bluuebunny/crossref_metadata_2025 huggingface dataset:
Study of a Mixed Conductive Layer Fabricated by Ion Implantation and Distribution Theory
Authors: Fan Xuerui , Zhang Huiyan , Wei Yi , Huang Yao , He Huimei , Wang Yun , Meng Qingyun , Wu Wenjie
Published: January 2023

Electrodes are essential parts of capacitors that can consist of a variety of materials depending on the application. In dielectric elastomer transducers (DETs)—a type of special variable capacitor—the electrode needs to deform with a soft base. However, the current carbon-based electrodes are not stable, and the metal-based ones are not flexible for use in DETs. Thus, the need to fabricate an electrode which can meet both the stability and flexibility requirements is extremely important. In this work, silver ions with energy levels of 40 keV were implanted into the surface of polydimethylsiloxane (PDMS) to explore the effect of ion implantation on surface conductivity. The experimental results showed that the surface resistivity of PDMS reached 251.85 kΩ per square and dropped by 10 orders of magnitude after ion implantation. This indicates that the surface conductivity was significantly improved. EDS characterization results showed that the maximum penetration depth that ions could reach was about 2.5 μm. The surface resistivity of the sample coated with carbon black was further reduced by an order of magnitude after ion implantation and changed more stably with time. A quasi-melting-collision model was established to investigate the distribution of carbon black particles. The concentration of carbon black particles at a distance from the PDMS surface followed a Gaussian-like distribution.
Type-A Gelatin-Based Hydrogel Infiltration and Degradation in Titanium Foams as a Potential Method for Localised Drug Delivery
Authors: Mehdi-Sefiani Hanaa , Perez-Puyana Víctor , Ostos Francisco José , Sepúlveda Ranier , Romero Alberto , Rafii-El-Idrissi Benhnia Mohammed , Chicardi Ernesto
Published: January 2023

A gelatin-based hydrogel was infiltrated and degraded-released in two different titanium foams with porosities of 30 and 60 vol.% (Ti30 and Ti60 foams) and fabricated by the space holder technique to evaluate its potential to act as an innovative, alternative, and localised method to introduce both active pharmaceutical ingredients, such as antibiotics and non-steroidal anti-inflammatory drugs, and growth factors, such as morphogens, required after bone-tissue replacement surgeries. In addition, the kinetic behaviour was studied for both infiltration and degradation-release processes. A higher infiltration rate was observed in the Ti60 foam. The maximum infiltration hydrogel was achieved for the Ti30 and Ti60 foams after 120 min and 75 min, respectively. Further, both processes followed a Lucas-Washburn theoretical behaviour, typical for the infiltration of a fluid by capillarity in porous channels. Regarding the subsequent degradation-release process, both systems showed similar exponential degradation performance, with the full release from Ti60 foam (80 min), versus 45 min for Ti30, due to the greater interconnected porosity open to the surface of the Ti60 foam in comparison with the Ti30 foam. In addition, the optimal biocompatibility of the hydrogel was confirmed, with the total absence of cytotoxicity and the promotion of cell growth in the fibroblast cells evaluated.
Research Status and Prospects of Control Strategies for High Speed On/Off Valves
Authors: Gao Qiang , Wang Jie , Zhu Yong , Wang Jun , Wang Jinchuan
Published: January 2023

As the working conditions of host equipment become more complex and severe, performance improvement and increased intelligence of high speed on/off valves (HSV) are inevitable trends in the development of digital hydraulic technology. The characteristics of HSVs can be regulated by control strategies, which determine the comprehensive performance of the system. This paper discusses the development of control strategies for HSVs. First, the results of research in relation to the discrete voltage and pulse control of single HSVs and the coding control of parallel HSVs are summarized. In addition, the advantages, disadvantages and application scope of different control strategies are analyzed and compared. Finally, the development trends are predicted from the performance regulation, intelligent maintenance, intelligent coding and function programmability.
Investigation of Island Growth on Fluidized Particles Coated by Means of Aerosol
Authors: Akbas Serap , Chen Kaicheng , Hoffmann Torsten , Scheffler Franziska , Tsotsas Evangelos
Published: January 2023

In this study, an aerosol fluidized bed is used to coat particles. A new aerosol generator is used to obtain coating solution droplets with a diameter of around 1 μm or smaller. Glass particles, which have a mean diameter of 653 μm, were the non-porous core material and the coating solution was sodium benzoate. Scanning electron microscope pictures were analyzed by MATLAB image processing for evaluating the coverage with the curvature effect. Monte Carlo simulation was used to describe the coating of fluidized particles by aerosol droplets. The purpose of this work was the determination of possible island growth on particles, and investigation of the reasons of it by comparing the experimental and simulation results. The preferential deposition of droplets on already occupied positions is seen as the main possible reason for island growth.
Combining APHRODITE Rain Gauges-Based Precipitation with Downscaled-TRMM Data to Translate High-Resolution Precipitation Estimates in the Indus Basin
Authors: Noor Rabeea , Arshad Arfan , Shafeeque Muhammad , Liu Jinping , Baig Azhar , Ali Shoaib , Maqsood Aarish , Pham Quoc Bao , Dilawar Adil , Khan Shahbaz Nasir , Anh Duong Tran , Elbeltagi Ahmed
Published: January 2023

