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https://www.readbyqxmd.com/read/28926195/non-targeted-volatile-profiles-for-the-classification-of-the-botanical-origin-of-chinese-honey-by-solid-phase-microextraction-and-gc-ms-combined-with-chemometrics
#1
Hui Chen, Linghe Jin, Chunlin Fan, Wenwen Wang
A potential method for the discrimination and prediction of honey samples of various botanical origins was developed based on the non-targeted volatile profiles obtained by solid-phase microextraction with gas chromatography and mass spectrometry combined with chemometrics. The blind analysis of non-targeted volatile profiles was carried out using solid-phase microextraction with gas chromatography and mass spectrometry for 87 authentic honey samples from four botanical origins (acacia, linden, vitex and rape)...
September 19, 2017: Journal of Separation Science
https://www.readbyqxmd.com/read/28925954/quantitative-structure-activity-relationship-modeling-of-kinase-selectivity-profiles
#2
Sandeepkumar Kothiwale, Corina Borza, Ambra Pozzi, Jens Meiler
The discovery of selective inhibitors of biological target proteins is the primary goal of many drug discovery campaigns. However, this goal has proven elusive, especially for inhibitors targeting the well-conserved orthosteric adenosine triphosphate (ATP) binding pocket of kinase enzymes. The human kinome is large and it is rather difficult to profile early lead compounds against around 500 targets to gain an upfront knowledge on selectivity. Further, selectivity can change drastically during derivatization of an initial lead compound...
September 19, 2017: Molecules: a Journal of Synthetic Chemistry and Natural Product Chemistry
https://www.readbyqxmd.com/read/28925817/using-multiple-classifiers-for-predicting-the-risk-of-endovascular-aortic-aneurysm-repair-re-intervention-through-hybrid-feature-selection
#3
Omneya Attallah, Alan Karthikesalingam, Peter Je Holt, Matthew M Thompson, Rob Sayers, Matthew J Bown, Eddie C Choke, Xianghong Ma
Feature selection is essential in medical area; however, its process becomes complicated with the presence of censoring which is the unique character of survival analysis. Most survival feature selection methods are based on Cox's proportional hazard model, though machine learning classifiers are preferred. They are less employed in survival analysis due to censoring which prevents them from directly being used to survival data. Among the few work that employed machine learning classifiers, partial logistic artificial neural network with auto-relevance determination is a well-known method that deals with censoring and perform feature selection for survival data...
September 1, 2017: Proceedings of the Institution of Mechanical Engineers. Part H, Journal of Engineering in Medicine
https://www.readbyqxmd.com/read/28924568/convolutional-neural-network-for-high-accuracy-functional-near-infrared-spectroscopy-in-a-brain-computer-interface-three-class-classification-of-rest-right-and-left-hand-motor-execution
#4
Thanawin Trakoolwilaiwan, Bahareh Behboodi, Jaeseok Lee, Kyungsoo Kim, Ji-Woong Choi
The aim of this work is to develop an effective brain-computer interface (BCI) method based on functional near-infrared spectroscopy (fNIRS). In order to improve the performance of the BCI system in terms of accuracy, the ability to discriminate features from input signals and proper classification are desired. Previous studies have mainly extracted features from the signal manually, but proper features need to be selected carefully. To avoid performance degradation caused by manual feature selection, we applied convolutional neural networks (CNNs) as the automatic feature extractor and classifier for fNIRS-based BCI...
January 2018: Neurophotonics
https://www.readbyqxmd.com/read/28924506/automated-classification-of-tropical-shrub-species-a-hybrid-of-leaf-shape-and-machine-learning-approach
#5
Miraemiliana Murat, Siow-Wee Chang, Arpah Abu, Hwa Jen Yap, Kien-Thai Yong
Plants play a crucial role in foodstuff, medicine, industry, and environmental protection. The skill of recognising plants is very important in some applications, including conservation of endangered species and rehabilitation of lands after mining activities. However, it is a difficult task to identify plant species because it requires specialized knowledge. Developing an automated classification system for plant species is necessary and valuable since it can help specialists as well as the public in identifying plant species easily...
