bluuebunny/crossref_metadata_2025 huggingface dataset:
An Adaptive Attention Fusion Mechanism Convolutional Network for Object Detection in Remote Sensing Images
Authors: Ye Yuanxin , Ren Xiaoyue , Zhu Bai , Tang Tengfeng , Tan Xin , Gui Yang , Yao Qin
Published: January 2022

For remote sensing object detection, fusing the optimal feature information automatically and overcoming the sensitivity to adapt multi-scale objects remains a significant challenge for the existing convolutional neural networks. Given this, we develop a convolutional network model with an adaptive attention fusion mechanism (AAFM). The model is proposed based on the backbone network of EfficientDet. Firstly, according to the characteristics of object distribution in datasets, the stitcher is applied to make one image containing objects of various scales. Such a process can effectively balance the proportion of multi-scale objects and handle the scale-variable properties. In addition, inspired by channel attention, a spatial attention model is also introduced in the construction of the adaptive attention fusion mechanism. In this mechanism, the semantic information of the different feature maps is obtained via convolution and different pooling operations. Then, the parallel spatial and channel attention are fused in the optimal proportions by the fusion factors to get the further representative feature information. Finally, the Complete Intersection over Union (CIoU) loss is used to make the bounding box better cover the ground truth. The experimental results of the optical image dataset DIOR demonstrate that, compared with state-of-the-art detectors such as the Single Shot multibox Detector (SSD), You Only Look Once (YOLO) v4, and EfficientDet, the proposed module improves accuracy and has stronger robustness.
Precipitation Dominates the Relative Contributions of Climate Factors to Grasslands Spring Phenology on the Tibetan Plateau
Authors: Cheng Min , Wang Ying , Zhu Jinxia , Pan Yi
Published: January 2022

Temperature and precipitation are the primary regulators of vegetation phenology in temperate zones. However, the relative contributions of each factor and their underlying combined effect on vegetation phenology are much less clear, especially for the grassland of the Tibetan Plateau To quantify the contribution of each factor and the potential interactions, we conducted redundancy analysis for grasslands spring phenology on the Tibetan Plateau during 2000–2017. Generally, the individual contribution of temperature and precipitation to grasslands spring phenology (the start of growing season (SOS)) was lower, despite a higher correlation coefficient, which further implied that these factors interact to affect the SOS. The contributions of temperature and precipitation to the grasslands spring phenology varied across space on the Tibetan Plateau, and these spatial heterogeneities can be mainly explained by the spatial gradient of long-term average precipitation during spring over 2000–2017. Specifically, the SOS for meadow was dominated by the mean temperature in spring (Tspring) in the eastern wetter ecoregion, with an individual contribution of 24.16% (p < 0.05), while it was strongly negatively correlated with the accumulated precipitation in spring (Pspring) in the western drier ecoregion. Spatially, a 10 mm increase in long-term average precipitation in spring resulted in an increase in the contribution of Tspring of 2.0% (p < 0.1) for meadow, while it caused a decrease in the contribution of Pspring of −0.3% (p < 0.05). Similarly, a higher contribution of Pspring for steppe was found in drier ecoregions. A spatial decrease in precipitation of 10 mm increased the contribution of Pspring of 1.4% (p < 0.05). Considering these impacts of precipitation on the relative contribution of warming and precipitation to the SOS, projected climate change would have a stronger impact on advancing SOS in a relatively moist environment compared to that of drier areas. Hence, these quantitative interactions and contributions must be included in current ecosystem models, mostly driven by indicators with the direct and the overall effect in response to projected climate warming.
Predicting the Chlorophyll Content of Maize over Phenotyping as a Proxy for Crop Health in Smallholder Farming Systems
Authors: Brewer Kiara , Clulow Alistair , Sibanda Mbulisi , Gokool Shaeden , Naiken Vivek , Mabhaudhi Tafadzwanashe
Published: January 2022

Smallholder farmers depend on healthy and productive crop yields to sustain their socio-economic status and ensure livelihood security. Advances in South African precision agriculture in the form of unmanned aerial vehicles (UAVs) provide spatially explicit near-real-time information that can be used to assess crop dynamics and inform smallholder farmers. The use of UAVs with remote-sensing techniques allows for the acquisition of high spatial resolution data at various spatio-temporal planes, which is particularly useful at the scale of fields and farms. Specifically, crop chlorophyll content is assessed as it is one of the best known and reliable indicators of crop health, due to its biophysical pigment and biochemical processes that indicate plant productivity. In this regard, the study evaluated the utility of multispectral UAV imagery using the random forest machine learning algorithm to estimate the chlorophyll content of maize through the various growth stages. The results showed that the near-infrared and red-edge wavelength bands and vegetation indices derived from these wavelengths were essential for estimating chlorophyll content during the phenotyping of maize. Furthermore, the random forest model optimally estimated the chlorophyll content of maize over the various phenological stages. Particularly, maize chlorophyll was best predicted during the early reproductive, late vegetative, and early vegetative growth stages to RMSE accuracies of 40.4 µmol/m−2, 39 µmol/m−2, and 61.6 µmol/m−2, respectively. The least accurate chlorophyll content results were predicted during the mid-reproductive and late reproductive growth stages to RMSE accuracies of 66.6 µmol/m−2 and 69.6 µmol/m−2, respectively, as a consequence of a hailstorm. A resultant chlorophyll variation map of the maize growth stages captured the spatial heterogeneity of chlorophyll within the maize field. Therefore, the study’s findings demonstrate that the use of remotely sensed UAV imagery with a robust machine algorithm is a critical tool to support the decision-making and management in smallholder farms.
Response of Precipitation in Tianshan to Global Climate Change Based on the Berkeley Earth and ERA5 Reanalysis Products
Authors: Fan Mengtian , Xu Jianhua , Li Dahui , Chen Yaning
Published: January 2022

