bluuebunny/crossref_metadata_2025 huggingface dataset:
Millets have the potential to increase satiety and reduce the feeling of hunger: a systematic review
Authors: Anitha Seetha , Upadhyay Shweta , Kane-Potaka Joanna
Published: June 2024

A systematic review was conducted to understand the satiety value of millets and their ability to lessen the feeling of hunger. Only six eligible studies had the relevant information for this analysis. These studies compared millet-based foods with refined rice, potatoes, wheat, oats, and rye and found that millets have the potential to lower the hunger index. The proposed mechanism suggests that millets’ richness in fiber is responsible for increasing gastric volume and prolonging gastric emptying time. Millet-based food stays longer in the stomach, thereby prolonging the feeling of satiety or fullness. Fiber also helps to slow down the release of glucose into the blood. Furthermore, the protein in millets increases insulin sensitivity, which also reduces the glucose response. This proposed mechanism, which increases satiety and delays the glucose response, is responsible for lowering the blood lipid profile and promoting weight loss.
Expanding access to veterinary clinical decision support in resource-limited settings: a scoping review of clinical decision support tools in medicine and antimicrobial stewardship
Authors: Yusuf Havan , Hillman Alison , Stegeman Jan Arend , Cameron Angus , Badger Skye
Published: June 2024

Introduction

Digital clinical decision support (CDS) tools are of growing importance in supporting healthcare professionals in understanding complex clinical problems and arriving at decisions that improve patient outcomes. CDS tools are also increasingly used to improve antimicrobial stewardship (AMS) practices in healthcare settings. However, far fewer CDS tools are available in lowerand middle-income countries (LMICs) and in animal health settings, where their use in improving diagnostic and treatment decision-making is likely to have the greatest impact. The aim of this study was to evaluate digital CDS tools designed as a direct aid to support diagnosis and/or treatment decisionmaking, by reviewing their scope, functions, methodologies, and quality. Recommendations for the development of veterinary CDS tools in LMICs are then provided.

Methods

The review considered studies and reports published between January 2017 and October 2023 in the English language in peer-reviewed and gray literature.

Results

A total of 41 studies and reports detailing CDS tools were included in the final review, with 35 CDS tools designed for human healthcare settings and six tools for animal healthcare settings. Of the tools reviewed, the majority were deployed in high-income countries (80.5%). Support for AMS programs was a feature in 12 (29.3%) of the tools, with 10 tools in human healthcare settings. The capabilities of the CDS tools varied when reviewed against the GUIDES checklist.

Discussion

We recommend a methodological approach for the development of veterinary CDS tools in LMICs predicated on securing sufficient and sustainable funding. Employing a multidisciplinary development team is an important first step. Developing standalone CDS tools using Bayesian algorithms based on local expert knowledge will provide users with rapid and reliable access to quality guidance on diagnoses and treatments. Such tools are likely to contribute to improved disease management on farms and reduce inappropriate antimicrobial use, thus supporting AMS practices in areas of high need.
Effectiveness of animal-assisted activities and therapies for autism spectrum disorder: a systematic review and meta-analysis
Authors: Xiao Ningkun , Bagayi Vaishnavi , Yang Dandan , Huang Xinlin , Zhong Lei , Kiselev Sergey , Bolkov Mikhail A. , Tuzankina Irina A. , Chereshnev Valery A.
Published: June 2024

Background

Given the rising interest in complementary therapeutic strategies for autism spectrum disorder (ASD), this research aims to provide a comprehensive analysis of the impact of animal-assisted activities and therapies (AAAT) on various ASD symptoms.

Methods

A meticulous search of databases, including Scopus and PubMed, was conducted to gather relevant research on AAAT for ASD. This process led to the selection of 45 studies encompassing 1,212 participants. The chosen studies were then subjected to a meta-analysis to evaluate the efficacy of AAAT in alleviating core ASD symptoms.

Results

The meta-analysis revealed significant improvements in several core ASD symptoms due to AAAT. Notably, there were improvements in social communication (MD = −4.96, 95% CI [−7.49, −2.44]), irritability (MD = −2.38, 95% CI [−4.06, −0.71]), hyperactivity (MD = −4.03, 95% CI [−6.17, −1.89]), and different word usage skills (MD = 20.48, 95% CI [7.41, 33.55]). However, social awareness (MD = −1.63, 95% CI [−4.07, 0.81]), social cognition (MD = −3.60, 95% CI [−9.36, 2.17]), social mannerisms (MD = −0.73, 95% CI [−2.55, 1.09]), social motivation (MD = −1.21, 95% CI [−2.56, 0.13]), lethargy (MD = −1.12, 95% CI [−3.92, 1.68]), and stereotypical behaviors (MD = −0.23, 95% CI [−1.27, 0.80]) did not significantly improve.

