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3D hand pose estimation from single depth is a fundamental problem in computer vision, and has wide applications.However, the existing methods still can not achieve satisfactory hand pose estimation results due to view variation and occlusion of human hand. In this paper, we propose a new virtual view selection and fusion module for 3D hand pose estimation from single depth.We propose to automatically select multiple virtual viewpoints for pose estimation and fuse the results of all and find this empirically delivers accurate and robust pose estimation. In order to select most effective virtual views for pose fusion, we evaluate the virtual views based on the confidence of virtual views using a light-weight network via network distillation. Experiments on three main benchmark datasets including NYU, ICVL and Hands2019 demonstrate that our method outperforms the state-of-the-arts on NYU and ICVL, and achieves very competitive performance on Hands2019-Task1, and our proposed virtual view selection and fusion module is both effective for 3D hand pose estimation., Comment: Accepted by AAAI2022

vmax, rmw and r17 in experiment CNTL and CNTL_B03.

Colorectal cancer (CRC) is the third most common malignancy and the second most common cause of cancer-related mortality worldwide. A total of 20% of CRC patients present with distant metastasis. The hepatic portal venous system, responsible for collecting most intestinal blood, makes the liver the most common site of CRC metastasis. The formation of liver metastases from colorectal cancer is a long and complex process. It involves the maintenance of primary tumors, vasculature invasion, distant colonization, and metastasis formation. In this review, we serve on how the CRC cells acquire stemness, invade the vascular, and colonize the liver. In addition, we highlight how the resident cells of the liver and immune cells interact with CRC cells. We also discuss the current immunotherapy approaches and challenges we face, and finally, we look forward to finding new therapeutic targets based on novel sequencing technologies.

In this paper, we investigate the mass spectra of bottom-charm baryons systematically, where the relativistic quark model and the infinitesimally shifted Gaussian basis function method are employed. Our calculation shows that the $\rho$-mode appears lower in energy than the other excited modes. According to this feature, the allowed quantum states are selected and a systematic study of the mass spectra for $\Xi_{bc}^{'}$ ($\Xi_{bc}$) and $\Omega_{bc}^{'}$ ($\Omega_{bc}$) families is performed. The root mean square radii and quark radial probability density distributions of these baryons are analyzed as well. Next, the Regge trajectories in the $(J,M^{2})$ plane are successfully constructed based on the mass spectra. At last, we present the structures of the mass spectra, and analyze the difficulty and opportunity in searching for the ground states of bottom-charm baryons in experiment., Comment: 19 pages, 9 figures, 6 tables. arXiv admin note: text overlap with arXiv:2210.13085

A novel Fe-Cr-B-C-Al-Si-Mn composite coating was designed and synthesized on 2Cr13 steel substrate using laser cladding technique in this study. The microstructure evolution, microhardness and wear resistance of the composite coating were investigated. The results showed that the microstructure of the coating was mainly composed of α-(Fe,Cr,Al) martensite, retained γ-Fe, and the eutectic comprised of CrFeB, M3(C,B)2, M2(B,C) and M23(C,B)6. The average microhardness of the coating (742.1 HV0.5) was 3.95 times compared with the 2Cr13 steel substrate, and the wear resistance was enhanced by 12.5 times compared with the 2Cr13 steel substrate. The wear mechanisms were dominated by abrasive wear and oxidative wear.

Based on the relativistic quark model and the infinitesimally shifted Gaussian basis function method, we investigate the mass spectra of double bottom baryons systematically. In the $\rho$-mode which appears lower in energy than the other excited modes, we obtain the allowed quantum states and perform a systematic study of the mass spectra of the $\Xi_{bb}$ and $\Omega_{bb}$ families. We analyze the root mean square radii and quark radial probability density distributions to deeply understand the structure of the heavy baryons. Meanwhile, the mass spectra allow us to successfully construct the Regge trajectories in the $(J,M^{2})$ plane. We also predict the masses of the ground states of double bottom baryons and discuss the differences between the structures of our spectra and those from other theoretical methods. At last, the shell structure of the double bottom baryon spectra is shown, from which one could get a bird's-eye view of the mass spectra., Comment: 16 pages, 9 figures, 5 tables. arXiv admin note: text overlap with arXiv:2207.04167

Deep code generation is a topic of deep learning for software engineering (DL4SE), which adopts neural models to generate code for the intended functions. Since end-to-end neural methods lack the awareness of domain knowledge and software hierarchy, the results often require manual correction. To systematically explore the potential improvements of code generation, we let it participate in the whole top-down development from intentions to realizations, which is possible in limited scopes. In the process, it benefits from massive samples, features, and knowledge. As the foundation, we suggest building a taxonomy on code data, namely code taxonomy, leveraging the categorization of code information. Moreover, we introduce a three-layer semantic pyramid (SP) to associate text data and code data. It identifies the information of different abstraction levels, and thus introduces the domain knowledge on development and reveals the hierarchy of software. Furthermore, we propose a semantic pyramid framework (SPF) as the approach, focusing on softwares of high modularity and low complexity. SPF divides the code generation process into stages and reserves spots for potential interactions. Eventually, we conceived application scopes for SPF., 5 pages, 3 figures, 2 tables, under revision

