Source Separation of Unknown Numbers of Single-Channel Underwater Acoustic Signals Based on Autoencoders

The separation of single-channel underwater acoustic signals is a challenging problem with practical significance. Few existing studies focus on the source separation problem with unknown numbers of signals, and how to evaluate the performances of the systems is not yet clear. We propose a solution with a fixed number of output channels to address these two problems, enabling it to avoid the dimensional disaster caused by the permutation problem induced by the alignment of outputs to targets. Specifically, we propose a two-step algorithm based on autoencoders and a new performance evaluation method for situations with mute channels. Experiments conducted on simulated mixtures of radiated ship noise show that the proposed solution can achieve similar separation performance to that attained with a known number of signals. The proposed algorithm achieved competitive performance as two algorithms developed for known numbers of signals, which is highly explainable and extensible and get the state of the art under this framework.Comment: 14 pages, 4 figures, 3 tables. For codes, see https://github.com/QinggangSUN/unknown_number_source_separatio

Design and Operation of Biomass Circulating Fluidized Bed Boiler with High Steam Parameter

Two circulating fluidized bed(CFB) boilers with capacity of 12 MWe and 25 MWe, respectively, with biomass as fuel, adopting the basic technology independently developed by Institute of Engineering Thermophysics (IET), Chinese Academy of Sciences, have been in commercial operation since March 2010 in China. This paper focuses on the design principles, the design specifications and operating results of the two CFB boilers

Conditional Knockout of Raptor/mTORC1 Results in Dentin Malformation

mTORC1 signaling plays an important role in extracellular and intracellular signals, including growth factors, nutrients, energy metabolism, and stress. However, the functional role of mTORC1 in dentinogenesis is unknown. To study the role of Raptor/mTORC1 in dentinogenesis, an Raptorfl/fl; Osx-Cre (Rap-Osx) mouse, in which Raptor was conditionally deleted in odontoblasts and dental mesenchymal cells, was generated, and postnatal tooth development was compared between Rap-Osx mice and control littermates. Rap-Osx mice presented a phenotype known as dentinogenesis imperfecta and had smaller tooth volume, a thinner dentin layer and a larger pulp chamber. The proliferation and differentiation of odontoblasts/preodontoblasts were attenuated in mutant mice, which was likely responsible for the defects in dentinogenesis. Raptor/mTORC1-pS6K1 signaling was inactivated during tooth development in Rap-Osx mice, whereas it was activated in control mice. These results indicate that Raptor/mTORC1 plays a critical role in dentinogenesis via promoting odontoblasts/preodontoblasts proliferation and differentiation. Raptor/mTORC1 might regulate tooth development through the pS6K1 signaling pathway

A no-reference optical flow-based quality evaluator for stereoscopic videos in curvelet domain

Most of the existing 3D video quality assessment (3D-VQA/SVQA) methods only consider spatial information by directly using an image quality evaluation method. In addition, a few take the motion information of adjacent frames into consideration. In practice, one may assume that a single data-view is unlikely to be sufficient for effectively learning the video quality. Therefore, integration of multi-view information is both valuable and necessary. In this paper, we propose an effective multi-view feature learning metric for blind stereoscopic video quality assessment (BSVQA), which jointly focuses on spatial information, temporal information and inter-frame spatio-temporal information. In our study, a set of local binary patterns (LBP) statistical features extracted from a computed frame curvelet representation are used as spatial and spatio-temporal description, and the local flow statistical features based on the estimation of optical flow are used to describe the temporal distortion. Subsequently, a support vector regression (SVR) is utilized to map the feature vectors of each single view to subjective quality scores. Finally, the scores of multiple views are pooled into the final score according to their contribution rate. Experimental results demonstrate that the proposed metric significantly outperforms the existing metrics and can achieve higher consistency with subjective quality assessment

A developmental approach to robotic pointing via human–robot interaction

This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/3.0/)The ability of pointing is recognised as an essential skill of a robot in its communication and social interaction. This paper introduces a developmental learning approach to robotic pointing, by exploiting the interactions between a human and a robot. The approach is inspired through observing the process of human infant development. It works by first applying a reinforcement learning algorithm to guide the robot to create attempt movements towards a salient object that is out of the robot's initial reachable space. Through such movements, a human demonstrator is able to understand the robot desires to touch the target and consequently, to assist the robot to eventually reach the object successfully. The human-robot interaction helps establish the understanding of pointing gestures in the perception of both the human and the robot. From this, the robot can collect the successful pointing gestures in an effort to learn how to interact with humans. Developmental constraints are utilised to drive the entire learning procedure. The work is supported by experimental evaluation, demonstrating that the proposed approach can lead the robot to gradually gain the desirable pointing ability. It also allows that the resulting robot system exhibits similar developmental progress and features as with human infants

