Level set medical image segmentation aided by cooperative quantum particle optimization with Lévy flights

Image segmentation plays an important part of image processing, and is also the premise and basis of image analysis and image understanding and recognition. Among the level set based methods, the original Local Binary Fitting (LBF) algorithm is a successful deterministic algorithm that suffers from sensitization to size of the local minimum, image contours, shapes, and initial positions. Among them, Level Set method promotes the two-dimensional problem to the three-dimensional one and then solves it using implicit method to express closed curve of plane. In this article, a novel Level Set model aided by PSO was proposed to solve automated medical image segmentation. The experimental result of segmentations on the benchmark shows that our proposed method is effective to both simple and complex medical images

Flapping vortex dynamics of two coupled side-by-side flexible plates submerged in the wake of a square cylinder

The flapping vortex dynamics of two flexible plates submerged side-by-side in the wake of a square cylinder are investigated through a two-way fluid–structure interaction (FSI) simulation. The gap between the two plates can stabilize wakes, lengthen vortex formation, elongate vortices, suppress vortex shedding, and decrease hydrodynamic forces. The numerical results indicate that the two flexible plates can exhibit four distinct modes of coupled motion: out-of-phase flapping, in-phase flapping, transition flapping, and decoupled flapping, depending on the gap spacing. Additionally, it is discovered that each of the four coupling modes has a unique pattern of vortex development. The findings of this study should proved valuable in the design of FSI-based piezoelectric energy harvesters utilizing cylinder–plate systems

Causal relationship between human blood metabolites and risk of ischemic stroke: a Mendelian randomization study

Background: Ischemic stroke (IS) is a major cause of death and disability worldwide. Previous studies have reported associations between metabolic disorders and IS. However, evidence regarding the causal relationship between blood metabolites and IS lacking.Methods: A two-sample Mendelian randomization analysis (MR) was used to assess the causal relationship between 1,400 serum metabolites and IS. The inverse variance-weighted (IVW) method was employed to estimate the causal effect between exposure and outcome. Additionally, MR-Egger regression, weighted median, simple mode, and weighted mode approaches were employed as supplementary comprehensive evaluations of the causal effects between blood metabolites and IS. Tests for pleiotropy and heterogeneity were conducted.Results: After rigorous selection, 23 known and 5 unknown metabolites were identified to be associated with IS. Among the 23 known metabolites, 13 showed significant causal effects with IS based on 2 MR methods, including 5-acetylamino-6-formylamino-3-methyluracil, 1-ribosyl-imidazoleacetate, Behenoylcarnitine (C22), N-acetyltyrosine, and N-acetylputrescine to (N (1) + N (8))-acetate,these five metabolites were positively associated with increased IS risk. Xanthurenate, Glycosyl-N-tricosanoyl-sphingadienine, Orotate, Bilirubin (E,E), Bilirubin degradation product, C17H18N2O, Bilirubin (Z,Z) to androsterone glucuronide, Bilirubin (Z,Z) to etiocholanolone glucuronide, Biliverdin, and Uridine to pseudouridine ratio were associated with decreased IS risk.Conclusion: Among 1,400 blood metabolites, this study identified 23 known metabolites that are significantly associated with IS risk, with 13 being more prominent. The integration of genomics and metabolomics provides important insights for the screening and prevention of IS

Recognition of cavitation characteristics in non-clogging pumps based on the improved Lévy flight bat algorithm

The performance and operational stability of non-clogging pumps can be affected by cavitation. To accurately identify the cavitation state of the non-clogging pump and provide technical references for monitoring its operation, a study was conducted on the optimization of Elman neural networks for cavitation monitoring and identification using the Improved Lévy Flight Bat Algorithm (ILBA) on the basis of the traditional Bat Algorithm (BA). The ILBA employs multiple bats to interact and search for targets and utilizes the local search strategy of Lévy flight, effectively avoiding local minima by taking advantage of the non-uniform random walk characteristics of large jumps. The ILBA algorithm demonstrates superior performance compared to other traditional algorithms through simulation testing and comparative calculations with eight benchmark test functions. On this basis, the optimization of the weights and thresholds of the Elman neural network was carried out by the improved bat algorithm. This leads to an enhancement in the accuracy of the neural network for identifying and classifying cavitation data, and the establishment of the ILBA-Elman cavitation diagnosis model was achieved. Collect pressure pulsation signals at the tongue of the non-clogging pump volute through cavitation tests. Through the cavitation feature extraction method based on Variational Mode Decomposition (VMD) and Multi-scale Dispersion Entropy (MDE), the interference signal can be effectively suppressed and the complexity of the time series can be measured from multiple angles, thereby creating a cavitation feature data set. The improved cavitation diagnosis model (ILBA-Elman) can realize the effective identification of the cavitation characteristics of non-clogging pumps through a variety of algorithm comparison experiments

