bluuebunny/crossref_metadata_2025 huggingface dataset:
Understanding older adults’ acceptance of Chatbots in healthcare delivery: an extended UTAUT model
Authors: Yu Shulan , Chen Tianyue
Published: November 2024

Background

Chatbots are increasingly integrated into the lives of older adults to assist with health and wellness tasks. This study aimed to understand the factors that enhance older adults’ acceptance of chatbots in healthcare delivery.

Methods

This study proposed an extended Unified Theory of Acceptance and Use of Technology model (UTAUT), including aging factors of perceived physical condition, self-actualization needs, and technology anxiety. The model was tested by PLS (Partial Least Squares) with data collected from 428 Chinese citizens aged 60 and above.

Results

The results reveal that performance expectancy, effort expectancy, and social influence significantly affected older adults’ behavioral intention to use chatbots. The facilitating conditions, self-actualization needs, and perceived physical condition significantly affected the actual use behavior of chatbots by older adults, whereas technology anxiety did not. Furthermore, the influence of effort expectancy and social influence on behavioral intention were moderated by experience.

Conclusion

The behavioral intentions of older adults with low experience are more strongly influenced by social influences and effort expectancy. Furthermore, healthcare providers, designers, and policymakers should emphasize the impact of facilitating conditions, self-actualization needs, and perceived physical conditions on chatbot applications among older adults.
Study on the co-occurrence of multiple health service needs throughout the lifecourse of rural residents in China based on association rules
Authors: Jia Jingjing , Liu Xuejiao , Ren Panpan , Chen Mengyao , Xu Jinglin , Zhang Xiang
Published: November 2024

Objective

To understand the multiple health service needs of rural residents in China and explore the co-occurrence patterns of these needs throughout the entire life course, providing a basis for the formulation and optimization of health service packaging policies.

Methods

This study utilized a stratified random sampling method, resulting in a final sample size of 15,125 individuals. The R statistical software was employed to apply the Apriori algorithm to mine the co-occurrence relationships among multiple health service needs across the life course and to explore the packaging model of these services.

Results

The health service needs rate among rural residents in China is 86.76%, with a multiple health service needs rate of 78.72%. The most needed services are health exercise guidance (17.10%), Traditional Chinese Medicine health care (15.53%), and internet health information services (14.40%). The highest combined health service need is for “exercise guidance need + internet health information need + Traditional Chinese Medicine health care need,” followed by “exercise guidance need + internet information need.” There are significant differences in the content and strength of associations in the co-occurrence structure of multiple health service needs across different age groups. During the life preparation stage, the need for multiple health services is high, with modern medical care and child management having the highest support. In the life protection stage, the focus shifts to preventive health needs, with strong associations among co-occurring needs (the highest support rule being Traditional Chinese Medicine health care + exercise guidance, support = 21.12%). The co-occurrence of medical and preventive health service needs among the older adult is diverse, with the strongest association being between chronic disease management services and rehabilitation services (support = 31.24%).

Conclusion

The multiple health service needs rate among rural residents in China is high, with the greatest needs being for exercise guidance, Traditional Chinese Medicine health care, and internet health information services. There are significant differences in health service needs across different life stages. It is essential to enhance the integration and packaging of health service resources to promote diversity in health services and meet the multiple health service needs of residents throughout their life courses.
Sufficiency health-wise: sustainable paths towards planetary and public health
Authors: Geiselhart Klaus , Damm Maik , Jeske Niklas , Knappmann Alexia , Nasser Gabriela Pen , Roth Laura Franziska , Unkels Regine , Winkler Andrea Sylvia , Wolf Jennyfer , Falkenberg Timo
Published: November 2024

Planet Earth is threatened by the human population. Energy and resource use are far beyond the planet’s carrying capacity. Planetary Health suggests an alternative idea of prosperity as the best possible human health for all within planetary boundaries. This implies giving priority to ecology because human health depends ultimately on the integrity of the global biosphere. This paper presents a Health Sufficiency Framework, based on the Doughnut Economics Model. It is meant to fuel discussions on delicate topics of the required transformations of health care and public health.
Vision-language models for medical report generation and visual question answering: a review
Authors: Hartsock Iryna , Rasool Ghulam
Published: November 2024

Medical vision-language models (VLMs) combine computer vision (CV) and natural language processing (NLP) to analyze visual and textual medical data. Our paper reviews recent advancements in developing VLMs specialized for healthcare, focusing on publicly available models designed for medical report generation and visual question answering (VQA). We provide background on NLP and CV, explaining how techniques from both fields are integrated into VLMs, with visual and language data often fused using Transformer-based architectures to enable effective learning from multimodal data. Key areas we address include the exploration of 18 public medical vision-language datasets, in-depth analyses of the architectures and pre-training strategies of 16 recent noteworthy medical VLMs, and comprehensive discussion on evaluation metrics for assessing VLMs' performance in medical report generation and VQA. We also highlight current challenges facing medical VLM development, including limited data availability, concerns with data privacy, and lack of proper evaluation metrics, among others, while also proposing future directions to address these obstacles. Overall, our review summarizes the recent progress in developing VLMs to harness multimodal medical data for improved healthcare applications.
Thou shalt not pass - arachnid venom peptides interacting with biological membranes
Authors: Wang Yachen , Guo Shaodong , Jee Katie F. , Herzig Volker
Published: November 2024

