bluuebunny/crossref_metadata_2025 huggingface dataset:
Carbon Fixation and Soil Aggregation Affected by Biochar Oxidized with Hydrogen Peroxide: Considering the Efficiency of Pyrolysis Temperature
Authors: Ghorbani Mohammad , Neugschwandtner Reinhard W. , Soja Gerhard , Konvalina Petr , Kopecký Marek
Published: April 2023

Biochar, as a carbon-rich material, may have a notable influence on carbon balance, especially that in soil mediums. The oxidation of biochar modifies the biochar’s effects on the soil’s carbon dynamics. To evaluate the alteration in soil carbon storage, biochars derived from wheat straw (WS) and wood residues (WR) produced at 350, 450, and 550 °C (marked BWS350, BWS450, BWS550, BWR350, BWR450, and BWR550) were oxidized with hydrogen peroxide (H2O2) and applied on a loamy soil (2% d.m.) for a 180-day greenhouse incubation period. The highest organic carbon (OC) concentration and carbon pool index (CPI) were obtained from the oxidized BWS550, with 154% and 70% increases, respectively, compared to the unamended control. For both the WS and WR biochars, applying oxidation significantly improved the soil’s aggregation indices, i.e., the mean weight diameter (MWD), water stable aggregates (WSA), and fractal dimension (D). BWS350, BWS450, and BWS550 showed significantly higher WSAs, with percentages of 68, 74, and 76% compared to the control (41%). The fractal dimensions decreased with an increasing pyrolysis temperature in both the biochar types. All the biochar treatments significantly decreased the soil bulk density (BD), while for both the pristine and oxidized biochars, the lowest BD was related to the biochars produced at high temperatures. The structural qualities of the biochars were enhanced by oxidation, particularly their specific surface areas and porosities, and this had a substantial impact on the soil structure and carbon status. The wheat straw biochar was more effective than the wood residue biochar and a higher pyrolysis temperature was more effective than lower ones for supporting the enhancement of the soil carbon pool.
Investigation and Implementation of New Technology Wearable Mobile Laser Scanning (WMLS) in Transition to an Intelligent Geospatial Cadastral Information System
Authors: Yiğit Abdurahman Yasin , Hamal Seda Nur Gamze , Yakar Murat , Ulvi Ali
Published: April 2023

The human population is constantly increasing throughout the world, and accordingly, construction is increasing in the same way. Therefore, there is an emergence of irregular and unplanned urbanization. In order to achieve the goal of preventing irregular and unplanned urbanization, it is necessary to monitor the cadastral borders quickly. In this sense, the concept of a sensitive, up-to-date, object-based, 3D, and 4D (4D, 3D + time) cadastral have to be a priority. Therefore, continuously updating cadastral maps is important in terms of sustainability and intelligent urbanization. In addition, due to the increase in urbanization, it has become necessary to update the cadastral information system and produce 3D cadastral maps. However, since there are big problems in data collection in urban areas where construction is rapid, different data-collection devices are constantly being applied. While these data-collection devices have proven themselves in terms of accuracy and precision, new technologies have started to be developed in urban areas especially, which is due to the increase in human population and the influence of environmental factors. For this reason, LiDAR data collection methods and the SLAM algorithm can offer a new perspective for producing cadastral maps in complex urban areas. In this study, 3D laser scanning data obtained from a portable sensor based on the SLAM algorithm are tested, which is a relatively new approach for cadastral surveys in complex urban areas. At the end of this study, two different statistical comparisons and accurate analyses of the proposed methodology with reference data were made. First, WMLS data were compared with GNSS data and RMSE values for X, Y, and Z, and were found to be 4.13, 4.91, and 7.77 cm, respectively. In addition, WMLS length data and cadastral length data from total-station data were compared and RMSE values were calculated as 4.76 cm.
Distribution Patterns and Driving Factors of the Phytoplankton Community in the Middle Reaches of the Yarlung Zangbo River
Authors: Li Xiaodong , Zhang Peng , Yang Qing , Liu Huiqiu , Chao Xin , Yang Shengxian , Ba Sang
Published: April 2023

The middle reaches of the Yarlung Zangbo River are a hot zone of the Alpine Water System and its ecological environment is diverse but vulnerable. We systematically examined and detailed the phytoplankton community’s composition, spatial-temporal dynamics, and driving factors in this area. A total of 224 samples from 28 sampling sites across wet and dry seasons were analyzed. The results showed that: (1) the community structure of the main stream is more complex and stable than that of the tributaries; (2) the number of species, average cell abundance, and average biomass in the main stream were higher than those in the tributaries; (3) TN, TUR, WT, and pH were the main influencing factors for the difference in the phytoplankton community’s structure between the main stream and the tributaries; (4) the phytoplankton community had a closer structure, higher connectivity, stronger resistance to environmental disturbance, and higher stability in the main stream, while those in the tributaries had higher interspecific synergy; and (5) the phytoplankton community’s assembly process in the main stream was mainly influenced by random processes and was mainly driven by dispersal limitation in the middle reaches of the Yarlung Zangbo River.
Protection Technique of Support System for Dynamic Disaster in Deep Underground Engineering: A Case Study
Authors: Liu Yunqiu , Zhao Yuemao , Wang Kun , Li Gongcheng , Ge Zhengchen
Published: April 2023

