bluuebunny/crossref_metadata_2025 huggingface dataset:
Biowaste-Derived Humic-like Substances Improve Growth and Quality of Orange Jasmine (Murraya paniculata L. Jacq.) Plants in Soilless Potted Culture
Authors: Fascella Giancarlo , Montoneri Enzo , Rouphael Youssef
Published: August 2021

Humic-like substances (HLS) are among the most used biostimulants in agriculture as a means for improving plant growth, nutrient uptake, crop yield, and stress tolerance. HLS derived from municipal biowastes were applied as a substrate drench in order to evaluate their biostimulatory effect on the growth and ornamental quality of Orange Jasmine (Murraya paniculata L. Jacq.) potted plants. Two HLS, derived from the digestion of the organic humic fraction and from composting of a mix of sewage sludge digestate and gardening residues, were compared with a commercial leonardite-based product in the framework of a greenhouse experiment in soilless culture. The application of the two biowaste-derived HLS resulted in plants showing a 39.9%, 87.0%, 111.6%, 35.4%, 37.9%, 35.3%, and 81.3% increase in plant height, number of flowers and fruits, leaf production, total dry biomass, root length, and water use efficiency, respectively, compared to those treated with the commercial product and the untreated (control) plants. The enhanced growth performance of HLS-treated plants was due to the higher chlorophyll relative content (+24.2% on average) and net photosynthesis (+114.7% on average) of their leaves. The positive results obtained from the application of non-commercial HLS suggest that biowaste recycling is a sustainable and environment-friendly source of biostimulants, as an alternative to agrochemicals and existing leonardite-based plant biostimulants.
Policy Instruments to Encourage the Adoption of Nature-Based Solutions in Urban Landscapes
Authors: Mendonça Rita , Roebeling Peter , Fidélis Teresa , Saraiva Miguel
Published: August 2021

Urban landscapes are under great pressure and particularly vulnerable, due to climate change, population growth and economic development. Despite the growing understanding that Nature-Based Solutions (NBS) represent efficient solutions to facilitate adaptation to climate change and increase cities’ resilience, their wide-scale adoption is still limited. There is a need to include NBS in urban governance and planning agendas through policy instruments, such as plan/legislative, economic and information instruments. However, there is a lack of studies that assess such policy instruments and, through the use of specific examples, how they can foster NBS adoption. The objective of this study is to address this gap by conducting a systematic literature review, using a bibliometric and a content analysis, collating and reviewing papers that consider policy instruments and NBS in order to: (i) assess the existence of policy instruments that influence the adoption of NBS; and (ii) evaluate the existence of specific examples of policy instruments. Results show that plan/legislative instruments are most mentioned, followed by economic and information instruments. However, examples of specific policy instruments being used in practice are still scarce in literature, as most studies remain theoretical.
Estimating Control Points for B-Spline Surfaces Using Fully Populated Synthetic Variance–Covariance Matrices for TLS Point Clouds
Authors: Raschhofer Jakob , Kerekes Gabriel , Harmening Corinna , Neuner Hans , Schwieger Volker
Published: August 2021

A flexible approach for geometric modelling of point clouds obtained from Terrestrial Laser Scanning (TLS) is by means of B-splines. These functions have gained some popularity in the engineering geodesy as they provide a suitable basis for a spatially continuous and parametric deformation analysis. In the predominant studies on geometric modelling of point clouds by B-splines, uncorrelated and equally weighted measurements are assumed. Trying to overcome this, the elementary errors theory is applied for establishing fully populated covariance matrices of TLS observations that consider correlations in the observed point clouds. In this article, a systematic approach for establishing realistic synthetic variance–covariance matrices (SVCMs) is presented and afterward used to model TLS point clouds by B-splines. Additionally, three criteria are selected to analyze the impact of different SVCMs on the functional and stochastic components of the estimation results. Plausible levels for variances and covariances are obtained using a test specimen of several dm—dimension. It is used to identify the most dominant elementary errors under laboratory conditions. Starting values for the variance level are obtained from a TLS calibration. The impact of SVCMs with different structures and different numeric values are comparatively investigated. Main findings of the paper are that for the analyzed object size and distances, the structure of the covariance matrix does not significantly affect the location of the estimated surface control points, but their precision in terms of the corresponding standard deviations. Regarding the latter, properly setting the main diagonal terms of the SVCM is of superordinate importance compared to setting the off-diagonal ones. The investigation of some individual errors revealed that the influence of their standard deviation on the precision of the estimated parameters is primarily dependent on the scanning distance. When the distance stays the same, one-sided influences on the precision of the estimated control points can be observed with an increase in the standard deviations.
Measurement of Forest Inventory Parameters with Apple iPad Pro and Integrated LiDAR Technology
Authors: Gollob Christoph , Ritter Tim , Kraßnitzer Ralf , Tockner Andreas , Nothdurft Arne
Published: August 2021

