bluuebunny/crossref_metadata_2025 huggingface dataset:
Absolute Radiometric Calibration of an Imaging Spectroradiometer Using a Laboratory Detector-Based Approach
Authors: Wang Zhipeng , Thome Kurtis , Lockwood Ronald , Wenny Brian N.
Published: May 2022

The HyperSpectral Imager for Climate Science (HySICS) is the core instrument of the Climate Absolute Refractivity and Reflectance Observatory (CLARREO) Pathfinder (CPF) mission and is currently scheduled to be launched to the International Space Station (ISS) in 2023. HySICS is an Offner–Chrisp imaging spectrometer designed to meet an unprecedented radiometric uncertainty requirement of 0.3% (k = 1) over its entire spectral range of 350–2300 nm. The approach represents the need for significant improvement over the Radiometric Calibration (RadCal) of existing space-borne spectrometers. One strategy to demonstrate that HySICS achieves this level of accuracy is through an Independent Calibration (IndCal) effort that can provide an alternative referencing RadCal, which follows a traceability chain independent of the operational RadCal of ratioing approach. The IndCal relies on a pre-launch detector-based absolute RadCal of HySICS, using a tunable laser system as source, and the system planned for the HySICS absolute RadCal is the Goddard Laser for Absolute Measurement of Radiance (GLAMR). GLAMR was developed at NASA’s Goddard Space Flight Center and has been used to calibrate multiple operational remote sensing instruments, as well as the SOlar, Lunar Absolute Reflectance Imaging Spectroradiometer (SOLARIS), a calibration demonstration system developed for the CLARREO mission. In this work, the data of SOLARIS GLAMR RadCal conducted in 2019 are processed to derive the Absolute Spectral Response (ASR) functions and other key characterization parameters of SOLARIS detectors. The results are further analyzed with the goals to plan the HySICS GLAMR RadCal, in particular to optimize its configuration, to demonstrate the traceability route to the NIST standard, and to develop the error budget of the calibration approach. The SOLARIS calibration is also compared with other source- and detector-based calibrations to validate the absolute radiometric accuracy achieved.
A Novel Remote Visual Inspection System for Bridge Predictive Maintenance
Authors: Galdelli Alessandro , D’Imperio Mariapaola , Marchello Gabriele , Mancini Adriano , Scaccia Massimiliano , Sasso Michele , Frontoni Emanuele , Cannella Ferdinando
Published: May 2022

Predictive maintenance on infrastructures is currently a hot topic. Its importance is proportional to the damages resulting from the collapse of the infrastructure. Bridges, dams and tunnels are placed on top on the scale of severity of potential damages due to the fact that they can cause loss of lives. Traditional inspection methods are not objective, tied to the inspector’s experience and require human presence on site. To overpass the limits of the current technologies and methods, the authors of this paper developed a unique new concept: a remote visual inspection system to perform predictive maintenance on infrastructures such as bridges. This is based on the fusion between advanced robotic technologies and the Automated Visual Inspection that guarantees objective results, high-level of safety and low processing time of the results.
Preliminary Evaluation of FY-3E Microwave Temperature Sounder Performance Based on Observation Minus Simulation
Authors: Qian Xiaoli , Qin Zhengkun , Li Juan , Han Yang , Liu Guiqing
Published: May 2022

The FY-3E satellite was successfully launched on 5 July 2021 and carries on board the Microwave Temperature Sounder-III (MWTS-III). In this study, the biases of MWTS-III data with respect to simulations are analyzed according to the instrument field of view and location latitude over the Pacific region. The cloud liquid water path (CLWP) over oceans is retrieved from two new window channels at 23.8 and 31.4 GHz and is used for detecting the clouds-affected microwave sounding data. The absolute bias between the observed and simulated brightness temperature (O–B) under the clear sky point is, in general, less than 2.0 K, depending on the MWTS-III channel. The standard deviations of O-B in most channels are less 1.0 K, but they are 1–1.5 K in channels 1–4 and 17. The average and the standard deviation of O−B from the channels 1–10 shows an obvious symmetrical variation with FOV. The evaluation results all indicate good prospects for the assimilation application of FY-3E microwave sounding data.
SCE-Net: Self- and Cross-Enhancement Network for Single-View Height Estimation and Semantic Segmentation
Authors: Xing Siyuan , Dong Qiulei , Hu Zhanyi
Published: May 2022

