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Frontiers in Neuroscience 2023Multimodal emotion recognition has become a hot topic in human-computer interaction and intelligent healthcare fields. However, combining information from different...
INTRODUCTION
Multimodal emotion recognition has become a hot topic in human-computer interaction and intelligent healthcare fields. However, combining information from different human different modalities for emotion computation is still challenging.
METHODS
In this paper, we propose a three-dimensional convolutional recurrent neural network model (referred to as 3FACRNN network) based on multimodal fusion and attention mechanism. The 3FACRNN network model consists of a visual network and an EEG network. The visual network is composed of a cascaded convolutional neural network-time convolutional network (CNN-TCN). In the EEG network, the 3D feature building module was added to integrate band information, spatial information and temporal information of the EEG signal, and the band attention and self-attention modules were added to the convolutional recurrent neural network (CRNN). The former explores the effect of different frequency bands on network recognition performance, while the latter is to obtain the intrinsic similarity of different EEG samples.
RESULTS
To investigate the effect of different frequency bands on the experiment, we obtained the average attention mask for all subjects in different frequency bands. The distribution of the attention masks across the different frequency bands suggests that signals more relevant to human emotions may be active in the high frequency bands γ (31-50 Hz). Finally, we try to use the multi-task loss function Lc to force the approximation of the intermediate feature vectors of the visual and EEG modalities, with the aim of using the knowledge of the visual modalities to improve the performance of the EEG network model. The mean recognition accuracy and standard deviation of the proposed method on the two multimodal sentiment datasets DEAP and MAHNOB-HCI (arousal, valence) were 96.75 ± 1.75, 96.86 ± 1.33; 97.55 ± 1.51, 98.37 ± 1.07, better than those of the state-of-the-art multimodal recognition approaches.
DISCUSSION
The experimental results show that starting from the multimodal information, the facial video frames and electroencephalogram (EEG) signals of the subjects are used as inputs to the emotion recognition network, which can enhance the stability of the emotion network and improve the recognition accuracy of the emotion network. In addition, in future work, we will try to utilize sparse matrix methods and deep convolutional networks to improve the performance of multimodal emotion networks.
PubMed: 38268710
DOI: 10.3389/fnins.2023.1330077 -
Materials (Basel, Switzerland) Oct 2023In this study, the microstructure of the Mg-4Zn-4Sn-1Mn-xAl (x = 0, 0.3 wt.%, denoted as ZTM441 and ZTM441-0.3Al) as-cast alloys was investigated using scanning electron...
In this study, the microstructure of the Mg-4Zn-4Sn-1Mn-xAl (x = 0, 0.3 wt.%, denoted as ZTM441 and ZTM441-0.3Al) as-cast alloys was investigated using scanning electron microscopy (SEM), focused-ion/electron-beam (FIB) micromachining, transmission electron microscopy (TEM), and high-angle annular dark-field scanning transmission electron microscopy (HAADF-STEM). The analysis results revealed that the microstructure of the ZTM441 and ZTM441-0.3Al as-cast alloys both mainly consist of the α-Mg matrix, skeleton-shaped MgZn eutectic texture, block-shaped MgSn, and Zn/Sn-rich nanoscale precipitate bands along the grain boundary and the interdendrite. Nanoscale α-Mn dispersoids formed in the grain in the ZTM441 alloy, while no α-Mn formed in the ZTM441-0.3Al alloy instead of nanoscale AlMn particles. In the ZTM441 as-cast alloy, part of the Zn element is dissolved into the α-Mn phase, and part of the Mn element is dissolved into the MgZn phase, but in the ZTM441-0.3Al alloy, there are no such characteristics of mutual solubility. Zn and Mn elements are easy to combine in ZTM441 as-cast alloy, while Al and Mn are easy to combine in ZTM441-0.3Al as-cast alloy. The Mg-Zn phases have not only MgZn-type crystal structure but also MgZn- and MgZn-type crystal structure in the ZTM441-0.3Al as-cast alloy. The addition of Al changes the combination of Mn and Zn, promotes the formation of AlMn, and the growth of the grain.
PubMed: 37959576
DOI: 10.3390/ma16216979 -
Inorganic Chemistry Jul 2023Agile and efficient upconversion luminescence (UCL) fine-tuning strategies are the most demanded for in the frontier applications of highly doped upconversion...
