bluuebunny/crossref_metadata_2025 huggingface dataset:
Being and Becoming among Young People Revealed through the Experience of COVID-19
Authors: Andersen Aida Hougaard , Viftrup Dorte T. , Bank Mads
Published: December 2022

The lockdown of society arising out of COVID-19 can be viewed as a microscope exposing the existential conditions and challenges of young people’s lives and their manner of dealing with crises. This study employs a qualitative research methodology using semi-structured interviews of 19 young people, aged 16–17 years, after the second COVID-19 lockdown in Denmark, March 2021. An analytical strategy was applied using reflexive methodology taking concepts from Søren Kierkegaard, Martin Buber, and Martin Heidegger to interpret the participants’ experiences of existential themes important to them, such as identity. Drawing on Kierkegaard’s idea of different “interpretive spheres” of life, we suggest that crisis revealed a disruption of the young peoples’ performance-oriented approach to life that made it possible to reflect and relate to themselves through aesthetic, ethical and self-transcending spheres. We suggest that the relationship to the other—as an ethical obligation, as an affective Being-with, and as something bigger than themselves—is crucial to the ways in which young people handle and relate to existential challenges and the experience of being and becoming themselves. The findings contribute to education and well-being, pointing out mental challenges among young people and stressing an existential focus as a priority in educational practice.
Continuing Risks
Authors: Constantinescu Corina , Guillen Montserrat , Steffensen Mogens
Published: December 2022

Risks will soon celebrate its tenth anniversary [...]
Performance Assessment of Multi-GNSS Real-Time Products from Various Analysis Centers
Authors: Yu Chao , Zhang Yize , Chen Junping , Chen Qian , Xu Kexin , Wang Bin
Published: December 2022

The performance of real-time precise point positioning (PPP) relies primarily on the availability and quality of orbit and clock corrections. In this research, we collected data streams from 12 real-time mount points of IGS Real-Time Service (RTS) or analysis centers for a one-month period and conducted a performance assessment, including product latency and data availability, accuracy of orbit, clock and positioning performance. The epoch availability of GPS, GLONASS, Galileo and BDS was more than 98.5%, 95.79%, 94.20% and 85.9%, respectively. In addition, the orbit and clock errors of different real-time corrections was investigated. Then, PPP in static and kinematic for 16 IGS stations was conducted. The results show the real-time PPP for different products has a longer convergence time and a slightly worse accuracy than those of the post-processing PPP. For static PPP over 24 h, the real-time products of WHU had the best performance, with a mean RMSE of 1.0 cm in the horizontal and vertical directions and a median convergence time of 12.0 min. The products of CAS had the faster convergence speed due to the shortest product latency. Regarding real-time kinematic PPP for GPS only in an hourly batch, the real-time products of WHU and ESA performed best with a mean RMSE of 10.8 cm and 9.5 cm in the horizontal and vertical directions, respectively. Additionally, the PPP for different real-time products with the multi-GNSS combination obtained higher accuracy than those with GPS only in post-processing or real-time mode, and the PPP with the GPS/GLONASS/Galileo/BDS combination had the fastest convergence speed and best positioning performance. The hourly based kinematic PPP results of CAS, DLR, GFZ and WHU with the GREC combination had positioning errors smaller than 5.2 cm.
Near-UV Pulsations in the Aurora Region Measured by Orbital Telescope TUS during High-Intensity and Long-Duration Continuous AE Activity
Authors: Klimov Pavel , Kalegaev Vladimir , Sigaeva Ksenia , Ivanova Alexandra , Antonyuk Grigory , Benghin Viktor , Zolotarev Ivan
Published: December 2022

Tracking Ultraviolet Set-up (TUS) on board the Lomonosov satellite measured the UV intensity pulsations in the auroral region. Sixty-four events with pulsations were registered during two measurement periods from 26 December 2016–10 January 2017 and 8–15 November 2017. During both periods, a high-intensity, long-duration, continuous auroral activity (HILDCAA) was detected. Simultaneous measurements in LEO by Lomonosov (DEPRON detector) and Meteor-M2 satellites show the enhanced fluxes of the trapped and precipitated energetic electrons in the region of the Earth’s outer radiation belt during these periods. We found that most of the UV-events correspond to energetic electron (E > 100 keV) precipitation. One can suggest that particles of these and higher energies cause a pulsating emission relatively deep in the atmosphere.
Surface Soil Moisture Retrieval on Qinghai-Tibetan Plateau Using Sentinel-1 Synthetic Aperture Radar Data and Machine Learning Algorithms
Authors: Dong Leilei , Wang Weizhen , Jin Rui , Xu Feinan , Zhang Yang
Published: December 2022

