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Recently, deep learning-based models such as transformer have achieved significant performance for industrial remaining useful life (RUL) prediction due to their strong representation ability. In many industrial practices, RUL prediction algorithms are deployed on edge devices for real-time response. However, the high computational cost of deep learning models makes it difficult to meet the requirements of edge intelligence. In this article, a lightweight group transformer with multihierarchy time-series reduction (GT-MRNet) is proposed to alleviate this problem. Different from most existing RUL methods computing all time series, GT-MRNet can adaptively select necessary time steps to compute the RUL. First, a lightweight group transformer is constructed to extract features by employing group linear transformation with significantly fewer parameters. Then, a time-series reduction strategy is proposed to adaptively filter out unimportant time steps at each layer. Finally, a multihierarchy learning mechanism is developed to further stabilize the performance of time-series reduction. Extensive experimental results on the real-world condition datasets demonstrate that the proposed method can significantly reduce up to 74.7% parameters and 91.8% computation cost without sacrificing accuracy.
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Inverse Anderson transitions, where the flat-band localization is destroyed by disorder, have been wildly investigated in quantum and classical systems in the presence of Abelian gauge fields. Here, we report the first investigation on inverse Anderson transitions in the system with non-Abelian gauge fields. It is found that pseudospin-dependent localized and delocalized eigenstates coexist in the disordered non-Abelian Aharonov-Bohm cage, making inverse Anderson transitions depend on the relative phase of two internal pseudospins. Such an exotic phenomenon induced by the interplay between non-Abelian gauge fields and disorder has no Abelian analogy. Furthermore, we theoretically design and experimentally fabricate non-Abelian Aharonov-Bohm topolectrical circuits to observe the non-Abelian inverse Anderson transition. Through the direct measurements of frequency-dependent impedance responses and voltage dynamics, the pseudospin-dependent non-Abelian inverse Anderson transitions are observed. Our results establish the connection between inverse Anderson transitions and non-Abelian gauge fields, and thus comprise a new insight on the fundamental aspects of localization in disordered non-Abelian flat-band systems.
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Introduction: The detrimental effects of sleep deprivation (SD) on cognitive function and quality of life are well known, and sleep disturbances are a major physical and mental health issue worldwide. Working memory plays an important role in many complex cognitive processes. Therefore, it is necessary to identify strategies that can effectively counteract the negative effects of SD on working memory. Methods: In the present study, we utilized event-related potentials (ERPs) to investigate the restorative effects of 8 h of recovery sleep (RS) on working memory impairments induced by total sleep deprivation for 36 h. We analyzed ERP data from 42 healthy male participants who were randomly assigned to two groups. The nocturnal sleep (NS) group completed a 2-back working memory task before and after normal sleep for 8 h. The sleep deprivation (SD) group completed a 2-back working memory task before and after 36 h of total sleep deprivation (TSD) and after 8 h of RS. Electroencephalographic data were recorded during each task. Results: The N2 and P3 components-which are related to working memory-exhibited low-amplitude and slow-wave characteristics after 36 h of TSD. Additionally, we observed a significant decrease in N2 latency after 8 h of RS. RS also induced significant increases in the amplitude of the P3 component and in the behavioral indicators. Discussion: Overall, 8 h of RS attenuated the decrease in working memory performance caused by 36 h of TSD. However, the effects of RS appear to be limited.
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Representation learning-based remaining useful life (RUL) prediction plays a crucial role in improving the security and reducing the maintenance cost of complex systems. Despite the superior performance, the high computational cost of deep networks hinders deploying the models on low-compute platforms. A significant reason for the high cost is the computation of representing long sequences. In contrast to most RUL prediction methods that learn features of the same sequence length, we consider that each time series has its characteristics and the sequence length should be adjusted adaptively. Our motivation is that an "easy" sample with representative characteristics can be correctly predicted even when short feature representation is provided, while "hard" samples need complete feature representation. Therefore, we focus on sequence length and propose a dynamic length transformer (DLformer) that can adaptively learn sequence representation of different lengths. Then, a feature reuse mechanism is developed to utilize previously learned features to reduce redundant computation. Finally, in order to achieve dynamic feature representation, a particular confidence strategy is designed to calculate the confidence level for the prediction results. Regarding interpretability, the dynamic architecture can help human understand which part of the model is activated. Experiments on multiple datasets show that DLformer can increase up to 90% inference speed, with less than 5% degradation in model accuracy.