Understanding the pixel-scale hydrology and the spatiotemporal distribution of regional precipitation requires high precision and high-resolution precipitation data. Satellite-based precipitation products have coarse spatial resolutions (~10 km–75 km), rendering them incapable of translating high-resolution precipitation variability induced by dynamic interactions between climatic forcing, ground cover, and altitude variations. This study investigates the performance of a downscaled-calibration procedure to generate fine-scale (1 km × 1 km) gridded precipitation estimates from the coarser resolution of TRMM data (~25 km) in the Indus Basin. The mixed geographically weighted regression (MGWR) and random forest (RF) models were utilized to spatially downscale the TRMM precipitation data using high-resolution (1 km × 1 km) explanatory variables. Downscaled precipitation estimates were combined with APHRODITE rain gauge-based data using the calibration procedure (geographical ratio analysis (GRA)). Results indicated that the MGWR model performed better on fit and accuracy than the RF model to predict the precipitation. Annual TRMM estimates after downscaling and calibration not only translate the spatial heterogeneity of precipitation but also improved the agreement with rain gauge observations with a reduction in RMSE and bias of ~88 mm/year and 27%, respectively. Significant improvement was also observed in monthly (and daily) precipitation estimates with a higher reduction in RMSE and bias of ~30 mm mm/month (0.92 mm/day) and 10.57% (3.93%), respectively, after downscaling and calibration procedures. In general, the higher reduction in bias values after downscaling and calibration procedures was noted across the downstream low elevation zones (e.g., zone 1 correspond to elevation changes from 0 to 500 m). The low performance of precipitation products across the elevation zone 3 (>1000 m) might be associated with the fact that satellite observations at high-altitude regions with glacier coverage are most likely subjected to higher uncertainties. The high-resolution grided precipitation data generated by the MGWR-based proposed framework can facilitate the characterization of distributed hydrology in the Indus Basin. The method may have strong adoptability in the other catchments of the world, with varying climates and topography conditions.
Novel Knowledge Graph- and Knowledge Reasoning-Based Classification Prototype for OBIA Using High Resolution Remote Sensing Imagery
Authors: Gun Zhao , Chen Jianyu
Published: January 2023

Although many machine learning methods have been successfully applied for the object-based classification of high resolution (HR) remote sensing imagery, current methods are highly dependent on the spectral similarity between segmented objects and have disappointingly poor performance when dealing with different segmented objects that have similar spectra. To overcome this limitation, this study exploited a knowledge graph (KG) that preserved the spatial relationships between segmented objects and has a reasoning capability that can assist in improving the probability of correctly classifying different segmented objects with similar spectra. In addition, to assist the knowledge graph classifications, an image segmentation method generating segmented objects that closely resemble real ground objects in size was used, which improves the integrity of the object classification results. Therefore, a novel HR remote sensing image classification scheme is proposed that involves a knowledge graph and an optimal segmentation algorithm, which takes full advantage of object-based classification and knowledge inference. This method effectively addresses the problems of object classification integrity and misclassification of objects with the same spectrum. In the evaluation experiments, three QuickBird-2 images and over 15 different land cover classes were utilized. The results showed that the classification accuracy of the proposed method is high, with overall accuracies exceeding 0.85. These accuracies are higher than the K Nearest Neighbors (KNN), Support Vector Machine (SVM), Decision Tree (DT), and Random Forest (RF) methods. The evaluated results confirmed that the proposed method offers excellent performance in HR remote sensing image classification.
Scene Classification Based on Heterogeneous Features of Multi-Source Data
Authors: Xu Chengjun , Shu Jingqian , Zhu Guobin
Published: January 2023

Remote sensing scene classification is quite important in earth observation and other fields. Previous research has found that most of the existing models are based on deep learning models. However, the classification accuracy of the deep learning model is difficult to break through due to the challenges of difficulty distinguishing the socio-economic attributes of scenes, high interclass similarity, and large intraclass differences. To tackle the challenges, we propose a novel scene classification model that integrates heterogeneous features of multi-source data. Firstly, a multi-granularity feature learning module is designed, which can conduct uniform grid sampling of images to learn multi-granularity features. In this module, in addition to the features of our previous research, we also supplemented the socio-economic semantic features of the scene, and attention-based pooling is introduced to achieve different levels of representation of images. Then, to reduce the dimension of the feature, we adopt the feature-level fusion method. Next, the maxout-based module is designed to fuse the features of different granularity and extract the most distinguishing second-order latent ontology essence features. The weighted adaptive fusion method is used to fuse all the features. Finally, the Lie Group Fisher algorithm is used for scene classification. Extensive experimentation and evaluations show that our proposed model can find better solutions to the above challenges.
Rice Straw Composting Improves the Microbial Diversity of Paddy Soils to Stimulate the Growth, Yield, and Grain Quality of Rice
Authors: Huang Xingchen , Wang Hong , Zou Yuning , Qiao Cece , Hao Bing , Shao Qingqin , Wu Wenge , Wu Hua , Zhao Jianrong , Ren Lantian
Published: January 2023