Soil moisture is a key factor in the water and heat exchange and energy transformation of the ecological systems and is of critical importance to the accurate obtainment of the soil moisture content for supervising water resources and protecting regional and global eco environments. In this study, we selected the soil moisture monitoring networks of Naqu, Maqu, and Tianjun on the Qinghai–Tibetan Plateau as the research areas, and we established a database of surface microwave scattering with the AIEM (advanced integral equation model) and the mathematical expressions for the backscattering coefficient, soil moisture, and surface roughness of the VV and VH polarizations.We proposed the soil moisture retrieval models of empirical and machine learnings algorithms (backpropagation neural network (BPNN), support vector machine (SVM), K-nearest neighbors (KNN), and random forest (RF)) for the ascending and descending orbits using Sentinel-1 and measurement data, and we also validated the accuracies of the retrieval model in the research areas. According to the results, there is a substantial logarithmic correlation among the backscattering coefficient, soil moisture, and combined roughness. Generally, we can use empirical models to estimate the soil moisture content, with an R² of 0.609, RMSE of 0.08, and MAE of 0.064 for the ascending orbit model and an R² of 0.554, RMSE of 0.086, and MAE of 0.071 for the descending orbit model. The soil moisture contents are underestimated when the volumetric water content is high. The soil moisture retrieval accuracy is improved with machine learning algorithms compared to the empirical model, and the performance of the RF algorithm is superior to those of the other machine learning algorithms. The RF algorithm also achieved satisfactory performances for the Maqu and Tianjun networks. The accuracies of the inversion models for the ascending orbit in the three soil moisture monitoring networks were better than those for the descending orbit.
The Troposphere-to-Stratosphere Transport Caused by a Rossby Wave Breaking Event over the Tibetan Plateau in Mid-March 2006
Authors: Zhu Jinyao , Jin Xin , Shi Chunhua , Chen Dan
Published: December 2022

Based on reanalysis data, satellite ozone concentration observations, and a Lagrangian trajectory simulation, a Rossby wave breaking (RWB) event and its effect on stratosphere–troposphere exchange (STE) over the Tibetan Plateau in mid-March 2006 were investigated. Results showed that the increased eddy heat flux from the subtropical westerly jet magnified the amplitude of the Rossby wave, which contributed to the occurrence of the cyclonic RWB event. The quasi-horizontal cyclonic motion of the isentropic potential vorticity in the RWB cut the tropical tropospheric air mass into the extratropical stratosphere, completing the stratosphere–troposphere mass exchange. Meanwhile, the tropopause folding zone extended polewards by 10° of latitude and the tropospheric air mass escaped from the tropical tropopause layer into the extratropical stratosphere through the tropopause folding zone. The particles in the troposphere-to-stratosphere transport (TST) pathway migrated both eastwards and polewards in the horizontal direction, and shifted upwards in the vertical direction. Eventually, the mass of the TST particles reached about 3.8 × 1014 kg, accounting for 42.2% of the particles near the tropopause in the RWB event. The rest of the particles remained in the troposphere, where they moved eastwards rapidly along the westerly jet and slid down in the downstream upper frontal zone.
Evaluation of Numerous Kinetic Energy-Rainfall Intensity Equations Using Disdrometer Data
Authors: Van Linh Nguyen , Le Xuan-Hien , Nguyen Giang V. , Yeon Minho , Do May-Thi Tuyet , Lee Giha
Published: December 2022

Calculating rainfall erosivity, which is the capacity of rainfall to dislodge soil particles and cause erosion, requires the measurement of the rainfall kinetic energy (KE). Direct measurement of KE has its own challenges, owing to the high cost and complexity of the measuring instruments involved. Consequently, the KE is often approximated using empirical equations derived from rainfall intensity (Ir) inputs in the absence of such instruments. However, the KE–Ir equations strongly depend on local climate patterns and measurement methods. Therefore, this study aims to compare and evaluate the efficacy of 27 KE–Ir equations with observed data. Based on a re-analysis, we also propose an exponential KE–Ir equation for the entire Korean site, and the spatial distribution of its parameter in the equation is also discussed. In this investigation, we used an optical disdrometer (OTT Parsivel2) to gather data in Sangju City (Korea) between June 2020 and December 2021. The outputs of this study are shown as follows: (1) The statistically most accurate estimates of KE expenditure and KE content in Sangju City are obtained using power-law equations given by Sanchez-Moreno et al. and exponential equations published by Lee and Won, respectively. (2) The suggested KE–Ir equation applied to the entire Korean site exhibits a comparable general correlation with the observed data. The parameter maps indicate a high variance in geography.
Forest Height Inversion Based on Time–Frequency RVoG Model Using Single-Baseline L-Band Sublook-InSAR Data
Authors: Wang Lei , Zhou Yushan , Shen Gaoyun , Xiong Junnan , Shi Hongtao
Published: December 2022

