Using Granule to Search Privacy Preserving Voice in Home IoT Systems

The Home IoT Voice System (HIVS) such as Amazon Alexa or Apple Siri can provide voice-based interfaces for people to conduct the search tasks using their voice. However, how to protect privacy is a big challenge. This paper proposes a novel personalized search scheme of encrypting voice with privacy-preserving by the granule computing technique. Firstly, Mel-Frequency Cepstrum Coefficients (MFCC) are used to extract voice features. These features are obfuscated by obfuscation function to protect them from being disclosed the server. Secondly, a series of definitions are presented, including fuzzy granule, fuzzy granule vector, ciphertext granule, operators and metrics. Thirdly, the AES method is used to encrypt voices. A scheme of searchable encrypted voice is designed by creating the fuzzy granule of obfuscation features of voices and the ciphertext granule of the voice. The experiments are conducted on corpus including English, Chinese and Arabic. The results show the feasibility and good performance of the proposed scheme

Long noncoding RNA AFAP1-AS1 acts as a competing endogenous RNA of miR-423-5p to facilitate nasopharyngeal carcinoma metastasis through regulating the Rho/Rac pathway

Background: Actin filament-associated protein 1 antisense RNA 1 (AFAP1-AS1), a long noncoding RNA, is significantly highly expressed and associated with metastasis and poor prognosis in many cancers, including nasopharyngeal carcinoma (NPC). In this study, we aim to identify the role of AFAP1-AS1 acting as an oncogenic lncRNA to promote NPC metastasis. Methods: The role of AFAP1-AS1, miR-423-5p, and FOSL2 in NPC metastasis was investigated in vitro and in vivo. Bioinformatics analysis and luciferase activity assays were used to identify the interaction between AFAP1-AS1, miR-423- 5p, and FOSL2. Additionally, real-time PCR and western blotting were used to assess the function of AFAP1-AS1 acting as an oncogenic lncRNA to promote NPC progression by regulating miR-423-5p and the downstream Rho/Rac pathway. Results: In this study, we determined that AFAP1-AS1 functions as a competing endogenous RNA in NPC to regulate the Rho/Rac pathway through miR-423-5p. These interactions can mediate the expression of RAB11B, LASP1, and FOSL2 and accelerate cell migration and invasion via the Rho/Rac signaling pathway or FOSL2. AFAP1-AS1 and FOSL2 could competitively bind with miR-423-5p to regulate several molecules, including RAB11B and LASP1 of the Rho/Rac signaling pathway. AFAP1-AS1 can also regulate the expression of LASP1, which was transcriptionally regulated by FOSL2, resulting in increased migration and invasion of NPC cells via the Rho/Rac signaling pathway. Conclusions: The observations in this study identify an important role for AFAP1-AS1 as a competing endogenous RNA (ceRNA) in NPC pathogenesis and indicate that it may serve as a potential target for cancer diagnosis and treatment

Author Correction: Single-atom Cu anchored catalysts for photocatalytic renewable H2 production with a quantum efficiency of 56%

Correction to: Nature Communications https://doi.org/10.1038/s41467-021-27698-3, published online 10 January 2022.In Supplementary Fig. 28b in the Supplementary PDF for this article, the figure panel incorrectly read ‘345 mW/cm2’ but should have been ‘34.5 mW/cm2’.In the caption of Supplementary Fig. 20 in the Supplementary PDF for this article, the term ‘isotropic analysis’ should have read ‘isotopic analysis’.In the caption of Supplementary Fig. 21 in the Supplementary PDF for this article, the term ‘isotropic analysis’ should have read ‘isotopic analysis’.In the caption of Supplementary Fig. 28b in the Supplementary PDF for this article, the term ‘isotropic test’ should have read ‘isotopic test’

Peripheral Arterial and Venous Response to Tilt Test after a 60-Day Bedrest with and without Countermeasures (ES-IBREP)

