bluuebunny/crossref_metadata_2025 huggingface dataset:
Development of Prediction Models for Estimating Key Rice Growth Variables Using Visible and NIR Images from Unmanned Aerial Systems
Authors: Qiu Zhengchao , Ma Fei , Li Zhenwang , Xu Xuebin , Du Changwen
Published: March 2022

The rapid and accurate acquisition of rice growth variables using unmanned aerial system (UAS) is useful for assessing rice growth and variable fertilization in precision agriculture. In this study, rice plant height (PH), leaf area index (LAI), aboveground biomass (AGB), and nitrogen nutrient index (NNI) were obtained for different growth periods in field experiments with different nitrogen (N) treatments from 2019–2020. Known spectral indices derived from the visible and NIR images and key rice growth variables measured in the field at different growth periods were used to build a prediction model using the random forest (RF) algorithm. The results showed that the different N fertilizer applications resulted in significant differences in rice growth variables; the correlation coefficients of PH and LAI with visible-near infrared (V-NIR) images at different growth periods were larger than those with visible (V) images while the reverse was true for AGB and NNI. RF models for estimating key rice growth variables were established using V-NIR images and V images, and the results were validated with an R2 value greater than 0.8 for all growth stages. The accuracy of the RF model established from V images was slightly higher than that established from V-NIR images. The RF models were further tested using V images from 2019: R2 values of 0.75, 0.75, 0.72, and 0.68 and RMSE values of 11.68, 1.58, 3.74, and 0.13 were achieved for PH, LAI, AGB, and NNI, respectively, demonstrating that RGB UAS achieved the same performance as multispectral UAS for monitoring rice growth.
Imaging Parameters-Considered Slender Target Detection in Optical Satellite Images
Authors: Huang Zhaoyang , Wang Feng , You Hongjian , Hu Yuxin
Published: March 2022

The existing slender target detection methods based on optical satellite images are greatly affected by the satellite perspective and the solar perspective. Due to limited data sources, it is difficult to implement a fully data-driven approach. This work introduces the imaging parameters of optical satellite images, which greatly reduces the influence of the satellite perspectives and the solar perspectives, and reduces the demand for the amount of data. We improve the oriented bounding box (OBB) detector based on faster R-CNN (region convolutional neural networks) and propose an imaging parameters-considered detector (IPC-Det) which is more suitable for our task. Specifically, in the first stage, the umbra and the shadow are extracted by horizontal bounding box (HBB), respectively, and then the matching of the umbra and the shadow is realized according to the imaging parameters. In the second stage, the paired umbra and shadow features are used to complete the classification and regression, and the target is obtained by OBB. In experiments, after introducing imaging parameters, our detection accuracy is improved by 3.9% (up to 87.5%), proving that this work is a successful attempt to introduce imaging parameters for slender target detection.
Customizable FPGA-Based Hardware Accelerator for Standard Convolution Processes Empowered with Quantization Applied to LiDAR Data
Authors: Silva João , Pereira Pedro , Machado Rui , Névoa Rafael , Melo-Pinto Pedro , Fernandes Duarte
Published: March 2022

In recent years there has been an increase in the number of research and developments in deep learning solutions for object detection applied to driverless vehicles. This application benefited from the growing trend felt in innovative perception solutions, such as LiDAR sensors. Currently, this is the preferred device to accomplish those tasks in autonomous vehicles. There is a broad variety of research works on models based on point clouds, standing out for being efficient and robust in their intended tasks, but they are also characterized by requiring point cloud processing times greater than the minimum required, given the risky nature of the application. This research work aims to provide a design and implementation of a hardware IP optimized for computing convolutions, rectified linear unit (ReLU), padding, and max pooling. This engine was designed to enable the configuration of features such as varying the size of the feature map, filter size, stride, number of inputs, number of filters, and the number of hardware resources required for a specific convolution. Performance results show that by resorting to parallelism and quantization approach, the proposed solution could reduce the amount of logical FPGA resources by 40 to 50%, enhancing the processing time by 50% while maintaining the deep learning operation accuracy.
Dual-Frequency Linear-to-Circular Polarization Converter for Ka-Band Applications
Authors: Greco Francesco , Arnieri Emilio
Published: March 2022

A dual-band linear-to-circular planar polarization converter based on a multilayer printed circuit board (PCB) is proposed and demonstrated. Each cell of the periodic surface is formed by six substrate layers separated by five foam spacers. The three top layers are identical and contain an ‘I’-type strip, while the three layers on the bottom side are realized with three identical Jerusalem crosses (JC). A linearly polarized (LP) wave tilted 45° relative to the x- and y-axis of the converter is used to illuminate the polarizer. In this configuration, right-handed circularly polarized (RHCP) waves are generated at the Ka-band while left-handed circularly polarized (LHCP) waves are generated at the K-band. An equivalent circuit model based on transmission lines is proposed and used to design the polarizer together with full-wave simulations. The simulated/measured axial ratio (AR) remains below 3 dB in the bands 19.4–21.8 GHz (12.5%) and 27.9–30.5 GHz (8.7%) with an insertion loss better than 0.5 dB.
IoT Platforms and Security: An Analysis of the Leading Industrial/Commercial Solutions
Authors: Fortino Giancarlo , Guerrieri Antonio , Pace Pasquale , Savaglio Claudio , Spezzano Giandomenico
Published: March 2022

