Global Parameters Research Articles

Association of serum uric acid with right cardiac chamber remodeling assessed by cardiovascular magnetic resonance feature tracking in patients with connective tissue disease.

Right cardiac chamber remodeling is widespread in patients with connective tissue disease (CTD). Serum uric acid (SUA) is considered a potential independent risk factor for cardiovascular disease, and elevated SUA levels are often observed in patients with CTD. The correlation between SUA levels and right cardiac chamber remodeling remains unclear. This study investigated the association of SUA with right cardiac chamber remodeling as assessed by cardiac magnetic resonance feature-tracking (CMR-FT) in CTD patients. In this cross-sectional study, a total of 104 CTD patients and 52 age- and sex-matched controls were consecutively recruited. All individuals underwent CMR imaging, and their SUA levels were recorded. The patients were divided into three subgroups based on the tertiles of SUA level in the present study. CMR-FT was used to evaluate the right atrial (RA) longitudinal strain and strain rate parameters as well as right ventricular (RV) global systolic peak strain and strain rate in longitudinal and circumferential directions for each subject. Univariable and multivariable linear regression analyses were used to explore the association of SUA with RV and RA strain parameters. Compared with the controls, the CTD patients showed significantly higher SUA levels but a lower RV global circumferential strain (GCS) and RA phasic strain parameters (all p < 0.05), except the RA booster strain rate. RV GCS remained impaired even in CTD patients with preserved RV ejection fraction. Among subgroups, the patients in the third tertile had significantly impaired RV longitudinal strain (GLS), RV GCS, and RA reservoir and conduit strain compared with those in the first tertile (all p < 0.05). The SUA levels were negatively correlated with RV GLS and RV GCS as well as with RA reservoir and conduit strain and strain rates (the absolute values of β were 0.250 to 0.293, all P < 0.05). In the multivariable linear regression analysis, the SUA level was still an independent determinant of RA conduit strain (β = -0.212, P = 0.035) and RV GCS (β = 0.207, P = 0.019). SUA may be a potential risk factor of right cardiac chamber remodeling and is independently associated with impaired RA conduit strain and RV GCS in CTD patients.

Continua and persistence of periodic orbits in ensembles of oscillators

Certain systems of coupled identical oscillators like the Kuramoto–Sakaguchi or the active rotator model possess the remarkable property of being Watanabe–Strogatz integrable. We prove that such systems, which couple via a global order parameter, feature a normally attracting invariant manifold that is foliated by periodic orbits. This allows us to study the asymptotic dynamics of general ensembles of identical oscillators by applying averaging theory. For the active rotator model, perturbations result in only finitely many persisting orbits, one of them giving rise to splay state dynamics. This sheds some light on the persistence and typical behavior of splay states previously observed.

FedAGAT: Real-time traffic flow prediction based on federated community and adaptive graph attention network

Predicting traffic flow is vital for optimizing intelligent transportation systems (ITS) and reducing congestion by forecasting traffic patterns accurately. However, current centralized TFP systems have limitations, e.g., slow training, high communication costs, and privacy concerns. To address these challenges, this study proposes FedAGAT, a system for short-term traffic flow prediction (TFP) based on federated community and adaptive spatial-temporal graph attention networks (AGAT). The FedAGAT system allows for local data processing and sharing only model updates with the server. This enables real-time, scalable, and secure TFP - essential capabilities for efficient ITS. AGAT is employed to capture intricate spatial-temporal dependencies in traffic flow, while federated learning facilitates decentralized learning, enhancing privacy. The FedAGAT prediction process involves four steps: dividing the local subnetwork using spectral community detection, locally training based on global parameters, uploading updated parameters, and creating a global model prediction based on the aggregated parameters. To evaluate the performance of FedAGAT, two real-world traffic datasets were utilized for benchmarking against seven statistical and deep learning models. Results demonstrate that FedAGAT provides relatively higher accuracy for short- and mid-term forecasting horizons. Moreover, FedAGAT predictions closely match real traffic flow values, and the overall performance is comparable to a global model, while requiring less time.

