bluuebunny/crossref_metadata_2025 huggingface dataset:
The Characteristics of Fracturing Fluid Distribution after Fracturing and Shut-In Time Optimization in Unconventional Reservoirs Using NMR
Authors: Huang Xin , Wang Lei , Wang Nan , Li Ming , Wu Shuangliang , Ding Qun , Xu Shucan , Tuo Zhilin , Yu Wenqiang
Published: August 2023

Post-fracturing shut-in, as an important means of improving the energy efficiency of fracturing fluid, has been widely used in the development process of unconventional reservoirs. The determination of the shut-in duration is key to the effectiveness of shut-in measures. However, the distribution characteristics of the fracturing fluid during the post-fracturing shut-in period in unconventional reservoirs, such as the Chang 7 reservoir, were not clear, and the shut-in duration needed further optimization. Therefore, this paper employed low-field nuclear magnetic resonance (NMR) technology to study the distribution characteristics of the fracturing fluid during the post-fracturing shut-in period in unconventional reservoirs and optimized the shut-in duration. The study showed that the Chang 7 reservoir had a complex pore structure and relatively low porosity and permeability. During the shut-in process, the filtrate was distributed in pore throats with radii ranging from 0.0012 μm to 0.025 μm. Pore throats with radii ranging from 0.003 μm to 0.07 μm acted as dynamic pore throats in the process of imbibition displacement. When the shut-in duration for the Chang 7 segment was 7 days, the growth rate of the retained volume of fracturing fluid filtrate was the highest. When the shut-in duration was 10 days, there was no oil displacement in the medium and large pores, and the retained volume of filtrate was lower than that at 7 days shut-in, indicating that an optimal shut-in duration would be 7 days. This study can provide theoretical and technical support for the development of unconventional reservoirs.
A Comprehensive Asset Evaluation Method for Oil and Gas Projects
Authors: Zhang Muzhen , Jia Ailin , Lei Zhanxiang , Lei Gang
Published: August 2023

The rapid and accurate evaluation of oil and gas assets, specifically for new development projects, poses a significant challenge due to the various project types, limited data availability, brief periods for assessment and decision making, and constraints arising from varying contractual and taxation conditions, political stability, and societal factors. This study leverages the grading standards of the evaluation index system for new oil and gas field development projects, along with relevant mathematical theories and methods for project evaluation and optimization. We developed an asset evaluation approach for new oil and gas projects by analyzing the assets of six new oil and gas field development projects in Brazil. This analysis resulted in the grading and ranking of new projects, and we tested and demonstrated four asset optimization techniques. After a comparative analysis with conventional evaluation results, we established an oil and gas project asset optimization approach centered on the cloud model comprehensive evaluation and linear weighted ranking, exhibiting Kendall’s tau coefficient of 0.8667 with conventional methods. The findings suggest that the combination of the cloud model comprehensive evaluation method with the linear weighted ranking method can facilitate asset optimization for oil and gas field development projects, meeting the practical needs for fast selection among various new projects. Furthermore, this research offers a technical and theoretical foundation for rapid evaluation and decision making regarding new assets.
Experimental Study of Sound Pressure Level in Hydraulic Power Unit with External Gear Pump
Authors: Mitov Alexander , Nedelchev Krasimir , Kralov Ivan
Published: August 2023

The article presents the results of an experimental study of the sound pressure level (SPL) caused by a hydraulic power unit with an external gear pump. The study was carried out with a specially developed laboratory experimental setup based on a common architecture used in hydraulic power units. Both the hydraulic system and the measuring equipment used are described in detail. The design of the experimental studies performed, including two main configurations with specific parameters regarding the operating modes of the system, is presented. The experimental results obtained are presented in the form of magnitude frequency responses which are compared in accordance with the experiment design. An analysis of the results obtained is performed using various quantitative indicators. For specific operating modes, parametric models were derived by approximation of the experimental data. The resulting models can serve in future work to reduce the SPL by passive or active means (e.g., frequency control of the electric motor). The quantitative analysis can serve as a basis of comparison with results obtained after adding passive (damping ring, etc.) or active means to reduce the SPL.
Biodegradable Composite Film of Brewers’ Spent Grain and Poly(Vinyl Alcohol)
Authors: Lin Lilian , Mirkin Sarah , Park Heon E.
Published: August 2023

Plastic pollution and food waste are two pressing global challenges that require immediate attention and innovative solutions. In this study, we address these challenges by upcycling brewers’ spent grain (BSG) into biodegradable composite films. BSG, a by-product of the beer brewing process, is commonly discarded in landfills or used as animal feed. By utilizing BSG as a raw material for biodegradable films, we simultaneously reduce waste and decrease plastic pollution. To create the composite films, we employed poly(vinyl alcohol) (PVA) and glycerol as binder materials, along with hexamethoxymethylmelamine (HMMM) as a water-repelling agent. By varying the ratios of these components, we investigated the effects on film properties. Our characterization included assessing moisture uptake and tensile properties. The results revealed that the practical BSG content in the films was 20–60 wt%. Films with this composition exhibited a balance between moisture absorption and mechanical strength. The addition of glycerol improved the flexibility and toughness of the films, while HMMM reduced moisture absorption, enhancing their water resistance. This study contributes to the development of sustainable materials by showcasing the potential of upcycling BSG into valuable biodegradable films. By transforming food waste into useful applications, we reduce environmental burdens and promote a circular economy. Further research is warranted to explore the potential applications and optimize the properties of BSG-based composites.
High-Resolution and Wide-Swath 3D Imaging for Urban Areas Based on Distributed Spaceborne SAR
Authors: Yang Yaqian , Zhang Fubo , Tian Ye , Chen Longyong , Wang Robert , Wu Yirong
Published: August 2023

