bluuebunny/crossref_metadata_2025 huggingface dataset:
Multi-Scale Feature and Multi-Channel Selection toward Parkinson’s Disease Diagnosis with EEG
Authors: Wu Haoyu , Qi Jun , Purwanto Erick , Zhu Xiaohui , Yang Po , Chen Jianjun
Published: July 2024

Objective: Motivated by Health Care 4.0, this study aims to reducing the dimensionality of traditional EEG features based on manual extracted features, including statistical features in the time and frequency domains. Methods: A total of 22 multi-scale features were extracted from the UNM and Iowa datasets using a 4th order Butterworth filter and wavelet packet transform. Based on single-channel validation, 29 channels with the highest R2 scores were selected from a pool of 59 common channels. The proposed channel selection scheme was validated on the UNM dataset and tested on the Iowa dataset to compare its generalizability against models trained without channel selection. Results: The experimental results demonstrate that the proposed model achieves an optimal classification accuracy of 100%. Additionally, the generalization capability of the channel selection method is validated through out-of-sample testing based on the Iowa dataset Conclusions: Using single-channel validation, we proposed a channel selection scheme based on traditional statistical features, resulting in a selection of 29 channels. This scheme significantly reduced the dimensionality of EEG feature vectors related to Parkinson’s disease by 50%. Remarkably, this approach demonstrated considerable classification performance on both the UNM and Iowa datasets. For the closed-eye state, the highest classification accuracy achieved was 100%, while for the open-eye state, the highest accuracy reached 93.75%.
Study on the Determination of Flavor Value of Rice Based on Grid Iterative Search Swarm Optimization Support Vector Machine Model and Hyperspectral Imaging
Authors: Yang Han , Qu Fuheng , Yang Yong , Li Xiaofeng , Wang Ping , Guo Sike , Wang Lu
Published: July 2024

In the field of rice processing and cultivation, it is crucial to adopt efficient, rapid and user-friendly techniques to detect the flavor values of various rice varieties. The conventional methods for flavor value assessment mainly rely on chemical analysis and technical evaluation, which not only deplete the rice resources but also incur significant time and labor costs. In this study, hyperspectral imaging technology was utilized in combination with an improved Particle Swarm Optimization Support Vector Machine (PSO-SVM) algorithm, i.e., the Grid Iterative Search Particle Swarm Optimization Support Vector Machine (GISPSO-SVM) algorithm, introducing a new non-destructive technique to determine the flavor value of rice. The method captures the hyperspectral feature data of different rice varieties through image acquisition, preprocessing and feature extraction, and then uses these features to train a model using an optimized machine learning algorithm. The results show that the introduction of GIS algorithms in a PSO-optimized SVM is very effective and can improve the parameter finding ability. In terms of flavor value prediction accuracy, the Principal Component Analysis (PCA) combined with the GISPSO-SVM algorithm achieved 96% accuracy, which was higher than the 93% of the Competitive Adaptive Weighted Sampling (CARS) algorithm. And the introduction of the GIS algorithm in different feature selection can improve the accuracy to different degrees. This novel approach helps to evaluate the flavor values of new rice varieties non-destructively and provides a new perspective for future rice flavor value detection methods.
MambaReID: Exploiting Vision Mamba for Multi-Modal Object Re-Identification
Authors: Zhang Ruijuan , Xu Lizhong , Yang Song , Wang Li
Published: July 2024

Multi-modal object re-identification (ReID) is a challenging task that seeks to identify objects across different image modalities by leveraging their complementary information. Traditional CNN-based methods are constrained by limited receptive fields, whereas Transformer-based approaches are hindered by high computational demands and a lack of convolutional biases. To overcome these limitations, we propose a novel fusion framework named MambaReID, integrating the strengths of both architectures with the effective VMamba. Specifically, our MambaReID consists of three components: Three-Stage VMamba (TSV), Dense Mamba (DM), and Consistent VMamba Fusion (CVF). TSV efficiently captures global context information and local details with low computational complexity. DM enhances feature discriminability by fully integrating inter-modality information with shallow and deep features through dense connections. Additionally, with well-aligned multi-modal images, CVF provides more granular modal aggregation, thereby improving feature robustness. The MambaReID framework, with its innovative components, not only achieves superior performance in multi-modal object ReID tasks, but also does so with fewer parameters and lower computational costs. Our proposed MambaReID’s effectiveness is validated by extensive experiments conducted on three multi-modal object ReID benchmarks.
A Model of Adaptive Error Management Practices Addressing the Higher-Order Factors of the Dirty Dozen Error Classification—Implications for Organizational Resilience in Sociotechnical Systems
Authors: Marquardt Nicki , Gades-Büttrich Ricarda , Brandenberg Tammy , Schürmann Verena
Published: July 2024

