Sketch-based Video Object Segmentation: Benchmark and Analysis

Reference-based video object segmentation is an emerging topic which aims to segment the corresponding target object in each video frame referred by a given reference, such as a language expression or a photo mask. However, language expressions can sometimes be vague in conveying an intended concept and ambiguous when similar objects in one frame are hard to distinguish by language. Meanwhile, photo masks are costly to annotate and less practical to provide in a real application. This paper introduces a new task of sketch-based video object segmentation, an associated benchmark, and a strong baseline. Our benchmark includes three datasets, Sketch-DAVIS16, Sketch-DAVIS17 and Sketch-YouTube-VOS, which exploit human-drawn sketches as an informative yet low-cost reference for video object segmentation. We take advantage of STCN, a popular baseline of semi-supervised VOS task, and evaluate what the most effective design for incorporating a sketch reference is. Experimental results show sketch is more effective yet annotation-efficient than other references, such as photo masks, language and scribble.Comment: BMVC 202

Comparative transcriptome analysis reveals the involvement of an MYB transcriptional activator, SmMYB108, in anther dehiscence in eggplant

Male sterility is a highly attractive agronomic trait as it effectively prevents self-fertilization and facilitates the production of high-quality hybrid seeds in plants. Timely release of mature pollen following anther dehiscence is essential for stamen development in flowering plants. Although several theories have been proposed regarding this, the specific mechanism of anther development in eggplant remains elusive. In this study, we selected an R2R3-MYB transcription factor gene, SmMYB108, that encodes a protein localized primarily in the nucleus by comparing the transcriptomics of different floral bud developmental stages of the eggplant fertile line, F142. Quantitative reverse transcription polymerase chain reaction revealed that SmMYB108 was preferentially expressed in flowers, and its expression increased significantly on the day of flowering. Overexpression of SmMYB108 in tobacco caused anther dehiscence. In addition, we found that SmMYB108 primarily functions as a transcriptional activator via C-terminal activation (amino acid 262–317). Yeast one-hybrid and dual-luciferase reporter assays revealed that genes (SmMYB21, SmARF6, and SmARF8) related to anther development targeted the SmMYB108 promoter. Overall, our results provide insights into the molecular mechanisms involved in the regulation of anther development by SmMYB108

Detection of Thermal Covert Channel Attacks Based on Classification of Components of the Thermal Signal Features

In response to growing security challenges facing many-core systems imposed by thermal covert channel (TCC) attacks, a number of threshold-based detection methods have been proposed. In this paper, we show that these threshold-based detection methods are inadequate to detect TCCs that harness advanced signaling and specific modulation techniques. Since the frequency representation of a TCC signal is found to have multiple side lobes, this important feature shall be explored to enhance the TCC detection capability. To this end, we present a pattern-classification-based TCC detection method using an artificial neural network that is trained with a large volume of spectrum traces of TCC signals. After proper training, this classifier is applied at runtime to infer TCCs, should they exist. The proposed detection method is able to achieve a detection accuracy of 99%, even in the presence of the stealthiest TCCs ever discovered. Because of its low runtime overhead (<0.187%) and low energy overhead (<0.072%), this proposed detection method can be indispensable in fighting against TCC attacks in many-core systems. With such a high accuracy in detecting TCCs, powerful countermeasures, like the ones based on dynamic voltage and frequency scaling (DVFS), can be rightfully applied to neutralize any malicious core participating in a TCC attack

Distinct resting-state effective connectivity of large-scale networks in first-episode and recurrent major depression disorder: evidence from the REST-meta-MDD consortium

IntroductionPrevious studies have shown disrupted effective connectivity in the large-scale brain networks of individuals with major depressive disorder (MDD). However, it is unclear whether these changes differ between first-episode drug-naive MDD (FEDN-MDD) and recurrent MDD (R-MDD).MethodsThis study utilized resting-state fMRI data from 17 sites in the Chinese REST-meta-MDD project, consisting of 839 patients with MDD and 788 normal controls (NCs). All data was preprocessed using a standardized protocol. Then, we performed a granger causality analysis to calculate the effectivity connectivity (EC) within and between brain networks for each participant, and compared the differences between the groups.ResultsOur findings revealed that R-MDD exhibited increased EC in the fronto-parietal network (FPN) and decreased EC in the cerebellum network, while FEDN-MDD demonstrated increased EC from the sensorimotor network (SMN) to the FPN compared with the NCs. Importantly, the two MDD subgroups displayed significant differences in EC within the FPN and between the SMN and visual network. Moreover, the EC from the cingulo-opercular network to the SMN showed a significant negative correlation with the Hamilton Rating Scale for Depression (HAMD) score in the FEDN-MDD group.ConclusionThese findings suggest that first-episode and recurrent MDD have distinct effects on the effective connectivity in large-scale brain networks, which could be potential neural mechanisms underlying their different clinical manifestations

