bluuebunny/crossref_metadata_2025 huggingface dataset:
The “Four Principles” of Western Medical Bioethics and the Bioethics of Shīʿī Islam in Iran—Is the Claim of Universality by Both Justified?
Authors: Plöckinger Ursula , Auga Ulrike
Published: November 2022

The four principles of Western medical bioethics, i.e., autonomy, nonmaleficence, beneficence and justice, published by Beauchamps and Childress in their seminal ‘Principles of Biomedical Ethics’, are understood as universal. However, Non-Western governments argue that they refer to Western cultural contexts, neglecting specifics of Non-Western, for instance Islamic, civilizations. This paper addresses the claim of bioethical universality of both the West’s and Iran’s Shīʿī Islamic bioethics. We describe the historical development and the normative sources of Western and Shīʿī bioethics, i.e., common morality, the ontogeny of human morality and Shī’ī Islamic religious foundation. Both concepts support nonmaleficence and justice yet diverge with respect to beneficence, autonomy and normative justification. The Iranian screening program for ß-thalassemia major exemplifies the differences in both concepts. We conclude that nonmaleficence and justice are universal moral rules based on the ontogeny of morality. Beneficence can be characterized as a universal moral ideal. In contrast, autonomy, appreciated in the West, is neither justified by common morality nor the ontogeny of morality and has no equivalent in more communitarian-oriented societies. It thus fails to quality as a universal norm.
The Bible in Native American Literature
Authors: Lyons Scott Richard
Published: November 2022

For at least a century the Bible played a significant, positive role in Native American letters starting with the eighteenth-century writings of Samson Occom. A product of the Great Awakening, Occom’s engagements with the Bible resembled those of other Protestant thinkers and writers of his time, although his sermons were sometimes specifically tailored for Indian audiences and topics. After Occom, Indian authors in the nineteenth century such as Elias Boudinot and William Apess drew upon the Bible to make arguments against removal and “scientific racism.” In the twentieth century writers like Zitkala-Ša and Charles Alexander Eastman cast a critical eye on Christianity and reconsidered the virtues of traditionalism. John G. Neihardt’s Black Elk Speaks (1932) was the century’s fullest literary depiction of a traditional religion, but it came at the cost of concealing Black Elk’s actual religion, Catholicism. During the 1960s and 70s oral tradition was privileged over sacred scripture, as seen in N. Scott Momaday’s House Made of Dawn (1968). While the Bible makes fewer appearances than it used to in Native American literature, it would be premature to suggest that Christianity is finished in Indian country.
Improved One-Stage Detectors with Neck Attention Block for Object Detection in Remote Sensing
Authors: Lang Kaiqi , Yang Mingyu , Wang Hao , Wang Hanyu , Wang Zilong , Zhang Jingzhong , Shen Honghai
Published: November 2022

Object detection in remote sensing is becoming a conspicuous challenge with the rapidly increasing quantity and quality of remote sensing images. Although the application of Deep Learning has obtained remarkable performance in Computer Vision, detecting multi-scale targets in remote sensing images is still an unsolved problem, especially for small instances which possess limited features and intricate backgrounds. In this work, we managed to cope with this problem by designing a neck attention block (NAB), a simple and flexible module which combines the convolutional bottleneck structure and the attention mechanism, different from traditional attention mechanisms that focus on designing complicated attention branches. In addition, Vehicle in High-Resolution Aerial Imagery (VHRAI), a diverse, dense, and challenging dataset, was proposed for studying small object detection. To validate the effectiveness and generalization of NAB, we conducted experiments on a variety of datasets with the improved YOLOv3, YOLOv4-Tiny, and SSD. On VHRAI, the improved YOLOv3 and YOLOv4-Tiny surpassed the original models by 1.98% and 1.89% mAP, respectively. Similarly, they exceeded the original models by 1.12% and 3.72% mAP on TGRS-HRRSD, a large multi-scale dataset. Including SSD, these three models also showed excellent generalizability on PASCAL VOC.
Prediction Interval Estimation of Landslide Displacement Using Bootstrap, Variational Mode Decomposition, and Long and Short-Term Time-Series Network
Authors: Bai Dongxin , Lu Guangyin , Zhu Ziqiang , Zhu Xudong , Tao Chuanyi , Fang Ji , Li Yani
Published: November 2022

