bluuebunny/crossref_metadata_2025 huggingface dataset:
Prediction of Preterm Labor from the Electrohysterogram Signals Based on Different Gestational Weeks
Authors: Mohammadi Far Somayeh , Beiramvand Matin , Shahbakhti Mohammad , Augustyniak Piotr
Published: June 2023

Timely preterm labor prediction plays an important role for increasing the chance of neonate survival, the mother’s mental health, and reducing financial burdens imposed on the family. The objective of this study is to propose a method for the reliable prediction of preterm labor from the electrohysterogram (EHG) signals based on different pregnancy weeks. In this paper, EHG signals recorded from 300 subjects were split into 2 groups: (I) those with preterm and term labor EHG data that were recorded prior to the 26th week of pregnancy (referred to as the PE-TE group), and (II) those with preterm and term labor EHG data that were recorded after the 26th week of pregnancy (referred to as the PL-TL group). After decomposing each EHG signal into four intrinsic mode functions (IMFs) by empirical mode decomposition (EMD), several linear and nonlinear features were extracted. Then, a self-adaptive synthetic over-sampling method was used to balance the feature vector for each group. Finally, a feature selection method was performed and the prominent ones were fed to different classifiers for discriminating between term and preterm labor. For both groups, the AdaBoost classifier achieved the best results with a mean accuracy, sensitivity, specificity, and area under the curve (AUC) of 95%, 92%, 97%, and 0.99 for the PE-TE group and a mean accuracy, sensitivity, specificity, and AUC of 93%, 90%, 94%, and 0.98 for the PL-TL group. The similarity between the obtained results indicates the feasibility of the proposed method for the prediction of preterm labor based on different pregnancy weeks.
From Corrective to Predictive Maintenance—A Review of Maintenance Approaches for the Power Industry
Authors: Molęda Marek , Małysiak-Mrozek Bożena , Ding Weiping , Sunderam Vaidy , Mrozek Dariusz
Published: June 2023

Appropriate maintenance of industrial equipment keeps production systems in good health and ensures the stability of production processes. In specific production sectors, such as the electrical power industry, equipment failures are rare but may lead to high costs and substantial economic losses not only for the power plant but for consumers and the larger society. Therefore, the power production industry relies on a variety of approaches to maintenance tasks, ranging from traditional solutions and engineering know-how to smart, AI-based analytics to avoid potential downtimes. This review shows the evolution of maintenance approaches to support maintenance planning, equipment monitoring and supervision. We present older techniques traditionally used in maintenance tasks and those that rely on IT analytics to automate tasks and perform the inference process for failure detection. We analyze prognostics and health-management techniques in detail, including their requirements, advantages and limitations. The review focuses on the power-generation sector. However, some of the issues addressed are common to other industries. The article also presents concepts and solutions that utilize emerging technologies related to Industry 4.0, touching on prescriptive analysis, Big Data and the Internet of Things. The primary motivation and purpose of the article are to present the existing practices and classic methods used by engineers, as well as modern approaches drawing from Artificial Intelligence and the concept of Industry 4.0. The summary of existing practices and the state of the art in the area of predictive maintenance provides two benefits. On the one hand, it leads to improving processes by matching existing tools and methods. On the other hand, it shows researchers potential directions for further analysis and new developments.
Structural Monitoring of a Large-Span Arch Bridge Using Customized Sensors
Authors: Ietka Isabelle , Moutinho Carlos , Pereira Sérgio , Cunha Álvaro
Published: June 2023

Due to the increasing importance of the continuous monitoring of Civil Structures, this research aims to take advantage of new solutions of measurement systems and sensors in the Structural Health Monitoring of bridges, using the reinforced concrete arch Arrábida Bridge as a case study. With the support of customized sensors, this work starts by performing preliminary ambient vibration tests on Arrábida Bridge, aiming at the identification of the natural frequencies and respective vibration modes of the deck. Then, the measurement campaigns carried over time are described, which involved different types of customized sensors, namely, accelerometers, temperature sensors and displacement sensors. Based on the signals collected by these devices, some preliminary analyses were performed. The results show that the temperature measured at the deck sections presents different amplitudes and phase shifts when compared to the temperature measured at the arch sections. Moreover, using the temperature measurements, it is possible to estimate with good accuracy the displacements in the expansion joints of the bridge. It was also observed that the displacements in these joints, although being conditioned by the temperature effects, are also marked by a dynamic component arising from the traffic loads over the deck. The observation of this phenomenon is an innovative aspect found in this investigation, which can be used in the future to characterize the traffic loads on the structure.
Learning Background-Suppressed Dual-Regression Correlation Filters for Visual Tracking
Authors: He Jianzhong , Ji Yuanfa , Sun Xiyan , Wu Sunyong , Wu Chunping , Chen Yuxiang
Published: June 2023