The Lower Limb Muscle Co-Activation Map during Human Locomotion: From Slow Walking to Running.

The central nervous system (CNS) controls movements and regulates joint stiffness with muscle co-activation, but until now, few studies have examined muscle pairs during running. This study aims to investigate differences in lower limb muscle coactivation during gait at different speeds, from walking to running. Nineteen healthy runners walked and ran at speeds ranging from 0.8 km/h to 9.3 km/h. Twelve lower limb muscles' co-activation was calculated using the time-varying multi-muscle co-activation function (TMCf) with global, flexor-extension, and rostro-caudal approaches. Spatiotemporal and kinematic parameters were also measured. We found that TMCf, spatiotemporal, and kinematic parameters were significantly affected by gait speed for all approaches. Significant differences were observed in the main parameters of each co-activation approach and in the spatiotemporal and kinematic parameters at the transition between walking and running. In particular, significant differences were observed in the global co-activation (CIglob, main effect F(1,17) = 641.04, p < 0.001; at the transition p < 0.001), the stride length (main effect F(1,17) = 253.03, p < 0.001; at the transition p < 0.001), the stride frequency (main effect F(1,17) = 714.22, p < 0.001; at the transition p < 0.001) and the Center of Mass displacement in the vertical (CoMy, main effect F(1,17) = 426.2, p < 0.001; at the transition p < 0.001) and medial-lateral (CoMz, main effect F(1,17) = 120.29 p < 0.001; at the transition p < 0.001) directions. Regarding the correlation analysis, the CoMy was positively correlated with a higher CIglob (r = 0.88, p < 0.001) and negatively correlated with Full Width at Half Maximum (FWHMglob, r = -0.83, p < 0.001), whereas the CoMz was positively correlated with the global Center of Activity (CoAglob, r = 0.97, p < 0.001). Positive and negative strong correlations were found between global co-activation parameters and center of mass displacements, as well as some spatiotemporal parameters, regardless of gait speed. Our findings suggest that walking and running have different co-activation patterns and kinematic characteristics, with the whole-limb stiffness exerted more synchronously and stably during running. The co-activation indexes and kinematic parameters could be the result of global co-activation, which is a sensory-control integration process used by the CNS to deal with more demanding and potentially unstable tasks like running.

Impaired long-range excitatory time scale predicts abnormal neural oscillations and cognitive deficits in Alzheimer’s disease

BackgroundAlzheimer’s disease (AD) is the most common form of dementia, progressively impairing cognitive abilities. While neuroimaging studies have revealed functional abnormalities in AD, how these relate to aberrant neuronal circuit mechanisms remains unclear. Using magnetoencephalography imaging we documented abnormal local neural synchrony patterns in patients with AD. To identify global abnormal biophysical mechanisms underlying the spatial and spectral electrophysiological patterns in AD, we estimated the parameters of a biophysical spectral graph model (SGM).MethodsSGM is an analytic neural mass model that describes how long-range fiber projections in the brain mediate the excitatory and inhibitory activity of local neuronal subpopulations. Unlike other coupled neuronal mass models, the SGM is linear, available in closed-form, and parameterized by a small set of biophysical interpretable global parameters. This facilitates their rapid and unambiguous inference which we performed here on a well-characterized clinical population of patients with AD (N = 88, age = 62.73 +/- 8.64 years) and a cohort of age-matched controls (N = 88, age = 65.07 +/- 9.92 years).ResultsPatients with AD showed significantly elevated long-range excitatory neuronal time scales, local excitatory neuronal time scales and local inhibitory neural synaptic strength. The long-range excitatory time scale had a larger effect size, compared to local excitatory time scale and inhibitory synaptic strength and contributed highest for the accurate classification of patients with AD from controls. Furthermore, increased long-range time scale was associated with greater deficits in global cognition.ConclusionsThese results demonstrate that long-range excitatory time scale of neuronal activity, despite being a global measure, is a key determinant in the local spectral signatures and cognition in the human brain, and how it might be a parsimonious factor underlying altered neuronal activity in AD. Our findings provide new insights into mechanistic links between abnormal local spectral signatures and global connectivity measures in AD.