For simplifying and speeding up the development of the Internet of Things (IoT) ecosystem, there has been a proliferation of IoT platforms, built up according to different design principles, computing paradigms, technologies, and targets. This paper proposes a review of main examples populating the wide landscape of IoT platforms and their comparison based on the IoT-A reference architecture. In such a way, heterogeneous IoT platforms (both current and future) can be analyzed regardless of their low-level specifications but exclusively through the lens of those key functionalities and architectural building blocks that enable the interplay among devices, data flow, software, and stakeholders within the IoT ecosystem. Among these, security by design (i.e., the inclusion of security design principles, technology, and governance at every level) must be integrated into every tier, component, and application to minimize the risk of cyber threats and preserve the integrity of the IoT platforms, not only within individual components but also for all the components working together as a whole.
A Review of the Existing Potentials in Biodiesel Production in Iran
Authors: Shadidi Behdad , Najafi Gholamhassan , Zolfigol Mohammad Ali
Published: March 2022

Petroleum fuel plays an important role in industry, transportation, agriculture and other related industries in Iran. Iran has about 9.5% of the world’s total oil reserves in 2020 and is ranked 4th in the world. The presence of sufficient conventional fossil fuels for internal combustion engines has caused environmental problems. If these Iranian fossil fuels were to run out right now, there is no suitable alternative that is just as effective. The need to research alternative fuels in Iran is therefore unavoidable. In this study, the potential and available resources of raw materials, including rapeseed oil, palm oil, fish oil, waste oil, algae, animal fat, olive oil and jatropha oil for biodiesel production in different regions of Iran, have been reviewed. Given the potentials and resources described in this study, it is hoped that the findings of this study will play an important role in biodiesel production in Iran in the future and stimulate more researchers to create biodiesel from existing sources. It is also expected that this study will increase the attention of the governmental and non-governmental organizations in Iran to the existing resources for biodiesel production and development of these resources and get rid of the existing problems of fossil fuels by investing in this field.
Toward a Comprehensive Model of Green Marketing and Innovative Green Adoption: Application of a Stimulus-Organism-Response Model
Authors: Amaya Rivas Adriana , Liao Ying-Kai , Vu Minh-Quan , Hung Chia-Sheng
Published: March 2022

An increasing number of people and organizations have become aware of global warming and environmental deterioration and have become engaged in socially responsible activities to save the Earth. However, a comprehensive model that integrates the antecedents, mediators, and moderators of green adoption is yet to be developed. In this study, a comprehensive research model was developed that incorporates a stimulus-organism-response (S-O-R) model, consumption value theory, and value–belief–norm theory. A quantitative approach was adopted to collect data from customers who had experience with green purchasing in Taiwan. The empirical findings reveal that the influence of green marketing activities on three mediators—consumers’ environmental attitude, consumption values, and personal norms—is significant. These three mediators have a significant impact on consumers’ innovative green adoption. Thus, a full meditation effect is found, suggesting that marketers should increase their focus on promoting innovative green adoption through environmental attitude, consumption values, and personal norms. The findings of this study may help academicians in conducting further theoretical validation and professionals in developing applicable marketing strategies to promote green adoption.
Dynamic Graphical Instructions Result in Improved Attitudes and Decreased Task Completion Time in Human–Robot Co-Working: An Experimental Manufacturing Study
Authors: Eimontaite Iveta , Cameron David , Rolph Joe , Mokaram Saeid , Aitken Jonathan M. , Gwilt Ian , Law James
Published: March 2022

Collaborative robots offer opportunities to increase the sustainability of work and workforces by increasing productivity, quality, and efficiency, whilst removing workers from hazardous, repetitive, and strenuous tasks. They also offer opportunities for increasing accessibility to work, supporting those who may otherwise be disadvantaged through age, ability, gender, or other characteristics. However, to maximise the benefits, employers must overcome negative attitudes toward, and a lack of confidence in, the technology, and must take steps to reduce errors arising from misuse. This study explores how dynamic graphical signage could be employed to address these issues in a manufacturing task. Forty employees from one UK manufacturing company participated in a field experiment to complete a precision pick-and-place task working in conjunction with a collaborative robotic arm. Twenty-one participants completed the task with the support of dynamic graphical signage that provided information about the robot and the activity, while the rest completed the same task with no signage. The presence of the signage improved the completion time of the task as well as reducing negative attitudes towards the robots. Furthermore, participants provided with no signage had worse outcome expectancies as a function of their response time. Our results indicate that the provision of instructional information conveyed through appropriate graphical signage can improve task efficiency and user wellbeing, contributing to greater workforce sustainability. The findings will be of interest for companies introducing collaborative robots as well as those wanting to improve their workforce wellbeing and technology acceptance.
Blockchain Technology for Enhancing Supply Chain Performance and Reducing the Threats Arising from the COVID-19 Pandemic
Authors: Muduli Kamalakanta , Raut Rakesh , Narkhede Balkrishna Eknath , Shee Himanshu
Published: March 2022

