bluuebunny/crossref_metadata_2025 huggingface dataset:
Highly Sensitive and Selective Dopamine Determination in Real Samples Using Au Nanoparticles Decorated Marimo-like Graphene Microbead-Based Electrochemical Sensors
Authors: Tian Qichen , She Yuanbin , Zhu Yangguang , Dai Dan , Shi Mingjiao , Chu Wubo , Cai Tao , Tsai Hsu-Sheng , Li He , Jiang Nan , Fu Li , Xia Hongyan , Lin Cheng-Te , Ye Chen
Published: March 2023

A sensitive and selective electrochemical dopamine (DA) sensor has been developed using gold nanoparticles decorated marimo-like graphene (Au NP/MG) as a modifier of the glassy carbon electrode (GCE). Marimo-like graphene (MG) was prepared by partial exfoliation on the mesocarbon microbeads (MCMB) through molten KOH intercalation. Characterization via transmission electron microscopy confirmed that the surface of MG is composed of multi-layer graphene nanowalls. The graphene nanowalls structure of MG provided abundant surface area and electroactive sites. Electrochemical properties of Au NP/MG/GCE electrode were investigated by cyclic voltammetry and differential pulse voltammetry techniques. The electrode exhibited high electrochemical activity towards DA oxidation. The oxidation peak current increased linearly in proportion to the DA concentration in a range from 0.02 to 10 μM with a detection limit of 0.016 μM. The detection selectivity was carried out with the presence of 20 μM uric acid in goat serum real samples. This study demonstrated a promising method to fabricate DA sensor-based on MCMB derivatives as electrochemical modifiers.
An Online 3D Modeling Method for Pose Measurement under Uncertain Dynamic Occlusion Based on Binocular Camera
Authors: Gao Xuanchang , Yu Junzhi , Tan Min
Published: March 2023

3D modeling plays a significant role in many industrial applications that require geometry information for pose measurements, such as grasping, spraying, etc. Due to random pose changes in the workpieces on the production line, demand for online 3D modeling has increased and many researchers have focused on it. However, online 3D modeling has not been entirely determined due to the occlusion of uncertain dynamic objects that disturb the modeling process. In this study, we propose an online 3D modeling method under uncertain dynamic occlusion based on a binocular camera. Firstly, focusing on uncertain dynamic objects, a novel dynamic object segmentation method based on motion consistency constraints is proposed, which achieves segmentation by random sampling and poses hypotheses clustering without any prior knowledge about objects. Then, in order to better register the incomplete point cloud of each frame, an optimization method based on local constraints of overlapping view regions and a global loop closure is introduced. It establishes constraints in covisibility regions between adjacent frames to optimize the registration of each frame, and it also establishes them between the global closed-loop frames to jointly optimize the entire 3D model. Finally, a confirmatory experimental workspace is designed and built to verify and evaluate our method. Our method achieves online 3D modeling under uncertain dynamic occlusion and acquires an entire 3D model. The pose measurement results further reflect the effectiveness.
A Development of an IoT-Based Connected University System: Progress Report
Authors: Matuska Slavomir , Machaj Juraj , Hutar Miroslav , Brida Peter
Published: March 2023

In this paper, a report on the development of an Internet of Things (IoT)-based connected university system is presented. There have been multiple smart solutions developed at the university over recent years. However, the user base of these systems is limited. The IoT-based connected university system allows for integration of multiple subsystems without the need to implement all of them in the same environment, thus enabling end-users to access multiple solutions through a single common interface. The implementation is based on microservice architecture, with the focus mainly on system robustness, scalability, and universality. In the system design, four subsystems are currently implemented, i.e., the subsystem for indoor navigation, the subsystem for parking assistants, the subsystem for smart classrooms or offices, and the subsystem for news aggregation from university life. The principles of all implemented subsystems, as well as the implementation of the system as a web interface and a mobile application, are presented in the paper. Moreover, the implementation of the indoor navigation subsystem that uses signals from Bluetooth beacons is described in detail. The paper also presents results proving the concept of the Bluetooth-based indoor navigation, taking into account different placements of nodes. The tests were performed in a real-world environment to evaluate the feasibility of the navigation module that utilizes deterministic fingerprinting algorithms to estimate the positions of users’ devices.
Evaluation of Red Wine Acidification Using an E-Nose System with Venturi Tool Sampling
Authors: Hernández Esmeralda , Pelegrí-Sebastiá José , Sogorb Tomás , Chilo José
Published: March 2023

The quality of wine is checked both during the production process and upon consumption. Therefore, manual wine-tasting work is still valuable. Due to the nature of wine, many volatile components are released, and it is therefore difficult to determine which elements need to be controlled. Acetic acid is one of the substances found in wine and is a crucial substance for wine quality. Gas sensor systems may be a potential alternative for manual wine tasting. In this work, we have developed a TGS2620 gas sensor module to analyze acetic acid levels in red wine. The gas sensor module was refined according to the Venturi effect along with signal slope analysis, providing promising results. The example included in this paper demonstrates that there is a direct relationship between the slope of the MOS gas sensor response and the acetic acid concentration. This relationship is useful to evaluate the ethanol oxidation in acetic acid in red wine during its production process.
Combined Prediction Model of Gas Concentration Based on Indicators Dynamic Optimization and Bi-LSTMs
Authors: Peng Yujie , Song Dazhao , Qiu Liming , Wang Honglei , He Xueqiu , Liu Qiang
Published: March 2023

