The Global Attractors For The Higher-order Kirchhoff-type Equation With Nonlinear Strongly Damped Term

The paper studies the longtime behavior of solutions to the initial boundary value problem for a class of Higher-order Kirchhoff models: For strong nonlinear damping and , we make assumptions (H1)-(H3). are nonlinear function specified later , we make assumptions (G1)-(G3). Under of the proper assume, the main results are existence and uniqueness of the solution are proved , and deal with the global attractors in natural energy space

Exponential attractor for the Higher-order Kirchhoff-type equation with nonlinear strongly damped term

We investigate the existence of exponential attractor for the Higher-order Kirchhoff-type equation with nonlinear strongly damped term: .For strong nonlinear damping σ(s) and φ(s) ,we assumptions .Under of the proper assume H1-H3, we first prove the squeezing property of the nonlinear semigroup associated with this equation, then the existence of exponential attractor is proved

Large-scale prediction of long non-coding RNA functions in a coding–non-coding gene co-expression network

Although accumulating evidence has provided insight into the various functions of long-non-coding RNAs (lncRNAs), the exact functions of the majority of such transcripts are still unknown. Here, we report the first computational annotation of lncRNA functions based on public microarray expression profiles. A coding–non-coding gene co-expression (CNC) network was constructed from re-annotated Affymetrix Mouse Genome Array data. Probable functions for altogether 340 lncRNAs were predicted based on topological or other network characteristics, such as module sharing, association with network hubs and combinations of co-expression and genomic adjacency. The functions annotated to the lncRNAs mainly involve organ or tissue development (e.g. neuron, eye and muscle development), cellular transport (e.g. neuronal transport and sodium ion, acid or lipid transport) or metabolic processes (e.g. involving macromolecules, phosphocreatine and tyrosine)

Modeling Documents with Event Model

Currently deep learning has made great breakthroughs in visual and speech processing, mainly because it draws lessons from the hierarchical mode that brain deals with images and speech. In the field of NLP, a topic model is one of the important ways for modeling documents. Topic models are built on a generative model that clearly does not match the way humans write. In this paper, we propose Event Model, which is unsupervised and based on the language processing mechanism of neurolinguistics, to model documents. In Event Model, documents are descriptions of concrete or abstract events seen, heard, or sensed by people and words are objects in the events. Event Model has two stages: word learning and dimensionality reduction. Word learning is to learn semantics of words based on deep learning. Dimensionality reduction is the process that representing a document as a low dimensional vector by a linear mode that is completely different from topic models. Event Model achieves state-of-the-art results on document retrieval tasks

The Global Attractors and Their Hausdorff and Fractal Dimensions Estimation for the Higher-Order Nonlinear Kirchhoff-Type Equation with Strong Linear Damping

Abstract In this paper, we study the longtime behavior of solution to the initial boundary value problem for a class of strongly damped Higher-order Kirchhoff type equations: At first, we prove the existence and uniqueness of the solution by priori estimation and the Galerkin method. Then, we obtain to the existence of the global attractor. At last, we consider that the estimation of the upper bounds of Hausdorff and fractal dimensions for the global attractors are obtained

Label-Free LSPR-Vertical Microcavity Biosensor for On-Site SARS-CoV-2 Detection

Cost-effective, rapid, and sensitive detection of SARS-CoV-2, in high-throughput, is crucial in controlling the COVID-19 epidemic. In this study, we proposed a vertical microcavity and localized surface plasmon resonance hybrid biosensor for SARS-CoV-2 detection in artificial saliva and assessed its efficacy. The proposed biosensor monitors the valley shifts in the reflectance spectrum, as induced by changes in the refractive index within the proximity of the sensor surface. A low-cost and fast method was developed to form nanoporous gold (NPG) with different surface morphologies on the vertical microcavity wafer, followed by immobilization with the SARS-CoV-2 antibody for capturing the virus. Modeling and simulation were conducted to optimize the microcavity structure and the NPG parameters. Simulation results revealed that NPG-deposited sensors performed better in resonance quality and in sensitivity compared to gold-deposited and pure microcavity sensors. The experiment confirmed the effect of NPG surface morphology on the biosensor sensitivity as demonstrated by simulation. Pre-clinical validation revealed that 40% porosity led to the highest sensitivity for SARS-CoV-2 pseudovirus at 319 copies/mL in artificial saliva. The proposed automatic biosensing system delivered the results of 100 samples within 30 min, demonstrating its potential for on-site coronavirus detection with sufficient sensitivity

