Miracle-dz/UniFAR-FTUs huggingface dataset:
Concordance Among Indices of Intrinsic Brain Function: Inter-Individual Variation and Temporal Dynamics Perspectives

Various resting-state fMRI (R-fMRI) measures have been developed to characterize intrinsic brain activity. While each of these measures has gained a growing presence in the literature, questions remain regarding the common and unique aspects these indices capture. The present work provided a comprehensive examination of inter-individual variation and intra-individual temporal variation for commonly used measures, including fractional amplitude of low frequency fluctuations, regional homogeneity, voxel-mirrored homotopic connectivity, network centrality and global signal correlation. Regardless of whether examining intra-individual or inter-individual variation, we found that these definitionally distinct R-fMRI indices tend to exhibit a relatively high degree of covariation. When taken as a measure of intrinsic brain function, inter-individual differences in concordance for R-fMRI indices appeared to be stable, and negatively related to age (i.e., functional concordance among indices decreases with age). To understand the functional significance of concordance, we noted that higher concordance was generally associated with higher strengths of R-fMRI indices, regardless of whether looking through the lens of inter-individual (i.e., high vs. low concordance participants) or intra-individual (i.e., high vs. low concordance states identified via temporal dynamic analyses) differences. Finally, temporal dynamics analyses also revealed that high concordance states are characterized by increased within- and between-network functional connectivity, suggesting more general variations in network integration and segregation. The current study draws attention to questions regarding how to select an R-fMRI index for usage in a given study, as well as how to compare findings across studies that examine inter-individual or group differences using different indices. Additionally, our work suggests global neural signals exist in the brain, and their spontaneous variations over time result in fluctuations in the connectedness of brain regions.
A Novel Method for Edge Detection of Natural Color Images

In this paper a novel natural color images edge detection algorithm is proposed using a relational operations. A relational shift operation can be found in order to detect the best quality edge in natural color images. First of all real complement of each channel is taken to get a matrices. After that each matrices converted into a binary matrices and each matrices are shifted left, right, up and down. After that <= operation is performed between original image and shifted matrices and result are stored in different variables. After that ~= operation is performed between the results. The results of ~=operation are summed together using addition operation. At last all the results for different channels are sunned together to get final image in which only edge are present. Experimental results on both the synthetic image and natural color images show that the proposed method is accurately gives better results. The method that is presented in this paper is simple and runs in polynomial time.
A Brain MR Image De-bias Model based on Entropy

This paper uses Legendre polynomial functions to reconstruct the bias, which make the entropy of the recovered image be smallest. In order to calculate the parameters of the basis functions, a new particle swarm technique is proposed that incorporates initial location information and use mutate operation make the particles away from local maxima. The experiments show that the new method can get accurate result robustly.
Acetate Production from Syngas Produced from Lignocellulosic Biomass Materials along with Gaseous Fermentation of the Syngas: A Review

Biotransformation of lignocellulose-derived synthetic gas (syngas) into acetic acid is a promising way of creating biochemicals from lignocellulosic waste materials. Acetic acid has a growing market with applications within food, plastics and for upgrading into a wide range of biofuels and bio-products. In this paper, we will review the microbial conversion of syngas to acetic acid. This will include the presentation of acetate-producing bacterial strains and their optimal fermentation conditions, such as pH, temperature, media composition, and syngas composition, to enhance acetate production. The influence of syngas impurities generated from lignocellulose gasification will further be covered along with the means to alleviate impurity problems through gas purification. The problem with mass transfer limitation of gaseous fermentation will further be discussed as well as ways to improve gas uptake during the fermentation.
Series Resonant Converter With Multiple Resonant Points Using Sequential PWM for Electrical Vehicle On-Board Charger

In electric vehicle (EV) charging applications, maintaining high efficiency over a wide output voltage range is considered the most challenging mission. Pulse width modulation (PWM) controlled resonant converter can be a nice candidate, because its output voltage boosting capability is independent to the resonant tank components. However, it reveals its limitation showing efficiency drop between two resonant points. This paper proposes a resonant converter with “sequential PWM” achieving multiple resonant points while doubling the output voltage. The proposed converter significantly reduces turnoff loss and maximum resonant current by having multiple resonant points while doubling the output voltage. Accordingly, proposed converter maintains competitive high efficiency over a wide output voltage range.
Leak detection in water distribution network using machine learning techniques

