Consistent and Specific Multi-View Functional Brain Networks Fusion for Autism Spectrum Disorder Diagnosis

Functional brain networks (FBN) based on resting-state functional magnetic resonance imaging (rs-fMRI) have become an important tool for exploring underlying organization patterns in the brain, which can provide an objective basis for brain disorders such as autistic spectrum disorder (ASD). Due to its importance, researchers have proposed a number of FBN estimation methods. However, most existing methods only model a type of functional connection relationship between brain regions-of-interest (ROIs), such as partial correlation or full correlation, which is difficult to fully capture the subtle connections among ROIs since these connections are extremely complex. Motivated by the multi-view learning, in this study we propose a novel Consistent and Specific Multi-view FBNs Fusion (CSMF) approach. Concretely, we first construct multi-view FBNs (i.e., multiple types of FBNs modelling various relationships among ROIs), and then these FBNs are decomposed into a consistent representation matrix and their own specific matrices which capture their common and unique information, respectively. Lastly, to obtain a better brain representation, it is fusing the consistent and specific representation matrices in the latent representation spaces of FBNs, but not directly fusing the original FBNs. This potentially makes it more easily to find the comprehensively brain connections. The experimental results of ASD identification on the ABIDE datasets validate the effectiveness of our proposed method compared to several state-of-the-art methods. Our proposed CSMF method achieved 72.8% and 76.67% classification performance on the ABIDE dataset.

Estimating Brain Functional Networks Based on Spatiotemporal Higher-Order Correlations for Autism Identification

Brain functional network (BFN) has become an important tool for the analysis and diagnosis of brain diseases, and how to build a high-quality BFN based on resting-state functional magnetic resonance imaging (rs-fMRI) has become a growing concern in the neuroscience community. Although some methods have been proposed to construct a high-quality BFN, they only encode the spatial characteristics of the ROIs, ignoring the temporal characteristics. As a result, it becomes challenging to accurately capture the true state of the brain. To address this problem, we propose a novel method to construct a higher-order BFN, considering both temporal and spatial domain characteristics. In particular, we get the characteristics of the temporal domain by differentiating the rs-fMRI signal itself, and then we integrate the information of the spatial domain and temporal domain to build a high-order BFN. To evaluate the proposed method, we conduct our experiments on ABIDE database to identify subjects with Autism Spectrum Disorder (ASD) from normal controls. Experimental results show that our method can achieve higher performance than baseline methods.

SPECTRAL ANALYSIS OF SOME INDEPENDENCES OF MULTIPLE-VALUED LOGICAL FUNCTIONS ON THEIR VARIABLES

There are many kinds of special relationships between multiple-valued logical func-tions and their variables, and they are difficult to be judged from their expressions. In thispaper, some sufficient and necessary conditions of the independence and statistical independenceof multiple-valued logical functions on their variables are given. Some conditions of algebraicindependence of multiple-valued logical functions on some of their variables and the way to de-generate a function to the greatest extent are proposed, and some applications of these resultsare indicated. All the results are studied by using Chrestenson spectral techniques.

239Pu alpha spectrum analysis based on PIPS detector response function and variations with vacuum and distance

Effect factors of the absorption of the source,air,entrance window,and dead layer of a detector must be considered in the measurement of monoenergetic alpha particles,along with statistical noise and other factors that collectively cause the alpha spectrum to exhibit a well-known low-energy tail.Therefore,the estabUshment of an alpha spectrum detector response function from the perspective of a signaling system must consider the various factors mentioned above.The detector response function is the convolution of an alphaparticle pulse function,two exponential functions,and a Gaussian function,followed by calculation of the parameters of the detector response function using the weighted leastsquares fitting method as proposed in this paper.In our experiment,^(239)Pu alpha spectra were measured by a highresolution,passivated implanted planar silicon(PIPS)detector at 10 levels of vacuum and 10 source-detector distances.The spectrum-fitting results were excellent as evaluated by reduced Chi-square(x^2) and correlation coefficients.Finally,the variation of parameters with vacuum level and source-detector distance was studied.Results demonstrate that σ,τ_1,and τ_2 exhibit no obvious trend of variation with vacuum in the range 2000-20,000 mTorr,and at a confidence level of 95%,the values of τ_1 and τ_2 decline in a similar fashion with source-detector distance by the power exponential function,while the value of a declines linearly.