Conclusion

The study demonstrates the potential of AAAT in improving certain core symptoms of ASD, such as social communication, irritability, hyperactivity, and word usage skills. However, the effectiveness of AAAT in other ASD symptom domains remains uncertain. The research is limited by the absence of long-term follow-up data and a high risk of bias in existing studies. Therefore, while the findings indicate the promise of AAAT in specific areas, caution is advised in generalizing its efficacy across all ASD symptoms.
Hepatic vascular hamartoma in a cat: a case report with literature review
Authors: Negoescu Andrada , Gal Claudiu , Bărbulescu Andra , Vulcan Elena , Rădulescu Alice , Cătoi Cornel , Taulescu Marian
Published: June 2024

Vascular hamartomas represent a focal proliferation of disorganized vascular tissue, which is usually present at birth. An 8-month-old Scottish fold female cat presented with abdominal distention, mild dyspnea, pale mucous membranes, and lethargy. Ultrasound examination revealed a hepatic mass resembling multiple cysts affecting the right medial lobe. Surgical excision was performed, and tissue samples were sent for histopathological evaluation. The mass was composed of multiple, dilated, variably-sized well-differentiated arterioles and venules, consistent with vascular hamartoma. Immunohistochemical investigation of the cells lining the cystic structures showed positive immunolabeling for vimentin and negative immunolabeling for PanCK, supporting the histological diagnosis. Based on existing literature, this represents the first case of hepatic localization of vascular hamartoma in a cat. In addition, a comparative histological study between vascular hamartoma and biliary duct hamartoma and a review on hepatic vascular hamartomas in animals and hepatic cystic masses in cats was made.
Synergistic Activity of Temocillin and Fosfomycin Combination against KPC-Producing Klebsiella pneumoniae Clinical Isolates
Authors: Costantino Venera , Principe Luigi , Mehat Jai , Busetti Marina , Piccirilli Alessandra , Perilli Mariagrazia , Luzzati Roberto , Zerbato Verena , Meliadò Antonietta , La Ragione Roberto , Di Bella Stefano
Published: June 2024

Infections caused by KPC-producing K. pneumoniae continue to pose a significant clinical challenge due to their emerging resistance to new antimicrobials. We investigated the association between two drugs whose roles have been repurposed against multidrug-resistant bacteria: fosfomycin and temocillin. Temocillin exhibits unusual stability against KPC enzymes, while fosfomycin acts as a potent “synergizer”. We conducted in vitro antimicrobial activity studies on 100 clinical isolates of KPC-producing K. pneumoniae using a combination of fosfomycin and temocillin. The results demonstrated synergistic activity in 91% of the isolates. Subsequently, we assessed the effect on Galleria mellonella larvae using five genetically different KPC-Kp isolates. The addition of fosfomycin to temocillin increased larvae survival from 73 to 97% (+Δ 32%; isolate 1), from 93 to 100% (+Δ 7%; isolate 2), from 63 to 86% (+Δ 36%; isolate 3), from 63 to 90% (+Δ 42%; isolate 4), and from 93 to 97% (+Δ 4%; isolate 10). Among the temocillin-resistant KPC-producing K. pneumoniae isolates (24 isolates), the addition of fosfomycin reduced temocillin MIC values below the resistance breakpoint in all isolates except one. Temocillin combined with fosfomycin emerges as a promising combination against KPC-producing K. pneumoniae, warranting further clinical evaluation.
Integration of Antioxidant Activity Assays Data of Stevia Leaf Extracts: A Systematic Review and Meta-Analysis
Authors: Papaefthimiou Maria , Kontou Panagiota I. , Bagos Pantelis G. , Braliou Georgia G.
Published: June 2024

Stevia rebaudiana Bertoni, a no-calorie natural sweetener, contains a plethora of polyphenols that exert antioxidant properties with potential medicinal significance. Due to the variety of functional groups, polyphenols exhibit varying solubility depending on the nature of the extraction solvents (water, organic, or their mixtures, defined further on as hydroalcoholic extracts). In the present study, we performed a systematic review, following PRISMA guidelines, and meta-analysis, synthesizing all available data from 45 articles encompassing 250 different studies. Our results showed that the total phenolic content (TPC) of hydroalcoholic and aqueous extracts presents higher values (64.77 and 63.73 mg GAE/g) compared to organic extracts (33.39). Total flavonoid content (TFC) was also higher in aqueous and hydroalcoholic extracts; meta-regression analysis revealed that outcomes in different measuring units (mg QE/g, mg CE/g, and mg RUE/g) do not present statistically significant differences and can be synthesized in meta-analysis. Using meta-regression analysis, we showed that outcomes from the chemical-based ABTS, FRAP, and ORAC antioxidant assays for the same extract type can be combined in meta-analysis because they do not differ statistically significantly. Meta-analysis of ABTS, FRAP, and ORAC assays outcomes revealed that the antioxidant activity profile of various extract types follows that of their phenolic and flavonoid content. Using regression meta-analysis, we also presented that outcomes from SOD, CAT, and POX enzymatic antioxidant assays are independent of the assay type (p-value = 0.905) and can be combined. Our study constitutes the first effort to quantitatively and statistically synthesize the research results of individual studies using all methods measuring the antioxidant activity of stevia leaf extracts. Our results, in light of evidence-based practice, uncover the need for a broadly accepted, unified, methodological strategy to perform antioxidant tests, and offer documentation that the use of ethanol:water 1:1 mixtures or pure water can more efficiently extract stevia antioxidant compounds.
Image Detection Network Based on Enhanced Small Target Recognition Details and Its Application in Fine Granularity
Authors: Fu Qiang , Tao Xiaoping , Deng Weijie , Liu Hongliang
Published: June 2024

