Input-to-State Stability for Dynamical Neural Networks with Time-Varying Delays

A class of dynamical neural network models with time-varying delays is considered. By employing the Lyapunov-Krasovskii functional method and linear matrix inequalities (LMIs) technique, some new sufficient conditions ensuring the input-to-state stability (ISS) property of the nonlinear network systems are obtained. Finally, numerical examples are provided to illustrate the efficiency of the derived results

EFFECT OF CARDIOPULMONARY BYPASS ON ANNEXIN A1 EXPRESSION IN PERIPHERAL BLOOD MONONUCLEAR CELLS OF CHILDREN WITH CONGENITAL HEART DISEASE UTICAJ KARDIOPULMONARNOG BAJPASA NA EKSPRESIJU ANEKSINA A1 U MONONUKLEARNIM ]ELIJAMA PERIFERNE KRVI DECE SA URO\ENIM

Summary: This study aimed to investigate the effect of cardiopulmonary bypass (CPB) on Annexin A1 expression in the peripheral blood mononuclear cells (PBMCs) of children with congenital heart disease (CHD). A total of 30 children receiving CPB for interventricular septal defect were included. Peripheral blood was collected before and after CPB. PBMCs were collected by density gradient centrifugation. Protein extra ction was performed by lysis and subjected to 2D-QUANT for protein quantitation. Isoelectric focusing electrophoresis (IEF) was carried out followed by gel image analysis. Protein spots with a difference in expression of >1.5 fold were collected as candidate proteins which were subjected to mass spectrometry for the identification of diffe rentially expressed proteins. Western blot assay was emplo yed to confirm the expressions of target proteins. Peripheral blood collected at two time points was subjected to two-dimensional electrophoresis, and a total of 12 differentially expressed proteins were identified. Of them, 5 proteins had decreased expression before CPB (T0) but their expressions increased after CPB (T1); the remaining 7 proteins had in cre ased expres sions before CPB but their expressions re du ced after CPB. One of these differentially expres sed proteins was Annexin A1. Western blot assay confirmed that Annexin A1 expression began to increase at 0.5 h after CPB, and the increase of Annexin A1 was more obvious after CPB. Our findings primarily indicate the potential mechanism underlying the role of PBMC in inflammatory response following CPB, and provide a target for the prevention and control of post-CPB systemic inflammatory response syndrome (SIRS). Keywords: annexin A1, cardiopulmonary bypass, peripheral blood mononuclear cells, congenital heart disease Kratak sadr`aj: Svrha studije bila je da se istra`i uticaj kardiopulmonarnog bajpasa (KPB) na ekspresiju aneksina A1 u mononuklearnim }elijama periferne krvi (M]PK) dece sa uro|enim sr~anim oboljenjima (SO). Istra`ivanjem je obuhva}eno ukupno 30 dece kod koje je zbog interventrikularnog septalnog defekta izveden kardiopulmonarni bajpas. Uzorci periferne krvi uzeti su pre i posle zahvata. M]PK su sakupljene centrifugiranjem u gradijentu gustine. Proteini su ekstra hovani lizom a kvantitacija proteina obavljena je metodom 2D-QUANT. Izvr{ena je elektroforeza izoelektri~nim fokusiranjem (EIF) a potom analiza gel image. Proteinske ta~ke sa razlikom u ekspresiji >1,5 puta uzete su kao proteini kandidati, koji su podvrgnuti masenoj spektrometriji radi identifikovanja razli~ite ekspresije proteina. Za potvr|ivanje ekspresija ciljnih proteina upotrebljen je test Western blot. Uzorci periferne krvi uzeti su dva puta u odre|enom vremenskom razmaku i podvrgnuti dvodimenzionalnoj elektroforezi te je identifikovano ukupno 12 diferencijalno izra`enih proteina. Od toga je 5 proteina imalo smanjenu ekspresiju pre KPB (T0), ali se njihova ekspresija posle KPB pove}ala (T1); preostalih 7 proteina imalo je pove}anu ekspresiju pre KPB, ali se njihova ekspresija smanjila posle KPB. Jedan od ovih diferencijalno izra`enih proteina bio je aneksin A1. Testom Western blot potvr|eno je da je ekspresija aneksina A1 poela da raste 0,5 h posle KPB, dok je porast aneksina A1 posle KPB bio upadljiviji. Na{i nalazi prevashodno ukazuju na potencijalni mehanizam uloge M]PK u inflamatornom odgo voru posle KPB i pru`aju metu za prevenciju i kontrolu sindroma post-KPB sistemskog inflamatornog odgovora (SSIO). Klju~ne re~i: aneksin A1, kardiopulmonarni bajpas, mo nonuklearne }elije periferne krvi, uro|eno sr~ano oboljenj

