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Globally, the positive effects of aerobic fermentation industry on the resource utilization of agricultural waste and products on the agricultural production environment have been fully proved. Therefore, it is of great and far-reaching significance to improve the development level of agricultural waste aerobic fermentation industry. In this paper, the current situation of agricultural waste in China, the requirements of aerobic fermentation raw materials and the process were reviewed in order to provide scientific basis for the study of aerobic fermentation of agricultural waste.

As the L2 Motivational Self System (L2MSS) is premised on monolingualism, which ignores the cross-cutting properties of multilingual environments, this study investigates the English Learning Self and its structural characteristics of students in a junior high school in a minority-inhabited area of Guizhou Province, China. These ethnic minority students not only learn their native language (minority languages), but also learn Mandarin Chinese, through which they learn English as their third language, with features of low English proficiency, weak motivation to learn English, and low frequency of English use. Data were collected from 159 Han Chinese students and 274 ethnic minority students in the eighth grade of the junior high school. Structural equation modelling revealed that the Ideal English Self contains three factors: Ideal English Learner, Ideal English Career and Ideal English User, and the most significant Ideal English Self exhibited by the middle school students was Ideal English Learner; while the Ought-to English Self contains three factors: Meeting Other’s Expectation, Self’s Future Expectation and Self’s Present Demand, with Meeting Other’s Expectation marking contributed the most. Through comparative analysis, this study further found that there was no significant difference between local Han Chinese students and ethnic minority students in terms of English Learning Self.

Cryptocaryon irritans infestations on marine teleosts are a considerable burden on factory mariculture. Ultraviolet (UV) light can kill C. irritans under laboratory conditions. However, a rational method for using UV in factory aquaculture to control cryptocaryoniasis has not been developed. This study focused on evaluating the killing effect of UV on protomonts and tomonts of C. irritans and established an automatic UV parasiticide device for the prevention and control of cryptocaryoniasis in marine teleosts.The survival rate of protomonts and tomonts decreased with an increase in the UV irradiation dose. All the protomonts and tomonts died within 14 and 24 min, respectively. The lowest UV lethal doses of protomonts and tomonts of C. irritans were 2.0 × 10The automation of traditional physical methods conforms to the sustainable development of aquaculture and provides a theoretical reference for the prevention and control of cryptocaryoniasis in mariculture. © 2022 Society of Chemical Industry.

Activity-based protein profiling (ABPP) is a versatile strategy for identifying and characterizing functional protein sites and compounds for therapeutic development. However, the vast majority of ABPP methods for covalent drug discovery target highly nucleophilic amino acids such as cysteine or lysine. Here, we report a methionine-directed ABPP platform using Redox-Activated Chemical Tagging (ReACT), which leverages a biomimetic oxidative ligation strategy for selective methionine modification. Application of ReACT to oncoprotein cyclin-dependent kinase 4 (CDK4) as a representative high-value drug target identified three new ligandable methionine sites. We then synthesized a methionine-targeting covalent ligand library bearing a diverse array of heterocyclic, heteroatom, and stereochemically rich substituents. ABPP screening of this focused library identified 1oxF11 as a covalent modifier of CDK4 at an allosteric M169 site. This compound inhibited kinase activity in a dose-dependent manner on purified protein and in breast cancer cells. Further investigation of 1oxF11 found prominent cation-π and H-bonding interactions stabilizing the binding of this fragment at the M169 site. Quantitative mass-spectrometry studies validated 1oxF11 ligation of CDK4 in breast cancer cell lysates. Further biochemical analyses revealed cross-talk between M169 oxidation and T172 phosphorylation, where M169 oxidation prevented phosphorylation of the activating T172 site on CDK4 and blocked cell cycle progression. By identifying a new mechanism for allosteric methionine redox regulation on CDK4 and developing a unique modality for its therapeutic intervention, this work showcases a generalizable platform that provides a starting point for engaging in broader chemoproteomics and protein ligand discovery efforts to find and target previously undruggable methionine sites.

Based on a large number of drilling and laboratory test data in Weibei loess tableland area, the correlation of three conventional physical and mechanical indexes of loess in this area, such as void ratio, compression coefficient and collapsibility coefficient, was analyzed and studied. The results show that void ratio is positively correlated with compression coefficient and collapsibility coefficient, and the correlation between void ratio and collapsibility coefficient is higher. The correlation between compression coefficient and collapsibility coefficient is obvious when the compressibility of soil is small, but there is no obvious correlation between collapsibility coefficient and compression coefficient when the compression coefficient is large.

