Exploration of Miniature Flexible Devices Empowered by Van Der Waals Material

This research mainly focuses on the fabrication of miniature flexible devices empowered by van der Waals materials. Through the extensive experiments contained in this thesis, by exploring the characteristics of van der Waals materials, optimizing the manufacturing process of lithography technology, and characterizing the photoelectric performance of micro devices, this thesis has promoted the development of micro flexible device manufacturing and expanded its applications in the fields of biological detection, medical treatment, and environmental monitoring. We introduced a miniature van der Waals semiconductor empowered vertical color sensor, which saves three times the volume space compared to the traditional planer color sensor and includes multiple optical aberration correction functions as well. Such a small red, green, and blue (RGB) color sensor can be applied in bionic eyes, breaking through the limitations of existing black and white recognition. On this basis, we further explored the stretchability of two-dimensional materials represented by MoS2. We proposed a chemical treatment method combined with gold nanoparticles and (3-mercaptopropyl)trimethoxysilane (MPTMS) to realize the relocation of flexible micro devices. This method improves the adhesion between the material layer and the flexible substrate (PDMS), which significantly increases the flexible device stretchability, and prolongs its service life. Through the above work, this thesis explores the van der Waals materials’ properties, and optimizes the manufacturing process of micro devices, further exerts the advantages of material flexibility, therefore provides more possibilities for the development of smart wearable devices, biomedical detection, and other fields

Online Video Super-Resolution with Convolutional Kernel Bypass Graft

Deep learning-based models have achieved remarkable performance in video super-resolution (VSR) in recent years, but most of these models are less applicable to online video applications. These methods solely consider the distortion quality and ignore crucial requirements for online applications, e.g., low latency and low model complexity. In this paper, we focus on online video transmission, in which VSR algorithms are required to generate high-resolution video sequences frame by frame in real time. To address such challenges, we propose an extremely low-latency VSR algorithm based on a novel kernel knowledge transfer method, named convolutional kernel bypass graft (CKBG). First, we design a lightweight network structure that does not require future frames as inputs and saves extra time costs for caching these frames. Then, our proposed CKBG method enhances this lightweight base model by bypassing the original network with ``kernel grafts'', which are extra convolutional kernels containing the prior knowledge of external pretrained image SR models. In the testing phase, we further accelerate the grafted multi-branch network by converting it into a simple single-path structure. Experiment results show that our proposed method can process online video sequences up to 110 FPS, with very low model complexity and competitive SR performance

Identification and validation of critical genes with prognostic value in gastric cancer

Background: Gastric cancer (GC) is a digestive system tumor with high morbidity and mortality rates. Molecular targeted therapies, including those targeting human epidermal factor receptor 2 (HER2), have proven to be effective in clinical treatment. However, better identification and description of tumor-promoting genes in GC is still necessary for antitumor therapy.Methods: Gene expression and clinical data of GC patients were downloaded from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) databases. Last absolute shrinkage and selection operator (LASSO) Cox regression were applied to build a prognostic model, the Prognosis Score. Functional enrichment and single-sample gene set enrichment analysis (ssGSEA) were used to explore potential mechanisms. Western blotting, RNA interference, cell migration, and wound healing assays were used to detect the expression and function of myosin light chain 9 (MYL9) in GC.Results: A four-gene prognostic model was constructed and GC patients from TCGA and meta-GEO cohorts were stratified into high-prognosis score groups or low-prognosis score groups. GC patients in the high-prognosis score group had significantly poorer overall survival (OS) than those in the low-prognosis score groups. The GC prognostic model was formulated as PrognosisScore = (0.06 × expression of BGN) - (0.008 × expression of ATP4A) + (0.12 × expression of MYL9) - (0.01 × expression of ALDH3A1). The prognosis score was identified as an independent predictor of OS. High expression of MYL9, the highest weighted gene in the prognosis score, was correlated with worse clinical outcomes. Functional analysis revealed that MYL9 is mainly associated with the biological function of epithelial-mesenchymal transition (EMT). Knockdown of MYL9 expression inhibits migration of GC cells in vitro.Conclusion: We found that PrognosisScore is potential reliable prognostic marker and verified that MYL9 promotes the migration and metastasis of GC cells

Online Streaming Video Super-Resolution with Convolutional Look-Up Table

Online video streaming has fundamental limitations on the transmission bandwidth and computational capacity and super-resolution is a promising potential solution. However, applying existing video super-resolution methods to online streaming is non-trivial. Existing video codecs and streaming protocols (\eg, WebRTC) dynamically change the video quality both spatially and temporally, which leads to diverse and dynamic degradations. Furthermore, online streaming has a strict requirement for latency that most existing methods are less applicable. As a result, this paper focuses on the rarely exploited problem setting of online streaming video super resolution. To facilitate the research on this problem, a new benchmark dataset named LDV-WebRTC is constructed based on a real-world online streaming system. Leveraging the new benchmark dataset, we proposed a novel method specifically for online video streaming, which contains a convolution and Look-Up Table (LUT) hybrid model to achieve better performance-latency trade-off. To tackle the changing degradations, we propose a mixture-of-expert-LUT module, where a set of LUT specialized in different degradations are built and adaptively combined to handle different degradations. Experiments show our method achieves 720P video SR around 100 FPS, while significantly outperforms existing LUT-based methods and offers competitive performance compared to efficient CNN-based methods

