bluuebunny/crossref_metadata_2025 huggingface dataset:
Residence Time Section Evaluation and Feasibility Studies for One-Column Simulated Moving Bed Processes (1-SMB)
Authors: Zobel-Roos Steffen , Vetter Florian , Strube Jochen
Published: May 2023

The simulated moving bed (SMB) is a well-established, fully continuous process for chromatographic separation of difficult tasks with overlapping peaks, but it is relatively complex. The 1-SMB, which uses only one column but includes residence time zones to preserve concentration profiles, is a simpler semi-continuous alternative. This work examines the possible design of these residence time zones. Simulation studies were conducted to investigate the dependence of process metrics, such as purity, yield, productivity, and eluent consumption, on fluid dynamics. No deterioration in purity was observed, and the other variables remained constant over a wide range of axial dispersion before decreasing sharply. Pilot-scale experiments were conducted with various devices, including coiled flow inverters, eluate recycling devices, packed columns, and tank arrangements, to validate possible apparatus implementations with fluid dynamic measurements. It was demonstrated that the 1-SMB offers similar performance to the 4-SMB, albeit with reduced yield and lower apparatus complexity.
Understanding Embodied Effects of Posture: A Qualitative Study
Authors: Lin Karen , Broadbent Elizabeth
Published: May 2023

Some evidence suggests body postures can elicit emotion. Compared to neutral postures, constrictive postures are associated with negative affect and low arousal, whereas expansive postures have shown mixed effects. Qualitative methods may allow insights into this phenomenon. We asked 15 participants (mean age 43 years) to adopt eight different expansive, constrictive, or neutral postures, drawn from previous power posing or postural studies. After a minute in each posture, participants were interviewed about how they felt and when they might adopt the posture in real life. Interviews were audio recorded and inductive thematic analysis conducted. Power poses were associated with power and confidence, but also aggression, arrogance, intimidation, and disrespect. The slumped posture was associated with sadness and low control, and the upright seated posture with being alert and apprehensive as well as formality. Neutral postures were associated with feeling relaxed and comfortable. These results suggest that expansive postures have mixed emotional effects, but are inappropriate in some contexts.
Microplastic Pollution in Terrestrial Ecosystems and Its Interaction with Other Soil Pollutants: A Potential Threat to Soil Ecosystem Sustainability
Authors: Rai Meera , Pant Gaurav , Pant Kumud , Aloo Becky N. , Kumar Gaurav , Singh Harikesh Bahadur , Tripathi Vishal
Published: May 2023

The production and disposal of plastics have become significant concerns for the sustainability of the planet. During the past 75 years, around 80% of plastic waste has either ended up in landfills or been released into the environment. Plastic debris released into the environment breaks down into smaller particles through fragmentation, weathering, and other disintegration processes, generating microplastics (plastic particles ≤ 5 mm in size). Although marine and aquatic ecosystems have been the primary focus of microplastic pollution research, a growing body of evidence suggests that terrestrial ecosystems are equally at risk. Microplastic contamination has been reported in various terrestrial environments from several sources such as plastics mulch, pharmaceuticals and cosmetics, tire abrasions (tire wear particles), textiles industries (microfibers), sewage sludge, and plastic dumping. Recent studies suggest that the soil has become a significant sink for pollutants released into terrestrial ecosystems and is often contaminated with a mixture of organic and inorganic pollutants. This has gradually caused adverse impacts on soil health and fertility by affecting soil pH, porosity, water-holding capacity, and soil microbial enzymatic activities. Microplastics can interact with the co-existing pollutants of the environments by adsorbing the contaminants onto their surfaces through various intermolecular forces, including electrostatic, hydrophobic, non-covalent, partition effects, van der Waals forces, and microporous filling mechanisms. This subsequently delays the degradation process of existing contaminants, thereby affecting the soil and various ecological activities of the ecosystem. Thus, the present article aims to elucidate the deleterious impact of microplastics and their interactions with other pollutants in the terrestrial ecosystem. This review also addresses the impact of microplastics in disrupting the soil sustainability of the planet.
Monitoring the Impact of Heat Damage on Summer Maize on the Huanghuaihai Plain, China
Authors: Yang Lei , Song Jinling , Hu Fangze , Han Lijuan , Wang Jing
Published: May 2023

