bluuebunny/crossref_metadata_2025 huggingface dataset:
Modeling Vegetation Water Stress over the Forest from Space: Temperature Vegetation Water Stress Index (TVWSI)
Authors: Joshi Rakesh Chandra , Ryu Dongryeol , Sheridan Gary J. , Lane Patrick N. J.
Published: November 2021

The conventional Land Surface Temperature (LST)–Normalized Difference Vegetation Index (NDVI) trapezoid model has been widely used to retrieve vegetation water stress. However, it has two inherent limitations: (1) its complex and computationally intensive parameterization for multi-temporal observations and (2) deficiency in canopy water content information. We tested the hypothesis that an improved water stress index could be constructed by the representation of canopy water content information to the LST–NDVI trapezoid model. Therefore, this study proposes a new index that combines three indicators associated with vegetation water stress: canopy temperature through LST, canopy water content through Surface Water Content Index (SWCI), and canopy fractional cover through NDVI in one temporally transferrable index. Firstly, a new optical space of SWCI–NDVI was conceptualized based on the linear physical relationship between shortwave infrared (SWIR) and soil moisture. Secondly, the SWCI–NDVI feature space was parameterized, and an index d(SWCI, NDVI) was computed based on the distribution of the observations in the SWCI–NDVI spectral space. Finally, standardized LST (LST/long term mean of LST) was combined to d(SWCI, NDVI) to give a new water stress index, Temperature Vegetation Water Stress Index (TVWSI). The modeled soil moisture from the Australian Water Resource Assessment—Landscape (AWRA-L) and Soil Water Fraction (SWF) from four FLUXNET sites across Victoria and New South Wales were used to evaluate TVWSI. The index TVWSI exhibited a high correlation with AWRA-L soil moisture (R2 of 0.71 with p < 0.001) and the ground-based SWF (R2 of 0.25–0.51 with p < 0.001). TVWSI predicted soil moisture more accurately with RMSE of 21.82 mm (AWRA-L) and 0.02–0.04 (SWF) compared to the RMSE ranging 28.98–36.68 mm (AWRA-L) and 0.03–0.05 (SWF) were obtained for some widely used water stress indices. The TVWSI could also be a useful input parameter for other environmental models.
Multi-Hypothesis Topological Isomorphism Matching Method for Synthetic Aperture Radar Images with Large Geometric Distortion
Authors: Jiao Runzhi , Wang Qingsong , Lai Tao , Huang Haifeng
Published: November 2021

The dramatic undulations of a mountainous terrain will introduce large geometric distortions in each Synthetic Aperture Radar (SAR) image with different look angles, resulting in a poor registration performance. To this end, this paper proposes a multi-hypothesis topological isomorphism matching method for SAR images with large geometric distortions. The method includes the Ridge-Line Keypoint Detection (RLKD) and Multi-Hypothesis Topological Isomorphism Matching (MHTIM). Firstly, based on the analysis of the ridge structure, a ridge keypoint detection module and a keypoint similarity description method are designed, which aim to quickly produce a small number of stable matching keypoint pairs under large look angle differences and large terrain undulations. The keypoint pairs are further fed into the MHTIM module. Subsequently, the MHTIM method is proposed, which uses the stability and isomorphism of the topological structure of the keypoint set under different perspectives to generate a variety of matching hypotheses, and iteratively achieves the keypoint matching. This method uses both local and global geometric relationships between two keypoints, hence it achieving better performance compared with traditional methods. We tested our approach on both simulated and real mountain SAR images with different look angles and different elevation ranges. The experimental results demonstrate the effectiveness and stable matching performance of our approach.
Optical Remote Sensing Indexes of Soil Moisture: Evaluation and Improvement Based on Aircraft Experiment Observations
Authors: Sun Hao , Liu Hao , Ma Yanhui , Xia Qunbo
Published: November 2021

Optical remote sensing (about 0.4~2.0 μm) indexes of soil moisture (SM) are valuable for some specific applications such as monitoring agricultural drought and downscaling microwave SM, due to their abundant data sources, higher spatial resolution, and easy-to-use features, etc. In this study, we evaluated thirteen typical optical SM indexes with aircraft and in situ observed SM from two field campaigns, the Soil Moisture Active Passive Validation Experiment 2012 (SMAPVEX12) and 2016 (SMAPVEX16) conducted in Manitoba, Canada. MODIS surface reflectance products (MOD09A1) and Sentinel-2 multispectral imager Level-1C data were utilized to calculate the optical SM indexes. The evaluation results demonstrated that (1) the Visible and Shortwave Infrared Drought Index (VSDI) and Optical TRApezoid Model (OPTRAM) outperform the other eleven optical SM indexes as compared with aircraft and in situ observed SM. They also presented well consistence in temporal variation with the in situ observed SM. (2) The VSDI achieved comparable performance with the OPTRAM while the former has very simple calculation expression and the latter requires complex process to determine the dry and wet boundaries. (3) Both the VSDI and OPTRAM utilize two sensitive bands of soil and vegetation moisture, i.e., Red and SWIR bands, whereas the other eleven SM indexes only employ one sensitive band. This may be the main reason of the evaluation results. (4) Based on this recognition, improvements of the VSDI and OPTRAM were created and validated in this study through adding more sensitive band to VSDI and combining NDVI and modified VSDI into a new feature space for calculating the optical SM index as with OPTRAM. The results are conducive to selecting and utilizing the current numerous optical SM indexes for SM and drought monitoring.
The Potential of Moonlight Remote Sensing: A Systematic Assessment with Multi-Source Nightlight Remote Sensing Data
Authors: Liu Di , Zhang Qingling , Wang Jiao , Wang Yifang , Shen Yanyun , Shuai Yanmin
Published: November 2021