During excavation in a deep tunnel, dynamic disaster is an extremely severe impact failure. The necessity of an energy-absorbing support system is analyzed for different characteristics of dynamic disaster (rockburst) failure. The energy-absorbing support system design includes a combination of early-warning, energy-absorbing bolts, and other components. This support system is designed to meet the energy requirement of a rockburst disaster based on an early warning. The energy-absorbing rockbolt uses the stepwise decoupling technique to realize the brittle-ductile transition of the structure, which is referred to as a stepwise decoupling rockbolt (SD-bolt). The ultimate force, ultimate deformation, and energy were calculated as 241 kN, 442.3 mm, and 95.89 kJ under static pull-out load. Monitored by a microseismic system, the support system was tested by moderate rockburst disaster impact on site. Considering similar rockburst disaster failure cases, this energy-absorbing support system can reduce rockburst disaster damage to a certain extent and improve overall safety during deep engineering construction.
Testing the Affective Events Theory in Hospitality Management: A Multi-Sample Approach
Authors: Junça-Silva Ana , Lopes Eunice
Published: April 2023

Relying on the affective events theory, we argued that daily micro-events occurring in a hospitality context—daily hassles and uplifts—would influence hotel employees’ well-being and performance through affective reactions. Furthermore, we also expected that mindfulness would moderate these indirect relationships. Data were collected from employees who worked in hospitality working settings, and included both mindfulness practitioners (n = 182) and non-practitioners (n = 211). The findings evidenced that affective reactions mediated the path from daily micro-events and well-being and performance, in both samples. In addition, in the sample of non-mindfulness practitioners, mindfulness moderated the indirect relationship between daily micro-events and well-being through affective reactions, in such a way that the relationship became stronger for those who scored higher on mindfulness (versus those who scored lower). These findings were not significant for those who practiced mindfulness. Lastly, mindfulness did not moderate the relationship between daily micro-events and performance via affective reactions (for both samples). This study expands the affective events theory for the hospitality context and thus highlights the role of daily micro-events in stimulating employees’ performance and well-being. Furthermore, it shows how mindfulness as a trait may be relevant for employees who work in this context.
Safety Evaluation of Plain Concrete Lining Considering Deterioration and Aerodynamic Effects
Authors: Lu Feng , Wang Yi , Fu Junfu , Yang Yanxing , Qiu Wenge , Jing Yawen , Jiang Manlin , Li Huayun
Published: April 2023

With an increase in the service time of high-speed railway tunnels, various defects caused by construction-quality defects in the secondary lining begin to appear. How to evaluate the safety of such tunnels and take countermeasures is very important for the safe operation of tunnels. Based on the load-structure method and a numerical simulation, this paper studied the short-term and long-term safety of the missing section of anti-crack reinforcement mesh in the plain concrete lining of a high-speed railway mountain tunnel. The short-term safety evaluation considered the influence of negative pressure caused by aerodynamic effects. The long-term safety evaluation considered the combined influence of the surrounding rock and concrete deterioration and the negative pressure and concrete fatigue damage caused by aerodynamic effects. The results showed that under the negative pressure generated by aerodynamic effects, the minimum tensile safety factor of the lining in the defective section increased by 3.8%, while the minimum compressive safety factor of the lining decreased by 7.9%. The negative pressure generated by the aerodynamic effects had little impact on the short-term safety of the lining in the defective section. During the long-term safety evaluation, the overall safety of the defective section decreased significantly, and the minimum tensile and minimum compressive safety factors of the lining decreased by 59.4% and 66.8%, respectively. The calculation results for the initial design do not meet the long-term design requirements and cannot guarantee the long-term safe operation of the tunnel. Finally, two new strengthening methods of galvanized steel mesh-short bolts and galvanized corrugated steel plate-short bolts were proposed to strengthen the defective section of the concrete lining, so as to improve the ultimate bearing capacity and toughness of the plain concrete lining structure.
Exploitation or Exploration? Managerial Myopia, Economic Policy Uncertainty and Ambidextrous Innovation Investment
Authors: Yang Tingyu , Cui Yongmei , Li Rui
Published: April 2023

In today’s increasingly competitive international environment, original technology innovation has become essential for enhancing enterprises’ sustainability. As key innovation needs constant exploration rather than growing leaps and bounds, it is often ignored by managers who focus on short-term performance. Taking the data of publicly listed Chinese companies from 2010 to 2020 as a sample, this paper put forward the relation between managerial myopia and ambidextrous innovation investment on the basis of a empirical approach combining machine learning technology. Results revealed that managerial myopia has different effects on the ambidextrous innovation investment of enterprises. Specifically, the study finds a significant negative association between managerial myopia and exploratory innovation investment, while there is no significant relationship with regard to exploitative innovation investment. Further study showed that the negative influence is weakened by economic policy uncertainty and stronger in companies with more severe agency problems. By shedding light on the way that managerial myopia affects enterprises’ ambidextrous innovation investment, this research contributes to the literature on the impact of managerial myopia, offering key insights into how to cultivate the core competitiveness of enterprises and ensure their sustainable development.
Synthetic Dataset of Electroluminescence Images of Photovoltaic Cells by Deep Convolutional Generative Adversarial Networks
Authors: Romero Héctor Felipe Mateo , Hernández-Callejo Luis , Rebollo Miguel Ángel González , Cardeñoso-Payo Valentín , Gómez Victor Alonso , Bello Hugo Jose , Moyo Ranganai Tawanda , Aragonés Jose Ignacio Morales
Published: April 2023

