105 research outputs found
GCNs-Net: A Graph Convolutional Neural Network Approach for Decoding Time-resolved EEG Motor Imagery Signals
Towards developing effective and efficient brain-computer interface (BCI)
systems, precise decoding of brain activity measured by electroencephalogram
(EEG), is highly demanded. Traditional works classify EEG signals without
considering the topological relationship among electrodes. However,
neuroscience research has increasingly emphasized network patterns of brain
dynamics. Thus, the Euclidean structure of electrodes might not adequately
reflect the interaction between signals. To fill the gap, a novel deep learning
framework based on the graph convolutional neural networks (GCNs) was presented
to enhance the decoding performance of raw EEG signals during different types
of motor imagery (MI) tasks while cooperating with the functional topological
relationship of electrodes. Based on the absolute Pearson's matrix of overall
signals, the graph Laplacian of EEG electrodes was built up. The GCNs-Net
constructed by graph convolutional layers learns the generalized features. The
followed pooling layers reduce dimensionality, and the fully-connected softmax
layer derives the final prediction. The introduced approach has been shown to
converge for both personalized and group-wise predictions. It has achieved the
highest averaged accuracy, 93.056% and 88.57% (PhysioNet Dataset), 96.24% and
80.89% (High Gamma Dataset), at the subject and group level, respectively,
compared with existing studies, which suggests adaptability and robustness to
individual variability. Moreover, the performance was stably reproducible among
repetitive experiments for cross-validation. To conclude, the GCNs-Net filters
EEG signals based on the functional topological relationship, which manages to
decode relevant features for brain motor imagery
Application of metadata modeling to dispute review report management
Disagreements in construction projects often result in litigation that is both time‐consuming and expensive. A dispute review board (DRB) provides a valuable and proven alternative method of dispute resolution. Currently, the Florida Department of Transportation (FDOT) stores DRB reports in portable document format (PDF) with limited search capability. Improving information retrieval of DRB documents and providing a certain level of integration of DRB reports with relevant but heterogeneous data and documents is the key to enhancing the current FDOT DRB system. This paper presents a web‐based data management framework to improve information management processes of the FDOT DRB system by providing key features such as metadata generation, an integrated review process, a simple issue description, member information management, and versatile information search. The new system not only allows DRB members and FDOT construction engineers to store and retrieve DRB reports but also provides more functionality to process those re‐ports. New functionalities include a structured search based on the metadata of DRB reports, an unstructured search using advanced computer technology, and the integration of DRB reports with other related information for analysis. This type of functionality improves the efficiency and effectiveness of the DRB system.
Santrauka
Del nesutarimu vykdant statybos projektus dažnai kyla teisminiu ginču, kurie yra brangūs ir trunka ilgai. Vertingas ir praktikoje prigijes alternatyvus ginču sprendimo metodas yra ginču nagrinejimo taryba (GNT). Šiuo metu Floridos transporto departamentas (FTD) yra sukaupes GNT ataskaitas PDF formatu su ribota paieškos galimybe. GNT dokumentu informacijos paieška ir tinkamo lygio GNT ataskaitu integravimas su reikalingais, bet heterogeniniais duomenimis yra esmine prielaida tobulinti dabartine FTD GNT sistema. Straipsnyje pristatoma internetine duomenu valdymo sistema, skirta patobulinti FTD GNT valdymo procesa remiantis šiomis esminemis savybemis: metaduomenu generavimo, integruoto peržiūros proceso, paprasto ginčo aprašymo, dalyvio informacijos valdymo, visapusiškos informacijos paieškos. Naujoji sistema ne tik leidžia FTD BNT nariams saugoti bei rasti GNT ataskaitas, bet ir sudaro galimybes funkcionaliau jas apdoroti. Naujos sistemos funkcijos apima struktūrizuota paieška GNT ataskaitu metaduomenu pagrindu, restruktūri‐zuota paieška naudojant pažangias kompiuteriu technologijas ir GNT ataskaitu integravima su kita susijusia analizuojama informacija. Šios funkcines savybes pagerina GNT sistemos efektyvuma.
