bluuebunny/crossref_metadata_2025 huggingface dataset:
Adaptive Optimization Design of Building Energy System for Smart Elderly Care Community Based on Deep Deterministic Policy Gradient
Authors: Liu Chunmei , Xue Zhe
Published: July 2023

In smart elderly care communities, optimizing the design of building energy systems is crucial for improving the quality of life and health of the elderly. This study pioneers an innovative adaptive optimization design methodology for building energy systems by harnessing the cutting-edge capabilities of deep reinforcement learning. This avant-garde method initially involves modeling a myriad of energy equipment embedded within the energy ecosystem of smart elderly care community buildings, thereby extracting their energy computation formulae. In a groundbreaking progression, this study ingeniously employs the actor–critic (AC) algorithm to refine the deep deterministic policy gradient (DDPG) algorithm. The enhanced DDPG algorithm is then adeptly wielded to perform adaptive optimization of the operational states within the energy system of a smart retirement community building, signifying a trailblazing approach in this realm. Simulation experiments indicate that the proposed method has better stability and convergence compared to traditional deep Q-learning algorithms. When the environmental interaction coefficient and learning ratio is 4, the improved DDPG algorithm under the AC framework can converge after 60 iterations. The stable reward value in the convergence state is −996. When the scheduling cycle of the energy system is between 0:00 and 8:00, the photovoltaic output of the system optimized by the DDPG algorithm is 0. The wind power output fluctuates within 50 kW. This study realizes efficient operation, energy saving, and emission reduction in building energy systems in smart elderly care communities and provides new ideas and methods for research in this field. It also provides an important reference for the design and operation of building energy systems in smart elderly care communities.
IOTA Data Preservation Implementation for Industrial Automation and Control Systems
Authors: Lin Iuon-Chang , Tseng Pai-Ching , Chang Yu-Sung , Weng Tzu-Ching
Published: July 2023

Blockchain 3.0, an advanced iteration of blockchain technology, has emerged with diverse applications encompassing various sectors such as identity authentication, logistics, medical care, and Industry 4.0/5.0. Notably, the integration of blockchain with industrial automation and control systems (IACS) holds immense potential in this evolving landscape. As industrial automation and control systems gain popularity alongside the widespread adoption of 5G networks, Internet of Things (IoT) devices are transforming into integral nodes within the blockchain network. This facilitates decentralized communication and verification, paving the way for a fully decentralized network. This paper focuses on showcasing the implementation and execution results of data preservation from industrial automation and control systems to IOTA, a prominent distributed ledger technology. The findings demonstrate the practical application of IOTA in securely preserving data within the context of industrial automation and control systems. The presented numerical results validate the effectiveness and feasibility of leveraging IOTA for seamless data preservation, ensuring data integrity, confidentiality, and transparency. By adopting IOTA’s innovative approach based on Directed Acyclic Graph (DAG), the paper contributes to the advancement of blockchain technology in the domain of Industry 4.0/5.0.
The Spatio-Temporal Changes of Small Lakes of the Qilian Mountains from 1987 to 2020 and Their Driving Mechanisms
Authors: Li Chao , Zhang Shiqiang , Chen Rensheng , Zhang Dahong , Zhou Gang , Li Wen , Rao Tianxing
Published: July 2023

Small lakes (areas ranging from 0.01 km2 to 1 km2) are highly sensitive to climate change and human activities. However, few studies have investigated the long-term intra-annual trends in the number and area of small lakes and their driving mechanisms in the Qinghai–Tibet Plateau (QTP). As a significant water tower in northwest China, the Qilian Mountains region (QMR) in the QTP is essential for sustaining regional industrial and agricultural production, biodiversity, and human well-being. We conducted an analysis of the dynamics of small lakes in the QMR region. In this study, we employed Geodetector and examined nine factors to investigate the driving mechanisms behind the long-term variations in the small lake water bodies (SLWBs). We specifically focused on understanding the effects of single-factor and two-factor interactions. The results indicate that the number and area of small lakes had a fluctuating trend from 1987 to 2020. Initially, there was a decrease followed by an increase, which was generally consistent with trends in the large lakes on the QTP. All basins had far more expanding than shrinking lakes. The area of seasonal SLWBs in each basin was increasing more rapidly than permanent SLWBs. The distribution and trends in the area and number of small lakes varied widely across elevation zones. Runoff, snow depth, and temperature contributed the most to SLWB changes. Human activities and wind speed contributed the least. However, the main drivers varied across basins. The impact of two-factor interactions on SLWB changes in basins was greater than that of single factors. Our results provide useful information for planning and managing water resources and studies of small lakes.
Spatial-Aware Transformer (SAT): Enhancing Global Modeling in Transformer Segmentation for Remote Sensing Images
Authors: Wang Duolin , Chen Yadang , Naz Bushra , Sun Le , Li Baozhu
Published: July 2023

