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Background Ibrutinib and acalabrutinib are Bruton tyrosine kinase inhibitors used in the treatment of B‐cell lymphoproliferative disorders. Ibrutinib is associated with new‐onset atrial fibrillation. Cases of sinus bradycardia and sinus arrest have also been reported following ibrutinib treatment. Conversely, acalabrutinib is less arrhythmogenic. The basis for these different effects is unclear. Methods and Results The effects of ibrutinib and acalabrutinib on atrial electrophysiology were investigated in anesthetized mice using intracardiac electrophysiology, in isolated atrial preparations using high‐resolution optical mapping, and in isolated atrial and sinoatrial node (SAN) myocytes using patch‐clamping. Acute delivery of acalabrutinib did not affect atrial fibrillation susceptibility or other measures of atrial electrophysiology in mice in vivo. Optical mapping demonstrates that ibrutinib dose‐dependently impaired atrial and SAN conduction and slowed beating rate. Acalabrutinib had no effect on atrial and SAN conduction or beating rate. In isolated atrial myocytes, ibrutinib reduced action potential upstroke velocity and Na + current. In contrast, acalabrutinib had no effects on atrial myocyte upstroke velocity or Na + current. Both drugs increased action potential duration, but these effects were smaller for acalabrutinib compared with ibrutinib and occurred by different mechanisms. In SAN myocytes, ibrutinib impaired spontaneous action potential firing by inhibiting the delayed rectifier K + current, while acalabrutinib had no effects on SAN myocyte action potential firing. Conclusions Ibrutinib and acalabrutinib have distinct effects on atrial electrophysiology and ion channel function that provide insight into the basis for increased atrial fibrillation susceptibility and SAN dysfunction with ibrutinib, but not with acalabrutinib.

Women with pre‐gestational diabetes have a higher risk of producing children with congenital heart defects (CHDs), caused predominantly by hyperglycemia‐induced oxidative stress. In this study, we evaluated if exercise during pregnancy could mitigate oxidative stress and reduce the incidence of CHDs in the offspring of diabetic mice. Female mice were treated with streptozotocin to induce pre‐gestational diabetes, then mated with healthy males to produce offspring. They were also given access to running wheels 1 week before mating and allowed to exercise voluntarily until E18.5. Heart morphology, gene expression, and oxidative stress were assessed in foetal hearts. Maternal voluntary exercise results in a significantly lower incidence of CHDs from 59.5% to 25%. Additionally, diabetes‐induced defects in coronary artery and capillary morphogenesis were also lower with exercise. Myocardial cell proliferation and epithelial‐mesenchymal transition at E12.5 was significantly lower with pre‐gestational diabetes which was mitigated with maternal exercise. Cardiac gene expression of Notch1, Snail1, Gata4 and Cyclin D1 was significantly higher in the embryos of diabetic mice that exercised compared to the non‐exercised group. Furthermore, maternal exercise produced lower reactive oxygen species (ROS) and oxidative stress in the foetal heart. In conclusion, maternal exercise mitigates ROS and oxidative damage in the foetal heart, and results in a lower incidence of CHDs in the offspring of pre‐gestational diabetes. Exercise may be an effective intervention to compliment clinical management and further minimize CHD risk in mothers with diabetes.

Polyphonic sound event detection and direction-of-arrival estimation require different input features from audio signals. While sound event detection mainly relies on time-frequency patterns, direction-of-arrival estimation relies on magnitude or phase differences between microphones. Previous approaches use the same input features for sound event detection and direction-of-arrival estimation, and train the two tasks jointly or in a two-stage transfer-learning manner. We propose a two-step approach that decouples the learning of the sound event detection and directional-of-arrival estimation systems. In the first step, we detect the sound events and estimate the directions-of-arrival separately to optimize the performance of each system. In the second step, we train a deep neural network to match the two output sequences of the event detector and the direction-of-arrival estimator. This modular and hierarchical approach allows the flexibility in the system design, and increase the performance of the whole sound event localization and detection system. The experimental results using the DCASE 2019 sound event localization and detection dataset show an improved performance compared to the previous state-of-the-art solutions., to be published in 2020 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)

Many signal processing-based methods for sound source direction-of-arrival estimation produce a spatial pseudo-spectrum of which the local maxima strongly indicate the source directions. Due to different levels of noise, reverberation and different number of overlapping sources, the spatial pseudo-spectra are noisy even after smoothing. In addition, the number of sources is often unknown. As a result, selecting the peaks from these spectra is susceptible to error. Convolutional neural network has been successfully applied to many image processing problems in general and direction-of-arrival estimation in particular. In addition, deep learning-based methods for direction-of-arrival estimation show good generalization to different environments. We propose to use a 2D convolutional neural network with multi-task learning to robustly estimate the number of sources and the directions-of-arrival from short-time spatial pseudo-spectra, which have useful directional information from audio input signals. This approach reduces the tendency of the neural network to learn unwanted association between sound classes and directional information, and helps the network generalize to unseen sound classes. The simulation and experimental results show that the proposed methods outperform other directional-of-arrival estimation methods in different levels of noise and reverberation, and different number of sources. Accepted version This research was conducted at Singtel Cognitive and Artificial Intelligence Lab for Enterprises (SCALE@NTU), which is a collaboration between Singapore Telecommunications Limited (Singtel) and Nanyang Technological University (NTU) that is funded by the Singapore Government through the Industry Alignment Fund - Industry Collaboration Projects Grant. The authors would like to thank Mr. Kenneth Ooi and Mr. Sathish Jayabalan for helping us with the data collection for the experiment.

