Neuropeptide cholecystokinin:a key neuromodulator for hippocampal functions

Spatial memory is crucial for survival within external surroundings and wild environments.The hippocampus,a critical hub for spatial learning and memory formation,has received extensive investigations on how neuromodulators shape its functions(Teixeira et al.,2018;Zhang et al.,2024).However,the landscape of neuromodulations in the hippocampal system remains poorly understood because most studies focus on classical monoamine neuromodulators,such as acetylcholine,serotonin,dopamine,and noradrenaline.The neuropeptides,comprising the most abundant neuromodulators in the central nervous system,play a pivotal role in neural information processing in the hippocampal system.Cholecystokinin(CCK),one of the most abundant neuropeptides,has been implicated in regulating various physiological and neurobiological statuses(Chen et al.,2019).CCK-A receptor(CCK-AR)and CCK-B receptors(CCK-BR)are two key receptors mediating the biological functions of CCK,both of which belong to class-A sevenfold transmembrane G protein-coupled receptors(Nishimura et al.,2015).CCK-AR preferentially reacts to sulfated CCK,whereas CCK-BR binds both CCK and gastrin with similar affinities(Ding et al.,2022).The expression patterns of CCK-AR and CCK-BR are distinct,implying that CCK has various functions in target regions.For instance,CCK-AR is widely expressed in the GI and brain subregions and is hence implicated in the control of digestive function and satiety regulation.Conversely,CCK-BR is abundantly and widely distributed in the central nervous system,which majorly regulates anxiety,learning,and memory(Ding et al.,2022).However,the roles of endogenous CCK and CCK receptors in regulating hippocampal function at electrophysiological and behavioral levels have received less attention.

Analysis of the optical quality by determining the modulation transfer function for anterior corneal surface in myopes

AIM: To describe the characteristics of modulation transfer function (MTF) of anterior corneal surface, and obtain the the normal reference range of MTF at different spatial frequencies and optical zones of the anterior corneal surface in myopes. METHODS: Four hundred eyes from 200 patients were examined under SIRIUS corneal topography system. Phoenis analysis software was applied to simulate the MTF curves of anterior corneal surface at vertical and horizontal meridians at the 3, 4, 5, 6, 7mm optical zones of cornea. The MTF values at spatial frequencies of 5, 10, 15, 20, 25, 30, 35, 40, 45, 50, 55 and 60 cycles/degree (c/d) were selected. RESULTS: The MTF curve of anterior corneal surface decreased rapidly from low to intermediate frequency (0-15cpd) at various optical zones of cornea, the value decreased to 0 slowly at higher frequency (>15cpd). With the increase of the optical zones of cornea, MTF curve decreased gradually. 3) In the range of 3 mm- 6 mm optical zones of the cornea, the MTF values measured at horizontal meridian were greater than the corresponding values at horizontal meridian of each spatial frequency, the difference was statistically significant (P<0.05). At 7 mm optical zones of cornea, the MTF values measured at horizontal meridian were less than the corresponding values at vertical meridian at 10-60 spatial frequencies (cpd), and the difference was statistically significant in 25, 30, 35, 40, 45, 50 cpd(P<0.05). CONCLUSION: MTF can be used to describe the imaging quality of optical systems at anterior corneal surface objectively in detail.

Modulation transfer function characteristic of uniform-doping transmission-mode GaAs/GaAlAs photocathode

The resolution characteristic can be obtained by the modulation transfer function （MTF） of a GaAs/GaA1As photocathode. After establishing the theoretical model of GaAs（100）-oriented atomic configuration and the formula for the ionized impurity scattering of the non-equilibrium carriers, this paper calculates the trajectories of photoelectrons in a photocathode. Thus the distribution of photoelectron spots on the emit-face is obtained, which is namely the point spread function. The MTF is obtained by Fourier transfer of the line spread function obtained from the point spread function. The MTF obtained from these calculations is shown to depend heavily on the electron diffusion length, and enhanced considerably by decreasing the electron diffusion length and increasing the doping concentration. Furthermore, the resolution is enhanced considerably by increasing the active-layer thickness, especially at high spatial frequencies. The best spatial resolution is 860 lp/mm, for the GaAs photocathode of doping concentration 1 ×10^19 cm 3 electron diffusion length 3.6 μm and the active-layer thickness 2 μm, under the 633-nm light irradiated. This research will contribute to the future improvement of the cathode＇s resolution for preparing a high performance GaAs photocathode, and improve the resolution of a low light level image intensifier.