This study aimed to explore the effects of straw compost with different proportions as replacement to chemical fertilizer on soil microorganisms as well as rice growth yield and quality. The rice variety Quan9you 063 in Fengyang, Anhui province was employed as the research subject. Four experimental treatments were set: local conventional fertilization as a control (CK) and compost substituting chemical fertilizer at 10% (T1), 20% (T2), and 30% (T3) to investigate the effects of straw composting. Our findings revealed that T1 treatment had the best rice yield-increasing effect (p < 0.05). Compared with CK, the rice yield, grain number per panicle, and rice polishing rate increased by 6.43%, 21.60%, and 0.47%, respectively; the chalkiness and chalky grain rate decreased by 25.77% and 55.76%, respectively. The T1 treatment achieved significantly higher relative abundance of β-Proteobacteria, Sideroxydans, Methanoregula, and Candidatus Nitrosocosmicus, indicating that the compost replacing 10% chemical fertilizer notably increased the microbial diversity. Hence, the replacement of 10% of chemical fertilizers with compost can enhance the rice yield.
Urban Planning for Climate Change: Comparing Climate Adaptation Plans between Taipei and Boston
Authors: Tu Shin , Yu Siyu
Published: January 2023

Climate change issues are gradually gaining attention in the planning field, especially in urban regions due to high vulnerability caused by their dense population and complex networks. Communities depend on local policy tools to identify threats, determine goals, and implement strategies. Consequently, many cities around the world have developed climate adaptation plans to reduce climate impacts in the past decades. This study applied a plan evaluation framework to analyze and compare the plan quality of the latest climate adaptation plan in Taipei and Boston. The study examines key elements of adaptation plans to reveal strengths and weaknesses, and to compare and learn between adaptation plans internationally. Findings suggest that the framework provides comparable measures and analysis across international settings. We find that Taipei has a weak fact base and fails to address uncertainty, which importance in adaptation plans has been acknowledged only recently. We also identified shortfalls in public participation and implementation items in both cities. The study concludes by discussing results and giving recommendations to inform more effective approaches as practitioners develop or reevaluate climate adaptation plans.
Ethnic Soups from Rupea Area (Romania) as Resources for Sustainable Local Development
Authors: Borcoman Mariana , Sorea Daniela
Published: January 2023

In Rupea area, in central Romania, Romanians, Saxons, Magyars and Roma people live. Their traditional ethnic cuisines represent intangible cultural heritage resources. In a qualitative research based on semi-structured interviews with respondents from all four ethnicities, we identified the dishes, spices and tastes considered representative by them through thematic analysis. We compared ethnic gastronomic characteristics using doublets of gustemes, based on Claude Lévi-Strauss’ model, and highlighted the touristic potential of serving the soups of all ethnic groups as a common touristic package. The comparison highlighted similarities due to the dependence of all locals on indigenous food resources, but also differences due to the different propensity to capitalize on spontaneous flora or to adopt Austro-Hungarian influences. The soups, with their similarities and differences, are gastronomic reflections of the historical status and the long coexistence of the ethnic groups in Transylvania. The touristic capitalization of soups as an intangible cultural heritage resource can become a source of income for local people, contributing to the strengthening of local identity and the sustainable development of the area. It is supported by social entrepreneurship tourism and the consolidation of local networks of producers. In addition, ethnic soups can also be used as a quick and effective lunch option for assisted elderly people, students or busy employees.
How Does Graduate Training Promote Sustainable Development of Higher Education: Evidence from China’s “Double First-Class” Universities’ Programs
Authors: Wang Man , Zhou Cheng
Published: January 2023

Higher education is crucial to sustainable development. The construction of a “double first-class” university (the 42 top universities in China) is an important initiative to improve the quality of higher education and promote its sustainable development. The aim of the study discussed here was to explore how graduate training promotes the sustainable development of higher education and the main characteristics of graduate training in China’s “double first-class” universities. The research in this paper involved 42 “double first-class” universities’ graduate training programs (including training objectives, training process, and training methods) for which coding analysis using NVivo12 plus was carried out. It was found that the main characteristics of China’s “double first-class” university graduate training are as follows: (1) clear decomposition of quality and ability structure; (2) taking quality as the core of the connotative development of higher education; and (3) innovation in talent training methods. This study focused on talent training itself, which is of significant importance in the competition for talent around the world. China’s double first-class universities can not only provide experience for the graduate education of domestic universities, but also for those in other countries.
Identifying Traffic Congestion Patterns of Urban Road Network Based on Traffic Performance Index
Authors: Zang Jinrui , Jiao Pengpeng , Liu Sining , Zhang Xi , Song Guohua , Yu Lei
Published: January 2023