As an important food crop, summer maize is widely planted all over the world. Monitoring its growth and output is of great significance for world food security. With the trend of global warming and deterioration, the frequency of high temperature and heat damage affecting summer corn has been increasing in the past ten years. Therefore, there is an increasing demand for monitoring the high temperature and heat damage of summer maize. At present, there are nearly a hundred indices or methods for research on high temperature and heat damage. However, research based on the vegetation index cannot fully describe the damage caused by high-temperature thermal damage, and there is an obvious asynchrony effect. Research based on hyperspectral remote sensing has many inconveniences in data acquisition and complex physical model construction. Therefore, this study uses remote sensing data, including MODIS surface reflection data, MODIS land surface temperature products, as well as ground observation data and statistical data, combined with multiple remote sensing indices and land surface temperature, to construct a remote sensing index, LSHDI (land surface heat damage index). The LSHDI first searches for a location with the worst vegetation growth conditions in the three-dimensional feature space based on the LST (land surface temperature), the normalized difference vegetation index (NDVI), and the land surface water index (LSWI). Then, it calculates the distance between each point and this location to measure the degree of vegetation affected by high temperature and heat damage. Finally, because there is no reliable disaster verification dataset that has been published at present, this study uses soil moisture as a reference to explain the performance and stability of the LSHDI. The results showed that their coefficient of determination was above 0.5 and reached a significance level of 0.01. The LSHDI can well-reflect the high temperature and heat damage of land surface vegetation and can provide important data support and references for agricultural management departments.
Mapping Paddy Rice Planting Area in Dongting Lake Area Combining Time Series Sentinel-1 and Sentinel-2 Images
Authors: Jiang Qin , Tang Zhiguang , Zhou Linghua , Hu Guojie , Deng Gang , Xu Meifeng , Sang Guoqing
Published: May 2023

Accurate and timely acquisition of cropping intensity and spatial distribution of paddy rice is not only an important basis for monitoring growth and predicting yields, but also for ensuring food security and optimizing the agricultural production management system of cropland. However, due to the monsoon climate in southern China, it is cloudy and rainy throughout the year, which makes it difficult to obtain accurate information on rice cultivation based on optical time series images. Conventional image synthesis is prone to omission or redundancy of spectral and temporal features that are potentially important for rice-growth identification, making it difficult to determine the optimal features for high-precision mapping of paddy rice. To address these issues, we develop a method to granulate the effective use interval of classification features by extracting phenological signatures of rice to obtain cost-effective and highly accurate mapping results. Two steps are involved in this method: (1) analyzing the information on various features (spectra, polarization, and seasonal regularity) to identify three key phenological periods throughout the lifespan of paddy rice; (2) identifying the features with the highest class separation between paddy rice, non-paddy crops, and wetlands under different phenological stages; and (3) removing redundant features to retain the optimal feature combinations. Subsequently, the obtained feature sets are used as input data for the random forest classifier. The results showed that the overall accuracy of the identified rice results was 95.44% with F1 scores above 93% for both single- and double-cropping rice. Meanwhile, the correlation coefficient of our mapped rice area compared with the official statistics of rice area at county and district levels was 0.86. In addition, we found that combining Sentinel-1 and Sentinel-2 images for rice recognition was better than using Sentinel-1 or Sentinel-2 alone, and the classification accuracy was improved by 5.82% and 2.39%, which confirms that the synergistic Sentinel-1 and Sentinel-2 data can effectively overcome the problem of missing optical images caused by clouds and rain. Our study demonstrates the potential of distinguishing mixed rice-cropping systems in subtropical regions with fragmented rice-field distribution in a cloudy and rainy environment, and also provides a basis for the rational layout of rice production and improvement of cultivation systems.
Robust Loop Closure Selection Based on Inter-Robot and Intra-Robot Consistency for Multi-Robot Map Fusion
Authors: Chen Zhihong , Zhao Junqiao , Feng Tiantian , Ye Chen , Xiong Lu
Published: May 2023

In multi-robot simultaneous localization and mapping (SLAM) systems, the system must create a consistent global map with multiple local maps and loop closures between robot poses. However, false-positive loop closures caused by perceptual aliasing can severely distort the global map, especially in GNSS-denied areas, where a good prior of relative poses between robots is unavailable. In addition, the performance of the consistency metric in existing map fusion methods relies on accurate odometry from each robot. However, in practice, cumulative noise is inevitably present in robot trajectories, which leads to poor map fusion with existing methods. Thus, in this paper, we propose a robust consistency-based inter-robot and intra-robot loop closure selection algorithm for map fusion. We consider both pairwise-loop consistency and loop-odometry consistency to improve robustness against false-positive loop closures and accumulative noise in the odometry. Specifically, we select a reliable inter-robot loop closure measurement with a consistency-based strategy to provide an initial prior of relative pose between two robot trajectories and update the pose variables of the robot trajectories. The loop closure selection problem is formulated as a maximum edge weight clique problem in graph theory. A performance evaluation of the proposed method was conducted on the ManhattanOlson3500, modified CSAIL and Bicocca datasets, and the experimental results demonstrate that the proposed method outperforms the pairwise consistency measurement set maximization method (PCM) under severe accumulative noise and can be integrated with M-estimation methods.
Differentiation between Phyllodes Tumors and Fibroadenomas through Breast Ultrasound: Deep-Learning Model Outperforms Ultrasound Physicians
Authors: Shi Zhaoting , Ma Yebo , Ma Xiaowen , Jin Anqi , Zhou Jin , Li Na , Sheng Danli , Chang Cai , Chen Jiangang , Li Jiawei
Published: May 2023

