This article presents the design principle and fabrication of a variable stiffness soft robotic gripper for adaptive grasping robust holding. The proposed is based on finger that combines fiber-reinforced actuator particle pack. responsible bending motion finger, pack acts as stiffness-changeable interface between object. In natural state, to part geometry. It can rapidly stiffen (through vacuum) resist external load or freeze currently bent contour finger. Experimental studies have shown...

Abstract The recent breakthrough of single-cell RNA velocity methods brings attractive promises to reveal directed trajectory on cell differentiation, states transition and response perturbations. However, the existing are often found return erroneous results, partly due model violation or lack temporal regularization. Here, we present UniTVelo, a statistical framework that models dynamics spliced unspliced RNAs via flexible transcription activities. Uniquely, it also supports inference...

Although massive open online courses (MOOCs) have attracted much worldwide attention, scholars still understand little about the specific elements that students find engaging in these large courses. This study offers a new original contribution by using machine learning classifier to analyze 24,612 reflective sentences posted 5,884 students, who participated one or more of 18 highly rated MOOCs. Highly MOOCs were sampled because they exemplify good practices teaching strategies. We selected...

Significance The recently introduced RNA velocity methods, by leveraging the intrinsic splicing process, have shown their unique capability of identifying directionality cell differentiation trajectory. However, due to minimal amount unspliced contents, estimation suffers from high noise and may result in less reliable trajectories. Here, we present Velocity Autoencoder (VeloAE), a tailored autoencoder denoise for more accurate quantification transitions. Through various biological systems,...

Abstract Mitochondrial mutations are increasingly recognised as informative endogenous genetic markers that can be used to reconstruct cellular clonal structure using single-cell RNA or DNA sequencing data. However, identifying mtDNA variants in noisy and sparse data is still challenging with few computation methods available. Here we present an open source computational tool MQuad accurately calls clonally a population of single cells, analysis suite for complete clonality inference, based...

Individual tree detection and counting in unmanned aerial vehicle (UAV) imagery constitute a vital practical research field. Vegetation remote sensing captures large-scale trees characterized by complex textures, significant growth variations, high species similarity within the vegetation, which presents challenges for annotation detection. Existing methods based on bounding boxes have struggled to convey semantics information about crowns. This paper proposes novel deep learning network...

Abstract Background Recently, it has been reported that miRNA is involved in pterygium, however the exact underlying mechanism pterygium unrevealed and require further investigation. Methods The differential expression of was profiled using microarray validated with quantitative real-time polymerase chain reaction (qRT-PCR). Human conjunctival epithelial cells (HCEs) were cultured treated transforming growth factor β (TGF-β) epidermal (EGF) transfected miR-199a-3p/5p mimic inhibitor. Markers...

Imputation of missing features in spatial transcriptomics is urgently needed due to technological limitations. However, most existing computational methods suffer from moderate accuracy and cannot estimate the reliability imputation. To fill this research gap, we introduce a model, TransImpute, that imputes feature modality by mapping it single-cell reference data. We derive set attributes can accurately predict imputation uncertainty, enabling us select reliably imputed genes. In addition,...

For accurate gene expression quantification, normalization of data against reliable reference genes is required. It known that the levels commonly used vary considerably under different experimental conditions, and therefore, their use for limited. In this study, an unbiased identification in Caenorhabditis elegans was performed based on 145 microarray datasets (2296 array samples) covering developmental stages, tissues, drug treatments, lifestyle, various stresses. As a result, thirteen...

MiRNAs have been widely analyzed in the occurrence and development of many diseases, including pterygium. This study aimed to identify key genes miRNAs pterygium explore underlying molecular mechanisms.MiRNA expression was initially extracted pooled by published literature. Microarray data about differentially expressed downloaded from Gene Expression Omnibus (GEO) database with R programming language. Functional pathway enrichment analyses were performed using for Annotation, Visualization...