Within the dynamic, complex, and often safety-critical operations of many process industries, the integration of technology and human elements has given rise to sociotechnical systems (STSs), where the interaction between people and technology plays a pivotal role. To thrive in this complex environment, organizations must adopt adaptive error management strategies and cultivate organizational resilience. This approach involves managing the unexpected and designing systems to embrace disorder by organizational learning from errors in STSs. The main objective of this article was to present empirical data of error-causing elements in STSs based on the Dirty Dozen concept, their underlying structure, and implications for error causation screening and adaptive error management systems. A sample of 544 workers employed in seven process industries, such as automotive, chemicals, defense, metal, and timber, participated in this study. The results revealed a three-factor model of human error causation in STSs. Based on these results, an adaptive error management system (AEMS), which includes evidence-based interventions to manage causes of human errors and mitigate their risky consequences, was presented. Finally, implications for organizational resilience and safety culture in STSs were discussed.
Implementation of an Antimicrobial Stewardship Program at the Hospital and ICU Level of a Clinic in Sincelejo-Sucre
Authors: Diaz-Morales Erick , Pacheco-Hermosilla Ana Paola , Castro-Mangonez Daniel Esteban , Pajaro-Castro Nerlis
Published: July 2024

Objectives: In this retrospective observational study, the aim is to establish how the implementation of the use of antimicrobial stewardship programs at the hospital and intensive care unit level in a Sucre Clinic in Sincelejo has had a significant impact on the improvement of the rational use of antibiotics, due to the alarming situation of increasing antibiotic resistance. Materials and methods: The methodology used was to analyze the Excel database of the Clinic in such a way as to compare the data from 2017, the period prior to the implementation of the antimicrobial stewardship program (ASP), with the subsequent evolution between the years 2018 and 2022, in relation to the institutional records of four antibiotics—ceftriaxone3, ciprofloxacin4, meropenem5, and vancomycin6, measured in defined daily dose (DDD). Results: According to the defined daily dose values obtained for the four antibiotics, a reduction in the defined daily dose was identified in the post-implementation period. On the other hand, considering the DDD reported by the World Health Organization for each of the antibiotics, significant differences were verified in comparison with those obtained in the clinic in the hospitalization and intensive care unit services. Conclusions: In conclusion, in the clinic, a reduction in the defined daily dose was verified in the period after the implementation of the antimicrobial stewardship program compared to the previous period, both in the hospitalization and intensive care unit, as well as having a mild-to-large effect with Cohen’s D.
Evaluation of the Arthur Project: Evidence-Based Mentoring in a Social Work Framework with a Social Justice Approach
Authors: Miner-Romanoff Karen , Greenawalt Jessica
Published: July 2024

Low-income students from underrepresented communities experience significant educational inequalities, including chronic absenteeism, mental health crises, trauma exposure, and social injustices. These conditions escalate risks of dropping out and justice system involvement. Middle-school youth must navigate intense social and emotional change. To address such challenges, The Arthur Project (TAP) provides intensive, in-school, therapeutic mentoring and family support. The program teaches students essential life skills, such as problem-solving, communication, and academic engagement. Students are empowered to strengthen their resilience, perseverance, self-actualization, and confidence. TAP provides up to 500 h of therapeutic mentoring yearly over three years, delivered individually and in small groups by social work interns. The research question was as follows: Does structured, intensive in-school therapeutic mentoring with social work interns increase the socioemotional, cognitive, noncognitive, and academic skills and engagement of underserved middle-school students? This evaluation for the school year 2022–2023 is based on the program of 200 students and 30 mentors, with quantitative mentee, mentor, teacher, and caregiver surveys and qualitative interview data. The program and evaluation methodology are described, with results and conclusions. Students showed significant improvement in all domains; mentors reported student increases in confidence, perseverance, problem-solving, and communication; and teachers and caregivers reported students’ increased academic engagement. The Arthur Project program can become a national middle-school mentoring model to address widespread student inequalities.
Analyzing the Impact of Social Media Influencers on Consumer Shopping Behavior: Empirical Evidence from Pakistan
Authors: Afzal Bilal , Wen Xiao , Nazir Ahad , Junaid Danish , Olarte Silva Leidy Johanna
Published: July 2024

This study provides valuable insights into the impact of social media influencers (SMIs) on consumer shopping behavior through the lens of social influence theory. It focuses on the mediating role of shopping intentions and the moderating effects of brand credibility and individual shopping values in Pakistan. Using online questionnaires, data were collected from 988 individuals with first-hand experience of social commerce. To investigate a moderated mediation model, we used Smart-PLS 4, which examines how SMIs affect shopping behavior through shopping intention in the case of social media buying. The moderating effects of brand credibility and individual shopping values, specifically hedonic and utilitarian, are also examined. The results show that brand credibility significantly moderates the relationship between SMIs and shopping intentions. Utilitarian shopping value significantly moderates the conversion of shopping intentions into actual shopping behavior, while hedonic shopping value is found to be insignificant. This study uses social influence theory to emphasize the importance of critical variables in digital consumer behavior. The findings suggest that marketers should emphasize brand credibility and practical values to boost social commerce and engagement, providing a practical guide for their strategies.
Machine Learning Models for Solar Power Generation Forecasting in Microgrid Application Implications for Smart Cities
Authors: Suanpang Pannee , Jamjuntr Pitchaya
Published: July 2024