Arachnid venom peptides receive increasing attention from researchers for possible applications as human therapeutics, as bioinsecticides in agriculture or for targeting vectors of human disease. One commonly perceived disadvantage of peptides in contrast to small molecule drugs is their inability of crossing biological membranes comprised of lipid bilayers, providing a major obstacle for the delivery of peptide-based drugs and bioinsecticides. However, some arachnid venom peptides were reported to cross biological membranes, including cellular membranes, the vertebrate and insect blood brain barrier (BBB) and the insect midgut epithelium. This review will focus on these membrane-permeating arachnid peptides and discuss the underlying mechanisms. Different physico-chemical properties of membrane-permeating arachnid peptides and their contribution to the ability of crossing biological membranes will also be examined. In addition, several methods that facilitate or enable peptides to cross biological membranes will be discussed, which can be employed on peptides with no inherent membrane-permeating capabilities.
Attitudes of employers towards people with visual impairment: a scoping review
Authors: Castle Claire L.
Published: November 2024

This scoping review explored literature relating to employer attitudes towards employees and candidates with visual impairment (VI). Systematic searches identified 17 relevant articles published since 2018. Thematic synthesis highlighted findings relating to several themes: explicit and implicit attitudes of employers; employer concerns, including those relating to employee performance, and the experiences of both customers and colleagues; and factors which might impact on employer attitudes, such as gender and prior experience of having hired someone with VI. Findings indicate a tendency for employers to possess negative or, at best, neutral attitudes towards people with VI, and the central role that improved knowledge of VI and the capabilities of people with VI may play in generating positive employer attitudes. The review highlights the need for further exploration of this topic, particularly given the limited geographical spread of recent research, and a lack of consideration of the shared experience of employer and employee.
Level of health laboratory service quality, service interruptions, and its predictors in public hospitals in Harar town, eastern Ethiopia
Authors: Zakir Dire , Mekonnen Getachaw Kabew , Negash Belay , Marami Dadi
Published: November 2024

Background

Quality laboratory services are key in the healthcare system for successful diagnosis and patient care. Uninterrupted laboratory services are needed to meet the needs of all patients and clinical personnel, but studies in developing nations revealed that most clinicians were dissatisfied due to the lack of quality laboratory services and frequent interruptions.

Objective

This study aimed to assess the level of health laboratory service quality, service interruptions, and its predictors in public Hospitals in Harar town, eastern Ethiopia.

Method

A facility-based cross-sectional study was conducted at Hiwot Fana Specialized University Hospital and Jugel General Hospital between January and April 2024. Data collection utilized Standardized Stepwise Laboratory Improvement Process Towards Accreditation (SLIPTA) checklists and questionnaires based on the Ethiopian Hospital Standard Transformation Guidelines. Data were entered and analyzed by Statistical Package for the Social Sciences, version 26. Descriptive statistics such as frequencies, proportions, and means, were calculated. Binary and multivariable logistic regression models were applied to identify predictors with adjusted odds ratio (AOR) and a cut-off p-values <0.05 with 95% confidence interval (CI).

Results

Two public hospital laboratories and their 54 laboratory professionals were involved in our study. According to our study, the mean score of the two public hospitals was 168.5 (61%), while Hiwot Fana specialized university hospital scored 212 (77%) and Jugel General Hospital scored 127 (46.1%). The study also revealed that out of 72 tests, 31 (43.05%) were interrupted, with clinical chemistry tests being the most interrupted (16, 51.6%) followed by Serology (7, 22.6%) and Hematology (4, 12.9%) tests. Lack of timely management response (AOR = 7.78, 95% CI = 1.48–40.83) and shortage of supplies (AOR = 60.8, 95% CI = 1.07–32.83) were significantly associated predictors of laboratory service interruptions.

Conclusion

Neither of the hospital's laboratories met the required score of the SLIPTA standard for quality clinical laboratory services. Moreover, laboratory service interruptions were very common in the two public hospitals in which clinical chemistry, serology and hematology tests were the most frequently interrupted. Shortage of reagents and supplies and inefficient laboratory management are the major causes of service interruptions. So, policymakers and other stakeholders should support continuous quality improvement for a better patient clinical outcome.
How organ-on-a-chip is advancing cancer research and oncology - a cancer hallmarks’ perspective
Authors: Avula Leela Rani , Grodzinski Piotr
Published: November 2024