Tomographic synthetic aperture radar (TomoSAR) obtains elevation resolution by adding multiple baselines successively in the direction perpendicular to the line of sight, thereby realizing three-dimensional (3D) reconstruction of complex scenes and significantly promoting the development of the 3D application field. However, a large data redundancy and long mapping time in traditional 3D imaging lead to a large data transmission burden, low efficiency, and high costs. To solve the above problems, this paper proposes a distributed SAR high-resolution and wide-swath (HRWS) 3D imaging technology scheme. The proposed scheme overcomes the size limitation of traditional single-satellite antennas through the multi-channel arrangement of multiple satellites in the elevation direction to achieve HRWS imaging; meanwhile, the distributed SAR system is integrated with tomographic processing technology to realize 3D imaging of difficult areas by using the elevation directional resolution of TomoSAR systems. HRWS 3D SAR increases the baseline length and channel number by transmission in turn, which leads to excessive pulse repetition frequency and causes echoes of different pulse signals to overlap in the same receiving cycle, resulting in range ambiguity and thus seriously affecting the quality of the 3D reconstruction. To solve this problem, this paper proposes a range ambiguity resolution algorithm based on multi-beam forming and verifies it on the measured data from airborne array SAR. Compared with the traditional TomoSAR, the distributed HRWS 3D SAR scheme proposed in this paper can obtain a greater mapping bandwidth with the same resolution in a single flight, thereby enhancing the time correlation, reducing data redundancy, and greatly improving mapping efficiency.
High-Resolution Image Products Acquired from Mid-Sized Uncrewed Aerial Systems for Land–Atmosphere Studies
Authors: Goldberger Lexie , Gonzalez-Hirshfeld Ilan , Nelson Kristian , Mehta Hardeep , Mei Fan , Tomlinson Jason , Schmid Beat , Tagestad Jerry
Published: August 2023

We assess the viability of deploying commercially available multispectral and thermal imagers designed for integration on small uncrewed aerial systems (sUASs, <25 kg) on a mid-size Group-3-classification UAS (weight: 25–600 kg, maximum altitude: 5486 m MSL, maximum speed: 128 m/s) for the purpose of collecting a higher spatial resolution dataset that can be used for evaluating the surface energy budget and effects of surface heterogeneity on atmospheric processes than those datasets traditionally collected by instrumentation deployed on satellites and eddy covariance towers. A MicaSense Altum multispectral imager was deployed on two very similar mid-sized UASs operated by the Atmospheric Radiation Measurement (ARM) Aviation Facility. This paper evaluates the effects of flight on imaging systems mounted on UASs flying at higher altitudes and faster speeds for extended durations. We assess optimal calibration methods, acquisition rates, and flight plans for maximizing land surface area measurements. We developed, in-house, an automated workflow to correct the raw image frames and produce final data products, which we assess against known spectral ground targets and independent sources. We intend this manuscript to be used as a reference for collecting similar datasets in the future and for the datasets described within this manuscript to be used as launching points for future research.
Monitoring Inland Water Quantity Variations: A Comprehensive Analysis of Multi-Source Satellite Observation Technology Applications
Authors: Huang Zhengkai , Wu Xin , Wang Haihong , Hwang Cheinway , He Xiaoxing
Published: August 2023

The advancement of multi-source Earth observation technology has led to a substantial body of literature on inland water monitoring. This has resulted in the emergence of a distinct interdisciplinary field encompassing the application of multi-source Earth observation techniques in inland water monitoring. Despite this growth, few systematic reviews of this field exist. Therefore, in this paper, we offer a comprehensive analysis based on 30,212 publications spanning the years 1990 to 2022, providing valuable insights. We collected and analyzed fundamental information such as publication year, country, affiliation, journal, and author details. Through co-occurrence analysis, we identified country and author partnerships, while co-citation analysis revealed the influence of journals, authors, and documents. We employed keywords to explore the evolution of hydrological phenomena and study areas, using burst analysis to predict trends and frontiers. We discovered exponential growth in this field with a closer integration of hydrological phenomena and Earth observation techniques. The research focus has shifted from large glaciers to encompass large river basins and the Tibetan Plateau. Long-term research attention has been dedicated to optical properties, sea level, and satellite gravity. The adoption of automatic image recognition and processing, enabled by deep learning and artificial intelligence, has opened new interdisciplinary avenues. The results of the study emphasize the significance of long-term, stable, and accurate global observation and monitoring of inland water, particularly in the context of cloud computing and big data.
Monopulse Parameter Estimation for FDA-MIMO Radar under Mainlobe Deception Jamming
Authors: Chen Hao , Li Rongfeng , Chen Hui , Qu Qizhe , Zhou Bilei , Li Binbin , Wang Yongliang
Published: August 2023

