bluuebunny/crossref_metadata_2025 huggingface dataset:
Maternal Diet Quality during Pregnancy Is Associated with Neonatal Brain White Matter Development
Authors: Na Xiaoxu , Glasier Charles M. , Andres Aline , Ou Xiawei
Published: December 2023

Maternal diet and nutrient intake are important for fetal growth and development. In this study, we aim to evaluate whether there are associations between maternal diet quality and the offspring’s brain white matter development. Healthy pregnant women’s (N = 44) nutrition intake was assessed by the Healthy Eating Index-2015 (HEI-2015) during the first, second, and third trimesters, respectively. Correlations between MRI diffusion tensor imaging measured fractional anisotropy (FA) of the neonatal brain and the HEI-2015 scores were evaluated using voxel-wise analysis with appropriate multiple comparisons correction and post hoc analysis based on regions of interest. Significant correlations were found between sodium scores at the first trimester of pregnancy and mean neonatal FA values in parietal white matter (R = 0.39, p = 0.01), anterior corona radiata (R = 0.43, p = 0.006), posterior limb of internal capsule (R = 0.53, p < 0.001), external capsule (R = 0.44, p = 0.004), and temporal white matter (R = 0.50, p = 0.001) of the left hemisphere. No other correlations were identified. In conclusion, the relationships between the maternal sodium intake score and the neonatal white matter microstructural development indicate sodium intake patterns better aligned with the Dietary Guidelines for Americans during early pregnancy are associated with greater white matter development in the offspring’s brain.
Antimicrobial, Anticancer, and Antioxidant Activities of Maize and Clover Pollen Grains Extracts: A Comparative Study with Phytochemical Characterizations
Authors: Barnawi Heba , Qanash Husam , Aldarhami Abdu , Alsaif Ghaida , Alharbi Bandar , Almashjary Majed N. , Almotiri Alhomidi , Bazaid Abdulrahman S.
Published: December 2023

The failure to treat infectious diseases due to the continual emergence of drug-resistant microbes poses a huge and serious challenge for human health globally. Currently, the discovery and development of natural therapeutic compounds are attracting considerable attention from researchers worldwide. In this project, two types of pollen grains (maize and clover) were evaluated for potential antimicrobial activities. Extracts of both pollen grains were purified using HPLC, which has been shown to have numerous phenolic and flavonoid compounds. Pyro catechol and methyl gallate were detected in high concentrations (1145.56 and 1056.57 µg/mL, respectively) in the maize extract, while caffeic acid, quercetin, and kaempferol (464.73, 393.05, and 390.93 µg/mL, respectively) were among the compounds observed at high concentrations in the clover pollen grains extract. Staphylococcus aureus, Escherichia coli, Salmonella typhi, and Candida albicans were more sensitive to the clover pollen grains extract with inhibition zones of 22 ± 0.2, 18 ± 0.1, 29 ± 0.3, and 42 ± 0.4 mm compared to the size of the inhibitory zones caused by the maize pollen grains extract (19 ± 0.3, 15 ± 0.4, 27 ± 0.1, and 22 ± 0.4 mm, respectively). Moreover, lower MIC values for the clover pollen grains extract were recorded against C. albicans (1.97 ± 0.04 µg/mL), S. aureus (62.5 ± 1.00 µg/mL), and E. coli (62.5 ± 0.07 µg/mL) than the MICs caused by the maize pollen grains extract. The use of a transmission electron microscope revealed that the E. coli that had been treated with the clover pollen grains extract showed changes in its cell walls compared to that treated with the maize pollen grains extract. The clover pollen grains extract exhibited a stronger antioxidant potential, with an IC50 value of 22.18 µg/mL, compared to an IC50 value of 54.85 µg/mL for the maize pollen grains extract, via a DPPH scavenging assay. Regarding anticancer activity, the maize pollen grains extract was revealed to be more effective in terms of inhibiting the human colon cancer cell line HCT-116, with an IC50 value of 67.02 ± 1.37 µg/mL, compared with the observed toxicity caused by the clover extract, with an IC50 value of 75.03 ± 1.02 µg/mL. Overall, the clover pollen grains extract demonstrated potent antibacterial and antioxidant activities, but not anticancer activity, when compared to the maize grains extract. Thus, the current findings related to both types of pollen grains (clover and maize) highlight their potential therapeutic applications for the treatment of certain infectious diseases and malignancies.
Compatibility Study of Peptide and Glycerol Using Chromatographic and Spectroscopic Techniques: Application to a Novel Antimicrobial Peptide Cbf-14 Gel
Authors: Yang Jixue , Huo Yitong , Jin Xin , Liu Meiyun , Lu Yuting , Ma Lingman , Zhou Changlin , Hang Taijun , Song Min
Published: December 2023