The blockchain is expected to radically alter people’s real-time interactions and transactions, culminating in the birth of a new economy in a digital era [...]
The EU Mountain Product Voluntary Quality Term as a Valorization Tool for Livestock Farms: Challenges and Opportunities in an Alpine Context
Authors: Pagliacci Francesco , Cei Leonardo , Defrancesco Edi , Gatto Paola
Published: March 2022

European mountain areas have experienced a persistent loss of agricultural land and economic activities over time, with negative effects from both an environmental and a cultural perspective. In 2012, the European Union devised the mountain product (MP) quality term to provide to mountain producers a tool to better market their products and thus increase their income. In this article, we tried to understand what the current challenges and opportunities are concerning this quality term, focusing on meat products in the Italian Alpine context. To this end, interviews were conducted with producers who are allowed to use the term on meat in this area and with regional persons in charge of the food quality policy. The SWOT analysis performed on the results of these interviews highlights that the lack of stringent requirements and simple bureaucratic procedures are the main strengths of this tool, while the interest of consumers in mountain products is a factor that can stimulate the spread of its use. However, four crucial needs should be addressed, namely increasing consumers’ awareness of MP, providing information on MP to producers, increasing the protection of the term and developing a more collaborative approach among producers.
E-Learning Experience in Higher Education amid COVID-19: Does Gender Really Matter in A Gender-Segregated Culture?
Authors: Alyahya Mansour A. , Elshaer Ibrahim A. , Abunasser Fathi , Hassan Osama H. Mahmoud , Sobaih Abu Elnasr E.
Published: March 2022

Despite a plethora of research on students’ experiences of electronic (e) learning amid COVID-19 in higher education institutions (HEI), limited research has recognized the differences between students based on their gender. This research aims to examine the differences between students regarding their e-learning experiences amid COVID-19, especially in a gender-segregated culture where female students do not have full access to conventional learning as their male counterparts do, albeit they often have more access to technology-based learning. A total of 1200 online questionnaires were analyzed from students (600 male and 600 female) in public universities in Saudi Arabia, which tend to use Blackboard to sustain their communication with students and e-learning amid COVID-19. The results of structural model and multi-group analysis using AMOS supported all the research hypotheses. The results showed that the path coefficients and significant values were higher among female students than among male students. Additionally, the explanatory power of the male structural model regarding the e-learning experience (0.58) was lower than that of the structural model of female students (0.85), reflecting a higher explanatory power to explain the e-learning experience. The research findings have numerous theoretical and practical implications, especially in gender-segregated cultures.
Workplace 4.0: Exploring the Implications of Technology Adoption in Digital Manufacturing on a Sustainable Workforce
Authors: Leesakul Natalie , Oostveen Anne-Marie , Eimontaite Iveta , Wilson Max L. , Hyde Richard
Published: March 2022

As part of the Industry 4.0 movement, the introduction of digital manufacturing technologies (DMTs) poses various concerns, particularly the impact of technology adoption on the workforce. In consideration of adoption challenges and implications, various studies explore the topic from the perspective of safety, socio-economic impact, technical readiness, and risk assessment. This paper presents mixed methods research to explore the challenges and acceptance factors of the adoption of human-robot collaboration (HRC) applications and other digital manufacturing technologies from the perspective of different stakeholders: from manufacturing employees at all levels to legal experts to consultants to ethicists. We found that some of the prominent challenges and tensions inherent in technology adoption are job displacement, employee’s acceptance, trust, and privacy. This paper argues that it is crucial to understand the wider human factors implications to better strategize technology adoption; therefore, it recommends interventions targeted at individual employees and at the organisational level. This paper contributes to the roadmap of responsible DMT and HRC implementation to encourage a sustainable workforce in digital manufacturing.
Musawah: A Data-Driven AI Approach and Tool to Co-Create Healthcare Services with a Case Study on Cancer Disease in Saudi Arabia
Authors: Alahmari Nala , Alswedani Sarah , Alzahrani Ahmed , Katib Iyad , Albeshri Aiiad , Mehmood Rashid
Published: March 2022

