bluuebunny/crossref_metadata_2025 huggingface dataset:
A Two-Phase Machine Learning Framework for Context-Aware Service Selection to Empower People with Disabilities
Authors: Namoun Abdallah , Abi Sen Adnan Ahmed , Tufail Ali , Alshanqiti Abdullah , Nawaz Waqas , BenRhouma Oussama
Published: July 2022

The use of software and IoT services is increasing significantly among people with special needs, who constitute 15% of the world’s population. However, selecting appropriate services to create a composite assistive service based on the evolving needs and context of disabled user groups remains a challenging research endeavor. Our research applies a scenario-based design technique to contribute (1) an inclusive disability ontology for assistive service selection, (2) semi-synthetic generated disability service datasets, and (3) a machine learning (ML) framework to choose services adaptively to suit the dynamic requirements of people with special needs. The ML-based selection framework is applied in two complementary phases. In the first phase, all available atomic tasks are assessed to determine their appropriateness to the user goal and profiles, whereas in the subsequent phase, the list of service providers is narrowed by matching their quality-of-service factors against the context and characteristics of the disabled person. Our methodology is centered around a myriad of user characteristics, including their disability profile, preferences, environment, and available IT resources. To this end, we extended the widely used QWS V2.0 and WS-DREAM web services datasets with a fusion of selected accessibility features. To ascertain the validity of our approach, we compared its performance against common multi-criteria decision making (MCDM) models, namely AHP, SAW, PROMETHEE, and TOPSIS. The findings demonstrate superior service selection accuracy in contrast to the other methods while ensuring accessibility requirements are satisfied.
Easy-Scalable Flexible Sensors Made of Carbon Nanotube-Doped Polydimethylsiloxane: Analysis of Manufacturing Conditions and Proof of Concept
Authors: del Bosque Antonio , Sánchez-Romate Xoan F. , Sánchez María , Ureña Alejandro
Published: July 2022

Carbon nanotube (CNT) reinforced polydimethylsiloxane (PDMS) easy-scalable sensors for human motion monitoring are proposed. First, the analysis of the dispersion procedure of nanoparticles into the polymer matrix shows that the ultrasonication (US) technique provides a higher electrical sensitivity in comparison to three-roll milling (3RM) due to the higher homogeneity of the CNT distribution induced by the cavitation forces. Furthermore, the gauge factor (GF) calculated from tensile tests decreases with increasing the CNT content, as the interparticle distance between CNTs is reduced and, thus, the contribution of the tunnelling mechanisms diminishes. Therefore, the optimum conditions were set at 0.4 CNT wt.% dispersed by US procedure, providing a GF of approximately 37 for large strains. The electrical response under cycling load was tested at 2%, 5%, and 10% strain level, indicating a high robustness of the developed sensors. Thus, this strain sensor is in a privileged position with respect to the state-of-the-art, considering all the characteristics that this type of sensor must accomplish: high GF, high flexibility, high reproducibility, easy manufacturing, and friendly operation. Finally, a proof-of-concept of human motion monitoring by placing a sensor for elbow and finger movements is carried out. The electrical resistance was found to increase, as expected, with the bending angle and it is totally recovered after stretching, indicating that there is no prevalent damage and highlighting the huge robustness and applicability of the proposed materials as wearable sensors.
Inertia Sensors for Measuring Spasticity of the Ankle Plantarflexors Using the Modified Tardieu Scale—A Proof of Concept Study
Authors: Banky Megan , Williams Gavin , Davey Rebecca , Tirosh Oren
Published: July 2022

Ankle spasticity is clinically assessed using goniometry to measure the angle of muscle reaction during the Modified Tardieu Scale (MTS). The precision of the goniometric method is questionable as the measured angle may not represent when the spastic muscle reaction occurred. This work proposes a method to accurately determine the angle of muscle reaction during the MTS assessment by measuring the maximum angular velocity and the corresponding ankle joint angle, using two affordable inertial sensors. Initially we identified the association between muscle onset and peak joint angular velocity using surface electromyography and an inertial sensor. The maximum foot angular velocity occurred 0.049 and 0.032 s following the spastic muscle reaction for Gastrocnemius and Soleus, respectively. Next, we explored the use of two affordable inertial sensors to identify the angle of muscle reaction using the peak ankle angular velocity. The angle of muscle reaction and the maximum dorsiflexion angle were significantly different for both Gastrocnemius and Soleus MTS tests (p = 0.028 and p = 0.009, respectively), indicating that the system is able to accurately detect a spastic muscle response before the end of the movement. This work successfully demonstrates how wearable technology can be used in a clinical setting to identify the onset of muscle spasticity and proposes a more accurate method that clinicians can use to measure the angle of muscle reaction during the MTS assessment. Furthermore, the proposed method may provide an opportunity to monitor the degree of spasticity where the direct help of experienced therapists is inaccessible, e.g., in rural or remote areas.
Blockchain Token-Based Wild-Simulated Ginseng Quality Management Method
Authors: Sung Youngjun , Yu Sunghyun , Won Yoojae
Published: July 2022