In the context of escalating concerns about environmental sustainability in smart cities, solar power and other renewable energy sources have emerged as pivotal players in the global effort to curtail greenhouse gas emissions and combat climate change. The precise prediction of solar power generation holds a critical role in the seamless integration and effective management of renewable energy systems within microgrids. This research delves into a comparative analysis of two machine learning models, specifically the Light Gradient Boosting Machine (LGBM) and K Nearest Neighbors (KNN), with the objective of forecasting solar power generation in microgrid applications. The study meticulously evaluates these models’ accuracy, reliability, training times, and memory usage, providing detailed experimental insights into optimizing solar energy utilization and driving environmental sustainability forward. The comparison between the LGBM and KNN models reveals significant performance differences. The LGBM model demonstrates superior accuracy with an R-squared of 0.84 compared to KNN’s 0.77, along with lower Root Mean Squared Error (RMSE: 5.77 vs. 6.93) and Mean Absolute Error (MAE: 3.93 vs. 4.34). However, the LGBM model requires longer training times (120 s vs. 90 s) and higher memory usage (500 MB vs. 300 MB). Despite these computational differences, the LGBM model exhibits stability across diverse time frames and seasons, showing robustness in handling outliers. These findings underscore its suitability for microgrid applications, offering enhanced energy management strategies crucial for advancing environmental sustainability. This research provides essential insights into sustainable practices and lays the foundation for a cleaner energy future, emphasizing the importance of accurate solar power forecasting in microgrid planning and operation.
Analyzing Young Adult Travelers’ Perception and Impacts of Carpooling on Traffic Sustainability
Authors: Haroon Waqas , Khan Muhammad Arsalan , Ilyas Zeeshan , Almujibah Hamad R. , Zubair Muhammad Umer , Ashfaq Muhammad , Hamza Muhammad
Published: July 2024

Since young adults (i.e., aged between 18 and 30) are generally more flexible and conscious of economic and environmental concerns, it is essential to assess their travel perceptions and tendency to shift towards sustainable transportation modes. Therefore, this research aims to evaluate the acceptance of carpooling (CP) in the younger population to alleviate traffic congestion, fuel demand, and pollution. This study was conducted in Islamabad, a fast-growing city in Pakistan with a high percentage of young residents, to evaluate travelers’ perceptions, mode choice decisions, and potential acceptance of CP. An online questionnaire-based survey was developed and distributed to collect a total of 656 responses from the young adult population. Various factors influencing travel perceptions, mode choice, and tendency to carpool were categorized and analyzed using confirmatory factor analysis, stepwise, and mediated multiple regression analysis. Thereafter, the tangible impacts of CP, including reduced traffic congestion, fuel consumption, and emissions resulting from the potential adoption of CP by the younger population, were quantified. The findings imply that young travelers’ mode choice mediates the relationship between travelers’ perception and the tendency to carpool. The outcomes also affirm the impact of demographic variables, including gender and education levels, on the willingness of the young adult population to shift towards carpooling. Furthermore, results predicted that adopting CP, especially by younger adults, may reduce by about 33.6% the number of private vehicles in Islamabad. The findings of this study could offer helpful insights for transport planners, commercial carpool service operators, environmentalists, and policymakers to promote carpool systems, especially among young adults.
Investigating the Relationship between Recycling/Reuse Knowledge and Recycling/Reuse Intention: The Moderating Role of Self-Efficacy
Authors: Noh Mijeong
Published: July 2024

This study examined whether an individual’s self-efficacy has a moderating role in the relationship between the different types of recycling/reuse knowledge they may have and their recycling/reuse intention, and the positive relationship between recycling/reuse intention and recycling/reuse behavior. A total of 725 undergraduate and graduate university students were recruited to complete an online survey via MTurk, with the survey covering topics such as recycling/reuse knowledge, intention, behavior, and self-efficacy. Five hypotheses were tested via structural equation modeling. The results showed that even with low self-efficacy, acquiring “effectiveness” recycling/reuse knowledge can enhance recycling/reuse intention and behavior. Conversely, the respondents with high self-efficacy were shown to have positive recycling/reuse intentions and behaviors due to their “social” recycling/reuse knowledge. In general, recycling/reuse intention and behavior were positively related. These significant findings imply that educators, environmental agencies, and brand managers must develop efficient education and/or advertising strategies to provide appropriate action-related recycling/reuse knowledge (including both effectiveness and social knowledge) to university students with either low or high self-efficacy in order to enhance recycling/reuse intention and, ultimately, behavior.
Thermal Comfort Research on the Rural Elderly in the Guanzhong Region: A Comparative Analysis Based on Age Stratification of Residential Environments
Authors: Ji Tongtong , Zhang Tao , Fukuda Hiroatsu
Published: July 2024