Multiple input multiple output with frequency diversity array (FDA-MIMO) radar has unique advantages in mainlobe deception jamming suppression and target location. However, if the training sample contains the target signal, it will lead to poor jamming suppression performance and large target measurement error. To deal with the problem, a method of coarse target location in the time domain is proposed based on the cumulative sampling analysis. Taking full advantages of the strongest correlation characteristic between the expected steering vector and the true target, the feature vector and feature value corresponding to the true target are found after feature decomposition. The time domain location of the target is roughly estimated during the cumulative sampling analysis from near to far. Then, a pure jamming training sample can be obtained by avoiding the location. Noise subspace projection algorithm is used to measure the angle and range of the target while suppressing mainlobe jamming. The simulation results show that the proposed method can roughly estimate the target location in the time domain when the mainlobe deception jamming completely covers the target. Compared with conventional methods, the performance of jamming suppression and target localization error are closer to the performance of ideal sampling.
Reconfiguration Error Correction Model for an FBG Shape Sensor Based on the Sparrow Search Algorithm
Authors: Shang Qiufeng , Liu Feng
Published: August 2023

A reconfiguration error correction model for an FBG shape sensor (FSS) is proposed. The model includes curvature, bending direction error correction, and the self-correction of the FBG placement angle and calibration error based on an improved sparrow search algorithm (SSA). SSA could automatically correct the placement angle and calibration direction of the FBG, and then use the corrected placement angle and calibration direction to correct the curvature and bending direction of the FSS, thereby improving the accuracy of shape reconfiguration. After error correction, the tail point reconfiguration errors of different shapes were reduced from 2.56% and 4.96% to 1.12% and 2.45%, respectively. This paper provides a new reconfiguration error correction method for FSS that does not require a complicated experimental calibration process, is simpler, more efficient, and more operable than traditional methods, and has great potential in FSS application scenarios.
Teaching Qualitative Research in Psychology: A Look at the Portuguese Reality
Authors: Antunes Ana Pereira , Martins Silvana
Published: August 2023

Qualitative research has been increasingly used in the field of psychology. Consequently, concerns about the development of students’ skills in qualitative research have arisen. The main goal of this paper is to characterize the current state of art of the qualitative research teaching in Portuguese bachelor’s degrees in psychology. A documentary analysis was performed, and the data collection was conducted through an online search: first on the website of the General Directorate of Higher Education, and afterwards on the online sites of each of the Portuguese universities where the first cycle of psychology is taught. A content analysis was made by two coders and a discussion about categories was made until a consensus was reached. The data revealed the existence of 31 undergraduate courses in psychology at 31 Portuguese teaching institutions. There were 12 undergraduate courses at 12 public universities, and 19 undergraduate courses at 19 private universities. Despite the diversity in the study plans in the degree of psychology, most of them included qualitative research methodology teaching. However, the data analysis revealed different designations of the curricular units (CUs) related to qualitative research, as well as a different number of credits (European Credit Transfer and Accumulation System—ECTS). In addition, there were variations in the academic year in which the qualitative research CUs were taught and registered in their syllabi. This study indicates that undergraduate Portuguese psychology students generally have some training in qualitative research but the way it is carried out and the training contents are not uniform for all the existing degrees. It is important to reflect on the importance of qualitative research in psychology and further studies on qualitative methods teaching practices are still needed.
Social Representations of Trans People in the Workplace
Authors: Baptista José , Costa Dália , Gonçalves Sónia P.
Published: August 2023

Organizations show tendencies to discriminate against trans people, making them significantly more likely to face barriers in the professional context, where the highest rates of discrimination against trans people are reported. This study intends to acknowledge the SRs that are associated with trans people in the workplace since the Theory of Social Representations suggests that Social Representations (SRs) are useful to regulate perceptions and the way we act in the world. Also, through Intergroup Contact Theory, by suggesting that contact with a minority population will reduce the associated prejudice, we also intend to understand the impact contact has on SRs. By applying a questionnaire between 20 January and 21 February 2022 on a random sample of 217 people, and respective analyses in MAXQDA 2022 and EVOC 2005 software, the results indicate that the SRs most associated with trans people in a professional context are discrimination, normality, equality, difficulties, and prejudice. Although the term “discrimination” was the most mentioned, it is worth underlining the appearance of positive (and neutral) terms, which may, according to Intergroup Contact Theory, be justified by contact since the majority of the sample (57.6%, n = 125) have had contact with trans people.
Unlocking Drone Potential in the Pharma Supply Chain: A Hybrid Machine Learning and GIS Approach
Authors: Bridgelall Raj
Published: August 2023

