4,701 results match your criteria features extracts


Pygidial glands of three ground beetle taxa (Insecta, Coleoptera, Carabidae): a study on their morphology and chemical composition of their secretions.

Zoology (Jena) 2021 Jul 2;148:125948. Epub 2021 Jul 2.

Institute of Zoology, University of Belgrade - Faculty of Biology, Studentski Trg 16, Belgrade, 11000, Serbia.

Morphology of the pygidial glands and chemical compositions of their secretion were analysed in the adults of three selected ground beetle taxa. Secretions of pygidial glands of Cychrus (Cychrus) semigranosus, Patrobus atrorufus and Pterostichus (Platysma) niger were chemically tested. Additionally, pygidial glands of the latter two species were investigated using bright-field microscopy and nonlinear microscopy and morphological features of the glands were described in detail. Read More

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Functional magnetic resonance imaging progressive deformable registration based on a cascaded convolutional neural network.

Quant Imaging Med Surg 2021 Aug;11(8):3569-3583

School of Biomedical Engineering, Southern Medical University, Guangzhou, China.

Background: Intersubject registration of functional magnetic resonance imaging (fMRI) is necessary for group analysis. Accurate image registration can significantly improve the results of statistical analysis. Traditional methods are achieved by using high-resolution structural images or manually extracting functional information. Read More

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DSmishSMS-A System to Detect Smishing SMS.

Neural Comput Appl 2021 Jul 28:1-18. Epub 2021 Jul 28.

Department of Computer Science & Engineering and Information Technology, Jaypee Institute of Information Technology, Sector-128, Noida, India.

With the origin of smart homes, smart cities, and smart everything, smart phones came up as an area of magnificent growth and development. These devices became a part of daily activities of human life. This impact and growth have made these devices more vulnerable to attacks than other devices such as desktops or laptops. Read More

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Towards real-time diagnosis for pediatric sepsis using graph neural network and ensemble methods.

Eur Rev Med Pharmacol Sci 2021 Jul;25(14):4693-4701

University of Chinese Academy of Sciences, Beijing, China.

Objective: The rapid onset of pediatric sepsis and the short optimal time for resuscitation pose a severe threat to children's health in the ICU. Timely diagnosis and intervention are essential to curing sepsis, but there is a lack of research on the prediction of sepsis at shorter time intervals. This study proposes a predictive model towards real-time diagnosis of sepsis to help reduce the time to first antibiotic treatment. Read More

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CT Image Analysis and Clinical Diagnosis of New Coronary Pneumonia Based on Improved Convolutional Neural Network.

Comput Math Methods Med 2021 20;2021:7259414. Epub 2021 Jul 20.

Information Center/Engineering Research Center of Medical Information Technology, West China Hospital of Sichuan University, Chengdu Sichuan 610000, China.

In this paper, based on the improved convolutional neural network, in-depth analysis of the CT image of the new coronary pneumonia, using the U-Net series of deep neural networks to semantically segment the CT image of the new coronary pneumonia, to obtain the new coronary pneumonia area as the foreground and the remaining areas as the background of the binary image, provides a basis for subsequent image diagnosis. Secondly, the target-detection framework Faster RCNN extracts features from the CT image of the new coronary pneumonia tumor, obtains a higher-level abstract representation of the data, determines the lesion location of the new coronary pneumonia tumor, and gives its bounding box in the image. By generating an adversarial network to diagnose the lesion area of the CT image of the new coronary pneumonia tumor, obtaining a complete image of the new coronary pneumonia, achieving the effect of the CT image diagnosis of the new coronary pneumonia tumor, and three-dimensionally reconstructing the complete new coronary pneumonia model, filling the current the gap in this aspect, provide a basis to produce new coronary pneumonia prosthesis and improve the accuracy of diagnosis. Read More

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The Role of Computer Remote Monitoring Technology for Nursing Care in Elderly Breast Cancer Complications.

J Healthc Eng 2021 15;2021:5475997. Epub 2021 Jul 15.

Department of Breast Nail Surgery, Xiangya Third Hospital, Central South University, Changsha, Hunan 410013, China.

