Electroencephalogram (EEG) signals recorded from sensor electrodes on the scalp can directly detect the brain dynamics in response to different emotional states. Emotion recognition from EEG signals ...has attracted broad attention, partly due to the rapid development of wearable computing and the needs of a more immersive human-computer interface (HCI) environment. To improve the recognition performance, multi-channel EEG signals are usually used. A large set of EEG sensor channels will add to the computational complexity and cause users inconvenience. ReliefF-based channel selection methods were systematically investigated for EEG-based emotion recognition on a database for emotion analysis using physiological signals (DEAP). Three strategies were employed to select the best channels in classifying four emotional states (joy, fear, sadness and relaxation). Furthermore, support vector machine (SVM) was used as a classifier to validate the performance of the channel selection results. The experimental results showed the effectiveness of our methods and the comparison with the similar strategies, based on the F-score, was given. Strategies to evaluate a channel as a unity gave better performance in channel reduction with an acceptable loss of accuracy. In the third strategy, after adjusting channels' weights according to their contribution to the classification accuracy, the number of channels was reduced to eight with a slight loss of accuracy (58.51% ± 10.05% versus the best classification accuracy 59.13% ± 11.00% using 19 channels). In addition, the study of selecting subject-independent channels, related to emotion processing, was also implemented. The sensors, selected subject-independently from frontal, parietal lobes, have been identified to provide more discriminative information associated with emotion processing, and are distributed symmetrically over the scalp, which is consistent with the existing literature. The results will make a contribution to the realization of a practical EEG-based emotion recognition system.
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IZUM, KILJ, NUK, PILJ, PNG, SAZU, UL, UM, UPUK
Motor Imagery (MI) paradigm is critical in neural rehabilitation and gaming. Advances in brain-computer interface (BCI) technology have facilitated the detection of MI from electroencephalogram ...(EEG). Previous studies have proposed various EEG-based classification algorithms to identify the MI, however, the performance of prior models was limited due to the cross-subject heterogeneity in EEG data and the shortage of EEG data for training. Therefore, inspired by generative adversarial network (GAN), this study aims to propose an improved domain adaption network based on Wasserstein distance, which utilizes existing labeled data from multiple subjects (source domain) to improve the performance of MI classification on a single subject (target domain). Specifically, our proposed framework consists of three components, including a feature extractor, a domain discriminator, and a classifier. The feature extractor employs an attention mechanism and a variance layer to improve the discrimination of features extracted from different MI classes. Next, the domain discriminator adopts the Wasserstein matrix to measure the distance between source domain and target domain, and aligns the data distributions of source and target domain via adversarial learning strategy. Finally, the classifier uses the knowledge acquired from the source domain to predict the labels in the target domain. The proposed EEG-based MI classification framework was evaluated by two open-source datasets, the BCI Competition IV Datasets 2a and 2b. Our results demonstrated that the proposed framework could enhance the performance of EEG-based MI detection, achieving better classification results compared with several state-of-the-art algorithms. In conclusion, this study is promising in helping the neural rehabilitation of different neuropsychiatric diseases.
Driver fatigue is attracting more and more attention, as it is the main cause of traffic accidents, which bring great harm to society and families. This paper proposes to use deep convolutional ...neural networks, and deep residual learning, to predict the mental states of drivers from electroencephalography (EEG) signals. Accordingly we have developed two mental state classification models called EEG-Conv and EEG-Conv-R. Tested on intra- and inter-subject, our results show that both models outperform the traditional LSTM- and SVM-based classifiers. Our major findings include (1) Both EEG-Conv and EEG-Conv-R yield very good classification performance for mental state prediction; (2) EEG-Conv-R is more suitable for inter-subject mental state prediction; (3) EEG-Conv-R converges more quickly than EEG-Conv. In summary, our proposed classifiers have better predictive power and are promising for application in practical brain-computer interaction .
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EMUNI, FIS, FZAB, GEOZS, GIS, IJS, IMTLJ, KILJ, KISLJ, MFDPS, NLZOH, NUK, OBVAL, OILJ, PNG, SAZU, SBCE, SBJE, SBMB, SBNM, UKNU, UL, UM, UPUK, VKSCE, ZAGLJ
•An energy dissipation-based stability analysis model of rock mass was proposed.•Excavation relaxation characteristics of surrounding rock mass were analyzed.•A delineation criterion of surrounding ...rock mass was put forward.•Phenomena and law of deformation and failure of surrounding rock were revealed.
