bluuebunny/crossref_metadata_2025_split huggingface dataset:
Two-dimensional ECG-based cardiac arrhythmia classification using DSE-ResNet
Authors: Li Jiahao , Pang Shao-peng , Xu Fangzhou , Ji Peng , Zhou Shuwang , Shu Minglei 
Published: August 2022

AbstractElectrocardiogram (ECG) is mostly used for the clinical diagnosis of cardiac arrhythmia due to its simplicity, non-invasiveness, and reliability. Recently, many models based on the deep neural networks have been applied to the automatic classification of cardiac arrhythmia with great success. However, most models independently extract the internal features of each lead in the 12-lead ECG during the training phase, resulting in a lack of inter-lead features. Here, we propose a general model based on the two-dimensional ECG and ResNet with detached squeeze-and-excitation modules (DSE-ResNet) to realize the automatic classification of normal rhythm and 8 cardiac arrhythmias. The original 12-lead ECG is spliced into a two-dimensional plane like a grayscale picture. DSE-ResNet is used to simultaneously extract the internal and inter-lead features of the two-dimensional ECG. Furthermore, an orthogonal experiment method is used to optimize the hyper-parameters of DSE-ResNet and a multi-model voting strategy is used to improve classification performance. Experimental results based on the test set of China Physiological Signal Challenge 2018 (CPSC2018) show that our model has average $$F_1= 0.817$$

F
1

=
0.817

for classifying normal rhythm and 8 cardiac arrhythmias. Meanwhile, compared with the state-of-art model in CPSC2018, our model achieved the best $$F_1$$

F
1

in 2 sub-abnormal types. This shows that the model based on the two-dimensional ECG and DSE-ResNet has advantage in detecting some cardiac arrhythmias and has the potential to be used as an auxiliary tool to help doctors perform cardiac arrhythmias analysis.
Fungal succession on the decomposition of three plant species from a Brazilian mangrove
Authors: Moitinho Marta A. , Chiaramonte Josiane B. , Bononi Laura , Gumiere Thiago , Melo Itamar S. , Taketani Rodrigo G. 
Published: August 2022

AbstractLeaf decomposition is the primary process in release of nutrients in the dynamic mangrove habitat, supporting the ecosystem food webs. On most environments, fungi are an essential part of this process. However, due to the peculiarities of mangrove forests, this group is currently neglected. Thus, this study tests the hypothesis that fungal communities display a specific succession pattern in different mangrove species and this due to differences in their ecological role. A molecular approach was employed to investigate the dynamics of the fungal community during the decomposition of three common plant species (Rhizophora mangle, Laguncularia racemosa, and Avicennia schaueriana) from a mangrove habitat located at the southeast of Brazil. Plant material was the primary driver of fungi communities, but time also was marginally significant for the process, and evident changes in the fungal community during the decomposition process were observed. The five most abundant classes common to all the three plant species were Saccharomycetes, Sordariomycetes, Tremellomycetes, Eurotiomycetes, and Dothideomycetes, all belonging to the Phylum Ascomycota. Microbotryomycetes class were shared only by A. schaueriana and L. racemosa, while Agaricomycetes class were shared by L. racemosa and R. mangle. The class Glomeromycetes were shared by A. schaueriana and R. mangle. The analysis of the core microbiome showed that Saccharomycetes was the most abundant class. In the variable community, Sordariomycetes was the most abundant one, mainly in the Laguncularia racemosa plant. The results presented in this work shows a specialization of the fungal community regarding plant material during litter decomposition which might be related to the different chemical composition and rate of degradation.
Spin-polarized imaging of the antiferromagnetic structure and field-tunable bound states in kagome magnet FeSn
Authors: Li Hong , Zhao He , Yin Qiangwei , Wang Qi , Ren Zheng , Sharma Shrinkhala , Lei Hechang , Wang Ziqiang , Zeljkovic Ilija 
Published: August 2022