In major metropolitan areas, the growing levels of congestion pose a significant risk of supply chain disruptions by hindering surface transportation of commodities. To address this challenge, cargo drones are emerging as a potential mode of transport that could improve the reliability of the pharmaceutical supply chain and enhance healthcare. This study proposes a novel hybrid workflow that combines machine learning and a geographic information system to identify the fewest locations where providers can initiate cargo drone services to yield the greatest initial benefits. The results show that by starting a service in only nine metropolitan areas across four regions of the contiguous United States, drones with a robust 400-mile range can initially move more than 28% of the weight of all pharmaceuticals. The medical community, supply chain managers, and policymakers worldwide can use this workflow to make data-driven decisions about where to access the largest opportunities for pharmaceutical transport by drones. The proposed approach can inform policies and standards such as Advanced Air Mobility to help address supply chain disruptions, reduce transportation costs, and improve healthcare outcomes.
Predictive Factors for Union Time in Adult Diaphyseal Forearm Fractures
Authors: Factor Shai , Gurel Ron , Eisenberg Gilad , Tordjman Daniel , Rosenblatt Yishai , Pritsch Tamir , Atlan Franck
Published: August 2023

Purpose: Although open reduction and internal fixation (ORIF) by plating are the treatment of choice for diaphyseal fractures of the forearm, delayed union and non-union remain as existing complications. This study aimed to analyze predictive factors for the union time in diaphyseal fractures of the forearm. Methods: A retrospective study was conducted on all adult patients with diaphyseal forearm fractures who underwent surgical treatment with plate fixation between 2007 and 2016 at a tertiary care referral center. The patients were divided into two groups based on their union times: ≤3 months or >3 months. They were then compared for demographics, fracture pattern and characteristics, associated injuries, type of fixation, and quality of postoperative reduction. Results: Eighty-six diaphyseal forearm bone fractures (radius, ulna, or both) were observed in 55 adults. Out of these fractures, 55 (65.1%) achieved union within ≤3 months, 26 (30.3%) took more than 3 months to achieve union, and 4 (4.6%) resulted in nonunion. The use of a locking plate in open reduction and internal fixation of diaphyseal forearm fractures significantly increased the likelihood of union within ≤3 months (p = 0.043). The parameter of gap width at the fracture site, as observed on postoperative X-rays, showed a qualitative and quantitative correlation with union time (p = 0.028). Conclusion: The use of a locking plate, combined with reducing the gap width at the fracture site after reduction during open reduction and internal fixation (ORIF) of diaphyseal forearm fractures, is significantly correlated with an increased likelihood of achieving bone union within 3 months.
Lightweight Federated Learning for Rice Leaf Disease Classification Using Non Independent and Identically Distributed Images
Authors: Aggarwal Meenakshi , Khullar Vikas , Goyal Nitin , Alammari Abdullah , Albahar Marwan Ali , Singh Aman
Published: August 2023

Rice (Oryza sativa L.) is a vital food source all over the world, contributing 15% of the protein and 21% of the energy intake per person in Asia, where most rice is produced and consumed. However, bacterial, fungal, and other microbial diseases that have a negative effect on the health of plants and crop yield are a major problem for rice farmers. It is challenging to diagnose these diseases manually, especially in areas with a shortage of crop protection experts. Automating disease identification and providing readily available decision-support tools are essential for enabling effective rice leaf protection measures and minimising rice crop losses. Although there are numerous classification systems for the diagnosis of rice leaf disease, no reliable, secure method has been identified that meets these needs. This paper proposes a lightweight federated deep learning architecture while maintaining data privacy constraints for rice leaf disease classification. The distributed client–server design of this framework protects the data privacy of all clients, and by using independent and identically distributed (IID) and non-IID data, the validity of the federated deep learning models was examined. To validate the framework’s efficacy, the researchers conducted experiments in a variety of settings, including conventional learning, federated learning via a single client, as well as federated learning via multiple clients. The study began by extracting features from various pre-trained models, ultimately selecting EfficientNetB3 with an impressive 99% accuracy as the baseline model. Subsequently, experimental results were conducted using the federated learning (FL) approach with both IID and non-IID datasets. The FL approach, along with a dense neural network trained and evaluated on an IID dataset, achieved outstanding training and evaluated accuracies of 99% with minimal losses of 0.006 and 0.03, respectively. Similarly, on a non-IID dataset, the FL approach maintained a high training accuracy of 99% with a loss of 0.04 and an evaluation accuracy of 95% with a loss of 0.08. These results indicate that the FL approach performs nearly as well as the base model, EfficientNetB3, highlighting its effectiveness in handling both IID and non-IID data. It was found that federated deep learning models with multiple clients outperformed conventional pre-trained models. The unique characteristics of the proposed framework, such as its data privacy for edge devices with limited resources, set it apart from the existing classification schemes for rice leaf diseases. The framework is the best alternative solution for the early classification of rice leaf disease because of these additional features.
Development of a Safety Heavy-Duty Vehicle Model Considering Unsafe Acts, Unsafe Conditions and Near-Miss Events Using Structural Equation Model
Authors: Pumpugsri Nattawut , Rattanawong Wanchai , Vongmanee Varin
Published: August 2023