Polyphonic sound event detection and localization (SELD) task is challenging because it is difficult to jointly optimize sound event detection (SED) and direction-of-arrival (DOA) estimation in the same network. We propose a general network architecture for SELD in which the SELD network comprises sub-networks that are pre-trained to solve SED and DOA estimation independently, and a recurrent layer that combines the SED and DOA estimation outputs into SELD outputs. The recurrent layer does the alignment between the sound classes and DOAs of sound events while being unaware of how these outputs are produced by the upstream SED and DOA estimation algorithms. This simple network architecture is compatible with different existing SED and DOA estimation algorithms. It is highly practical since the sub-networks can be improved independently. The experimental results using the DCASE 2020 SELD dataset show that the performances of our proposed network architecture using different SED and DOA estimation algorithms and different audio formats are competitive with other state-of-the-art SELD algorithms. The source code for the proposed SELD network architecture is available at Github 1.

Background: Ischemic heart injury activates calpains and endoplasmic reticulum (ER) stress in cardiomyocytes. This study investigated whether over-expression of calpastatin, an endogenous calpain inhibitor, protects the heart against myocardial infarction (MI) by inhibiting ER stress. Methods: Mice over-expressing calpastatin (Tg-CAST) and littermate wild type (WT) mice were divided into four groups: WT-sham, Tg-CAST-sham, WT-MI, and Tg-CAST-MI, respectively. WT-sham and Tg- CAST-sham mice showed similar cardiac function at baseline. MI for 7 days impaired cardiac function in WT-MI mice, which was ameliorated in Tg-CAST-MI mice. Results: Tg-CAST-MI mice exhibited significantly decreased diameter of the left ventricular cavity, scar area, and cardiac cell death compared to WT-MI mice. WT-MI mice had higher cardiac expression of C/ EBP homologous protein (CHOP) and BIP, indicators of ER stress, compared to WT-sham mice, indicative of MI-induced ER stress. This increase was abolished in Tg-CAST-MI hearts. Furthermore, administration of tauroursodeoxycholic acid, an inhibitor of ER stress, reduced MI-induced expression of CHOP and BIP, scar area, and myocardial dysfunction. In an in vitro model of oxidative stress, H 2 O 2 stimulation of H9c2 cardiomyoblasts induced calpain activation, CHOP expression, and cell death, all of which were prevented by the calpain inhibitor PD150606, as well as CHOP silencing. Conclusions: Over-expression of calpastatin ameliorates MI-induced myocardial injury in mice. These protective effects of calpastatin are partially achieved through suppression of the ER stress/CHOP pathway.

Obstructive sleep apnea, which involves chronic intermittent hypoxia (CIH), is a major risk factor for developing atrial fibrillation (AF). Whether or not CIH alone alters cardiac mechanisms to support AF is unknown. This study investigated the effects of CIH on atrial electrophysiology and arrhythmia vulnerability and evaluated the role of autonomics in CIH promotion of AF. Adult male Sprague-Dawley rats were exposed to 8 h/day of CIH or normoxia for 7 days. After exposure, rats were anesthetized for intracardiac electrophysiological experiments. Atrial effective refractory periods (AERPs) and AF inducibility were determined using programmed electrical stimulation and burst pacing in the absence and presence of autonomic receptor agonists and antagonists. Western blot analysis measured atrial protein expression of muscarinic M2, M3, and β1-adrenergic receptors. Compared with normoxia-exposed control rats, CIH-exposed rats had enhanced AF vulnerability using both programmed electrical stimulation and burst pacing, accompanied by greater AERP responses to carbachol and propranolol, lesser responses to isoproterenol, and higher atrial M2 receptor protein levels. Enhanced atrial vulnerability was accentuated by carbachol and abolished by atropine, indicating that the AF-promoting effects of CIH depended principally on parasympathetic activation. Enhancement of atrial vulnerability and AERP shortening with cholinergic agonists in CIH-exposed rats is consistent with sensitivity to parasympathetic activation. Higher responses to adrenergic receptor blockade in CIH-exposed rats is consistent with sympathetic potentiation. These findings implicate CIH as an important mediator of enhanced AF susceptibility in obstructive sleep apnea and provide novel insights into the underlying mechanisms. NEW & NOTEWORTHY Our study demonstrates, for the first time, that chronic intermittent hypoxia alone enhances vulnerability to atrial arrhythmia induction, which depends principally on parasympathetic activation. Enhanced atrial vulnerability was accompanied by heightened electrophysiological responses of the atrial myocardium to carbachol and isoproterenol, dampened responses to propranolol, and increased atrial M2 receptor protein levels.

© 2019 Wiley Periodicals, Inc. Introduction: Catheter-tissue contact force is a determinant of radiofrequency (RF) ablation lesion effectiveness. However, ablation on a beating heart is subject to force variability, making it difficult to optimally deliver consistently durable and transmural lesions. This work evaluates improvements in contact force stability and lesion reproducibility by using a catheter contact-force controller (CFC) during lesion delivery in vitro and in vivo. Methods and Results: Using a sheath and force-sensing catheter, an experienced operator attempted to maintain a constant force of 20 g at targets within the atria and left ventricle of a pig manually and using the CFC; the average force and contact-force variation (CFV) achieved using each approach were compared. Ablation lesions (20 W, 30 seconds, 17 mL/min irrigation) were created in bovine tissue samples mounted on a platform programmed to reproduce clinically relevant motion. CFC-assisted lesions were delivered to stationary and moving tissue with forces of 5 to 35 g. Mimicking manual intervention, lesions were also delivered to moving tissue while the CFC was disabled. Resultant lesion volumes were compared using two-way analysis of variance. When using the CFC, the average force was within 1 g of the set level, with a CFV less than 5 g, during both in vitro and in vivo experiments. Reproducible and statistically identical (P =.82) lesion volumes proportional to the set force were achieved in both stationary and moving tissue when the CFC was used. Conclusions: CFC assistance maintains constant force in vivo and removes effect of motion on lesion volume during RF lesion delivery.

Audio classification techniques often depend on the availability of a large labeled training dataset for successful performance. However, in many application domains of audio classification (e.g., wildlife monitoring), obtaining labeled data is still a costly and laborious process. Motivated by this observation, a technique is proposed to efficiently learn a clean template from a few labeled, but likely corrupted (by noise and interferences), data samples. This learning can be done efficiently via tensorial dynamic time warping on the articulation index-based time-frequency representations of audio data. The learned template can then be used in audio classification following the standard template-based approach. Experimental results show that the proposed approach outperforms both (1) the recurrent neural network approach and (2) the state-of-the-art in the template-based approach on a wildlife detection application with few training samples.