The discriminative correlation filter (DCF)-based tracking method has shown good accuracy and efficiency in visual tracking. However, the periodic assumption of sample space causes unwanted boundary effects, restricting the tracker’s ability to distinguish between the target and background. Additionally, in the real tracking environment, interference factors such as occlusion, background clutter, and illumination changes cause response aberration and, thus, tracking failure. To address these issues, this work proposed a novel tracking method named the background-suppressed dual-regression correlation filter (BSDCF) for visual tracking. First, we utilize the background-suppressed function to crop out the target features from the global features. In the training step, while introducing the spatial regularity constraint and background response suppression regularization, we construct a dual regression structure to train the target and global filters separately. The aim is to exploit the difference between the output response maps for mutual constraint to highlight the target and suppress the background interference. Furthermore, in the detection step, the global response can be enhanced by a weighted fusion of the target response to further improve the tracking performance in complex scenes. Finally, extensive experiments are conducted on three public benchmarks (including OTB100, TC128, and UAVDT), and the experimental results indicate that the proposed BSDCF tracker achieves tracking performance comparable to many state-of-the-art (SOTA) trackers in a variety of complex situations.
A Multi-Scale Dehazing Network with Dark Channel Priors
Authors: Yang Guoliang , Yang Hao , Yu Shuaiying , Wang Jixiang , Nie Ziling
Published: June 2023

Image dehazing based on convolutional neural networks has achieved significant success; however, there are still some problems, such as incomplete dehazing, color deviation, and loss of detailed information. To address these issues, in this study, we propose a multi-scale dehazing network with dark channel priors (MSDN-DCP). First, we introduce a feature extraction module (FEM), which effectively enhances the ability of feature extraction and correlation through a two-branch residual structure. Second, a feature fusion module (FFM) is devised to combine multi-scale features adaptively at different stages. Finally, we propose a dark channel refinement module (DCRM) that implements the dark channel prior theory to guide the network in learning the features of the hazy region, ultimately refining the feature map that the network extracted. We conduct experiments using the Haze4K dataset, and the achieved results include a peak signal-to-noise ratio of 29.57 dB and a structural similarity of 98.1%. The experimental results show that the MSDN-DCP can achieve superior dehazing compared to other algorithms in terms of objective metrics and visual perception.
Radiation Source Localization Using a Model-Based Approach
Authors: Molnár András , Kiss Daniel , Domozi Zsolt
Published: June 2023

The procedure is practically an optimization method, during which it is assumed that the gamma dose values detected at different points above the area come from the background radiation and from a single source found in the area. Accordingly, the procedure searches within the area for a geographical coordinate for which the distance law for the spatial propagation of radiation will be true. In order to validate the procedure, we performed measurements in a test area in such a way that all parameters of the source, including its location, were well defined. However, these data were not taken into account during the processing, i.e., the search procedure did not have these data. We can estimate the radiation position without a positional parameter. The exact coordinate and the intensity of the radiating sample were only used when checking the results. We have also applied the method to the raw data of our experiments carried out in the past if we used one source for them. The results confirmed our assumptions. The method is suitable for determining the starting parameters of more complex processes that can even detect multiple sources, but assuming one source, it has proven to be a reliable analytical method on its own.
High-Speed Rail Tunnel Panoramic Inspection Image Recognition Technology Based on Improved YOLOv5
Authors: Duan Yixin , Qiu Su , Jin Weiqi , Lu Taoran , Li Xingsheng
Published: June 2023

In order to meet the fast and accurate automatic detection requirements of equipment maintenance in railway tunnels in the era of high-speed railways, as well as adapting to the high dynamic, low-illumination imaging environment formed by strong light at the tunnel exit, we propose an automatic inspection solution based on panoramic imaging and object recognition with deep learning. We installed a hyperboloid catadioptric panoramic imaging system on an inspection vehicle to obtain a large field of view as well as to shield the high dynamic phenomena at the tunnel exit, and proposed a YOLOv5-CCFE object detection model based on railway equipment recognition. The experimental results show that the mAP@0.5 value of the YOLOv5-CCFE model reaches 98.6%, and mAP@0.5:0.95 reaches 68.9%. The FPS value is 158, which can meet the automatic inspection requirements of railway tunnel equipment along the line and has high practical application value.
How Do Self-Service Kiosks Improve COVID-19 Pandemic Resilience in the Restaurant Industry?
Authors: Kim Jin-Kyu , Yang Jae-Jang , Lee Yong-Ki
Published: June 2023

