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https://www.readbyqxmd.com/read/28231585/is-imprint-cytology-useful-to-diagnose-malignancy-for-brenner-tumors-a-case-series-at-a-single-institute
#1
Junko Minato, Hideki Tokunaga, Satoshi Okamoto, Yusuke Shibuya, Hitoshi Niikura, Nobuo Yaegashi
BACKGROUND: The aim of this study was to investigate cytological features of Brenner tumors according to tumor grade using imprint cytology. CASE: Between 2004 and 2015, intraoperative imprint cytology was performed on 8 patients with Brenner tumors suspected to be malignant neoplasmas on gross examination because of their large size and solid part. These consisted of 1 benign, 3 borderline, and 4 malignant tumors. In patients with benign and borderline tumors, naked nucleus-like stromal cells and tumor cells in a sheet-like arrangement were observed against a clear background...
February 24, 2017: Acta Cytologica
https://www.readbyqxmd.com/read/28231160/sourdough-based-biotechnologies-for-the-production-of-gluten-free-foods
#2
REVIEW
Luana Nionelli, Carlo Giuseppe Rizzello
Sourdough fermentation, a traditional biotechnology for making leavened baked goods, was almost completely replaced by the use of baker's yeast and chemical leavening agents in the last century. Recently, it has been rediscovered by the scientific community, consumers, and producers, thanks to several effects on organoleptic, technological, nutritional, and functional features of cereal-based products. Acidification, proteolysis, and activation of endogenous enzymes cause several changes during sourdough fermentation, carried out by lactic acid bacteria and yeasts, which positively affect the overall quality of the baked goods...
September 20, 2016: Foods (Basel, Switzerland)
https://www.readbyqxmd.com/read/28230966/increasing-peak-capacity-in-non-targeted-omics-applications-by-combining-full-scan-field-asymmetric-waveform-ion-mobility-spectrometry-with-liquid-chromatography-mass-spectrometry
#3
Kayleigh L Arthur, Matthew A Turner, James C Reynolds, Colin S Creaser
Full scan field asymmetric waveform ion mobility spectrometry (FAIMS) combined with liquid chromatography and mass spectrometry (LC-FAIMS-MS) is shown to enhance peak capacity for omics applications. A miniaturized FAIMS device capable of rapid compensation field scanning has been incorporated into an ultra-high performance liquid chromatography (UHPLC) and time-of-flight (TOF) mass spectrometry analysis, allowing the acquisition of full scan FAIMS and MS nested data sets within the timescale of a UHPLC peak...
February 23, 2017: Analytical Chemistry
https://www.readbyqxmd.com/read/28230918/single-crystal-flexible-electronics-enabled-by-3d-spalling
#4
Ning Li, Stephen Bedell, Huan Hu, Shu-Jen Han, Xiao Hu Liu, Katherine Saenger, Devendra Sadana
Flexible and stretchable electronics are becoming increasingly important in many emerging applications. Due to the outstanding electrical properties of single crystal semiconductors, there is great interest in releasing single crystal thin films and fabricating flexible electronics with these conventionally rigid materials. In this study the authors report a universal single crystal layer release process, called "3D spalling," extending beyond prior art. In contrast to the conventional way of removing blanket layers from their substrates, the new process reported here enables 3D control over the shape and thickness of the removed regions, allowing direct formation of arbitrarily shaped structures of released film and locally specified thickness for each region...
February 23, 2017: Advanced Materials
https://www.readbyqxmd.com/read/28230767/an-adaptive-multi-sensor-data-fusion-method-based-on-deep-convolutional-neural-networks-for-fault-diagnosis-of-planetary-gearbox
#5
Luyang Jing, Taiyong Wang, Ming Zhao, Peng Wang
A fault diagnosis approach based on multi-sensor data fusion is a promising tool to deal with complicated damage detection problems of mechanical systems. Nevertheless, this approach suffers from two challenges, which are (1) the feature extraction from various types of sensory data and (2) the selection of a suitable fusion level. It is usually difficult to choose an optimal feature or fusion level for a specific fault diagnosis task, and extensive domain expertise and human labor are also highly required during these selections...
February 21, 2017: Sensors
https://www.readbyqxmd.com/read/28230528/biologically-plausible-learning-in-recurrent-neural-networks-reproduces-neural-dynamics-observed-during-cognitive-tasks
#6
Thomas Miconi
Neural activity during cognitive tasks exhibits complex dynamics that flexibly encode task-relevant variables. Chaotic recurrent networks, which spontaneously generate rich dynamics, have been proposed as a model of cortical computation during cognitive tasks. However, existing methods for training these networks are either biologically implausible, and/or require a continuous, real-time error signal to guide learning. Here we show that a biologically plausible learning rule can train such recurrent networks, guided solely by delayed, phasic rewards at the end of each trial...