Previous studies in our laboratory have shown that muscarinic receptors become uncoupled from G-proteins in brains of patients with Alzheimer’s disease (AD). Interestingly, this process began prior...

Background Remote catheter navigation systems protect interventionalists from scattered ionizing radiation. However, these systems typically require specialized catheters and extensive operator training. Methods A new compact and sterilizable telerobotic system is described, which allows remote navigation of conventional tip-steerable catheters, with three degrees of freedom, using an interface that takes advantage of the interventionalist's existing dexterity skills. The performance of the system is evaluated ex vivo and in vivo for remote catheter navigation and ablation delivery. Results The system has absolute errors of 0.1 ± 0.1 mm and 7 ± 6° over 100 mm of axial motion and 360° of catheter rotation, respectively. In vivo experiments proved the safety of the proposed telerobotic system and demonstrated the feasibility of remote navigation and delivery of ablation. Conclusion The proposed telerobotic system allows the interventionalist to use conventional steerable catheters; while maintaining a safe distance from the radiation source, he/she can remotely navigate the catheter and deliver ablation lesions. Copyright © 2015 John Wiley & Sons, Ltd.

This paper presents an Immersive Telepresence system for Entertainment and Meetings (ITEM). The system aims to provide a radically new video communication experience by seamlessly merging participants into the same virtual space to allow a natural interaction among them and shared collaborative contents. With the goal to make a scalable, flexible system for various business solutions as well as easily accessible by massive consumers, we address the challenges in the whole pipeline of media processing, communication, and displaying in our design and realization of such a system. Particularly, in this paper we focus on the system aspects that maximize the end-user experience, optimize the system and network resources, and enable various teleimmersive application scenarios. In addition, we also present a few key technologies, i.e. fast object-based video coding for real world data and spatialized audio capture and 3D sound localization for group teleconferencing. Our effort is to investigate and optimize the key system components and provide an efficient end-to-end optimization and integration by considering user needs and preferences. Extensive experiments show the developed system runs reliably and comfortably in real time with a minimal setup requirement (e.g. a webcam and/or a depth camera, an optional microphone array, a laptop/desktop connected to the public Internet) for teleimmersive communication. With such a really minimal deployment requirement, we present a variety of interesting applications and user experiences created by ITEM.

In this brief, we present a novel architecture for pseudorandom (PN) code acquisition based on statistical error compensation (SEC), which achieves significant power savings. SEC treats errors in hardware as noise in communication networks, and employs robust estimation theory to compensate for errors. We apply SEC to a 256-tap PN code acquisition filter in a 180- nm CMOS process. Multiple (five) dies were tested under voltage overscaling to achieve a near constant detection probability $(P_{\rm det})$ above 90%. The minimum energy consumption ranged from 72.89 to 210.59 pJ (ave 122.52 pJ) for supply voltages between 0.69 and 0.70 V. These operating conditions result in raw error rates of 85.83%–91.23% (ave 88.99%). Energy savings over a conventional error-free design ranges from $2.4{\times}$ to $5.8{\times}$ (ave $3.86{\times}$ ). Energy savings over past work ranges from $1.55{\times}$ to $3.79{\times}$ (ave $2.52{\times}$ ). Improvement in error-tolerance over existing error-tolerant designs range from $2146{\times}$ to $2281{\times}$ (ave $2225{\times}$ ). The large energy savings were found to be due to a combination of voltage scaling and activity factor reduction. The proposed design achieves a $2.5{\times}$ improvement in the figure of merit $[{\rm normalized~power}/(\#{\rm taps}~^{\ast}~{{\rm precision}~^{\ast}}~{\rm sample~rate})]$ compared with conventional PN code acquisition filters.

Atrial fibrillation is a side effect of ibrutinib, an irreversible inhibitor of Bruton tyrosine kinase used for treatment of B-cell lymphoproliferative disorders. We determined if single (2 or 10 mg/kg), or chronic (14 days) oral ibrutinib followed by 24-hour washout conferred susceptibility to electrically induced arrhythmias in 1-month-old male C57BL/6 mice. A single higher dose of ibrutinib increased arrhythmia inducibility. There was no inducibility difference after chronic dosing with washout. This suggests that high serum drug levels might be responsible for the proarrhythmic effect of ibrutinib and that an altered dosing strategy might mitigate the side effects.

Acoustic beamforming has played a key role in the robust automatic speech recognition (ASR) applications. Accurate estimates of the speech and noise spatial covariance matrices (SCM) are crucial for successfully applying the minimum variance distortionless response (MVDR) beamforming. Reliable estimation of time-frequency (TF) masks can improve the estimation of the SCMs and significantly improve the performance of the MVDR beamforming in ASR tasks. In this paper, we focus on the TF mask estimation using recurrent neural networks (RNN). Specifically, our methods include training the RNN to estimate the speech and noise masks independently, training the RNN to minimize the ASR cost function directly, and performing multiple passes to iteratively improve the mask estimation. The proposed methods are evaluated individually and overally on the CHiME-4 challenge. The results show that the proposed methods improve the ASR performance individually and also work complementarily. The overall performance achieves a word error rate of 8.9% with 6-microphone configuration, which is much better than 12.0% achieved with the state-of-the-art MVDR implementation.