In order to accurately predict the gas concentration, find out the gas abnormal emission in advance, and take effective measures to reduce the gas concentration in time, this paper analyzes multivariate monitoring data and proposes a new dynamic combined prediction method of gas concentration. Spearman’s rank correlation coefficient is applied for the dynamic optimization of prediction indicators. The time series and spatial topology features of the optimized indicators are extracted and input into the combined prediction model of gas concentration based on indicators dynamic optimization and Bi-LSTMs (Bi-directional Long Short-term Memory), which can predict the gas concentration for the next 30 min. The results show that the other gas concentration, temperature, and humidity indicators are strongly correlated with the gas concentration to be predicted, and Spearman’s rank correlation coefficient is up to 0.92 at most. The average R2 of predicted value and real value is 0.965, and the average prediction efficiency R for gas abnormal or normal emission is 79.9%. Compared with the other models, the proposed dynamic optimized indicators combined model is more accurate, and the missing alarm of gas abnormal emission is significantly alleviated, which greatly improves the early alarming accuracy. It can assist the safety monitoring personnel in decision making and has certain significance to improve the safety production efficiency of coal mines.
Fabrication of Organic Solvent Nanofiltration Membrane through Interfacial Polymerization Using N-Phenylthioure as Monomer for Dimethyl Sulfoxide Recovery
Authors: Zhou Ayang , Hu Guangle , Guo Keying , Zhang Mengnan , Liu Xiangnan
Published: March 2023

To recover dimethyl sulfoxide, an organic solvent nanofiltration membrane is prepared via the interfacial polymerization method. N-Phenylthiourea (NP)is applied as a water-soluble monomer, reacted with trimesoyl chloride (TMC) on the polyetherimide substrate crosslinked by ethylenediamine. The results of attenuated total reflectance-fourier transform infrared spectroscopy and X-ray electron spectroscopy confirm that N-Phenylthiourea reacts with TMC. The membrane morphology is investigated through atomic force microscopy and scanning electronic microscopy, respectively. The resultant optimized TFC membranes NF-1NP exhibited stable permeance of about 4.3 L m−2 h−1 bar-1 and rejection of 97% for crystal violet (407.98 g mol−1) during a 36 h continuous separation operation. It was also found that the NF-1NP membrane has the highest rejection rate in dimethyl sulfoxide (DMSO), and the rejection rates in methanol, acetone, tetrahydrofuran, ethyl acetate and dimethylacetamide(DMAc) are 51%, 84%, 94%, 96% and 92% respectively. The maximum flux in the methanol system is 11 L m−2 h−1 bar−1, while that in acetone, tetrahydrofuran, ethyl acetate and DMAc is 4.3 L m−2 h−1 bar−1, 6.3 L m−2 h−1 bar−1, 3.2 L m−2 h−1 bar−1, 4.9 L m−2 h−1 bar−1 and 2.1 L m−2 h−1 bar−1, respectively. It was also found that the membrane prepared by N-Phenylthiourea containing aromatic groups has lower mobility and stronger solvent resistance than that of by thiosemicarbazide.
Accumulation of Na+ in Cotton Field under Mulched Drip Irrigation of Brackish Water in Arid Areas
Authors: Dong Rui , Liu Wenkai , Qu Jihong , Cao Wengeng
Published: March 2023

In arid areas, the disordered accumulation of Na+ in cotton fields under mulched drip irrigation seriously affects the normal growth and development of cotton. To reveal the process and mechanism of Na+ accumulation, in situ field tests were conducted in typical cotton planting bases in the south of Xinjiang, China. Eight experimental scenarios were set up to use brackish and fresh water for drip irrigation under mulch during the whole growth period of cotton according to the drip irrigation system. By monitoring the weather, groundwater level, and soil moisture before and after irrigation, and testing the soil salinity and Na+ concentration, the temporal and spatial distribution and transport characteristics of Na+ were compared and studied. The results showed that: (1) owing to the strong spatial variation of soil permeability, soil water and salt dynamics exhibited significant differences after irrigation in all experimental scenarios in the study area, especially at a depth of 0–60 cm. (2) The Na+ profile exhibited a “thin waist”, whose depth depended on the climate and lithology of the soil; however, this phenomenon was not observed in the salt profile. (3) The accumulation of Na+ in cotton fields is an extremely complex dynamic process that is influenced by both natural and human activities. This process is controlled by the dynamic characteristics of soil water and salt, but it is different from the distribution of soil salt in time and space. This study provides necessary technical support for the formulation of drip irrigation systems under brackish water film, and provides a scientific basis for fine agricultural planting and water resources management in arid areas.
Complexities of the Ethical Dilemmas in Qualitative International Relations Research: Research Subjects, Ethical Codes, and Constructing Qualitative Rigor
Authors: Putra Bama Andika
Published: March 2023