As many customers stopped dining out during COVID-19, most restaurants suffered financially. Even after the pandemic, some customers remain wary of being in a crowded place and show resistance to eating out. Restaurants faced with customer resistance and a labor shortage started to adopt electronic devices to minimize human contact and were recognized as having safety protocols in place. Kiosks have gained popularity in the restaurant industry as they can help reduce interpersonal contact, save labor costs, streamline the ordering process, and increase customer satisfaction and loyalty. This study finds that self-service technologies (e.g., kiosks) can be an effective tool for restaurants to utilize in dealing with COVID-wary customers and to remain resilient. This study not only examines various kiosk attributes and their effect on the customers’ experience but also links them to potential revenue growth. By examining a comprehensive set of kiosk attributes, the objective of this study is to understand the role of kiosk attributes in creating a memorable experience for customers based on the concept of the experience economy. The data were collected from 408 restaurant patrons in South Korea who had used self-service technologies. Three analyses were performed using partial least squares structural equation modeling (PLS-SEM), multigroup analysis (MGA), and importance–performance map analysis (IPMA) with SmartPLS 4. The findings are as follows: for male customers, assurance, customization, enjoyment, design, and functionality are considered important aspects of their experience. For female customers, design, enjoyment, and security are important factors in their experience. The finding suggests that males and females consider different attributes in evaluating the technology experience. Additionally, this study finds that a memorable experience with technology affects customers’ intention to revisit the restaurant, playing a mediating role between technology attributes and revisit intention. Lastly, this study finds distinct differences between males and females in their assessment of customization and design. The gender-based differences suggest that men and women assess kiosk technologies differently. Future research may be needed to further investigate the underlying causes of the differences.
Manufacturing in the Age of Human-Centric and Sustainable Industry 5.0: Application to Holonic, Flexible, Reconfigurable and Smart Manufacturing Systems
Authors: Turner Chris , Oyekan John
Published: June 2023

This paper provides a classification of manufacturing types in terms of new technological tools provided in the Industry 5.0 framework. The manufacturing types agile, holonic, flexible and reconfigurable benefit from and are potentially changed by Industry 4.0 technologies and the human-centric focus of Industry 5.0. Furthermore, the use of Lifecycle Analysis (LCA) provides a holistic method for estimating the true value of emissions emitted during the carrying out of manufacturing decisions. As a result, LCA may be used as a central guiding framework, in addition to the use of Circular Economy metrics, for decisions in manufacturing whose results could be presented to humans as part of a scenario-generation system using visualisations within a Digital Twin environment. This enables a decision maker to make informed decisions regarding current and future production needs. Regardless of the size of production facility, this integrated approach is perhaps the most significant gap in research identified by this survey of manufacturing types and systems when viewed through the lens of Industry 5.0. This paper makes the contribution of providing an assessment of the major manufacturing types in the context of Industry 5.0, highlighting the gaps in the current research and providing a sustainable and human-centric agenda supported by LCA use with modern production methodologies.
Estimation of Population Parameters of Glossogobius giuris in the Rabnabad Channel, Southern Bangladesh: Implications for Sustainable Management
Authors: Ahamed Ferdous , Rakib Mohaiminul Haque , Roy Dipto , Akter Hamida , Ahmed Zoarder Faruque
Published: June 2023

The tank goby Glossogobius giuris is a commercially important dominant fish species in the Rabnabad Channel in southern Bangladesh. However, information on the population parameters of this species is not available to support its sustainable management. Therefore, the present study was undertaken to estimate the population parameters to understand both the current status and yield, and to suggest sustainable management measures for this species, using monthly samples collected from September 2021 to August 2022. Our results showed that the size of this species at first sexual maturity was 8.5 cm in total length (TL). The gonadosomatic index indicated a prolonged spawning season, with three peaks in January–February (minor peak), April–May (minor peak), and August–November (major peak). Recruitment occurred at ~8.2 cm TL for an extended period of the year with three pulses in March (major pulse), May–June (minor pulse), and December (minor pulse). The von Bertalanffy growth parameters were TL∞ = 25.0 cm and K = 1.10 year−1. The growth performance index and longevity were 2.84 and 2.7 years, respectively. The estimated fishing, natural, and total mortalities were 0.42, 2.00, and 2.42 year−1, respectively. Therefore, the exploitation rate was 0.17, and the maximum sustainable yield was 0.37, indicating that the stock of G. giuris was not subjected to overexploitation. Hence, management intervention is not needed at this moment. Rather, a substantial amount of fishing pressure could be increased to obtain the maximum benefit.
Analysis of Optimal Buffer Distance for Linear Hazard Factors in Landslide Susceptibility Prediction
Authors: Fang Lu , Wang Qian , Yue Jianping , Xing Yin
Published: June 2023

A linear hazard-causing factor is the environmental element of landslide susceptibility prediction, and the setting of buffer distance of a linear hazard-causing factor has an important influence on the accuracy of landslide susceptibility prediction based on machine learning algorithms. A geographic information system (GIS) has generally been accepted in the correlation analysis between linear hazard-causing factors and landslides; the most common are statistical models based on buffer zone analysis and superposition analysis for linear causative factor distances and landslide counts. However, there is a problem in the process of model building: the buffer distance that is used to build the statistical model and its statistical results can appropriately reflect the correlation between the linear disaster-causing factors and landslides. To solve this problem, a statistical model of landslide density and distance of linear disaster-causing factors under different single-loop buffer distances was established based on Pearson’s method with 12 environmental factors, such as elevation, topographic relief, and distance from the water system and road, in Ruijin City, Jiangxi Province to obtain the most relevant single-loop buffer distance linear disaster-causing factor combinations; random forest (RF) machine learning models were then used to predict landslide susceptibility. Finally, the Kappa coefficient and the distribution characteristics of the susceptibility index were used to investigate the modeling laws. The analysis results indicate that the prediction accuracy of the most correlated single-loop buffer distance combination reaches 96.65%, the error rate of non-landslide points is 4.2%, and the error of landslide points is 11.3%, which is higher than the same single-loop buffer distance combination, confirming the reasonableness of the method of using correlation to obtain the linear disaster-causing factor buffer distance.
ICT as a Support for Value Chain Management in Tourism Destinations: The Case of the City of Cuenca, Ecuador
Authors: Gómez-Ceballos Gliceria , Menoya-Zayas Sandys , Vázquez-Loaiza Juan Pablo
Published: June 2023