The interferometric synthetic aperture radar (InSAR) technique based on time–frequency (TF) analysis has great potential for mapping the forest canopy height model (CHM) at regional and global scales, as it benefits from the additional InSAR observations provided by the sublook decomposition. Meanwhile, due to the wider swath and higher spatial resolution of single-polarization data, InSAR has a higher observation efficiency in comparison with PolInSAR. However, the accuracy of the CHM inversion obtained by the TF-InSAR method is attenuated by its inaccurate coherent scattering modeling and uncertain parameter calculation. Hence, a new approach for CHM estimation based on single-baseline InSAR data and sublook decomposition is proposed in this study. With its derivation of the coherent scattering modeling based on the scattering matrix of sublook observations, a time–frequency based random volume over ground (TF-RVoG) model is proposed to describe the relationship between the sublook coherence and the forest biophysical parameters. Then, a modified three-stage method based on the TF-RVoG model is used for CHM retrieval. Finally, the two-dimensional (2-D) ambiguous error of pure volume coherence caused by residual ground scattering and temporal decorrelation is alleviated in the complex unit circle. The performance of the proposed method was tested with airborne L-band E-SAR data at the Krycklan test site in Northern Sweden. Results show that the modified three-stage method provides a root-mean-square error (RMSE) of 5.61 m using InSAR and 14.3% improvement over the PolInSAR technique with respect to the classical three-stage inversion result. An inversion accuracy of RMSE = 2.54 m is obtained when the spatial heterogeneity of CHM is considered using the proposed method, demonstrating a noticeable improvement of 32.8% compared with results from the existing method which introduces the fixed temporal decorrelation factor.
Study of Efficiency of Capacity Gradient Ion-Exchange Stationary Phases
Authors: Horváth Szabolcs , Lukács Diána , Farsang Evelin , Horváth Krisztián
Published: December 2022

Highly efficient columns are necessary for the modern analytical applications of liquid chromatography. In this work, the separation efficiency of ion-exchange capacity gradient stationary phases combined with eluent concentration gradient was studied by a theoretical approach. In the course of our work three different scenarios of capacity gradients were used with different shapes (linear, convex and concave). The resolutions of different gradient columns were calculated for each scenario. As a reference, a uniform column was considered, which had the same analysis time as the non-uniform column. In the case of separation of ions with same charges, the gradient column offered only a marginal advantage compared to the uniform column due to the bandwidth compression caused by the capacity gradient. In the case of ions with different charges, however, the advantage of the gradient column was more significant. This was mainly due to the increased retention time difference of solutes. Ion-exchange capacity gradient columns may be a new way to separate ions more efficiently.
Relative Contribution of Anxiety, Depression and Difficulties in Emotional Regulation in Forecasting Emotional Sensitivity of Autistic Children’s Mothers
Authors: Gobrial Ereny , Shoeib Ali
Published: December 2022

This study aimed to determine the relative contribution of anxiety, depression, and difficulties in emotional regulation (DER) on emotional sensitivity (ES) among mothers of autistic children. Methods: Ninety-one mothers (Mean age= 36.4 years, SD = 6.95) participated in this study. GAD-7, HDRS-17, and emotional sensitivity scales were applied in this study. DER was measured with difficulties of emotion regulation scale. Results: Findings indicated that mothers of autistic children exhibit high anxiety, depression, DER, and ES levels. These findings provide evidence of a unique association between ES and anxiety and depression. Findings highlighted that ES is directly related to anxiety and depression, while DER had no influence on ES among these mothers. Conclusions: The findings advance our understanding of how ES is influenced by the most prevalent emotional problems (anxiety and depression) among mothers of autistic children. The results were clear about the unique role of depression and anxiety in predicting the risk for ES. These findings highlight the importance of screening for anxiety and depression in autistic children’s mothers to avoid elevated levels of ES and potentially to protect the mother’s psychological well-being.
Digital News and Political Tweets in the Lower Austrian Municipal Elections: A Case Study on Digital Journalism and Political Communication
Authors: Lampoltshammer Thomas J. , De Luca Gabriele , Thurnay Lőrinc
Published: December 2022

In this paper, we study the problem of agenda setting by news media in relation to the political discourse by politicians at the time of local elections. We first evaluate the applicability of the agenda-setting theory against the theory of policy agenda building to determine the possible alternative directions for constructing a political agenda at the time of elections. Namely, we identify a non-linear interaction between news organizations, politicians, and the general public during the electoral campaign. This interaction, in turn, shapes the dynamic evolution of the public discourse concerning politics, and it is characterized by high sensitivity to initial conditions and non-linearity. Then, we attempt to identify the presence of an evolutionary trajectory of the political discourse in Lower Austria at the time of elections by observing whether, as the time of an election approaches, the interaction between news organizations and politicians flattens and becomes more linear without the news or the politicians causing the agenda of the other to be set accordingly. Finally, we provide a new methodology for identifying the topics contained in such an agenda so that empirical verification of the proposed hypothesis becomes possible.
Estimating Smoothness and Optimal Bandwidth for Probability Density Functions
Authors: Politis Dimitris N. , Tarassenko Peter F. , Vasiliev Vyacheslav A.
Published: December 2022