The sustainability of human existence is in dire danger and this threat applies to our environment, societies, and economies. Smartization of cities and societies has the potential to unite individuals and nations towards sustainability as it requires engaging with our environments, analyzing them, and making sustainable decisions regulated by triple bottom line (TBL). Poor healthcare systems affect individuals, societies, the planet, and economies. This paper proposes a data-driven artificial intelligence (AI) based approach called Musawah to automatically discover healthcare services that can be developed or co-created by various stakeholders using social media analysis. The case study focuses on cancer disease in Saudi Arabia using Twitter data in the Arabic language. Specifically, we discover 17 services using machine learning from Twitter data using the Latent Dirichlet Allocation algorithm (LDA) and group them into five macro-services, namely, Prevention, Treatment, Psychological Support, Socioeconomic Sustainability, and Information Availability. Subsequently, we show the possibility of finding additional services by employing a topical search over the dataset and have discovered 42 additional services. We developed a software tool from scratch for this work that implements a complete machine learning pipeline using a dataset containing over 1.35 million tweets we curated during September–November 2021. Open service and value healthcare systems based on freely available information can revolutionize healthcare in manners similar to the open-source revolution by using information made available by the public, the government, third and fourth sectors, or others, allowing new forms of preventions, cures, treatments, and support structures.
Designing Smart Energy Systems in an Industry 4.0 Paradigm towards Sustainable Environment
Authors: Morelli Giovanna , Magazzino Cosimo , Gurrieri Antonia Rosa , Pozzi Cesare , Mele Marco
Published: March 2022

Among the Sustainable Development Goals, ‘Green Issues’ have attracted significant research on sustainability transitions and regional diversification. The introduction of green environmental technologies within the frame of the Fourth Industrial Revolution is crucial for the diversification of local, sustainable activities to protect the environment against negative climate changes. The present paper provides evidence of the positive correlation among green activities if, and only if, green culture and capabilities are robust and exist. Close international coordination is needed. We point out that smart energy-designed systems are a real revolution in the post-industrial society dominated by the service sectors. Therefore, promoting ‘intelligent’ meters is a robust policy action in world energy-based economies. We investigate the policy effects for smart meter rollout in European countries by testing this green policy tool on different economic literature strands. A theoretical model is introduced, showing that a sustainable and efficient policy instrument will reinforce and develop local green culture. The spatial unit of investigation is the EU-28, and it verifies the effectiveness of smart meters as a valid post-industrial design tool toward more sustainable environmental policies.
Language Competition and Language Shift in Friuli-Venezia Giulia: Projection and Trajectory for the Number of Friulian Speakers to 2050
Authors: Gazzola Michele , Templin Torsten
Published: March 2022

This article analyses how the number of speakers of the Friulian language changes over time in the territory where this language is traditionally spoken, that is, the provinces of Udine, Pordenone, and Gorizia, located in the north-east of Italy in the autonomous region of Friuli-Venezia Giulia. The aim of this research is twofold. First, it illustrates how the number of speakers of Friulian evolved over the past 40 years. To this end, we provide an overview of the findings of empirical studies on the Friulian language from 1977, 1998, and 2014. We complement these findings with population figures, birth and death rates, as well as data on migration and language transmission in order to provide a better understanding of the current situation in the three provinces. Second, these data are used to set up a mathematical language dynamic (or language competition) model. With the help of this empirically informed model, we derive projections for the future of the Friulian language in the three provinces. The results show that the number of Friulian speakers will decrease from 600,000 in 2014 to about 530,000 in 2050 (−11%), and that the number of regular Friulian speakers will decreases from 420,000 to 320,000 (−23%). By 2050, about 30% of the population will speak Friulian regularly and about 50% will speak Friulian regularly or occasionally. Only in the province of Udine will Friulian speakers still be in a clear majority. The analysis suggests that a stronger commitment to language policy protecting and promoting Friulian is needed in order to counteract these trends.
Sustainable Technology in High-Income Economies: The Role of Innovation
Authors: Uğurluay Koray , Kirikkaleli Dervis
Published: March 2022

The aim of this article is to examine the effects of innovation on the availability of cutting-edge technologies while controlling education, public funds and life expectancy in high-income countries from 2008 to 2018. In this study, Westerlund cointegration, fully modified ordinary least squares and dynamic ordinary least squares tests were applied. The research results indicate that: (i) there is a cointegrating link between the availability of the latest technologies and innovation, education, public funding and life expectancy; (ii) innovation increases the availability of cutting-edge technologies in high-income economies, whereas education, public funds and life expectancy contribute to sustainable technological availability; (iii) innovation, education, public funding and life expectancy result in the availability of cutting-edge technologies. The results are important in showing why policymakers in high-income economies should foster innovation capacity to sustain technological development.
Innovations in the T&L (Transport and Logistics) Sector during the COVID-19 Pandemic in Sweden, Germany and Poland
Authors: Klein Monika , Gutowska Ewelina , Gutowski Piotr
Published: March 2022