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Spatial cognition facilitates the successful completion of specific cognitive tasks through lateral processing and neuroplasticity. Long-term training in table tennis induces neural processing efficiency in the visuospatial cognitive processing cortex of athletes. However, the lateralization characteristics and neural mechanisms of visual−spatial cognitive processing in table tennis players in non-sport domains are unclear. This study utilized event-related potentials to investigate differences in the spatial cognition abilities of regular college students (controls) and table tennis players. A total of 48 participants (28 controls; 20 s-level national table tennis players) completed spatial cognitive tasks while electroencephalography data were recorded. Task performance was better in the table tennis group than in the control group (reaction time: P < 0.001; correct number/sec: P = 0.043), P3 amplitude was greater in the table tennis group (P = 0.040), spatial cognition showed obvious lateralization characteristics (P < 0.001), table tennis players showed a more obvious right-hemisphere advantage, and the P3 amplitude in the right hemisphere was significantly greater in table tennis athletes than in the control group. (P = 0.044). Our findings demonstrate a right-hemisphere advantage in spatial cognition. Long-term training strengthened the visual−spatial processing ability of table tennis players, and this advantage effect was reflected in the neuroplasticity of the right hemisphere (the dominant hemisphere for spatial processing).
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An amputation is known to seriously affect patient quality of life. This study aimed to investigate changes in neural activity in amputees during the postoperative period using neural electrophysiological techniques. In total, 14 patients with left lower limb amputation and 18 healthy participants were included in our study. All participants were required to perform motor imagery paradigm tasks while electroencephalogram (EEG) data were recorded. Data analysis results indicated that the beta frequency band showed significantly decreased oscillatory activity in motor imaging-related brain regions such as the frontal lobe and the precentral and postcentral gyri in amputees. Furthermore, the functional independent component analysis (fICA) value of neural oscillation negatively correlated with the C4 electrode power value of the motor imagery task in amputees (p < 0.05). Therefore, changes in neural oscillations and beta frequency band in motor imagery regions may be related to brain remodeling in amputees.
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To study the mechanical deformation characteristics and anti-explosion mechanisms of steel-structure protective doors under chemical explosion shock wave loads, numerical simulations of loads and door damage were carried out using the AUTODYN and LS-DYNA software based on model tuning with actual field test results. The finite element simulation results were compared with the test results to verify the accuracy of the simulation model and material parameters. A parametric analysis was carried out on the influencing factors of the anti-explosion performance of the beam-plate steel structure protective door under typical shock wave loads. The impact of the material strength and geometry of each part of the protective door on its anti-explosion performance was studied. The results showed that the protective door sustained a uniform shock wave load and that increasing the steel strength of the skeleton could significantly reduce the maximum response displacement of the protective door. The steel strength increase of the inner and outer panels had little or a negligible effect on the anti-explosion performance of the protective door. The geometric dimensions of different parts of the protective door had different effects on the anti-explosion performance. Increasing the skeleton height had the most significant effect on the anti-explosion performance. The skeleton's I-steel flange thickness and the inner and outer panel thicknesses had less significant effects.
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The default mode network (DMN) has a unique activity pattern in the resting brain. Studies on resting-state brain activity are helpful to identify various brain dynamic characteristics of patients with mental diseases and those of healthy people. The brain produces a series of changes in different eye states. However, the relationship between eye states and the DMN, which is closely related to the resting state, has not been widely examined. This study recruited 42 healthy students aged 17-22. Participants completed the Profile of Mood States questionnaire. Thereafter, the electroencephalogram data was collected with the patients' eyes open and closed. Changes in neural oscillation and the DMN's information transmission during different eye openness states were compared. The results showed that the neural oscillation activities of the parietal-occipital network such as the superior parietal lobule and precuneus were significantly enhanced in the eyes open state. In addition, the effective connectivity within the DMN was enhanced during opened eyes, especially from the left precuneus to the left posterior cingulate cortex, and this connectivity was negatively correlated with the Vigor-Activity mood state in the eyes open state. The activity of the DMN in the resting-state is regulated by eye states, which may relate to mood and emotional perception.
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Bloch oscillations are exotic phenomena describing the periodic motion of a wave packet subjected to an external force in a lattice, where a system possessing single or multiple particles could exhibit distinct oscillation behaviors. In particular, it has been pointed out that quantum statistics could dramatically affect the Bloch oscillation even in the absence of particle interactions, where the oscillation frequency of two pseudofermions with an anyonic statistical angle of [Formula: see text] becomes half of that for two bosons. However, these statistically dependent Bloch oscillations have never been observed in experiments until now. Here, we report the experimental simulation of anyonic Bloch oscillations using electric circuits. By mapping the eigenstates of two anyons to the modes of the designed circuit simulators, the Bloch oscillations of two bosons and two pseudofermions are verified by measuring the voltage dynamics. The oscillation period in the two-boson simulator is almost twice of that in the two-pseudofermion simulator, that is consistent with the theoretical prediction. Our proposal provides a flexible platform to investigate and visualize many interesting phenomena related to particle statistics and could have potential applications in the field of the signal control.