In this research, we present the Spatial-Aware Transformer (SAT), an enhanced implementation of the Swin Transformer module, purposed to augment the global modeling capabilities of existing transformer segmentation mechanisms within remote sensing. The current landscape of transformer segmentation techniques is encumbered by an inability to effectively model global dependencies, a deficiency that is especially pronounced in the context of occluded objects. Our innovative solution embeds spatial information into the Swin Transformer block, facilitating the creation of pixel-level correlations, and thereby significantly elevating the feature representation potency for occluded subjects. We have incorporated a boundary-aware module into our decoder to mitigate the commonly encountered shortcoming of inaccurate boundary segmentation. This component serves as an innovative refinement instrument, fortifying the precision of boundary demarcation. After these strategic enhancements, the Spatial-Aware Transformer achieved state-of-the-art performance benchmarks on the Potsdam, Vaihingen, and Aerial datasets, demonstrating its superior capabilities in recognizing occluded objects and distinguishing unique features, even under challenging conditions. This investigation constitutes a significant advancement toward optimizing transformer segmentation algorithms in remote sensing, opening a wealth of opportunities for future research and development.
Analysis of a Relative Offset between the North American and the Global Vertical Datum in Gravity Potential Space
Authors: Guo Dongmei , Xue Zhixin
Published: July 2023

The accurate estimation of the zero-height geopotential level in a local vertical datum (LVD) is critical for linking traditional height reference systems to a global height system. In this paper, we investigate the theoretical and practical challenges involved in determining the offset between the North American vertical datum (NAVD) and the global vertical datum (GVD). Drawing on the classical theory of the vertical system in physical geodesy, we define the vertical datum offset and derive rigorous formulas for its calculation. We examine various factors that affect the determination of the offset, including the global gravitational models (GGMs), geodetic reference system, tide system, tilt error, and omission error. Using terrestrial gravity data and gravity anomalies from multiple GGMs in conjunction with Global Navigation Satellite System (GNSS) and orthometric heights, we estimate the vertical offset between the NAVD and GVD. Our results indicate that the geopotential difference approach and the geodetic boundary value problem (GBVP) approach yield consistent results. When the normal gravity geopotential of the geodetic reference system is selected as the gravity geopotential of the global height datum, the NAVD is approximately 0.04 m higher than the GVD relative to the GRS80 ellipsoid, and 0.97 cm higher than the GVD relative to the WGS84 ellipsoid. When the Gauss–Listing geopotential value is chosen as the gravity geopotential of the global height datum, the NAVD is roughly 1.45 m higher than the GVD relative to the GRS80 ellipsoid, and approximately 0.52 m higher than the GVD relative to the WGS84 ellipsoid.
Flexible Learning Environments for a Sustainable Lifelong Learning Process for Teachers in the School Context
Authors: Sangiuliano Intra Francesca , Nasti Carla , Massaro Rita , Perretta Armando Junior , Di Girolamo Amalia , Brighi Antonella , Biroli Pietro
Published: July 2023

The flexibility of digital learning environments allows for personalized content delivery tailored to individual teachers’ needs, fostering active and engaged learning. The opportunities offered by these digital technologies can help teachers adopt a lifelong learning attitude, which has become necessary to maintaining high educational standards in line with international guidelines and policy. However, teachers often struggle to leverage these digital technologies and integrate them in their daily activities. To overcome this problem, we developed a custom-built webinar training course focused on enhancing distance learning teaching in a flexible environment. We tested this training course on a group of 197 primary school teachers and examine the relationship between learning goal orientation, motivation, and intention to transfer and how they related to teachers’ personality traits. We found that our webinar training course is easily implementable and valued by teachers, who highlight the importance of allowing the choice between different training levels. The data analysis indicates that intention to transfer is predicted by learning goal orientation and motivation. In conclusion, the study emphasizes the importance of flexible learning environments and tailored training programs that meet teachers’ needs and interests. From a sustainable perspective, such approaches foster teachers’ lifelong learning, enhance their professional development, nurture a growth mindset, and facilitate adaptability to change.
Assessment of Socioeconomic Resilience to Pandemic Disasters in Island Tourist Destinations
Authors: Hafsi Adel , Aguilar-Becerra César Daniel , Frausto-Martínez Oscar , Rivas-Tapia Alejandra Sarhai
Published: July 2023

The pandemic has led to a sharp contraction in economic activity with diverse businesses shutting down or reducing their operations. The COVID-19 pandemic is recognized as a challenge in the travel and tourism services industry. Therefore, this paper aims to evaluate the socioeconomic resilience of the island tourist destination of Cozumel and to determine its ability to manage a pandemic by identifying its strengths and weaknesses. This study was based on the Indicators of Socioeconomic Resilience in Island Destinations (ISRID) matrix adapted to the study territory to achieve this aim. As a result, 63 out of 890 research articles were reviewed, from which 1222 indicators were collected; nevertheless, only thirty-three indicators were selected. The assessment was also structured on a matrix of double data collection before and after the pandemic to analyze the evolution of the components essential to strengthening socioeconomic resilience. In this way, this study revealed that the island of Cozumel does not have good risk management in the presence of a pandemic phenomenon. Thus, the principal axes to reinforce abilities were implementing a comprehensive plan with multidisciplinary approaches containing themes like social participation, access to information, health, economic resources, gender inequalities, marginalization, environmental impacts, and endemic resources. Finally, the matrix developed can aid decision-makers in generating corresponding actions when designing, implementing, and evaluating socioeconomic resilience capacities to cope with a pandemic disaster in island tourist destinations.
Coordination Mechanism of Revenue Sharing Contracts in Port Supply Chains: A Case Study of China’s Nantong Port
Authors: Lu Yongming , Tan Yuning
Published: July 2023

