway to valorize this industrial waste into a valuable material. This approach contributes to environmental sustainability by reducing dependence on rare chemicals while offering innovative solutions for the industry’s sustainable development.
Jesus’s Origins (Matthew 1–2) as Cultural Trauma
Authors: Doane Sébastien
Published: August 2024

Jeffrey Alexander’s social theory about trauma provides a theoretical framework to explore Matthew’s Gospel’s two first chapters as a trauma narrative that wrestles in a creative way with at least two significant issues for its original audience: (1) How can Jesus be the Christ/Messiah and yet undergo a shameful and violent death? (2) What are the national and theological implications of the destruction of the Temple in AD 70? Alexander’s four dimensions of representations of cultural trauma (the nature of the pain; the nature of the victim; the relation of the trauma victim to a wider audience; and the attribution of responsibility) guide the analysis. Matthew 1–2, as a trauma narrative, processes past trauma to encourage resilience against future traumatization. This can be a powerful tool to shape identity and promote solidarity by opening new avenues for understanding violent imagery.
Significant Increase in African Water Vapor over 2001–2020
Authors: Wang Ruonan , Wu Guiping , Liu Yongwei , Wang Rong , Fan Xingwang , Liu Yuanbo
Published: August 2024

Atmospheric water vapor is not only a key element of the global hydrological cycle but also the most abundant greenhouse gas. The phase transition and transportation of water vapor are essential for maintaining global energy balance and regulating hydrological processes. However, due to insufficient meteorological observational data, climate research in Africa faces significant limitations despite its substantial contribution to changes in global precipitable water vapor (PWV). In this study, we used MODIS near-infrared (NIR) PWV products and Berkeley temperature data to depict the spatial–temporal variability in PWV across Africa from 2001 to 2020. The results reveal a significant increasing trend in PWV over Africa, with an increase of 0.0158 cm/year. Nearly 99.96% of Africa shows an increase in PWV, with 88.95% of these areas experiencing statistically significant changes, particularly in central regions of Africa. The increase in PWV is more pronounced in high-value months compared to low-value months. The equatorial region of the Congo Basin exhibits higher PWV, which gradually decreases as latitude increases. Despite significant warming (0.0162 °C/year) in Africa, there is no consistent positive correlation between temperature and water vapor. A positive relationship between PWV and temperature is observed in western Africa, while a negative relationship is noted in eastern and southern Africa on an annual scale. Additionally, an increasing trend in precipitation (4.6669 mm/year) is observed, with a significant positive correlation between PWV and precipitation across most of Africa, although this relationship varies by month. These findings provide valuable insights into the comprehension of the hydrothermal variation in Africa amidst climate warming.
Calculating Vegetation Index-Based Crop Coefficients for Alfalfa in the Mesilla Valley, New Mexico Using Harmonized Landsat Sentinel-2 (HLS) Data and Eddy Covariance Flux Tower Data
Authors: Sabie Robert , Bawazir A. Salim , Buenemann Michaela , Steele Caitriana , Fernald Alexander
Published: August 2024

The goal of this study is to investigate the usefulness of the relatively new 30 m spatial and <5.7-day temporal resolution Harmonized Landsat Sentinel-2 (HLS) dataset for calculating vegetation index-based crop coefficients (KcVI) for estimating field scale crop evapotranspiration (ETc). Increased spatial and temporal resolution ETc estimates are needed for improving irrigation scheduling, monitoring impacts of water conservation programs, and improving crop yield. The crop coefficient (Kc) method is widely used for estimating ETc. Remote sensing vegetation indices (VI) are highly correlated to Kc and allow the creation of a KcVI but the approach is limited by the availability of high temporal and spatial resolutions. We selected and calculated sixteen commonly used VIs using HLS data and regressed them against field-measured ET for alfalfa in the Mesilla Valley, New Mexico to create linear KcVI models. All models showed good agreement with Kc (r2 > 0.67 and RMSE < 0.15). ETc prediction resulted in an MAE ranging between 0.35- and 0.64-mm day−1, an MSE ranging between 0.20- and 0.75-mm day−1 and an MAPD ranging between 10.0 and 16.5%. The largest differences in predicted ETc occurred early in the growing season and during cutting periods when the spectral signal could be influenced by soil background or irrigation events. The results suggest that applying the KcVI approach to the HLS dataset can help fill in the data gap in remote sensing ET tools. Future work should focus on assessing additional crops and integration into other tools such as the emerging OpenET platform.
Implicit Sharpness-Aware Minimization for Domain Generalization
Authors: Dong Mingrong , Yang Yixuan , Zeng Kai , Wang Qingwang , Shen Tao
Published: August 2024