Affordable and clean energy is one of the Sustainable Development Goals (SDG). SDG compliance and economic crises have boosted investment in solar energy as an important source of renewable generation. Nevertheless, the complex maintenance of solar plants is behind the increasing trend to use advanced artificial intelligence techniques, which critically depend on big amounts of data. In this work, a model based on Deep Convolutional Generative Adversarial Neural Networks (DCGANs) was trained in order to generate a synthetic dataset made of 10,000 electroluminescence images of photovoltaic cells, which extends a smaller dataset of experimentally acquired images. The energy output of the virtual cells associated with the synthetic dataset is predicted using a Random Forest regression model trained from real IV curves measured on real cells during the image acquisition process. The assessment of the resulting synthetic dataset gives an Inception Score of 2.3 and a Fréchet Inception Distance of 15.8 to the real original images, which ensures the excellent quality of the generated images. The final dataset can thus be later used to improve machine learning algorithms or to analyze patterns of solar cell defects.
Tourism Demand Prediction after COVID-19 with Deep Learning Hybrid CNN–LSTM—Case Study of Vietnam and Provinces
Authors: Nguyen-Da Thao , Li Yi-Min , Peng Chi-Lu , Cho Ming-Yuan , Nguyen-Thanh Phuong
Published: April 2023

The tourism industry experienced a positive increase after COVID-19 and is the largest segment in the foreign exchange contribution in developing countries, especially in Vietnam, where China has begun reopening its borders and lifted the pandemic limitation on foreign travel. This research proposes a hybrid algorithm, combined convolution neural network (CNN) and long short-term memory (LSTM), to accurately predict the tourism demand in Vietnam and some provinces. The number of new COVID-19 cases worldwide and in Vietnam is considered a promising feature in predicting algorithms, which is novel in this research. The Pearson matrix, which evaluates the correlation between selected features and target variables, is computed to select the most appropriate input parameters. The architecture of the hybrid CNN–LSTM is optimized by utilizing hyperparameter fine-tuning, which improves the prediction accuracy and efficiency of the proposed algorithm. Moreover, the proposed CNN–LSTM outperformed other traditional approaches, including the backpropagation neural network (BPNN), CNN, recurrent neural network (RNN), gated recurrent unit (GRU), and LSTM algorithms, by deploying the K-fold cross-validation methodology. The developed algorithm could be utilized as the baseline strategy for resource planning, which could efficiently maximize and deeply utilize the available resource in Vietnam.
Plastic Management and Sustainability: A Data-Driven Study
Authors: El-Rayes Nesreen , Chang Aichih (Jasmine) , Shi Jim
Published: April 2023

The world is experiencing a rapidly increasing plastic production and consumption trend. The exacerbating plastic crisis has attracted various initiatives and actions across numerous organizations to foster stakeholder collaboration. In particular, academic researchers have paid considerable attention to the inherent supply chain sustainability. This study aims to (1) examine the status quo of plastic management research and provide recommendations and directions gleaned from the literature survey using text mining; and (2) perform descriptive and predictive analysis based on datasets collected from governmental, public, private, and not-for-profit institutions in the United States between 2016 and 2021 to quantify the size and severity of the crisis on various levels. Echoing the same global plastic production trend, our study reveals that the plastic debris that ends up in the ocean is growing exponentially, and global plastic production is expected to fluctuate between 500 and 600 million metric tons by 2025. From a research perspective, there is a remarkable shortage of publications empowering Blockchain technology (BCT) to address the plastic crisis. Little research is related to scaling up the plastic waste collection and re-thinking or re-designing products. There is no significant connection between ‘re-purpose’ and ‘innovation’. The industry and not-for-profit organizations are typically the forerunners of the campaign compared to academia in terms of investigating the adoption of technology to address the plastic crisis. This study features rich data-driven results and interpretation.
The Impact of ESG Scores on Risk Market Performance
Authors: Aldieri Luigi , Amendola Alessandra , Candila Vincenzo
Published: April 2023