Considering the port function’s importance, the supply chain’s overall and individual revenues, and the port supply chain’s uniqueness, a game model for a two-stage port supply chain composed of port service providers and port enterprises was developed. Using revenue sharing contracts (RSCs) as a coordination mechanism, game equilibriums were investigated under two conditions: price-sensitive or price-insensitive port logistics service demand. The results suggested that RSCs can achieve Pareto improvement in both cases, thereby coordinating port supply chain revenues. Led by the port logistics service provider and port enterprise, the coordination mechanisms based on RSCs of port supply chain were discussed using logistics service capacity as the coordination link. Despite differing decision orders, the RSC model can coordinate the port’s supply chain with its service provider, while the port and logistics service provider determine the retention ratio. This paper also proposed coordination measures for the Nantong Port, one of the most important ports in China, to maximize the logistics capacity of iron ore supply chain and enhance the port logistics’ value-added services.
Evaluating the Enablers of Green Entrepreneurship in Circular Economy: Organizational Enablers in Focus
Authors: Soleimani Maryam , Mollaei Elahe , Beinabaj Mojgan Hamidi , Salamzadeh Aidin
Published: July 2023

In recent decades, green entrepreneurship has been at the center of attention as an effective strategy to maintain sustainability and create a competitive advantage for organizations in a circular economy. However, the successful implementation of this strategy requires organizations to have internal enablers. This study endeavored to identify and evaluate organizational enablers for green entrepreneurship in manufacturing Small and Medium Enterprises (SMEs) in Iran. Identifying organizational enablers can help SMEs in facilitating the conditions for adopting green entrepreneurship. To these ends, organizational enablers were extracted by reviewing the literature and then, using the viewpoints of 17 active experts in different industries in SMEs, they were classified. In the next step, the “Best Worst Method” was employed to prioritize the identified enablers (5 factors) and sub-enablers (20 factors). The contextual hierarchical relationships between these factors were identified through the “Interpretive Structural Modeling” method. Using the Matrix of Cross-Impact Multiplications Applied to Classification (MICMAC) analysis, the driving and dependence powers of organizational enablers were computed and the enablers were clustered. Based on the results, among the five enablers, three including total quality management, circular supply chain management, and corporate social responsibility were the most important from the point of view of the experts. Moreover, among the sub-enablers, strategic planning, green purchasing, and corporate social responsibility motivation were more important than other sub-enablers. The results of ISM analysis provided a seven-level hierarchical model and the relationships between them. The results of the MICMAC analysis led to the clustering of 20 organizational enablers in three main clusters: driving (nine factors), linkage (four factors), and dependent (seven factors). The results of this study provide practical suggestions for active senior managers to implement green entrepreneurship in SMEs.
Optimized Design of Skylight Arrangement to Enhance the Uniformity of Indoor Sunlight Illumination
Authors: Jia Bowen , Li Wenjie , Chen Guanyu , Sun Wenbin , Wang Bowen , Xu Ning
Published: July 2023

The use of skylights in buildings introduces natural light into the interior space, thereby reducing the reliance on artificial lighting and aligning with the principles of low carbon and environmental sustainability. To ensure optimal indoor lighting quality, it is essential to optimize the arrangement of skylights to strike a balance between high average illumination and uniformity of illumination. Recent initiatives by the Chinese government have emphasized the construction and renovation of numerous gymnasiums. In this research, a novel approach based on optimized algorithms was employed to design skylights and improve the uniformity of indoor illuminance. Simulation results demonstrated that the skylight arrangements derived from the optimization algorithms exhibited significantly higher levels of illumination uniformity, while maintaining comparable average illumination and skylight areas, when compared to conventional designs. Additionally, the study employed genetic algorithms to optimize the skylight arrangement for a specific gymnasium, resulting in a remarkable 32% increase in illumination uniformity. The study also accounted for obstacles and seating in the skylight design, and the genetic algorithm generated desirable skylight arrangements with respective increases of 32% and 21% in illumination uniformity for scenarios involving obstacles and seating. Overall, this study underscores the potential of optimized algorithms in the design of skylights for green buildings, offering valuable insights for future research endeavors in this field.
A New Insight for Daily Solar Radiation Prediction by Meteorological Data Using an Advanced Artificial Intelligence Algorithm: Deep Extreme Learning Machine Integrated with Variational Mode Decomposition Technique
Authors: Alizamir Meysam , Othman Ahmed Kaywan , Shiri Jalal , Fakheri Fard Ahmad , Kim Sungwon , Heddam Salim , Kisi Ozgur
Published: July 2023