Urban congestion has become a global problem with urbanization and motorization. The analysis of time-varying traffic congestion patterns is necessary to formulate effective management strategies. The existing studies have focused on traffic flow patterns developed by the volume, speed and density of road sections in a limited district, while the long-time analysis of congestion patterns of the macro road network at the city level is inadequate. This paper aims to recognize traffic congestion patterns of the urban road network based on the traffic performance index (TPI) of 699 days in 2018, 2019 and 2021 in Beijing. The self-organizing maps (SOM) method improved by an automatic clustering number determination algorithm is proposed to cluster congestion patterns based on time-varying TPI. The traffic congestion of the macro road network is clustered into Mondays, Fridays, ordinary weekdays, congested weekdays, weekdays of winter and summer vacation, Saturdays, Sundays and festivals patterns. Patterns of Mondays and congested weekdays have a prominent morning peak, while patterns of Fridays, ordinary weekdays, and weekdays of winter and summer vacation have a prominent evening peak. Saturdays, Sundays and festivals are less congested than weekday patterns. It is verified that the SOM method proposed in this paper clusters traffic congestion into more detailed and accurate patterns, and it is applicable to TPI clustering in different years. The degree of congestion in 2021 increases by 7.15% in peak hours and decreases by 7.50% in off-peak hours compared with that in 2019 due to COVID-19. This method is helpful for traffic management in terms of making decisions according to different congestion patterns.
Simplified Model Predictive Current Control of Four-Level Nested Neutral Point Clamped Converter
Authors: Atif Rao , Hassan Mannan , Shahid Muhammad Bilal , Munir Hafiz Mudassir , Saeed Mahmoud S. R. , Shahzad Muhammad , Isik Semih , Alharbi Mohammed
Published: January 2023

Model predictive control (MPC) is an efficient and growing approach to power converter control. This paper proposes an improved and simplified model predictive current control (MPCC) technique for a four-level nested neutral point clamped (4L-NNPC) converter. Conventional MPCC exhibits better performances as compared to the conventional linear control system such as fast dynamic response, consideration of the system constraints, and nonlinearities. However, the application of the conventional model predictive current control (MPCC) approach on complex systems provokes a significant number of calculations, which is the main hurdle to its practical implementation. To fix this flaw, this paper proposes an effective algorithm to shorten the execution time of the conventional MPCC. In this proposed technique, 216 current predictions of the conventional MPCC are skipped and converted into one required voltage vector (RVV) prediction. With this equivalent reference voltage transformation, the calculation burden of MPCC is significantly reduced, while the output performance is not influenced. The results of the simplified MPCC for the 4L-NNPC converter are analyzed and compared with the conventional MPCC. The computational time is reduced by 19.56% using the simplified MPCC, while keeping an approximately similar error of output currents. The switching frequency and total harmonic distortion (THD) of the proposed method are reduced by 8.16% and 0.07%, respectively, as compared to the conventional technique. These results demonstrate the fact that that the performance of a conventional MPCC is enhanced with the proposed MPCC. The proposed algorithm can be applied to several inverter topologies.
Opportunities and Directions of Development of Agritourism: Evidence from Samarkand Region
Authors: Togaymurodov Elbek , Roman Michał , Prus Piotr
Published: January 2023

Agritourism can enhance rural development and is a useful alternative activity to increase farm incomes. It has attracted the attention of agricultural experts and researchers around the world in recent years. As a result of rapid growth worldwide, agritourism has become one of the most significant supplementary income sources for farmers. The main purpose of this study is to identify factors influencing participation of fermer in agritourism in the Samarkand region of Uzbekistan, using scientific studies and statistical data, which indicate that there are great opportunities for agritourism activities. Increasing the economic potential of the rural areas by introducing innovative activities on the Samarkand region’s medium-sized farms (fermers) and ensuring sustainable development are essential. In Samarkand, there are a lot of conditions for the development of tourism, especially agritourism. The study examined all 10 agritourism fermers and 100 randomly selected fermers in Samarkand that do not carry out agritourism activities. Based on this data collection and analysis using a logistic regression model, the results showed several factors influencing the participation of fermers in the Samarkand region in agritourism activities, which was analyzed using the logistic regression model. According to the results of this model, each fermer’s income, employment, fermer’s education, and distance from the city had a significantly positive effect on the fermer’s initiation of agritourism.
Effects of Object-Oriented Advance Guidance Signage on Lane-Changing Behaviors at the Mainline Toll Stations of Expressways
Authors: Wang Chaolun , Xiang Wang , Xu Guiqiu , Li Xiaomeng
Published: January 2023