Comparison of the retinal modulation transfer function between amblyopes successfully corrected and normal subjects

AIM:To analyze the retinal modulation transfer function between amblyopes whose visual acuity was corrected to 5.0 and normal subjects at the same age. METHODS: RM-800 used to detect contrast sensitivity was adopted to measure MTF of 96 amblyopes (96 eyes) whose visual acuity was corrected to 5.0 and 80 normal controls (80 eyes) at the same age under six interference fringes (IVA=0.06, 0.1, 0.2, 0.4, 0.6, 0.8). RESULTS: The functional values of amblyopes were significantly lower than those of normal subjects in every fringe (P<0.01), especially in medium and high frequency. CONCLUSION: For amblyopes, MTF was still abnormal after stopping the treatments.

Fuzzy image restoration using modulation transfer function

The key difficulty of restoring a fuzzy image is to estimate its point spread function( PSF). In the paper,PSF is modelled based on modulation transfer function( MTF). The first step is calculating the image MTF. In the traditional slanted-edge method,a sub-block is always manually extracted from original image and its MTF will be viewed as the result of the whole image. However,handcraft extraction is inefficient and will lead to inaccurate results. Given this,an automatic MTF computation algorithm is proposed,which extracts and screens out all the effective sub-blocks and calculates their average MTF as the final result. Then,a two-dimensional MTF restoration model is constructed by multiplying the horizontal and vertical MTF,and it is combined with conventional image restoration methods to restore fuzzy image. Experimental results indicate the proposed method implementes a fast and accurate MTF computation and the MTF model improves the performance of conventional restoration methods significantly.

Intensity Correlation Function of a Single-Mode Laser Driven by Colored Cross-Correlation Noises in Modulation of a Bias Signal

By using the linear approximation method, the intensity correlation function is calculated for a single-mode laser modulated by a bias signal and driven by colored pump and quantum noises with colored cross-correlation. We found that, when the correlation time between the two noises is very short, the behavior of the intensity correlation function versus the time, in addition to decreasing monotonously, also exhibits several cases, such as one maximum, one minimum, and two extrema. When the correlation time between the two noises is very long, the behavior of the intensity correlation function exhibits oscillation and the envelope is similar to the case of short cross-correlation time.

A new modulation transfer function for ocean wave spectra retrieval from X-band marine radar imagery

When imaging ocean surface waves by X-band marine radar, the radar backscatter from the sea surface is modulated by the long surface gravity waves. The modulation transfer function （MTF） comprises tilt, hydrodynamic, and shadowing modulations. A conventional linear MTF was derived using HH-polarized radar observations under conditions of deep water. In this study, we propose a new quadratic polynomial MTF based on W-polarized radar measurements taken from heterogeneous nearshore wave fields. This new MTF is obtained using a radar-observed image spectrum and in situ buoy-measured wave frequency spectrum. We validate the MTF by comparing peak and mean wave periods retrieved from X-band marine radar image sequences with those measured by the buoy. It is shown that the retrieval accuracies of peak and mean wave periods of the new MTF are better than the conventional MTF. The results also show that the bias and root mean square errors of the peak and mean wave periods of the new MTF are 0.05 and 0.88 s, and 0.32 and 0.53 s, respectively, while those of the conventional MTF are 0.61 and 0.98 s, and 1.39 and 1.48 s, respectively. Moreover, it is also shown that the retrieval results are insensitive to the coefficients in the proposed MTF.

A General Algorithm for Biorthogonal Functions and Performance Analysis of Biorthogonal Scramble Modulation System

Applying the theorems of Mobius inverse and Dirichlet inverse, a general algorithm to obtain biorthogonal functions based on generalized Fourier series analysis is introduced. In the algorithm, the orthogonal function can be not only Fourier or Legendre series, but also can be any one of all orthogonal function systems. These kinds of biorthogonal function sets are used as scramble signals to construct biorthogonal scramble modulation (BOSM) wireless transmission systems. In a BOSM system, the transmitted signal has significant security performance. Several different BOSM and orthogonal systems are compared on aspects of BER performance and spectrum efficiency, simulation results show that the BOSM systems based on Chebyshev polynomial and Legendre polynomial are better than BOSM system based on Fourier series, also better than orthogonal MCM and OFDM systems.

Cosine-modulated window function-based staggered-grid finite-difference forward modeling

The numerical dispersion and computational cost are high for conventional Taylor series expansion staggered-grid finite-difference forward modeling owing to the high frequency of the wavelets and the large grid intervals. In this study, the cosine-modulated binomial window function （CMBWF）-based staggered-grid finite-difference method is proposed. Two new parameters, the modulated time and modulated range are used in the new window function and by adjusting these two parameters we obtain different characteristics of the main and side lobes of the amplitude response. Numerical dispersion analysis and elastic wavefield forward modeling suggests that the CMBWF method is more precise and less computationally costly than the conventional Taylor series expansion staggered-grid finite-difference method.