One recent trend in optical remote sensing is to increase observation frequencies. However, there are still challenges on the night side when sunlight is not available. Due to their powerful capabilities in low-light sensing, nightlight satellite sensors have been deployed to capture nightscapes of Earth from space, observing anthropomorphic and natural activities at night. To date, the mainstream of nightlight remote sensing applications has mainly focused on artificial lights, especially within cities or self-luminous bodies, such as fisheries, oil, offshore rigs, etc. Observations taken under moonlight are often discarded or corrected to reduce lunar effects. Some researchers have discussed the possibility of using moonlight as a useful illuminating source at night for the detection of nocturnal features on Earth, but no quantitative analysis has been reported so far. This study aims to systematically evaluate the potential of moonlight remote sensing with mono-spectral Visible Infrared Imaging Radiometer Suite/Day-Night-Band (VIIRS/DNB) imagery and multi-spectral photos taken by astronauts from the International Space Station (ISS), as well as unmanned aerial vehicle (UAV) night-time imagery. Using the VIIRS/DNB, ISS and UAV moonlight images, the possibilities of the moonlight remote sensing were first discussed. Then, the VIIRS/DNB, ISS, UAV images were classified over different non-self-lighting land surfaces to explore the potential of moonlight remote sensing. The overall accuracies (OA) and kappa coefficients are 79.80% and 0.45, 87.16% and 0.77, 91.49% and 0.85, respectively, indicating a capability to characterize land surface that is very similar to daytime remote sensing. Finally, the characteristics of current moonlight remote sensing are discussed in terms of bands, spatial resolutions, and sensors. The results confirm that moonlight remote sensing has huge potential for Earth observation, which will be of great importance to significantly increase the temporal coverage of optical remote sensing during the whole diurnal cycle. Based on these discussions, we further examined requirements for next-generation nightlight remote sensing satellite sensors.
Covert Information Mapped Spatial and Directional Modulation toward Secure Wireless Transmission
Authors: Tian Jie , Chen Hao , Wang Zhigang , Shi Xianhua , Ji Zhengyu , Li Xianglu
Published: November 2021

Recently, the concept of spatial and direction modulation (SDM) has been developed to reap the advantages of both spatial modulation (SM) and directional modulation (DM). On the one hand, DM ensures the transmission security at the expected direction. On the other hand, the structure of SM-aided distributed receivers can enhance the security even if the eavesdropper is located in the same direction as the legitimate receiver. However, the above advantages are achieved based on the assumption that the eavesdropper is not equipped with distributed receivers. On the other hand, the information security can no longer be guaranteed when the eavesdropper is also equipped with distributed receivers. To alleviate this problem, we considered a joint design of SDM and covert information mapping (CIM) in order to conceive of a more robust structure of CIM-SDM. Furthermore, both the detection performances at the eavesdropper and the legitimate user were quantified through theoretical derivation. In general, both the analysis and simulation results supported that the proposed CIM-SDM structure provides more robust secure performance compared to the original SDM, even if the extreme condition of distributed receivers at the eavesdropper is considered, at the cost of moderate performance loss at the legitimate user.
Ecotourism Practices in Potatso National Park from the Perspective of Tourists: Assessment and Developing Contradictions
Authors: Zheng Rumin , Zhen Shuo , Mei Lin , Jiang Hongqiang
Published: November 2021

Ecotourism in Potatso National Park has been developing for more than 15 years, which has had important guiding significance for the development of China’s national parks. This paper analyzes ecotourism practices in Potatso by extracting related travel notes and adopting the ground theory and content analysis method. The results show that the current ecotourism practices in Potatso include 5 dimensions and 15 elements. The five dimensions are the natural environment, environmental education, community participation, ecotourism experience and socioeconomic background. The five most important elements are the ecosystem elements, sensory and behavioral ecotourism experience, ecological facilities and interpretation systems. There are also three contradictions: between tourists’ environmental awareness and lack of environmental behaviors, between community participation and residents’ reception capacity, and between environmental education and tourists’ experiences. Regarding the future development of Potatso, conservation will always come first. A breakthrough is needed to strengthen the conversion of environmental education to the environmental behavior of tourists, adjust the participation model of communities dynamically, and continue innovating in the form of environmental education.
Exploring the Critical Barriers to the Implementation of Renewable Technologies in Existing University Buildings
Authors: Fuentes-del-Burgo Joaquín , Navarro-Astor Elena , Ramos Nuno M. M. , Martins João Poças
Published: November 2021