February 23, 2017: ELife
https://www.readbyqxmd.com/read/28229906/enzyme-mediated-ligation-technologies-for-peptides-and-proteins
#7
REVIEW
Marcel Schmidt, Ana Toplak, Peter Jlm Quaedflieg, Timo Nuijens
With the steadily increasing complexity and quantity requirements for peptides in industry and academia, the efficient and site-selective ligation of peptides and proteins represents a highly desirable goal. Within this context, enzyme-mediated ligation technologies for peptides and proteins have attracted great interest in recent years as they represent an extremely powerful extension to the scope of chemical methodologies (e.g. native chemical ligation) in basic and applied research. Compared to chemical ligation methods, enzymatic strategies using ligases such as sortase, butelase, peptiligase or omniligase generally feature excellent chemoselectivity, therefore making them valuable tools for protein and peptide chemists...
February 18, 2017: Current Opinion in Chemical Biology
https://www.readbyqxmd.com/read/28228849/considerations-and-complications-of-mapping-small-rna-high-throughput-data-to-transposable-elements
#8
Alexandros Bousios, Brandon S Gaut, Nikos Darzentas
BACKGROUND: High-throughput sequencing (HTS) has revolutionized the way in which epigenetic research is conducted. When coupled with fully-sequenced genomes, millions of small RNA (sRNA) reads are mapped to regions of interest and the results scrutinized for clues about epigenetic mechanisms. However, this approach requires careful consideration in regards to experimental design, especially when one investigates repetitive parts of genomes such as transposable elements (TEs), or when such genomes are large, as is often the case in plants...
2017: Mobile DNA
https://www.readbyqxmd.com/read/28227980/motor-imagery-based-brain-computer-interface-using-transform-domain-features
#9
Ahmed M Elbaz, Ahmed T Ahmed, Ayman M Mohamed, Mohamed A Oransa, Khaled S Sayed, Ayman M Eldeib, Ahmed M Elbaz, Ahmed T Ahmed, Ayman M Mohamed, Mohamed A Oransa, Khaled S Sayed, Ayman M Eldeib, Mohamed A Oransa, Khaled S Sayed, Ayman M Mohamed, Ahmed T Ahmed, Ahmed M Elbaz, Ayman M Eldeib
Brain Computer Interface (BCI) is a channel of communication between the human brain and an external device through brain electrical activity. In this paper, we extracted different features to boost the classification accuracy as well as the mutual information of BCI systems. The extracted features include the magnitude of the discrete Fourier transform and the wavelet coefficients for the EEG signals in addition to distance series values and invariant moments calculated for the reconstructed phase space of the EEG measurements...
August 2016: Conference Proceedings: Annual International Conference of the IEEE Engineering in Medicine and Biology Society
https://www.readbyqxmd.com/read/28227953/in-vivo-characterization-of-a-versatile-8-channel-digital-biopotential-recording-system-with-sub-%C3%AE-vrms-input-noise
#10
Oscar F Cota, Dennis Plachta, Thomas Stieglitz, Sarath Kundumattathil, Yiannos Manoli, Matthias Kuhl, Oscar F Cota, Dennis Plachta, Thomas Stieglitz, Sarath Kundumattathil, Yiannos Manoli, Matthias Kuhl, Thomas Stieglitz, Dennis Plachta, Matthias Kuhl, Oscar F Cota, Yiannos Manoli, Sarath Kundumattathil
This work presents the design and testing of an integrated 8-channel CMOS biopotential recording chip, consisting of low-noise input stages, tunable second stage, a multiplexer, and two analog-to-digital converters (ADC). Through its variable supply concept, the integrated input-referred noise of the first stage is selectable from 1.5 down to 0.63 μVRMS (ISS = 200 μA), which is superior to standard laboratory recording systems. The device features variable lower and upper corner frequencies, and outputs two digital 16-bit data streams at 62...
August 2016: Conference Proceedings: Annual International Conference of the IEEE Engineering in Medicine and Biology Society
https://www.readbyqxmd.com/read/28227944/classification-of-squat-quality-with-inertial-measurement-units-in-the-single-leg-squat-mobility-test
#11
Rezvan Kianifar, Alex Lee, Sachin Raina, Dana Kulic, Rezvan Kianifar, Alex Lee, Sachin Raina, Dana Kulic, Alex Lee, Sachin Raina, Dana Kulic, Rezvan Kianifar
Many assessment and diagnosis protocols in rehabilitation, orthopedic surgery and sports medicine rely on mobility tests like the Single Leg Squat (SLS). In this study, a set of three Inertial Measurement Units (IMUs) were used to estimate the joint pose during SLS and to classify the SLS as poor, moderate or good. An Extended Kalman Filter pose estimation method was used to estimate kinematic joint variables, and time domain features were generated based on these variables. The most important features were then selected and used to train Support Vector Machine (SVM), Linear Multinomial Logistic Regression, and Decision Tree classifiers...