Reliable and precise estimation of solar energy as one of the green, clean, renewable and inexhaustible types of energies can play a vital role in energy management, especially in developing countries. Also, solar energy has less impact on the earth’s atmosphere and environment and can help to lessen the negative effects of climate change by lowering the level of emissions of greenhouse gas. This study developed thirteen different artificial intelligence models, including multivariate adaptive regression splines (MARS), extreme learning machine (ELM), Kernel extreme learning machine (KELM), online sequential extreme learning machine (OSELM), optimally pruned extreme learning machine (OPELM), outlier robust extreme learning machine (ORELM), deep extreme learning machine (DELM), and their versions combined with variational mode decomposition (VMD) as integrated models (VMD-DELM, VMD-ORELM, VMD-OPELM, VMD-OSELM, VMD-KELM, and VMD-ELM), for solar radiation estimation in Kurdistan region, Iraq. The daily meteorological data from 2017 to 2018 were used to implement suggested artificial models at Darbandikhan and Dukan stations, Iraq. The input parameters included daily data for maximum temperature (MAXTEMP), minimum temperature (MINTEMP), maximum relative humidity (MAXRH), minimum relative humidity (MINRH), sunshine duration (SUNDUR), wind speed (WINSPD), evaporation (EVAP), and cloud cover (CLOUDCOV). The results show that the proposed VMD-DELM algorithm considerably enhanced the simulation accuracy of standalone models’ daily solar radiation prediction, with average improvement in terms of RMSE of 13.3%, 20.36%, 25.1%, 27.1%, 34.17%, 38.64%, and 48.25% for Darbandikhan station and 5.22%, 10.01%, 10.26%, 21.01%, 29.7%, 35.8%, and 40.33% for Dukan station, respectively. The outcomes of this study reveal that the VMD-DELM two-stage model performed superiorly to the other approaches in predicting daily solar radiation by considering climatic predictors at both stations.
Consumer Preferences for Olive Oil in Spain: A Best-Worst Scaling Approach
Authors: Pérez y Pérez Luis , Gracia Azucena
Published: July 2023

This paper studies the preferences of consumers for olive oil in Spain, which is the largest producer and consumer of olive oil worldwide. Olive oil is a prominent, sustainable, healthy, and distinctive product associated with the Mediterranean diet. Based on a survey conducted among a sample of 402 consumers, we apply the Best Worst Scaling method to measure the importance of some attributes that influence consumer preferences for olive oil. Our results show that consumers rate price, geographical origin, protected designation of origin label, and olive variety, as important product attributes. Conversely, attributes such as organic label certification, size, and packaging material are considered less important. As the perceived importance of olive oil attributes differs across individuals, we further estimate a five-class solution and describe each class in terms of knowledge and consumption of Extra Virgin Olive Oil (EVOO) and the socio-demographic characteristics of the respondents. Finally, we discuss the implications of studying consumer preferences for olive oil and provide managerial insights.
Risk Prediction Method for Renewable Energy Investments Abroad Based on Cloud-DBN
Authors: Zai Wenjiao , He Yuying , Wang Huazhang
Published: July 2023

There are many specific risks in renewable energy (RE) investment projects, and the incidences of these risk factors are fuzzy and uncertain. In different stages of a project’s life cycle, the main risk factors frequently change. Therefore, this paper constructed a cloud dynamic Bayesian network model (Cloud-DBN) for RE operation processes; it uses the DBN graph theory to show the generation mechanism and evolution process of RE outbound investment risks, to make the risk prediction structure clear. Based on the statistical data of observation nodes, the probability of risk occurrence is deduced to ensure the scientific nature of the reasoning process. The probability of risk being low, medium, or high is given, which is highly consistent with the uncertainty and randomness of risk. An improved formula for quantitative data normalization is proposed, and an improved calculation method for joint conditional probability based on weight and contribution probability is proposed, which reduces the workload of determining numerous joint conditional probabilities and improves the practicability of the BN network with multiple parent nodes. According to the 20-year historical statistical data of observation nodes, the GM(1,1) algorithm was used to extract the transfer characteristics of observation nodes, construct the DBN network, and deduce the annual risk probability of each risk node during the operation period of the RE project. The method was applied to the wind power project invested by China in Pakistan, and the effectiveness of the method was tested. The method in this paper provides a basis for investment decisions in the RE project planning period and provides targeted risk reduction measures for the project’s operation period.
Post-Radiation Angiosarcoma (PRA) of the Small Bowel: Report of a Case and Review of the Literature
Authors: La Gatta Marco , Zorzetti Noemi , Baccaro Cinzia , Manuela Cuoghi , Fornelli Adele , Cennamo Vincenzo , Navarra Giuseppe Giovanni
Published: July 2023

Angiosarcoma is a rare and aggressive neoplasia of endothelial cells which represents only 2% of all soft-tissue tumors and frequently occurs in the skin and subcutaneous tissues. It is classified in two groups: the first is represented by primary angiosarcoma, which includes cutaneous and breast angiosarcoma; the second is constituted by secondary angiosarcoma, which is related to radiation therapy, lymphedema, exposure to some chemical toxins, and familiar syndromes. Post-radiation intestinal angiosarcoma is a special type of secondary angiosarcoma, and only a few cases have been reported in the literature. We present a case of radiation-induced small bowel angiosarcoma in an 88-year-old female patient who was admitted to our department for abdominal pain and signs of intestinal obstruction. Her clinical history included previous radiotherapy treatments after a hysterectomy for uterine fibroids, excision of the vaginal stump for squamous cell carcinoma, and the surgical removal of a left-leg cutaneous angiosarcoma. She underwent emergency surgery, and features of peritoneal carcinomatosis were detected. A histological examination showed the presence of a small intestinal angiosarcoma. At the histochemical analysis, MYC amplification was detected, suggesting that her small bowel angiosarcoma was related to past radiation treatments.
A Method to Identify Main Paths of Knowledge Diffusion for Collaborative Innovation Projects
Authors: Xu Lei , Tao Hu , Liu Shanshan , Wang Lei
Published: July 2023