Single-view height estimation and semantic segmentation have received increasing attention in recent years and play an important role in the photogrammetry and remote sensing communities. The height information and semantic information of images are correlated, and some recent works have shown that multi-task learning methods can achieve complementation of task-related features and improve the prediction results of the multiple tasks. Although much progress has been made in recent works, how to effectively extract and fuse height features and semantic features is still an open issue. In this paper, a self- and cross-enhancement network (SCE-Net) is proposed to jointly perform height estimation and semantic segmentation on single aerial images. A feature separation–fusion module is constructed to effectively separate and fuse height features and semantic features based on an attention mechanism for feature representation enhancement across tasks. In addition, a height-guided feature distance loss and a semantic-guided feature distance loss are designed based on deep metric learning to achieve task-aware feature representation enhancement. Extensive experiments are conducted on the Vaihingen dataset and the Potsdam dataset to verify the effectiveness of the proposed method. The experimental results demonstrate that the proposed SCE-Net could outperform the state-of-the-art methods and achieve better performance in both height estimation and semantic segmentation.
Comparative Study of the 60 GHz and 118 GHz Oxygen Absorption Bands for Sounding Sea Surface Barometric Pressure
Authors: He Qiurui , Li Jiaoyang , Wang Zhenzhan , Zhang Lanjie
Published: May 2022

The 60 GHz and 118 GHz oxygen absorption bands are prominent in the passive microwave remote sensing of atmospheric temperature, and also can be used for sounding sea surface barometric pressure (SSP). Microwave Temperature Sounder II (MWTS-II) has 13 channels in the 60 GHz band, and Microwave Humidity and Temperature Sounder (MWHTS) has 8 channels in the 118 GHz band. They are both carried on Fengyun-3C Satellite (FY-3C) and Fengyun-3D Satellite (FY-3D), which provide measurements for comparing the retrieval accuracies of SSP using 60 GHz and 118 GHz bands. In this study, based on the weighting functions for MWHTS and MWTS-II, the 60 GHz and 118 GHz channel combinations representing 60 GHz and 118 GHz are established, respectively, and the retrieval accuracies of SSP from these two channel combinations are compared in different weather conditions. The experimental results show that the retrieval accuracy of SSP at 60 GHz is higher than that of 118 GHz in clear, cloudy, and rainy sky conditions. In addition, the retrieval experiments of SSP from MWTS-II and MWHTS are also carried out, and the experimental results show that the retrieval accuracy of SSP from MWTS-II is higher. The comparative study of the 60 GHz and 118 GHz for sounding SSP can provide support for the theoretical study of microwave remote sensing of SSP with practical measurements, and further contribute to understand the performance of 60 GHz and 118 GHz in atmospheric sounding.
Detection of Flood Extent Using Sentinel-1A/B Synthetic Aperture Radar: An Application for Hurricane Harvey, Houston, TX
Authors: Tiampo Kristy F. , Huang Lingcao , Simmons Conor , Woods Clay , Glasscoe Margaret T.
Published: May 2022

The increasing number of flood events combined with coastal urbanization has contributed to significant economic losses and damage to buildings and infrastructure. Development of higher resolution SAR flood mapping that accurately identifies flood features at all scales can be incorporated into operational flood forecasting tools, improving response and resilience to large flood events. Here, we present a comparison of several methods for characterizing flood inundation using a combination of synthetic aperture radar (SAR) remote sensing data and machine learning methods. We implement two applications with SAR GRD data, an amplitude thresholding technique applied, for the first time, to Sentinel-1A/B SAR data, and a machine learning technique, DeepLabv3+. We also apply DeepLabv3+ to a false color RGB characterization of dual polarization SAR data. Analyses at 10 m pixel spacing are performed for the major flood event associated with Hurricane Harvey and associated inundation in Houston, TX in August of 2017. We compare these results with high-resolution aerial optical images over this time period, acquired by the NOAA Remote Sensing Division. We compare the results with NDWI produced from Sentinel-2 images, also at 10 m pixel spacing, and statistical testing suggests that the amplitude thresholding technique is the most effective, although the machine learning analysis is successful at reproducing the inundation shape and extent. These results demonstrate the effectiveness of flood inundation mapping at unprecedented resolutions and its potential for use in operational emergency hazard response to large flood events.
A Machine Learning Approach to Waterbody Segmentation in Thermal Infrared Imagery in Support of Tactical Wildfire Mapping
Authors: Oliver Jacqueline A. , Pivot Frédérique C. , Tan Qing , Cantin Alan S. , Wooster Martin J. , Johnston Joshua M.
Published: May 2022

Wildfire research is working toward near real-time tactical wildfire mapping through the application of computer vision techniques to airborne thermal infrared (IR) imagery. One issue hindering automation is the potential for waterbodies to be marked as areas of combustion due to their relative warmth in nighttime thermal imagery. Segmentation and masking of waterbodies could help resolve this issue, but the reliance on data captured exclusively in the thermal IR and the presence of real areas of combustion in some of the images introduces unique challenges. This study explores the use of the random forest (RF) classifier for the segmentation of waterbodies in thermal IR images containing a heterogenous wildfire. Features for classification are generated through the application of contextual and textural filters, as well as normalization techniques. The classifier’s outputs are compared against static GIS-based data on waterbody extent as well as the outputs of two unsupervised segmentation techniques, based on entropy and variance, respectively. Our results show that the RF classifier achieves very high balanced accuracy (>98.6%) for thermal imagery with and without wildfire pixels, with an overall F1 score of 0.98. The RF method surpassed the accuracy of all others tested, even with heterogenous training sets as small as 20 images. In addition to assisting automation of wildfire mapping, the efficiency and accuracy of this approach to segmentation can facilitate the creation of larger training data sets, which are necessary for invoking more complex deep learning approaches.
Experimental Study on the Exploration of Camera Scanning Reflective Fourier Ptychography Technology for Far-Field Imaging
Authors: Yang Mingyang , Fan Xuewu , Wang Yuming , Zhao Hui
Published: May 2022