Existing scholarship has not thoroughly explored topics of ethical dilemmas faced by qualitative international relations researchers. Due to the distinctiveness of the study and the need to address ethical concerns with regard to international relations research, this article aims to elucidate the ethical dilemmas in three aspects: ethical dilemmas of research subjects (gatekeepers and vulnerable groups), ethical codes and scientific conduct, and constructing qualitative rigor in international relations. It further attempts to connect to existing opinions of social research studies critical toward the positivist methodological stances of contemporary ethical reviews and echoes the need to reflect on ethical dilemmas on a case-by-case basis.
Can Managing Climate Risks Be a Catalyst for Broader Transformative Change?
Authors: Swart Rob , Timmermans Wim , Boon Eva , Van Ginkel Maarten , Goosen Hasse , Van Veldhoven Felix , Cilliers Jua , Ndaguba Emeka
Published: March 2023

This essay addresses the long-term effectiveness of urban climate change adaptation approaches, based, inter alia, on work in the C40 city network. We argue that in most cities, the dominant framing of climate risk management almost exclusively focuses on short-term incrementalities and preventive solutions directly tackling hazards, vulnerability, and exposure. This approach has serious flaws, leading to missed opportunities for longer-term sustainable urban development. Until very recently, climate science usually provided only a marginal input to long-term urban planning and design. We argue that any analysis of urban climate risk management and the associated climate services should be broadened beyond solely climate focusing on impacts. In this context, the development of positive urban visions is a key gap for both research and practice. A change is required from negatively addressing risks to positively pursuing a positive vision of attractive, resilient, and sustainable cities. The emphasis on short-term incremental solutions should shift towards long-term transformation. This embodies a paradigm shift from “function follows system” to “system follows function”. For many cities, this also means a change in procedural practice from siloed top-down to integrated, participatory urban transformation. Our main argument in this paper is that simple, longer-term sustainable urban transformation would not only reduce climate risks but also enhance overall environmental quality, economic opportunities, and social wellbeing.
The Opening of High-Speed Railway and Coordinated Development of the Core–Periphery Urban Economy in China
Authors: Li Jiaqi , Elahi Ehsan , Peng Cheng , Wu Aimin , Cao Fengtong , Wang Jian , Abro Mohammad , Khalid Zainab
Published: March 2023

The current study investigates the impact of the high-speed railway’s operation on the coordinated economic development of “core–periphery” cities using the multi-period difference-in-difference (DID) model. Data on 270 prefecture-level cities in China were collected for empirical analysis of collected data. The findings demonstrate that the high-speed railway’s operation has widened the economic development gap between core and peripheral cities and restrained the coordinated growth of the urban economy. The heterogeneity analysis found that the “siphon effect” of the high-speed railway’s operation in core cities is only effective within the distance of “one-hour metropolitan area”. Moreover, it is found that the high-speed railway has a threshold effect based on the size of cities. It depicts that the core cities in the high-speed railway network play a “siphon effect” and “diffusion effect” on large size cities and small (or medium) size cities, respectively, which is manifested as a suppression and promotion effect on the coordinated development of the urban economy. Furthermore, it is found that that technological innovation and economic agglomeration are two significant intermediary paths of high-speed railway opening that affect the level of “core–periphery” city economics coordination; however, technological innovation’s role as an intermediary has a stronger masking effect than economic agglomeration.
A Comprehensive Review on Development and Applications of Cross-Flow Wind Turbines
Authors: Sefidgar Zahra , Ahmadi Joneidi Amir , Arabkoohsar Ahmad
Published: March 2023

The rapid globalization of the energy crisis and the adverse effects of global warming have caused the need for non-conventional energy resources to be felt more than ever. As a result of this, vertical axis wind turbines (VAWT) have received much attention over the recent decades, and have thus been more developed and used worldwide. The cross-flow wind turbine (CFWT) is a wind turbine in the category of VAWTs, and perfectly suitable for urban applications due to its simplicity, high starting torque at low wind speed, and self-starting capability, even though its low power coefficient as its main drawback has slowed down its widespread use so far. The main aim of this paper is to review the scientific literature and recent developments in the field of CFWTs. The governing equations and turbulence models for the simulation of the turbine are discussed and various wind resource assessment methods for estimating potential site locations, different aspects, and wind energy harvesting systems from buildings are debated. The research gaps, challenges, and future possible works on such turbines and their applications are discussed. Investigations indicate that changing the rotor geometric parameters and adding innovative augmentation devices have been the most widely addressed approaches for making performance enhancement of the wind turbine in the literature. The critical performance-affecting parameters are improved by various innovative designs of the turbine structure or blades, as well as several augmentation techniques, such as guide nozzle, casing, windshield, guide vane, deflector, cowling, etc.
The “Double-Edged Sword” Effect of Personal Relationships between Boundary Personnel on Enterprise Opportunistic Behavior in Cooperative Innovation
Authors: Gao Mengli , Sarfraz Muddassar , Shah Wasi Ul Hassan
Published: March 2023

