bluuebunny/crossref_metadata_2025 huggingface dataset:
Reimagining Gender-Based Violence in the Eye of the COVID-19 Storm and Beyond: A Practical-Missiological Reflection on an African Family through the Lenses of the Biblical Narrative of Tamar
Authors: Mashau Thinandavha Derrick
Published: April 2022

Humanity is not battling only against the coronavirus disease 2019 (COVID-19) but also against gender-based violence (GBV), which has risen to epidemic proportions globally during the COVID-19 storm. There has been a rapid increase in domestic violence and other forms of GBV as nations imposed lockdown restrictions as a way to curb the COVID-19 storm. In this article, it is my contention that some of the people who were compelled to quarantine became vulnerable to GBV. In his presidential address to the nation on 18 June 2020, President Cyril Ramaphosa identified GBV in South Africa as a second pandemic. There is also a considerable outcry in our inability, both as humanity at large and government, in particular, to deal with this scourge and find lasting solutions to it. This article locates the scourge of GBV within the ‘storm’ of COVID-19 using an African family unit as a case study. Upon presenting a practical-missiological reflection of the biblical narrative of Tamar in 2 Samuel 13—both through missional lenses and hermeneutic analysis—this article reimagines an ecclesial praxis that is life-affirming and liberating to victims of GBV as it applies in family contexts. It proposes tangible solutions to GBV within an African family, but the results can be replicated globally where GBV remains a pandemic to be dealt with.
Multispectral Optical Diagnostics of Lightning from Space
Authors: Pérez-Invernón Francisco J. , Gordillo-Vázquez Francisco J. , Passas-Varo María , Neubert Torsten , Chanrion Olivier , Reglero Victor , Østgaard Nikolai
Published: April 2022

We present spectroscopic diagnostic methods that allow us to estimate the gas and the electron temperature in emerged lightning stroke channels (from thunderclouds) observed by the photometers and cameras of the Atmosphere Space Interaction Monitor (ASIM). We identify the species (molecules, atoms and ions) producing light emission in different wavelengths, and how the blue (337 ± 2 nm), red (777.4 ± 2.5 nm) and ultraviolet (180–230 nm) optical emissions captured by ASIM photometers change as a function of the temperature in the lightning stroke channel. We find good agreement between the light curves of the emerged lightning observed by ASIM and the synthetic ones obtained from calculated spectra. Our results suggest that (i) early stage (high temperature > 20,000 K) emerged lightning strokes at high altitude can contribute to the optical signals measured by the PH2 photometer (180–230 nm), (ii) intermediate stage (mid temperatures, 6000–21,000 K) emerged lightning strokes can produce 777.4 nm near-infrared radiation (observable by PH3) exhibiting higher intensity than PH1 observable N2 SPS between ∼6000 K and ∼8000 K, and than ion optical emissions (336.734 nm and 337.714 nm) between ∼16,000 K and ∼21,000 K, (iii) from ∼16,000 K to 35,000 K, neutral oxygen 777.4 nm radiation and ion emissions at 336.734 nm and 337.714 nm can be simultaneoulsy observed but 777.4 nm dominates only between ∼16,000 K and ∼21,000 K, (iv) the availability of detections with a narrow 0.5 nm gap filtered photometer (336.75–337.25 nm), with the same or better sensitivity than PH1 in ASIM-MMIA but with a central wavelength at exactly 337.0 nm (the strongest N2 SPS transition), would give access to the late stage of lightning strokes (emerged or not) when temperatures are between 8000 K and 5000 K (or lower for a photometer with better sensitivity than PH1 in ASIM-MMIA) when the production of nitrogen oxides (NOx) and hydroxyl radicals (OH) maximizes.
Semi-Supervised Classification for Intra-Pulse Modulation of Radar Emitter Signals Using Convolutional Neural Network
Authors: Yuan Shibo , Li Peng , Wu Bin , Li Xiao , Wang Jie
Published: April 2022

Intra-pulse modulation classification of radar emitter signals is beneficial in analyzing radar systems. Recently, convolutional neural networks (CNNs) have been used in classification of intra-pulse modulation of radar emitter signals, and the results proved better than the traditional methods. However, there is a key disadvantage in these CNN-based methods: the CNN requires enough labeled samples. Labeling the modulations of radar emitter signal samples requires a tremendous amount of prior knowledge and human resources. In many circumstances, the labeled samples are quite limited compared with the unlabeled samples, which means that the classification will be semi-supervised. In this paper, we propose a method which could adapt the CNN-based intra-pulse classification approach to the case where a very limited number of labeled samples and a large number of unlabeled samples are provided, to classify the intra-pulse modulations of radar emitter signals. The method is based on a one-dimensional CNN and uses pseudo labels and self-paced data augmentation, which could improve the accuracy of intra-pulse classification. Extensive experiments show that our proposed method can improve the intra-pulse modulation classification performance in the semi-supervised situations.
Utilization of Internet of Things and Wireless Sensor Networks for Sustainable Smallholder Agriculture
Authors: Bayih Amsale Zelalem , Morales Javier , Assabie Yaregal , de By Rolf A.
Published: April 2022

