bluuebunny/crossref_metadata_2025 huggingface dataset:
Dominant Modes of Tibetan Plateau Summer Surface Sensible Heating and Associated Atmospheric Circulation Anomalies
Authors: Fan Weiwei , Hu Zeyong , Ma Weiqiang , Ma Yaoming , Han Cunbo , Han Xiang , Yang Yaoxian , Yu Haipeng , Fu Chunwei , Wu Di
Published: February 2022

Based on empirical orthogonal function (EOF) analysis, the dominant modes of variations in summer surface sensible heating (SH) over the Tibetan Plateau (TP), as well as the associated atmospheric circulation anomalies, were investigated in this study. The results show that the first dominant mode of summer SH presents a feature of decadal reduction over the whole TP on an interdecadal time scale, and the second dominant mode is characterized by a zonally asymmetric pattern with positive (negative) SH anomalies in the western (eastern) TP on an interannual time scale. The variations of summer SH are dominated by anomalies in downwelling surface shortwave radiation (DSWR), which are associated with atmospheric circulation changes. The first dominant mode of variation in SH is connected to the interdecadal variation of the Silk Road Pattern (SRP). Further analysis reveals that the interdecadal phase shift of the SRP induces anticyclone circulation to the northeast of the TP, leading to enhanced water vapor supply and convergence over the TP. This can lead to an increase in the total cloud cover, and a reduction in DSWR, contributing to the decadal reduction in SH over the TP. The second dominant mode of variation in SH is related to a stationary teleconnection pattern over the Eurasian continent named the North Atlantic-East and North Asia pattern (NAENA). Corresponding to the positive phase of the NAENA, there is a cyclone anomaly to the west TP, leading to anomalous water vapor convergence (divergence) over the eastern (western) TP. This can result in enhanced (decreased) cloud cover, reduced (increased) DSWR, and therefore, an anomalous decrease (enhancement) in SH over the east (west) of the TP. Furthermore, the southwesterly wind anomaly, which is accompanied by the anomalous cyclone to the west TP, leads to positive SH in the western TP.
Built-Up Area Change Detection Using Multi-Task Network with Object-Level Refinement
Authors: Gao Song , Li Wangbin , Sun Kaimin , Wei Jinjiang , Chen Yepei , Wang Xuan
Published: February 2022

The detection and monitoring of changes in urban buildings, as a major place for human activities, have been considered profoundly in the field of remote sensing. In recent years, comparing with other traditional methods, the deep learning-based methods have become the mainstream methods for urban building change detection due to their strong learning ability and robustness. Unfortunately, often, it is difficult and costly to obtain sufficient samples for the change detection method development. As a result, the application of the deep learning-based building change detection methods is limited in practice. In our work, we proposed a novel multi-task network based on the idea of transfer learning, which is less dependent on change detection samples by appropriately selecting high-dimensional features for sharing and a unique decoding module. Different from other multi-task change detection networks, with the help of a high-accuracy building mask, our network can fully utilize the prior information from building detection branches and further improve the change detection result through the proposed object-level refinement algorithm. To evaluate the proposed method, experiments on the publicly available WHU Building Change Dataset were conducted. The experimental results show that the proposed method achieves F1 values of 0.8939, 0.9037, and 0.9212, respectively, when 10%, 25%, and 50% of change detection training samples are used for network training under the same conditions, thus, outperforming other methods.
Aventinus Minor Project: Remote Sensing for Archaeological Research in Rome (Italy)
Authors: Wueste Elizabeth , Facchin Giulia , Barone Pier Matteo
Published: February 2022

This paper presents the results of a preliminary survey in a central urban area of Rome, Italy. The results were obtained from both desktop and remote sensing surveys. The Aventinus Minor Project (AMP) is a community archaeological excavation project focusing on an understudied area in Rome with limited modern archaeological excavation: the Aventinus Minor or Little Aventine. The remote sensing (RS) anomalies revealed by the survey illustrate that this area is potentially rich in buried structures potentially correlated with ancient visible remains (i.e., the Servian Walls and Santa Balbina church). The application of RS approaches (such as NDVI, VARI, and GPR) and the creation of a GIS platform lays the foundations for a correct and georeferenced reporting of all collected data, providing a nuanced understanding of the urban archaeology in the dense topography of Rome.
Reinforcement Learning for Compressed-Sensing Based Frequency Agile Radar in the Presence of Active Interference
Authors: Wang Shanshan , Liu Zheng , Xie Rong , Ran Lei
Published: February 2022