The preoperative differentiation of breast phyllodes tumors (PTs) from fibroadenomas (FAs) plays a critical role in identifying an appropriate surgical treatment. Although several imaging modalities are available, reliable differentiation between PT and FA remains a great challenge for radiologists in clinical work. Artificial intelligence (AI)-assisted diagnosis has shown promise in distinguishing PT from FA. However, a very small sample size was adopted in previous studies. In this work, we retrospectively enrolled 656 breast tumors (372 FAs and 284 PTs) with 1945 ultrasound images in total. Two experienced ultrasound physicians independently evaluated the ultrasound images. Meanwhile, three deep-learning models (i.e., ResNet, VGG, and GoogLeNet) were applied to classify FAs and PTs. The robustness of the models was evaluated by fivefold cross validation. The performance of each model was assessed by using the receiver operating characteristic (ROC) curve. The area under the curve (AUC), accuracy, sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV) were also calculated. Among the three models, the ResNet model yielded the highest AUC value, of 0.91, with an accuracy value of 95.3%, a sensitivity value of 96.2%, and a specificity value of 94.7% in the testing data set. In contrast, the two physicians yielded an average AUC value of 0.69, an accuracy value of 70.7%, a sensitivity value of 54.4%, and a specificity value of 53.2%. Our findings indicate that the diagnostic performance of deep learning is better than that of physicians in the distinction of PTs from FAs. This further suggests that AI is a valuable tool for aiding clinical diagnosis, thereby advancing precision therapy.
Effect of Scale-Up on Residence Time and Uranium Extraction on Annular Centrifugal Contactors (ACCs)
Authors: Baker Alastair , Fells Alex , Shaw Thomas , Maher Chris J. , Hanson Bruce C.
Published: May 2023

This work reports the effect of scaling up annular centrifugal contactors (ACCs) upon the residence time distribution and the efficiency of extraction of uranium. The experiments were carried out in a multi-scale ACC platform of three ACCs with rotor diameters of 12, 25, and 40 mm. To enable direct comparison across all three scales of ACC, the residence time distributions were acquired by injecting dye into the solvent phase at a constant relative volume related to the ACC liquid holdup. Across all scales and flowrates, there was little difference in residence time distribution (<6 residence volumes), except for the smallest 12 mm rotor diameter ACC with a high solvent/aqueous feed ratio, which required 12 residence volumes, potentially due to internal circulation in the annulus. At low flowrates, the stage efficiency in all cases was >95%, and it improved further in larger rotor diameter ACCs.
Exploring the Chemical Composition and Antioxidant Properties of Apricot Kernel Oil
Authors: Makrygiannis Ioannis , Athanasiadis Vassilis , Chatzimitakos Theodoros , Bozinou Eleni , Mantzourani Christiana , Chatzilazarou Arhontoula , Makris Dimitris P. , Lalas Stavros I.
Published: May 2023

Apricot kernels are known to be rich in bioactive compounds such as polyphenols, which have applications in various fields such as cosmetology and the food industry. However, the extraction of these compounds has not been extensively studied. In this study, we aimed to extract oil from apricot kernels and investigate its composition and antioxidant properties. Samples from two years of apricot cannery by-products were used in the study. We employed a common extraction procedure using hexane as a solvent, followed by an analysis of the oil’s fatty acid composition and determination of its antioxidant properties using several methods. Our results indicated that the oil extracted from apricot kernels is rich in oleic and palmitoleic acids, which exhibit health benefits. As regards the volatile compounds of the oil, 2-methyl propanal, benzaldehyde, and benzyl alcohol were detected as the main compounds. Benzaldehyde was also found to be the main component of the essential oil of the kernel. Furthermore, the oil exhibited low antioxidant activity, as demonstrated by its ability to scavenge free radicals. Overall, our findings suggest that apricot kernels are a valuable source of oil with potential applications in the food and cosmetic industries.
IoT-Based Waste Segregation with Location Tracking and Air Quality Monitoring for Smart Cities
Authors: Lingaraju Abhishek Kadalagere , Niranjanamurthy Mudligiriyappa , Bose Priyanka , Acharya Biswaranjan , Gerogiannis Vassilis C. , Kanavos Andreas , Manika Stella
Published: May 2023

Massive human population, coupled with rapid urbanization, results in a substantial amount of garbage that requires daily collection. In urban areas, garbage often accumulates around dustbins without proper disposal at regular intervals, creating an unsanitary environment for humans, plants, and animals. This situation significantly degrades the environment. To address this problem, a Smart Waste Management System is introduced in this paper, employing machine learning techniques for air quality level classification. Furthermore, this system safeguards garbage collectors from severe health issues caused by inhaling harmful gases emitted from the waste. The proposed system not only proves cost-effective but also enhances waste management productivity by categorizing waste into three types: wet, dry, and metallic. Ultimately, by leveraging machine learning techniques, we can classify air quality levels and garbage weight into distinct categories. This system is beneficial for improving the well-being of individuals residing in close proximity to dustbins, as it enables constant monitoring and reporting of air quality to relevant city authorities.
Study on the Style Design and Anchoring Mechanism of Enlarged Head Anchors
Authors: Zhang Sifeng , Wang Yushuai , Li Chao , Wang Changwei , Zhang Guojian , Sun Shengzhi
Published: May 2023