Fourier ptychography imaging is a powerful phase retrieval method that can be used to realize super-resolution. In this study, we establish a mathematical model of long-distance camera scanning based on reflective Fourier ptychography imaging. In order to guarantee the effective recovery of a high-resolution image in the experiment, we analyze the influence of laser coherence in different modes and the surface properties of diverse materials for diffused targets. For the analysis, we choose a single-mode fiber laser as the illumination source and metal materials with high diffused reflectivity as the experimental targets to ensure the validity of the experimental results. Based on the above, we emulate camera scanning with a single camera attached to an X-Y translation stage, and an experimental system with a working distance of 3310 mm is used as an example to image a fifty-cent coin. We also perform speckle analysis for rough targets and calculate the average speckle size using a normalized autocorrelation function in different positions. The method of calculating the average speckle size for everyday objects provides the premise for subsequent research on image quality evaluation; meanwhile, the coherence of the light field and the targets with high reflectivity under this experiment provide an application direction for the further development of the technique, such as computer vision, surveillance and remote sensing.
Optical Turbulence Profile in Marine Environment with Artificial Neural Network Model
Authors: Bi Cuicui , Qing Chun , Wu Pengfei , Jin Xiaomei , Liu Qing , Qian Xianmei , Zhu Wenyue , Weng Ningquan
Published: May 2022

Optical turbulence strongly affects different types of optoelectronic and adaptive optics systems. Systematic direct measurements of optical turbulence profiles [Cn2(h)] are lacking for many climates and seasons, particularly in marine environments, because it is impractical and expensive to deploy instrumentation. Here, a backpropagation neural network optimized using a genetic algorithm (GA-BP) is developed to estimate atmospheric turbulence profiles in marine environments which is validated against corresponding [Cn2(h)] profile datasets from a field campaign of balloon-borne microthermal measurements at the Haikou marine environment site. Overall, the trend and magnitude of the GA-BP model and measurements agree. The [Cn2(h)] profiles from the GA-BP model are generally superior to those obtained by BP and the physically-based (HMNSP99) models. Several statistical operators were used to quantify the GA-BP model performance on reconstructing the optical turbulence profiles in marine environments. The characterization of vertical distributions of optical turbulence profiles and the main integral parameters derived from [Cn2(h)] profiles are presented. The median Fried parameter, isoplanatic angle, and coherence time are 9.94 cm, 0.69″, and 2.85 ms, respectively, providing independent optical turbulence parameters for adaptive optics systems. The proposed approach exhibits potential for implementation in ground-based optical applications in marine environments.
Urbanization Level in Chinese Counties: Imbalance Pattern and Driving Force
Authors: Zhang Baifa , Zhang Jing , Miao Changhong
Published: May 2022

Urbanization level is a key indicator for socioeconomic development and policy making, but the measurement data and methods need to be discussed further due to the limitation of a single index and the availability and accuracy of statistical data. China is urbanizing rapidly, but the urbanization level at the county scale remains a mystery due to its complexity and lack of unified and effective measurement indicators. In this paper, we proposed a new urbanization index to measure the Chinese urbanization level at the county scale by integrating population, land, and economic factors; by fusing remote sensing data and traditional demographic data, we investigated the multi-dimensional unbalanced development patterns and the driving mechanism from 1995 to 2015. Results indicate that: The average comprehensive urbanization level at the Chinese county scale has increased from 31.06% in 1995 to 45.23% in 2015, and the urbanization level in the permanent population may overestimate China’s urbanization process. There were significant but different spatial and temporal dynamic patterns in population, land, and economic levels as well as at a comprehensive urbanization level. The comprehensive urbanization level shows the pattern of being high in the south-east and low in the north-west, divided by “Hu line”. The urbanization of registered populations presents high in the northern border and the eastern coastal areas, which is further strengthened over time. Economic urbanization based on lighting data presents high in the east and low in the west. Land urbanization based on remote sensing data shows high in the south and low in the north. The registered population urbanization level is lower than economic and land urbanization. County urbanization was driven by large population size, reasonable industrial structure, and strong government capacity; 38% and 59% of urbanization levels can be regarded as the key nodes of the urbanization process. When the urbanization rate is lower than 38%, the secondary industry plays a strong role in powering urbanization; when the urbanization rate is higher than 38% but less than 59%, the promotion effect of the tertiary industry is more obvious, and the secondary industry is gradually weakened. When the urbanization rate exceeds 59%, the tertiary industry becomes the major driver.
An Integrated Model of Summer and Winter for Chlorophyll-a Retrieval in the Pearl River Estuary Based on Hyperspectral Data
Authors: Li Haitao , Xie Xuetong , Yang Xiankun , Cao Bowen , Xia Xuening
Published: May 2022