The estimation of single tree and complete stand information is one of the central tasks of forest inventory. In recent years, automatic algorithms have been successfully developed for the detection and measurement of trees with laser scanning technology. Nevertheless, most of the forest inventories are nowadays carried out with manual tree measurements using traditional instruments. This is due to the high investment costs for modern laser scanner equipment and, in particular, the time-consuming and incomplete nature of data acquisition with stationary terrestrial laser scanners. Traditionally, forest inventory data are collected through manual surveys with calipers or tapes. Practically, this is both labor and time-consuming. In 2020, Apple implemented a Light Detection and Ranging (LiDAR) sensor in the new Apple iPad Pro (4th Gen) and iPhone Pro 12. Since then, access to LiDAR-generated 3D point clouds has become possible with consumer-level devices. In this study, an Apple iPad Pro was tested to produce 3D point clouds, and its performance was compared with a personal laser scanning (PLS) approach to estimate individual tree parameters in different forest types and structures. Reference data were obtained by traditional measurements on 21 circular forest inventory sample plots with a 7 m radius. The tree mapping with the iPad showed a detection rate of 97.3% compared to 99.5% with the PLS scans for trees with a lower diameter at a breast height (dbh) threshold of 10 cm. The root mean square error (RMSE) of the best dbh measurement out of five different dbh modeling approaches was 3.13 cm with the iPad and 1.59 cm with PLS. The data acquisition time with the iPad was approximately 7.51 min per sample plot; this is twice as long as that with PLS but 2.5 times shorter than that with traditional forest inventory equipment. In conclusion, the proposed forest inventory with the iPad is generally feasible and achieves accurate and precise stem counts and dbh measurements with efficient labor effort compared to traditional approaches. Along with future technological developments, it is expected that other consumer-level handheld devices with integrated laser scanners will also be developed beyond the iPad, which will serve as an accurate and cost-efficient alternative solution to the approved but relatively expensive TLS and PLS systems. Such a development would be mandatory to broadly establish digital technology and fully automated routines in forest inventory practice. Finally, high-level progress is generally expected for the broader scientific community in forest ecosystem monitoring, as the collection of highly precise 3D point cloud data is no longer hindered by financial burdens.
Comparison of Multi-GNSS Time and Frequency Transfer Performance Using Overlap-Frequency Observations
Authors: Zhang Pengfei , Tu Rui , Gao Yuping , Hong Ju , Han Junqiang , Lu Xiaochun
Published: August 2021

The modernized GPS, Galileo, and BeiDou global navigation satellite system (BDS3) offers new potential for time transfer using overlap-frequency (L1/E1/B1, L5/E5a/B2a) observations. To assess the performance of time and frequency transfer with overlap-frequency observations for GPS, Galileo, and BDS3, the mathematical models of single- and dual-frequency using the carrier-phase (CP) technique are discussed and presented. For the single-frequency CP model, the three-day average RMS values of the L5/E5a/B2a clock difference series were 0.218 ns for Galileo and 0.263 ns for BDS3, of which the improvements were 36.2% for Galileo and 43.9% for BDS3 when compared with the L1/E1/B1 solution at BRUX–PTBB. For the hydrogen–cesium time link BRUX–KIRU, the RMS values of the L5/E5a/B2a solution were 0.490 ns for Galileo and 0.608 ns for BDS3, improving Galileo by 6.4% and BDS3 by 12.5% when compared with the L1/E1/B1 solution. For the dual-frequency CP model, the average stability values of the L5/E5a/B2a solution at the BRUX–PTBB time link were 3.54 × 10−12 for GPS, 2.20 × 10−12 for Galileo, and 2.69 × 10−12 for BDS3, of which the improvements were 21.0%, 45.1%, and 52.3%, respectively, when compared with the L1/E1/B1 solution. For the BRUX–KIRU time link, the improvements were 4.2%, 30.5%, and 36.1%, respectively.
Retrieving Water Turbidity in Araucanian Lakes (South-Central Chile) Based on Multispectral Landsat Imagery
Authors: Rodríguez-López Lien , Duran-Llacer Iongel , González-Rodríguez Lisdelys , Cardenas Rolando , Urrutia Roberto
Published: August 2021

Remote sensing was used as an early alert tool for water clarity changes in five Araucanian Lakes in South-Central Chile. Turbidity records are scarce or unavailable over large and remote areas needed to fully understand the factors associated with turbidity, and their spatial-temporal representation remains a limitation. This work aimed to develop and validate empirical models to estimate values of turbidity from Landsat images and determine the spatial distribution of estimated turbidity in the selected Araucanian Lakes. Secchi disk depth measurements were linked with turbidity measurements to obtain a turbidity dataset. This in turn was used to develop and validate a set of empirical models to predict turbidity based on four single bands and 16 combination bands from 15 multispectral Landsat images. The best empirical models predicted turbidity over the range of 0.3–12.3 NTUs with RMSE values around 0.31–1.03 NTU, R2 (Index of Agreement IA) around 0.93–0.99 (0.85–0.97) and mean bias error (MBE) around (−0.36–0.44 NTU). Estimation maps to analyze the temporal-spatial turbidity variation in the lakes were constructed. Finally, it was found that the meteorological conditions may affect the variation of turbidity, mainly precipitation and wind speed. The data indicate that the turbidity has slightly increased in winter–spring. These models will be used in the future to reconstruct large datasets that allow analyzing transparency trends in those lakes.
Automated Dynamic Mascon Generation for GRACE and GRACE-FO Harmonic Processing
Authors: Mohajerani Yara , Shean David , Arendt Anthony , Sutterley Tyler C.
Published: August 2021