ABSTRACT Leakage in the water distribution system (WDS) and its control has been challenging for water resources fraternity for management of precious water demand. This study examines an inverse engineering technique to ﬁnd the leaks in water supply pipelines. The main objective of the study has been to identify the patterns of deviations in the pressure/flow in the network, due to a single leak in the network, by solving classification and regression problems using artificial neural networks (ANNs) and support vector machines (SVMs). The leak detections were solved using two scenarios, wherein, (a) only pressure measurements and (b) only flow measurements, are undertaken in the system. The multi-layered perceptron (MLP) model and multi-label multi-class SVM classification and regression models were developed and trained using the pressure and flow signals, separately. It was found that the ANN model performed better than the SVM model in pressure- and flow-based leak detection in both classification and regression problems. The model performance could also be improved by optimizing the number of inputs to the model during the training phase. The present study would be useful for water supply management while applying the techniques for minimizing the losses in the water supply network due to leakages.
Inviscid Transonic Flow Computation Using TheDual Reciprocity Method

The Dual Reciprocity method (DRM) is applied to solve the problem of 2-d, inviscid, transonic flows with embedded shocks about airfoils. The flow is described by the non-linear full potential equation. The linear part is solved by an indirect boundary element method with singularity distributions on the airfoil surface. The non-linear part of the governing equation leads to a domain integral which is transformed to a boundary integral by using the DRM. The source term is calculated by an iterative procedure starting from the linear solution. The non-linear influences are coupled with the linear solution via modified boundary conditions. In case of transonic flows, the governing equation becomes hyperbolic in the supersonic regions. To cope with this problem and suppress possible expansion shocks an artificial dissipation model (ADM) is used. A conservative as well as a non-conservative formulation of the source term is investigated. The results obtained for subsonic and transonic flow cases show good agreement with other numerical solutions. Shock location and strength are predicted with satisfactory accuracy while any expansion shocks are suppressed by the ADM. The expected difference between the conservative and non-conservative formulation can be observed likewise.
An Analytical Antenna Modeling of Electromagnetic Wave Propagation in Inhomogeneous Media Using FDTD: A Comprehensive Study

This paper discusses the challenges in characterizing electromagnetic (EM) waves propagating through inhomogeneous media, such as reinforced cement concrete and hot mix asphalt. Understanding the EM properties of materials, including their dielectric constant, conductivity, and magnetic permeability, is crucial to analyzing the behavior of these waves. The focus of this study is to develop a numerical model for EM antennas using the finite difference time domain (FDTD) method, and to gain a deeper understanding of various EM wave phenomena. Additionally, we verify the accuracy of our model by comparing its results with experimental data. We analyze several antenna models with different materials, including the absorber, high-density polyethylene and perfect electrical conductors, to obtain an analytical signal response that is verified against the experimental response. Furthermore, we model the inhomogeneous mixture of randomly distributed aggregates and voids within a medium. We verify the practicality and reliability of our inhomogeneous models using experimental radar responses on an inhomogeneous medium.
Expanding the Role of DSOs in Establishing Flexible Local Markets: A Brokerage Perspective

As more distributed energy resources are deployed into distribution networks, supply and demand matching between prosumers becomes a new challenge for distribution system operators (DSOs) due to the intermittency of DERs. Recent studies begin to expand the responsibilities of DSOs towards local generation and consumption optimization, such as establishing a flexible local market. However, the difficulty of boosting local power exchange while reducing operation costs still remains unsolved. In this article, we propose a new way of power trading management for DSOs from a brokerage perspective. Specifically, DSOs endeavor to coordinate prosumers in the local market by setting a fair transactive price as incentive signals. Meanwhile, to compensate for the operation cost (e.g., power line loss), DSOs need to charge commission. We investigate how to compute the optimal transactive price in a privacy-preserving way by using a distributed algorithm and set a fair service fee, which attracts more power transactions in the local market as well as reduces the operation cost of DSOs. Moreover, to accelerate the distributed algorithm, we derive an optimal transactive price updating rule for DSOs, and the closed-form expression of the optimal strategy for each prosumer with respect to the transactive price. Numerical results on Southern California Edison 56-bus feeder and IEEE 123-node test feeder show that the proposed power trading management for DSOs from a brokerage perspective leads to a TRIPLE win. With the proposed mechanism, the prosumers' payoffs largely increase by as much as 192.85%. Then, the prosumers are more willing to exchange power locally, which significantly reduces the increasing transmission burden in transmission networks of power systems. Moreover, DSOs obtain compensation by charging a service commission and reduce their operating costs.
Reproducing biocultural heritage landscapes through alternative and retro-innovative food production