China has actively promoted electronic toll collection (ETC), increasing the proportion of ETC vehicles, and the number of ETC lanes at mainline toll stations has exceeded that of manual toll collection (MTC) lanes. To investigate the effects of ETC and MTC vehicles as guidance objects on the lane-changing behaviors of drivers, we designed three guidance signal plans, including the original sign plan (OR), a complete MTC sign plan (CMS), and a complete MTC sign plan with voice warnings (VW&CMS), for expressway mainline toll lanes. A driving simulator experiment with 40 participants was conducted to evaluate the efficacy of the plans. Generalized estimating equations were used to analyze the characteristics of lane-changing behaviors in different guidance plans, and an entropy weight model using the technique of ranking the order of preference by its similarity to the ideal solution (TOPSIS) was constructed to evaluate the guidance effects of different plans. The results showed that the CMS and VW&CMS plans significantly improved lane-changing behaviors. This improvement is demonstrated by a higher lane-changing ratio, shorter response time, earlier initiation of lane-changing location, higher speed, lower deceleration rate, and longer lane-changing duration distance. These findings can help expressway designers to optimize the guidance-sign system for mainline toll stations.
Shifting the Focus to Measurement: A Review of Socially Responsible Investing and Sustainability Indicators
Authors: Koenigsmarck Markus , Geissdoerfer Martin
Published: January 2023

An increasing number of investors is including sustainability considerations in their investment processes. This can improve both financial and corporate sustainability performance. The emergence of sustainable investing as an academic research field has been accompanied by considerable interest from the industry. Despite its importance, there is still no uniform understanding of what a socially responsible investment (SRI) comprises. There is a multitude of similar terms that are not clearly defined and delineated, accompanied by a lack of a uniform understanding of how sustainability should be measured in the investment context. The resulting confusion hinders conceptual clarity, a material barrier for both scholarly and practitioner endeavours in the field. We try to address these issues by conducting a structured literature review based on database searches and cross-reference snowballing. We aim to provide a synthesised and unified definition of SRI and ancillary terms and to draw attention to the exact sustainability measurements. We (1) outline the history of the concept, (2) concisely define SRI and related terms, (3) propose a trinomial sustainability indicator framework (the Cambridge SRI indicator framework) for conceptualisation, and (4) use this framework to provide a structured overview of sustainability indicators for SRIs.
Sustainable Business Models Innovation and Design Thinking: A Bibliometric Analysis and Systematic Review of Literature
Authors: Kurek Juliana , Brandli Luciana Londero , Leite Frandoloso Marcos Antonio , Lange Salvia Amanda , Mazutti Janaina
Published: January 2023

The process of integrating sustainability into businesses and processes is still recent, both in startups, small and medium-sized companies and even multinationals. Sustainable business models became a phenomenon of global interest and Design Thinking has been increasingly used as a strategy to support this process. In this context, the aim of this article is to improve the understanding of how Design Thinking (DT) and its set of tools and methods contribute to the creation and innovation of sustainable business models (SBM). The analysis of frameworks indicates that the main methodologies linking Design Thinking and Sustainable Business Models are Workshops, Brainstorming, Co-creation and Prototyping. Also, approaches such as Circular Economy, Business Models and Product-Service System models are emerging as a means of enabling the collaborative consumption of products and services and with positive results for sustainable business. The analysis of the articles reveals that user-oriented innovation and analysis of stakeholder needs is present in practically all evaluated frames, but prototyping and experimentation represent a gap that should be better explored in the frameworks.
Accounting for Carbon Emissions—Current State of Sustainability Reporting Practice under the GHG Protocol
Authors: Kasperzak Rainer , Kureljusic Marko , Reisch Lucas , Thies Simon
Published: January 2023

Climate-related reporting has become an integral part of firms’ disclosure. In this context, firms’ greenhouse gas (GHG) emissions are of major importance to stakeholders and management. For measuring GHG emissions, a global standard has been established with the GHG Protocol. This standard contains an important accounting policy option that significantly affects firms’ reported emissions by allowing them to use different consolidation approaches: the equity share, operational control, and financial control approach. However, there is limited evidence on firms’ use of these approaches, resulting in a lack of foundation for discussing the approaches’ sufficiency to support achieving environmental sustainability. Therefore, this paper aims to close this research gap by empirically investigating the approaches’ relevance using 16,604 firm-year observations between 2009 and 2019. We demonstrate that the operational control approach is used by most firms and that its predominance substantially increased during the last decade. However, the predominant use of the operational control approach is not fully compatible with societal and political sustainability goals as expressed in recent sustainability regulations. Therefore, policy makers need to critically assess whether current GHG reporting supports achieving their goals. Furthermore, we develop a research agenda to encourage future researchers to contribute to improvements in GHG reporting.
Geochemistry Process from Weathering Rocks to Soils: Perspective of an Ecological Geology Survey in China
Authors: Guo Xiao-Yu , Li Jun , Jia Yan-Hui , Yuan Guo-Li , Zheng Ji-Lin , Liu Zhi-Jie
Published: January 2023