GOMA:functional enrichment analysis tool based on GO modules

Analyzing the function of gene sets is a critical step in interpreting the results of high-throughput experiments in systems biology. A variety of enrichment analysis tools have been developed in recent years, but most output a long list of significantly enriched terms that are often redundant, making it difficult to extract the most meaningful functions. In this paper, we present GOMA, a novel enrichment analysis method based on the new concept of enriched functional Gene Ontology (GO) modules. With this method, we systematically revealed functional GO modules, i.e., groups of functionally similar GO terms, via an optimization model and then ranked them by enrichment scores. Our new method simplifies enrichment analysis results by reducing redundancy, thereby preventing inconsistent enrichment results among functionally similar terms and providing more biologically meaningful results.

Modulation recognition of communication signals based on SCHKS-SSVM

A novel modulation recognition algorithm is proposed by introducing a Chen-Harker-Kanzow-Smale (CHKS) smooth function into the C-support vector machine deformation algorithm. A set of seven characteristic parameters is selected from a range of parameters of communication signals including instantaneous amplitude, phase, and frequency. And the Newton-Armijo algorithm is utilized to train the proposed algorithm, namely, smooth CHKS smooth support vector machine (SCHKS-SSVM). Compared with the existing algorithms, the proposed algorithm not only solves the non-differentiable problem of the second order objective function, but also reduces the recognition error. It significantly improves the training speed and also saves a large amount of storage space through large-scale sorting problems. The simulation results show that the recognition rate of the algorithm can batch training. Therefore, the proposed algorithm is suitable for solving the problem of high dimension and its recognition can exceed 95% when the signal-to-noise ratio is no less than 10 dB.

Efficient design method of non-uniform cosine modulated filter bank for digital hearing aids

To promote the performance of the traditional multichannel filter bank which leads to speech quality degradation,an efficient design method of the non-uniform cosine modulated filter bank（CMFB） based on the audiogram for digital hearing aids is proposed. First, a low-pass prototype filter is designed by the linear iterative algorithm. Secondly,the uniform CMFB is achieved on the basis of the principle formulas. Then, the adjacent channels of a uniform filter bank which have low or gradual slopes are merged according to the trend of audiogram of the hearing impaired person. Finally,the corresponding non-uniform CMFB is obtained. Simulation results show that the signal processed by the proposed filter bank is similar to the original signal in a time-domain waveform and spectrogram without significant distortion or difference. The speech quality results show that the personal evaluation of speech quality（PESQ） of non-uniform CMFB is 35% higher than that of the traditional design, and the hearing-aid speech quality index（HASQI） increases by about 40%.

Free vibration of non-uniform axially functionally graded beams using the asymptotic development method

The asymptotic development method is applied to analyze the free vibration of non-uniform axially functionally graded(AFG) beams, of which the governing equations are differential equations with variable coefficients. By decomposing the variable flexural stiffness and mass per unit length into reference invariant and variant parts, the perturbation theory is introduced to obtain an approximate analytical formula of the natural frequencies of the non-uniform AFG beams with different boundary conditions.Furthermore, assuming polynomial distributions of Young's modulus and the mass density, the numerical results of the AFG beams with various taper ratios are obtained and compared with the published literature results. The discussion results illustrate that the proposed method yields an effective estimate of the first three order natural frequencies for the AFG tapered beams. However, the errors increase with the increase in the mode orders especially for the cases with variable heights. In brief, the asymptotic development method is verified to be simple and efficient to analytically study the free vibration of non-uniform AFG beams, and it could be used to analyze any tapered beams with an arbitrary varying cross width.

A Method of Clustering Components into Modules Based on Products' Functional and Structural Analysis

Modularity is the key to improving the cost-variety trade-off in product development. To achieve the functional independency and structural independency of modules, a method of clustering components to identify modules based on functional and structural analysis was presented. Two stages were included in the method. In the first stage the products’ function was analyzed to determine the primary level of modules. Then the objective function for modules identifying was formulated to achieve functional independency of modules. Finally the genetic algorithm was used to solve the combinatorial optimization problem in modules identifying to form the primary modules of products. In the second stage the cohesion degree of modules and the coupling degree between modules were analyzed. Based on this structural analysis the modular scheme was refined according to the thinking of structural independency. A case study on the gear reducer was conducted to illustrate the validity of the presented method.