The geological conditions of the underground caverns in the Jinping I hydropower station are particularly complicated, with high ground stress (the extreme value of the measuring point is 35.7 MPa), complicated deformation and failure mechanisms, and large unloading depth. The large deformation of the surrounding rock mass was beyond current engineering and academic understanding. During the construction period, the deformation and failure mechanisms were complex, and the unloading depth was large. The maximum deformation of the sidewall of the main powerhouse reached 246 mm. The monitoring results of multi-point extensometers basically converged two years after the completion of cavern excavation. Regarding the deformation and failure mechanism of the large underground caverns, the energy dissipation theory that can better describe the complex mechanical response analysis was proposed. The deformation failure mechanism, mechanical behaviour, supporting effect and stability evaluation of the large underground caverns were investigated from the perspectives of excavation unloading and energy dissipation and release. The excavation unloading-induced relaxation characteristics of the surrounding rock mass were analysed using a comprehensive approach incorporating the results of borehole television, acoustic wave testing, multipoint extensometer and numerical simulations. A criterion of the surrounding rock mass delineation incorporating the energy dissipation ratio, acoustic wave testing, wave velocity variation and elastic modulus variation was also proposed. Furthermore, the phenomena and law of deformation and failure of surrounding rock mass in the large underground caverns were revealed. The stability of surrounding rock mass in the underground caverns was evaluated. The related achievements can provide some references for similar deep underground rock engineering.
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GEOZS, IJS, IMTLJ, KILJ, KISLJ, NLZOH, NUK, OILJ, PNG, SAZU, SBCE, SBJE, UILJ, UL, UM, UPCLJ, UPUK, ZAGLJ, ZRSKP
The surrounding rock at the exit of the No. 1 drainage tunnel of the Artashi Water Conservancy Project is micritic bioclastic limestone with 55% bioclastic material. This rock underwent unpredictable ...large and time-dependent deformation during excavation. To date, the mechanical behaviour of this kind of rock has rarely been studied. In this study, traditional triaxial compression tests and multilevel creep tests were conducted on micritic bioclastic limestone, and the results clarified the instantaneous and time-dependent mechanical properties of the rock. Considering that the essence of rock failure is crack growth, the crack strain evolution properties were revealed in rock triaxial compression tests and multilevel creep tests. Based on triaxial compression tests, the evolution of axial cracks with increasing deviatoric stress ratio R.sub.d (ratio of deviatoric stress to peak deviatoric stress) was observed, and an axial crack closure element and new crack growth element were proposed. To simulate the creep behaviour of a rock specimen, the relationship of the rock creep crack strain rate with R.sub.d was studied. A creep crack element was created, and the creep crack strain evolution equation was obtained, which closely fit the experimental data. Combining the 4 element types (elastic element, crack closure element, crack growth element, and creep crack element), a unified transient creep constitutive model (Mo's model) was proposed, which represented both the transient and time-dependent mechanical properties of the micritic bioclastic limestone.
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DOBA, IZUM, KILJ, NUK, PILJ, PNG, SAZU, SIK, UILJ, UKNU, UL, UM, UPUK
Alzheimer's disease (AD) is pathologically characterized by amyloid-β (Aβ) accumulation, which induces Aβ-dependent neuronal dysfunctions. We focused on the early-stage disease progression and ...examined the neuronal network functioning in the 5xFAD mice. The simultaneous intracranial recordings were obtained from the hippocampal perforant path (PP) and the dentate gyrus (DG). Concomitant to Aβ accumulation, theta power was strongly attenuated in the PP and DG regions of 5xFAD mice compared to those in nontransgenic littermates. For either theta rhythm or gamma oscillation, the phase synchronization on the PP-DG pathway was impaired, evidenced by decreased phase locking value and diminished coherency index. To alleviate the neural oscillatory deficits in early-stage AD, a neural modulation approach (rTMS) was used to activate gamma oscillations and strengthen the synchronicity of neuronal activity on the PP-DG pathway. In brief, there was a significant neuronal network dysfunction at an early-stage AD-like pathology, which preceded the onset of cognitive deficits and was likely driven by Aβ accumulation, suggesting that the neural oscillation analysis played an important role in early AD diagnosis.