Traditional distributed detection systems are often designed for a single target application. However, with the emergence of the Internet of Things (IoT) paradigm, next-generation systems are expected to be a shared infrastructure for multiple applications. To this end, we propose a modular, cascade design for resource-efficient, multi-task detection systems. Two (classes of) applications are considered in the system, a primary and a secondary one. The primary application has universal features that can be shared with other applications, to reduce the overall feature extraction cost, while the secondary application does not. In this setting, the two applications can collaborate via feature sharing. We provide a method to optimize the operation of the multi-application cascade system based on an accurate resource consumption model. In addition, the inherent uncertainties in feature models are articulated and taken into account. For evaluation, the twin-comparison argument is invoked, and it is shown that, with the optimal feature sharing strategy, a system can achieve 9$\times$ resource saving and 1.43$\times$ improvement in detection performance., Comment: preprint, the published version is in IEEE Journal of Selected Topics in Signal Processing, Special Issue on Cooperative Signal Processing for Heterogeneous and Multi-Task Wireless Sensor Networks, 2017

This paper presents a new approach for the estimation of two-dimensional (2D) direction-of-arrival (DOA) of more sources than sensors using an Acoustic Vector Sensor (AVS). The approach is developed based on Khatri-Rao (KR) product by exploiting the subspace characteristics of the time variant covariance matrices of the uncorrelated quasi-stationary source signals. An AVS is used to measure both the acoustic pressure and pressure gradients in a complete sound field and the DOAs are determined in both horizontal and vertical planes. The identifiability of the presented KR-AVS approach is studied in both theoretic analysis and computer simulations. Computer simulations demonstrated that 2D DOAs of six speech sources are successfully estimated. Superior root mean square error (RMSE) is obtained using the new KR-AVS array approach compared to the other geometries of the non-uniform linear array, the 2D L-shape array, and the 2D triangular array.

Beta-blockers are the standard of care for the treatment of long QT syndrome (LQTS), and have been shown to reduce recurrent syncope and mortality in patients with type 1 LQTS (LQT1). Although beta-blockers have minimal effect on the resting corrected QT interval, their effect on the dynamics of the non-corrected QT interval is unknown, and may provide insight into their protective effects.Twenty-three patients from eight families with genetically distinct mutations for LQT1 performed exercise stress testing before and after beta-blockade. One hundred and fifty-two QT, QTc, and Tpeak-Tend intervals were measured before starting beta-blockers and compared with those at matched identical cycle lengths following beta-blockade. Beta-blockers demonstrated heart-rate-dependent effects on the QT and QTc intervals. In the slowest heart rate tertile (90 b.p.m.), beta-blockade increased the QT and QTc intervals (QT: 405 vs. 409 ms; P = 0.06; QTc: 459 vs. 464 ms; P = 0.06). In the fastest heart rate tertile (100 b.p.m.), the use of beta-blocker was associated with a reduction in both the QT and QTc intervals (QT: 367 vs. 358 ms; P0.0001; QTc: 500 vs. 486 ms; P0.0001). The Tpeak-Tend interval showed minimal change at slower heart rates (90 b.p.m.) (93 vs. 87 ms; P = 0.09) and at faster heart rates (100 b.p.m.) (87 vs. 84 ms; P = NS) following beta-blockade.Beta-blockers have heart-rate-dependent effects on the QT and QTc intervals in LQTS. They appear to increase the QT and QTc intervals at slower heart rates and shorten them at faster heart rates during exercise.

In many species of chorusing frogs, callers can rapidly adjust their call timing with reference to neighboring callers so as to maintain call rate while minimizing acoustic interference. The rules governing the interactions, in particular, who is listening to whom are largely unknown, presumably influenced by distance between callers, caller density, and intensities of interfering calls. We report vocal interactions in a unison bout caller, the green tree frog (Hyla cinerea). Using a microphone array, we monitored bouts from a local group of six callers embedded in a larger chorus. Data were analyzed in a 21-min segment at the peak of the chorus. Callers within this group were localized and their voices were separated for analysis of spatio-temporal interactions. We show that callers in this group: (1) synchronize with one another, (2) prefer to time their calls antiphonally, almost exactly at one-third and two-thirds of the call intervals of their neighbors, (3) tolerate call collision when antiphonal calling is not possible, and (4) perform discrete phase-hopping between three preferred phases when tracking other callers. Further, call collision increases and phase-locking decreases, with increasing inter-caller spacing. We conclude that the precise phase-positioning, phase-tracking, and phase-hopping minimizes acoustic jamming while maintaining chorus synchrony.

Direction-of-arrival (DoA) estimation of incoming electromagnetic signals can play a critical role in surveillance, sensing, and cognitive radio applications. Typical DoA antenna arrays use an aperture measuring several wavelengths across to ensure reliable measurement of phase information. For a UHF application, such an array would need to be a few meters across-too large for a portable array. This work demonstrates a practical DoA array composed of antennas with diverse radiation patterns which is combined with an algorithm which relies primarily on amplitude information rather than phase information. This approach yields a much smaller array with similar direction-finding capabilities to larger ones. A calibration procedure captures the antenna responses, including the parasitic effects of the closely spaced antennas. The calibrated array and direction-finding algorithm then achieves measured accuracy with resolution of six degrees with no front-to-back or quadrant ambiguities.

Equipping everyday objects with sensing and computational capabilities creates the potential to achieve context and situational awareness through the detection of natural events. A major challenge in energy-constrained devices is that the detection of natural events generally demands sophisticated signal modeling and processing, along with continuous sensing. In this paper, we propose to use a cascade architecture to control signal-model complexity; this approach allows the device to sense continuously and trigger a more accurate signal model only when an event of interest is likely to be occurring. The sensitivity of the triggering affects detection performance and device energy consumption, so we formulate and solve the problem of optimal threshold allocation to control this sensitivity. We prove that for controlling signal-model complexity, triggering as often as possible maximizes detection performance; this seemingly intuitive result does not hold in other popular cascading techniques, most notably in low-power wakeup mechanisms. Our analysis leads to a simple threshold-tracking algorithm that can adjust to time-varying environmental conditions and energy supply. Combining a low-power MCU with controllable supply-voltage scaling, we present an acoustic wildlife monitoring system that exhibits 12× energy scalability from cascading detectors, and an additional 2× from synergistic hardware scaling on commercially available components. In practical scenarios, we demonstrate energy savings ranging from 3× to 20× with minimal loss in performance, compared to the conventional approach.

