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Accurate and robust calibration of multifocal plenoptic cameras is essential for high-precision 3D light field reconstruction. In this work, we propose a blur feature-guided cascaded calibration for the plenoptic camera. First, white images at different aperture values are used to estimate the high-confidence center point and radius of micro-images, and the defocus theory is used to estimate the initial values of the intrinsic parameters. Second, the gradient value is introduced to quantify the degree of blurring of the corner points, which are then divided into three types: clear, semi-clear, and blurred. Furthermore, a joint geometric constraint model of epipolar lines and virtual depth is constructed, and the coordinates of the semi-clear and blurred corner points are optimized in a step-by-step manner by using the clear corner point coordinates. The micro-image center ray projection equation is then devised to assist in the optimization of the microlens array core parameters and establish blur-adaptive credibility weights, thereby constructing a global nonlinear optimization. Finally, the proposed method is tested on both simulated and captured datasets, and the results exhibit superior performance when compared with the established methods described by Labussière, Nousias, and Liu. The proposed method excels in corner feature extraction, calibration accuracy of both internal and external parameters, and calibration sensitivity when applied to multifocal-length light field cameras, highlighting its advantages and robustness.

ZNF800 is a novel gene affecting the malignant progression of several cancers. However, the involvement of ZNF800 in the malignant evolution of lower-grade gliomas (LGG) and poor prognosis of patients remains unclear. This study comprehensively revealed the association between ZNF800 and LGG malignant progression by analyzing 958 clinical samples from multiple public databases. The mRNA and protein expression levels of ZNF800 were higher in LGG tissues than in non-LGG tissues and were associated with malignant clinical features associated with a poor prognosis. High ZNF800 expression was closely related to the infiltration of some immune cells, particularly CD8 + T cells and dendritic cell activation. ZNF800 was positively associated with several immune checkpoint genes, such as CD274 and PDCD1 encoding PD-1 and PD-L1, respectively. Moreover, knocking down ZNF800 can significantly inhibit the proliferation and invasion ability of glioma cells. Therefore, ZNF800 can be used as an effective biomarker for LGG diagnosis and prognosis and can provide a theoretical basis for potential targets of combined immunotherapy in patients with LGG.

The shale reservoir consists mainly of mud shale, characterized by its unique physical and chemical properties, extensive bedding, and micro-cracks. As a result, it is susceptible to hydration and dispersion, leading to the instability of the wellbore during drilling. To address this issue, chemical or physical methods are necessary to enhance the wellbore integrity and ensure stability during the drilling process. This paper focuses on simulating the biomimetic mineralization process to study the composite membrane structure formed by the deposition of montmorillonite and polyelectrolyte. The study investigates the reinforcement effect of the composite membrane on the wellbore wall. By examining the morphology and structure of montmorillonite and BPEI deposition films, the influence of deposition times and polyelectrolyte variations on the deposition film is analyzed. Additionally, the mechanical properties of the montmorillonite and BPEI deposition film are evaluated. The investigation also employs simulated drilling fluid circulation deposition to assess the reinforcement effect of the deposition film on the well wall. Experimental results indicate that the deposition film formed by montmorillonite and BPEI demonstrates a certain level of effectiveness in improving wellbore stability. These findings provide a solid basis for further research on process technology and offer new insights for ensuring the safety of shale oil reservoir drilling.

Thermophilicity is a very important property of proteins, as it sometimes determines denaturation and cell death. Thus, methods for predicting thermophilic proteins and non-thermophilic proteins are of interest and can contribute to the design and engineering of proteins. In this article, we describe the use of feature dimension reduction technology and LIBSVM to identify thermophilic proteins. The highest accuracy obtained by cross-validation was 96.02% with 119 parameters. When using only 16 features, we obtained an accuracy of 93.33%. We discuss the importance of the different characteristics in identification and report a comparison of the performance of support vector machine to that of other methods.