First Published Online: 10 Feb 2011
Reikšminiai žodžiai: ginču sprendimas, sutarčiu dokumentai, informacijos valdymas, duomenu baze
Progressive Learning with Visual Prompt Tuning for Variable-Rate Image Compression
In this paper, we propose a progressive learning paradigm for
transformer-based variable-rate image compression. Our approach covers a wide
range of compression rates with the assistance of the Layer-adaptive Prompt
Module (LPM). Inspired by visual prompt tuning, we use LPM to extract prompts
for input images and hidden features at the encoder side and decoder side,
respectively, which are fed as additional information into the Swin Transformer
layer of a pre-trained transformer-based image compression model to affect the
allocation of attention region and the bits, which in turn changes the target
compression ratio of the model. To ensure the network is more lightweight, we
involves the integration of prompt networks with less convolutional layers.
Exhaustive experiments show that compared to methods based on multiple models,
which are optimized separately for different target rates, the proposed method
arrives at the same performance with 80% savings in parameter storage and 90%
savings in datasets. Meanwhile, our model outperforms all current variable
bitrate image methods in terms of rate-distortion performance and approaches
the state-of-the-art fixed bitrate image compression methods trained from
scratch
Identification of ZNF26 as a Prognostic Biomarker in Colorectal Cancer by an Integrated Bioinformatic Analysis
The dysregulation of transcriptional factors (TFs) leads to malignant growth and the development of colorectal cancer (CRC). Herein, we sought to identify the transcription factors relevant to the prognosis of colorectal cancer patients. We found 526 differentially expressed TFs using the TCGA database of colorectal cancer patients (n = 544) for the differential analysis of TFs (n = 1,665) with 210 upregulated genes as well as 316 downregulated genes. Subsequently, GO analysis and KEGG pathway analysis were performed for these differential genes for investigating their pathways and function. At the same time, we established a genetic risk scoring model for predicting the overall survival (OS) by using the mRNA expression levels of these differentially regulated TFs, and defined the CRC into low and high-risk categories which showed significant survival differences. The genetic risk scoring model included four high-risk genes (HSF4, HEYL, SIX2, and ZNF26) and two low-risk genes (ETS2 and SALL1), and validated the OS in two GEO databases (p = 0.0023 for the GSE17536, p = 0.0193 for the GSE29623). To analyze the genetic and epigenetic changes of these six risk-related TFs, a unified bioinformatics analysis was conducted. Among them, ZNF26 is progressive in CRC and its high expression is linked with a poor diagnosis as well. Knockdown of ZNF26 inhibits the proliferative capacity of CRC cells. Moreover, the positive association between ZNF26 and cyclins (CDK2, CCNE2, CDK6, CHEK1) was also identified. Therefore, as a novel biomarker, ZNF26 may be a promising candidate in the diagnosis and prognostic evaluation of colorectal cancer
BING, a novel antimicrobial peptide isolated from Japanese medaka plasma, targets bacterial envelope stress response by suppressing cpxR expression
Antimicrobial peptides (AMPs) have emerged as a promising alternative to small molecule antibiotics. Although AMPs have previously been isolated in many organisms, efforts on the systematic identification of AMPs in fish have been lagging. Here, we collected peptides from the plasma of medaka (Oryzias latipes) fish. By using mass spectrometry, 6399 unique sequences were identified from the isolated peptides, among which 430 peptides were bioinformatically predicted to be potential AMPs. One of them, a thermostable 13-residue peptide named BING, shows a broad-spectrum toxicity against pathogenic bacteria including drug-resistant strains, at concentrations that presented relatively low toxicity to mammalian cell lines and medaka. Proteomic analysis indicated that BING treatment induced a deregulation of periplasmic peptidyl-prolyl isomerases in gram-negative bacteria. We observed that BING reduced the RNA level of cpxR, an upstream regulator of envelope stress responses. cpxR is known to play a crucial role in the development of antimicrobial resistance, including the regulation of genes involved in drug efflux. BING downregulated the expression of efflux pump components mexB, mexY and oprM in P. aeruginosa and significantly synergised the toxicity of antibiotics towards these bacteria. In addition, exposure to sublethal doses of BING delayed the development of antibiotic resistance. To our knowledge, BING is the first AMP shown to suppress cpxR expression in Gram-negative bacteria. This discovery highlights the cpxR pathway as a potential antimicrobial target