This paper analysed a total of 334 English language articles on teaching Chinese as a second or foreign language from the Web of Science, during the period from 2001 to 2020. By examining the bibliometric indices of the literature, the analysis found that: 1) The numbers of research publication and citation have gone through slow growth in the first decade and strong growth in the second decade. 2) Highly cited journals are mainly from four categories: educational technology, linguistics, education and psychology. 3) Highly productive authors are mainly from the fields of computing and education, with research interests focused on the use of digital technology to help Chinese language learning. 4) Highly co-cited articles include keywords related to young Chinese learners, foreign language, English context and character learning. 5) The topical trends in Chinese language education research have evolved from an early focus on Chinese writing, learning strategies and cross-cultural language teaching to a mid-term focus on issues such as classroom management and task-based teaching, and further expansion to a more recent focus on the integration of digital technologies and multimodal approaches to teaching and learning. By reviewing these five areas, this study aims to provide a complete picture of the research on teaching Chinese as a second or foreign language outside mainland China. It is intended to help build bridges of collaboration between researchers and institutions within and outside mainland China by highlighting the researchers who have made significant contributions and the wide range of issues being explored.

The authors co-chaired this symposium, entitled How to Make Peer Feedback Work and hosted online by the Malaysian Association of Applied Linguistics (MAAL) on 1 September 2022. The speakers, Juuso Henrik Nieminen (Assistant Professor, University of Hong Kong), James Wood (Associate Teaching Professor, Seoul National University), Wei Wei (Associate Professor, Macao Polytechnic University), Tingting Liu (PhD candidate, Nanyang Technological University), and Vahid Aryadoust (Associate Professor, Nanyang Technological University) delivered enlightening presentations to over 50 participants, in turn, discussing topics related to authentic assessment, dialogic peer screencast feedback, self-efficacy, teacher video feedback, and gender and academic major bias in relation to peer assessment.

The Chinese medicine of Cannabis sativa fruit is called “Hemp Seed” or “Cannabis Kernel.” It is calm, sweet, and has the function of moistening the intestines and treating dry stool. The flower is called “Ma Bo,” and it treats evil wind, amenorrhea, and forgetfulness. After the extraction of active ingredient from Cannabis sativa, its treatment activity against acute coronary artery was determined and the detailed mechanism was also examined. First of all, ELISA was exploited to investigate the release of inflammatory cytokines in plasma. After that, via utilizing real time RT-PCR, the activation for the signaling pathway of NF-κB existing in endothelial cell could be identified after the specific treatment. For the Cannabis sativa, its complete chloroplast genome was analyzed through Illumina pair-end sequencing. According to neighbor-joining (NJ) phylogenetic analysis, the Humulus lupulus and Cannabis sativa come together and become the sisters of other associated species.

PurposeThis meta-analysis compared the long-term (12 months or 24 months) efficacy and safety of intravitreal aflibercept injection (IAI) for diabetic macular edema (DME) and proliferative diabetic retinopathy (PDR).MethodsWe selected 16 randomized controlled trials (RCTs) performed after 2015 that had a minimum of 12 months and up to 24 months of treatment and conducted a meta-analysis with Review Manager version 5.3. Visual acuity (VA), central subfield thickness (CST) and adverse events were the outcomes selected for evaluation from the eligible studies.ResultsBased on 16 RCTs, we evaluated a total of 7125 patients. For PDR and severe DME with poor baseline vision, after a minimum of 12 months and up to 24 months of treatment, the aflibercept treatment group obtained better VA improvement than the focal/grid laser photocoagulation treatment group (MD=13.30; 95%CI: 13.01~13.58; PPPPConclusionsThis meta-analysis showed that the advantages of IAI are obvious in the management of DME and PDR with poor baseline vision for long-term observation (a minimum of 12 months and up to 24 months) with both VA improvement and CST reduction. Applied IAI separately trended to be more effective than panretinal photocoagulation separately in VA improvement for PDR. More parameters should be required to assess functional and anatomic outcomes.

The catenin beta 1 gene (CTNNB1) plays a crucial role in the malignant progression of various cancers. Emerging studies have suggested that its hyperactivation is closely related to the occurrence and development of bladder cancer(BCa). Here, we report that UCHL3(Ubiquitin C-terminal hydrolase L3), a deubiquitinating enzyme promotes the development of bladder cancer through Wnt signaling pathway by interacting with and stabilizing CTNNB1 in vitro and in vivo. GSEA analysis showed that UCHL3 was highly associated with Wnt signaling pathway, and it was validated by luciferase reporter assays and RT-PCR, which found that its functions depend on its deubiquitinating activity. We also found that the overexpression of UCHL3 boosted the bladder cancer cells proliferation, invasion and migration, while the depletion of UCHL3 in bladder cancer cells delayed the tumor tumorigenesis in vitro and in vivo. Especially, Uchl3-deficient mice were less susceptible to bladder tumorigenesis. Additionally, UCHL3 was highly expressed in bladder cancer and associated with advanced clinicopathological parameters. These findings provided direct insight into the molecular mechanism of the functions of UCHL3 in bladder cancer, and provided new target for therapeutic approach against bladder cancer.