Image detection technology is of paramount importance across various fields. This significance is not only seen in general images with everyday scenes but also holds substantial research value in the field of remote sensing. Remote sensing images involve capturing images from aircraft or satellites. These images typically feature diverse scenes, large image formats, and varying imaging heights, thus leading to numerous small-sized targets in the captured images. Accurately identifying these small targets, which may occupy only a few pixels, is a challenging and active research area. Current methods mainly fall into two categories: enhancing small target features by improving resolution and increasing the number of small targets to bolster training datasets. However, these approaches often fail to address the core distinguishing features of small targets in the original images, thus resulting in suboptimal performance in fine-grained classification tasks. To address this situation, we propose a new network structure DDU (Downsample Difference Upsample), which is based on differential and resolution changing methods in the Neck layer of deep learning networks to enhance the recognition features of small targets, thus further improving the feature richness of recognition and effectively solving the problem of low accuracy in small target object recognition. At the same time, in order to take into account the recognition effect of targets of other sizes in the image, a new attention mechanism called PNOC (protecting the number of channels) is proposed, which integrates small target features and universal object features without losing the number of channels, thereby increasing the accuracy of recognition. And experimental verification was conducted on the PASCAL-VOC dataset. At the same time, it was applied to the testing of the fine-grained MAR20 dataset and found that the performance was better than other classic algorithms. At the same time, because the proposed framework belongs to a one-stage detection method, it has good engineering applicability and scalability, and universality in scientific research applications are good. Through comparative experiments, it was found that our algorithm improved the performance of the mAP by 0.7% compared to the original YOLOv8 algorithm.
A Spatial Analysis of Urban Tree Canopy Using High-Resolution Land Cover Data for Chattanooga, Tennessee
Authors: Mix Charles , Hunt Nyssa , Stuart William , Hossain A.K.M. Azad , Bishop Bradley Wade
Published: June 2024

Urban tree canopy (UTC) provides urban residents with numerous benefits, including positive mental and physical health, the mitigation and prevention of urban heat islands, and a sense of place. Numerous studies have shown that as the wealth of a community decreases, so does the amount of UTC found in the community; thus, wealthier communities are more likely to enjoy the benefits that urban forests provide. Emerging technologies in remote sensing and GIS are allowing for new opportunities to study and understand the relationships between urban neighborhoods and UTC. In this study, land cover data for Chattanooga, Tennessee were derived from high-resolution (50 cm) multispectral imagery to assess the previously unknown extent and distribution of UTC and to measure the extent of UTC by neighborhood and census block group level. Using exploratory regression analysis, variables representing income, population density, race, educational attainment, and urban heat islands were analyzed to investigate the influence of UTC on neighborhood characteristics. This study found that UTC represented half of the total land cover composition, the tree equity was not as profound as shown in other cities, and the lack of UTC likely influences the prevalence of urban heat islands. This study also shows the importance and utility of using high-resolution imagery and land cover to assess and understand the impact and distribution of UTC in urban environments.
Machine Learning-Driven Calibration of Traffic Models Based on a Real-Time Video Analysis
Authors: Lopukhova Ekaterina , Abdulnagimov Ansaf , Voronkov Grigory , Grakhova Elizaveta
Published: June 2024

Accurate traffic simulation models play a crucial role in developing intelligent transport systems that offer timely traffic information to users and efficient traffic management. However, calibrating these models to represent real-world traffic conditions accurately poses a significant challenge due to the dynamic nature of traffic flow and the limitations of traditional calibration methods. This article introduces a machine learning-based approach to calibrate macroscopic traffic simulation models using real-time traffic video stream data. The proposed method for creating and calibrating a traffic simulation model has significantly improved the statistical correspondence between the generated vehicle characteristics and real data about cars on the simulated road section. The correspondence has increased from 37% to 73%. Machine learning models trained on generated data and tested on real data show improved accuracy rates. Mean absolute error, mean square error, and mean absolute percentage error decreased by more than two orders of magnitude. The coefficient of determination has also increased, approaching 1. This method eliminates the need to deploy wireless sensor networks, which can reduce the cost of implementing intelligent transport systems.
Blockchain-Based Quality Assurance System for Academic Programs
Authors: Alkhatib Mohammad , Albalawi Talal , Saeed Fahman
Published: June 2024