Quinoxaline based Schiff bases: An effective calorimetric chemosensor for cyanide ion detection, application in logic gate and DFT studies

Cyanide ion is very toxic for both environment and human being, so it is necessary to design a chemosensor for cyanide ion detection. For this purpose, Two novel chemosensors based on 3-hydrazinylquinoxalin-2(1H)-one and aromatic aldehydes were synthesized named as (E)-3-(2-(5-fluoro-2-oxo-1H-indol-3(2H,3aH,7aH)-ylidene)hydrazinyl)quinoxalin-2(1H)-one (HG-1) and (Z)-3-(2-(4-morpholinobenzylidene)hydrazinyl)quinoxalin-2(1H)-one (HG-2) for selective detection of cyanide ion. The structural characterization was done by analytical techniques such as UV/Visible, FTIR, 1HNMR, 13CNMR, EI-MS and UPLC. Further confirmation of chemosensor sensing was done by DFT and TDDFT calculations with B3LYP/6-31G (d, p) method by performing QTAIM, FMO, UV/Vis and global reactivity parameters (GRPs) elucidation. The binding constant was calculated as 4.14 × 106 M−1 and detection limit was calculated as 21 × 10−6 M. In the presence of CN͞ ion, chemosensor HG-1 generated a noticeable color change from light yellow to orange. To build a combinatorial logic circuit gate, the reverse reaction of chemosensor with methanol is useful. Overall results shows that chemosensor HG-1 has greater selectivity for CN͞ ion than HG-2. Test strips were made for CN͞ ion detection.

Crystal structure, hydrogen bonding interactions, Hirshfeld surfaces, energy frameworks, and DFT calculation of Diethyl 3-(4-substitutedbenzoyl)indolizine-1,2-dicarboxylates

The diethyl 3-(4-substitutedbenzoyl)indolizine-1,2-dicarboxylates have been synthesized by reacting the electron-deficient diethyl but-2-ynedioate with 1-(2-(4-substitutedphenyl)-2-oxoethyl)pyridin-1-ium bromide, the intermediates obtained from the reaction of pyridine and 4-substituted phenacyl bromides. The synthesized compounds were investigated by FT-IR, NMR (1H and 13C), LC-MS, and elemental analysis spectroscopic methods along with PXRD. The molecular structures were determined using the single crystal X-ray diffraction technique which revealed that 5a and 5c crystallize in triclinic space group P1¯. The crystal structures of 5a and 5c preferred the C-H···O hydrogen-bonded dimeric ring motifs, resembling those observed in the earlier reported 5b. Furthermore, various computational analyzes such as Hirshfeld surface, Energy framework, and MEP analysis predicted the interaction site and inter-molecular interactions in these molecules. The FMOs analysis was carried out to obtain global reactivity parameters for the synthesized compounds (5a-c). The NCI and QTAIM studies revealed the nature as well as qualitative and quantitative description of intra and inter-molecular hydrogen bonding interactions present in these molecules and their crystal packing.

Physicochemical properties, pharmacokinetic studies, DFT approach, and antioxidant activity of nitro and chloro indolinone derivatives.

The process of developing of new drugs is greatly hampered by their inadequate physicochemical, pharmacokinetic, and intrinsic characteristics. In this regard, the selected chloro indolinone, (Z)-6-chloro-3-(2-chlorobenzylidene)indolin-2-one (C1), and nitro indolinone, (Z)-6-chloro-3-(2-nitrobenzylidene)indolin-2-one (C2), were subjected to SwissADME and density function theory (DFT) analysis. For compounds C1 and C2, the BOILED-Egg pharmacokinetic model predicted intestinal absorption, blood-brain barrier (BBB) penetration, and p-glycoprotein interaction. According to the physicochemical analysis, C1 has exceptional drug-like characteristics suitable for oral absorption. Despite only being substrates for some of the major CYP 450 isoforms, compounds C1 and C2 were anticipated to have strong plasma protein binding and efficient distribution and block these isoforms. The DFT study using the B3LYP/6-311G(d,p) approach with implicit water effects was performed to assess the structural features, electronic properties, and global reactivity parameters (GRP) of C1 and C2. The DFT results provided further support for other studies, implying that C2 is more water-soluble than C1 and that both compounds can form hydrogen bonds and (weak) dispersion interactions with other molecules, such as solvents and biomolecules. Furthermore, the GRP study suggested that C1 should be more stable and less reactive than C2. A concentration-dependent 2,2-diphenyl-1-picrylhydrazyl (DPPH) and 2,2'-azino-bis(3-ethylbenzothiazoline-6-sulfonic acid (ABTS) radical scavenging activity was shown by both C1 and C2. In brief, this finding has provided a strong foundation to explore further the therapeutic potential of these molecules against a variety of human disorders.