Compressed sensing (CS)-based frequency agile radar (FAR) is attractive due to its superior data rate and target measurement performance. However, traditional frequency strategies for CS-based FAR are not cognitive enough to adapt well to the increasingly severe active interference environment. In this paper, we propose a cognitive frequency design method for CS-based FAR using reinforcement learning (RL). Specifically, we formulate the frequency design of CS-based FAR as a model-free partially observable Markov decision process (POMDP) to cope with the non-cooperation of the active interference environment. Then, a recognizer-based belief state computing method is proposed to relieve the storage and computation burdens in solving the model-free POMDP. This method is independent of the environmental knowledge and robust to the sensing scenario. Finally, the double deep Q network-based method using the exploration strategy integrating the CS-based recovery metric into the ϵ-greedy strategy (DDQN-CSR-ϵ-greedy) is proposed to solve the model-free POMDP. This can achieve better target measurement performance while avoiding active interference compared to the existing techniques. A number of examples are presented to demonstrate the effectiveness and advantage of the proposed design.
An Analysis of Arctic Sea Ice Leads Retrieved from AMSR-E/AMSR2
Authors: Li Ming , Liu Jiping , Qu Meng , Zhang Zhanhai , Liang Xi
Published: February 2022

In this study, we retrieve an Arctic sea ice lead fraction from AMSR2 passive microwave data in winter from 2012 to 2020 based on an algorithm developed for AMSR-E data. The derived AMSR2 sea ice lead fraction is validated against MODIS images. The results show that the derived AMSR2 sea ice lead detects approximately 50% of the ice leads shown in the MODIS images, which is close to the amount of sea ice lead detected from the AMSR-E data from 2002 to 2011. Utilizing the retrievals from both the AMSR-E and AMSR2, our analysis shows no significant trend, but moderate interannual variation exists for the ice lead fraction in the Arctic basin scale over the past two decades. The maximum width and total length of sea ice lead show a significant decreasing trend for the whole Arctic, but the mean width does not exhibit a significant change over the studied period. In the Beaufort Sea the lead fraction varies from 2.06% to 12.35%, with a mean value of 5.72%. In the Greenland Sea the mean lead fraction over the studied period is 5.77%, and there is a significant increase in the lead fraction, with a rate of 0.13% per year. The maximum width in the Greenland Sea is substantially higher than that of other regions, and the mean width increases significantly.
Spatio-Temporal Changes in Ecosystem Service Value and Its Coordinated Development with Economy: A Case Study in Hainan Province, China
Authors: Fu Jie , Zhang Qing , Wang Ping , Zhang Li , Tian Yanqin , Li Xingrong
Published: February 2022

Ecosystem service value is crucial to people’s intuitive understanding of ecological protection and the decision making with regard to ecological protection and economic green development. This study improved the benefit transfer method to evaluate ESV in Hainan Province, proposed the coupling analysis method of economic and environmental coordination, and explored the relationship between ESV and economic development based on the medium-resolution remote sensing land use data and socio-economic data from 2000 to 2020. The results show that Hainan Province’s ESV decreased by 33.305 billion CNY from 2000 to 2020. The highest ESV per unit area was found in the water system and forest ecosystem, mainly distributed in the central mountainous area. The overall condition of EEC decreased from a basic coordination state to a moderate disorder state. Areas with high economic development had better EEC, such as Haikou and Sanya. Meanwhile, we analyzed the driving force of ESV and EEC by Geodetector. The results show that land use intensity was the most important driving factor affecting ESV, with a contribution rate of 0.712. Total real estate investment was the most important driving factor affecting EEC, with a contribution rate of 0.679. These results provide important guidance for the coordinated development of regional economy and ecosystem protection.
Detection of Invasive Black Locust (Robinia pseudoacacia) in Small Woody Features Using Spatiotemporal Compositing of Sentinel-2 Data
Authors: Rusňák Tomáš , Halabuk Andrej , Halada Ľuboš , Hilbert Hubert , Gerhátová Katarína
Published: February 2022

Recognition of invasive species and their distribution is key for managing and protecting native species within both natural and man-made ecosystems. Small woody features (SWF) represent fragmented patches or narrow linear tree features that are of high importance in intensively utilized agricultural landscapes. Simultaneously, they frequently serve as expansion pathways for invasive species such as black locust. In this study, Sentinel-2 products, combined with spatiotemporal compositing approaches, are used to address the challenge of broad area black locust mapping at a high granularity. This is accomplished by conducting a comprehensive analysis of the classification performance of various compositing approaches and multitemporal classification settings throughout four vegetation seasons. The annual, seasonal (bi-monthly), and monthly median values of cloud-masked Sentinel-2 reflectance products are aggregated and stacked into varied time-series datasets per given year. The random forest algorithm is trained and output classification maps validated based on field-based reference datasets across Danubian lowlands (Slovakia). The main results of the study proved the usefulness of spatiotemporal compositing of Sentinel-2 products for mapping black locust in small woody features across wide area. In particular, temporally aggregated monthly composites stacked to seasonal time series datasets yielded consistently high overall accuracies ranging from 89.10% to 91.47% with balanced producer’s and user’s accuracies for each year’s annual series. We presume that a similar approach could be used for a broader scale species distribution mapping, assuming they are spectrally or phenologically distinctive, as is often the case for many invasive species.
A Scale-Aware Pyramid Network for Multi-Scale Object Detection in SAR Images
Authors: Tang Linbo , Tang Wei , Qu Xin , Han Yuqi , Wang Wenzheng , Zhao Baojun
Published: February 2022