Innovation is one of the most important factors stimulating the economy. It plays a special role in the Transport and Logistics (T&L) sector as it enables the acceleration of meeting needs process. During the COVID-19 coronavirus pandemic, many industries were and still are facing a tough economic test. The recession is also noticeable in transport, freight forwarding and logistics. However, how does this sector cope with the existing problems? Has the adoption rate of innovation been stopped in this sector? Do T&L developers see the potential of innovations and do they see them as a remedy and response to the pandemic threat? These issues have been thoroughly considered in the presented publication. The paper presents conclusions and selected results from a study on the adoption of innovations by companies in the transport and logistics sector during the COVID-19 coronavirus pandemic in Sweden, Germany and Poland. As many as three research hypotheses were adopted, which after being subjected to statistical fractional verification and evaluated substantively on the basis of the literature review and conclusions of research conducted, proved to be true. The aim of this paper was to verify the principles and determinants of innovation policy in T&L enterprises in selected countries during the pandemic crisis. Moreover, the paper contains an analysis of the entrepreneurs’ experiences in the context of improving and developing their activities during economic crises, e.g., in 2008. It also presents the motivation and methodology of research. In addition to standard quantitative summaries, the authors conducted identification of correlations between the studied phenomena using the Cramer’s V method and chi-square statistics. Obtained results allowed to better understand the processes taking place and to determine the general state and prospects of further innovation development in the T&L sector during the pandemic and ubiquitous restrictions.
The Effect of Door-to-Door Salespeople’s Individual Sales Capabilities on Selling Behavior and Performance: The Moderating Effect of Competitive Intensity
Authors: Yi Ho-Taek , Amenuvor Fortune Edem
Published: March 2022

The present study investigates the effect of salespeople’s individual sales capabilities on selling behaviors and sales performance in door-to-door personal selling channels. The data are gathered from 219 South Korean salespeople. The hypotheses are tested using the structural equation modeling technique. The study finds that salespeople's individual sales capabilities have a greater impact on customer-oriented selling behavior than sales-oriented selling behavior. Similarly, both sales-oriented and customer-oriented selling behaviors have significant positive effects on sales performance. The study also discovers that competitive intensity moderates the relationship between customer-oriented selling behavior and sales performance, but has no significant effect on the relationship between sales-oriented selling behavior and sales performance. The current research only looks at door-to-door personal selling channels in South Korea. The implication is that the impacts of individual selling capabilities may differ in other contexts. The current study demonstrates that competitive intensity can reduce the impact that a “customer orientation” has on sales performance, and thus a blend of the two orientations (SOCO) is recommended for desired performance outcomes in the face of competition. Additionally, firms should focus on creating a culture that builds and enriches the sales capabilities of salespeople.
Classification of Industry 4.0 for Total Quality Management: A Review
Authors: Baran Erhan , Korkusuz Polat Tulay
Published: March 2022

The philosophy of total quality management is based on meeting quality requirements in all processes and meeting customer needs quickly and accurately through the contribution of all employees. This concept means that all the processes in an enterprise, all the technology used, and all the workforce employed represent the total quality of the enterprise, with the necessary controls and corrections made to ensure that the quality is sustainable. In this study, a detailed literature review and classification study regarding Industry 4.0, Industry 4.0 technologies, and quality has been carried out. The place and importance of quality in Industry 4.0 applications have been revealed by this classification study. In previous studies in the literature, the relationship between Industry 4.0 technologies and quality has not been examined. With this classification study, the importance of quality in Industry 4.0 has emerged, and an analysis has been conducted regarding which quality criteria are used and how often.
Influence Mechanism of Industrial Agglomeration and Technological Innovation on Land Granting on Green Total Factor Productivity
Authors: Yang Haoran , Lin Yaoben , Hu Yang , Liu Xueqing , Wu Qun
Published: March 2022

