A Decoding Scheme for Incomplete Motor Imagery EEG With Deep Belief Network

High accuracy decoding of electroencephalogram (EEG) signal is still a major challenge that can hardly be solved in the design of an effective motor imagery-based brain-computer interface (BCI), especially when the signal contains various extreme artifacts and outliers arose from data loss. The conventional process to avoid such cases is to directly reject the entire severely contaminated EEG segments, which leads to a drawback that the BCI has no decoding results during that certain period. In this study, a novel decoding scheme based on the combination of Lomb-Scargle periodogram (LSP) and deep belief network (DBN) was proposed to recognize the incomplete motor imagery EEG. Particularly, instead of discarding the entire segment, two forms of data removal were adopted to eliminate the EEG portions with extreme artifacts and data loss. The LSP was utilized to steadily extract the power spectral density (PSD) features from the incomplete EEG constructed by the remaining portions. A DBN structure based on the restricted Boltzmann machine (RBM) was exploited and optimized to perform the classification task. Various comparative experiments were conducted and evaluated on simulated signal and real incomplete motor imagery EEG, including the comparison of three PSD extraction methods (fast Fourier transform, Welch and LSP) and two classifiers (DBN and support vector machine, SVM). The results demonstrate that the LSP can estimate relative robust PSD features and the proposed scheme can significantly improve the decoding performance for the incomplete motor imagery EEG. This scheme can provide an alternative decoding solution for the motor imagery EEG contaminated by extreme artifacts and data loss. It can be beneficial to promote the stability, smoothness and maintain consecutive outputs without interruption for a BCI system that is suitable for the online and long-term application

Pulmonary Cryptococcosis Diagnosed by Metagenomic Next-Generation Sequencing in a Young Patient With Normal Immune Function: A Case Report

BackgroundPulmonary cryptococcosis (PC) is a serious opportunistic fungal infection that usually occurs in immunocompromised patients. This disease is often difficult to diagnose in time due to its clinical manifestations and radiological feature similar to other pulmonary infections, as well as the low sensitivity of conventional diagnostic methods. Cryptococcosis in immune-competent patients is rare.Case PresentationHere we report a case of PC in an immune-competent patient. Tuberculosis was suspected according to radiological features due to the positive T-lymphocyte spot test and pure protein derivative skin test. To further detect the pathogen, bronchoalveolar lavage fluid (BALF) was collected for metagenomic next-generation sequencing (mNGS). Cryptococcus neoformans (one specific read) was identified by mNGS, indicating the PC of this patient. The following BALF culture and cryptococcal antigen lateral flow assay (CrAg-LFA) test also showed Cryptococcus infection, confirming the mNGS detection. Voriconazole (0.4 g daily) was given orally according to the subsequent susceptibility results. After seven months of treatment, the patient's condition improved.ConclusionMetagenomic next-generation sequencing (mNGS) is a better diagnostic tool to help clinicians distinguish pulmonary cryptococcosis from other atypical pulmonary infections

Comparing the difference of adverse events with HER2 inhibitors: a study of the FDA adverse event reporting system (FAERS)

Aim and background: This study attempted to identify similarities and differences in adverse events (AEs) between human epidermal growth factor receptor 2 (HER2) inhibitors, especially those related to hemorrhagic events and nervous system disorders.Methods: This study summarized the types, frequencies, and system organ classes (SOCs) of AEs of HER2 inhibitors. The US Food and Drug Administration Adverse Event Reporting System (FAERS) data from January 2004 through March 2022 was collected and analyzed. Disproportionality analyses were conducted to detect AEs signals for every HER2 inhibitor. The chi-square test, Wilcoxon test, and descriptive analysis were used to compare the differences of AEs for specific SOCs or drugs.Results: A total of 47,899 AE reports were obtained for eight HER2 inhibitors. Trastuzumab-related AEs were reported in the highest number and combination of regimens. In monotherapy, trastuzumab had the highest reported rate of cardiac disorders-related AEs (24.0%). However, small-molecule drugs exceeded other drugs in the reported rates of AEs related to gastrointestinal disorders, metabolism and nutrition disorders. The highest reported rates of respiratory disorders (47.3%) and hematologic disorders (22.4%) were associated with treatment with trastuzumab deruxtecan (T-DXd). Patients treated with trastuzumab emtansine (TDM-1) had the highest reported rate (7.28%) of hemorrhagic events, especially intracranial haemorrhage events. In addition, patients treated with TDM-1 with concomitant thrombocytopenia were likely to experience hemorrhagic events compared to other HER2 inhibitors (p < 0.001). The median time to onset of intracranial haemorrhage associated with trastuzumab (0.5 months) and TDM-1 (0.75 months) was short. However, there was no significant difference in median time to onset intracranial haemorrhage between patients in different age groups or with different outcomes. Disproportionality analysis results reveal that cerebral haemorrhage is a positive signal associated with T-DXd and TDM-1. In addition, tucatinib was the drug with the highest rate of reported nervous system disorders (31.38%). Memory impairment (83 cases) is a positive signal for tucatinib.Conclusion: The types and reporting rates of AEs associated with different HER2 inhibitors vary across multiple systems. In addition, hemorrhagic events concomitant with TDM-1 treatment and nervous system disorders concomitant with tucatinib treatment may be worthy of attention