To resolve insufficient traditional bolt supports due to the complexity of geological conditions, the optimal design of an expanded head bolt was investigated by using theoretical calculations and experiments. The results show that the drawing capacity of an expanded head bolt is affected by the bearing capacity of front and rear ends, side bearing capacity, and side friction resistance. For a circular anchor bolt, stepped anchor bolt, and semi-ellipsoidal anchor bolt, with an increase in the front section’s radius, the lateral friction resistance of the inner anchor section is gradually shared by the bearing force of the front end of the inner anchor section; the bearing effect of the front end of the inner anchor section is enhanced; and the pulling performance of the anchor bolt is enhanced. Therefore, the pulling force of the circular anchor bolt is at the maximum, followed by the stepped anchor bolt, and the semi-ellipsoidal bolt is at the minimum. The increase in the rear section can provide greater lateral friction resistance and end-bearing force. Compared with cylindrical enlarged head anchors, the circular, stepped, and semi-elliptic enlarged head anchors have a smaller front section but a larger rear section, and the reduction in the front section’s bearing capacity is less than the increase in the side bearing capacity and rear-end bearing capacity; thus, the cylindrical bolt has the lowest pulling force. Compared with the front radius, the back radius has more influence on the drawing ability of the enlarged head anchor. The longer the inner anchorage section, the larger the distribution range in the compression zone that is formed in the soil body and the smaller the range in the tension zone that is formed in the rear. The increase in the length of the inner anchorage section is conducive to improving the reinforcement effect of the soil in front of the anchorage section in the bolt. Therefore, this parameter plays an important role in the redistribution of the soil in front of the force. The ultimate pull-out force of a circular table-shaped tensile bolt is the highest, followed by the stepped bolt, and the semi-elliptic bolt comes in third, with the cylindrical bolt exhibiting the lowest pull-out force; the circular table-shaped enlarged head anchor constitutes the best style design.
Spatiotemporal Analysis of Earthquake Distribution and Associated Losses in Chinese Mainland from 1949 to 2021
Authors: Zheng Tongyan , Li Lei , Xu Chong , Huang Yuandong
Published: May 2023

A comprehensive earthquake hazard database is crucial for comprehending the characteristics of earthquake-related losses and establishing accurate loss prediction models. In this study, we compiled the earthquake events that have caused losses since 1949, and established and shared a database of earthquake hazard information for the Chinese mainland from 1949 to 2021. On this basis, we preliminarily analyzed the spatiotemporal distribution characteristics of 608 earthquake events and the associated losses. The results show the following: (1) The number of earthquakes is generally increasing, with an average of annual occurrence rising from three to twelve, and the rise in the economic losses is not significant. The number of earthquakes occurring in the summer is slightly higher than that in the other three seasons. (2) The average depths of earthquakes within the six blocks display a decreasing trend from west to east, with a majority (63.8%) of earthquakes occurring at depths ranging from 5 to 16 km. (3) Although the number of earthquakes in the east is lower than that in the west, earthquakes in the east are more likely to cause casualties when they have the same epicenter intensity. Southwest China is located in the Circum-Pacific seismic zone where earthquake hazards are highly frequent. The results can provide fundamental data for developing earthquake-related loss prediction models.
Research on the Structure and Characteristics of Adolescent Physical Health Policy in China Based on Policy Text Tool
Authors: Hu Yuting , Ma Xinyu
Published: May 2023

The health of young people is an important guarantee for national development and rejuvenation. In the past five years, the Chinese government has issued a series of policies on adolescent physical health, which have effectively promoted the development of adolescent health. In this study, we collected national policies on adolescent physical health from 2016 to 2022 as research objects. Based on the theory of policy instruments, this paper constructs a three-dimensional framework of “policy instrument-adolescent physical health contents-adolescent physical health policy target audience”. The study found that the use of adolescent health policy tools in China is uneven, as most policies are biased towards supply-side policies. The lack of targeted protection policies for adolescents’ physical health is due to the lagging development of physical standards, lack of monitoring technology, and complex governance policies. Policy use by governments, schools, and communities is widely distributed, resulting in a lag in the overall effectiveness of adolescent physical health policies. To this end, we put forward the following suggestions: First, the use of policy instruments should be optimized. Secondly, on the basis of adolescent health monitoring, the physical health standards suitable for national conditions should be formulated. Moreover, we should improve the governance model and guarantee a system to fill the policy blank of the implementation of adolescent physical health. Finally, we should promote the coordinated development of mental health with “moral” as the core.
Amendment of Saline–Alkaline Soil with Flue-Gas Desulfurization Gypsum in the Yinchuan Plain, Northwest China
Authors: Wang Jing , Zhao Aiqin , Ma Fei , Liu Jili , Xiao Guoju , Xu Xing
Published: May 2023