Geriatric patients undergoing mastectomy have a weakened organism and slow recovery of gastrointestinal function after surgery, which may lead to various complications, affect the absorption of intestinal nutrients, and prolong the healing rate of wounds. Therefore, it is necessary to find an effective nursing program to promote the recovery of gastrointestinal function and prevent postoperative complications in elderly patients undergoing mastectomy. With the continuous development and advancement of computer and communication technologies, telecare is gaining more and more attention and has become an important part of medical information technology construction. Read More

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Toxicity in vitro and in Zebrafish Embryonic Development of Gold Nanoparticles Biosynthesized Using Macroalgae Extracts.

Int J Nanomedicine 2021 23;16:5017-5036. Epub 2021 Jul 23.

Centre of Molecular and Environmental Biology (CBMA), Universidade do Minho, Campus de Gualtar, Braga, 4710-057, Portugal.

Introduction: Research on gold nanoparticles (AuNPs) occupies a prominent place in the field of biomedicine nowadays, being their putative toxicity and bioactivity areas of major concern. The green synthesis of metallic nanoparticles using extracts from marine organisms allows the avoidance of hazardous production steps while maintaining features of interest, thus enabling the exploitation of their promising bioactivity.

Objective: To synthesize and characterize AuNPs using, for the first time, macroalga aqueous extract ([email protected]). Read More

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EOGNET: A Novel Deep Learning Model for Sleep Stage Classification Based on Single-Channel EOG Signal.

Front Neurosci 2021 12;15:573194. Epub 2021 Jul 12.

Center for Intelligent Medical Electronics, School of Information Science and Technology, Fudan University, Shanghai, China.

In recent years, automatic sleep staging methods have achieved competitive performance using electroencephalography (EEG) signals. However, the acquisition of EEG signals is cumbersome and inconvenient. Therefore, we propose a novel sleep staging approach using electrooculogram (EOG) signals, which are more convenient to acquire than the EEG. Read More

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A Temporal-Spectral-Based Squeeze-and- Excitation Feature Fusion Network for Motor Imagery EEG Decoding.

IEEE Trans Neural Syst Rehabil Eng 2021 3;29:1534-1545. Epub 2021 Aug 3.

Motor imagery (MI) electroencephalography (EEG) decoding plays an important role in brain-computer interface (BCI), which enables motor-disabled patients to communicate with the outside world via external devices. Recent deep learning methods, which fail to fully explore both deep-temporal characterizations in EEGs itself and multi-spectral information in different rhythms, generally ignore the temporal or spectral dependencies in MI-EEG. Also, the lack of effective feature fusion probably leads to redundant or irrelative information and thus fails to achieve the most discriminative features, resulting in the limited MI-EEG decoding performance. Read More

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Three-Dimensional Convolutional Autoencoder Extracts Features of Structural Brain Images With a "Diagnostic Label-Free" Approach: Application to Schizophrenia Datasets.

Front Neurosci 2021 7;15:652987. Epub 2021 Jul 7.

Department of Information Medicine, National Center of Neurology and Psychiatry, National Institute of Neuroscience, Tokyo, Japan.

There has been increasing interest in performing psychiatric brain imaging studies using deep learning. However, most studies in this field disregard three-dimensional (3D) spatial information and targeted disease discrimination, without considering the genetic and clinical heterogeneity of psychiatric disorders. The purpose of this study was to investigate the efficacy of a 3D convolutional autoencoder (3D-CAE) for extracting features related to psychiatric disorders without diagnostic labels. Read More

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Fast and Accurate Lane Detection via Graph Structure and Disentangled Representation Learning.

Sensors (Basel) 2021 Jul 7;21(14). Epub 2021 Jul 7.

College of Computer, National University of Defense Technology, Changsha 410073, China.

It is desirable to maintain high accuracy and runtime efficiency at the same time in lane detection. However, due to the long and thin properties of lanes, extracting features with both strong discrimination and perception abilities needs a huge amount of calculation, which seriously slows down the running speed. Therefore, we design a more efficient way to extract the features of lanes, including two phases: (1) Local feature extraction, which sets a series of predefined anchor lines, and extracts the local features through their locations. Read More

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iDNA6mA-Rice-DL: A local web server for identifying DNA N6-methyladenine sites in rice genome by deep learning method.

J Bioinform Comput Biol 2021 Jul 21:2150019. Epub 2021 Jul 21.