Over the last two decades, there has been an increased attention to and awareness of corporate environmental, social, and governance (ESG) responsibilities. The asset allocation process has changed accordingly to consider these ESG responsibilities, and it has largely been recognized that private and institutional investors are sensitive to ESG factors when deciding on firms in which to invest. In addition to ESG factors, other key stock-related factors to which investors generally pay attention are risk-adjusted indicators, such as the Sharpe ratio (SR) and the Sortino index (SI), as well as tail risk measures, such as the Value-at-Risk (VaR) and the Expected Shortfall (ES). Overall, the SR, SI, VaR, and ES can provide a guide for investors concerning the risk market performance of a stock under investigation. In this context, the research question that arises is the following: are firms’ performances sensitive to ESG rates? The present contribution aims to answer this question. In particular, the SR, SI, VaR, and ES measures of a set of listed firms are calculated and evaluated. Among these, there are firms with low ESG grades and some with high ESG grades according to two ESG rate providers. The list of stocks under consideration consists of the first 25 constituents (by weight) of the S&P500 index in the period from 2020 and 2022. The empirical findings indicate that risk market performance does not properly depend on high or low ESG rates.
Using Importance–Performance Analysis (IPA) to Improve Golf Club Management: The Gap between Users and Managers’ Perceptions
Authors: Serrano-Gómez Virginia , García-García Oscar , Rial-Boubeta Antonio
Published: April 2023

This work is carried out in order to provide new evidence on the usefulness of the Importance–Performance Analysis (IPA) in the management of golf courses, identifying the main strengths, weaknesses, and discrepancies between managers and users. This information will make it possible to identify potentially mistaken beliefs of managers regarding the service and to design improvement strategies based on the results. The participants were 11 managers, with an average age of 35.4 years (σ 6.5), of whom 72.7% were men and 27.3% were women, and 891 users, with an average age of 47.5 years (σ 12.3), of whom 81.7% were men and 18.3% were women. The instrument used was the Q-Golf scale, and among others, it was applied to the IPA. The results obtained show how the perception of managers regarding the service is worse than that of users. Additionally, the global assessment of the users is higher than the average assessment of each of the items of the club. This positive halo effect, which is not found in the case of managers, is very interesting from the point of view of the loyalty of golf users.
Participatory Planning for the Drafting of a Regional Law on the Bioeconomy
Authors: Tarsitano Elvira , Giordano Simona , de Gennaro Gianluigi , Turi Annalisa , Ronco Giovanni , Parchitelli Lucia
Published: April 2023

In an increasingly complex global economic scenario, sustainability represents a fundamental compass aimed to guide actions of institutions and individuals. A nondissipative use of Earth’s resources is feasible through a common effort that reconsiders the actual development system according to the key principles of the bioeconomy. It is vital to start from local contexts to reach the global dimension by exploiting the opportunities available in each territory. Starting from these assumptions, the participatory process activated in the Apulia region has represented the first step towards an intervention strategy in the panorama of the bioeconomy, and has made it possible to increase the awareness of a development based on the adoption of bioeconomy models and, therefore, circular economy ones through an effective inclusion process. A process has given rise to a project allowing all involved actors to reflect on the double economy–environment system, to share good practices and promote the adoption of lifestyles and consumption styles more compatible with the principles of the bioeconomy and to elaborate a proposal for a participatory regional law for the bioeconomy in the Apulia region as an expression of the collaboration between different bodies and institutions (universities, Confindustria and the council of the Puglia region).
Digital Ethnography? Our Experiences in the Use of SenseMaker for Understanding Gendered Climate Vulnerabilities amongst Marginalized Agrarian Communities
Authors: Joshi Deepa , Panagiotou Anna , Bisht Meera , Udalagama Upandha , Schindler Alexandra
Published: April 2023

Digital innovations and interventions can potentially revolutionize agri-food systems, especially in coping with climate challenges. On a similar note, digital research tools and methods are increasingly popular for the efficient collection and analysis of real-time, large-scale data. It is claimed that these methods can also minimize subjective biases that are prevalent in traditional qualitative research. However, given the digital divide, especially affecting women and marginalized communities, these innovations could potentially introduce further disparities. To assess these contradictions, we piloted SenseMaker, a digital ethnography tool designed to capture individual, embodied experiences, biases, and perceptions to map vulnerabilities and resilience to climate impacts in the Gaya District in Bihar. Our research shows that this digital tool allows for a systematic co-design of the research framework, allows for the collection of large volumes of data in a relatively short time, and a co-analysis of the research data by the researchers and the researched. This process allowed us to map and capture the complexities of intersectional inequalities in relation to climate change vulnerability. However, we also noted that the application of the tool is influenced by the prior exposure to technology (digital devices) of both the enumerators and researched groups and requires significant resources when implemented in contexts where there is a need to translate the data from local dialects and languages to more dominant languages (English). Most importantly, perceptions, positionalities, and biases of researchers can significantly impact the design of the tool’s signification framework, reiterating the fact that researcher bias persists regardless of technological innovations in research methodology.
Carbazole Degradation and Genetic Analyses of Sphingobium sp. Strain BS19 Isolated from Antarctic Soil
Authors: Sato Kenta , Take Seiryu , Ahmad Siti Aqlima , Gomez-Fuentes Claudio , Zulkharnain Azham
Published: April 2023