The effective and safe use of FGD gypsum in agricultural land is still debated in some countries even though its effectiveness in soil management has been reported in many studies. Thus, the changes in the levels of soil salinity, alkalinity, crop yield, and other physicochemical properties in different soil types and crops after reclamation and planting with FGD gypsum over four years are evaluated in this paper. The main aim of this paper is to review the effects of six treatment technologies in addressing soil salinity and sodicity and crop production in soils, with a focus on the basic theory, key technologies, and industrialized applications. This paper also shows that soil conditions can be improved and crop yields can be increased by using FGD alone or in combination with humic acid or fertilizer. FGD gypsum plus K–Zn–Mn fertilizer increased the yield of rice by 135%. In alkaline, salinized, and secondary salinized soils, FGD gypsum combined with organic fertilizer or organic plus chemical fertilizer increased the yield of rice by 21.2% and 60.4%, the yield of sunflower by 2.4% and 23.6%, and the yield of medlar by 18.81% and 20.78%, respectively. The application of FGD gypsum also increased the salt tolerance of salt-tolerant plants. Combined with drainage, laser field levelling and tillage decreased soil salinity by more than 63.76% and increased the yield of oil sunflower by up to 96.96%. This study provides convincing evidence of the benefits of the application of the six treatments to reclaim saline–alkali soils. It is suggested that comprehensive measures should be taken to improve saline–alkaline soil.
Assessment of Students’ Mathematical Skills in Relation to Their Strengths and Weaknesses, at Different Levels of the European Qualifications Framework
Authors: Stańdo Jacek , Kołodziejski Kamil , Fechner Żywilla
Published: May 2023

Many scientific studies focus on finding the relationship between students’ mathematical skills and socio-economic, demographic, and ontogenetic factors. In this publication, we answer the question of how students’ mathematical skills are achieved in relation to their strengths and weaknesses, also with regard to the use of mathematics in everyday life. In this article, we examine the relationship between the results of the mock final math exam for eighth grade primary school students/final year high school students and additional math classes, the application of math in everyday life and the greatest difficulties with specific areas of taught material. The study was conducted in Poland on almost ten thousand eighth graders and high school leavers who took part in mock exams online, respectively: eighth-grader exam, and school-leaving maturity exam. The participants of these online exams were asked to respond to a survey that pertained to their math grades, attending additional math classes, their perceived most useful mathematical topics in everyday life and future professional work, and identification of their strengths and weaknesses. In the following paper, the relationships between the answers to the survey questions and the results of the mock online exam are analyzed. The results indicate that there are differences in the area of results of the mock exam and answers about strengths and weakness in mathematical literacy. The analysis of answers about use the mathematical knowledge are different for eight-graders and high-school students. Eight-graders indicate the importance of arithmetic operations while high -school students point out more abstract topics like probability, statistics and geometry. The results of the study are compared to the existing results.
Hydrological Functioning and Water Availability in a Himalayan Karst Basin under Climate Change
Authors: Sarker Shishir K. , Zhu Junfeng , Fryar Alan E. , Jeelani Ghulam
Published: May 2023

Karst springs are important water sources for both human needs and environmental flows. The responses of karst springs to hydrometeorological factors vary depending on local conditions. In this study, we investigated Martandnag spring in the Liddar catchment in the Kashmir valley of northern India. We used statistical time series (autocorrelation and cross-correlation) and machine-learning (ML) techniques (random forest regression (RFR) and support vector regression (SVR)) to characterize how rainfall, temperature, and snow cover affect the karst spring flow and predict the future responses of the spring stage based on climate scenarios, in the Intergovernmental Panel on Climate Change Assessment Report 6. The statistical time series showed that the memory effect of Martandnag spring varies from 43 to 61 days, indicating moderate karstification and a relatively high storage capacity of the karst aquifer in the Liddar catchment. The delay between recharge and discharge varies from 13 to 44 days, and it is more strongly correlated to snow/ice melt than to rainfall. The ML analysis shows that SVR outperformed RFR in predicting spring flow. Under all climate scenarios, a trained SVR model showed that spring flow increased during the late winter to early spring, and decreased during the summer (except in August) and in autumn. Scenarios with increased greenhouse gas emissions further reduced flow in the summer and autumn. These predictions can be helpful for water-resource planning in similar watersheds in the Western Himalayas.
Gig Workers’ Quality of Life (QoL) and Psychological Well-Being in Service Delivery Platform
Authors: Kim Yeong Gug , Chung Yeasun Kate , Woo Eunju
Published: May 2023