The World Health Organization has revealed that Thailand ranks first in Asia with regard to the region’s road traffic death rate. Due to the growth in the domestic economy and demands in logistics, traffic congestion regularly occurs and brings higher risks to transportation, resulting in a constant increase in the accident rate involving heavy-duty vehicles (HDVs), with a tendency to escalate in the future. To prevent its occurrence and solve the problem, this research aims to present a “Safety HDV Model” based on four dimensions, namely, driver behaviors, unsafe roadway environment, types of vehicles and near-miss events, which are all considered as causes of accidents. In this study, the researchers use the Delphi method to obtain a consensus from experts in logistics and safety from both public and private organizations, and then they define indicators and assess the complex dimensions. Based on the consensus, the researchers find 4 dimensions, 15 factors and 55 indicators with a high level of consensus at the Kendall’s coefficient of concordance (W) of 0.402 and P less than 0.001 to be relevant to safety in logistics. To estimate the influences among dimensions, the researchers apply a structural equation model and find that both absolute fit indices and incremental fit indices demonstrate good fit, with a CMIN/DF of 1.90, RMSEA of 0.048, GFI of 0.95, AGFI of 0.92 and RMR of 0.032 for the absolute fit indices and NFI of 0.97, CFI of 0.98, TLI of 0.98 and IFI of 0.98 for the incremental fit indices. As the model is consistent with data and variables, it is considered to be valid to be adopted by responsible authorities to improve unsafe roadway environments and behaviors of HDV drivers. As the data in the model can be altered by location, the model can be utilized as a tool in strategic planning and management to prevent accidents in each area of the country in the future.
Reuse within the UK’s Charity Retail Sector: Steps towards Sustainability
Authors: Dolphin Bethan R. , Shaw Peter J. , Williams Ian D.
Published: August 2023

The social benefits of charity retail are widely recognized. However, data relating to the potential benefits to the sustainable use of end-of-use consumer goods are scarce. A general survey and an observational study at a typical charity shop aimed to quantify and evaluate reuse via charity retail outlets. We reveal valuable insights to stock data recording, procedures for receiving/dealing with donations (by category), use of standard approaches, quantification of key variables, and accuracy of previous survey data. Methods were successfully developed and trialled to (a) quantify diversion of end-of-use products from residual waste via reuse/recycling, and (b) estimate the cost of unsaleable donations. Future routine use of these methods for charity retail shops is recommended while acknowledging the limitations due to reporting capabilities. We identify four key groups of beneficiaries: (1) the parent charity, (2) charity shop workers (paid and unpaid), (3) donors, and (4) customers. Specific benefits, such as social interactions, are not exclusive to specific beneficiaries. Efforts to improve positive impacts should focus on securing appropriate donations, facilitating information capture, and promoting reuse. An important balance is required between maximising income and reuse, and retaining the social benefits that charities provide to communities.
Molecular Dynamics Simulation of Forsterite and Magnesite Mechanical Properties: Does Mineral Carbonation Reduce Comminution Energy?
Authors: Talapatra Akash , Nojabaei Bahareh
Published: August 2023

This work compares the mechanical properties of two geomaterials: forsterite and magnesite. Various physical conditions are considered to investigate the evolution of stress–strain relationships for these two polycrystals. A molecular-scale study is performed on three-dimensional models of forsterite and magnesite. Three different temperatures (300 K, 500 K, and 700 K) and strain rates (0.001, 0.01, and 0.05 ps−1) are considered to initiate deformation in the polycrystals under tensile and compressive forces. The polycrystalline structures face deformation at lower peaks at high temperatures. The Young’s modulus values of forsterite and magnesite are found to be approximately 154.7451 GPa and 92.84 GPa under tensile forces and these values are found to be around 120.457 GPa (forsterite) and 77.04 GPa (magnesite) for compressive forces. Increasing temperature reduces the maximum strength of the polycrystalline structures, but forsterite shows higher ductility compared to magnesite. Strain rate sensitivity and the effect of grain size are also studied. The yield strengths of the forsterite and magnesite drop by 7.89% and 9.09% when the grain size is reduced by 20% and 15%, respectively. This study also focuses on the changes in elastic properties for different pressures and temperatures. In addition, from the radial distribution function (RDF) results, it was observed that the peak intensity of pairwise interaction of Si–O is higher than that of Mg–O. Finally, it is found that the formation of magnesite, which is the product of mineral carbonation of forsterite, is favorable in terms of mechanical properties for the comminution process.
Extension of Computational Co-Design Methods for Modular, Prefabricated Composite Building Components Using Bio-Based Material Systems
Authors: Zechmeister Christoph , Gil Pérez Marta , Dambrosio Niccolo , Knippers Jan , Menges Achim
Published: August 2023