The sea-gale process (SGP) is a significant and disastrous weather event for the marine industry. However, the sub-seasonal predictability of SGP remains unclear. In this study, we investigate the influence of low-frequency oscillation on SGP in the Yangtze River estuary from November to April, and its implications for sub-seasonal prediction. We noted that SGPs have a close relationship with the 10~30 day low-frequency component of the 10-m wind speed in the Yangtze River estuary, and typically occur during the peak phase of the low-frequency oscillation. The 10~30 day low-frequency oscillation of 10-m wind was found to be linked to the eastward propagation of extratropical Rossby waves from the North Atlantic across Europe to East Asia. This Rossby wave leads to the low-frequency oscillation of the Siberian high pressure and Japan Sea low pressure, which is indicative of the 10~30 day low-frequency oscillations of the 10-m wind speed in the Yangtze River Estuary. A sea-gale process index (SGPI) was constructed based on the low-frequency oscillation of the Siberian high and the Japan Sea low in order to predict SGPs at the sub-seasonal time scale. Hindcast and real-time forecasts showed that 2/3 of SGPs can be predicted with a leading time of 10~30 days, and that good sub-seasonal predictions of SGPs are connected with strong low-frequency oscillations at the initial forecast time. Therefore, SGPI can be adopted for the sub-seasonal prediction of SGPs in the Yangtze River Estuary.

The representation of landform element varies over multiple scales, or multiresolution digital elevation model (DEM) and its derivatives. When more details of land surfaces are available to be characterized based on the existing high spatial resolution elevation products, the influence of scale variation might become more significant. This poses a demand for determining a scale-independent approach being competent to support multiscale landform element detection on high-resolution DEMs. Although the practicability of the state-of-the-art scale-independent approaches have been reported on moderate-resolution DEMs, how these approaches perform based on the multiscale data including high and moderate spatial-resolution DEMs is still unexplored. This letter evaluates the performance of four scale-independent techniques including filtering, spatial pyramid, multiscale segmentation, and spatial-contextual approach in landform element detection on different spatial resolution DEMs. The experimental results show that spatial-contextual approach is more effective to support multiscale landform element detection than others.

Lineup selection is an essential and important task in soccer matches. To win a match, coaches must consider various factors and select appropriate players for a planned formation. Computation-based tools have been proposed to help coaches on this complex task, but they are usually based on over-simplified models on player performances, do not support interactive analysis, and overlook the inputs by coaches. In this paper, we propose a method for visual analytics of soccer lineup selection by tackling two challenges: characterizing essential factors involved in generating optimal lineup, and supporting coach-driven visual analytics of lineup selection. We develop a lineup selection model that integrates such important factors, such as spatial regions of player actions and defensive interactions with opponent players. A visualization system, Team-Builder, is developed to help coaches control the process of lineup generation, explanation, and comparison through multiple coordinated views. The usefulness and effectiveness of our system are demonstrated by two case studies on a real-world soccer event dataset.

Tactic analysis is a major issue in badminton as the effective usage of tactics is the key to win. The tactic in badminton is defined as a sequence of consecutive strokes. Most existing methods use statistical models to find sequential patterns of strokes and apply 2D visualizations such as glyphs and statistical charts to explore and analyze the discovered patterns. However, in badminton, spatial information like the shuttle trajectory, which is inherently 3D, is the core of a tactic. The lack of sufficient spatial awareness in 2D visualizations largely limited the tactic analysis of badminton. In this work, we collaborate with domain experts to study the tactic analysis of badminton in a 3D environment and propose an immersive visual analytics system, TIVEE, to assist users in exploring and explaining badminton tactics from multi-levels. Users can first explore various tactics from the third-person perspective using an unfolded visual presentation of stroke sequences. By selecting a tactic of interest, users can turn to the first-person perspective to perceive the detailed kinematic characteristics and explain its effects on the game result. The effectiveness and usefulness of TIVEE are demonstrated by case studies and an expert interview.

In a basketball play, players who are not in possession of the ball (i.e., off-ball players) can still effectively contribute to the team's offense, such as making a sudden move to create scoring opportunities. Analyzing the movements of off-ball players can thus facilitate the development of effective strategies for coaches. However, common basketball statistics (e.g., points and assists) primarily focus on what happens around the ball and are mostly result-oriented, making it challenging to objectively assess and fully understand the contributions of off-ball movements. To address these challenges, we collaborate closely with domain experts and summarize the multi-level requirements for off-ball movement analysis in basketball. We first establish an assessment model to quantitatively evaluate the offensive contribution of an off-ball movement considering both the position of players and the team cooperation. Based on the model, we design and develop a visual analytics system called OBTracker to support the multifaceted analysis of off-ball movements. OBTracker enables users to identify the frequency and effectiveness of off-ball movement patterns and learn the performance of different off-ball players. A tailored visualization based on the Voronoi diagram is proposed to help users interpret the contribution of off-ball movements from a temporal perspective. We conduct two case studies based on the tracking data from NBA games and demonstrate the effectiveness and usability of OBTracker through expert feedback.