Agile and efficient upconversion luminescence (UCL) fine-tuning strategies are the most demanded for in the frontier applications of highly doped upconversion nanoparticles (UCNPs). By doping Zn ions into NaHoF and NaGdF:Yb shells using the oleate method, the separate influences of Zn on Ho and Yb ions in UCL-related processes were analyzed in detail, revealing relevant UCL changes and underlying energy mechanisms from a novel but explicit perspective. Different behaviors of green and red UCL before and after Zn-ion doping were attributed to the disparities in the energy pathways and features of the sample structures. Herein, the populations of S/F and F states, not the usually mentioned decay time, decided the UCL intensities of the NaHoF@NaYbF-structured highly doped UCNPs. The advantageous small sizes and intense single-band red UCL of these UCNPs were further developed by combining our previous strategies with introducing Zn ions into the NaHoF matrix. Overcoming energy loss by surface quenchers and Zn-triggered inner defects is the key factor in maximizing 4f-4f transitions. To the best of our knowledge, the current study is the first attempt to date to experimentally reveal separate impacts of the heteroions on activators and sensitizers in UCL-related processes and can deepen the theoretical investigation of Ho-based UCL for the broadened applications of NaHoF UCNPs.
PubMed: 37364168
DOI: 10.1021/acs.inorgchem.3c01423 -
Nature Communications Oct 2023The theorems of density functional theory (DFT) establish bijective maps between the local external potential of a many-body system and its electron density,...
The theorems of density functional theory (DFT) establish bijective maps between the local external potential of a many-body system and its electron density, wavefunction and, therefore, one-particle reduced density matrix. Building on this foundation, we show that machine learning models based on the one-electron reduced density matrix can be used to generate surrogate electronic structure methods. We generate surrogates of local and hybrid DFT, Hartree-Fock and full configuration interaction theories for systems ranging from small molecules such as water to more complex compounds like benzene and propanol. The surrogate models use the one-electron reduced density matrix as the central quantity to be learned. From the predicted density matrices, we show that either standard quantum chemistry or a second machine-learning model can be used to compute molecular observables, energies, and atomic forces. The surrogate models can generate essentially anything that a standard electronic structure method can, ranging from band gaps and Kohn-Sham orbitals to energy-conserving ab-initio molecular dynamics simulations and infrared spectra, which account for anharmonicity and thermal effects, without the need to employ computationally expensive algorithms such as self-consistent field theory. The algorithms are packaged in an efficient and easy to use Python code, QMLearn, accessible on popular platforms.
PubMed: 37805614
DOI: 10.1038/s41467-023-41953-9 -
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 -
Seizure Dec 2023High-frequency oscillations (HFOs) are an efficient indicator to locate the epileptogenic zone (EZ). However, physiological HFOs produced in the normal brain region may...
OBJECTIVE
High-frequency oscillations (HFOs) are an efficient indicator to locate the epileptogenic zone (EZ). However, physiological HFOs produced in the normal brain region may interfere with EZ localization. The present study aimed to build a machine learning-based classifier to distinguish the properties of each HFO event based on features in different domains.
METHODS
HFOs were detected in focal epilepsy patients from two different hospitals who underwent stereoelectroencephalography and subsequent resection surgery. Subsequently, 37 features in four different domains (time, frequency and time-frequency, entropy-based and nonlinear) were extracted for each HFO. After extraction, a fast correlation-based filter (FCBF) algorithm was applied for feature selection. The machine learning classifier was trained on the feature matrix with and without FCBF and then tested on the data set from patients in another hospital.
RESULTS
A dataset was compiled, consisting of 89,844 pathological HFOs and 23,613 physiological HFOs from 17 patients assigned to the training dataset. Additionally, 12,695 pathological HFOs and 5,599 physiological HFOs from 9 patients were assigned to the testing dataset. Four features (ripple band power, arithmetic mean, Petrosian fractal dimension and zero crossings) were obtained for classifier training after FCBF. The classifier showed an area under the curve (AUC) of 0.95/0.98 for FCBF/no FCBF features in the training dataset and AUC of 0.82/0.90 for FCBF/no FCBF features in the testing dataset. Our findings indicated that the classifier utilizing all features demonstrated superior performance compared to the one relying on FCBF-processed features.