Phase spectrum estimation of the seismic wavelet based on a criterion function

Phase spectrum estimation of the seismic wavelet is an important issue in high-resolution seismic data processing and interpretation. On the basis of two patterns of constant-phase rotation and root transform for wavelet phase spectrum variation, we introduce six sparse criteria, including Lu’s improved kurtosis criterion, the parsimony criterion, exponential transform criterion, Sech criterion, Cauchy criterion, and the modified Cauchy criterion, to phase spectrum estimation of the seismic wavelet, obtaining an equivalent effect to the kurtosis criterion. Through numerical experiments, we find that when the reflectivity is not a sparse sequence, the estimated phase spectrum of the seismic wavelet based on the criterion function will deviate from the true value. In order to eliminate the influence of non-sparse reflectivity series in a single trace, we apply the method to the multi-trace seismogram, improving the accuracy of seismic wavelet phase spectrum estimation.

A proposed directional function and wind-wave directional spectrum

A directional function for frequencies equal to and larger than the peak frequency of a wind-wave frequency spectrum is constructed by fitting the angular spreading based on the analytically derived directional spectrum of Wen et al. (1993, Journal of Oceanography, 49(2), 131～147, 149～172). For frequencies smaller than the peak frequency, the directional function is obtained by comparing and analyzing existing formulas. The nondimensional wind-wave frequency spectrum of Wen et al. (1994, Progress in Natural Seience, 4(4). 407～427;4 (5), 586～596) has been used together with the directional function just mentioned to obtain the directional spectrum for easier application.

Geant4 simulation of multi-sphere spectrometer response function and the detection of 241Am–Be neutron spectrum

This paper is aimed at detecting the neutron spectrum of^(241)Am–Be, a widely used neutron source, with the SP9 ~3He proportional counter, which is a multi-sphere spectrometer system of eight thermal neutron detectors embedded in eight polyethylene(PE) spheres of varying diameters. The transport processes of a neutron in the multi-sphere spectrometer are simulated using the Geant4 code. Two sets of response functions of the PE spheres are obtained for calculating the^(241)Am–Be neutron spectrum.Response Function 1 utilizes the thermal neutron scattering model G4 Neutron HPThermal Scattering for neutron energies of ≤4 eV, and Response Function 2 has no thermal treatment. Neutron spectra of an^(241)Am–Be neutron source are measured and compared to those calculated by using the response functions. The results show that response function with thermal treatment is more accurate and closer to the real spectrum.

Alkyl group functionalization-induced phonon thermal conductivity attenuation in graphene nanoribbons

We calculated the room-temperature phonon thermal conductivity and phonon spectrum of alkyl group-functionalized zigzag graphene nanoribbons(ZGNRs) with molecular dynamics simulations. The increase in both chain length and concentration of alkyl groups caused remarkable reduction of phonon thermal conductivity in functionalized ZGNRs. Phonon spectra analysis showed that functionalization of ZGNR with alkyl functional groups induced phonon–structural defect scattering, thus leading to the reduction of phonon thermal conductivity of ZGNR. Our study showed that surface functionalization is an effective routine to tune the phonon thermal conductivity of GNRs, which is useful in graphene thermal-related applications.

The Effects of Xbox Kinect Active Video Gaming on Executive Function, Inhibition, in Children with and without Autism Spectrum Disorder: A Pilot Study

The purpose of this study was to compare the effects of sedentary video gaming (SVG), active video gaming (AVG), and brisk walking (WLK) on inhibition and reaction time using the Flanker task in boys with and without autism spectrum disorder (ASD). We had 9 participants with ASD and 10 age-matched participants without ASD perform 20-minute bouts of each activity, and then had them take the Flanker test. Dependent measures were reaction time (RT) and accuracy (ACC). A Chi-Square analysis revealed that the ASD and TD groups significantly differed in the percent of participants who improved in both of these measures. Next, we looked at each of the conditions exclusively within the ASD group and compared congruent and incongruent trials. In the AVG condition, participants improved a significantly higher percentage on ACC. In the SVG condition, participants improved a significantly higher percentage on incongruent in RT;for ACC, a higher percentage improved on the congruent trials. In WLK, participants improved a significantly higher percentage in RT in the congruent condition.

MODAL PARAMETERS EXTRACTION WITH CROSS CORRELATION FUNCTION AND CROSS POWER SPECTRUM UNDER UNKNOWN EXCITATION

In most of real operational conditions only response data are measurable while the actual excitations are unknown, so modal parameter must be extracted only from responses. This paper gives a theoretical formulation for the cross correlation functions and cross power spectra between the outputs under the assumption of white noise excitation. It widens the field of modal analysis under ambient excitation because many classical methods by impulse response functions or frequency response functions can be used easily for modal analysis under unknown excitation. The Polyreference Complex Exponential method and Eigensystem Realization Algorithm using cross correlation functions in time domain and Orthogonal Polynomial method using cross power spectra in frequency domain are applied to a steel frame to extract modal parameters under operational conditions. The modal properties of the steel frame from these three methods are compared with those from frequency response functions analysis. The results show that the modal analysis method using cross correlation functions or cross power spectra presented in this paper can extract modal parameters efficiently under unknown excitation.

