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Objective Quantitative Real-time PCR (qPCR) is used to detect the differential expression of Circular RNAs in patients of Premature Ovarian Insufficiency (POI), in order to explore the new biomarkers of POI that can be detected from blood as soon as possible. Methods The study collected plasma samples from 30 patients in POI group and 30 normal people group that meet the inclusion criteria, who visited the gynecology clinic of The First Affiliated Hospital of Guangzhou University of Chinese Medicine from July 2019 to December 2020. Then circRNAs in plasmawere extracted for qPCR validation. Results 1. qPCR technology was performed on hsa_circRNA_008901 and hsa_circRNA_403959, and it was found that the levels of both were considerably downregulated in POI group. Clinical evaluation showed that both hsa_circRNA_008901 and hsa_circRNA_403959 have good diagnostic value for POI. 2. According to miRNA Regulatory Element (MRE) analysis, the predicted target miRNAs of hsa_circRNA_008901 are: hsa-miR-548c-3p, hsa-miR-924, hsa-miR-4677-5p, hsa-miR-6786 -3p and hsa-miR-7974; the predicted target miRNAs of hsa_circRNA_403959 are: hsa-miR-1207-5p, hsa-miR-4691-5p, hsa-miR-4763-3p, hsa-miR-6807-5p and hsa -miR-7160-5p. Conclusion Compared with the normal group, the expression levels of hsa_circRNA_008901 and hsa_circRNA_403959 in the POI group were downregulated, suggesting that these two circRNAs may be potential biomarkers of POI. Bioinformatics analysis indicated that hsa_circRNA_008901 and hsa_circRNA_403959 may regulate their binding miRNA through the action form of “molecular sponge", and then regulate the signaling pathway regulated by miRNA, and ultimately affect the disease progression of POI.

Background. Zishen Yutai Pills (ZSYTP) is a prescription based on traditional Chinese medicine used to treat kidney-deficient pattern in traditional Chinese medicine. It is also widely used clinically for the treatment of polycystic ovary syndrome (PCOS) with positive results. This study aims to explore the potential pharmacological mechanism of ZSYTP for the treatment of PCOS by a network pharmacology approach. Methods. Compounds were collected from the Traditional Chinese Medicine Systems Pharmacology Database and Analysis Platform and Bioinformatics Analysis Tool for Molecular mechanism of Traditional Chinese Medicine and TCM Database@ Taiwan, and the corresponding targets were retrieved from PubChem, Swiss Target Prediction, STITCH, and DrugBank. Meanwhile, PCOS targets were retrieved from the GeneCards database, the Online Mendelian Inheritance in Man database, National Center for Biotechnology Information Database, and DrugBank. Subsequently, multiple network construction and gene enrichment analyses were conducted with Cytoscape 3.8.2 software. Based on the previous results in the study, molecular docking simulations were done. Results. 205 active compounds and 478 ZSYTP target genes were obtained after screening by ADME consideration. 1881 disease-related targets were obtained after removing duplicates. 148 intersection target genes between drug and disease targets were isolated. Gene ontology enrichment analysis and Kyoto Encyclopedia of Genes and Genomes analysis highlighted multiple gene functions and different signaling pathways to treat PCOS. Further molecular docking demonstrated the practicality of in vivo action of ZSYTP to a certain extent. Conclusions. It is possible that the pharmacological effect of ZSYTP on PCOS is linked to the hypoxia-inducible factor 1 (HIF-1) signaling pathway, improving insulin resistance, the variation on gene expression such as RNA splicing, and regulation of mRNA metabolic process. This study paves the way for further research investigating its mechanisms.

Depth images play an important role and are prevalently used in many computer vision and computational imaging tasks. However, due to the limitation of active sensing technology, the captured depth images in practice usually suffer from low resolution and noise, which prevents its further applications. To remedy this problem, in this paper, we first propose an adaptive data fidelity formulation to optimally generate each depth pixel from a mixture probability distribution, characterizing the similarity both in the depth map and the corresponding high-resolution guided color image. The proposed method is able to fit the distribution of the input depth signal as an optimization problem by maximizing the mixture probability. Furthermore, to promote the piecewise property that depth images exhibit, we propose a transferred graph Laplacian model as a regularization term, which is general and able to handle various depth recovery tasks such as super-resolution and denoising well. Specifically, each pixel within the recovered depth image is represented as a vertex in a graph with weights in connected edges representing the similarity between vertices. By minimizing the squared variations of the image signal, the task of depth image recovery can be converted to the problem of graph-based image filtering. Since the proposed graph Laplacian regularization model is able to fully exploit a priori information about the depth image, a much more accurate and robust estimation of the underlying depth can be obtained. Extensive experiment evaluations verify that the proposed method obtains recovered depth with higher quality in terms of both objective and subjective criteria, compared with most of the state-of-the-art methods.