The interactions between active pharmaceutical ingredients (APIs) and excipients may lead to API degradation, thereby affecting the safety and efficacy of drug products. Cbf-14 is a synthetic peptide derived from Cathelicidin-BF, showing potential for bacterial and fungal infections. In order to assess impurities in Cbf-14 gel, we developed a two-dimensional liquid chromatography coupled with quadrupole/time-of-flight mass spectrometric method. A total of eleven peptide degradation impurities were identified and characterized. Furthermore, the compatibility tests were conducted to evaluate the interactions of Cbf-14 with glycerol and methylcellulose, respectively. The results revealed that the impurities originated from condensation reactions between Cbf-14 and aldehydes caused by glycerol degradation. Several aldehydes were employed to validate this hypothesis. The formation mechanisms were elucidated as Maillard reactions between primary amino groups of Cbf-14 and aldehydes derived from glycerol degradation. Additionally, the compatibility of Cbf-14 with glycerol from different sources and with varying storage times was investigated. Notably, the interaction products in the gel increased with extended storage time, even when fresh glycerol for injection was added. This study offers unique insights into the compatibility study of peptides and glycerol, contributing to the ongoing quality study of Cbf-14 gel. It also serves as a reference for the design of other peptide preparations and excipients selections.
Using Mesoporous Silica-Based Dual Biomimetic Nano-Erythrocytes for an Improved Antitumor Effect
Authors: Xi Ziyue , Jiang Yingying , Ma Zitong , Li Qun , Xi Xinran , Fan Chuanyong , Zhu Shuang , Zhang Junjie , Xu Lu
Published: December 2023

The nano-delivery system with a dual biomimetic effect can penetrate deeper in tumor microenvironments (TMEs) and release sufficient antitumor drugs, which has attracted much attention. In this study, we synthesized erythrocyte-like mesoporous silica nanoparticles (EMSNs) as the core loaded with doxorubicin (DOX) and coated them with calcium phosphate (CaP) and erythrocyte membrane (EM) to obtain DOX/EsPMs. The transmission electron microscopy (TEM), fluorescent co-localization and protein bands of SDS-PAGE were used to confirm the complete fabrication of EsPMs. The EsPMs with erythrocyte-like shape exhibited superior penetration ability in in vitro diffusion and tumor-sphere penetration experiments. Intracellular Ca2+ and ROS detection experiments showed that the CaP membranes of EsPMs with pH-sensitivity could provide Ca2+ continuously to induce reactive oxide species’ (ROS) generation in the TME. The EM as a perfect “camouflaged clothing” which could confuse macrophagocytes into prolonging blood circulation. Hemolysis and non-specific protein adsorption tests proved the desirable biocompatibility of EsPMs. An in vivo pharmacodynamics evaluation showed that the DOX/EsPMs group had a satisfactory tumor-inhibition effect. These advantages of the nano-erythrocytes suggest that by modifying the existing materials to construct a nano-delivery system, nanoparticles will achieve a biomimetic effect from both their structure and function with a facilitated and sufficient drug release profile, which is of great significance for antitumor therapy.
Refractivity of P2O5-Al2O3-SiO2 Glass in Optical Fibers
Authors: Likhachev Mikhail E. , Zaushitsyna Tatiana S. , Agakhanova Vitaliya A. , Iskhakova Liudmila D. , Aleshkina Svetlana S. , Bubnov Mikhail M. , Lobanov Alexey S. , Lipatov Denis S.
Published: December 2023

A significant change in the refractive index profiles for the large mode area phosphoroaluminosilicate (PAS) core optical fibers was observed in comparison to that in preforms. This study shows that the refractive index of the PAS core can vary from negative (in preform) to positive (in fiber), and the difference in the refractive index between the core and preform can exceed a few thousand. By measuring a large set of fibers with different concentrations of P2O5 and Al2O3, we define the refractivity of each dopant (P2O5, Al2O3 and AlPO4 joint) after drawing fiber from the preform and discuss the possible origin of the observed refractive index variation.
Bio-Based Alkali Lignin Cooperative Systems for Improving the Flame Retardant and Mechanical Properties of Rigid Polyurethane Foam
Authors: Li Xu , Liu Chang , An Xinyu , Niu Li , Feng Jacko , Liu Zhiming
Published: December 2023

Lignin was utilized as an environmentally friendly synergistic agent to augment the fire resistance and mechanical characteristics of rigid polyurethane foam (PUF)/melamine–formaldehyde resin ammonium polyphosphate (MFAPP). The incorporation of lignin significantly enhanced the charring capability and flame retardancy of PUF/MFAPP. Specifically, PUF/MFAPP12/A-lignin3 exhibited a charring residue of 23.1% at 800 °C, accompanied by an increase in the limiting oxygen index (LOI) to 23.1%, resulting in a UL-94 V-0 rating. The cone calorimeter test (CCT) revealed that the peak heat release rate (PHRR), total heat release (THR), smoke production rate (SPR), and total smoke production (TSP) values of PUF/MFAPP12/A-lignin3 were all lower than for pure PUF. MFAPP and alkali lignin exerted a noticeable influence on the physical and mechanical properties, leading to increases in density (35.4 kg/m3), thermal conductivity (32.68 mW/(m·K)), and compressive strength (160.5 kPa). Observations of the morphology and elemental composition of char residues after combustion indicated the formation of an intact, thick, and continuous char layer enriched with nitrogen and phosphorus elements, which acted as a protective shield for the underlying foam.
Influence of 3D Printing Direction in PLA Acoustic Guitars on Vibration Response
Authors: Burgos-Pintos Álvaro , Fernández-Zacarías Francisco , Mayuet Pedro F. , Hernández-Molina Ricardo , Rodríguez-Parada Lucía
Published: December 2023