Domain generalization (DG) aims to learn knowledge from multiple related domains to achieve a robust generalization performance in unseen target domains, which is an effective approach to mitigate domain shift in remote sensing image classification. Although the sharpness-aware minimization (SAM) method enhances DG capability and improves remote sensing image classification performance by promoting the convergence of the loss minimum to a flatter loss surface, the perturbation loss (maximum loss within the neighborhood of a local minimum) of SAM fails to accurately measure the true sharpness of the loss landscape. Furthermore, its variants often overlook gradient conflicts, thereby limiting further improvement in DG performance. In this paper, we introduce implicit sharpness-aware minimization (ISAM), a novel method that addresses the deficiencies of SAM and mitigates gradient conflicts. Specifically, we demonstrate that the discrepancy in training loss during gradient ascent or descent serves as an equivalent measure of the dominant eigenvalue of the Hessian matrix. This discrepancy provides a reliable measure for sharpness. ISAM effectively reduces sharpness and mitigates potential conflicts between gradients by implicitly minimizing the discrepancy between training losses while ensuring a sufficiently low minimum through minimizing perturbation loss. Extensive experiments and analyses demonstrate that ISAM significantly enhances the model’s generalization ability on remote sensing and DG datasets, outperforming existing state-of-the-art methods.
Advancing Volcanic Activity Monitoring: A Near-Real-Time Approach with Remote Sensing Data Fusion for Radiative Power Estimation
Authors: Di Bella Giovanni Salvatore , Corradino Claudia , Cariello Simona , Torrisi Federica , Del Negro Ciro
Published: August 2024

The global, near-real-time monitoring of volcano thermal activity has become feasible through thermal infrared sensors on various satellite platforms, which enable accurate estimations of volcanic emissions. Specifically, these sensors facilitate reliable estimation of Volcanic Radiative Power (VRP), representing the heat radiated during volcanic activity. A critical factor influencing VRP estimates is the identification of hotspots in satellite imagery, typically based on intensity. Different satellite sensors employ unique algorithms due to their distinct characteristics. Integrating data from multiple satellite sources, each with different spatial and spectral resolutions, offers a more comprehensive analysis than using individual data sources alone. We introduce an innovative Remote Sensing Data Fusion (RSDF) algorithm, developed within a Cloud Computing environment that provides scalable, on-demand computing resources and services via the internet, to monitor VRP locally using data from various multispectral satellite sensors: the polar-orbiting Moderate Resolution Imaging Spectroradiometer (MODIS), the Sea and Land Surface Temperature Radiometer (SLSTR), and the Visible Infrared Imaging Radiometer Suite (VIIRS), along with the geostationary Spinning Enhanced Visible and InfraRed Imager (SEVIRI). We describe and demonstrate the operation of this algorithm through the analysis of recent eruptive activities at the Etna and Stromboli volcanoes. The RSDF algorithm, leveraging both spatial and intensity features, demonstrates heightened sensitivity in detecting high-temperature volcanic features, thereby improving VRP monitoring compared to conventional pre-processed products available online. The overall accuracy increased significantly, with the omission rate dropping from 75.5% to 3.7% and the false detection rate decreasing from 11.0% to 4.3%. The proposed multi-sensor approach markedly enhances the ability to monitor and analyze volcanic activity.
TC–Radar: Transformer–CNN Hybrid Network for Millimeter-Wave Radar Object Detection
Authors: Jia Fengde , Li Chenyang , Bi Siyi , Qian Junhui , Wei Leizhe , Sun Guohao
Published: August 2024

In smart transportation, assisted driving relies on data integration from various sensors, notably LiDAR and cameras. However, their optical performance can degrade under adverse weather conditions, potentially compromising vehicle safety. Millimeter-wave radar, which can overcome these issues more economically, has been re-evaluated. Despite this, developing an accurate detection model is challenging due to significant noise interference and limited semantic information. To address these practical challenges, this paper presents the TC–Radar model, a novel approach that synergistically integrates the strengths of transformer and the convolutional neural network (CNN) to optimize the sensing potential of millimeter-wave radar in smart transportation systems. The rationale for this integration lies in the complementary nature of CNNs, which are adept at capturing local spatial features, and transformers, which excel at modeling long-range dependencies and global context within data. This hybrid approach allows for a more robust and accurate representation of radar signals, leading to enhanced detection performance. A key innovation of our approach is the introduction of the Cross-Attention (CA) module, which facilitates efficient and dynamic information exchange between the encoder and decoder stages of the network. This CA mechanism ensures that critical features are accurately captured and transferred, thereby significantly improving the overall network performance. In addition, the model contains the dense information fusion block (DIFB) to further enrich the feature representation by integrating different high-frequency local features. This integration process ensures thorough incorporation of key data points. Extensive tests conducted on the CRUW and CARRADA datasets validate the strengths of this method, with the model achieving an average precision (AP) of 83.99% and a mean intersection over union (mIoU) of 45.2%, demonstrating robust radar sensing capabilities.
Investigating the Impacts of Autonomous Vehicles on the Efficiency of Road Network and Traffic Demand: A Case Study of Qingdao, China
Authors: Liu Chunguang , Zyryanov Vladimir , Topilin Ivan , Feofilova Anastasia , Shao Mengru
Published: August 2024