Agriculture is the economy’s backbone for most developing countries. Most of these countries suffer from insufficient agricultural production. The availability of real-time, reliable and farm-specific information may significantly contribute to more sufficient and sustained production. Typically, such information is usually fragmented and often does fit one-on-one with the farm or farm plot. Automated, precise and affordable data collection and dissemination tools are vital to bring such information to these levels. The tools must address details of spatial and temporal variability. The Internet of Things (IoT) and wireless sensor networks (WSNs) are useful technology in this respect. This paper investigates the usability of IoT and WSN for smallholder agriculture applications. An in-depth qualitative and quantitative analysis of relevant work over the past decade was conducted. We explore the type and purpose of agricultural parameters, study and describe available resources, needed skills and technological requirements that allow sustained deployment of IoT and WSN technology. Our findings reveal significant gaps in utilization of the technology in the context of smallholder farm practices caused by social, economic, infrastructural and technological barriers. We also identify a significant future opportunity to design and implement affordable and reliable data acquisition tools and frameworks, with a possible integration of citizen science.
Ultrasound Evaluation of the Primary α Phase Grain Size Based on Generative Adversarial Network
Authors: Peng Siqin , Chen Xi , Wu Guanhua , Li Ming , Chen Hao
Published: April 2022

Because of the high cost of experimental data acquisition, the limited size of the sample set available when conducting tissue structure ultrasound evaluation can cause the evaluation model to have low accuracy. To address such a small-sample problem, the sample set size can be expanded by using virtual samples. In this study, an ultrasound evaluation method for the primary α phase grain size based on the generation of virtual samples by a generative adversarial network (GAN) was developed. TC25 titanium alloy forgings were treated as the research object. Virtual samples were generated by the GAN with a fully connected network of different sizes used as the generator and discriminator. A virtual sample screening mechanism was constructed to obtain the virtual sample set, taking the optimization rate as the validity criterion. Moreover, an ultrasound evaluation optimization problem was constructed with accuracy as the target. It was solved by using support vector machine regression to obtain the final ultrasound evaluation model. A benchmark function was adopted to verify the effectiveness of the method, and a series of experiments and comparison experiments were performed on the ultrasound evaluation model using test samples. The results show that the learning accuracy of the original small samples can be increased by effective virtual samples. The ultrasound evaluation model built based on the proposed method has a higher accuracy and better stability than other models.
QUantitative and Automatic Atmospheric Correction (QUAAC): Application and Validation
Authors: Liu Shumin , Zhang Yunli , Zhao Limin , Chen Xingfeng , Zhou Ruoxuan , Zheng Fengjie , Li Zhiliang , Li Jiaguo , Yang Hang , Li Huafu , Yang Jian , Gao Hailiang , Gu Xingfa
Published: April 2022

The difficulty of atmospheric correction based on a radiative transfer model lies in the acquisition of synchronized atmospheric parameters, especially the aerosol optical depth (AOD). At the moment, there is no fully automatic and high-efficiency atmospheric correction method to make full use of the advantages of geostationary meteorological satellites in large-scale and efficient atmospheric monitoring. Therefore, a QUantitative and Automatic Atmospheric Correction (QUAAC) method is proposed which can efficiently correct high-spatial-resolution (HSR) satellite images. QUAAC uses the atmospheric aerosol products of geostationary satellites to match the synchronized AOD according to the temporal and spatial information of HSR satellite images. This method solves the problem that the AOD is difficult to obtain or the accuracy is not high enough to meet the demand of atmospheric correction. By using the obtained atmospheric parameters, atmospheric correction is performed to obtain the surface reflectance (SR). The whole process can achieve fully automatic operation without manual intervention. After QUAAC applied to Gaofen-2 (GF-2) HSR satellite and Himawari-8 (H-8) geostationary satellite, the results show that the effect of QUAAC correction is slightly better than that of the Fast Line-of-sight Atmospheric Analysis of Spectral Hypercubes (FLAASH) correction, and the QUAAC−corrected surface spectral curves have good coherence to that of the synchronously measured by field experiments.
Design of a Surface Plasmon Resonance CO Sensor
Authors: Pérez-Ocón Francisco , Pozo Antonio Manuel , Cortina Jorge , Rabaza Ovidio
Published: April 2022

Carbon monoxide (CO) is a highly toxic gas, which can cause death if it is inhaled in small quantities for a long time or in large quantities for a short time. Since this gas can be lethal, it is essential to detect it from minute to large concentrations. Our study consists of the design of a superficial plasmonic resonance (SPR) CO sensor of tiny dimensions which is capable of giving an immediate response at different concentrations. It is designed to work at different heights above sea level since the refractive index of this gas depends on a mixture with air and the air pressure. Due to its low weight and tiny dimensions, it is ideal for space travel or on airplanes. The results show a high resolution and sensitivity (~10−5 RIU of resolution and a sensitivity of 13.51–81.26 RIU−1).
Can Gamification Influence the Academic Performance of Students?
Authors: Arufe Giráldez Víctor , Sanmiguel-Rodríguez Alberto , Ramos Álvarez Oliver , Navarro-Patón Rubén
Published: April 2022