Using multi-source monitoring data to model and predict the displacement behavior of landslides is of great significance for the judgment and decision-making of future landslide risks. This research proposes a landslide displacement prediction model that combines Variational Mode Decomposition (VMD) and the Long and Short-Term Time-Series Network (LSTNet). The bootstrap algorithm is then used to estimate the Prediction Intervals (PIs) to quantify the uncertainty of the proposed model. First, the cumulative displacements are decomposed into trend displacement, periodic displacement, and random displacement using the VMD with the minimum sample entropy constraint. The feature factors are also decomposed into high-frequency components and low-frequency components. Second, this study uses an improved polynomial function fitting method combining the time window and threshold to predict trend displacement and uses feature factors obtained by grey relational analysis to train the LSTNet networks and predict periodic and random displacements. Finally, the predicted trend, periodic, and random displacement are summed to the predicted cumulative displacement, while the bootstrap algorithm is used to evaluate the PIs of the proposed model at different confidence levels. The proposed model was verified and evaluated by the case of the Baishuihe landslide in the Three Gorges reservoir area of China. The case results show that the proposed model has better point prediction accuracy than the three baseline models of LSSVR, BP, and LSTM, and the reliability and quality of the PIs constructed at 90%, 95%, and 99% confidence levels are also better than those of the baseline models.
Fast Ionogram Observations of Ascending Thin Layers Locally Transported from the E to F Region at Equatorial and Low Latitudes
Authors: Hu Lianhuan , Li Guozhu , Ding Zonghua , Sun Wenjie , Zhao Xiukuan , Xie Haiyong , Zhu Zhengping , Yokoyama Tatsuhiro , Lan Jiaping , Huang Zhaoguo , Ning Baiqi
Published: November 2022

By using fast ionogram observations, we report the first simultaneous observations of ascending ion layers at equatorial and low latitudes. The ionosonde measurements at Sanya (18.3°N, 109.6°E; dip lat. 12.2°N) and Chumphon (10.7°N, 99.4°E; dip lat. 3.8°N) show that a high Es layer, which might contain metallic ions, was directly lifted upward from the local E region to F region bottomside at morning hours, in a pattern similar to the vertical drift of the F region background ionosphere driven by the daytime eastward electric field. A statistical analysis with Sanya ionosonde measurements shows that the low latitude ascending ion layer is not a rare phenomenon, with a maximum occurrence of 22% during equinox. The results indicate that at the latitudes far away from the magnetic equator, the local E region metallic ions could be directly brought into the F region with the ascending layer. It can be expected that fast ionogram measurements, which can easily capture the rapid evolution of the background ionosphere, will play an important role in studying the formation of some unexpected high altitude metallic layers.
On the Effects of the Incidence Angle on the L-Band Multi-Polarisation Scattering of a Small Ship
Authors: Adil Muhammad , Buono Andrea , Nunziata Ferdinando , Ferrentino Emanuele , Velotto Domenico , Migliaccio Maurizio
Published: November 2022

The monitoring of ships is of paramount importance for ocean and coastal area surveillance. The synthetic aperture radar is shown to be a key sensor to provide effective and continuous observation of ships due to its unique imaging capabilities. When advanced synthetic aperture radar imaging systems are considered, the full scattering information is available that was demonstrated to be beneficial in developing improved ship detection and classification algorithms. Nonetheless, the capability of polarimetric synthetic aperture radar to observe marine vessels is significantly affected by several imaging and environmental parameters, including the incidence angle. Nonetheless, how changes in the incidence angle affect the scattering of ships still needs to be further investigated since only a sparse analysis, i.e., on different kinds of ships of different sizes observed at multiple incidence angles, has been performed. Hence, in this study, for the first time, the polarimetric scattering of the same ship, i.e., a small fishing trawler, which is imaged multiple times under the same sea state conditions but in a wide range of incidence angles, is analysed. This unique opportunity is provided by a premium L-band UAVSAR airborne dataset that consists of five full-polarimetric synthetic aperture radar scenes collected in the Gulf of Mexico. Experimental results highlight the key role played by the incidence angle on both coherent, i.e., co-polarisation signature and pedestal height, and incoherent, i.e., multi-polarisation and total backscattering power, polarimetric scattering descriptors. Experimental results show that: (1) the polarised scattering component is more sensitive to the incidence angle with respect to the unpolarised one; (2) the co-polarised channel under horizontal polarisation dominated the polarimetric backscattering from the fishing trawler at lower angles of incidence, while both co-polarised channels contribute to the polarimetric backscattering at higher incidence angles; (3) the HV polarisation provides the largest target-to-clutter ratio at lower incidence angles, while the HH polarisation should be preferred at higher angles of incidence.
Quantitative Short-Term Precipitation Model Using Multimodal Data Fusion Based on a Cross-Attention Mechanism
Authors: Cui Yingjie , Qiu Yunan , Sun Le , Shu Xinyao , Lu Zhenyu
Published: November 2022

Short-term precipitation prediction through abundant observation data (ground observation station data, radar data, etc.) is an essential part of the contemporary meteorological prediction system. However, most current studies only use single-modal data, which leads to some problems, such as poor prediction accuracy and little prediction timeliness. This paper proposes a multimodal data fusion precipitation prediction model integrating station data and radar data. Specifically, our model consists of three parts. Firstly, the radar feature encoder comprises a shallow convolution neural network and a stacked convolutional long short term memory network (ConvLSTM), which is used to extract the spatio-temporal features of radar-echo data. The weather station data feature encoder is composed of a fully connected network and an LSTM, which is used to extract the sequential features of the weather station data. Then, the cross-modal feature encoder obtains cross-modal features by aligning and exchanging the feature information of the radar data and the weather station data through the cross-attention mechanism. Finally, the decoder outputs the quantitative short-term precipitation prediction value. Our model can integrate station and radar data characteristics and improve prediction accuracy and timeliness, and can flexibly add other modal features. We have verified our model on four short-term and impending rainfall datasets in South Eastern China, achieving the best performance among the algorithms.
Pathways to the Sustainable Development of Quality Education for International Students in China: An fsQCA Approach
Authors: Wang Yunbo , Duan Xiuping , Chen Ziyi
Published: November 2022