The properties of non-parametric kernel estimators for probability density function from two special classes are investigated. Each class is parametrized with distribution smoothness parameter. One of the classes was introduced by Rosenblatt, another one is introduced in this paper. For the case of the known smoothness parameter, the rates of mean square convergence of optimal (on the bandwidth) density estimators are found. For the case of unknown smoothness parameter, the estimation procedure of the parameter is developed and almost surely convergency is proved. The convergence rates in the almost sure sense of these estimators are obtained. Adaptive estimators of densities from the given class on the basis of the constructed smoothness parameter estimators are presented. It is shown in examples how parameters of the adaptive density estimation procedures can be chosen. Non-asymptotic and asymptotic properties of these estimators are investigated. Specifically, the upper bounds for the mean square error of the adaptive density estimators for a fixed sample size are found and their strong consistency is proved. The convergence of these estimators in the almost sure sense is established. Simulation results illustrate the realization of the asymptotic behavior when the sample size grows large.
Potential Phytoremediation of Aquatic Macrophyte Species for Heavy Metals in Urban Environments in the Southern Area of Brazil
Authors: Demarco Carolina Faccio , Afonso Thays França , Pieniz Simone , Selau Filipe Carlos , Machado Fernando Machado , Andreazza Robson
Published: December 2022

This research investigated four different species of aquatic macrophytes with natural occurrence in an urban environment highly anthropized in Southern Brazil. The aim of the research was to compare the phytoremediation potential among the species E. anagallis, H. grumosa, H. ranunculoides, and S. montevidensis through Pearson´s correlation analysis and cluster analysis, using the heavy metal content identified through HNO3 - HClO4 and phytoremediation indexes. The results highlighted the bioconcentration factor (BCF) of H. ranunculoides, with outstanding results for Cu BCF = 667.09, Zn BCF = 149.93, Cd BCF = 26.85, Cr BCF = 31.77, Ni BCF = 35.47, and Pb BCF= 126.29. Additionally, H. grumosa and S. montevidensis were also highlighted, considering the potential phytoremoval (g ha−1). Therefore, this study demonstrates the tolerance and potential for removal of heavy metals Cu, Cr, Cd, Pb, Ni, and Zn by the evaluated aquatic macrophyte species and elucidates the outstanding potential of application in phytoremediation purposes.
Simulation Study on Topology Characteristics and Cascading Failure of Hefei Subway Network
Authors: Yin Xiaohong , Wu Jiakun
Published: December 2022

The structural characteristics and robustness of subway networks are important for improving the safety and efficiency of subway operations. Based on complex network theory, this study analyzed the structural characteristics of the Hefei subway network and evaluated its robustness after suffering from accidents. Specifically: (1) A model of the Hefei subway network was established using the space-L method, and its topological structural characteristics were quantitatively analyzed; (2) An improved cascading failure simulation model was established, and a node importance evaluation system was developed to identify the critical nodes in the Hefei subway network; (3) A simulation analysis was conducted to evaluate the robustness of the Hefei subway network under different scenarios. The results show that the Hefei subway network is different from a scale-free network and small-world network, and the structure was most severely damaged when facing attacks against critical nodes in the cascading failure scenario. Moreover, as the value of the parameter of the control node capacity in the cascade failure model varied, the degree of damage to the subway network also varied considerably. We believe that the results obtained from the study could provide a reference for the construction and planning of the subway network.
The Impact of Institutional Friction Cost on Economic Growth: Evidence from OECD Countries
Authors: Zhou Qingjie , Yu Dongyao , Xu Feng , Sun Jiamin
Published: December 2022

The institutional environment is critical to economic growth. A favorable business environment can reduce unnecessary transaction costs. This study examined the impact of institutional friction costs on economic growth, based on panel data for 38 OECD countries from 2004 to 2020. The contribution of this paper is that, first, we explore methods to measure the cost of institutional friction, and the measurements show that the total cost of institutional friction tends to be lower in high-income countries than in upper-middle-income countries. Second, we find that reducing the cost of institutional friction helps to promote economic growth through an empirical fixed-effects analysis approach with panel data. The empirical results remain significant after robustness and endogeneity tests. Third, we find that the effect of institutional friction costs on economic growth is more pronounced in high-income countries and even more pronounced in countries with inefficient governments. Fourth, the mediation effect test finds that institutional friction costs affect economic growth by increasing firm innovation. Overall, reducing the costs of institutional friction helps promote economic growth, and this study suggests that policy makers in each country should develop measures to reduce the costs of institutional friction to improve efficiency and economic development.
Prediction of the Discharge Coefficient in Compound Broad-Crested-Weir Gate by Supervised Data Mining Techniques
Authors: Nouri Meysam , Sihag Parveen , Kisi Ozgur , Hemmati Mohammad , Shahid Shamsuddin , Adnan Rana Muhammad
Published: December 2022