Nowadays, technology is increasingly being adopted in different kinds of businesses to process, store, and share sensitive information in digital environments that include enormous numbers of users. However, this has also increased the likelihood of cyberattacks and misuse of information, potentially causing severe damage. One promising technology, which can provide the required security services with an improved level of efficiency, is blockchain. This research explores the use of Ethereum blockchain and smart contracts to create a secure and efficient quality assurance system (QAS) for academic programs. By utilizing blockchain and smart contracts, the proposed approach improves the integrity and reliability of sensitive information processed by the QAS, promotes transparency and governance, and reduces the time and effort required for quality operations. The current approach uses an additional access control layer to further enhance user privacy. Smart contracts automate various quality transactions and saves time and resources, and hence increases the efficiency of the QAS. The interplanetary file system (IPFS) is used to address the challenge of size limitations in blockchain. Additionally, this research investigates the use of various cryptographic schemes to provide robust security services at the application layer. The experimental results showed that the use of a hybrid cryptosystem relying on an Elliptic curve digital signature and AES encryption (AES_ECCDSA) outperforms other counterparts’ cryptosystems using an RSA digital signature and AES encryption (AES_RSADSA) and Elliptic Curve Integrated Encryption Scheme (ECIES) in terms of speed. The performance results showed that AES_ECCDSA consumes 188 ms to perform the required cryptographic operations for a standard-quality document with a size of 8088 KB, compared to the 231 ms and 739 ms consumed by the AES_RSADSA and ECIES schemes, respectively. This study presents a prototype implementation of the blockchain-based QAS, which outlines the processing model and system requirements for key QAS processes. It has been found that the cost and time required for blockchain operations vary depending on the size of the input data—a larger data size requires more time and costs more to process. The results of the current study showed that the time delay for blockchain transactions ranges from 15 to 120 s, while the cost ranges from USD 50 to USD 400. This research provides evidence that blockchain and smart contract technologies have the potential to create a secure, efficient, and trustworthy QAS environment for academic programs.
Developing the NLP-QFD Model to Discover Key Success Factors of Short Videos on Social Media
Authors: Wu Hsin-Cheng , Jeng Wu-Der , Chen Long-Sheng , Ho Cheng-Chin
Published: June 2024

In the transition from television to mobile devices, short videos have emerged as the primary content format, possessing tremendous potential in various fields such as marketing, promotion, education, advertising, and so on. However, from the available literature, there is a lack of studies investigating the elements necessary for the success of short videos, specifically regarding what factors need to be considered during production to increase viewership. Therefore, this study proposed the NLP-QFD model, integrating Natural Language Processing (NLP), Latent Dirichlet Allocation (LDA), and Quality Function Deployment (QFD) methods. Real short videos from mainstream Western media (CNN) and regional media (Middle East Eye) will be employed as case studies. In addition to analyzing the content of short videos and audiences’ reviews, we will utilize the NLP-QFD model to identify the key success factors (KSFs) of short videos, providing guidance for future short video creators, especially for small-scale businesses, to produce successful short videos and expand their influence through social media. The results indicate that the success factors for short videos include the movie title, promotion, reviews, and social media. For large enterprises, endorsements by famous individuals are crucial, while music and shooting are key elements for the success of short videos for small businesses.
Optimizing Construction Engineering Management Using Metaheuristic Methods and Bayesian Networks
Authors: Jakubczyk-Gałczyńska Anna , Siemaszko Agata , Poltavets Maryna
Published: June 2024

The construction of buildings invariably involves time and costs, and disruptions impact ongoing construction projects. Crisis situations in management strategies, structural confusion, and financial miscalculations often arise due to misguided decision-making. This article proposes a method that combines the learning of Bayesian Networks and heuristic techniques to optimize decision-making processes in construction scheduling. As an innovative approach in order to enhance construction management, the functioning of biological, molecular, and physical objects and nervous systems is considered, applying bionic features to mimic their efficiency and precision, thereby optimizing construction processes and improving coordination and decision-making. Bayesian Networks are used for probabilistic analysis, and heuristic methods guide quick decision-making. The results demonstrate the effectiveness of Bayesian Networks and heuristic methods in data analysis and decision-making in construction engineering. The developed algorithm can be successfully applied to both erecting and planning construction projects.
Special Issue “Feature Review Papers in Mechanical Engineering”
Authors: Renna Paolo , Ambrico Michele
Published: June 2024

The study and advancement of crank-slide actuating mechanisms based on four-link structural groups are promising for the development of new designs of crank presses and other stamping and forging machines [...]
A Metaheuristic Framework with Experience Reuse for Dynamic Multi-Objective Big Data Optimization
Authors: Zheng Xuanyu , Zhang Changsheng , An Yang , Zhang Bin
Published: June 2024

Dynamic multi-objective big data optimization problems (DMBDOPs) are challenging because of the difficulty of dealing with large-scale decision variables and continuous problem changes. In contrast to classical multi-objective optimization problems, DMBDOPs are still not intensively explored by researchers in the optimization field. At the same time, there is lacking a software framework to provide algorithmic examples to solve DMBDOPs and categorize benchmarks for relevant studies. This paper presents a metaheuristic software framework for DMBDOPs to remedy these issues. The proposed framework has a lightweight architecture and a decoupled design between modules, ensuring that the framework is easy to use and has enough flexibility to be extended and modified. Specifically, the framework now integrates four basic dynamic metaheuristic algorithms, eight test suites of different types of optimization problems, as well as some performance indicators and data visualization tools. In addition, we have proposed an experience reuse method, speeding up the algorithm’s convergence. Moreover, we have implemented parallel computing with Apache Spark to enhance computing efficiency. In the experiments, algorithms integrated into the framework are tested on the test suites for DMBDOPs on an Apache Hadoop cluster with three nodes. The experience reuse method is compared to two restart strategies for dynamic metaheuristics.
Oncom from Surplus Bread Enriched in Vitamin B12 via In Situ Production by Propionibacterium freudenreichii
Authors: Stodolak Bożena , Starzyńska-Janiszewska Anna , Poniewska Dagmara
Published: June 2024