Gamification along with a whole range of other active methodologies are being incorporated into university classrooms due to their potential benefits for student learning. The aim of this paper was to analyse how a multimodal learning environment based on gamification could affect the final grades of university students in a subject taught at the Faculty of Education in a spanish university. The research was made up of 133 Spanish university students (Mage = 19.60; SDage = 0.43 years old). A quasi-experimental post-test design with a control group was used. The control group and the intervention group consisted of 66 and 67 students respectively. A multimodal gamified learning environment was set up for the intervention group, in contrast to traditional teaching methods which were reserved for the control group. Each one was implemented throughout an academic year. The results revealed statistically significant differences in the final average grade (p < 0.001), with students from the intervention group obtaining higher overall scores. The same occurred in the voluntary learning tasks, with students from the intervention group earning more Health Points (p = 0.006), more Experience Points (p = 0.005), a higher Total Score (p = 0.002) and a higher Level Achieved (p = 0.002). These findings point to the fact that a multimodal gamified learning environment can influence the academic performance of students. However, more scientific research has to be carried out in order to support these findings.
Environmental Factors at Different Canopy Heights Had Significant Effects on Leaf Water-Use Efficiency in Cold-Temperate Larch Forest
Authors: Ge Zhaoxin , Man Xiuling , Cai Tijiu , Duan Beixing , Xiao Ruihan , Xu Zhipeng
Published: April 2022

It is of great significance to study short-term water-use efficiency (WUEs) at different canopy heights for accurately evaluating the adaptability of cold-temperate larch (Larix gmelinii) forest to climate change. The stable isotope method combining data of gradient meteorology, photosynthetic properties and leaf structure were used to assess the influence of different canopy heights on short-term water-use efficiency (WUEs) in larch forests in the northern Da Hinggan Mountains. The results show that: (1) The rank of leaf WUEs at different canopy heights was upper canopy > middle canopy > lower canopy. The leaf WUEs in upper canopy was significantly higher than those in the middle and lower canopy (p < 0.01), and no significant difference was found between the middle and lower canopy (p > 0.05). (2) The environmental factors, the photosynthetic characteristics, the specific leaf weight (LMA) and stomatal density (SD) had significant impact (p < 0.05) on leaf WUEs at different canopy heights of larch forest. (3) The results of the weighted random forest analysis show that the main factor affecting WUEs in larch forests at different canopy heights was vapor pressure deficit (VPD), followed by relative humidity (RH) and net photosynthetic rate (Pn), while LMA and SD made relatively small contributions. This indicates that the variation of leaf WUEs at different canopy heights is mainly due to environmental factors. Our results highlight that the difference of environmental factors at different canopy heights should be considered in the future study of leaf WUE. Our results contribute to a better understanding of water utilization strategies and carbohydrate relations in the boreal forest ecosystems, which is of great significance for improving the sustainable management measures and strategies of boreal forest resources.
An Analysis of Driving Behavior of Educated Youth in Bangladesh Considering Physiological, Cultural and Socioeconomic Variables
Authors: Rayed Ashraf Mahmud , Tariq Muhammad Atiq Ur Rehman , Rahman Mizanur , Ng A. W. M. , Nahid Md. Khairul Alam , Mridul Mahibuzzaman , Islam Wazed Al , Mohiuddin Muhammad
Published: April 2022

One of the alarming aspects of Bangladesh’s traffic safety is the massive growth in the number of drivers without previous driving instruction or licenses. Proper traffic safety is defined as systems and techniques used to safeguard road users against dying or being severely injured. A driving simulator policy and an environmental model are validated in this research. It aims to create a safe mass transit system with a minimal number of fatalities and injuries. The study focuses on current road and transportation strategies. Educated and internet-using Bangladeshi drivers took part in a questionnaire about their emotional stability on an online platform with more than 100 questions comprising two parts. While one of the part outlines the physiological, cultural, and socioeconomic factors and driver education, in another part, an 18-point Driver’s Behavior Questionnaire was introduced to the responders. About 40% of the surveyed drivers in the poll were inexperienced. However, 49% of people prefer to ride two-wheelers. Moreover, 70% of surveyed drivers hold valid driver’s licenses. At the same time, 35.2% of those were college graduates. Even 34.8% of accidents were caused by excessive speed and non-aggressive driving. In addition, age and degree of education were significant indicators of distracted driving violations. The study’s findings will raise awareness about the country’s undesirable driving patterns, resulting in a safer transit system with fewer accidents and deaths. In addition, the findings may be utilized to improve present road and transit policies and lead to the development of a driving simulator program for Bangladeshis.
The Ethics of AI-Powered Climate Nudging—How Much AI Should We Use to Save the Planet?
Authors: Bartmann Marius
Published: April 2022

