bluuebunny/crossref_metadata_2025_split huggingface dataset:
Realtime RONS Monitoring of Cold Plasma-activated Aqueous Media Based on Time-resolved Phosphorescence Spectroscopy
Authors: Taheri Donya , Hajisharifi Kamal , Heydari Esmaeil , MirzaHosseini Fatemeh Karbalaei , Mehdian Hassan , Robert Eric 
Published: May 2024

Abstract

Besides many efforts on the detection and quantification of reactive oxygen and nitrogen species (RONSs) in the aqueous media activated by the cold atmospheric plasma, to get a better insight into the dominant mechanism and reactive species in medical applications, a challenge still remains in monitoring the real-time evaluation of them. To this end, in the present work, relying on the photonic technology based on the time-resolved phosphorescence spectroscopy, real-time tracking of RONSs concentration in treated aqueous media has been achieved by following the dissolved oxygen (DO) production/consumption. Using a photonic-based dissolved oxygen sensor, the dependence of real-time RONS concentration evaluation of plasma activated medium on plasma nozzle distance, non-thermal plasma jet exposure time, various culture media, and presence of cells has been investigated. Analyzing the results, the activation parameters including the time of reaching maximum RONS concentration after treatment and defined activation parameter \(\epsilon\) of the treated media for each case have been measured and compared together. Moreover, employing the scavengers related to two involved ROSs, the dominant chemical reactions as well as ROS contributed in the DMEM medium have been determined. As a promising result, the obtained correlation between the real-time DO level and viability and toxicity of the cancer cells, MCF-7 breast cancer cells, could enable us to exploit the present photonic setup as an alternative technique for the biological assessment.
Porcine circovirus type 2 (PCV2) in Brazil in the past 55 years (1967-2022): Evolutionary rates and patterns
Authors: Rodrigues I. L.F. , Cruz A. C.M. , Souza A. E. , Knackfuss F. B. , Costa C. H.C. , Lago B. V. , Silveira R. L. , Castro T. X. 
Published: May 2024

Abstract

Porcine circovirus type 2 (PCV2) is a common viral agent frequently described in herds, with a marked genetic variability impacted by factors such as vaccination and commercial trade. In this study, a retrospective analysis of PCV2 was performed based on molecular characterization, Bayesian inference, and the haplotype network in tissue samples obtained from Brazilian herds from 1967 to 2018. A nested PCR targeting a 225-base pair (bp) fragment of the PCV2 capsid gene was performed followed by a bi-directional sequencing. A total of 39/178 (21.9%) samples tested positive for PCV2. Genotype 2d was the major genotype described, and this genotype was detected before the introduction of the PCV2 vaccination. The mean substitution rate was 1.54 × 10− 3 substitutions per site per year (s/s/y). The haplotype diversity of PCV2 was 0.98, which shows a high mutational rate compatible with the topology found in the haplotype network. In conclusion, most of the Brazilian samples were genotyped as PCV2d, even those obtained before the introduction of the PCV2 vaccine in Brazilian herds. The PCV2 sequence from 1967 represented the oldest description in America, and the second oldest description in the world; phylogenetic analysis and haplotype network indicated the high diversity of PCV2 as well as its high evolution rate. Our results may increase knowledge about the genetic diversity, evolution, and dispersal patterns of PCV2 in Brazil.
A Comprehensive Study on Capillary Surface Modifications for Electrophoretic Separations of Liposomes
Authors: Šimonová Alice , Píplová Renata , Balouch Martin , Štěpánek František , Křížek Tomáš 
Published: May 2024

