Speech Acquisition and Automatic Speech Recognition for Integrated Spacesuit Audio Systems

A voice-command human-machine interface system has been developed for spacesuit extravehicular activity (EVA) missions. A multichannel acoustic signal processing method has been created for distant speech acquisition in noisy and reverberant environments. This technology reduces noise by exploiting differences in the statistical nature of signal (i.e., speech) and noise that exists in the spatial and temporal domains. As a result, the automatic speech recognition (ASR) accuracy can be improved to the level at which crewmembers would find the speech interface useful. The developed speech human/machine interface will enable both crewmember usability and operational efficiency. It can enjoy a fast rate of data/text entry, small overall size, and can be lightweight. In addition, this design will free the hands and eyes of a suited crewmember. The system components and steps include beam forming/multi-channel noise reduction, single-channel noise reduction, speech feature extraction, feature transformation and normalization, feature compression, model adaption, ASR HMM (Hidden Markov Model) training, and ASR decoding. A state-of-the-art phoneme recognizer can obtain an accuracy rate of 65 percent when the training and testing data are free of noise. When it is used in spacesuits, the rate drops to about 33 percent. With the developed microphone array speech-processing technologies, the performance is improved and the phoneme recognition accuracy rate rises to 44 percent. The recognizer can be further improved by combining the microphone array and HMM model adaptation techniques and using speech samples collected from inside spacesuits. In addition, arithmetic complexity models for the major HMMbased ASR components were developed. They can help real-time ASR system designers select proper tasks when in the face of constraints in computational resources

Methanol extract of Aruncus dioicus exerts antidiabetic effect via PCSK9/LDLR pathway

Purpose: To investigate the antidiabetic effect of methanol extract of Aruncus dioicus, and the underlying mechanism(s). Methods: Twenty-four adult female albino mice were randomly assigned to four groups of six mice each: normal control group, diabetic control group and two treatment groups. With the exception of normal control group, the diabetic control and treatment groups consisted of leptin receptor-deficient (db/db) type 2 diabetic mice. The diabetic control group was not treated, while the treatment groups received 200 or 400 mg/kg extract/day orally for 4 weeks. The effect of the extract on fasting blood glucose (FBG), proprotein convertase subtilisin/kexin type 9 (PCSK9), glycogen and lipid profiles were determined. The expressions of PCSK9, low-density lipoprotein receptor (LDL-R) and glucokinase (GCK) were determined in liver tissues using western blotting and real-time quantitative polymerase chain reaction (qRT-PCR). Results: Fasting blood glucose (FBG) was significantly and dose-dependently reduced in the treatment groups, relative to diabetic control group at different time-points (p < 0.05). Total cholesterol (TC), triacylglycerol (TG), low-density lipoprotein cholesterol (LDL-C) and high-density lipoprotein cholesterol (HDL-C) were significantly higher in the diabetic control group than in normal control group (p < 0.05). However, treatment with methanol extract of A. dioicus significantly and dose-dependently reversed the changes in the levels of these parameters (p < 0.05). The expressions of LDLR and GCK were significantly down-regulated in diabetic control group, when compared with normal control group, but their expressions were significantly dose-dependently upregulated in the treatment groups (p < 0.05). Treatment with the extract significantly and dose-dependently down-regulated PCSK9 expression (p < 0.05). Liver injury characterized by large distended lipid droplets and fat accumulation was seen in diabetic mice, but treatment with methanol extract of A. dioicus significantly reversed the histopathological changes induced by DM. Conclusion: These results indicate that the antidiabetic effect of methanol extract of A. dioicus is exerted via a mechanism involving PCSK9/LDLR pathway