Despite significant improvements in methodologies behind the development of new anticancer therapies, the path from early-stage drug development through preclinical and clinical development pipeline is still arduous. Further refinement of the current preclinical models and the development of complementing alternative techniques that enable more reliable studies are paramount. The emerging organ-on-a-chip (OoC) technologies are physiological-like organ biomimetic systems built on a microfluidic chip, capable of enabling precise control over various physicochemical and biomechanical parameters and helping recreate the natural physiology and mechanical forces that cells experience in the human body. In oncology research, especially, since cancer has been understood to be a dynamic disease featured by complex interactions between cancer cells and their environment, this technology offers added advantage as it is able to provide a dynamic platform to simulate cancer-on-a-chip emulating the biological context of tumor microenvironment (TME); demonstrating progression to metastases to multiorgans; and helping to unravel complex information that other current in vitro methods are otherwise not able to provide. In this contribution, we provide a biological perspective on the recent advances in the field of OoC models in cancer biology studies from a cancer hallmark perspective. We also discuss current prospects and funding opportunities in this space, as well as a possible future outlook from a biology perspective, including major challenges and new opportunities as a way forward to OoC technologies.
A bibliometric review of predictive modelling for cervical cancer risk
Authors: Ngema Francis , Mdhluli Bonginkosi , Mmileng Pako , Shungube Precious , Makgaba Mokgoropo , Hossana Twinomurinzi
Published: November 2024

Cervical cancer represents a significant public health challenge, particularly affecting women's health globally. This study aims to advance the understanding of cervical cancer risk prediction research through a bibliometric analysis. The study identified 800 records from Scopus and Web of Science databases, which were reduced to 142 unique records after removing duplicates. Out of 100 abstracts assessed, 42 were excluded based on specific criteria, resulting in 58 studies included in the bibliometric review. Multiple scoping methods such as thematic analysis, citation analysis, bibliographic coupling, natural language processing, Latent Dirichlet Allocation and other visualisation techniques were used to analyse related publications between 2013 and 2024. The key findings revealed the importance of interdisciplinary collaboration in cervical cancer risk prediction, integrating expertise from mathematical disciplines, biomedical health, healthcare practitioners, public health, and policy. This approach significantly enhanced the accuracy and efficiency of cervical cancer detection and predictive modelling by adopting advanced machine learning algorithms, such as random forests and support vector machines. The main challenges were the lack of external validation on independent datasets and the need to address model interpretability to ensure healthcare providers understand and trust the predictive models. The study revealed the importance of interdisciplinary collaboration in cervical cancer risk prediction. It made recommendations for future research to focus on increasing the external validation of models, improving model interpretability, and promoting global research collaborations to enhance the comprehensiveness and applicability of cervical cancer risk prediction models.
The ability of the Lab4 probiotic consortium to impact upon the functionality of serum deprived human keratinocytes in vitro
Authors: Thomas Sophie E. , Kerry-Smith Joshua , Plummer Susan F. , Bate Jack P. , John Daniel A. , Lawrence Evie , Powell Lydia , Dally Jordanna , Moseley Ryan , Michael Daryn R.
Published: November 2024

Introduction

Dysfunction of keratinocytes contributes to a weakened skin barrier and impaired wound healing capability. Evidence suggests that probiotic supplementation can lead to improved skin function in vitro and in vivo. The Lab4 probiotic consortium comprises of two strains of Lactobacillus species and two strains of Bifidobacterium species.

Methods

Using serum deprived conditions to impair the functionality of immortalized human HaCaT keratinocytes, this study aimed to assess the impact of metabolites derived from the Lab4 probiotic consortium on keratinocyte function.

Results

A significant improvement in HaCaT metabolic activity and lower apoptotic activity was observed in tandem with a reduction in Caspase-3 gene expression and a lower Bax/Bcl2 ratio following the addition of Lab4. The probiotic also supported barrier integrity which was better maintained with a significant increase in Filaggrin gene expression. In damaged keratinocytes, Lab4 enhanced rates of re-epithelialization, which were associated with significantly increased gene expression of MMP-1 and enhanced secretion of IL-6 and IL-8.

Discussion

These results suggest that the Lab4 probiotic consortium may have the ability to benefit the functionality of skin.
Implications of feed and seed costs in Asian seabass mariculture in the face of climate change
Authors: Divu Damodaran Nair , Mojjada Suresh Kumar , Sudhakaran Prateesh Omana , Sundaram Swathi Lekshmi Perumal , Menon Muktha , George Grinson , Tade Mayur Shivdas , Mojjada Ramesh Kumar , Radhakrishnan Kalidoss , Vishwambharan Vinuja Syamala , Shree Jai , Subramanian Aarsha , Ignatius Boby , Raghavan Suresh Vettath , Gopalakrishnan Achamveetil
Published: November 2024

