Perceptual quality prediction for stereoscopic images is of fundamental importance in determining the level of quality perceived by humans in terms of the 3D viewing experience. However, the existing ...no-reference quality assessment (NR-IQA) framework has its limitation in addressing binocular combination for stereoscopic images. In this paper, we propose a new NR-IQA for stereoscopic images using joint sparse representation. We analyze the relationship between left and right quality predictors, and formulate stereoscopic quality prediction as a combination of feature-prior and feature-distribution. Based on this finding, we extract feature vector that handles different features to be interacted by joint sparse representation, and use support vector regression to characterize feature-prior. Meanwhile, we implement feature-distribution using sparsity regularization as the basis of weights for binocular combination to derive the overall quality score. Experimental results on five public 3D IQA databases demonstrate that in comparison with the existing methods, the devised algorithm achieves high consistent alignment with subjective assessment.
The quality assessment of 3D images is more challenging than its 2D counterparts, and little investigation has been dedicated to blind quality assessment of stereoscopic images. In this letter, we ...propose a novel blind quality assessment for stereoscopic images based on binocular feature combination. The prominent contribution of this work is that we simplify the process of binocular quality prediction as monocular feature encoding and binocular feature combination. Experimental results on two publicly available 3D image quality assessment databases demonstrate the promising performance of the proposed method.
Human pose estimation (HPE) is an integral component of numerous applications ranging from healthcare monitoring to human-computer interaction, traditionally relying on vision-based systems. These ...systems, however, face challenges such as privacy concerns and dependency on lighting conditions. As an alternative, short-range radar technology offers a non-invasive, lighting-insensitive solution that preserves user privacy. This paper presents a novel radar-based framework for HPE, SCRP-Radar (space-aware coordinate representation for human pose estimation using single-input single-output (SISO) ultra-wideband (UWB) radar). The methodology begins with clutter suppression and denoising techniques to enhance the quality of radar echo signals, followed by the construction of a micro-Doppler (MD) matrix from these refined signals. This matrix is segmented into bins to extract distinctive features that are critical for pose estimation. The SCRP-Radar leverages the Hrnet and LiteHrnet networks, incorporating space-aware coordinate representation to reconstruct 2D human poses with high precision. Our method redefines HPE as dual classification tasks for vertical and horizontal coordinates, which is a significant departure from existing methods such as RF-Pose, RF-Pose 3D, UWB-Pose, and RadarFormer. Extensive experimental evaluations demonstrate that SCRP-Radar significantly surpasses these methods in accuracy and robustness, consistently exhibiting lower average error rates, achieving less than 40 mm across 17 skeletal key-points. This innovative approach not only enhances the precision of radar-based HPE but also sets a new benchmark for future research and application, particularly in sectors that benefit from accurate and privacy-preserving monitoring technologies.
In this paper, we propose an innovative approach for transforming 2D human pose estimation into 3D models using Single Input–Single Output (SISO) Ultra-Wideband (UWB) radar technology. This method ...addresses the significant challenge of reconstructing 3D human poses from 1D radar signals, a task traditionally hindered by low spatial resolution and complex inverse problems. The difficulty is further exacerbated by the ambiguity in 3D pose reconstruction, as multiple 3D poses may correspond to similar 2D projections. Our solution, termed the Radar PoseLifter network, leverages the micro-Doppler signatures inherent in 1D radar echoes to effectively convert 2D pose information into 3D structures. The network is specifically designed to handle the long-range dependencies present in sequences of 2D poses. It employs a fully convolutional architecture, enhanced with a dilated temporal convolutions network, for efficient data processing. We rigorously evaluated the Radar PoseLifter network using the HPSUR dataset, which includes a diverse range of human movements. This dataset comprises data from five individuals with varying physical characteristics, performing a variety of actions. Our experimental results demonstrate the method’s robustness and accuracy in estimating complex human poses, highlighting its effectiveness. This research contributes significantly to the advancement of human motion capture using radar technology. It presents a viable solution for applications where precision and reliability in motion capture are paramount. The study not only enhances the understanding of 3D pose estimation from radar data but also opens new avenues for practical applications in various fields.
Multi-modal fusion can exploit complementary information from various modalities and improve the accuracy of prediction or classification tasks. In this paper, we propose a parallel, multi-modal, ...factorized, bilinear pooling method based on a semi-tensor product (STP) for information fusion in emotion recognition. Initially, we apply the STP to factorize a high-dimensional weight matrix into two low-rank factor matrices without dimension matching constraints. Next, we project the multi-modal features to the low-dimensional matrices and perform multiplication based on the STP to capture the rich interactions between the features. Finally, we utilize an STP-pooling method to reduce the dimensionality to get the final features. This method can achieve the information fusion between modalities of different scales and dimensions and avoids data redundancy due to dimension matching. Experimental verification of the proposed method on the emotion-recognition task using the IEMOCAP and CMU-MOSI datasets showed a significant reduction in storage space and recognition time. The results also validate that the proposed method improves the performance and reduces both the training time and the number of parameters.
Objective: To determine the relationships between BMI and workforce participation and the presence of work limitations in a U.S. working‐age population.
Research Methods and Procedures: We used data ...from the Panel Study of Income Dynamics, a nationwide prospective cohort, to estimate the effect of obesity in 1986 on employment and work limitations in 1999. Individuals were classified into the following weight categories: underweight (BMI < 18.5), normal weight (18.5 ≤ BMI < 25), overweight (25 ≤ BMI < 30), and obese (BMI ≥ 30). Using multivariable probit models, we estimated the relationships between obesity and both employment and work disability. All analyses were stratified by sex.