Bread is a frequently wasted food product. Surplus or stale bread can be successfully processed by solid-state fermentation and used as the only fermentation substrate. Oncom, which originated in Indonesia, is made with moulds of the Neurospora genus. This experiment aimed to obtain oncome from stale bread enriched in vitamin B12. Co-fermentation with N. sitophila and Propionibacterium freudenreichii was carried out on two types of bread differing in chemical composition and initial pH value. Oncom obtained after 5 days of fermentation, depending on the substrate used and the fermentation variant (fungal, fungal-bacterial), contained from 35 to 40% dry mass, from 17.5 to about 23% protein, about 2 to max 5% fat, and from 65 to 74% carbohydrates by weight in dry mass. Vitamin B12 content depended largely on the bacterial strain, the colony-forming unit dose in the inoculum, and also the initial pH of the substrate. The oncom product obtained after co-fermentation with P. freudenreichii DSM 20271 contained a maximum of 1.3 µg/100 g, which corresponds to the vitamin B12 level in a chicken egg.
Beyond Sight: Enhancing Augmented Reality Interactivity with Audio-Based and Non-Visual Interfaces
Authors: Li Jingya
Published: June 2024

Augmented Reality (AR) is rapidly advancing, with a new focus on broadening accessibility beyond the visually dominant interfaces. This study explores the integration of audio-based non-visual interfaces within AR, aiming to cater to a diverse audience, including users with visual impairments. The objective was to develop a prototype that leverages audio feedback to facilitate interaction with the AR environment, enhancing spatial awareness and mental imagery for all users without relying on visual cues. Employing a user-centered design approach, we conducted a comprehensive evaluation with university students to assess the prototype’s usability and immersive potential compared to traditional touchscreen interfaces. The findings highlighted a pronounced preference for the Audio-Based Natural Interface, emphasizing its capacity to provide an intuitive and immersive AR experience through sound alone. These results underline the potential of audio feedback in creating more inclusive AR experiences, suggesting a paradigm shift towards developing AR technologies that are accessible to a wider user base. Our study concludes that audio-based non-visual interfaces represent a viable and innovative direction for AR development, advocating for their further exploration to ensure AR’s universality and inclusivity.
Abelian Extensions of Modified λ-Differential Left-Symmetric Algebras and Crossed Modules
Authors: Zhu Fuyang , You Taijie , Teng Wen
Published: June 2024

In this paper, we define a cohomology theory of a modified λ-differential left-symmetric algebra. Moreover, we introduce the notion of modified λ-differential left-symmetric 2-algebras, which is the categorization of a modified λ-differential left-symmetric algebra. As applications of cohomology, we classify linear deformations and abelian extensions of modified λ-differential left-symmetric algebras using the second cohomology group and classify skeletal modified λ-differential left-symmetric 2-algebra using the third cohomology group. Finally, we show that strict modified λ-differential left-symmetric 2-algebras are equivalent to crossed modules of modified λ-differential left-symmetric algebras.
Exploring Clique Transversal Problems for d-degenerate Graphs with Fixed d: From Polynomial-Time Solvability to Parameterized Complexity
Authors: Lee Chuan-Min
Published: June 2024

This paper explores the computational challenges of clique transversal problems in d-degenerate graphs, which are commonly encountered across theoretical computer science and various network applications. We examine d-degenerate graphs to highlight their utility in representing sparse structures and assess several variations of clique transversal problems, including the b-fold and {b}-clique transversal problems, focusing on their computational complexities for different graph categories. Our analysis identifies that certain instances of these problems are polynomial-time solvable in specific graph classes, such as 1-degenerate or 2-degenerate graphs. However, for d-degenerate graphs where d≥2, these problems generally escalate to NP-completeness. We also explore the parameterized complexity, pinpointing specific conditions that render these problems fixed-parameter tractable.
The Existence and Uniqueness of Radial Solutions for Biharmonic Elliptic Equations in an Annulus
Authors: Li Yongxiang , Wang Yanyan
Published: June 2024

This paper concerns with the existence of radial solutions of the biharmonic elliptic equation ▵2u=f(|x|,u,|∇u|,▵u) in an annular domain Ω={x∈RN:r1<|x|<r2}(N≥2) with the boundary conditions u|∂Ω=0 and ▵u|∂Ω=0, where f:[r1,r2]×R×R+×R→R is continuous. Under certain inequality conditions on f involving the principal eigenvalue λ1 of the Laplace operator −▵ with boundary condition u|∂Ω=0, an existence result and a uniqueness result are obtained. The inequality conditions allow for f(r,ξ,ζ,η) to be a superlinear growth on ξ,ζ,η as |(ξ,ζ,η)|→∞. Our discussion is based on the Leray–Schauder fixed point theorem, spectral theory of linear operators and technique of prior estimates.
Toward Interpretable Cell Image Representation and Abnormality Scoring for Cervical Cancer Screening Using Pap Smears
Authors: Ando Yu , Cho Junghwan , Park Nora Jee-Young , Ko Seokhwan , Han Hyungsoo
Published: June 2024