Mariculture, a sustainable and rapidly growing aquaculture sub-sector, meets global seafood demand while reducing strain on wild fish stocks and continues to expand worldwide. However, rising feed and seed costs pose significant challenges, overshadowing other farming expenses. Climate change exacerbates the profitability of sea cage farming, increasing volatility. The surge in fishmeal costs has a detrimental impact on operational expenditure (Opex) and continues to be a threat. Consequently, sea cage farming in India is at a critical juncture, needing a balance between technological advancements and stakeholders’ fiscal needs. In this context, this study examines peer-reviewed synthesized data by employing metrics to evaluate the implications of feed and seed costs in Asian Seabass (Lates calcarifer) sea cage farming over a 10-year horizon. The total sales revenue over the 10-year period was US $100,848, with a net profit of US $55,198.89. A 30% increase in feed and seed prices significantly altered the economic dynamics of the enterprise, leading to an 8.8 and 9.2% rise in the respective break-even points. There was also a significant effect on the Benefit–Cost Ratio (BCR), with a 30% increase in each factor resulting in a 10 and 18% change in the projected BCR, respectively. Therefore, the significance of feed and seed cost has been established, necessitating an inevitable shift from low-value fish to formulated feed adaption for sustainable mariculture development. The study suggests improvements to existing practices to maximize efficiency and minimize production costs.
Carbon farming in the living soils of the Americas
Authors: Cerri Carlos Eduardo Pellegrino , Cherubin Maurício Roberto , Villela João Marcos , Locatelli Jorge Luiz , Carvalho Martha Lustosa , Villarreal Federico , de Castro Mello Francisco Fujita , Ibrahim Muhammad Akbar , Lal Rattan
Published: November 2024

Soil represents Earth’s largest terrestrial reservoir of carbon (C) and is an important sink of C from the atmosphere. However, the potential of adopting best management practices (BMPs) to increase soil C sequestration and offset greenhouse gas (GHG) emissions in agroecosystems remains unclear. Synthesizing available information on soil C sink capacity is important for identifying priority areas and systems to be monitored, an essential step to properly estimate large-scale C sequestration potential. This study brings an overview of thousands of research articles conducted in the Americas and presents the current state-of-the-art on soil C research. Additionally, it estimates the large-scale BMPs adoption impact over soil C dynamics in the region. Results indicated that soil C-related terms are widely cited in the literature. Despite that, from a total of ~13 thousand research articles recovered in the systematic literature review, only 9.2% evaluated soil C (at any depth), and only 4.6% measured soil C for the 0–30 cm soil layer, mostly conducted in North and South America regions. Literature review showed a low occurrence of terms related to BMPs (e.g., cover cropping), suggesting a research gap on the subject. Estimates revealed that upscaling of BMPs over 30% of agricultural land area (334 Mha) of the Americas can lead to soil C sequestration of 13.1 (±7.1) Pg CO2eq over 20 years, offsetting ~39% of agricultural GHG emissions over the same period. Results suggest that efforts should be made to monitor the impact of cropping system on soil C dynamics on the continents, especially in regions where data availability is low (e.g., Central, Caribbean, and Andean regions). Estimating the available degraded area for the continent and the soil C sequestration rates under BMPs adoption for Central, Andean, and Caribbean regions were major shortcomings encountered in our analysis. Thus, it is expected that some degree of uncertainty may be associated with the obtained results. Despite these limitations, upscaling of BMPs across the Americas suggests having great potential for C removal from the atmosphere and represents a global positive impact in terms of climate change mitigation and adaptation.
Simplifying the Animal Welfare Assessment Grid for enhanced accessibility
Authors: Kim Ji-yoon , Choi Jae-Hyeon , Ryu HyunYoung , Kang Hye-Jin
Published: November 2024

Ensuring animal welfare is essential for both the well-being of zoo animals and the effective management of zoological facilities. This study introduces the Simplified Animal Welfare Assessment Grid (S-AWAG), a streamlined adaptation of the original AWAG framework that integrates the Five Domains Model with an observation-based approach. Designed for non-expert users, S-AWAG focuses on easily observable welfare indicators—such as health and environmental conditions—making it particularly suitable for small, private zoos, including petting zoos, roadside zoos, indoor zoos, and animal cafés. We conducted welfare assessments on 304 animals from 11 species across nine zoos in South Korea. The results revealed significant differences in welfare standards between accredited and non-accredited zoos, with accredited facilities consistently demonstrating better welfare conditions (p < 0.05). The tool exhibited high inter-rater reliability (IRR = 0.839), confirming its consistency across assessors with varying levels of expertise and ensuring reliable and accurate results. Pearson correlation analysis identified strong positive associations between health and environmental factors, reinforcing the comprehensive nature of the tool’s evaluation approach. With its user-friendly, efficient, and adaptable design, S-AWAG has the potential to improve animal welfare standards not only in South Korea but also globally, particularly in smaller, resource-constrained facilities.
Research advancements on the diversity and host interaction of gut microbiota in chickens
Authors: Yue Yong , Luasiri Pichitpon , Li Jiezhang , Laosam Phanthipha , Sangsawad Papungkorn
Published: November 2024