School of Information Science and Engineering, Yanshan University, Qinhuangdao 066000, P. R. China.

Accurate detection of N6-methyladenine (6mA) sites by biochemical experiments will help to reveal their biological functions, still, these wet experiments are laborious and expensive. Therefore, it is necessary to introduce a powerful computational model to identify the 6mA sites on a genomic scale, especially for plant genomes. In view of this, we proposed a model called iDNA6mA-Rice-DL for the effective identification of 6mA sites in rice genome, which is an intelligent computing model based on deep learning method. Read More

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[Molluscicidal activity of the Y6 strain against and its preliminary mechanisms of molluscicidal actions].

Zhongguo Xue Xi Chong Bing Fang Zhi Za Zhi 2021 Jul;33(3):248-253

Department of Microbiology and Immunology, Wannan Medical College, Wuhu 241002, China.

Objective: To assess the molluscicidal activity of the of Y6 strain against in laboratory, and to preliminarily investigate its mechanisms of molluscicidal actions.

Methods: Biological identification of the Y6 strain was performed based on analysis of its morphological and physiochemical features and homology analysis of the gene sequence. Y6 suspensions were formulated at concentrations of 0. Read More

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Mechanistic aspects of plant-based silver nanoparticles against multi-drug resistant bacteria.

Heliyon 2021 Jul 1;7(7):e07448. Epub 2021 Jul 1.

Department of Biology, University of North Carolina at Greensboro, NC, United States.

Resistance among pathogenic bacteria to the existing antibiotics is one of the most alarming problems of the modern world. Alongwith reducing the use of antibiotics, and antibiotic stewardship, an alternative to antibiotics is much needed in the current scenario to combact infectious diseases. One alternative is to produce nanomaterials, especially, silver nanoparticles (AgNPs) against antibiotic-resistant bacteria. Read More

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Analysis of Stadium Operation Risk Warning Model Based on Deep Confidence Neural Network Algorithm.

Comput Intell Neurosci 2021 5;2021:3715116. Epub 2021 Jul 5.

Gangneung-Wonju National University, Gangneung-si 25457, Republic of Korea.

In this paper, a deep confidence neural network algorithm is used to design and deeply analyze the risk warning model for stadium operation. Many factors, such as video shooting angle, background brightness, diversity of features, and the relationship between human behaviors, make feature attribute-based behavior detection a focus of researchers' attention. To address these factors, researchers have proposed a method to extract human behavior skeleton and optical flow feature information from videos. Read More

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Determining soil particle-size distribution from infrared spectra using machine learning predictions: Methodology and modeling.

PLoS One 2021 20;16(7):e0233242. Epub 2021 Jul 20.

Department of Soils and Agrifood Engineering, Université Laval, Québec, Canada.

Accuracy of infrared (IR) models to measure soil particle-size distribution (PSD) depends on soil preparation, methodology (sedimentation, laser), settling times and relevant soil features. Compositional soil data may require log ratio (ilr) transformation to avoid numerical biases. Machine learning can relate numerous independent variables that may impact on NIR spectra to assess particle-size distribution. Read More

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Recognizing and Counting Freehand Exercises Using Ubiquitous Cellular Signals.

Sensors (Basel) 2021 Jul 4;21(13). Epub 2021 Jul 4.

Department of Computer Science and Technology, Ocean University of China, Qingdao 266100, China.

Freehand exercises help improve physical fitness without any requirements for devices or places. Existing fitness assistant systems are typically restricted to wearable devices or exercising at specific positions, compromising the ubiquitous availability of freehand exercises. In this paper, we develop MobiFit, a contactless freehand exercise assistant using just one cellular signal receiver placed on the ground. Read More

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Alpha and high gamma phase amplitude coupling during motor imagery and weighted cross-frequency coupling to extract discriminative cross-frequency patterns.

Neuroimage 2021 Jul 16;240:118403. Epub 2021 Jul 16.

Department of Information and Communication Engineering, Handong Global University, 37554 South Korea; School of Computer Science and Electrical Engineering, Handong Global University, 37554 South Korea. Electronic address:

Motor imagery modulates specific neural oscillations like actual movement does. Representatively, suppression of the alpha power (e.g. Read More

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Relationship between Micromolecules and Quality Changes of Tilapia Fillets after Partial Freezing Treatment with Polyphenols.