Spectrum Response Estimation for Deep-Water Floating Platforms via Retardation Function Representation

The key concept of spectrum response estimation with commercial software,such as the SESAM software tool,typically includes two main steps:finding a suitable loading spectrum and computing the response amplitude operators(RAOs) subjected to a frequency-specified wave component.In this paper,we propose a nontraditional spectrum response estimation method that uses a numerical representation of the retardation functions.Based on estimated added mass and damping matrices of the structure,we decompose and replace the convolution terms with a series of poles and corresponding residues in the Laplace domain.Then,we estimate the power density corresponding to each frequency component using the improved periodogram method.The advantage of this approach is that the frequency-dependent motion equations in the time domain can be transformed into the Laplace domain without requiring Laplace-domain expressions for the added mass and damping.To validate the proposed method,we use a numerical semi-submerged pontoon from the SESAM.The numerical results show that the responses of the proposed method match well with those obtained from the traditional method.Furthermore,the estimated spectrum also matches well,which indicates its potential application to deep-water floating structures.

Chrestenson Spectrum and Auto-Correlation Function of Inverse Permutations of Quick Trickle Permutations

In this paper, a sufficient and necessary condition of quick trickle permutations is given from the point of inverse permutations. The bridge is built between quick trickle permutations and m-value logic functions. By the methods of the Chrestenson spectrum of m-value logic functions and the auto-correlation function of m-value logic functions to investigate the Chrestenson spectral characteristics and the auto-correlation function charac- teristics of inverse permutations of quick trickle permutations, a determinant arithmetic of quick trickle permutations is given. Using the results, it becomes easy to judge that a permutation is a quick trickle permutation or not by using computer. This gives a new pathway to study constructions and enumerations of quick trickle permutations.

Density Functional Theoretical Study of 5 ,5 '-Azotetrazolate Nonmetallic Salts

The structures, infrared spectra and cation stability of seven 5,5′-azotetrazolate nonmetallic salts are investigated by using B3LYP method with 6-311+G (d) basis set. The salts are guanidinium (GZT), aminoguanidinium (AGZT), diaminoguanidinium (DAGZT), triaminoguanidinium (TAGZT), azidoformamidinium (AFZT), ammonium (AZT), and hydrazinium (HZT), respectively. The calculated results indicate that the carbon and nitrogen atoms of the cations in seven nonmetallic salts are characterized to be sp2 hybrid atoms, and the ranges of characteristic absorption peaks in IR spectra of the seven nonmetallic salts are approximative consistent. All their cations are stable and their stabilities decrease with the increase in their nitrogen contents.

Simulation of γ spectrum-shifting based on the parameter adjustment of Gaussian function space

Based on the statistical characteristics of energy spectrum and the features of spectrum-shifting in spectrometry,the parameter adjustment method of Gaussian function space was applied in the simulation of spectrum-shifting.The transient characteristics of energy spectrum were described by the Gaussian function space,and then the Gaussian function space was transferred by parameter adjustment method.Furthermore,the spectrum-shifting in measurement of energy spectrum was simulated.The applied example shows that the parameters can be adjusted flexibly by this method to meet the various requirements in simulation of energy spectrum-shifting.This method was one parameterized simulation method with good performance for the practical application.

Ultraviolet laser ionization studies of 1-fluoronaphthalene clusters and density functional theory calculations

This paper studies supersonic jet-cooled 1-fluoronaphthalene （1FN） clusters by ultraviolet （UV） laser ionization at 281 nm in a time-of-flight mass spectrometer. The （1FN）＋ （n=1-3） series cluster ions are observed where the signal intensity decreases with increasing cluster size. The effects of sample inlet pressures and ionization laser fluxes to mass spectral distribution are measured. Using density functional theory calculations, it obtains a planar geometric structure of 1FN dimer which is combined through two hydrogen bonds. The mass spectra indicate that the intensity of 1FN trimer is much weaker than that of 1FN dimer and this feature is attributed to the fact that the dimer may form the first ＂shell＂ in geometric structure while the larger clusters are generated based on this fundamental unit.