For more than a decade, the European Union has been implementing an ambitious energy policy focused on reducing CO2 emissions, increasing the use of renewable energy and improving energy efficiency. This paper investigates the factors that hinder the application of renewable energy technologies (RETs) in existing university buildings in Spain and Portugal. Following a qualitative methodology, 33 technicians working in the infrastructure management offices of 24 universities have been interviewed. The factors identified have been classified into economic-financial, administrative and legislative barriers, architectural, urban planning, technological, networking, social acceptance, institutional and others. It is concluded that there have not been sufficient economic incentives to carry out RETs projects in this type of building. Conditioning factors can act individually or jointly, generating a greater effect. Most participants consider that there are no social acceptance barriers. Knowledge of these determinants can facilitate actions that help implement this technology on university campuses in both countries.
Are You Happy to Be a Farmer? Understanding Indicators Related to Agricultural Production and Influencing Factors: GAP-Şanlıurfa, Turkey
Authors: Aydoğdu Mustafa Hakkı , Cançelik Mehmet , Sevinç Mehmet Reşit , Çullu Mehmet Ali , Yenigün Kasım , Küçük Nihat , Karlı Bahri , Ökten Şevket , Beyazgül Uğur , Doğan Hatice Parlakçı , Sevinç Gönül , Şahin Zeliha , Mutlu Nusret , Kaya Celal , Yenikale Ayla , Yenikale Akif
Published: November 2021

Recently, agricultural production areas and farmer numbers have been decreasing in Turkey, which has started to cause concern. This study aimed to analyze the satisfaction levels of farmers in different irrigation areas in the Southeastern Anatolia Project (GAP)-Şanlıurfa region, based on indicators related to agricultural production and influencing factors. The data were obtained through face-to-face surveys with farmers in 2020 and analyzed by logistic regression in STATA. According to the results, 43.3% of the farmers are happy to be farmers in the current situation, and 35.6% want their children to continue farming activities. It was determined that the area of irrigation, education level, income, and farming experience were statistically significant at different rates in terms of the happiness of the farmers. On the other hand, livestock, number of households, and land size were not statistically significant. While 27.5% of the participants were fully satisfied with the given public support, 15.7% were satisfied with the market selling prices of their products, and 43.5% stated that effective organizations are needed to live well. To ensure agricultural sustainability in the research area, there is a need for more agricultural support, effective extension services, and the development of rural tourism with the participation of the public and private sectors. This study was the first of its kind to be conducted in Turkey.
A Study on Intelligent Technology Valuation System: Introduction of KIBO Patent Appraisal System II
Authors: Kim Min-Seung , Lee Chan-Ho , Choi Ji-Hye , Jang Yong-Ju , Lee Jeong-Hee , Lee Jaesik , Sung Tae-Eung
Published: November 2021

Technology finance, which has attracted worldwide attention for the successful business development of small-and-medium enterprises (SMEs) or start-ups, has advanced an innovation or stagnation way-out resolution strategy for companies in line with the low-growth economic trends. Although the development of new technologies and the establishment of active R&D and commercialization strategies are essential factors in a company’s management sustainability, the activation of the technology market in practice is still in progress for its golden age. In this study, to promote a technology transfer-based company’s growth and to run technology-based various financial support activities, we develop and propose a new intelligent, deep learning-based technology valuation system that enables technology holders to estimate the economic values of their innovative technologies and further to establish a firm’s commercialization strategy. For the last years, the KIBO Patent Appraisal System (KPAS-II) herein proposed has been advanced by KIBO as a web-based, artificial intelligence (AI) and evaluation data applications valuation system that automatically calculates and estimates a technology’s feasible economic value by utilizing both the intrinsic and extrinsic index information of a patent and the commercialization entity’s business capabilities, and by applying to the discounted cash flow (DCF) method in valuation theory, and finally integrating with deep learning results based on the in-advance previously established patent DB and the financial DB. The KPAS-II proposed in this study can be said to have dramatically overcome the long-term preparation period and high levels of R&D and commercialization costs in terms of the limitations that the existing technology valuation method possesses by enhancing the reliability of approximate economic values from the deep learning results based on financial data and completed valuation data. In addition, it is expected that technology marketing coordinators, researchers, and non-specialty business agents, not limited to valuation experts, can easily estimate the economic values of their patents or technologies, and they can be actively utilized in a technology-based company’s decision-making and technologically dependent financial activities.
Improving the E-Commerce Business Model in a Sustainable Environment
Authors: Sun Mingwei , Grondys Katarzyna , Hajiyev Nazim , Zhukov Pavel
Published: November 2021