Detection systems in the emerging Internet of Things (IoT) paradigm, unlike existing stovepipe ones, are envisioned to be a platform for multiple applications. As a result, the design for IoT systems often places strong emphasis on modularity, where components can be composed to form various applications. This modular constraint creates new challenges in finding the optimal trade-off between resource consumption and performance of detection systems. This work focuses on the problem of optimizing modular detection systems whose modules are cascade. The solution results in a dynamic-programming-based algorithm that can optimize cascade detection systems with an arbitrary number of modules. Simulation results on both synthetic and real data confirm the superiority of an optimized system against unoptimized ones.

This paper presents an eigenvector clustering approach for estimating the direction of arrival (DOA) of multiple speech signals using a microphone array. Existing clustering approaches usually only use low frequencies to avoid spatial aliasing. In this study, we propose a probabilistic eigenvector clustering approach to use all frequencies. In our work, time-frequency (TF) bins dominated by only one source are first detected using a combination of noise-floor tracking, onset detection and coherence test. For each selected TF bin, the largest eigenvector of its spatial covariance matrix is extracted for clustering. A mixture density model is introduced to model the distribution of the eigenvectors, where each component distribution corresponds to one source and is parameterized by the source DOA. To use eigenvectors of all frequencies, the steering vectors of all frequencies of the sources are used in the distribution function. The DOAs of the sources can be estimated by maximizing the likelihood of the eigenvectors using an expectation-maximization (EM) algorithm. Simulation and experimental results show that the proposed approach significantly improves the root-mean-square error (RMSE) for DOA estimation of multiple speech sources compared to the MUSIC algorithm implemented on the single-source dominated TF bins and our previous clustering approach.

Transcatheter aortic valve implantation is a minimally invasive alternative to open-heart surgery for aortic stenosis in which a stent-based bioprosthetic valve is delivered into the heart on a catheter. Limited visualization during this procedure can lead to severe complications. Improved visualization can be provided by live registration of transesophageal echo (TEE) and fluoroscopy images intraoperatively. Since the TEE probe is always visible in the fluoroscopy image, it is possible to track it using fiducial-based single-perspective pose estimation. In this study, inherent probe tracking performance was assessed, and TEE to fluoroscopy registration accuracy and robustness were evaluated. Results demonstrated probe tracking errors of below 0.6 mm and 0.2°, a 2-D RMS registration error of 1.5 mm, and a tracking failure rate of below 1%. In addition to providing live registration and better accuracy and robustness compared to existing TEE probe tracking methods, this system is designed to be suitable for clinical use. It is fully automatic, requires no additional operating room hardware, does not require intraoperative calibration, maintains existing procedure and imaging workflow without modification, and can be implemented in all cardiac centers at extremely low cost.

Tele-Operated Catheter Ablation, In Vivo. Introduction: The close proximity between the interventionalist and patient during catheter-based interventions for cardiac arrhythmia exposes the interventionalist to harmful radiation. A prototype remote catheter navigation system (RCNS) has been developed to reduce occupational dose. The safety, feasibility of this RCNS and a comparison of remote and conventional navigation techniques is investigated in vivo. Methods: Seven anatomical locations in the right side of the heart in porcine models were chosen as navigation targets. Using fluoroscopy and electrogram analysis, an experienced electrophysiology interventionalist manipulated a radiofrequency (RF) ablation catheter to each target using the RCNS and conventional navigation. Success rate, navigation time, exposure, exposure time and procedure time was recorded for all anatomical targets. Time to integrate the RCNS with the procedure suite was also measured. Results: All targets were successfully reached with the RCNS and conventional navigation. No erratic catheter motion was observed with the RCNS whereas 1 operation failure occurred. The anatomical targets were found to have the largest effect on navigation time (P < 0.05), exposure (P < 0.05), and exposure time (P < 0.01), although the navigation method had little to no effect on the metrics. These results suggest that remote navigation procedures can be performed with navigation times comparable to conventional bedside navigation. Conclusion: Remote navigation with the RCNS may present a safe method of reducing occupational dose, while providing comparable navigation time with conventional bedside navigation. (J Cardiovasc Electrophysiol, Vol. 23, pp. 81-87, January 2012)

Spinal Cord Stimulation Modulates Vagal Atrial Influences. Introduction: Experimental evidence suggests that spinal cord stimulation (SCS) can cause augmentation of parasympathetic influences on the heart via enhanced vagus nerve (VgN) activity. Herein, we investigated whether this might lead to enhanced inducibility of vagally mediated atrial tachyarrhythmias (AT) and whether such actions depend on intact autonomic neural connections with central neurons. Method and Results: Epidural SCS electrodes were implanted at T1-T4 in anesthetized canines. Sinus cycle length prolongation, atrial repolarization changes (191 epicardial electrode sites), and AT inducibility in response to right VgN stimuli applied at the cervical level were determined before and during SCS. VgN-induced sinus cycle length prolongation was potentiated during SCS among the animals with intact neural connections or bilateral vagotomy proximal to the stimulation site, whereas such prolongation was unaffected by SCS among animals with bilateral decentralization of stellate ganglia. Likewise, the atrial surface area in which VgN-induced repolarization wave form changes were identified was significantly augmented during SCS among the former but not among the latter. AT facilitation occurred during SCS in the majority of animals with intact neural connections, particularly among those displaying relatively greater potentiation of vagally mediated sinus cycle length prolongation. Conclusion: The data indicate that SCS may cause potentiation of parasympathetic influences on the atria in response to cervical VgN stimulation. Such SCS effects appear to be mediated via decreased tonic inhibitory sympathetic influences in the presence of intact stellate ganglion connections to central neurons. (J Cardiovasc Electrophysiol, Vol. 22, pp. 440-447)

This paper discusses the use of ground-penetrating radar (GPR) to assess railroad track substructure conditions. An ultra-wide band (UWB) GPR system, having a centre frequency at or higher than 2 GHz, can be used to detect the scattering pattern and to predict air void volume in railroad ballast. A time–frequency technique was implemented to characterise the signal in time and frequency domains simultaneously. Because electromagnetic energy attenuation is highly frequency dependent, the frequency sub-bands of the reflected UWB GPR signal can be analysed separately to quantify the fouling material and quantify moisture content. Additionally, to validate the GPR system capability, a ground truth field survey was conducted. Using ballast samples collected from the field for validation, this paper shows that a time–frequency analysis may provide a new method to measure the thickness of clean ballast, detect the trapped water and assess the ballast fouling and moisture content along the track.