The current investigation evaluated the discharge coefficient of a combined compound rectangular broad-crested-weir (BCW) gate (Cdt) using the computational fluid dynamics (CFD) modeling approach and soft computing models. First, CFD was applied to the experimental data and 61 compound BCW gates were numerically simulated by resolving the Reynolds-averaged Navier–Stokes equations and stress turbulence models. Then, six data-driven procedures, including M5P tree, random forest (RF), support vector machine (SVM), Gaussian process (GP), multimode ANN and multilinear regression (MLR) were used for estimating the coefficient of discharge (Cdt) of the weir gates. The results showed the superlative accuracy of the SVM model compared to M5P, RF, GP and MLR in predicting the discharge coefficient. The sensitivity investigation revealed the h1/H as the most effective parameter in predicting the Cdt, followed by the d/p, b/B0, B/B0 and z/p. The multimode ANN model reduced the root mean square error (RMSE) of M5P, RF, GP, SVM and MLR by 37, 13, 6.9, 6.5 and 32%, respectively. The graphical inspection indicated the multimode ANN model as the most suitable for predicting the Cdt of a BCW gate with minimum RMSE and maximum correlation.
Comparison between MICP-Based Bio-Cementation Versus Traditional Portland Cementation for Oil-Contaminated Soil Stabilisation
Authors: Yin Jie , Wu Jian-Xin , Zhang Ke , Shahin Mohamed A. , Cheng Liang
Published: December 2022

In recent years, oil spills and leakages have often occurred during oil exploration, transportation, handling, usage, and processing, causing serious global environmental problems. Microbially-induced carbonate precipitation (MICP) is an emerging green, environmentally friendly, and sustainable technology that has proven to be a promising alternative for soil stabilisation. This paper provides a comparison between the mechanical performance of oil-polluted sand treated with biocement and traditional Portland cement. A series of laboratory tests, including permeability, unconfined compressive strength (UCS), and triaxial consolidated undrained (CU) tests, was conducted. Even though oil contamination deteriorates the bonding strength of treated soil for both biocement and Portland cement soils, the biocement-treated oil-contaminated sand was found to achieve higher strength (up to four times) than cement-treated soil in the presence of similar content of cementing agent. After eight treatment cycles, the UCS value of oil-contaminated sand treated with biocement reached 1 MPa, demonstrating a high potential for oil-contaminated soil stabilisation in regions of oil spills and leakages.
Deep-Reinforcement-Learning-Based Active Disturbance Rejection Control for Lateral Path Following of Parafoil System
Authors: Zheng Yuemin , Tao Jin , Sun Qinglin , Sun Hao , Chen Zengqiang , Sun Mingwei , Duan Feng
Published: December 2022

The path-following control of the parafoil system is essential for executing missions, such as accurate homing and delivery. In this paper, the lateral path-following control of the parafoil system is studied. First, considering the relative motion between the parafoil canopy and the payload, an eight-degree-of-freedom (DOF) model of the parafoil system is constructed. Then, a guidance law containing the position deviation and heading angle deviation is proposed. Moreover, a linear active disturbance rejection controller (LADRC) is designed based on the guidance law to allow the parafoil system to track the desired path under internal unmodeled dynamics or external environmental disturbances. For the adaptive tuning of the controller parameters, a deep Q-network (DQN) is applied to the LADRC-based path-following control system, and the controller parameters can be adjusted in real time according to the system’s states. Finally, the effectiveness of the proposed method is applied to a parafoil system following circular and straight paths in an environment with wind disturbances. The simulation results show that the proposed method is an effective means to realize the lateral path-following control of the parafoil system, and it can also promote the development of intelligent controllers.
Weather Impact on Solar Farm Performance: A Comparative Analysis of Machine Learning Techniques
Authors: Gopi Ajith , Sharma Prabhakar , Sudhakar Kumarasamy , Ngui Wai Keng , Kirpichnikova Irina , Cuce Erdem
Published: December 2022

Forecasting the performance and energy yield of photovoltaic (PV) farms is crucial for establishing the economic sustainability of a newly installed system. The present study aims to develop a prediction model to forecast an installed PV system’s annual power generation yield and performance ratio (PR) using three environmental input parameters: solar irradiance, wind speed, and ambient air temperature. Three data-based artificial intelligence (AI) techniques, namely, adaptive neuro-fuzzy inference system (ANFIS), response surface methodology (RSM), and artificial neural network (ANN), were employed. The models were developed using three years of data from an operational 2MWp Solar PV Project at Kuzhalmannam, Kerala state, India. Statistical indices such as Pearson’s R, coefficient of determination (R2), root-mean-squared error (RMSE), Nash-Sutcliffe efficiency (NSCE), mean absolute-percentage error (MAPE), Kling-Gupta efficiency (KGE), Taylor’s diagram, and correlation matrix were used to determine the most accurate prediction model. The results demonstrate that ANFIS was the most precise performance ratio prediction model, with an R2 value of 0.9830 and an RMSE of 0.6. It is envisaged that the forecast model would be a valuable tool for policymakers, solar energy researchers, and solar farm developers.
Risk Assessment of Innovation Prototype for the Example Hydraulic Cylinder
Authors: Deptuła Anna M. , Stosiak Michał , Deptuła Adam , Lubecki Marek , Karpenko Mykola , Skačkauskas Paulius , Urbanowicz Kamil , Danilevičius Algimantas
Published: December 2022