RNA methylation has been known to promote the initiation and progression of many types of cancer, including hepatocellular carcinoma (HCC). To fully understand the importance of this post-transcriptional modification in HCC, a thorough investigation that combines different patterns of RNA methylation is urgently needed. In this study, we investigated the regulators of the three most common types of RNA methylation: m6A, N1-methyladenosine (m1A) and 5-methylcytosine (m5C). Based on the genomic and proteomic data, we constructed a classifier consisting of seven RNA methylation regulators. This classifier performed well and robustly predicted the prognosis of HCC patients. By analysis using this classifier, we found that the primary bile acid biosynthesis pathway was mostly downregulated in high-risk HCC patients. Furthermore, we found that the gene expression patterns regulated by several bile acids were similar to those regulated by some well-defined anti-tumor compounds, indicating that bile acid metabolism plays a crucial role in the progression of HCC, and the related metabolites can be used as the potential agents for HCC treatments. Moreover, our study revealed a crosstalk between RNA methylation and bile acid regulators, demonstrating a novel mechanism of the downregulation of bile acid metabolism in HCC and providing new insights into how RNA methylation regulators affect the oncogenesis of HCC.

Data for picture in Paper, including low-level wind, RMW, R17, tangential wind budget, SE drived vertical velocity.

Shuo Wang,1 Biyu Lei,1 E Zhang,2 Puyang Gong,1 Jian Gu,1 Lili He,1 Lu Han,1 Zhixiang Yuan1 1College of Pharmacy, Southwest Minzu University, Chengdu, 610041, Sichuan, People’s Republic of China; 2Department of Basic Sciences, Officers College of People’s Armed Police, Chengdu, Sichuan, 610213, People’s Republic of ChinaCorrespondence: Zhixiang Yuan; Lu Han, Email zhixiang-yuan@hotmail.com; lunahan@swun.edu.cnAbstract: Inflammation is a beneficial and physiological process, but there are a number of inflammatory diseases which have detrimental effects on the body. In addition, the drugs used to treat inflammation have toxic side effects when used over a long period of time. Mesenchymal stem cells (MSCs) are pluripotent stem cells that can be isolated from a variety of tissues and can be differentiate into diverse cell types under appropriate conditions. They also exhibit noteworthy anti-inflammatory properties, providing new options for the treatment of inflammatory diseases. The therapeutic potential of MSCs is currently being investigated for various inflammatory diseases, such as kidney injury, lung injury, osteoarthritis (OA), rheumatoid arthritis (RA), and inflammatory bowel disease (IBD). MSCs can perform multiple functions, including immunomodulation, homing, and differentiation, to enable damaged tissues to form a balanced inflammatory and regenerative microenvironment under severe inflammatory conditions. In addition, accumulated evidence indicates that exosomes from extracellular vesicles of MSCs (MSC-Exos) play an extraordinary role, mainly by transferring their components to recipient cells. In this review, we summarize the mechanism and clinical trials of MSCs and MSC-Exos in various inflammatory diseases in detail, with a view to contributing to the treatment of MSCs and MSC-Exos in inflammatory diseases.Keywords: mesenchymal stem cells, exosome, inflammatory diseases, clinic data, drug delivery, targeted therapy

Insulin growth-like factor-1 (IGF-1) and its main binding protein insulin growth-like factor binding protein 3 (IGFBP-3) play important roles in cancer development and progression. We hypothesize that circulating IGF-1 and IGFBP-3 may have significant prognostic values in renal cell carcinoma (RCC) patients. We used 1,010 histologically confirmed RCC patients in this case series study to test this hypothesis. We constructed a weighted genetic risk score (GRS) using a large panel of genome-wide association study (GWAS)-identified single nucleotide polymorphisms (SNPs) to predict circulating IGF-1 and IGFBP-3 level, respectively. We analyzed the associations of the GRS with the prognosis of RCC patients using multivariate Cox proportional hazards model. We found significant associations between genetically predicted circulating IGF-1 level, but not IGFBP-3, and RCC prognosis. RCC patients with better prognosis had significantly higher baseline circulating IGF-1 level than those with worse prognosis. Dichotomized at the median value of GRS, patients with high IGF-1 exhibited significantly lower risks of recurrence (HR=0.81, 95% CI, 0.65-0.99, P=0.045) and death (HR=0.74, 95% CI, 0.60-0.91, P=0.004). If patients were dichotomized at the 75% value of GRS, those with the highest quarter of GRS had 27% lower risk of recurrence (OR=0.73, 95% CI, 0.55-0.96, P=0.025) and 34% lower risk of death (OR=0.66, 95% CI, 0.50-0.87, P=0.003) than the other three quarters of patients. High IGF-1/IGFBP-3 ratio was also associated with reduced risks of recurrence and survival. In conclusion, high circulating IGF-1 level and IGF-1/IGFBP-3 ratio at diagnosis is associated with better prognosis in RCC patients.