Screening is critical for prevention and early detection of cervical cancer but it is time-consuming and laborious. Supervised deep convolutional neural networks have been developed to automate pap smear screening and the results are promising. However, the interest in using only normal samples to train deep neural networks has increased owing to the class imbalance problems and high-labeling costs that are both prevalent in healthcare. In this study, we introduce a method to learn explainable deep cervical cell representations for pap smear cytology images based on one-class classification using variational autoencoders. Findings demonstrate that a score can be calculated for cell abnormality without training models with abnormal samples, and we localize abnormality to interpret our results with a novel metric based on absolute difference in cross-entropy in agglomerative clustering. The best model that discriminates squamous cell carcinoma (SCC) from normals gives 0.908±0.003 area under operating characteristic curve (AUC) and one that discriminates high-grade epithelial lesion (HSIL) 0.920±0.002 AUC. Compared to other clustering methods, our method enhances the V-measure and yields higher homogeneity scores, which more effectively isolate different abnormality regions, aiding in the interpretation of our results. Evaluation using an external dataset shows that our model can discriminate abnormality without the need for additional training of deep models.
Molecular Detection and Genetic Variability of Hepatozoon canis in Golden Jackals (Canis aureus L. 1758) in Serbia
Authors: Kuručki Milica , Sukara Ratko , Ćirković Valentina , Ćirović Duško , Tomanović Snežana
Published: June 2024

Hepatozoon canis is a protozoan tick-borne parasite infecting domestic and wild canids, including foxes, wolves, and jackals. It is mainly found in dogs but has also been detected in several wild carnivores, including foxes, wolves, and jackals. Host transmission primarily occurs through the ingestion of infected ticks, typically Rhipicephalus sanguineus, with documented instances of transplacental transmission from infected females to cubs. In Serbia, the golden jackal is common throughout the country, and its population has increased in recent years. Previous research has documented the presence of several vector-borne pathogens in the jackal population in Serbia, so we conducted this study to determine the presence, prevalence, and genetic variability of H. canis. Over eleven years (2010–2020), 114 animal samples were collected from 23 localities in Serbia. A total of 90/114 (78.95%) jackals were positive for H. canis, and they came from 22 localities. Among 15 juveniles, almost half (6/15 (40%)) tested positive for H. canis. In addition to the high prevalence, high genetic variability of the pathogen was also found. According to the mutated positions, four sequence types (S4–S7) of H. canis were determined. Based on our earlier research on the grey wolf and on this study, it can be observed that various sequence types of H. canis circulate within wild canid populations in Serbia. The prevalence of H. canis infection in wild carnivores raises significant concerns for wildlife conservation and animal health. Infected animals may act as reservoirs for the disease, posing a potential risk to domestic animals by acting as a source of infection.
The Impact of COVID-19 on the Guillain–Barré Syndrome Incidence
Authors: Kopańko Magdalena , Zabłudowska Magdalena , Zajkowska Monika , Gudowska-Sawczuk Monika , Mucha Mateusz , Mroczko Barbara
Published: June 2024

Despite the fact that the global COVID-19 pandemic has officially ended, we continue to feel its effects and discover new correlations between SARS-CoV-2 infection and changes in the organism that have occurred in patients. It has been shown that the disease can be associated with a variety of complications, including disorders of the nervous system such as a characteristic loss of smell and taste, as well as less commonly reported incidents such as cranial polyneuropathy or neuromuscular disorders. Nervous system diseases that are suspected to be related to COVID-19 include Guillain–Barré syndrome, which is frequently caused by viruses. During the course of the disease, autoimmunity destroys peripheral nerves, which despite its rare occurrence, can lead to serious consequences, such as symmetrical muscle weakness and deep reflexes, or even their complete abolition. Since the beginning of the pandemic, case reports suggesting a relationship between these two disease entities have been published, and in some countries, the increasing number of Guillain–Barré syndrome cases have also been reported. This suggests that previous contact with SARS-CoV-2 may have had an impact on their occurrence. This article is a review and summary of the literature that raises awareness of the neurological symptoms’ prevalence, including Guillain–Barré syndrome, which may be impacted by the commonly occurring COVID-19 disease or vaccination against it. The aim of this review was to better understand the mechanisms of the virus’s action on the nervous system, allowing for better detection and the prevention of its complications.
Formation of Multinucleated Giant Cells after Experimental Intracerebral Hemorrhage: Characteristics and Role of Complement C3
Authors: Fu Xiongjie , Wang Ming , Wan Yingfeng , Hua Ya , Keep Richard F. , Xi Guohua
Published: June 2024