Countries require measures to prevent food fraud, such as forgery of certificates or content change during production, which can occur throughout the supply chain, even if they have a certification system for quality food management. Therefore, there are recent cases of the introduction of blockchain tokens for quality and supply chain management; however, there are difficulties in introducing tokens in food fields, such as forest and agricultural products. To introduce tokens in the food sector, we selected wild-simulated ginseng, subject to quality management in Korea, analyzed the quality management process of wild-simulated ginseng, and selected the target for blockchain token introduction. We then identified potential token-related issues from consumers and suggested possible solutions.
Adaptive Articulation Angle Preview-Based Path-Following Algorithm for Tractor-Semitrailer Using Optimal Control
Authors: Tang Xuequan , Yan Yunbing , Wang Baohua , Zhang Lin
Published: July 2022

Most existing Path-Following Algorithms (PFAs) are developed for single-unit vehicles (SUVs) and rarely for articulated vehicles (AVs). Since these PFAs ignore the motion of the trailer, they may cause large tracking deviations and ride stability issues when cornering. To this end, an Adaptive Articulation Angle Preview-based Path-Following Algorithm (AAAP-PFA) is proposed for AVs. Different from previous PFAs, in this model, a simple linear vehicle dynamics model is used as the prediction model, and an offset distance calculated by an articulation angle is used as part of the preview distance. An adaptive posture control strategy is designed to trade off the trajectory tracking performance and lateral stability performance during the path-following process. Considering a large prediction mismatch caused by using a linear vehicle dynamics model, a feedback correction method is proposed to improve the robustness of the steering control. In the comparison simulation experiment with SUV-PFA, it is confirmed that the novel PFA has better adaptability to the contradictory relationship between tracking performance and lateral stability and has strong steering control robustness.
An Oversampling Method of Unbalanced Data for Mechanical Fault Diagnosis Based on MeanRadius-SMOTE
Authors: Duan Feng , Zhang Shuai , Yan Yinze , Cai Zhiqiang
Published: July 2022

With the development of machine learning, data-driven mechanical fault diagnosis methods have been widely used in the field of PHM. Due to the limitation of the amount of fault data, it is a difficult problem for fault diagnosis to solve the problem of unbalanced data sets. Under unbalanced data sets, faults with little historical data are always difficult to diagnose and lead to economic losses. In order to improve the prediction accuracy under unbalanced data sets, this paper proposes MeanRadius-SMOTE based on the traditional SMOTE oversampling algorithm, which effectively avoids the generation of useless samples and noise samples. This paper validates the effectiveness of the algorithm on three linear unbalanced data sets and four step unbalanced data sets. Experimental results show that MeanRadius-SMOTE outperforms SMOTE and LR-SMOTE in various evaluation indicators, as well as has better robustness against different imbalance rates. In addition, MeanRadius-SMOTE can take into account the prediction accuracy of the overall and minority class, which is of great significance for engineering applications.
Heuristic Attention Representation Learning for Self-Supervised Pretraining
Authors: Tran Van Nhiem , Liu Shen-Hsuan , Li Yung-Hui , Wang Jia-Ching
Published: July 2022

Recently, self-supervised learning methods have been shown to be very powerful and efficient for yielding robust representation learning by maximizing the similarity across different augmented views in embedding vector space. However, the main challenge is generating different views with random cropping; the semantic feature might exist differently across different views leading to inappropriately maximizing similarity objective. We tackle this problem by introducing Heuristic Attention Representation Learning (HARL). This self-supervised framework relies on the joint embedding architecture in which the two neural networks are trained to produce similar embedding for different augmented views of the same image. HARL framework adopts prior visual object-level attention by generating a heuristic mask proposal for each training image and maximizes the abstract object-level embedding on vector space instead of whole image representation from previous works. As a result, HARL extracts the quality semantic representation from each training sample and outperforms existing self-supervised baselines on several downstream tasks. In addition, we provide efficient techniques based on conventional computer vision and deep learning methods for generating heuristic mask proposals on natural image datasets. Our HARL achieves +1.3% advancement in the ImageNet semi-supervised learning benchmark and +0.9% improvement in AP50 of the COCO object detection task over the previous state-of-the-art method BYOL. Our code implementation is available for both TensorFlow and PyTorch frameworks.
On-Device IoT-Based Predictive Maintenance Analytics Model: Comparing TinyLSTM and TinyModel from Edge Impulse
Authors: Mihigo Irene Niyonambaza , Zennaro Marco , Uwitonze Alfred , Rwigema James , Rovai Marcelo
Published: July 2022