The accelerated development of information and communication technologies (ICTs) has had an impact on the way tourism is carried out today. The concept of smart cities and smart destinations is gaining momentum, which also requires smart consumers, i.e., informed, communicated, and connected. In this sense, the application of the value chain concept to tourism implies reconsidering the weight of digital technologies in its structure and, therefore, in the decision-making process of current and potential tourists. The study aims to demonstrate the need and convenience of incorporating technology as an innovative factor in the management process of the tourism value chain and its contribution to the positioning of the destination, taking the city of Cuenca (Ecuador) as a case study. The contributions are, firstly, the ICT adoption as an innovation factor in the value chain. In addition, through a survey of foreign tourists, it was verified that ICTs are a trend as a personalized communication channel, which contributes to valuing the integral tourism offer of the territory.
Does Drop and Pull Transport Have a Chance? The Case of China
Authors: Shao Mingyue , Chen Dongxu , Lu Xiaolong , Liu Xuefei , Yang Zhongzhen
Published: June 2023

To determine why drop and pull transport is developing so slowly in China and whether there is a chance for its further development, this paper formulates a model to compute two threshold values of freight demand, namely the value that makes drop and pull transport profitable and the value at which it is more profitable than traditional truck transport. The results indicates that the most favorable freight market for drop and pull transport has a demand distribution in which most demand is concentrated on a few highway corridors and approximately equal in both directions along each corridor. Based on a comparison between the computed results and the actual demand distribution, it is found that the current Chinese highway freight market is not ideal for fostering drop and pull transport. The results further indicate that specific model markets should be selected for trial drop and pull transport. Since drop and pull transport will only be successful in a market with favorable freight demand distribution, successful attempts in model markets are the key to expanding the use of drop and pull transport.
On Increasing Service Organizations’ Agility: An Artifact-Based Framework to Elicit Improvement Initiatives
Authors: Fulea Mircea , Mocan Bogdan , Dragomir Mihai , Murar Mircea
Published: June 2023

The present research focuses on operational agility in service organizations, which are subject to variability through customers, service providers, suppliers, or unexpected events. As such, their management teams may face challenges in understanding their agility-related assets and success metrics, and furthermore in defining the scope of work for improvement initiatives. Previous research offers quite general insights into agility-related capabilities, practices, obstacles, or (agility-related) information quality evaluation. Yet, management teams need specific practices and techniques in order to improve operational agility capabilities, and thus increase their sustainable performance. We propose a conceptual framework and an artifact-centric algorithm that elicits and prioritizes improvement initiatives by (a) understanding agility-related assets by modelling operational business artifacts, (b) determining agility bottlenecks by identifying quality issues in operational artifacts, and (c) eliciting and prioritizing improvement initiatives to increase artifact quality. The framework application is discussed through a case study in a company operating in the rail freight industry, in which a set of initiatives to improve operational agility capabilities is obtained and prioritized. We conclude that the proposed algorithm is an applicable and relevant tool for management teams in service organizations, in their operational agility improvement endeavors.
Research on Sharing Behavior Strategy of Cultural Heritage Institutions Based on Evolutionary Game Theory
Authors: Cao Ling , Yin Jie
Published: June 2023

With the accelerated digitalization of China’s cultural heritage conservation, cultural heritage data sharing has been gaining more and more attention as an essential link in cultural heritage conservation and transmission. However, there are many problems in cultural heritage sharing, one of which is the low willingness of institutions to share among themselves and the seriousness of information silos. To motivate more cultural heritage institutions to participate in platform sharing and promote long-term, stable data sharing behavior, the dynamic evolution process and the law of institutions’ sharing behavior in cultural heritage sharing platforms must be further studied. This paper constructs an evolutionary game model based on evolutionary game theory to explore the evolutionary paths of finite rational cultural heritage institutions to reach a stable strategy, discusses the relevant factors affecting these evolutionary paths, and conducts simulation experiments with the help of MATLAB. This paper finds that the sharing behavior of institutions in cultural heritage sharing platforms is affected by the initial state over time. The free-riding penalty of non-sharing parties, the coefficient of synergistic benefit, the data sharing volume, and the proportion of data complementarity have positive effects on the sharing behavior of cultural heritage institutions; meanwhile, the fixed sharing costs and the loss of gains of sharing parties have an adverse impact on the sharing behavior of cultural heritage institutions. The findings of this paper are essential for solving the cultural heritage sharing dilemma, improving the competitiveness of cultural heritage institutions, and promoting the sustainable development of cultural heritage sharing platforms, which can help promote the development of cultural heritage and help the implementation of cultural digitalization strategies.
The Role and Development Trend of Third-Party Mediation in Environmental Disputes
Authors: He Tao , Liu Lulu , Gu Manyi
Published: June 2023