Rotation Symmetry Spontaneous Breaking of Edge States in Zigzag Carbon Nanotubes

Analytical solutions of the edge states were obtained for the (N, 0) type carbon nanotubes with distorted ending bonds. It was found that the edge states are mixed via the distortion. The total energies for N=5 and N>=7 are lower in the asymmetric configurations of ending bonds than those having axial rotation symmetry. Thereby the symmetry is breaking spontaneously. The results imply that the symmetry of electronic states at the apex depends on the occupation; the electron density pattern at the apex could change dramatically and could be controlled by applying an external field.Comment: 19 pages, 3 figure

25th annual computational neuroscience meeting: CNS-2016

The same neuron may play different functional roles in the neural circuits to which it belongs. For example, neurons in the Tritonia pedal ganglia may participate in variable phases of the swim motor rhythms [1]. While such neuronal functional variability is likely to play a major role the delivery of the functionality of neural systems, it is difficult to study it in most nervous systems. We work on the pyloric rhythm network of the crustacean stomatogastric ganglion (STG) [2]. Typically network models of the STG treat neurons of the same functional type as a single model neuron (e.g. PD neurons), assuming the same conductance parameters for these neurons and implying their synchronous firing [3, 4]. However, simultaneous recording of PD neurons shows differences between the timings of spikes of these neurons. This may indicate functional variability of these neurons. Here we modelled separately the two PD neurons of the STG in a multi-neuron model of the pyloric network. Our neuron models comply with known correlations between conductance parameters of ionic currents. Our results reproduce the experimental finding of increasing spike time distance between spikes originating from the two model PD neurons during their synchronised burst phase. The PD neuron with the larger calcium conductance generates its spikes before the other PD neuron. Larger potassium conductance values in the follower neuron imply longer delays between spikes, see Fig. 17.Neuromodulators change the conductance parameters of neurons and maintain the ratios of these parameters [5]. Our results show that such changes may shift the individual contribution of two PD neurons to the PD-phase of the pyloric rhythm altering their functionality within this rhythm. Our work paves the way towards an accessible experimental and computational framework for the analysis of the mechanisms and impact of functional variability of neurons within the neural circuits to which they belong

An Approach towards user interface derivation from business process model

This paper proposes an approach for user interface (UI) generation and updating. A role-enriched business process model is developed with detailed description for tasks and associated data. The model is specified in an extended BPMN. A set of control flow patterns and data flow patterns are identified based on the proposed model for UI derivation. A comprehensive set of constraints and recommendations are specified for supporting the UI generation and updating. This early work will lay a foundation towards an effective tool for supporting UIs development and maintenance.10 page(s

User interface derivation based on role-enriched business process model

This work proposes an approach for User Interface (UI) derivation based on a role-enriched Business Process (BP) model with the capability to describe the details of the control flow and data operations in a BP. For each user role, data relationships are extracted according to the identified control flow patterns and data operation patterns. A set of mandatory and recommended UI derivation rules are specified as the cornerstones to derive the UI logic from a BP. The algorithm for UI derivation is provided. This UI derivation approach provides the basis for UI development and maintenance.15 page(s

Frequency Domain Response of Jacket Platforms under Random Wave Loads

This article presents a procedure that simplifies an offshore jacket platform as a non-uniform cantilever beam subjected to an axial force. A Ritz method combined with a pseudo-excitation method is then used to analyze the responses of the jacket platform under random wave loads with the associated power spectral densities, variances and higher spectral moments. The theoretical basis and pertinent governing equations are derived. The proposed procedure not only eases the process of determining the pseudo wave loads, but also requires only the rudimentary structural details that are typically available at the preliminary design stage. Additionally, the merit of the proposed procedure is that the process does not require one to compute the normal modes, which saves time and is particularly convenient for the dynamic-response analysis of a complex structure (such as an offshore platform). An illustrative example based on a three-deck jacket platform is presented to demonstrate the procedure used to obtain the power spectral densities, variances and second spectral moments of jacket-top displacement and the bending moment of the jacket at the mud line. The results obtained are compared with those obtained using a Finite Element Mothed (FEM) model. Based on the findings of the study and good agreement shown in the comparison of results, it is concluded that the proposed method is effective, simple and convenient, and can be a useful tool for the preliminary design analysis of offshore platforms