The Impact of Mutations in SARS-CoV-2 Spike on Viral Infectivity and Antigenicity.

The spike protein of SARS-CoV-2 has been undergoing mutations and is highly glycosylated. It is critically important to investigate the biological significance of these mutations. Here, we investigated 80 variants and 26 glycosylation site modifications for the infectivity and reactivity to a panel of neutralizing antibodies and sera from convalescent patients. D614G, along with several variants containing both D614G and another amino acid change, were significantly more infectious. Most variants with amino acid change at receptor binding domain were less infectious, but variants including A475V, L452R, V483A, and F490L became resistant to some neutralizing antibodies. Moreover, the majority of glycosylation deletions were less infectious, whereas deletion of both N331 and N343 glycosylation drastically reduced infectivity, revealing the importance of glycosylation for viral infectivity. Interestingly, N234Q was markedly resistant to neutralizing antibodies, whereas N165Q became more sensitive. These findings could be of value in the development of vaccine and therapeutic antibodies.

Diagnostic and prognostic value of miR-486-5p, miR-451a, miR-21-5p and monocyte to high-density lipoprotein cholesterol ratio in patients with acute myocardial infarction.

Acute myocardial infarction (AMI) is one of the most serious complications of coronary heart disease. Although morbidity and mortality have been decreasing year by year, acute coronary syndrome still has a high mortality rate and disability rate. To search for accurate and effective biomarkers, we explore the diagnostic and prognostic value of microRNAs (miRNAs) and the monocyte to high-density lipoprotein cholesterol ratio (MHR) in patients with AMI. By referring to the relevant literature, miR-486-5p, miR-451a and miR-21-5p were reportedly altered in the blood of patients with ischemic heart disease. These miRNAs were selected and validated in 40 AMI patients, 22 unstable angina pectoris (UAP) and 22 healthy groups (HC) by real-time fluorescent quantitative polymerase chain reaction (RT-qPCR). All patients with AMI underwent primary percutaneous coronary intervention (PCI) and were followed up 3 months after the operation. MHR and miR-451a expression were markedly elevated in plasma samples of AMI patients compared with the UAP and HC groups, but the expressions of miR-486-5p and miR-21-5p were significantly decreased. The expression level of miRNA-451a increased gradually among the three groups (p < 0.05). However, the expression of miRNA-21-5p showed a downward trend (p < 0.05). More importantly, MHR was significantly different before and after PCI in AMI patients (p < 0.05). Receiver operating characteristic (ROC) analysis indicated that MHR, miR-486-5p, miR-451a and miR-21-5p could diagnose and predict AMI. MiR-451a was a more reliable biomarker for AMI diagnosis among these miRNAs. Moreover, the combination of MHR and miRNAs had higher diagnostic value for AMI. We further demonstrated that miR-21-5p had a strong predictive ability for the occurrence of major adverse cardiovascular events (MACE) after 3 months. The results showed that circulating miR-486-5p, miR-451a, miR-21-5p and MHR may play critical roles in the early phase of AMI, and may be used as potential predictors for AMI diagnosis. Importantly, miR-451a was a more reliable biomarker in diagnosing AMI patients. Circulating miR-21-5p may be used as a predictor of MACE occurrence.

Secondary lens with hybrid structure of freeform surface and microstructure for ultra-thin backlight unit.

Ultra-thin has become the development trend of the direct-lit backlight unit (BLU). Double freeform surface lenses are commonly used in direct-lit BLUs to reduce thickness. However, for an ultra-thin BLU with quite small optical distance (OD) and a large LED pitch distance, the curvature of the designed lens would be quite large, which would make the final optical performance heavily affected by fabrication errors. This paper proposes a lens with freeform surfaces and microstructures. The rays from LEDs are first collimated by the freeform surfaces and the collimated rays are then reflected by the microstructures to the bottom of the BLU, which can effectively enlarge the spot size and reduce the OD. The simulation results show that the uniformity can be improved from 41.3% of the conventional double freeform surface lens to 83% when OD is 3 mm. Such hybrid lenses can avoid the fabrication of freeform surfaces with large curvature and the advantages of easy design and easy fabrication.