This paper presents both an example of the innovation prototype risk assessment and the universal way of conduct in assessing such solutions. For this purpose, the authors proposed a prototype risk assessment method based on the assumptions of the SWOT and TOWS analysis and the multi-criteria technical innovation risk assessment method. In the assumptions of the developed method, an account was taken of the conclusions resulting from the prospect theory. A symptom of this action was, e.g., a characterization of the team of experts (working on the prototype) in terms of their individual personality traits and mind (which has not been used so far in practical methods of assessing risk). As a result of the conducted assessment (for an innovative hydraulic cylinder prototype), the innovation prototype risk was determined as low, which was presented both on the map of domination and the map of risk assessment for this prototype. The procedure presented in the paper was planned so as to ensure that, after the prototype moves to the commercialization phase, it will be possible, on the basis of the already made calculations, to apply the full risk assessment dedicated for technical innovations with ease. This gives it a universal nature.
Coordinated Decision-Making in Embedded Supply Chain from a Sustainable Development Perspective
Authors: Dong Fang , Shi Chengdong , Yu Weitong
Published: December 2022

Government carbon policies and consumers’ preferences are forcing companies to reduce their carbon emissions. Due to financial and technical constraints, carbon-dependent manufacturers are seeking embedded services from energy service companies. By considering these government carbon policies and consumer preferences, this paper constructs a revenue-sharing contract and a two-part contract model for an embedded low-carbon service supply chain using the Stackelberg game to investigate the contractual coordination between the manufacturer and energy service company and their optimal decision making. The equilibrium decisions and the selection of contracts in the supply chain with different parameter levels were obtained. The model’s validity was verified through numerical simulation analysis, and the impacts of the main parameters on the equilibrium decisions and expected utility for the supply chain were analyzed. The results showed that both contracts would enable manufacturers and low-carbon service providers to achieve profit maximization goals when the parameters meet certain constraints. Changes in consumers’ low-carbon and low-price preferences can cause manufacturers to change their business strategies. In addition, the level of technology of ESCOs affects the selection of the type of contract between manufacturers and energy service companies. The findings described in this paper can provide management insights for manufacturers regarding carbon reduction in practice.
The Influence of Sociodemographic Characteristics and the Experience of Recreational Divers on the Preference for Diving Sites
Authors: Zhang Ke , Ma Anson T. H. , Lam Theresa W. L. , Fang Wei , Cheung Lewis T. O.
Published: December 2022

Understanding the preferences of scuba divers is crucial for authorities to establish appropriate management plans and for service providers to offer a wide range of recreation opportunities to promote long-term industrial sustainability. This study categorized diving preferences into two subgroups (physical and biological) to explore the association between diving preferences and divers’ sociodemographic characteristics, as well as diving experiences through multiple regression analysis. Questionnaire surveys were administered, with 398 completed responses successfully collected from diving hotspots in Hong Kong. Results revealed that divers’ sociodemographic status, particularly monthly salary, could affect their physical and biological preferences. Meanwhile, divers’ diving experience was found to be a significant predictor in figuring out their biological preferences. However, no relationship between diving experience and physical preference was identified in this study. These results could inform management authorities in implementing ecological and environmental protection because biological conditions are considered the most attractive motivation for divers to dive in Hong Kong. Similarly, these results may help managers better understand divers’ recreation needs based on different sociodemographic characteristics and diving experiences to create diverse recreation opportunities while enhancing their satisfaction by avoiding the negative impacts associated with identified preference attributes.
Investigation of the Level of Knowledge in Different Countries about Edible Insects: Cluster Segmentation
Authors: Guiné Raquel P. F. , Florença Sofia G. , Costa Cristina A. , Correia Paula M. R. , Ferreira Manuela , Cardoso Ana P. , Campos Sofia , Anjos Ofélia , Chuck-Hernández Cristina , Sarić Marijana Matek , Djekic Ilija , Papageorgiou Maria , Baro José M. F. , Korzeniowska Malgorzata , Černelič-Bizjak Maša , Bartkiene Elena , Tarcea Monica , Boustani Nada M. , Klava Dace , Damarli Emel
Published: December 2022