Robotic coreless filament winding using alternative material systems based on natural fibers and bio-based resin systems offers possible solutions to the productivity and sustainability challenges of the building and construction sector. Their application in modular, prefabricated structures allows for material-efficient and fast production under tightly controlled conditions leading to high-quality building parts with minimal production waste. Plant fibers made of flax or hemp have high stiffness and strength values and their production consumes less non-renewable energy than glass or carbon fibers. However, the introduction of natural material systems increases uncertainties in structural performance and fabrication parameters. The development process of coreless wound composite parts must thus be approached from the bottom up, treating the material system as an integral part of design and evaluation. Existing design and fabrication methods, as well as equipment, are adjusted to emphasize material aspects throughout the development, increasing the importance of material characterization and scalability evaluation. The reciprocity of material characterization and the fabrication process is highlighted and contributes to a non-linear, cyclical workflow. The implementation of extensions and adaptations are showcased in the development of the livMatS pavilion, a first attempt at coreless filament winding using natural material systems in architecture.
How Does Green Insurance Affect Green Innovation? Evidence from China
Authors: Hu Yucai , Du Shaorui , Wang Yukun , Yang Xinya
Published: August 2023

In the context of the rapid development of green finance, this paper examines the impact of green insurance on green innovation. Based on panel data of listed firms from 2008 to 2020, we find that green insurance significantly increased firms’ green patent applications. The mechanisms driving this positive relationship between green insurance and green innovation include that the insured firms are able to obtain more resources, are more willing to take risks, and are more likely to have a long-term vision. Further analysis shows that green insurance can enhance a firm’s environmental performance by promoting green innovation. This study deepens our understanding of green insurance and enriches the research related to green finance.
Green and Environmental Marketing Strategies and Ethical Consumption: Evidence from the Tourism Sector
Authors: Nassani Abdelmohsen A. , Yousaf Zahid , Grigorescu Adriana , Popa Alexandra
Published: August 2023

Sustainable business in the hospitality sector should be designed and restructured to offer services meant to satisfy the customers aware of the ethical behavior toward environment. Green environmental marketing strategies (GES) are based on the desire of the customers to access hospitality services with zero or a less negative impact with the adaptation of greening activities. Therefore, this research aims to explore the direct effects of green environmental strategies on ethical consumption and the indirect influence of green marketing and its mediating effect between green environmental strategies and ethical consumption links. Additionally, this research also reveals that psychological aspects play the moderating role in the relationship between GES and ethical consumption. The data were collected from a sample of 545 respondents with the support of Saudi tourism companies, and a structural equation model was used to process them. The findings confirm the positive relationship between green environmental strategy and ethical consumption. The outcomes also corroborate that green marketing is interplaying between green environmental strategy and ethical consumption. In addition, this study validates that psychological aspects strengthen the link between GES and ethical consumption. This study adds to the knowledge in the literature through emphasizing the crucial role of psychological factors in improving green environmental strategies and developing ethical consumption habits among members to increase ethical consumption among tourism companies. The findings support companies from the hospitality sector implementing green sustainable services, to stimulate ethical consumption and to use their competitive advantage in green marketing strategies.
Spatial and Temporal Evolutionary Characteristics of Vegetation in Different Geomorphic Zones of Loess Plateau and Its Driving Factor Analysis
Authors: Li Xue , Yu Kunxia , Zhang Xiang , Zhang Guojun , Li Zhanbin , Li Peng , Zhang Xiaoming , Zhao Yang , Ma Wentao
Published: August 2023

Based on MODIS NDVI and a meteorological dataset, this study analyzed the spatial and temporal variation characteristics of vegetation cover in different geomorphic zones of Loess Plateau (LP) from 2000 to 2020 with trend analysis, partial correlation, residual analysis and the CA–Markov method and discussed the driving factors. The research results show that: (1) There are spatial differences in vegetation coverage in different geomorphic regions. The Loess Hills and Forests zone (LF) exhibits the highest coverage, with a multi-year average of 86.64%, and the Arid Grassland (AG) has the poorest vegetation with only 8.53%. Overall, there has been significant improvement in vegetation coverage over the past two decades, although certain geomorphic zones, particularly the Highland Steppe zone (HS) and Alluvial Plains zone (AP), show signs of degradation. (2) Relative humidity has the greatest impact on vegetation among the three climate factors, i.e., relative humidity, precipitation and temperature. Relative humidity predominantly promotes vegetation in all geomorphic zones. Temperature generally inhibits vegetation growth, except in the Wind Sandy zone (WA) and AG. The impact of precipitation on vegetation depends on the region. A lag effect is observed, with temperature and humidity showing a one-month lag and precipitation showing a two-month lag on vegetation response. (3) Human activities play a crucial role in promoting vegetation, particularly in the WA zone, in which the percentage of area where human activities contribute to vegetation has changed from 13.80% to 86.85%, an increase of 73.05%, while the HS experiences an inhibitory effect due to overgrazing and water resource overutilization. Similarly, the AP zone’s vegetation growth is hindered by urban development and land use changes. (4) Land use change significantly impacts vegetation dynamics on the LP. Over the past two decades, the area of forest lawn increased by 122,800 km2, which is 1.5 times more than the area of reduction. However, conversion to building land has hindered vegetation growth in certain regions. A comprehensive strategy is required to conserve land resources and promote healthy vegetation growth on the LP.
New Trends in Smart Cities: The Evolutionary Directions Using Topic Modeling and Network Analysis
Authors: Oh Minjeong , Ahn Chulok , Nam Hyundong , Choi Sungyong
Published: August 2023