J Agric Food Chem 2021 Jul 15;69(29):8213-8226. Epub 2021 Jul 15.

Hainan Provincial Engineering Research Centre of Aquatic Resources Efficient Utilization in the South China Sea, School of Food Science and Engineering, Hainan University, Haikou 570228, China.

The study investigated the main characteristic micromolecular changes in tilapia fillets after partial freezing treatment with polyphenols by ultrahigh-performance liquid chromatography-quadrupole time-of-flight mass spectrometry (UHPLC-Q-TOF-MS) analysis. A total of 2121 metabolite ion features were identified. The result suggested that procyanidin treatment increased the sweet, salty, and thick peptides' contents and suppressed the formation of bitter peptides. Read More

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Breviscapine: A Review on its Phytochemistry, Pharmacokinetics and Therapeutic Effects.

Am J Chin Med 2021 14;49(6):1369-1397. Epub 2021 Jul 14.

School of Chinese Materia Medica, Beijing University of Chinese Medicine, Beijing 102488, P. R. China.

Breviscapine is one of the extracts of several flavonoids of . Scutellarin is the main active component of breviscapine, and the qualitative or quantitative criteria as well. Scutellarin and its analogs share a similar skeleton of the flavonoids. Read More

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High Potential for Secondary Metabolite Production of CP157, Isolated From the Crustacean .

Front Microbiol 2021 28;12:688754. Epub 2021 Jun 28.

Institute for Chemistry and Biology of the Marine Environment, University of Oldenburg, Oldenburg, Germany.

Secondary metabolites are key components in microbial ecology by mediating interactions between bacteria and their environment, neighboring species or host organisms. Bioactivities can be beneficial for both interaction partners or provide a competitive advantage only for the producer. Colonizers of confined habitats such as biofilms are known as prolific producers of a great number of bioactive secondary metabolites and are a potential source for novel compounds. Read More

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Label-Free Fluorescent Aptasensor for Adenosine Triphosphate Detection Using SYBR Gold as a Probe.

Appl Spectrosc 2021 Jul 14:37028211028668. Epub 2021 Jul 14.

College of Agriculture, Yanbian University, Yanji, China.

In this experimental research, a label-free sensing strategy is developed and employed to detect adenosine triphosphate with utilization of aptamers, including exonuclease I and SYBR Gold. The conformation of aptamers bonding to the specific target molecule (ATP) is transformed into an antiparallel G-quadruplex structure from a random coil. Afterwards, considering the unfolded aptamers are the preferred substrates for exonuclease I, the addition of exonuclease I is used so as to digest unfolded aptamers in the mixture in a selective manner. Read More

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A graph convolutional neural network for gene expression data analysis with multiple gene networks.

Stat Med 2021 Jul 14. Epub 2021 Jul 14.

Division of Biostatistics, University of Minnesota, Minneapolis, Minnesota, USA.

Spectral graph convolutional neural networks (GCN) are proposed to incorporate important information contained in graphs such as gene networks. In a standard spectral GCN, there is only one gene network to describe the relationships among genes. However, for genomic applications, due to condition- or tissue-specific gene function and regulation, multiple gene networks may be available; it is unclear how to apply GCNs to disease classification with multiple networks. Read More

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spp.: A Comprehensive Review on Bioactivities and Health-Enhancing Effects and Their Potential for the Formulation of Functional Foods and Pharmaceutical Drugs.

Oxid Med Cell Longev 2021 27;2021:5900422. Epub 2021 Jun 27.

Department of Clinical Oncology, Queen Elizabeth Hospital, Kowloon, Hong Kong.

The genus includes four species widely distributed in warm temperate to subtropical regions from the Mediterranean to Mongolia as well as certain regions in America. Among these species, L., distributed from the Mediterranean region to Central Asia, has been studied and its phytochemical profile, traditional folk use, and application in pharmacological and clinical trials are well known. Read More

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EnHiC: learning fine-resolution Hi-C contact maps using a generative adversarial framework.

Bioinformatics 2021 07;37(Suppl_1):i272-i279

Department of Statistics, University of California Riverside, Riverside, CA 92521, USA.