Addressing the thermal comfort of the elderly is a pressing concern amidst the escalating aging population in rural China. This study presents a comprehensive assessment of the thermal comfort within traditional and self-built dwellings in the Guanzhong region. Utilizing a mixed-methods approach encompassing both on-site measurements and questionnaire surveys, with a novel approach of segmenting the elderly population into three distinct age groups. The findings indicate that: (1) An average clothing thermal resistance of 1.83 clo among the elderly, which was found to be relatively higher when compared to other areas and positively correlated with age; (2) A thermal neutral temperature of 8.46 °C for traditional dwellings and 10.53 °C for self-built dwellings, both of which were lower than anticipated, indicating a discrepancy between current living conditions and elderly residents’ thermal expectations; (3) A positive correlation between age and the preferred neutral temperature, with the elderly showing a preference for warmer indoor environments. Additionally, we propose targeted strategies to enhance the thermal comfort of the elderly across different age groups and dwelling types. This study refines the thermal comfort evaluation system for the elderly in China’s cold climate regions, offering theoretical insights and practical guidance for the renovation of rural dwellings and the improvement of elderly living standards in the Guanzhong area.
Beijing Symbiotic Courtyard Model’s Post Evaluation from the Perspective of Stock Renewal
Authors: Li Qin , Chen Zonghao , Cui Jingya , Lin Jiaqi , Li Wenlong , Liu Yijun
Published: July 2024

Stock renewal is one of the important methods of urban renewal, which focuses on optimizing and reusing existing urban spaces. With the increasing land pressure in present-day China and the need for land to be reclassified, the thinking mode of stock updating has become increasingly important. Beijing symbiotic courtyard is a representative urban renewal model that combines the characteristics of traditional quadrangle dwelling and modern architecture, aiming to achieve the symbiosis of history and modernity. After several years of implementation, the effectiveness of this model has become a matter of concern for all parties involved. Therefore, this paper takes stock renewal as the observation perspective, describing an evaluation for the Beijing symbiotic courtyard model, which contains different types of residents living in particular historical districts. It attempts to propose corresponding strategies, aiming to provide a more comprehensive thinking angle and planning method for the sustainability of stock renewal. In contrast to earlier studies, the proposed methods involve a specific mathematical statistical model called the IPA-KANO model, in addition to other traditional urban renewal methods. For a wide range of problems including historical district evaluation and renewal, the approach leads to potentially less errors than caused by manual operation. This comes from the fact that all the data are collected through survey questionnaires and big data, so the technical restriction of using mathematical model is to some extent ruled out in this new approach. Moreover, the approach offers new potential problems that cannot be handled using earlier techniques. After the calculation, although there are still defects, local residents are generally satisfied with the Beijing symbiotic courtyard model. The result suggests that it is of importance to reference this model for urban renewal so that can be widely promoted in historical district vitality regeneration.
Understanding Zinc Transport in Estuarine Environments: Insights from Sediment Composition
Authors: Xiong Hao-Qin , Du Yan-Yun , Fang Yi-Chuan , Xiang Hong , Qu Jia-Zhuo , Sun Xiao-Long
Published: July 2024

Sediments are sources and sinks of heavy metals in water, and estuaries are heavily influenced by human production and life. Therefore, it is of great significance to study the composition of estuarine sediments and the relationship between their components to understand the transport and transformation pathways of heavy metals in the environment. In this research, we investigated the characteristics and patterns of Zn adsorption by organic–inorganic composites, organic–clay mineral composites, and iron oxide–clay mineral composites in eight estuarine sediment samples from Dianchi Lake. The results show that both Langmuir and Freundlich isothermal models can describe the adsorption behaviour of the adsorbent better. The order of the adsorption capacity of the three groups of samples for zinc was organic–inorganic composites > organic–clay mineral composites > iron oxide–clay mineral composites. Through FTIR and XRD analyses, the adsorption of Zn2+ on the three groups of samples was dominated by electrostatic attraction and coordination adsorption, accompanied by the occurrence of ion exchange and co-precipitation. After FTIR semi-quantitative analysis, it was found that the source of the differences in the high and low Zn adsorption of the three types of samples may be mainly due to the content of phenolic functional groups in the organic matter. This may be related to the low redox site of the phenolic hydroxyl group, which, as an electron donor, is susceptible to electrostatic attraction and complexation with heavy metal cations. The organic–inorganic composite has a higher adsorption capacity for Zn when the ratio of the active fraction of organic matter to the free iron oxide content is 0.65–0.70. In this range, the organic matter can provide enough negative charge without making the sample surface too dense. Iron oxides can also activate the sample by providing sufficient contact between the clay minerals and the organic matter. When this ratio is too high or too low, it will be unfavourable for Zn adsorption.
Modeling and Monitoring CO2 Emissions in G20 Countries: A Comparative Analysis of Multiple Statistical Models
Authors: Hussain Anwar , Khan Firdos , Albalawi Olayan
Published: July 2024