Diagnostic and prognostic value of circulating miRNA-499 and miRNA-22 in acute myocardial infarction.

BACKGROUND: Currently, acute myocardial infarction (AMI) represents a serious cardiovascular disease with high morbidity and mortality. Therefore, this study aimed to systematically evaluate the roles of miRNA-499 and miRNA-22 as potential biomarkers for AMI. METHODS: According to the inclusion and exclusion criteria, we measured circulating levels of miRNAs in 50 AMI patients and 50 non-MI populations. The expression levels of plasma miRNA-499 and miRNA-22 were analyzed by real-time fluorescent quantitative polymerase chain reaction (qRT-PCR). A statistical analysis of clinical data of AMI patients was conducted by 90-day follow-up. RESULTS: Real-time PCR analysis showed that the relative expression level of miRNA-499 increased gradually among the three groups (P < .05). However, the expression of miRNA-22 showed a downward trend (P < .05). According to logistic analysis, the relative levels of miRNA-499 and miRNA-22 were important predictors of AMI. When the miRNA-499 and miRNA-22 levels were 0.377 and 0.946 separately, the diagnostic value of miRNA-499 and miRNA-22 for AMI was 86.00% and 86.00% for sensitivity, and 98.00% and 94.00% for specificity, respectively. In addition, compared to the baseline GRACE scoring system, the combination of miRNA-499, miRNA-22, and GRACE scores had a stronger discriminating power for MACE occurrence, with a sensitivity of 100.00% and a specificity of 79.40%. CONCLUSIONS: The results showed that plasma miRNA-499 and miRNA-22 were more sensitive and specific for the diagnosis of AMI, suggesting that they can be used as potential biomarkers for clinical diagnosis of AMI.

LncRNA PVT1 regulates growth, migration, and invasion of bladder cancer by miR-31/ CDK1.

PURPOSE: The aim of our study was to validate the sway of long noncoding RNA (lncRNA) plasmacytoma variant translocation 1 (PVT1) on the metabolism and growth of bladder cancer cells by microRNA-31 (miR-31)/cyclin-dependent kinase 1 ( CDK1). METHODS: The Gene Expression Omnibus database was used for analyzing the differentially expressed lncRNA and messenger RNA (mRNA) in bladder cancer tissues, with the highly expressed lncRNA PVT1 and mRNA CDK1 screened out. The expression level of PVT1 was detected by quantitative reverse-transcription polymerase chain reaction, cell viability by Cell Counting Kit-8 assay, cell proliferation and scratch by 5-bromo-2'-deoxyuridine assay, cell migration and invasion by transwell assays, the expression level of CDK1 by immunohistochemistry and western blot analysis, transcription factor targeting by dual-luciferase assay, and the effect of PVT1 on bladder cancer growth by nude mice tumor formation experiment. RESULTS: LncRNA PVT1 and mRNA CDK1 had a higher expression in bladder cancer cells than that in neighboring tissues. Activity, proliferation, colony formation, migration, and invasion of bladder cancer cell were noticeably reduced by the PVT1 inhibitor than that of control group. PVT1 and CDK1 have binding sites with miR-31. When miR-31 decreased, CDK1 mRNA and protein levels increased in vivo experiments in nude mice. When PVT1 was downregulated, the tumor size was significantly reduced and tumor proliferation was curbed. Immunohistochemistry showed that the positive rate of CDK1 and Ki-67 decreased and the expression of miR-31 increased after PVT1 was inhibited. CONCLUSIONS: LncRNA PVT1 was overexpressed in bladder cancer cells, and it was downregulated miR-31 to enhance CDK1 expression and facilitate bladder cancer cells proliferation, migration, and invasion.

Cycle-SfM: Joint self-supervised learning of depth and camera motion from monocular image sequences.