August 2016: Conference Proceedings: Annual International Conference of the IEEE Engineering in Medicine and Biology Society
https://www.readbyqxmd.com/read/28227914/automated-classification-of-pathological-gait-after-stroke-using-ubiquitous-sensing-technology
#12
Elham Dolatabadi, Babak Taati, Alex Mihailidis, Elham Dolatabadi, Babak Taati, Alex Mihailidis, Babak Taati, Alex Mihailidis, Elham Dolatabadi
This study uses machine learning methods to distinguish between healthy and pathological gait. Examples of multi-dimensional pathological and normal gait sequences were collected from post-stroke and healthy individuals in a real clinical setting and with two Kinect sensors. The trajectories of rotational angle and global velocity of selected body joints (hips, spine, shoulders, neck, knees and ankles) over time formed the gait sequences. The combination of k nearest neighbor (kNN) and dynamic time warping (DTW) was used for classification...
August 2016: Conference Proceedings: Annual International Conference of the IEEE Engineering in Medicine and Biology Society
https://www.readbyqxmd.com/read/28227863/age-estimation-using-effective-brain-local-features-from-t1-weighted-images
#13
Ryuichi Fujimoto, Chihiro Kondo, Koichi Ito, Kai Wu, Kazunori Sato, Yasuyuki Taki, Hiroshi Fukuda, Takafumi Aoki, Ryuichi Fujimoto, Chihiro Kondo, Koichi Ito, Kai Wu, Kazunori Sato, Yasuyuki Taki, Hiroshi Fukuda, Takafumi Aoki, Koichi Ito, Yasuyuki Taki, Takafumi Aoki, Chihiro Kondo, Kazunori Sato, Hiroshi Fukuda, Ryuichi Fujimoto, Kai Wu
This paper proposes a simple method of selecting effective brain local features for age estimation from T1-weighted MR images. We also employ the high-resolution AAL atlas, which is defined by 1,024 local regions, to improve the accuracy of age estimation. We evaluate performance of the proposed method using 1,099 T1-weighted images from a large-scale brain MR image database of healthy Japanese, and demonstrate that the proposed method exhibits efficient performance of age estimation compared with conventional methods...
August 2016: Conference Proceedings: Annual International Conference of the IEEE Engineering in Medicine and Biology Society
https://www.readbyqxmd.com/read/28227860/classification-of-adhd-subgroup-with-recursive-feature-elimination-for-structural-brain-mri
#14
Muhammad Naveed Iqbal Qureshi, Boreom Lee, Muhammad Naveed Iqbal Qureshi, Boreom Lee, Boreom Lee
This article reports the binary classification results of ADHD patients among three subgroups by using ADHD-200 dataset. We have proposed a modified feature selection approach using standard RFE-SVM model. Our results show the significance of the proposed method by making a comparison of J-statistics, F1-score and classification accuracy based on the feature selection from the original RFE-SVM vs. the proposed modification of RFE-SVM. In addition, we have also compared the number of features in each setting to achieve the highest accuracy...
August 2016: Conference Proceedings: Annual International Conference of the IEEE Engineering in Medicine and Biology Society
https://www.readbyqxmd.com/read/28227841/comparing-eeg-its-time-derivative-and-their-joint-use-as-features-in-a-bci-for-2-d-pointer-control
#15
Dimitrios Andreou, Riccardo Poli, Dimitrios Andreou, Riccardo Poli, Riccardo Poli, Dimitrios Andreou
Efficient and accurate classification of event related potentials is a core task in brain-computer interfaces (BCI). This is normally obtained by first extracting features from the voltage amplitudes recorded via EEG at different channels and then feeding them into a classifier. In this paper we evaluate the relative benefits of using the first order temporal derivatives of the EEG signals, not the EEG signals themselves, as inputs to the BCI: an area that has not been thoroughly examined. Specifically, we compare the classification performance of features extracted from the first derivative, with those derived from the amplitude, as well as their combination using data from a P300-based BCI mouse...