The study aims to determine the understanding and perception of working conditions perceived by platform workers in terms of work/life balance and the quality of life. In addition, this current study empirically analyzes their perception on the structural relationship amongst work and life balance and the quality of life. The study uses quality of life and work/life balance to build a conceptual model, and questionnaires were collected through an online survey of 447 gig workers using a convenience sampling method. Confirmatory factor analysis (CFA) was employed to investigate the adequacy of the measurement model, and structural equation modeling (SEM) was performed along with the maximum likelihood method to examine relationships amongst the seven constructs in the proposed model. The study results show there were statistically significant values in five paths (working environment → overall QOL; leisure domain → overall QOL; economic domain → overall QOL; emotional domain → overall QOL; and overall QOL → psychological well-being), except for ‘social support → overall QoL’. It was found that the economic and emotional factors that belong to the life domain had more impact on the overall quality of life than the components of the ‘work category’. Implications for future research and the work environment perceived by gig workers for the platform market are discussed.
Mechanical Performance of 3D-Printed Cornstarch–Sandstone Sustainable Material
Authors: Mansour Gabriel , Papageorgiou Vasileios , Zoumaki Maria , Tsongas Konstantinos , Mansour Michel T. , Tzetzis Dimitrios
Published: May 2023

The objective of this research is the improvement of the physical properties of artificial sandstone in order to obtain a printable construction material whose composition and structure is suitable for the design, study and construction of environmentally friendly architectural structures. To investigate the suitability of the researched material for 3D printing and determine the physical and mechanical properties of the starch-based sandstone 3D-printed material, both cylindrical and cellular samples were designed. The 3D-printed artificial starch–sandstone material was found to have satisfactory mechanical properties.
Uncovering Equity and Travelers’ Behavior on the Expressway: A Case Study of Shandong, China
Authors: Cao Rong , Chen Xuehui , Jia Jianmin , Zhang Hui
Published: May 2023

Understanding equity and travelers’ behavior plays a key role in creating suitable strategies to promote the development of the expressway. Especially, finding clusters of expressway users could help managers provide targeted policies in order to enhance service quality. However, it is challenging to identify expressway travel behaviors, such as traffic flow distribution and users’ classification. Electronic toll collection (ETC) has been widely applied to improve expressway management, because it can record the origin–destination information of users. This paper proposes a framework to analyze the equity and travel behavior of expressway users with a large amount of ETC data. In the first stage, the Gini coefficient is adopted to analyze expressway equity. In the second stage, 12 kinds of indicators are extracted, including number of trips, car type, mean distance, etc. In the third stage, kmeans algorithm is adopted to cluster the users, based on the introduced indicators. Finally, we analyze the traffic flow distribution of each group by constructing a traffic flow network. The results show that the Gini coefficient is 0.4193, which demonstrates evident inequity in the expressway service. Moreover, statistical analysis shows that expressway flow is complicated and 70.77% of travelers do not make repeat trips. It is demonstrated that expressway users can be divided into six groups, and the flow networks of cluster 2 and cluster 3 are connected more closely and evenly than other clusters are.
Airbnb’s Negative Externalities from the Consumer’s Perspective: How the Effects Influence the Booking Intention of Potential Guests
Authors: Ho Chaang-Iuan , Chen Tzong-Shyuan , Li Chin-Pei
Published: May 2023

Local governments worldwide have been making efforts to regulate Airbnb and its negative externalities (NEs), as peer-to-peer (P2P) accommodations have grown exponentially. This study seeks to explore the perceptions of potential guests regarding the NEs of Airbnb accommodation by using a contextual approach and multiple methodologies to understand the effects of their choice. Through an experiment involving the collection of data on the responses of 296 participants from Taiwan’s post-Millennials and ordered probit model estimations, this study provides a quantitative analysis to distinguish the factors and NEs affecting the likelihood of choosing Airbnb. Under the circumstance where concern for NEs was not included, the results indicated that the accommodation environments and interactive experiences were among the significant Airbnb service features that attracted consumers. However, when NE factors were added a potential effect was identified, with the community environment and security assurances being factors that decreased the likelihood of choosing Airbnb. Previous experiences of staying in hotels were also found to reduce the acceptance of Airbnb as an accommodation mode. These research findings provide insights into Airbnb preferences which could assist in improving the administrative and managerial efforts of P2P accommodation platforms.
Relationship between Job Satisfaction and Employee Performance in the Construction Industry of Pakistan
Authors: Memon Aftab Hameed , Khahro Shabir Hussain , Memon Nafees Ahmed , Memon Zubair Ahmed , Mustafa Ahmed
Published: May 2023