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Working memory functions are known to be altered after total sleep deprivation (TSD). However, few studies have explored the deficits of working memory updating (WMU) after TSD, or the underlying electrophysiological mechanisms of these alterations. In the current exploratory study, we enrolled 14 young male volunteers who performed two kinds of WMU tasks-spatial and object two-back tasks-with simultaneous electroencephalography recordings under two sleep conditions: a normal sleep baseline condition and after 36 h of TSD. Repeated-measures analysis of variance showed that compared with those at baseline, the rates of correct responses in the WMU tasks decreased significantly after TSD. Analysis of event-related potentials revealed that the average amplitude of P3 components decreased significantly in the frontal and central brain regions and increased significantly in the parietal brain regions. Our findings suggest that TSD damages WMU behavior, impairs cognitive functions in the frontal and central brain regions, and triggers greater activation in the parietal brain regions. This is the first study to report the existence of event-related compensatory neural activity. This event-related compensatory effect may provide a new perspective for understanding the mechanisms underlying the influences triggered by sleep loss.
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Sleep loss not only compromises individual physiological functions but also induces a psychocognitive decline and even impairs the motor control and regulatory network. In this study, we analyzed whole-brain functional connectivity changes in the putamen and caudate nucleus as seed points in the neostriatum after 36 h of complete sleep deprivation in 30 healthy adult men by resting state functional magnetic resonance imaging to investigate the physiological mechanisms involved in impaired motor control and regulatory network in individuals in the sleep-deprived state. The functional connectivity between the putamen and the bilateral precentral, postcentral, superior temporal, and middle temporal gyrus, and the left caudate nucleus and the postcentral and inferior temporal gyrus were significantly reduced after 36 h of total sleep deprivation. This may contribute to impaired motor perception, fine motor control, and speech motor control in individuals. It may also provide some evidence for neurophysiological changes in the brain in the sleep-deprived state and shed new light on the study of the neostriatum in the basal ganglia.
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This study aimed to analyze the effect of lactobacillus johnsonii BS15 (isolation of homemade yogurt from Ahu Hongyuan Grassland) combined with abdominal massage on intestinal permeability in rats with nonalcoholic fatty liver disease (NAFLD) and cell biofilm repair. Forty-five rats were divided randomly into five groups, four of which were fed with high-fat diet to establish NAFLD models. According to the treatment methods, they were grouped into group A (lactic acid bacteria feeding), group B (abdominal massage), group A + B (a combination of the two methods), model group (distilled water feeding), and normal group (distilled water feeding). Then, the pathological indexes of liver and intestinal permeability were observed. FITC-Dextran content of the model group elevated markedly compared with normal group (P < 0.01), indicating that the intestinal permeability of NAFLD rats fed with high-fat diet increased. The intestinal permeability of groups A, B, and A + B was lower sharply than that of model group (P < 0.01), and the effect of group A + B was the most obvious. HE staining of liver tissues showed that combined treatment could improve structural changes in liver cells caused by modeling and restore the normal structure of intestinal cells. Lactobacillus combined with abdominal massage was better than two treatments alone, further promoting the permeability of intestinal mucosa in NAFLD rats and repair biofilm of hepatocytes. The results initially verified the intervention effect of abdominal massage on intestinal mucosal permeability, and further revealed the mechanism of abdominal massage in treatment of NAFLD by improving intestinal mucosal barrier permeability.