Hematoma clearance is critical for mitigating intracerebral hemorrhage (ICH)-induced brain injury. Multinucleated giant cells (MGCs), a type of phagocyte, and the complement system may play a pivotal role in hematoma resolution, but whether the complement system regulates MGC formation after ICH remains unclear. The current study investigated the following: (1) the characteristics of MGC formation after ICH, (2) whether it was impacted by complement C3 deficiency in mice and (3) whether it also influenced hematoma degradation (hemosiderin formation). Young and aged male mice, young female mice and C3-deficient and -sufficient mice received a 30 μL injection of autologous whole blood into the right basal ganglia. Brain histology and immunohistochemistry were used to examine MGC formation on days 3 and 7. Hemosiderin deposition was examined by autofluorescence on day 28. Following ICH, MGCs were predominantly located in the peri-hematoma region exhibiting multiple nuclei and containing red blood cells or their metabolites. Aging was associated with a decrease in MGC formation after ICH, while sex showed no discernible effect. C3 deficiency reduced MGC formation and reduced hemosiderin formation. Peri-hematomal MGCs may play an important role in hematoma resolution. Understanding how aging and complement C3 impact MGCs may provide important insights into how to regulate hematoma resolution.
Octopus-Inspired Soft Robot for Slow Drug Release
Authors: Tong Dingwen , Zhao Yiqun , Wu Zhengnan , Chen Yutan , Xu Xinmiao , Chen Qinkai , Fan Xinjian , Yang Zhan
Published: June 2024

Octopus tentacles are equipped with numerous suckers, wherein the muscles contract and expel air, creating a pressure difference. Subsequently, when the muscular tension is released, objects can be securely adhered to. This mechanism has been widely employed in the development of adhesive systems. However, most existing octopus-inspired structures are passive and static, lacking dynamic and controllable adhesive switching capabilities and excellent locomotion performance. Here, we present an octopus-inspired soft robot (OISR). Attracted by the magnetic gradient field, the suction cup structure inside the OISR can generate a strong adsorption force, producing dynamically controllable adsorption and separation in the gastrointestinal (GI) tract. The experimental results show that the OISR has a variety of controllable locomotion behaviors, including quick scrolling and rolling motions, generating fast locomotion responses, rolling over gastric folds, and tumbling and swimming inside liquids. By carrying drugs that are absorbable by GI epithelial cells to target areas, the OISR enables continuous drug delivery at lesions or inflamed regions of the GI tract. This research may be a potential approach for achieving localized slow drug release within the GI tract.
Europium Nanoparticle-Based Lateral Flow Strip Biosensors for the Detection of Quinoxaline Antibiotics and Their Main Metabolites in Fish Feeds and Tissues
Authors: Mei Qing , Ma Biao , Fang Yun , Gong Yunfei , Li Jiali , Zhang Mingzhou
Published: June 2024

Olaquindox (OLA) and quinocetone (QCT) have been prohibited in aquatic products due to their significant toxicity and side effects. In this study, rapid and visual europium nanoparticle (EuNP)-based lateral flow strip biosensors (LFSBs) were developed for the simultaneous quantitative detection of OLA, QCT, and 3-methyl-quinoxaline-2-carboxylic acid (MQCA) in fish feed and tissue. The EuNP-LFSBs enabled sensitive detection for OLA, QCT, and MQCA with a limit of detection of 0.067, 0.017, and 0.099 ng/mL (R2 ≥ 0.9776) within 10 min. The average recovery of the EuNP-LFSBs was 95.13%, and relative standard deviations were below 9.38%. The method was verified by high-performance liquid chromatography (HPLC), and the test results were consistent. Therefore, the proposed LFSBs serve as a powerful tool to monitor quinoxalines in fish feeds and their residues in fish tissues.
Crack Detection of Curved Surface Structure Based on Multi-Image Stitching Method
Authors: Cui Dashun , Zhang Chunwei
Published: June 2024

The crack detection method based on image processing has been a new achievement in the field of civil engineering inspection in recent years. Column piers are generally used in bridge structures. When a digital camera collects cracks on the pier surface, the loss of crack dimension information leads to errors in crack detection results. In this paper, an image stitching method based on Speed-Up Robust Features (SURFs) is adopted to stitch the surface crack images captured from different angles into a complete crack image to improve the accuracy of the crack detection method based on image processing in curved structures. Based on the proposed method, simulated crack tests of vertical, inclined, and transverse cracks on five different structural surfaces were conducted. The results showed that the influence of structural curvature on the measurement results of vertical cracks is very small and can be ignored. Nevertheless, the loss of depth information at both ends of curved cracks will lead to errors in crack measurement outcomes, and the factors that affect the precision of crack detection include the curvature of the surface and the length of the crack. Compared with inclined cracks, the structural curvature significantly influences the measurement results of transverse cracks, especially the length measurement results of transverse cracks. The image stitching method can effectively reduce the errors caused by the structural curved surface, and the stitching effect of three images is better than that of two images.
On the Shear Force Redistribution in Composite Steel and Concrete Beams with Web Openings
Authors: Bartus Jakub , Odrobinak Jaroslav
Published: June 2024