The number of areas in which artificial intelligence (AI) technology is being employed increases continually, and climate change is no exception. There are already growing efforts to encourage people to engage more actively in sustainable environmental behavior, so-called “green nudging”. Nudging in general is a widespread policymaking tool designed to influence people’s behavior while preserving their freedom of choice. Given the enormous challenges humanity is facing in fighting climate change, the question naturally arises: Why not combine the power of AI and the effectiveness of nudging to get people to behave in more climate-friendly ways? However, nudging has been highly controversial from the very beginning because critics fear it undermines autonomy and democracy. In this article I investigate the ethics of AI-powered climate nudging and address the question whether implementing corresponding policies may represent hidden and unacceptable costs of AI in the form of a substantive damage to autonomy and democracy. I will argue that, although there are perfectly legitimate concerns and objections against certain forms of nudging, AI-powered climate nudging can be ethically permissible under certain conditions, namely if the nudging practice takes the form of what I will call “self-governance”.
Cool Pavements: State of the Art and New Technologies
Authors: Kappou Sophia , Souliotis Manolis , Papaefthimiou Spiros , Panaras Giorgos , Paravantis John A. , Michalena Evanthie , Hills Jeremy Maxwell , Vouros Andreas P. , Ntymenou Aikaterini , Mihalakakou Giouli
Published: April 2022

With growing urban populations, methods of reducing the urban heat island effect have become increasingly important. Cool pavements altering the heat storage of materials used in pavements can lead to lower surface temperatures and reduce the thermal radiation emitted to the atmosphere. Cool pavement technologies utilize various strategies to reduce the temperature of new and existing pavements, including increased albedo, evaporative cooling, and reduced heat conduction. This process of negative radiation forces helps offset the impacts of increasing atmospheric temperatures. This paper presents an extensive analysis of the state of the art of cool pavements. The properties and principles of cool pavements are reviewed, including reflectivity, thermal emittance, heat transfer, thermal capacity, and permeability. The different types, research directions, and applications of reflective pavements are outlined and discussed. Maintenance and restoration technologies of cool pavements are reviewed, including permeable pavements. Results show that cool pavements have significant temperature reduction potential in the urban environment. This research is important for policy actions of the European Union, noting that European and international business stakeholders have recently expressed their interest in new ways of reducing energy consumption through technologically advanced pavements.
Street Usage Characteristics, Subjective Perception and Urban Form of Aging Group: A Case Study of Shanghai, China
Authors: Zhu He , Ji Qianyun , Lin Ying , Wang Ting , Lu Jingqing
Published: April 2022

Against the background of the aging trend in China, construction and regeneration strategies for an aging-friendly built environment are becoming common, led by urban governments, and public street spaces are the focus of these strategies. Exploring such planning and design strategies can help to improve the social welfare of the aging population and meet their diverse needs. Thus, this paper, through analyzing the determinants of the elderly’s needs, examines the relationship between spatial perception and street form, using Shanghai, in China, as a case study. This study contributes to the current literature in two ways: first, it constitutes the first attempt to build a needs hierarchy for aging people in a Chinese developed city; second, our statistical analysis involves large-scale population surveys, which helps us to comprehensively and deeply understand the impact of detailed street forms on the elderly’s various spatial perceptions. Our results indicate that the renovation of street space in different areas of cities can be improved by the control of street form, to meet the diverse needs of the local aging group.
Progressing towards Global Citizenship and a Sustainable Nation: Pillars of Climate Change Education and Actions
Authors: Radzi Siti Nur Fatehah , Osman Kamisah , Mohd Said Mohd Nizam
Published: April 2022

This systematic review article focuses on the elements of climate change that have been used to create climate change awareness and hence inculcate sustainable literacy among secondary school students as well as actions that have been undertaken to nourish students’ global competencies on climate change. Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) was adapted for the review of the current research, which utilised two main databases, namely, Scopus and Web of Science. The findings indicate that 35 articles were successfully selected, and were subsequently critically and systematically analysed. The review has successfully formulated three main themes that were commonly used to create climate change awareness among schoolchildren: effects of climate change, factors affecting climate change, and mitigation plans in handling climate change issues. The review has also revealed four major themes and actions that have been used as platforms towards instilling global competencies towards climate actions; indeed, the findings of this systematic review will provide meaningful information, especially to educators as well as decision-makers in developing more effective, efficient, and sustainable strategies that will shape future globally competent citizens in mitigating and adapting climate change issues and problems.
Woody Species Diversity, Community Structure, and Regeneration Capacity in Central Ethiopian Urban Forest Patches
Authors: Semu Arayaselassie Abebe , Bekele Tamrat , Cariñanos Paloma , Anwar Tauseef , Qureshi Huma
Published: April 2022