Understanding 3D scene geometry is a fundamental research topic in computer vision, including various subproblems, such as depth prediction, visual odometry, optical flow, etc. With the advent of artificial intelligence methods like deep learning, many approaches have emerged to deal with such problems in an end-to-end manner. These pipelines take the 3D understanding task as a nonlinear optimization problem, with the purpose of minimizing the cost function of the whole framework. Here, we present a self-supervised framework for jointly learning the monocular depth and camera's ego-motion from unlabeled, unstructured, and monocular video sequences. We propose a forward-backward consistency constraint on view reconstruction to capture temporal relations across adjacent frames, whose purpose is to explore and make full use of the bidirectional projection information. A simple and practicable improvement on the design of cost function is proposed to enhance the estimated accuracy. Due to the fact that our improvement is a lightweight and general module, it can be integrated into any self-supervised architectures seamlessly, and more accurate results can be obtained. The evaluation on the KITTI dataset demonstrates that our approach is highly efficient and performs better than the existing works in pose estimation, while the results in depth estimation perform comparably with the existing ones.

Synaptogyrin-2 Promotes Replication of a Novel Tick-borne Bunyavirus through Interacting with Viral Nonstructural Protein NSs.

Synaptogyrin-2 is a non-neuronal member of the synaptogyrin family involved in synaptic vesicle biogenesis and trafficking. Little is known about the function of synaptogyrin-2. Severe fever with thrombocytopenia syndrome (SFTS) is an emerging infectious disease characterized by high fever, thrombocytopenia, and leukocytopenia with high mortality, caused by a novel tick-borne phlebovirus in the family Bunyaviridae. Our previous studies have shown that the viral nonstructural protein NSs forms inclusion bodies (IBs) that are involved in viral immune evasion, as well as viral RNA replication. In this study, we sought to elucidate the mechanism by which NSs formed the IBs, a lipid droplet-based structure confirmed by NSs co-localization with perilipin A and adipose differentiation-related protein (ADRP). Through a high throughput screening, we identified synaptogyrin-2 to be highly up-regulated in response to SFTS bunyavirus (SFTSV) infection and to be a promoter of viral replication. We demonstrated that synaptogyrin-2 interacted with NSs and was translocated into the IBs, which were reconstructed from lipid droplets into large structures in infection. Viral RNA replication decreased, and infectious virus titers were lowered significantly when synaptogyrin-2 was silenced in specific shRNA-expressing cells, which correlated with the reduced number of the large IBs restructured from regular lipid droplets. We hypothesize that synaptogyrin-2 is essential to promoting the formation of the IBs to become virus factories for viral RNA replication through its interaction with NSs. These findings unveil the function of synaptogyrin-2 as an enhancer in viral infection.

Identification and characterization of novel serum microRNAs in unstable angina pectoris and subclinical atherosclerotic patients.

BACKGROUND: MicroRNAs (miRNAs) are involved in cardiac developmental and pathological processes, and serum profile is useful for identifying novel miRNAs. METHODS AND RESULTS: Serum samples were collected from unstable angina pectoris (UAP) and subclinical atherosclerotic (AS) patients. Solexa sequencing was used to predict novel miRNAs in 15 control individuals, 15 AS patients and 15 UAP patients. After bioinformatics analysis and filtering out in the newest version of miRbase (version 20.0), three novel miRNAs were validated in 80 control individuals, 80 AS patients and 80 UAP patients by quantitative reverse transcriptase polymerase chain reaction. Two of the three novel microRNAs (N1 and N3) were expressed at the highest levels in the AS group. N1 had an area under curve (AUC) of 0.811 (95% confidence interval 0.743-0.880) for AS. N3 showed a moderate separation with an area under curve (AUC) of 0.748 (95% confidence interval 0.664-0.833) for AS. Combined the two novel microRNAs can significantly distinguish AS from control. CONCLUSIONS: Three novel miRNAs were identified by Solexa sequencing and two of them may be new potential predictors for arthrosclerosis.

The correlation between serum lipid profile with carotid intima-media thickness and plaque.