2017: PeerJ
https://www.readbyqxmd.com/read/28924210/kinase-inhibitor-screening-using-artificial-neural-networks-and-engineered-cardiac-biowires
#6
Genevieve Conant, Samad Ahadian, Yimu Zhao, Milica Radisic
Kinase inhibitors are often used as cancer targeting agents for their ability to prevent the activation of cell growth and proliferation signals. Cardiotoxic effects have been identified for some marketed kinase inhibitors that were not detected during clinical trials. We hypothesize that more predictive cardiac functional assessments of kinase inhibitors on human myocardium can be established by combining a high-throughput two-dimensional (2D) screening assay and a high-content three-dimensional (3D) engineered cardiac tissue (Biowire(TM)) based assay, and using human induced pluripotent stem cell-derived CMs (hiPSC-CMs)...
September 18, 2017: Scientific Reports
https://www.readbyqxmd.com/read/28922645/spectrophotometric-determination-of-fluoxetine-by-molecularly-imprinted-polypyrrole-and-optimization-by-experimental-design-artificial-neural-network-and-genetic-algorithm
#7
Azizollah Nezhadali, Maryam Omidvar Motlagh, Samira Sadeghzadeh
A selective method based on molecularly imprinted polymer (MIP) solid-phase extraction (SPE) using UV-Vis spectrophotometry as a detection technique was developed for the determination of fluoxetine (FLU) in pharmaceutical and human serum samples. The MIPs were synthesized using pyrrole as a functional monomer in the presence of FLU as a template molecule. The factors that affecting the preparation and extraction ability of MIP such as amount of sorbent, initiator concentration, the amount of monomer to template ratio, uptake shaking rate, uptake time, washing buffer pH, take shaking rate, Taking time and polymerization time were considered for optimization...
September 13, 2017: Spectrochimica Acta. Part A, Molecular and Biomolecular Spectroscopy
https://www.readbyqxmd.com/read/28922130/haze-removal-using-radial-basis-function-networks-for-visibility-restoration-applications
#8
Bo-Hao Chen, Shih-Chia Huang, Chian-Ying Li, Sy-Yen Kuo
Restoration of visibility in hazy images is the first relevant step of information analysis in many outdoor computer vision applications. To this aim, the restored image must feature clear visibility with sufficient brightness and visible edges, while avoiding the production of noticeable artifacts. In this paper, we propose a haze removal approach based on the radial basis function (RBF) through artificial neural networks dedicated to effectively removing haze formation while retaining not only the visible edges but also the brightness of restored images...
September 15, 2017: IEEE Transactions on Neural Networks and Learning Systems
https://www.readbyqxmd.com/read/28922116/iterative-low-dose-ct-reconstruction-with-priors-trained-by-artificial-neural-network
#9
Dufan Wu, Kyungsang Kim, Georges El Fakhri, Quanzheng Li
Dose reduction in computed tomography (CT) is essential for decreasing radiation risk in clinical applications. Iterative reconstruction algorithms are one of the most promising way to compensate for the increased noise due to reduction of photon flux. Most iterative reconstruction algorithms incorporate manually designed prior functions of the reconstructed image to suppress noises while maintaining structures of the image. These priors basically rely on smoothness constraints and cannot exploit more complex features of the image...
September 15, 2017: IEEE Transactions on Medical Imaging
https://www.readbyqxmd.com/read/28921876/validation-of-artificial-neural-networks-as-a-methodology-for-donor-recipient-matching-for-liver-transplantation
#10
María Dolores Ayllón, Rubén Ciria, Manuel Cruz-Ramírez, María Pérez-Ortiz, Roberto Valente, John O'Grady, Manuel de la Mata, César Hervás-Martínez, Nigel D Heaton, Javier Briceño
BACKGROUND: In 2014, we reported a model for Donor-Recipient matching (D-R) in liver transplantation (LT) based on artificial-neural-networks (ANN) from a Spanish multicentre study (MADR-E: Model for Allocation of Donor and Recipient in España). The aim is to test the ANN-based methodology in a different European-healthcare system in order to validate it. METHODS: An ANN model was designed using a cohort of patients from King's College Hospital (KCH) (N=822). The ANN was trained and tested using KCH pairs for both 3- and 12-months survival models...