The spatial time series generated by city sensors allow us to observe urban phenomena like environmental pollution and traffic congestion at an unprecedented scale. However, recovering causal relations from these observations to explain the sources of urban phenomena remains a challenging task because these causal relations tend to be time-varying and demand proper time series partitioning for effective analyses. The prior approaches extract one causal graph given long-time observations, which cannot be directly applied to capturing, interpreting, and validating dynamic urban causality. This paper presents Compass, a novel visual analytics approach for in-depth analyses of the dynamic causality in urban time series. To develop Compass, we identify and address three challenges: detecting urban causality, interpreting dynamic causal relations, and unveiling suspicious causal relations. First, multiple causal graphs over time among urban time series are obtained with a causal detection framework extended from the Granger causality test. Then, a dynamic causal graph visualization is designed to reveal the time-varying causal relations across these causal graphs and facilitate the exploration of the graphs along the time. Finally, a tailored multi-dimensional visualization is developed to support the identification of spurious causal relations, thereby improving the reliability of causal analyses. The effectiveness of Compass is evaluated with two case studies conducted on the real-world urban datasets, including the air pollution and traffic speed datasets, and positive feedback was received from domain experts.

Detecting areas where a landslide or a mudslide might occur is critical for emergency response, disaster recovery, and disaster cost estimation. Previous works have reported that a variety of convolutional neural networks (CNNs) significantly outperform traditional approaches for landslide/mudslide detection. These approaches always consider features from the local window and neighborhood information. The CNNs mainly focus on the features derived at a local scale, which might be inefficient for recognizing complex landslide and mudslide scenes. To effectively identify landslide and mudslide risks at a local and global scale, this paper integrates attentions into the architecture of state-of-the-art CNNs—including Faster RCNN—to develop an attention-enhanced region proposal network for multi-scale landslide/mudslide detection. In detail, we employed the attentions to process the region proposals generated by a region proposal network and then combined the results obtained from the attentions and region proposal network to identify whether the object included in a region proposal was a landslide/mudslide. Based on our developed dataset and the Bijie dataset, the experimental results prove that: (1) although the state-of-the-art CNNs for object detection can precisely detect landslides and mudslides, they are inadequate in dealing with similarity to non-landslide/non-mudslide regions; and (2) the proposed method, which integrates global features from attention layers into local features derived from CNNs, outperforms the unmodified CNNs in detecting non-landslides and non-mudslides. Our findings prove that the representations at the local and global scale might be significant for precise landslide and mudslide detection.

Ancient landslide has strong concealment and disturbance sensitivity due to its special geotechnical mechanical characteristics, and it is the potential hazard that cannot be ignored in human activities and major engineering planning. The quantitative assessment of ancient landslide reactivation risk has become more necessary for pre-disaster scientific warning. However, because the mechanisms of deformation and damage during the evolution of ancient landslides are quite complex, traditional landslide risk assessment methods only select the single-time scale and relatively stable environmental factors for analysis, lacking consideration of dynamic triggering factors such as rainfall. Focusing on the complexity, a quantitative enhanced assessment for ancient landslide reactivation risk considering cross-time scale joint response mechanism is proposed. First, on the basis of systematic analysis of the implicit genesis mechanism and explicit characterization, an evaluation system of the cross-time scale joint characteristics of ancient landslide reactivation is constructed. Then, XGBoost algorithm and SBAS-InSAR are used to establish the long-time scale developmental evolution mechanism model and the short-time scale dynamical trigger model, respectively. Subsequently, we propose a cross-time scale joint response mechanism. The information entropy weight method is applied to calculate the contribution degree of long-short time scale assessment models for ancient landslide reactivation based on the constraints of quantitative interval thresholds, and the assessment processes of different time scales are dynamically and quantitatively correlated. Finally, the updated optimization of the assessment of ancient landslide reactivation risk is achieved. In this research, experimental analysis was carried out for ancient landslide groups in a geological hazard-prone area in Fengjie County, Chongqing, a typical mountainous region of China. The results of the comparative analysis validate the superiority of the method in this paper. It helps to accurately assess the ancient landslide potential hazard in advance, providing scientific basis and technical support for the risk assessment of mountainous watershed geological hazards and major engineering projects.

