Project description:Neuronal oscillations are ubiquitous in the human brain and are implicated in virtually all brain functions. Although they can be described by a prominent peak in the power spectrum, their waveform is not necessarily sinusoidal and shows rather complex morphology. Both frequency and temporal descriptions of such non-sinusoidal neuronal oscillations can be utilized. However, in non-invasive EEG/MEG recordings the waveform of oscillations often takes a sinusoidal shape which in turn leads to a rather oversimplified view on oscillatory processes. In this study, we show in simulations how spatial synchronization can mask non-sinusoidal features of the underlying rhythmic neuronal processes. Consequently, the degree of non-sinusoidality can serve as a measure of spatial synchronization. To confirm this empirically, we show that a mixture of EEG components is indeed associated with more sinusoidal oscillations compared to the waveform of oscillations in each constituent component. Using simulations, we also show that the spatial mixing of the non-sinusoidal neuronal signals strongly affects the amplitude ratio of the spectral harmonics constituting the waveform. Finally, our simulations show how spatial mixing can affect the strength and even the direction of the amplitude coupling between constituent neuronal harmonics at different frequencies. Validating these simulations, we also demonstrate these effects in real EEG recordings. Our findings have far reaching implications for the neurophysiological interpretation of spectral profiles, cross-frequency interactions, as well as for the unequivocal determination of oscillatory phase.
Project description:This paper describes the design and calibration of a highly accurate temperature measurement system for pervasive computing applications. A negative temperature coefficient (NTC) thermistor with high resistance tolerance is interfaced through a conditioning circuit to a 12-bit digital converter of a wireless microcontroller. The system is calibrated to minimize the effect of component uncertainties and achieves an accuracy of ±0.03 °C on average (±0.05 °C in worst cases) in a 5 °C to 45 °C range. The calibration process is based on a continuous temperature sweep, while calibration data are simultaneously logged to reduce the delays and cost of conventional calibration approaches. An uncertainty analysis is performed to support the validity of the reported performance results. The described approach for interfacing the thermistor to the hardware platform can be straightforwardly adjusted for different thermistors, temperature ranges/accuracy levels/resolutions, and voltage ranges. The low power communication combined with the energy consumption optimization adopted enable an operation to be autonomic for several months to years depending on the application's measurement frequency requirements. The system cost is approximately $45 USD in components, while its design and compact size allow its integration with extended monitoring systems in various pervasive computing environments. The system has been thoroughly tested and validated in a field trial concerning a precision agriculture application and is currently used in a health monitoring application.
Project description:The loads acting on a workpiece during machining processes determine the modification of the surface of the final workpiece and, thus, its functional properties. In this work, a method that uses thermocouples to measure the temperature in precision fly-cutting machining with high spatial and temporal resolution is presented. Experiments were conducted for various materials and machining parameters. We compare experimental measurement data with results from modern and advanced machining process simulation and find a good match between experimental and simulation results. Therefore, the simulation is validated by experimental data and can be used to calculate realistic internal loads of machining processes.
Project description:In recent years, precision medical detection techniques experienced a rapid transformation from low-throughput to high-throughput genomic sequencing, from multicell promiscuous detection to single-cell precision sequencing. The emergence of liquid biopsy technology has compensated for the many limitations of tissue biopsy, leading to a tremendous transformation in precision detection. Precision detection techniques contribute to monitoring disease development more closely, evaluating therapeutic effects more scientifically, and developing new targets and new drugs. In the future, the role of precision detection and the joint detection in epigenetics, rare gene detection, individualized targeted therapy, and multigene targeted drug combination therapy should be extensively explored. This article reviews the changes in precision medical detection technology in the era of precision medicine, as well as the development, clinical application, and future challenges of liquid biopsy.
Project description:Sixty years after the discovery of 154Dy, the half-life of this pure alpha-emitter was re-measured. 154Dy was radiochemically separated from proton-irradiated tantalum samples. Sector field- and multicollector-inductively coupled plasma mass spectrometry were used to determine the amount of 154Dy retrieved. The disintegration rate of the radio-lanthanide was measured by means of α-spectrometry. The half-life value was determined as (1.40 ± 0.08)∙106 y, with an uncertainty reduced by a factor of ~ 10 compared to the currently adopted value of (3.0 ± 1.5)∙106 y. This precise half-life value is useful for the the correct testing and evaluation of p-process nucleosynthetic models using 154Dy as a seed nucleus or as a reaction product, as well as for the safe disposal of irradiated target material from accelerator driven facilities. As a first application of the half-life value determined in this work, the excitation functions for the production of 154Dy in proton-irradiated Ta, Pb, and W targets were re-evaluated, which are now in agreement with theoretical calculations.