The influence of land granting on green total factor productivity (GTFP) and its mechanisms remain under-explored. Based on dynamic spatial panel data of 30 provincial administrative regions in China from 2007 to 2017, this study attempts to establish the framework of a transmission mechanism among land granting, manufacturing agglomeration and technological innovation, and green total factor productivity, and measures their interactions by the mixed directional distance function and Global Malmquist–Luenberger index model containing undesirable output. Then, this paper empirically estimates the impacts of land granting, industrial agglomeration and technological innovation on green total factor productivity in China with a dynamic spatial mediating effect model. The results show that the development paradigm of China’s industrial green economy is characterized by path dependence, and industrial GTFP has a significant spatial effect. Local governments rely on low-price competition to obtain cost advantages and facilitate the agglomeration of local manufacturing industries, and promote the impact of negotiation on industrial GTFP through the mediating effect of manufacturing agglomeration. There exists a non-linear relationship between manufacturing agglomeration and industrial GTFP. The land acquired through negotiation has a promoting effect on green technology innovation, and will foster industrial GTFP through the intermediary effect of technological innovation. No obvious non-linear relationship is observed between technological innovation and industrial GTFP. The grant of “Tender, Auction and Listing” has no significant influence on the industrial GTFP, and the mediating conduction effect on the GTFP of industry is not established. Industrial structure, government management and infrastructure will significantly promote the improvement of industrial GTFP, while the level of transportation will inhibit the improvement of industrial GTFP. Through administrative intervention in low-production capacity departments, local governments can integrate regional resource endowments, give play to the comparative advantages of industries, and achieve industrial structure upgrades and core competitiveness, which will be conducive to the improvement of industrial GTFP. High-level transportation conditions increase energy consumption and greenhouse gas emissions in transportation operation, which makes no contribution to the enhancement of industrial GTFP.
A Sustainability Lens on the Paradox of Chinese Learners: Four Studies on Chinese Students’ Learning Concepts under Li’s “Virtue–Mind” Framework
Authors: Gao Ruixiang , Zhang Jiayin , Liu Yirao , Zeng Jielin , Wu Danying , Huang Xiaoxiao , Liu Xiaoqing , Mo Lei , Zhan Zehui , Zuo Huang
Published: March 2022

The paradox of Chinese learners refers to a contrast between poor learning approaches and high achievement in China, which reveals a lack of sustainability in Chinese education. In addressing this paradox, Jin Li stood out by studying culture-based learning concepts and providing a comprehensive theoretical framework of the Eastern virtue model versus the Western mind model. However, this framework has not been thoroughly tested in the age of global cultural exchange, and the best learning model for learners has not been determined. This paper used both qualitative (replicating Li’s word association test) and quantitative methods to retest and enrich Li’s theory in present-day China, using four empirical studies. Studies 1 and 2 revealed the influence of global cultural exchange in narrowing the gap between the two models, with appropriate modifications made to Li’s theory. Studies 3 and 4 demonstrated that both of the two models were conducive to students’ academic achievement and creativity, greatly enriching Li’s theory. The implications of achieving a dynamic balance between the virtue model and the mind model to improve the sustainability of Chinese student development are discussed, which contributes to achieving the United Nations’ Sustainable Development Goals.
Analysis of Lanthanum and Cobalt Leaching Aimed at Effective Recycling Strategies of Solid Oxide Cells
Authors: Benedetto Mas Alice , Fiore Silvia , Fiorilli Sonia , Smeacetto Federico , Santarelli Massimo , Schiavi Ilaria
Published: March 2022

Lanthanum and cobalt are Critical Raw Materials and components of Solid Oxide Cells—SOCs electrodes. This review analyses lanthanum and cobalt leaching from waste materials (e-waste, batteries, spent catalysts), aiming to provide a starting point for SOC recycling, not yet investigated. The literature was surveyed with a specific interest for leaching, the first phase of hydrometallurgy recycling. Most references (86%) were published after 2012, with an interest higher (85%) for cobalt. Inorganic acids were the prevailing (>80%) leaching agents, particularly for lanthanum, while leaching processes using organic acids mostly involved cobalt. The experimental conditions adopted more diluted organic acids (median 0.55 M for lanthanum and 1.4 M for cobalt) compared to inorganic acids (median value 2 M for both metals). Organic acids required a higher solid to liquid ratio (200 g/L), compared to inorganic ones (100 g/L) to solubilize lanthanum, while the opposite happened for cobalt (20 vs. 50 g/L). The process temperature didn’t change considerably with the solvent (45–75 °C for lanthanum, and 75–88 °C for cobalt). The contact time was higher for lanthanum than for cobalt (median 3–4 h vs. 75–85 min). Specific recycling processes are crucial to support SOCs value chain in Europe, and this review can help define the existing challenges and future perspectives.
Inclusive Design of Workspaces: Mixed Methods Approach to Understanding Users
Authors: Narenthiran Olivia Phoeby , Torero Jose , Woodrow Michael
Published: March 2022

Accessible design within the built environment has often focused on mobility conditions and has recently widened to include mental health. Additionally, as one in seven are neurodivergent (including conditions such as ADHD, autism, dyslexia, and dyspraxia), this highlights a growing need for designing for ‘non-visible’ conditions in addition to mobility. Emphasised by the growing disability pay gap and the disability perception gap, people with disabilities are still facing discrimination and physical barriers within the workplace. This research aimed to identify key ways of reducing physical barriers faced by people with a disability and thus encourage more comfortable and productive use of workspaces for all. Once the need for designing for a spectrum of users and inclusive workspace design was understood, a survey was then circulated to students and staff at a large university in the UK (working remotely from home), with the aim of understanding how people have adapted their home spaces and what barriers they continue to face. Quantitative and qualitative results were compared to the literature read with key issues emerging, such as separating work and rest from spaces in bedrooms. The survey findings and literature were evaluated, extracting key performance-based goals (e.g., productivity and focus within a study space) and prescriptive design features (e.g., lighting, furniture, and thermal comfort), whilst also considering the inclusivity of these features. The key conclusion establishes that, to achieve maximum benefit, it is important to work with the users to understand specific needs and identify creative and inclusive solutions.
Multispectral Analysis of Small Plots Based on Field and Remote Sensing Surveys—A Comparative Evaluation
Authors: Csajbók József , Buday-Bódi Erika , Nagy Attila , Fehér Zsolt Zoltán , Tamás András , Virág István Csaba , Bojtor Csaba , Forgács Fanni , Vad Attila Miklós , Kutasy Erika
Published: March 2022