The purpose of this study is to develop a comprehensive methodological approach to assess the sustainability of the e-commerce business model based on the integration of key performance indicators into a single vector of business model sustainability. The proposed vector approach allows for predicting and evaluating the effects of different kinds of measures, identifying and implementing the most effective tools for sustainable e-commerce business development. The methodology of this study is based on correlation, cluster and regression analysis. The scientific contribution of this study is the proposed methodological approach, which not only allows one to analyze business model sustainability, but also to compare companies in a competitive environment to determine the priorities of their functioning to achieve leadership positions on the background of sustainable development. The correlation analysis proved that in modern conditions, both economic and environmental components are significant for business model effectiveness in e-commerce. The clustering of the studied e-commerce companies provided an opportunity to take into account the peculiarities of the studied companies, to group them by similar performance indicators. This made it possible to develop more accurate regression models for each cluster. In this case, there is a correlation between the sustainability vector of the business model of a company and its assignment to a particular cluster. The conducted modeling and determination of the level of business model sustainability allowed for determining a relationship between it and the performance of e-commerce companies in the context of economic, environmental and social dimensions. At the same time, the results show that increasing the sustainability vector brings a company closer to the business sustainability benchmark.
Enhancement of Multi-Class Structural Defect Recognition Using Generative Adversarial Network
Authors: Shin Hyunkyu , Ahn Yonghan , Tae Sungho , Gil Heungbae , Song Mihwa , Lee Sanghyo
Published: November 2021

Recently, in the building and infrastructure fields, studies on defect detection methods using deep learning have been widely implemented. For robust automatic recognition of defects in buildings, a sufficiently large training dataset is required for the target defects. However, it is challenging to collect sufficient data from degrading building structures. To address the data shortage and imbalance problem, in this study, a data augmentation method was developed using a generative adversarial network (GAN). To confirm the effect of data augmentation in the defect dataset of old structures, two scenarios were compared and experiments were conducted. As a result, in the models that applied the GAN-based data augmentation experimentally, the average performance increased by approximately 0.16 compared to the model trained using a small dataset. Based on the results of the experiments, the GAN-based data augmentation strategy is expected to be a reliable alternative to complement defect datasets with an unbalanced number of objects.
The Relationship between the Conception of Nature and Environmental Valuation
Authors: Nagao Yamane , Nishikori Ayano , Imoto Tomoko
Published: November 2021

As individuals’ relationships with nature become more diverse, so do their conceptions of nature. In this study, the image of nature and derived feelings are defined as the conception of nature. This study aimed to identify the conceptions of nature held by individuals and their influence on environmental valuation. The number of respondents who imagined natural forests when they heard the word “nature” was the highest (58%), followed by those who imagined Satoyama (31%). The factor analysis extracted five feelings toward the image of nature: care, oneness, aversion, mystery, and restorativeness. These feelings differed depending on the image of nature conjured up by individuals. Respondents who imagined natural forests and Satoyama had a higher sense of care, causing higher willingness-to-pay for forest conservation. These results revealed that the image of nature differed from person to person, contrary to previous studies where nature was regarded as predominantly represented by vegetation. Feelings for the image of nature also differed. It can be concluded that an individuals’ conception of nature influences their environmental valuation.
Effectiveness of Work-Integrated Learning Partnerships: Case Study of Cooperative Education in Agricultural Tertiary Education
Authors: Kassem Hazem S. , Al-Zaidi Abdullah Awad , Baessa Awadh
Published: November 2021

The growing demand for promoting the role of higher education institutions in sustainability has contributed to creating new partnerships with other actors. In the field of education, the formation of cooperative education (co-op) partnerships was adopted as a strategy for work-integrated learning in cooperation with industry. This study investigated the effectiveness of co-op partnerships and the factors that influence them in the context of tertiary agriculture education in Saudi Arabia. A random sample of 130 co-op students was selected within the Bachelor of Agricultural Sciences delivered by the College of Food and Agriculture Sciences at King Saud University. The satisfaction level of students was explored in terms of four main areas, namely, the quality of the program design, organizational climate, personal and professional qualities, and program learning outcomes. The majority of students (70%) were highly satisfied with the quality of the program design, while they had a moderate level of satisfaction regarding the organizational climate of the co-op program (74.6%). Furthermore, 85.4% of students were highly satisfied regarding the learning outcomes they gained. The results also revealed that there were significant positive relationships between the level of satisfaction of students regarding program learning outcomes and their quality assessments of the program design, personal and professional qualities, and organizational climate. The measurement scale used in this study may assist in assessing the sustainability of co-op partnerships. Moreover, understanding the satisfaction level of students can help to identify areas that should be improved and, in turn, contribute to improving the governance and sustainability of co-op partnerships for all stakeholders.
Energy Stored in Above-Ground Biomass Fractions and Model Trees of the Main Coniferous Woody Plants
Authors: Petráš Rudolf , Mecko Julian , Kukla Ján , Kuklová Margita , Krupová Danica , Pástor Michal , Raček Marcel , Pivková Ivica
Published: November 2021