AbstractKagome metals are an exciting playground for the explorations of novel phenomena at the intersection of topology, electron correlations and magnetism. The family of FeSn-based kagome magnets in particular attracted a lot of attention for simplicity of the layered crystal structure and tunable topological electronic band structure. Despite a significant progress in understanding their bulk properties, surface electronic and magnetic structures are yet to be fully explored in many of these systems. In this work, we focus on a prototypical kagome metal FeSn. Using a combination of spin-averaged and spin-polarized scanning tunneling microscopy, we provide the first atomic-scale visualization of the layered antiferromagnetic structure at the surface of FeSn. In contrast to the field-tunable electronic structure of cousin material Fe3Sn2that is a ferromagnet, we find that electronic density-of-states of FeSn is robust to the application of external magnetic field. Interestingly, despite the field insensitive electronic band structure, FeSn exhibits bound states tied to specific impurities with large effective moments that strongly couple to the magnetic field. Our experiments provide microscopic insights necessary for theoretical modeling of FeSn and serve as a spring board for spin-polarized measurements of topological magnets in general.
Prevention of carcinogen-induced oral cancers by polymeric black tea polyphenols via modulation of EGFR-Akt-mTOR pathway
Authors: Nimbalkar Vaishnavi K. , Gangar Jeet , Shai Saptarsi , Rane Pallavi , Mohanta Subham Kumar , Kannan Sadhana , Ingle Arvind , Mittal Neha , Rane Swapnil , Mahimkar Manoj B. 
Published: August 2022

AbstractThe overexpression of Epidermal Growth Factor Receptor (EGFR) and dysregulation of its downstream effector pathways are important molecular hallmarks of oral cancers. Present study investigates the chemopreventive potential of polymeric black tea polyphenols (PBPs)/thearubigins (TRs) in the hamster model of oral carcinogenesis as well as determine the effect of PBPs on EGFR and the molecular players in the EGFR pathway. In dose-dependent manner, pre and concurrent treatment with PBPs (1.5%, 5%, 10%) decreased the number and volume of macroscopic tumors as well as the number and area of microscopic lesions. Interestingly, at 10% dose of PBPs, no macroscopic or microscopic tumors were observed. We observed PBPs mediated dose-dependent decrease in oxidative DNA damage (8OHdG); inflammation (COX-2); proliferation (PCNA, Cyclin D1); expression of EGFR, and its downstream signaling kinases (pAkt, Akt, and mTOR); hypoxia (HIF1α) and angiogenesis (VEGF). There was also a PBPs mediated dose-dependent increase in apoptosis (Bax). Thus, our data clearly indicate that the observed chemopreventive potential of PBPs was due to modulation in the EGFR pathway associated with cell proliferation, hypoxia, and angiogenesis. Taken together, our results demonstrate preclinical chemopreventive efficacy of PBPs and give an insight into its mechanistic role in the chemoprevention of experimental oral cancer.
Expansion of the RNAStructuromeDB to include secondary structural data spanning the human protein-coding transcriptome
Authors: Rouse Warren B. , O’Leary Collin A. , Booher Nicholas J. , Moss Walter N. 
Published: August 2022

AbstractRNA plays vital functional roles in almost every component of biology, and these functional roles are often influenced by its folding into secondary and tertiary structures. An important role of RNA secondary structure is in maintaining proper gene regulation; therefore, making accurate predictions of the structures involved in these processes is important. In this study, we have expanded on our previous work that led to the creation of the RNAStructuromeDB. Unlike this previous study that analyzed the human genome at low resolution, we have now scanned the protein-coding human transcriptome at high (single nt) resolution. This provides more robust structure predictions for over 100,000 isoforms of known protein-coding genes. Notably, we also utilize the motif identification tool, , to model structures with high propensity for ordered/evolved stability. All data have been uploaded to the RNAStructuromeDB, allowing for easy searching of transcripts, visualization of data tracks (via the or ), and download of data—including unique highly-ordered motifs. Herein, we provide an example analysis of MAT2A to demonstrate the utility of at finding known and novel secondary structures, highlighting regions of potential functionality, and guiding generation of functional hypotheses through use of the data.
The impact of Angiopoietin-2 genetic polymorphisms on susceptibility for malignant breast neoplasms
Authors: Hu Gui-Nv , Wang Yan , Tang Chih-Hsin , Jin Lu-Lu , Huang Bi-Fei , Wang Qian , Shao Jun-Kang , Wang Chao-Qun , Su Chen-Ming 
Published: August 2022