The design of musical instruments is a discipline that is still carried out in an artisanal way, with limitations and high costs. With the additive manufacturing technique, it is possible to obtain results for the generation of not only electrical but also acoustic instruments. However, it is necessary to generate a procedure to evaluate the influence of the process on the final result of the acoustics obtained. This study focuses on investigating the relationship between the construction of acoustic guitars and their final sound. The reinforcement structures at the top of the instrument are analysed, as well as how this design affects the vibratory behaviour of the top in the first five vibratory modes. Specifically, this article presents a procedure for the design of customised acoustic guitars using additive manufacturing through parametrisation and a vibrational analysis of the designed tops using finite element (FEA) and experimental physical tests, in order to develop a methodology for the study of stringed instruments. As a result, an 11% increase in the high-frequency response was achieved with a printing direction of +45°, and a reduction in the high-frequency response with ±45°. In addition, at high frequencies, a relative error of 5% was achieved with respect to the simulation. This work fulfils an identified need to study the manufacture of acoustic guitars using polylactic acid (PLA), and to be able to offer the musician a customised instrument. This represents a breakthrough in the use of this manufacturing technology, extending its relationship with product design.
A Flexibility Platform for Managing Outages and Ensuring the Power System’s Resilience during Extreme Weather Conditions
Authors: Zafeiropoulou Magda , Sijakovic Nenad , Zarkovic Mileta , Ristic Vladan , Terzic Aleksandar , Makrygiorgou Dimitra , Zoulias Emmanouil , Vita Vasiliki , Maris Theodoros I. , Fotis Georgios
Published: December 2023

It is challenging for the European power system to exactly predict RES output and match energy production with demand due to changes in wind and sun intensity and the unavoidable disruptions caused by severe weather conditions. Therefore, in order to address the so-called “flexibility challenge” and implement the variable RES production, the European Union needs flexible solutions. In order to accommodate quicker reactions, compared to those performed today, and the adaptive exploitation of flexibility, grid operators must adjust their operational business model, as the electrical grid transitions from a fully centralized to a largely decentralized system. OneNet aspires to complete this crucial step by setting up a new generation of grid services that can fully utilize distributed generation, storage, and demand responses while also guaranteeing fair, open, and transparent conditions for the consumer. Using AI methods and a cloud-computing approach, the current work anticipates that active management of the power system for TSO–DSO coordination will be improved by the web-based client-server application F-channel. In the current work, a user’s experience with the platform for a Business Use Case (BUC) under the scenario of severe weather conditions is presented. The current work aims to increase the reliability of outage and maintenance plans for the system operators (SOs) by granting them a more accurate insight into the conditions under which the system may be forced to operate in the upcoming period and the challenges that it might face based on those conditions. In this way, the methodology applied in this case could, via AI-driven data exchange and analyses, help SOs change the maintenance and outage plans so the potential grave consequences for the system can be avoided. The SOs will have accurate forecasts of the relevant weather parameters at their disposal that will be used in order to achieve the set targets. The main results of the presented work are that it has a major contribution to the optimal allocation of the available resources, ensures the voltage and frequency stability of the system, and provides an early warning for hazardous power system regimes.
Dynamic Job-Shop Scheduling Based on Transformer and Deep Reinforcement Learning
Authors: Song Liyuan , Li Yuanyuan , Xu Jiacheng
Published: December 2023

The dynamic job-shop scheduling problem is a complex and uncertain task that involves optimizing production planning and resource allocation in a dynamic production environment. Traditional methods are limited in effectively handling dynamic events and quickly generating scheduling solutions; in order to solve this problem, this paper proposes a solution by transforming the dynamic job-shop scheduling problem into a Markov decision process and leveraging deep reinforcement learning techniques. The proposed framework introduces several innovative components, which make full use of human domain knowledge and machine computing power, to realize the goal of man–machine collaborative decision-making. Firstly, we utilize disjunctive graphs as the state representation, capturing the complex relationships between various elements of the scheduling problem. Secondly, we select a set of dispatching rules through data envelopment analysis to form the action space, allowing for flexible and efficient scheduling decisions. Thirdly, the transformer model is employed as the feature extraction module, enabling effective capturing of state relationships and improving the representation power. Moreover, the framework incorporates the dueling double deep Q-network with prioritized experience replay, mapping each state to the most appropriate dispatching rule. Additionally, a dynamic target strategy with an elite mechanism is proposed. Through extensive experiments conducted on multiple examples, our proposed framework consistently outperformed traditional dispatching rules, genetic algorithms, and other reinforcement learning methods, achieving improvements of 15.98%, 17.98%, and 13.84%, respectively. These results validate the effectiveness and superiority of our approach in addressing dynamic job-shop scheduling problems.
A Review on Citric Acid Production by Yarrowia lipolytica Yeast: Past and Present Challenges and Developments
Authors: Kamzolova Svetlana V.
Published: December 2023