Ambipolar Field Effect in Topological Insulator Nanoplates of (BixSb1-x)2Te3

Topological insulators represent a new state of quantum matter attractive to both fundamental physics and technological applications such as spintronics and quantum information processing. In a topological insulator, the bulk energy gap is traversed by spin-momentum locked surface states forming an odd number of surface bands that possesses unique electronic properties. However, transport measurements have often been dominated by residual bulk carriers from crystal defects or environmental doping which mask the topological surface contribution. Here we demonstrate (BixSb1-x)2Te3 as a tunable topological insulator system to manipulate bulk conductivity by varying the Bi/Sb composition ratio. (BixSb1-x)2Te3 ternary compounds are confirmed as topological insulators for the entire composition range by angle resolved photoemission spectroscopy (ARPES) measurements and ab initio calculations. Additionally, we observe a clear ambipolar gating effect similar to that observed in graphene using nanoplates of (BixSb1-x)2Te3 in field-effect-transistor (FET) devices. The manipulation of carrier type and concentration in topological insulator nanostructures demonstrated in this study paves the way for implementation of topological insulators in nanoelectronics and spintronics.Comment: 7 pages, 4 figure

VAMP-2 is a surrogate cerebrospinal fluid marker of Alzheimer-related cognitive impairment in adults with Down syndrome

Altres ajuts: Fundació la Marató de TV3/20141210There is an urgent need for objective markers of Alzheimer's disease (AD)-related cognitive impairment in people with Down syndrome (DS) to improve diagnosis, monitor disease progression, and assess response to disease-modifying therapies. Previously, GluA4 and neuronal pentraxin 2 (NPTX2) showed limited potential as cerebrospinal fluid (CSF) markers of cognitive impairment in adults with DS. Here, we compare the CSF profile of a panel of synaptic proteins (Calsyntenin-1, Neuroligin-2, Neurexin-2A, Neurexin-3A, Syntaxin-1B, Thy-1, VAMP-2) to that of NPTX2 and GluA4 in a large cohort of subjects with DS across the preclinical and clinical AD continuum and explore their correlation with cognitive impairment. We quantified the synaptic panel proteins by selected reaction monitoring in CSF from 20 non-trisomic cognitively normal controls (mean age 44) and 80 adults with DS grouped according to clinical AD diagnosis (asymptomatic, prodromal AD or AD dementia). We used regression analyses to determine CSF changes across the AD continuum and explored correlations with age, global cognitive performance (CAMCOG), episodic memory (modified cued-recall test; mCRT) and CSF biomarkers, CSF Aβ ratio, CSF Aβ, CSF p-tau, and CSF NFL. P values were adjusted for multiple testing. In adults with DS, VAMP-2 was the only synaptic protein to correlate with episodic memory (delayed recall adj.p =.04) and age (adj.p =.0008) and was the best correlate of CSF Aβ (adj.p =.0001), p-tau (adj.p < .0001), and NFL (adj.p < .0001). Compared to controls, mean VAMP-2 levels were lower in asymptomatic adults with DS only (adj.p =.02). CSF levels of Neurexin-3A, Thy-1, Neurexin-2A, Calysntenin-1, Neuroligin-2, GluA4, and Syntaxin-1B all strongly correlated with NPTX2 (p <.0001), which was the only synaptic protein to show reduced CSF levels in DS at all AD stages compared to controls (adj.p <.002). These data show proof-of-concept for CSF VAMP-2 as a potential marker of synapse degeneration that correlates with CSF AD and axonal degeneration markers and cognitive performance