BACKGROUND: It is indicated that non-HDL cholesterol and lipid ratios, including total/HDL cholesterol and LDL/HDL cholesterol ratios, are risk indicators with greater predictive value for coronary atherosclerotic progression or regression compared with conventional lipid profile. However, there have been few reports about the correlation between serum lipid profile with carotid intima-media thickness (IMT) and plaque in Chinese general people. METHODS: We examined 402 subjects without apparent diseases in a cross-sectional study (mean age 50.16 years; 36.07% female). Demographics, anthropometrics, and laboratory data were collected. The presence of carotid plaque and intima-media thickness were evaluated by ultrasonography. RESULTS: Univariate correlations showed carotid IMT was correlated with LDL-C (r = 0.137, p = 0.009), non-LDL-C levels (r = 0.140, p = 0.008) and LDL-C/HDL-C ratio (r = 0.169, p = 0.001). After adjustment for potential covariates, LDL-C/HDL-C ratio (ß = 0.132, p < 0.001) were independent variables that interacted on carotid IMT. Other risk factors including age and systolic blood pressure were independently associated with carotid IMT. LDL-C levels, non-HDL-C levels, TC/HDL-C and LDL-C/HDL-C ratios were significantly higher, but HDL-C levels were significantly lower in subjects with carotid plaque than those without it. The subsequent multiple logistic regression analysis showed that LDL-C (OR; 1.325, 95% CI; 1.046-1.821, p = 0.033) and HDL-C levels (OR; 0.093, 95% CI; 0.038-0.227, p < 0.001) were significantly associated with the presence of carotid plaque after adjustment of age. Furthermore, LDL-C combined with HDL-C levels showed the highest area under the curve (0.788, 95% CI; 0.740-0.837, p < 0.001). CONCLUSIONS: Serum LDL-C/HDL-C ratio represents as an independent index associated with increased carotid IMT and LDL-C combined with HDL-C levels may be useful markers for predicting the presence of carotid plaque in the Chinese general population.

Insulin-like growth factor-1 in myocardial ischemia-reperfusion injury: A review.

Myocardial ischemia-reperfusion injury (MIRI) is a severe damage inflicted on the ischemic myocardium when blood flow is restored, and it commonly occurs in a wide range of cardiovascular diseases. Presently, no effective clinical treatment exists for MIRI. Accumulating evidence indicates that insulin-like growth factor-1 (IGF-1) plays a role in the intricate chain of cardiovascular events, in addition to its well-recognized growth-promoting and metabolic effects. IGF-1, a member of the insulin family, exhibits a broad spectrum of protective effects against ischemia/reperfusion injury in various tissues, especially the myocardium. In particular, earlier research has demonstrated that IGF-1 reduces cellular oxidative stress, improves mitochondrial function, interacts with noncoding RNAs, and activates cardiac downstream protective genes and protective signaling channels. This review aimed to summarize the role of IGF-1 in MIRI and elucidate its related mechanisms of action. In addition, IGF-1-related interventions for MIRI, such as ischemic preconditioning and post-conditioning, were discussed. The purpose of this review was to provide evidence supporting the activation of IGF-1 in MIRI and advocate its use as a therapeutic target.

Albumin combined with neutrophil-to-lymphocyte ratio score and outcomes in patients with acute coronary syndrome treated with percutaneous coronary intervention.

BACKGROUND: Evidence about the association between albumin combined with neutrophil-to-lymphocyte ratio score (ANS) and survival outcomes in patients with acute coronary syndrome (ACS) undergoing percutaneous coronary intervention (PCI) is rare. This study aimed to evaluate the prognostic value of ANS in patients with ACS undergoing PCI by propensity score matching (PSM) analysis. PATIENTS AND METHODS: Patients with ACS undergoing PCI were consecutively enrolled in this prospective cohort study from January 2016 to December 2018. The albumin and neutrophil-to-lymphocyte ratio cutoff values for predicting major adverse cardiovascular events (MACEs) were calculated using receiver operating characteristic curves. Survival analysis was performed using Kaplan-Meier estimates, the Cox proportional hazard regression models and PSM. The study endpoint was the occurrence of a MACE, which included all-cause mortality and rehospitalization for severe heart failure during follow-up. RESULTS: Overall, 1549 patients with adequate specimens were identified and assigned into different groups for comparison. Before and after PSM, the Kaplan-Meier curves showed that a higher ANS value was associated with a higher risk of MACEs (all P  < 0.001). The multivariate Cox proportional hazard regression model showed that the ANS (per 1 score increase) [hazard ratio (HR), 2.016; 95% confidence interval (CI), 1.329-3.057; P  = 0.001 vs. HR, 2.166; 95% CI, 1.344-3.492; P  = 0.002] was an independent predictor for MACEs. CONCLUSION: This study tentatively confirms that ANS may be a valuable clinical indicator to identify high-risk ACS patients after PCI. More high-quality prospective studies are needed in the future.