Chlorophyll-a (Chla) is an important parameter for water quality. For remote sensing-based methods for the measurement of Chla, in-situ hyperspectral data is crucial for building retrieval models. In the Pearl River Estuary, we used 61 groups of in-situ hyperspectral data and corresponding Chla concentrations collected in July and December 2020 to build a Chla retrieval model that takes the two different seasons and the turbidity of water into consideration. The following results were obtained. (1) Based on the pre-processing techniques for hyperspectral data, it was shown that the first-derivative of 680 nm is the optimal band for the estimation of Chla in the Pearl River Estuary, with R2 > 0.8 and MAPE of 26.03%. (2) To overcome the spectral resolution problem in satellite image retrieval, based on the simulated reflectance from the Sentinel-2 satellite and the shape of the discrete spectral curve, we constructed a multispectral model using the slope difference index method, which reached a R2 of 0.78 and MAPE of 35.21% and can integrate the summer and winter data. (3) The slope difference method applied to the Sentinel-2 image shows better performance than the red-NIR ratio method. Therefore, the method proposed in this paper is practicable for Chla monitoring of coastal waters based on both in-situ data and images.
Combining Different Transformations of Ground Hyperspectral Data with Unmanned Aerial Vehicle (UAV) Images for Anthocyanin Estimation in Tree Peony Leaves
Authors: Luo Lili , Chang Qinrui , Gao Yifan , Jiang Danyao , Li Fenling
Published: May 2022

To explore rapid anthocyanin (Anth) detection technology based on remote sensing (RS) in tree peony leaves, we considered 30 species of tree peonies located in Shaanxi Province, China. We used an SVC HR~1024i portable ground object spectrometer and mini-unmanned aerial vehicle (UAV)-borne RS systems to obtain hyperspectral (HS) reflectance and images of canopy leaves. First, we performed principal component analysis (PCA), first-order differential (FD), and continuum removal (CR) transformations on the original ground-based spectra; commonly used spectral parameters were implemented to estimate Anth content using multiple stepwise regression (MSR), partial least squares (PLS), back-propagation neural network (BPNN), and random forest (RF) models. The spectral transformation highlighted the characteristics of spectral curves and improved the relationship between spectral reflectance and Anth, and the RF model based on the FD spectrum portrayed the best estimation accuracy (R2c = 0.91; R2v = 0.51). Then, the RGB (red-green-blue) gray vegetation index (VI) and the texture parameters were constructed using UAV images, and an Anth estimation model was constructed using UAV parameters. Finally, the UAV image was fused with the ground spectral data, and a multisource RS model of Anth estimation was constructed, based on PCA + UAV, FD + UAV, and CR + UAV, using MSR, PLS, BPNN, and RF methods. The RF model based on FD+UAV portrayed the best modeling and verification effect (R2c = 0.93; R2v = 0.76); compared with the FD-RF model, R2c increased only slightly, but R2v increased greatly from 0.51 to 0.76, indicating improved modeling and testing accuracy. The optimal spectral transformation for the Anth estimation of tree peony leaves was obtained, and a high-precision Anth multisource RS model was constructed. Our results can be used for the selection of ground-based HS transformation in future plant Anth estimation, and as a theoretical basis for plant growth monitoring based on ground and UAV multisource RS.
Local Persistent Ionospheric Positive Responses to the Geomagnetic Storm in August 2018 Using BDS-GEO Satellites over Low-Latitude Regions in Eastern Hemisphere
Authors: Tang Jun , Gao Xin , Yang Dengpan , Zhong Zhengyu , Huo Xingliang , Wu Xuequn
Published: May 2022

We present the ionospheric disturbance responses over low-latitude regions by using total electron content from Geostationary Earth Orbit (GEO) satellites of the BeiDou Navigation Satellite System (BDS), ionosonde data and Swarm satellite data, during the geomagnetic storm in August 2018. The results show that a prominent total electron content (TEC) enhancement over low-latitude regions is observed during the main phase of the storm. There is a persistent TEC increase lasting for about 1–2 days and a moderately positive disturbance response during the recovery phase on 27–28 August, which distinguishes from the general performance of ionospheric TEC in the previous storms. We also find that this phenomenon is a unique local-area disturbance of the ionosphere during the recovery phase of the storm. The enhanced foF2 and hmF2 of the ionospheric F2 layer is observed by SANYA and LEARMONTH ionosonde stations during the recovery phase. The electron density from Swarm satellites shows a strong equatorial ionization anomaly (EIA) crest over the low-latitude area during the main phase of storm, which is simultaneous with the uplift of the ionospheric F2 layer from the SANYA ionosonde. Meanwhile, the thermosphere O/N2 ratio shows a local increase on 27–28 August over low-latitude regions. From the above results, this study suggests that the uplift of F layer height and the enhanced O/N2 ratio are possibly main factors causing the local-area positive disturbance responses during the recovery phase of the storm in August 2018.
A Underwater Sequence Image Dataset for Sharpness and Color Analysis
Authors: Yang Miao , Yin Ge , Wang Haiwen , Dong Jinnai , Xie Zhuoran , Zheng Bing
Published: May 2022