As far as research into the field of composite steel and concrete beams with web openings has shown, the initiation of a complex stress state due to the introduction of web openings is, unfortunately, inevitable. As a logical consequence, estimation of the resistance becomes complex as well. Aiming to provide a more convenient approach, especially for evaluation of the bending resistance to the Vierendeel effect with the presence of high shear forces, a marked simplification with respect to quantification of the shear force redistribution between T-sections is presented. This novel approach stands on strong fundamentals of experimental evidence and parametric finite element (FE) investigation. Concretely, within the experimental part of this investigation, the load response of four composite beam samples was recorded and profoundly analyzed. Subsequently, a detailed FE analysis in the software ANSYS 2024 R1 (ANSYS Inc., Canonsburg, PA, USA), exploiting its parametric design language (APDL), was conducted. Finally, concise data compilation and their comprehensible interpretation were enabled by employing the software MATLAB 2024a (The MathWorks, Inc., Natick, MA, USA). In view of this treatment, a cornerstone for successive assessment of the obtained data was laid. Attempting to identify the key factors influencing the shear force proportion between the tees, integration of the shear stresses along the vertical sections with regular spacing along the FE beam models was conducted. By virtue of this concept, not only the magnitudes of the shear forces for the tees were obtained but also the leading importance of the opening depth was demonstrated. Furthermore, a complete picture of the shear force behavior along the composite perforated beams was derived. On this basis, a novel method representing a simpler and more accurate form of estimation of the shear force proportion for T-sections was proposed.
Multifractal Characteristics and Displacement Prediction of Deformation on Tunnel Portal Slope of Shallow Buried Tunnel Adjacent to Important Structures
Authors: Zhou Xiannian , He Yurui , Zhang Wanmao , Liu Dunwen
Published: June 2024

The tunnel portal section is often in extremely weak and fragmented strata, and the deformation of the portal side and slope will affect the stability of the surrounding rock and the tunnel-supporting structure. However, the deformation characteristics and displacement development patterns of slopes in the tunnel portal section are not clear. In this paper, the multifractal characteristics and displacement prediction of the deformation sequence of the tunnel portal slope at of a weak and water-rich shallow buried tunnel adjacent to an important structure are studied in depth. Combined with the deformation characteristics of the tunnel portal slope, a suitable slope monitoring and measurement scheme is designed to analyze the deformation pattern of the tunnel portal slope. Based on the multifractal detrended fluctuation analysis (MF-DFA) method, the multifractal characteristics of the deformation monitoring sequences at each monitoring point of the tunnel portal slope are analyzed. The multifractal characteristics of displacement sequences at different monitoring points of the tunnel portal slope are consistent with the actual monitoring results. Furthermore, the Long Short-Term Memory (LSTM) model is optimized using the Particle Swarm Optimization (PSO) algorithm to predict the deformation of the tunnel portal slope. The results show that the maximum mean square error (MSE) of the horizontal displacement test set prediction results is 0.142, and the coefficient of determination (R2) is higher than 91%. The maximum value of MSE for vertical displacement test set prediction is 0.069, and the R2 are higher than 91%. The study shows that the performance of the PSO-LSTM prediction model can meet the requirements for predicting the displacement of the tunnel portal slope. Based on the MF-DFA method and PSO-LSTM prediction model, the fluctuation characteristics of the displacement value of the tunnel portal section can be accurately identified and the displacement development pattern can be effectively predicted. The conclusions of the study are of great practical significance for the safe construction of the tunnel portal section.
Leveraging User-Friendly Mobile Medical Devices to Facilitate Early Hospital Discharges in a Pediatric Setting: A Randomized Trial Study Protocol
Authors: Zuccotti Gianvincenzo , Marsilio Marta , Fiori Laura , Erba Paola , Destro Francesca , Zamana Costantino , Folgori Laura , Mandelli Anna , Braghieri Davide , Guglielmetti Chiara , Pisarra Martina , Magnani Letizia , Infante Gabriele , Dilillo Dario , Fabiano Valentina , Carlucci Patrizia , Zoia Elena , Pelizzo Gloria , Calcaterra Valeria
Published: June 2024

Background: Mobile technology is increasingly prevalent in healthcare, serving various purposes, including remote health monitoring and patient self-management, which could prove beneficial to early hospital discharges. Aims: This study investigates the transitional care program experience facilitating early discharges in a pediatric setting through the use of an easy-to-use mobile medical device (TytoCare™, TytoCare Ltd., Natanya, Israel). Outcomes: This study aims to assess the effectiveness of telehomecare in achieving complete resolution of diseases without readmission, compare the length of stay between intervention and standard care groups, and gather user and professional experiences. Methods: A randomized open-label, controlled pilot study enrolled 102 children, randomly assigned to the telehomecare (TELE) group (n = 51, adopting early hospital discharge with continued home monitoring) or the standard-of-care (STAND) group (n = 51). Primary outcomes include complete disease resolution without readmission. Secondary objectives include recording a shorter length of stay in the intervention group. Surveys on user and professional experiences were conducted. A group of 51 children declining telemedicine services (NO-TELE) was also included. Results: In the TELE group, 100% of children achieved complete disease resolution without readmission, with a median duration of stay of 4 days, significantly shorter than the 7 days in the STAND group (p = 0.01). The telemedicine system demonstrated efficient performance and high satisfaction levels. The NO-TELE group showed no significant differences in demographics or digital technology competence. Perceived benefits of telemedicine included time and cost savings, reduced hospital stays, and technology utility and usability. Conclusions: This study demonstrates that user-friendly mobile medical devices effectively facilitate early hospital discharges in a pediatric setting. These devices serve as a bridge between home and hospital, optimizing care pathways.