Objective To investigate the regulating function of human gingival mesenchymal stem cell (GMSC) on the proliferation and differentiation of B cells and its underlying molecular mechanism. Methods GMSC were isolated and B cells were isolated from peripheral blood. GMSC or fibroblasts were co-cultured with B cells in vitro and assigned into the GMSC group and fibroblast group. The proliferation of B cells was detected in two groups. The expression of IgG1 and IgM in the cell supernatants was measured between two groups. The secretion of interleukin (IL)-6, Perforin, interferon (IFN)-γ and tumor necrosis factor (TNF)-α was compared between two groups. The expression levels ofIL-10 and transforming growth factor (TGF)-β in B cells were detected between two groups. The expression of PC-1 in B cells was measured in two groups. The signaling pathway involved with the regulating effect of GMSC on B cell function was investigated. The regulating effect of GMSC on the role of B cells in activating T cell function was assessed. Results Compared with the fibroblast group, the proliferation of B cells was significantly weakened in the GMSC group (P < 0.05). Co-culture of GMSC and B cells significantly inhibited the secretion of IgG1 and IgM from B cells and the secretion ofIL-6, Perforin, IFN-γ and TNF-α (all P < 0.05). Compared with the fibroblast group, the secretion of IL-10 and TGF-βwas significantly higher in the GMSC group (both P < 0.05). The expression level of PC-1 in the GMSC group was significantly down-regulated (P < 0.05). After adding ALK5, an inhibitor of TGF-β receptor, the inhibitory effect of GMSC upon B cells was significantly weakened (P < 0.05). Compared with the fibroblast group, the ability of B cells to activate and proliferate T cells was significantly attenuated in the GMSC group (P < 0.05). Conclusions GMSC can inhibit B cells and their mediated immune responses. The activation of B cells and other related functions can be suppressed through the TGF-β signaling pathway.

Heme oxygenase (HO)-1 and its enzymolysis products can mitigate hepatic ischemia-reperfusion injury (HIRI) by alleviating the damage of reactive oxygen free radicals, mitigating cell apoptosis, inhibiting inflammatory reaction and maintaining microcirculation stability. Autophagy is a process in which the cells utilize lysosomes to degrade their damaged organelles and macromolecular substances. It is considered as an adaptive response to alleviate cell damage under stress, which can effectively reduce cell death. In recent years, more and more studies have demonstrated that autophagy is also significantly correlated with HIRI. This article reviewed recent research progresses at home and abroad on HO-1 and HIRI, autophagy and HIRI, the interaction and mechanism between HO-1 and autophagy in HIRI.

Automatic code summarization is beneficial to daily software development since it could help reduce the requirement of manual writing. Currently, artificial intelligence is undergoing a paradigm shift. The foundation models pretrained on massive data and finetuned to downstream tasks surpass specially customized models. This trend inspired us to consider reusing foundation models instead of learning from scratch. Thereby, we propose a flexible and robust approach for automatic code summarization, based on neural models. We assemble available foundation models, such as CodeBERT and GPT-2, into a single neural model named AdaMo. Moreover, we utilize Gaussian noise as the simulation of contextual information to optimize the latent representation. Furthermore, we introduce two adaptive schemes from the perspective of knowledge transfer, namely continuous pretraining and intermediate finetuning, and design intermediate stage tasks for general sequence-to-sequence learning. Finally, we evaluate AdaMo against a benchmark dataset for code summarization, by comparing it with state-of-the-art models.

Automatic code summarization is beneficial to daily software development since it could help reduce the requirement of manual writing. Currently, artificial intelligence is undergoing a paradigm shift. The foundation models pretrained on massive data and finetuned to downstream tasks surpass specially customized models. This trend inspired us to consider reusing foundation models instead of learning from scratch. Thereby, we propose a flexible and robust approach for automatic code summarization, based on neural models. We assemble available foundation models, such as CodeBERT and GPT-2, into a single neural model named AdaMo. Moreover, we utilize Gaussian noise as the simulation of contextual information to optimize the latent representation. Furthermore, we introduce two adaptive schemes from the perspective of knowledge transfer, namely continuous pretraining and intermediate finetuning, and design intermediate stage tasks for general sequence-to-sequence learning. Finally, we evaluate AdaMo against a benchmark dataset for code summarization, by comparing it with state-of-the-art models.

Motivated by the experimental progress in the study of heavy baryons, we investigate the mass spectra of strange single heavy baryons in the $λ$-mode, where the relativistic quark model and the infinitesimally shifted Gaussian basis function method are employed. It is shown that the experimental data can be well reproduced by the predicted masses. The root mean square radii and radial probability density distributions of the wave functions are analyzed in detail. Meanwhile, the mass spectra allow us to successfully construct the Regge trajectories in the $(J,M^{2})$ plane. We also preliminarily assign quantum numbers to the recently observed baryons, including $Ξ_{c}(3055)$, $Ξ_{c}(3080)$, $Ξ_{c}(2930)$, $Ξ_{c}(2923)$, $Ξ_{c}(2939)$, $Ξ_{c}(2965)$, $Ξ_{c}(2970)$, $Ξ_{c}(3123)$, $Ξ_{b}(6100)$, $Ξ_{b}(6227)$, $Ξ_{b}(6327)$ and $Ξ_{b}(6333)$. At last, the spectral structure of the strange single heavy baryons is shown. Accordingly, we predict several new baryons that might be observed in forthcoming experiments., 27 pages, 11 figures, 8 tables