The complex underwater environment usually leads to the problem of quality degradation in underwater images, and the distortion of sharpness and color are the main factors to the quality of underwater images. The paper discloses an underwater sequence image dataset called TankImage-I with gradually changing sharpness and color distortion collected in a pool. TankImage-I contains two plane targets, a total of 78 images. It includes two lighting conditions and three different water transparency. The imaging distance is also changed during the photographing process. The paper introduces the relevant details of the photographing process, and provides the measurement results of the sharpness and color distortion of the sequence images. In addition, we verify the performance of 14 image quality assessment methods on TankImage-I, and analyze the results of 14 image quality assessment methods from the aspects of sharpness and color, which provides a reference for the design and improvement of underwater image quality assessment algorithm and underwater imaging system design.
Dominant Narratives of Whiteness in Identity Construction of Mixed-Race Young Adults in Post-Apartheid South Africa
Authors: Metcalfe Jody
Published: May 2022

Despite the relative freedoms gained after the transition to democracy in 1994 in South Africa, dominant narratives of Whiteness stemming from settler-colonial and apartheid legacies of White supremacy remain pervasive within all structures of post-apartheid society, including the identity construction and racialisation of first-generation mixed-race people. This research explored how dominant narratives of Whiteness influence the construction of identity among mixed-race youth in post-apartheid South Africa. In-depth, semi-structured interviews were conducted with 10 participants who have one White parent and one parent of colour and were considered ‘born frees’, as they were born during or after the transition to democracy. Guided by critical race theory, through thematic analysis, three main themes emerged: defying Rainbowism, rejecting Whiteness, and policing identity. Ultimately, this research critically investigates how mixed-race people have constructed their identities while navigating pervasive power structures of White supremacy that continue to shape the rigid racial categorisations in post-apartheid South Africa.
Female Corporate Leadership and Firm Growth Strategy: A Global Perspective
Authors: Laidoja Lagle , Li Xuanye , Liu Wenyuan , Ren Ting
Published: May 2022

This study aims to understand the relationship between female corporate leadership and firm performance based on exploration and exploitation strategies using a global enterprise data set. Previous studies report conflicting evidence of female corporate leadership on firm performance. This study applies an exploration–exploitation framework and suggests that the relative advantage of female corporate leadership relies upon certain aspects of the firm’s growth strategy. The empirical evidence confirms that the relative advantage of female corporate leadership resides more in the exploitation than the exploration aspect of a firm’s growth strategy compared to male corporate leadership. The study thus offers important implications for broader business practices when considering the alignment between the choice of corporate leadership and firm growth strategy.
How do Internal Control Environments Connect to Sustainable Development to Curb Fraud in Brazil?
Authors: Mendes de Oliveira Debora Kobayashi , Imoniana Joshua Onome , Slomski Valmor , Reginato Luciane , Slomski Vilma Geni
Published: May 2022

This paper investigates the connection of internal control environment to sustainable development goals to curb fraud in Brazil. We drew on the interpretivist and constructivist perspectives with discourse analysis. Data corpus consists of interviews of 20 respondents who are external auditors, internal auditors, and employees of the controller’s department of an organization of ecommerce and archival documents. Results did not find any significant relationship between the connection of internal control functions (ICF) and the Sustainable Development Goals (SDGs) inasmuch as the connection of ICF to efficiency is tied to policies in compliance with standards, management tone, roles of enforcement, accountability, and adherence and obedience of rules. Triangulating SDG-16 with the dimensions of the control environment, fraud manifests mainly as a result of lack of commitment to integrity and values, as well as ineffectiveness of monitoring functions. This study concludes for the building of effective, accountable and even institutions with the embedding monitoring functions to sustain development goals. Since ex ante literatures examined the conceptual framework in isolation, this study connects it to sustainable development goals. Finally, this study signals an implication in the internal control literature as it clarifies the scientific theories and practical baseline of internal control environment to the policymakers, practitioners, and academia in view of the way forward on the connection of ICF to the SDG in the fight against corporate frauds.
Microwave-Assisted Exploration of Yellow Natural Dyes for Nylon Fabric
Authors: Rehman Fazal Ur , Adeel Shahid , Haddar Wafa , Bibi Razia , Azeem Muhammad , Mia Rony , Ahmed Bulbul
Published: May 2022