In collaborative innovation, personal relationships between boundary personnel of knowledge-intensive business service (KIBS) enterprises and organizational customers have a “double-edged sword” effect on inter-organizational relations. This study adopts the empirical research method based on KIBS enterprises’ cooperative innovation projects with organizational customers in China. Based on the theory of the inter-organizational relationship, this study explores the influence of personal relationships between employees at the boundary of enterprises on organizational customers’ opportunistic behavior. It analyzes the mediating effect of relationship governance and contract governance. The results show that personal relationships between boundary personnel will improve the probability of corporate customer opportunism. The relationship between governance and contract governance for enterprises can effectively restrain the opportunistic behavior of organizational customers. Further, the personal relationships between boundary personnel will enhance the relationship norms and inhibit the opportunistic behavior of organizational customers, and relationship governance plays a partial intermediary role in this. The personal relationships between employees at an enterprise’s boundary will relax the contract’s supervision and encourage corporate customer opportunism. Contract governance plays a partial intermediary role in this.
Interval-Valued Hesitant Fuzzy DEMATEL-Based Blockchain Technology Adoption Barriers Evaluation Methodology in Agricultural Supply Chain Management
Authors: Tsai Jung-Fa , Tran Dinh-Hieu , Nguyen Phi-Hung , Lin Ming-Hua
Published: March 2023

Blockchain technology is emerging and has high potential to improve and transform the agricultural supply chain. This study investigates the critical barriers to blockchain technology adoption in the Vietnamese agricultural supply chain using a novel interval-valued hesitant fuzzy Decision-Making Trial and Evaluation Laboratory (IVHF-DEMATEL) approach. The IVHF-DEMATEL technique is applied to identify cause-and-effect relationships and draw the influence-relations map of the barriers. In contrast to prior work, which converts fuzzy sets into crisp sets and then uses crisp set operations, this study is the first study to investigate the Vietnamese agricultural supply chain that uses fully hesitant fuzzy operations representing experts’ assessment without information loss during the conversion. Our results show that ‘lack of government regulation’, ‘lack of scalability and system speed’, ‘a large amount of resource and capital requirements’, and ‘lack of trust among agro-stakeholder or public perception’ are the main barriers. Consistent with previous studies, ‘lack of government regulation’ is the most significant barrier. The results also indicate the hesitant degree of each barrier and better inform decision-makers about uncertain situations. Moreover, a priority order for tackling barriers is proposed to accelerate blockchain adoption in the Vietnamese agricultural supply chain.
Understanding the Uncivilized Tourism Behavior of Tourists: A Planned Behavior Model Based on the Perspectives of Cognitive Dissonance and Neutralization
Authors: Zhang Ping , Cao Kaijun
Published: March 2023

Effectively regulating and managing the uncivilized tourism behavior of tourists is a key strategy for the sustainable development of tourism destinations. In this paper, the dissonance–neutralization model was proposed by integrating planned behavior, cognitive dissonance, and neutralization theories. Partial least squares structural equation modeling (PLS-SEM) was used to test the impact and effect of this model on the uncivilized tourism behavior of 387 tourists at natural heritage sites. Overall, the research results show the following: (1) Uncivilized tourism behavior is not only determined by behavioral intention and perceived behavioral control. Attitude, subjective norms, and perceived behavioral control also all have a significant influence on behavioral intention. (2) Cognitive dissonance is a parallel predictor of behavior. (3) Neutralization techniques can effectively reduce cognitive dissonance, thus allowing uncivilized tourist behavior to continue.
The “I” and the “We” in Nature Conservation—Investigating Personal and Collective Motives to Protect One’s Regional and Global Nature
Authors: Hoppe Annedore , Fritsche Immo , Chokrai Parissa
Published: March 2023

Personal pro-environmental action has often been explained in terms of personal cost-benefit analyses and personal capabilities. However, given that only collectives and not single individuals can effectively address large-scale environmental crises, such as mass extinction of species, peoples’ pro-environmental motivation might emerge from their perceived involvement in agentic collectives, as proposed in the social identity model of pro-environmental action (SIMPEA). Collective cognition and motivation (e.g., ingroup identification, ingroup norms, collective efficacy, and group-based emotion) might drive identified group members’ nature protection intention and behavior both directly and indirectly by affecting personal factors (e.g., personal attitudes). We tested this in two related nationally representative surveys of N = 2065 Germans, measuring both personal and collective predictors as well as nature protection intentions and behavior on either the regional or the worldwide, global level. As hypothesized, blockwise regression analyses suggest that collective factors affect people’s conservation action both directly and indirectly. In addition, participants’ identification with all humanity moderated the relationship between collective factors and personal intention (and personal norms) to protect global nature. Overall, the results support propositions of the social identity model of pro-environmental action and highlight the importance of collective factors motivating citizens’ conservation action.
Optimal Time Phase Identification for Apple Orchard Land Recognition and Spatial Analysis Using Multitemporal Sentinel-2 Images and Random Forest Classification
Authors: Yan Yuxiang , Tang Xiaoying , Zhu Xicun , Yu Xinyang
Published: March 2023