Ecological characteristics are very important for the Earth’s environment and human lives. Recently, more attention has been paid to the ecological problems in the world. The soil and its parent materials/rocks serve as the supporting materials for the ecological system on the Earth’s surface. The ecological characteristics in one region are associated with or even dependent on the soil-forming process. Thus, the study of the weathering process of parent materials/rocks is important for our understanding of the geological genesis of ecological problems. In this study, three typical ecological problems in China are introduced: land salinization in the north, the desertification of land in the northwest, and Karst rocky desertification in the south. We chose 23 typical profiles for observation and sampling. The soil-forming processes in these areas were investigated by geochemical research, and eco-geology models were subsequently established to explain the profound relationship between vegetation cover and the soil-forming process. Our work first focuses on the geochemical methods used to explore these ecological issues, emphasizing the contribution of the geological genesis to the ecological characteristics. Using geochemical methods, such as the chemical index of alteration (CIA), major element and trace element distribution characteristics, the formation processes, and characteristics of bedrock-weathering soils under diverse epigenetic geological settings were determined. Eco-geology models were then developed by evaluating the vertical structure and material composition of soil, the characteristics of elemental migration during soil formation, and the enrichment and loss of elements in the supporting layers and their repercussions.
Investigation into the Water Exit Behavior of a Cavity
Authors: Li Xueyi , Zheng Feidong
Published: January 2023

Launching-type ship lifts are commonly used in navigational mountain rivers to realize river channelization and communicate different water systems. However, the complicated water–gas–solid coupling process incurred during the water exit of cavities beneath a ship chamber can strongly affect the stability of the chamber and even affect the ship lift operation. In this study, the water exit behavior of a generalized cavity model was investigated using an experimental–numerical approach. Both the air pressure and flow patterns during the water exit process were analyzed. The results demonstrate three different types of air pressure process in cavity exits. Based on the results, a series of relationships are proposed to predict the maximum negative pressure incurred in the water exit process. Moreover, a method was developed to determine the optimum ported area of the cavity regarding the absence of additional hydrodynamic loads. Furthermore, a classification system to typify the flow patterns manifesting in the cavity is proposed. It was found that the transition from a slug flow to a drop flow could be determined as a transition coefficient K equal to 1.
A Third Angular Momentum of Photons
Authors: Sahoo Pathik , Singh Pushpendra , Manna Jhimli , Singh Ravindra P. , Hill Jonathan P. , Nakayama Tomonobu , Ghosh Subrata , Bandyopadhyay Anirban
Published: January 2023

Photons that acquire orbital angular momentum move in a helical path and are observed as a light ring. During helical motion, if a force is applied perpendicular to the direction of motion, an additional radial angular momentum is introduced, and alternate dark spots appear on the light ring. Here, a third, centrifugal angular momentum has been added by twisting the helical path further according to the three-step hierarchical assembly of helical organic nanowires. Attaining a third angular momentum is the theoretical limit for a photon. The additional angular momentum converts the dimensionless photon to a hollow spherical photon condensate with interactive dark regions. A stream of these photon condensates can interfere like a wave or disintegrate like matter, similar to the behavior of electrons.
Effectiveness of AR Board Game on Computational Thinking and Programming Skills for Elementary School Students
Authors: Huang Shih-Yun , Tarng Wernhuar , Ou Kuo-Liang
Published: January 2023

This study integrated the augmented reality (AR) technology into the “Coding Ocean” board game to provide players with real-time simulation of ship paths and learning scaffolds. Combined with Scratch block-based programming, an interactive learning environment is developed to assist elementary school students in learning coding skills from the unplugged board game to enhance their computational thinking concepts. The AR board game is focused on the programming concepts of sequential, and/or and loop. Through the process of treasure hunting, the basic concepts of computational thinking can be developed, i.e., abstraction, problem decomposition, pattern recognition and algorithmic thinking. In order to investigate the learning effectiveness of the AR board game on computational thinking and programming skills, a number of 51 third graders from an elementary school were recruited as research samples. The experimental group (n = 26) used the AR board game and the control group (n = 25) used the traditional board game for game-based learning. The experimental results indicate: (1) the learning effectiveness of computational thinking for the experimental group was significantly higher than that of the control group; (2) the learning achievement of the block-based programming skills for the experimental group was significantly higher than that of the control group; (3) the cognitive load of the experimental group was significantly lower than that of the control group. The AR technology can combine the unplugged board games with plugged learning modules to assist students in game-based learning, which is useful for enhancing computational thinking abilities while reducing the cognitive load.
Motor Vehicle Insurance Anti-Fraud Modeling Based on a Stochastic Differential Game System
Authors: Li Meixuan , Liu Wei , Yan Chun , Zhang Mengchao
Published: January 2023

In this paper, we regard policyholders, insurance companies, and government departments to be an anti-fraud supervision system, and we explore the supervision of motor vehicle insurance fraud from the perspective of a tripartite game. Taking into consideration the bad reputation records of policyholders as a state variable, through continuous accumulation in effective time, it creates a continuous growth-type warning effect on policyholders, and thus, effectively curbs policyholder fraud and false supervision by insurance companies. At the same time, by considering the influence of random factors on the anti-fraud game of motor vehicle insurance, in this paper, we establish a stochastic differential game model to explore the optimal strategy, the optimal income level, and the expectation and variance of the insured’s bad reputation record stock under the conditions of with and without government supervision. Finally, through a simulation analysis, it is found that the game with government supervision is more conducive to reduce the insured’s fraud intensity, and the simulation proves the impact of different parameters on system stability.
Remediation Agents Drive Bacterial Community in a Cd-Contaminated Soil
Authors: Cui Wenzhi , Liu Yingying , Li Wenguang , Pei Lei , Xu Shuang , Sun Yuhuan , Liu Jianbo , Wang Fayuan
Published: January 2023