Global climate change has readjusted a global-scale precipitation distribution in magnitude and timing. In mountainous areas, meteorological stations and observation data are very limited, making it difficult to accurately understand the response of precipitation to global climate change. Based on ECMWF Reanalysis v5 precipitation products, Berkeley Earth global temperature, and typical atmospheric circulation indexes, we integrated a gradient descent-nonlinear regression downscaling model, cross wavelet transform, and wavelet correlation method to analyze the precipitation response in Tianshan to global climate change. This study provides a high-resolution (90 m × 90 m) precipitation dataset in Tianshan and confirms that global warming, the North Pacific Pattern (NP), the Western Hemisphere Warm Pool (WHWP), and the Atlantic Multidecadal Oscillation (AMO) are related to the humidification of Tianshan over the past 40 years. The precipitation in Tianshan and global temperature have a resonance period of 8–15 months, and the correlation coefficient is above 0.9. In Tianshan, spring precipitation is determined mainly by AMO, North Tropical Atlantic Sea Level Temperature, Pacific Interdecadal Oscillation (PDO), Tropical North Atlantic Index, WHWP, NP, summer by NP, North Atlantic Oscillation, and PDO, autumn by AMO, and winter by Arctic Oscillation. This research can serve the precipitation forecast of Tianshan and help in the understanding of the regional response to global climate change.
TRDet: Two-Stage Rotated Detection of Rural Buildings in Remote Sensing Images
Authors: Peng Baochai , Ren Dong , Zheng Cheng , Lu Anxiang
Published: January 2022

Fast and accurate acquisition of the outline of rural buildings on remote sensing images is an efficient method to monitor illegal rural buildings. The traditional object detection method produces useless background information when detecting rural buildings; the semantic segmentation method cannot accurately segment the contours between buildings; the instance segmentation method cannot obtain regular building contours. The rotated object detection methods can effectively solve the problem that the traditional artificial intelligence method cannot accurately extract the outline of buildings. However, the rotated object detection methods are easy to lose location information of small objects in advanced feature maps and are sensitive to noise. To resolve these problems, this paper proposes a two-stage rotated object detection network for rural buildings (TRDet) by using a deep feature fusion network (DFF-Net) and a pixel attention module (PAM). Specifically, TRDet first fuses low-level location and high-level semantic information through the DFF-Net and then reduces the interference of noise information to the network through the PAM. The experimental results show that the mean average precession (mAP), precision, recall rate, and F1 score of the proposed TRDet are 83.57%, 91.11%, 86.5%, and 88.74%, respectively, which outperform the R2CNN model by 15%, 15.54%, 4.01%, and 9.87%. The results demonstrate that the TRDet can achieve better detection in small rural buildings and dense rural buildings.
Challenges and Possibilities of Archaeological Sites Virtual Tours: The Ulaca Oppidum (Central Spain) as a Case Study
Authors: Maté-González Miguel Ángel , Rodríguez-Hernández Jesús , Sáez Blázquez Cristina , Troitiño Torralba Libertad , Sánchez-Aparicio Luis Javier , Fernández Hernández Jesús , Herrero Tejedor Tomás Ramón , Fabián García José Francisco , Piras Marco , Díaz-Sánchez Carlos , González-Aguilera Diego , Ruiz Zapatero Gonzalo , Álvarez-Sanchís Jesús R.
Published: January 2022