The Antarctic region is facing a higher risk of hydrocarbon pollution due to increased human activities. Compounds such as polycyclic aromatic hydrocarbons (PAHs) and heterocyclic compounds available in fuel are highly stable and can reside in the environment for prolonged periods if left untreated. The isolation of native strains is needed to develop bioremediation applications suitable for Antarctica. Strain BS19 was isolated as heterocyclic compound carbazole-degrading bacterium from Antarctic soil through culture enrichment. The 16S rRNA gene sequences identified strain BS19 as a member of the Sphingonium genus. Strain BS19 could remove 75% of carbazole after 15 days of culture at 15 °C. Whole genome sequencing resulted in incomplete genomes of 4.77 Mb in 96 contigs with the lowest GC content among Sphingobium sp. strains. The analyses revealed car gene cluster and ant genes and cat gene cluster required for the complete metabolism of carbazole as a source of carbon and energy. The comparison of the car gene cluster showed a similarity to the car gene cluster of Novosphingobium KA1. The expression of the car gene cluster was confirmed with an RT-PCR analysis indicating the involvement of the predicted genes in carbazole degradation. The findings from this study could provide more insight into developing bioremediation applications and approaches for Antarctica and other cold environments.
A Comprehensive Analysis of Security-Based Schemes in Underwater Wireless Sensor Networks
Authors: Saeed Khalid , Khalil Wajeeha , Al-Shamayleh Ahmad Sami , Ahmed Sheeraz , Akhunzada Adnan , Alharthi Salman Z. , Gani Abdullah
Published: April 2023

Underwater wireless sensor networks (UWSNs) are comprised of sensor nodes that are deployed under the water having limited battery power and other limited resources. Applications of UWSNs include monitoring the quality of the water, mine detection, environment monitoring, military surveillance, disaster prediction, and underwater navigation. UWSNs are more vulnerable to security attacks as compared to their counterparts such as wireless sensor networks (WSNs). The possible attacks in UWSNs can abrupt the operation of entire network. This research work presents the analysis of relevant research done on security-based schemes in UWSNs. The security-based schemes are categorized into five sub-categories. Each technique in each category is analyzed in detail. The major contribution in each security-based scheme along with technique used, possible future research issues and implementation tool are discussed in detail. The open research issues and future trends identified and presented in this research can be further explored by the research community.
Institutional Differences and the Choice of Outward Foreign Direct Investment Mode under the “Belt and Road” Initiative: Experience Analysis Based on China’s Manufacturing Enterprises
Authors: Xie Qing , Yin Hua
Published: April 2023

Based on 1692 outward foreign direct investment (OFDI) events of 735 A-share listed companies in China’s manufacturing industry from 2010 to 2019, this paper empirically examines the effect of investment motivation and the impact of institutional differences between China and the host country on the choice of OFDI entry mode; the paper also investigates the moderating effect of the “Belt and Road” Initiative (BRI) on Chinese manufacturing enterprises (CMEs) through use of the logit model. The empirical results show that, with greater institutional differences, CMEs become more inclined to choose cross-border mergers and acquisitions (M&A). Furthermore, a positive moderating effect of resource-seeking motivation on the choice of M&A OFDI by CMEs is observed. The signing of the “Belt and Road” cooperation document positively moderates institutional differences in promoting CMEs—especially state-owned CMEs—to choose the M&A mode. The “Belt and Road” Initiative provides an efficient supply system for OFDI by CMEs. This study enriches and extends existing institutional theories and provides suggestions for the promotion of the geopolitical pattern and international cooperation regarding the “Belt and Road” Initiative.
A Collection of Two-Dimensional Copulas Based on an Original Parametric Ratio Scheme
Authors: Chesneau Christophe
Published: April 2023

The creation of two-dimensional copulas is crucial for the proposal of novel families of two-dimensional distributions and the analysis of original dependence structures between two quantitative variables. Such copulas can be developed in a variety of ways. In this article, we provide theoretical contributions to this subject; we emphasize a new parametric ratio scheme to create copulas of the following form: C(x,y)=(b+1)xy/[b+ϕ(x,y)], where b is a constant and ϕ(x,y) is a two-dimensional function. As a notable feature, this form can operate an original trade-off between the product copula and more versatile copulas (not symmetric, with tail dependence, etc.). Instead of a global study, we examine seven concrete examples of such copulas, which have never been considered before. Most of them are extended versions of existing non-ratio copulas, such as the Celebioglu–Cuadras, Ali-Mikhail-Haq, and Gumbel–Barnett copulas. We discuss their attractive properties, including their symmetry, dominance, dependence, and correlation features. Some graphics and tables are given as complementary works. Our findings expand the horizons of new two-dimensional distributional or dependence modeling.
Design of Axially Symmetric Fluid–Spring Vibration Absorber with Five DOFs Based on Orthogonal Experiment
Authors: Liu Youyu , Fang Zhao , Ma Liteng , Tao Wanbao , Wang Peng , Wang Zhijia
Published: April 2023