Prevotella genus and its related NOD-like receptor signaling pathway in young males with stage III periodontitis

BackgroundAs periodontitis progresses, the oral microbiota community changes dynamically. In this study, we evaluated the dominant bacteria and their roles in the potential pathway in young males with stage III periodontitis.Methods16S rRNA sequencing was performed to evaluate variations in the composition of oral bacteria between males with stage I and III periodontitis and identify the dominant bacteria of each group. Function prediction was obtained based on 16S rRNA sequencing data. The inhibitor of the predominant pathway for stage III periodontitis was used to investigate the role of the dominant bacteria in periodontitis in vivo and in vitro.ResultsChao1 index, Observed Species and Phylogenetic Diversity (PD) whole tree values were significantly higher in the stage III periodontitis group. β-diversity suggested that samples could be divided according to the stages of periodontitis. The dominant bacteria in stage III periodontitis were Prevotella, Prevotella_7, and Dialister, whereas that in stage I periodontitis was Cardiobacterium. KEGG analysis predicted that variations in the oral microbiome may be related to the NOD-like receptor signaling pathway. The inhibitor of this pathway, NOD-IN-1, decreased P. intermedia -induced Tnf-α mRNA expression and increased P. intermedia -induced Il-6 mRNA expression, consistent with the ELISA results. Immunohistochemistry confirmed the down-regulation of TNF-α and IL-6 expressions by NOD-IN-1 in P. intermedia–induced periodontitis.ConclusionThe composition of the oral bacteria in young males varied according to the stage of periodontitis. The species richness of oral microtia was greater in young males with stage III periodontitis than those with stage I periodontitis. Prevotella was the dominant bacteria in young males with stage III periodontitis, and inhibition of the NOD-like receptor signaling pathway can decrease the periodontal inflammation induced by P. intermedia

Understanding Anti-Semitic Hate Crimes and the Safety Needs of Jewish People in South Florida

Approximately 514,000 Jewish immigrants fled from different countries during World War II and migrated to South Florida. They came from Poland, Russia, Cuba, Brazil, France, Syria, Israel, and other countries, hoping to find a more tolerant and secure place to raise their families. However, anti-Semitic violence and incidents have occurred over the years. This dissertation relies on Social Identity Theory and Human Needs Theory to understand the causes of the conflicts among the different groups. Using a quantitative methodology, the author collected information on participants’ perceptions toward anti-Semitism and safety needs. This study included 300 participants of the second and third Jewish immigrant generations from Miami Dade County, Broward County, and Palm Beach County in Florida. The results indicated that over 64.7% of Jewish participants strongly agreed or agreed they were more worried about encountering anti-Semitism or discrimination in neighborhoods, workplaces, schools, or other places now than in the past ten years. There were 76.3% believed the lack of awareness of cultural diversity and inclusion was a cause of anti-Semitism and discrimination. The results also showed 55.3% of participants thought a lack of awareness of cultural diversity and inclusion was a factor for a person to experience an anti-Semitic attack or discrimination. This study provided explicit recommendations for different groups dealing with anti-Semitism and discrimination

Silk nanofibril as nanobinder for preparing COF nanosheet-based proton exchange membrane

Two-dimensional covalent organic framework nanosheets (CONs) with ultrathin thickness and porous crystalline nature show substantial potential as novel membrane materials. However, bringing CONs materials into flexible membrane form is a monumental challenge due to the limitation of weak interactions among CONs. Herein, one-dimensional silk nanofibrils (SNFs) from silkworm cocoon are designed as the nanobinder to link sulfonated CON (SCON) into robust SCON-based membrane through vacuum-filtration method. Ultrathin and large lateral-sized SCONs are synthesized via bottom-up interface-confined synthesis approach. Benefiting from high length-diameter ratio of SNF and rich functional groups in both SNF and SCON, two-dimensional (2D) SCONs are effectively connected together by physical entanglement and strong H-bond interactions. The resultant SCON/SNF membrane displays dense structure, high mechanical integrity and good stability. Importantly, the rigid porous nanochannels of SCON, high-concentration –SO3H groups insides the pores and H-bonds at SCON–SNF interfaces impart SCON/SNF membrane high-rate proton transfer pathways. Consequently, a superior proton conductivity of 365 mS cm−1 is achieved at 80 °C and 100% RH by SCON/SNF membrane. This work offers a promising approach for connecting 2D CON materials into flexible membrane as high-performance solid electrolyte for hydrogen fuel cell and may be applied in membrane-related other fields