A precise prediction of the health status of industrial equipment is of significant importance to determine its reliability and lifespan. This prediction provides users information that is useful in determining when to service, repair, or replace the unhealthy equipment’s components. In the last decades, many works have been conducted on data-driven prognostic models to estimate the asset’s remaining useful life. These models require updates on the novel happenings from regular diagnostics, otherwise, failure may happen before the estimated time due to different facts that may oblige rapid maintenance actions, including unexpected replacement. Adding to offline prognostic models, the continuous monitoring and prediction of remaining useful life can prevent failures, increase the useful lifespan through on-time maintenance actions, and reduce the unnecessary preventive maintenance and associated costs. This paper presents the ability of the two real-time tiny predictive analytics models: tiny long short-term memory (TinyLSTM) and sequential dense neural network (DNN). The model (TinyModel) from Edge Impulse is used to predict the remaining useful life of the equipment by considering the status of its different components. The equipment degradation insights were assessed through the real-time data gathered from operating equipment. To label our dataset, fuzzy logic based on the maintainer’s expertise is used to generate maintenance priorities, which are later used to compute the actual remaining useful life. The predictive analytic models were developed and performed well, with an evaluation loss of 0.01 and 0.11, respectively, for the LSTM and model from Edge Impulse. Both models were converted into TinyModels for on-device deployment. Unseen data were used to simulate the deployment of both TinyModels. Conferring to the evaluation and deployment results, both TinyLSTM and TinyModel from Edge Impulse are powerful in real-time predictive maintenance, but the model from Edge Impulse is much easier in terms of development, conversion to Tiny version, and deployment.
Perverse Fluidity?—Differential Impacts of Family Resources on Educational and Occupational Attainment for Young Adults from White and Ethnic Minority Heritages in England
Authors: Li Yaojun
Published: July 2022

This study examines the intergenerational transmission of family resources (class, education and income) on people’s educational and occupational attainment in their early career life. It asks whether parental resources remain effective or fall into insignificance. It also asks whether the resources operate in a similar way for the ethnic minorities as for the majority. Drawing on data from the Longitudinal Study of Young Persons in England, the study focuses on resource transmission in degree attainment, access to elite class position, unemployment rates, labour market earnings, and continuous income. In each aspect, we test not only the net effects of parental resources, but also the differential transmission between the majority and ethnic minority groups. The analysis shows strong effects of parental resources on educational and occupational attainment for whites but rather weak effects for the ethnic minorities. Ethnic minority children tend to grow up in poor families, yet even those whose parents manage to achieve socio-economic parity with whites do not enjoy similar benefits. Reducing inequality in family socio-economic conditions and inequality in labour market opportunities is key to achieving social justice.
Core Elements Affecting the Circularity of Materials
Authors: Burinskienė Aurelija , Lingaitienė Olga , Jakubavičius Artūras
Published: July 2022

The authors have revised the circularity of materials, which is essential to stimulate circular activity processes. The theoretical part starts with the revision of material circularity under linear and circular models, and answers to the question of how to use modern technologies to ensure the sustainable use of natural resources. Later on, the authors describe the material circularity in the concept of close-loop and open-loop production. Further on, the authors examine the recycling of different waste categories as an essential element necessary for the circularity, give the results of reviewing various sectors and present key elements affecting material circularity. The authors revised the set of variables and formed a correlation matrix and used a dynamic regression model to identify the circular material use rate. The authors suggested a three-level methodology that provided a dynamic regression model that could be applied for forecasting the size of circular material use rate in European Union countries. The empirical research results show that the key elements affecting the circularity of materials are private investments dedicated for recycling, the recycling of electronic waste and other municipal waste.
Sustainable Development and Workers Ability: Considerations on the Education Index in the Human Development Index
Authors: Grisolia Giulia , Lucia Umberto , Torchio Marco Filippo
Published: July 2022

Sustainability is an imperative of the 21st century in order to preserve the environment for the next generations, but sustainable development also requires the introduction and use of new technologies, and the related abilities for their use. The United Nations have adopted the Human Development Index HDI in order to assess human well-being. This index includes a component related to knowledge, the Education Index, which is expressed in terms of the mean schooling years. However, this information does not contain a measure of the student’s ability to solve complex problems or ability to reason, which are fundamental skills for sustainable development. In this study, an improved version of the Education Index was developed by considering the data available from the OECD’s Programme for International Student Assessment (PISA). This new index takes into account both the social impact of schooling years and the outcomes of the education systems for each country (PISA scores). As a consequence of this new Education Index, a new Human Development Index, HDI*, is proposed. Two case studies were performed, comparing the European and non-European countries, focusing on government education spending. Moreover, the trends of an energy and an environmental indicator are analyzed in relation to the HDI*.
A Graphical Method for Designing the Horizontal Alignment and the Cant in High-Speed Railway Lines Aimed at Mixed-Speed Traffic
Authors: Alqatawna Ali , Sánchez-Cambronero Santos , Gallego Inmaculada , López-Morales Juan Miguel
Published: July 2022