Commonly used mass-concentration (mascon) solutions estimated from Level-1B Gravity Recovery and Climate Experiment (GRACE) and GRACE Follow-On data, provided by processing centers such as the Jet Propulsion Laboratory (JPL) or the Goddard Space Flight Center (GSFC), do not give users control over the placement of mascons or inversion assumptions, such as regularization. While a few studies have focused on regional or global mascon optimization from spherical harmonics data, a global optimization based on the geometry of geophysical signal as a standardized product with user-defined points has not been addressed. Finding the optimal configuration with enough coverage to account for far-field leakage is not a trivial task and is often approached in an ad-hoc manner, if at all. Here, we present an automated approach to defining non-uniform, global mascon solutions that focus on a region of interest specified by the user, while maintaining few global degrees of freedom to minimize noise and leakage. We showcase our approach in High Mountain Asia (HMA) and Alaska, and compare the results with global uniform mascon solutions from range-rate data. We show that the custom mascon solutions can lead to improved regional trends due to a more careful sampling of geophysically distinct regions. In addition, the custom mascon solutions exhibit different seasonal variation compared to the regularized solutions. Our open-source pipeline will allow the community to quickly and efficiently develop optimized global mascon solutions for an arbitrary point or polygon anywhere on the surface of the Earth.
Investigation on the Relationship between Satellite Air Quality Measurements and Industrial Production by Generalized Additive Modeling
Authors: Tong Chao , Zhang Chengxin , Liu Cheng
Published: August 2021

The development of the green economy is universally recognized as a solution to natural resource shortages and environmental pollution. When exploring and developing a green economy, it is important to study the relationships between the environment and economic development. As opposed to descriptive and qualitative research without modeling or based on environmental Kuznets curves, quantitative relationships between environmental protection and economic development must be identified for exploration and practice. In this paper, we used the generalized additive model (GAM) regression method to identify relationships between atmospheric pollutants (e.g., NO2, SO2 and CO) from remote sensing and in situ measurements and their driving effectors, including meteorology and economic indicators. Three representative cities in the Anhui province, such as Hefei (technology-based industry), Tongling (resource-based industry) and Huangshan (tourism-based industry), were studied from 2016 to 2020. After eliminating the influence of meteorological factors, the relationship between air quality indexes and industrial production in the target cities was clearly observed. Taking Hefei, for example, when the normalized output of chemical products increases by one unit, the effect on atmospheric NO2 content increases by about 20%. When the normalized output of chemical product increases by one unit, the effect on atmospheric SO2 content increases by about 10%. When chemical and steel product outputs increase by one unit, the effect on atmospheric CO content increases by 25% and 20%, respectively. These results can help different cities predict local economic development trends varying by the changes in air quality and adjust local industrial structure.
The Algorithm of Determining an Anti-Collision Manoeuvre Trajectory Based on the Interpolation of Ship’s State Vector
Authors: Borkowski Piotr , Pietrzykowski Zbigniew , Magaj Janusz
Published: August 2021

The determination of a ship’s safe trajectory in collision situations at sea is one of the basic functions in autonomous navigation of ships. While planning a collision avoiding manoeuvre in open waters, the navigator has to take into account the ships manoeuvrability and hydrometeorological conditions. To this end, the ship’s state vector is predicted—position coordinates, speed, heading, and other movement parameters—at fixed time intervals for different steering scenarios. One possible way to solve this problem is a method using the interpolation of the ship’s state vector based on the data from measurements conducted during the sea trials of the ship. This article presents the interpolating function within any convex quadrilateral with the nodes being its vertices. The proposed function interpolates the parameters of the ship’s state vector for the specified point of a plane, where the values in the interpolation nodes are data obtained from measurements performed during a series of turning circle tests, conducted for different starting conditions and various rudder settings. The proposed method of interpolation was used in the process of determining the anti-collision manoeuvre trajectory. The mechanism is based on the principles of a modified Dijkstra algorithm, in which the graph takes the form of a regular network of points. The transition between the graph vertices depends on the safe passing level of other objects and the degree of departure from the planned route. The determined shortest path between the starting vertex and the target vertex is the optimal solution for the discrete space of solutions. The algorithm for determining the trajectory of the anti-collision manoeuvre was implemented in autonomous sea-going vessel technology. This article presents the results of laboratory tests and tests conducted under quasi-real conditions using physical ship models. The experiments confirmed the effective operation of the developed algorithm of the determination of the anti-collision manoeuvre trajectory in the technological framework of autonomous ship navigation.
Environmental Assessment of Recycling (EAoR) for Safe Recycling of Steelmaking Slag in the Republic of Korea: Applications, Leaching Test, and Toxicity
Authors: Lee Min-Yong , Kang Jang-Hyun , Hwang Dong-Gun , Yoon Young-Sam , Yoo Myung-Soo , Jeon Tae-Wan
Published: August 2021