Traditional integrated circuit design achieves error-free operation by designing with margins (clock frequency and supply voltage) and/or including hardware replication and recomputation, which may counter the full energy and area benefits of aggressive technology scaling. It is thus desirable that modern systems-on-chip (SoCs) permit hardware errors while maintaining robust system-level performance. Treating hardware errors as computational noise and extending traditional estimation theory to include practical SoC design constraints yields a novel and general design optimization framework. This work demonstrates the breadth of applicability of the estimation-theoretic framework for system design by showcasing two different application classes that demonstrate 36% to 50% power reduction.

Background— Neuronal nitric oxide synthase (nNOS) is expressed in cardiomyocytes and plays a role in regulating cardiac function and Ca 2+ homeostasis. However, the role of nNOS in cardiac electrophysiology after myocardial infarction (MI) is unclear. We hypothesized that nNOS deficiency increases ventricular arrhythmia and mortality after MI. Methods and Results— MI was induced in wild-type (WT) or nNOS −/− mice by ligation of the left coronary artery. Thirty-day mortality was significantly higher in nNOS −/− compared with WT mice. Additionally, nNOS −/− mice had impaired cardiac function 2 days after MI. Telemetric ECG monitoring showed that compared with WT, nNOS −/− mice had significantly more ventricular arrhythmias and were more likely to develop ventricular fibrillation after MI. Treatment with the L-type Ca 2+ channel blocker verapamil reduced the incidence of arrhythmia and ventricular fibrillation in nNOS −/− mice after MI. To assess the role of nNOS in Ca 2+ handling, patch-clamp and Ca 2+ fluorescence techniques were used. Ca 2+ transients and L-type Ca 2+ currents were higher in nNOS −/− compared with WT cardiomyocytes. Additionally, nNOS −/− cardiomyocytes exhibited significantly higher systolic and diastolic Ca 2+ over a range of pacing frequencies. Treatment with the NO donor S -nitroso N -acetyl-penicillamine decreased Ca 2+ transients and L-type Ca 2+ current in both nNOS −/− and WT cardiomyocytes. Furthermore, S -nitrosylation of Ca 2+ handling proteins was significantly decreased in nNOS −/− myocardium after MI. Conclusions— Deficiency in nNOS increases ventricular arrhythmia and mortality after MI in mice. The antiarrhythmic effect of nNOS involves inhibition of L-type Ca 2+ channel activity and regulation of Ca 2+ handling proteins via S -nitrosylation.

Objective To test an alternative to catheter and open-heart techniques, by documenting the feasibility of implanting an unmodified mechanical aortic valve (AoV) in the off pump, beating heart using the universal cardiac introducer (UCI) attached to the left ventricular (LV) apex. Methods In six pigs, the LV apex was exposed by a median sternotomy. The UCI was attached to the apex. A 12-mm punching tool (punch), introduced through the UCI, was used to create a cylindrical opening through the apex. Then, the AoV, secured to a holder, was introduced into the LV, using transesophageal echocardiographic, guided through the apical LV opening, navigated into the LV outflow tract, and positioned within the aortic annulus. Trans-esophageal echocardiographic guidance was useful for navigation and positioning by superimposing the aortic annulus and prosthetic ring while Doppler imaging verified preserved prosthetic function and absence of perivalvular leaks. The valve function and hemodynamics were observed before termination for macroscopic evaluation. Results The punch produced a clean opening without fragmentation or myocardial embolization. During advancement of the mechanical AoV, there were no arrhythmias, mitral valve dysfunctions, evidence of myocardial ischemia, or hemodynamic instability. The AoVs were well seated over the annulus, without obstructing the coronaries or contact with the conduction system. The ring of AoVs was well circumscribed by the aortic annulus. Conclusions This study documented the feasibility of positioning a mechanical AoV on the closed, beating heart. These results should encourage the development of adjunct technologies to deliver current tissue or mechanical AoV with minimal side effects.

Two-dimensional ultrasound (US) is widely used in minimally invasive cardiac procedures due to its convenience of use and noninvasive nature. However, the low quality of US images often limits their utility as a means for guiding procedures, since it is often difficult to relate the images to their anatomical context. To improve the interpretability of the US images while maintaining US as a flexible anatomical and functional real-time imaging modality, we describe a multimodality image navigation system that integrates 2D US images with their 3D context by registering them to high quality preoperative models based on magnetic resonance imaging (MRI) or computed tomography (CT) images. The mapping from such a model to the patient is completed using spatial and temporal registrations. Spatial registration is performed by a two-step rapid registration method that first approximately aligns the two images as a starting point to an automatic registration procedure. Temporal alignment is performed with the aid of electrocardiograph (ECG) signals and a latency compensation method. Registration accuracy is measured by calculating the TRE. Results show that the error between the US and preoperative images of a beating heart phantom is 1.7plusmn0.4 mm, with a similar performance being observed in in vivo animal experiments.