To realize the design of mixed-traffic railway lines, the choice of radius must ensure a comfortable ride for passenger vehicles, safe freight transport, and acceptable maintenance costs of vehicle wheels and railway infrastructure. This is not a straightforward task, and what is worse, there is a worldwide lack of clear criteria to limit the design parameters involved in the geometric definition of high-speed railway lines. The proof of this is the great number of technical standards (or recommendations) that are applied depending on the period of time, the administrations involved, or the technicians in charge. If the line is going to be aimed at mixed-speed traffic, this indetermination is even more severe, as the different type of trains that are forecasted to use the tracks (with different loads, speeds, etc.) should affect the limits of the design parameters. To begin to solve this problem, this paper aimed (1) to analyze the design parameters and limitation defined in several technical standards that are used to design high-speed railway lines, (2) to propose a graphical method for designing the horizontal alignment (the cant, the radius, and the clothoid), and (3) to apply the method to a real example to compare our proposed design with the original project for a case study in Spain.
Safety Assessment of Channel Seepage by Using Monitoring Data and Detection Information
Authors: Zhao Mengdie , Zhang Chao , Chen Shoukai , Jiang Haifeng
Published: July 2022

Seepage analysis has always been the focus of channel safety and stability research. Establishing a diagnosis method based on osmotic pressure monitoring data and combining the detection information to achieve osmotic safety is also an effective way to ensure the safety and stability of osmotic engineering. In this paper, a high-fill channel section of a water diversion project is taken as an example, and the study of osmotic safety is carried out by analyzing the engineering characteristics of linear engineering. High-fill channel sections were selected to study the temporal and spatial characteristics of various monitoring data reflecting the osmotic behavior of linear engineering; that is, these data reflect the time-varying regularity characteristics of the osmotic pressure value and the changing regularity of environmental variables. A single-point multifactor model of the monitoring data was established by establishing an evaluation index system, combining the monitoring index value method and the cloud model theory method according to the distribution law of the measured data and considering the uncertainty of the osmotic pressure data. Additionally, this model was integrated with the set pair analysis method to determine the monitoring data evaluation level; channel detection data information was collected, the abnormal detection of detection information was realized, and the monitoring data results were used to verify the detection results. In this way, an adaptive evaluation method reflecting the working behavior of high-filled channel sections is established, and a diagnostic technology for the safe operation of high-filled channel sections of linear engineering is proposed. The application results show that this method is suitable for engineering an osmotic safety assessment.
Determination of Fractured Water-Conducting Zone Height Based on Microseismic Monitoring: A Case Study in Weiqiang Coalmine, Shaanxi, China
Authors: Gao Wei , Li Yingchun , He Qingyuan
Published: July 2022

The NO. 3 coal seam of the Weiqiang coalmine is faced with a water inrush threat caused by two large reservoirs and the upper confined aquifer. However, existing empirical formulas cannot accurately predict the height of the fractured water-conducting zone; thus, it is necessary to investigate the extent of the fractured water-conducting zone according to the geological conditions of the No. 3 coal seam. The microseismic monitoring system (MMS) was used to monitor the surrounding area of the 1311 working face in real time to obtain the microseismic event information during the fracture development. The detailed situation of the fractured water-conducting zone in three-dimensional space was determined by computer analysis. The results show that the height of the fractured water-conducting zone is 110 m, which is consistent with the range (105.4~120.4 m) measured by various field drilling results and the mechanical mechanism analysis based on the key strata theory (112 m). The achievement of microseismic monitoring provides a guarantee for safety production and prevention and control of mine water disaster in the 1311 working face of the No. 3 coal seam, and can also be applied and promoted in coalmines with similar geological conditions, with significant social and economic benefits.
Understanding the Relational Dynamics of Chilean Rural Teachers: Contributions from a Narrative-Generative Perspective
Authors: Sandoval-Obando Eduardo , Pareja Arellano Nicolás , Acevedo-Duque Ángel , Riquelme-Brevis Hernán , Hernández-Mosqueira Claudio , Rivas-Valenzuela Johan
Published: July 2022