Rapid urbanization has led to the development of intelligent transport in China. As active safety technology evolves, the integration of autonomous active safety systems is receiving increasing attention to enable the transition from functional to all-weather intelligent driving. In this process of transformation, the goal of automobile development becomes clear: autonomous vehicles. According to the Report on Development Forecast and Strategic Investment Planning Analysis of China’s autonomous vehicle industry, at present, the development scale of China’s intelligent autonomous vehicles has exceeded market expectations. Considering limited research on utilizing autonomous vehicles to meet the needs of urban transportation (transporting passengers), this study investigates how autonomous vehicles affect traffic demand in specific areas, using traffic modeling. It examines how different penetration rates of autonomous vehicles in various scenarios impact the efficiency of road networks with constant traffic demand. In addition, this study also predicts future changes in commuter traffic demand in selected regions using a constructed NL model. The results aim to simulate the delivery of autonomous vehicles to meet the transportation needs of the region.
Artificial Internet of Things, Sensor-Based Digital Twin Urban Computing Vision Algorithms, and Blockchain Cloud Networks in Sustainable Smart City Administration
Authors: Matei Ani , Cocoșatu Mădălina
Published: August 2024

The aim of this paper is to synthesize and analyze existing evidence on interconnected sensor networks and digital urban governance in data-driven smart sustainable cities. The research topic of this systematic review is whether and to what extent smart city governance can effectively integrate the Internet of Things (IoT), Artificial Intelligence of Things (AIoT), intelligent decision algorithms based on big data technologies, and cloud computing. This is relevant since smart cities place special emphasis on the involvement of citizens in decision-making processes and sustainable urban development. To investigate the work to date, search outcome management and systematic review screening procedures were handled by PRISMA and Shiny app flow design. A quantitative literature review was carried out in June 2024 for published original and review research between 2018 and 2024. For qualitative and quantitative data management and analysis in the research review process, data extraction tools, study screening, reference management software, evidence map visualization, machine learning classifiers, and reference management software were harnessed. Dimensions and VOSviewer were deployed to explore and visualize the bibliometric data.
Poverty in the Kazakhstan Regions: Assessing the Influence of Key Indicators on Differences in Its Level
Authors: Chulanova Zaure , Brimbetova Nursaule , Satybaldin Azimkhan , Dzhanegizova Aisulu
Published: August 2024

Modern Kazakhstan is characterized by significant regional socioeconomic differences due to climatic conditions, natural resources, migration, and regional specialization. The persistence of these regional differences can lead to increased stratification of society, social tension, and disruption of the country’s economic stability. These issues have intensified under the influence of Industry 4.0 trends and geopolitical processes in the region. Among the various sources of social inequality, we have chosen to focus on the problem of population poverty in our study. Addressing this problem is crucial for taking a comprehensive approach to addressing regional disparities in social development. The purpose of our study is to determine and assess the features of poverty in the regions of Kazakhstan. Our research methodology is based on evaluating the integral poverty index using four indicators: the share of the population with incomes below the subsistence level, the population under 60 years of age, youth aged 15–17 who are not working or studying, and the unemployment rate in the regions of Kazakhstan. Based on these indicators, we grouped the regions according to their poverty level, identified and compared regional differences, and identified the most vulnerable areas in need of intervention. This approach has enabled us to propose appropriate instruments of state support for different territories and promote inclusive regional development to overcome social imbalances.
Concerned about Climate Change and Ready to Take Action? An Analysis of the Pro-Climate Actions Individuals Are Motivated to Take to Lower Their Carbon Footprints
Authors: Olson Sarah , Szafraniec Małgorzata , Heinonen Jukka , Árnadóttir Áróra
Published: August 2024