CONCLUSION
Our classifier could reliably differentiate pathological HFOs from physiological ones, which could promote the development of HFOs in EZ localization.
Topics: Humans; Electroencephalography; Brain; Epilepsies, Partial; Brain Waves; Machine Learning
PubMed: 37984126
DOI: 10.1016/j.seizure.2023.11.005 -
Accounts of Chemical Research May 2024ConspectusNonradiative processes with the determined role in excited-state energy conversion, such as internal conversion (IC), vibrational relaxation (VR), intersystem...
ConspectusNonradiative processes with the determined role in excited-state energy conversion, such as internal conversion (IC), vibrational relaxation (VR), intersystem crossing (ISC), and energy or electron transfer (ET or eT), have exerted a crucial effect on biological functions in nature. Inspired by these, nonradiative process manipulation has been extensively utilized to develop organic functional materials in the fields of energy and biomedicine. Therefore, comprehensive knowledge and effective manipulation of sophisticated nonradiative processes for achieving high-efficiency excited-state energy conversion are quintessential. So far, many strategies focused on molecular engineering have demonstrated tremendous potential in manipulating nonradiative processes to tailor excited-state energy conversion. Besides, molecular aggregation considerably affects nonradiative processes due to their ultrasensitivity, thus providing us with another essential approach to manipulating nonradiative processes, such as the famous aggregation-induced emission. However, the weak interactions established upon aggregation, namely, the aggregation microenvironment (AME), possess hierarchical, dynamic, and systemic characteristics and are extremely complicated to elucidate. Revealing the relationship between the AME and nonradiative process and employing it to customize excited-state energy conversion would greatly promote advanced materials in energy utilization, biomedicine, etc., but remain a huge challenge. Our group has devoted much effort to achieving this goal.In this Account, we focus on our recent developments in nonradiative process manipulation based on AME. First, we provide insight into the effect of the AME on nonradiative process in terms of its steric effect and electronic regulation, illustrating the possibility of nonradiative process manipulation through AME modulation. Second, the distinct enhanced steric effect is established by crystallization and heterogeneous polymerization to conduct crystallization-induced reversal from dark to bright excited states and dynamic hardening-triggered nonradiative process suppression for highly efficient luminescence. Meanwhile, promoting the ISC process and stabilizing the triplet state are also manipulated by the crystal and polymer matrix to induce room-temperature phosphorescence. Furthermore, the strategies employed to exploit nonradiative processes for photothermy and photosensitization are reviewed. For photothermal conversion, besides the weakened steric effect with promoted molecular motions, a new strategy involving the introduction of diradicals upon aggregation to narrow the energy band gap and enhance intermolecular interactions is put forward to facilitate IC and VR for high-efficiency photothermal conversion. For photosensitization, both the enhanced steric effect from the rigid matrix and the effective electronic regulation from the electron-rich microenvironment are demonstrated to facilitate ISC, ET, and eT for superior photosensitization. Finally, we explore the existing challenges and future directions of nonradiative process manipulation by AME modulation for customized excited-state energy conversion. We hope that this Account will be of wide interest to readers from different disciplines.
PubMed: 38669148
DOI: 10.1021/acs.accounts.4c00071 -
BMC Oral Health Oct 2023Proper proximal contact in direct composite restorations is crucial for periodontal health. Over a one-year period, this study was conducted to assess successive... (Randomized Controlled Trial)
Randomized Controlled Trial
Evaluation of the proximal contact tightness in class II resin composite restorations using different contact forming instruments: a 1-year randomized controlled clinical trial.
BACKGROUND
Proper proximal contact in direct composite restorations is crucial for periodontal health. Over a one-year period, this study was conducted to assess successive biological changes in proximal contact tightness PCT in class II direct composite restorations and the adjacent teeth by applying sectional matrix system along with different contact forming instruments.
METHODS
72 direct compound class II composite restorations were performed in patients aged 18-40 years and divided into 4 groups: Group I (n = 18): proximal contact was restored with Palodent plus sectional matrix system, Group II (n = 18): Trimax as contact forming instrument, Group III (n = 18): Perform as contact forming instrument and Group IV (n = 18): Contact pro as contact forming instrument. All contact forming instruments were used along with Palodent plus matrix system. PCT was measured using a digital force gauge before (T0), immediate post operative (T1) and at 3 (T2), 6 (T3), 9 (T4), and 12 months (T5) after restorative treatment. Using One-Way ANOVA, Tukey's post hoc test, and Bonferroni correction, PCT values were compared between groups before and after the intervention restoration. Meanwhile, for comparisons within groups, a paired t-test was conducted (p ≤ 0.05).