The biosynthesis of citric acid (CA) and its derivatives is of great interest due to its wide range of applications in various manufacturing sectors. The fungus Aspergillus niger is mainly used for the commercial production of CA, using sucrose and molasses as the primary carbon sources. Since the 1960s, intensive research has been underway to introduce Yarrowia lipolytica yeast as an alternative to traditional fungal technology. This review discusses the practical uses of CA and its derivatives. Also, the challenges and developments that have led to efficient and green CA synthesis technologies using Y. lipolytica are outlined. The nutrient medium requirements and the use of various carbon sources, encompassing pure substrates and industry, agriculture, and food waste are considered. Additionally, the choice and improvement of strain producers, including efficient mutagenesis, genetic modification, and screening methods, are discussed.
Detection and Analysis of the Variation in the Minimum Ecological Instream Flow Requirement in the Chinese Northwestern Inland Arid Region by Using a New Remote Sensing Method
Authors: Yang Shengtian , Li Jiekang , Lou Hezhen , Dai Yunmeng , Pan Zihao , Zhou Baichi , Wang Huaixing , Li Hao , Ding Jianli , Zheng Jianghua
Published: December 2023

With the development of human society, the balance between the minimum ecological instream flow requirement (MEIFR), which is an essential part of the ecological water demand in arid areas, and anthropogenic water depletion has received increasing attention. However, due to the lack of hydrological station data and river information on arid basins, previous researchers usually considered only the individual ecological water demand of rivers, lakes, or oases. To address this issue, a new method that combines river hydraulic parameters and the wet circumference obtained by an unmanned aerial vehicle (UAV) and remote sensing hydrological station (RSHS) technologies was applied to obtain the MEIFR and, then, systematically and quantitatively explore the balance from the perspective of the entire basin of Aiding Lake from 1990 to 2022, which is the lowest point of Chinese terrestrial territory. The results showed the following: (1) since 1990, the discharge of the seven rivers in the study area increased by 1–6%, and the MEIFR of these rivers increased by 15–100%; both quantities decreased by 3–5% from the upper to the lower reaches of the basin; (2) the surface area and water level of Aiding Lake decreased by 5% and 14%, respectively, but the MEIFR first decreased by 25% from 1990 to 2013 and, then, increased by 66.7% from 2013 to 2022; and (3) from 2011 to 2022, the MEIFR and anthropogenic water depletion exhibited a balance. Against the background of climate change, this research revealed that the MEIFR of the rivers in the Aiding Lake Basin have shown an upward trend over the past 30 years and quantitatively determined the above balance relationship and the period of its occurrence. This study supplied a method that could provide guidance for water resource management by decision-makers at a global level, thus helping achieve the sustainable development goals (SDGs).
Construction of an Ecological Security Pattern in Rapidly Urbanizing Areas Based on Ecosystem Sustainability, Stability, and Integrity
Authors: Gong Daohong , Huang Min , Lin Hui
Published: December 2023

The escalating pace of urbanization and human activities presents formidable challenges to landuse patterns and ecological environments. Achieving a harmonious coexistence between humans and nature of high quality has emerged as a global imperative. Constructing an ecological security pattern has become an essential approach to mitigating the adverse ecological impacts of urban sprawl, safeguarding human well-being, and promoting the healthy development of ecosystems. Focusing on ecosystem sustainability, stability, and integrity, this study constructed the ecological security pattern in rapidly urbanizing areas, emphasizing achieving a well-balanced integration of urban expansion and ecological preservation. Ecological sources were identified by an evaluation system of “ecosystem service function–ecological sensitivity–landscape connectivity”. Resistance surfaces were constructed by integrating natural and human factors. Ecological corridors and nodes were extracted by methods such as the minimum cumulative resistance and gravity models. Taking Nanchang City as an example, the results show that there were 15 ecological sources, primarily woodland, displaying a distinct “island” phenomenon. Additionally, there were 41 ecological corridors with a combined length of 2170.54 km, exhibiting a dense distribution in the southwest and a sparse distribution in the northeast. The city was found to encompass 122 ecological nodes, predominantly situated along the corridors near the ecological sources, indicating a strong spatial aggregation pattern. An optimized ecological security pattern of “one ring, two belts, three zones, and multiple nodes” was proposed for synergizing ecological protection, restoration, and rapid urbanizing.
Temporal and Spatial Surface Heat Source Variation in the Gurbantunggut Desert from 1950 to 2021
Authors: Aihaiti Ailiyaer , Wang Yu , Mamtimin Ali , Liu Junjian , Gao Jiacheng , Song Meiqi , Wen Cong , Ju Chenxiang , Yang Fan , Huo Wen
Published: December 2023