The number of international students in China continues to grow rapidly. Consequently, taking practical and effective measures to achieve the sustainable development of education for international students in China has become an urgent problem. In this study, 425 representative colleges and universities in China were selected to participate in questionnaire surveys; fuzzy set qualitative comparative analysis (fsQCA) configuration analysis methods were adopted, and pathways to effectively improving the quality of education were studied from a holistic perspective. The findings showed that a combination of influencing factors can best achieve the sustainable development of the education of international students in China. The quality of international student sources plays a vital role in the sustainable development of education in colleges and universities in China. The two areas of educational training and management service have strong importance in the process of improving education for international students in China. When the quality of student sources cannot be improved, institutions can achieve the sustainable development of education by strengthening education training and teaching management.
Household Physical Activity for Adults in the Context of the Pandemic: A Systematic Review
Authors: Zhang Yu , Li Jiayu , Jiang Xiaoping
Published: November 2022

Background: People were isolated at home during the COVID-19 pandemic and were restricted from going outside, leaving them with the option of physical activity at home. The purpose of this paper is to examine how home isolation during an epidemic changes adult lifestyle and health behaviors and the role of physical activity during home isolation in improving adult dysphoria. Methods: Four major databases were searched and the 21 final included papers on home physical activity during the epidemic were evaluated. The literature was analyzed and evaluated using generalization, summarization, analysis, and evaluation methods. The findings revealed that home isolation during the epidemic changed the lifestyle and physical activity behavior of adults. Participation in physical activity varied among different levels of the population during home isolation for the epidemic. In addition, physical activity in home isolation during the epidemic helped improve adults’ poor mood. The negative impact of prolonged home isolation on the health of the global population cannot be ignored, and more encouragement should be given to diversified indoor physical activities to maintain physical and mental health. In addition, there is a need to develop more personalized technology tools for physical activity supervision regarding use.
Realization of Sustainable Development Goals with Disruptive Technologies by Integrating Industry 5.0, Society 5.0, Smart Cities and Villages
Authors: Kasinathan Padmanathan , Pugazhendhi Rishi , Elavarasan Rajvikram Madurai , Ramachandaramurthy Vigna Kumaran , Ramanathan Vinoth , Subramanian Senthilkumar , Kumar Sachin , Nandhagopal Kamalakannan , Raghavan Raghavendra Rajan Vijaya , Rangasamy Sankar , Devendiran Ramkumar , Alsharif Mohammed H.
Published: November 2022

Significant changes in society were emphasized as being required to achieve Sustainable Development Goals, a need which was further intensified with the emergence of the pandemic. The prospective society should be directed towards sustainable development, a process in which technology plays a crucial role. The proposed study discusses the technological potential for attaining the Sustainable Development Goals via disruptive technologies. This study further analyzes the outcome of disruptive technologies from the aspects of product development, health care transformation, a pandemic case study, nature-inclusive business models, smart cities and villages. These outcomes are mapped as a direct influence on Sustainable Development Goals 3, 8, 9 and 11. Various disruptive technologies and the ways in which the Sustainable Development Goals are influenced are elaborated. The investigation into the potential of disruptive technologies highlighted that Industry 5.0 and Society 5.0 are the most supportive development to underpin the efforts to achieve the Sustainable Development Goals. The study proposes the scenario where both Industry 5.0 and Society 5.0 are integrated to form smart cities and villages where the prospects of achieving Sustainable Development Goals are more favorable due to the integrated framework and Sustainable Development Goals’ interactions. Furthermore, the study proposes an integrated framework for including new age technologies to establish the concepts of Industry 5.0 and Society 5.0 integrated into smart cities and villages. The corresponding influence on the Sustainable Development Goals are also mapped. A SWOT analysis is performed to assess the proposed integrated approach to achieve Sustainable Development Goals. Ultimately, this study can assist the industrialist, policy makers and researchers in envisioning Sustainable Development Goals from technological perspectives.
Different Stakeholders’ Conceptualizations and Perspectives of Regenerative Agriculture Reveals More Consensus Than Discord
Authors: Wilson Kelly R. , Myers Robert L. , Hendrickson Mary K. , Heaton Emily A.
Published: November 2022