The emission of carbon dioxide (CO2) is considered one of the main factors responsible for one of the greatest challenges faced by the world today: climate change. On the other hand, with the increase in energy demand due to the increase in population and industrialization, the emission of CO2 has increased rapidly in the past few decades. However, the world’s leaders, including the United Nations, are now taking serious action on how to minimize the emission of CO2 into the atmosphere. Towards this end, accurate modeling and monitoring of historical CO2 can help in the development of rational policies. This study aims to analyze the carbon emitted by the Group Twenty (G20) countries for the period 1971–2021. The datasets include CO2 emissions, nonrenewable energy (NREN), renewable energy (REN), Gross Domestic Product (GDP), and Urbanization (URB). Various regression-based models, including multiple linear regression models, quantile regression models, and panel data models with different variants, were used to quantify the influence of independent variables on the response variable. In this study, CO2 is a response variable, and the other variables are covariates. The ultimate objective was to choose the best model among the competing models. It is noted that the USA, Canada, and Australia produced the highest amount of CO2 consistently for the entire duration; however, in the last decade (2011–2021) it has decreased to 12.63–17.95 metric tons per capita as compared to the duration of 1971–1980 (14.33–22.16 metric tons per capita). In contrast, CO2 emissions have increased in Saudi Arabia and China recently. For modeling purposes, the duration of the data has been divided into two independent, equal parts: 1971–1995 and 1996–2021. The panel fixed effect model (PFEM) and panel mixed effect model (PMEM) outperformed the other competing models using model selection and model prediction criteria. Different models provide different insights into the relationship between CO2 emissions and independent variables. In the later duration, all models show that REN has negative impacts on CO2 emissions, except the quantile regression model with tau = 0.25. In contrast, NREN has strong positive impacts on CO2 emissions. URB has significantly negative impacts on CO2 emissions globally. The findings of this study hold the potential to provide valuable information to policymakers on carbon emissions and monitoring globally. In addition, results can help in addressing some of the sustainable development goals of the United Nation Development Programme.
Factors That Influence Clothing Upcycling Behavior in Japan: Extending the Theory of Planned Behavior
Authors: Ly Sovanna , Furukawa Ryuzo
Published: July 2024

In recent times, clothing upcycling has emerged as a sustainable solution to tackling textile waste. Despite its popularity, there remains a limited understanding of the factors driving individuals’ upcycling behavior. This study delves into the determinants of clothing upcycling behavior within the Japanese population. Administered via an online survey involving 433 participants in Japan, this research utilized structural equation modeling to assess a theoretical model that integrates personal norms, attitudes, social norms, perceived behavioral control, and intention within the theory of planned behavior. The outcomes reveal that both personal norms and perceived behavioral control exert a substantial influence on individuals’ intentions to participate in upcycling activities. Interestingly, the impact of attitude on upcycling intentions is moderate, while subjective norms surprisingly showed no significant influence. These findings contribute to the pro-environmental behavior literature and can guide the development of focused interventions that promote sustainable fashion consumption through upcycling.
Urban Air Pollution Exposure Impact on COVID-19 Transmission in a Few Metropolitan Regions
Authors: Zoran Maria , Radvan Roxana , Savastru Dan , Tautan Marina
Published: July 2024

Based on outdoor air pollution and meteorological daily time series observational and in-situ monitoring data, this study investigated the impacts of environmental factors under different urban climates on COVID-19 transmission in four hotspot European metropolises (Berlin, London, Madrid, and Paris) from March 2020 to March 2022. Through applied statistical methods and cross-correlation tests involving multiple datasets pertaining to the main air pollutants (inhalable particulate matter PM2.5 and PM10, nitrogen dioxide (NO2), and ozone (O3)) and climate parameters (air temperature at 2 m height, relative humidity, wind speed intensity and direction, planetary boundary layer height, and surface solar irradiance), a direct positive impact of aerosol loading (PM2.5, PM10, and aerosol optical depth (AOD)) on COVID-19 spreading and severity was revealed. Despite some urban differences existing between the selected cities, particularly for the spring–summer periods, we have observed negative correlations between daily new COVID-19 cases and deaths and daily average ground-level ozone concentration, air temperature at 2 m height, planetary boundary layer height, and surface solar irradiance. Air relative humidity and urban population density have a direct impact on COVID-19 diffusion in large metropolitan areas, and the findings of this study highlight the crucial role of air pollution, in synergy with climate variability, in viral pathogens dispersion in COVID-19 transmission in large urban areas. This information can be used by decision-makers to develop targeted interventions during epidemic periods to reduce the potential risks associated with air pollution exposure and to promote the sustainable development of urban economies.
Development of a New Prototype Paediatric Central Sleep Apnoea Monitor
Authors: Saatchi Reza , Elphick Heather , Rowson Jennifer , Wesseler Mark , Marris Jacob , Shortland Sarah , Thomas Lowri
Published: July 2024

A new prototype device to monitor breathing in children diagnosed with central sleep apnoea (CSA) was developed. CSA is caused by the failure of central nervous system signals to the respiratory muscles and results in intermittent breathing pauses during sleep. Children diagnosed with CSA require home respiration monitoring during sleep. Apnoea monitors initiate an audio alarm when the breath-to-breath respiration interval exceeds a preset time. This allows the child’s parents to attend to the child to ensure safety. The article describes the development of the monitor’s hardware, software, and evaluation. Features of the device include the detection of abnormal respiratory pauses and the generation of an associated alarm, the ability to record the respiratory signal and its storage using an on-board disk, miniaturised hardware, child-friendliness, cost-effectiveness, and ease of use. The device was evaluated on 10 healthy adult volunteers with a mean age of 46.6 years (and a standard deviation of 14.4 years). The participants randomly intentionally paused their breathing during the recording. The device detected and provided an alarm when the respiratory pauses exceeded the preset time. The respiration rates determined from the device closely matched the values from a commercial respiration monitor. The study indicated the peak-detection method of the respiration rate measurement is more robust than the zero-crossing method.
Chimeric Viruses Enable Study of Antibody Responses to Human Rotaviruses in Mice
Authors: Woodyear Sarah , Chandler Tawny L. , Kawagishi Takahiro , Lonergan Tom M. , Patel Vanshika A. , Williams Caitlin A. , Permar Sallie R. , Ding Siyuan , Caddy Sarah L.
Published: July 2024

