SG is an effective bariatric procedure with a lasting effect on EWL. Compared with gastric bypasses, there is no difference in EWL at the time point of 24 months.

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The results show that RAS is feasible and safe. It appears to be an alternative to OS due to lower intraoperative blood loss and potentially fewer postoperative complications, as well as shorter hospital stay. Though, RAS is not superior to CLS.

In this work, we propose an algorithm for acoustic source localization based on time delay of arrival (TDOA) estimation. In earlier work by other authors, an initial closed-form approximation was first used to estimate the true position of the speaker followed by a Kalman filtering stage to smooth the time series of estimates. In the proposed algorithm, this closed-form approximation is eliminated by employing a Kalman filter to directly update the speaker's position estimate based on the observed TDOAs. In particular, the TDOAs comprise the observation associated with an extended Kalman filter whose state corresponds to the speaker's position. We tested our algorithm on a data set consisting of seminars held by actual speakers. Our experiments revealed that the proposed algorithm provides source localization accuracy superior to the standard spherical and linear intersection techniques. Moreover, the proposed algorithm, although relying on an iterative optimization scheme, proved efficient enough for real-time operation.

IMPORTANCE Negative pressure wound therapy (NPWT) is an established treatment option, but there is no evidence of benefit for subcutaneous abdominal wound healing impairment (SAWHI). OBJECTIVE To evaluate the effectiveness and safety of NPWT for SAWHI after surgery in clinical practice. DESIGN, SETTING, AND PARTICIPANTSThe multicenter, multinational, observer-blinded, randomized clinical SAWHI study enrolled patients between August 2, 2011, and January 31, 2018. The last follow-up date was June 11, 2018. The trial included 34 abdominal surgical departments of hospitals in Germany, Belgium, and the Netherlands, and 539 consecutive, compliant adult patients with SAWHI after surgery without fascia dehiscence were randomly assigned to the treatment arms in a 1:1 ratio stratified by study site and wound size using a centralized web-based tool. A total of 507 study participants (NPWT, 256; CWT, 251) were assessed for the primary end point in the modified intention-to-treat (ITT) population.INTERVENTIONS Negative pressure wound therapy and conventional wound treatment (CWT). MAIN OUTCOMES AND MEASURESThe primary outcome was time until wound closure (delayed primary closure or by secondary intention) within 42 days. Safety analysis comprised the adverse events (AEs). Secondary outcomes included wound closure rate, quality of life (SF-36), pain, and patient satisfaction. RESULTSOf the 507 study participants included in the modified ITT population, 287 were men (56.6%) (NPWT, 155 [60.5%] and CWT, 132 [52.6%]) and 220 were women (43.4%) (NPWT, 101 [39.5%] and CWT 119 [47.4%]). The median (IQR) age of the participants was 66 (18) years in the NPWT arm and 66 (20) years in the CWT arm. Mean time to wound closure was significantly shorter in the NPWT arm (36.1 days) than in the CWT arm (39.1 days) (difference, 3.0 days; 95% CI 1.6-4.4; P < .001). Wound closure rate within 42 days was significantly higher with NPWT (35.9%) than with CWT (21.5%) (difference, 14.4%; 95% CI, 6.6%-22.2%; P < .001). In the therapy-compliant population, excluding study participants with unauthorized treatment changes (NPWT, 22; CWT, 50), the risk for wound-related AEs was higher in the NPWT arm (risk ratio, 1.51; 95% CI, 0.99-2.35).CONCLUSIONS AND RELEVANCE Negative pressure wound therapy is an effective treatment option for SAWHI after surgery; however, it causes more wound-related AEs. TRIAL REGISTRATION ClinicalTrials.gov Identifier: NCT01528033 JAMA Surg. 2020;155(6):469-478.

In this paper, we present a novel approach for tracking a lecturer during the course of his speech. We use features from multiple cameras and microphones, and process them in a joint particle filter framework. The filter performs sampled projections of 3D location hypotheses and scores them using features from both audio and video. On the video side, the features are based on foreground segmentation, multiview face detection and upper body detection. On the audio side, the time delays of arrival between pairs of microphones are estimated with a generalized cross correlation function. Computationally expensive features are evaluated only at the particles' projected positions in the respective camera images, thus the complexity of the proposed algorithm is low. We evaluated the system on data that was recorded during actual lectures. The results of our experiments were 36 cm average error for video only tracking, 46 cm for audio only, and 31 cm for the combined audio-video system.

In prior work, we proposed using an extended Kalman filter to directly update position estimates in a speaker localization system based on time delays of arrival. We found that such a scheme provided superior tracking quality as compared with the conventional closed-form approximation methods. In this work, we enhance our audio localizer with video information. We propose an algorithm to incorporate detected face positions in different camera views into the Kalman filter without doing any explicit triangulation. This approach yields a robust source localizer that functions reliably both for segments wherein the speaker is silent, which would be detrimental for an audio only tracker, and wherein many faces appear, which would confuse a video only tracker. We tested our algorithm on a data set consisting of seminars held by actual speakers. Our experiments revealed that the audio-video localizer functioned better than a localizer based solely on audio or solely on video features.

In this work, we consider an acoustic beamforming application where two speakers are simultaneously active. We construct one subband-domain beamformer in generalized sidelobe canceller (GSC) configuration for each source. In contrast to normal practice, we then jointly optimize the active weight vectors of both GSCs to obtain two output signals with minimum mutual information (MMI). Assuming that the subband snapshots are Gaussian-distributed, this MMI criterion reduces to the requirement that the cross-correlation coefficient of the subband outputs of the two GSCs vanishes. We also compare separation performance under the Gaussian assumption with that obtained from several super-Gaussian probability density functions (pdfs), namely, the Laplace, K0, and Γ pdfs. Our proposed technique provides effective nulling of the undesired source, but without the signal cancellation problems seen in conventional beamforming. Moreover, our technique does not suffer from the source permutation and scaling ambiguities encountered in conventional blind source separation algorithms. We demonstrate the effectiveness of our proposed technique through a series of far-field automatic speech recognition experiments on data from the PASCAL Speech Separation Challenge (SSC). On the SSC development data, the simple delay-and-sum beamformer achieves a word error rate (WER) of 70.4%. The MMI beamformer under a Gaussian assumption achieves a 55.2% WER, which is further reduced to 52.0% with a K0 pdf, whereas the WER for data recorded with a close-talking microphone is 21.6%.