A range of content analyses have recently sought to define the term “regenerative agriculture”, which has gained a surge of attention in the last few years. However, these studies have not incorporated the voices of those using the term to define their work: the farmers, private companies, researchers, and NGOs giving energy to the movement. In this study, we conducted qualitative interviews with 19 stakeholders from across the United States. Key points of consensus were that regenerative agriculture moves beyond sustainability, is outcomes-based, and, as such, is context-specific: focusing on outcomes provides opportunities to be adaptive to a specific context and that, depending on one’s context, different practices may be used to achieve target outcomes. We identified three categories of outcomes: climate adaptation and mitigation, socio-economic benefits, and integrated systems. We also found several opportunities within the energy of the movement. First, regenerative agriculture remains a “big tent” that is still accessible to a broad range of farmers. Participants also underscore the need to move toward systems-based research as opposed to reductionist research. Finally, we present participants’ mixed perspectives on the role of government, the private sector, and third parties in moving regenerative agriculture forward.
Transformative Resilience: An Overview of Its Structure, Evolution, and Trends
Authors: Asadzadeh Asad , Khavarian-Garmsir Amir Reza , Sharifi Ayyoob , Salehi Pourya , Kötter Theo
Published: November 2022

Transformational resilience is at the forefront of academic and policy initiatives on sustainable development, climate adaptation, and disaster risk reduction as a result of successive and complex changes in global dynamics. While the literature on transformative resilience is growing, there is no comprehensive analysis of its trends and development. This paper aims to close this knowledge gap by presenting a multifaceted bibliometric overview of transformative resilience literature, revealing its trends, focus areas, transitions, and intellectual foundations. This is based on 415 Web of Science-indexed articles published between 1996 and 2021. According to the findings, the concept has developed primarily around four key presentive domains: vulnerability and climate change adaptation, urban and regional disaster resilience, sustainability management and institutional transformation, and COVID-19. While priorities and subjects of research have evolved over time, key concepts such as resilience, adaptation, and climate change have recurred. Influential authors and documents from three interrelated resilience schools, including sustainable development, climate change adaptation, and disaster risk reduction, have shaped the field’s intellectual foundations. We contend that a greater variety of contexts is required to facilitate transformative resilience’s investigation, description, and experimentation.
Reuse and Reconversion as Sustainability Paradigm for Marginal Areas Regeneration
Authors: Cervesato Alberto
Published: November 2022

Imagining the future has become an increasingly arduous exercise especially if we consider the constant anthropic modifications and their consequences to which the environment is subjected. In the face of climate change, the reduction in land consumption and the energy efficiency of buildings are some of the missions to be pursued to achieve an adequate level of sustainability, in the constant search for inclusive, safe, and durable urban settlements. Trying to rebalance a relationship, which has been compromised for too long, between nature and artifice can only take place through an ecosystem approach capable of promoting conservation, productivity, and resilience. These indications become the tracks to formulate exploratory projects of urban regeneration for marginal territories, linking, through a multidisciplinary approach, the architectural scale and the urban scale. In particular, this contribution addresses the debated topic, especially in the Italian context, of possible sustainable transformation scenarios for inland areas, with a focus on hamlets and villages and reflects on the possibility of working on the resilience of territories either by recovering the heritage of villages for housing purposes or enhancing the ecological–environmental component through renaturalization.
Neural Network-Augmented Locally Adaptive Linear Regression Model for Tabular Data
Authors: Munkhdalai Lkhagvadorj , Munkhdalai Tsendsuren , Pham Van Huy , Hong Jang-Eui , Ryu Keun Ho , Theera-Umpon Nipon
Published: November 2022

Creating an interpretable model with high predictive performance is crucial in eXplainable AI (XAI) field. We introduce an interpretable neural network-based regression model for tabular data in this study. Our proposed model uses ordinary least squares (OLS) regression as a base-learner, and we re-update the parameters of our base-learner by using neural networks, which is a meta-learner in our proposed model. The meta-learner updates the regression coefficients using the confidence interval formula. We extensively compared our proposed model to other benchmark approaches on public datasets for regression task. The results showed that our proposed neural network-based interpretable model showed outperformed results compared to the benchmark models. We also applied our proposed model to the synthetic data to measure model interpretability, and we showed that our proposed model can explain the correlation between input and output variables by approximating the local linear function for each point. In addition, we trained our model on the economic data to discover the correlation between the central bank policy rate and inflation over time. As a result, it is drawn that the effect of central bank policy rates on inflation tends to strengthen during a recession and weaken during an expansion. We also performed the analysis on CO2 emission data, and our model discovered some interesting explanations between input and target variables, such as a parabolic relationship between CO2 emissions and gross national product (GNP). Finally, these experiments showed that our proposed neural network-based interpretable model could be applicable for many real-world applications where data type is tabular and explainable models are required.
Circular Design Principles Applied on Dye-Sensitized Solar Cells
Authors: Schoden Fabian , Schnatmann Anna Katharina , Blachowicz Tomasz , Manz-Schumacher Hildegard , Schwenzfeier-Hellkamp Eva
Published: November 2022