Bearings of rail vehicles bear various dynamic forces. Any fault of the bearing seriously threatens running safety. For fault diagnosis, vibration and temperature measured from the bogie and acoustic signals measured from trackside are often used. However, installing additional sensing devices on the bogie increases manufacturing cost while trackside monitoring is susceptible to ambient noise. For other application, structural displacement based on computer vision is widely applied for deflection measurement and damage identification of bridges. This article proposes to monitor the health condition of the rail vehicle bearings by detecting the displacement of bolts on the end cap of the bearing box. This study is performed based on an experimental platform of bearing systems. The displacement is monitored by computer vision, which can image real-time displacement of the bolts. The health condition of bearings is reflected by the amplitude of the detected displacement by phase correlation method which is separately studied by simulation. To improve the calculation rate, the computer vision only locally focuses on three bolts rather than the whole image. The displacement amplitudes of the bearing system in the vertical direction are derived by comparing the correlations of the image’s gray-level co-occurrence matrix (GLCM). For verification, the measured displacement is checked against the measurement from laser displacement sensors, which shows that the displacement accuracy is 0.05 mm while improving calculation rate by 68%. This study also found that the displacement of the bearing system increases with the increase in rotational speed while decreasing with static load.

Berry firmness is one of the main selection criteria for table grape breeding. However, the underlying genetic determinants and mechanisms involved in gene expression during berry development are still poorly understood. In this study, eighteen libraries sampled from Vitis vinifera L. cv. 'Red Globe' and 'Muscat Hamburg' at three developmental stages (preveraison, veraison and maturation) were analyzed by RNA sequencing (RNA-Seq). The firmness of 'Red Globe' was significantly higher than that of 'Muscat Hamburg' at the three developmental stages. In total, a set of 4,559 differentially expressed genes (DEGs) was identified between 'Red Globe' and 'Muscat Hamburg' in the preveraison (2,259), veraison (2030) and maturation stages (2682), including 302 transcription factors (TFs). Weighted gene coexpression network analysis (WGCNA) showed that 23 TFs were predicted to be highly correlated with fruit firmness and propectin content. In addition, the differential expression of the PE, PL, PG, [beta]-GAL, GATL, WAK, XTH and EXP genes might be the reason for the differences in firmness between 'Red Globe' and 'Muscat Hamburg'. The results will provide new information for analysis of grape berry firmness and softening.

The structure from motion (SfM) method has achieved great success in 3D sparse reconstruction, but it still faces serious challenges in large-scale scenes. Existing hybrid SfM methods usually do not fully consider the compactness between images and the connectivity between subclusters, resulting in a loose spatial distribution of images within subclusters, unbalanced connectivity between subclusters, and poor robustness in the merging stage. In this paper, an efficient and robust hybrid SfM method is proposed. First, the multifactor joint scene partition measure and the preassignment balanced image expansion algorithm among subclusters are constructed, which effectively solves the loose spatial distribution of images in subclusters problem and improves the degree of connection among subclusters. Second, the global GlobalACSfM method is used to complete the local sparse reconstruction of the subclusters under the cluster parallel framework. Then, a decentralized dynamic merging rule considering the connectivity of subclusters is proposed to realize robust merging among subclusters. Finally, public datasets and oblique photography datasets are used for experimental verification. The results show that the method proposed in this paper is superior to the state-of-the-art methods in terms of accuracy and robustness and has good feasibility and advancement prospects.

Mesh simplification is an effective way to solve the contradiction between 3D models and limited transmission bandwidth and smooth model rendering. The existing mesh simplification algorithms usually have problems of texture distortion, deformation of different degrees, and no texture simplification. In this paper, a model simplification algorithm suitable for 3D reconstruction is proposed by taking full advantage of the recovered 3D scene structure and calibrated images. First, the reference 3D model scene is constructed on the basis of the original mesh; second, the images are collected on the basis of the reference 3D model scene; then, the mesh and texture are simplified by using the reference image set combined with the QEM algorithm. Lastly, the 3D model data of a town in Tengzhou are used for experimental verification. The results show that the algorithm proposed in this paper basically has no texture distortion and deformation problems in texture simplification and can effectively reduce the amount of texture data, with good feasibility.