Additional file1: Supplementary Table 1. Thedifference in basic information between the training and test datasets in MIMIC III and MIMIC IV. Supplementary Table 2. Themodel performance for prediction of in-hospital mortality in the test datasetin MIMIC III and MIMIC IV

Lymphoma risk is elevated for relatives with common non-Hodgkin lymphoma (NHL) subtypes, suggesting shared genetic susceptibility across subtypes. To evaluate the extent of mutual heritability among NHL subtypes and discover novel loci shared among subtypes, we analyzed data from eight genome-wide association studies within the InterLymph Consortium, including 10,629 cases and 9505 controls. We utilized Association analysis based on SubSETs (ASSET) to discover loci for subsets of NHL subtypes and evaluated shared heritability across the genome using Genome-wide Complex Trait Analysis (GCTA) and polygenic risk scores. We discovered 17 genome-wide significant loci (P < 5 × 10−8) for subsets of NHL subtypes, including a novel locus at 10q23.33 (HHEX) (P = 3.27 × 10−9). Most subset associations were driven primarily by only one subtype. Genome-wide genetic correlations between pairs of subtypes varied broadly from 0.20 to 0.86, suggesting substantial heterogeneity in the extent of shared heritability among subtypes. Polygenic risk score analyses of established loci for different lymphoid malignancies identified strong associations with some NHL subtypes (P < 5 × 10−8), but weak or null associations with others. Although our analyses suggest partially shared heritability and biological pathways, they reveal substantial heterogeneity among NHL subtypes with each having its own distinct germline genetic architecture.

Rationale: Astroblastoma is a rare tumor of the central nervous system with uncertain biological behavior and origin. Its histopathological features have been well established, while, to our knowledge, astroblastoma with oligodendroglial-like cells have not been reported. Patient concerns: A 15-year-old girl presented with nausea, vomiting, headache, and visual disturbance. Diagnosis: Magnetic resonance imaging revealed a large neoplasm in the left temporal. Histologically, the tumor showed solid and pseudopapillary structure. Immunohistochemical staining showed that the tumor cells were positive for glial fibrillary acidic protein and vimentin. The oligodendroglial-like cells were positive for glial fibrillary acidic protein, vimentin, and oligodendrocyte transcription factor 2. The antigen KI67 labeling index was about 4%. Sequencing for isocitrate dehydrogenase (IDH) 1 codon 132 and IDH2 codon 172 gene mutations showed negative results. Furthermore, fluorescent analysis revealed neither 1p nor 19q deletion in the lesion. Based on these findings, the girl was finally diagnosed as astroblastoma. Interventions: A craniotomy with total excision of the tumor was performed. Outcomes: The follow-up time was 1 year, no evidence of disease recurrence was found in magnetic resonance imaging. Lessons: Cerebral astroblastoma with oligodendroglial-like cells is a clinically rare tumor of central nervous system. Clear distinction and diagnosis are critical.

In recent years, coal mine has applied shield tunneling machines to roadway excavation to improve production efficiency. Geological condition is an important factor that determines the efficiency of shield machines. The shield machine is most favorable for medium to hard surrounding rocks such as limestone and sandstone. Therefore, the lithology prediction of the location of a planned excavation roadway becomes the core issue in improving the efficiency of the shield machine. At present, seismic inversion is an essential method for lithology prediction. However, in Yangquan Xinjing area, missing P-wave logging curves affects the impedance inversion. Therefore, using existing logging curves to generate missing P-wave logging curves and using sandstone exposure data to continuously update lithology distribution prediction results are of great interest. In this study, logging curves were first pretreated by standardization to ensure the inversion effect. Because of the missing acoustic logging curves, the random forest regression algorithm was introduced using density, natural gamma, apparent resistivity, and spontaneous potential curves as characteristic variables to establish a curve regression prediction model. Then, P-wave logging curves were acquired. After a full analysis of the principles of acoustic and gamma curves, a quasi-acoustic curve is constructed, and a quasi-acoustic inversion was performed. The top and bottom interfaces of the K7 sandstone were interpreted on the inversion data body. The interpreted horizon information was converted from the time domain to the depth domain. The predicted results agreed well with the exposed data. At the same time, combined with the lithology exposure data from the shield tunneling machine, the distribution prediction of the K7 sand body in the target roadway section was updated and iterated many times, which provided effective guidance for the optimization of the tunneling route of the shield tunneling machine.