In a world with growing demand for resources and a worsening climate crisis, it is imperative to research and put into practice more sustainable and regenerative products and processes. Especially in the energy sector, more sustainable systems that are recyclable, repairable and remanufacturable are needed. One promising technology is dye-sensitized solar cells (DSSCs). They can be manufactured with low energy input and can be made from non-toxic components. More than 70% of the environmental impact of a product is already determined in the design phase of a product, which is why it is essential to implement repair, remanufacturing and recycling concepts into the product design. In this publication, we explore appropriate design principles and business models that can be applied to DSSC technology. To realize this, we applied the concept of Circo Track, a method developed by the Technical University of Delft, to DSSCs and investigated which design concepts and business models are applicable. This method enables companies to transform a product that is disposed of after its useful life into one that can be used for longer and circulates in material cycles. The most important result is the description of a performance-based business model in which DSSCs are integrated into the customer’s building and green energy is provided as a service. During the operational phase, data is collected for product improvement and maintenance, and repair is executed when necessary. When the contract expires, it can be renewed, otherwise the modules are dismantled, reused, remanufactured or recycled.
Effects of Different Socioeconomic Development Levels on Extreme Precipitation Events in Mainland China
Authors: Zhang Junyao , Yao Ning , Li Yi , Li Feng , Pulatov Bakhtiyor
Published: November 2022

Understanding the impacts of human activities on extreme precipitation events at different socioeconomic development levels (SEDLs) is critical for humans to tackle extreme events. This research aims to investigate the temporal variations of six extreme precipitation indices (EPIs) over 2000–2018 at different SEDLs for the selected 525 sites (considering socioeconomic and weather data availability and completeness) in mainland China and to assess the impacts of SEDL on extreme precipitation events. Six EPIs were selected according to the Expert Team on Climate Change Detection and Indices (ETCCDI), which were: consecutive dry days—(CDD); consecutive wet days—(CWD); simple daily intensity index—(SDII); the 95th percentile of precipitation on wet days—(R95p); maximum 1-day precipitation—(Rx1day); Annual total wet–day precipitation—(PRCPTOT), respectively. As important human activity—indicators, population and Gross Domestic Product (GDP) in 2018 were used to classify the SEDLs. The levels of SEDL for the sites were classified as I to VI, in which the population increased from 50 to ≥1000 × 104 and the GDP increased from <100 to ≥10,000 × 108 RMB. The Pearson correlations between the linear slopes (LS) of population (PopuLS) or GDPLS and six EPIs at different SEDLs were conducted to show the impacts of human activities on changes of EPIs over 2000–2018. The variations of six EPILS with the SEDLs were further studied with the Pearson correlation. The results showed that: (1) High risks of extreme precipitation events occurred at SEDL VI, which was highly affected by human activity; and SDII, R95p, Rx1day and PRCPTOT were the highest in 2016, being 15.2 mm day−1, 545.9 mm, 159.8 mm and 1617.9 mm. (2) There were higher risks of drought occurring for SEDL I, which was least affected by human activity; and three EPIs (R95p, Rx1day and PRCPTOT) were the lowest in 2011, being 156.9 mm, 53.1 mm and 601.6 mm. (3) As the SEDL increased from I to VI, the five EPILS (except CWD) increased and implied increasing risks of extreme flooding events. This research provided useful references for assessing comprehensive influences of human activities on extreme precipitation events.
Study on Removal of Methylene Blue by Condensation Self-Assembled Graphene Oxide/Thiourea Composite Adsorbent
Authors: Bu Jiaqi , Yuan Lu , Jiang Hongru , Wang Chongqing
Published: November 2022

A novel adsorbent (GO-TOA) was prepared by condensation and self-assembly of graphene oxide (GO) and thiourea, and it was characterized systematically. The results revealed that thiourea has anchored on graphene oxide (GO) successfully. The results showed that GO-TOA had a higher adsorption capacity (641.724 mg/g) and adsorption rate (92.32%) than GO (196.8 mg/g and 65.6%), indicating that the introduction of thiourea greatly improved the adsorption capacity of GO. Adsorption kinetics, adsorption thermodynamics isotherm, and adsorption thermodynamics were used to study the adsorption mechanism. The results show that GO-TOA still has an adsorption rate of 90.44% compared with 0 cycles (92.32), indicating that GO-TOA has good activation and regeneration capacity. In addition, ethanol and dilute hydrochloric acid were used for the desorption of MB, and the effect of desorption was found very well. Through reusability experiments, we also found that GO-TOA has excellent application potential. We believe that GO-TOA will be a potential adsorbent for MB.
Evolution of the Online Sales of Sustainable Products in the COVID-19 Pandemic
Authors: Iordache Platis Magdalena , Olteanu Cosmin , Hotoi Anca Luiza
Published: November 2022