The paper considers energy stored in above-ground biomass fractions and in model trees of the main coniferous woody plants (Picea abies (L.) H. Karst., Abies alba Mill., Pinus sylvestris (L.), Larix decidua Mill.), sampled in 22 forest stands selected in different parts of Slovakia. A total of 43 trees were felled, of which there were 12 spruces, 11 firs, 10 pines, and 10 larches. Gross and net calorific values were determined in samples of wood, bark, small-wood, twigs, and needles. Our results show that these values significantly depend on the tree species, biomass fractions, and sampling point on the tree. The energy stored in the model trees calculated on the basis of volume production taken from yield tables increases as follows: spruce < fir < pine < larch. Combustion of tree biomass releases an aliquot amount of a greenhouse gas—CO2, as well as an important plant nutrient, nitrogen—into the atmosphere. The obtained data must be taken into account in the case of the economic utilization of energy stored in the fractions of above-ground tree biomass and in whole trees. The achieved data can be used to assess forest ecosystems in terms of the flow of solar energy, its accumulation in the various components of tree biomass, and the risk of biomass combustion in relation to the release of greenhouse gases.
The Chemical and Cytotoxic Properties of Sambucus nigra Extracts—A Natural Food Colorant
Authors: Banach Mariusz , Khaidakov Barbara , Korewo Daria , Węsierska Magdalena , Cyplik Wojciech , Kujawa Joanna , Ahrné Lilia , Kujawski Wojciech
Published: November 2021

Elderberry fruits contain valuable components that are beneficial to human health. Owing to the high content of anthocyanins, elderberry extracts can be used as natural food colorants with health-promoting properties. Moreover, the development of new natural food dyes enables the reduction in the use of synthetic ones. Anthocyanins-rich elderberry dry extracts (EDE) were prepared from the same batch of frozen fruits applying water extraction, followed by membrane separation (batch B1) or purification by column chromatography (batch B2) and then spray-dried. Subsequently, the content of anthocyanins, flavonols, and polyphenols was determined. The extract obtained with the application of column chromatography (B2) contained 33% anthocyanins, which is more than typical market standards, whereas the extract B1 contained 14% anthocyanins. The color properties of both extracts were also determined. Since water was used as an extractant, the extracts are well soluble in water and can therefore be used as a natural food colorant. The cytotoxic activity of both extracts was additionally determined using the MTT test and the tumor cells of the A-549, A-2780, MCF-7, Caco-2 line, and Peripheral blood mononuclear cells. It was revealed that both EDEs inhibit the proliferation of cancer cells, except those of the lung cancers. Extract B2 showed a much stronger cytotoxic effect. Additionally, both extracts stimulate the proliferation of peripheral blood mononuclear cells since they may have immunostimulatory properties.
Assessing the Performance of Environmentally Friendly-Produced Zerovalent Iron Nanoparticles to Remove Pharmaceuticals from Water
Authors: Panagou Iliana , Noutsopoulos Constantinos , Mystrioti Christiana , Barka Evridiki , Koumaki Elena , Kalli Maria , Malamis Simos , Papassiopi Nymphodora , Mamais Daniel
Published: November 2021

Nano zerovalent iron (nZVI), produced from green tea extracts, was incorporated in a cation exchange resin (R-nFe) to investigate its performance regarding the removal of four non-steroidal anti-inflammatory drugs (NSAIDs): ibuprofen (IBU), naproxen (NPX), ketoprofen (KTP) and diclofenac (DCF). The effect of contact time, NaCl pretreatment, pH, R-nFe dose, the role of the supporting material, the initial concentration of pollutants, and the combined effect of nZVI with oxidative reagents was assessed through a series of batch experiments. According to the results, the best removal efficiencies obtained for DCF and KTP were 86% and 73%, respectively, at 48 h of contact time with NaCl pretreated R-nFe at a dose of 15 g L−1 and a pH of 4. The maximum removal efficiency for NPX was 90% for a contact time of 60 min with PS 1 mM and a pH of 3, which was quite similar to the experiment with a greater contact time of 48 h without PS addition. The maximum IBU removal was 70%; this was reached at pH 3, with a contact time of 30 min and R-nFe 15 g L−1. To the authors’ best knowledge, this is the first study investigating the utilization of nZVI, produced from leaf extracts and incorporated into a cationic exchange resin, to remove NSAIDs from water.
Advanced Emission Controls and Sustainable Renewable Fuels for Low Pollutant and CO2 Emissions on a Diesel Passenger Car
Authors: Demuynck Joachim , Dauphin Roland , Yugo Marta , Mendoza Villafuerte Pablo , Bosteels Dirk
Published: November 2021

Research efforts into advanced emission control systems led to significant reduction of pollutant emissions of modern internal combustion engines. Sustainable renewable fuels are used to further reduce their Well-to-Wheels greenhouse gas emissions. The novel aspect of this paper is the compatibility investigation of existing advanced emission control technologies for achieving low pollutant emissions with the use of sustainable renewable fuels with vehicle tests. This is done on a diesel demonstrator vehicle, equipped with Lean NOx trap and dual-SCR technologies in combination with a 48V mild-hybrid powertrain. Tailpipe pollutant and CO2 emissions are measured for market diesel fuel with 7% renewable fatty-acid-methyl-ester (FAME) (B7), diesel fuel with 30% FAME (B30), and 100% renewable hydrotreated vegetable oil (HVO). Results show no significant difference in pollutant emissions between the different fuels used. In a second part of the study, a Well-to-Wheels (WTW) analysis is conducted. This includes different pathways for the biomass-to-liquid fuels that were tested on the vehicle, as well as a power-to-diesel (e-diesel) assessment. Results show that significant WTW CO2 reductions are possibly compared to the state-of-the-art market diesel fuel. Part of this reduction is already possible for the existing fleet as most of paraffinic compounds are drop-in for market diesel fuel.
Climate Change, Farming, and Gardening in Alaska: Cultivating Opportunities
Authors: Fresco Nancy , Bennett Alec , Bieniek Peter , Rosner Carolyn
Published: November 2021