Insulin growth factor-1 (IGF-1) plays important roles in carcinogenesis. Previous studies have linked circulating IGF-1 and its main binding protein, insulin-like growth factor-binding protein-3 (IGFBP-3), to cancer risks. However, no study has been conducted in soft tissue sarcoma (STS). In this study, we investigated the relationship of genetically predicted circulating IGF-1 and IGFBP-3 with STS risks. Recent large genome-wide association studies (GWAS) have identified 413 single nucleotide polymorphisms (SNPs) associated with IGF-1 and 4 SNPs associated with IGFBP-3. We genotyped these SNPs in 821 patients and 851 healthy controls. We constructed weighted genetic risk scores (GRS) to predict circulating IGF-1 and IGFBP-3. We determined the associations of individual SNPs and GRS with the risks of STS using multivariate logistic regression analysis. We found high genetically predicted circulating IGF-1 and IGFBP-3 were both associated with increased STS risks. Dichotomized at the median values of IGF-1 and IGFBP-3 in controls, individuals with high level of IGF-1 exhibited a 27% increased risk of STS (odds ratio [OR]=1.27, 95% confidence interval [CI]=1.04-1.54, P=0.017), whereas the OR for high IGFBP-3 was 1.45 (95% CI=1.20-1.77, P

This study investigates the precipitation symmetrization preceding rapid intensification (RI) of tropical cyclones (TCs) experiencing vertical wind shear by analyzing numerical simulations of Typhoon Mujigae (2015) with warm (CTL) and relatively cool (S1) sea surface temperatures (SSTs). A novel finding is that precipitation symmetrization is maintained by the continuous development of deep convection along the inward flank of a convective precipitation shield (CPS), especially in the downwind part. Beneath the CPS, downdrafts flush the boundary layer with low-entropy parcels. These low-entropy parcels do not necessarily weaken the TCs; instead, they are “recycled” in the TC circulation, gradually recovered by positive enthalpy fluxes, and develop into convection during their propagation toward a downshear convergence zone. Along-trajectory vertical momentum budget analyses reveal the predominant role of buoyancy acceleration in the convective development in both experiments. The boundary layer recovery is more efficient for warmer SST, and the stronger buoyancy acceleration accounts for the higher probability of these parcels developing into deep convection in the downwind part of the CPS, which helps maintain the precipitation symmetrization in CTL. In contrast, less efficient boundary layer recovery and less upshear deep convection hinder the precipitation symmetrization in S1. These findings highlight the key role of boundary layer recovery in regulating the precipitation symmetrization and upshear deep convection, which further accounts for an earlier RI onset timing of the CTL TC. The inward rebuilding pathway also illuminates why deep convection is preferentially located inside the radius of maximum wind of sheared TCs undergoing RI.

The cyclic oxidation behavior of Hf/Y-doped B2 FeAl intermetallics at 1373 K was investigated. For an undoped FeAl alloy, premature spallation of the alumina film occurs due to the formation of numerous voids at the film/alloy interface and apparent shrinkage in the film. In contrast to this, doping with either Hf or Y significantly improves the interfacial adhesion between the alumina film and the alloy substrate, particularly with Hf-doping. Microstructural observation in combination with Auger electron spectroscopic analysis suggests that in addition to prohibiting interfacial void formation and alleviating film shrinkage, the addition of Hf in the FeAl alloy could consolidate the film/alloy interface by directly participating in chemical bonding across the interface as a Hf ion. This causes the spallation of alumina film from the equiaxed grains/columnar grains interface rather than the bottom of the film.

In this paper, graphene@cuprous oxide (rGO@Cu2O) nanocomposite was designed and prepared with graphene oxide, CuSO4, NaOH and L-ascorbic acid via an in-situ reaction process, and the as-prepared rGO@Cu2O nanocomposite was characterized by XRD, FT-IR, Raman spectroscopy, XPS, SEM-EDS and TEM. The results reveal that the rGO@Cu2O nanocomposite is of homogeneous distribution, and the Cu2O nanoparticles adsorbed on graphene sheets are with a fairly uniform size of 2.3 nm. The rGO@Cu2O/acrylic resin self-polishing marine antifouling paint with functional surfaces was also prepared in this work, and a series of measurements were carried out for the obtained product. The WCAs of paint is up to 113°, and the adhesive force is averaged to 3.69 MPa. After being immersed into seawater, the whole bared panels show an abundant growth of marine organisms within 90 days, but the rGO@Cu2O paint coated surfaces are hardly fouled by marine organisms within 365 days. This work demonstrates that in situ synthesis of rGO@Cu2O is a tin-free potential alternative to inhibit biofouling.

This study investigates the intensity change of binary tropical cyclones (TCs) in idealized cloud-resolving simulations. Four simulations of binary interaction between two initially identical mature TCs of about 70 ms−1 with initial separation distance varying from 480 to 840 km are conducted in a quiescent f-plane environment. Results show that two identical TCs finally merge if their initial separation distance is within 600 km. The binary TCs presents two weakening stages (stages 1 and 3) with a quasi-steady evolution (stage 2) in between. Such intensity change of one TC is correlated with the upper-layer vertical wind shear (VWS) associated with the upper-level anticyclone (ULA) of the other TC. The potential temperature budget shows that eddy radial advection of potential temperature induced by large upper-layer VWS contributes to the weakening of the upper-level warm core and thereby the weakening of binary TCs in stage 1. In stage 2, the upper-layer VWS first weakens and then re-strengthens with relatively weak magnitude, leading to a quasi-steady intensity evolution. In stage 3, due to the increasing upper-layer VWS, the non-merging binary TCs weaken again until their separation distance exceeds the local Rossby radius of deformation of the ULA (about 1600 km), which can serve as a dynamical critical distance within which direct interaction can occur between two TCs. In the merging cases, the binary TCs weaken prior to merging because highly asymmetric structure develops as a result of strong horizontal deformation of the inner core. However, the merged system intensifies shortly after merging.