Multi-scale object detection within Synthetic Aperture Radar (SAR) images has become a research hotspot in SAR image interpretation. Over the past few years, CNN-based detectors have advanced sharply in SAR object detection. However, the state-of-the-art detection methods are continuously limited in Feature Pyramid Network (FPN) designing and detection anchor setting aspects due to feature misalignment and targets’ appearance variation (i.e., scale change, aspect ratio change). To address the mentioned limitations, a scale-aware feature pyramid network (SARFNet) is proposed in this study, which comprises a scale-adaptive feature extraction module and a learnable anchor assignment strategy. To be specific, an enhanced feature pyramid sub-network is developed by introducing a feature alignment module to estimate the pixel offset and contextually align the high-level features. Moreover, a scale-equalizing pyramid convolution is built through 3-D convolution within the feature pyramid to improve inter-scale correlation at different feature levels. Furthermore, a self-learning anchor assignment is set to update hand-crafted anchor assignments to learnable anchor/feature configuration. By using the dynamic anchors, the detector of this study is capable of flexibly matching the target with different appearance changes. According to extensive experiments on public SAR image data sets (SSDD and HRSID), our algorithm is demonstrated to outperform existing boat detectors.
The Road Safety Education Program for Adolescents Using Social Media, Proving Increasing Knowledge, Beliefs, Attitudes, Intentions and Behavior
Authors: Zainafree Intan , Hadisaputro Suharyo , Suwandono Agus , Widjanarko Bagoes
Published: February 2022

Deaths due to road traffic accidents (RTA) accounted for 2.46% of deaths out of the total deaths in Indonesia. Road safety education (RSE), as an effort to prevent RTA, focuses on increasing knowledge; however, variations of techniques, methods, and media are less used. This study aims to analyze the application of RSE innovations that have been compiled based on interests and needs of adolescents, which are expected to be able to increase knowledge, beliefs, attitudes, intentions, and safe driving behavior. This research used a quasi-experimental approach with a non-randomized pre-test–post-test control group design approach. The Zainafree Program intervention model was conducted for 6 weeks on 362 students who were selected using purposive sampling technique at two schools with the same characteristics. The bivariate analysis was conducted to observe the effect of the model on changes in knowledge, beliefs, attitudes, intentions, and behavior. We analyzed multivariately using GLM-RMA to determine the effectiveness of the model from various confounding factors. The Mann–Whitney test in the intervention and control group demonstrated a significant difference in the average post-test score of two on all dependent variables (p = 0.000). The results of the GLM-RMA test demonstrated the effect of the Zainafree Program on knowledge (p = 0.000; ETA Square = 35.1), beliefs (p = 0.000; ETA Square = 32.0), attitudes (p = 0.000; ETA Square = 50.9), intentions (p = 0.000, ETA Square = 20.7), and behavior (p = 0.000; ETA Square = 28.2), after adjusting for involvement between confounding variables (p = 0.000; ETA Square = 16.2), which demonstrated that the intervention was able to explain 16.2 changes that occur in the scores of five aspects together. The RSE program was proven to be successful in increasing students’ knowledge, beliefs, attitudes, intentions, and behavior compared to those who did not receive the program.
Evaluating the Performance of Lightweight Ciphers in Constrained Environments—The Case of Saturnin
Authors: Podimatas Panagiotis , Limniotis Konstantinos
Published: February 2022

The use of lightweight cryptographic algorithms is essential for addressing security in highly constrained environments such as the Internet of Things. In this paper, the performance of lightweight block ciphers in such highly constrained environments is studied. More precisely, focusing—as a case study—on an important family of lightweight ciphers called “Saturnin”, which has been evaluated as a candidate for standardization in the relative ongoing NIST’s competition, we analyze its efficiency in case that it is implemented in a specific resource-constrained environment. To evaluate the results, a comparative study with the Advanced Encryption Standard (AES) is performed, through an appropriate experimental environment. Our results illustrate that significant gain in performance can be achieved, since Saturnin—whose design is inspired by the design of AES—can be almost two times faster than AES in such restricted environments.
Employee Pro-Environmental Behavior: The Impact of Environmental Transformational Leadership and GHRM
Authors: Omarova Laura , Jo Sung-Jun
Published: February 2022

We investigated the impact of environmental transformational leadership (ETL) on pro-environmental behavior (PEB) of employees in Kazakhstan. The study also examined the potential mediating effect of environmental awareness and green human resource management (GHRM) as a moderating effect, using the theory of planned behavior. An online cross-sectional survey was conducted with 268 Kazakh employees from private and public organizations. Structural equation modeling was used to test the theory-driven model. The results show that environmental leadership predicted employees’ PEB, environmental awareness mediated the relationship, and GHRM partially moderated the relationship. The results of bootstrapping tests reveal that environmental awareness played successive mediating roles in the link between ETL and PEBs, but the simple slope test did not support the moderating effect of GHRM. Environmental awareness and GHRM were identified as fundamental mechanisms that accounted for the connection between ETL and PEBs.
Critical Infrastructures Overview: Past, Present and Future
Authors: De Felice Fabio , Baffo Ilaria , Petrillo Antonella
Published: February 2022