September 16, 2017: Liver Transplantation
https://www.readbyqxmd.com/read/28918577/microarray-based-snp-genotyping-to-identify-genetic-risk-factors-of-triple-negative-breast-cancer-tnbc-in-south-indian-population
#11
M Aravind Kumar, Vineeta Singh, Shaik Mohammad Naushad, Uday Shanker, M Lakshmi Narasu
In the view of aggressive nature of Triple-Negative Breast cancer (TNBC) due to the lack of receptors (ER, PR, HER2) and high incidence of drug resistance associated with it, a case-control association study was conducted to identify the contributing genetic risk factors for Triple-negative breast cancer (TNBC). A total of 30 TNBC patients and 50 age and gender-matched controls of Indian origin were screened for 9,00,000 SNP markers using microarray-based SNP genotyping approach. The initial PLINK association analysis (p < 0...
September 16, 2017: Molecular and Cellular Biochemistry
https://www.readbyqxmd.com/read/28914603/synaptic-up-scaling-preserves-motor-circuit-output-after-chronic-natural-inactivity
#12
Joseph M Santin, Mauricio Vallejo, Lynn K Hartzler
Neural systems use homeostatic plasticity to maintain normal brain functions and to prevent abnormal activity.  Surprisingly, homeostatic mechanisms that regulate circuit output have mainly been demonstrated during artificial and/or pathological perturbations.  Natural, physiological scenarios that activate these stabilizing mechanisms in neural networks of mature animals remain elusive.  To establish the extent to which a naturally inactive circuit engages mechanisms of homeostatic plasticity, we utilized the respiratory motor circuit in bullfrogs that normally remains inactive for several months during the winter...
September 15, 2017: ELife
https://www.readbyqxmd.com/read/28913722/nonlinear-data-assimilation-for-the-regional-modeling-of-maximum-ozone-values
#13
Marija Zlata Božnar, Boštjan Grašič, Primož Mlakar, Dejan Gradišar, Juš Kocijan
We present a new method of data assimilation with the aim of correcting the forecast of the maximum values of ozone in regional photo-chemical models for areas over complex terrain using multilayer perceptron artificial neural networks. Up until now, these types of models have been used as a single model for one location when forecasting concentrations of air pollutants. We propose a method for constructing a more ambitious model: a single model, which can be used at several locations because the model is spatially transferable and is valid for the whole 2D domain...
September 14, 2017: Environmental Science and Pollution Research International
https://www.readbyqxmd.com/read/28906450/obstacle-recognition-based-on-machine-learning-for-on-chip-lidar-sensors-in-a-cyber-physical-system
#14
Fernando Castaño, Gerardo Beruvides, Rodolfo E Haber, Antonio Artuñedo
Collision avoidance is an important feature in advanced driver-assistance systems, aimed at providing correct, timely and reliable warnings before an imminent collision (with objects, vehicles, pedestrians, etc.). The obstacle recognition library is designed and implemented to address the design and evaluation of obstacle detection in a transportation cyber-physical system. The library is integrated into a co-simulation framework that is supported on the interaction between SCANeR software and Matlab/Simulink...
September 14, 2017: Sensors
https://www.readbyqxmd.com/read/28900900/mapping-the-information-trace-in-local-field-potentials-by-a-computational-method-of-two-dimensional-time-shifting-synchronization-likelihood-based-on-graphic-processing-unit-acceleration
#15
Zi-Fang Zhao, Xue-Zhu Li, You Wan
The local field potential (LFP) is a signal reflecting the electrical activity of neurons surrounding the electrode tip. Synchronization between LFP signals provides important details about how neural networks are organized. Synchronization between two distant brain regions is hard to detect using linear synchronization algorithms like correlation and coherence. Synchronization likelihood (SL) is a non-linear synchronization-detecting algorithm widely used in studies of neural signals from two distant brain areas...