Compared with other parts of the plant, leaves are easy to obtain and have obvious features. Therefore, leaf identification is also considered as one of the best methods for plant identification. For this reason, a transfer learning leaf recognition method based on VGG16 deep learning network is proposed. This method firstly carries out preprocess operations such as background whitening and standard normalization processing, then carries out data augmentation, then uses transfer learning to train VGG16 network model, and finally completes leaf recognition. The experimental results of Middle European Woody (MEW) plants data set and UCI Folio Leaf data set show that the recognition accuracy under a single background reaches 93.4% and 97.9%, respectively, which are significantly higher than traditional convolutional neural network and other recognition methods, effectively improving the recognition accuracy rate of plant leaves.

With the rapid development of artificial intelligence, the purpose of image classification is not only to identify the major categories of objects, but also to classify the images of the same category into more detailed subcategories. In order to effectively discriminate small differences between regions, a fine-grained classification algorithm was proposed based on Attention Self-supervision (ASS). Firstly, the ResNet-152 pre-trained model was applied to extract the global image features and to forecast the attention maps with Depthwise Separable convolution (DS conv). Subsequently, the Weakly Supervised Data Augmentation Network (WS-DAN) was applied to feed the augmented image back into the network and enhance the generalization ability of the network to prevent overfitting. Finally, linear fusion of attention features in ASS network was further performed to improve the accuracy of the classification. The experimental results show that the method achieves 89.6% accuracy rate on CUB-200-2011 dataset.

Most of screening-detected prostate cancer (PCa) are indolent and not lethal. Biomarkers that can predict aggressive diseases independently of clinical features are needed to improve risk stratification of localized PCa patients and reduce overtreatment. We aimed to identify leukocyte DNA methylation differences between clinically defined aggressive and non-aggressive PCa. We performed whole genome DNA methylation profiling in leukocyte DNA from 287 PCa patients with Gleason Score (GS) 6 and ≥8 using Illumina 450k methylation arrays. We observed a global hypomethylation in GS≥8 patients compared to GS=6 PCa patients; in contrast, the methylation level in core promoter and exon 1 region was significantly higher in GS≥8 patients than GS=6 PCa. We then performed 5-fold cross validated random forest model training on 1,459 differentially methylated CpG Probes (DMPs) with false discovery rate (FDR)

Dyslipidemia, characterized by metabolic abnormalities, has become an important participant in colorectal cancer (CRC). Dyslipidemia aggravates intestinal inflammation, destroys the protective mucous layer, and disrupts the balance between injury and recovery. On the other hand, antioxidants induced by oxidative stress enhance glycolysis to maintain the acquisition of ATP allowing epithelial cells with damaged genomes to survive. In the repetitive phase of colitis, survival factors enable these epithelial cells to continuously proliferate. The main purpose is to restore and rebuild damaged mucosa, mainly aiming to recover mucosal damage and reconstruct mucosa, but it is also implicated in the occurrence and malignancy of CRC. The metabolic reprogramming of aerobic glycolysis and lipid synthesis enables these transformed epithelial cells to convert raw carbohydrate and amino acid substrates, thereby synthesizing protein and phospholipid biomass. Stearoyl-CoA desaturase, responsible for the fatty acid desaturation, improves the fluidity and permeability of cell membranes, which is one of the key factors affecting metabolic rate. In response to available fat, tumor cells reprogram their metabolism to better plunder energy-rich lipids and rapidly scavenge these lipids through continuous proliferation. However, lipid metabolic disorders inhibit the function of immune-infiltrating cells in the tumor microenvironment through the cross-talk between tumor cells and immunosuppressive stromal cells, thereby providing opportunities for tumor progress. Nonsteroidal anti-inflammatory drugs and lipid-lowering drugs can decrease the formation of aberrant crypt foci, lower the burden of the adenomatous polyp, and reduce the incidence of CRC. This review provides a comprehensive understanding of dyslipidemia on tumorigenesis and tumor progression and a development prospect of lipid disorders on tumor immunity.

Additional file 1: Table S1. Univariate analysis of associations with clinical outcomes. Figure S1. Kaplan-Meier survival plots of mCRPC patients. The survival differences were compared between patients with ≥5 CTCs and those with

A facile method was used to prepare graphene from discarded polyethylene plastic bags in our work. In order to make high-quality graphene, PE plastic bags were ultrasonically cleaned, ball milled and microwave sintered successively. The height of the 2D band was 1.3 times that of the G band, which reveals that the layer number of as-prepared graphene was 1-2. The atomic ratio of C and O for graphene was more than 54, which indicates that it mainly consists of carbon. The size of graphene was within 4-10 μm. Bi-layer sheets were inevitably observed through high resolution imaging of graphene edges. The BET SSA and the electrical conductivity of graphene were 1521.3 m2 g-1 and 4618 S m-1, respectively. This work provides a new approach to large-scale and high-quality synthesis of graphene from waste polluting materials.