Industrialized societies depend on the proper functioning of a whole range of technological infrastructures, such as electricity, road and railway networks and telecommunications which, due to their importance, are generically referred to as critical infrastructures (CIs). Technical failures, natural disasters and malicious events, if not terrorist, could have devastating effects on these infrastructures. The events of the last few years have accelerated efforts to identify and designate CIs at national and European levels and have reinforced concerns about increasing their protection in sensitive sectors for the safety of the individual and the community. The aim of this research is to provide the basic elements to understand the issue along with the reasons for its importance both at national, European and international level. In particular, after analyzing the origin of the problem, a systematic literature review is carried out to study the current research around future perspectives relating to the management of Cis, with particular focus on three research questions: RQ1 “What types of risk assessment methods are used to manage CIs?”, RQ2 “What are the environmental risk mitigation strategies for CIs?” and RQ3 “What is the role of the human factor in the prevention of risks for CIs?”. The results aim to be guidelines for decision makers and researchers interested in this topic.
Quantifying the Lost Safety Benefits of ADAS Technologies Due to Inadequate Supporting Road Infrastructure
Authors: Peiris Sujanie , Newstead Stuart , Berecki-Gisolf Janneke , Chen Bernard , Fildes Brian
Published: February 2022

Advanced driver assistance systems (ADAS) provide warnings to drivers and, if applicable, intervene to mitigate a collision if one is imminent. Autonomous emergency brakes (AEB) and lane keep assistance (LKA) systems are mandated in several new vehicles, given their predicted injury and fatality reduction benefits. These predicted benefits are based on the assumption that roads are always entirely supportive of ADAS technologies. Little research, however, has been conducted regarding the preparedness of the road network to support these technologies in Australia, given its vastly expansive terrain and varying road quality. The objective of this study was to estimate what proportion of crashes that are sensitive to AEB and LKA, would not be mitigated due to unsupportive road infrastructure, and therefore, the lost benefits of the technologies due to inadequate road infrastructure. To do this, previously identified technology effectiveness estimates and a published methodology for identifying ADAS-supportive infrastructure availability was applied to an estimated AEB and LKA-sensitive crash subset (using crash data from Victoria, South Australia and Queensland, 2013–2018 inclusive). Findings demonstrate that while the road networks across the three states appeared largely supportive of AEB technology, the lack of delineation across arterial and sub-arterial (or equivalent) roads is likely to have serious implications on road safety, given 13–23% of all fatal and serious injury (FSI) crashes that occurred on these road classes were LKA-sensitive. Based on historical crash data, over 37 fatalities and 357 serious injuries may not be avoided annually across the three Australian states based on the lack of satisfactory road delineation on arterial and sub-arterial (or equivalent) roads alone. Further, almost 24% of fatalities in Victoria, 24% of fatalities in Queensland and 21% of fatalities in South Australia (that are AEB- or LKA-sensitive) are unlikely to be prevented, given existing road infrastructure. These figures are conservative estimates of the lost benefits of the technologies as they only consider fatal and serious injury crashes and do not include minor injury or property damage crashes, the benefits of pedestrian-sensitive AEB crashes in high-speed zones or AEB fitted to heavy vehicles. It is timely for road investments to be considered, prioritised and allocated, given the anticipated penetration of the new technologies into the fleet, to ensure that the road infrastructure is capable of supporting the upcoming fleet safety improvements.
Case Study Research to Foster the Optimization of Supply Chain Management through the PSS Approach
Authors: Fargnoli Mario , Haber Nicolas , Tronci Massimo
Published: February 2022

The optimization of a product’s whole life cycle has become a mandatory task for manufacturers seeking to deal with circular economy requirements while gaining competitiveness in the market. In order to achieve such a sustainability goal, alignment of production, distribution, and field service activities is needed. In the literature, numerous studies indicate the product–service system (PSS) approach as one of the most promising business models to combine the needs of manufacturers and customers in an efficient and effective manner. However, PSS solutions aimed at practically optimizing supply chain management have scarcely been addressed. In order to reduce this gap, the current study proposes a procedure based on the PSS Functional Matrix, the Screening Life Cycle Modelling (SLCM) method, and stock management theory to optimize aftermarket services based on market demand. A case study in the medical equipment sector, where market demand can fluctuate during the contract period, is presented. The analytical results show beneficial effects in terms of both costs and environmental impact, suggesting the need for further research to augment knowledge on PSS and supply chain management. In particular, the PSS allowed the company to customize the manufacturer’s business model, adapting the supply of aftermarket services to varying customer needs.
Impacts of Real-Time Traffic State on Urban Expressway Crashes by Collision and Vehicle Type
Authors: Wang Chen , Zhong Ming , Zhang Hui , Li Siyao
Published: February 2022