Steel slag is a major waste product of the steelmaking process. Owing to its chemical composition, it can be reused as a raw material in steel mills and a substitute for aggregates in engineering. In 2016, the Republic of Korea (ROK) introduced the Environmental Assessment of Recycling (EAoR) system for the safe recycling of waste products, which divides recycling methods into either matrix contact or non-matrix contact types; numerous challenges have been raised regarding weaknesses in the matrix contact type. Consequently, the standards for matrix contact recycling of slag (inorganic waste) have become stricter, and the recycling applications have also become more diverse. This study investigates the treatment, recycling, and management of steel slag in the ROK. In 2019, the annual generation of slag in the ROK exceeded 23.03 million tons with a recycling rate of 98.3%, showing a high level of recycling, compared with that of the United States (81.3%), the European Union (87%), Australia (100%), and Japan (98.4%). However, a comparative analysis of overseas slag recycling systems and recycling standards found that the recycling applications and recycling standards of slag in the ROK were somewhat stricter than those in the European Union and the United States. Furthermore, an investigation comparing the applications of recycled slag in different countries showed that the ROK could expand its applications of recycled slag. The limitation of the EAoR system was that the excluding products, environmentally certified from Korean Standards in the EAoR regulations, might be attributing to environmental pollution. The leaching and toxicity tests for recycling application of steelmaking slag were evaluated and showed no significant negative effects. Lastly, there is an urgent need for environmental standards relating to slag that can be recycled as a product, and the recycling and environmental label certification for products should also be amended. In addition, the applications of steelmaking slag were necessary to partially extend according to the hazardous characteristics.
Safety Evaluation of Turbo-Roundabouts with and without Internal Traffic Separations Considering Autonomous Vehicles Operation
Authors: Giuffrè Tullio , Granà Anna , Trubia Salvatore
Published: August 2021

The paper presents a microsimulation approach for assessing the safety performance of turbo-roundabouts where Cooperative Autonomous Vehicles “CAVs” have been introduced into the traffic mix alongside conventional vehicles “CVs”. Based on the analysis of vehicle trajectories from VISSIM and subsequent analysis of traffic conflicts through the Surrogate Safety Assessment Model (SSAM), the research aims to evaluate the safety benefits of turbo-roundabouts where the lanes are physically separated by raised curbs, compared to roundabouts without such curbs. The paper will then describe the methodological path followed to build VISSIM models of turbo-roundabouts with and without raised curbs in order to calibrate the simulation models and estimate the potential conflicts when a higher percentage of CAVs are introduced into the traffic mix. A criterion has been also proposed for setting properly the principal SSAM filters. The results confirmed both higher safety levels for turbo-roundabouts equipped with raised lane dividers compared to turbo-roundabout solutions without curbs, and better safety conditions under the traffic mix of CVs and CAVs. Therefore, it follows that, in absence of crash data including CAVs, the surrogate measures of safety are the only approach in which the safety performance of any roundabout or road entity can be evaluated.
Innovative Approaches to Model Visualization for Integrated Management Systems
Authors: Pauliková Alena , Lestyánszka Škůrková Katarína , Kopilčáková Lucia , Zhelyazkova-Stoyanova Antoaneta , Kirechev Damyan
Published: August 2021

With a growing number of standards and their related requirements for manufacturers and/or service providers, there is a need to simplify their application process. The aim of this article is to propose a simplified implementation of multiple management system standards (MSSs) through visualization management. Results of visualization provide a perspective of interrelatedness of requirements of MSSs, and how they fit in the overall context. The three standards used in this project, defined as a complex triplet of integrated management systems (IMSs), are: Quality (QMS), Environment (EMS) and Event Sustainability (ESMS) Management Standards. Visualization is developed by creating clusters using a program intended for creating small world networks. This step is preceded by the creation of a database in a spreadsheet format for data mining, where the requirements are divided into specific and common ones. The main emphasis will be on facilitating the assessment of synergies. The resulting visualized composed cluster model of selected areas includes the clauses. It is possible to further extend the model by adding other standards, depending on needs of interested parties. In essence, the model is a part of visual process, and it simplifies, speeds up and clarifies managerial decision-making processes related to the implementation of the MSSs.
The COVID-19 Pandemic and Sustainable Life of Korean Adolescents: Exploring Gender Differences
Authors: Yu Seunghee , Choe Chung
Published: August 2021