Today, the global community is appreciating green technologies in the application of green products in textiles. The aim of the current study is to use a sustainable heating technique for the isolation of colorant from plant sources and to use eco-friendly anchors to improve the fastness of dyed fabrics with new shades. The current study used microwave radiation to isolate natural colorants from saffron (Crocus sativus) and safflower (Carthamus tinctorius L.) petals for polyamide (nylon) fabric dyeing. For this purpose, acidic extract and fabric were exposed to MW treatment for up to 6 min and employed at various conditions. To make the dyeing process sustainable, bio-mordants have been employed and compared with synthetic mordants. It has been found that 6 min is the optimal radiation time for the isolation of colorant to get good results onto irradiated polyamide (nylon) fabric when employed at 65 °C for 45 min containing 1 g/100 mL of table salt for saffron and 3 g/100 mL of table salt for safflower dyeing. For improving color strength and giving an acceptable rating of fastness, 7% of turmeric as a pre-bio mordant and 7% pomegranate as a post-mordant has given high results using saffron extract. Similarly, with safflower extract, 5% of turmeric as a pre-mordant and 5% of turmeric extracts as a post-mordant have given high results as compared to chemical mordants used. It is concluded that microwave treatment has a high potential for investigating the coloring efficacy of crocin-containing saffron petals and safflower petals as carthamin as a yellow natural dye for bio-mordanted polyamide fabrics. It is recommended that such tools for the isolation of colorant from new dye-producing plants should be used, whereas green mordants should be used to develop new colorfast shades to make process more green and sustainable.
Study of the Relationship of Bullying with the Levels of Eudaemonic Psychological Well-Being in Victims and Aggressors
Authors: Carretero Bermejo Raúl , Nolasco Hernández Alberto , Sánchez Laura Gracia
Published: May 2022

Bullying has a negative impact on adolescents’ emotional and social development, especially in the case of victims. This study aims to explore the association of engagement in bullying behaviours, for both the victim and aggressor, with psychological well-being. A non-experimental, cross-sectional and correlational quantitative study was designed, with the participation of 570 students between 14 and 15 years old (SD 0.99), of which 50.5% were girls and 49.5% boys, who were selected through stratified random sampling. Mean differences, bivariate correlations and multiple linear regressions were calculated to study the relationship between bullying and psychological well-being. Victims scored lower for subjective well-being, with the educational and social implications that this means. As for the aggressors, who scored higher on well-being than non-aggressors, the question is raised as to whether well-being increases with aggression or whether aggression is the result of lower levels of well-being. Female bullying victims belonging to the older age group are the participant profile with the lowest well-being scores. This gender perspective can be considered not only with regards to coexistence and bullying prevention plans but also shows the need to promote psychological well-being to educate towards equality.
Ecological–Economic Modelling of Traditional Agroforestry to Promote Farmland Biodiversity with Cost-Effective Payments
Authors: Nishizawa Takamasa , Kay Sonja , Schuler Johannes , Klein Noëlle , Herzog Felix , Aurbacher Joachim , Zander Peter
Published: May 2022

Orchard meadows, a traditional agroforestry system in Switzerland combining the dual use fruit and fodder production, are declining, even though the farmland managed under agri-environmental schemes (AES) has been expanding. Despite increasing interest in agroforestry research for developing sustainable agriculture, it is poorly understood how subsidies contribute to the maintenance of trees on agricultural land and the promotion of farmland biodiversity. Therefore, the objective of the present study is to examine the effects of incentive-based AES on both farmers’ decisions regarding trees and biodiversity by developing an ecological–economic assessment model. To explore cost-effective AES, we explicitly consider the heterogeneity of farm types. We apply this integrated model to the farms in Schwarzbubenland, a small hilly region in Northern Switzerland. Results show that the adoption of AES and the compliance costs of participating in AES considerably vary among farm types, and the current AES do not provide farmers with sufficient payments to maintain any type of orchard meadows, despite the ecological benefits of orchard meadows. The integrating modeling developed in this study enables us to better understand the relationship between subsidies and biodiversity through farmers’ decisions on land use and facilitates the design of cost-effective payments for the maintenance of agroforestry.
Energy-Saving Effect of Regional Development Strategy in Western China
Authors: Zheng Chunji , Deng Feng , Li Chengyou
Published: May 2022

Improving energy utilisation efficiency is imperative to ensuring economic growth and achieving sustainable development. China’s Western Development Strategy (WDS) is a major driver to accelerate the economic development of Western China. It stresses the rational control of energy consumption through the vigorous development of a circular economy to achieve the goal of energy conservation. Based on the measurement of energy utilisation efficiency at the provincial level in China, this study evaluates the impact of the WDS on energy utilisation efficiency through a synthetic control method. Then, the internal impact mechanism of the WDS on energy utilisation efficiency is investigated. In addition, this paper tests the heterogeneous effects of the WDS on energy utilisation efficiency from the perspective of the regional scale, resource endowment, performance appraisal, and institutional quality. It is found that the WDS improves energy utilisation efficiency not only through direct effects but also indirectly by accelerating the spatial agglomeration of advantage industries in Western China, which enhanced technological innovation capacity, optimised industrial structure, and improved the human capital level to ameliorate energy utilisation efficiency. Further analysis proves that the energy-saving effect of the WDS is significant in provinces with a small regional scale, less abundant resources, higher levels of the performance appraisal index and quality system. Accordingly, some targeted policy suggestions are made for the government herein.
Self-Regulation, Teaching Presence, and Social Presence: Predictors of Students’ Learning Engagement and Persistence in Blended Synchronous Learning
Authors: Zhong Qiuju , Wang Ying , Lv Wu , Xu Jie , Zhang Yichun
Published: May 2022