Lnc-PLCB1 is stabilized by METTL14 induced m6A modification and inhibits Helicobacter pylori mediated gastric cancer by destabilizing DDX21.

Helicobacter pylori (H. pylori) infection is considered to be an important factor in gastric cancer (GC). Long noncoding RNA (lncRNA) and m6A modification are involved in the occurrence and development of GC, but the role of lncRNA m6A modification in the development of GC mediated by H. pylori is still unclear. Here, we found that H. pylori infection downregulated the expression of lnc-PLCB1 through METTL14-mediated m6A modification and IRF2-mediated transcriptional regulation. Overexpression of lnc-PLCB1 inhibited the proliferation and migration of GC cells, while downregulation of lnc-PLCB1 promoted the proliferation and migration ability of GC cells. In addition, clinical analysis showed that lnc-PLCB1 is lower in GC tissues than in normal tissues. Further study found that lnc-PLCB1 reduced the protein stability of its binding protein DEAD-box helicase 21 (DDX21) and then downregulated the expression of CCND1 and Slug, thereby playing tumour suppressing role in the occurrence and development of GC. In conclusion, the METTL14/lnc-PLCB1/DDX21 axis plays an important role in H. pylori-mediated GC, and lnc-PLCB1 can be used as a new target for GC treatment.

Learn to Adapt for Self-Supervised Monocular Depth Estimation.

Monocular depth estimation is one of the fundamental tasks in environmental perception and has achieved tremendous progress by virtue of deep learning. However, the performance of trained models tends to degrade or deteriorate when employed on other new datasets due to the gap between different datasets. Though some methods utilize domain adaptation technologies to jointly train different domains and narrow the gap between them, the trained models cannot generalize to new domains that are not involved in training. To boost the transferability of self-supervised monocular depth estimation models and mitigate the issue of meta-overfitting, we train the model in the pipeline of meta-learning and propose an adversarial depth estimation task. We adopt model-agnostic meta-learning (MAML) to obtain universal initial parameters for further adaptation and train the network in an adversarial manner to extract domain-invariant representations for easing meta-overfitting. In addition, we propose a constraint to impose upon cross-task depth consistency to compel the depth estimation to be identical in different adversarial tasks, which improves the performance of our method and smoothens the training process. Experiments on four new datasets demonstrate that our method adapts quite fast to new domains. Our method trained after 0.5 epoch achieves comparable results with the state-of-the-art methods trained at least 20 epochs.

Molecular Joint Representation Learning via Multi-Modal Information of SMILES and Graphs.

In recent years, artificial intelligence has played an important role on accelerating the whole process of drug discovery. Various of molecular representation schemes of different modals (e.g., textual sequence or graph) are developed. By digitally encoding them, different chemical information can be learned through corresponding network structures. Molecular graphs and Simplified Molecular Input Line Entry System (SMILES) are popular means for molecular representation learning in current. Previous works have done attempts by combining both of them to solve the problem of specific information loss in single-modal representation on various tasks. To further fusing such multi-modal imformation, the correspondence between learned chemical feature from different representation should be considered. To realize this, we propose a novel framework of molecular joint representation learning via Multi-Modal information of SMILES and molecular Graphs, called MMSG. We improve the self-attention mechanism by introducing bond-level graph representation as attention bias in Transformer to reinforce feature correspondence between multi-modal information. We further propose a Bidirectional Message Communication Graph Neural Network (BMC GNN) to strengthen the information flow aggregated from graphs for further combination. Numerous experiments on public property prediction datasets have demonstrated the effectiveness of our model.