To ensure that adolescents continue to lead healthy, well-adjusted lives—“sustainable lives”—after the COVID-19 pandemic, it is important to examine the latter’s impact on various aspects of their lives compared to the socio-cultural context before the outbreak. This study used national representative data on Korean adolescents to analyze the impact of the pandemic on adolescent life from various perspectives, with a focus on gender differences. Our findings confirm that during the pandemic physical activity and sitting time for study purposes decreased, while sleeping and sitting for purposes other than studying increased, with more pronounced changes among girls. Drinking and smoking decreased and boys experienced greater decreases. The findings also indicated that the pandemic generated positive outcomes for mental health: stress, sadness/despair, and suicidal ideation decreased, which was counterintuitive to our general expectations, with a greater impact seen among girls.
Predicting Parameters of Heat Transfer in a Shell and Tube Heat Exchanger Using Aluminum Oxide Nanofluid with Artificial Neural Network (ANN) and Self-Organizing Map (SOM)
Authors: Zolghadri Amir , Maddah Heydar , Ahmadi Mohammad Hossein , Sharifpur Mohsen
Published: August 2021

This study is a model of artificial perceptron neural network including three inputs to predict the Nusselt number and energy consumption in the processing of tomato paste in a shell-and-tube heat exchanger with aluminum oxide nanofluid. The Reynolds number in the range of 150–350, temperature in the range of 70–90 K, and nanoparticle concentration in the range of 2–4% were selected as network input variables, while the corresponding Nusselt number and energy consumption were considered as the network target. The network has 3 inputs, 1 hidden layer with 22 neurons and an output layer. The SOM neural network was also used to determine the number of winner neurons. The advanced optimal artificial neural network model shows a reasonable agreement in predicting experimental data with mean square errors of 0.0023357 and 0.00011465 and correlation coefficients of 0.9994 and 0.9993 for the Nusselt number and energy consumption data set. The obtained values of eMAX for the Nusselt number and energy consumption are 0.1114, and 0.02, respectively. Desirable results obtained for the two factors of correlation coefficient and mean square error indicate the successful prediction by artificial neural network with a topology of 3-22-2.
A Machine Learning Approach to Determine Airport Asphalt Concrete Layer Moduli Using Heavy Weight Deflectometer Data
Authors: Baldo Nicola , Miani Matteo , Rondinella Fabio , Celauro Clara
Published: August 2021

An integrated approach based on machine learning and data augmentation techniques has been developed in order to predict the stiffness modulus of the asphalt concrete layer of an airport runway, from data acquired with a heavy weight deflectometer (HWD). The predictive model relies on a shallow neural network (SNN) trained with the results of a backcalculation, by means of a data augmentation method and can produce estimations of the stiffness modulus even at runway points not yet sampled. The Bayesian regularization algorithm was used for training of the feedforward backpropagation SNN, and a k-fold cross-validation procedure was implemented for a fair performance evaluation. The testing phase result concerning the stiffness modulus prediction was characterized by a coefficient of correlation equal to 0.9864 demonstrating that the proposed neural approach is fully reliable for performance evaluation of airfield pavements or any other paved area. Such a performance prediction model can play a crucial role in airport pavement management systems (APMS), allowing the maintenance budget to be optimized.
Estimation of Travel Demand Models with Limited Information: Floating Car Data for Parameters’ Calibration
Authors: Croce Antonello Ignazio , Musolino Giuseppe , Rindone Corrado , Vitetta Antonino
Published: August 2021

This paper attempts to integrate data from models, traditional surveys and big data in a situation of limited information. The goal is to increase the capacity of transport planners to analyze, forecast, and plan passenger mobility. (Big) data are a precious source of information and substantial effort is necessary to filter, integrate, and convert big data into travel demand estimates. Moreover, data analytics approaches without demand models are limited because they allow: (a) the analysis of historical and/or real-time transport system configurations, and (b) the forecasting of transport system configurations in ordinary conditions. Without the support of travel demand models, the mere use of (big) data does not allow the forecasting of mobility patterns. The paper attempts to support traditional methods of transport systems engineering with new data sources from ICTs. By combining traditional data and floating car data (FCD), the proposed framework allows the estimation of travel demand models (e.g., trip generation and destination). The proposed method can be applied in a specific case of an area where FCD are available, and other sources of information are not available. The results of an application of the proposed framework in a sub-regional area (Calabria, southern Italy) are presented.
Optimal Scheduling of Hydro–Thermal–Wind–Photovoltaic Generation Using Lightning Attachment Procedure Optimizer
Authors: Mohamed Maha , Youssef Abdel-Raheem , Kamel Salah , Ebeed Mohamed , Elattar Ehab E.
Published: August 2021