Blended synchronous learning (BSL) is becoming increasingly widely implemented in many higher education institutions due to its accessibility and flexibility. However, little research has been conducted to explore students’ engagement and persistence and their possible predictors in such a learning mode. The purpose of this study was to investigate how to facilitate students’ engagement and persistence in BSL. In detail, this study used structural equation modeling to explore the relationships among specific predictors (self-regulation, teaching presence, and social presence), learning engagement, and learning persistence in BSL. We recruited 319 students who were enrolled in BSL at a Chinese university. The online survey was administered to gather data on the variables of this study. The results demonstrated that self-regulation, teaching presence, and social presence were positively associated with learning engagement. Self-regulation and learning engagement were positively associated with learning persistence. Moreover, learning engagement mediated the relationships between self-regulation, teaching presence, social presence, and learning persistence. This study suggests that self-regulation, teaching presence, and social presence are significant predictors for student learning engagement and persistence in BSL.
The Impact of Airport Physical Environment on Perceived Safety and Domestic Travel Intention of Chinese Passengers during the COVID-19 Pandemic: The Mediating Role of Passenger Satisfaction
Authors: Ma Guofeng , Ding Yue , Ma Junyi
Published: May 2022

The COVID-19 pandemic, which has become an important new research topic, has exerted a huge impact on airports and the antecedents of passengers’ travel decisions following its outbreak. In the current study, we aimed to investigate the influences of four attributes of airport physical environment (facility functionality, facility aesthetics, layout accessibility, and cleanliness) on passengers’ perceived safety, satisfaction, and travel intention, as well as the mediating role of passenger satisfaction. We built a structural equation model to assume the relationship between these variables. A total of 398 domestic travelers were asked to fill out a survey in order to reveal their perceptions of airport physical environment, perceived safety, satisfaction, and travel intention. The results indicate that passengers with positive perceptions of the facility functionality, layout accessibility, and cleanliness of airports had a higher degree of satisfaction and might be more willing to engage in more air travel in the future. In particular, a clean airport environment significantly improved passengers’ perceived safety. Moreover, facility functionality, layout accessibility, cleanliness, and perceived safety all had an effect on travel intention through the mediating role of satisfaction. Overall, these findings offer suggestions for airport authorities aiming to revive demand for air travel. Discussions about airport physical environment improvements along with limitations and suggestions for future research are provided.
Economical Productivity of Maize Genotypes under Different Herbicides Application in Two Contrasting Climatic Conditions
Authors: Božović Dragan , Popović Dragana , Popović Vera , Živanović Tomislav , Ljubičić Nataša , Ćosić Milivoje , Spahić Anđela , Simić Divna , Filipović Vladimir
Published: May 2022

Maize ranks first among worldwide production and an important source of human and animal feed. Its production can be affected by management practices and climatic conditions. The objective of this study was to estimate stability of yield and hundred grains weight of six maize genotypes during two growing seasons at two locations, subjected to four different treatments: T1 treatment—without herbicide, Control; T2 treatment—active substance Nicosulfuron and Motivell commercial preparation; T3 treatment—active substance Rimsulfuron and Tarot; and, T4 treatment—active substance Forasulfuron and Equip. Additive main effects and multiplicative interaction—AMMI model and genotype × environment interaction—GGE biplot were used to estimate GEI—genotype by environment interaction. The results showed that the influence of genotype (G), year (Y), locality (L), treatment (T) and all interaction on hundred grains weight were significant. The share of genotypes in the total phenotypic variance was 64.70%, while the share in total interaction was 26.88%. The share of IPCA1 in terms of G × T interaction was 50.6%, while share of IPCA2 was 44.74%, which comprised together 94.80% of interaction. The first IPCA1 axis showed high share in the total interaction, which indicates out significance of genotype in total variation and interaction, while high level of IPCA2 indicates a significant treatment effect. Genotype L-6 had the same mass of 100 grains (37.96 g) during both years of testing, while genotype L-1, with 4.46 g, had the largest difference between years. This clearly indicates the influence of genotype but also stress under the influence of sulfonylureas and environmental factors. The maize genotype with the highest values of hundred grains weight, L-5 and L-6, expressed the highest values of grain yield (4665 kg ha−1 and 4445 kg ha−1).
Monitoring and Evaluation of Eco-Environment Quality Based on Remote Sensing-Based Ecological Index (RSEI) in Taihu Lake Basin, China
Authors: Zhou Jianbo , Liu Wanqing
Published: May 2022