September 12, 2017: Neuroscience Bulletin
https://www.readbyqxmd.com/read/28898271/a-neural-network-based-computational-model-to-predict-the-output-power-of-different-types-of-photovoltaic-cells
#16
WenBo Xiao, Gina Nazario, HuaMing Wu, HuaMing Zhang, Feng Cheng
In this article, we introduced an artificial neural network (ANN) based computational model to predict the output power of three types of photovoltaic cells, mono-crystalline (mono-), multi-crystalline (multi-), and amorphous (amor-) crystalline. The prediction results are very close to the experimental data, and were also influenced by numbers of hidden neurons. The order of the solar generation power output influenced by the external conditions from smallest to biggest is: multi-, mono-, and amor- crystalline silicon cells...
2017: PloS One
https://www.readbyqxmd.com/read/28894961/digital-soil-mapping-using-remote-sensing-indices-terrain-attributes-and-vegetation-features-in-the-rangelands-of-northeastern-iran
#17
Ebrahim Mahmoudabadi, Alireza Karimi, Gholam Hosain Haghnia, Adel Sepehr
Digital soil mapping has been introduced as a viable alternative to the traditional mapping methods due to being fast and cost-effective. The objective of the present study was to investigate the capability of the vegetation features and spectral indices as auxiliary variables in digital soil mapping models to predict soil properties. A region with an area of 1225 ha located in Bajgiran rangelands, Khorasan Razavi province, northeastern Iran, was chosen. A total of 137 sampling sites, each containing 3-5 plots with 10-m interval distance along a transect established based on randomized-systematic method, were investigated...
September 11, 2017: Environmental Monitoring and Assessment
https://www.readbyqxmd.com/read/28893410/an-artificial-neural-network-to-predict-resting-energy-expenditure-in-obesity
#18
Emmanuel Disse, Séverine Ledoux, Cécile Bétry, Cyrielle Caussy, Christine Maitrepierre, Muriel Coupaye, Martine Laville, Chantal Simon
BACKGROUND & AIMS: The resting energy expenditure (REE) determination is important in nutrition for adequate dietary prescription. The gold standard i.e. indirect calorimetry is not available in clinical settings. Thus, several predictive equations have been developed, but they lack of accuracy in subjects with extreme weight including obese populations. Artificial neural networks (ANN) are useful predictive tools in the area of artificial intelligence, used in numerous clinical fields...
September 1, 2017: Clinical Nutrition: Official Journal of the European Society of Parenteral and Enteral Nutrition
https://www.readbyqxmd.com/read/28891000/clinical-application-of-modified-bag-of-features-coupled-with-hybrid-neural-based-classifier-in-dengue-fever-classification-using-gene-expression-data
#19
Sankhadeep Chatterjee, Nilanjan Dey, Fuqian Shi, Amira S Ashour, Simon James Fong, Soumya Sen
Dengue fever detection and classification have a vital role due to the recent outbreaks of different kinds of dengue fever. Recently, the advancement in the microarray technology can be employed for such classification process. Several studies have established that the gene selection phase takes a significant role in the classifier performance. Subsequently, the current study focused on detecting two different variations, namely, dengue fever (DF) and dengue hemorrhagic fever (DHF). A modified bag-of-features method has been proposed to select the most promising genes in the classification process...
September 11, 2017: Medical & Biological Engineering & Computing
https://www.readbyqxmd.com/read/28890770/using-non-supervised-artificial-neural-network-for-determination-of-anthropogenic-disturbance-in-a-river-system
#20
Nurul Ruhayu Mohd Rosli, Khairun Yahya
The study of river water quality plays an important role in assessing the pollution status and health of the water bodies. Human-induced activities such as domestic activities, aquaculture, agriculture and industries have detrimentally affected the river water quality. Pinang River is one of the important rivers in Balik Pulau District that supplies freshwater for human consumption. A total of 442 physical and chemical parameters data of the Pinang River, Balik Pulau catchment were analysed to determine the sources of pollutants entering the river...
July 2017: Tropical Life Sciences Research
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