The strong and complex vibration from a manipulator for anchor drilling will damage the key components of the manipulator and produce noise at the same time. According to its vibration characteristics, a fluid–spring vibration absorption approach with five degrees of freedom (DOFs) is proposed, which has perfect symmetry, and a vibration absorber was designed with a symmetrical structure. Employing the generalization formula of the Bernoulli equation and dynamic equation, a fluid–spring coupling damping coefficient equation was constructed. Vibration transmissibility was used as the evaluation index of vibration absorption performance. The elastic coefficients of the tension spring and torsion spring, the area ratio of circular through-holes to the vibration-absorbing plate, and the radius of circular through-holes were the main independent factors influencing the damping coefficients. An orthogonal experiment with four factors and four levels was designed. Using FLUENT and SIMULATION to implement joint simulations, the distribution law of the flow fields and the damping coefficients of each approach were obtained, and then the best combination of factors was selected. Taking a manipulator used for anchor drilling in Huainan of China as a case study, using the designed fluid–spring vibration absorber, the vibration displacements in the five DOFs were reduced by 68.32%, 49.82%, 52.17%, 49.01%, and 57.09% respectively, indicating a good vibration absorption performance with symmetry about the z→-axis.
A Data-Driven Two-Phase Multi-Split Causal Ensemble Model for Time Series
Authors: Ma Zhipeng , Kemmerling Marco , Buschmann Daniel , Enslin Chrismarie , Lütticke Daniel , Schmitt Robert H.
Published: April 2023

Causal inference is a fundamental research topic for discovering the cause–effect relationships in many disciplines. Inferring causality means identifying asymmetric relations between two variables. In real-world systems, e.g., finance, healthcare, and industrial processes, time series data from sensors and other data sources offer an especially good basis to infer causal relationships. Therefore, many different time series causal inference algorithms have been proposed in recent years. However, not all algorithms are equally well-suited for a given dataset. For instance, some approaches may only be able to identify linear relationships, while others are applicable for non-linearities. Algorithms further vary in their sensitivity to noise and their ability to infer causal information from coupled vs. non-coupled time series. As a consequence, different algorithms often generate different causal relationships for the same input. In order to achieve a more robust causal inference result, this publication proposes a novel data-driven two-phase multi-split causal ensemble model to combine the strengths of different causality base algorithms. In comparison to existing approaches, the proposed ensemble method reduces the influence of noise through a data partitioning scheme in a first phase. To achieve this, the data are initially divided into several partitions and the base causal inference algorithms are applied to each partition. Subsequently, Gaussian mixture models are used to identify the causal relationships derived from the different partitions that are likely to be valid. In the second phase, the identified relationships from each base algorithm are then merged based on three combination rules. The proposed ensemble approach is evaluated using multiple metrics, among them a newly developed evaluation index for causal ensemble approaches. We perform experiments using three synthetic datasets with different volumes and complexity, which have been specifically designed to test causality detection methods under different circumstances while knowing the ground truth causal relationships. In these experiments, our causality ensemble outperforms each of its base algorithms. In practical applications, the use of the proposed method could hence lead to more robust and reliable causality results.
Hybridization of Particle Swarm Optimization with Variable Neighborhood Search and Simulated Annealing for Improved Handling of the Permutation Flow-Shop Scheduling Problem
Authors: Hayat Iqbal , Tariq Adnan , Shahzad Waseem , Masud Manzar , Ahmed Shahzad , Ali Muhammad Umair , Zafar Amad
Published: April 2023

Permutation flow-shop scheduling is the strategy that ensures the processing of jobs on each subsequent machine in the exact same order while optimizing an objective, which generally is the minimization of makespan. Because of its NP-Complete nature, a substantial portion of the literature has mainly focused on computational efficiency and the development of different AI-based hybrid techniques. Particle Swarm Optimization (PSO) has also been frequently used for this purpose in the recent past. Following the trend and to further explore the optimizing capabilities of PSO, first, a standard PSO was developed during this research, then the same PSO was hybridized with Variable Neighborhood Search (PSO-VNS) and later on with Simulated Annealing (PSO-VNS-SA) to handle Permutation Flow-Shop Scheduling Problems (PFSP). The effect of hybridization was validated through an internal comparison based on the results of 120 different instances devised by Taillard with variable problem sizes. Moreover, further comparison with other reported hybrid metaheuristics has proved that the hybrid PSO (HPSO) developed during this research performed exceedingly well. A smaller value of 0.48 of ARPD (Average Relative Performance Difference) for the algorithm is evidence of its robust nature and significantly improved performance in optimizing the makespan as compared to other algorithms.
The INPReS Intervention Escalation Framework for Avoiding Overcrowding in Tourism Destinations
Authors: Schmücker Dirk , Reif Julian , Horster Eric , Engelhardt Denise , Höftmann Nele , Naschert Lisa , Radlmayr Christof
Published: April 2023

Visitor management is one way to avoid or mitigate the negative effects of overcrowding in tourism destinations. Visitor management depends upon a set of interventions aimed at guiding visitors and recommending alternatives. Here, we present a conceptual framework of such interventions using an escalation from information, nudging, pricing, and reservation to stoppage (INPReS). The interventions are discussed against the backdrop of the changing role of destination management organisations (DMOs) in smart destinations, the challenges to DMO stewardship in avoiding overcrowding, and the design considerations between nudging and persuasion.
A Review of Traditional and Emerging Residual Chlorine Quenchers on Disinfection By-Products: Impact and Mechanisms
Authors: Li Xue , Zhao Zhijing , Qu Zheng , Li Xinyu , Zhang Zengli , Liang Xiaojun , Chen Jingsi , Li Jiafu
Published: April 2023