Ongoing climate change and associated food security concerns are pressing issues globally, and are of particular concern in the far north where warming is accelerated and markets are remote. The objective of this research was to model current and projected climate conditions pertinent to gardeners and farmers in Alaska. Research commenced with information-sharing between local agriculturalists and climate modelers to determine primary questions, available data, and effective strategies. Four variables were selected: summer season length, growing degree days, temperature of the coldest winter day, and plant hardiness zone. In addition, peonies were selected as a case study. Each variable was modeled using regional projected climate data downscaled using the delta method, followed by extraction of key variables (e.g., mean coldest winter day for a given decade). An online interface was developed to allow diverse users to access, manipulate, view, download, and understand the data. Interpretive text and a summary of the case study explained all of the methods and outcomes. The results showed marked projected increases in summer season length and growing degree days coupled with seasonal shifts and warmer winter temperatures, suggesting that agriculture in Alaska is undergoing and will continue to undergo profound change. This presents opportunities and challenges for farmers and gardeners.
Seasonal Performance Evaluation of Pavement Base Using Recycled Materials
Authors: Zhang Yang , Cetin Bora , Edil Tuncer B.
Published: November 2021

Using recycled pavement materials to construct new pavement base is currently an important construction strategy bringing improved sustainability. This study investigates the long-term performance of pavement bases constructed with recycled concrete aggregate (RCA), reclaimed asphalt pavement (RAP), and blends with natural aggregates in a seasonal frost region. The stabilization effect of fly ash on RAP was studied as well. In situ falling weight deflectometer (FWD) tests were routinely conducted to provide seasonal deflection data, which were used to back-calculate the layer modulus. Seasonal changes in the base layer modulus along with the pavement ride quality were monitored. One of the two lanes at the test sections was consistently subjected to traffic loading, whereas the other one was not. Findings from this field research indicated that after undergoing over 8 years of naturally seasonal freeze-thaw conditions, 100% RCA, 50% RCA, plus 50% natural aggregates, and 100% RAP, presented improved performance over 100% natural aggregates. However, 50% RAP blended with 50% natural aggregates performed comparably to natural aggregates only, and fly ash did not provide considerable improvement on the long-term performance of 50% RAP plus 50% natural aggregate base. Seasonal climatic variations turned out to affect pavement performance more critically than traffic loading.
Integrated Urban Mobility for Our Health and the Climate: Recommended Approaches from an Interdisciplinary Consortium
Authors: Dogra Shilpa , O’Rourke Nicholas , Jenkins Michael , Hoornweg Daniel
Published: November 2021

Background: The purpose of this paper is to suggest an approach to aid with the creation of an interdisciplinary team and evidence-informed solutions addressing the urban mobility challenges facing many communities. Methods: We created a local Urban Mobility Consortium with experts from different disciplines to discuss the development of healthy, accessible communities, electrification, ride-sharing, and overarching issues related to urban mobility. A workshop and survey data collected during COVID-19 are presented in this paper. Results: Several evidence-informed recommendations are provided. Broadly, these were: (1) support the creation and development of accessible and safe active-transportation infrastructure; (2) incentivize and prioritize the use of active, public, and shared transportation over use of personal vehicles; (3) ensure connectivity of active transportation infrastructure with major destinations and public transportation options; (4) work towards electrification of personal and public transportation; and (5) work across siloes to improve integrated mobility to impact climate and health related outcomes, and enhance overall efficiency. Conclusions: An integrated approach is needed to improve mobility, access, and environmental impact. This needs to be carried out in the local context and requires government and non-governmental leadership.
Loyalty of Paratransit Users in the Era of Competition with Ride Sourcing
Authors: Joewono Tri Basuki , Matthew Ariel , Rizki Muhamad
Published: November 2021

As a mode serving urban mobility in developing countries, paratransit is experiencing competition with the fast and massive growth of ride sourcing. This study aims to investigate the loyalty of paratransit users in Bandung, Indonesia, in the era of competition with ride sourcing. Data collected by questionnaires and distributed to 400 paratransit users in Bandung were analysed using hierarchical structural equation modelling. The analysis shows that satisfaction is positively influenced by service quality variables. Though there is less satisfaction compared to the previous decade, satisfaction with the service still has a positive influence on total satisfaction with the mode. It can also be concluded that loyalty is positively influenced by satisfaction. Satisfaction with the image and the unique characteristics of paratransit retains passengers’ intentions toward loyalty in the future, including current personal characteristics (i.e., age, income, occupation) and travel characteristics (i.e., fare, vehicle ownership) of passengers. This study warns of the high probability of mode-changing behaviour from paratransit to another mode.
Intersection Safety Assessment Using Video-Based Traffic Conflict Analysis: The Case Study of Thailand
Authors: Kronprasert Nopadon , Sutheerakul Chomphunut , Satiennam Thaned , Luathep Paramet
Published: November 2021