August 2016: Conference Proceedings: Annual International Conference of the IEEE Engineering in Medicine and Biology Society
https://www.readbyqxmd.com/read/28227809/feature-domain-specific-movement-intention-detection-for-stroke-rehabilitation-with-brain-computer-interfaces
#16
J T Hadsund, M B Sorensen, A C Royo, I K Niazi, H Rovsing, C Rovsing, M Jochumsen, J T Hadsund, M B Sorensen, A C Royo, I K Niazi, H Rovsing, C Rovsing, M Jochumsen, H Rovsing, M Jochumsen, M B Sorensen, C Rovsing, A C Royo, I K Niazi, J T Hadsund
Brain-computer interface (BCI) driven electrical stimulation has been proposed for neuromodulation for stroke rehabilitation by pairing intentions to move with somatosensory feedback from electrical stimulation. Movement intentions have been detected in several studies using different techniques, with temporal and spectral features being the most common. A few studies have compared temporal and spectral features, but conflicting results have been reported. In this study, the aim was to investigate if complexity measures can be used for movement intention detection and to compare the detection performance based on features extracted from three different domains (time, frequency and complexity) from single-trial EEG...
August 2016: Conference Proceedings: Annual International Conference of the IEEE Engineering in Medicine and Biology Society
https://www.readbyqxmd.com/read/28227702/socioeconomic-status-age-and-heart-rate-variability-in-a-bangladeshi-community
#17
Nishat E-Sharmin Trisha, Herbert F Jelinek, Mika P Tarvainen, David J Cornforth, Dewan S Alam, Megan Smith, Nishat E-Sharmin Trisha, Herbert F Jelinek, Mika P Tarvainen, David J Cornforth, Dewan S Alam, Megan Smith, Herbert F Jelinek, David J Cornforth, Megan Smith, Nishat E-Sharmin Trisha, Dewan S Alam, Mika P Tarvainen
Socioeconomic status (SES) is a risk factor for cardiovascular disease (CVD) and either low or high heart rate variability (HRV) at rest has been shown to predict cardiovascular morbidity and mortality. The study investigated the extent HRV features can predict SES. Four hundred and twenty eight people were randomly selected from the commercial districts (high SES) and slum areas (low SES) within Dhaka city. Demographic, clinical, and HRV features were recorded. Of the clinical variables age, waist circumference and diastolic blood pressure (p<;0...
August 2016: Conference Proceedings: Annual International Conference of the IEEE Engineering in Medicine and Biology Society
https://www.readbyqxmd.com/read/28227617/detection-of-chewing-from-piezoelectric-film-sensor-signals-using-ensemble-classifiers
#18
Muhammad Farooq, Edward Sazonov, Muhammad Farooq, Edward Sazonov, Muhammad Farooq, Edward Sazonov
Selection and use of pattern recognition algorithms is application dependent. In this work, we explored the use of several ensembles of weak classifiers to classify signals captured from a wearable sensor system to detect food intake based on chewing. Three sensor signals (Piezoelectric sensor, accelerometer, and hand to mouth gesture) were collected from 12 subjects in free-living conditions for 24 hrs. Sensor signals were divided into 10 seconds epochs and for each epoch combination of time and frequency domain features were computed...
August 2016: Conference Proceedings: Annual International Conference of the IEEE Engineering in Medicine and Biology Society
https://www.readbyqxmd.com/read/28227558/the-limb-movement-analysis-of-rehabilitation-exercises-using-wearable-inertial-sensors
#19
Bingquan Huang, Oonagh Giggins, Tahar Kechadi, Brian Caulfield, Bingquan Huang, Oonagh Giggins, Tahar Kechadi, Brian Caulfield, Bingquan Huang, Brian Caulfield, Oonagh Giggins, Tahar Kechadi
Due to no supervision of a therapist in home based exercise programs, inertial sensor based feedback systems which can accurately assess movement repetitions are urgently required. The synchronicity and the degrees of freedom both show that one movement might resemble another movement signal which is mixed in with another not precisely defined movement. Therefore, the data and feature selections are important for movement analysis. This paper explores the data and feature selection for the limb movement analysis of rehabilitation exercises...
August 2016: Conference Proceedings: Annual International Conference of the IEEE Engineering in Medicine and Biology Society
https://www.readbyqxmd.com/read/28227551/detecting-slow-eye-movement-for-recognizing-driver-s-sleep-onset-period-with-eeg-features
#20
Yingying Jiao, Bao-Liang Lu, Yingying Jiao, Bao-Liang Lu, Baa-Liang Lu, Yingying Jiao
Slow eye movement (SEM) is reported as a reliable indicator of sleep onset period (SOP) in sleep researches, but its characteristics and functions for detecting driving fatigue have not been fully studied. Through visual observations on ten subjects' experimental data, we found that SEMs tend to occur during eye closure events (ECEs). SEMs accompanied with alpha wave's attenuation during simulated driving was observed in our study. We used box plots to analyze the distribution of durations of different ECEs to measure sleepiness level...
August 2016: Conference Proceedings: Annual International Conference of the IEEE Engineering in Medicine and Biology Society
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