This research presents a virtual tour performed on the oppidum of Ulaca, one of the most relevant archaeological sites of the Iberian Peninsula during the Late Iron Age (ca. 400–50 BC). Beyond the clear benefits of the tool to the interpretation, dissemination, and knowledge of the mentioned archaeological site and its surroundings, the novelty of this research is the implementation of the platform in alternative scenarios and purposes. In this way, the present work verifies how the access to multi-source and spatially geolocated information in the same tool (working as a geospatial database) allows the promotion of cross-sectional investigations in which different specialists intervene. This peculiarity is also considered useful to promote tourism with an interest beyond the purely historical/archaeological side. Likewise, the possibility of storing and managing a large amount of information in different formats facilitates the investigation in the contexts of excavations and archaeological or environmental works. In this sense, the use of this kind of tool for the study of cultural landscapes is especially novel. In order to better contextualize the potential of the virtual tour presented here, an analysis about the challenges and possibilities of implementing this tool in environments such as the Ulaca oppidum is performed. The selected site stands out for: (i) being in a unique geological, environmental and ecological context, allowing us to appreciate how human beings have modified the landscape over time; (ii) presenting numerous visible archaeological remains with certain conservation problems; and (iii) not having easy access for visitors.
Satellite Survey of Offshore Oil Seep Sites in the Caspian Sea
Authors: Mityagina Marina , Lavrova Olga
Published: January 2022

This paper presents the results of a long-term survey of the Caspian Sea using satellite SAR and multispectral sensors. The primary environmental problem of the Caspian Sea is oil pollution which is determined by its natural properties, mainly by the presence of big oil and gas deposits beneath the seabed. Our research focuses on natural oil slicks (NOS), i.e., oil showings on the sea surface due to natural hydrocarbon emission from seabed seeps. The spatial and temporal variability of NOS in the Caspian Sea and the possibilities of their reliable detection using satellite data are examined. NOS frequency and detectability in satellite images depending on sensor type, season and geographical region are assessed. It is shown that both parameters vary significantly, and largely depend on sensor type and season, with season being most pronounced in visible (VIS) data. The locations of two offshore seep sites at the Iranian and Turkmenian shelves are accurately estimated. Statistics on individual sizes of NOS are drawn. The release rates of crude oil from the seabed to the sea surface are compared. Detailed maps of NOS are put together, and areas exposed to high risk of sea surface oil pollution are determined.
A New Space-to-Ground Microwave-Based Two-Way Time Synchronization Method for Next-Generation Space Atomic Clocks
Authors: Guo Yanming , Gao Shuaihe , Bai Yan , Pan Zhibing , Liu Yinhua , Lu Xiaochun , Zhang Shougang
Published: January 2022

The accuracy of time synchronization can be significantly increased by enhancing the performance of atomic clocks. Future-generation time-frequency loads will be equipped with the latest ultrahigh-precision atomic clocks (with a day stability better than 10−17) and will leverage advantages of the space environment such as microgravity and low interference to operate a new generation of high-performance time-frequency payloads on low-orbit spacecraft. Moreover, using the high-precision time-frequency system of ground stations, low-time-delay high-performance time-frequency transmission networks, which have the potential to achieve ultrahigh-precision time synchronization, will be constructed. By considering full link error terms above the picosecond level, this paper proposes a new space-to-ground microwave two-way time synchronization method for scenarios involving low-orbit spacecraft and ground stations. Using the theoretical principles and practical application scenarios related to this method, a theoretical and simulation verification platform was developed to research the impact of the attitude, phase center calibration, and orbit determination errors on the single-frequency two-way time synchronization method. The effectiveness of this new method was verified. The results showed that when the attitude error is less than 72 arc seconds (0.02°), the phase center calibration error is less than 1 mm, and the precision orbit determination (POD) error is less than 10 cm (three-axis). After disregarding nonlink error terms such as equipment noise, this method can attain a space-to-ground time synchronization accuracy of better than 1.5 ps, and the time deviation (TDEV) of the transfer link is better than 0.7 ps @ 100 s, which results in ultrahigh-precision space-to-ground time synchronization.
Monitoring and Stability Analysis of the Deformation in the Woda Landslide Area in Tibet, China by the DS-InSAR Method
Authors: Liu Youfeng , Yang Honglei , Wang Shizheng , Xu Linlin , Peng Junhuan
Published: January 2022

The Woda area in the upper Jinsha River has steep terrain and broken structures, causing landslide disasters frequently. Here, we used the distributed scatterer interferometric SAR (DS-InSAR) method to monitor and analyze the Woda landslide area. With the DS-InSAR method, we derived the deformation of the Woda landslide area from 106 Sentinel-1A ascending images acquired between 5 November 2014 and 4 September 2019 and 102 Sentinel-1A descending images acquired between 31 October 2014 and 11 September 2019. The obvious advantage of the DS-InSAR method compared to the persistent scatterer (PS) InSAR (PS-InSAR) method is that the densities of the monitoring points were increased by 25.1% and 22.9% in the ascending and descending images, respectively. The two-dimensional deformation of the landslide area shows that the maximum surface deformation rate in the normal direction was −80 mm/yr, and in the east–west direction, 118 mm/yr. According to the rescaled range (R/S) analysis, the Hurst index values of the deformation trends were all greater than 0.5, which means the deformation trend will continue for some time. In addition, we analyzed the influencing factors and the deformation mechanism of the Woda landslide area and found that the surface deformation is closely related to the geological structure and precipitation, among which precipitation is the main factor triggering the deformation. Our monitoring results will help the local government to conduct regular inspections and strengthen landslide disaster prevention in low-coherence mountainous areas.
Improving the Inversion Accuracy of Terrestrial Water Storage Anomaly by Combining GNSS and LSTM Algorithm and Its Application in Mainland China
Authors: Shen Yifan , Zheng Wei , Yin Wenjie , Xu Aigong , Zhu Huizhong , Wang Qingqing , Chen Zhiwei
Published: January 2022