Soil remediation agents (SRAs) such as biochar and hydroxyapatite (HAP) have shown a promising prospect in in situ soil remediation programs and safe crop production. However, the effects of SRAs on soil microbial communities still remain unclear, particularly under field conditions. Here, a field case study was conducted to compare the effects of biochar and HAP on soil bacterial communities in a slightly Cd-contaminated farmland grown with sweet sorghum of different planting densities. We found that both biochar and HAP decreased the diversity and richness of soil bacteria, but they differently altered bacterial community structure. Biochar decreased Chao1 (−7.3%), Observed_species (−8.6%), and Shannon indexes (−1.3%), and HAP caused Shannon (−2.0%) and Simpson indexes (−0.1%) to decline. The relative abundance (RA) of some specific taxa and marker species was differently changed by biochar and HAP. Overall, sweet sorghum cultivation did not significantly alter soil bacterial diversity and richness but caused changes in the RA of some taxa. Some significant correlations were observed between soil properties and bacterial abundance. In conclusion, soil remediation with biochar and HAP caused alterations in soil bacterial communities. Our findings help to understand the ecological impacts of SRAs in soil remediation programs.
The Size Screening Could Greatly Degrade the Health Risk of Fish Consuming Associated to Metals Pollution—An Investigation of Angling Fish in Guangzhou, China
Authors: Miao Xiongyi , Zhang Qian , Hao Yupei , Zhang Hucai
Published: January 2023

Fish size can heavily impact the bioaccumulation of metals, but it was rarely applied to screen out the fish with low health risk for consuming. Given the widespread metals contamination of angling fish, the angling fish collected from Guangzhou, China, were taken as an example in this study. The screening length and weight were detailed in accordance with the investigation of metals contamination among angling fish. Importantly, the feasibility of size screening on mitigating the health risk of angling fish was evaluated. The results revealed that the concentration of Cr and As were relatively high and beyond the maximum residue limit (MRL) in some fish. The mean pollution index (Pi) of As, Cr, and Pb were beyond 0.2, suggesting the widespread minor contamination. The total metal pollution index (MPI) manifested Oreochroms mossambcus was the most contaminated. The target hazard quotient (THQ) of Cr, As, and Hg were relatively higher, but the higher probability of THQ > 1 indicated the health risk should be dominantly from As. The highest TTHQ suggested the highest risk of Oreochroms mossambcus. Regression analysis determined the fish of THQ < 1 should be more likely centralized in the size that is beyond 13.7 cm and 45.0 g for adults and 19.8 cm and 127.9 g for children. Significantly reducing THQ among these screened fish confirmed their effect on the degrading health risk of metals; particularly, the children’s THQ returned below 1. The commonly contaminated Oreochroms mossambcus was further excluded to remove the screened fish with THQ > 1; the further decrease in THQ confirmed that the exclusion of a contaminated species could improve the effect of size screening.
Risk Assessment of Combined Exposure to Multiple Chemicals at the European Food Safety Authority: Principles, Guidance Documents, Applications and Future Challenges
Authors: Cattaneo Irene , Kalian Alexander D. , Di Nicola Matteo R. , Dujardin Bruno , Levorato Sara , Mohimont Luc , Nathanail Alexis V. , Carnessechi Edoardo , Astuto Maria Chiara , Tarazona Jose V. , Kass George E. N. , Liem Antoine K. Djien , Robinson Tobin , Manini Paola , Hogstrand Christer , Price Paul S. , Dorne Jean Lou C. M.
Published: January 2023

Human health and animal health risk assessment of combined exposure to multiple chemicals use the same steps as single-substance risk assessment, namely problem formulation, exposure assessment, hazard assessment and risk characterisation. The main unique feature of combined RA is the assessment of combined exposure, toxicity and risk. Recently, the Scientific Committee of the European Food Safety Authority (EFSA) published two relevant guidance documents. The first one “Harmonised methodologies for the human health, animal health and ecological risk assessment of combined exposure to multiple chemicals” provides principles and explores methodologies for all steps of risk assessment together with a reporting table. This guidance supports also the default assumption that dose addition is applied for combined toxicity of the chemicals unless evidence for response addition or interactions (antagonism or synergism) is available. The second guidance document provides an account of the scientific criteria to group chemicals in assessment groups using hazard-driven criteria and prioritisation methods, i.e., exposure-driven and risk-based approaches. This manuscript describes such principles, provides a brief description of EFSA’s guidance documents, examples of applications in the human health and animal health area and concludes with a discussion on future challenges in this field.
Anaerobes and Toxins, a Tradition of the Institut Pasteur
Authors: Popoff Michel R. , Legout Sandra
Published: January 2023