The maintenance of host health and immune function is heavily dependent on the gut microbiota. However, the precise contribution of individual microbial taxa to regulating the overall functionality of the gut microbiome remains inadequately investigated. Chickens are commonly used as models for studying poultry gut microbiota, with high-throughput 16S rRNA sequencing has emerged as a valuable tool for assessing both its composition and functionality. The interactions between the gut’s microbial community and its host significantly influence health outcomes, disease susceptibility, and various mechanisms affecting gastrointestinal function. Despite substantial research efforts, the dynamic nature of this microbial ecosystem has led to inconsistencies in findings related to chicken gut microbiota, which is largely attributed to variations in rearing conditions. Consequently, the interaction between the chickens’ gut microflora and its host remains inadequately explored. This review highlights recent advances in understanding these relationships, with a specific focus on microbial composition, diversity, functional mechanisms, and their potential implications for improving poultry production.
Overcoming Lung Challenges in TA-NRP Assisted Heart Recovery in Donation After the Circulatory Determination of Death
Authors: Royo-Villanova Mario , Moya Sánchez José , Ortín Freire Alejandro , De Gea García Jose H. , Rebollo Acebes Sergio , Moreno Flores Alba , Blanco Morillo Juan , Cánovas Sergio , Domínguez-Gil Beatriz
Published: November 2024

Thoraco-abdominal normothermic regional perfusion (TA-NRP), utilizing Extra Corporeal Membrane Oxygenation (ECMO) devices, has emerged as an effective strategy for heart recovery in donors declared dead by circulatory criteria (DCDD). After death declaration, TA-NRP restores heart activity by reperfusing the arrested heart with oxygenated blood at normothermia. Mechanical ventilation resumption in the donor enables weaning from ECMO and restores systemic circulation and oxygenation using the donor’s heart and lungs. However, if pre-existing conditions prevent the donor’s lungs from oxygenating blood post-cardiac activity restoration, weaning from veno-arterial ECMO may lead to systemic hypoxia, jeopardizing the restored cardiac function. Anticipating this scenario may guide planning a split ECMO circuit to facilitate earlier and more effective recovery of donor heart function post-ECMO weaning. This manuscript describes three cases of DCDD donors with hypoxic respiratory failure undergoing TA-NRP for heart recovery. By establishing a bridge in the arterial portion of the circuit, clamped out after weaning from veno-arterial ECMO, donor heart function was assessed exclusively with veno-venous ECMO support, leading to successful heart transplantation.
Study on the Mechanism of Agricultural Greenhouse Gas Emission Reduction Under Macro Emission Reduction Measures
Authors: Gong Zeyu , Huo Xuexi
Published: November 2024

Clarifying the impact of macro emission reduction measures on the mechanism of agricultural greenhouse gas emission reduction is of great significance in promoting climate change governance and the construction of a carbon emission reduction policy system. This paper explores the mechanism of important macro emission reduction measures based on a multi-level progressive factor decomposition perspective and designs a coupled model of computable general equilibrium and structural path decomposition to identify the key emission reduction paths of major macro emission reduction measures and to decompose the drivers that promote emission reduction in each path. This study found that: (1) The emission reduction effect of the combination of carbon tax, carbon sink and carbon capture, utilization, and storage macro emission reduction measures is dominated by the indirect emission reduction triggered by the industrial chain, accounting for 95.67% of the total agricultural GHG emission reduction, and the emission reduction effect is gradually weakened with the increase in the production level. (2) The emission intensity effect and the industrial structure effect are the main drivers of the macro emission reduction portfolio measures to promote emission reduction, but there are differences in the roles of the different drivers on the various production levels and different emission reduction pathways. (3) Vegetables, fertilizers, the light industry, and other key industries are the main agricultural greenhouse gas emission reduction contributing industries, of which the emission reduction contribution from citizen consumption is the largest, and the emission reduction is mainly achieved by influencing the demand path of the vegetable industry and the light industry to the upstream high-energy-consuming or high-emission industries. Therefore, there is a need to fully utilize the mechanisms that drive emission reduction at different production levels and pathways by each key factor and to take targeted measures to promote synergistic emission reduction among industries. In the short term, focus on enhancing the role of the emission intensity effect, while in the medium and long term, pay much attention to the positive role of the industrial structure effect on agricultural greenhouse gas emissions.
The Role of Sodium Alginate Hydrogel in Maintaining Soil Homeostasis Exposed to Sulcotrione
Authors: Baćmaga Małgorzata , Wyszkowska Jadwiga , Kucharski Jan
Published: November 2024