Densely distributed Global Navigation Satellite System (GNSS) stations can invert the terrestrial water storage anomaly (TWSA) with high precision. However, the uneven distribution of GNSS stations greatly limits the application of TWSA inversion. The purpose of this study was to compensate for the spatial coverage of GNSS stations by simulating the vertical deformation in unobserved grids. First, a new deep learning weight loading inversion model (DWLIM) was constructed by combining the long short-term memory (LSTM) algorithm, inverse distance weight, and the crustal load model. DWLIM is beneficial for improving the inversion accuracy of TWSA based on the GNSS vertical displacement. Second, the DWLIM-based and traditional GNSS-derived TWSA methods were utilized to derive TWSA over mainland China. Furthermore, the TWSA results were compared with the TWSA solutions of the Gravity Recovery and Climate Experiment (GRACE) and Global Land Data Assimilation System (GLDAS) model. The results indicate that the maximum Pearson’s correlation coefficient (PCC), Nash–Sutcliffe efficiency (NSE) coefficient, and root mean square error (RMSE) equal 0.81, 0.61, and 2.18 cm, respectively. The accuracy of DWLIM was higher than that of the traditional GNSS inversion method according to PCC, NSE, and RMSE, which were increased by 67.11, 128.15, and 22.75%. The inversion strategy of DWLIM can effectively improve the accuracy of TWSA inversion in regions with unevenly distributed GNSS stations. Third, this study investigated the variation characteristics of TWSA based on DWLIM in 10 river basins over mainland China. The analysis shows that the TWSA amplitudes of Songhua and Liaohe River basins are significantly higher than those of the other basins. Moreover, TWSA sequences in each river basin contain annual seasonal signals, and the wave peaks of TWSA estimates emerge between June and July. Overall, DWLIM provides a useful measure to derive TWSA in regions where GNSS stations are uneven or sparse.
Application of Complex Geophysical Methods for the Detection of Unconsolidated Zones in Flood Dikes
Authors: Gołębiowski Tomisław , Piwakowski Bogdan , Ćwiklik Michał
Published: January 2022

The flood levees in the vicinity of Krakow city (Poland) are, in some places, over 100 years old. Thereupon, in the flood dike, and its subsoil, can appear unconsolidated zones, which, during the flood stage, can be a simple way of water flow and/or even can be the place where the levee body will be destroyed. This phenomenon took place in Wawrzeńczyce village, near Krakow city, during the flood in 2010. The geophysical research was carried out, in order to develop a methodology of recognition of potential areas where the levee body can be damaged. The geophysical surveys were conducted with the use of electrical and electromagnetic methods, as well as utilizing the seismic method. The general identification of examined media was realized by the electrical resistivity tomography (ERT) method. The ERT surveys were supplemented by capacitively-coupled resistivity (CCR) measurements, in order to analyze the usefulness of the CCR method for the examination of river dikes and reduction of interpretation ambiguity. The ground penetrating radar (GPR) method detected small anomalies in the body dike, due to the very high resolution of this method, which were not detected by the ERT and CCR techniques. During GPR surveys, non-standard measurement techniques were applied. Finally, the high-resolution seismic reflection (HRSR) method provided a clear and high-resolution image of the dike structure up to the water table and assisted with the identification of the hazard non-consolidated zones.
A New Type of Red-Green-Blue Composite and Its Application in Tropical Cyclone Center Positioning
Authors: Chen Liren , Zhuge Xiaoyong , Tang Xiaodong , Song Jinjie , Wang Yuan
Published: January 2022

Weak tropical cyclone (TC) center positioning is difficult work in operational forecasting. In the present study, a TC-red-green-blue (TC-RGB) composite was designed by using satellite multichannel observations (reflectance, brightness temperature, and brightness temperature differences). Compared with single channel images, TC-RGB composites can clearly show the exposed low-level circulation (LLC) of weak TCs under large vertical wind shear. Based on the guidelines of TC-RGB composites for TC center positioning, we repositioned 83 western North Pacific (WNP) TC cases during 2017–2019. Then, the comparisons of TC center positions were made between the TC-RGB composite and the Regional Specialized Meteorological Centre-Tokyo (RSMC-Tokyo), the Joint Typhoon Warning Center (JTWC) and the China Meteorological Administration-Shanghai Typhoon Institute (CMA-STI). Via case analysis of TC Kalmaegi (2019), it was found that the best-track data from the RSMC-Tokyo, JTWC and CMA-STI would have over 100 km biases at the early stage of TC life history. Taking all the 83 TC cases into account, the results show that the average center position biases and standard deviations for weak TCs under small vertical wind shear in the daytime are 5 km larger than those under large vertical wind shear at nighttime. When considering the 83 TC cases with clear LLC centers, the difference of these two biases is 10 km. The average biases are mostly above 20 km in the areas south of 18° N and north of 36° N over the WNP. Conversely, in the areas between 18° N and 36° N over the WNP, they are mostly below 20 km.
Online Detection of Surface Defects Based on Improved YOLOV3
Authors: Chen Xuechun , Lv Jun , Fang Yulun , Du Shichang
Published: January 2022