The rural teaching profession demands a genuine commitment to the development of future generations, ensuring a legacy that transcends time. Thus, generativity would be a characteristic dimension of the teaching function manifested in various forms, roles and tasks aimed at caring for students and their communities of origin. Objective: To explore the relational dynamics that rural teachers have constructed throughout their life trajectories and how these have influenced the potentially generative development of their teaching identity. Method: an interpretative-qualitative approach was adopted, following a descriptive, exploratory and cross-sectional design. The purposive sample consisted of twelve teachers with an average of 33 years of experience in rural schools in the Metropolitan Region, La Araucanía and Los Ríos (Chile). In-depth interviews from a narrative-generative perspective were used to collect the data. Subsequently, the stories were subjected to content analysis, following the logic of Grounded Theory. Results: The teachers show a potentially generative development, expressed in the construction of relational dynamics of trust, reciprocity and positive affection with their students. With their peers, they demonstrate collaborative practices, teamwork and orientation towards continuous improvement in their professional work. At the management level, they stand out for their leadership skills and commitment to the development of rural communities.
Maximum Take-Off Mass Estimation of a 19-Seat Fuel Cell Aircraft Consuming Liquid Hydrogen
Authors: Marksel Maršenka , Prapotnik Brdnik Anita
Published: July 2022

In this paper, the maximum take-off mass (MTOM) of a 19-seat fuel cell aircraft with similar characteristics to a conventional 19-seat aircraft is estimated using the combination of a rapid method and semi-empirical equations. The study shows that the MTOM of a 19-seat fuel cell aircraft with current technology would be 25% greater than that of a conventional aircraft. However, with the expected technological improvements, the MTOM of a 19-seat fuel cell aircraft could reach lower values than that of a conventional aircraft. The most important parameter affecting the MTOM of fuel cell aircraft is the power-to-weight ratio of the fuel cells. If this ratio of fuel cell aircraft does not improve significantly in the future, fuel cell aircraft with lower power loading will become the preferred choice; thus, certain trade-offs in flight performance, such as a longer takeoff distance, will be accepted. The study provides the basis for further economic analysis of fuel cell aircraft, which has yet to be conducted.
We Need to Do Better: Five Notable Failings in Science Communication
Authors: Cormick Craig
Published: July 2022

Despite significant growth in interest and investment in science communication, the field has demonstrated some high-profile failures in recent years—exemplified by anti-vaccine and anti-climate change beliefs—supported by interest groups that are often highly effective at promoting anti-science messages. This paper looks at five key areas where science communication research and practice need to do better, and offers some solutions, in order to achieve the impact that science communicators strive for.
Dynamic Modelling of Enzymatic Hydrolysis of Oil Using Lipase Immobilized on Zeolite
Authors: Al Qayoudi Aysha , Al-Zuhair Sulaiman
Published: July 2022

Immobilization has been proposed as a way to simplify the separation and repeated reuse of enzymes, which is essential for their feasible application at industrial scales. However, in their immobilized form, enzyme activity is fully utilized, due primarily to the additional diffusion limitations. Here, the immobilization of lipase on zeolite and its use in catalyzing oil hydrolysis is studied. Adsorption isotherms were investigated, and the data identified the model that best describes the process, which is the Sips model. The adsorption capacity of zeolite was determined as 62.6 mg/g, which is relatively high due to the high porosity of the support. The rate of enzymatic hydrolysis of olive oil, using the immobilized lipase, was determined at a pH of 7 and a temperature of 40 °C and was compared to that when using free enzymes. The results determined the parameters for a diffusion-reaction model. The effects of both the surface reaction and diffusion were found to be significant, with a slightly higher effect from surface reactions.
A Study on the Trends of Acceptance Criteria of the Relocation of Architectural Heritages and Priority Values of Monuments in Seoul
Authors: Kee Sehwang
Published: July 2022

Relocation of architectural heritage at home and abroad has been permitted only in cases where it is ‘only as a last resort, if protection cannot be achieved by any other means’, but this standard is not specifically set, causing confusion. Against this background, this study looked at the allowable standards for relocation of all architectural heritage cases relocated within Seoul. The acceptance criteria for relocation could be divided into two categories: for urban development or for restoration. Riegl’s monument value system was borrowed in order to determine under what values of the times the permission of such a move was permitted. As a result, from the 1960s to the 1990s, structures of architectural heritage were recognized as objects of conservation, but the original site (land) was not. Additionally, at this time, the ‘values of the present’ of the architectural heritage (includes both the structure and the site) was given priority over the ‘values of the past’ of it. It is after the 1990s that the ‘values of the past’ of the site have been recognized, and as it becomes closer in recent years, the relocation of architectural heritage tends to be carried out only to restore its original site. In this study, by analyzing the case of Seoul, it was revealed in what cases the relocation of architectural heritage was allowed, and the value priorities that acted on the background were analyzed. This study is representative in that Seoul is the capital and largest city of Korea. In addition, this study examines the change in perception, values, and paradigm of each cultural heritage that has been shown by various national institutions (Cultural Heritage Administration, President, Seoul Metropolitan Government) from the 1960s to the present by analyzing the criteria for permission for the act of moving. It allows interpretation and comparison.
Residents’ Motivations to Participate in Decision-Making for Cultural Heritage Tourism: Case Study of New Delhi
Authors: Chauhan Ekta
Published: July 2022