Environmental issues such as industrial pollution, excessive packaging, light pollution, and rubbish pollution in households are all growing at an alarming rate with the rapid expansion of the economy. It is necessary for government departments and the judiciary to work together to resolve issues that are brought on by the environment. There has been a progressive development of a variety of mechanisms for the resolution of environmental conflicts; nevertheless, these mechanisms are still unable to fulfill all of the requirements that the public has for the resolution of environmental disputes, and a significant percentage of disputes cannot be resolved on time. The Chinese government has investigated alternative dispute resolution (ADR), established professional mediation institutions and social organizations as neutral third parties to intervene in environmental disputes, and provided reasonable solutions based on local policies and specific disputes through full understanding of issues. As a result, the Chinese government has achieved remarkable results. This article examines the pros and cons of using third-party mediation in the process of resolving environmental disputes and makes comparisons between the traditional method of resolving environmental disputes and third-party mediation as a method for resolving environmental disputes. The article uses statistical correlation methods to analyze the role of third-party mediation in natural environmental pollution control issues in various countries. Based on the analysis results, suggestions are put forward to improve the third-party mediation system of environmental disputes in our country. Experimental results show that the mediation system can promote information sharing, strengthen social cooperation and encourage all parties to take more coordinated actions in environmental protection, thereby promoting sustainable development and the realization of an ecological balance.
How Does Systemic Design Facilitate the Sustainability Transition of Rural Communities? A Comparative Case Study between China and Italy
Authors: Zang Dan , Xie Yumei , Barbero Silvia , Pereno Amina
Published: June 2023

Rural sustainability has emerged as a ‘wicked problem’ for practitioners within and outside design. Many efforts that adopted a systematic approach since the 1980s paved the road for addressing such a systemic problem. Moreover, stakeholders from the systemic design field have made significant strides by developing a systemic approach to rural systems since 2012 and implementing numerous localised design practices globally. Despite these efforts, the essence of systemic design for sustainable rural development remains relatively unclear because of its infancy. Therefore, this study tries to answer the question of “how does systemic design facilitate the sustainability transition of rural communities” by conducting field visits to two typical systemic design projects: Future Village Lab in rural China (Tieniu Village) and Systemic Design Lab in Italy (Ostana). Thereafter, drawing on insights from organisational management studies, this study pioneers a novel theoretical framework called ‘Situation-Cognition-Action’ to compare and analyse these two cases. The results highlight the role of systemic design in contributing to rural sustainability by enhancing the understanding of complex situations, fostering cognitive capacity, and creating a solution ecosystem for collaborative action. Finally, it elucidates how systemic design addresses three crucial trade-offs and effectively promotes rural sustainability in various rural contexts.
Unveiling the Predictive Effect of Students’ Perceived EFL Teacher Support on Academic Achievement: The Mediating Role of Academic Buoyancy
Authors: Li Xiaoxue , Duan Siyu , Liu Honggang
Published: June 2023

Recent studies have shown the crucial role of students’ perceived English as a foreign language (EFL) teacher support in their academic learning within their immediate social environments. Nevertheless, little is known about the intricate links among dimensions of perceived EFL teacher support and academic achievement as well as the mediating function of personalities (e.g., academic buoyancy). To close these gaps, in the current study, a quantitative approach was used to examine the effects of particular dimensions of students’ perceived EFL teacher support (i.e., academic, emotional, and instrumental support) on educational outcomes. The mediating role of academic buoyancy was also investigated. A total of 402 Chinese senior high school students who learn English as a foreign language were invited to complete the questionnaires to evaluate their academic buoyancy and three types of perceived EFL teacher support. The results of structural equation modelling indicate that none of these three dimensions of students’ perceived EFL teacher support could directly predict academic achievement. Students’ perceived EFL teacher support could only indirectly affect educational outcomes via the complete mediation of academic buoyancy. This study provides teachers with tips on fostering students’ personality traits and aiding their academic progress.
Investigating the Impact of Environmental Graphics on Local Culture in Sustainable Rural Cultural Tourism Spaces
Authors: Liu Xiaodong , Zhang Jingchun , Zhou Zhicheng , Feng Zhiyu
Published: June 2023