Organizations focus on human resources to improve performance as a result of high global competition and a dynamic business environment. In today’s competitive environment, employee performance and job satisfaction are critical to the achievement of a company’s goals. Job satisfaction is an organization’s unnoticed success. Employee performance and job satisfaction are powerful tools that help in continuously developing and improving organizational performance to achieve strategic objectives. Job satisfaction is critical to the overall productivity of any given industry. Job satisfaction is important for both the employer and the employee. According to studies, employers greatly benefit from satisfied employees because they are more productive. One of the most important goals of a company is to maximize employee performance to achieve those goals. As a result, the focus of this study was on identifying the factors of job satisfaction and employee performance. It also evaluated the relationship between job satisfaction and employee performance in Pakistani construction projects. A detailed literature review was used to identify various factors, which were then shortlisted based on their relevance to the Pakistani construction industry by interviewing ten experienced practitioners. Totals of 11 job satisfaction and eight employee performance parameters were discovered. In total, 85 samples were collected as part of the data collection process via a questionnaire survey and statistically analyzed using multiple regression analysis. According to the results, all of the models have a high ability to compute the increase in employee performance criteria via the predicting variables. The overall models are significant because a value less than 0.05 indicates that they are. The study’s findings will assist practitioners in understanding the critical criteria that will increase employer satisfaction and improve performance.
Evolution and Impacting Factors of Global Renewable Energy Products Trade Network: An Empirical Investigation Based on ERGM Model
Authors: Li Juan , Liu Keyin , Yang Zixin , Qu Yi
Published: May 2023

Global trade of renewable energy products has increased significantly in recent years. This paper constructs an analytical framework of a global trade network for renewable energy products based on bilateral trade data between 2009 and 2019. It analyses its structural evolution at the global and local levels and investigates the influencing factors of the network with the Exponential Random Graph Model. The empirical results indicate that countries in the trade network have become more closely connected, featuring a core-periphery and increasing reciprocity relationship. China, Germany, and Japan have remained in the position of core countries; China has especially been prominent among core countries. Our empirical results verify that the sender-receiver effects can explain the evolution of this global trade network. The empirical results also indicate that the climate change agreement network and the common border network have positive effects on the formation of the trade network. As regards political implications, the core countries in the trade network should optimize the layout of renewable energy development and improve infrastructure accordingly. Countries should also jointly build a more fair and reasonable multilateral system that fulfills their responsibilities.
Exploring Artificial Intelligence in Anesthesia: A Primer on Ethics, and Clinical Applications
Authors: Cascella Marco , Tracey Maura C. , Petrucci Emiliano , Bignami Elena Giovanna
Published: May 2023

The field of anesthesia has always been at the forefront of innovation and technology, and the integration of Artificial Intelligence (AI) represents the next frontier in anesthesia care. The use of AI and its subtypes, such as machine learning, has the potential to improve efficiency, reduce costs, and ameliorate patient outcomes. AI can assist with decision making, but its primary advantage lies in empowering anesthesiologists to adopt a proactive approach to address clinical issues. The potential uses of AI in anesthesia can be schematically grouped into clinical decision support and pharmacologic and mechanical robotic applications. Tele-anesthesia includes strategies of telemedicine, as well as device networking, for improving logistics in the operating room, and augmented reality approaches for training and assistance. Despite the growing scientific interest, further research and validation are needed to fully understand the benefits and limitations of these applications in clinical practice. Moreover, the ethical implications of AI in anesthesia must also be considered to ensure that patient safety and privacy are not compromised. This paper aims to provide a comprehensive overview of AI in anesthesia, including its current and potential applications, and the ethical considerations that must be considered to ensure the safe and effective use of the technology.
Symmetries and Asymmetries in Branching Processes
Authors: Pázsit Imre
Published: May 2023

As is known in stochastic particle theory, the same random process can be described by two different master equations for the evolution of the probability density, namely, by a forward or a backward master equation. These are the generalised analogues of the direct and adjoint equations of traditional transport theory. At the level of the first moment, these two equations show considerable resemblance to each other, but they become increasingly different with increasing moment order. The purpose of this paper is to demonstrate this increasing asymmetry and to discuss the underlying reasons. It is argued that since the reason of the different forms of the forward and the backward equations lies in the lack of invariance of the process to time reversal, the reason for the increasing asymmetry between the two forms for higher-order moments or processes with several variables (particle types) can be related to the increasing level of the violation of the invariance to time reversal, as is illustrated with some examples.
Predictive Models for Compound Binding to Androgen and Estrogen Receptors Based on Counter-Propagation Artificial Neural Networks
Authors: Stanojević Mark , Sollner Dolenc Marija , Vračko Marjan
Published: May 2023

Endocrine-disrupting chemicals (EDCs) are exogenous substances that interfere with the normal function of the human endocrine system. These chemicals can affect specific nuclear receptors, such as androgen receptors (ARs) or estrogen receptors (ER) α and β, which play a crucial role in regulating complex physiological processes in humans. It is now more crucial than ever to identify EDCs and reduce exposure to them. For screening and prioritizing chemicals for further experimentation, the use of artificial neural networks (ANN), which allow the modeling of complicated, nonlinear relationships, is most appropriate. We developed six models that predict the binding of a compound to ARs, ERα, or ERβ as agonists or antagonists, using counter-propagation artificial neural networks (CPANN). Models were trained on a dataset of structurally diverse compounds, and activity data were obtained from the CompTox Chemicals Dashboard. Leave-one-out (LOO) tests were performed to validate the models. The results showed that the models had excellent performance with prediction accuracy ranging from 94% to 100%. Therefore, the models can predict the binding affinity of an unknown compound to the selected nuclear receptor based solely on its chemical structure. As such, they represent important alternatives for the safety prioritization of chemicals.
Evaluation of Tropane Alkaloids in Teas and Herbal Infusions: Effect of Brewing Time and Temperature on Atropine and Scopolamine Content
Authors: González-Gómez Lorena , Morante-Zarcero Sonia , Pereira Jorge A. M. , Câmara José S. , Sierra Isabel
Published: May 2023