Evaluating the quantum optimal biased bound in a unitary evolution process

Seeking the available precision limit of unknown parameters is a significant task in quantum parameter estimation. One often resorts to the widely utilized quantum Cramer-Rao bound (QCRB) based on unbiased estimators to finish this task. Nevertheless, most actual estimators are usually biased in the limited number of trials. For this reason, we introduce two effective error bounds for biased estimators based on a unitary evolution process in the framework of the quantum optimal biased bound. Furthermore, we show their estimation performance by two specific examples of the unitary evolution process, including the phase encoding and the SU(2) interferometer process. Our findings will provide an useful guidance for finding the precision limit of unknown parameters.Comment: 11 pages, 3 figures, welcome comment

ZenG:AR neurofeedback for meditative mixed reality

In this paper we present ZenG, a neurofeedback ARapplication concept based on Zen Gardening to fostercreativity, self-awareness, and relaxation through embodiedinteractions in a mixed reality environment. We developedan initial prototype which combined physiological sensingthrough EEG with AR visualisation on the Magic LeapDisplay. We evaluated the prototype through preliminaryuser testing with 12 adults. Results suggest users found theexperience to be enjoyable and relaxing, however theapplication could be improved by including more featuresand functionality. ZenG shows the potential for AR toprovide immersive and interactive environments that couldpromote creativity and relaxation, providing solid groundsfor further research

Nipah virus attachment glycoprotein ectodomain delivered by type 5 adenovirus vector elicits broad immune response against NiV and HeV

Nipah virus (NiV) and Hendra virus (HeV) are newly emerging dangerous zoonotic pathogens of the Henipavirus genus of the Paramyxoviridae family. NiV and HeV (HNVs) which are transmitted by bats cause acute respiratory disease and fatal encephalitis in humans. To date, as there is a lack of antiviral drugs or effective antiviral therapies, the development of vaccines against those two viruses is of primary importance, and the immunogen design is crucial to the success of vaccines. In this study, the full-length protein (G), the ectodomain (Ge) and the head domain (Gs) of NiV attachment glycoprotein were delivered by the replication-defective type 5 adenovirus vector (Ad5) respectively, and the recombinant Ad5-NiV vaccine candidates (Ad5-NiVG, Ad5-NiVGe and Ad5-NiVGs) were constructed and their immunogenicity were evaluated in mice. The results showed that all the vaccine candidates stimulated specific humoral and cellular immune responses efficiently and rapidly against both NiV and HeV, and the Ad5-NiVGe elicited the strongest immune responses after a single-dose immunization. Furthermore, the potent conserved T-cell epitope DTLYFPAVGFL shared by NiV and HeV was identified in the study, which may provide valid information on the mechanism of HNVs-specific cellular immunity. In summary, this study demonstrates that the Ad5-NiVGe could be a potent vaccine candidate against HNVs by inducing robust humoral and cellular immune responses

Improving Virtual Reality safety precautions with depth sensing.

Virtual Reality (VR) technology provides a computer-generated three-dimensional environment, in which the user can interact with virtual objects in real time and walk naturally with the locomotion techniques. However, because of the fully immersive design of VR headsets, free walking with VR headsets may result in people colliding with surrounding obstacles and cause serious physical injury. Securing users' safety is a prerequisite for any VR experience no matter in which kinds of circumstances. To improve VR interaction safety, virtual safety walls textured with a grid, such as HTC Chaperone and Oculus Guardian, have been widely adopted by many VR companies to remind users of safe interaction boundaries. However, they cannot provide detailed geometrical information of the environment, and limit users to stay within a small interactive space. In this thesis, we developed two Augmented Virtuality (AV) interfaces that integrate depth sensing of surroundings into the VR scene for safety precautions, 1) a 3D Virtual Monochrome Grid (3DVMG), and 2) a 3D Virtual Coloured Grid (3DVCG). For 3DVCG, colours vary according to the distance objects are away from the user. We then conducted a user study to evaluate the usability of our proposed interfaces, and to investigate whether VR interaction safety can be improved with depth sensing and colour cues while the user navigates in VR. 2D Outlines of Surroundings (2DOoS) was used as a control. There are two main findings from the experiment. First, with either of 3D interfaces, participants can navigate the virtual environment more confidently. Second, the colour visualization provides more hints to users for determining distances between real objects and their own positions and provide better assistance in avoiding obstructions than only superimposing the depth clues

Assessing spatial variability of soil organic carbon and total nitrogen in eroded hilly region of subtropical China.