The COVID-19 pandemic has affected smart city operations and planning. Smart cities, where digital technologies are concentrated and implemented, face new challenges in becoming sustainable from social, ecological, and economic perspectives. Using text mining methodologies of topic modeling and network analysis, this study aims to identify keywords in the field of smart cities after the pandemic and provide a future-oriented perspective on the direction of smart cities. A corpus of 1882 papers was collected from the Web of Science and Scopus databases from December 2019 to November 2022. We identified six categories of potential issues in smart cities using topic modeling: “supply chain”, “resilience”, “culture and tourism”, “population density”, “mobility”, and “zero carbon emission”. This study differs from previous research because it is a quantitative study based on text mining analysis and deals with smart cities, given the prevalence of COVID-19. This study also provides insights into the development of smart city policies and strategies to improve urban resilience during the pandemic by anticipating and addressing related issues. The findings of this study will assist researchers, policymakers, and planners in developing smart city strategies and decision-making in socioeconomic, environmental, and technological areas.
Research on Users’ Exercise Behaviors of Online Exercise Community Based on Social Capital Theory
Authors: Fan Jing , Guo Xingchen , Liu Xuan , Xue Xinyi
Published: August 2023

Online exercise communities play an important role in their users’ self-health management. The willingness of users to interact and create user-generated content in online communities reflects the vitality of the online exercise community and the positive impact it has on offline users’ health performance. Therefore, based on social capital theory, we study the relationship between three types of social capital and users’ offline exercise behaviors and add off-topics in the community in the model. We select the KEEP health community user group as the research setting and conduct the regression analysis. The results show that owned centrality and reciprocity have a significant positive relationship with users’ exercise behaviors; accessed centrality and trust have a significant negative relationship with users’ exercise behaviors; and common topics and off-topics show a partly significant correlation. As a moderating variable, off-topics have a negative moderating effect on owned centrality and betweenness centrality, but a positive moderating effect on reciprocity and trust among group members. The results enrich and expand social capital theory, deepen the research on users’ exercise behaviors in the online exercise community, and provide a good reference for online exercise community management.
Fuzzy Logic System for Classifying Multiple Sclerosis Patients as High, Medium, or Low Responders to Interferon-Beta
Authors: Ponce de Leon-Sanchez Edgar Rafael , Mendiola-Santibañez Jorge Domingo , Dominguez-Ramirez Omar Arturo , Herrera-Navarro Ana Marcela , Vazquez-Cervantes Alberto , Jimenez-Hernandez Hugo , Senties-Madrid Horacio
Published: August 2023

Interferon-beta is one of the most widely prescribed disease-modifying therapies for multiple sclerosis patients. However, this treatment is only partially effective, and a significant proportion of patients do not respond to this drug. This paper proposes an alternative fuzzy logic system, based on the opinion of a neurology expert, to classify relapsing–remitting multiple sclerosis patients as high, medium, or low responders to interferon-beta. Also, a pipeline prediction model trained with biomarkers associated with interferon-beta responses is proposed, for predicting whether patients are potential candidates to be treated with this drug, in order to avoid ineffective therapies. The classification results showed that the fuzzy system presented 100% efficiency, compared to an unsupervised hierarchical clustering method (52%). So, the performance of the prediction model was evaluated, and 0.8 testing accuracy was achieved. Hence, a pipeline model, including data standardization, data compression, and a learning algorithm, could be a useful tool for getting reliable predictions about responses to interferon-beta.
Estimation of Health Risks Caused by Metals Contained in E-Cigarette Aerosol through Passive Vaping
Authors: Su Wei-Chung , Lee Jinho , Zhang Kai , Wong Su-Wei , Buu Anne
Published: August 2023

It is expected that secondary exposure to e-cigarette aerosol (passive vaping) will soon become an issue of public health. Passive vaping inhales e-cigarette aerosol containing similar harmful substances as active vaping. However, parallel studies on passive vaping are minimal. Therefore, there is a need for passive vaping-related health risk studies to assess the impact of vaping on public health. This research conducted a series of experiments in a room using a puffing machine and the Mobile Aerosol Lung Deposition Apparatus (MALDA) to study e-cigarette aerosol respiratory deposition through passive vaping. The experimental data acquired were applied to estimate the deposited mass and health risks caused by toxic metals contained in e-cigarette aerosol. Five popular e-cigarette products were used in this study to generate e-cigarette aerosol for deposition experiments. In addition, size-segregated e-cigarette aerosol samples were collected, and metal compositions in the e-cigarette aerosol were analyzed. Results obtained showed that estimated non-cancer risks were all acceptable, with hazard quotient and hazard index all less than 1.0. The calculated cancer risks were also found acceptable, with lifetime excess cancer risk generally less than 1E-6. Therefore, the e-cigarettes tested and the passive vaping exposure scenarios studied do not seem to induce any potential for metal-related respiratory health effects.
Effectiveness of Silymarin, Sulforaphane, Lycopene, Green Tea, Tryptophan, Glutathione, and Escin on Human Health: A Narrative Review
Authors: Sebastiani Francesco , D’Alterio Carlo , Vocca Cristina , Gallelli Luca , Palumbo Fabrizio , Cai Tommaso , Palmieri Alessandro
Published: August 2023