While academic research has established the need and importance of community participation in decision-making for cultural heritage tourism (CHT), there is still a lacuna in our knowledge when it comes to understanding what are the perspectives and motivations of people to participate in collaborative governance; thus, policymaking suffers from a lack of knowledge on how to effectively motivate and engage communities in heritage tourism management. Participatory approaches often focus on the management of various stakeholders without emphasising enough the understanding of practical and ideological factors that affect their participation. This study seeks to fill this gap in knowledge by attempting to understand residents’ attitudes and motivation towards participating in collaborative decision-making for cultural heritage tourism in their area. The objective of the study is twofold: (1) to identify residents’ attitudes towards CHT in their area and (2) to understand residents’ motivation for participating in participatory governance of CHT. The attitudes and motivations of the residents are looked at from a Weberian lens of formal and substantive rationality and it is established that residents are affected by both economic and non-economic factors in their support for tourism activities in the areas as well as to participate in collaborative decision-making. The study adopts a qualitative approach to study two heritage precincts of New Delhi, India. While the findings are based on the case study areas, they can be used to understand communities of other developing nations as well.
Assessment of the Climate-Smart Agriculture Interventions towards the Avenues of Sustainable Production–Consumption
Authors: Qureshi Mohamed Rafik Noor Mohamed , Almuflih Ali Saeed , Sharma Janpriy , Tyagi Mohit , Singh Shubhendu , Almakayeel Naif
Published: July 2022

In the current scenario, climatic adversities and a growing population are adding woes to the concerns of food safety and security. Furthermore, with the implementation of Sustainable Development Goal (SDG) 12 by the United Nations (UN), focusing on sustainable production–consumption, climatic vulnerabilities need to be addressed. Hence, in order to map the sustainable production–consumption avenues, agricultural practices need to be investigated for practices like Climate-Smart Agriculture (CSA). A need has arisen to align the existing agricultural practices in the developing nation towards the avenues of CSA, in order to counter the abrupt climatic changes. Addressing the same, a relation hierarchical model is developed which clusters the various governing criteria and their allied attributes dedicated towards the adoption of CSA practices. Furthermore, the developed model is contemplated for securing the primacies of promising practices for the enactment of CSA using the duo of the Analytical Hierarchical Process (AHP) and Fuzzy AHP (FAHP). The outcomes result in the substantial sequencing of the key attributes acting as a roadmap toward the CSA. This emphasizes the adoption of knowledge-based smart practices, which leaps from the current agricultural practices toward the CSA. Furthermore, by intensifying the utilization of the improved and resilient seed varieties and implying the fundamentals of agroforestry, we secure primacy to counter the adversities of the climate.
Seismic Resilience Assessment Strategy for Social and Sustainability Impact Evaluation on Transportation Road Network: A Seismic Liquefaction-Induced Damage Application
Authors: D’Apuzzo Mauro , Evangelisti Azzurra , Spacagna Rose Line , Cappelli Giuseppe , Nicolosi Vittorio , Modoni Giuseppe , Paolella Luca
Published: July 2022

Transport networks play a critical role for living communities, as they facilitate the exchange of people and goods and foster economic growth. Improving their resilience against seismic hazards, among which liquefaction is by far one of the most significant and complex, is consistent with most of the Sustainable Development Goals pinpointed by the United Nations’ Agenda. In this paper, an original methodological framework, combining innovative Geo-statistical approaches to analyze soil properties, prediction models for soil liquefaction, and calibrated transport demand models providing the social and economic cost associated with seismic-induced road damages and closures within a renewed Geographical Information Systems (GIS) workspace, is proposed. In particular, based on traditional risk assessment evaluation, an innovative approach to evaluate the exposure in terms of economic loss due to lack of accessibility is presented. The methodology is applied to a district area in northern Italy that underwent a recent seismic event that caused several soil liquefaction phenomena. Results provided by a sensitivity analysis on a stochastic (return period) basis are derived: as the seismic intensity increases, the total social costs increase, but the trend of the rates due to traffic delays and the loss of accessibility are irregular. Although further simulation scenarios need to be undertaken, the proposed methodology seems to provide an effective planning tool to evaluate preventive strategies aimed at improving the resilience of transport networks against liquefaction risk.
Residential Buildings’ Real Estate Values Linked to Summer Surface Thermal Anomaly Patterns and Urban Features: A Florence (Italy) Case Study
Authors: Guerri Giulia , Crisci Alfonso , Cresci Irene , Congedo Luca , Munafò Michele , Morabito Marco
Published: July 2022