Project description:Evaluation of treatments of many spine disorders requires precise measurement of the heights of vertebral bodies and disk spaces. The authors present a semiautomated computer algorithm measuring those heights from spine computed tomography (CT) scans and evaluate its precision.Eight patients underwent two spine CT scans in the same day. In each scan, five thoracolumbar vertebral heights and four disk heights were estimated using the algorithm. To assess precision, the authors computed the differences between the height measurements in the two scans, coefficients of variation (CV), and 95% limits of agreement. Intraoperator and interoperator precisions were evaluated. For local vertebral and disk height measurement (anterior, middle, posterior) the algorithm was compared to a manual mid-sagittal plane method.The mean (standard deviation) interscan difference was as low as 0.043 (0.031) mm for disk heights and 0.044 (0.043) mm for vertebral heights. The corresponding 95% limits of agreement were [-0.085, 0.11] and [-0.10, 0.12] mm, respectively. Intraoperator and interoperator precision was high, with a maximal CV of 0.30%. For local vertebral and disk heights, the algorithm improved upon the precision of the manual mid-sagittal plane measurement by as much as a factor of 6 and 4, respectively.The authors evaluated the precision of a novel computer algorithm for measuring vertebral body heights and disk heights using short term repeat CT scans of patients. The 95% limits of agreement indicate that the algorithm can detect small height changes of the order of 0.1 mm.
Project description:To advance the development of point-of-care technology (POCT), the National Institute of Biomedical Imaging and Bioengineering established the POCT Research Network (POCTRN), comprised of Centers that emphasize multidisciplinary partnerships and close facilitation to move technologies from an early stage of development into clinical testing and patient use. This paper describes the POCTRN and the three currently funded Centers as examples of academic-based organizations that support collaborations across disciplines, institutions, and geographic regions to successfully drive innovative solutions from concept to patient care.
Project description:The structure of the X-ray emission lines of the Cu Kα complex has been remeasured on a newly commissioned instrument, in a manner directly traceable to the Système Internationale definition of the meter. In this measurement, the region from 8000 eV to 8100 eV has been covered with a highly precise angular scale, and well-defined system efficiency, providing accurate wavelengths and relative intensities. This measurement updates the standard multi-Lorentzian-fit parameters from Härtwig, Hölzer, et al., and is in modest disagreement with their results for the wavelength of the Kα1 line when compared via quadratic fitting of the peak top; the intensity ratio of Kα1 to Kα2 agrees within the combined error bounds. However, the position of the fitted top of Kα1 is very sensitive to the fit parameters, so it is not believed to be a robust value to quote without further qualification. We also provide accurate intensity and wavelength information for the so-called Kα3,4 "satellite" complex. Supplementary data is provided which gives the entire shape of the spectrum in this region, allowing it to be used directly in cases where simplified, multi-Lorentzian fits to it are not sufficiently accurate.
Project description:Oxytocin is a nonapeptide hormone involved in numerous physiological functions. Real-time electrochemical measurements of oxytocin in living tissue are challenging due to electrode fouling and the large potentials needed to oxidize the tyrosine residue. Here, we used fast-scan cyclic voltammetry at carbon-fiber microelectrodes and flow injection analysis to optimize a waveform for the measurement of oxytocin. This optimized waveform employed an accumulation potential of -0.6 V, multiple scan rates, and a 3 ms holding potential at a positive, oxidizing potential of +1.4 V before linearly scanning the potential back to -0.6 V (versus Ag/AgCl). We obtained a limit of quantitation of 0.34 ± 0.02 μM, and our electrodes did not foul upon multiple injections. Moreover, to demonstrate the utility of our method, we measured the release of oxytocin, evoked by light application and mechanical perturbation, in whole brains from genetically engineered adult zebrafish that express channelrhodopsin-2 selectively on oxytocinergic neurons. Collectively, this work expands the toolkit for the measurement of peptides in living tissue preparations.
Project description:Breast cancer screening using Mammography serves as the earliest defense against breast cancer, revealing anomalous tissue years before it can be detected through physical screening. Despite the use of high resolution radiography, the presence of densely overlapping patterns challenges the consistency of human-driven diagnosis and drives interest in leveraging state-of-art localization ability of deep convolutional neural networks (DCNN). The growing availability of digitized clinical archives enables the training of deep segmentation models, but training using the most widely available form of coarse hand-drawn annotations works against learning the precise boundary of cancerous tissue in evaluation, while producing results that are more aligned with the annotations rather than the underlying lesions. The expense of collecting high quality pixel-level data in the field of medical science makes this even more difficult. To surmount this fundamental challenge, we propose LatentCADx, a deep learning segmentation model capable of precisely annotating cancer lesions underlying hand-drawn annotations, which we procedurally obtain using joint classification training and a strict segmentation penalty. We demonstrate the capability of LatentCADx on a publicly available dataset of 2,620 Mammogram case files, where LatentCADx obtains classification ROC of 0.97, AP of 0.87, and segmentation AP of 0.75 (IOU = 0.5), giving comparable or better performance than other models. Qualitative and precision evaluation of LatentCADx annotations on validation samples reveals that LatentCADx increases the specificity of segmentations beyond that of existing models trained on hand-drawn annotations, with pixel level specificity reaching a staggering value of 0.90. It also obtains sharp boundary around lesions unlike other methods, reducing the confused pixels in the output by more than 60%.