The main paths of the knowledge diffusion network can reveal the important actors and diffusion process, which has an important significance in improving the efficiency of knowledge diffusion. Due to the independent path choice of project actors, knowledge diffusion networks show a dynamic characteristic in collaborative innovation projects. Taking into account this dynamic characteristic, dynamic main path analysis method for project context is proposed. The method, constructed by MATLAB simulation modeling, proposes calculation index and analysis strategies. Contrastive application of two main types of path analysis (the main path analysis method and dynamic main path analysis method) is carried out through a collaborative innovation project case, in order to verify the effectiveness and applicability of this method. The comparison results show that the main paths identified by the new method are more consistent with the actual main paths in knowledge diffusion practice, and the level of knowledge flow through main paths is higher. Therefore, our conclusion is that the dynamic main path analysis method proposed in this research has high applicability and accuracy for identifying the main paths in the collaborative innovation projects.
Diversity, Relationship, and Distribution of Virophages and Large Algal Viruses in Global Ocean Viromes
Authors: Wu Zhenqi , Chu Ting , Sheng Yijian , Yu Yongxin , Wang Yongjie
Published: July 2023

Virophages are a group of small double-stranded DNA viruses that replicate and proliferate with the help of the viral factory of large host viruses. They are widely distributed in aquatic environments but are more abundant in freshwater ecosystems. Here, we mined the Global Ocean Viromes 2.0 (GOV 2.0) dataset for the diversity, distribution, and association of virophages and their potential host large viruses in marine environments. We identified 94 virophage sequences (>5 kbp in length), of which eight were complete genomes. The MCP phylogenetic tree showed that the GOV virophages were widely distributed on the global virophage tree but relatively clustered on three major branches. The gene-sharing network divided GOV virophages into 21 outliers, 2 overlaps, and 14 viral clusters, of which 4 consisted of only the GOV virophages. We also identified 45 large virus sequences, 8 of which were >100 kbp in length and possibly involved in cell–virus–virophage (C–V–v) trisome relationships. The potential eukaryotic hosts of these eight large viruses and the eight virophages with their complete genomes identified are likely to be algae, based on comparative genomic analysis. Both homologous gene and codon usage analyses support a possible interaction between a virophage (GOVv18) and a large algal virus (GOVLV1). These results indicate that diverse and novel virophages and large viruses are widespread in global marine environments, suggesting their important roles and the presence of complicated unknown C–V–v relationships in marine ecosystems.
A Systematic Review of Behaviour Change Techniques within Interventions to Increase Vaccine Uptake among Ethnic Minority Populations
Authors: Ekezie Winifred , Connor Aaisha , Gibson Emma , Khunti Kamlesh , Kamal Atiya
Published: July 2023

COVID-19 caused significant morbidity and mortality amongst ethnic minority groups, but vaccine uptake remained lower than non-minoritised groups. Interventions to increase vaccine uptake among ethnic minority communities are crucial. This systematic review synthesises and evaluates behaviour change techniques (BCTs) in interventions to increase vaccination uptake in ethnic minority populations. We searched five databases and grey literature sources. From 7637 records identified, 23 studies were included in the review. Interventions were categorised using the Behaviour Change Wheel (BCW) and Behaviour Change Taxonomy v1. Vaccines included influenza, pertussis, tetanus, diphtheria, meningitis and hepatitis. Interventions were primarily delivered in health centres/clinics and community settings. Six BCW intervention functions and policy categories and 26 BCTs were identified. The main intervention functions used were education, persuasion and enablement. Overall, effective interventions had multi-components and were tailored to specific populations. No strong evidence was observed to recommend specific interventions, but raising awareness and involvement of community organisations was associated with positive effects. Several strategies are used to increase vaccine uptake among ethnic minority communities; however, these do not address all issues related to low vaccine acceptance. There is a strong need for an increased understanding of addressing vaccine hesitancy among ethnic minority groups.
Risk of Testing Positive for COVID-19 among Healthcare and Healthcare-Related Workers
Authors: Ríos-Bracamontes Eder Fernando , Iñiguez-Arias Luz Elena , Ochoa-Jiménez Rodolfo José , Guzmán-Esquivel José , Cárdenas-Rojas Martha Irazema , Murillo-Zamora Efrén
Published: July 2023