Aptamers as theranostic agents: modifications, serum stability and functionalisation
Aptamers, and the selection process known as Systematic Evolution of Ligands by Exponential Enrichment (SELEX) used to generate them, were first described more than twenty years ago. Since then, there have been numerous modifications to the selectionprocedures. This review discusses the use of modified bases as a means of enhancing serum stability and producing effective therapeutic tools, as well as functionalising these nucleic acids to be used as potential diagnostic agents
Hyperoxemia and excess oxygen use in early acute respiratory distress syndrome : Insights from the LUNG SAFE study
Publisher Copyright: © 2020 The Author(s). Copyright: Copyright 2020 Elsevier B.V., All rights reserved.Background: Concerns exist regarding the prevalence and impact of unnecessary oxygen use in patients with acute respiratory distress syndrome (ARDS). We examined this issue in patients with ARDS enrolled in the Large observational study to UNderstand the Global impact of Severe Acute respiratory FailurE (LUNG SAFE) study. Methods: In this secondary analysis of the LUNG SAFE study, we wished to determine the prevalence and the outcomes associated with hyperoxemia on day 1, sustained hyperoxemia, and excessive oxygen use in patients with early ARDS. Patients who fulfilled criteria of ARDS on day 1 and day 2 of acute hypoxemic respiratory failure were categorized based on the presence of hyperoxemia (PaO2 > 100 mmHg) on day 1, sustained (i.e., present on day 1 and day 2) hyperoxemia, or excessive oxygen use (FIO2 ≥ 0.60 during hyperoxemia). Results: Of 2005 patients that met the inclusion criteria, 131 (6.5%) were hypoxemic (PaO2 < 55 mmHg), 607 (30%) had hyperoxemia on day 1, and 250 (12%) had sustained hyperoxemia. Excess FIO2 use occurred in 400 (66%) out of 607 patients with hyperoxemia. Excess FIO2 use decreased from day 1 to day 2 of ARDS, with most hyperoxemic patients on day 2 receiving relatively low FIO2. Multivariate analyses found no independent relationship between day 1 hyperoxemia, sustained hyperoxemia, or excess FIO2 use and adverse clinical outcomes. Mortality was 42% in patients with excess FIO2 use, compared to 39% in a propensity-matched sample of normoxemic (PaO2 55-100 mmHg) patients (P = 0.47). Conclusions: Hyperoxemia and excess oxygen use are both prevalent in early ARDS but are most often non-sustained. No relationship was found between hyperoxemia or excessive oxygen use and patient outcome in this cohort. Trial registration: LUNG-SAFE is registered with ClinicalTrials.gov, NCT02010073publishersversionPeer reviewe
Finishing the euchromatic sequence of the human genome
The sequence of the human genome encodes the genetic instructions for human physiology, as well as rich information about human evolution. In 2001, the International Human Genome Sequencing Consortium reported a draft sequence of the euchromatic portion of the human genome. Since then, the international collaboration has worked to convert this draft into a genome sequence with high accuracy and nearly complete coverage. Here, we report the result of this finishing process. The current genome sequence (Build 35) contains 2.85 billion nucleotides interrupted by only 341 gaps. It covers ∼99% of the euchromatic genome and is accurate to an error rate of ∼1 event per 100,000 bases. Many of the remaining euchromatic gaps are associated with segmental duplications and will require focused work with new methods. The near-complete sequence, the first for a vertebrate, greatly improves the precision of biological analyses of the human genome including studies of gene number, birth and death. Notably, the human enome seems to encode only 20,000-25,000 protein-coding genes. The genome sequence reported here should serve as a firm foundation for biomedical research in the decades ahead
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