Cyclophosphamide-induced testosterone deficiency (CPTD) during the treatment of cancers and autoimmune disorders severely influences the quality of life of patients. Currently, several guidelines recommend patients suffering from CPTD receive testosterone replacement therapy (TRT). However, TRT has many disadvantages underscoring the requirement for alternative, nontoxic treatment strategies. We previously reported bone marrow mesenchymal stem cells-derived exosomes (BMSCs-exos) could alleviate cyclophosphamide (CP)-induced spermatogenesis dysfunction, highlighting their role in the treatment of male reproductive disorders. Therefore, we further investigated whether BMSCs-exos affect autophagy and testosterone synthesis in Leydig cells (LCs). Here, we examined the effects and probed the molecular mechanisms of BMSCs-exos on CPTD in vivo and in vitro by detecting the expression levels of genes and proteins related to autophagy and testosterone synthesis. Furthermore, the testosterone concentration in serum and cell-conditioned medium, and the photophosphorylation protein levels of adenosine monophosphate-activated protein kinase (AMPK) and mammalian target of rapamycin (mTOR) were measured. Our results suggest that BMSCs-exos could be absorbed by LCs through the blood-testis barrier in mice, promoting autophagy in LCs and improving the CP-induced low serum testosterone levels. BMSCs-exos inhibited cell death in CP-exposed LCs, regulated the AMPK-mTOR signaling pathway to promote autophagy in LCs, and then improved the low testosterone synthesis ability of CP-induced LCs. Moreover, the autophagy inhibitor, 3-methyladenine (3-MA), significantly reversed the therapeutic effects of BMSCs-exos. These findings suggest that BMSCs-exos promote LC autophagy by regulating the AMPK-mTOR signaling pathway, thereby ameliorating CPTD. This study provides novel evidence for the clinical improvement of CPTD using BMSCs-exos.

Being an efficient image reconstruction and recognition algorithm, two-dimensional PCA (2DPCA) has an obvious disadvantage in that it treats the rows and columns of images unequally. To exploit the other lateral information of images, alternative 2DPCA (A2DPCA) and a series of bilateral 2DPCA algorithms have been proposed. This paper proposes a new algorithm named direct bilateral 2DPCA (DB2DPCA) by fusing bilateral information from images directly—that is, we concatenate the projection results of 2DPCA and A2DPCA together as the projection result of DB2DPCA and we average between the reconstruction results of 2DPCA and A2DPCA as the reconstruction result of DB2DPCA. The relationships between DB2DPCA and related algorithms are discussed under some extreme conditions when images are reshaped. To test the proposed algorithm, we conduct experiments of image reconstruction and recognition on two face databases, a handwritten character database and a palmprint database. The performances of different algorithms are evaluated by reconstruction errors and classification accuracies. Experimental results show that DB2DPCA generally outperforms competing algorithms both in image reconstruction and recognition. Additional experiments on reordered and reshaped databases further demonstrate the superiority of the proposed algorithm. In conclusion, DB2DPCA is a rather simple but highly effective algorithm for image reconstruction and recognition.

Experimental studies were conducted in a super-large wave flume, aiming at uncovering the hydrodynamic characteristics involved in the turbulent wave boundary layer of full scale environment. An explicit formula of boundary layer thickness on rough turbulent flow was presented based on the measured velocity data of the present study and collected experimental data on wave boundary layer. It was found that the bottom wave-associated nominal stresses under the conditions of prototype scale tests suppress the vertical turbulence scattering upward over the boundary layer, which accounts for thickening of the boundary layer under wave condition. Such effect has yet not been reported in the literatures using oscillatory U-tube or small-sized wave flume. The phase inconsistency in the turbulent boundary layer to the free stream velocity (velocity immediately outside the boundary layer) is within 15°, which is remarkably smaller than the results from oscillatory U-tubes, as well as the larger wave flume experiment presented by Xie et al. (2021), showing that the coarser bed would further reduce the phase lead. The intensity of the vertical turbulent component is approximately 1/2 of the horizontal component, which has larger ratio compared with the value of 1/5 reported by previous studies. Especially, it was also found that the vertical turbulent energy was approximately 3/4 of the turbulent energy in spanwise directions (y-direction). This means that the turbulent fluctuation has similar order in all three-directions (x, y, z) in a full scale environment and highlights that the turbulent components in all the three directions should not be neglected when calculating the total turbulent energy.