Background: Recently, the role of nutraceutical compounds in the prevention of human diseases has been rapidly increasing. Here, we aim to evaluate the beneficial effect of dietary supplementation with seven active principles, i.e., lycopene, sulforaphane, silymarin, glutathione, escin, tryptophan, and green tea catechins, on human health. Methods: An extensive search of PubMed and Medline database was performed with the following keywords: “silymarin”, “sulforaphane”, “lycopene”, “green tea catechins”, “tryptophan”, “glutathione” and “escin” accompanied by the keywords “supplement”, “supplementation”, and “nutraceutics”. All preclinical and clinical trials were considered for this review. Results: One hundred and eighteen full-text articles were eligible for inclusion in this review. The papers examined presented considerable variability due to the wide heterogeneity of dosages administered, population involved, and outcomes pursued. Conclusion: Nutritional supplementation with lycopene, sulforaphane, silymarin, glutathione, escin, tryptophan, and green tea catechins appears to exert a wide range of benefits on human health, ranging from mood and cognition to cardiovascular health, fertility, metabolism, antioxidant, and anti-inflammatory capabilities, as well as potential anticancer effects. Further studies are required to better define the potential synergic effect, optimal dosage, mechanism of action, and tolerability profiles of these substances.
Variant Analysis of the Thymidine Kinase and DNA Polymerase Genes of Herpes Simplex Virus in Korea: Frequency of Acyclovir Resistance Mutations
Authors: Hyun Jungwon , Lee Su Kyung , Kim Ji Hyun , Cho Eun-Jung , Kim Han-Sung , Kim Jae-Seok , Song Wonkeun , Kim Hyun Soo
Published: August 2023

The thymidine kinase (TK) and DNA polymerase (pol) genes of the herpes simplex viruses type 1 (HSV-1) and type 2 (HSV-2) are two important genes involved in antiviral resistance. We investigated the genetic polymorphisms of the HSV-TK and pol genes in clinical isolates from Korean HSV-infected patients using next-generation sequencing (NGS) for the first time in Korea. A total of 81 HSV-1 and 47 HSV-2 isolates were examined. NGS was used to amplify and sequence the TK and pol genes. Among the 81 HSV-1 isolates, 12 and 17 natural polymorphisms and 9 and 23 polymorphisms of unknown significance in TK and pol were found, respectively. Two HSV-1 isolates (2.5%) exhibited the E257K amino acid substitution in TK, associated with antiviral resistance. Out of 47 HSV-2 isolates, 8 natural polymorphisms were identified in TK, and 9 in pol, with 13 polymorphisms of unknown significance in TK and 10 in pol. No known resistance-related mutations were observed in HSV-2. These findings contribute to our understanding of the genetic variants associated with antiviral resistance in HSV-1 and HSV-2 in Korea, with frequencies of known antiviral resistance-related mutations of 2.5% and 0% in HSV-1 and HSV-2, respectively.
The Adjuvant Activity of BCG Cell Wall Cytoskeleton on a Dengue Virus-2 Subunit Vaccine
Authors: Jearanaiwitayakul Tuksin , Warit Saradee , Lekjinda Kritsadayut , Seesen Mathurin , Limthongkul Jitra , Midoeng Panuwat , Sunintaboon Panya , Ubol Sukathida
Published: August 2023

The uneven immunogenicity of the attenuated tetravalent dengue vaccine has made it difficult to achieve balanced protection against all four serotypes of the dengue virus (DENV). To overcome this problem, non-replicative vaccines have come into focus, as their immunogenicity is adjustable. This approach is excellent for multivalent vaccines but commonly faces the issue of low immunogenicity. In this present study, we developed a non-replicating dengue vaccine composed of UV-inactivated dengue virus-2 (UV-DENV-2) and DENV-2 NS1-279 protein encapsidated within nanoparticles. This vaccine candidate was administered in the presence of BCG cell wall cytoskeleton (BCG-CWS) as an adjuvant. We revealed, here, that encapsidated immunogens with BCG-CWS exerted potent activities on both B and T cells and elicited Th-1/Th-2 responses in mice. This was evidenced by BCG-CWS significantly augmenting antibody-mediated complement-fixing activity, strongly stimulating the antigen-specific polyfunctional T cell responses, and activating mixed Th-1/Th-2 responses specific to DENV-2- and NS1-279 antigens. In conclusion, BCG-CWS potently adjuvanted the inactivated DENV-2 and DENV subunit immunogens. The mechanism of adjuvanticity remains unclear. This study revealed the potential use of BCG-CWS in vaccine development.