With the rapid development of urban expressway systems in China in recent years, traffic safety problems have attracted more attention. Variation of traffic flow is considered to have significant impact on the safety performance of expressways. Therefore, the motivation of this study is to explore the mechanism of how the variation of traffic flow measurements such as average speed, speed variation and traffic volume impact the crash risk. Firstly, the crashes were classified according to crash type and vehicles involved: and they are labeled with rear-end collisions or side-impact collisions, they are labeled with heavy-vehicle related collisions or light-vehicle related collisions as well. Then, the corresponding crash data were aggregated based on the similarity of traffic flow conditions and types of crashes. Finally, a random effect negative binomial model was introduced to consider the heterogeneity of the crash risk due to the variance within the traffic flow and crash types. The results show that the significant influencing factors of each type of crashes are not consistent. Specifically, the percentage of heavy vehicles within traffic flow is found to have a negative impact on rear-end collisions and light-vehicle-related collisions, but it has no obvious correlation with side-impact collisions and heavy-vehicle-related collisions. Average speed, speed variation and traffic volume have an interactive effect on the crash rate. In conclusion, if the traffic flow is with higher speed variation within lanes and is with lower average speed, the risk of all types of crashes tends to be higher. If the speed variation within lanes decreases and the average speed increases, the crash risk will also increase. In addition, if the traffic flow is under the conditions of higher speed variation between lanes and lower traffic volume, the risk of rear-end collisions, side-impact collisions and heavy-vehicles related collisions tend to be higher. Meanwhile, if the speed variation between lanes decreases and the traffic volume increases, the crash risk is found to increase as well.
Composite Soil Made of Rubber Fibers from Waste Tires, Blended Sugar Cane Molasses, and Kaolin Clay
Authors: Jiménez Juan E. , Fontes Vieira Carlos Mauricio , Colorado Henry A.
Published: February 2022

The use of different chemical and biological admixtures to improve the ground conditions has been a common practice in geotechnical engineering for decades. The use of waste material in these mixtures has received increasing attention in the recent years. This investigation evaluates the effects of using recycled tire polymer fibers (RTPF) and sugar molasses mixed with kaolin clay on the engineering properties of the soil. RTPF were obtained from a tire recycling company, while the molasses were extracted from a sugar cane manufacturer, both located in Colombia. RTPF is a waste and therefore its utilization is the first positive impact of this research, a green solution for this byproduct. Treated kaolin clay is widely used in many industrial processes, such as concrete, paper, paint, and traditional ceramics. The characterization was conducted with scanning electron microscopy, compression strength, particle-size distribution, x-ray diffraction, compressive and density tests. The results showed that the unconfined compressive strength improved from about 1.42 MPa for unstabilized samples, to 2.04 MPa for samples with 0.1 wt% of fibers, and 2.0 wt% molasses with respect to the dry weight of the soil. Furthermore, it was observed that soil microorganisms developed in some of the samples due to the organic nature of the molasses.
Design, Experimentation and Statistical Validation of a Methodology to Solve Complex Engineering Problems in Higher Education
Authors: Rosales-Torres Conrado , Gijón-Rivera Carlos , Garay-Rondero Claudia Lizette , Castillo-Paz Álvaro , Domínguez-Ramírez Gerardo
Published: February 2022

This article proposes a methodology that addresses the problem that many university professors often have with their students when facing complex engineering problems, causing frustration and desertion (abandonment of the problem to be solved). Although there are antecedents of works that emphasize the relevance of the realistic context in engineering problems and the importance of being structured in solving problems, we did not find measured effectiveness from the study of a group of students. This methodology focuses on engineering problems, in such a way that the decomposition of the problems in four steps responds to the solution process of the profiles of the analyzed subjects. The process followed in the preparation, implementation, validation, and reliability of this methodology is detailed. The experiment was designed to test both the effectiveness and reliability of the methodology. Four control groups for three different courses and periods were analyzed before and after the training of the four-step methodology. The observed factor was the variable score (0–100 points). The statistical analysis comprises descriptive statistics; Normality test for each population group; Paired t-Test/Wilcoxon test, and General linear model ANOVA (2 factors). The statistical analysis and tests show how the groups involved in the experiment obtained a significant benefit when the methodology for academic performance evaluations was applied.
Land Use, Landform, and Soil Management as Determinants of Soil Physicochemical Properties and Microbial Abundance of Lower Brahmaputra Valley, India
Authors: Hota Surabhi , Mishra Vidyanand , Mourya Krishna Kumar , Giri Krishna , Kumar Dinesh , Jha Prakash Kumar , Saikia Uday Shankar , Prasad P. V. Vara , Ray Sanjay Kumar
Published: February 2022