Erythropoietin (EPO) is a potent cardioprotective agent in models of myocardial ischemia and reperfusion (I/R). It has been suggested recently that EPO may also reduce ventricular arrhythmia after I/R. The present study investigated the role of neuronal nitric oxide synthase (nNOS) on the antiarrhythmic effects of EPO. EPO treatment increased nNOS expression in isolated neonatal mouse ventricular myocytes. Cotreatment with the phosphatidylinositol 3 (PI3)-kinase inhibitor, LY294002 [2-(4-morpholinyl)-8-phenyl-1(4H)-benzopyran-4-one hydrochloride], or treatment of cardiomyocytes infected with a dominant negative adenovirus targeted to Akt1 (ADV-dnAkt1) blocked the effects of EPO on nNOS expression, suggesting that EPO regulates nNOS expression via PI3-kinase and Akt. To examine the in vivo antiarrhythmic effects of EPO, wild-type (WT) and nNOS(-/-) mice were anesthetized and, after a baseline measurement, subjected to myocardial I/R to provoke ventricular arrhythmias. Pretreatment with EPO 24 h before ischemia increased nNOS expression and significantly reduced the number of premature ventricular contractions (PVCs) and the incidence of ventricular tachycardia (VT) in WT mice. In contrast, treatment with EPO had no effect on PVCs or the incidence of VT in nNOS(-/-) mice. Furthermore, EPO treatment after ischemia significantly reduced the threshold dose of cesium chloride (CsCl) to induce VT. We conclude that EPO via nNOS protects the heart from spontaneous and CsCl-induced ventricular arrhythmia during myocardial I/R.

Objective Optimal atrial septal defect (ASD) closure should combine off-pump techniques with the effectiveness and versatility of open-heart techniques. We report our experience with off-pump ASD closure using the Universal Cardiac Introducer (UCI) in a porcine model. The goal was to create an ASD over the fossa ovale (FO) and position a patch over the ASD under ultrasound (US) imaging and augmented virtual reality guidance. Methods An US probe (tracked with a magnetic tracking system) was positioned into the esophagus (transesophageal echocardiographic probe) for real-time image-guidance. The right atrium (RA) of six pigs was exposed via a right lateral thoracotomy or medial sternotomy. The UCI was attached to the RA wall. A punching tool was introduced via the UCI, navigated and positioned, under US guidance, to create an ASD into the FO. A patch with its holder and a stapling device were introduced into the RA via the UCI. The patch was positioned on the ASD. Occlusion of the ASD was determined using US and Doppler imaging. Results The FO membrane was excised successfully in all animals. US image-guidance provided excellent visualization. The patch was positioned in all cases with complete occlusion of the ASD. The stapling device proved too bulky, impeding circumferential positioning. Conclusions Using the UCI, ASD closure was safe and feasible. US imaging, combined with virtual and augmented reality provided accurate navigating and positioning. This study also provided valuable information on the future design of anchoring devices for intracardiac procedures.

Accurate detection of low contrast-to-noise ratio (CNR) blood oxygenation level dependent (BOLD) signals in functional magnetic resonance imaging (fMRI) data is important for presurgical planning and cognitive research. Robust detection is challenging in small regions of low CNR activation since the probability of detecting each individual voxel is low. We present a processing technique for improving the detection of localized low CNR BOLD signals in fMRI data. When applied to synthetic fMRI data, this blind estimation scheme significantly improves the probability of correctly detecting voxels in a small region of activation with a CNR between 0.5 and 1.0 compared to the standard general linear model approach. More activation is detected in expected (based on input stimulus) regions of experimental data after processing with the proposed technique.

Our project is the reintroduction of off-pump intracardiac surgery using the Universal Cardiac Introducer (UCI) for safe intracardiac access. The purpose of this study was to evaluate multimodality visualization using three ultrasound modalities and ultrasound augmented with virtual reality. Image guidance was tested on implanting a mitral valve prosthesis via the UCI in 12 pigs. Initially, two-dimensional (2-D) transesophageal echocardiography (TEE) ultrasound, intravascular ultrasound (intracardiac echocardiography [ICE]), and three-dimensional (3-D) epicardial ultrasound were utilized. Ultrasound augmented with virtual reality was used in the last three experiments. A 2-D TEE assisted navigating the prosthesis into the orifice. Positioning was not intuitive and required trial and error method. A 3-D epicardial ultrasound allowed positioning of the valve into the orifice. Positioning of the clip was difficult because of artifacts with multiple reflections and shadowing. Augmented reality displayed the entire prosthesis and the tools without artifacts; provided intuitive information on navigation, positioning, and orientation of tools; and improved significantly image guidance and surgical skill. Augmented virtual reality, with tracked 2-D or 3-D ultrasound imaging, provides guidance that can effectively substitute for direct vision during beating heart intracardiac surgery.

In the censoring approach to decentralized detection, sensors transmit real-valued functions of their observations when "informative" and save energy by not transmitting otherwise. We address several practical issues in the design of censoring sensor networks including the joint dependence of sensor decision rules, randomization of decision strategies, and partially known distributions. In canonical decentralized detection problems involving quantization of sensor observations, joint optimization of the sensor quantizers is necessary. We show that under a send/no-send constraint on each sensor and when the fusion center has its own observations, the sensor decision rules can be determined independently. In terms of design, and particularly for adaptive systems, the independence of sensor decision rules implies that minimal communication is required. We address the uncertainty in the distribution of the observations typically encountered in practice by determining the optimal sensor decision rules and fusion rule for three formulations: a robust formulation, generalized likelihood ratio tests, and a locally optimum formulation. Examples are provided to illustrate the independence of sensor decision rules, and to evaluate the partially known formulations.

We previously published encircling endocardial cryo-isolation of the pulmonary vein (PV) region. This study documented mechanisms of isolation failure using CARTO® mapping. Cryo-isolation used a modified Surgifrost® introduced via a Universal Cardiac Introducer® on the left atrial appendage. Of five pigs, two had incomplete isolation and repeat mapping: Activation was over Bachmann’s bundle (BB) in one and the coronary sinus (CS) in the other. Repeat cryoablation failed to eliminate gaps. Histologically, the BB gap had nonlesioned sub-epicardial fibres and thick fat covering the cryolesioned BB: fat protecting the epicardium from cryoablation. The inferior gap had a large CS, and a thick myocardium bridging the isthmus: myocardial thickness and CS thermal sink preventing transmural cryolesions. CARTO® mapping localized gaps. Although the CS is known to cause failure, its protective mechanism is not well documented. The BB gap is novel. These findings have important clinical implications for isolation of the PV region.