Understanding the risk factors associated with COVID-19 infection among healthcare workers is crucial for infection prevention and control. The aim of this study was to examine the risk of testing positive for COVID-19 among a multicenter cohort of workers, taking into account their occupational roles (medical professionals, staff in operational and administrative roles, or laboratory personnel) in healthcare settings. The data analyzed in this study included 2163 individuals with suggestive COVID-19 symptoms who underwent laboratory testing. The incidence rate in the study sample was calculated to be 15.3 cases per 10,000 person-days. The results from the multiple regression model indicated that job roles were not significantly associated with the risk of testing positive. However, age and the duration of the pandemic were identified as significant risk factors, with increasing age and longer pandemic duration being associated with a higher risk of testing positive. Additionally, vaccination was found to reduce the risk of testing positive. These findings provide valuable insights into COVID-19 transmission among indoor healthcare workers, highlighting the influence of age, pandemic duration, and vaccination on infection risk. Further research is needed to develop evidence-based strategies aimed at protecting healthcare workers and preventing virus spread in healthcare settings.
An Analysis of Linker-Dependent Effects on the APC Activation and In Vivo Immunogenicity of an R848-Conjugated Influenza Vaccine
Authors: Crofts Kali F. , Page Courtney L. , Swedik Stephanie M. , Holbrook Beth C. , Meyers Allison K. , Zhu Xuewei , Parsonage Derek , Westcott Marlena M. , Alexander-Miller Martha A.
Published: July 2023

Subunit or inactivated vaccines comprise the majority of vaccines used against viral and bacterial pathogens. However, compared to their live/attenuated counterparts, these vaccines often demonstrate reduced immunogenicity, requiring multiple boosters and or adjuvants to elicit protective immune responses. For this reason, studies of adjuvants and the mechanism through which they can improve inactivated vaccine responses are critical for the development of vaccines with increased efficacy. Studies have shown that the direct conjugation of adjuvant to antigen promotes vaccine immunogenicity, with the advantage of both the adjuvant and antigen targeting the same cell. Using this strategy of direct linkage, we developed an inactivated influenza A (IAV) vaccine that is directly conjugated with the Toll-like receptor 7/8 agonist resiquimod (R848) through a heterobifunctional crosslinker. Previously, we showed that this vaccine resulted in improved protection and viral clearance in newborn nonhuman primates compared to a non-adjuvanted vaccine. We subsequently discovered that the choice of linker used to conjugate R848 to the virus alters the stimulatory activity of the vaccine, promoting increased maturation and proinflammatory cytokine production from DC differentiated in vitro. With this knowledge, we explored how the choice of crosslinker impacts the stimulatory activity of these vaccines. We found that the linker choice alters signaling through the NF-κB pathway in human monocyte-derived dendritic cells (moDCs). Further, we extended our analyses to in vivo differentiated APC present in human peripheral blood, replicating the linker-dependent differences found in in vitro differentiated cells. Finally, we demonstrated in a mouse model that the choice of linker impacts the amount of IAV-specific IgG antibody produced in response to vaccination. These data enhance our understanding of conjugation approaches for improving vaccine immunogenicity.
Exploring the Immunoprotective Potential of a Nanocarrier Immersion Vaccine Encoding Sip against Streptococcus Infection in Tilapia (Oreochromis niloticus)
Authors: Cao Ye , Liu Jia , Liu Gaoyang , Du Hui , Liu Tianqiang , Wang Gaoxue , Wang Qing , Zhou Ya , Wang Erlong
Published: July 2023

Tilapia, as one of the fish widely cultured around the world, is suffering severe impact from the streptococcus disease with the deterioration of the breeding environment and the increasing of breeding density, which brings serious economic loss to tilapia farming. In this study, the surface immunogenic protein (Sip) of Streptococcus agalactiae (S. agalactiae) was selected as the potential candidate antigen and connected with bacterial nano cellulose (BNC) to construct the nanocarrier subunit vaccine (BNC-rSip), and the immersion immune effects against S. agalactiae and Streptococcus iniae (S. iniae) in Nile tilapia were evaluated on the basis of the serum antibody level, non-specific enzyme activity, the immune-related gene expression and relative percent survival (RPS). The results indicated that Sip possessed the expected immunogenicity according to the immunoinformatic analysis. Compared with the rSip group, BNC-rSip significantly induced serum antibody production and improved the innate immunity level of tilapia. After challenge, the RPS of BNC-rSip groups were 78.95% (S. agalactiae) and 67.86% (S. iniae), which were both higher than those of rSip groups,31.58% (S. agalactiae) and 35.71% (S. iniae), respectively. Our study indicated that BNC-rSip can induce protective immunity for tilapia through immersion immunization and may be an ideal candidate vaccine for controlling tilapia streptococcal disease.
Path Planning for Perpendicular Parking of Large Articulated Vehicles Based on Qualitative Kinematics and Geometric Methods
Authors: Han Inhwan
Published: July 2023