Abstract

Electroosmotic flow significantly impacts the resolution of separations in capillary electrophoresis and its modification is often necessary. Coating of the inner capillary surface either dynamically or permanently offers a way to alter the electroosmotic flow, potentially reducing the adsorption of analytes, in our case liposomes, to the capillary wall. At first, we measured fluorescently labeled liposomes in an uncoated capillary by capillary electrophoresis with laser-induced fluorescence detection. We used a special procedure of the electrophoretic experiment allowing us to observe the development of peak shape at the early stages of migration. We proved that the liposomes were adsorbed to the capillary wall, which led to a very quick and severe dispersion of their peak during their electromigration. For this reason, we used a commercially coated capillary with polyvinyl alcohol, where at the same separation conditions, we observed the peak of the liposome with a stable shape during the migration. However, this capillary is costly, thus four simple dynamic coating methods were tested for four polymers, namely Pluronic F-127, polyvinyl pyrrolidone K30, polyethylene glycol, and polydiallyldimethylammonium chloride. Among them, we chose a method where we flushed the capillary with a 10% solution of polyvinyl pyrrolidone K30 before the first measurement. In addition, in-house made permanent coating with linear polyacrylamide was investigated, which has led to effective suppression of the electroosmotic flow and stable liposome peak, not dispersed during its migration. Liposome separation using this coating fully confirmed that the studied liposomes are negatively charged and migrate in the anodic direction.
Helminths of free-ranging dogs and cats in an urban natural reserve in Mexico City and their potential risk as zoonotic agents
Authors: Camacho-Giles Valeria , Hortelano-Moncada Yolanda , Torres-Carrera Gerardo , Gil-Alarcón Guillermo , Oceguera-Figueroa Alejandro , García-Prieto Luis , Osorio-Sarabia David , Cervantes Fernando A. , Arenas Pablo 
Published: May 2024

Abstract

In the Reserva Ecológica del Pedregal San Ángel, located south of Mexico City, Mexico, dogs and cats coexist in freedom with 148 species of birds, 33 of mammals, 23 of reptiles and seven of amphibians, that represent a remnant of the original fauna of the Mexican Plateau. The negative impact that dogs and cats have on local fauna is unobjectionable, however, the fact that these introduced vertebrates may function as potential transmitters of infectious diseases for native fauna and humans, is much less understood. Information about parasitic infections in native and introduced animals in this area is scarce. In order to ameliorate this lack of information, the objective of this study is to characterize the helminth fauna of the free-ranging dogs and cats of the ecological reserve. Between 2018 and 2023, 36 Felis silvestris catus and 7 Canis lupus familiaris were studied from the helminthological perspective. Endoparasites were obtained of the digestive tract and were specifically determined using morphological and molecular evidence. Hosts were parasitized by eight species of helminths: in cats the cestodes Hydatigera taeniaeformis, Mesocestoides sp., Taenia rileyi and the nematode Toxocara cati were recorded, while in dogs, the cestode Taenia pisiformis and the nematodes Ancylostoma caninum, and Uncinaria stenocephala were found. The only species shared was the cestode Dipylidium caninum. These free-ranging animals act as definitive hosts of 5 species known to have zoonotic potential; their presence in the area may generate a public and animal health problem if programs of fauna control are not continued.
Novel ARMC5 mutations in primary bilateral macronodular adrenal hyperplasia: a family report
Authors: Wang Yi-kai , Shuang Wei-bing 
Published: May 2024

Abstract

Primary bilateral macronodular adrenal hyperplasia (PBMAH) is a rare cause of overt Cushing's syndrome (CS), which usually manifests as bilateral macronodular adrenal nodules and varying levels of cortisol secretion. Previous studies have shown that ARMC5 gene belongs to tumor suppressor gene, and its germline variants play a huge role in the occurrence of PBMAH, which may be inherited to family members and lead to more severe clinical symptoms. ARMC5 variants may be associated with meningiomas, which is also illustrated by our report. In addition, our discovery of a new mutation site in a family can also provide new targets and new directions for the study of PBMAH patients with ARMC5 mutations, and can also deepen clinicians' understanding of this disease.
FTL: Transfer Learning Nonlinear Plasma Dynamic Transitions in Low Dimensional Embeddings via Deep Neural Networks
Authors: Bai Zhe , Wei Xishuo , Tang William , Oliker Leonid , Lin Zhihong , Williams Samuel 
Published: May 2024