AbstractBreast cancer causes morbidity and mortality among women worldwide, despite much research illuminating the genetic basis of this disease. Anti-angiogenesis therapies have been widely studied, although the association between angiopoietin-2 (ANGPT2) single nucleotide polymorphisms (SNPs) and breast cancer subtypes remains unclear. This case–control study included 464 patients with malignant breast neoplasms and 539 cancer-free females. We explored the effects of ANGPT2 SNPs on the susceptibility for a malignant breast neoplasm in a Chinese Han population. Five ANGPT2 SNPs (rs2442598, rs734701, rs1823375, 11,137,037, and rs12674822) were analyzed using TaqMan SNP genotyping. Carriers of the variant GG allele of rs1823375 were less likely than wild-type carriers to be diagnosed with clinically staged breast cancer, while females with human epidermal growth factor receptor 2 (HER2)-enriched disease carrying the CG or the CG+GG genotype at rs1823375 were significantly less likely than CC genotype carriers to be of lymph node status N1–N3. We also found that the T-T-C-A-T ANGPT2 haplotype significantly increased the risk for developing a malignant breast neoplasm by 1.385-fold (95% CI: 1.025–1.871; p < 0.05). Our study is the first to document a correlation between ANGPT2 polymorphisms and the development and progression of a malignant breast neoplasm in females of Chinese Han ethnicity.
Assessment of genetic diversity and SNP marker development within peanut germplasm in Taiwan by RAD-seq
Authors: Hsu Yu-Ming , Wang Sheng-Shan , Tseng Yu-Chien , Lee Shin-Ruei , Fang Hsiang , Hung Wei-Chia , Kuo Hsin-I. , Dai Hung-Yu 
Published: August 2022

AbstractThe cultivated peanut (Arachis hypogaea L.) is an important oil crop but has a narrow genetic diversity. Molecular markers can be used to probe the genetic diversity of various germplasm. In this study, the restriction site associated DNA (RAD) approach was utilized to sequence 31 accessions of Taiwanese peanut germplasm, leading to the identification of a total of 17,610 single nucleotide polymorphisms (SNPs). When we grouped these 31 accessions into two subsets according to origin, we found that the “global” subset (n = 17) was more genetically diverse than the “local” subset (n = 14). Concerning botanical varieties, the var. fastigiata subset had greater genetic diversity than the other two subsets of var. vulgaris and var. hypogaea, suggesting that novel genetic resources should be introduced into breeding programs to enhance genetic diversity. Principal component analysis (PCA) of genotyping data separated the 31 accessions into three clusters largely according to the botanical varieties, consistent with the PCA result for 282 accessions genotyped by 14 kompetitive allele-specific PCR (KASP) markers developed in this study. The SNP markers identified in this work not only revealed the genetic relationship and population structure of current germplasm in Taiwan, but also offer an efficient tool for breeding and further genetic applications.
Spectral index selection method for remote moisture sensing under challenging illumination conditions
Authors: Graham Christopher , Girkin John , Bourgenot Cyril 
Published: August 2022

AbstractRemote sensing using passive solar illumination in the Short-Wave Infrared spectrum is exposed to strong intensity variation in the spectral bands due to atmospheric changing conditions and spectral absorption. More robust spectral analysis methods, insensitive to these effects, are increasingly required to improve the accuracy of the data analysis in the field and extend the use of the system to “non ideal” illumination condition. A computational hyperspectral image analysis method (named HIAM) for deriving optimal reflectance indices for use in remote sensing of soil moisture content is detailed and demonstrated. Using histogram analysis of hyperspectral images of wet and dry soil, contrast ratios and wavelength pairings were tested to find a suitable spectral index to recover soil moisture content. Measurements of local soil samples under laboratory and field conditions have been used to demonstrate the robustness of the index to varying lighting conditions, while publicly available databases have been used to test across a selection of soil classes. In both cases, the moisture was recovered with RMS error better than 5%. As the method is independent of material type, this method has the potential to also be applied across a variety of biological and man-made samples.
Analysis of the influence of passenger load on bus energy consumption a vehicle-engine combined model-based simulation framework
Authors: Yang Xinfeng , Liu Lanfen 
Published: August 2022