DUAL-GLOW: Conditional Flow-Based Generative Model for Modality Transfer

Positron emission tomography (PET) imaging is an imaging modality for diagnosing a number of neurological diseases. In contrast to Magnetic Resonance Imaging (MRI), PET is costly and involves injecting a radioactive substance into the patient. Motivated by developments in modality transfer in vision, we study the generation of certain types of PET images from MRI data. We derive new flow-based generative models which we show perform well in this small sample size regime (much smaller than dataset sizes available in standard vision tasks). Our formulation, DUAL-GLOW, is based on two invertible networks and a relation network that maps the latent spaces to each other. We discuss how given the prior distribution, learning the conditional distribution of PET given the MRI image reduces to obtaining the conditional distribution between the two latent codes w.r.t. the two image types. We also extend our framework to leverage 'side' information (or attributes) when available. By controlling the PET generation through 'conditioning' on age, our model is also able to capture brain FDG-PET (hypometabolism) changes, as a function of age. We present experiments on the Alzheimers Disease Neuroimaging Initiative (ADNI) dataset with 826 subjects, and obtain good performance in PET image synthesis, qualitatively and quantitatively better than recent works

A fast phenotype approach of 3D point clouds of Pinus massoniana seedlings

The phenotyping of Pinus massoniana seedlings is essential for breeding, vegetation protection, resource investigation, and so on. Few reports regarding estimating phenotypic parameters accurately in the seeding stage of Pinus massoniana plants using 3D point clouds exist. In this study, seedlings with heights of approximately 15-30 cm were taken as the research object, and an improved approach was proposed to automatically calculate five key parameters. The key procedure of our proposed method includes point cloud preprocessing, stem and leaf segmentation, and morphological trait extraction steps. In the skeletonization step, the cloud points were sliced in vertical and horizontal directions, gray value clustering was performed, the centroid of the slice was regarded as the skeleton point, and the alternative skeleton point of the main stem was determined by the DAG single source shortest path algorithm. Then, the skeleton points of the canopy in the alternative skeleton point were removed, and the skeleton point of the main stem was obtained. Last, the main stem skeleton point after linear interpolation was restored, while stem and leaf segmentation was achieved. Because of the leaf morphological characteristics of Pinus massoniana, its leaves are large and dense. Even using a high-precision industrial digital readout, it is impossible to obtain a 3D model of Pinus massoniana leaves. In this study, an improved algorithm based on density and projection is proposed to estimate the relevant parameters of Pinus massoniana leaves. Finally, five important phenotypic parameters, namely plant height, stem diameter, main stem length, regional leaf length, and total leaf number, are obtained from the skeleton and the point cloud after separation and reconstruction. The experimental results showed that there was a high correlation between the actual value from manual measurement and the predicted value from the algorithm output. The accuracies of the main stem diameter, main stem length, and leaf length were 93.5%, 95.7%, and 83.8%, respectively, which meet the requirements of real applications

Shining a Light on the Challenging Behaviors of Adolescents with Comorbid Diagnoses: Use of Pictorial Concurrent Operant Preference Assessment

Currently, there are no published studies that have used the concurrent operant preference assessment procedure to identify functions of challenging behaviors displayed by individuals with comorbid diagnoses. Four participants (aged 11–16 years) with comorbid diagnoses who displayed multiple challenging behaviors were referred to this study. We modified the standard concurrent operant preference assessment and used the new modified version, the pictorial concurrent operant preference assessment, to identify the functions of the challenging behaviors. Utilizing the triangulation mixed-methods design, we compared the indirect functional behavioral assessment (FBA) and the direct FBA with the pictorial concurrent operant preference assessment. The results obtained successfully demonstrated the concordance among these assessments in identifying the behavioral function for each participant. The results further showed that (1) the preferences served the same functional effects on both the challenging behaviors and the adaptive behaviors and (2) the pictorial concurrent operant preference assessment can be used independently to identify potential behavioral function and to specify the reinforcing potency of each behavioral function. The significance of the study results, limitations of this study, and directions for future research and clinical practice are discussed

Quick Identification of ABC Trilayer Graphene at Nanoscale Resolution via a Near-field Optical Route

ABC-stacked trilayer graphene has exhibited a variety of correlated phenomena owing to its relatively flat bands and gate-tunable bandgap. However, convenient methods are still lacking for identifying ABC graphene with nanometer-scale resolution. Here we demonstrate that the scanning near-field optical microscope (SNOM) working in ambient conditions can provide quick recognition of ABC trilayer graphene with no ambiguity and excellent resolution (~20 nm). The recognition is based on the difference in their near-field infrared (IR) responses between the ABA and ABC trilayers. We show that in most frequencies, the response of the ABC trilayer is weaker than the ABA trilayer. However, near the graphene phonon frequency (~1585 cm-1), ABC's response increases dramatically when gated and exhibits a narrow and sharp Fano-shape resonant line, whereas the ABA trilayer is largely featherless. Consequently, the IR contrast between ABC and ABA becomes reversed and can even be striking (ABC/ABA~3) near the graphene phonon frequency. The observed near-field IR features can serve as a golden rule to quickly distinguish ABA and ABC trilayers with no ambiguity, which could largely advance the exploration of correlation physics in ABC-stacked trilayer graphene