Herbicides are the most widely used agrochemicals in crop protection, which has led to serious environmental pollution around the world, including soil ecosystems. It is important to look for new solutions that lead to an improvement in soil quality, even if only through the use of hydrogels. The aim of this study was therefore to determine the effect of sodium alginate on the microbiological and biochemical properties of sulcotrione-treated soil. It was found that both the herbicide and the sodium alginate had a significant effect on the soil environment. An amount of 10 g kg−1 of sodium alginate was applied to the soil, while sulcotrione was applied to the soil in the following amounts: 0.00 (C), 0.200 (R), 0.999 (5R), and 9.999 mg kg−1 (50R). Sulcotrione stimulated the activity of dehydrogenases, catalase, arylsulfatase, and β-glucosidase and inhibited the activities of alkaline phosphatase, acid phosphatase, and urease as well as the proliferation of organotrophic bacteria, actinobacteria, and fungi. This caused an increase in the colony development index (CD) of organotrophic bacteria and fungi and decreased the colony development index value of actinobacteria. It also increased the value of the ecophysiological diversity index (EP) of fungi. The addition of sodium alginate to the soil increased the numbers of organotrophic bacteria, actinobacteria, and fungi as well as the activities of dehydrogenases, catalase, urease, alkaline phosphatase, and arylsulfatase. The hydrogel had different effects on β-glucosidase activity. Acid phosphatase showed a significant decrease in activity after the addition of sodium alginate to the soil. Under the influence of sodium alginate, there was an increase in the index of colony development of actinobacteria and fungi, while there were decreases in organotrophic bacteria and the index of ecophysiological diversity of actinobacteria and fungi. The proliferation of microorganisms and the enzymatic activity of the soil changed over time both in soil enriched with sodium alginate and without its addition. This study may be useful for evaluating the effects of sulcotrione on the microbiological and biochemical properties of soil and the effectiveness of sodium alginate in improving the quality of soil exposed to sulcotrione.
Mastitis Classification in Dairy Cows Using Weakly Supervised Representation Learning
Authors: Cho Soo-Hyun , Lee Mingyung , Lee Wang-Hee , Seo Seongwon , Lee Dae-Hyun
Published: November 2024

Detecting mastitis on time in dairy cows is crucial for maintaining milk production and preventing significant economic losses, and machine learning has recently gained significant attention as a promising solution to address this issue. Most studies have detected mastitis on time series data using a supervised learning model, which requires the scale of labeled data; however, annotating the onset of mastitis in milking data from dairy cows is very difficult and costly, while supervised learning relies on accurate labels for ensuring the performance. Therefore, this study proposed a mastitis classification based on weakly supervised representation learning using an autoencoder on time series milking data, which allows for concurrent milking representation learning and weakly supervision with low-cost labels. The proposed method employed a structure where the classifier branches from the latent space of a 1D-convolutional autoencoder, enabling representation learning of milking data to be conducted from the perspective of reconstructing the original information and detecting mastitis. The branched classifier backpropagate the mastitis symptoms, which are less costly than mastitis diagnosis, during the encoder’s representation learning. The results showed that the proposed method achieved an F1-score of 0.6 that demonstrates performance comparable to previous studies despite using low-cost labels. Our method has the advantage of being easily reproducible across various data domains through low-cost annotation for supervised learning and is practical as it can be implemented with just milking data and weak labels, which can be collected in the field.
Defoliation Categorization in Soybean with Machine Learning Algorithms and UAV Multispectral Data
Authors: Ferraz Marcelo Araújo Junqueira , Santiago Afrânio Gabriel da Silva Godinho , Bruzi Adriano Teodoro , Vilela Nelson Júnior Dias , Ferraz Gabriel Araújo e Silva
Published: November 2024

Traditional disease severity monitoring is subjective and inefficient. This study employs a Parrot multispectral sensor mounted on an unmanned aerial vehicle (UAV) to apply machine learning algorithms, such as random forest, for categorizing defoliation levels in R7-stage soybean plants. This research assesses the effectiveness of vegetation indices, spectral bands, and relative vegetation cover as input parameters, demonstrating that machine learning approaches combined with multispectral imagery can provide a more accurate and efficient assessment of Asian soybean rust in commercial soybean fields. The random forest algorithm exhibited satisfactory classification performance when compared to recent studies, achieving accuracy, precision, recall, F1-score, specificity, and AUC values of 0.94, 0.92, 0.92, 0.92, 0.97, and 0.97, respectively. The input variables identified as most important for the classification model were the WDRVI and MPRI indices, the red-edge and NIR bands, and relative vegetation cover, with the highest Gini importance index.
Accurate Phase Calibration of Multistatic Imaging System for Medical and Industrial Applications
Authors: Tabata Hiroshi , Asakawa Makoto R. , Yamaguchi Soichiro
Published: November 2024

Multistatic imaging systems are commonly used in radar systems and microwave imaging. In these systems, many antennas are arranged three-dimensionally and connected to RF switches. The length of each transmitter (Tx) and receiver (Rx) channel differs slightly, causing artifacts in high-resolution image reconstruction. This study presents a novel method for the phase calibration of multistatic systems. This method does not require system reconstruction and can automatically perform phase calibration in a short time. This method is expected to facilitate an accurate phase measurement in multistatic systems. The approach involves phase calibration by analyzing the reflection coefficients of antenna elements in the time domain. Imaging experiments were performed on a multistatic imaging system using this calibration method, and the position and shape of a metal rod with a diameter one-fourth of a wavelength were reconstructed by simple back-projection with an accuracy beyond the diffraction limit.
Propagation, Scattering and Defect Detection in a Circular Edge with Quasi-Edge Waves
Authors: Liang Peifeng , Kotousov Andrei , Ng Ching Tai
Published: November 2024