In the road transport network, intersections are among the most critical locations leading to a risk of death and serious injury. The traditional methods to assess the safety of intersections are based on statistical analyses that require crash data. However, such data may be under-reported and omit important crash-related factors. The conventional approaches, therefore, are not easily applied to making comparisons of intersection designs under different road classifications. This study developed a risk-based approach that incorporates video-based traffic conflict analysis to investigate vehicle conflicts under mixed traffic conditions including motorcycles and cars in Thailand. The study applied such conflict data to assess the risk of intersections in terms of time-to-collision and conflict speed. Five functional classes of intersections were investigated, including local-road/local-road, local-road/collector, collector/arterial, collector/collector, and arterial/arterial intersections. The results showed that intersection classes, characteristics, and control affect the behavior of motorists and the safety of intersections. The results found that the low-order intersections with stop/no control are high risks due to the short time-to-collision of motorcycle-related conflicts. They generate frequent conflicts with low chance of injury. The high-order intersections with signal control are high risks due to high conflicting speeds of motorcycle–car conflicts. They generate few conflicts but at a high chance of injury. The study presents the applicability of video-based traffic conflict analysis for systematically estimating the crash risk of intersections. The risk-based approach can be deemed as a supplement indicator in addition to limited crash data to evaluate the safety of intersections. However, future research is needed to explore the potential of other road infrastructure under different circumstances.
Quality-Certified Hotels: The Role of Certification Bodies on the Formation of Customer Behavioral Intentions
Authors: Collado Agudo Jesús , Martínez García de Leaniz Patricia , Herrero Crespo Ángel , Gómez-López Raquel
Published: November 2021

This study attempts to explore the role of certification bodies on the formation of customer behavioral intentions. A structured questionnaire was used to collect data from hotel customers in Spain. The results of the structural equation modeling indicate that a certified hotel’s image will positively influence stay intention and willingness to pay a premium. At the same time, awareness of, and trust in, certification bodies both have a positive effect on a certified hotel’s image. Finally, awareness of certification bodies also exerts a positive effect on trust in certification bodies. The results offer hoteliers potential strategies for customer behavioral intentions enhancement.
Geometry of α-Cosymplectic Metric as ∗-Conformal η-Ricci–Yamabe Solitons Admitting Quarter-Symmetric Metric Connection
Authors: Zhang Pengfei , Li Yanlin , Roy Soumendu , Dey Santu
Published: November 2021

The outline of this research article is to initiate the development of a ∗-conformal η-Ricci–Yamabe soliton in α-Cosymplectic manifolds according to the quarter-symmetric metric connection. Here, we have established some curvature properties of α-Cosymplectic manifolds in regard to the quarter-symmetric metric connection. Further, the attributes of the soliton when the manifold gratifies a quarter-symmetric metric connection have been displayed in this article. Later, we picked up the Laplace equation from ∗-conformal η-Ricci–Yamabe soliton equation when the potential vector field ξ of the soliton is of gradient type, admitting quarter-symmetric metric connection. Next, we evolved the nature of the soliton when the vector field’s conformal killing reveals a quarter-symmetric metric connection. We show an example of a 5-dimensional α-cosymplectic metric as a ∗-conformal η-Ricci–Yamabe soliton acknowledges quarter-symmetric metric connection to prove our results.
A Hybrid Vegetation Detection Framework: Integrating Vegetation Indices and Convolutional Neural Network
Authors: Hashim Wahidah , Eng Lim Soon , Alkawsi Gamal , Ismail Rozita , Alkahtani Ammar Ahmed , Dzulkifly Sumayyah , Baashar Yahia , Hussain Azham
Published: November 2021

Vegetation inspection and monitoring is a time-consuming task. In the era of industrial revolution 4.0 (IR 4.0), unmanned aerial vehicles (UAV), commercially known as drones, are in demand, being adopted for vegetation inspection and monitoring activities. However, most off-the-shelf drones are least favoured by vegetation maintenance departments for on-site inspection due to limited spectral bands camera restricting advanced vegetation analysis. Most of these drones are normally equipped with a normal red, green, and blue (RGB) camera. Additional spectral bands are found to produce more accurate analysis during vegetation inspection, but at the cost of advanced camera functionalities, such as multispectral camera. Vegetation indices (VI) is a technique to maximize detection sensitivity related to vegetation characteristics while minimizing other factors which are not categorised otherwise. The emergence of machine learning has slowly influenced the existing vegetation analysis technique in order to improve detection accuracy. This study focuses on exploring VI techniques in identifying vegetation objects. The selected VIs investigated are Visible Atmospheric Resistant Index (VARI), Green Leaf Index (GLI), and Vegetation Index Green (VIgreen). The chosen machine learning technique is You Only Look Once (YOLO), which is a clever convolutional neural network (CNN) offering object detection in real time. The CNN model has a symmetrical structure along the direction of the tensor flow. Several series of data collection have been conducted at identified locations to obtain aerial images. The proposed hybrid methods were tested on captured aerial images to observe vegetation detection performance. Segmentation in image analysis is a process to divide the targeted pixels for further detection testing. Based on our findings, more than 70% of the vegetation objects in the images were accurately detected, which reduces the misdetection issue faced by previous VI techniques. On the other hand, hybrid segmentation methods perform best with the combination of VARI and YOLO at 84% detection accuracy.
Effects of the Tensor Force on the Ground Properties of Zr Isotopes
Authors: Chen Chao-Feng , Chen Qi-Bo , Zhou Xian-Rong , Cheng Yi-Yuan
Published: November 2021

