Notes

Degradation associated with Tetracycline using BiFeO₃ Cooked by an easy Hydrothermal Method.
A similar process implemented clinically can reduce time required for optimizing implant operation and enable personalized fitting of retinal prostheses.The addition of manual pressure on the electrode during neuromuscular electrical stimulation (NMES) has been used to reduce current intensity and perceived discomfort. In this study we aimed to test i) whether this approach affect the reliability of commonly made torque output measurements and ii) whether subcutaneous-fat thickness influence the efficacy of this approach in reducing current intensity and perceived discomfort. Twenty-one men (24 ± 3.1 years) performed knee extension maximal voluntary isometric contractions with and without manual pressure on the NMES femoral nerve electrode (superimposed and resting doublets, 2 pulses at 100 Hz) during two separate sessions. Torque output was measured in an isokinetic dynamometer and thigh subcutaneous-fat thickness assessed with ultrasonography. A scale of perceived discomfort was presented after contractions. Reductions in current intensity ( ) and discomfort during superimposed doublet ( p=0.002 ) and resting doublet ( p=0.002 ) were confirmed for the condition in which pressure was applied to the electrode. Fat thickness was correlated to changes in current intensity (r = 0.63; p = 0.002) and changes in discomfort (r = 0.45; p = 0.04) and no differences between pressure conditions and testing sessions were observed for torque output ( p > 0.05; ICC 0.95). Adding manual pressure during NMES on femoral nerve reduces discomfort and the maximal NMES intensity required to reach maximum torque without affecting torque output magnitude and reliability. Greater reduction in intensity and discomfort were observed in participants with higher subcutaneous-fat thickness levels after adding pressure on the electrode.The early diagnosis of cerebral palsy is an area which has recently seen significant multi-disciplinary research. Diagnostic tools such as the General Movements Assessment (GMA), have produced some very promising results. Recilisib ic50 However, the prospect of automating these processes may improve accessibility of the assessment and also enhance the understanding of movement development of infants. Previous works have established the viability of using pose-based features extracted from RGB video sequences to undertake classification of infant body movements based upon the GMA. In this paper, we propose a series of new and improved features, and a feature fusion pipeline for this classification task. We also introduce the RVI-38 dataset, a series of videos captured as part of routine clinical care. By utilising this challenging dataset we establish the robustness of several motion features for classification, subsequently informing the design of our proposed feature fusion framework based upon the GMA. We evaluate our proposed framework's classification performance using both the RVI-38 dataset and the publicly available MINI-RGBD dataset. We also implement several other methods from the literature for direct comparison using these two independent datasets. Our experimental results and feature analysis show that our proposed pose-based method performs well across both datasets. The proposed features afford us the opportunity to include finer detail than previous methods, and further model GMA specific body movements. These new features also allow us to take advantage of additional body-part specific information as a means of improving the overall classification performance, whilst retaining GMA relevant, interpretable, and shareable features.Maintaining global consistency continues to be critical for online 3D indoor scene reconstruction. However, it is still challenging to generate satisfactory 3D reconstruction in terms of global consistency for previous approaches using purely geometric analysis, even with bundle adjustment or loop closure techniques. In this paper, we propose a novel real-time 3D reconstruction approach which effectively integrates both semantic and geometric cues. The key challenge is how to map this indicative information, i.e. semantic priors, into a metric space as measurable information, thus enabling more accurate semantic fusion leveraging both the geometric and semantic cues. To this end, we introduce a semantic space with a continuous metric function measuring the distance between discrete semantic observations. Within the semantic space, we present an accurate frame-to-model semantic tracker for camera pose estimation, and semantic pose graph equipped with semantic links between submaps for globally consistent 3D scene reconstruction. With extensive evaluation on public synthetic and real-world 3D indoor scene RGB-D datasets, we show that our approach outperforms the previous approaches for 3D scene reconstruction both quantitatively and qualitatively, especially in terms of global consistency.Recent research studies show that acoustic emission (AE) technologies have great potential in detecting the flattened defects of wheel; however, the wheel-rail rolling interference (WRRI) significantly influences the accuracy of wheel defect detection. Aiming to solve the above-mentioned problem, a novel detection method, which combines an improved synthesized health index (ISHI) with a time adaptive threshold (time-ATH), is proposed in this article. In order to obtain the defect information from the signals generated by the wheels, a completed feature set that contains many types of features is extracted from AE signals. Then, the ISHI is fused by several effective features that are selected from the completed feature set, according to detection rate and accuracy. Besides, a time-ATH