Xiao Xie, Fangbao Ding, Haibo Xiao Department of Cardiothoracic Surgery, Xinhua Hospital Affiliated to Shanghai Jiao Tong University School of Medicine, Shanghai, 200092, People’s Republic of ChinaCorrespondence: Fangbao Ding; Haibo XiaoDepartment of Cardiothoracic Surgery, Xinhua Hospital Affiliated to Shanghai Jiao Tong University School of Medicine, No. 1665 Kongjiang Road, Shanghai, 200092, People’s Republic of ChinaEmail dingfangbao@xinhuamed.com.cn; xiaohaibo@xinhuamed.com.cnBackground: Non-small cell lung cancer (NSCLC) is a subtype of lung cancer which seriously threatens the health of people. Circular RNAs (CircRNAs) are endogenous RNAs which have stable closed structure; they are known to be involved in tumorigenesis of NSCLC. Meanwhile, hsa_circ_0000729 was reported to be upregulated in NSCLC. Nevertheless, the function of hsa_circ_0000729 in NSCLC remains unclear.Methods: Western blot and RT-qPCR were performed to investigate protein and mRNA levels, respectively. CCK-8 assay was performed to test the cell viability and cell death was investigated by flow cytometry. NSCLC cell pyroptosis was observed by electron microscope. In addition, the migration and invasion of NSCLC cells were detected by wound healing and transwell assay. The relation among hsa_circ_0000729, miR-1281 and FOXO3 was explored by dual luciferase reporter assay and RNA pull-down.Results: Hsa_circ_0000729 was found to be upregulated in NSCLC cells, and hsa_circ_0000729 knockdown obviously suppressed the proliferation of NSCLC cells through inducing pyroptosis. In addition, silencing of hsa_circ_0000729 notably inhibited the invasion and migration of NSCLC cells. Meanwhile, hsa_circ_0000729 could bind with miR-1281, and FOXO3 was directly targeted by miR-1281. Moreover, the anti-tumor effect of hsa_circ_0000729 siRNAs on NSCLC was markedly reversed by miR-1281 antagomir. Furthermore, silencing of hsa_circ_0000729 inhibited the tumor growth of NSCLC in vivo.Conclusion: Knockdown of hsa_circ_0000729 inhibits the tumorigenesis of NSCLC through mediation of miR-1281/FOXO3 axis. Thus, hsa_circ_0000729 might be served as a crucial mediator in NSCLC.Keywords: hsa_circ_0000729, miR-1281, FOXO3, pyroptosis

The value of the high-resolution data lies in the high-precision information discovery. The fine-detailed landform element extraction is thus the basis of high-fidelity application of the high-resolution digital elevation models (DEMs). However, the results of landform element extraction generated by classical methods might be ungrounded on high-resolution DEMs. This paper presents our research on using the aspect to reinforce the applicability and robustness of the classical approaches in landform element extraction. First, according to the research of pattern recognition, we assume that aspect-enhanced landform representation is robust to rotation, scaling and affine variance. To testify the role of aspect, we respectively integrated the aspect into three classical approaches: mean curvature-based fuzzy classification, elevation-based feature descriptor, and object-based segmentation. In the experiment, based on four types of high-resolution DEMs (1 m, 2 m, 4 m and 8 m), we compare each classical approaches and their corresponding aspect-enhanced approaches based on extracting the rims of two craters having different landforms, and the ridgelines and valleylines of a region covered by few vegetables and man-made buildings. In comparison to the results generated by curvature-based fuzzy classification, the aspect enhanced curvature-based fuzzy classification can effectively filter a number of noises outperforms the curvature-based one. Otherwise, the aspect-enhanced feature descriptor can detect more landform elements than the elevation-based feature descriptor. Moreover, the aspect-based segmentation can detect the main structure of landform, while the boundaries segmented by classical approaches are messing and meaningless. The systematic experiments on meter-level resolution DEMs proved that the aspect in topography could effectively to improve the classical method-system, including fuzzy-based classification, feature descriptors-based detection and object-based segmentation. The value of aspect is significantly great to be worthy of attentions in landform representation.

How could soccer player migration impact national team performance, or vice versa? The answer to this question could play an essential role in making appropriate decisions and policies regarding the international mobility of soccer players. However, answering such a question faces two main challenges, including the complex relationship between variables in multi-attribute temporal data describing migrated players and national team performance, and the interpretation of analysis results in policymaking scenarios. In this work, we have closely collaborated with domain experts and characterized the problems of soccer player migration analysis. To address the first challenge, we adapt a cross-lagged panel analysis model into the player migration analysis problem. This cross-lagged panel analysis model is effective to evaluate the impact strength between player migration and national team performance, and straightforward to reveal the causal relationship. To address the second challenge, we design and develop a visual analytics system, MIG-Viewer, to help the experts to interpret the results of the proposed model efficiently. With MIG-Viewer, the experts can navigate the countries of interest in accordance with migration strategy, conduct comprehensive analysis with the comparison of impact strength, and adjust player migration and inspect further details of a specific country. We present two case studies using global player migration data since 1992 with three soccer analysis experts to demonstrate the effectiveness and usefulness of the system.