Based on data from the Gurbantunggut Desert, the largest fixed/semi-fixed desert in China, and ERA5-Land reanalysis data, the long-term variations and spatial surface heat source (SHS) differences in the Gurbantunggut Desert are discussed herein. The results show the following: (1) The hourly SHS at the Kelameili station during the 2013–2021 period was a weak heat source at night; contrastingly, it was a strong heat source during the day. The duration of the hourly SHS increased gradually from January to July, but it decreased gradually from July to December. The daily SHS showed obvious seasonal variation, reaching the maximum in summer and the minimum in winter. The ERA5-Land reanalysis can reproduce all the variation characteristics of the SHS well. (2) The climatology (i.e., multi-year mean) of the monthly SHS intensity was lower than 50 W/m2 during the January–March and September–December periods in the Gurbantunggut Desert, indicating a weak heat source. On the other hand, the climatology recorded in April–August was higher than 50 W/m2, with a strong heat source. From the perspective of spatial distribution, the eastern and western regions of the Gurbantunggut Desert show strong heat sources, while the central region shows weak heat sources. The spatial distribution of the first and second modes of the empirical orthogonal function (EOF) decomposition reflected the consistent spatial variability and a north–south (or east–west) polarity variation of the monthly SHS in the Gurbantunggut Desert, respectively. (3) The yearly SHS showed negative anomalies during the 1950–1954, 1964–1982 and 2004–2015 periods, and positive anomalies during the 1955–1963, 1983–2003 and 2016–2021 periods in the Gurbantunggut Desert. Additionally, the time series of the SHS anomalies was positively correlated with the Interdecadal Pacific Oscillation (IPO) index. During the negative IPO phase, the yearly SHS showed a negative anomaly in the Gurbantunggut Desert, while the yearly SHS showed a positive anomaly during the positive IPO phase in most regions of the Gurbantunggut Desert.
Three-Dimensional Distribution and Transport Features of Dust and Polluted Dust over China and Surrounding Areas from CALIPSO
Authors: Xu Xiaofeng , Yang Yudi , Xiong Zixu , Gong Jianming , Luo Tianyang
Published: December 2023

Dust plays a very important role in the Earth’s climate system by its direct and indirect effects. Deserts in northwestern China contribute a large amount of dust particles, both inland and outside, while the vertical distribution and transport mechanism of dust still have many uncertainties. Using Level 3 cloud-free monthly aerosol products of the Cloud–Aerosol Lidar and Infrared Pathfinder Satellite Observations (CALIPSO) system from 2007 to 2020, we analyzed the spatial and temporal variations and transport features for dust and polluted dust aerosols over China and the surrounding areas. The results show that the Taklimakan Desert (TD) and the Thar Desert (TRD) always act as the high-value centers of dust optical depth (DOD), while the centers of polluted dust optical depth (PDOD) are located in eastern China, the Sichuan Basin and the Indian subcontinent. The DOD shows an increasing trend in most areas, while the PDOD presents a significant decrease and increase in eastern China and central India, respectively. The largest DOD appears in spring over the TD and the Gobi Desert (GD), while the largest DOD in summer is over the TRD. Although most dusts in the TD and TRD are concentrated below 4 km, they may be higher over the TD. Most of the polluted dusts are confined to under 2 km. The dust input to the Tibetan Plateau (TP) could come from both the TD and TRD and occurs mostly in spring and summer, respectively. The polluted dusts of South Asia and the Indian subcontinent are mostly contained in the boundary layer in winter, but they could extend much higher in spring and summer, which favors their transport into southwestern China. The dust layer shows apparent seasonality. Its top reaches a higher level in spring and summer, while the base stays at a similar height in all seasons. The dust layer appears to be the thickest in spring over most areas, while the thickest layer in summer is over the TD and TRD. The polluted dust layer is thickest in the Indian subcontinent in spring. The overlapping of dust and polluted dust layers present different patterns in different regions, which suggests diverse mixture processes of dusts and pollutants. Finally, we compared and found different influences of meteorological factors, such as wind field, boundary layer height and precipitation, on the variations in DOD and PDOD over dust sources and other areas.
Extracting Plastic Greenhouses from Remote Sensing Images with a Novel U-FDS Net
Authors: Mo Yan , Zhou Wanting , Chen Wei
Published: December 2023

The fast and accurate extraction of plastic greenhouses over large areas is important for environmental and agricultural management. Traditional spectral index methods and object-based methods can suffer from poor transferability or high computational costs. Current deep learning-based algorithms are seldom specifically aimed at extracting plastic greenhouses at large scales. To extract plastic greenhouses at large scales with high accuracy, this study proposed a new deep learning-based network, U-FDS Net, specifically for plastic greenhouse extraction over large areas. U-FDS Net combines full-scale dense connections and adaptive deep supervision and has strong future fusion capabilities, allowing more accurate extraction results. To test the extraction accuracy, this study compiled new greenhouse datasets covering Beijing and Shandong with a total number of more than 12,000 image samples. The results showed that the proposed U-FDS net is particularly suitable for complex backgrounds and reducing false positive conditions for nongreenhouse ground objects, with the highest mIoU (mean intersection over union) an increase of ~2%. This study provides a high-performance method for plastic greenhouse extraction to enable environmental management, pollution control and agricultural plans.
An Information Extraction Method for Industrial and Commercial Rooftop Photovoltaics Based on GaoFen-7 Remote Sensing Images
Authors: Tao Haoxiang , He Guojin , Wang Guizhou , Yang Ruiqing , Peng Xueli , Yin Ranyu
Published: December 2023