Lifestyle changes are recognized as an important part of climate change mitigation. The influence of climate concern on taking individual actions for climate mitigation is well studied; however, the impact that climate concern has on consumption-based carbon footprints (CBCFs) is less studied. We aim to address this gap by examining the relationship of pro-climate actions, climate motivation, and CBCFs. We utilize data from a carbon footprint calculator with around 8000 responses from residents of the Nordic region. Respondents reported their personal consumption over the past year and answered questions about their participation in pro-climate actions and whether they were motivated by reducing their CBCF. We found that the high-impact actions of avoiding meat and flying had the most impact on CBCFs and had the highest correlation with climate motivation; however, the engagement levels were low. Conversely, the actions with the most participation had a lower impact on CBCFs and correlated less with climate motivation. Although respondents who reported a higher engagement with pro-climate actions and a higher climate motivation generally had lower CBCFs, their footprints were still not compatible with 1.5-degree limits. This study highlights the gap between climate motivation and the level of engagement in high-impact actions necessary for climate-sustainable lifestyles.
Analysis of the Current Situation of the Construction Industry in Saudi Arabia and the Factors Affecting It: An Empirical Study
Authors: Yu Haian , Shang Zufeng , Wang Fenglai
Published: August 2024

The construction industry in Saudi Arabia has been modernized through the implementation of green building technologies and intelligent building systems, which have facilitated the sustainable development of the construction industry in Saudi Arabia. However, there is a paucity of research on the current situation of the construction industry in Saudi Arabia. In this study, the super-efficient epsilon-based measurement (EBM)–Malmquist model was used to measure the static and dynamic efficiency of the construction industry in the administrative areas of the 13 provinces of Saudi Arabia from 2013 to 2022, and the Tobit model was used to empirically analyze the factors affecting the efficiency of the industry. In addition, the spatial autocorrelation of the efficiency of the industry was analyzed using Moran’s Index (MI) to study the characteristics of the spatial distribution of industrial efficiency as well as the effectiveness of resource allocation. The study shows that Saudi Arabia’s construction industry is at a low level of development; the population, GDP, and carbon dioxide emissions have a significant impact on the efficiency of the industry; and the development of the industry can help to reduce carbon dioxide emissions, thus promoting environmental sustainability; Saudi Arabia’s construction industry has a spatial spillover effect but does not have a significant agglomeration effect. This study accurately identifies the current situation of the development of the construction industry in Saudi Arabia and proposes several countermeasures and opinions, which are expected to provide a theoretical basis for realizing its sustainable development.
Voltage Hierarchical Control Strategy for Distribution Networks Based on Regional Autonomy and Photovoltaic-Storage Coordination
Authors: Wang Jiang , Lan Jinchen , Wang Lianhui , Lin Yan , Hao Meimei , Zhang Yan , Xiang Yang , Qin Liang
Published: August 2024

High-penetration photovoltaic (PV) integration into a distribution network can cause serious voltage overruns. This study proposes a voltage hierarchical control method based on active and reactive power coordination to enhance the regional voltage autonomy of an active distribution network and improve the sustainability of new energy consumption. First, considering the reactive power margin and spatiotemporal characteristics of distributed photovoltaics, a reactive voltage modularity function is proposed to divide a distribution grid into voltage regions. Voltage region types and their weak points are then defined, and the voltage characteristics and governance needs of different regions are obtained through photovoltaic voltage regulation. Subsequently, a dual-layer optimal configuration model of energy storage that accounts for regional voltage regulation is established. The upper-layer model focuses on planned configurations to minimize the annual comprehensive operating cost of the energy storage system (ESS), while the lower-layer model focuses on optimal dispatch to achieve the best regional voltage quality. KKT conditions and the Big-M method are employed to convert the dual-layer model into a single-layer linear model for optimization and solution. Finally, an IEEE 33-node system with high-penetration photovoltaics is modeled using MATLAB (2022a). A comparative analysis of four scenarios shows that the comprehensive cost of an ESS decreased by 8.49%, total revenue increased by 19.36%, and the overall voltage deviation in the distribution network was reduced to 0.217%.
Digital Policy, Green Innovation, and Digital-Intelligent Transformation of Companies
Authors: Tan Xin , Jiao Jinfang , Jiang Ming , Chen Ming , Wang Wenpeng , Sun Yijun
Published: August 2024