Machine-learning-based global optimization of microwave passives with variable-fidelity EM models and response features

Maximizing microwave passive component performance demands precise parameter tuning, particularly as modern circuits grow increasingly intricate. Yet, achieving this often requires a comprehensive approach due to their complex geometries and miniaturized structures. However, the computational burden of optimizing these components via full-wave electromagnetic (EM) simulations is substantial. EM analysis remains crucial for circuit reliability, but the expense of conducting rudimentary EM-driven global optimization by means of popular bio-inspired algorithms is impractical. Similarly, nonlinear system characteristics pose challenges for surrogate-assisted methods. This paper introduces an innovative technique leveraging variable-fidelity EM simulations and response feature technology within a kriging-based machine-learning framework for cost-effective global parameter tuning of microwave passives. The efficiency of this approach stems from performing most operations at the low-fidelity simulation level and regularizing the objective function landscape through the response feature method. The primary prediction tool is a co-kriging surrogate, while a particle swarm optimizer, guided by predicted objective function improvements, handles the search process. Rigorous validation demonstrates the proposed framework's competitive efficacy in design quality and computational cost, typically requiring only sixty high-fidelity EM analyses, juxtaposed with various state-of-the-art benchmark methods. These benchmarks encompass nature-inspired algorithms, gradient search, and machine learning techniques directly interacting with the circuit's frequency characteristics.

Unveiling diverse coordination-defined electronic structures of reconstructed anatase TiO2(001)-(1 × 4) surface

Transition metal oxides (TMOs) exhibit fascinating physicochemical properties, which originate from the diverse coordination structures between the transition metal and oxygen atoms. Accurate determination of such structure-property relationships of TMOs requires to correlate structural and electronic properties by capturing the global parameters with high resolution in energy, real, and momentum spaces, but it is still challenging. Herein, we report the determination of characteristic electronic structures from diverse coordination environments on the prototypical anatase-TiO2(001) with (1 × 4) reconstruction, using high-resolution angle-resolved photoemission spectroscopy and scanning tunneling microscopy/atomic force microscopy, in combination with density functional theory calculation. We unveil that the shifted positions of O 2s and 2p levels and the gap-state Ti 3p levels can sensitively characterize the O and Ti coordination environments in the (1 × 4) reconstructed surface, which show distinguishable features from those in bulk. Our findings provide a paradigm to interrogate the intricate reconstruction-relevant properties in many other TMO surfaces.

Research and application of the global positioning system (GPS) clustering algorithm based on multilevel functions

With the rapid development and widespread adoption of wearable technology, a new type of lifelog data is being collected and used in numerous studies. We refer to these data as informative lifelog which usually contain GPS, images, videos, text, etc. GPS trajectory data in lifelogs is typically categorized into continuous and discrete trajectories. Finding a point of interest (POI) from discrete trajectories is a challenging task to do and has caught little attention so far. This paper suggests an LP-DBSCAN model for mining personal trajectories from discrete GPS trajectory data. It makes use of the hierarchical structure information implied in GPS trajectory data and it is suggested a variable-levels, variable-parameters clustering method (LP-DBSCAN) based on the DBSCAN algorithm to increase the precision of finding POI information. Finally, the Liu lifelog dataset is subjected to a systematic evaluation. In terms of GPS data that are not evenly distributed geographically, the experimental results demonstrated that the proposed algorithm could more accurately identify POI information and address the adverse effects caused by the global parameters of the traditional DBSCAN algorithm.