Structural components with curved edges are common in many engineering designs. Fatigue cracks, corrosion and other types of defects and mechanical damage often initiate from (or are located close to) edges. Damage and defect detection in the presence of complex geometry represents a significant challenge for non-destructive testing (NDT). To address this challenge, this paper investigates the fundamental mode of the quasi-symmetric edge-guided wave (QES0) propagating along a curved edge, as well as its scattering characteristics in the presence of different types of edge defects. The finite element (FE) approach is used to investigate the propagation and mode shapes of the QES0. It was found that the wave attenuation dramatically increases when the radius-to-thickness ratio is less than 20. Moreover, the mode shapes are significantly affected by the waveguide curvature as well as the excitation frequency. Additionally, to evaluate the sensitivity of QES0 to edge defects, different sizes of edge defects were investigated with the FE model, which validated against experimental results. The validated FE model was further employed to quantify the dependence of the amplitude of scattered waves for different types of edge defects. These studies indicate that the amplitude of scattered wave is very sensitive to the presence of edge defects. The main outcome of this work is the demonstrated ability of the QES0 wave mode to propagate over long distances and a high sensitivity of this mode to different types of edge defects, which manifest its great potential for detecting and characterising damage near the curved edges of structural components.
Novel Q-Carbon Anodes for Sodium-Ion Batteries
Authors: Pethe Saurabh Prakash , Sahoo Siba Sundar , Ganesan Arvind , Meyer Harry M. , Sun Xiao-Guang , Narayan Jagdish , Paranthaman Mariappan Parans
Published: November 2024

The lack of a standard anode for sodium-ion batteries (SIBs) has greatly hindered their applications. Herein, we show that a novel phase of carbon, namely Q-carbon, is an effective anode material for sodium-ion batteries. The Q-carbon, which is a metastable phase of carbon consisting of about 80% sp3- and 20% sp2-bonded carbon, is synthesized by nonequilibrium pulsed laser annealing and arc-discharge methods. Two types of Q-carbons, Q1 and Q2, were evaluated as anode material for SIBs. Q1 had a slow quench and was used as the control, whereas Q2 was Q-carbon with a rapid quenching. Q1 exhibits a high initial columbic efficiency of 81% and a low-capacity retention of less than 60%, whereas Q2 has a low initial columbic efficiency of 58% and a high-capacity retention of 81%. Q2 exhibits a stable capacity of 168 mAh·g−1 at a cycling rate of C/3 (124 mA·g−1), which is comparable to other hard carbon anodes reported in the literature. This unique synthesis method opens a pathway for the further tuning of Q-carbon with higher trapping/charging of Na+ ions in improved SIBs.
Temporal Structure of Bouts in Men’s Olympic Boxing: Featherweight, Lightweight, Welterweight, Light Heavyweight, and Heavyweight Categories
Authors: Gutiérrez-Santiago Alfonso , Morquillas-Riobó Miguel , Reguera-López-de-la-Osa Xoana , Silva-Pinto Antonio José , Argibay-González Juan Carlos , Prieto-Lage Iván
Published: November 2024

Background: Men’s Olympic boxing follows a regulatory temporal structure, but previous studies have shown that this structure varies during competitions. However, these investigations have not thoroughly analyzed the differences in bout development according to weight category. Additionally, most studies have focused on a limited number of categories, leaving gaps in the temporal analysis of various categories. Aim: To determine the temporal structure in the featherweight, lightweight, welterweight, light heavyweight, and heavyweight categories of men’s Olympic boxing, in order to establish models that can help adjust training to meet competitive demands. Methods: An observational approach was used, analyzing 73 bouts involving 80 boxers who competed in the 2020 Tokyo Olympic Games. Results: Most bouts ended after the completion of the full regulation time across all categories. The most common actions were short punching sequences (two to five punches), occurring mainly in the center of the ring. Differences between weight categories were minimal, with the welterweight category showing the most variability. Conclusion: This study presents temporal models that will help coaches and boxers adjust their training with greater precision, improving the efficiency of training sessions according to competitive objectives.
Towards a System Dynamics Model on Risk Factors of Knee Osteoarthritis: A Study Protocol for the DYNAMIKOS Model
Authors: Tsarbou Charis , Liveris Nikolaos I. , Papageorgiou George , Kvist Joanna , Tsepis Elias , Billis Evdokia , Gliatis John , Xergia Sofia A.
Published: November 2024