Land cover change in Addis Ababa, Ethiopia’s capital, is driven by recurring drought and the economic problems of society-initiated afforestation. The goal of this study was to learn about the state of woody species regeneration in Yeka’s urban forest patches. Thirty plots (20 m × 20 m in size) were sampled to identify plants for this purpose. All wooden trees with a height greater than 1.3 m in each plot were identified, enumerated, and their diameter were measured. Acacia decurrens was determined to be the predominant species, with an importance value index (IVI) of 161.09, followed by Acacia melanoxlon (IVI = 44.69). The bootstrapping PERMANOVA test was used to show how the species in the community overlapped. The result reveals that dissimilarity is low (p > 0.05), which is supported by the assumption of multivariate dispersion homogeneity. The area’s generalized linear model (GLM) showed all species statistically significant for characteristics associated with closure year and presence of mature trees and the entire closure year. Two of the twenty tree species, i.e., Acacia decurrens and Acacia melanoxylon were found in nearly equal numbers in all three growth stages as well as having strong regenerating potential. The rapid expansion of exotic Acacia spp. necessitates careful attention to their regeneration. To reinforce and improve ecosystem services, conservation and restoration efforts should encourage the regeneration of native plant species.
Temporal Spatial Mutations of Soil Erosion in the Middle and Lower Reaches of the Lancang River Basin and Its Influencing Mechanisms
Authors: Wu Jinkun , Cheng Yao , Mu Zheng , Dong Wei , Zheng Yunpu , Chen Chenchen , Wang Yuchun
Published: April 2022

As a major threat to ecosystem functions and national food security, soil erosion also exerts an influence on the water quality in basins and the operation and maintenance of hydropower plants. Existing discussions about trends of soil erosion focus mainly on its variation and mutation over time. Few studies have addressed the spatial mutation of soil erosion and its influence mechanism. In this research, Sen’s slope estimation was coupled with a Mann–Kendall model to explore the spatiotemporal distribution, spatial mutation characteristics and influence mechanisms of soil erosion, and conduct a case study on the Middle and Lower reaches of the Lancang River Basin (ML-LRB) in China. There are three main conclusions from this study: (1) During 2000–2019, the annual soil erosion in the ML-LRB variation ranged from 0 to 7.00 × 103 t/(km2·a) with a multi-year mean of 1.53 × 103 t/(km2·a), decreasing year by year from north to south, while an increasing trend began to appear in the central above region after 2015. (2) The areas with decreased soil erosion were much larger than those with increased soil erosion during 2000–2019, and there was a concentrated increase in soil erosion in Dali and in Xishuangbanna. (3) The mutation of the soil erosion intensity was spatially consistent with that of the Normalized Difference Vegetation Index (NDVI). Overall, this paper provides a new perspective for the study of factors affecting the trends and spatial mutation of soil erosion.
Enhancing Resilience of Cultural Heritage in Historical Areas: A Collection of Good Practices
Authors: Santangelo Angela , Melandri Eleonora , Marzani Giulia , Tondelli Simona , Ugolini Andrea
Published: April 2022

Although the need to protect and draw upon the various benefits of heritage as an asset for resilience is nowadays more clearly highlighted than in the past, policies to protect heritage from disaster risk remain fragmented, while the importance of learning from heritage and existing knowledge for building resilience is underestimated. The aim of this study is to provide an insight on good practices dealing with cultural heritage when it comes to disaster risk management and climate change adaptation, aiming at increasing cultural heritage resilience of historical areas. To this aim, the paper applies the best practice research methodology for investigating cultural heritage resilience in historical areas through the codification and analysis of good practices collected from EU-funded projects. The results consist of more than 90 good practices reviewed and analyzed according to a set of criteria. The research findings, organized according to three main categories (i.e., institutional, structural/physical, social), contribute to emphasizing the importance of improving knowledge from already available good practices. Two main approaches have been highlighted in the discussion, according to the key role assigned to stakeholders, education, data, and technology. The results allow to take advantage of existing knowledge to support communities to increase resilience of cultural heritage in historical areas.
From “Land-Oriented” to “Human-Oriented”: Research on Evolution Features of China’s Industrial Park Planning Standards
Authors: Chen Xiao , Wang Xingping
Published: April 2022

This paper uses the time-series analysis function in CiteSpace software to systematically review the planning standards of Chinese industrial parks between 1985 and 2021, and then studies the framework, content, regions, and industry characteristics of these standards. The study shows that China’s industrial park planning standards have evolved through a series of developmental stages, namely from being land-oriented, then sector-oriented, and, most recently, human-oriented. The study also shows that through this process, a multi-layered, cross-domain framework of park planning standards has emerged. Due to the challenges posed by reforms in national land and spatial planning systems, the movement to transform and upgrade China’s industrial parks, as well as the rapid development of overseas parks, and the further development of industrial park planning standards, offer important new opportunities. Towards this end, this paper concludes by putting forward several strategies on how to best improve the framework of these standards, which is based upon keeping up with advanced technologies and basing development on practice.
Dynamic Scheduling Method for Job-Shop Manufacturing Systems by Deep Reinforcement Learning with Proximal Policy Optimization
Authors: Zhang Ming , Lu Yang , Hu Youxi , Amaitik Nasser , Xu Yuchun
Published: April 2022