With the increasing global focus on renewable energy, distributed rooftop photovoltaics (PVs) are gradually becoming an important form of energy generation. Effective monitoring of rooftop PV information can obtain their spatial distribution and installed capacity, which is the basis used by management departments to formulate regulatory policies. Due to the time-consuming and labor-intensive problems involved in manual monitoring, remote-sensing-based monitoring methods are getting more attention. Currently, remote-sensing-based distributed rooftop PV monitoring methods are mainly used as household rooftop PVs, and most of them use aerial or satellite images with a resolution higher than 0.3 m; there is no research on industrial and commercial rooftop PVs. This study focuses on the distributed industrial and commercial rooftop PV information extraction method based on the Gaofen-7 satellite with a resolution of 0.65 m. First, the distributed industrial and commercial rooftop PV dataset based on Gaofen-7 satellite and the optimized public PV datasets were constructed. Second, an advanced MANet model was proposed. Compared to MANet, the proposed model removed the downsample operation in the first stage of the encoder and added an auxiliary branch containing the Atrous Spatial Pyramid Pooling (ASPP) module in the decoder. Comparative experiments were conducted between the advanced MANet and state-of-the-art semantic segmentation models. In the Gaofen-7 satellite PV dataset, the Intersection over Union (IoU) of the advanced MANet in the test set was improved by 13.5%, 8.96%, 2.67%, 0.63%, and 0.75% over Deeplabv3+, U2net-lite, U2net-full, Unet, and MANet. In order to further verify the performance of the proposed model, experiments were conducted on optimized public PV datasets. The IoU was improved by 3.18%, 3.78%, 3.29%, 4.98%, and 0.42%, demonstrating that it outperformed the other models.
Screening Image Features of Collapsed Buildings for Operational and Rapid Remote Sensing Identification
Authors: Liu Ruoyang , Zhu Wenquan , Yang Xinyi
Published: December 2023

The accurate detection of collapsed buildings is of great significance for post-disaster rescue and reconstruction. High-resolution optical images are important data sources for identifying collapsed buildings, and the identification accuracy mainly depends on the features extracted from the images. However, existing research lacks a comprehensive screening and general evaluation of the ability of remote sensing features to detect collapsed buildings, and there is still a considerable gap in the operational process of rapid identification of collapsed buildings in remote sensing. Based on 2630 pairs of building samples distributed in 6 regions worldwide, this study evaluated the ability of 25 remote sensing features (including spectral and spatial features) to detect collapsed buildings and select the most capable ones. Then, we test the application effect of selected features in identifying collapsed buildings on large-scale remote sensing images. Based on the two experiments above, an operational process for rapid identification of collapsed buildings was suggested. The result shows that Homogeneity, Energy, Local Entropy, Local Standard Deviation, and Gradient can effectively and stably distinguish collapsed buildings from non-collapsed buildings (Jeffries-Matusita distances are greater than 1.59 and Transformed Divergences are greater than 1.60) and have high recognition accuracy for collapsed buildings on large-scale remote sensing images (F1-scores are 0.71–0.94). In addition, Contrast, Local Coefficient of Variation, Edge Density, and Global Entropy can also distinguish collapsed buildings from non-collapsed buildings at a normal level (Jeffries-Matusita distances are 1.14–1.28, and Transformed Divergences are 1.24–1.48), while Gradient Orientation Entropy, Fractal Dimension, Local Binary Patterns, Edge, Local Mean, Correlation, Gradient Orientation Standard Deviation, Global Coefficient of Variation, Gabor feature, Local Moran’I, and six spectral features have relatively weak abilities (Jeffries-Matusita distances are less than 0.73, and Transformed Divergences are less than 1.07). The selected remote sensing features can support rapid identification of potential collapsed building areas from post-disaster remote sensing images.
Self-Distillation-Based Polarimetric Image Classification with Noisy and Sparse Labels
Authors: Wang Ningwei , Bi Haixia , Li Fan , Xu Chen , Gao Jinghuai
Published: December 2023

Polarimetric synthetic aperture radar (PolSAR) image classification, a field crucial in remote sensing, faces significant challenges due to the intricate expertise required for accurate annotation, leading to susceptibility to labeling inaccuracies. Compounding this challenge are the constraints posed by limited labeled samples and the perennial issue of class imbalance inherent in PolSAR image classification. Our research objectives are to address these challenges by developing a novel label correction mechanism, implementing self-distillation-based contrastive learning, and introducing a sample rebalancing loss function. To address the quandary of noisy labels, we proffer a novel label correction mechanism that capitalizes on inherent sample similarities to rectify erroneously labeled instances. In parallel, to mitigate the limitation of sparsely labeled data, this study delves into self-distillation-based contrastive learning, harnessing sample affinities for nuanced feature extraction. Moreover, we introduce a sample rebalancing loss function that adjusts class weights and augments data for small classes. Through extensive experiments on four benchmark PolSAR images, our approach demonstrates its effectiveness in addressing label inaccuracies, limited samples, and class imbalance. Through extensive experiments on four benchmark PolSAR images, our research substantiates the robustness of our proposed methodology, particularly in rectifying label discrepancies in contexts marked by sample paucity and imbalance. The empirical findings illuminate the superior efficacy of our approach, positioning it at the forefront of state-of-the-art PolSAR classification techniques.
A Study on the Spatial Change of Production–Living–Ecology in China in the Past Two Decades Based on Intensity Analysis in the Context of Arable Land Protection and Sustainable Development
Authors: Cui Guangyuan , Dong Donglin , Gao Qiang
Published: December 2023