The leading cause of gastroenteritis in children under the age of five is rotavirus infection, accounting for 37% of diarrhoeal deaths in infants and young children globally. Oral rotavirus vaccines have been widely incorporated into national immunisation programs, but whilst these vaccines have excellent efficacy in high-income countries, they protect less than 50% of vaccinated individuals in low- and middle-income countries. In order to facilitate the development of improved vaccine strategies, a greater understanding of the immune response to existing vaccines is urgently needed. However, the use of mouse models to study immune responses to human rotavirus strains is currently limited as rotaviruses are highly species-specific and replication of human rotaviruses is minimal in mice. To enable characterisation of immune responses to human rotavirus in mice, we have generated chimeric viruses that combat the issue of rotavirus host range restriction. Using reverse genetics, the rotavirus outer capsid proteins (VP4 and VP7) from either human or murine rotavirus strains were encoded in a murine rotavirus backbone. Neonatal mice were infected with chimeric viruses and monitored daily for development of diarrhoea. Stool samples were collected to quantify viral shedding, and antibody responses were comprehensively evaluated. We demonstrated that chimeric rotaviruses were able to efficiently replicate in mice. Moreover, the chimeric rotavirus containing human rotavirus outer capsid proteins elicited a robust antibody response to human rotavirus antigens, whilst the control chimeric murine rotavirus did not. This chimeric human rotavirus therefore provides a new strategy for studying human-rotavirus-specific immunity to the outer capsid, and could be used to investigate factors causing variability in rotavirus vaccine efficacy. This small animal platform therefore has the potential to test the efficacy of new vaccines and antibody-based therapeutics.
The Oncolytic Avian Reovirus p17 Protein Inhibits Invadopodia Formation in Murine Melanoma Cancer Cells by Suppressing the FAK/Src Pathway and the Formation of theTKs5/NCK1 Complex
Authors: Hsu Chao-Yu , Li Jyun-Yi , Yang En-Ying , Liao Tsai-Ling , Wen Hsiao-Wei , Tsai Pei-Chien , Ju Tz-Chuen , Lye Lon-Fye , Nielsen Brent L. , Liu Hung-Jen
Published: July 2024

To explore whether the p17 protein of oncolytic avian reovirus (ARV) mediates cell migration and invadopodia formation, we applied several molecular biological approaches for studying the involved cellular factors and signal pathways. We found that ARV p17 activates the p53/phosphatase and tensin homolog (PTEN) pathway to suppress the focal adhesion kinase (FAK)/Src signaling and downstream signal molecules, thus inhibiting cell migration and the formation of invadopodia in murine melanoma cancer cell line (B16-F10). Importantly, p17-induced formation of invadopodia could be reversed in cells transfected with the mutant PTENC124A. p17 protein was found to significantly reduce the expression levels of tyrosine kinase substrate 5 (TKs5), Rab40b, non-catalytic region of tyrosine kinase adaptor protein 1 (NCK1), and matrix metalloproteinases (MMP9), suggesting that TKs5 and Rab40b were transcriptionally downregulated by p17. Furthermore, we found that p17 suppresses the formation of the TKs5/NCK1 complex. Coexpression of TKs5 and Rab40b in B16-F10 cancer cells reversed p17-modulated suppression of the formation of invadopodia. This work provides new insights into p17-modulated suppression of invadopodia formation by activating the p53/PTEN pathway, suppressing the FAK/Src pathway, and inhibiting the formation of the TKs5/NCK1 complex.
Real World Use of Tixagevimab/Cilgavimab Pre-Exposure Prophylaxis of COVID-19 in Immunocompromised Individuals: Data from the OCTOPUS Study
Authors: Vergori Alessandra , Matusali Giulia , Cimini Eleonora , Bordi Licia , Borrelli Paola , Lanini Simone , Palazzi Roberta , Paulicelli Jessica , Mariotti Davide , Mazzotta Valentina , Notari Stefania , Casetti Rita , Francalancia Massimo , Rosati Silvia , D’Abramo Alessandra , Mija Cosmina , Mencarini Paola , Milozzi Eugenia , Caraffa Emanuela , Sica Simona , Metafuni Elisabetta , Sorà Federica , Rago Angela , Siniscalchi Agostina , Abruzzese Elisabetta , Garzia Mariagrazia , Luzi Giovanni , Battistini Roberta , Prosperini Luca , Cingolani Antonella , Girardi Enrico , Maggi Fabrizio , Antinori Andrea
Published: July 2024