This study takes the first step to bridge the gap between the pressure drag of a shallow cloud ensemble and that of an individual cloud composed of rising thermals. It is found that the pressure drag for a cloud ensemble is primarily controlled by the dynamical component. The dominance of dynamical pressure drag and its increased magnitude with height are independent of cloud lifetime and are common features of individual clouds except that the total drag of a single cloud over life cycle presents vertical oscillations. These oscillations are associated with successive rising thermals but are further complicated by the evaporation-driven downdrafts outside the cloud. The horizontal vorticity associated with the vortical structure is amplified as the thermals rise to higher altitudes due to continuous baroclinic vorticity generation. This leads to the increased magnitude of local minima of dynamical pressure perturbation with height and consequently to increased dynamical pressure drag.

Background Two-line hybrid wheat system using thermo-photo sensitive genic male sterility (TPSGMS) is currently the most promising approach for wheat heterosis utilization in China. However, during past 20 years only few TPSGMS lines were developed in hybrid wheat breeding, which has been the main limiting factor to create heterotic hybrids. Application of doubled haploid (DH) breeding provides a useful strategy to efficiently develop practically usable TPSGMS lines. Results F1s and selected F2 and F3 sterile plants of eight crosses made from two commercial TPSGMS lines were used to produce DH lines. We developed a total of 24 elite DH sterile lines with stable sterility, good outcrossing and yield potential, resistance to yellow rust and powdery mildew, as well as desirable plant height (50–60 cm). These DH lines were developed within 4 years through at least 1 year of evaluation. The stability of male sterility was confirmed for most (20/24) of these elite DH sterile lines by multiple tests in two or 3 years. These lines are expected to be used in hybrid wheat breeding. The percentage of elite lines developed from the tested DH lines produced from filial generations was in the order of F2 > F3 > F1. Conclusions We demonstrate that coupling DH techniques with conventional breeding is an efficient strategy for accelerating the development of more practical wheat TPSGMS lines. Generation of DHs from F2 generation appeared to be the better choice considering the balance of shortening breeding time and overall breeding efficiency.

Jin-Xing Gong,1 Jian-Wei Gu,1 Feng Ji,1 Kun Li,1 Qi Zhu,1 Fang-Ying Gu,1 Yan Chen,1 Qing-Hai Ji2 1Department Four of Surgery, Kunshan Hospital of Traditional Chinese Medicine, Kunshan 215300, People’s Republic of China; 2Head & Neck Surgery, Fudan University Shanghai Cancer Center, Shanghai 200000, People’s Republic of ChinaCorrespondence: Jian-Wei GuDepartment Four of Surgery, Kunshan Hospital of Traditional Chinese Medicine, No. 189 of Chaoyang Street, Yushan Town, Kunshan 215300, People’s Republic of ChinaTel +86-051257310000-3698Email jwgdr_999@163.comObjective: This study aims to investigate the risk factors of prelaryngeal lymph node metastasis in papillary thyroid carcinoma and its clinical application value.Methods: The clinical pathological features and metastatic risks were statistically analyzed by reviewing 254 patients with papillary thyroid carcinoma, who received their first operation and prelaryngeal lymph node dissection in our department.Results: The detection of prelaryngeal lymph nodes, tumor size and any paratracheal lymph node metastasis were correlated with the number of paratracheal lymph node metastasis (P< 0.05), but these were not correlated with age, gender, multiple foci, tumor size, any paratracheal lymph node metastasis, metastatic location, or foci location (P> 0.05).Conclusion: Paratracheal lymph node metastasis indicates a high possibility of prelaryngeal lymph node metastasis. Paratracheal lymph node dissection combined with prelaryngeal lymph node dissection should be simultaneously considered in operations for thyroid papilla carcinoma.Keywords: papillary thyroid cancer, delphian lymph node, lymph node metastasis, lymph node dissection, tumor

This paper proposes a knowledge distillation method for foreground object search (FoS). Given a background and a rectangle specifying the foreground location and scale, FoS retrieves compatible foregrounds in a certain category for later image composition. Foregrounds within the same category can be grouped into a small number of patterns. Instances within each pattern are compatible with any query input interchangeably. These instances are referred to as interchangeable foregrounds. We first present a pipeline to build pattern-level FoS dataset containing labels of interchangeable foregrounds. We then establish a benchmark dataset for further training and testing following the pipeline. As for the proposed method, we first train a foreground encoder to learn representations of interchangeable foregrounds. We then train a query encoder to learn query-foreground compatibility following a knowledge distillation framework. It aims to transfer knowledge from interchangeable foregrounds to supervise representation learning of compatibility. The query feature representation is projected to the same latent space as interchangeable foregrounds, enabling very efficient and interpretable instance-level search. Furthermore, pattern-level search is feasible to retrieve more controllable, reasonable and diverse foregrounds. The proposed method outperforms the previous state-of-the-art by 10.42% in absolute difference and 24.06% in relative improvement evaluated by mean average precision (mAP). Extensive experimental results also demonstrate its efficacy from various aspects. The benchmark dataset and code will be release shortly., Comment: This paper will appear at ECCV 2020

Additional file 1 : Table S1. The primers for amplification and sequencing the exons of G6PD gene.