Synthesis, Solvatochromic Studies, DFT Calculations, Characterization, and In Silico Molecular Docking Studies of Azo Dyes of 3‐Methyl‐1‐phenyl‐1H‐pyrazol‐5‐amine

AbstractIn this work, the four azo dyes (A1–A4) were synthesized using 5‐amino‐3‐methyl‐1‐phenyl pyrazole with four different coupling components by the conventional, simple diazo‐coupling method. These synthesized azo molecules were confirmed by various spectroscopic methods viz, FT‐IR spectra, HR‐MS spectra, 1H NMR spectra, and 13C NMR spectra. The electronic absorption and fluorescence spectra of synthesized azo compounds were recorded at room temperature, with different solvents. The DFT calculations were performed using 6‐311++G (d, p) basis set to evaluate the global reactive parameters of the synthesized azo dyes. The anti‐microbial activities were studied; the compound A1 exhibited a good antibacterial and anti‐fungal activities. The study of in silico molecular docking of the azo compounds revealed that all the compounds found to possess were extraordinary binding affinity as compared to the standards. The anti‐tuberculosis study was carried against mycobacterium tuberculosis and the results have shown that, the compound A2 showed good sensitivity to the studied azo compounds.

Epilepsy-related functional brain network alterations are already present at an early age in the GAERS rat model of genetic absence epilepsy.

Genetic Absence Epilepsy Rats from Strasbourg (GAERS) represent a model of genetic generalized epilepsy. The present longitudinal study in GAERS and age-matched non-epileptic controls (NEC) aimed to characterize the epileptic brain network using two functional measures, resting state-functional magnetic resonance imaging (rs-fMRI) and manganese-enhanced MRI (MEMRI) combined with morphometry, and to investigate potential brain network alterations, following long-term seizure activity. Repeated rs-fMRI measurements at 9.4 T between 3 and 8 months of age were combined with MEMRI at the final time point of the study. We used graph theory analysis to infer community structure and global and local network parameters from rs-fMRI data and compared them to brain region-wise manganese accumulation patterns and deformation-based morphometry (DBM). Functional connectivity (FC) was generally higher in GAERS when compared to NEC. Global network parameters and community structure were similar in NEC and GAERS, suggesting efficiently functioning networks in both strains. No progressive FC changes were observed in epileptic animals. Network-based statistics (NBS) revealed stronger FC within the cortical community, including regions of association and sensorimotor cortex, and with basal ganglia and limbic regions in GAERS, irrespective of age. Higher manganese accumulation in GAERS than in NEC was observed at 8 months of age, consistent with higher overall rs-FC, particularly in sensorimotor cortex and association cortex regions. Functional measures showed less similarity in subcortical regions. Whole brain volumes of 8 months-old GAERS were higher when compared to age-matched NEC, and DBM revealed increased volumes of several association and sensorimotor cortex regions and of the thalamus. rs-fMRI, MEMRI, and volumetric data collectively suggest the significance of cortical networks in GAERS, which correlates with an increased fronto-central connectivity in childhood absence epilepsy (CAE). Our findings also verify involvement of basal ganglia and limbic regions. Epilepsy-related network alterations are already present in juvenile animals. Consequently, this early condition seems to play a greater role in dynamic brain function than chronic absence seizures.

Capillary refill time assessment after fluid challenge in patients on venoarterial extracorporeal membrane oxygenation: A retrospective study