Objective. We aimed to report the real-world use and outcomes over time in immunocompromised individuals receiving tixagevimab/cilgavimab (T/C) pre-exposure prophylaxis (PrEP). Methods. This observational study included participants who received T/C PrEP, categorized into three groups: (i) No COVID-19 (NoC), i.e., participants who never had COVID-19; (ii) Hybrids (H), i.e., participants who had COVID-19 before PrEP; and (iii) Break-through Infections (BTIs), i.e., participants who had COVID-19 after PrEP. The study measured several immune markers at the administration of T/C (T0) at 3 (T1), 6 (T2), and 9 (T3) months afterward. These markers included: anti-receptor-binding domain (RBD) IgG antibodies; BA.5-neutralizing antibodies (nAbs); mucosal IgG; and T cell immunity. The incidence rate ratios for BTIs were analyzed using a Poisson regression model. Results. A total of 231 participants with a median age of 63 years (IQR 54.0–73.0). were included. Among these, 84% had hematological diseases and received a median of three vaccine doses. N = 72 participants belonged to the NoC group, N = 103 to the H group, and n = 56 to the BTI group (24%), with most BTIs being mild/moderate. The incidence rate (IR) of BTIs was 4.2 per 100 patient-months (95% CI 3.2–5.4), with no associated risk factors identified. There was a significant increase in anti-RBD IgG levels 3 months after the T/C administration in all groups, followed by a decline at 6 months, whereas at the same time points, geometric mean titers (GMTs) of anti-BA.5 nAbs were low for all groups and were around or below the detection threshold. No significant changes were observed in IFN-γ levels. The mucosal immune response was observed only 3 months after the PrEP administration. Conclusion. We provided a real-world experience model on the clinical efficacy of T/C PrEP in preventing severe COVID-19 during the Omicron wave through a comprehensive virological and immunological study. While waiting for the arrival of new monoclonal antibodies that can effectively neutralize the most recent variants, T/C PrEP remains the only viable strategy in the available armamentarium today to prevent COVID-19 complications in an extremely fragile population with suboptimal immune responses to COVID-19 vaccines.
Humoral and Cellular Response Induced by Primary Series and Booster Doses of mRNA Coronavirus Disease 2019 Vaccine in Patients with Cardiovascular Disease: A Longitudinal Study
Authors: Ishihara Yuya , Naruse Hiroyuki , Fujigaki Hidetsugu , Murakami Reiko , Ando Tatsuya , Sakurai Kouhei , Uehara Komei , Shimomae Koki , Sakaguchi Eirin , Hattori Hidekazu , Sarai Masayoshi , Ishii Junnichi , Fujii Ryosuke , Ito Hiroyasu , Saito Kuniaki , Izawa Hideo
Published: July 2024

Preexisting cardiovascular disease (CVD) is a pivotal risk factor for severe coronavirus disease 2019 (COVID-19). We investigated the longitudinal (over 1 year and 9 months) humoral and cellular responses to primary series and booster doses of mRNA COVID-19 vaccines in patients with CVD. Twenty-six patients with CVD who received monovalent mRNA COVID-19 vaccines were enrolled in this study. Peripheral blood samples were serially drawn nine times from each patient. IgG against the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) spike receptor-binding domain (RBD) was measured using an enzyme-linked immunosorbent assay. The numbers of interferon-γ-releasing cells in response to SARS-CoV-2 peptides were measured using an enzyme-linked immunospot assay. The RBD-IgG titers increased 2 weeks after the primary series and booster vaccination and waned 6 months after vaccination. The S1-specific T cell responses in patients aged < 75 years were favorable before and after booster doses; however, the Omicron BA.1-specific T cell responses were poor. These results suggest that regular vaccination is useful to maintain long-term antibody levels and has implications for booster dose strategies in patients with CVD. Additional booster doses, including Omicron variant-adapted mRNA vaccines, may be recommended for patients with CVD, regardless of age.
Evaluating Two Educational Interventions for Enhancing COVID-19 Knowledge and Attitudes in a Sample American Indian/Alaska Native Population
Authors: Takagi Maya Asami , Rhodes Simone T. , Kim Jun Hwan , King Maxwell , Soukar Stephanie , Martin Chad , Sasaki Cole Angela , Chan Arlene , Brennan Ciara , Zyzanski Stephen , Kissoondial Barry , Ragina Neli
Published: July 2024

Background: The COVID-19 pandemic has exacerbated existing healthcare disparities among American Indian/Alaska Native (AI/AN) populations rooted in historical traumas and systemic marginalization. Methods: This study conducted at a single Indian Health Service (IHS) clinic in central Michigan evaluates two educational interventions for enhancing COVID-19 knowledge and attitudes in a sample AI/AN population. Utilizing a pre/post-intervention prospective study design, participants received either a video or infographic educational intervention, followed by a survey assessing their COVID-19 knowledge and attitudes. Results: The results indicate significant improvements in knowledge and attitudes post-intervention, with both modalities proving effective. However, specific factors such as gender, political affiliation, and place of residence influenced COVID-19 attitudes and knowledge, emphasizing the importance of tailored interventions. Conclusions: Despite limitations, this study highlights the critical role of educational interventions in addressing vaccine hesitancy and promoting health equity within AI/AN communities. Moving forward, comprehensive strategies involving increased Indian Health Service funding, culturally relevant interventions, and policy advocacy are crucial in mitigating healthcare disparities and promoting health equity within AI/AN communities.
Use of a Capsaicin Cough Challenge Test to Compare Four Different Techniques for Nebulization Delivery in Cats
Authors: Talavera-López Jesús , Tudela-González Ana , Muñoz-Prieto Alberto
Published: July 2024