Aiming at the problems of low efficiency and poor accuracy in the product surface defect detection. In this paper, an online surface defects detection method based on YOLOV3 is proposed. Firstly, using lightweight network MobileNetV2 to replace the original backbone as the feature extractor to improve network speed. Then, we propose an extended feature pyramid network (EFPN) to extend the detection layer for multi-size object detection and design a novel feature fusing module (FFM) embedded in the extend layer to super-resolve features and capture more regional details. In addition, we add an IoU loss function to solve the mismatch between classification and bounding box regression. The proposed method is used to train and test on the hot rolled steel open dataset NEU-DET, which contains six typical defects of a steel surface, namely rolled-in scale, patches, crazing, pitted surface, inclusion and scratches. The experimental results show that our method achieves a satisfactory balance between performance and consumption and reaches 86.96% mAP with a speed of 80.96 FPS, which is more accurate and faster than many other algorithms and can realize real-time and high-precision inspection of product surface defects.
Beyond the Screen: Violence and Aggression towards Women within an Excepted Online Space
Authors: Bernstein Shireen , Warburton Wayne A. , Bussey Kay , Sweller Naomi
Published: January 2022

This theoretical review explores the possibility that the consumption of internet pornography (IP) represents a credible risk factor in the perpetration of aggression and violence against women. Sexual violence, abuse, and degradation of women is commonly depicted in mainstream heterosexual IP. Despite the violent tenor, the effect this material may have on beliefs, attitudes and behaviors is understudied, as are the reasons why violent and degrading IP is so widely viewed, enjoyed, and accepted. Both theory and empirical findings support the contention that depictions of violence in IP may contribute to real world aggression and violence against women, with two relevant spheres of inquiry proposed in this theoretical review. The first considers IP as a ‘zone of cultural exception’, in which the perpetration of violent and degrading acts against women are eroticized and celebrated, despite such behaviors being considered antisocial in wider society. It is suggested that this excepted status is enabled by the operation of the third person effect to negate the detrimental effects of IP. The second explores the objectification and dehumanization of women in IP and the use of moral disengagement by viewers to enable their disavowal of any harm in the depicted violence.
A Comprehensive Methodology for Assessing the Impact of Smart City Interventions: Evidence from Espoo Transformation Process
Authors: Ntafalias Aristotelis , Papadopoulos Giorgos , Papadopoulos Panagiotis , Huovila Aapo
Published: January 2022

In recent years, the world’s population living in cities has been rapidly increasing. Cities are transforming their infrastructure in a smarter and more efficient way so that sustainable development forms part of their long-term strategy. However, this transformation does not always result in expected benefits due to a variety of factors such as an absence of social acceptance, a lack of holistic design and the development of unilateral interventions. An analysis of the scientific literature related to the evaluation of the impact of smart city actions revealed a gap in the holistic methods for their assessment. To this end, an accurate evaluation of implemented smart solutions focusing on the energy domain is necessary in order to assess the expected and realized impact of each solution. This paper proposes a seven-step methodology for assessing the impact of smart city interventions and presents a use case for the city of Espoo. A number of major findings were the outcome of our research and development work, such as the need for a thorough analysis of the long-term vision of the city, a combined top-down and bottom-up approach and the ongoing cooperation between all stakeholders involved in urban planning and transformation, in which necessary Key Performance Indicators (KPIs) are defined.
The Impact of Sport Education on Chinese Physical Education Majors’ Volleyball Competence and Knowledge
Authors: Li Ping , Wang Wei , Liu Hairui , Zhang Chunhe , Hastie Peter A.
Published: January 2022

The Sport Education curriculum model, while well studied in primary and secondary school settings, has been much less evaluated in university physical education. In this study, 110 Chinese university students were randomly assigned to participate in 6 classes taught using either Sport Education or a more traditional teacher-directed style. Data were collected on the students’ skill execution, game performance, and knowledge. Over the course of a 16-week term, all participants showed significant improvements. However, the Sport Education students’ gain scores were significantly higher after controlling for pretest scores. It is suggested that the features of Sport Education that have been shown to motivate students in previous studies (persisting teams, developmentally appropriate competition, and taking roles other than player) serve to stimulate students toward achieving the multiple goals of Chinese university physical education.
Using Data from Earth Observation to Support Sustainable Development Indicators: An Analysis of the Literature and Challenges for the Future
Authors: Andries Ana , Morse Stephen , Murphy Richard J. , Lynch Jim , Woolliams Emma R.
Published: January 2022