One of the significant mechanical property variations under long term fatigue is the change in material or component stiffness. So stiffness reduction can be used as a damage parameter to assess damage in composite laminates under fatigue loading. It has been observed that the stiffness decreases monotonically under cyclic loading. One of the main advantages of using stiffness as a damage parameter is, it can be measured nondestructively in service. In this investigation the S–N diagram of two thick section fiberglass/epoxy composites has been determined and their stiffness degradation during fatigue loading has been monitored. A constitutive model has been used to simulate the stiffness degradation of composite laminates under fatigue loading. The sensitivity of model parameters has been tested and the values of the parameters can be determined from the experimental data for different loading conditions. Static tensile tests have also been carried out in order to determine the ultimate strength of this composite. During subsequent fatigue tests loads ranging from 45% to 70% of the ultimate load were applied to each specimen.

Two reasons for the recent rise in radiation exposure from CT are increases in its clinical applicability and the desire to maintain high SNR while acquiring smaller voxels. To address this emerging dose problem, several strategies for reducing patient exposure have already been proposed. One method employed in cardiacimaging is ECG-driven modulation of the tube current between 100% at one time point in the cardiac cycle and a reduced fraction at the remaining phases. In this paper, we describe how images obtained during such acquisition can be used to reconstruct 4D data of consistent high quality throughout the cardiac cycle. In our approach, we assume that the mid-diastole (MD) phase is imaged with full dose. The MD image is then independently registered to lower dose images (lower SNR) at other frames, resulting in a set of transformations. Finally, the transformations are used to warp the MD frame through the cardiac cycle to generate the full 4D image. In addition, the transformations may be interpolated to increase the temporal sampling or to generate images at arbitrary time points. Our approach was validated using various data obtained with simulated and scanner-implemented dose modulation. We determined that as little as 10% of the total dose was required to reproduce full quality images with a 1 mm spatial error and an error in intensity values on the order of the imagenoise. Thus, our technique offers considerable dose reductions compared to standard imaging protocols, with minimal effects on the quality of the final data.

Modern-day train operations rely on wireless communications. Unlike other mobile systems, the train vehicle operations are tightly interwound with and remain physically close to the railway and the trackside infrastructure, providing a suitable platform to deploy leaky-waveguide-based communication. Due to the train system's safety-critical application and its exposure to the public, it is critical to address security in train communications. To investigate the availability of leaky waveguide communications, we first study prior leaky waveguide implementations in train systems and, based on those studies, construct a model to characterize the path loss of inside-waveguide propagation and the repeater implementations. Using our model, we analyze the jamming impact and contrast with jamming in free space without a waveguide. As a result, we establish that jamming the waveguide takes advantage of the waveguide infrastructure to extend its impact beyond the traditional jamming range and breaks the spatial dependence on the jamming source.

Urban railway systems are increasingly relying on information and communications technologies (ICT). This evolution makes cybersecurity an important concern, in addition to the traditional focus on reliability, availability, maintainability and safety. In this paper, we examine two examples of cyberintensive systems in urban railway environments—a communications-based train control system, and a mobile app that provides transit information to commuters—and use them to study the challenges for conducting security analysis in this domain. We show the need for a cyber-physical perspective in order to understand the cross-domain attack/defense and the complicated physical consequence of cyber breaches.We present security analysis results from two different methods that are used in the safety and ICT security engineering domains respectively, and use them as concrete references to discuss the way to move forward.

This paper presents a learning-based approach to the task of direction of arrival estimation (DOA) from microphone array input. Traditional signal processing methods such as the classic least square (LS) method rely on strong assumptions on signal models and accurate estimations of time delay of arrival (TDOA) . They only work well in relatively clean conditions, but suffer from noise and reverberation distortions. In this paper, we propose a learning-based approach that can learn from a large amount of simulated noisy and reverberant microphone array inputs for robust DOA estimation. Specifically, we extract features from the generalised cross correlation (GCC) vectors and use a multilayer perceptron neural network to learn the nonlinear mapping from such features to the DOA. One advantage of the learning based method is that as more and more training data becomes available, the DOA estimation will become more and more accurate. Experimental results on simulated data show that the proposed learning based method produces much better results than the state-of-the-art LS method. The testing results on real data recorded in meeting rooms show improved root-mean-square error (RMSE) compared to the LS method.

Nearly all underwater vehicles and surface ships today use sonar and vision for imaging and navigation. However, sonar and vision systems face various limitations, e.g., sonar blind zones, dark or murky environments, etc. Evolved over millions of years, fish use the lateral line, a distributed linear array of flow sensing organs, for underwater hydrodynamic imaging and information extraction. We demonstrate here a proof-of-concept artificial lateral line system. It enables a distant touch hydrodynamic imaging capability to critically augment sonar and vision systems. We show that the artificial lateral line can successfully perform dipole source localization and hydrodynamic wake detection. The development of the artificial lateral line is aimed at fundamentally enhancing human ability to detect, navigate, and survive in the underwater environment.

Mobile devices primarily processing multimedia data need to support multimedia quality with limited battery energy. To address this challenging problem, researchers have introduced adaptation into multiple system layers, ranging from hardware to applications. Given these adaptive layers, a new challenge is how to coordinate them to fully exploit the adaptation benefits. This paper presents a novel cross-layer adaptation framework, called GRACE-1, that coordinates the adaptation of the CPU hardware, OS scheduling, and multimedia quality based on users' preferences. To balance the benefits and overhead of cross-layer adaptation, GRACE-1 takes a hierarchical approach: It globally adapts all three layers to large system changes, such as application entry or exit, and internally adapts individual layers to small changes in the processed multimedia data. We have implemented GRACE-1 on an HIP laptop with the adaptive Athlon CPU, Linux-based OS, and video codecs. Our experimental results show that, compared to schemes that adapt only some layers or adapt only to large changes, GRACE-1 reduces the laptop's energy consumption up to 31.4 percent while providing better or the same video quality.