Successful aerosol therapy might rely more heavily on proper drug delivery than on the effectiveness of the medication. This study compared four techniques for nebulization delivery in cats. Tolerance rate (TR) was subjectively evaluated (1–3). Increasing capsaicin concentrations were nebulized for objective evaluation of efficiency. The positive response (PR) was considered when more than five coughs were induced. The following delivery methods were tested: flow-by (FB); face mask (FM); plastic-covered Elizabethan collar (EC); and plexiglass chamber (PC). The number of PRs (NPR) and the concentration of capsaicin that induced a PR (CCP) were statistically compared (p < 0.05). The PC method was the best tolerated (TR = 3.0 ± 0.0), followed by the FB (2.7 ± 0.5) and FM (2.6 ± 0.5). The EC was very stressful, and the test had to be suspended in four out of nine cats. The lowest CCP was found with the FM (91.8 ± 157.2 µM), followed by the FB (166.7 ± 190.9 µM), PC (242.6 ± 244.8 µM), and EC (350.0 ± 225.7 µM), with significant differences only between the FM and EC (p = 0.02). The highest NPR (8) corresponded to the FM, followed by the FB (7), the PC (5), and the EC (3), with significant differences between the FM and EC (p = 0.016). In conclusion, the capsaicin cough test induces reproducible and quantifiable cat responses. The FM is the most efficient for nebulization delivery, offering good compliance and the best quantitative results. FB nebulization is less efficient but may be practical if the FM is not tolerated. PC offers minor efficiency but may be useful for very stressed or aggressive cats. The EC presents low efficiency and compliance.
Effects of Irrigation Approaches and Mulching on Greenhouse Melon Production and Water Use in Northern China
Authors: Liu Shengyao , Li Jingsong , Jia Songnan , Dai Zhihong , Du Fenghuan , Zhao Nan , Fan Fengcui , Liu Zehao , Zhao Sheng
Published: July 2024

To explore the effects of different irrigation approaches, mulching, and their interaction on greenhouse melon (Cucumis melo L.) production and water use, a field experiment was conducted in Northern China using four treatments: mulching drip irrigation (MDI), mulching furrow irrigation (MFI), drip irrigation (DI), and furrow irrigation (FI; CK). The plant biomass, yield, water consumption, and water use efficiency (WUE) of melons were measured at different growth stages. The results showed that mulching has significant positive impacts on the growth as well as the fruit yield of melons. However, the water use characteristics of the plant were more greatly determined by the various irrigation approaches, and there was a significant interaction between the irrigation approach and mulching for both the total water consumption and WUE of the greenhouse melon. Of these treatments, MDI resulted in the highest yield of 38.49 t/hm2, which was significantly higher than the yields obtained with DI (32.36 t·hm−2) and FI (CK, 30.34 t·hm−2). In addition, the water consumption under MDI was 45.80% lower than FI (CK), which resulted in the promotion of WUE under MDI. The WUE range of the greenhouse melon is as follows: MDI (334.77 kg·mm−1·hm−2) > DI (244.84 kg·mm−1·hm−2) > MFI (189.78 kg·mm−1·hm−2) > FI (CK; 142.94 kg·mm−1·hm−2). The findings of this study indicate that mulching can boost melon yield, and drip irrigation can limit water consumption. This study provides a reference point for policymakers, indicating that drip irrigation with plastic mulching could be a feasible adaptation strategy for increasing greenhouse melon production in Northern China, as well as other agriculture regions that suffer from water shortages.
Hydrological Performance Assessment of Low-Impact Development Practices: A Vegetated Swale Case Study
Authors: Lhamidi Khalil , El Khattabi Jamal , Nguyen Hoang Dung , Aljer Ammar
Published: July 2024

The increase in rainfall intensity caused by climate change, combined with high levels of urban soil sealing and the limited capacity of drainage systems, is significantly increasing flooding risk. Integrated stormwater management is a key factor in dealing with the consequences of climate change by mitigating flood risk based on nature-based solutions. An experimental site was designed to assess the hydrological response of vegetated swales depending on different catchment surfaces, and to evaluate the impact of spatial variability of the hydraulic conductivity (K). A hydrological model was developed on EPA SWMM and calibrated based on measured data in two experimental swales with different active surfaces (N6—50 m2 and N11—100 m2). The model validation was assessed with NSE scores higher than 0.7. The simulations considered various factors, such as the water level in the swales, the actual rainfall, the evapotranspiration, the swale geometry, the catchment area (Sa), and the hydraulic conductivities of the natural silty soil, to assess, for the heaviest rainfall event, the best swale morphological characteristics. The study examined the combined impact of K (8) and Sa (6) on swale storage capacity, designed with a 250 mm depth. The simulations showed that the 250 mm overflow limit was exceeded for N10 (90 m2) when K ≤ 2 × 10−6 m/s, and for N11 (100 m2) when K ≤ 4 × 10−6 m/s. These results provide valuable information on the optimal storage capacity based on the swales’ geometrical and physical properties.