With the rapid development of Industrial 4.0, the modern manufacturing system has been experiencing profoundly digital transformation. The development of new technologies helps to improve the efficiency of production and the quality of products. However, for the increasingly complex production systems, operational decision making encounters more challenges in terms of having sustainable manufacturing to satisfy customers and markets’ rapidly changing demands. Nowadays, rule-based heuristic approaches are widely used for scheduling management in production systems, which, however, significantly depends on the expert domain knowledge. In this way, the efficiency of decision making could not be guaranteed nor meet the dynamic scheduling requirement in the job-shop manufacturing environment. In this study, we propose using deep reinforcement learning (DRL) methods to tackle the dynamic scheduling problem in the job-shop manufacturing system with unexpected machine failure. The proximal policy optimization (PPO) algorithm was used in the DRL framework to accelerate the learning process and improve performance. The proposed method was testified within a real-world dynamic production environment, and it performs better compared with the state-of-the-art methods.
The Evolution of Land Resource Carrying Capacity in 35 Major Cities in China
Authors: Luo Wenzhu , Jin Chi , Shen Liyin
Published: April 2022

With the rapid development of urbanization, it is necessary to understand the evolution of land resource carrying capacity (LRCC), so as to avoid irreversible damage to the land resources system in a specific region. Therefore, this paper aims to study the evolution of LRCC by four carrying status intervals of land resources. LRCC based on an evolutionary perspective can help the government manage land resources dynamically and rationally. This study defines LRCC from a carrier–load perspective and considers a higher or lower LRCC when facing the unbalanced relationship between socio-economic development and the supply capacity of land resources. Then, boxplots are used to investigate the LRCC in 35 major cities in China at different time points from 2012 to 2017. The results indicate that there was an increase in the number of cities with LRCC values in the unbalanced interval, with socio-economic development higher than the supply capacity of land resources. Shijiazhuang, Dalian, Harbin, Fuzhou, Chongqing, Kunming, and Taiyuan had LRCC values leaning towards an unbalanced situation. The main drivers that cause the phenomena mentioned above include policy, socio-economic development, and land use change. This study not only improves the understanding of the relationship between socio-economic development and the supply capacity of land resources and identifies the main drivers, but also provides a basis for control of LRCC according to the identifications of the main drivers.
Estimating Land-Use Change Using Machine Learning: A Case Study on Five Central Coastal Provinces of Vietnam
Authors: Giang Nguyen Hong , Wang Yu-Ren , Hieu Tran Dinh , Ngu Nguyen Huu , Dang Thanh-Tuan
Published: April 2022

Population growth is one factor relevant to land-use transformation and expansion in urban areas. This creates a regular mission for local governments in evaluating land resources and proposing plans based on various scenarios. This paper discussed the future trend of three kinds of land-use in the five central coast provinces. Afterwards, the paper deployed machine learning such as Multivariate Adaptive Regression Splines (MARS), Random Forest Regression (RFR), and Lasso Linear Regression (LLR) to analyze the trend of rural land use and industrial land-use to urban land-use in the Central Coast Region of Vietnam. The input variables of land-use from 2010 to 2020 were obtained by the five provinces of the Department of Natural Resources and Environment (DONRE). The results showed that these models provided pieces of information about the relationship between urban, rural, and industrial land-use change data. Furthermore, the MARS model proved to be accurate in the Quang Binh, Quang Tri, and Quang Nam provinces, whereas RFR demonstrated efficiency in the Thua Thien-Hue province and Da Nang city in the fields of land change prediction. Furthermore, the result enables to support land-use planners and decision-makers to propose strategies for urban development.
Economic and Environmental Potential of Wire-Arc Additive Manufacturing
Authors: Dias Manuel , Pragana João P. M. , Ferreira Bruna , Ribeiro Inês , Silva Carlos M. A.
Published: April 2022

Since its creation, Additive Manufacturing (AM) has experienced a tremendous growth particularly over the last decade due to the industrial paradigm shift intended for improving conventional manufacturing procedures. This work is focused on an emerging AM process known as Wire-Arc Additive Manufacturing (WAAM) to assess its potential for further applications involving metallic costumer-oriented parts. Contrary to most AM processes, WAAM allows deposition of material layer-by-layer to be accomplished under high deposition rates, low production times and near 100% material efficiency using accessible equipment. The work stems from evaluating the economic viability in the production of parts by WAAM as an alternative for conventional processes such as those used in traditional subtractive approaches. For that purpose, a process-based cost model (PBCM) was developed for estimating production costs using a strong technological approach. The PBCM was tested with the production of a case study part by WAAM and its environmental impact was further assessed through life cycle assessment (LCA). Results show that WAAM can be economically and environmentally viable within specific industrial contexts. Moreover, further developments and optimizations of process variables and equipment will allow this technology to mature into tackling novel production challenges in a time and cost-effective manner.
Sustainability Communication through Bio-Based Experiential Learning
Authors: Arief N. Nurlaela , Famiola Melia , Pratama Andika Putra , Anggahegari Prameshwara , Putri Aghnia Nadhira Aliya
Published: April 2022