Disinfection by-products (DBPs) are the most common organic contaminants in tap water and are of wide concern because of their highly developmental toxic, cytotoxic, and carcinogenic properties. Typically, to control the proliferation of pathogenic microorganisms, a certain concentration of residual chlorine is retained in the factory water, which reacts with the natural organic matter and the disinfection by-products that have been formed, thus affecting the determination of DBPs. Therefore, to obtain an accurate concentration, residual chlorine in tap water needs to be quenched prior to treatment. Currently, the most commonly used quenching agents are ascorbic acid, sodium thiosulfate, ammonium chloride, sodium sulfite, and sodium arsenite, but these quenching agents can cause varying degrees of DBPs degradation. Therefore, in recent years, researchers have attempted to find emerging chlorine quenchers. However, no studies have been conducted to systematically review the effects of traditional quenchers and new ones on DBPs, as well as their advantages, disadvantages, and scope of application. For inorganic DBPs (bromate, chlorate, and chlorite), sodium sulfite has been proven to be the ideal chlorine quencher. For organic DBPs, although ascorbic acid caused the degradation of some DBPs, it remains the ideal quenching agent for most known DBPs. Among the studied emerging chlorine quenchers, n-acetylcysteine (NAC), glutathione (GSH), and 1,3,5-trimethoxybenzene are promising for their application as the ideal chlorine quencher of organic DBPs. The dehalogenation of trichloronitromethane, trichloroacetonitrile, trichloroacetamide, and bromochlorophenol by sodium sulfite is caused by nucleophilic substitution reaction. This paper takes the understanding of DBPs and traditional and emerging chlorine quenchers as a starting point to comprehensively summarize their effects on different types of DBPs, and to provide assistance in understanding and selecting the most suitable residual chlorine quenchers during DBPs research.
A New Method for Ecological Risk Assessment of Combined Contaminated Soil
Authors: Wang Qiaoping , Wang Junhuan , Cheng Jiaqi , Zhu Yingying , Geng Jian , Wang Xin , Feng Xianjie , Hou Hong
Published: April 2023

Ecological risk assessment of combined polluted soil has been conducted mostly on the basis of the risk screening value (RSV) of a single pollutant. However, due to its defects, this method is not accurate enough. Not only were the effects of soil properties neglected, but the interactions among different pollutants were also overlooked. In this study, the ecological risks of 22 soils collected from four smelting sites were assessed by toxicity tests using soil invertebrates (Eisenia fetida, Folsomia candida, Caenorhabditis elegans) as subjects. Besides a risk assessment based on RSVs, a new method was developed and applied. A toxicity effect index (EI) was introduced to normalize the toxicity effects of different toxicity endpoints, rendering assessments comparable based on different toxicity endpoints. Additionally, an assessment method of ecological risk probability (RP), based on the cumulative probability distribution of EI, was established. Significant correlation was found between EI−based RP and the RSV−based Nemerow ecological risk index (NRI) (p < 0.05). In addition, the new method can visually present the probability distribution of different toxicity endpoints, which is conducive to aiding risk managers in establishing more reasonable risk management plans to protect key species. The new method is expected to be combined with a complex dose–effect relationship prediction model constructed by machine learning algorithm, providing a new method and idea for the ecological risk assessment of combined contaminated soil.
Correction: Kurpas et al. Genomic Analysis of SARS-CoV-2 Alpha, Beta and Delta Variants of Concern Uncovers Signatures of Neutral and Non-Neutral Evolution. Viruses 2022, 14, 2375
Authors: Kurpas Monika Klara , Jaksik Roman , Kuś Pawel , Kimmel Marek
Published: April 2023

Missing Funding [...]
Poxvirus Infections in Dairy Farms and Transhumance Cattle Herds in Nigeria
Authors: Omoniwa David Oludare , Meki Irene Kasindi , Kudi Caleb Ayuba , Sackey Anthony Kojo , Aminu Maryam , Adedeji Adeyinka Jeremy , Meseko Clement Adebajo , Luka Pam Dachung , Asala Olayinka Oluwafemi , Adole Jolly Amoche , Atai Rebecca Bitiyong , Atuman Yakubu Joel , Settypalli Tirumala Bharani Kumar , Cattoli Giovanni , Lamien Charles Euloge
Published: April 2023