In this paper, the strain energy density (SED) is used to study the over-examination to tire in flywheel test induced by pressure correction process. Flywheel test is the main method for evaluating tire durability, which cannot be measured on flat ground due to the variable road conditions. “Pressure Correction” is a necessary step in flywheel tests, but this process can lead to an over-examination of tire durability, which means the tire durability will be underestimated. However, it is impossible to obtain the tire durability from ideal flat ground test, so this paper utilizes the finite element method (FEM) to simulate the tire rolling condition on flat ground and differently sized flywheels, and the SED is used to evaluate the over-examination of tire durability in flywheel test. According to the results, a flywheel with too small diameter has a large amount of over-examination, and the amount caused by a large flywheel is acceptable. This methodology can be a guideline to assess the over-examination on different sized flywheel tests relative to the flat ground, and for the certain tire in this study, flywheels with 3–5 times the tire diameter appear to have an acceptable over-examination.

Stress shielding is an important factor in the internal fixation of a fracture. To explore the regularity of stress shielding in internal fixation, a simplified model of a comminuted femoral shaft fracture bridged by a locking plate was established and finite element analysis was performed to analyze the load distribution between the plate and femur from the proximal end of the femur to the fracture line and investigate the stress shielding degree of the plate on the bone. The stress, deformation, and axial compressive force distribution of four internal fixation schemes under compression were obtained, and the stress shielding degrees on each section was calculated. To compare the regularity of stress shielding and flow distribution, the relationship between the compressive force increment and stress shielding degree was established. The normalized curves of compressive force increment with the plate section position were compared with the flow distribution in a Z-type manifold, a parallel pipe system similar to an internal fixation system in structure and working characteristics. For quantitative comparison, the similarity between normalized curves of the compressive force increment and simulated flow distribution was calculated. The regularity of load distribution along the section position of the plate was similar to the flow distribution in the Z-type manifold. Therefore, the flow distribution pattern of the Z-type manifold can be used to characterize the regularity of load distribution in internal fixation. This study provided a new method to characterize the stress shielding degree of a locking plate on bone.

In this paper, we propose a variable rate image compression framework for low bit-rate image compression task. Unlike most of the variational auto-encoder (VAE) based methods, our proposal is able to achieve continuously variable rate in a single model by introducing a pair of gain units into VAE. Besides, a content adaptive optimization is applied to adapt the latent representation to the specific content while keeping the parameters of the network and the predictive model fixed. After that, due to the variable rate characteristics of our method, each image can be compressed into any quality level through a unified codec. Finally, an efficient rate control algorithm is designed to find the optimal bit allocation scheme under the constraint of the low rate challenge.

With the development of deep learning techniques, the combination of deep learning with image compression has drawn lots of attention. Recently, learned image compression methods had exceeded their classical counterparts in terms of rate-distortion performance. However, continuous rate adaptation remains an open question. Some learned image compression methods use multiple networks for multiple rates, while others use one single model at the expense of computational complexity increase and performance degradation. In this paper, we propose a continuously rate adjustable learned image compression framework, Asymmetric Gained Variational Autoencoder (AG-VAE). AG-VAE utilizes a pair of gain units to achieve discrete rate adaptation in one single model with a negligible additional computation. Then, by using exponential interpolation, continuous rate adaptation is achieved without compromising performance. Besides, we propose the asymmetric Gaussian entropy model for more accurate entropy estimation. Exhaustive experiments show that our method achieves comparable quantitative performance with SOTA learned image compression methods and better qualitative performance than classical image codecs. In the ablation study, we confirm the usefulness and superiority of gain units and the asymmetric Gaussian entropy model., Accepted by CVPR 2021

When exposed to heavy-ion radiation, metallic glasses (MGs) often exhibit an excellent irradiation tolerance at room temperature compared with their crystalline counterparts; however, their structural evolution and mechanical response at elevated temperature is largely unknown. Here, the phase stability and crystallization behavior of ZrTiHfCuBeNi MG were investigated by irradiating it with an 8.0 MeV Xe29+ ion beam at 550°C. Nanocrystal precipitation randomly appeared in the MG matrix at low fluences, which overlapped and aggregated at higher fluences. In addition, non-edge-on faulted dislocations were formed between neighboring grains due to irradiation-induced stress. Moreover, delays in the first pop-in events after irradiation were attributed to irradiation-induced structural rearrangement and the precipitation of nanocrystals. This work sheds light on the structural evolution and mechanical properties of MGs when irradiated at elevated temperature.

When exposed to He radiation, metallic glasses (MGs) often undergo a unique transformation and mechanical evolution, unlike their crystalline counterparts. However, the relationship between He bubble evolution and the mechanical response is largely unknown. Here, a localized hardness change along ion irradiation direction was discovered under the condition that He ion irradiation does not induced nanocrystallizaiton. The location of the localized hardening peak shifted to the right, and this was accompanied by nucleation and growth of the He bubbles as the fluence increased. Besides, coalescence and overlap of the He bubbles were observed in the central of the bubble layer at the highest fluence. The localized hardness change was quantified by a model based on the He bubbles size and density. The results of this study provide insights into the effect of He bubbles on mechanical evolution and pave the way for designing MGs suitable for the nuclear industry.