In the context of the COVID-19 pandemic, online sales have increased in recent years for many products. Responsible consumption has also been considered by households and individuals, and interest in sustainable products has positively evolved. Although sustainable products have more and more been considered by consumers and producers as appropriate alternatives, the results are still underwhelming. This study aims to demonstrate the relationship between the online sales of sustainable products and the online marketing costs expressed by the cost-per-click in Romania in the last three years. This quantitative research is a conclusive and descriptive study based on secondary data sets collected from the evidence registered in an online agency, which, in turn, was based on a sample of companies and products in three industries considered highly open to sustainable approaches: electronics; home and garden; clothing and footwear. The results show different relationships between the online marketing cost and the sales of sustainable products in the above-mentioned industries. In addition, online consumer purchasing intention is a mediator for the relationship between marketing cost and online sales in one industry only, namely electronics. The study reveals the development of the online transactions of sustainable products, considering the connection between marketing costs and subsequent sales.
Sustainable Water Resources Management Assessment Frameworks (SWRM-AF) for Arid and Semi-Arid Regions: A Systematic Review
Authors: Alsaeed Badir S. , Hunt Dexter V. L. , Sharifi Soroosh
Published: November 2022

Sustainable water resources management assessment frameworks (SWRM-AF) with associated indicators and benchmarks have appeared widely during the last decades to improve or maintain water resources. Examination or evaluation of their appropriateness and refinement for particular arid and semi-arid regions is a relatively unexplored area. To fill this gap in knowledge, a systematic review of relevant 21st century studies identified within two extensive databases, Scopus and Engineering Village, and in grey literature, is undertaken in this study. Therein, 17 studies are identified and thoroughly explored to identify their focus, application, and framework construction. The results of the comparative analysis among these frameworks show that the average numbers of components and indicators are 4.5 and 17.6, respectively. Meanwhile, categorical rescaling (47.1%), equal weighting (47.1%), arithmetic technique (82.35%), local scale (52.8%), and interval of the final index value of [0–100] (41.2%) are the most commonly used normalization methods and elements. The paper concludes that none of the existing tools reviewed is 100% applicable for arid and semi-arid regions, and therefore the case is made for developing a new bespoke SWRM-AF. The outcomes of this paper provide some useful insights into what should be included therein (e.g., stakeholder engagement and specific indicators to fit the context).
Disentangling Microplastic Pollution on Beach Sand of Puerto Princesa, Palawan Island, Philippines: Abundance and Characteristics
Authors: Sajorne Recca E. , Cayabo Genese Divine B. , Gajardo Lea Janine A. , Mabuhay-Omar Jhonamie A. , Creencia Lota A. , Bacosa Hernando P.
Published: November 2022

Microplastics (MPs) have become an emerging threat to the marine environment and biota. This study was conducted to determine the occurrence of MPs on the beach sand of Puerto Princesa, Philippines. Microplastics were extracted from the beach sand through the flotation method and preliminarily identified using a stereomicroscope. A total of 47 MPs were extracted from beach sand. Among the 21 sampling sites, the beach sands from 15 sites were contaminated with MPs. The east coast of Puerto Princesa (0.023 particles/g) has significantly higher MP abundance than the west coast (0.006 particles/g). The shapes of MPs were predominantly fiber (79%), and the majority were blue. Fourier transform infrared spectroscopy (FTIR) analysis identified polymer types of mainly polyethylene terephthalate (PET) and polypropylene (PP). Overall, 71% of the sampling sites showed the presence of MPs. Future studies should consider the presence and effects of MPs in the food chain, particularly on seafood.
New Insights into the Impact of Local Corruption on China’s Regional Carbon Emissions Performance Based on the Spatial Spillover Effects
Authors: Xu Xianpu , Yi Bijiao
Published: November 2022

The increase of carbon dioxide emissions (CO2) is one of the greatest challenges facing mankind today. Although some studies have examined the factors influencing carbon emissions from various angles, research on the nexus between corruption and carbon pollution has not received enough attention. In this context, using provincial panel data for China from 2003 to 2017, this paper adopts spatial econometric methods to explore the effect and mechanisms of corruption on CO2 emissions. The results indicate that: (1) China’s carbon emissions present significant spatial agglomeration characteristics; (2) Corruption not only directly exacerbates CO2 emissions, but also, and more importantly, has a positive and significant spatial spillover effect on pollutant emissions, implying that corruption stimulates the production of carbon dioxide on a regional level, as well as in neighboring regions. As an internal mechanism, the influence of corruption on CO2 emissions mainly reflects the “local competition” and “innovation distortion” effects; (3) Improvements at the economic level, the increase in FDI, and upgrades to the structure of industry can promote carbon emission reductions, while R&D investment has an inhibitory effect. Finally, this paper proposes countermeasures to promote sustainable and high-quality development of China’s economy by strengthening regional collaboration and intensifying institutional supervision.
Spatial Distribution Characteristics of Traditional Villages and Influence Factors Thereof in Hilly and Gully Areas of Northern Shaanxi
Authors: Li Bingqian , Wang Jun , Jin Yibing
Published: November 2022