This study aimed to investigate the level of knowledge about edible insects (EIs) in a sample of people from thirteen countries (Croatia, Greece, Latvia, Lebanon, Lithuania, Mexico, Poland, Portugal, Romania, Serbia, Slovenia, Spain, and Turkey). Data collection was based on a questionnaire survey applied through online tools between July and November 2021. For data analysis, techniques such as factor analysis, cluster analysis, and chi-square tests were used, with a significance level of 5%. A total of 27 items were used to measure knowledge on a five-point Likert scale. Applying factor analysis with principal components and Varimax rotation, a solution that explains about 55% of variance was obtained. This accounts for four factors that retained 22 of the 27 initial items: F1 = Sustainability (8 items), F2 = Nutrition (8 items), F3 = Production Factors (2 items), and F4 = Health Concerns (4 items). Internal consistency was evaluated through Cronbach’s alpha. The cluster analysis consisted of the application of hierarchical methods followed by k-means and produced three clusters (1—‘fearful’, 2—‘farming,’ and 3—‘ecological’ individuals). The characterisation of the clusters revealed that age did not influence cluster membership, while sex, education, country, living environment, professional area, and income all influenced the composition of the clusters. While participants from Mexico and Spain were fewer in the ‘fearful’ cluster, in those from Greece, Latvia, Lebanon, and Turkey, the situation was opposed. Participants from rural areas were mostly in cluster 2, which also included a higher percentage of participants with lower income. Participants from professional areas linked with biology, food, and nutrition were mostly in cluster 3. In this way, we concluded that the level of knowledge about EIs is highly variable according to the individual characteristics, namely that the social and cultural influences of the different countries lead to distinct levels of knowledge and interpretation of information, thus producing divergent approaches to the consumption of insects—some more reluctant and measuring possible risks. In contrast, others consider EIs a good and sustainable protein-food alternative.
Unlocking the Land Capability and Soil Suitability of Makuleke Farm for Sustainable Banana Production
Authors: Swafo Seome Michael , Dlamini Phesheya Eugine
Published: December 2022

Sub-Saharan Africa (SSA) is experiencing an increase in food insecurity, which is fueled by both high population growth and low agricultural productivity. Smallholder farmers are seriously affected by low soil fertility, land degradation, and poor agronomic management practices that reduce crop productivity. Therefore, there is a huge need for reliable soil information to support agricultural decision-making in smallholder farms to ensure sustainable agricultural production. However, most studies focused on land capability and soil suitability do not consider the spatial variability of soils and their inherent properties. The main objectives of this study were (1) to survey, classify and characterise soils at Makuleke farm in order to derive and map the land capability classes and (2) to quantify the physical and chemical properties of the soils in order to derive and map the suitability classes. A field survey and classification of soils led by transect walks complemented by auger holes revealed existential spatial variation of soils across the 12 ha banana plantation. The dominating soil forms in the plantation were Hutton, Westleigh, Glenrosa and Valsrivier. Land capability analysis revealed that 17% of the 12 ha portion of the farm had very high arable potential, while 60% had medium arable potential, 6% of the farm had low arable potential and 17% was considered non-arable. Subsequent soil suitability analysis revealed that 12% of the farm is highly suitable, 34% is moderately suitable, 38% is marginally suitable and 16% is permanently not suitable for banana production. The variable capability of the land and suitability of soils for banana production led to notable yield gaps. The in-depth description and quantification of the productive capacity of the land is pivotal to the farmers at Makuleke farm as it unlocks their true potential and such information is crucial to effectively manage the soil and utilize the land for sustainable banana production.
Moving toward a More Sustainable Autonomous Mobility, Case of Heterogeneity in Preferences
Authors: Farzin Iman , Abbasi Mohammadhossein , Macioszek Elżbieta , Mamdoohi Amir Reza , Ciari Francesco
Published: December 2022

Autonomous vehicles (AVs) have a number of potential advantages, although some research indicates that this technology may increase dependence on private cars. An alternative approach to bringing such technology to market is through autonomous taxis (ATs) and buses, which can assist in making transportation more sustainable. This paper aims at examining the role of attitudinal, travel-related, and individual factors in preferences for a modal shift from conventional cars toward ATs and exclusive-lane autonomous buses (ELABs), exploring the existence of heterogeneity and its possible sources. The proposed mixed logit model with a decomposition of random coefficients uses 1251 valid responses from a stated preference survey distributed in Tehran, in 2019. Results show that there is significant taste variation among individuals with respect to ATs’ travel costs, ELABs’ travel times, and walking distances to ELAB stations. Furthermore, exploring the sources of heterogeneity indicates that women are more sensitive to ATs’ travel costs and walking distances to ELAB stations while they are less sensitive to ELABs’ travel times. Moreover, travel time in discretionary activities reduces the utility of ELABs more than it does in mandatory activities. Transportation authorities can use these findings to establish more effective policies for the successful implementation of AVs.
Reframing the Intersections of Pilgrimage, Religious Tourism, and Sustainability
Authors: Shinde Kiran A. , Olsen Daniel H.
Published: December 2022