(1) Background: Osteoarthritis (OA) is a serious chronic disease mostly affecting the knee joint. Despite the many efforts for developing strategies to predict and control Knee Osteoarthritis (KOA), the disease is on the rise. This paper describes the process for the creation of a simulation model, the Dynamic Knee Osteoarthritis Simulation (DYNAMIKOS) model, that captures the complex interrelationships of the risk factors for the development of KOA; (2) Methods: The DYNAMIKOS model will be based on the System Dynamics approach. The first step will be to develop a Causal Loop Diagram (CLD) model for the risk factors involved incorporating a series of Group Modeling Building (GMB) workshops with experts and stakeholders. Using data from a representative sample of KOA patients, the statistical approaches Exploratory Factor Analysis, Confirmatory Factor Analysis, and Structural Equation Modeling (SEM) will be carried out. (3) Results: This study will develop a simulation System Dynamics model for the risk factors of KOA based on the results of CLD and SEM; (4) Conclusions: The proposed DYNAMIKOS model could be used for effectively analyzing the complex interrelationships among the multiple factors that constitute the spread of KOA. In this way, plausible prevention strategies could be implemented for effectively managing and leading the potential eradication of KOA.
Spatiotemporal Analysis of Light Purse Seine Fishing Vessel Operations in the Arabian High Seas Based on Automatic Identification System Data
Authors: Yang Shenglong , Yu Linlin , Jiang Keji , Fan Xiumei , Wan Lijun , Fan Wei , Zhang Heng
Published: November 2024

Understanding the dynamic spatial distribution and characteristics of fishing activities is crucial for fisheries management and sustainable development. In recent years, small pelagic fish and cephalopods in the Arabian Sea have become new targets for light purse seine fishing; however, there is a lack of publicly available reports. This study uses automatic identification system (AIS) data from January to May and October to December of 2021 to 2022 in the region between 58°–70° E and 10°–22° N to extract spatial distribution information through three methods. The results show that with a spatial resolution of 0.25° × 0.25°, the spatial similarity index between the fishing ground information extracted in 2022 and catch data was consistently above 0.60, reaching 0.76 in March 2021 and 0.79 in November 2022, while the spatial similarity index in March 2022 exceeded 0.71. The spatial distribution of fishing effort and kernel density was similar to that of the fishing grounds, and the fishing intensity information exhibited the highest spatiotemporal similarity with commercial catch data, making it more suitable as a substitute for fishery data. Therefore, effective international cooperation and efficient joint management mechanisms for fishing vessels are needed to enhance the regulatory oversight of fishing vessels in this region. Integrating AIS data with other technological methods is crucial for more effective monitoring and management of fishing vessels. The findings presented in this paper provide both quantitative and qualitative scientific support for resource conservation and sustainable development in the region.
Theoretical Analysis of Shaft Wall Damage and Failure Under Impacting of Ore-Rock Falling in Vertical Ore Pass
Authors: Ma Qiangying , Ma Chi , Li Jiaoqun , Lu Zengxiang , Xia Zhiguo
Published: November 2024

The impact of ore-rock blocks on the shaft wall of a vertical ore pass is a crucial cause of shaft wall damage and failure. Based on the structure and parameters of the ore pass in a case mine, the first collision’s position of the ore-rock block with respect to the ore pass wall and the angle between the impacting direction of the ore-rock block and the horizontal plane before and after the collision are investigated via a kinematic analysis. The normal and tangential analysis models of ore rock impacting the shaft wall are established and analyzed based on contact mechanics. The results show that: (1) based on the kinematic analysis of ore rock moving in the ore pass and on the colliding condition of the ore-rock block the first time that it collides with the ore pass wall, the coordinates and angles of the collision are proposed; (2) the impacting process of ore rock is categorized into elastic compression, elastic–plastic compression, and rebound of the shaft wall material. The relationship between the normal impact force and the penetrating depth is determined, and the slipping distance of the ore-rock block along the shaft wall and the lost volume of the shaft material are established. (3) The wall material’s normal, tangential, and total restitution coefficient is acquired. (4) The total lost volume during the collision is obtained through the analysis and solution of the model. (5) Based on the characteristics and parameters of the ore pass in the case mine, the influence of the impact velocity and angle of the ore-rock block on the restitution coefficient, maximum normal intrusion depth, maximum tangential displacement, and volume loss of the shaft wall are analyzed by using relevant formulas.
Advanced Virtual Fit Technology for Precision Pressure Application in Medical Compression Waistbands
Authors: Youn Seonyoung , Zhan Sheng , Mathur Kavita
Published: November 2024

The design of medical-grade compression garments is essential for therapeutic efficacy, requiring precise pressure distribution on specific body areas. This study evaluates the effectiveness of virtual fit technology, focusing on CLO3D, in designing these garments. Simulated strain and pressure values from CLO3D were compared to experimental measurements, alongside the development of a CP model using CLO3D’s digitized stretch stiffness (Youn’s CP model). Using a 3D-scanned manikin, the mechanical behavior of eight knit fabrics, including composite structures, was assessed under strain of 5%, 10%, 15%, and 20%. The results showed that CLO3D’s built-in pressure simulation overestimated the pressure, especially in plaited fabrics such as SJP and INTP, with discrepancies of up to 10 kPa at strain levels above 15%. In contrast, the experimental pressure measurements using the Kikuhime and PPS sensors varied within 0.13 to 2.59 kPa. Youn’s CP model provided a closer fit to the experimental data, with deviations limited to within 1.9 kPa. This finding highlights the limitations of CLO3D for precision-required applications and underscores the need for more advanced, customized algorithms in virtual fit technology to ensure reliable compression garment design, particularly in medical contexts, where precise pressure control is critical for patient outcomes.