In recent traditional village studies, spatial distribution characteristics have gained importance as a basis for rural revitalization and holistic protection; however, the total number of such studies remains small, and these studies do not account for the specific geographical area of China’s Loess Plateau. Contributing to recent efforts, the primary objective of this study was to evaluate the spatial distribution characteristics of the traditional villages in the hilly and gully areas of northern Shaanxi and to link their distribution patterns to the conservation and development of the traditional villages. ArcGIS and GeoDetector software were used to analyze the correlation between the village distribution characteristics and the influencing factors, as well as the differences in the influence of each factor. The research results show the following: (1) The traditional villages in the hilly and gully areas of northern Shaanxi present an uneven agglomeration distribution. The Mizhi, Suide, and Jiaxian areas are the main core agglomeration areas, and Yanchuan is a secondary core agglomeration area. An outward radiation forms with the “dual-core” as a center. (2) The spatial distribution of the traditional villages is positively correlated with slope, average annual temperature, solar radiation, and population density and is negatively correlated with the distance from a river and the GDP per capita; it has a median distribution for elevation, aspect, terrain undulation, and rainfall, and the distribution of the urbanization rate fluctuates. (3) The factor detection results of GeoDetector showed that the socio-economic factors had the strongest influence, followed by the climatic factors. The influence of the geographical factors was weak; the interaction between the influencing factors was enhanced, and the interaction between the population density and the climatic factors was the most obvious. (4) In terms of the influence mechanism, this study supports the claim that “natural environmental factors are the basis for the formation of traditional villages, and socio-economic factors determine the direction of development”. However, it is worth noting that the unique natural and human characteristics of the hilly and gully areas of northern Shaanxi are the fundamental reasons for the differences in the spatial distribution compared to the other regions.
Water Column Detection Method at Impact Point Based on Improved YOLOv4 Algorithm
Authors: Shi Jiaowei , Sun Shiyan , Shi Zhangsong , Zheng Chaobing , She Bo
Published: November 2022

For a long time, the water column at the impact point of a naval gun firing at the sea has mainly depended on manual detection methods for locating, which has problems such as low accuracy, subjectivity and inefficiency. In order to solve the above problems, this paper proposes a water column detection method based on an improved you-only-look-once version 4 (YOLOv4) algorithm. Firstly, the method detects the sea antenna through the Hoffman line detection method to constrain the sensitive area in the current detection image so as to improve the accuracy of water column detection; secondly, density-based spatial clustering of applications with noise (DBSCAN) + K-means clustering algorithm is used to obtain a better prior bounding box, which is input into the YOLOv4 network to improve the positioning accuracy of the water column; finally, the convolutional block attention module (CBAM) is added in the PANet structure to improve the detection accuracy of the water column. The experimental results show that the above algorithm can effectively improve the detection accuracy and positioning accuracy of the water column at the impact point.
A CLUMondo Model-Based Multi-Scenario Land-Use Change Simulation in the Yangtze River Delta Urban Agglomeration, China
Authors: Zhao Yanhua , Su De , Bao Yang , Yang Wei , Sun Yibo
Published: November 2022

Land-use changes have profound effects on both socio-economic development and the environment. As a result, to optimize land-use planning and management, models are often employed to identify land-use patterns and their associated driving forces. In this work, physical and socioeconomic factors within the Yangtze River Delta Urban Agglomeration (YRDUA) from 2000 to 2015 were identified, integrated, and used as the foundation for a CLUMondo model. Subsequently, the Markov model and the CLUMondo model were combined to predict land-use changes in 2035. Natural growth (NG), economic development (ED), ecological protection (EP), and coordinated social and economic development (CSE) scenarios were set according to the land-use date in the assessment. Results showed that: (1) From 2000 to 2015, urban land increased by 8139.5 km2 (3.93%), and the paddy field decreased by 7315.8 km2 (8.78%). The Kappa coefficient of the CLUMondo model was 0.86, indicating that this model can be used to predict the land-use changes of the YRDUA. (2) When this trend was used to simulate landscape patterns in 2035, the land-use structure and landscape patterns varied among the four simulated urban development scenarios. Specifically, urban land increased by 47.6% (NG), 39.6% (ED), 32.9% (EP), and 23.2% (CSE). The paddy field was still the primary landscape, with 35.85% NG, 36.95% ED, 37.01% EP, and 36.96% CSE. Furthermore, under all four scenarios, the landscape pattern tended to simplify and fragment, while connectivity and equilibrium diminished. The results provided herein are intended to elucidate the law of urban agglomeration development and aid in promoting urban sustainable development.
Cellulose Textiles from Hemp Biomass: Opportunities and Challenges
Authors: Lawson Lelia , Degenstein Lauren M. , Bates Bronwyn , Chute Wade , King Dan , Dolez Patricia I.
Published: November 2022