Remote sensing is an efficient method of monitoring experiments rapidly and by enabling the collection of significantly more detailed data, than using only field measurements, ensuring new possibilities in scientific research. A small plot field experiment was conducted in a randomized block design with winter oat (Avena sativa L.) varieties in Debrecen, Hungary in the 2020/2021 cropping year. Multiple field measurements and aerial surveys were carried out examining the response of oat on Silicon and Sulfur foliar fertilization treatments thereby monitoring their effects on the physiology, production and stress tolerance. Parallel application of in situ (elevation, soil pH, NDVI, SPAD, chlorophyll content) and aerial (NDVI, NDRE) surveys including unmanned aerial vehicles (UAVs) provided a diverse source of data for evaluation. Both the oat varieties (88.9%) and the foliar fertilization treatments (87.5%) were correctly classified and clearly separated with the discriminant analysis based on measured data. The Pearson correlation analysis showed a very strong positive connection (r = 0.895–1.00) between the NDVI values measured using a hand-held system and UAV-installed camera, except the third measurement time, where the correlation was weaker (r = 0.70). Our results indicate that field experiments can be effectively supported by UAVs.
Urban Public Food Procurement in Kiambu and Machakos Counties as a Driver of Food and Nutrition Security and Sustainability: A Literature Review and Case Studies
Authors: Xie Julian Z. , Demmler Kathrin M. , Trevenen-Jones Ann , Brownell Kelly D.
Published: March 2022

Urban public food procurement can address malnutrition and improve the beneficiary experience at public institutions whilst reshaping food systems to be healthier and more sustainable. We reviewed grey and peer-reviewed literature on urban public food procurement in Kiambu and Machakos counties in Kenya. From the literature, we selected programmes for case study research through stakeholder interviews and targeted literature searching. We searched 11 databases and reviewed 23 relevant articles. The case studies involved early childhood education centre and primary school feeding, hospital food provision, and COVID-19 responses. We found that actionable data and public–private partnerships are enabling factors. Similarly, multistakeholder involvement and governance increase coordination. However, budget constraints threaten programme stability. Procurement criteria focused on nutrition, food quality, and community development, but did not explicitly include environmental sustainability. We linked case studies to the United Nations Sustainable Development Goals 2, 3, 4, 5, 8, and 12. By developing, improving, and scaling public food procurement, urban governments in low- and middle-income countries (LMICs) can reach the most vulnerable whilst improving farmer livelihoods, creating business opportunities, and addressing environmental concerns. This paper contributes implementational insights in Kenyan urban contexts by highlighting opportunities for local and regional policymakers in LMICs and their partners to strengthen public food procurement.
Resilience-Based Repair Strategy for Gas Network System and Water Network System in Urban City
Authors: Bi Xirong , Wu Jingxian , Sun Cheng , Ji Kun
Published: March 2022

In resilience-based frameworks, optimizing the repair strategy and approaches is important for the recovery of the function of gas network systems (GNS) and water network systems (WNS). According to the resilience quantification results of GNS and WNS for a real example urban city in China, the potential impact of utilizing different repair sequences and repair/replacement approaches was investigated. First, a Monte Carlo simulation-based method was proposed to search for the optimal repair sequence according to the skew of the recovery trajectory (SRT). Under high seismic intensity conditions, the significant difference between the repair sequence corresponding to maximum SRT and minimum SRT indicates that choosing the optimal repair sequence is important in the enhancement of repair efficiency, especially when the pipelines have experienced serious damage. We also discussed the parallel repair strategy, which is more consistent with the practice, and can greatly improve the recovery efficiency compared with the single pipeline repair strategy under large damage conditions; however, under minor damage levels, the parallel repair strategy may result in a certain degree of redundancy. Next, three different repair approaches were thoroughly compared, including the point-by-point repair approach, whole pipeline replacement, and hybrid repair approach. At the condition of high seismic intensity (e.g., macroseismic intensity IX), the resilience curves for the hybrid repair approach and the pipeline replacement approach are overall similar and take less time and economic cost than the point-by-point repair approach. However, when the seismic intensity is low, the point-by-point repair approach is most efficient and has the shortest recovery time. Therefore, the choice of repair approach should be determined by stakeholders based on the specific pipeline’s damage situation. Finally, we calculated the joint resilience curves by allocating different weight factors to GNS and WNS, to represent the proportion of water and gas supply that contributes to community resilience.
The Skills of Medium-Range Precipitation Forecasts in the Senegal River Basin
Authors: Gebremichael Mekonnen , Yue Haowen , Nourani Vahid , Damoah Richard
Published: March 2022