This paper presents an effective solution for the short-term hydrothermal generation scheduling (STHS) problem using an integration of wind and photovoltaic power (PV) system. Wind and PV power are integrated into the power system to minimize the total fuel cost of thermal units. In this paper, the lightning attachment procedure optimization algorithm (LAPO) is employed to solve the STHS problem using the wind and PV power integration system. The proposed method is applied for solving five test systems with different characteristics, considering the valve-point loading impact of the thermal unit. The first and third test systems include hydro and thermal units only, and the rest of the systems consist of hydro and thermal units with integrating wind and PV power-generating units to inspect the effect of renewable energy sources in the selected test systems. The simulation results are compared with other studied methods. It is found that the proposed method is superior, and it has the ability to obtain the best solutions with respect to other optimization methods that are implemented to solve the STHS problem.
The Impact of Organic Traffic of Crowdsourcing Platforms on Airlines’ Website Traffic and User Engagement
Authors: Sakas Damianos P. , Reklitis Dimitrios P.
Published: August 2021

With airline companies increasingly relying on crowdsourcing websites to deploy their digital marketing strategies, marketeers and strategists seek to acquire an understanding of the factors affecting airlines’ organic traffic and user engagement. Such an understanding is acquired through the consideration of variables that influence a company’s organic traffic and user engagement and their correlation to each other. A three-stage data-driven analysis is used to examine the correlation between the foregoing variables and to consider strategies that can be implemented to optimize organic traffic and user engagement. The first section gathers data from five airline companies’ websites and five crowdsourcing websites over an interval of 180 days. The second stage creates an exploratory diagnostic model, through Fuzzy Cognitive Mapping, to visually illustrate the cause-and-effect correlations between the examined metrics. Finally, a predictive micro-level agent-based model simulates optimization strategies that can be used to improve organic traffic and user engagement. The results of this study, reveal that crowdsourcing organic traffic increases airline websites’ user engagement through paid campaigns, while a limited correlation was found to exist between the average duration of a user to organic traffic. The results of this study provide tangible digital marketing strategies which can be used by airline companies to improve the influence of their digital marketing strategies on their users.
Sustainability of Rural Tourism and Promotion of Local Development
Authors: Ivona Antonietta
Published: August 2021

Since the 1970s but with greater intensity in the 1980s, strong, social, economic, and cultural transformations have led to the post-Fordist or post-productivist countryside determining what researchers identify as “rural restructuring” [...]
The Direct Reduction of Iron Ore with Hydrogen
Authors: Li Shuo , Zhang Huili , Nie Jiapei , Dewil Raf , Baeyens Jan , Deng Yimin
Published: August 2021

The steel industry represents about 7% of the world’s anthropogenic CO2 emissions due to the high use of fossil fuels. The CO2-lean direct reduction of iron ore with hydrogen is considered to offer a high potential to reduce CO2 emissions, and this direct reduction of Fe2O3 powder is investigated in this research. The H2 reduction reaction kinetics and fluidization characteristics of fine and cohesive Fe2O3 particles were examined in a vibrated fluidized bed reactor. A smooth bubbling fluidization was achieved. An increase in external force due to vibration slightly increased the pressure drop. The minimum fluidization velocity was nearly independent of the operating temperature. The yield of the direct H2-driven reduction was examined and found to exceed 90%, with a maximum of 98% under the vibration of ~47 Hz with an amplitude of 0.6 mm, and operating temperatures close to 500 °C. Towards the future of direct steel ore reduction, cheap and “green” hydrogen sources need to be developed. H2 can be formed through various techniques with the catalytic decomposition of NH3 (and CH4), methanol and ethanol offering an important potential towards production cost, yield and environmental CO2 emission reductions.
The Impact of Work–Family Enrichment on Subjective Career Success through Job Engagement: A Case of Banking Sector
Authors: Awan Khalil , Ahmad Naveed , Naveed Rana Tahir , Scholz Miklas , Adnan Mohammad , Han Heesup
Published: August 2021

To survive in the current competitive era, organizations need continuous performance and development. The performance of any organization is linked with their employees’ performance. However, employees give their best when they see subjective career success in the organization. There are certain factors such as work–family enrichment (WFE) that affect employee’s subjective career success. The purpose of this research is to investigate the relationship between work–family enrichment and subjective career success through the mediating effect of work engagement. The data for this study were collected from various private banks located in a large metropolitan city through a self-administered questionnaire. The data were analyzed through the structural equation modeling (SEM) method. The results confirmed that work–family enrichment (WFE) positively affects subjective career success (SCS), and job engagement (JE) completely mediates this relationship. These findings will be helpful for banking sector policymakers to improve the subjective career success of personnel at the workplace through WFE and JE.
Multipurpose Retrofitting of a Tower Building in Brescia
Authors: Cardani Giuliana , Massetti Gian Ermes , Riva Davide
Published: August 2021