The Relationship between Executive Functioning and Emotional Intelligence in Children with Autism Spectrum Disorder

Children with Autism Spectrum Disorder (ASD) demonstrate marked deficits in the ability to initiate, maintain and sustain meaningful social interaction. While the social-emotional deficits represent a core set of problems, persons with ASD also demonstrate significant problems in initiating, sustaining and maintaining appropriate goal directed behaviors. Emotional Intelligence (EI) is a construct that has been successfully applied to a range of skills that allow for the prediction of competent human social behavior. Executive Functions (EF) refer to constructs involving cognitive abilities necessary for initiating, sustaining and maintaining purposeful goal-oriented behavior. While both children and adults with ASD have previously shown to have atypical patterns of EF skills, little is known about EI in either children or adults with ASD. Moreover, there is no study examining the relationship between EI and EF that has been reported in individuals with ASD. The current study examined the relationship between EF and EI in children with ASD. Twenty children with ASD were compared to twenty neurotypical children on self-report and clinical assessments of EI and EF. Although the relationship between EF and EI was not statistically significant, results showed that children with ASD have deficits in interpersonal skills, intrapersonal skills and overall EI when compared to their neurotypical peers. These results suggest that EF and EI are relatively independent domains of development that show compromise in persons with ASD and each may be necessary to support typical socially directed behaviors.

Correlation between cerebral cortex changes and clinical features in patients with neuromyelitis optica spectrum disorder with normal-appearing brain tissue:a case-control study

Neuro myelitis optica spectrum disorder(NMOSD) is an inflammatory demyelinating disease of the central nervous system.However,whether and how cortical changes occur in NMOSD with normal-appearing brain tissue,or whether any cortical changes correlate with clinical chara cteristics,is not completely clear.The current study recruited 43 patients with NMOSD who had normal-appearing brain tissue and 45 healthy controls matched for age,sex,and educational background from December 2020 to February 2022.A surface-based morphological analysis of high-resolution T1-weighted structural magnetic resonance images was used to calculate the cortical thickness,sulcal depth,and gyrification index.Analysis showed that cortical thickness in the bilate ral rostral middle frontal gyrus and left superior frontal gyrus was lower in the patients with NMOSD than in the control participants.Subgroup analysis of the patients with NMOSD indicated that compared with those who did not have any optic neuritis episodes,those who did have such episodes exhibited noticeably thinner cortex in the bilateral cuneus,superior parietal co rtex,and pericalcarine co rtex.Correlation analysis indicated that co rtical thickness in the bilateral rostral middle frontal gyrus was positively correlated with scores on the Digit Symbol Substitution Test and negatively correlated with scores on the Trail Making Test and the Expanded Disability Status Scale.These results are evidence that cortical thinning of the bilateral regional frontal cortex occurs in patients with NMOSD who have normal-appearing brain tissue,and that the degree of thinning is correlated with clinical disability and cognitive function.These findings will help im prove our understanding of the imaging chara cteristics in NMOSD and their potential clinical significance.

Estimating Functional Brain Network with Low-Rank Structure via Matrix Factorization for MCI/ASD Identification

Functional brain networks (FBNs) provide a potential way for understanding the brain organizational patterns and diagnosing neurological diseases. Due to its importance, many FBN construction methods have been proposed currently, including the low-order Pearson’s correlation (PC) and sparse representation (SR), as well as the high-order functional connection (HoFC). However, most existing methods usually ignore the information of topological structures of FBN, such as low-rank structure which can reduce the noise and improve modularity to enhance the stability of networks. In this paper, we propose a novel method for improving the estimated FBNs utilizing matrix factorization (MF). More specifically, we firstly construct FBNs based on three traditional methods, including PC, SR, and HoFC. Then, we reduce the rank of these FBNs via MF model for estimating FBN with low-rank structure. Finally, to evaluate the effectiveness of the proposed method, experiments have been conducted to identify the subjects with mild cognitive impairment (MCI) and autism spectrum disorder (ASD) from norm controls (NCs) using the estimated FBNs. The results on Alzheimer’s Disease Neuroimaging Initiative (ADNI) dataset and Autism Brain Imaging Data Exchange (ABIDE) dataset demonstrate that the classification performances achieved by our proposed method are better than the selected baseline methods.

A single diffractive optical element implementing spectrum-splitting and beam-concentration functions simultaneously with high diffraction efficiency

In this paper,a novel method is proposed and employed to design a single diffractive optical element（DOE） for implementing spectrum-splitting and beam-concentration（SSBC） functions simultaneously.We develop an optimization algorithm,through which the SSBC DOE can be optimized within an arbitrary thickness range according to the limitations of modern photolithography technology.Theoretical simulation results reveal that the designed SSBC DOE has a high optical focusing efficiency.It is expected that the designed SSBC DOE should have practical applications in high-efficiency solar cell systems.