The Sustainable Development Goals (SDG) framework aims to end poverty, improve health and education, reduce inequality, design sustainable cities, support economic growth, tackle climate change and leave no one behind. To monitor and report the progress on the 231 unique SDGs indicators in all signatory countries, data play a key role. Here, we reviewed the data challenges and costs associated with obtaining traditional data and satellite data (particularly for developing countries), emphasizing the benefits of using satellite data, alongside their portal and platforms in data access. We then assessed, under the maturity matrix framework (MMF 2.0), the current potential of satellite data applications on the SDG indicators that were classified into the sustainability pillars. Despite the SDG framework having more focus on socio-economic aspects of sustainability, there has been a rapidly growing literature in the last few years giving practical examples in using earth observation (EO) to monitor both environmental and socio-economic SDG indicators; there is a potential to populate 108 indicators by using EO data. EO also has a wider potential to support the SDGs beyond the existing indicators.
Sustainable Economic Development Education: The Use of Artificial Neural Networks for the Profile Estimation of Students from Developing Countries
Authors: Solano-Sánchez Miguel Ángel , Domínguez-Valerio Cándida María , Lendínez-Turón Ana , Aguilar-Rivero Minerva
Published: January 2022

Environmentally friendly behaviour and the equitable and sustainable use of natural resources can contribute to solving various environmental, economic, and social problems in different countries. The analysis of the perception of young students is important because schools are suitable for educating future generations and shaping their attitudes to also include a greater concern for the environment. This research aims to determine the degree of influence that a series of Likert-type questions of knowledge, attitudes, and behaviours about sustainable development has on a series of items of the student profile (gender, age, course, and household members) in a developing country. For this, an artificial neural network is used that allows us not only to quantify the degree of influence but also to obtain an estimation of the student’s profile according to the responses obtained on sustainable development. The network developed allows us to obtain, through a determined collection of answers to questions about sustainable development, the estimation of a specific profile of a student from a developing country. This can be useful to educational communities interested in optimising economic resources through sustainable development, allowing them to know which issues they should focus more (or less) on according to the profile of the student they are targeting.
Not Like My Parents! The Intention to Become a Successor of Latin American Students with Entrepreneur Parents
Authors: Romaní Gianni , Soria-Barreto Karla , Honores-Marín Guillermo , Ruiz Escorcia Rafael , Rueda Javier
Published: January 2022

The article presents an extension of the theory of planned behaviour (TPB) to identify, in a Latin American university, the students who are children of entrepreneurial parents and the determinants of their willingness to succeed them. The TPB is used as a basis to analyse the intention to be a successor, and three constructs are added: affective commitment, normative commitment and parental role model. The analysis is carried out using structural equations via the partial least squares (PLS) method, which allows for the study of multiple relationships between construct-type variables. The sample includes 16,185 Latin American university students from the Global University Entrepreneurial Spirit Students’ Survey 2018 database. The results show that, in Latin American students, the determining factors in the intention to be a successor are attitude, the affective and normative commitment and the parental role model. The latter has a negative and significant effect on the intention to be a successor in the family business. One of the practical implications of this study has to do with the development of an affective feeling of the offspring towards the family business. Generating this kind of attachment since childhood could lead to achieving a greater relevance of the parental role model and a stronger interest in the succession of the business.
Effects of a Three-Month COVID-19 Lockdown on Body Mass and Nutritional Status of Lebanese Students Who Study Physical Education
Authors: El Zoghbi Allen , Milanović Ivana , Janić Snežana Radisavljević , Mirkov Dragan , Kukić Filip
Published: January 2022

This study investigated the effects of a three-month COVID-19 lockdown on the body mass of Lebanese students who study physical education and whether these changes reflected in distribution changes in underweight, normal weight, and overweight/obese status. Furthermore, the study investigated whether lockdown affected physical activity behavior and if students who reduced the frequency of training sessions were more likely to increase their body mass. Body mass and body height were assessed in 174 Lebanese physical education students immediately before and at the end of COVID-19 lockdown. Their training routine was assessed using by questionnaire. Wilcoxon signed-rank order assessed the effects of lockdown on body mass, while Chi square test tested the differences in distribution of underweight, normal weight, and overweight/obese status before and after the lockdown. In general, there was a significant (p < 0.001) small increase in body mass. However, about 27% of participants had a moderate to major increase in body mass. This was reflected in a significant shift in nutritional status as the number of overweight/obese students increased by 5.2%. In addition, students who reduced their training frequency due to lockdown were three times more likely to increase body mass than those who remained active (i.e., 38 vs. 5 with moderate to major increase). Given that an increase in body mass increases all health risks, remaining physically active is of high importance for health prevention, especially considering all other positive effects of physical activity on cardio-respiratory and muscle function.
E-commerce Adoption and Technical Efficiency of Wheat Production in China
Authors: Chen Dongshi , Guo Hongdong , Zhang Qianqian , Jin Songqing
Published: January 2022