Lumpy Skin disease (LSD) is an economically important disease in cattle caused by the LSD virus (LSDV) of the genus Capripoxvirus, while pseudocowpox (PCP) is a widely distributed zoonotic cattle disease caused by the PCP virus (PCPV) of the genus Parapoxvirus. Though both viral pox infections are reportedly present in Nigeria, similarities in their clinical presentation and limited access to laboratories often lead to misdiagnosis in the field. This study investigated suspected LSD outbreaks in organized and transhumance cattle herds in Nigeria in 2020. A total of 42 scab/skin biopsy samples were collected from 16 outbreaks of suspected LSD in five northern States of Nigeria. The samples were analyzed using a high-resolution multiplex melting (HRM) assay to differentiate poxviruses belonging to Orthopoxvirus, Capripoxvirus, and Parapoxvirus genera. LSDV was characterized using four gene segments, namely the RNA polymerase 30 kDa subunit (RPO30), G-protein-coupled receptor (GPCR), the extracellular enveloped virus (EEV) glycoprotein and CaPV homolog of the variola virus B22R. Likewise, the partial B2L gene of PCPV was also analyzed. Nineteen samples (45.2%) were positive according to the HRM assay for LSDV, and five (11.9%) were co-infected with LSDV and PCPV. The multiple sequence alignments of the GPCR, EEV, and B22R showed 100% similarity among the Nigerian LSDV samples, unlike the RPO30 phylogeny, which showed two clusters. Some of the Nigerian LSDVs clustered within LSDV SG II were with commonly circulating LSDV field isolates in Africa, the Middle East, and Europe, while the remaining Nigerian LSDVs produced a unique sub-group. The B2L sequences of Nigerian PCPVs were 100% identical and clustered within the PCPV group containing cattle/Reindeer isolates, close to PCPVs from Zambia and Botswana. The results show the diversity of Nigerian LSDV strains. This paper also reports the first documented co-infection of LSDV and PCPV in Nigeria.
Targeting the Human Influenza a Virus: The Methods, Limitations, and Pitfalls of Virtual Screening for Drug-like Candidates Including Scaffold Hopping and Compound Profiling
Authors: Scior Thomas , Cuanalo-Contreras Karina , Islas Angel A. , Martinez-Laguna Ygnacio
Published: April 2023

In this study, we describe the input data and processing steps to find antiviral lead compounds by a virtual screen. Two-dimensional and three-dimensional filters were designed based on the X-ray crystallographic structures of viral neuraminidase co-crystallized with substrate sialic acid, substrate-like DANA, and four inhibitors (oseltamivir, zanamivir, laninamivir, and peramivir). As a result, ligand–receptor interactions were modeled, and those necessary for binding were utilized as screen filters. Prospective virtual screening (VS) was carried out in a virtual chemical library of over half a million small organic substances. Orderly filtered moieties were investigated based on 2D- and 3D-predicted binding fingerprints disregarding the “rule-of-five” for drug likeness, and followed by docking and ADMET profiling. Two-dimensional and three-dimensional screening were supervised after enriching the dataset with known reference drugs and decoys. All 2D, 3D, and 4D procedures were calibrated before execution, and were then validated. Presently, two top-ranked substances underwent successful patent filing. In addition, the study demonstrates how to work around reported VS pitfalls in detail.
Recombinant Virus Quantification Using Single-Cell Droplet Digital PCR: A Method for Infectious Titer Quantification
Authors: Korotkaja Ksenija , Zajakina Anna
Published: April 2023

The quantification of viruses is necessary for both research and clinical applications. The methods available for RNA virus quantification possess several drawbacks, including sensitivity to inhibitors and the necessity of a standard curve generation. The main purpose of this study was to develop and validate a method for the quantification of recombinant, replication-deficient Semliki Forest virus (SFV) vectors using droplet digital PCR (ddPCR). This technique demonstrated stability and reproducibility using various sets of primers that targeted inserted transgenes, as well as the nsP1 and nsP4 genes of the SFV genome. Furthermore, the genome titers in the mixture of two types of replication-deficient recombinant virus particles were successfully measured after optimizing the annealing/extension temperature and virus:virus ratios. To measure the infectious units, we developed a single-cell ddPCR, adding the whole infected cells to the droplet PCR mixture. Cell distribution in the droplets was investigated, and β-actin primers were used to normalize the quantification. As a result, the number of infected cells and the virus infectious units were quantified. Potentially, the proposed single-cell ddPCR approach could be used to quantify infected cells for clinical applications.
Calcinosis Cutis and Calciphylaxis in Autoimmune Connective Tissue Diseases
Authors: Mormile Ilaria , Mosella Francesca , Turco Piergiorgio , Napolitano Filomena , de Paulis Amato , Rossi Francesca Wanda
Published: April 2023

Calcinosis represents a severe complication of several autoimmune disorders. Soft-tissue calcifications have been classified into five major types: dystrophic, metastatic, idiopathic, iatrogenic, and calciphylaxis. Autoimmune diseases are usually associated with dystrophic calcifications, including calcinosis cutis, occurring in damaged or devitalized tissues in the presence of normal serum levels of calcium and phosphate. In particular, calcinosis cutis has been described in dermatomyositis, polymyositis, juvenile dermatomyositis, systemic sclerosis, systemic lupus erythematosus, primary Sjögren’s syndrome, overlap syndrome, mixed connective tissue disease, and rheumatoid arthritis. Calciphylaxis, a severe and life-threatening syndrome presenting with vascular calcifications and thrombosis, has also been associated with some autoimmune conditions. Due to the potentially disabling character of calcinosis cutis and calciphylaxis, physicians’ awareness about the clinical presentation and management of these diseases should be increased to select the most appropriate treatment option and avoid long-term complications. In this review, we aim to analyze the clinical features of calcinosis cutis and calciphylaxis associated with autoimmune diseases, and the main treatment strategies evaluated up to now for treating this potentially disabling disease.