Reliable information on medium-range (1–15 day) precipitation forecasts is useful in reservoir operation, among many other applications. Such forecasts are increasingly becoming available from global models. The skills of medium-range precipitation forecasts derived from Global Forecast System (GFS) are assessed in the Senegal River Basin, focusing on the watershed its major hydropower dams: Manantali (located in relatively wet, Southern Sudan climate and mountainous region), Foum Gleita (relatively dry, Sahel climate and low-elevation), and Diama (a large watershed covering almost the entire basin, dominated by Sahel climate). IMERG Final, a satellite product involving rain gauge data for bias correction, is used as reference. GFS has the ability capture the overall spatial and monthly pattern of rainfall in the region. However, GFS tends to overestimate rainfall in the wet parts of the region, and slightly underestimate in the dry part. The skill of daily GFS forecast is low over Manantali (Kling-Gupta Efficiency, KGE of 0.29), but slightly higher over Foum Gleita (KGE of 0.53) and Diama (KGE of 0.59). For 15-day accumulation, GFS forecast shows higher skill over Manantali (KGE of 0.60) and Diama (KGE of 0.79) but does not change much over Foul Gleita (KGE of 0.51) compared to daily rainfall forecasts. IMERG Early, a satellite-only product available at near-real time, has better performance than GFS. This study suggests the need for further improving the accuracy of GFS forecasts, and identifies IMERG Early as a potential source of data that can help in this effort.
Pesticides Xenobiotics in Soil Ecosystem and Their Remediation Approaches
Authors: Wang Xingwen , Sial Muhammad Umair , Bashir Muhammad Amjad , Bilal Muhammad , Raza Qurat-Ul-Ain , Ali Raza Hafiz Muhammad , Rehim Abdur , Geng Yucong
Published: March 2022

Globally, the rapid rise in the human population has increased the crop production, resulting in increased pesticide xenobiotics. Despite the fact that pesticide xenobiotics toxify the soil environment and ecosystem, synthetic pesticides have increased agricultural yields and reduced disease vectors. Pesticide use has increased, resulting in an increase in environmental pollution. Various methods of controlling and eliminating these contaminants have been proposed to address this issue. Pesticide impurity in the climate presents a genuine danger to individuals and other oceanic and earthly life. If not controlled, the pollution can prompt difficult issues for the climate. Some viable and cost-effective alternative approaches are needed to maintain this emission level at a low level. Phytoremediation and microbial remediation are effective methods for removing acaricide scrapings from the atmosphere using plants and organisms. This review gives an overview of different types of xenobiotics, how they get into the environment, and how the remediation of pesticides has progressed. It focuses on simple procedures that can be used in many countries. In addition, we have talked about the benefits and drawbacks of natural remediation methods.
Pricing Decision for a Closed-Loop Supply Chain with Technology Licensing under Collection and Remanufacturing Cost Disruptions
Authors: Huang Zuqing , Shao Wei , Meng Lijun , Zhang Guoqing , (Patrick) Qiang Qiang
Published: March 2022

Closed-loop supply chain (CLSC) management faces collection and remanufacturing cost disruption challenges. This study explores a CLSC system wherein original equipment manufacturers (OEMs) license the third-party remanufacturer (TPR) to bear the remanufacturing activities and investigate pricing decisions in the CLSC, while considering collection and remanufacturing cost disruptions. To obtain the optimal pricing strategy, we develop game theory models under the disruptions of both centralized and decentralized CLSCs. Based on theoretical and numerical analyses, we obtain the following results: (1) Whether or not disruption events occur, the centralized supply chain can better encourage consumers to participate in the collection of used products than a decentralized supply chain; (2) when collection disruption in a large positive region or the remanufacturing cost disruption in a large negative region occurs, OEM and TPR profits will greatly increase, and the OEM will raise the licensing fee to extract more profit from the remanufacturing activity; (3) a certain robust region exists for the retail price and wholesale price when the supply chain faces disruption increase; (4) when the supply chain faces the disruptions, it has great influence on the OEM’s licensing fee but little on the TPR’s acquisition price. The main contributions of the study include: (1) We considered the impacts of both technology licensing and collection and remanufacturing cost disruption; (2) we developed game theory models to determine the optimal manufacturing and remanufacturing quantities, and pricing strategy under the disruptions; (3) based on theoretical and numerical analyses, we presented some interesting and important insights. The results of this paper could provide useful guidelines for supply chain members on how to effectively control costs to obtain more profit by adjusting prices and selecting a better operation mode for the closed-loop supply chain.