Sustainability-related communication involving youth and children continues to be difficult to practice effectively and sustainably. This study examines how effective a particular approach to sustainability communication is at raising children’s environmental awareness through an educational program. Participatory action research and storytelling as a narrative paradigm were used to examine the effectiveness of bio-based experiential learning. A total of 74 students (ages 9 to 11) from Bandung, Indonesia, participated in the program. Twenty parents also participated in providing feedback for the campaign on how to change their children’s behavior towards the environment. The outcome demonstrates that the communication approach of bio-based experiential learning activities provides children with valuable education. The children are taught about urban farming, environmental awareness, and social responsibility. In the long run, it is hoped that children will be motivated to start an environmentally friendly business, particularly in biotechnology for the environment, to foster a sustainable city.
On Odd Perks-G Class of Distributions: Properties, Regression Model, Discretization, Bayesian and Non-Bayesian Estimation, and Applications
Authors: Elbatal Ibrahim , Alotaibi Naif , Almetwally Ehab M. , Alyami Salem A. , Elgarhy Mohammed
Published: April 2022

In this paper, we present a new univariate flexible generator of distributions, namely, the odd Perks-G class. Some special models in this class are introduced. The quantile function (QFUN), ordinary and incomplete moments (MOMs), generating function (GFUN), moments of residual and reversed residual lifetimes (RLT), and four different types of entropy are all structural aspects of the proposed family that hold for any baseline model. Maximum likelihood (ML) and maximum product spacing (MPS) estimates of the model parameters are given. Bayesian estimates of the model parameters are obtained. We also present a novel log-location-scale regression model based on the odd Perks–Weibull distribution. Due to the significance of the odd Perks-G family and the survival discretization method, both are used to introduce the discrete odd Perks-G family, a novel discrete distribution class. Real-world data sets are used to emphasize the importance and applicability of the proposed models.
Bayesian Phylodynamic Analysis Reveals the Dispersal Patterns of African Swine Fever Virus
Authors: Shen Zhao-Ji , Jia Hong , Xie Chun-Di , Shagainar Jurmt , Feng Zheng , Zhang Xiaodong , Li Kui , Zhou Rong
Published: April 2022

The evolutionary and demographic history of African swine fever virus (ASFV) is potentially quite valuable for developing efficient and sustainable management strategies. In this study, we performed phylogenetic, phylodynamic, and phylogeographic analyses of worldwide ASFV based on complete ASFV genomes, B646L gene, and E183L gene sequences obtained from NCBI to understand the epidemiology of ASFV. Bayesian phylodynamic analysis and phylogenetic analysis showed highly similar results of group clustering between E183L and the complete genome. The evidence of migration and the demographic history of ASFV were also revealed by the Bayesian phylodynamic analysis. The evolutionary rate was estimated to be 1.14 × 10−5 substitution/site/year. The large out-migration from the viral population in South Africa played a crucial role in spreading the virus worldwide. Our study not only provides resources for the better utilization of genomic data but also reveals the comprehensive worldwide evolutionary history of ASFV with a broad sampling window across ~70 years. The characteristics of the virus spatiotemporal transmission are also elucidated, which could be of great importance for devising strategies to control the virus.
Evaluation of the Immunogenicity in Mice Orally Immunized with Recombinant Lactobacillus casei Expressing Porcine Epidemic Diarrhea Virus S1 Protein
Authors: Xiao Ya , Wang Xiaona , Li Yue , Li Fengsai , Zhao Haiyuan , Shao Yilan , Zhang Liu , Ding Guojie , Li Jiaxuan , Jiang Yanping , Cui Wen , Shan Zhifu , Zhou Han , Wang Li , Qiao Xinyuan , Tang Lijie , Li Yijing
Published: April 2022

Porcine epidemic diarrhea (PED), characterized by diarrhea, vomiting, and dehydration, is an acute enteric infectious disease of pigs. The disease is caused by porcine epidemic diarrhea virus (PEDV), which infects the intestinal mucosal surface. Therefore, mucosal immunization through the oral route is an effective method of immunization. Lactic acid bacteria, which are acid resistant and bile-salt resistant and improve mucosal immunity, are ideal carriers for oral vaccines. The S1 glycoprotein of PEDV mediates binding of the virus with cell receptors and induces neutralizing antibodies against the virus. Therefore, we reversely screened the recombinant strain pPG-SD-S1/Δupp ATCC 393 expressing PEDV S1 glycoprotein by Lactobacillus casei deficient in upp genotype (Δupp ATCC 393). Mice were orally immunized three times with the recombinant bacteria that had been identified for expression, and the changes of anti-PEDV IgG and secreted immunoglobulin A levels were observed over 70 days. The results indicated that the antibody levels notably increased after oral administration of recombinant bacteria. The detection of extracellular cytokines on the 42nd day after immunization indicated high levels of humoral and cellular immune responses in mice. The above results demonstrate that pPG-SD-S1/Δupp ATCC 393 has great potential as an oral vaccine against PEDV.
Identification and Functional Analyses of Host Proteins Interacting with the p17 Protein of Avian Reovirus
Authors: Zhang Chengcheng , Liu Xinyi , Zhao Fuxi , Zhang Qingqing , Zuo Wei , Guo Mengjiao , Zhang Xiaorong , Wu Yantao
Published: April 2022