Abstract Landscapes rich in biocultural heritage are declining en masse across Europe. This is due to the effects of countryside depopulation and to large-scale, industrial agriculture. Landscape heritage and its associated biodiversity largely depend on pre-industrial agrarian management. Because authoritative conservation cares only for minor, more spectacular, landscape segments, other forms of everyday management of the more mundane biocultural heritage are needed. Herein, innovative, alternative food producers (i.e. environmentally and animal-friendly farmers) are investigated as potential stewards of biocultural heritage. The results show that alternative food producers contribute to new ways of reproducing the biocultural heritage, albeit with greater emphasis on its ‘green’ side (e.g. biodiversity) than that of cultural heritage. They also face numerous challenges that threaten their businesses.
Translation, rotation and scaling changes in image registration based affine transformation model

In this paper, translation, rotation and scale properties of 2\|D affine transformation are discussed. Visual and IR image registration require a feature\|based apporach. Establishing affine transformation and extracting edge points as feature, this method calculates the cross\|correlation between edges and searches out the relation of corresponding edge points. The maximum correlation principle is involved to adaptively determine the optimal registration parameters k、θ、Δx and Δy . Experimental results using real visual/IR sensor image are presented. It is shown that this model is effective in image registration.
A continuation-passing-style interpretation of simply-typed call-by-need λ-calculus with control within System F

Ariola et al defined a call-by-need λ-calculi with control, together with a sequent calculus presentation of it, and a mechanically generated continuation-passing-style transformation simulating the reduction. We present here a simply-typed version of this calculus and shows that it maps to System F through the continuation-passing-style transformation. This implies in particular the normaliza-tion of this simply-typed call-by-need calculus with control. Incidentally, we treat bound variables for the continuation-passing-style transformation in a precise way using indices rather than up to α-conversion, what makes it directly implementable.
Lycium barbarum Oligosaccharides Alleviate Hepatic Steatosis by Modulating Gut Microbiota in C57BL/6J Mice Fed a High-Fat Diet

High-fat diets (HFD) can promote the development of hepatic steatosis by altering the structure and composition of gut flora. In this study, the potential therapeutic mechanism of Lycium barbarum oligosaccharide (LBO) against hepatic steatosis was investigated by analyzing the changes in the intestinal flora and metabolites in mice. Mice on an HFD were administered LBO by gavage once daily for a continuous period of eight weeks. Compared with the HFD group, the levels of triglyceride (TG), alanine aminotransferase (ALT) in the serum, and hepatic TG were significantly reduced in the LBO group, and liver lipid accumulation was obviously improved. In addition, LBO could regulate the HFD-induced alteration of intestinal flora. The HFD increased the proportion of Barnesiellaceae, Barnesiella, and CHKCI001. LBO increased the proportion of Dubosiella, Eubacterium, and Lactobacillus. LBO also altered the fecal metabolic profile. Significantly different metabolites between LBO and the HFD, such as taurochenodeoxycholate, taurocholate, fluvastatin, and kynurenic acid, were related to the cholesterol metabolism, bile acid metabolism, and tryptophan metabolic pathways. In light of the above, LBO can alleviate HFD-induced NAFLD by modulating the components of the intestinal flora and fecal metabolites.
User-centered development process of an operating interface to couple a robotic glove with a virtual environment to optimize hand rehabilitation following a stroke

Introduction Task-specific neurorehabilitation is crucial to optimize hand recovery shortly after a stroke, but intensive neurorehabilitation remains limited in resource-constrained healthcare systems. This has led to a growing interest in the use of robotic gloves as an adjunct intervention to intensify hand-specific neurorehabilitation. This study aims to develop and assess the usability of an operating interface supporting such a technology coupled with a virtual environment through a user-centered design approach. Methods Fourteen participants with hand hemiparesis following a stroke were invited to don the robotic glove before browsing through the operating interface and its functionalities, and perform two mobility exercises in a virtual environment. Feedback was collected for improving technology usability. Participants completed the System Usability Scale and ABILHAND questionnaires and their recommendations were gathered and prioritized in a Pugh Matrix. Results The System Usability Scale (SUS) score for the operating interface was excellent (M = 87.0 SD = 11.6). A total of 74 recommendations to improve the user interface, calibration process, and exercise usability were identified. Conclusion The application of a full cycle of user-centred design approach confirms the high level of usability of the system which is perceived by end users as acceptable and useful for intensifying neurorehabilitation.
Ag-ZnS Embedded Polymeric Receptors for the Recognition of Human Serum Albumin