Climate-change-related extreme events impact ecosystems, people, economy, and infrastructures, with important consequences on the real estate market as well. This study aims to investigate the variation of residential buildings’ real estate values in a historic Italian city in relation to the summer surface thermal anomaly pattern and urban features surrounding buildings. Open data from remote sensing products and the national database of the Revenue Agency of Italy were used. Real estate values of residential buildings were spatially analyzed in four urban belts, and the association with daytime summer surface hot- and cool-spot zones was studied through odds ratio (OR) statistic. Urban features (impervious area, tree cover, grassland area, and water body) surrounding residential buildings with different real estate values were also analyzed. Considering the whole Florentine municipality, 13.0% of residential buildings fell into hot-spot zones (only 0.6% into cool-spot ones), characterized by very low tree cover surfaces (generally <1%), most of which were in the central belt (37% of all buildings in central belt). Almost 10% of these buildings belonged to the highest market value class revealing a positive association (OR = 1.53) with hot-spot zones. This study provides useful information to plan targeted building interventions to avoid a probable decrease of the value of residential properties in high heat-related risk areas.
Dispersion of Family Ownership and Innovation Input in Family Firms
Authors: Wei Xiao , Chen Ling
Published: July 2022

Innovation is an investment in future growth and development, and it is critical for family businesses to maintain a competitive advantage. Different types of innovation inputs have different uncertainties, advantages, and risks. Product innovation and process innovation are two distinct types of innovation that necessitate significantly different organizational resource allocation and risk taking. Ownership is the source of decision-making authority, and the dispersion of intra-family ownership influence goal preferences, risk taking, and resource allocation. We investigate the effect of intra-family ownership dispersion on the decision preferences of two unique types of innovation inputs by distinguishing between product and process innovations. The greater the concentration of ownership within the family, the more likely it is that the proportion of product innovation input is higher than the proportion of process innovation input. We further discuss the moderating effects of both the proportion of family directors and collective decision-making mode on the different innovation input decisions by family firms. Using a sample of 882 Chinese small- and medium-sized family firms from the 2015 All-China Federation of Industry and Commerce, we find support for these proposed relationships. The implications of these findings extend to both family business and innovation research.
Supply Chain Risk Diffusion Model Considering Multi-Factor Influences under Hypernetwork Vision
Authors: Yu Ping , Wang Peiwen , Wang Zhiping , Wang Jia
Published: July 2022

Considering the problem of risk diffusion in increasingly complex supply chain networks, we propose using the supply chain risk diffusion model, under the hypernetwork vision, to study the influence of certain factors on risk diffusion, including the herd mentality, self-vigilance, talent recruitment, and enterprise management. First of all, the state transition probability tree is constructed to represent the state transition of each enterprise, then the Microscopic Markov Chain Approach (MMCA) is used to analyze the scale of risk spread, and the diffusion threshold of risk is discussed. We find that the herd mentality, self-vigilance, talent recruitment, and enterprise management will effectively curb the spread of risks. Directly recruiting talents and strengthening enterprise management is more effective than increasing vigilance. This study helps professionals to understand the mechanism of risk diffusion, and it provides effective suggestions on how to suppress risk diffusion in the real world.
Resilience Assessment of Urban Complex Giant Systems in Hubei Section of the Three Gorges Reservoir Area Based on Multi-Source Data
Authors: Li Guiyuan , Cheng Guo , Wu Zhenying
Published: July 2022

Due to a lack of guidance in urban systems thinking, China’s rapid urbanization has intensified the interactions and coercive effects between the various urban space subsystems. As a result, “urban diseases” such as environmental pollution, frequent earthquakes, and unbalanced urban–rural development have spread. As a complex giant system, the exploration of urban resilience enhancement is critical to ensuring the joint spatial development of cities and towns. Based on the PSR model, this study screens 38 indicators in five levels of the natural-material-economic-social-intelligent regulation subsystem of the Three Gorges Reservoir Area urban giant system, and constructs a multi-source data resilience assessment framework. Likewise, it employs the Geodetector model to investigate the key factors impacting the resilience mechanism. The results demonstrate that: (1) between 2011 and 2020, the overall resilience in the Hubei section of the Three Gorges Reservoir Area increased from low to high and the coupled characterization of the “pressure-state-response” increased at different rates, with the state layer increasing the most; (2) the frequency of geological hazards, urbanization rate, and total number of early warning and monitoring of geological hazards are the key factors that contribute to changes in spatial resilience; (3) enhanced resilience is the result of the synergistic effects of different driving factors. Our model is used to assess the resilience of the urban system, assisting decision-makers in planning strategies to respond to urban system problems effectively and improve urban resilience.
A Comparative Analysis of Plant-Based Milk Alternatives Part 2: Environmental Impacts
Authors: Geburt Katrin , Albrecht Elke Herta , Pointke Marcel , Pawelzik Elke , Gerken Martina , Traulsen Imke
Published: July 2022