Abstract

Deep learning algorithms provide a new paradigm to study high-dimensional dynamical behaviors, such as those in fusion plasma systems. Development of novel model reduction methods, coupled with detection of abnormal modes with plasma physics, opens a unique opportunity for building efficient models to identify plasma instabilities for real-time control. Our Fusion Transfer Learning (FTL) model demonstrates success in reconstructing nonlinear kink mode structures by learning from a limited amount of nonlinear simulation data. The knowledge transfer process leverages a pre-trained neural encoder-decoder network, initially trained on linear simulations, to effectively capture nonlinear dynamics. The low-dimensional embeddings extract the coherent structures of interest, while preserving the inherent dynamics of the complex system. Experimental results highlight FTL’s capacity to capture transitional behaviors and dynamical features in plasma dynamics -- a task often challenging for conventional methods. The model developed in this study is generalizable and can be extended broadly through transfer learning to address various magnetohydrodynamics (MHD) modes.
Study on the chloride binding capacity of sulfoaluminate cement concrete containing different mineral admixtures
Authors: Wei Yuhang , Cao Zhonglu , Hou Jinfang , Li Bin , Jia Guanyuan , Chen Pang , Liu Ping 
Published: May 2024

Abstract

In this study, the chloride ion binding ability of sulfoaluminate cement concrete (SAC) containing different mineral admixtures was investigated. The effects of chloride concentration, curing age, and the type and amount of mineral admixture on the chloride binding rate of SAC were analyzed. It was found that the content of water-soluble chloride ions in SAC decreased with the increase of curing age, while the chloride binding ratio increased accordingly, indicating that its resistance to internal chloride permeation increased. The addition of fly ash (FA) and ground granulated blast furnace slag (GGBS) can significantly improve the chloride binding capacity of SAC, and the chloride binding rate increases to 46.6% with 20% of FA and 38.7% with 40% of GGBS. The effects of mineral dopants on the microstructure and phase composition of SAC were further investigated by X-ray diffraction (XRD) analysis. The results showed that the addition of FA and GGBS promoted the formation of C-S-H (calcium silicate hydrate) gels and improved the resistance of SAC to chloride ion penetration. On the other hand, the excessive addition of silica fume (SF) led to a decrease in the chloride binding capacity, whereas a moderate amount of limestone powder (LP) improved the chloride binding capacity.
A novel 3D method for live imaging of mitochondria at super resolution during animal development
Authors: Segos Ioannis , Eeckhoven Jens Van , Greig Alan , Redd Michael , Thrasivoulou Christopher , Conradt Barbara 
Published: May 2024

Abstract

Super-Resolution (SR) 3D rendering allows superior quantitative analysis of intracellular structures but has largely been limited to fixed or ex-vivo samples. Here we developed a method to perform SR live imaging of mitochondria during post-embryonic development of C. elegans larvae. Our workflow includes the drug-free mechanical immobilization of animals using polystyrene nanobeads, which has previously not been used for in vivo SR imaging. Based on the alignment of moving objects and global threshold-based image segmentation, our method enables an efficient 3D reconstruction of individual mitochondria. We demonstrate for the first time that the frequency distribution of fluorescence intensities is not affected by photobleaching, and that global thresholding alone enables the quantitative comparison of mitochondria along timeseries. Our composite approach significantly improves the study of biological structures and processes in SR during C. elegans post-embryonic development. Furthermore, the discovery that image segmentation does not require any prior correction against photobleaching, a fundamental problem in fluorescence microscopy, will impact experimental strategies aimed at quantitatively studying the dynamics of organelles and other intracellular compartments in any biological system.
Addressing the Burden and Detection Gap of Latent Tuberculosis Infection in Schoolchildren and Adolescents in China: A Cross-sectional Study
Authors: Wu Bo , Yu Ya , Wu Chengguo , Shi Yaling , Liu Ying , Yin Jin , Su Qian , Zhang Zhengyu , Huang Xueyong , Wang Mei , Pang Yan , Zhong Jiyuan , Fan Jun 
Published: May 2024

Abstract

Background
The latent tuberculosis infection (LTBI) burden is still unclear in schoolchildren and adolescents in China. Previous study and daily surveillance data indicate a LTBI detection gap. The research objective was to evaluate the LTBI burden and detection gap among schoolchildren and adolescents in China.
Methods
A cross-sectional study was conducted among 69667 schoolchildren and adolescents in Chongqing, China between September 2022 and December 2023 implemented by Chongqing Municipal Institute of Tuberculosis using tuberculin skin test (TST) and creation tuberculin skin test (C-TST). To evaluate the LTBI detection gap, the pulmonary tuberculosis (PTB) screening data implemented by Chongqing Municipal Institute of Tuberculosis have been compared with the data in 2021 implemented by community-level medical and health care institutions.
Results
the LTBI prevalence rate using TST and C-TST implemented by Chongqing Municipal Institute of Tuberculosis was 12.7% (95%CI, 12.5%-13%) and 6.4% (95%CI, 6%-6.8%) respectively. The LTBI prevalence rate by Chongqing Municipal Institute of Tuberculosis was 9.6% higher than that by community-level medical and health care institutions (χ2 = 2931.9, P < 0.001).
Conclusions
The LTBI detection gap existed among schoolchildren and adolescents in Chongqing, and it also may exist in other similar countries and regions. National screening strategy needs improvement. Regular training and quality assurance could improve the performance of TST and C-TST and close the detection gap of LTBI.
Evaluating Diverse Meta-Modeling Approaches for Predicting Performance Characteristics of a Twin Air Intake Based on Experimental Data
Authors: AMIRI Human , Küçük Umut Can 
Published: May 2024