AbstractAnalyzing of the energy consumption (EC) in bus operation is important for reducing operating costs, improving sustainable solutions and creating environmentally friendly cities. The purpose of this paper is to identify the factors, such as passenger load, speed and acceleration, that affect significantly EC in bus operation. This paper builds a simulation framework for describing the level of energy based on the vehicle-engine combined (VEC) EC model. On the basis of the relationship between engine torque, power, traction and EC, the simulation framework mainly includes the road model, vehicle model, engine model and driver strategy. Furthermore, the correlations between energy consumption, passenger load, vehicle speed and acceleration are analyzed in different station spacing. The results show that the passenger load has a significant impact on EC of buses, and is related to the vehicle’s speed and acceleration. Generally, the higher the maximum driving speed, the higher the EC of the bus. Acceleration strategies and maximum speed limits are critical factors determining the EC of bus for a certain passenger load and station spacing. For the same station spacing and maximum driving speed, the acceleration phase is under a greater contribution to the increase of EC. In addition, the greater the maximum speed limit or the acceleration, the greater the contribution percentage of EC increase in the acceleration phase. The simulation framework based on vehicle-engine combined EC model and specific fuel consumption maps can obtain the operating EC of buses for situations with different station spacing and maximum speed, which is conducive to vehicle operation EC analysis. Acceleration strategies and maximum speed limits are critical factors determining the EC of bus for a certain passenger load and station spacing. Therefore, energy savings can be obtained by optimizing the driving strategy.
Discovery of levodopa-induced dyskinesia-associated genes using genomic studies in patients and Drosophila behavioral analyses
Authors: Yoon Woongchang , Min Soohong , Ryu Ho-Sung , Chung Sun Ju , Chung Jongkyeong 
Published: August 2022

AbstractAlthough levodopa is the most effective medication for Parkinson’s disease, long-term levodopa treatment is largely compromised due to late motor complications, including levodopa-induced dyskinesia (LID). However, the genetic basis of LID pathogenesis has not been fully understood. Here, we discover genes pathogenic for LID usingDrosophilagenetics and behavioral analyses combined with genome-wide association studies on 578 patients clinically diagnosed with LID. Similar to the therapeutic effect of levodopa in patients, acute levodopa treatments restore the motor defect of Parkinson’s disease model flies, while prolonged treatments cause LID-related symptoms, such as increased yawing, freezing and abrupt acceleration of locomotion. These symptoms requiredopamine 1-like receptor 1and are induced by neuronal overexpression of the receptor. Among genes selected from our analyses in the patient genome, neuronal knockdown ofadenylyl cyclase 2suppresses the levodopa-induced phenotypes and the receptor overexpression-induced symptoms inDrosophila. Together, our study provides genetic insights for LID pathogenesis through the D1-like receptor-adenylyl cyclase 2 signaling axis.
Broad clinical manifestations of polygenic risk for coronary artery disease in the Women’s Health Initiative
Authors: Clarke Shoa L. , Parham Matthew , Lankester Joanna , Shadyab Aladdin H. , Liu Simin , Kooperberg Charles , Manson JoAnn E. , Tcheandjieu Catherine , Assimes Themistocles L. 
Published: August 2022

AbstractBackgroundThe genetic basis for coronary artery disease (CAD) risk is highly complex. Genome-wide polygenic risk scores (PRS) can help to quantify that risk, but the broader impacts of polygenic risk for CAD are not well characterized.MethodsWe measured polygenic risk for CAD using the meta genomic risk score, a previously validated genome-wide PRS, in a subset of genotyped participants from the Women’s Health Initiative and applied a phenome-wide association study framework to assess associations between the PRS and a broad range of blood biomarkers, clinical measurements, and health outcomes.ResultsPolygenic risk for CAD is associated with a variety of biomarkers, clinical measurements, behaviors, and diagnoses related to traditional risk factors, as well as risk-enhancing factors. Analysis of adjudicated outcomes shows a graded association between atherosclerosis related outcomes, with the highest odds ratios being observed for the most severe manifestations of CAD. We find associations between increased polygenic risk for CAD and decreased risk for incident breast and lung cancer, with replication of the breast cancer finding in an external cohort. Genetic correlation and two-sample Mendelian randomization suggest that breast cancer association is likely due to horizontal pleiotropy, while the association with lung cancer may be causal.ConclusionPolygenic risk for CAD has broad clinical manifestations, reflected in biomarkers, clinical measurements, behaviors, and diagnoses. Some of these associations may represent direct pathways between genetic risk and CAD while others may reflect pleiotropic effects independent of CAD risk.
A non‐isolated quadratic boost converter with improved gain, high efficiency, and continuous input current
Authors: Izadi Mahnaz , Mosallanejad Ali , Lahooti Eshkevari Alireza 
Published: August 2022