RESULTS
Contact forming instruments combined with Palodent plus sectional matrix system achieved better PCT. Trimax led to a statistically considerable tighter proximal contacts than the other groups (p < 0.05). No statistically significant difference was found in PCT between Contact pro-2, Perform and Palodent plus sectional matrix system. By means of multivariate analysis, the PCT between both T0 and T1 were increased (p < 0.001) and then it decreased till T5.
CONCLUSIONS
The use of transparent contact forming instruments achieved greater PCT compared to Palodent sectional matrix system alone that gradually decreased throughout 12 months and reached the PCT between the natural teeth. Using Trimax system provided the tightest proximal contacts. Additionally, digital force gauge was confirmed as an inclusive and accurate method to quantify PCT.
TRIAL REGISTRATION
ClinicalTrials.gov NCT05749640: 24/5/2022.
Topics: Humans; Dental Restoration, Permanent; Dental Cavity Preparation; Matrix Bands; Composite Resins; Bicuspid
PubMed: 37805456
DOI: 10.1186/s12903-023-03462-5 -
Journal of Physics. Condensed Matter :... Sep 2023When non-magnetic impurity immerses in Fermi sea, a regular modulation of charge density around impurity will appear and such phenomena is called Friedel oscillation...
When non-magnetic impurity immerses in Fermi sea, a regular modulation of charge density around impurity will appear and such phenomena is called Friedel oscillation (FO). Although both Luttinger liquid and Landau Fermi liquid show such characteristic oscillation, FO in generic non-Fermi liquid (NFL) phase is still largely unknown. Here, we show that FO indeed exists in NFL state of an exactly solvable model, i.e. the Hatsugai-Kohmoto model which has been intensively explored in recent years. Combining T-matrix approximation and linear-response-theory, an interesting picture emerges, if two interaction-induced quasi-particles bands in NFL are partially occupied, FO in this situation is determined by a novel structure in momentum space, i.e. the 'average Fermi surface' (average over two quasi-particle Fermi surface), which highlights the inter-band particle-hole excitation. We hope our study here provides a counterintuitive example in which FO with Fermi surface coexists with NFL quasi-particle, and it may be useful to detect hidden 'average Fermi surface' structure in other correlated electron systems.
PubMed: 37666256
DOI: 10.1088/1361-648X/acf69f -
ACS Nano May 2024Radar-absorbing materials (RAMs) covering the exterior surfaces of installed parts and assembled devices are crucial in absorbing most incident electromagnetic (EM)...
Radar-absorbing materials (RAMs) covering the exterior surfaces of installed parts and assembled devices are crucial in absorbing most incident electromagnetic (EM) waves. This absorption minimizes reflected energy, thereby enhancing pilot safety and the stability of operating electronic devices without interference. Particularly, active stealth aircraft require effective protection from near- and far-field EM radiation across a wide spectrum of frequencies from both highly integrated electronic components and advanced enemy radars. Studies of RAMs often prioritize absorption over crucial tunability in frequency selectivity, revealing a research gap. In this study, we propose smart RAMs with frequency-selective absorption capabilities. Our approach involves incorporating two types of core-shell spheres in a polymer matrix, which feature shells of either wave-diffuse reflecting metal or wave-absorbing graphene. The key innovation lies in the ability to tailor absorption frequencies in the X-band range (8.2-12.4 GHz) by adjusting the interstitial spaces between the metallic spheres while the scattered waves are efficiently attenuated by graphene networks in the composites. On a metal substrate, a 2 mm-thick composite with an optimized structural composition and ratio of the two types of spheres exhibits a maximum absorption efficiency of 99.3%, effectively trapping and extinguishing incident waves. Combined with the structural tunability and frequency-selective properties of spherical fillers, our approach provides a scalable and effective method for creating functional isotropic coverings on various metallic surfaces.
PubMed: 38697128
DOI: 10.1021/acsnano.4c00624