Penetration of the blood-brain barrier and anti-tumor effect of a novel PLGA-lysoGM1/DOX micelles drug delivery system

Effective treatment of glioma and other central nervous system (CNS) diseases is hindered by the presence of the blood-brain barrier (BBB). A novel nano-delivery vehicle system comprised of PLGA-lysoGM1/DOX micelles was developed to across the BBB for CNS administration. We have shown that Doxorubicin (DOX) as a model drug encapsulated in PLGA-lysoGM1 micelles, can achieve up to 3.8% loading efficiency and 61.6% encapsulation efficiency by the orthogonal test design. Our in vitro experiments demonstrate that PLGA-lysoGM1/DOX micelles have a slow and sustainable drug release under physiological conditions and exhibit a high cellular uptake through the macropinocytosis and the autophagy/lysosomal pathways. In vivo experimental studies in zebrafish and mice confirmed that PLGA-lysoGM1/DOX micelles could across the BBB and specifically accumulated in the brain. Moreover, an excellent anti-glioma effect presented in intracranial glioma‐bearing rat. Therefore, PLGA-lysoGM1/DOX micelles not only effectively acrossed the BBB, but our results suggest it has a great potential for anti-glioma therapy and other central nervous system diseases

Characterization and Comparison of the Tissue-Related Modules in Human and Mouse

BACKGROUND: Due to the advances of high throughput technology and data-collection approaches, we are now in an unprecedented position to understand the evolution of organisms. Great efforts have characterized many individual genes responsible for the interspecies divergence, yet little is known about the genome-wide divergence at a higher level. Modules, serving as the building blocks and operational units of biological systems, provide more information than individual genes. Hence, the comparative analysis between species at the module level would shed more light on the mechanisms underlying the evolution of organisms than the traditional comparative genomics approaches. RESULTS: We systematically identified the tissue-related modules using the iterative signature algorithm (ISA), and we detected 52 and 65 modules in the human and mouse genomes, respectively. The gene expression patterns indicate that all of these predicted modules have a high possibility of serving as real biological modules. In addition, we defined a novel quantity, "total constraint intensity," a proxy of multiple constraints (of co-regulated genes and tissues where the co-regulation occurs) on the evolution of genes in module context. We demonstrate that the evolutionary rate of a gene is negatively correlated with its total constraint intensity. Furthermore, there are modules coding the same essential biological processes, while their gene contents have diverged extensively between human and mouse. CONCLUSIONS: Our results suggest that unlike the composition of module, which exhibits a great difference between human and mouse, the functional organization of the corresponding modules may evolve in a more conservative manner. Most importantly, our findings imply that similar biological processes can be carried out by different sets of genes from human and mouse, therefore, the functional data of individual genes from mouse may not apply to human in certain occasions

Incidence and influencing factors of acute gastrointestinal injury after cardiac surgery

Abstract Background To investigate the incidence and influencing factors of acute gastrointestinal injury (AGI) after cardiac surgery. Methods A total of 346 cases receiving treatment in the Intensive Care Unit (ICU) of the Department of Cardiovascular Surgery in our hospital from January 2021 to December 2021 were enrolled and their basic information was collected, including age, gender, height, weight, past medical history, Nutrition Risk Screening 2002, Body Mass Index (BMI), total operation duration, stay in ICU, preoperative blood routine examination results, complete biochemical examination, diamine oxidase (DAO) on Day 1, D-lactic acid index, a postoperative gastrointestinal condition, other postoperative complications and death during hospitalization. Moreover, logistic regression analysis was performed to identify the independent risk factors influencing the incidence of AGI after cardiac surgery. Results The incidence and mortality of AGI after cardiac surgery were 10.40% (36/346) and 25% (9/36), respectively. A dichotomous logistic regression multivariate analysis revealed that DAO on Day 1 (odd ratio = 1.062, p = 0.006) and stay in ICU (odd ratio = 1.192, p < 0.001) were independent risk factors of AGI after cardiac surgery, and total protein is a protective factor (odd ratio = 0.914, p = 0.012). Conclusions Factors influencing AGI after cardiac surgery have been determined in this study. Our data suggest that patients with AGI after cardiac surgery have a decreased preoperative total protein, and elevated DAO on Day 1. Total protein and DAO on Day 1 were found to be correlated with AGI