During the period of rapid social and economic development spanning four decades of reform and opening up, China has witnessed significant transformations in its patterns of production, living, and ecology. Notably, there has been a noticeable escalation in the conflict between the spatial requirements for agricultural production and those for residential and ecological purposes. In order to address this issue, the government has enacted a set of measures aimed at safeguarding arable land. This study utilizes land use data from 2000, 2010, and 2020 to establish a spatial dataset representing China’s production–living–ecological space (PLES). The intensity analysis approach is employed to examine the features of changes in China’s PLES over the previous two decades. The findings of this study indicate that agricultural production space is mostly concentrated in the northeastern region and the plains of the Yangtze and Yellow River Basins. This distribution pattern has undergone a notable transformation characterized by a period of decline followed by subsequent growth. Simultaneously, the ecological space is primarily dispersed in the northwestern region and the Tibetan Plateau. South of the Hu Huanyong Line, there is a greater proportion of rural living area, urban living space, and industrial production space. Between the years 2000 and 2020, there was an observed increase in the intensity of PLES. This rising trend was primarily characterized by quantitative changes and exchange changes within each type of space. In contrast, between 2010 and 2020, there was a notable increase in the frequency and intensity of spatial transitions, particularly in relation to agricultural production space. Nevertheless, the transition to agricultural production space mostly entails ecological implications, characterized by a decline in cultivation quality but an improvement in environmental advantages. The policy of protecting arable land has a significant influence on the dynamics of the production, living, and ecological domains. To achieve the objective of maintaining the “trinity” of arable land quantity, quality, and ecology, it is imperative for the government to establish a comprehensive system for spatial category conversion. This will ensure the coordinated development of PLES. This study elucidates the constituents of intensity analysis and its analytical concepts, which can be employed to identify alterations in spatial patterns in different areas. It offers scholarly references for the subsequent execution of policies aimed at safeguarding arable land and the development of sustainable land management strategies. Consequently, this study holds substantial importance for advancing economic and social development and fostering sustainable growth.
Exploring the Impact of Integrated Marketing Communication Tools on Green Product Purchase Intentions among Diverse Green Consumer Segments
Authors: Chen Chun-Shuo , Yu Chih-Ching , Tu Kuan-Yu
Published: December 2023

In response to escalating environmental pressures and the growing global consensus on comprehensive green initiatives, marketers encounter the challenge of effectively communicating with diverse green consumer segments. The purpose of this study is to explore the preferences of different IMC tools among different types of green consumers and then attempt to propose effective communication tools for different types of green consumers to boost sustainable consumption. This study examined 13 widely used integrated marketing communication (IMC) tools and delved into their impact on the purchase intentions of different consumer segments toward green products. Meanwhile, departing from conventional approaches, we replaced consumer awareness with actual consumer behavior to more accurately segment green consumers. This distinction allowed us to categorize green consumers into three segments: light green (including colorless), medium green, and dark green consumers. By analyzing these IMC tools based on the dimensions of media richness theory—feedback, multiple cues, language variety, and personal focus—we found that (1) only three communication tools can effectively provide green consumers with different levels of green behavior with the green product information they need to enhance their green products purchase intention; (2) dark green consumers demonstrate a markedly stronger preference for these three types of IMC tools than the others; (3) there are significant differences in only two constructs, namely “feedback” and “language variety” among these three types of green consumers; and (4) both dark green and medium green consumers are more concerned about the level of personalization in messages than light green (including colorless) consumers. Ultimately, practical insights are provided to empower businesses and marketers in boosting consumer preference for green products.
Does New Infrastructure Affect Regional Carbon Intensity? Empirical Evidence from China
Authors: Liu Bingquan , Nie Boyang , Wang Yakun , Han Xuemin , Li Yongqing
Published: December 2023