calculation is proposed to detect the defective signals of wheels and reduce the influence of the WRRI. The method is fully verified in actual datasets, and the results show that the proposed method achieves a better detection rate and accuracy. Moreover, it provides an effective way for the AE detection of wheel-flattened defects under strong and numerous WRRI.Photoacoustic imaging is a new and rapidly growing hybrid biomedical imaging modality that combines the virtues of both optical and ultrasonic imaging. The nature of the interaction between light and ultrasound waves allows photoacoustic imaging to make good use of the rich contrast produced by optics while retaining the imaging depths in ultrasonic imaging. High-frequency ultrasonic transducers are an important part of the photoacoustic imaging systems, used to detect the high-frequency and broad-bandwidth photoacoustic signals excited by the target tissues irradiated by short laser pulses. Advancement in high-frequency ultrasonic transducer technology has influenced the boost of photoacoustic imaging to broad applications. Here, we present a review on high-frequency ultrasonic transducer technologies for photoacoustic imaging applications including advanced piezoelectric materials and representative transducers. In addition, we discuss the new challenges and directions facing the development of high-frequency ultrasonic transducers for photoacoustic imaging applications.Intracranial blood pressure can directly reflect the status of blood vessels in real time. However, it can only be estimated invasively using a microcatheter during craniotomy. Subharmonic-aided pressure estimation (SHAPE) is a promising technique for estimating cardiac pressures but mainly uses Sonazoid, whereas SHAPE using SonoVue is still in the early stages of development. The aim of this study was to optimize transcranial SHAPE using SonoVue by investigating the relationship between subharmonic signals and middle cerebral artery pressure (MCAP) (20-160 mmHg) in vitro. We examined the effect of acoustic output levels (peak negative pressures (PNPs) of 238, 346, and 454 kPa), time in suspension (time from reconstituting the suspension to extracting it 0-30 min), and exposure to gas-equilibrated saline (3 min, 1 h, or original gas completely replaced by air) on the subharmonic-pressure relationship. A mean subharmonic amplitude over a 0.4 MHz bandwidth was extracted using a 5 MHz 12-cycle pulse. A PNP of 346 kPa elicited the best subharmonic sensitivity for assessing hydrostatic pressures up to 0.24 dB/mmHg, possibly because compression-only behavior no longer occurs at this pressure. Moreover, the expansion force is not large enough to offset the effects of hydrostatic pressure. A linear monotonic relationship between the subharmonic amplitude and hydrostatic pressure was only observed for just prepared SonoVue. Excessive exposure to gas-equilibrated saline also affected the subharmonic-pressure relationship. Therefore, just prepared SonoVue should be used, and the duration of the pressure estimation process should be strictly controlled.Lesion detectability (LD) quantifies how easily a lesion or target can be distinguished from the background. LD is commonly used to assess the performance of new ultrasound imaging methods. The contrast-to-noise ratio (CNR) is the most popular measure of LD; however, recent work has exposed its vulnerability to manipulations of dynamic range. The generalized CNR (gCNR) has been proposed as a robust histogram-based alternative that is invariant to such manipulations. Here, we identify key shortcomings of CNR and strengths of gCNR as LD metrics for modern beamformers. Using the measure theory, we pose LD as a distance between empirical probability measures (i.e., histograms) and prove that 1) gCNR is equal to the total variation distance between probability measures and 2) gCNR is one minus the error rate of the ideal observer. We then explore several consequences of measure-theoretic LD in simulation studies. We find that histogram distances depend on bin selection that LD must be considered in the context of spatial resolution and that many histogram distances are invariant under measure-preserving isomorphisms of the sample space (e.g., dynamic range transformations). Finally, we provide a mathematical interpretation for why quantitative values such as contrast ratio (CR), CNR, and signal-to-noise ratio should not be compared between images with different dynamic ranges or underlying units and demonstrate how histogram matching can be used to reenable such quantitative comparisons.Characterizing myocardial activation is of major interest for understanding the underlying mechanism of cardiac arrhythmias. Electromechanical wave imaging (EWI) is an ultrafast ultrasound-based method used to map the propagation of the local contraction triggered by electrical activation of the heart. This study introduces a novel way to characterize cardiac activation based on the time evolution of the instantaneous frequency content of the cardiac tissue displacement curves. The first validation of this method was performed on an ex vivo dataset of 36 acquisitions acquired from two working heart models in paced rhythms. It was shown that the activation mapping described by spectral analysis of interframe displacement is similar to the standard EWI method based on zero-crossing of interframe strain. An average median error of 3.3 ms was found in the ex vivo dataset between the activation maps obtained with the two methods. The feasibility of mapping cardiac activation by EWI was then investigated on two open-chest pigs during sinus and paced rhythms in a pilot trial of cardiac mapping with an intracardiac probe.
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