Human food production is the largest cause of global environmental changes. Environmental benefits could be achieved by replacing diets with a high amount of animal-sourced foods with more plant-based foods, due to their smaller environmental impacts. The objective of this study was to assess the environmental impacts of the three most common plant-based milk alternatives (PBMAs)—oat, soy, and almond drink—in comparison with conventional and organic cow milk. Life cycle assessments (LCA) were calculated by the ReCiPe 2016 midpoint method, in addition to the single issue methods “Ecosystem damage potential” and “Water scarcity index”. PBMAs achieved lower impact values in almost all 12 of the calculated impact categories, with oat drink and the organic soy drink being the most environmentally friendly. However, when LCA results were expressed per energy and by the protein content of the beverages, the ranking of the beverages, in terms of their environmental impacts, changed greatly, and the results of PBMAs approached those of milk, particularly with regard to the protein index. The study highlights the importance of considering a broader range of impact categories when comparing the impacts of PBMAs and milk.
A Decarbonization Roadmap for Taiwan and Its Energy Policy Implications
Authors: Lau Hon Chung , Tsai Steve C.
Published: July 2022

The objective of this paper is to propose a decarbonization roadmap for Taiwan to achieve net-zero emissions by 2050 by analyzing the status of fossil and non-fossil energies, screening applicable decarbonization technologies for their effectiveness, and then proposing an energy mix for the future. The novelty of this work lies in the screening process, which considers six, instead of one or two, categories: sustainability, security, affordability, reliability, technology readiness, and technology impact. Based on this screening, a decarbonization roadmap is proposed and compared with the announced net-zero emissions (NZE) plan. The proposed roadmap requires renewable electricity to grow at an average annual growth rate of 7% between now and 2050, instead of the 10.1% required by the NZE plan, which is more achievable based on issues identified with renewable energies during our screening exercise. The proposed roadmap improves on the NZE plan in the following aspects: (1) using clean coal technologies to decarbonize existing coal-fired power plants, (2) relying more on gas than wind and solar energies to replace coal and nuclear energy for power generation, (3) accelerating carbon capture and storage (CCS) implementation, (4) delaying the phaseout of nuclear energy until 2050, and (5) using blue instead of green hydrogen to decarbonize the transport and industry sectors. Implications of this roadmap for future research and development and energy policies are also discussed.
Enhancing Foreign Language Learning Outcomes and Mitigating Cultural Attributes Inherent in Asian Culture in a Mobile-Assisted Language Learning Environment
Authors: Shadiev Rustam , Wang Xun , Halubitskaya Yuliya , Huang Yueh-Min
Published: July 2022

To achieve sustainable language learning, we designed a foreign language learning activity that extended traditional lectures in classrooms to informal learning in the real world using mobile technology. Chinese undergraduate students participated in our learning activity. We tested whether our learning activity could enhance their language learning outcomes through employing a single group pretest post-test design. We explored how the participants perceived the usefulness of the activity to foster language learning by administering a questionnaire survey. Finally, we investigated whether our learning activity could mitigate the cultural attributes inherent in Asian culture through interviews with the participants and their instructors. Our results demonstrated that participant learning outcomes improved during the learning activity. The results also showed that the perceptions of most participants of the value of the exercise were high. In the interviews, the participants and the instructors revealed that they felt the learning activity was useful and interesting. They also claimed that the learning activity helped mitigate cultural attributes, such as shyness, reservedness, passiveness, inhibition, lack of confidence, risk-avoidance, test-oriented learning, reliance on teachers for knowledge, and memorization. Based on these results, we provide some implications and useful suggestions for educators and researchers.
The Economies of Identities: Recognising the Economic Value of the Characteristics of Territories
Authors: Gusman Inês , Sandry Alan
Published: July 2022

The economic relevance of the characteristics of territories has been addressed by many approaches across different disciplines. While some consider them an important source for the reputation of territories, others rely on the fact that in a global mass market the territorial embeddedness of goods and services increase their market value through the assertion of their uniqueness and authenticity. In this article we propose the integration of these different interpretations on a common framework to better understand the underlying mechanisms and processes associated with the economic consequences of those characteristics that make territories unique and form their identity. We conduct a literature review to identify basic definitions, existing methodologies and core features of the most relevant studies on the topic to provide a broad conceptual framework for the analysis and economic promotion of the identities of territories. Additionally, two illustrative case studies are presented, covering successful strategies where identities have been put in the centre of an economic development strategy: the Way of Saint James (Galicia, Spain) and the Douro Valley (Portugal). Through the lens of the reviewed concepts, both strategies are assessed. Building on a broad repertoire of research approaches and disciplines, we conclude by outlining a new research agenda on the economies of identities and stressing the potentialities and limitations of mobilising the identities of territories as a resource for economic development.