The effects of the tensor force on the ground properties of Zr isotopes are studied in the framework of the Skyrme–Hartree–Fock approach. It is found that the tensor force strongly affects the ground state energies and the geometric symmetry properties, in particular for those isotopes near N=60 region. The effects are attributed to the fact that the tensor force enlarges the spin and pseudospin symmetry breaking and therefore results in a ∼2 MeV sub-shell gap between d3/2 and s1/2 single-particle levels.
Identifying Climate Adjacency for Enhancing Climate Action Using Systems Thinking and Modelling
Authors: Sharma Kabir , Mathur Mihir
Published: November 2021

This paper presents findings from a process aimed at identifying the climate linkages of non-climate focused environment and development projects in India. Findings from four case studies based on workshops using participatory systems thinking are summarized. These climate adjacencies are documented as systems stories using the tools of systems thinking—behavior over time graphs and causal loop diagrams. These place-based stories highlight how the environment and development projects have linkages with climate change mitigation and adaptation. An attempt has been made to convert one of the systems stories into a computable simulation model using system dynamics modelling. A small concept model has been created thus and used to perform simulation runs. Four scenarios have been generated and the results discussed. Our learning from converting feedback maps into stock-flow models is presented. The insights generated from interpreting the feedback maps and simulation results are also presented. These insights are then compared and the benefits of simulation evaluated. The paper highlights the need to document climate linkages of non-climate-focused development projects and the benefit of converting systems stories into simulation models for developing operational insights. The important role such methods can play in developing capacities for enhancing climate action is also discussed.
A Review on Tough Soft Composites at Different Length Scales
Authors: Cui Wei , Zhu Ruijie
Published: November 2021

Soft composites are widely employed in industrial and biomedical fields, which often serve as load-bearing structural materials by virtue of a special combination of high strength, high toughness, and low flexural stiffness. Understanding the toughening mechanism of such composites is crucial for designing the next-generation soft materials. In this review, we give an overview of recent progress in soft composites, focusing on the design strategy, mechanical properties, toughening mechanisms, and relevant applications. Fundamental design strategies for soft composites that dissipate energy at different length scales are firstly described. By subsequently elucidating the synergistic effects of combining soft and hard phases, we show how a resulting composite can achieve unprecedented mechanical performance by optimizing the energy dissipation. Relevant toughening models are discussed to interpret the superior strength and fracture toughness of such soft composites. We also highlight relevant applications of these soft composites by taking advantage of their special mechanical responses.
Global Dynamics of the Hořava–Lifshitz Cosmological Model in a Non-Flat Universe with Non-Zero Cosmological Constant
Authors: Gao Fabao , Llibre Jaume
Published: November 2021

When the cosmological constant is non-zero, the dynamics of the cosmological model based on Hořava–Lifshitz gravity in a non-flat universe are characterized by using the qualitative theory of differential equations.
The Distribution and Composition of Vector Abundance in Hanoi City, Vietnam: Association with Livestock Keeping and Flavivirus Detection
Authors: Nguyen-Tien Thang , Bui Anh Ngoc , Ling Jiaxin , Tran-Hai Son , Pham-Thanh Long , Bui Vuong Nghia , Dao Tung Duy , Hoang Thuy Thi , Vu Lieu Thi , Tran Phong Vu , Vu Duoc Trong , Lundkvist Åke , Nguyen-Viet Hung , Magnusson Ulf , Lindahl Johanna Frida
Published: November 2021

Background: Dengue virus and Japanese encephalitis virus are two common flaviviruses that are spread widely by Aedes and Culex mosquitoes. Livestock keeping is vital for cities; however, it can pose the risk of increasing the mosquito population. Our study explored how livestock keeping in and around a large city is associated with the presence of mosquitoes and the risk of them spreading flaviviruses. Methods: An entomological study was conducted in 6 districts with 233 households with livestock, and 280 households without livestock, in Hanoi city. BG-Sentinel traps and CDC light traps were used to collect mosquitoes close to animal farms and human habitats. Adult mosquitoes were counted, identified to species level, and grouped into 385 pools, which were screened for flaviviruses using a pan-flavivirus qPCR protocol and sequencing. Results: A total of 12,861 adult mosquitoes were collected at the 513 households, with 5 different genera collected, of which the Culex genus was the most abundant. Our study found that there was a positive association between livestock keeping and the size of the mosquito population—most predominantly between pig rearing and Culex species (p < 0.001). One pool of Cx. tritaeniorhynchus, collected in a peri-urban district, was found to be positive for Japanese encephalitis virus. Conclusions: The risk of flavivirus transmission in urban areas of Hanoi city due to the spread of Culex and Aedes mosquitoes could be facilitated by livestock keeping.