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Brain Sciences Feb 2024Mathematical modeling and computer simulation are important methods for understanding complex neural systems. The whole-brain network model can help people understand...
BACKGROUND
Mathematical modeling and computer simulation are important methods for understanding complex neural systems. The whole-brain network model can help people understand the neurophysiological mechanisms of brain cognition and functional diseases of the brain.
METHODS
In this study, we constructed a resting-state whole-brain network model (WBNM) by using the Wendling neural mass model as the node and a real structural connectivity matrix as the edge of the network. By analyzing the correlation between the simulated functional connectivity matrix in the resting state and the empirical functional connectivity matrix, an optimal global coupling coefficient was obtained. Then, the waveforms and spectra of simulated EEG signals and four commonly used measures from graph theory and small-world network properties of simulated brain networks under different thresholds were analyzed.
RESULTS
The results showed that the correlation coefficient of the functional connectivity matrix of the simulated WBNM and empirical brain networks could reach a maximum value of 0.676 when the global coupling coefficient was set to 20.3. The simulated EEG signals showed rich waveform and frequency-band characteristics. The commonly used graph-theoretical measures and small-world properties of the constructed WBNM were similar to those of empirical brain networks. When the threshold was set to 0.22, the maximum correlation between the simulated WBNM and empirical brain networks was 0.709.
CONCLUSIONS
The constructed resting-state WBNM is similar to a real brain network to a certain extent and can be used to study the neurophysiological mechanisms of complex brain networks.
PubMed: 38539628
DOI: 10.3390/brainsci14030240 -
Brain Sciences Feb 2024In recent years, the integration of brain-computer interface technology and neural networks in the field of music generation has garnered widespread attention. These...
In recent years, the integration of brain-computer interface technology and neural networks in the field of music generation has garnered widespread attention. These studies aimed to extract individual-specific emotional and state information from electroencephalogram (EEG) signals to generate unique musical compositions. While existing research has focused primarily on brain regions associated with emotions, this study extends this research to brain regions related to musical composition. To this end, a novel neural network model incorporating attention mechanisms and steady-state activation mapping (SSAM) was proposed. In this model, the self-attention module enhances task-related information in the current state matrix, while the extended attention module captures the importance of state matrices over different time frames. Additionally, a convolutional neural network layer is used to capture spatial information. Finally, the ECA module integrates the frequency information learned by the model in each of the four frequency bands, mapping these by learning their complementary frequency information into the final attention representation. Evaluations conducted on a dataset specifically constructed for this study revealed that the model surpassed representative models in the emotion recognition field, with recognition rate improvements of 1.47% and 3.83% for two different music states. Analysis of the attention matrix indicates that the left frontal lobe and occipital lobe are the most critical brain regions in distinguishing between 'recall and creation' states, while FP1, FPZ, O1, OZ, and O2 are the electrodes most related to this state. In our study of the correlations and significances between these areas and other electrodes, we found that individuals with musical training exhibit more extensive functional connectivity across multiple brain regions. This discovery not only deepens our understanding of how musical training can enhance the brain's ability to work in coordination but also provides crucial guidance for the advancement of brain-computer music generation technologies, particularly in the selection of key brain areas and electrode configurations. We hope our research can guide the work of EEG-based music generation to create better and more personalized music.
PubMed: 38539605
DOI: 10.3390/brainsci14030216 -
Dentistry Journal Mar 2024The purpose of this study was to identify changes in the temporomandibular joint disc affected by effusion by using texture analysis of magnetic resonance images (MRIs).
UNLABELLED
The purpose of this study was to identify changes in the temporomandibular joint disc affected by effusion by using texture analysis of magnetic resonance images (MRIs).
METHODS
A total of 223 images of the TMJ, 42 with joint effusion and 181 without, were analyzed. Three consecutive slices were then exported to MaZda software, in which two oval ROIs (one in the anterior band and another in the intermediate zone of the joint disc) were determined in each slice and eleven texture parameters were calculated by using a gray-level co-occurrence matrix. Spearman's correlation coefficient test was used to assess the correlation between texture variables and to select variables for analysis. The Mann-Whitney test was used to compare the groups.
RESULTS
The significance level was set at 5%, with the results demonstrating that there was no high correlation between the parameter directions. It was possible to observe a trend between the average parameters, in which the group with effusion always had smaller values than the group without effusion, except for the parameter measuring the difference in entropy.
CONCLUSION
The trend towards lower overall values for the texture parameters suggested a different behavior between TMJ discs affected by effusion and those not affected, indicating that there may be intrinsic changes.
PubMed: 38534306
DOI: 10.3390/dj12030082 -
Plant Phenomics (Washington, D.C.) 2024Automation of plant phenotyping using data from high-dimensional imaging sensors is on the forefront of agricultural research for its potential to improve seasonal yield...