The hilly red soil region of southern China suffers from severe soil erosion that has led to soil degradation and loss of soil nutrients. Estimating the content and spatial variability of soil organic carbon (SOC) and soil total nitrogen (STN) and assessing the influence of topography and land-use type on SOC and STN after years of soil erosion control are important for vegetation restoration and ecological reconstruction. A total of 375 topsoil samples were collected from Changting County, and their SOC and STN distributions were studied by using descriptive statistics and geostatistical methods. Elevation, slope, aspect and land-use type were selected to investigate the impacts of natural and human factors on the spatial heterogeneity of SOC and STN. The mean SOC and STN concentrations were 15.85 and 0.98 g kg-1 with moderate spatial variations, respectively. SOC and STN exhibited relatively uniform distributions that decreased gradually from the outside parts to the center of the study area. The SOC and STN contents in the study area were still at moderate and low levels after years of erosion control, which suggests that soil nutrient improvement is a slow process. The lowest SOC and STN values were at lower elevations in the center of Changting County. The results indicated that the SOC and STN contents increased most significantly with elevation and slope due to the influence of topography on the regional natural environment and soil erosion in the eroded hilly region. No significant variations were observed among different slope directions and land-use types

Labor Cost Analysis for Pome Production in Different Cultivation Modes in Hebei Province

Taking the traditional fruit pear as the example, this paper analyzes labor cost for pome production in Hebei Province, based on the representative cases and the research of pome production in different cultivation modes. Firstly, it conducts cost analysis for medium-density pome production in Xinji City, focusing on the comparison of the costs for the main production labor in standard thin planting mode and dwarf close planting mode. According to the research results, labor cost has a great influence on the total production cost of pome. The methods to reduce labor cost include: adopting dwarfing rootstock close planting and intensively efficient pome cultivation method; simplifying the pruning method when matching up the shape of tree; improving soil by the methods of natural grasses and addition of organic materials, and increasing mechanized operation

RGBD Salient Object Detection, Based on Specific Object Imaging

RGBD salient object detection, based on the convolutional neural network, has achieved rapid development in recent years. However, existing models often focus on detecting salient object edges, instead of objects. Importantly, detecting objects can more intuitively display the complete information of the detection target. To take care of this issue, we propose a RGBD salient object detection method, based on specific object imaging, which can quickly capture and process important information on object features, and effectively screen out the salient objects in the scene. The screened target objects include not only the edge of the object, but also the complete feature information of the object, which realizes the detection and imaging of the salient objects. We conduct experiments on benchmark datasets and validate with two common metrics, and the results show that our method reduces the error by 0.003 and 0.201 (MAE) on D3Net and JLDCF, respectively. In addition, our method can still achieve a very good detection and imaging performance in the case of the greatly reduced training data

Displacement damage effects on CMOS APS image sensors induced by neutron irradiation from a nuclear reactor

The experiments of displacement damage effects on CMOS APS image sensors induced by neutron irradiation from a nuclear reactor are presented. The CMOS APS image sensors are manufactured in the standard 0.35 μm CMOS technology. The flux of neutron beams was about 1.33 × 108 n/cm2s. The three samples were exposed by 1 MeV neutron equivalent-fluence of 1 × 1011, 5 × 1011, and 1 × 1012 n/cm2, respectively. The mean dark signal (KD), dark signal spike, dark signal non-uniformity (DSNU), noise (VN), saturation output signal voltage (VS), and dynamic range (DR) versus neutron fluence are investigated. The degradation mechanisms of CMOS APS image sensors are analyzed. The mean dark signal increase due to neutron displacement damage appears to be proportional to displacement damage dose. The dark images from CMOS APS image sensors irradiated by neutrons are presented to investigate the generation of dark signal spike