Since large articulated vehicles have uncertainties in trailer articulation angle as well as dynamic complexity, it is not easy to accurately establish a reliable motion plan. In this paper, two geometric path plans constructed based on the empirical rules of driving experts are presented so that articulated vehicles can automatically perform perpendicular parking on a reverse path. By analyzing the empirical parking methods of professional drivers, these path plans were constructed by appropriately combining several standardized simple basic motions to facilitate implementation in real vehicles. In addition, the path plans included appropriate complementary motions to effectively respond to uncertainties arising from articulation angles, etc. The complementary motions developed in this study are based on the results of qualitative analysis on the behavior of articulated vehicles. The usefulness of the proposed articulated vehicle parking method has been proven through hundreds of experimental tests using a scaled model automated vehicle.
Granular Segregation in Gravity-Driven, Dense, Steady, Fluid–Particle Flows over Erodible Beds and Rigid, Bumpy Bases
Authors: Jenkins James T. , Larcher Michele
Published: July 2023

Kinetic theory is used to propose and solve boundary value problems for fully developed, steady, dense gravity-driven flows of mixtures composed of identical inelastic spheres and water over both inclined erodible beds and rigid, bumpy bases confined by vertical sidewalls. We solve the boundary value problems assuming values of the mass density and of the size of the spheres typical of natural materials and show the numerical solutions for the profiles of the mean velocities of the particles and fluid, the intensity of the particle velocity fluctuations, and the granular concentration. In addition, we indicate how the features of the grain velocity fluctuations profile would influence segregation in three situations when the particle phase consists of two sizes of spheres: (1) the spheres are of the same material, and only gradients of temperature influence their segregation; (2) the mass densities of the material of the spheres are such that only gravity influences segregation; and (3) the mass densities are such that the coefficients of the temperature gradients and gravity segregation mechanisms are equal. For spheres of the same material, over a rigid bumpy base, the concentration of larger spheres increases from zero at the bed to the maximum value at the top of the flow; while over an erodible bed, this concentration has its maximum value at both the bed and the top of the flow.
Serving the Needs of Separating and Divorcing Families: A National Survey of Extension Parenting Education Programs and Resources
Authors: Mulroy Maureen , Riffe Jane , Brandon Denise , Lo Yi , Vaidyanath Harini
Published: July 2023

An online survey was developed to map Extension's presence in divorce education initiatives and to catalogue the amount, type, and availability of resources that each state has dedicated to meeting the needs of this parent audience. Requests for participation were sent to members on the National Extension Human Service listserv and resulted in representation from 48 out of 50 states and one U. S. territory. Results document a national presence, outline the nature and expression of Extension divorce education programs, and suggest a direction for future collaboration related to this topic.
Using Mixed-Mode Contacts in Client Surveys: Getting More Bang for Your Buck
Authors: Israel Glenn
Published: July 2023

Surveys are commonly used in Extension to identify client needs or evaluate program outcomes. This article examines how available email addresses can be incorporated into mixed-mode procedures for surveys. When mail and email addresses are used to implement a sequence of email and postal invitations in a mixed-mode survey, response rates were somewhat lower than those for mail only surveys. Item nonresponse is, however, lower for questionnaires completed via the Web, and costs for postage were substantially lower for the mixed-mode groups (because 60% of the surveys were completed via the Web). The study demonstrates the benefit of using mixed-mode surveys.
Ethical Issues in the French Vaccination Campaign Against COVID-19*
Authors: JOE Tegu
Published: July 2023

Thanks to COVID-19 vaccines that developed earlier than expected, the end of long Coronavirus era seems to be in sight. However, the vaccination news from all across the world tells us that Coronavirus vaccinations are a matter of order, unlike prevention. In particular, right after the French vaccination campaign launched on December 27th, 2020, the confusion and chaos shown in its early stage of the French vaccination campaign require a close examination since their vaccination strategy was based on the ethical value of respect for human dignity. In the initial French vaccination plan, their vaccine prioritization criteria were established based on, first of all, saving lives. They tried to maximize the liberty of the individual by ensuring patient autonomy in its execution. The values that the French vaccination campaign based on were fundamental and universal human values that everyone could agree on. Thus, the confusion shown in the French vaccination campaign raises the following question: “In a crisis like a global pandemic, does emphasizing the universal values only delay or worsen the existing crisis situation?” In this paper, we analyze the initial French vaccination campaign and reveal the underlying ethical assumptions. Then we track the later revisions of the campaign and evaluate them. Finally, we conclude with the answer to the upper mentioned question.
Validity and Reliability of Korean Version of the Schwartz Center Compassionate Care Scale*
Authors: KIM Seong Eun , KIM Jeong Suk
Published: July 2023

This study was conducted to evaluate the validity and reliability of the Korean version of Schwartz Center Compassionate Care Scale (K-SCCCS) in recent hospitalizations. Participants were 306 adults (15 ? 64 years old), who had been hospitalized for more than 24 hours at general or tertiary hospital within the last 3 months. Internal consistency, stability, reliability, construct validity (exploratory and confirmatory factor analysis), and criterion validity were evaluated. Using the Rasch model, the persons and items fit, distribution of item difficulty, and appropriateness of the rating scale were also investigated. The confirmatory factor analysis showed a reasonable fit (RMSEA=0.08, CFI=97, TLI=0.96). There were significant correlations between K-SCCCS and individualized care (0.70, p <.001), clinical compassion (0.67, p <.001) and subjective satisfaction with compassionate care (0.66, p <.001). Overall internal reliability (Cronbach’s alpha=0.97) and test-retest reliability (0.66) were good. All items and scales adjusted well to the model (fit indices range: 0.66~1.22) except for item 12. The K-SCCCS had satisfactory person separation reliability (0.97) and item separation reliability (0.93). There were no disordered thresholds in the 10-point rating scale. The K-SCCCS is a useful and reliable scale to assess compassionate care in Korean inpatient populations.
Factors Affecting Ethical Competence in Nurses*
Authors: KIM Sanghee , SEO Minjeong , KIM Doo Ree
Published: July 2023