Atropine and scopolamine belong to the tropane alkaloid (TA) family of natural toxins. They can contaminate teas and herbal teas and appear in infusions. Therefore, this study focused on analyzing atropine and scopolamine in 33 samples of tea and herbal tea infusions purchased in Spain and Portugal to determine the presence of these compounds in infusions brewed at 97 °C for 5 min. A rapid microextraction technique (µSPEed®) followed by high-performance liquid chromatography–tandem mass spectrometry (HPLC–MS/MS) was used to analyze the selected TAs. The results showed that 64% of the analyzed samples were contaminated by one or both toxins. White and green teas were generally more contaminated than black and other herbal teas. Of the 21 contaminated samples, 15 had concentrations above the maximum limit for liquid herbal infusions (0.2 ng/mL) set by Commission Regulation (EU) 2021/1408. In addition, the effects of heating conditions (time and temperature) on atropine and scopolamine standards and naturally contaminated samples of white, green, and black teas were evaluated. The results showed that at the concentrations studied (0.2 and 4 ng/mL), there was no degradation in the standard solutions. Brewing with boiling water (decoction) for 5 and 10 min allowed for higher extraction of TAs from dry tea to infusion water.
Comparative Study of Dayside Pulsating Auroras Induced by Ultralow-Frequency Waves
Authors: Li Xing-Yu , Zong Qiu-Gang , Liu Jian-Jun , Yin Ze-Fan , Hu Ze-Jun , Zhou Xu-Zhi , Yue Chao , Liu Zhi-Yang , Zhao Xing-Xin , Xie Zi-Kang , Blake J. Bernard , Russell Christopher T. , Ergun Robert E. , Lindqvist Per-Arne
Published: May 2023

Pulsating auroras are usually observed with ultralow-frequency (ULF) waves in the Pc 3–5 band (period 10–600 s). These auroras are thought to result from interactions between energetic electrons and chorus waves, but their relationship with ULF waves remains an open question. In this study, we investigated this question by conducting a comparative study on two ULF wave events with pulsating auroras observed near the magnetic footprints. Conjugate observations from the Magnetospheric Multiscale mission and the Chinese Yellow River Station were used. In both events, lower-band chorus waves were observed, which were suggested to be connected with the auroral pulsations by wavelet analysis. The intensity of these waves oscillates at the period of the ULF waves, but the physics laid behind them differs by events. During the event of 22 January 2019, compressional ULF waves changed the threshold for the whistler anisotropy instability periodically, affecting the emission of chorus waves. In the event on 10 January 2016, poloidal ULF waves modulated the chorus wave generation by regulating electron temperature anisotropy through drift resonance. ULF waves in these events may originate from perturbations in the solar wind. We highlight the role of ULF waves in the solar wind–magnetosphere–ionosphere coupling, which requires further study.
Virome Profiling of Chickens with Hepatomegaly Rupture Syndrome Reveals Coinfection of Multiple Viruses
Authors: Wang Guoshuai , He Yaqi , Yan Xiaomin , Sun Yue , Yi Le , Tu Changchun , He Biao
Published: May 2023

Liver diseases seriously challenge the health of chickens raised on scaled farms and cause tremendous economic losses to farm owners. The causative agents for liver diseases are still elusive, even though various pathogens, such as the hepatitis E virus, have been reported. In the winter of 2021, a liver disease was observed on a chicken farm in Dalian, China, which increased chicken mortality by up to 18%. We conducted panvirome profiling of the livers, spleens, kidneys, and recta of 20 diseased chickens. The viromic results revealed coinfection of multiple viruses, including pathogenic ones, in these organs. The viruses were highly identical to those detected in other provinces, and the vaccine and field strains of avian encephalomyelitis virus (AEV) and chicken infectious anemia virus (CIAV) cocirculated on the farm. In particular, the liver showed higher abundance of AEV and multiple fowl adenoviruses than other organs. Furthermore, the liver also contracted avian leukemia virus and CIAV. Experimental animals with infected liver samples developed minor to medium lesions of the liver and showed a virus abundance profile for AEV across internal organs similar to that in the original samples. These results suggest that coinfection with multiple pathogenic viruses influences the occurrence and development of infectious liver disease. The results also highlight that strong farm management standards with strict biosafety measures are needed to minimize the risk of pathogenic virus introduction to the farm.