The paper aims to report a proper low-impact integrated study approach for the energy and seismic retrofitting of a tower building located in the city centre of Brescia (Italy). The building consists of a group of aggregate buildings built in the 1950s, from which emerged an 11-storey tower. It was built with the technology of the time by means of a perimeter and spine framed structure in reinforced concrete, double perimeter infill with a hollow brick air chamber, external cladding on the main fronts with small Botticino marble tiles. The building is registered by the Ministry of Cultural Heritage for its facade and is located in a seismic zone of category two. When work began, the construction was in a class three; thus, the whole project was updated to obtain the new seismic authorisation. The coating showed progressive decay, with dangerous structural instability of the heavy coating. The design team decided to adopt wider corrective action compared to the observed phenomenon, integrating it with a local seismic and global energy improvement through the insertion of a ventilated wall in the building and the realisation of accurate thermal and energy insulation systems. At the end of the intervention, this building became the first condominium in Italy in 2018, certified in class A and upgraded with sustainability criteria in which the application of the GBC Italy (Green Building Council) Condominiums protocol, currently in its final publication phase for the energy–environmental sustainability of condominiums, has been tested.
Migration and Climate Change Impacts on Rural Entrepreneurs in Nigeria: A Gender Perspective
Authors: Akinbami Catherine Abiola O.
Published: August 2021

Although the effects of climate change are universal, some groups are more negatively affected than others, which has raised global concerns. The most affected are families involved with agriculture or that use natural resources in rural areas as a means of livelihood. This study aimed to assess the responses of rural dwellers to climate change and migration, determine the extent of climate change as a driver of migration, assess the viability of migration as an option for climate change adaptation, and evaluate the gender perspective of migration and the impact of climate change on entrepreneurial development in rural areas. A qualitative method was employed to solicit responses from respondents in selected rural areas under four different vegetation zones through in-depth interviews and focus group discussions. Data were analyzed using Atlas.ti. A difference was found in gender reactions to migration due to socio-cultural factors and family responsibilities. In addition, different types of migration patterns were found to exist among men and women. The study also revealed that climate change is a major driver of migration, affects livelihood practices differently in the vegetation zones, and has a negative impact on the entrepreneurship development of the rural areas. Finally, this study provides insights into the effect of migration type on the entrepreneurship development by gender.
Analysis of Professionals’ and the General Public’s Perceptions of Passive Houses in Korea: Needs Assessment for the Improvement of the Energy Efficiency and Indoor Environmental Quality
Authors: Lee Joohyun , Shepley Mardelle McCuskey , Choi Jungmann
Published: August 2021

Despite the economic and environmental benefits of passive houses, their market penetration has been low, which is partially due to misperceptions regarding their cost. This study examined the perceptions of building-related professionals and the general public regarding Korean passive houses to explore strategies for spurring passive house concepts and practices. The participants took an online survey on their interest in and reasons to reside in passive houses and their expected construction costs. The results from two separate groups of participants, including 162 professionals and 130 members of the general public, were analyzed using descriptive and inferential statistics. Both the professional and general public groups expressed a strong interest in passive houses because of the comfortable and healthy indoor environment, energy efficiency, cost savings, and sustainability that they provide. However, the expected construction costs of passive houses were perceived differently by the two groups: They were believed to be less expensive by the professionals and more expensive by the public respondents. This difference seems to result from their prior knowledge or experience regarding passive houses. Both groups were willing to pay more and assumed that the high expected costs were related to the construction products, systems, and labor costs of passive houses. The results showed that the lack of information or education on passive houses could be a major barrier to accessing passive houses, especially with the general public, while the cost could pose less of a barrier to the overall growth of the Korean passive house market. Further efforts by the government and industry are needed in order to provide more educational programs and to identify and manufacture more reasonably priced construction materials.
Spatial-Temporal Integrated Measurement of the Efficiency of Urban Land Use in Yellow River Basin
Authors: Li Hengji , Qu Jiansheng , Wang Dai , Meng Peng , Lu Chenyu , Zeng Jingjing
Published: August 2021

As the product of natural process, land is an essential but nonrenewable resource for humankind. Urban land use efficiency directly reflects the coupling between urban systems and land use systems. It also serves as the key indicator for measuring land productivity and regional development quality. In this study, the land use efficiency of 65 county-level cities in the Yellow River Basin has been measured by applying the Data Envelope Analysis (DEA) and Spatial Autocorrelation Analysis methods. It makes up for the deficiency and defect of the existing research. The result indicates that in 2000~2018, the overall urban land use efficiency in 65 prefecture-level cities is unbalanced, with significant gaps between cities with high efficiency and low efficiency. In 2000~2018, the average urban land use efficiency in these 65 cities shows a tendency of declining. In 2000~2018, the spatial distribution of land use efficiency of these 65 cities indicates significant positive correlation, featured by the clustering of regions with high (low) efficiency. In terms of the spatial distribution of urban land use efficiency in the Yellow River Basin, it is marked by apparent spatial clustering. Specifically, from east to west, from coastal areas to inland regions, from downstream to upstream, the urban land use efficiency differs from high value areas to low value areas. On the whole, it is featured by high value in the east and low value in the west, while declining from downstream to upstream.
Effects of Exercise Intensity on Pedal Force Asymmetry during Cycling
Authors: Farrell John Wayland , Pribble Brian A. , Larson Rebecca D.
Published: August 2021