Additional file 1: Table S1. C1-INH antigenic levels of patients with missense mutation data.

In recent decades, various software systems have gradually become the basis of our society. Programmers search existing code snippets from time to time in their daily life. It would be beneficial and meaningful to have better solutions for the task of semantic code search, which is to find the most semantically relevant code snippets for a given query. Our approach is to introduce tree representations by multi-modal learning. The core idea is to enrich semantic information for code snippets by preparing data of different modalities, and meanwhile ignore syntactic information. We design one novel tree structure named Simplified Semantic Tree and then extract RootPath representations from that. We utilize RootPath representation to complement the conventional sequential representation, namely the token sequence of the code snippet. Our multi-modal model receives code-query pair as input and computes similarity score as output, following the pseudo-siamese architecture. For each pair, besides the ready-made code sequence and query sequence, we extra one extra tree sequence from Simplified Semantic Tree. There are three encoders in our model, and they respectively encode these three sequences as vectors of the same length. Then we combine the code vector with the tree vector for one joint vector, which is still of the same length, as the multi-modal representation for the code snippet. We introduce triplet loss to ensure vectors of code and query in the same pair be close at the shared vector space. We conduct experiments in one large-scale multi-language corpus, with comparisons of strong baseline models by specified performance metrics. Among baseline models, the simplest Neural Bag-of-Words model is with the most satisfying performance. It indicates that syntactic information is likely to distract complex models from critical semantic information. Results show that our multi-modal representation approach performs better because it surpasses baseline models by far in most cases. The key to our multi-modal model is that it is totally about semantic information, and it learns from data of multiple modalities. Under de senaste decennierna har olika programvarusystem gradvis blivit basen i vårt samhälle. Programmerare söker i befintliga kodavsnitt från tid till annan i deras dagliga liv. Det skulle vara fördelaktigt och meningsfullt att ha bättre lösningar för uppgiften att semantisk kodsökning, vilket är att hitta de mest semantiskt relevanta kodavsnitten för en given fråga. Vår metod är att introducera trädrepresentationer genom multimodal inlärning. Grundidén är att berika semantisk information för kodavsnitt genom att förbereda data med olika modaliteter och samtidigt ignorera syntaktisk information. Vi designar en ny trädstruktur med namnet Simplified Semantic Tree och extraherar sedan RootPath-representationer från det. Vi använder RootPath-representation för att komplettera den konventionella sekvensrepresentationen, nämligen kodsekvensens symbolsekvens. Vår multimodala modell får kodfrågeställningar som inmatning och beräknar likhetspoäng som utgång efter den pseudo-siamesiska arkitekturen. För varje par, förutom den färdiga kodsekvensen och frågesekvensen, extrager vi en extra trädsekvens från Simplified Semantic Tree. Det finns tre kodare i vår modell, och de kodar respektive tre sekvenser som vektorer av samma längd. Sedan kombinerar vi kodvektorn med trädvektorn för en gemensam vektor, som fortfarande är av samma längd som den multimodala representationen för kodavsnittet. Vi introducerar tripletförlust för att säkerställa att vektorer av kod och fråga i samma par är nära det delade vektorn. Vi genomför experiment i ett storskaligt flerspråkigt korpus, med jämförelser av starka baslinjemodeller med specificerade prestandametriker. Bland baslinjemodellerna är den enklaste Neural Bag-of-Words-modellen med den mest tillfredsställande prestanda. Det indikerar att syntaktisk information sannolikt kommer att distrahera komplexa modeller från kritisk semantisk information. Resultaten visar att vår multimodala representationsmetod fungerar bättre eftersom den överträffar basmodellerna i de flesta fall. Nyckeln till vår multimodala modell är att den helt handlar om semantisk information, och den lär sig av data om flera modaliteter.

Additional file 8. Supplementary Materials and Methods.

Layered adhesive structures are widely used in the aerospace field, and thus their defect detection is a critical part of quality control. Hence, this paper proposes a method to identify bonding defects relying on dynamic time warping (DTW) and simulation analysis. Based on the transfer matrix method, the propagation simulation model of the layered structure is established, and the simulation signal of the normal area and the characteristic interval of the defects are obtained. DTW is adopted to regularize the simulated and the real signals, and then the Pearson correlation coefficient is employed to calculate the regularized signals’ similarity. On this basis, the proposed scheme is considered a similarity imaging method, attaining an appealing identification error for the three- and the five-layered adhesive structure cases examined involving various defect thicknesses and glue layers. Compared to current imaging methods, the proposed one demonstrates a better and more effective imaging effect appropriate for bonding defect detection.

In the three-dimensional coordinate system, there are four omnidirectional antenna radar stations with fixed coordinates. These radar stations form a network radar and observe the target. In this paper, the beat signal with white Gaussian noise obtained by mixing the FMCW(Frequency Modulated Continuous Wave) transmission signal and the echo signal is processed by FFT to obtain the frequency value of the beat signal. Finally, the state information including the target distance obtained by the improved Jacobi iterative algorithm is compared and compared with the traditional Jacobi iterative algorithm. The simulation results were analyzed, and the superiority of the improved algorithm was verified, which provided help for accurate and timely meteorological observations.