We quantified the impact of 60-day head-down bed rest (HDBR) with countermeasures on arterial and venous response to tilt. Methods: Twenty-one males: 7 control (Con), 7 resistive vibration exercise (RVE) and 7 Chinese herb (Herb) were assessed. Subjects were identified as finisher (F) or non-finishers (NF) at the post-HDBR 20-min tilt test. The cerebral (MCA), femoral (FEM) arterial flow velocity and leg vascular resistance (FRI), the portal vein section (PV), the flow redistribution ratios (MCA/FEM; MCA/PV), the tibial (Tib), gastrocnemius (Gast), and saphenous (Saph) vein sections were measured by echography and Doppler ultrasonography. Arterial and venous parameters were measured at 3-min pre-tilt in the supine position, and at 1 min before the end of the tilt. Results: At post-HDBR tilt, MCA decreased more compared with pre-HDBR tilt in the Con, RVE, and Herb groups, the MCA/FEM tended to decrease in the Con and Herb groups (not significant) but remained stable in the RVE gr. FRI dropped in the Con gr, but remained stable in the Herb gr and increased in the RVE gr. PV decreased less in the Con and Herb groups but remained unchanged in the RVE gr. MCA/PV decreased in the Con and Herb groups, but increased to a similar extent in the RVE gr. Gast section significantly increased more in the Con gr only, whereas Tib section increased more in the Con and Herb groups but not in the RVE gr. The percent change in Saph section was similar at pre- and post-HDBR tilt. Conclusion: In the Con gr, vasoconstriction was reduced in leg and splanchnic areas. RVE and Herb contributed to prevent the loss of vasoconstriction in both areas, but the effect of RVE was higher. RVE and Herb contributed to limit Gast distension whereas only RVE had a protective effect on the Tib

Diagnostic value of contrast-enhanced ultrasonography for solitary necrotic nodule of the liver

Objective To summarize the imaging characteristics of solitary necrotic nodule of the liver (SNNL) on contrast-enhanced ultrasonography (CEUS) and to investigate the role CEUS plays in the diagnosis and differential diagnosis of SNNL. Methods Twenty-five lesions of 23 cases diagnosed with SNNL by CEUS were retrospectively analyzed for findings of ultrasonography and contrast enhancement. Results Five patients were confirmed with SNNL by pathological examination of surgically resected liver tissue; necrotic nodule was confirmed in 18 patients by ultrasonographic follow-up or other imaging methods (contrast-enhanced computed tomography or contrast-enhanced magnetic resonance imaging). In 12 of the 25 SNNL lesions, no contrast agent enhancement was observed in all phases; 13 lesions showed thin-ring enhancement around the lesions on the arterial phase images and iso-enhancement with the liver on the portal and delayed phase images without enhancement inside the lesions in all phases. Conclusion The typical imaging of SNNL on CEUS is no enhancement of the whole lesion in all phases or thin-ring enhancement around the lesion with no enhancement inside the lesion in all phases, which is helpful for the differentiation from other space-occupying lesions of the liver

Dynamic Path Flow Estimation Using Automatic Vehicle Identification and Probe Vehicle Trajectory Data: A 3D Convolutional Neural Network Model

Dynamic path flows, referring to the number of vehicles that choose each path in a network over time, are generally estimated with the partial observations as the input. The automatic vehicle identification (AVI) system and probe vehicle trajectories are now popular and can provide rich and complementary trip information, but the data fusion was rarely explored. Therefore, in this paper, the dynamic path flow estimation is based on these two data sources and transformed into a feature learning problem. To fuse the two data sources belonging to different detection ways at the data level, the virtual AVI points, analogous to the real AVI points (turning movements at nodes with AVI detectors), are defined and selected to statically observe the dynamic movement of the probe vehicles. The corresponding selection principles and a programming model considering the distribution of real AVI points are first established. The selected virtual AVI points are used to construct the input tensor, and the turning movement-based observations from both the data sources can be extracted and fused. Then, a three-dimensional (3D) convolutional neural network (CNN) model is designed to exploit the hidden patterns from the tensor and establish the high-dimensional correlations with path flows. As the path flow labels commonly with noises, the bootstrapping method is adopted for model training and the corresponding relabeling principle is defined to purify the noisy labels. The entire model is extensively tested based on a realistic road network, and the results show that the designed CNN model with the presented data fusion method can perform well in training time and estimation accuracy. The robustness of a model to noisy labels is also improved through the bootstrapping method. The dynamic path flows estimated by the trained model can be applied to travel information provision, proactive route guidance, and signal control with high real-time requirements