Improving technical efficiency (TE) is crucial for the sustainable growth of smallholder agriculture in developing countries. While there has been a large literature investigating the determinants of smallholders’ agricultural technical efficiency, little is known about the effect of e-commerce on agriculture and crop production efficiency despite the growing importance of rural e-commerce in developing countries. This study, therefore, bridges the research gap by examining the impact of e-commerce adoption on TE using household survey data of wheat farmers in China. We employ the combination of propensity score matching (PSM) and a selectivity-corrected stochastic production frontier model to address the possible selection biases stemming from both observable and unobservable factors. We found that e-commerce adoption would lead to a 2.75 per cent increase in the technical efficiency of wheat production. Our study also complements the existing research of rural e-commerce, which mainly focuses on the benefits of e-commerce from the perspective of market opportunity and farmers’ welfare.
Conceptualising Disruptions in British Beef and Sheep Supply Chains during the COVID-19 Crisis
Authors: Payne-Gifford Sophie , Whatford Louise , Tak Mehroosh , Van Winden Steven , Barling David
Published: January 2022

This paper explores the impacts of the COVID-19 crisis as a disruptor to Britain’s beef and sheep supply chains. The assessment of COVID-19 impacts is based on the triangulation of farming and industry news reports, submissions to a government COVID-19 enquiry and interviews with industry experts. We find that livestock farming and farm services were least affected compared to processing, retailing, foodservice, or consumers. Primary and secondary processors continued to operate during the first COVID-19 lockdown but had to quickly become ‘COVID secure’. The most dramatic effect was the overnight closure of hospitality and catering and the redirection of supplies to the retail sector. This picture of a resilient British beef and sheep industry may also be conceptualised as relatively locked in and resistant to change. Red meat production is tied to the land it farms on and operates on 12–36-month production cycles, making it difficult to change trajectory if disruptions do not directly affect farming. Emerging changes in agricultural payments, trade post-Brexit, and societal and environmental pressures may well be the disruptors that have far-reaching impacts on the beef and sheep supply chains.
Improving Effects of Afforestation with Different Forest Types on Soil Nutrients and Bacterial Community in Barren Hills of North China
Authors: Qiu Zhenlu , Shi Cong , Zhao Mingyuan , Wang Kefan , Zhang Mei , Wang Tongtong , Shi Fuchen
Published: January 2022

Afforestation can improve soil nutrient content and microbial community structure, increase soil carbon sequestration, and reduce greenhouse gas emissions. However, at present, there is a lack of research on the low hills and mountainous areas in North China. In order to scientifically evaluate the effect of afforestation recovery with different forest types on the improvement of the soil ecological system, the Fanggan ecological restoration in North China was taken as the research sample, and the coniferous forests, mixed coniferous and broad-leaved forest quadrats and broad-leaved forests, as well as the contrast of barren hills bushes were set to achieve the research goals. Research results of different forest types on soil nutrient and bacterial community in the Fanggan ecological restoration area have shown that afforestation with broad-leaved forests most obviously improved the nutrition properties and bacterial community of soil. (1) Broad-leaved forest afforestation obviously improved water retention and ammonia nitrogen content but reduced the content of available phosphorus and nitrate nitrogen of surface soil. It also increased available phosphorus, ammonia nitrogen, and nitrate nitrogen content of lower soil. (2) Broad-leaved forest afforestation significantly increased α-diversity of the bacterial community in surface soil, but only enhanced the Chao1 and ACE indices of lower soil. In addition, afforestation has also significantly changed the structure of soil bacterial community and β-diversity index. (3) Proteobacteria, Acidobacteria, Actinobacteria, and Verrucomicrobia accounted for the highest proportion of soil bacterial community. Proteobacteria and Verrucomicrobia occupied higher proportion in broad-leaved forests than in other forest types, while the proportion of Acidobacteria and Actinobacteria was the opposite. (4) Afforestation decreased cooperation and increased competition among bacteria of surface soil as well as increased coexistence and rejection among subsoil bacteria. (5) pH, ammonia nitrogen, organic carbon, and available phosphorus have exhibited a significant impact on the structure of bacterial community in the surface soil, while the bacterial community structure of the lower soil was mainly affected by pH and available phosphorus. Results have fully demonstrated the positive effects of broad-leaved forest on the restoration of soil nutrients and microbial community structure. Meanwhile, the important combinations of soil physical and chemical factors affecting soil bacterial community structure were also explored. The results can provide scientific basis for revealing the mechanism of soil organic matter, nutrient and ecological function restoration by artificial afforestation, and also offer theoretical support and practical reference for the restoration of artificial afforestation in the hilly and mountainous areas of North China.
Managerial and Economical Aspects of the Just-In-Time System “Lean Management in the Time of Pandemic”
Authors: Milewski Dariusz
Published: January 2022