The significance of identifying apple orchard land and monitoring its spatial distribution patterns is increasing for precise yield prediction and agricultural sustainable development. This study strived to identify the optimal time phase to efficiently extract apple orchard land and monitor its spatial characteristics based on the random forest (RF) classification method and multitemporal Sentinel-2 images. Firstly, the Normalized Difference Vegetation Index (NDVI), Soil-Adjusted Vegetation Index (SAVI), Ratio Vegetation Index (RVI), and Difference Vegetation Index (DVI) between apple orchard land and other green vegetation (other orchards, forest and grassland) during the growing stage were calculated and compared to identify the optimal time phase for apple orchard land extraction; the RF classifier was then constructed using multifeature variables on Google Earth Engine to efficiently identify apple orchard land, and the support vector machine (SVM) classification results were used as a comparison; GIS spatial analysis, a slope calculation model, and Moran’s I and Getis-Ord GI* analysis were employed to further analyze the spatial patterns of the apple orchard land. The results found the following: (1) April, May, and October were the optimal time phases for apple orchard identification. (2) The RF-based method combining coefficients of indexes, the grayscale co-occurrence matrix, and 70% of the ground reference data can precisely classify apple orchards with an overall accuracy of 90% and a Kappa coefficient of 0.88, increasing by 9.2% and 11.4% compared to those using the SVM. (3) The total area of apple orchard land in the study area was 485.8 km2, which is 0.6% less than the government’s statistical results. More than half (55.7%) of the apple orchard land was distributed on the gentle slope (Grade II, 6–15°) and the flat slope (Grade I, 0–5°); SiKou, Songshan, and Shewopo contained more than 50% of the total orchard land area. (4) The distribution of apple orchard land has a positive spatial autocorrelation (0.309, p = 0.000). High–High cluster types occurred mainly in Sikou (60%), High–Low clusters in Songshan (40%), Low–High clusters in Sikou (47.5%), and Low–Low clusters in Taocun and Tingkou (37.4%). The distribution patterns of cold and hot spots converged with those of the Local Moran Index computation results. The findings of this study can provide theoretical and methodological references for orchard land identification and spatial analysis.
Sustainability Assessment of Municipal Infrastructure Projects Based on Continuous Interval Argumentation Ordered Weighted Average (C-OWA) and Cloud Models
Authors: Liu Xun , Xue Zhiyuan , Ding Zhenhan , Chen Siyu
Published: March 2023

The goals of sustainable development are constantly negatively impacted by infrastructure initiatives. The importance of these projects in advancing the economic, social, and civilizational growth of the country will, however, prevent their construction from being stopped. The overall construction of the project is related to the scientific and unbiased assessment of an infrastructure project’s sustainability throughout the decision-making stage. Based on the references documents, this paper establishes an index system for evaluating an infrastructure project’s sustainability from three aspects: environment, economy, and society. In the assessment process, the cloud model was used to describe the various attribute values of infrastructure project sustainability, which achieved the uncertainty measures for infrastructure project sustainability, and a cloud model-based assessment method for infrastructure project sustainability was proposed by modifying the attribute value by the penalty factor. Finally, an assessment method for infrastructure project sustainability based on the cloud model was proposed after the attribute values were modified by using a continuous interval argument ordered weighted average (C-OWA) operator. The model carries out an overall sustainability assessment by generating a synthesized cloud with the weight to calculate the similarity of assessment factors, which takes the randomness, fuzziness, and uncertainty of expert qualitative assessment into account, and uses the analytic hierarchy process (AHP) method and the C-OWA operator to determine the weight of the sustainable index and the aggregation of the expert scoring interval. A case study was conducted to clarify how this strategy was applied. The study provides a valuable and useful tool for the operational stage to assess the achievability of municipal infrastructure projects.
Sustainability Assessment of Energy Storage Technologies Based on Commercialization Viability: MCDM Model
Authors: Shu Xiaoyang , Kumar Raman , Saha Rajeev Kumar , Dev Nikhil , Stević Željko , Sharma Shubham , Rafighi Mohammad
Published: March 2023