Diabetic nephropathy is a common complication of diabetes, accumulating evidence underscores the pivotal role tubulointerstitial fibrosis in progression diabetic nephropathy. However, underlying mechanisms remain incompletely understood. Although have been focus many studies, only limited information currently available concerning microRNA regulation fibrosis. In this study, we aimed to investigated roles miR-320a-3p and bone morphogenetic protein-6 (BMP6) After inducing with high glucose...

The competing endogenous RNA (ceRNA) network regulatory has been investigated in the occurrence and development of many diseases. This research aimed at identifying key RNAs ceRNA pterygium exploring underlying molecular mechanism.Differentially expressed long noncoding (lncRNAs), microRNAs (miRNAs), mRNAs were obtained from Gene Expression Omnibus (GEO) database analyzed with R programming language. LncRNA miRNA expressions extracted pooled by GEO compared those published literature....

Various automated classifiers have been implemented to categorise learning-related texts into cognitive domains. However, existing studies applied limited linguistic features, and most focused on written in English, with little attention given Chinese. This study has tried fill the gaps by applying a comprehensive set of features that rarely used collectively previous research, focus Chinese analytical texts. Experiments were conducted for classifier learning evaluation, where feature...

Abstract The recent breakthrough of single-cell RNA velocity methods brings attractive promises to reveal directed trajectory on cell differentiation, states transition and response perturbations. However, the existing are often found return erroneous results, partly due model violation or lack temporal regularization. Here, we present UniTVelo, a statistical framework that models dynamics spliced unspliced RNAs via flexible transcription activities. Uniquely, it also supports inference...

As an attack of social engineering, phishing email has caused tremendous financial loss to recipients. Therefore, there is urgent need for detection with high accuracy. In this paper, we proposed emails based on hybrid features. By analysing the email-header structure, email-URL information, email-script function and psychological features, extracted 18 Then chose Support Vector Machine (SVM) classifier evaluate our experiments. Experiments are performed a dataset consisting 500 legitimate...

A bstract Imputation of missing features in spatial transcriptomics is urgently demanded due to technology limitations, while most existing computational methods suffer from moderate accuracy and cannot estimate the reliability imputation. To fill research gaps, we introduce a model, TransImp, that imputes feature modality by mapping it single-cell reference. Uniquely, derived set attributes can accurately predict imputation uncertainty, hence enabling us select reliably imputed genes. Also,...

Digital platforms enable the observation of learning behaviors through fine-grained log traces, offering more detailed clues for analysis. In addition to previous descriptive and predictive analysis, this study aims simultaneously model learner activities, event time spans, interaction levels using proposed Hidden Behavior Traits Model (HBTM). We evaluated performance explored their capability clustering learners on a public dataset, tried interpret machine recognized latent behavior...

Abstract Information service providers often require evidence from multiple, heterogeneous information sources to better characterize users and offer personalized service. In many cases, statistic (for example, users' profiles) sequentially dynamic logs of interaction with systems) are two prominent that can be combined achieve optimized results. Previous attempts in combining these mainly exploited models designed for either static or sequential information, but not both. This study aims...

A bstract RNA velocity is a promising technique to reveal transient cellular dynamics among heterogeneous cell population and quantify their transitions from single-cell transcriptome experiments. However, the estimated high dimensional are often unstable or inaccurate, partly due technical noise less informative projection. Here, we present VeloAE, tailored representation learning method learn low-dimensional of on which can be robustly estimated. From various experimental datasets, show...

Imputation of missing features in spatial transcriptomics is urgently demanded due to technology limitations, while most existing computational methods suffer from moderate accuracy and cannot estimate the reliability imputation. To fill research gaps, we introduce a model, TransImp, that imputes feature modality by mapping it single-cell reference. Uniquely, derived set attributes can accurately predict imputation uncertainty, hence enabling us select reliably imputed genes. Also,...

In this paper, some new mappings called relaxed η-α quasimonotone and a properly operator are first introduced. The relationships between them obtained. After this, the variational-like inequality problem Minty discussed by use of proposed generalized monotone operators. Furthermore, we give gap function two inequalities kinds optimization problems. Finally, point out that problems equivalent under conditions. MSC:90C26, 90C30.