The purpose of this study was to identify the factors affecting ethical
competence in nurses. This study was conducted a cross-sectional descriptive
design with a convenience sample of 100 nurses from a university affiliated
hospital in Seoul. The study collected data on items drawn from CENAS (The
Clinical Ethics Need Assessment Survey), ethics education needs, ethical
confidence, moral sensitivity, and ethical competence. The data were analyzed
using descriptive statistics, a t-test, a one-way ANOVA, correlation analysis,
and multiple linear regression analysis with SPSS Win 21 program. The results
indicate that the main factor influencing nurses’ ethical competence is as
ethical confidence (β = .53), which accounted for 42.0% of variance. These
results suggest development of ethical education program for nurses for
improving nurses’ ethical capabilities.
INTERNET TV NAVIGATION MODEL FOR THE ELDERLY BASED ON PERSUASIVE DESIGN TECHNOLOGY
Authors: Vadivalu Kalaivani , Singh Dalbir
Published: July 2023

In today's technological era, the design and navigation process is the focal point of every conversation surrounding the development of any application. Furthermore, the rapid evolution of television is consistent with the notion that humans may see and hear at any time and place, leading to Internet TV's emergence. However, the current interface design may not be compatible with the physical and cognitive abilities of the elderly. Consequently, even though the features and functions of Internet TV are relatively straightforward, its adaption for the elderly can be challenging. Therefore, the purpose of this study is to comprehend the difficulties faced by the elderly in terms of the design and navigation of Internet TV and to propose guidelines and a model using Persuasive Technology. This model strives to develop an interface with a user-friendly appearance and feel and an environment that encourages users to return frequently and use the product without feeling frightened, disturbed, or anxious. This research employs Usability Testing (UT) to conduct trials. This investigation was conducted with ten volunteers aged 60 and older. The method consists of two sections: UT1 and UT2. In UT1, users were given seven activities using Astro-On-The-Go (AOTG). These activities collect problems, challenges, and feedback to enhance the present interface. Participant feedback was used to develop a prototype with enhanced features and functions. In UT2, the newly created prototype served as the experiment's foundation. Participants are evaluated by completing specified activities. After collecting feedback, a comparison is made between UT1 and UT2 to determine the study's findings. It was discovered that the participants were more receptive to the new prototype due to its user-friendly interface and navigation, which was reinforced with compelling elements. These findings can serve as a foundation for future recommendations and enhancements.
Analysis of Vegetation Index in Ambon City Using Sentinel-2 Satellite Image Data with Normalized Difference Vegetation Index (NDVI) Method based on Google Earth Engine
Authors: Rakuasa Heinrich , Sihasale Daniel Anthoni
Published: July 2023

Rapid urban development and increasing human activities in the city can affect the decline in the Vegetation Index in Ambon City. The research aims to analyze the vegetation index using sentinel-2 satellite image data with the Normalized Difference Vegetation Index (NDVI) method based on Google Earth Engine (GEE) in Ambon City in 2023. This research uses Sentinel-2 Satellite Image data which is analyzed using Google Earth Engine with the Normalized Difference Vegetation Index (NDVI) method. The results showed that the vegetation index value in Ambon City in 2023 was the lowest value of -0.672381 and the highest value of 0.949297. The vegetation index value is then divided into four classes, namely No Vegetation which has an area of 4,448.99 ha or 13.67%, Low Vegetation areas have an area of 1,611.06 ha or 4.95%, Moderate Vegetation areas have an area of 2,895.12 ha or 8.89% and High Vegetation areas have an area of 23,597.35 ha or 72.49%. Analysis of the vegetation index in Ambon City is very important to maintain environmental balance and a healthy and sustainable environment.
MVLP: Multi-perspective Vision-Language Pre-training Model for Ethically Aligned Meme Detection
Authors: Zhang Ning , Feng Xuan , Gu Tianlong , Chang Liang
Published: July 2023

Ethically aligned design aims to ensure that intelligent systems remain human-centric, serving humanity’s values and ethical principles. Moderating content for achieving ethically aligned design is a critical step toward the realization of trustworthy AI. However, current content moderation methods focus on the detection of harmful content and ignore ethical considerations. Likewise, multi-modal meme detection tasks lack designs for more complex ethical discriminations. Memes pose an interesting multi-modal fusion problem, i.e., their understanding requires a very specific combination of information from different modalities (the text and the image), and have become an influential medium for conveying ideas, socio-cultural, and political views. Therefore, ethically aligned meme detection is crucial to investigate modalities and ensure that they are aligned with our social values and goals. In this paper, we propose MVLP, a Multi-perspective Vision-Language Pre-training model for ethically aligned meme detection.