Advances in developed and developing countries are more attributable to growth in industrial activities that directly impact increasing energy demand. Energy availability has been inconsistent globally, necessitating energy storage (ES) for use as per requirement. Various energy storage technologies (ESTs) are available in mechanical, electrochemical, electrical, chemical, and thermal forms to fulfil the energy demand of a user as and when required. The factors responsible for making a commercially viable energy storage product are further being researched for an eco-friendly and optimal solution to store energy for a longer duration. Researchers are employing different strategies to evaluate the energy efficiency of storage technologies. This paper uses the VIKOR technique to analyze ESTs while assigning objective weights with the entropy weights method based on identified energy performance indicators and ranking them according to their commercialization viability. The method helps a consumer choose better ESTs as per their requirement while manufacturers compete with each other to enhance the commercial value of their energy storage products. Sensitivity analysis has been performed to understand the uncertainties, pros, and cons with the limitations and scope of using the decision model and thus taking an informed decision. The analysis of different energy storage technologies has indicated Hydrogen Fuel Cells (HFC) to be impressive and promising for the future.
Study on the Early Effect of Excitation Method on the Alkaline Steel Slag
Authors: Li Maohui , Lu Youjun , Yang Shaolin , Chu Jingjun , Liu Yajuan
Published: March 2023

The change law of alkaline steel slag cementitious activity was investigated by mechanical excitation, alkaline excitation, and salt excitation methods. The effect of grinding time, chemical activators, and content of steel slag on the properties of cement replaced by steel slag was studied. The hydration products of cement replaced by steel slag were analyzed by XRD and SEM. The results show mechanical excitation can effectively improve the particle size distribution and cementitious activity of steel slag. The best mechanical properties are obtained when grinding for 20 min and adding 10% steel slag. Chemical excitation can further improve the cementitious activity of steel slag based on mechanical stimulation. The optimal mechanical properties are obtained when the dosage of sodium hydroxide is 1.0%, the dosage of early strength agent is 2.0%, and the dosage of steel slag is 25%. The main hydration products of cement replaced by steel slag are calcite (CaCO3), calcium hydroxide (Ca(OH)2), dicalcium silicate (Ca2SiO4), and C-S-H gel. The microstructure presents a fibrous network structure, laying the foundation for improving mechanical properties.
Impact of Urbanisation on the Spatial and Temporal Evolution of Carbon Emissions and the Potential for Emission Reduction in a Dual-Carbon Reduction Context
Authors: Xue Pengcheng , Liu Jiaxin , Liu Binbin , Zhu Chuang
Published: March 2023

Urbanisation is accelerating under the new economic development trend, but the global warming exacerbated by greenhouse gases has caused a certain degree of constraint on the speed and quality of economic development, among which anthropogenic emissions, mainly from transportation, are more obvious. Therefore, based on the background of urbanisation and taking urban agglomerations as the research object, this study investigates the spatial and temporal mechanisms and dynamics of carbon emissions through the construction of carbon emission models, the identification of influencing factors, and the processing of spatial data and proposes relevant measures for carbon emission control mechanisms. This study finds that the improvement of the per capita economic level and the urbanisation rate will correspondingly lead to an increase in carbon emissions and that the spatial distribution of carbon emissions under passenger and freight transport modes shows a pattern of “low at the ends and high in the middle”, with the predicted carbon emission levels remaining balanced over a long period of time, with a variation rate of less than 1%. The model idea proposed in this study can effectively provide new perspectives and ideas for the differentiated formulation of emission reduction policies, and the government ought to focus more on the dynamic changes of urbanised carbon emissions in future development so as to realise the potential of urban emission reduction.
The Effect of Cognitive Dissonance Theory and Brand Loyalty on Consumer Complaint Behaviors: A Cross-Cultural Study
Authors: Yakın Volkan , Güven Hüseyin , David Sofia , Güven Esra , Bărbuță-Mișu Nicoleta , Güven Emine Türkan Ayvaz , Virlanuta Florina Oana
Published: March 2023

Consumers tend to exhibit e-WOM behavior or retention behavior or communicate with official channels rather than the brand, which can damage the brand in cases where the channels through which customers are expected to reach the brand for their complaints are dysfunctional. This study aims to examine the relationship between cognitive dissonance and brand loyalty factors as well as their impact on consumer complaint behavior in terms of differences between Turkish and Romanian consumers. For this purpose, a simultaneous quantitative research study was conducted in these two countries, with a total of 790 participants surveyed. The findings showed that the consumers’ level of brand loyalty had a significant positive effect on the level of cognitive dissonance, which significantly impacted complaint behavior. On the other hand, it was concluded that brand loyalty did not significantly affect complaint behavior. The comparative analysis revealed that Romanian customers’ brand loyalty was higher than Turkish customers’, and the dimensions concerning cognitive dissonance and complaint behavior were higher among Turkish customers.
Primordial Gravitational Wave Circuit Complexity
Authors: Adhikari Kiran , Choudhury Sayantan , Pandya Hardey N. , Srivastava Rohan
Published: March 2023