It is paramount that local cultural sustainability be preserved as China implements its rural revitalization strategy, and the integration and transformation of rural cultural tourism spaces based on this foundation is unprecedented. However, rural cultural tourism spaces face many challenges at present, including a lack of cultural appeal and homogenized spatial expression methods. Environmental graphics, a concept widely utilized in urban branding systems, serve as a novel spatial text that combines both material and immaterial aspects within the extension of brand design systems. Creatively intervening in the shaping of rural cultural tourism spaces, environmental graphics enhance the spatial experience of rural tourism. In this study, we introduced a model that uses an experiential design approach to explore and transform local culture into environmental graphics. Through three application case studies of cultural tourism spaces with diverse cultural backgrounds, this study illustrates how environmental graphics can revitalize the cultural and historical allure of rural heritage by transforming local elements through contemporary language. Moreover, the study aims to further validate its findings through practical applications in future research to convert experiential design into cultural sustainability.
Service Mechanism for the Cloud–Edge Collaboration System Considering Quality of Experience in the Digital Economy Era: An Evolutionary Game Approach
Authors: Li Shiyong , Xu Min , Liu Huan , Sun Wei
Published: June 2023

In the digital economy era, cloud–edge collaboration technology provides the necessary technical support for the digital transformation of enterprises, which can improve the quality of services (QoS), and it attracts extensive attention from scholars and entrepreneurs from all fields. Under the bounded-rationality hypothesis, this paper investigates the service mechanism for the cloud–edge collaboration system considering the quality of experience (QoE) and presents a dynamic evolutionary game model between cloud service providers and edge operators by applying the evolutionary game theory. Then, this paper analyzes the equilibrium and stability conditions for the decision-making of both parties involved to guarantee the QoE reaches the ideal state. In addition, we investigate the factors that influence the stable cooperation between the two evolutionary stable strategies and validate the theoretical analytical results with numerical simulations. The research results show that the final evolution of the cloud–edge collaboration system depends on the benefits and costs of the game matrix between the two parties and the initial state values of the system. Under a specific condition, the cloud–edge collaboration system can eventually be driven to be an ideal state by reducing the collaboration cost and improving the collaboration benefit. The more both parties focus on the QoE, the more conducive it will be for the formation of a cloud–edge collaboration, thus effectively promoting long-term stability and better serving enterprises’ digital transformation.
Machine Learning with Alpha Toxin Phenotype to Predict Clinical Outcome in Patients with Staphylococcus aureus Bloodstream Infection
Authors: Beadell Brent , Nehra Surya , Gusenov Elizabeth , Huse Holly , Wong-Beringer Annie
Published: June 2023

Staphylococcus aureus bloodstream (SAB) infection remains a leading cause of sepsis-related mortality. Yet, current treatment does not account for variable virulence traits that mediate host dysregulated immune response, such as SA α-toxin (Hla)-mediated thrombocytopenia. Here, we applied machine learning (ML) to bacterial growth images combined with platelet count data to predict patient outcomes. We profiled Hla phenotypes of SA isolates collected from patients with bacteremia by taking smartphone images of beta-hemolytic growth on sheep blood agar (SBA). Electronic medical records were reviewed to extract relevant laboratory and clinical data. A convolutional neural network was applied to process the plate image data for input along with day 1 patient platelet count to generate ML-based models that predict thrombocytopenia on day 4 and mortality. A total of 229 patients infected with SA strains exhibiting varying zone sizes of beta-hemolysis on SBA were included. A total of 539 images of bacterial growth on SBA were generated as inputs for model development. One-third of patients developed thrombocytopenia at onset, with an overall mortality rate of 18.8%. The models developed from the ML algorithm showed strong performance (AUC 0.92) for predicting thrombocytopenia on day 4 of infection and modest performance (AUC 0.711) for mortality. Our findings support further development and validation of a proof-of-concept ML application in digital microbiology, with a measure of bacterial virulence factor production that carries prognostic significance and can help guide treatment selection.
Pre-Treatment HIV Drug Resistance and Genetic Diversity in Cameroon: Implications for First-Line Regimens
Authors: Fokam Joseph , Chenwi Collins Ambe , Tala Valère , Takou Désiré , Santoro Maria Mercedes , Teto George , Dambaya Beatrice , Anubodem Felix , Semengue Ezechiel Ngoufack Jagni , Beloumou Grace , Djupsa Sandrine , Assomo Edgar , Fokunang Charles , Alteri Claudia , Billong Serge , Bouba Nounouce Pamen , Ajeh Rogers , Colizzi Vittorio , Mbanya Dora , Ceccherini-Silberstein Francesca , Perno Carlo-Federico , Ndjolo Alexis
Published: June 2023