The detection of human serum albumin (HSA) is of significant clinical importance in disease diagnoses. In this work, polymer-based synthetic receptors are designed by incorporating Ag-ZnS microspheres in molecularly imprinted poly(methacrylic acid-co-ethylene glycol dimethacrylate) (MIPs) for the gravimetric detection of HSA. Among different compositions of Ag-ZnS@MIPs, MIPs having methacrylic acid and ethylene glycol dimethacrylate volume ratio of 3:2 exhibit enhanced HSA sensitivity in the concentration range of 5–200 ng/mL. A remarkably low threshold limit of detection (LOD = 0.364 ng/mL) is achieved with quartz crystal microbalance (QCM) based gravimetric sensors. Furthermore, the Ag-ZnS@MIPs/QCM sensors show high selectivity for HSA compared to other proteins, e.g., bovine serum albumin (BSA), glycoprotein, ribonuclease, and lysozyme. Hence, the gravimetric quantification of HSA realizes a highly sensitive, selective, and label-free detection mechanism with a limit of quantification down to 1.1 ng/mL.
Experimental analysis of polarization characteristics of surface targets based on active illumination

Light source condition is an important factor affecting image quality in active illumination polarization imaging system. It is of practical significance to study the variation trend of polarization degree contrast between target and water surface background under different light source conditions for water surface target recognition and classification using active illumination polarization imaging technology. In this paper, polarization imaging experiments of iron, aluminum, wood and foam are carried out under water background, and the variation trend of polarization contrast between target and water background is studied under different incident zenith Angle, different polarization states and different light source of visible light band. The results show that the polarization contrast between targets of different materials and water surface background has different sensitive range to the change of incident zenith Angle, and the appropriate incident zenith Angle can be selected according to the actual demand in water surface target recognition and classification. The smooth surface material is more sensitive to the change of incident light band than the rough surface material, and the depolarization ability of the rough surface target to the single-band polarized light is weaker than that of the all-band visible polarized light, which is more conducive to the observation of the surface characteristics of the rough target. Compared with 0° and 90° linearly polarized light, linearly polarized light with incident light of ±45° has a greater polarization contrast and is more conducive to target recognition under water background.
Threshold-based magnitude difference function pitch determination algorithms

Variations of the widely used ‘average magnitude difference function’ (AMDF) algorithm for pitch determination are developed. They are called ‘threshold-based MDF’ (TMDF) and FasTMDF PDAs and incorporate significant computational improvements. Tests and comparisons for all the algorithms discussed are also presented. Real-time implementation is considered both on programmable and special-purpose DSPs. Comparison of execution times on the TMS32020/C25 and the DSP56001 are also included.
Linear Self-Calibration Technique Based on Active Vision

A linear self-calibration technique based on orthogonal motion is brought forth.When the camera model is one that is complete perspective,the five intrinsic parameters of the camera can be calculated linearly by controlling the camera to undergo a pure axial motion and three two-orthogonal motion.When the camera's skew factor is zero,only two two-orthogonal motion is needed to calculate the camera's intrinsic parameters linearly.Simulative and real experimental results show that the intrinsic parameters can be calculated precisely by applying this technique.
MAST Plasma Response Investigations using DINA-CH

Introduction: At low aspect ratio, the radial field necessarily tends towards zero on the inboard side, so that both the radial field from the vertical position control coils, and to a lesser extent the decay index − R Bz ∂Bz ∂R , become inhomogeneous. As a result, the response of the plasma to a vertical perturbation, and thus the vertical control, is suspected to be more non-linear than for conventional R/a tokamaks.
A fully etched high efficiency silicon nitride waveguide grating coupler

The rapid development in the field of optoelectronic integration requires highly efficient coupling between optical fibers and on-chip waveguides. Here, we report an efficient vertical grating coupler which is compatible with COMS process and suitable for silicon nitride photonic integration. The optimized design, fabrication and optical characterizations are presented in details for a silicon nitride waveguide grating coupler. The preliminary results show that the output power of the optimal device structure is 0.25dBm, in good agreement with the simulation result. The fully etched waveguide design needs only one-step etching, which greatly simplifies the fabrication process. Meanwhile, spin coating of Ma2400 series photoresist is innovatively used instead of evaporating SiO2 as the cladding layer of the device, which offers an efficient and economic way to obtain a flat top surface for integration of other devices. Our study provides an alternative method for the heterogeneous integration of functional devices on the COMS compatible silicon nitride platform.
Application of Box Counting Fractal Dimension to Fault Diagnosis in Cracked Rotor

The vibration of large rotating machinery rotor system with a free-cracked shaft and cracked shafts was simulated on rotor experimental platform.According to the fractal characteristics of vibration signal about cracked rotor and free-cracked rotor shaft,fractal box counting dimensions of test data were calculated.The orbit of free-cracked shaft shows as an elliptic,the corresponding fractal box counting dimension is small;the orbit of cracked shaft becomes more complex and its corresponding fractal box counting dimension is larger than that of normal shaft.Therefore,the fractal box counting dimension can be used for fault diagnosis of cracked rotor.