Sparse representation based stereoscopic image quality assessment accounting for perceptual cognitive process

In this paper, we propose a sparse representation based Reduced-Reference Image Quality Assessment (RR-IQA) index for stereoscopic images from the following two perspectives: 1) Human visual system (HVS) always tries to infer the meaningful information and reduces uncertainty from the visual stimuli, and the entropy of primitive (EoP) can well describe this visual cognitive progress when perceiving natural images. 2) Ocular dominance (also known as binocularity) which represents the interaction between two eyes is quantified by the sparse representation coefficients. Inspired by previous research, the perception and understanding of an image is considered as an active inference process determined by the level of “surprise”, which can be described by EoP. Therefore, the primitives learnt from natural images can be utilized to evaluate the visual information by computing entropy. Meanwhile, considering the binocularity in stereo image quality assessment, a feasible way is proposed to characterize this binocular process according to the sparse representation coefficients of each view. Experimental results on LIVE 3D image databases and MCL database further demonstrate that the proposed algorithm achieves high consistency with subjective evaluation

Physical Activity and Survival After Prostate Cancer

AbstractBackgroundDespite the high global prevalence of prostate cancer (PCa), few epidemiologic studies have assessed physical activity in relation to PCa survival.ObjectiveTo evaluate different types, intensities, and timing of physical activity relative to PCa survival.Design, setting, and participantsA prospective study was conducted in Alberta, Canada, in a cohort of 830 stage II–IV incident PCa cases diagnosed between 1997 and 2000 with follow-up to 2014 (up to 17 yr). Prediagnosis lifetime activity was self-reported at diagnosis. Postdiagnosis activity was self-reported up to three times during follow-up.Outcome measurements and statistical analysisCox proportional hazards models related physical activity to all-cause and PCa-specific deaths and to first recurrence/progression of PCa.Results and limitationsA total of 458 deaths, 170 PCa-specific deaths, and, after first follow-up, 239 first recurrences/progressions occurred. Postdiagnosis total activity (>119 vs ≤42 metabolic equivalent [MET]-hours/week per year) was associated with a significantly lower all-cause mortality risk (hazard ratio [HR]: 0.58; 95% confidence interval [CI], 0.42–0.79; p value for trend <0.01). Postdiagnosis recreational activity (>26 vs ≤4 MET-hours/week per year) was associated with a significantly lower PCa-specific mortality risk (HR: 0.56; 95% CI, 0.35–0.90; p value for trend = 0.01). Sustained recreational activity before and after diagnosis (>18–20 vs <7–8 MET-hours/week per year) was associated with a lower risk of all-cause mortality (HR: 0.66; 95% CI, 0.49–0.88). Limitations included generalisability to healthier cases and an observational study design.ConclusionsThese findings support emerging recommendations to increase physical activity after the diagnosis of PCa and would inform a future exercise intervention trial examining PCa outcomes.Patient summaryIn a 17-yr prostate cancer (PCa) survival study, men who survived at least 2 yr who were more physically active postdiagnosis or performed more recreational physical activity before and after diagnosis survived longer. Recreational physical activity after diagnosis was associated with a lower risk of PCa death

No-reference stereoscopic image-quality metric accounting for left and right similarity map and spatial structure degradation

Blind quality assessment of 3D images is used to confront more real challenges than 2D images. In this Letter, we develop a no-reference stereoscopic image quality assessment (SIQA) model based on the proposed left and right (LR)-similarity map and structural degradation. In the proposed method, local binary pattern features are extracted from the cyclopean image that are effective for describing the distortion of 3D images. More importantly, we first propose the LR-similarity map that can indicate the stereopair quality and demonstrate that the use of LR-similarity information results in a consistent improvement in the performance. The massive experimental results on the LIVE 3D and IRCCyN IQA databases demonstrate that the designed model is strongly correlated to subjective quality evaluations and competitive to the state-of-the-art SIQA algorithms