The efficacy of first-line antiretroviral therapy (ART) may be hampered by the presence of HIV drug resistance (HIVDR). We described HIV-1 pre-treatment drug resistance (PDR) patterns, effect of viral clades on PDR, and programmatic implications on first-line regimens in Cameroon. A sentinel surveillance of PDR was conducted from 2014 to 2019. Sequencing of HIV-1 protease and reverse transcriptase was performed, and HIVDR was interpreted using Stanford HIVdb.v.9.4. In total, 379 sequences were obtained from participants (62% female, mean age 36 ± 10 years). The overall PDR rate was 15.0% [95% CI: 11.8–19.0] nationwide, with significant disparity between regions (p = 0.03). NNRTI PDR was highest (12.4%), of which 7.9% had DRMs to EFV/NVP. Two regions had EFV/NVP PDR above the 10% critical threshold, namely the Far North (15%) and East (10.9%). Eighteen viral strains were identified, predominated by CRF02_AG (65.4%), with no influence of genetic diversity PDR occurrence. TDF-3TC-DTG predictive efficacy was superior (98.4%) to TDF-3TC-EFV (92%), p < 0.0001. The overall high rate of PDR in Cameroon, not substantially affected by the wide HIV-1 genetic diversity, underscores the poor efficacy of EFV/NVP-based first-line ART nationwide, with major implications in two regions of the country. This supports the need for a rapid transition to NNRTI-sparing regimens, with TDF-3TC-DTG having optimal efficacy at the programmatic level.
P3 and NIa-Pro of Turnip Mosaic Virus Are Independent Elicitors of Superinfection Exclusion
Authors: Nunna Haritha , Qu Feng , Tatineni Satyanarayana
Published: June 2023

Superinfection exclusion (SIE) is an antagonistic interaction between identical or closely related viruses in host cells. Previous studies by us and others led to the hypothesis that SIE was elicited by one or more proteins encoded in the genomes of primary viruses. Here, we tested this hypothesis using Turnip mosaic virus (TuMV), a member of the genus Potyvirus of the family Potyviridae, with significant economic consequences. To this end, individual TuMV-encoded proteins were transiently expressed in the cells of Nicotiana benthamiana leaves, followed by challenging them with a modified TuMV expressing the green fluorescent protein (TuMV-GFP). Three days after TuMV-GFP delivery, these cells were examined for the replication-dependent expression of GFP. Cells expressing TuMV P1, HC-Pro, 6K1, CI, 6K2, NIa-VPg, NIb, or CP proteins permitted an efficient expression of GFP, suggesting that these proteins failed to block the replication of a superinfecting TuMV-GFP. By contrast, N. benthamiana cells expressing TuMV P3 or NIa-Pro did not express visible GFP fluorescence, suggesting that both of them could elicit potent SIE against TuMV-GFP. The SIE elicitor activity of P3 and NIa-Pro was further confirmed by their heterologous expression from a different potyvirus, potato virus A (PVA). Plants systemically infected with PVA variants expressing TuMV P3 or NIa-Pro blocked subsequent infection by TuMV-GFP. A +1-frameshift mutation in P3 and NIa-Pro cistrons facilitated superinfection by TuMV-GFP, suggesting that the P3 and NIa-Pro proteins, but not the RNA, are involved in SIE activity. Additionally, deletion mutagenesis identified P3 amino acids 3 to 200 of 352 and NIa-Pro amino acids 3 to 40 and 181 to 242 of 242 as essential for SIE elicitation. Collectively, our study demonstrates that TuMV encodes two spatially separated proteins that act independently to exert SIE on superinfecting TuMV. These results lay the foundation for further mechanistic interrogations of SIE in this virus.
Modeling of Sulfur and Iron Dynamics in Enclosed Bay Sediments and Evaluation of the Suppression Effect on Sulfide Release by Iron
Authors: Mochida Fumika , Miyatsuji Takashi , Nakamura Yoshiyuki , Inoue Tetsunori
Published: June 2023

In eutrophic waters, such as Mikawa Bay, Japan, anoxic bottom water develops in summer. This causes H2S release into seawater due to sulfate reduction in the sediment, leading to environmental problems. The addition of Fe to sediments is a method used to improve the sediment environment. However, this method, which was devised from a natural mechanism, has not yet been quantitatively evaluated. In this study, we aim to quantitatively evaluate the suppressive effect of Fe on H2S release. First, we developed a sediment model that focuses on S and Fe. We then attempted to reproduce the observations and experiments on H2S dynamics using the model. Consequently, the proposed model was able to reproduce field S and Fe dynamics in sediments even under anoxic conditions. Additionally, the model could describe the difference in H2S release depending on the amount, type, and time of iron-based additives. Finally, we conducted predictive calculations for one year assuming 637 g/m2 of iron materials, and quantitatively evaluated the effects of adding iron materials to the sediments in terms of S and Fe cycles. We found iron-based additives suppressed H2S release by 14 mmol/m2/d compared to the case without additives.
Bengal Delta, Charland Formation, and Riparian Hazards: Why Is a Flexible Planning Approach Needed for Deltaic Systems?
Authors: Haque C. Emdad , Jakariya Md.
Published: June 2023