Worldwide demand for man-made cellulosic fibres (MMCF) are increasing as availability of cotton fibre declines due to climate change. Feedstock for MMCF include virgin wood, agricultural residues (e.g., straw), and pre- and post-consumer cellulosic materials high in alpha-cellulose content. Lyocell MMCF (L-MMCF) offer large advantages over other MMCF processes in terms of both environmental and social impacts: the solvent for cellulosic dissolution, n-methyl-morpholine-n-oxide, can be recycled, and the process utilizes non-toxic chemicals and low amounts of water. Hemp can be a preferential cellulosic feedstock for L-MMCF as hemp cultivation results in carbon dioxide sequestration, and it requires less water, fertilizers, pesticides, and herbicides than other L-MMCF feedstock crops. These factors contribute to hemp being an environmentally conscious crop. The increased legalization of industrial hemp cultivation, as well as recent lifts on cannabis restrictions worldwide, allows accessibility to local sources of cellulose for the L-MMCF process. In addition, hemp biomass can offer a much larger feedstock for L-MMCF production per annum than other cellulosic sources, such as eucalyptus trees and bamboo. This paper offers perspectives on the agricultural, manufacturing, and economic opportunities and challenges of utilizing hemp biomass for the manufacturing of L-MMCF.
A Modified Wei-Hua-He Digital Signature Scheme Based on Factoring and Discrete Logarithm
Authors: R Elumalai , Anjaneyulu G.
Published: November 2022

A symmetric cipher such as AES in cryptography is much faster than an asymmetric cipher but digital signatures often use asymmetric key ciphers because they provides the sender’s identity and data integrity. In this paper, a modified-He digital signature scheme is proposed using a one-way hash function. The proposed scheme, unlike the He signature technique, employs Euclid’s Division Lemma with large prime moduli p. Its security is built on large integer factoring, discrete logarithms and expanded root problems. The time complexity of the proposed scheme is O(log3p). The proposed modified-He scheme is efficient, as evidenced by the analytical results with key lengths greater than 512 bits.
Research on Consumer Identity in Using Sustainable Mobility as a Service System in a Commuting Scenario
Authors: Cao Ming , Yang Chun
Published: November 2022

Social and economic development leads to the continuous urbanization process, accompanied by the increasingly prominent traffic congestion problem. Traffic congestion also brings problems such as serious environmental pollution and intensified social conflicts. Therefore, how to alleviate traffic congestion has become a concern of the government and related researchers. As the main cause of urban traffic, the efficiency of urban commuting is considered as the best embodiment of urban functionality. The mobile as a service (Maas) system may be a better solution. In order to make the mobile as a service system more popular, it is necessary to understand the internal motivations driving people’s corresponding behaviors. Therefore, this study aimed to explore the internal logic of consumer identity, attitude and related intentions through a structural equation model and chi-square analyses. The final behavioral intention of commuting consumers towards MaaS was explored by integrating relevant theoretical models and comparing different levels of identification and the views of different consumers towards MaaS. A result was provided that can be used by relevant government agencies or practitioners in order to gain a deeper understanding of the internal perceptions of consumers and promote the optimization and innovation of MaaS systems. In addition, the results of this study also identified the potential necessary factors for the adoption of MaaS by commuting consumers, which may influence the improvement or development of relevant policies. The results showed that the model used in this study was applicable to the consumption cognition of the MaaS system in the commuting scenario, which shows that the model has a certain effect in explaining consumers’ sustainable consumption attitudes, identities and intentions. The internalization of sustainable identity is the most important part for consumers, which indicates that consumers attach great importance to self-value affirmation and mutual affirmation of sustainable concepts. However, in the consumer group, there were still some consumers who had not transformed their sustainable attitudes and recognitions into actual behavior. Converting such consumers is, therefore, crucial and an important step towards sustainable development.
Detoxification of the Mycotoxin Citrinin by a Manganese Peroxidase from Moniliophthora roreri
Authors: Wang Shuai , Wang Xiaolu , Huang Huoqing , Tu Tao , Luo Huiying , Zhang Yuhong , Liu Bo , Yao Bin , Zhang Wei , Su Xiaoyun
Published: November 2022

Citrinin (CIT) is a mycotoxin found in foods and feeds and most commonly discovered in red yeast rice, a food additive made from ordinary rice by fermentation with Monascus. Currently, no enzyme is known to be able to degrade CIT effectively. In this study, it was discovered that manganese peroxidase (MrMnP) from Moniliophthora roreri could degrade CIT. The degradation appeared to be fulfilled by a combination of direct and indirect actions of the MrMnP with the CIT. Pure CIT, at a final concentration of 10 mg/L, was completely degraded by MrMnP within 72 h. One degradation product was identified to be dihydrocitrinone. The toxicity of the CIT-degradation product decreased, as monitored by the increased survival rate of the Caco-2 cells incubated with MrMnP-treated CIT. In addition, MrMnP could degrade CIT (with a starting concentration of up to 4.6 mg/L) completely contaminated in red yeast rice. MrMnP serves as an excellent candidate enzyme for CIT detoxification.