Motivation: The high-throughput chromosome conformation capture (Hi-C) technique has enabled genome-wide mapping of chromatin interactions. However, high-resolution Hi-C data requires costly, deep sequencing; therefore, it has only been achieved for a limited number of cell types. Machine learning models based on neural networks have been developed as a remedy to this problem. Read More

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Phenolic compounds in Nordic berry species and their application as potential natural food preservatives.

Authors:
Ye Tian Baoru Yang

Crit Rev Food Sci Nutr 2021 Jul 12:1-33. Epub 2021 Jul 12.

Food Chemistry and Food Development, Department of Life Technologies, Faculty of Technology, University of Turku, Turku, Finland.

An increasing demand for natural food preservatives is raised by consumers. For Nordic berry species, abundance of phenolic compounds and potent activities of anti-oxidation and anti-bacteria enables a great potential as food preservatives. This review provides a systematic examination of current literature on phenolic profiles, anti-oxidative and anti-bacterial activities of various extracts of Nordic berry species, as well as the impact of various structure features of phenolics on the bioactivities. Read More

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A temporal-spatial attention-based action recognition method for intelligent fault diagnosis.

ISA Trans 2021 Jul 3. Epub 2021 Jul 3.

Beijing Key Lab of Precision/Ultra-precision Manufacturing Equipments and Control, Department of Mechanical Engineering, Tsinghua University, Beijing, 100084, China.

The intelligent fault diagnosis of video data has become a demanding task in industrial applications. However, existing models require expensive computational cost and memory demand, which makes this technology applied in factories impossible. To address this problem, a temporal-spatial attention-based action recognition method (TARM) integrating TAB (temporal-attention-based frame splitting model), SAB (spatial-attention-based agent focusing mode) and LSB (long-short term feature learning mode) is proposed. Read More

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Improved prediction of protein-protein interaction using a hybrid of functional-link Siamese neural network and gradient boosting machines.

Brief Bioinform 2021 Jul 9. Epub 2021 Jul 9.

Department of Electronics and Communication, Birla Institute of Technology Mesra, Ranchi, India.

In this paper, for accurate prediction of protein-protein interaction (PPI), a novel hybrid classifier is developed by combining the functional-link Siamese neural network (FSNN) with the light gradient boosting machine (LGBM) classifier. The hybrid classifier (FSNN-LGBM) uses the fusion of features derived using pseudo amino acid composition and conjoint triad descriptors. The FSNN extracts the high-level abstraction features from the raw features and LGBM performs the PPI prediction task using these abstraction features. Read More

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Pharmacokinetics/pharmacometabolomics-pharmacodynamics reveals the synergistic mechanism of a multicomponent herbal formula, Baoyuan decoction against cardiac hypertrophy.

Biomed Pharmacother 2021 Jul 7;139:111665. Epub 2021 May 7.

State Key Laboratory of Natural and Biomimetic Drugs, School of Pharmaceutical Sciences, Peking University, Beijing 100191, People's Republic of China. Electronic address:

Multicomponent herbal formulas (MCHFs) have earned a wide reputation for their definite efficacy in preventing or treating chronic complex diseases. However, holistic elucidation of the causal relationship between the bioavailable ingredients of MCHFs and their multitarget interactions is very challenging. To solve this problem, pharmacokinetics/pharmacometabolomics-pharmacodynamics (PK/PM-PD) combined with a multivariate biological correlation-network strategy was developed and applied to a classic MCHF, Baoyuan decoction (BYD), to clarify its active components and synergistic mechanism against cardiac hypertrophy (CH). Read More

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A convolutional-recurrent neural network approach to resting-state EEG classification in Parkinson's disease.

J Neurosci Methods 2021 Jul 6;361:109282. Epub 2021 Jul 6.

Pacific Parkinson's Research Centre, University of British Columbia, Canada; Department of Medicine (Neurology), University of British Columbia, Canada. Electronic address:

Background: Parkinson's disease (PD) is expected to become more common, particularly with an aging population. Diagnosis and monitoring of the disease typically rely on the laborious examination of physical symptoms by medical experts, which is necessarily limited and may not detect the prodromal stages of the disease.

New Method: We propose a lightweight (~20 K parameters) deep learning model to classify resting-state EEG recorded from people with PD and healthy controls (HC). Read More

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