Results: After adjusting for baseline sociodemographic characteristics, smoking status, exercise, and self‐reported health, obesity was associated with reduced employment at follow‐up men: marginal effect (ME) −4.8 percentage points (pp); p < 0.05; women: ME −5.8 pp; p < 0.10. Among employed women, being either overweight or obese was associated with an increase in self‐reported work limitations when compared with normal‐weight individuals (overweight: ME +3.9 pp; p < 0.01; obese: ME +12.6 pp; p < 0.01). Among men, the relationship between obesity and work limitations was not statistically significant.
Discussion: Obesity appears to result in future productivity losses through reduced workforce participation and increased work limitations. These findings have important implications in the U.S., which is currently experiencing a rise in the prevalence of obesity.
Purpose
This study aims to analyze passenger service quality in Beijing West Railway Station from the perspective of passengers, to better understand the current service quality and obtain the areas ...of weakness for improvement.
Design/methodology/approach
The research investigates the passenger experience of service in Beijing West Railway Station by using a questionnaire survey. The service quality (SERVQUAL) evaluation method is used to analyze the survey data, and it divides the passenger service into 5 attributes with 20 indicators. This research uses the Likert five-level scale method to process data and calculates the SERVQUAL value and weight difference of each attribute to evaluate the passenger service. Therefore, the deficiencies have been pointed out, so the station manager can improve the passenger service accordingly.
Findings
It is indicated that among the five studied attributes, Beijing West Railway Station has the smallest service quality value in terms of timeliness, which means this part needs the largest improvement. To the five attributes, each lacks in station security check, ticketing efficiency, station identification accuracy, emergency processing of train delays and the restroom environment, respectively.
Originality/value
The research can provide specific suggestions for the optimization of the passenger service of Beijing West Railway Station, and provide reference information for the formulation of policies.
To evaluate the adaptation of different lithium disilicate glass-ceramic crown and whether different fabrication processes affect the adaptation of crowns.
Thirty epoxy dies crowns were divided into ...3 groups. They were cemented to domestic lithium disilicate glass-ceramic crowns in Group A, to IPS e.max CAD crowns in Group B and to IPS e.max Press crowns in Group C respectively. All crowns were cut by cutting machine. A confocal laser scanning microscope was used to measure the gap between crown tissue surface and die.
There were significant differences in the three groups of measurement points(P<0.05). Within the groups, specimens in group A showed in the lowest marginal fit(46.8±9.1 μm). Those in group B showed the lowest shoulder suitability(59.3±7.9 μm), axial plane(50.5±3.6 μm) and occlusal surface(87.6±11.6 μm. Those in group C demonstrated the lowest axial plane angle(84.4±10.1) μm. In addition to the axial plane angle, the CAD/CAM system exhibited good accuracy of fit.
The three groups of li
Quality assessment of 3D images encounters more challenges than its 2D counterparts. Directly applying 2D image quality metrics is not the solution. In this paper, we propose a new full-reference ...quality assessment for stereoscopic images by learning binocular receptive field properties to be more in line with human visual perception. To be more specific, in the training phase, we learn a multiscale dictionary from the training database, so that the latent structure of images can be represented as a set of basis vectors. In the quality estimation phase, we compute sparse feature similarity index based on the estimated sparse coefficient vectors by considering their phase difference and amplitude difference, and compute global luminance similarity index by considering luminance changes. The final quality score is obtained by incorporating binocular combination based on sparse energy and sparse complexity. Experimental results on five public 3D image quality assessment databases demonstrate that in comparison with the most related existing methods, the devised algorithm achieves high consistency with subjective assessment.
Aspartyl dipeptidase (dipeptidase E) can hydrolyze Asp-X dipeptides (where X is any amino acid), and the enzyme plays a key role in the degradation of peptides as nutrient sources. Dipeptidase E ...remains uncharacterized in
Streptomyces
. Orf2 from
Streptomyces
sp. 139 is located in the exopolysaccharide biosynthesis gene cluster, which may be a novel dipeptidase E with “S134-H170-D198” catalytic triad by sequence and structure comparison. Herein, recombinant Orf2 was expressed in
E. coli
and characterized dipeptidase E activity using the Asp-
ρ
NA substrate. The optimal pH and temperature for Orf2 are 7.5 and 40 ℃;
V
max and
K
m of Orf2 are 0.0787 mM·min
−1
and 1.709 mM, respectively. Orf2 exhibits significant degradation activities to Asp-Gly-Gly, Asp-Leu, Asp-His, and isoAsp-Leu and minimal activities to Asp-Pro and Asp-Ala. Orf2 contains a Ser-His-Asp catalytic triad characterized by point mutation. In addition, the Asp147 residue of Orf2 is also proven to be critical for the enzyme’s activity through molecular docking and point mutation. Transcriptome analysis reveals the upregulation of genes associated with ribosomes, amino acid biosynthesis, and aminoacyl-tRNA biosynthesis in the
orf2
mutant strain. Compared with the
orf2
mutant strain and WT, the yield of crude polysaccharide does not change significantly. However, crude polysaccharides from the
orf2
mutant strain exhibit a wider range of molecular weight distribution. The results indicate that the Orf2 links nutrient stress to secondary metabolism as a novel dipeptidase E.
Key points
• A novel dipeptidase E with a Ser-His-Asp catalytic triad was characterized from Streptomyces sp. 139.
• Orf2 was involved in peptide metabolism both in vitro and in vivo.
• Orf2 linked nutrient stress to mycelia formation and secondary metabolism in Streptomyces.
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