Objective To obtain the elastic quantitative and semi-quantitative indexes of solid breast masses using ultrasound linear array probes with two different frequencies, and to construct prediction models and evaluate their diagnostic values. Methods A total of 92 patients who were scheduled for surgical treatment on solid breast masses were enrolled in this study. Linear array probes with two frequencies, 9-3 MHz (L9 group) and 14-5 MHz (L14 group), were used for sound touch elastography and strain elastography before surgery, and the maximum elasticity value (Emax), average elasticity value (Emean), minimum elasticity value (Emin), standard deviation (SD)(in kPa), elasticity ratio (E), and strain ratio to fat (SRf) were recorded and calculated for the breast mass (A) and surrounding tissues (Shell). The elastic characteristic indexes of the L9 group and L14 group were compared, and the prediction models of these two groups were constructed using Logistic regression method. Results The diagnostic performance of the prediction model based on L9 group was better than the model based on L14 group (AUC: 0.904 vs. 0.810, P = 0.0343, z = 2.116) and the best single index EMax-shell-L9 (P = 0.0398, z = 2.056). The sensitivity of L9 based model was 85.19% and the specificity was 84.21%. Conclusion The prediction model based on quantitative and semi-quantitative elastic ultrasound indexes from L9-3 probe exhibited better performance, which could improve the diagnostic accuracy for malignant breast tumors.

Copper alloy sheets have been shown to prevent cryptocaryoniasis. Therefore, we studied the potential efficiency of copper alloy mesh (CAM) in aquaculture tanks to prevent cryptocaryoniasis outbreaks. The effectivenesses of CAM against the tomont stage of Cryptocaryon irritans and in protecting fish from cryptocaryoniasis were tested both in vitro and in vivo. The mortality rate of C. irritans tomonts increased as the contact time with CAM rose and peaked at 70 min (100% of mortality). Morphological changes were observed such as the shrinking of the protoplasm of the treated tomonts, resulting in a larger gap between the cytoplasm and the cyst wall. Mitochondrial dysfunction due to shrinkage in the inner portion, outer and inner mitochondrial membrane damage and cytoplasmic vacuolation was revealed by ultrastructural analysis. The use of CAM effectively preventing reinfection was also provided. In comparison with group B (infected fish without CAM), both groups A (uninfected fish as a control group) and C (infected fish treated with CAM) had a 100% survival rate until the end of the trial. CAM has the same anticryptocaryoniasis effect as copper alloy sheets but is more advantageous due to its lightweight, reduced labor cost and lower purchase cost. It is noticeable that CAM exposure also prevents the excessive accumulation of copper ions in aquaculture sea water.

Cultivated land is an important prerequisite and guarantee for food production and security, and the change of cultivated land resources in China has always been concerned. National land survey is an effective way to accurately grasp the area and distribution of cultivated land resources. However, due to the differences in technical means and statistical standards at different stages, there are obvious breakpoints among the cultivated land area data of the three land surveys in China, which hinders the in-depth study of the spatio-temporal distribution of cultivated land resources in long-time series. The Autoregressive Integrated Moving Average model is used to reconstruct and mine the cultivated land area data from 1996 to 2019 based on the data of the third land survey in China. The spatio-temporal variation characteristics of cultivated land area are explored by using Geographic Information System spatial analysis, and the driving factors of cultivated land change are analyzed based on Geographical Detector (GeoDetector) from the perspective of social, economic, agricultural and natural. The results show that the area of cultivated land in China decreased continuously from 1996 to 2019, with a sharp decrease from 1996 to 2004 and a slow decrease from 2005 to 2019. From 1996 to 2019, there were obvious spatial differences in the change of cultivated land area in 31 provincial units. From 1996 to 2008, the cultivated land area in 29 provinces showed a downward trend, especially in the central and northern regions such as Shaanxi, Sichuan and Inner Mongolia. From 2008 to 2019, the cultivated land area in the underdeveloped areas of Heilongjiang, Jilin, Liaoning, Xinjiang, Gansu and Tibet increased significantly, while the rest showed a downward trend. Factor detection found that the q values of population, regional gross domestic product grain output, the proportion of the added value of the primary industry and average slope were all more than 0.5, which had an important impact on the change of cultivated land area. The explanatory power of the interaction between factors on the change of cultivated land area is enhanced in different degrees compared with the single factor effect, which is manifested in the enhancement of bilinear or nonlinear enhancement, and the interaction of different factors promotes the change of cultivated land area. The change of cultivated land area is the result of complex interaction between factors, and is closely related to the land policy in the same period.

Conventional racket sports training highly relies on coaches' knowledge and experience, leading to biases in the guidance. To solve this problem, smart wearable devices based on Internet of Things technology (IoT) have been extensively investigated to support data-driven training. Considerable studies introduced methods to extract valuable information from the sensor data collected by IoT devices. However, the information cannot provide actionable insights for coaches due to the large data volume and high data dimensions. We proposed an IoT + VA framework, Tac-Trainer, to integrate the sensor data, the information, and coaches' knowledge to facilitate racket sports training. Tac-Trainer consists of four components: device configuration, data interpretation, training optimization, and result visualization. These components collect trainees' kinematic data through IoT devices, transform the data into attributes and indicators, generate training suggestions, and provide an interactive visualization interface for exploration, respectively. We further discuss new research opportunities and challenges inspired by our work from two perspectives, VA for IoT and IoT for VA.