•Early-stage dysfunction of oscillations driven by Aβ precedes cognitive deficits.•rTMS activated gamma oscillations disturbed by Aβ deposition.•rTMS enhanced oscillatory synchrony attenuated by Aβ deposition on PP-DG pathway.•Neural oscillation analysis could be used in early-stage AD diagnosis and prevention.
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GEOZS, IJS, IMTLJ, KILJ, KISLJ, NLZOH, NUK, OILJ, PNG, SAZU, SBCE, SBJE, UILJ, UL, UM, UPCLJ, UPUK, ZAGLJ, ZRSKP
The hypermobility of a large landslide makes it usually a catastrophic event whose mechanism is, however, not yet completely understood. As for supraglacial rock avalanches which typically occur in ...glacial environments, the runout can reach several to more than a dozen kilometers with a maximum velocity over 100 ms−1 and the mobility can be even stronger than that of the normal rock avalanches travelling on a rocky terrain. This phenomenon suggests a strong resistance reduction mechanism, such as ice melting, entrainment of ice and snow, and mass and momentum transfers between the solid and liquid components. Here we generalize the thermo-hydro-mechanical (THM) coupling analysis to study supraglacial rock avalanches taking into account ice-water phase transition due to frictional heating. Based on the fact that supraglacial avalanches can travel a long distance on the glacier surfaces whose path material mainly contains ice and snow, the ice content in the slip band can be relatively high which contributes to the basal lubrication as the ice melts. To assess the validity of the model, the 2016 Lamplugh supraglacial rock avalanche is chosen as a case study and the results are validated by comparisons with that from the seismic wave inversion, which suggests the THM analysis can capture the main characteristics of the supraglacial rock avalanche. A set of sensitivity analyses demonstrate the significance of considering the heat production and the ice-water phase transition, and principle factors are subsequently discussed. In particular, it is found that unlike normal rock avalanches in positive temperature environments, the initial temperature and porosity are significant for the initiation and motion processes of supraglacial rock avalanches in glacial environments.
•Thermo-hydro-mechanical analysis of supraglacial rock avalanches is carried out.•Ice-water phase change near slip surface due to frictional heating is considered.•THM coupling, viscous drag and basal lubrication characterize motion of avalanches.•Initial temperature and porosity are significant for the motion of the avalanche.•Various controlling factors should be considered comprehensively, not separately.
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GEOZS, IJS, IMTLJ, KILJ, KISLJ, NLZOH, NUK, OILJ, PNG, SAZU, SBCE, SBJE, UILJ, UL, UM, UPCLJ, UPUK, ZAGLJ, ZRSKP
Stress uniformity within the gauge zone of a cruciform specimen significantly affects materials’ in-plane biaxial mechanical properties in material testing. The stress uniformity depends on the load ...transmission of the cruciform specimen from the fixtures to the gauge zone. Previous studies failed to alter the nature of the load transmission of the geometric features using parametric optimisations. To improve stress uniformity in the gauge zone, we optimised the cross-arms to design a centre-reduced cruciform specimen with topology and shape optimisations. The simulations show that the optimised specimen obtains significantly less stress variation and range in the gauge zone than the optimised specimen under different observed areas, directions, and load ratios of von Mises, S11, S22, and S12. In the quantified gauge zone, a more uniform stress distribution could be generated by optimizing specimen geometry, whose value should be estimated indirectly each time through simulations. We found that topology and shape optimisations could markedly improve stress uniformity in the gauge zone, and stress concentration at the cross-arms intersection. We first optimised the cruciform specimen structure by combining topology and shape optimisations, which provided a cost-effective way to improve stress uniformity in the gauge zone and reduce stress concentration at the cross-arms intersection, helping obtain reliable data to perform large strains in the in-plane biaxial tensile test.
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•Arsenic exposure caused a significant accumulation of autophagosomes in MLTC-1 cells.•Arsenic up-regulated autophagic markers including LC3, Atg7, Beclin1 and Vps34 ...expressions.•Arsenic enhanced the transcript levels of mTOR-downstream genes and Beclin1-Vps34/PI3K complex associated members.•Silencing of Beclin1, and inhibition of Vps34/PI3K and mTOR affected the As-induced autophagosomes formation.•Arsenic blocked autophagosomes degradation by impaired function of lysosomes.