BackgroundMonitoring fluid therapy is challenging in patients assisted with Veno-arterial ECMO. The aim of our study was to evaluate the usefulness of capillary refill time to assess the response to fluid challenge in patients assisted with VA-ECMO. MethodsRetrospective monocentric study in a cardiac surgery ICU. We assess fluid responsiveness after a fluid challenge in patients on VA-ECMO. We recorded capillary refill time before and after fluid challenge and the evolution of global hemodynamic parameters. ResultsA total of 27 patients were included. The main indications for VA-ECMO were post-cardiotomy cardiogenic shock (44%). Thirteen patients (42%) were responders and 14 non-responders (58%). In the responder group, the index CRT decreased significantly (1.7 [1.5; 2.1] vs. 1.2 [1; 1.3] s; p = 0.01), whereas it remained stable in the non-responder group (1.4 [1.1; 2.5] vs. 1.6 [0.9; 1.9] s; p = 0.22). Diagnosis performance of CRT variation to assess response after fluid challenge shows an AUC of 0.68 (p = 0.10) with a sensitivity of 79% [95% CI, 52–92] and a specificity of 69% [95% CI, 42–87], with a threshold at 23%. ConclusionIn patients treated with VA-ECMO index capillary refill time is a reliable tool to assesses fluid responsiveness. SpecialtyCritical care, Cardiac surgery, ECMO.

Universal origin of glassy relaxation as recognized by configuration pattern matching.

Relaxation processes are crucial for understanding the structural rearrangements of liquids and amorphous materials. However, the overarching principle that governs these processes across vastly different materials remains an open question. Substantial analysis has been carried out based on the motions of individual particles. Here, as an alternative, we propose viewing the global configuration as a single entity. We introduce a global order parameter, namely the inherent structure minimal displacement (IS Dmin), to quantify the variability of configurations by a pattern-matching technique. Through atomic simulations of seven model glass-forming liquids, we unify the influences of temperature, pressure and perturbation time on the relaxation dissipation, via a scaling law between the mechanical damping factor and IS Dmin. Fundamentally, this scaling reflects the curvature of the local potential energy landscape. Our findings uncover a universal origin of glassy relaxation and offer an alternative approach to studying disordered systems.

Synthesis of a new hydrazone-based schiff base: Spectroscopy, single crystal, DNA binding and theoretical studies

A new thiosemicarbazide-based Schiff base (TSDHB) was synthesized from thiosemicarbazide and 2,3-dihydroxybenzaldehyde. The prepared thiosemicarbazone was characterized by elemental (CHN), FT-IR, 1H and 13C NMR techniques. Furthermore, the molecular structure was probed using the single-crystal X-ray diffraction (SC-XRD) technique, which confirmed the enol tautomeric form with two independent molecules in asymmetric unit. The dissimilarity between the molecular units was determined by molecular overlay plots. The various intermolecular interactions and solid-state assembly stabilization were explored by Hirshfeld surface analysis. Void analysis was executed to examine the mechanical stability of crystalline units. The bioactivity of thiosemicarbazone was probed with the help of its binding capacity with salmon sperm DNA (SS-DNA) by means of the absorption interaction method. Accompanied by biological activity, optoelectronic properties such as nonlinear optical properties of yielded crystal were also explored through the DFT approach at M06/6–311 G (d,p). For this, various kinds of investigations such as frontier molecular orbital (FMO), UV–Vis, global reactivity parameters (GRPs), transition density matrix (TDM), density of states (DOS), natural population analysis (NPA), and natural bond orbital analysis (NBO) were executed at M06 functional. A good agreement was examined between XRD and DFT findings of molecular geometric parameters. Notably, in comparison with urea, TSDHB demonstrated enhanced nonlinear optical properties (linear polarizability=4.766 × 10−23esu and third-order hyperpolarizability=5.939 × 10−35esu). These findings position TSDHB as a promising candidate for DNA binding as well as for photonic materials due to its unique molecular characteristics and enhanced nonlinear optical behavior.