Advanced Lung Cancer Inflammation Index for Predicting Prognostic Risk for Patients with Acute Coronary Syndrome Undergoing Percutaneous Coronary Intervention.

Purpose: The decreased advanced lung cancer inflammation index (ALI), defined as body mass index (BMI) * albumin (Alb)/neutrophil-to-lymphocyte ratio (NLR), is an independent prognostic risk factor for overall survival in gastric, lung, and colorectal cancers. This study aimed to investigate the value of ALI in predicting the risk of major adverse cardiovascular events (MACEs) in patients with acute coronary syndrome (ACS). Patients and Methods: A total of 1624 patients with ACS undergoing percutaneous coronary intervention (PCI) were consecutively enrolled between January 2016 and December 2018. Follow-up data were collected at 1, 3, 6, and 12 months and annually thereafter. The primary endpoints were MACEs. All endpoints were defined as all-cause mortality, recurrent angina pectoris, restenosis/intra stent thrombosis, stroke, heart failure, and all-cause bleeding. Results: The MACEs group and non-MACEs group showed significant differences in patients with age >65 years (28 [50.0%] vs 319 [23.7%]), history of heart failure (16 [28.6%] vs 127 [9.4%]), history of ischemic stroke (14 [25.0%] vs 186 [13.8%]), history of cardiogenic shock (6 [10.71%] vs 16 [1.19%]), left ventricular ejection fraction <40% (8 [14.29%] vs 33 [2.46%]), and ALI <343.96 (44 [78.65%] vs 680 [50.60%]) (all p<0.001). The optimal cut-off value for ALI was 334.96. The area under the curve (AUC) of the 1-, 2-, 3-, and 5-year was 0.560, 0.577, 0.665, and 0.749, respectively. The survival rate was significantly lower in the low ALI group than in the high ALI group (log-rank p<0.001). Low ALI was an independent risk factor for the long-term prognosis of patients with ACS after PCI, univariate HR: 3.671, 95% CI: 1.938-6.953, p<0.001; multivariate HR: 3.009, 95% CI: 1.57-5.769, p=0.001. Conclusion: ALI score less than 334.96 is an independent prognostic risk factor for patients with ACS undergoing PCI and may be a novel marker for clinical practice.

Perception and Navigation in Autonomous Systems in the Era of Learning: A Survey.

Autonomous systems possess the features of inferring their own state, understanding their surroundings, and performing autonomous navigation. With the applications of learning systems, like deep learning and reinforcement learning, the visual-based self-state estimation, environment perception, and navigation capabilities of autonomous systems have been efficiently addressed, and many new learning-based algorithms have surfaced with respect to autonomous visual perception and navigation. In this review, we focus on the applications of learning-based monocular approaches in ego-motion perception, environment perception, and navigation in autonomous systems, which is different from previous reviews that discussed traditional methods. First, we delineate the shortcomings of existing classical visual simultaneous localization and mapping (vSLAM) solutions, which demonstrate the necessity to integrate deep learning techniques. Second, we review the visual-based environmental perception and understanding methods based on deep learning, including deep learning-based monocular depth estimation, monocular ego-motion prediction, image enhancement, object detection, semantic segmentation, and their combinations with traditional vSLAM frameworks. Then, we focus on the visual navigation based on learning systems, mainly including reinforcement learning and deep reinforcement learning. Finally, we examine several challenges and promising directions discussed and concluded in related research of learning systems in the era of computer science and robotics.

Understanding learners' metacognitive experiences in learning to write in English as a foreign language: A structural equation modeling approach.