Due to the shifting course of the Brahmaputra River, the fluvial landforms of the Brahmaputra Valley of Assam, India, are prone to changes in landform and land use. For sustainable soil management under such conditions, it is crucial to have information about soil physicochemical and biological properties for different land uses. Therefore, the present study was conducted to investigate the soil physicochemical properties and soil microbial population across five major land uses under different landforms, such as paddy fields, banana systems, and arecanut cultivations in the alluvial plains; and rubber plantations and sal forests in the uplands, with varying slope gradients and soil depths (0–25 cm and 25–50 cm) in the lower Brahmaputra Valley. The results of the analysis of variance revealed that the effects of different landforms and land uses were found to be statistically significant on very labile soil organic carbon (VLSOC), available K, B, Fe, Mn, Zn, and Cu, and soil moisture content across two different soil depths. Paddy cultivated systems recorded the highest (1.23%) soil organic carbon (SOC), but these levels were statistically at par with other land use scenarios except for banana systems; whereas, forests and rubber plantations showed the highest VLSOC (0.38% and 0.34%, respectively,) and were significantly different from other land use scenarios. All soil microbial populations (bacteria, fungi, and actinomycetes) studied varied significantly in different land uses across varying soil depths. Perennial land uses under arecanut, rubber, and forest cultivations showed significantly higher microbial populations than paddy and banana systems. The principal component analysis (PCA) identified SOC, VLSOC, Cu, K, B, P, and the bacteria count as the major soil quality parameters of the study area. The results showed that landforms, land use, and management practices collectively affect soil properties. Therefore, soil management choices should take into consideration the landforms and land use for maintaining soil health and its sustainability.
Intermittency in Wind Energy and Emissions from the Electricity Sector: Evidence from 13 Years of Data
Authors: Uz Dilek , Chim Callista
Published: February 2022

Renewable subsidies and mandates currently play a central role in the environmental and energy policy in the United States, one of the world’s top greenhouse gas emitters. Therefore, accurately estimating the environmental benefits from wind energy is key to evaluating the existing policies and setting future directions and has been studied within a growing body of the literature. However, most of the existing studies do not take the intermittency into account, and the small number of studies that do only study a relatively short time period limiting the extent to which they can be informative within different ranges of wind generation capacity. In this paper, we present the first estimates of the environmental benefits of wind energy generation using a dataset that spans well over a decade. Specifically, we use 13 years of hourly and sub-hourly data to estimate the causal effect of wind generation and its intermittency on CO2, NOx, and SO2 emissions from the electricity sector in Texas. Additionally, we compared the full sample results to those from sub-samples where the dataset is divided into subgroups based on wind output level. We found that while wind generation clearly has a statistically significant negative marginal effect on all pollutants we studied, the marginal effect of intermittency varies across different wind output levels in a highly irregular way. Our findings suggest that conducting pooled analyses has the potential to mask the irregularity in the variation of the effect of intermittency in wind generation across different wind output levels.
Sustainable Production of Stiff and Crystalline Bacterial Cellulose from Orange Peel Extract
Authors: Padmanabhan Sanosh Kunjalukkal , Lionetto Francesca , Nisi Rossella , Stoppa Mariangela , Licciulli Antonio
Published: February 2022

In this work, a potentially economic and environmentally friendly method for the synthesis of bacterial cellulose (BC) by Gluconacetobacter xylinus from a biomass containing orange peel extract was evaluated. Orange peel extract was used as a culture medium without any hydrolysis treatment, thus speeding up the synthesis procedure. The efficacy of orange peel as a carbon source was compared with that of sucrose. The orange peel extract formed thicker cellulose gels than those formed using sucrose. X-ray diffraction (XRD) revealed both a high crystallinity index and crystallite size of BC nanofibers in samples obtained from orange peel (BC_Orange). Field emission scanning electron microscopy (FE-SEM) revealed a highly densely packed nanofibrous structure (50 nm in diameter). BC_Orange presented a two-fold increase in water holding capacity (WHC), and dynamic mechanical analysis (DMA) showed a 44% increase in storage modulus compared to sucrose derived BC. These results showed that the naturally available carbon sources derived from orange peel extract can be effectively used for BC production. The orange-based culture medium can be considered a profitable alternative to the generation of high-value products in a virtuous circular economy model.
Understanding the Implications of Predicted Function for Assessment of Rapid Bioremediation in a Farmland-Oilfield Mixed Area
Authors: Wang Haoyu , Wu Shanghua , Zhang Yuxiu , Bohu Tsing , Bai Zhihui , Zhuang Xuliang
Published: February 2022

Farmland-oilfield mixed areas are fragile ecosystems that require dynamic remediation to counteract the undesirable impact of energy development. Practicable assessment methods are pivotal to a fast and accurate evaluation of the in situ bioremediation process. Petroleum pollutants impose component-dependent effects on autochthonous microbiota before and after remediation. Here, the predicted functional response of soil microbiomes to petroleum pollutants was analyzed in a historically polluted farmland-oilfield mixed area from the perspective of developing a set of feasible biomarkers for immediate post-bioremediation evaluation. An array of microbial, genetic, systematic, and phenotypic biomarkers was proposed. Our results showed that the biomarkers could proxy the stage of the bioremediation multidimensionally. We argue that functional diversity should be considered together with microbial community dynamic to evaluate the restoration status of the microbial communities in petroleum-contaminated farmland-oilfield mixed environments.
Neurocomputing Modelling of Hydrochemical and Physical Properties of Groundwater Coupled with Spatial Clustering, GIS, and Statistical Techniques
Authors: Benaafi Mohammed , Yassin Mohamed A. , Usman A. G. , Abba S. I.
Published: February 2022