Abstract

Air intakes are critical components in maximizing the efficiency of jet-powered engines. Their diverse designs, ranging from conventional shapes to innovative configurations, coupled with the intricate interplay of fluid dynamics, boundary layer effects, and structural considerations, render the determination of their performance characteristics a time-consuming task. However, a meticulous and confident evaluation of these characteristics is the key to achieving optimal air intake design and, consequently, significant enhancement of overall engine performance. This article assesses various meta-modeling approaches for predicting the performance characteristics of a twin air intake system. A comprehensive exploration of meta-modeling methods, particularly those specifically tailored for data derived from experiments, is presented. A database of 4000 experimentally obtained runs is utilized to construct train and test data for diverse models, including polynomials, decision trees, random forest regression, multivariate adaptive regression splines, and neural networks. The performance of each model is rigorously evaluated based on goodness of fit, precision, accuracy, monotonicity, and interpretability. This study provides a cost-effective and time-efficient alternative for predicting crucial flow parameters associated with the air intake of jet engines. The results reveal that the Random Forest Regression (RFR) model outperforms all other models across all evaluated metrics, demonstrating its superior effectiveness in predicting the performance characteristics of the twin air intake system.
A new speaker verification model integrated with texture variational features
Authors: Zhang Jiahao , Sun Chengli , Sun Jiayi , Chen Feilong , Zou Cairong , Guo Qiaosheng 
Published: May 2024

Abstract

Different speakers exhibit unique acoustic characteristics, presenting distinct texture patterns in spectrograms. Current research primarily focused on speaker clustering and the design of speaker verification network architectures, but the potential effects of employing varying degrees of differentiation on speaker characteristics have not been explored in the context of speaker verification tasks. In this study, we drew inspiration from the application of edge-oriented convolution block for image texture extraction in image super-resolution analysis, and proposed a new speaker verification model integrated with texture variational features which designed a feature extraction module called order-FCM. We employed Sobel and Laplacian operators to compute first- and second-order differences in the time-frequency domain, aiming to enhance the network's learning of the richer dynamic properties and higher-order features of speech signals. Additionally, we introduced the global response normalization method from the field of computer vision to normalize global channel features at the end of order-FCM, mitigating potential feature collapse phenomena. We integrated the designed module with existing speaker verification networks, and experimental results demonstrated that the performance of this method significantly surpasses that of baseline models on validation sets provided by Vox1-O, Vox1-E, Vox1-H, and the 2023 International Speaker Recognition Challenge (Voxsrc2023).
Performance Evaluation of Machine Learning Approaches for Classification of Ddos Attacks in Software Defined
Authors: Wabi Abdullahi Aishatu , Idris Ismaila , Olaniyi Olayemi Mikail , Ojeniyi Joseph A. , Adebayo Olawale S. 
Published: May 2024

Abstract

Enhancing network management and centralized network control is the goal of software-defined network. It separates the data plane from the control plane. Pros of SDN include its programmability, flexibility, and manageability to accommodate network users' ever-increasing demands. SDN is known to be a strong and safe defense against malicious network activity, but it is also susceptible to attacks like distributed denial-of-service attacks. This is a result of its centralized control features. To defend against this threat, a number of machine learning strategies have been employed. This study evaluated the performance of five Machine learning (ML) Algorithm (Naive Bayes, K-nearest neighbour, Random Forest, support vector machine, Logistic regression) for classifcation of traffic dataset as either normal or DDOS attacks in SDN. The study adopted 10-fold cross validation on each of the ML Algorithms and the result showed Random forest has the highest performance compared with other machine learning model while Naive Bayes had the lowest training time.
Home-based physical activity intervention (Active-at-Home-HF) improves left atrial function, exercise duration and quality of life in heart failure with preserved ejection fraction
Authors: Sengupta Shantanu P. , Okwose Nduka C. , MacGowan Guy A. , Jakovljevic Djordje G. 
Published: May 2024