Automation of plant phenotyping using data from high-dimensional imaging sensors is on the forefront of agricultural research for its potential to improve seasonal yield by monitoring crop health and accelerating breeding programs. A common challenge when capturing images in the field relates to the spectral reflection of sunlight (glare) from crop leaves that, at certain solar incidences and sensor viewing angles, presents unwanted signals. The research presented here involves the convergence of 2 parallel projects to develop a facile algorithm that can use polarization data to decouple light reflected from the surface of the leaves and light scattered from the leaf's tissue. The first project is a mast-mounted hyperspectral imaging polarimeter (HIP) that can image a maize field across multiple diurnal cycles throughout a growing season. The second project is a multistatic fiber-based Mueller matrix bidirectional reflectance distribution function (mmBRDF) instrument which measures the polarized light-scattering behavior of individual maize leaves. The mmBRDF data was fitted to an existing model, which outputs parameters that were used to run simulations. The simulated data were then used to train a shallow neural network which works by comparing unpolarized 2-band vegetation index (VI) with linearly polarized data from the low-reflectivity bands of the VI. Using GNDVI and red-edge reflection ratio we saw an improvement of an order of magnitude or more in the mean error () and a reduction spanning 1.5 to 2.7 in their standard deviation () after applying the correction network on the HIP sensor data.
PubMed: 38524737
DOI: 10.34133/plantphenomics.0157 -
Journal of Biomaterials Applications May 2024Self-assembling peptides (SAPs) show promise in creating synthetic microenvironments that regulate cellular function and tissue repair. Also, the precise π-π... (Review)
Review
Self-assembling peptides (SAPs) show promise in creating synthetic microenvironments that regulate cellular function and tissue repair. Also, the precise π-π interactions and hydrogen bonding within self-assembled peptide structures enable the creation of quantum confined structures, leading to reduced band gaps and the emergence of semiconductor properties within the superstructures. This review emphasizes the need for standardized 3D cell culture methods and electronic devices based on SAPs for monitoring cell communication and controlling cell surface morphology. Additionally, the gap in understanding the relationship between SAP peptide sequences and nanostructures is highlighted, underscoring the importance of optimizing peptide deposition parameters, which affect charge transport and bioactivity due to varying morphologies. The potential of peptide nanofibers as extracellular matrix mimics and the introduction of the zone casting method for improved film deposition are discussed within this review, aiming to bridge knowledge gaps and offer insights into fields like tissue engineering and materials science, with the potential for groundbreaking applications at the interface of biology and materials engineering.
Topics: Humans; Peptides; Tissue Engineering; Animals; Nanofibers; Cell Culture Techniques, Three Dimensional; Biocompatible Materials; Extracellular Matrix; Tissue Scaffolds; Electronics
PubMed: 38502905
DOI: 10.1177/08853282241240139 -
ACS Applied Materials & Interfaces Mar 2024Metal-semiconductor nanocomposites have emerged as a viable strategy for concurrently tailoring both thermal and electronic transport properties of established...
Metal-semiconductor nanocomposites have emerged as a viable strategy for concurrently tailoring both thermal and electronic transport properties of established thermoelectric materials, ultimately achieving synergistic performance. In this investigation, a series of nanocomposite thin films were synthesized, embedding metallic cobalt telluride (CoTe) nanophase within the nanocrystalline ternary skutterudite (Co(GeSb)Te or CGST) matrix. Our approach harnessed composition fluctuation-induced phase separation and in situ growth during thermal annealing to seamlessly integrate the metallic phase. The distinctive band structures of both materials have developed an ohmic-type contact characteristic at the interface, which raised carrier density considerably yet negligibly affected the mobility counterpart, leading to a substantial improvement in electrical conductivity. The intricate balance in transport properties is further influenced by the metallic CoTe phase's role in diminishing lattice thermal conductivity. The presence of the metallic phase instigates enhanced phonon scattering at the interface boundaries. Consequently, a 2-fold enhancement in the thermoelectric figure of merit (zT ∼ 1.30) is attained with CGST-7 wt. % CoTe nanocomposite film at 655 K compared to that of pristine CGST.
PubMed: 38489232
DOI: 10.1021/acsami.3c17695 -
ACS Applied Energy Materials Mar 2024This work aims to understand the spin-coating growth process of BiVO photoanodes from a photon absorption and conversion perspective. BiVO layers with thicknesses...