Comprehensive analysis of LRR-RLKs and key gene identification in Pinus massoniana resistant to pine wood nematode

Pinus massoniana is a pioneer tree widely planted for afforestation on barren hills in southern China where the total planted area is 8.04 million ha. The invasive pine wood nematode (Bursaphelenchus xylophilus) poses a serious threat to the survival of P. massoniana. Plant resistance genes encoded by leucine-rich repeat-containing transmembrane-receptor proteins play important roles in plant defense. Leucine-rich repeat receptor-like kinases (LRR-RLKs), the largest subfamily of the RLK protein family, play an important role in sensing stress signals in plants. However, the LRR-RLKs of P. massoniana have not been characterized previously, and their role in resistance to B. xylophilus is unknown. In this study, 185 members of the LRR-RLK subfamily were identified in P. massoniana and were categorized into 14 subgroups. Transcriptomic and quantitative real-time RT-PCR analyses showed that PmRLKs32 was highly expressed in the stem tissue after inoculation with B. xylophilus. The gene exhibited high homology with AtFLS2 of Arabidopsis thaliana. PmRLKs32 was localized to the plasma membrane and was significantly upregulated in nematode-resistant and nematode-susceptible individuals. The transient expression of PmRLKs32 resulted in a burst of reactive oxygen species production in P. massoniana and Nicotiana benthamiana seedlings. These results lay a foundation for further exploration of the regulatory mechanism of LRR-RLKs in response to biotic stress in P. massoniana

Rapidly progressive interstitial lung disease risk prediction in anti-MDA5 positive dermatomyositis: the CROSS model

BackgroundThe prognosis of anti-melanoma differentiation-associated gene 5 positive dermatomyositis (anti-MDA5+DM) is poor and heterogeneous. Rapidly progressive interstitial lung disease (RP-ILD) is these patients’ leading cause of death. We sought to develop prediction models for RP-ILD risk in anti-MDA5+DM patients.MethodsPatients with anti-MDA5+DM were enrolled in two cohorts: 170 patients from the southern region of Jiangsu province (discovery cohort) and 85 patients from the northern region of Jiangsu province (validation cohort). Cox proportional hazards models were used to identify risk factors of RP-ILD. RP-ILD risk prediction models were developed and validated by testing every independent prognostic risk factor derived from the Cox model.ResultsThere are no significant differences in baseline clinical parameters and prognosis between discovery and validation cohorts. Among all 255 anti-MDA5+DM patients, with a median follow-up of 12 months, the incidence of RP-ILD was 36.86%. Using the discovery cohort, four variables were included in the final risk prediction model for RP-ILD: C-reactive protein (CRP) levels, anti-Ro52 antibody positivity, short disease duration, and male sex. A point scoring system was used to classify anti-MDA5+DM patients into moderate, high, and very high risk of RP-ILD. After one-year follow-up, the incidence of RP-ILD in the very high risk group was 71.3% and 85.71%, significantly higher than those in the high-risk group (35.19%, 41.69%) and moderate-risk group (9.54%, 6.67%) in both cohorts.ConclusionsThe CROSS model is an easy-to-use prediction classification system for RP-ILD risk in anti-MDA5+DM patients. It has great application prospect in disease management

Nonlinear magnetic-coupled flutter-based aeroelastic energy harvester: modeling, simulation and experimental verification

Aeroelastic energy harvesting can be used to power wireless sensors embedded into bridges, ducts, high-altitude buildings, etc. One challenging issue is that the wind speed in some application environments is low, which leads to an inefficiency of aeroelastic energy harvesters. This paper presents a novel nonlinear magnetic-coupled flutter-based aeroelastic energy harvester (FAEH) to enhance energy harvesting at low wind speeds. The presented harvester mainly consists of a piezoelectric beam, a two-dimensional airfoil, two tip magnets and two external magnets. The function of magnets is to reduce the cut-in wind speed of the FAEH and enhance energy harvesting performance at low wind speeds. A theoretical model is deduced based on Hamilton's principle, theory of aeroelasticity, Kirchhoff's laws and experimental measurements, etc. A good agreement is found between numerical simulation and experimental results, which verifies the accuracy of the theoretical model. Stability analysis is provided to determine the characteristics of the presented harvester. More importantly, it is numerically and experimentally verified that the presented harvester has a much lower cut-in wind speed (about 1.0 m s−1) and has a better energy harvesting performance at a low wind speed range from 1.0 m s−1 to 2.9 m s−1, when compared with traditional FAEHs