Augmented sports videos, which combine visualizations and video effects to present data in actual scenes, can communicate insights engagingly and thus have been increasingly popular for sports enthusiasts around the world. Yet, creating augmented sports videos remains a challenging task, requiring considerable time and video editing skills. On the other hand, sports insights are often communicated using natural language, such as in commentaries, oral presentations, and articles, but usually lack visual cues. Thus, this work aims to facilitate the creation of augmented sports videos by enabling analysts to directly create visualizations embedded in videos using insights expressed in natural language. To achieve this goal, we propose a three-step approach - 1) detecting visualizable entities in the text, 2) mapping these entities into visualizations, and 3) scheduling these visualizations to play with the video - and analyzed 155 sports video clips and the accompanying commentaries for accomplishing these steps. Informed by our analysis, we have designed and implemented Sporthesia, a proof-of-concept system that takes racket-based sports videos and textual commentaries as the input and outputs augmented videos. We demonstrate Sporthesia's applicability in two exemplar scenarios, i.e., authoring augmented sports videos using text and augmenting historical sports videos based on auditory comments. A technical evaluation shows that Sporthesia achieves high accuracy (F1-score of 0.9) in detecting visualizable entities in the text. An expert evaluation with eight sports analysts suggests high utility, effectiveness, and satisfaction with our language-driven authoring method and provides insights for future improvement and opportunities., 10 pages, IEEE VIS conference

The COVID-19 pandemic has demonstrated the need for real-time, open-access epidemiological information to inform public health decision-making and outbreak control efforts. In Canada, authority for healthcare delivery primarily lies at the provincial and territorial level; however, at the outset of the pandemic no definitive pan-Canadian COVID-19 datasets were available. The COVID-19 Canada Open Data Working Group was created to fill this crucial data gap. As a team of volunteer contributors, we collect daily COVID-19 data from a variety of governmental and non-governmental sources and curate a line-list of cases and mortality for all provinces and territories of Canada, including information on location, age, sex, travel history, and exposure, where available. We also curate time series of COVID-19 recoveries, testing, and vaccine doses administered and distributed. Data are recorded systematically at a fine sub-national scale, which can be used to support robust understanding of COVID-19 hotspots. We continue to maintain this dataset, and an accompanying online dashboard, to provide a reliable pan-Canadian COVID-19 resource to researchers, journalists, and the general public., Measurement(s) COVID-19 Cases • COVID-19 Mortalities • COVID-19 vaccination Technology Type(s) digital curation Sample Characteristic - Organism Homo sapiens Sample Characteristic - Location Canada Machine-accessible metadata file describing the reported data: 10.6084/m9.figshare.14331311

β-1,3-glucans, natural polysaccharide groups, exert immunomodulatory effects to improve the innate response and disease resistance in aquatic species and mammals. However, this β-glucan stimulant is yet to be assayed in swimming crab (Portunus trituberculatus) hemocytes. In this study, we explored the immunomodulatory effect of β-1,3-glucans (derived from Euglena gracilis) via in vitro 24 h stimulation assays in swimming crab hemocytes. We found that this algal β-1,3-glucans in crab hemocytes significantly elevated cellular enzymes related parameters, including phenoloxidase (PO), lysozyme, acid phosphatase (ACP) activities, and superoxide anion generation (O2−) rate both at intracellular (P 0.05). β-glucan significantly influenced (P

Chemoresistance is the most significant reason for the failure of cancer treatment following radical cystectomy. The response rate to the first-line chemotherapy of cisplatin and gemcitabine does not exceed 50%. In our previous research, elevated BMI1 (B-cell specific Moloney murine leukemia virus integration region 1) expression in bladder cancer conferred poor survival and was associated with chemoresistance. Herein, via analysis of The Cancer Genome Atlas database and validation of clinical samples, BMI1 was elevated in patients with bladder cancer resistant to cisplatin and gemcitabine, which conferred tumor relapse and progression. Consistently, BMI1 was markedly increased in the established cisplatin- and gemcitabine-resistant T24 cells (T24/DDP&GEM). Functionally, BMI1 overexpression dramatically promoted drug efflux, enhanced viability and decreased apoptosis of bladder cancer cells upon treatment with cisplatin or gemcitabine, whereas BMI1 downregulation reversed this effect. Mechanically, upon interaction with p53, BMI1 was recruited on the promoter of miR-3682-3p gene concomitant with an increase in the mono-ubiquitination of histone H2A lysine 119, leading to transcription repression of miR-3682-3p gene followed by derepression of ABCB1 (ATP binding cassette subfamily B member 1) gene. Moreover, suppression of P-glycoprotein by miR-3682-3p mimics or its inhibitor XR-9576, could significantly reverse chemoresistance of T24/DDP&GEM cells. These results provided a novel insight into a portion of the mechanism underlying BMI1-mediated chemoresistance in bladder cancer.