In this article, we investigate the various physical implications of quantum circuit complexity using the squeezed state formalism of Primordial Gravitational Waves (PGW). Recently, quantum information-theoretic concepts, such as entanglement entropy and complexity, have played a pivotal role in understanding the dynamics of quantum systems, even in diverse fields such as high-energy physics and cosmology. This paper is devoted to studying the quantum circuit complexity of PGW for various cosmological models, such as de Sitter, inflation, radiation, reheating, matter, bouncing, cyclic and black hole gas models, etc. We compute complexity measures using both Covariance and Nielsen’s wave function method for three different choices of quantum initial vacua: Motta-Allen, α and Bunch–Davies. Besides computing circuit complexity, we also compute the Von Neumann entanglement entropy. By making the comparison between complexity and entanglement entropy, we are able to probe various features regarding the dynamics of evolution for different cosmological models. Because entanglement entropy is independent of the squeezing angle, we are able to understand more details of the system using Nielsen’s measure of complexity, which is dependent on both squeezing parameter and angle. This implies that quantum complexity could indeed be a useful probe to study quantum features on a cosmological scale. Quantum complexity is also becoming a powerful technique to understand the chaotic behaviour and random fluctuations of quantum fields. Using the growth of complexity, we are able to compute the quantum Lyapunov exponent for various cosmological models and comment on its chaotic nature.
Epidemiological Analysis of Symmetry in Transmission of the Ebola Virus with Power Law Kernel
Authors: Hasan Ali , Akgül Ali , Farman Muhammad , Chaudhry Faryal , Sultan Muhammad , De la Sen Manuel
Published: March 2023

This study presents a mathematical model of non-integer order through the fractal fractional Caputo operator to determine the development of Ebola virus infections. To construct the model and conduct analysis, all Ebola virus cases are taken as incidence data. A symmetric approach is utilized for qualitative and quantitative analysis of the fractional order model. Additionally, stability is evaluated, along with the local and global effects of the virus that causes Ebola. Using the fractional order model of Ebola virus infections, the existence and uniqueness of solutions, as well the posedness and biological viability and disease free equilibrium points are confirmed. Many applications of fractional operators in modern mathematics exist, including the intricate and important study of symmetrical systems. Symmetry analysis is a powerful tool that enables the creation of numerical solutions for a given fractional differential equation very methodically. For this, we compare the results with the Caputo derivative operator to understand the dynamic behavior of the disease. The simulation demonstrates how all classes have convergent characteristics and maintain their places over time, reflecting the true behavior of Ebola virus infection. Power law kernel with the two step polynomial Newton method were used. This model seems to be quite strong and capable of reproducing the issue’s anticipated theoretical conditions.
RF-BiLSTM Neural Network Incorporating Attention Mechanism for Online Ride-Hailing Demand Forecasting
Authors: Zhao Xiangmo , Sun Kang , Gong Siyuan , Wu Xia
Published: March 2023

Accurately predicting online ride-hailing demand can help operators allocate vehicle resources on demand, avoid idle time, and improve traffic conditions. However, due to the randomness and complexity of online ride-hailing demand data, which are affected by many factors and mostly time-series in nature, it is difficult to forecast accurately and effectively based on traditional forecasting models. Therefore, this study proposes an online ride-hailing demand forecasting model based on the attention mechanism of a random forest (RF) combined with a symmetric bidirectional long short-term memory (BiLSTM) neural network (Att-RF-BiLSTM). The model optimizes the inputs and can use past and future data to forecast, improving the forecasting precision of online ride-hailing demand. The model utilizes a random forest to filter and optimize the input variables to reduce the neural network complexity, and then an attention mechanism was incorporated into the BiLSTM neural network to construct a demand forecasting model and validate it using actual Uber pickup data from New York City. Compared with other forecasting models (Att-XGBoost-BiLSTM, Att-BiLSTM, and pure LSTM), the results show that the proposed symmetrical Att-RF-BiLSTM online ride-hailing demand forecasting model has a higher forecasting precision and fitting degree, which indicates that the proposed model can be satisfactorily applied to the area of online ride-hailing demand.
Abnormal Waves Observation and Analysis of the Mechanism in the Pearl River Estuary, South China
Authors: Shi Hui , Luo Yao , Zhou Fenghua , Qiu Chunhua , Wang Dongxiao , Zhang Zhenqiu
Published: March 2023

The Pearl River Estuary is a typical estuary region in southern China, and the study of surface wave occurrence and characteristics is of great importance for shipping management, nearshore engineering, and monitoring shoreline changes and other human activities. Long-term and continuous observational data are critical for achieving a better understanding of waves. In this study, the wave measurements based on a high-precision wave gauge were analyzed and observation data over approximately two years at a sampling frequency of 2 Hz were obtained. The wave system in the Pearl River Estuary was found to deviate from the assumption of a stationary stochastic process similar to that in the open ocean, due to the effects of abnormal waves caused by human activities. Therefore, traditional distribution functions such as Rayleigh and Weibull were not suitable for accurately fitting the main wave parameters (Hs, Tp, etc.), particularly in the tail. Consequently, abnormal wave signals were extracted from all wave sets, and through the comparison and analysis of the wave spectral features, it was determined that these abnormal waves are caused by the ship wakes. The spectral characterization of these waves was performed to determine the characteristics of different ship wake processes. Ship wakes in the Pearl River Estuary are an important part of the wave system, and their wave height is significantly larger than the normal wave. Based on the spectral characteristics of ship wakes, this study proposed some news characteristics of ship wakes in the main channel of the Pearl River Estuary.
Failure Characteristics of the Water-Resisting Coal Pillar under Stress-Seepage Coupling and Determination of Reasonable Coal Pillar Width
Authors: Liu Quanhui , Xue Yuanbo , Ma Dan , Li Qiang
Published: March 2023