Rapid and effective access to the spatiotemporal patterns and evolutionary trends of the regional eco-environment is key to regional environment protection and planning. Based on the Google Earth Engine platform, we use 165 Landsat images from the summer and autumn seasons (May–November) of 2000, 2010, and 2018 as data sources to calculate the RSEI, which represents the quality of the eco-environment, and then analyze the factors influencing the spatial heterogeneity of the eco-environment and the relationship between eco-environment and land-use changes based on RSEI. The results showed the following: (1) From 2000 to 2018, the overall ecological environment quality of the Taihu Lake Basin showed a stage of rapid decline (2000–2010) and a stage of slow decline (2010–2018). (2) The factors were ranked in order of their explanatory power for the spatial heterogeneity of the RSEI: land-use (0.594) > population density (0.418) > slope (0.309) > elevation (0.308) > GDP (0.304) > temperature (0.233) > precipitation (0.208). An interactive effect was found for each factor of the RSEI, which is mainly represented by a mutual enhancement. (3) From 2000 to 2010, the rapid urban expansion was the main reason for the deterioration of ecological quality. From 2010 to 2018, urban expansion slowed down, and the trend of ecological quality deterioration was effectively curbed. Therefore, promoting the intensive use of land and reducing construction land expansion are key to ensuring sustainable regional socio-economic development.
Sustainable Development in Basic Education Sciences in Portugal—Perspective of Official Curriculum Documents
Authors: João Patrícia , Sá Patrícia , Henriques Maria Helena , Rodrigues Ana V.
Published: May 2022

This study aims to identify and characterize the understanding of the concept of Sustainable Development in the official scientific educational documents of basic education in Portugal. Methodologically, it is a qualitative study that fits into the interpretive paradigm; its implementation is based on an interpretative-descriptive strategy of exploratory nature. The study involved the organization of the analysis corpus and the subsequent content analysis of the selected documents. The documents included in this corpus are the official educational documents on the teaching and learning of Natural Sciences in Basic Education (1st to 9th grade—ages 6 to 15): the Essential Learning and two transversal documents (the Student Profile on Leaving Compulsory Schooling and the Environmental Education Framework for Sustainability). The obtained results show that these documents frame and guide the implementation of Education for Sustainable Development, in all its dimensions, throughout basic education. However, this does not happen in an equitable way, neither in all documents nor in all years of schooling.
A Study of Assessment and Prediction of Water Quality Index Using Fuzzy Logic and ANN Models
Authors: Trach Roman , Trach Yuliia , Kiersnowska Agnieszka , Markiewicz Anna , Lendo-Siwicka Marzena , Rusakov Konstantin
Published: May 2022

Various human activities have been the main causes of surface water pollution. The uneven distribution of industrial enterprises in the territories of the main river basins of Ukraine do not always allow the real state of the water quality to be assessed. This article has three purposes: (1) the modification of the Ukrainian method for assessing the WQI, taking into account the level of negative impact of the most dangerous chemical elements, (2) the modeling of WQI assessment using fuzzy logic and (3) the creation of an artificial neural network model for the prediction of the WQI. The fuzzy logic model used four input variables and calculated one output variable (WQI). In the final stage of the study, six ANN models were analyzed, which differed from each other in various loss function optimizers and activation functions. The optimal results were shown using an ANN with the softmax activation function and Adam’s loss function optimizer (MAPE = 9.6%; R2 = 0.964). A comparison of the MAPE and R2 indicators of the created ANN model with other models for assessing water quality showed that the level of agreement between the forecast and target data is satisfactory. The novelty of this study is in the proposal to modify the WQI assessment methodology which is used in Ukraine. At the same time, the phased and joint use of mathematical tools such as the fuzzy logic method and the ANN allow one to effectively evaluate and predict WQI values, respectively.
Sustainable Relationship in Design: The Contribution Wisdom of Academies Landscape in Southern Jiangsu from an “Interpersonal View” Perspective
Authors: Xu Shu , Guo Weimin , Wang Xinyi , Xing Zhaolian
Published: May 2022

In recent years, designers have increasingly emphasized sustainability in landscape design, but they have focused more on the “human-nature” relationship while neglecting the relationship between people. As a result, problems such as inconvenient use of the landscape and waste of resources for management and renovation have been caused. To solve this problem, it is necessary to establish the correct concept at the beginning of design. Traditional Chinese ideas can often provide appropriate reference points for many contemporary issues, including design. Taking the landscapes of ancient academies in southern Jiangsu as an example, this paper tries to explore the methods and ideas of the designers to deal with the “people-people” relationship in the process of construction, as an example of sustainable landscape design. Both textual research and metrological historiography were used to examine and summarize the characteristics of the landscape construction of the academies in southern Jiangsu, combined with the analysis of the theory of “interpersonal view”. It is apparent that the landscape construction of the academies in southern Jiangsu is characterized by site selection with favorable geography and people, scale and function with the balance of supply and demand, building construction with thrift and efficiency, and a site-specific and simple courtyard built. The formation of these characteristics originates from the founder’s design concept of care about education and being kind to scholars, saving materials and taking good care of the people, benefiting others before to themselves, and portraying the Confucian idea of “great harmony in the world”. The thought and design concept of the landscape construction of the academies in southern Jiangsu can provide a reference point for landscape designers to solve the sustainable problem of the “people-people” relationship in landscape design.