In this paper we address the problem of autonomous Impedance Mapping (IM) of an environment using a team of mobile robots. IM of a domain provides the boundary information required to model the sound propagation in the domain. We equip the robots with a speaker and two microphones and utilize the two-microphone reflection method to estimate the normal surface impedance of the boundaries. Specifically, while a speaker robot plays white noise, a listener robot measures the pressure values at two adjacent points next to the sample and uses this data to estimate its impedance. We model the collaborative IM task using Linear Temporal Logic and design motion plans that allow the robots to switch between speaker and listener roles while maintaining desired distances from each other and the samples, and measure the impedance of every boundary segment. We present experimental results and validate our impedance measurements by comparing to a standard method.

Fracture toughness is one of the crucial mechanical properties of brittle materials such as glasses and ceramics which demonstrate catastrophic failure modes. Conventional standardized testing methods adopted for fracture toughness determination require large specimens to satisfy the plane strain condition. As for small specimens, indentation is a popular, sometimes exclusive testing mode to determine fracture toughness for it can be performed on a small flat area of the specimen surface. This review focuses on the development of indentation fracture theories and the representative testing methods. Cracking pattern dependent on indenter geometry and material property plays an important role in modeling, and is the main reason for the diversity of indentation fracture theories and testing methods. Along with the simplicity of specimen requirement is the complexity of modeling and analysis which accounts for the semi-empirical features of indentation fracture tests. Some unresolved issues shaping the gap between indentation fracture tests and standardization are also discussed.

The existing single depth image super-resolution (SR) methods suppose that the image to be interpolated is noise free. However, the supposition is invalid in practice because noise will be inevitably introduced in the depth image acquisition process. In this paper, we address the problem of image denoising and SR jointly based on designing sparse graphs that are useful for describing the geometric structures of data domains. In our method, we first cluster similar patches in a noisy depth image and compute an average patch. Different from the majority of the graph Fourier transform (GFT) that assumed an underlying 4-connected graph structure with vertical and horizontal edges only, we select more general sparse graph structures and edges weights based on the difference of the blocks' structure tensors. For the average patch, a graph template with edges orthogonal to the principal gradient is designed. Finally, the graph based transform (GBT) dictionary is learned from the derived correlation graph for signal representation. As shown in our experimental results, the proposed method obtains a lot of improvement in performance.

This study investigated ion-irradiation performance and mechanical behavior of high-entropy metallic glasses (HE-MGs) irradiated at room temperature. The critical fluence for blister formation in ZrTiHfCuBeNi HE-MGs was higher than ZrTiHfCuBe HE-MGs because of the larger mixing entropy and negative mixing enthalpy. The ZrTiHfCuBeNi HE-MGs maintained a more moderate hardness value than ZrTiHfCuBe HE-MGs at a fluence of 1.0 × 1018 ions/cm2, implying a better irradiation tolerance and capacity of helium atoms. There was not a serrated flow or pop-in event that occurred in the HE-MGs after ion irradiation, which indicated that the formation of serrations was restricted. The total displacement and peak intensity in the creep relaxation spectrum increased as the ion fluence increased. The ZrTiHfCuBeNi HE-MGs exhibited a lesser change in peak intensity and relaxation time. This study demonstrated that HE-MGs may exhibit a favorable response to high levels of helium implantation, which exhibits potential uses under extreme irradiation conditions.

We propose a novel single image super-resolution (SR) algorithm based on the projective dictionary pair learning with anchored neighborhood regression. Different from previous dictionary learning methods that aim to learn only a synthesis or an analysis dictionary, our method would learn both types of dictionaries jointly for regression to achieve image SR. We first cluster the training features into K clusters in order to learn synthesis and analysis dictionaries. Moreover, we learn the regressions with the training samples at training phase and use them on reconstruction stage. As shown in our experimental results, the proposed method obtains high-quality SR results quantitatively and visually against state-of-the-art methods.

Structural relaxation by isothermal annealing below the glass transition temperature is conducted on a Zr 64.13 Cu 15.75 Ni 10.12 Al 10 bulk metallic glass. The effect of structural relaxation on thermal and mechanical properties was investigated by differential scanning calorimetry and instrumented nanoindentation. The recovery of the enthalpy in the DSC curves indicates that thermally unstable defects were annihilated through structural relaxation. During nanoindentation, the structural relaxation did not have a significant influence on the serrated plastic flow behavior. However, Structural relaxation shows an obvious effect in increasing both the hardness and elastic modulus, which is attributed to the annihilation of thermally unstable defects that resulted from the relaxation.