The article concerns the problem of efficiency of the Just-In-Time (JIT) system, taking into account the benefits for the company and external costs. The aim of the article was to present the conditions conducive to the effective implementation of the JIT system. The article refers to recent discussions in various publications on the effectiveness of the lean management (LM) concept and the JIT system in the context of the pandemic. It also presents the results of simulations carried out with the use of a model developed by the author concerning the transport distances at which JIT deliveries are profitable and the impact of JIT deliveries on the costs of logistics processes and external costs. The results of the conducted simulations showed in which specific cases JIT solutions were beneficial. The results showed that the scale of benefits was strongly dependent on the value of products and the scale of production. Simulations were carried out for four product groups: food products, footwear, electronics, and mobile phones. In the case of cheap products and small scale, the implementation of JIT resulted in a significant increase in the costs of logistics processes if delivery distances were not shortened. Savings of over 70% appeared in the case of expensive mobile phones, even over long distances. In the case of large-scale production and sales, large savings occurred in almost all cases (up to over 90%). Furthermore, simulations of the impact of JIT on the profitability of enterprises were also carried out using the data contained in the financial reports of listed companies. These simulations also showed a significant impact of JITs on the efficiency of companies, albeit assuming that the effect would be primarily an increase in revenues. If the current situation caused by the pandemic (disruptions in global supply chains, increased transport costs) contributes to the return of production to Europe, this may result in the creation of favorable conditions for the implementation of JIT. In this case, the result will be large savings in logistics costs, including external costs of these processes (almost 80%). Here, however, the factor contributing to the reduction in external costs would also be the scale of production and sales. The simulations carried out by the author are a novelty and constitute his contribution to scientific research in this area, as no such calculations have been carried out to date.
Life Cycle Assessment (LCA) of the Use of Metallurgical Process Gas for Heat and Electricity, Combined with Salt Removal from Discarded Water
Authors: Bogacka Magdalena , Iluk Tomasz , Pikoń Krzysztof , Ściążko Marek , Stec Marcin , Czaplicki Andrzej , Wajda Agata
Published: January 2022

The subject of the article is the assessment of the environmental impact of the technology concerning the use of low-quality post-process gas for the production of electricity and heat, along with the treatment of post-process wastewater. This assessment was carried out based on the results of the full life cycle assessment (LCA) analysis. The presented technology is based on the energetic use of low-quality process gases in a reciprocating engine for the production of electricity and heat in cogeneration with the use of heat in the wastewater treatment system. The article presents the adopted assumptions and the results of the LCA analysis for the RECLEG technology developed specifically for a zinc smelter. The aim of the analysis was to check whether the developed technology has a positive impact on the environment. The LCA analysis was performed using the ReCiPe methodology, which is one of the most frequently used methodologies in this field due to the possibility of observing the environmental impact in a full range of different environmental aspects. At the same time, the analysis also allows the results to be presented in three general impact categories: human health, ecosystem and natural resources, which are easier to interpret. By converting the waste post-process gas into electricity and heat, it is seen that this has a positive impact on the environment. Especially due to the waste nature of the source, which is the post-process gas. Each reduction of gas is potentially beneficial for the environment and, in addition, a replacement effect can be observed, because the gas was previously burned in a flare, where it additionally emitted exhaust gases, sent directly to the atmosphere. Moreover, the RECLEG technology combines post-process wastewater treatment, which has a positive effect on water management, and makes the process even more environmentally friendly.
The Impact of Financial Development and FDI on Renewable Energy in the UAE: A Path towards Sustainable Development
Authors: Samour Ahmed , Baskaya M. Mine , Tursoy Turgut
Published: January 2022

Several empirical studies have explored the influence of financial development on energy consumption; however, the impact of financial development, economic growth, and FDI on renewable energy consumption (REC) has not been studied in the case of the UAE. For this purpose, the long and short-run interactions among economic growth, FDI, financial development, and renewable energy consumption are explored by applying the new technique of bootstrap autoregressive distributed lag, along with Granger causality analysis, in the context of the UAE for the period from 1989–2019. Using estimation techniques, the study reveals the main findings and implications for policymakers in the UAE. The present research provides significant empirical evidence that financial development, FDI, and economic growth can significantly increase renewable energy consumption in the UAE. Therefore, it is essential to promote financial development in the UAE in order to avert the financial risks that undermine the stability of the financial markets and that negatively affect the REC. Furthermore, policymakers in the UAE should promote the concept of green finance and should provide more funds for investments in green energy for sustainable energy development in the UAE.