Abstract

Background: There is limited evidence regarding the effect of physical activity interventions on exercise tolerance, left ventricular filling pressure, and quality of life in patients with heart failure with preserved ejection fraction (HFpEF). This study assessed the acceptability, feasibility, and physiological outcome of a novel, personalized, home-based physical activity intervention in HFpEF.
Methods: This was a prospective, feasibility randomized study. Forty HFpEF patients who were clinically stable were randomized 2:1 ratio to an intervention group (60±6 years, n=25, 12 male) which involved increasing daily physical activity by 2,000 steps from baseline (Active-at-Home-HF) or to standard care control group (60±7 years, n=15, 4 male) for 12 weeks. Before and after the 12 weeks, patients underwent supervised exercise stress test on a treadmill, and assessment of exercise stress echocardiography, Quality of life (QoL) (Minnesota living with heart failure questionnaire) and N-terminal prohormone of brain natriuretic peptide (NTproBNP) were also assessed before and after intervention. All patients were monitored weekly via telephone and pedometers.
Results: In the intervention group, patients achieved target step count after three weeks (from 4457±653 to 6592±546 steps per day, p<0.001), and maintained throughout the duration of the study. Exercise duration increased significantly in the intervention (350±122 vs 463±135 secs) but not in control group (399±126 vs 358±88 secs p=0.007 group*time interaction) at follow-up. Left ventricular (LV) filling pressure (E/E’) improved in the intervention group (12.43±3.6 vs 9.72±1.86) but was not significantly different compared to controls (12.86±3.17 vs 12.44±2.23) (group*time interaction p=0.08). The left atrial reservoir strain significantly improved in intervention group (25.5±4.4 vs 23.3±4.5%) and not in non-intervention group (21.8±4.4 vs 21.9±4.8%)(p=0.015). There was no change in NT proBNP, left ventricular ejection fraction, LV longitudinal strain, stroke volume, cardiac output, cardiac power output and right ventricular systolic function in the intervention or control group (p>0.05). There were no adverse events.
Conclusions: In this study of HFpEF patients, a 12-week personalised home-based physical activity intervention is feasible, acceptable, safe, improves left atrial function, exercise duration and quality of life and may improve left ventricular filling pressures.
An Analysis of EEG Signal Classification for Digit Dataset
Authors: Iqbal Asif , Bhardwaj Arpit , Suhag Ashok Kumar , Diwakar Manoj , Bijalwan Anchit , Bhardwaj Aditi , Verma Madhushi 
Published: May 2024

Abstract

Artificial Intelligence (AI) and Machine Learning has brought significant atten- tion to the human brain, making it a prominent research area in engineering and technology and other non-medical sciences. Electroencephalogram (EEG) are one of many biological signals that are produced by human brain. EEG signals contain electrical properties and has frequency ranging between 0-100Hz. Fea- tures are the various attributes of the recorded signals which are associated with the state of the human brain. The data comprises values that correspond to the frequencies of EEG signals, specifically delta, theta, alpha, beta, and gamma. Additionally, it includes information about the level of attention, level of medita- tion, and the frequency of eye blinking of the subject. This research has given a notion of how a imagined digit is classified from an EEG signal by using machine learning algorithms. We have done the analysis by using models like k-Nearest Neighbor (kNN), Convolutional Neural Network (CNN) and Genetic Program- ming (GP). An original EEG data set is created for digit from 0–9 by using a non invasive single electrode (channel) EEG device. The obtained accuracy for kNN is 66.8%, for Convolutional Neural Network it is 73.1% and that for GP it is calculated equal to 82%. If the calculated accuracy of lower channel device is improved and further achieved more then one day they may replace higher chan- nel bulky devices. As single channel or lower channel EEG device are portable and easy to use therefore implementation of this work in future may meet a variety of applications in biomedical engineering, smart health care, personal assistance and automation.