In the midst of rigorous market rivalry, enhancing a company’s competitiveness and operational efficiency in an era of rapid IT advancement is a pressing concern for business leaders. The National Big Data Comprehensive Zone (BDCZ) pilot scheme, instituted by the Chinese government, systematically addresses seven core objectives, encompassing data resource management, sharing and disclosure, data center consolidation, application of data resources, and the circulation of data elements. This policy initiative aims to bolster the establishment of information infrastructure through big data applications, facilitate the influx and movement of talent, and propel corporate sustainable growth. Utilizing a quasi-natural experiment approach, we assess the pilot policy’s influence on the digital-intelligent transformation (DIT) of manufacturing companies from a green innovation ecosystem perspective, employing datasets from 2010 to 2022, and methodologies such as Difference-in-Differences (DID), Synthetic Differences-in-Differences (SDID), and Propensity Score Matching-DID (PSM-DID). The findings indicate that the BDCZ initiative significantly fosters DIT in manufacturing companies. The policy’s establishment confers benefits, including access to increased government support and innovation capital, thereby enhancing the sustainability of green innovation efforts. It also strengthens corporate collaboration, engendering synergistic benefits that improve regional economic progression and establish a conducive environment for digital development, ultimately enhancing the regional innovation ecosystem. The pilot policy’s impact varies across entities, with more profound effects observed in developed financial markets compared to underdeveloped ones. Additionally, non-state-owned companies exhibit a greater response to BDCZ policy interventions than their state-owned counterparts. Moreover, manufacturing bussiness with a higher proportion of executive shareholding are more substantially influenced by the BDCZ. This article fills the research gap by using the quasi-natural experiment of BDCZ to test the impact on DIT of companies and provides inspiration for local governments to mobilize the enthusiasm of manufacturing companies for DIT.
Integrating Consumption-Based Metrics into Sectoral Carbon Budgets to Enhance Sustainability Monitoring of Building Activities
Authors: Pellan Marin , Almeida Denise , Louërat Mathilde , Habert Guillaume
Published: August 2024

Climate policies such as sectoral carbon budgets use national greenhouse gas emissions inventories to track the decarbonization of sectors. While they provide an important compass to guide climate action, the accounting framework in which they are embedded lacks flexibility for activities that are international and at the crossroads of different sectors. The building activities, being largely linked with important upstream emitters such as energy production or industrial activities, which can take place outside of national borders, are such an example. As legislation increasingly addresses the whole-life carbon emissions of buildings, it is vital to develop cross-sectoral accounting methods that effectively measure and monitor the overall impact of buildings. Such methods are essential for creating sound and holistic decarbonization pathways that align with sustainability policies. This article aims to provide a consistent approach for depicting the life-cycle emissions of buildings at the national level, using France as a case study. By integrating the different emission scopes with decarbonization pathways, this approach also enables the creation of comprehensive whole-life carbon budgets. The results show that the French building stock footprint reached 162 MtCO2eq in 2019, with 64% attributed to operational emissions, primarily from fossil fuel combustion, and the remainder to embodied emissions, mainly from upstream industrial and energy sectors. Overall, 20% of the emissions occurred outside the national borders. Under various global decarbonization pathways, the significance of embodied emissions is projected to increase, potentially comprising 78% of the life-cycle emissions by 2050 under the current policies. This underscores the necessity for climate policies to address emissions beyond territorial and operational boundaries.
Quartet of Sustainable Job Security, Job Performance, Organizational Commitment, and Motivation in an Emerging Economy: Focusing on Northern Cyprus
Authors: Kayar Serhan , Yeşilada Tahir
Published: August 2024

High-performing employees are essential for an organization to achieve its goals and gain a competitive advantage. Hence, human resource factors are crucial drivers of an organization’s success. These factors include organizational commitment, which is an employee’s sense of belonging to an organization; motivation, which pushes employees to act in line with the organization’s goals; perceived job security; and sustainable job performance. In particular, job security, including excess job security, has significant effects on sustainable job performance, and policymakers and managers must continuously monitor this relationship via their employment policies. However, the legal and social dimensions of employment policies lack clarity, particularly in developing countries, affecting the development of sustainable economic and social structures. This study focuses on the public and private banking sectors of Northern Cyprus, which operate in a developing economy and cannot provide a sustainable political–social work balance. It analyzes and separately compares data collected from 582 public- and private-sector bank employees, examining the mediating effects of organizational commitment and motivation on the relationship between perceived job security and sustainable performance. The study found that job security positively affects sustainable job performance, with organizational commitment and motivation positively mediating this relationship. Moreover, the positive effects of job security on organizational commitment and motivation and, hence, on sustainable job performance differ across the public and private sectors. The findings of this study can provide a reference for labor employment policies in developing countries aiming to build a sustainable economic structure.