Groundwater (GW) is a critical freshwater resource for billions of individuals worldwide. Rapid anthropogenic exploitation has increasingly deteriorated GW quality and quantity. Reliable estimation of complex hydrochemical properties of GW is crucial for sustainable development. Real field and experimental studies in an agricultural area from the significant sandstone aquifers (Wajid Aquifer) were conducted. For the modelling purpose, three types of computational models, including the emerging Hammerstein–Wiener (HW), back propagation neural network (BPNN), and statistical multi-variate regression (MVR), were developed for the multi-station estimation of total dissolved solids (TDS) (mg/L) and total hardness (TH) (mg/L). A geographic information system (GIS) was used for the spatial variability assessment of 32 hydrochemical and physical properties of the GW aquifer. A comprehensive visualized literature review spanning several decades was conducted in order to gain an understanding of the existing research and debates relevant to a particular GW and artificial intelligence (AI) study. The experimental data, pre-processing, and feature selection were conducted to determine the most dominant variables for AI-based modelling. The estimation results were evaluated using determination coefficient (DC), mean bias error (MBE), mean square error (MSE), and root mean square error (RMSE). The outcomes proved that TDS (mg/L) and TH (mg/L) correlated more than 90% and 70–85% with Ca2+, Cl−, Br−, NO3−, and Fe, and Na+, SO42−, Mg2+, and F− combinations, respectively. HW-M1 justified promising among all the models with MBE = 1.41 × 10−11, 1.14 × 10−14, and MSE = 7.52 × 10−2, 3.88 × 10−11 for TDS (mg/L), TH (mg/L), respectively. The accuracy proved merit for the overall development of and practical estimation of hydrochemical variables (TDS, TH) (mg/L) and decision-making benchmarks.
Household Preferences for Improved Solid Waste Management (SWM) Services: A Randomized Conjoint Analysis in Kathmandu Metropolitan Ward No. 10
Authors: Bikash Bohara , Ichihashi Masaru
Published: February 2022

Solid waste management (SWM) is a severe environmental concern in many developing countries. The rapid pace of urban population growth and economic development worldwide has led to the increasing generation of municipal solid waste. A large amount of solid waste remains uncollected in metropolitan cities daily due to collection inefficiency. Kathmandu in Nepal also faces the same situation. Due to the lack of relevant studies, this study contributes to research based on quantitative evidence from households’ preference to think about the priority of making effective waste management policies. Prior studies have been less concerned with actual households’ preference or tendencies to improve current SWM (although most of them have pointed out existing waste problems such as the increasing presence of garbage and its composition). This study examines which factors have a causal effect on household decisions to choose improved SWM facilities in Kathmandu, Nepal by using a randomized conjoint experiment useful for effectively identifying respondents’ preference for SWM. Data were collected from 400 randomly selected households using paper questionnaires and face-to-face interviews. Since those households answered choice-card selection five times (and for two kinds of types), the observation number totaled 4000. Our results show that attributes such as monthly service charges, intermediate facilities, and temporary garbage collection spots have a significant effect on respondents’ preferences, while most households still tend to prefer current SWM services. The findings will aid SWM planners in developing and implementing an effective SWM policy that takes household preferences into account.
Symbiotic Relationships in Business Ecosystem: A Systematic Literature Review
Authors: Yoon Changhee , Moon Seungyeon , Lee Heesang
Published: February 2022

The business ecosystem shares many unique features with the biological ecosystem due to its origins. Similar to the biological ecosystem, the business ecosystem also emphasizes symbiotic relationships among symbionts (i.e., participants of a business ecosystem). In this study, we have broadened and deepened our knowledge of symbiosis in a business ecosystem, focusing on how each relationship develops and evolves through the interaction between keystone species and symbionts. We have introduced the typology of symbiotic relationships and highlighted the significant role of keystone species in business ecosystems. We defined three symbiosis types based on the analysis results: mutualism, commensalism, and parasitism. The findings indicated that each relationship continuously transitions into different symbiotic relationships as the relationship between the participants changes. The results also showed that a keystone species, a leader of a business ecosystem, can contribute to the success of a business ecosystem by strategically managing their relationship with symbionts.
Market Concentration, Producer Organizations, and Policy Measures to Strengthen the Opportunities of Farmers for Value Addition—Empirical Findings from the Austrian Meat Supply Chain Using a Multi-Method Approach
Authors: Pröll Simon , Grüneis Heidelinde , Sinabell Franz
Published: February 2022