Many researchers have acknowledged the role of metacognition in facilitating learning to write in English as a foreign language (EFL). Although research on metacognition has explored learners' metacognitive knowledge and metacognitive strategies in the field of EFL writing, little is known about the nature of learners' metacognitive experiences in EFL writing. To fill such an important gap, this study was designed to assess EFL learners' metacognitive experiences before, during, and after writing. Data were collected from a total of 760 undergraduates through three self-report questionnaires and a writing task. Results from quantitative analyses showed four subcategories of EFL learners' metacognitive experiences in writing: metacognitive feeling, metacognitive judgments/estimates, online task-specific metacognitive knowledge, and online task-specific metacognitive strategies. Based on the empirical evidence, we propose a model of metacognitive experiences in EFL writing. Theoretical, methodological, and pedagogical implications are discussed.

The role and features of peer assessment feedback in college English writing.

Peer assessment is a common pedagogical practice for evaluating students' writing in college English classrooms. However, in-depth research on the learning outcomes after peer assessment is scarce and inconsistent; how peer feedback is used has not been fully explored either. This study compared peer feedback to teacher feedback and explored the different features of feedback and its impact on draft revision. Two specific research questions were answered in this study: (1) In which aspects can peer feedback supplement teacher feedback in improving the linguistic features in writing? (2) What are the differences in features of peer feedback versus teacher feedback? And how do they connect to feedback take-in? Two writing tasks were assigned to 94 students. One received teacher feedback and the other peer feedback. Pre-feedback and post-feedback writings in both tasks (4 sets in total) were scored and human ratings were adjusted using Many-Facet Rasch modeling to control for differences in leniency. Drawing on three natural language processing (NLP) tools, this study also assessed writing qualities by comparing 22 selected indices related to the scoring rubrics for human raters, which involve three dimensions: cohesion, lexical quality and syntactic complexity. Peer and teacher feedback was then coded based on features of feedback to explore their influence on draft revision. The results showed that both peer and teacher feedback had positive effects on rating scores. We confirmed peer feedback as an effective classroom approach to improve writing, though limited compared to teacher feedback as reflected in the indices. In terms of feedback features, students often stopped at identifying the language problems, while the teacher provided more explanations, solutions or suggestions regarding the problems identified. Implications for peer feedback research and implementation of peer assessment activities are provided.

A visualization analysis of hotspots and frontiers of cardiovascular diseases with frailty.

Cardiovascular diseases (CVD) and frailty are common health problems among the elderly. This research aims to investigate the hotspots and frontiers of the field of CVD with frailty. Data of publications between 2000 and 2021 were collected from the Web of Science Core Collection (WoSCC) and CiteSpace was used for analyzing the hotspots and frontiers of cardiovascular diseases with frailty research from high-impact countries/regions, institutions, authors, cited references, cited journals, high-frequency keywords, and burst keywords. The results showed that the USA, England, and Canada were the leading countries/regions in research on CVD with frailty. Other countries/regions and regions lagged behind these developed countries/regions. There is a need to establish cooperation between developed countries/regions and developing countries/regions. Research hotspots focused on frailty in the elderly with CVD, exercise intervention, assessment for CVD patients with frailty, quality of life, and common diseases related to CVD with frailty. The frontier fields include care and intervention of CVD patients with frailty, social frailty, and validation of CVD with frailty.

Unsupervised Estimation of Monocular Depth and VO in Dynamic Environments via Hybrid Masks.

Deep learning-based methods mymargin have achieved remarkable performance in 3-D sensing since they perceive environments in a biologically inspired manner. Nevertheless, the existing approaches trained by monocular sequences are still prone to fail in dynamic environments. In this work, we mitigate the negative influence of dynamic environments on the joint estimation of depth and visual odometry (VO) through hybrid masks. Since both the VO estimation and view reconstruction process in the joint estimation framework is vulnerable to dynamic environments, we propose the cover mask and the filter mask to alleviate the adverse effects, respectively. As the depth and VO estimation are tightly coupled during training, the improved VO estimation promotes depth estimation as well. Besides, a depth-pose consistency loss is proposed to overcome the scale inconsistency between different training samples of monocular sequences. Experimental results show that both our depth prediction and globally consistent VO estimation are state of the art when evaluated on the KITTI benchmark. We evaluate our depth prediction model on the Make3D dataset to prove the transferability of our method as well.