Avian reovirus (ARV) causes viral arthritis, chronic respiratory diseases, retarded growth and malabsorption syndrome. However, the precise molecular mechanism remains unclear. Here, we report the host cellular proteins that interact with ARV p17 by yeast two-hybrid screening. In this study, the p17 gene was cloned into pGBKT7 to obtain the bait plasmid pGBKT7-p17. After several rounds of screening of a chicken cDNA library, 43 positive clones were identified as possible host factors that interacted with p17. A BLAST search of the sequences was performed on the NCBI website, which ultimately revealed 19 interacting proteins. Gene ontology enrichment and Kyoto Encyclopedia of Genes and Genome analyses indicated that the acquired proteins were involved in multicellular organismal processes, metabolic processes, and biological regulation. When the subcellular localization of the host protein and ARV p17 protein was investigated, we observed colocalization of p17-GFP with IGF2BP1-RED and PQBP1-RED in the transfected cells but not with FGF1-RED. The direct interaction of ARV p17 protein with IGF2BP1 and PQBP1 was confirmed by coimmunoprecipitation and GST pulldown assays. We used RT-qPCR to assess the expression variation during ARV infection. The results showed that IGF2BP1, PAPSS2, RPL5, NEDD4L, PRPS2 and IFI16 were significantly upregulated, whereas the expression of FGF1, CDH2 and PQBP1 was markedly decreased in DF-1 cells infected with ARV. Finally, we demonstrated that IGF2BP1 had a positive effect on ARV replication, while PQBP1 had the opposite effect. Our findings provide valuable information for better insights into ARV's pathogenesis and the role of the p17 protein in this process.
Vaccine Literacy and Source of Information about Vaccination among Staff of Nursing Homes: A Cross-Sectional Survey Conducted in Tuscany (Italy)
Authors: Lorini Chiara , Collini Francesca , Galletti Giacomo , Ierardi Francesca , Forni Silvia , Gatteschi Claudia , Gemmi Fabrizio , Stacchini Lorenzo , Papini Sophia , Velpini Beatrice , Biasio Luigi Roberto , Bonaccorsi Guglielmo
Published: April 2022

Vaccine literacy (VL) mediates the transfer of information and facilitates vaccination acceptance. The aims of this study are to validate the HLVa-IT (Health Literacy Vaccinale degli adulti in Italiano—Vaccine health literacy for adults in Italian language) for the staff of nursing homes (NHs), to measure VL in such a peculiar target group, and to assess its relationship with the sources used to obtain information about vaccines and vaccinations. A survey has been conducted in a sample of Tuscan NHs using an online questionnaire. Eight-hundred and fifty-three questionnaires were analyzed. Two dimensions of the HLVa-IT appeared (functional and interactive/communicative/critical VL). The HLVa-IT interactive/communicative/critical subscale score was slightly higher than the functional subscale, although with no statistical significance. General practitioners (GPs) or other professionals have been reported as the main source of information by most of the respondents (66.1%). The HLVa-IT total score was significantly higher among those who have declared to use official vaccination campaigns (mean score: 3.25 ± 0.49; p < 0.001), GPs or other health professionals (3.26 ± 0.47; p < 0.001), and search engines (3.27 ± 0.48; p = 0.040) as the main sources of information. In conclusion, the HLVa-IT could be reliable test to investigate VL for staff of NHs, and also to highlight criticalities related to information sources.
Insights into Flood Wave Propagation in Natural Streams as Captured with Acoustic Profilers at an Index-Velocity Gaging Station
Authors: Muste Marian , Kim Dongsu , Kim Kyungdong
Published: April 2022

Recent advances in instruments are transforming our capabilities to better understand, monitor, and model river systems. The present paper illustrates such capabilities by providing new insights into unsteady flows captured with a Horizontal Acoustic Current Profiler (HADCP) integrated at an operational index-velocity gaging station. The illustrations demonstrate that the high-resolution stage and velocity measurements directly acquired during flood wave propagation reveal the intricate interplay among flow variables that are essential for better supporting judicious decision making for river management, flooding, sediment transport, and stream ecology. The paper confirms that the index-velocity method better captures the unsteady flow dynamics in comparison with the stage-discharge monitoring approach. At a time when the intensity and frequency of floods is continuously increasing, a better understanding of the critical features of flood waves during extreme events and the possibility of capturing more accurately their dynamics in real time is of special socio-economic significance.