Groundwater inrush hazard has always been a great threat to the construction of vertical shafts in coal mines. Generally, the failure of the water-resisting coal pillar under coupled stress-seepage conditions around the vertical shaft is the main reason for the generation of the water inrush channel. In order to understand the mechanical behaviors of the water-resisting coal pillar, the strength of typical coal affected by the size and water content was investigated, and the stress sensitivity of permeability was investigated by a stress-seepage coupling test. The stress field and deformation of the water-resisting coal pillar were investigated by numerical simulation, the stability of the water-resisting coal pillars with different widths was evaluated, and the reasonable width of the coal pillars under coupled stress-seepage condition was determined. Results show that the water content and coal pillar width have a great influence on the mechanical characteristics of coal samples. Under the conditions of lower water content and larger coal sample width, the coal sample presents higher strength, smaller axial deformation, smaller permeability and porosity, and weak sensitivity to stress. The simulation results show that the boundary of the main roadway at the end of the coal pillar is dominated by tensile stress, and fractures can significantly contribute to the destruction of coal pillars. With the increase in the width of the water-resisting coal pillar, the internal damage variable, maximum tensile stress, porosity, and average water flow velocity of the coal pillar decrease, which reduces the risk of water inrush and improves the safety of the water-resisting coal pillar. An evaluation model of the reasonable width of the water-resisting coal pillar under the stress-seepage coupling was proposed, and the model was verified by the shear slip law and experimental results. This study provides theoretical and experimental guidance for the risk management of groundwater inrush disaster during the construction of vertical shafts in coal mines.
Multimethodological Revisit of the Surface Water and Groundwater Interaction in the Balaton Highland Region—Implications for the Overlooked Groundwater Component of Lake Balaton, Hungary
Authors: Tóth Ádám , Baják Petra , Szijártó Márk , Tiljander Mia , Korkka-Niemi Kirsti , Hendriksson Nina , Mádl-Szőnyi Judit
Published: March 2023

The hummocky Balaton Highland is located in western Hungary and is part of the Transdanubian Mountains, the most extensive carbonate aquifer system in Hungary. The study region also encompasses Lake Balaton, the biggest lake in central Europe, which is to the south of Balaton Highland. The surface water–groundwater interaction in the Balaton Highland–Lake Balaton region and the groundwater contribution to Lake Balaton are revisited in this paper. Hydrostratigraphic classification was performed first; then, groundwater flow directions by hydraulic head distribution were analysed, and baseflow indices of surface watercourses were calculated. Regarding hydrochemical characterisation, general hydrochemical facies were identified, natural tracers of temperature, chloride and uranium were applied, and the stable isotopic composition of oxygen and hydrogen was determined. Finally, groundwater flow and heat transport were simulated in a 2D numerical model. A high level of hydraulic interaction was evidenced between surface water and groundwater and the sub-regions of Bakony Mountains, Balaton Highland and Lake Balaton by physical and chemical parameters, numerical simulation and groundwater-flow-related natural manifestations, revealing hydraulic continuity in the study region. Based on the results, the division of legislative water bodies can be reconsidered, especially that surface water and groundwater should be regarded as interconnected, and Lake Balaton can be considered a groundwater-dependent ecosystem in any water-use planning in the region.
Zeolites for Nitrogen Recovery from the Anaerobic Membrane Bioreactor Permeate: Zeolite Characterization
Authors: Godifredo Jesús , Ferrer José , Seco Aurora , Barat Ramón
Published: March 2023

Anaerobic Membrane Bioreactor technology has great advantages for treating wastewater, including energy recovery from organic matter. However, when the legislation requires that effluent standards be met in sensitive areas, this treatment cannot remove the nutrients, thus the permeate generated needs post-treatment. Apart from the biological processes, ion exchange is an alternative treatment for this stream since it can remove nutrients and concentrate them for later recovery as fertilizers. In this work, the feasibility of using a natural zeolite (clinoptilolite) for treating NH4 from AnMBR permeate was studied and tests were carried out on the adsorption kinetics of ammonium. Isotherm tests verified that activating natural zeolite to its -Na form improves its performance by 20% and increases qe from 2.37 to 2.86 mg NH4-N/g for a Co of 30 mg NH4-N/L. It was also found that the cations present in the water (especially Ca2+ and Na+) caused a 22% reduction in ammonium adsorption while organic matter was responsible for improving the retained ammonium by 22%. It was also found that the working pH (7.2 ± 0.2) is close to the optimal pH range (6–7) for zeolite performance. The tests on the AnMBR permeate indicate that clinoptilolite is a suitable material since treating this stream can retain up to 7.44 mg NH4-N/g.