This work aims to understand the spin-coating growth process of BiVO photoanodes from a photon absorption and conversion perspective. BiVO layers with thicknesses ranging from 7 to 48 nm and the role of a thin (<5 nm) SnO hole-blocking layer have been studied. The internal absorbed photon-to-current efficiency (APCE) is found to be nonconstant, following a specific dependence of the internal charge separation and extraction on the increasing thickness. This APCE variation with BiVO thickness is key for precise computational simulation of light propagation in BiVO based on the transfer matrix method. Results are used for accurate incident photon-to-current efficiency (IPCE) prediction and will help in computational modeling of BiVO and other metal oxide photoanodes. This establishes a method to obtain the sample's thickness by knowing its IPCE, accounting for the change in the internal APCE conversion. Moreover, an improvement in fill factor and photogenerated voltage is attributed to the intermediate SnO hole-blocking layer, which was shown to have a negligible optical effect but to enhance charge separation and extraction for the lower energetic wavelengths. A Mott-Schottky analysis was used to confirm a photovoltage shift of 90 mV of the flat-band potential.
PubMed: 38487269
DOI: 10.1021/acsaem.3c02775 -
Journal of Oral Biology and... 2024The permanence of deep subgingival restorations are questionable both functionally and biologically. Crown lengthening is one of the traditionally performing procedures... (Review)
Review
The permanence of deep subgingival restorations are questionable both functionally and biologically. Crown lengthening is one of the traditionally performing procedures to visualize and relocate the deep margins, but the limitations of the invasive surgical procedure are anatomical complications like exposure of root concavities or furcation, violation of biological width, post operative discomfort because of sutures or periodontal packs; and less patient compliance. Other than crown lengthening, researchers tried some other techniques like modified matrix adaptation technique, using retraction cord, making holes in matrix band and flowing resin modified glass ionomer cement (RMGIC) to the root or cervical caries, orthodontic extrusion. But most of these procedures are failed to give adequate clinical success. Deep margin elevation (DME) is one of the minimally invasive and successful procedure performing in deep subgingival caries. But the evidences and knowledge in this technique is limited among practitioners. This review is to evaluate the applicability of DME, the current clinical concepts, techniques and materials for DME; and a comparison with traditionally used various techniques for cervical margin relocation also concluding that currently available various clinical parameters with this technique.
PubMed: 38481655
DOI: 10.1016/j.jobcr.2023.12.002 -
The Journal of Physical Chemistry. C,... Mar 2024We present a theoretical model to compute the efficiency of the generation of two or more electron-hole pairs in a semiconductor by the absorption of one photon via the...
We present a theoretical model to compute the efficiency of the generation of two or more electron-hole pairs in a semiconductor by the absorption of one photon via the process of carrier multiplication (CM). The photogeneration quantum yield of electron-hole pairs is calculated from the number of possible CM decay pathways of the electron and the hole. We apply our model to investigate the underlying cause of the high efficiency of CM in bulk 2H-MoTe, as compared to bulk PbS and PbSe. Electronic band structures were calculated with density functional theory, from which the number of possible CM decay pathways was calculated for all initial electron and hole states that can be produced at a given photon energy. The variation of the number of CM pathways with photon energy reflects the dependence of experimental CM quantum yields on the photon energy and material composition. We quantitatively reproduce experimental CM quantum yields for MoTe, PbS, and PbSe from the calculated number of CM pathways and one adjustable fit parameter. This parameter is related to the ratio of Coulomb coupling matrix elements and the cooling rate of the electrons and holes. Large variations of this fit parameter result in small changes in the modeled quantum yield for MoTe, which confirms that its high CM efficiency can be mainly attributed to its extraordinary large number of CM pathways. The methodology of this work can be applied to analyze or predict the CM efficiency of other materials.
PubMed: 38476826
DOI: 10.1021/acs.jpcc.4c00383 -
Polymers Mar 2024The application of absorbing materials for electromagnetic shielding is becoming extensive, and the use of absorbents is one of the most important points of preparing...
The application of absorbing materials for electromagnetic shielding is becoming extensive, and the use of absorbents is one of the most important points of preparing absorbing foam materials. In this work, epoxy resin was used as the matrix and carbonyl iron powder (CIP) was used as the absorbent, and the structural absorbing foam materials were prepared by the ball mill dispersion method. Scanning electron microscopy showed that the CIP was evenly dispersed in the resin matrix. The foam structures formed at pre-polymerization times of 10 min, 30 min and 50 min were analyzed, and it was found that the cell diameter decreased from 0.47 mm to 0.31 mm with the increase in the pre-polymerization time. The reflectivity of the frontal and reverse sides of the foam gradually tends to be unified at frequencies of 2-18 GHz. When the CIP content increased from 30 wt% to 70 wt%, the cell diameter increased from 0.32 mm to 0.4 mm, and the uniformity of CIP distribution deteriorated. However, with the increase in the CIP content, the absorption properties of the composite materials were enhanced, and the absorption frequency band broadened. When the CIP content reached 70 wt%, the compression strength and modulus of the foam increased to 1.32 MPa and 139.0 MPa, respectively, indicating a strong ability to resist deformation.
PubMed: 38475381
DOI: 10.3390/polym16050698