AbstractThis paper presents and comprehensively investigates a non‐isolated quadratic boost dc–dc converter (QBC), designed based on integrating a triple winding coupled inductor into the basic quadratic impedance network. The topology only contains ten components. It provides a high boost factor as well as high efficiency. Unlike most previous step‐up dc–dc converters, the employed improving method does not change the converter input current from continuous mode to pulsating or discontinuous shapes, making it suitable for connecting to the current sensitive resources. Thanks to this improvement, the voltage stress across the power switch is low, especially for higher winding coefficient values. A 20/240 V/240 W prototype has been designed and fabricated to evaluate the operating principle and performance of this QBC. Experimental results show the converter produces high gain (12 times as tested) and operate with high efficiency (up to 94%). Also, the voltage stress on the power switch is one‐third of the output voltage.
Körperliche Aktivität bei Krebs – Wirksamkeit bewegungstherapeutischer Ansätze
Authors: Siebert Stefanie , Kersten Jane , Theurich Sebastian , Baumann Freerk T. 
Published: August 2022

ZusammenfassungBewegungstherapie in individualisierter Form bei onkologischen Patienten ist vor, während und auch nach Abschluss der medizinischen Therapie machbar und sicher und kann Nebenwirkungen, wie beispielsweise dem Fatigue-Syndrom oder der Polyneuropathie entgegenwirken. Dieser Beitrag gibt einen Überblick über die aktuellen bewegungstherapeutischen Ansätze bei onkologischen Patienten.
Air thermochemistry in the converging section of de Laval nozzles on hypersonic wind tunnels
Authors: Gu Sangdi , Hao Jiaao , Wen Chih-yung 
Published: August 2022

State-to-state simulations of nonequilibrium flow in nozzles are made for a range of reservoir conditions and geometries. The geometry of the converging section and throat has little influence on the thermochemistry of the flow. Higher reservoir pressure and temperature both drive the thermochemistry toward equilibrium. For reservoir temperatures of 1500, 4000, and 7000 K, the flow property that has the largest departure from equilibrium is the N2 vibrational temperature, the O mass fraction, and the N mass fraction, respectively. Even at the lowest reservoir pressure, these departures from equilibrium are only 14%, 8%, and 2% for the 1500, 4000, and 7000 K reservoirs, respectively. The differences in these flow properties at the throat between the nonequilibrium and equilibrium simulations are maintained throughout in the nonequilibrium simulations of the diverging section. Applying the simplification of equilibrium flow in the converging section and around the throat yields almost no observable errors in the vibrational population distributions in the diverging section. The simplification is recommended for most practical intents and purposes, and the current work provides important quantitative information to make informed judgments when applying it.
Innovative methods and tools for obtaining pre-forecast information in the socio-economic processes research
Authors: Vasilenko I I , Kumratova A M , Semenova A N , Popova M I 
Published: August 2022

Abstract
By using the phase analysis algorithm mechanism and the visualization and data analysis methods, the authors clearly show the resulting synergistic effect from the complex socio-economic processes research in the context of the triad results: the initial time series, a number of its increments and aggregated data. The article is devoted to the adaptation of mathematical methods of nonlinear dynamics and the description of the tool for obtaining pre-forecast information about complex economic processes, in particular, the phase analysis algorithm testing in the research of the time series of the tourist flow to the Dombai ski village of the Karachay-Cherkess Republic. Phase analysis is the method for studying local fluctuations in a time series that are asymmetric, irregular, and have an unstable period.