Associations of dual-task walking costs with cognition in Parkinson’s disease

BackgroundGait and cognition are closely associated in Parkinson's disease (PD), with specific cognitive domains being associated with different motor symptoms. By identifying gait parameters affected by cognition, clinicians can develop targeted interventions that address cognitive impairment, improve gait, and reduce the risk of injury in PD patients. Research questionWhat gait parameters are affected by cognition in PD patients during dual-task walking, and how are these parameters related to cognitive function as measured by the Montreal Cognitive Assessment (MoCA)? Methods36 patients with available gait data and cognitive assessments were enrolled. Gait data of usual and dual-task walking sessions were recorded using lightweight wireless wearable sensors attached to trunk, lower, and upper extremities. Dual-task costs were calculated from usual and dual-task measures. Statistical analysis included non-parametric tests, Wilcoxon signed-rank test, Spearman’s correlation, and stepwise linear regression models. ResultsWalking speed, cadence, asymmetry in arm swing (ASA), between arms’ amplitude symmetry (BAS), average stride time, and jerk of the acceleration movement of the legs were found to be affected during the dual-task walking session (P<0.05). Spearman’s correlation showed significant correlations between MoCA scores and ASA (ρ=-0.469, P=0.036) and BAS (ρ=-0.448, P=0.036) costs. Stepwise linear regression models found that MoCA scores were significant predictors of BAS and ASA costs (P<0.05). SignificanceThis study found a significant association between global cognitive ability and several gait parameters costs under cognitive load caused by dual-task walking in PD patients. The study identified the gait parameters that were affected by cognitive load and found that MoCA scores were significant predictors of those gait parameters. Identifying gait parameters affected by cognition can lead to more targeted interventions for improving gait and reducing injury risk in PD patients.

Spiking autoencoder for nonlinear industrial process fault detection

In recent years, artificial neural networks have been found successful applications in process monitoring within metallurgy, chemical engineering and mechanical manufacturing owing to their superior ability to construct flexible models with varying degrees of nonlinearity and effectively handle large-scale data. However, the model's distinctiveness diminishes due to the high cost associated with neural network training and initializations, resulting in a more fluctuating fault detection performance. To alleviate this problem and inspired by the way biological neurons emit spikes to transmit information, the spiking neurons are employed in the construction of a spiking neural network, introducing a shift in parameter optimization from conventional global parameter tuning to two-stage layer-wise process. Based on this, a brain-like discrete model, spiking auto-encoder (SNNAE) is constructed. The SNNAE's training process is firstly compared with that of artificial neural networks with the same structure through modeling a numerical example, results show the superior efficiency and accuracy of SNNAE in modeling highly nonlinear data. To gauge its effectiveness in fault detection, SNNAE is then compared with the state-of-art methods through the same numerical example and a three-phase flow process, indicating its ability to significantly improve process monitoring performance in nonlinear processes while notably reducing its fluctuation.

Prolonged coagulation times in severe fever with thrombocytopenia syndrome virus infection, the indicators of heparin-like effect and increased haemorrhagic risk.

Prolonged coagulation times, such as activated partial thromboplastin time (APTT) and thrombin time (TT), are common in patients infected with severe fever with thrombocytopenia syndrome virus (SFTSV) and have been confirmed to be related to patient's poor outcome by previous studies. To find out the reason for prolonged coagulation time in patients with SFTSV infection, and whether it predicts haemorrhagic risk or not. Seventy-eight consecutive patients with confirmed SFTSV infection were enrolled in this prospective, single-centre, observational study. Several global and specific coagulation parameters of these patients on admission were detected, and the haemorrhagic events during hospitalization and their outcomes were recorded. Most of the enrolled patients had prolonged APTT (82.1%) and TT (80.8%), normal prothrombin time (83.3%) and intrinsic coagulation factors above haemostatic levels (97.4%). The heparin-like effect was confirmed by a protamine neutralization test and anti-Xa activity detection in most patients. Interestingly, the APTT and TT results were significantly positively correlated with the levels of endothelial markers and viral load, respectively. The APTT was independently associated with the haemorrhage of patients. The prolonged APTT and TT of SFTS patients may mainly be attributed to endogenous heparinoids and are associated with increased haemorrhagic risk.

Combined Global Seismic Damage for 3D RC Buildings Using Recorded Floor-Displacement Data

ABSTRACT A novel method is proposed for predicting the combined global damage index through newly developed formulae utilizing recorded floor-displacement data, local and global capacity-based parameters for 3D RC buildings. Multilinear regression analysis is performed to develop the new formulae for predicting the global damage index obtained from modified Park and Ang-type 3D local damage indices. Further, explicit expressions for the global damage coefficients of the new formulae are developed as a function of structural properties and soil type for wider applicability of the formulae. The computed global damage indices are found to represent the damage states of RC buildings satisfactorily.