IMMUNE RBF NETWORK AND ITS APPLICATION IN THE MODULATION-STYLE RECOGNITION OF RADAR SIGNALS

Based on Immune Programming(IP), a novel Radial Basis Function (RBF) networkdesigning method is proposed. Through extracting the preliminary knowledge about the widthof the basis function as the vaccine to form the immune operator, the algorithm reduces thesearching space of canonical algorithm and improves the convergence speed. The application ofthe RBF network trained with the algorithm in the modulation-style recognition of radar signalsdemonstrates that the network has a fast convergence speed with good performances.

Confinement-induced modulation of elastic properties of nano-confined fluids in slit pore

Based on statistical mechanics for classical fluids, the general expressions for the elastic moduli of inhomogeneous fluid are derived and expressed as functionals of density functions. Within the framework of classical density functional theory, the bulk modulus of confined argon in slit pore is calculated under different conditions. The effects of vapor pressure, temperature, and pore width on modulus are calculated and investigated. Obvious confinement-induced effect has been observed in the confined argon. In addition, the solvation pressure dependence of the bulk modulus is also investigated,and the results suggest that the Tait–Murnaghan equation is still valid for the confined fluids.

Research of Hybrid Modulation Radar Signal

Based on the advantage of phase coded signal and stepped frequency signal,a new hybrid modulation signal is introduced in this paper. It combines phase code modulation during the pulse with stepped frequency modulation between the pulses, which is named as phase-coded stepped-frequency ( PCSF ) signal. By analyzing its waveform and ambiguity function,the comparison between Stepped-Frequency ( SF) signal and PCSF signal is given,which shows that the PCSF signal is better than SF signal. Finally,the signal processing method with two stage compressed processing is presented. The simulation results show that this new hybrid modulation radar signal can get a higher stepped frequency than ordinary SF signal,realize the same equivalent bandwidth with less pulse number,and solve the conflict among the stepped frequency,the number of pulse, and transmit average power. Under the premises of a certain range resolution,this new hybrid modulation radar signal not only raises the data rate of radar system,but also reduces Doppler sensitivity with a good prospect, and the effect of one-dimensional range profile is much better than that of traditional SF signal. Therefore,this new hybrid modulation radar signal can be widely used in application.

A Wave Modulation Model of Ripples over Long Surface Waves

A study is presented on the modulation of ripples induced by a long surface wave (LW) and a new theoretical modula-tion model is proposed. In this model, the wind surface stress modulation is related to the modulation of ripple spectrum. The model results show that in the case of LW propagating in the wind direction with the wave age parameter of LW increasing, the area with enhanced shear stress shifts from the region near the LW crest on the upwind slope to the LW trough. With a smaller wave age parameter of LW, the ripple modulation has the maximum on the upwind slope in the vicinity of LW crest, while with a larger parameter the enhancement of ripple spectrum does not occur in that region. At low winds the amplitude of ripple modulation transfer function (MTF) is larger in the gravity wave range, while at moderate or high winds it changes little in the range from short gravity waves to capillary waves.

Unbiased parameter estimation of continuous-time system based on modulating functions with input and output white noises

An efficient unbiased estimation method is proposed for the direct identification of linear continuous-time system with noisy input and output measurements.Using the Gaussian modulating filters,by numerical integration,an equivalent discrete identification model which is parameterized with continuous-time model parameters is developed,and the parameters can be estimated by the least-squares (LS) algorithm.Even with white noises in input and output measurement data,the LS estimate is biased,and the bias is determined by the variances of noises.According to the asymptotic analysis,the relationship between bias and noise variances is derived.One equation relating to the measurement noise variances is derived through the analysis of the LS errors.Increasing the degree of denominator of the system transfer function by one,an extended model is constructed.By comparing the true value and LS estimates of the parameters between original and extended model,another equation with input and output noise variances is formulated.So,the noise variances are resolved by the set of equations,the LS bias is eliminated and the unbiased estimates of system parameters are obtained.A simulation example by comparing the standard LS with bias eliminating LS algorithm indicates that the proposed algorithm is an efficient method with noisy input and output measurements.

Discovering the cellular-localized functional modules and modular interactions in response to liver cancer

In this paper, we firstly identify the functional modules enriched with differentially expressed genes （DEGs） and characterized by biological processes in specific cellular locations, based on gene ontology （GO） and microarray data. Then, we further define and filter disease relevant signature modules according to the ranking of the disease discriminating abilities of the pre-selected functional modules. At last, we analyze the potential way by which they cooperate towards human disease. Application of the proposed method to the analysis of a liver cancer dataset shows that, using the same false discovery rate （ FDR ） threshold, we can find more biologically meaningful and detailed processes by using the cellular localization information. Some biological evidences support the relevancy of our biological modules to the disease mechanism.