Every year, hundreds of millions of people around the world travel to sacred places to worship and to learn. While the practice of pilgrimage has a long tradition and is an important part of many religious traditions and the spiritual development of individuals, some scholars have begun to question the sustainability of modern pilgrimage travel. Not only does pilgrimage, like other forms of mobility, contribute to the emission of greenhouse gases and waste accumulation, it also seems to be exempt from blame when it comes to the current environmental crisis. In addition, while mass religious gatherings have historically been tied to the transmission and spread of disease, the threat of pilgrims becoming infected while on pilgrimage has not historically been an inhibiter to religious mobility. Indeed, the demand for pilgrimage seems to increase during times of hardship and uncertainty. Given these inherent contradictions, the purpose of this conceptual paper is to question the notion of sustainability in the context of pilgrimage and religious tourism and discuss whether modern day pilgrimage and religious tourism can be structured and managed in a more sustainable manner. First, the authors discuss the existing academic literature on the positive and negative economics, socio-cultural, and environmental impacts of pilgrimage and religious tourism. The authors then question the validity of certain tourism-environment models, including the ‘Tourism Area Life Cycle’ and ‘Carrying Capacity’, in the context of pilgrimage and religious tourism, particularly as they apply to pilgrimage and religious tourism destinations that do not typically show a decline in their visitor numbers. The authors then expand upon a conceptual model that can help scholars analyze the impacts of pilgrimage and religious tourism on pilgrim-towns. The authors conclude by contending that future discussions regarding sustainability in the context of pilgrimage and religious tourism should include religious and cultural constructs of what constitutes the tangible and intangible forms of sacredness of a place.
Does Green Credit Policy Promote or Inhibit Firms’ Green Innovation in China? Moderating Effect of Environmental Information Disclosure
Authors: Liu Yu , Ding Huiping , Sun Biao
Published: December 2022

Green credit policy (GCP) serves as an important tool for environmental protection and economy development. However, conflicting evidence exists regarding its role in affecting firms’ green innovation. China’s GCP practice provides an opportunity to explore this issue in the context of developing economies. Taking the implementation of the “Green Credit Guidelines” in China in 2012 as an exogenous shock, this paper adopts the difference-in-differences (DIDs) method to separately explore GCP’s effect on green innovation of non-heavily polluting firms (non-HPFs) and heavily polluting firms (HPFs). Based on the microdata of Chinese firms from 2008 to 2020, this study finds that: (1) GCP promotes green innovation of non-HPFs, but inhibits green innovation of HPFs. (2) GCP’s promoting effect on green innovation of non-HPFs is more prominent in large-sized firms, regions with a higher financial development level, and regions with a higher pollution level. (3) GCP’s inhibiting effect on green innovation of HPFs is less prominent in regions with higher financial development level. (4) Environmental information disclosure (EID) strengthens GCP’s promoting effect on green innovation of non-HPFs. Overall, these findings help practitioners to better understand the impact of GCP on firms’ green innovation in developing countries.
How Do Logistics Disruptions Affect Rural Households? Evidence from COVID-19 in China
Authors: Li Nan , Chen Muzi , Huang Difang
Published: December 2022

Using a comprehensive survey of rural households during the early stage of the COVID-19 pandemic in China, we find that logistics disruptions due to the lockdown have resulted in severe economic losses for rural households. Insufficient production inputs and perishable outputs can aggravate the impact of logistics disruptions on losses, while the purchase of agriculture insurance and higher regional GDP can mitigate this effect. We further examine the mechanisms by which logistics disruptions affect rural households, including both sales and production channels in agricultural supply chains. The former includes changes in product prices and reduced sales, while the latter includes changes in input prices and shortages of raw materials, capital, and labor. Of these channels, logistics has the most severe impact on sales. Opening up the logistics of sales channels is the primary policy choice. More storage warehouses and insurance are also important preemptive measures. Building stable and sustainable agricultural supply chains can ensure rural household viability during the pandemic.
The Impacts of Government Subsidies and Consumer Preferences on Food Supply Chain Traceability under Different Power Structures
Authors: Xue Weixia , Xu Zhiduan
Published: December 2022

After the outbreak of the COVID-19 pandemic, the sustainability of the food supply chain (FSC) was greatly challenged. Enterprises and governments have taken various measures to enhance the resilience of the FSC and to achieve sustainable development. Product traceability systems are an important tool for improving the resilience of the FSC and for dealing with its risks. In this study, we developed a two-stage supply chain consisting of a manufacturer and a retailer to investigate how government subsidies, power structures, and consumer preferences affect the decisions involved with FSC traceability. Manufacturer–Stackelberg (MS) and retailer–Stackelberg (RS) power structures—with and without government subsidies—were constructed using game theory, and the equilibrium solutions of the four models were compared and analyzed. The research shows that (i) government subsidies have a positive effect on FSC traceability investments, benefiting both the manufacturer and the retailer; (ii) a retailer-dominated supply chain is more conducive to product traceability, which will benefit the retailer, and when the consumer traceability preference reaches a certain threshold, the manufacturer will also benefit; and (iii) government subsidies have a significant incentivizing effect on retailer-dominated supply chain traceability. Finally, we provide an example to analyze and compare the differences between decision-making processes and profits under various consumer preference scenarios. In conclusion, the government should provide subsidies, and the retailer needs to dominate the supply chain and improve consumer traceability preferences. The research in this paper provides insight into the implementation of traceability in the FSC for management.