Electroclinical characteristics of seizures arising from the precuneus based on stereoelectroencephalography (SEEG)

Abstract Background Seizures arising from the precuneus are rare, and few studies have aimed at characterizing the clinical presentation of such seizures within the anatomic context of the frontoparietal circuits. We aimed to characterize the electrophysiological properties and clinical features of seizures arising from the precuneus based on data from stereoelectroencephalography (SEEG). Methods The present retrospective study included 10 patients with medically intractable epilepsy, all of whom were diagnosed with precuneal epilepsy via stereoelectroencephalography (SEEG) at Yuquan Hospital and Xuan Wu Hospital between 2014 and 2016. Clinical semiology, scalp electroencephalography (EEG) findings, magnetic resonance images (MRI), and positron emission tomography (PET) images were analyzed during phase I preoperative evaluations. Following electrode implantation, the semiological sequence, ictal SEEG evolution, and anatomy of the relevant brain structures were analyzed for each seizure. Results Seven of ten patients reported auras, including body image disturbance (2/7), vestibular responses (2/7), somatosensory auras (1/7), visual auras (1/7), and non-specific auras (1/7). Primary motor manifestations included bilateral asymmetric tonic seizures (BATS) (7/10) and hypermotor seizures (HMS) (3/10). In one patient, epileptiform discharge on interictal EEG occurred ipsilateral to the side of the epileptogenic zone (EZ). Discharge was non-lateralized in the remaining nine patients. In six patients, interictal EEG signals were primarily localized in the temporal–parietal–occipital area. In two patients, ictal onset occurred ipsilateral to the EZ, which was mainly located in the temporal–parietal–occipital area. Two patterns of seizure spread were observed. The first pattern was characterized by BATS activity with ictal spread to the supplementary motor area (SMA), paracentral lobule (PCL), precentral gyrus (PrCG), or postcentral gyrus (PoCG). The second pattern was characterized by HMS activity with ictal spread to middle cingulate cortex (MCC) and posterior cingulate cortex (PCC). Conclusion Aura type (e.g., body image disturbance and vestibular response), BATS, and HMS are the main indicators of precuneal epilepsy. Scalp EEG is of little use when attempting to localize precuneal seizures. Our findings indicate that the clinical characteristics of precuneal epilepsy vary among patients, and that the final electro–clinical phenotype depends on the pattern of seizure spread

Quantifying the electrochemical maleimidation of large area graphene

The covalent modification of large-area graphene sheets by p-(N-Maleimido)phenyl (p-MP) via electrochemical grafting of p-(N-Maleimido)benzenediazonium tetrafluoroborate (p-MBDT) is successfully demonstrated for the first time. The deposition process is monitored in-situ using the mass change of a graphene/SiNX:H/Au-coated quartz crystal microbalance(QCM) chip. The resulting mass increase correlates with a maleimide thickness of approximately 2.3 molecular layers. The presence of an infrared absorption band at 1726 cm-1 shows that maleimide groups were deposited on the substrates. Raman backscattering spectra reveal the presence of D and D′ modes of the graphene layer, indicating that p-MP forms covalent bonds to graphene. Using the mass change and charge transfer during the potential cycling the faradaic efficiency of the functionalisation process was deduced, which amounts to eta = 22%