Improving market access and opportunities for value addition for small-scale food producers and family farms and properly functioning food commodity markets are among the objectives of the Sustainable Development Goals. Market structure and market concentration are important aspects that could make this goal attainable. In a case study, we explore the current conditions of pork and beef farmers in Austrian meat markets by combining a quantitative approach with qualitative inquiries. The quantitative analysis shows that the concentration of meat markets has been increasing in recent years. The rates of change differ in various segments of the value chain and across the types of markets. These results are the starting point for a qualitative analysis of the competitive situation in the observed markets. One finding is that in each market prices are set in idiosyncratic ways. Another one is that producer organizations are an appropriate means for small-scale and family-run farms to strengthen their position in the value chain. We conclude that policy initiatives to improve market access and value addition for farmers need to be complemented by targeted dissemination activities and that competition analyses should apply multi-method approaches similar to the one used in this analysis.
Housing Policy: An Analysis of Public Housing Policy Strategies for Low-Income Earners in Nigeria
Authors: Odoyi Emmanuel Joseph , Riekkinen Kirsikka
Published: February 2022

This article evaluates the Global South housing policy for low-income earners by utilising the Nigerian example to analyse public housing policy strategies used to provide housing to low-income earners. The materials employed in the study were housing policy programme documents provided by various ministries that are linked to housing between 1991 and 2020. The housing policy documents were subjected to qualitative content and thematic analysis. The analysis of the selected housing policy documents showed seven key policy strategies that are intended to strengthen affordable housing development. These strategic themes are funds, schemes, governments, implementation, development, land, and rurality. The findings indicated that the existence of housing policy strategical themes does not translate to affordable housing development and housing affordability for low-income earners, though the effective activation and implementation of strategical themes will promote affordable housing development.
Internal Governance and Corporate Social Responsibility: Evidence from Chinese Companies
Authors: Khan Farman Ullah , Trifan Vanina Adoriana , Pantea Mioara Florina , Zhang Junrui , Nouman Muhammad
Published: February 2022

Stakeholder management researchers have recently put a lot of effort into figuring out why organizations facing extensive pressure respond differently to social responsibilities. In particular, ethics researchers believe that senior management must drive corporate social responsibility since their attitudes toward such issues are so important. In line with this sentiment, our study develops a framework of management power, composed of CEOs’ power and the organizations’ power, and explores how managerial power heterogeneity affects the corporate social responsibility (CSR) performance of a firm. Using sample data from the largest emerging market—China—for the period 2010–2018, we submit that CEOs with structural power and shareholders with the highest concentration tend to show a lower commitment to CSR activities. On the other hand, we recognize that the ownership, expertise, and prestige power of CEOs’, the supervision, monitoring, and political power of the board can improve a firms’ CSR performance. These results are also validated by using a fixed effect model, two stage least square (2-SLS) regression, and the propensity score matching (PSM) technique. Our results imply that the implementation of social policies fundamentally results not only from powerful CEOs, but also from powerful boards and shareholders. Moreover, our study provides useful implications with regard to the social outcomes of power authorized by CEOs and the organizations.
Towards Smart and Sustainable Urban Electromobility: An Editorial Commentary
Authors: Yigitcanlar Tan
Published: February 2022

In the age of anthropogenic climate change, developing smart and sustainable transport systems is among the most popular urban policy debates [...]
Addressing the Phenomenon of Overtourism in Budapest from Multiple Angles Using Unconventional Methodologies and Data
Authors: Pérez Garrido Betsabé , Sebrek Szabolcs Szilárd , Semenova Viktoriia , Bal Damla , Michalkó Gábor
Published: February 2022

This paper addresses the phenomenon of overtourism in Budapest from multiple perspectives, starting with an overview that uses information collected from news, media, and academic tourism literature. Further, the phenomenon of overtourism is addressed quantitatively using different indicators, including tourism density and intensity. According to these indicators, the center of Budapest (formed by districts I, V, VI, VII, VIII, and IX) has been strongly affected by the presence of tourists, while districts physically far from the center have been less affected. This fact suggests the heterogeneity of the city in terms of overtourism. The number one catalyst of the negative impacts of foreign visitors’ behavior is party tourism (‘ruin pub’ tourism), which involves an unconventional use of the Hungarian capital. Finally, using an unconventional optimization method called fuzzy linear programming, we attempt to explore the challenging problem of identifying the optimal number of tourists for the city. The results of the study have important theoretical, methodological, and practical implications. On the theoretical side, we offer a comprehensive understanding of the phenomenon of overtourism in Budapest. Methodologically, the integrated approach in terms of data gathering and unconventional analytical methodologies (comprised of a case study analysis, the assessment of effective indicators for measuring the discussed phenomenon, and the demonstration of the sustainable number of visitors) represents a novel perspective about the extent of overtourism in Budapest. On the practical side, our findings provide valuable guidance for policymakers to help mitigate the problem of overtourism in the city. With regard to future research, we suggest extending and updating the results presented in this study to develop more sustainable tourism strategies.