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Post-cardiac arrest structure and also supervision in the neonatal intensive care unit.
We show that in a conventional deflection detection measurement, the phase of the bending signal can be a primary source of artefacts in the dissipation estimates. It is recognized that the measurement of cantilever displacement, which has negligibly small phase lag due to hydrodynamics of the cantilever at low excitation frequencies, is better suited for ensuring artefact-free measurement of viscoelasticity compared to the measurement of the cantilever bending. Further, it was possible to measure dissipation in molecular layers of water confined between the tip and the substrate using fibre interferometer based AFM with similar experimental parameters. It confirms that the dissipation coefficient of a single I278 is below the detection limit of AFM. The results shed light on the discrepancy observed in the measured diffusional dynamics of protein collapse measured using Force spectroscopic techniques and single-molecule optical techniques.The IRIS group at IFIC Valencia is developing a three-layer Compton camera for treatment monitoring in proton therapy. The system is composed of three detector planes, each made of a [Formula see text] monolithic crystal coupled to a SiPM array. Having obtained successful results with the first prototype (MACACO) that demonstrated the feasibility of the proposed technology, a second prototype (MACACO II) with improved performance has been developed, and is the subject of this work. The new system has an enhanced detector energy resolution which translates into a higher spatial resolution of the telescope. The image reconstruction method has also been improved with an accurate model of the sensitivity matrix. The device has been tested with high energy photons at the National Accelerator Centre (CNA, Seville). The tests involved a proton beam of 18 MeV impinging on a graphite target, to produce 4.4 MeV photons. Data were taken at different system positions of the telescope with the first detector at 65 and 160 mm from the target, and at different beam intensities. The measurements allowed successful reconstruction of the photon emission distribution at two target positions separated by 5 mm in different telescope configurations. This result was obtained both with data recorded in the first and second telescope planes (two interaction events) and, for the first time in beam experiments, with data recorded in the three planes (three interaction events).The metastable phase of solid4He and the possible role of point defects in its destabilization are investigated by the introduction of a trial function of the shadow class with an explicit symmetrical kernel. This is a trial function that ensures the possible exchange of atoms and the delocalization of atoms and defects in a very effective manner. We show that the formation energy for vacancies is equal to zero at a pressure Pc=20±2 atm, which is in excellent agreement with the experimental observation. The pressure at which a self-interstitial also has a formation energy equal to zero, is in agreement with the density where vacancies have the same property. Formation energies of a3He interstitial or a substitutional impurity were estimated. Other properties of interest for systems made from4He atoms are estimated and compared with results from the literature whenever available.Clinical dosimetry is typically performed using ion chambers calibrated in terms of absorbed dose to water. As primary measurement standards for this quantity for low and medium energy x-rays are available only since a few years, most dosimetry protocols for this photon energy range are still based on air kerma calibration. For that reason, data for beam quality correction factors [Formula see text], necessary for the application of dose to water based protocols, are scarce in literature. Currently the international IAEA TRS-398 Code of Practice is under revision and new [Formula see text] factors for a large number of ion chambers will be introduced in the update of this protocol. Several international groups provided the IAEA with experimental and Monte Carlo based data for this revision. Within the European Community the EURAMET 16NRM03 RTNORM project was initiated for that purpose. In the present study, Monte Carlo based results for the beam quality correction factors in medium energy x-ray beams for six ion chambers applying different Monte Carlo codes are presented. Additionally, the perturbation factor p Q , necessary for the calculation of dose to water from an air kerma calibration coefficient, was determined. The beam quality correction factor [Formula see text] for the chambers varied in the investigated energy range by about 4%-5%, and for five out of six chambers the data could be fitted by a simple logarithmic function, if the half-value-layer was used as the beam quality specifier. Corresponding data using different Monte Carlo codes for the same ion chamber agreed within 0.5%. For the perturbation factor p Q , the data did not obey a comparable simple relationship with the beam quality specifier. Compound 3 research buy The variation of p Q for all ion chambers was in the range of 3%-4%. Compared to recently published data, our p Q data is around 1% larger, although the same Monte Carlo code has been used. Compared to the latest experimental data, there are even deviations in the range of 2%.There has been substantial interest in developing techniques for synthesizing CT-like images from MRI inputs, with important applications in simultaneous PET/MR and radiotherapy planning. Deep learning has recently shown great potential for solving this problem. The goal of this research was to investigate the capability of four common clinical MRI sequences (T1-weighted gradient-echo [T1], T2-weighted fat-suppressed fast spin-echo [T2-FatSat], post-contrast T1-weighted gradient-echo [T1-Post], and fast spin-echo T2-weighted fluid-attenuated inversion recovery [CUBE-FLAIR]) as inputs into a deep CT synthesis pipeline. Data were obtained retrospectively in 92 subjects who had undergone an MRI and CT scan on the same day. The patient's MR and CT scans were registered to one another using affine registration. The deep learning model was a convolutional neural network encoder-decoder with skip connections similar to the U-net architecture and Inception V3 inspired blocks instead of sequential convolution blocks. After training with 150 epochs and a batch size of 6, the model was evaluated using structural similarity index (SSIM), peak SNR (PSNR), mean absolute error (MAE), and dice coefficient.
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