After the proposal of the carbon neutrality target, the reduction carbon emissions in China has become increasingly critical. The rapid advancement of new infrastructures, such as 5G infrastructure, artificial intelligence, and the industrial Internet, is a key factor influencing the change in carbon intensity through complex mechanisms, which necessitates a comprehensive understanding of their impact on regional carbon emission intensity. We employ the “structure-technology” effect as the transmission pathway and construct a model based on the STIRPAT model to compare and analyze the disparities in the influence of new infrastructures on the entire country and various regions. Moreover, spatial effects are also taken into consideration to investigate the pivotal areas for carbon emission reduction. The main results are as follows: (1) The carbon emission intensity in China demonstrates a consistent annual decline from 2011 to 2020. Regional disparities exist in both carbon emission intensity and the development of new infrastructure, with the western region exhibiting higher carbon emission intensity and lower investment in new infrastructure. (2) New infrastructure has the potential to positively impact the reduction of regional carbon intensity. However, the presence of an inverted U-shaped relationship suggests that China should avoid the indiscriminate expansion of new infrastructure. Instead, such projects can facilitate industrial structure optimization and technological advancements. (3) When considering regional nuances, the effect of industrial optimization is partially mediating in eastern and central China but obscuring in the western region. On the other hand, technological progress exhibits complete mediation in the central region. In conclusion, this study recommends specific measures for carbon emission reduction at both national and regional levels, accounting for the unique circumstances surrounding China’s ongoing development of new infrastructure.
Tourism and Conservation Empowered by Augmented Reality: A Scientometric Analysis Based on the Science Tree Metaphor
Authors: Ariza-Colpas Paola Patricia , Piñeres-Melo Marlon Alberto , Morales-Ortega Roberto-Cesar , Rodriguez-Bonilla Andres-Felipe , Butt-Aziz Shariq , Naz Sumera , Contreras-Chinchilla Leidys del Carmen , Romero-Mestre Maribel , Vacca Ascanio Ronald Alexander
Published: December 2023

Technology has emerged as an essential tool that has revolutionized the conditions for travelers to fully immerse themselves in the culture, gastronomy, and recreation of the places they explore. This literature review aims to understand the crucial contributions currently shaping the implementation of augmented reality as an enriching technological support for user experiences in tourism and the conservation of natural heritage. While the literature on this topic is scattered across specialized databases, this review provides a unique opportunity for a deeper and more cohesive analysis. Employing the metaphor of the tree of science, we have developed two valuable approaches to the data collected during our bibliographic exploration. On the one hand, we have examined scientometric statistics related to the countries, authors, universities, and research and technological development centers that are at the forefront of creating innovative augmented reality-based applications to promote tourism and conservation. On the other hand, we have conducted an evolutionary analysis based on the tree of science to trace the origins of the most significant contributions and understand how they have evolved over time in this dynamic and ever-developing field.
Synthesis and Environmental Applications of Nanoporous Materials Derived from Coal Fly Ash
Authors: Yuan Ning , Xu Hao , Liu Yanjun , Tan Kaiqi , Bao Yixiang
Published: December 2023

Coal fly ash (CFA) is the primary solid waste generated by the coal-fired industry, and the predominant treatment methods include accumulation, landfill, and the production of cement-based building materials. However, the availability of these methods is relatively limited, and there is a need for technological upgrades. The extensive accumulation not only leads to environmental pollution but also has detrimental effects on human health. With its loose structure and main chemical components of Al2O3 and SiO2, CFA is conducive to the synthesis of promising nanoporous materials for applications in adsorption. The use of CFA as a raw material can significantly reduce preparation costs, improve comprehensive utilization efficiency, and manufacture more valuable products, aligning with the current strategy of sustainable development. Currently, the most widely used synthesis method is hydrothermal synthesis. This review focuses on the principles, methods, and influencing factors of synthesis, with particular emphasis on CFA-based mesoporous silica, zeolites, and metal–organic frameworks (MOFs), which have not been systematically reviewed previously. The quality of these synthesized nanoporous materials can be finely adjusted through the synthesis process. A comparison of the advantages and disadvantages of each process will be made, and the impact of the synthesis conditions on the synthetic products will be analyzed. Additionally, a brief discussion on the latest research advances in their applications in adsorption will be provided. Finally, relevant challenges and issues have been proposed.
Deciphering the Evolution, Frontier, and Knowledge Clustering in Sustainable City Planning: A 60-Year Interdisciplinary Review
Authors: Qian Haochen , Zhang Fan , Qiu Bing
Published: December 2023

Scholars have sought to integrate sustainable principles, attitudes, and methodologies into urban development, drawing insights from the natural and social sciences as well as historical contexts. However, current sustainable urban planning (SUP) research has a broad scope, unclear boundaries, and an absence of systematic literature reviews. To fill this research gap, this review presents a visual analysis of 38,344 publications on SUP indexed in the Web of Science (WoS) from 1964 to 2023, with the aim of detailing the trajectory of SUP research. Utilizing data retrieval and scientific metrology techniques, we: (1) Identified distinct phases in SUP research: budding (pre-1990s), exploration (1990s), foundation (2000s), and maturation (2010–present). (2) Discovered that publications predominantly focused on urban research, landscape architecture, and ecological studies, with publishing trends favoring developed, highly urbanized, and coastal nations. (3) Employed visualized dual map overlays, co-citation clustering networks, and keyword statistical charts to construct a knowledge framework of the interdisciplinary progression and thematic shifts in SUP. Key knowledge clustering included ‘community planning’, ‘urban expansion’, ‘ecosystem services’, and ‘nature-based solutions’. (4) Described the progression of SUP, green innovation is the most promising direction for future research. (5) Defined its scope and elements and advocated for three foundational principles: equity and justice, value articulations, and practical needs, offering a path to actualize SUP efforts.