Arsenic poisoning and induced potential lesion is a global concern. However, the exact mechanisms underlying its toxicity especially in male reproductive system still remain unclear. Hence, this study aimed to explore the roles of mTOR and Beclin1-Vps34/PI3K complex during As-induced-toxicity using Rapamycin (mTOR inhibitor), Beclin1 siRNA and 3-methyladenine (3-MA, Vps34/PI3K inhibitor) in testicular stromal cells. For this, mouse testis Leydig Tumor Cell lines (MLTC-1) were challenged with As2O3 (0, 3, 6 and 9 μM) exposure for 24 hs. Lyso-Tracker Red and Monodansylcadaverine (MDC) staining results depicted a significant accumulation of autophagosomes in MLTC-1 cells exposed to arsenic. Meanwhile, arsenic treatment up-regulated autophagic markers including LC3, Atg7, Beclin1 and Vps34 expressions, mTOR downstream autophagy related genes and the Beclin1-Vps34/PI3K complex associated members. Furthermore, silencing of Beclin1, and inhibition of Vps34/PI3K and mTOR altered the arsenic-induced autophagosomes formation. However, p62, the substrate protein of autophagy, was also up-regulated by arsenic administration independent on Beclin1-Vps34/PI3K complex. Altogether, our results revealed that arsenic exposure induced autophagosomes formation via regulation of the Beclin1-Vps34/PI3K complex and mTOR pathway; the blockage of autophagosomes degradation maybe due to impaired function of lysosomes. Thus, this study provides a novel mechanistic approach with respect to As-induced male reproductive toxicity.
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GEOZS, IJS, IMTLJ, KILJ, KISLJ, NLZOH, NUK, OILJ, PNG, SAZU, SBCE, SBJE, UILJ, UL, UM, UPCLJ, UPUK, ZAGLJ, ZRSKP
For the past decade, there has been an increased concern about the health risks from arsenic (As) exposure, because of its neurotoxic effects on the developing brain. The exact mechanism underlying ...As-induced neurotoxicity during sensitive periods of brain development remains unclear, especially the role of blood–brain barrier’s (BBB) tight junction (TJ) proteins during As-induced neurotoxicity. Here, we highlight the involvement of TJ proteins in As-induced autophagy in cerebral cortex and hippocampus during developmental periods postnatal day (PND) 21, 28, 35 and 42. Here, the administration of arsenic trioxide (As
2
O
3
) at doses of 0.15 mg or 1.5 mg or 15 mg As
2
O
3
/L in drinking water from gestational to lactational and continued to the pups till PND42 resulted in a significant decrease in the mRNA expression levels of TJ proteins (Occludin, Claudin, ZO-1 and ZO-2) and Occludin protein expression level. In addition, As exposure significantly decreased PI3K, Akt, mTOR, and p62 with a concomitant increase in Beclin1, LC3I, LC3II, Atg5 and Atg12. Moreover, As exposure also significantly downregulated the protein expression levels of mTOR with a concomitant upregulation of Beclin 1, LC3 and Atg12 in all the developmental age points. However, no significant alterations were observed in low and medium dose-exposed groups of PND42. Histopathological analysis in As-exposed mice revealed decreased number of pyramidal neurons in hippocampus; and neurons with degenerating axons, shrinkage of cells, remarkable vacuolar degeneration in cytoplasm, karyolysis and pyknosis in cerebral cortex. Ultrastructural analysis by transmission electron microscopy revealed the occurrence of autophagosomes and vacuolated axons in the cerebral cortex and hippocampus of the mice exposed to high dose As at PND21 and 42. The severities of changes were found to more persist in the cerebral cortex than in the hippocampus of As-exposed mice. Finally, we conclude that the leaky BBB in cerebral cortex and hippocampus may facilitate the transfer of As and induces autophagy by inhibiting PI3K/Akt/mTOR signaling pathway in an age-dependent manner, i.e., among the four different developmental age points, PND21 animals were found to be more vulnerable to the As-induced neurotoxicity than the other three age points.
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EMUNI, FIS, FZAB, GEOZS, GIS, IJS, IMTLJ, KILJ, KISLJ, MFDPS, NLZOH, NUK, OBVAL, OILJ, PNG, SAZU, SBCE, SBJE, SBMB, SBNM, UKNU, UL, UM, UPUK, VKSCE, ZAGLJ
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