Background Glucose metabolic disorder is associated with the risk of heart failure (HF). Adiposity is a comorbidity that is inextricably linked with abnormal glucose metabolism in older individuals. However, the effect of adiposity on the association between glucose metabolic disorder and HF risk, and the underlying mechanism remain unclear. Methods A total of 13,251 participants aged ≥ 60 years from a cohort study were categorized into euglycemia, prediabetes, uncontrolled diabetes, and well-controlled diabetes. Adiposity was assessed using body mass index (BMI), waist-to-hip ratio (WHR), and visceral fat area (VFA). Adiposity-associated metabolic activities were evaluated using adiponectin-to-leptin ratio (ALR), homeostatic model assessment of insulin resistance (HOMA-IR), and triglyceride-glucose index (TyG). The first occurrence of HF served as the outcome during the follow-up period. Results A total of 1,138 participants developed HF over the course of an average follow-up period of 10.9 years. The rate of incident HF occurrence was higher in prediabetes, uncontrolled diabetes, and well-controlled diabetes participants compared to that in euglycemia participants. However, the high rates were significantly attenuated by BMI, VFA, and WHR. For WHR in particular, the hazard ratio for incident HF was 1.18 (95% confidence interval (CI): 1.03, 1.35, P adj. =0.017) in prediabetes, 1.59 (95% CI: 1.34, 1.90, P adj. <0.001) in uncontrolled diabetes, and 1.10 (95% CI: 0.85, 1.43, P adj. =0.466) in well-controlled diabetes. The population attributable risk percentage for central obesity classified by WHR for incident HF was 30.3% in euglycemia, 50.0% in prediabetes, 48.5% in uncontrolled diabetes, and 54.4% in well-controlled diabetes. Adiposity measures, especially WHR, showed a significant interaction with glucose metabolic disorder in incident HF (all P adj. <0.001). ALR was negatively associated and HOMA-IR and TyG were positively associated with BMI, WHR, VFA, and incident HF (all P adj. <0.05). ALR, HOMA-IR, and TyG mediated the associations for BMI, WHR and VFA with incident HF (all P adj .<0.05). Conclusions Adiposity attenuated the association of glucose metabolic disorder with incident HF. The results also showed that WHR may be an appropriate indicator for evaluating adiposity in older individuals. Adiposity-associated metabolic activities may have a bridging role in the process of adiposity attenuating the association between glucose metabolic disorder and incident HF. Trial registration retrospectively registered number: ChiCTR-EOC-17,013,598.

Existing evidence on the relationship between cardiovascular health (CVH) metrics and cardiovascular disease (CVD) was primarily derived from western populations. We aimed to evaluate the benefits of ideal CVH metrics on preventing incident atherosclerotic CVD (ASCVD) in Chinese population. This study was conducted among 93,987 adults from the China-PAR project (Prediction for ASCVD Risk in China) who were followed up until 2015. Cox proportional hazard regression models were used to estimate the hazard ratios (HRs) and their corresponding 95% confidence intervals (CIs) of CVH metrics for the risk of ASCVD, including coronary heart disease (CHD), stroke and ASCVD death. We further estimated the population-attributable risk percentage (PAR%) of these metrics in relation to each outcome. We observed gradient inverse associations between the number of ideal CVH metrics and ASCVD incidence. Compared with participants having ≤2 ideal CVH metrics, the multivariable-adjusted HRs (95% CIs) of ASCVD for those with 3, 4, 5, 6 and 7 ideal CVH metrics were 0.83 (0.74–0.93), 0.66 (0.59–0.74), 0.55 (0.48–0.61), 0.44 (0.38–0.50) and 0.24 (0.18–0.31), respectively (P for trend <0.0001). Approximately 62.1% of total ASCVD, 38.7% of CHD, 66.4% of stroke, and 60.5% of ASCVD death were attributable to not achieving all the seven ideal CVH metrics. After adjusting effects of ideal health factors, having four ideal health behaviors could independently bring adults health benefits in preventing 17.4% of ASCVD, 18.0% of CHD, 16.7% of stroke, and 10.1% of ASCVD death. Among all the seven CVH metrics, to keep with ideal blood pressure (BP) implied the largest public health gains against various ASCVD events (PAR% between 33.0% and 47.2%), while ideal diet was the metric most difficult to be achieved in the long term. Our study indicates that the more ideal CVH metrics adults have, the less ASCVD burden there is in China. Special efforts of health education and behavior modification should be made on keeping ideal BP and dietary habits in general Chinese population to prevent the epidemic of ASCVD.