Permeability Variation Models for Unsaturated Coalbed Methane Reservoirs

A large number of models have been established to describe permeability variation with the depletion of reservoir pressure to date. However, no attempt has been made to draw enough attention to the difference in the effect of various factors on permeability variation in different production stages of unsaturated CoalBed Methane (CBM) reservoirs. This paper summarizes the existing and common permeability models, determines the relationship between various effects (effective stress effect, matrix shrinkage effect and Klinkenberg effect) and desorption characteristics of the recovery of unsaturated CBM reservoirs, then establishes two improved models to quantificationally describe permeability variation, and finally discusses the effects of various factors (gas saturation, cleat porosity, Poisson’s ratio and shrinkage coefficient) on permeability variation. The results show that permeability variation during the recovery of unsaturated CBM reservoirs can be divided into two stages: the first one is that permeability variation is only affected by the effective stress effect, and the second is that permeability variation is affected by the combination of the effective stress effect, matrix shrinkage effect and Klinkenberg effect. In the second stage, matrix shrinkage effect and Klinkenberg effect play much more significant role than the effective stress effect, which leads to an increase in permeability with depletion of reservoir pressure. Sensitivity analysis of parameters in the improved models reveals that those parameters associated with gas saturation, such as gas content, reservoir pressure, Langmuir volume and Langmuir pressure, have a significant impact on permeability variation in the first stage, and the important parameters in the second stage are the gas content, reservoir pressure, Langmuir volume, Langmuir pressure, Poisson’s ratio, Young’s modulus and shrinkage coefficient during the depletion of reservoir pressure. A comparative study of the improved models indicates that the improved SD model has a greater sensitivity to various parameters than the improved PM model and the improved models describe permeability dynamic variation more exactly than the original ones

Permeability Variation Models for Unsaturated Coalbed Methane Reservoirs

A large number of models have been established to describe permeability variation with the depletion of reservoir pressure to date. However, no attempt has been made to draw enough attention to the difference in the effect of various factors on permeability variation in different production stages of unsaturated CoalBed Methane (CBM) reservoirs. This paper summarizes the existing and common permeability models, determines the relationship between various effects (effective stress effect, matrix shrinkage effect and Klinkenberg effect) and desorption characteristics of the recovery of unsaturated CBM reservoirs, then establishes two improved models to quantificationally describe permeability variation, and finally discusses the effects of various factors (gas saturation, cleat porosity, Poisson’s ratio and shrinkage coefficient) on permeability variation. The results show that permeability variation during the recovery of unsaturated CBM reservoirs can be divided into two stages: the first one is that permeability variation is only affected by the effective stress effect, and the second is that permeability variation is affected by the combination of the effective stress effect, matrix shrinkage effect and Klinkenberg effect. In the second stage, matrix shrinkage effect and Klinkenberg effect play much more significant role than the effective stress effect, which leads to an increase in permeability with depletion of reservoir pressure. Sensitivity analysis of parameters in the improved models reveals that those parameters associated with gas saturation, such as gas content, reservoir pressure, Langmuir volume and Langmuir pressure, have a significant impact on permeability variation in the first stage, and the important parameters in the second stage are the gas content, reservoir pressure, Langmuir volume, Langmuir pressure, Poisson’s ratio, Young’s modulus and shrinkage coefficient during the depletion of reservoir pressure. A comparative study of the improved models indicates that the improved SD model has a greater sensitivity to various parameters than the improved PM model and the improved models describe permeability dynamic variation more exactly than the original ones