A comprehensive understanding of the dynamic characteristics of geomorphological, ecological, and human systems is essential to explaining complex charland (mid-channel island) processes and crafting and implementing policy measures. This work demonstrates that the characteristics and outcomes of riparian hazards are determined by the interactive dynamics between hydrogeology and human conditions, which constitutes a novel contribution to the literature in this research area. We further contend that such dynamic social-ecological systems demand a flexible, adaptive management and planning approach. The present research has three key interdisciplinary objectives: (i) to analyze the salient features and characteristics of the geomorphological and riparian systems of the Bengal Delta; (ii) to analyze the evolutionary discourse of the legal systems concerning eroded (diluvion) and accreted (alluvion) land in Bangladesh; and (iii) to assess the characteristics of the coping and adaptation strategies employed by charland inhabitants. The findings of this research reveal that delta-building processes, which are characterized by dynamic shifts in the river channels, along with the erosion and accretion of charlands have made Bangladesh’s land and water systems very dynamic and unstable. The destabilization of these systems increases the inhabitants’ vulnerability to riparian hazards, which consistently results in the displacement of settlers and, consequently, a serious deterioration in their socioeconomic status. At present, Bangladesh does not have an effective institutional framework and structure for resettlement planning; therefore, the formulation of a comprehensive national resettlement policy with adequate flexibility to adapt to changing scenarios is urgently needed.
Current temperatures limit the potential impact of a commonly traded predatory gastropod
Authors: Dickey James W. E. , Jeschke Jonathan M. , Steffen Gregor T. , Kazanavičiūtė Elžbieta , Brennan Reid S. , Briski Elizabeta
Published: June 2023

The pet trade has facilitated the spread of invasive alien species (IAS) globally, with negative consequences for biodiversity. The prediction of impacts is a major goal for invasion ecologists, and is especially crucial in an industry often lacking knowledge about traded species. We focused on the predatory gastropod Anentome helena, a species originating in south-east Asia and traded around the world, but with taxonomic uncertainty. We first set out to determine where our study organism fell within the A. “helena” species complex, known to comprise at least four cryptic species, before assessing the effect of temperature on the number of prey, the pulmonate snail Physella acuta, killed per predator via functional response experiments at two temperatures. We used 22 °C as a recommended temperature for housing the species in captivity, and 18 °C as a representative summer lake temperature in temperate climates of Europe. We also assessed the role of predator group size (1×, 2×, 3×) on predation (total consumption and average per capita consumption) at the experimental temperatures with fixed densities of prey, as well as the effect of these temperatures on prey activity. Our organisms belonged to a cryptic species originating from Thailand (Anentome sp. A), matching the findings of aquarium trade samples in other continents. In the functional response experiments, we found maximum feeding rate to be significantly reduced at the lower temperature. A similar result ensued from group feeding, with total consumption significantly reduced and the reduction in average per capita consumption approaching significance at the lower temperature. There was no significant effect of group size on the average per capita consumption in the group trial, indicating neutral conspecific interactions. No significant effect of temperature on the activity of the prey species was found, suggesting decreased consumption was mainly driven by predator, rather than prey. These results suggest limited A. helena impacts in the short-term, but increasing temperatures with climate change may facilitate greater consequences from releases. We suggest future studies assess other potential predatory impacts and survival across relevant abiotic conditions, and encourage the use of similar methods to assess the impacts of other commonly traded species.
International Conference on Aquatic Invasive Species – ICAIS returned to Europe after 15 years
Authors: Verreycken Hugo , Collas Frank P. L. , Coughlan Neil E.
Published: June 2023

The 22nd International Conference on Aquatic Invasive Species (ICAIS) was held as a hybrid event in Oostende, Belgium from 18–22 April 2022. The conference addressed the theme of “Global Climate Change Amplifies Aquatic Invasive Species Impacts” and aimed to expand knowledge on the latest science and policy, inspire cooperation and collaboration on research and management projects at a global scale. Seven renowned international scientists provided keynote presentations on perspectives of climate change within their respective areas of expertise. This special issue of Aquatic Invasions presents nine academic papers addressing a range of aquatic invasive species issues including predation, life history dynamics, ecosystem impacts, and physiological tolerances. The papers highlight the need for regional, national, and international cooperation, collaboration on research and management projects, and targeted, specific, and actionable outreach to combat the growing threat posed by aquatic invasive species.
Religiões antigas: a vida e os ensinamentos dos essênios.
Authors: De Sousa Carvalho Nilmar
Published: June 2023

Este artigo tem como objetivo apresentar a origem, onde viveram e quais os ensinamentos da comunidade religiosa dos essênios, a partir de uma análise histórica, social e religiosa de fontes antigas que foram escritas por historiadores do primeiro século da era comum; das novidades presentes nos manuscritos do Mar Morto; das interpretações contidas nos textos publicados ao longo dos séculos, sobretudo, pelos pesquisadores contemporâneos Gabriele Boccaccini e García Martínez. Para isso, serão analisados os textos de Flávio Josefo, Fílon de Alexandria e Plínio acerca de suas abordagens sobre os essênios, quais as principais hipóteses sobre a sua origem, o lugar onde foram encontrados vestígios arqueológicos, quais as principais comunidades, as suas regras de convivência, a maneira como lidavam com os bens materiais e a concepção que tinham do casamento e do celibato.