Louis Pasteur, one of the eminent pioneers of microbiology, discovered life without oxygen and identified the first anaerobic pathogenic bacterium. Certain bacteria were found to be responsible for specific diseases. Pasteur was mainly interested in the prevention and treatment of infectious diseases with attenuated pathogens. The collaborators of Pasteur investigated the mechanisms of pathogenicity and showed that some bacterial soluble substances, called toxins, induce symptoms and lesions in experimental animals. Anaerobic bacteriology, which requires specific equipment, has emerged as a distinct part of microbiology. The first objectives were the identification and taxonomy of anaerobes. Several anaerobes producing potent toxins were associated with severe diseases. The investigation of toxins including sequencing, mode of action, and enzymatic activity led to a better understanding of toxin-mediated pathogenicity and allowed the development of safe and efficient prevention and treatment (vaccination with anatoxins, specific neutralizing antisera). Moreover, toxins turned out to be powerful tools in exploring cellular mechanisms supporting the concept of cellular microbiology. Pasteurians have made a wide contribution to anaerobic bacteriology and toxinology. The historical steps are summarized in this review.
Analysis of SARS-CoV-2 Cases, COVID-19 Outcomes and Vaccinations, during the Different SARS-CoV-2 Variants in Greece
Authors: Malli Foteini , Lampropoulos Ioannis C. , Perlepe Garifallia , Papagiannis Dimitrios , Gourgoulianis Konstantinos I.
Published: January 2023

Since the emergence of the SARS-CoV-2 Omicron variant, many issues have arisen. We report SARS-CoV-2 vaccinations, SARS-CoV-2 cases and COVID-19 outcomes in Greece during weeks 2–26 of 2021 (Alpha variant period), weeks 27–51 of 2021 (Delta variant period) and week 51 of 2021 to week 27 of 2022 (Omicron variant period). The average weekly cases were higher during the Omicron period vs. the Delta (25,354.17 cases/week) and Alpha periods (11,238.48 cases/week). The average weekly vaccinations were lower in the Omicron period (26,283.69/week) than in the Alpha and Delta period. Joinpoint regression analysis identified that the trend of SARS-CoV-2 cases increased by 88.5% during the rise of the Omicron wave in Greece. The trend of the intensive care unit (ICU) admissions related to COVID-19 decreased by 5.0% immediately after the rise of Omicron while the trend of COVID-19-related deaths decreased by 8.1% from the 5th week of the Omicron wave until the end of the study. For vaccinations, an increasing trend of 8.3% was observed in the first half of 2021 (weeks 18–25/2021), followed by a decreasing trend in weeks 26–43/2021. For the weeks before and during the early rise of Omicron (44/2021–1/2022), we identified an increasing trend of 10.7% and for weeks 2–27/2022 we observed a decreasing trend of 18.1%. Unfortunately, we do not have available data about the vaccination status of the SARS-CoV-2 cases, ICU admissions or deaths. Our findings suggest that the Omicron variant is associated with increased transmissibility and reduced morbidity and mortality despite the previous increase in the trend of SARS-CoV-2 vaccinations.
A Simple Epidemiologic Model for Predicting Impaired Neutralization of New SARS-CoV-2 Variants
Authors: Lippi Giuseppe , Henry Brandon M. , Plebani Mario
Published: January 2023

This study is aimed at developing a simple epidemiologic model that could help predict the impaired neutralization of new SARS-CoV-2 variants. We explored the potential association between neutralization of recent and more prevalent SARS-CoV-2 sublineages belonging to the Omicron family (i.e., BA.4/5, BA.4.6, BA.2.75.2, BQ.1.1 and XBB.1) expressed as FFRNT50 (>50% suppression of fluorescent foci fluorescent focus reduction neutralization test) in recipients of four doses of monovalent mRNA-based coronavirus disease 2019 (COVID-19) vaccines, with epidemiologic variables like emergence date and number of spike protein mutations of these sublineages, cumulative worldwide COVID-19 cases and cumulative number of COVID-19 vaccine doses administered worldwide at the time of SARS-CoV-2 Omicron sublineage emergence. In the univariate analysis, the FFRNT50 value for the different SARS-CoV-2 Omicron sublineages was significantly associated with all such variables except with the number of spike protein mutations. Such associations were confirmed in the multivariate analysis, which enabled the construction of the equation: “−0.3917 × [Emergence (date)] + 1.403 × [COVID-19 cases (million)] − 121.8 × [COVID-19 Vaccine doses (billion)] + 18,250”, predicting the FFRNT50 value of the five SARS-CoV-2 Omicron sublineages with 0.996 accuracy (p = 0.013). We have shown in this work that a simple mathematical approach, encompassing a limited number of widely available epidemiologic variables, such as emergence date of new variants and number of COVID-19 cases and vaccinations, could help identifying the emergence and surge of future lineages with major propensity to impair humoral immunity.