The purpose of the current investigation was to examine the effects of exercise intensity and a participant’s cycling experience on asymmetry in pedal forces during cycling. Participants were classified as cycling experienced (CE) or non-cycling experienced (NCE) based on self-reported training history. Participants completed an incremental cycling test via a cycle ergometer with inspired and expired gases, capillary blood lactate and pedaling forces collected throughout the test. Group X exercise intensity comparisons were analyzed at workloads corresponding to 2 mmol/L and 4 mmol/L for the blood lactate accumulation and peak power output, respectively. No Group X exercise intensity interactions for any variables (p > 0.05) were observed. The main effect on the exercise intensity was observed for absolute (p = 0.000, η2 = 0.836) and relative (p = 0.000, η2 = 0.752) power outputs and pedal force effectiveness (PFE) (p = 0.000, η2 = 0.728). The main effect for the group was observed for absolute (p = 0.007, η2 = 0.326) and relative (p = 0.001, η2 = 0.433) power outputs, the absolute difference between the lower limbs in power production (p = 0.047, η2 = 0.191), the peak crank torque asymmetry index (p = 0.031, η2 = 0.222) and the PFE (p = 0.014, η2 = 0.280). The exercise intensity was observed to have no impact on asymmetry in pedaling forces during cycling.
Automatic, Illumination-Invariant and Real-Time Green-Screen Keying Using Deeply Guided Linear Models
Authors: Li Hanxi , Zhu Wenyu , Jin Haiqiang , Ma Yong
Published: August 2021

The conventional green screen keying method requires users’ interaction to guide the whole process and usually assumes a well-controlled illumination environment. In the era of “we-media”, millions of short videos are shared online every day, and most of them are produced by amateurs in relatively poor conditions. As a result, a fully automatic, real-time, and illumination-robust keying method would be very helpful and commercially promising in this era. In this paper, we propose a linear model guided by deep learning prediction to solve this problem. The simple, yet effective algorithm inherits the robustness of the deep-learning-based segmentation method, as well as the high matting quality of energy-minimization-based matting algorithms. Furthermore, thanks to the introduction of linear models, the proposed minimization problem is much less complex, and thus, real-time green screen keying is achieved. In the experiment, our algorithm achieved comparable keying performance to the manual keying software and deep-learning-based methods while beating other shallow matting algorithms in terms of accuracy. As for the matting speed and robustness, which are critical for a practical matting system, the proposed method significantly outperformed all the compared methods and showed superiority over all the off-the-self approaches.
Symmetric and Asymmetric Diffusions through Age-Varying Mixed-Species Stand Parameters
Authors: Rupšys Petras , Petrauskas Edmundas
Published: August 2021

(1) Background: This paper deals with unevenly aged, whole-stand models from mixed-effect parameters diffusion processes and Voronoi diagram points of view and concentrates on the mixed-species stands in Lithuania. We focus on the Voronoi diagram of potentially available areas to tree positions as the measure of the competition effect of individual trees and the tree diameter at breast height to relate their evolution through time. (2) Methods: We consider a bivariate hybrid mixed-effect parameters stochastic differential equation for the parameterization of the diameter and available polygon area at age to ensure a proper description of the link between them during the age (time) span of a forest stand. In this study, the Voronoi diagram was used as a mathematical tool for the quantitative characterization of inter-tree competition. (3) Results: The newly derived model considers bivariate correlated observations, tree diameter, and polygon area arising from a particular stand and enables defining equations for calculating diameter, polygon-area, and stand-density predictions and forecasts. (4) Conclusions: From a statistical point of view, the newly developed models produced acceptable statistical measures of predictions and forecasts. All the results were implemented in the Maple computer algebra system.
A Framework for Exploring Churches/Monuments/Museums of Byzantine Cultural Influence Exploiting Immersive Technologies in Real-Time Networked Environments
Authors: Kontopanagou Katerina , Tsipis Athanasios , Komianos Vasileios
Published: August 2021

The unique art that was developed in Byzantine times is widely accepted as a precursor to the Renaissance and is still evident in monuments either from or influenced by the Byzantium. Visiting such a site is a unique experience due to the lavishly painted interior for both tourists and scholars. Taking advantage of the emerging 5G technologies, cloud/fog computing, and Augmented/Mixed Reality mechanisms, a common smart device (e.g., smartphone, tablet) could be employed to give a better experience to the end-users. The proposed framework is intended to provide visitors with interpretative information regarding the visited monuments and their paintings. Under the framework introduced in this paper, camera input is uploaded to a cloud/fog computing infrastructure where appropriate algorithms and services provide monument and painting recognition and the mobile application retrieves and projects the related information. In addition, the designed immersive user interfaces assist visitors in contributing in cases of monuments and paintings for which no available information exists. This paper presents the state of the art in approaches for immersive experiences in Digital Culture, reviews the current image recognition approaches and their suitability for Byzantine paintings, proposes interaction techniques appropriately designed for observation and interaction of paintings, and discusses the overall framework architecture that is needed to support the described functionality while stressing the challenging issues of the above aspects thus paving the road for future work and providing guidelines for a test-bed implementation.