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Absorção Gastrointestinal/fisiologia , Lactobacillus johnsonii , Massagem , Hepatopatia Gordurosa não Alcoólica , Animais , Biofilmes , Dieta Hiperlipídica , Mucosa Intestinal/metabolismo , Fígado/metabolismo , Fígado/patologia , Masculino , Hepatopatia Gordurosa não Alcoólica/metabolismo , Hepatopatia Gordurosa não Alcoólica/patologia , Ratos , Ratos Sprague-DawleyRESUMO
Homeostatic sleep pressure can cause cognitive impairment, in which executive function is the most affected. Previous studies have mainly focused on high homeostatic sleep pressure (long-term sleep deprivation); thus, there is still little related neuro-psycho-physiological evidence based on low homeostatic sleep pressure (12 h of continuous wakefulness) that affects executive function. This study aimed to investigate the impact of lower homeostatic sleep pressure on executive function. Our study included 14 healthy young male participants tested using the Go/NoGo task in normal resting wakefulness (10:00 am) and after low homeostatic sleep pressure (10:00 pm). Behavioral data (response time and accuracy) were collected, and electroencephalogram (EEG) data were recorded simultaneously, using repeated measures analysis of variance for data analysis. Compared with resting wakefulness, the participants' response time to the Go stimulus was shortened after low homeostatic sleep pressure, and the correct response rate was reduced. Furthermore, the peak amplitude of Go-P2 decreased significantly, and the peak latency did not change significantly. For NoGo stimulation, the peak amplitude of NoGo-P2 decreased significantly (p < 0.05), and the peak latency was significantly extended (p < 0.05). Thus, the P2 wave is likely related to the attention and visual processing and reflects the early judgment of the perceptual process. Therefore, the peak amplitude of Go-P2 and NoGo-P2 decreased, whereas the peak latency of NoGo-P2 increased, indicating that executive function is impaired after low homeostatic sleep pressure. This study has shown that the P2 wave is a sensitive indicator that reflects the effects of low homeostatic sleep pressure on executive function, and that it is also an important window to observe the effect of homeostatic sleep pressure and circadian rhythm on cognitive function.
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Total sleep deprivation (TSD) negatively affects cognitive function. Previous research has focused on individual variation in cognitive function following TSD, but we know less about how TSD influences the lateralization of spatial working memory. This study used event-related-potential techniques to explore asymmetry in spatial-working-memory impairment. Fourteen healthy male participants performed a two-back task with electroencephalogram (EEG) recordings conducted at baseline and after 36 h of TSD. We selected 12 EEG points corresponding to left and right sides of the brain and then observed changes in N2 and P3 components related to spatial working memory. Before TSD, P3 amplitude differed significantly between the left and right sides of the brain. This difference disappeared after TSD. Compared with baseline, P3 amplitude decreased for a duration as extended as the prolonged latency of N2 components. After 36 h of TSD, P3 amplitude decreased more in the right hemisphere than the left. We therefore conclude that TSD negatively affected spatial working memory, possibly through removing the right hemisphere advantage.
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Hydrophobic graphene-based material at the nanoscale was prepared by treatment of exfoliated graphene oxide with organic isocyanates. The lipophilic modified graphene oxide (LMGO) can then be exfoliated into the functionalized graphene nanoplatelets that can form a stable dispersion in polar aprotic solvents. AFM image shows the thickness of LMGO is approximately 1 nm. Characterization of LMGO by elemental analysis suggested that the chemical treatment results in the functionalization of the carboxyl and hydroxyl groups in GO via formation of amides and carbamate esters, respectively. The degree of GO functionalization can be controlled via either the reactivity of the isocyanate or the reaction time. Then we investigated the thermal properties of the SPFGraphene by using thermogravimetric analysis (TGA) and differential scanning calorimetry (DSC), the TGA curve shows a greater weight loss of approximately 20% occurred indicating removal of functional groups from the LMGO sheets and an obvious exothermic peak at 176 degrees can be observed from 150 to 250 degrees. We also compared the structure of graphene oxide with the structure of chemical treated graphene oxide by FT-IR spectroscopy. The morphology and microstructure of the LMGO nanosheets were also characterized by SEM and XRD. Graphene can be used to fabricate a wide range of simple electronic devices such as field-effect transistors, resonators, quantum dots and some other extensive industrial manufacture such as super capacitor, li ion battery, solar cells and even transparent electrodes in device applications.
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We prepared the exfoliation of graphite, which was necessary for the production of graphene sheets that are desirable for the fabrication of nano-composites. Then a Solution-Processable Functionalized Graphene (SPFGraphene) with functionalization groups doped with P3HT hybrid thin film-based organic photovoltaic cells (OPVCs) was systematically identified using a general device structure of, ITO/PEDOT:PSS/P3HT:SPFGraphene/LiF/Al. The effect of annealing on the photoelectric properties of the SPFGraphene was analyzed by Fourier transform infrared FT-IR spectroscopy and solar cell performance. After treatment at different annealing temperatures, with an increase in the SPFGraphene content, the short-circuit current density J(SC) and power conversion efficiency PCE of the hybrid devices increased first, reaching the peak efficiency for the 10 wt% SPFGraphene content, and then decreased. After annealing at 160 degrees C, the device containing 10 wt% SPFGraphene showed the open-circuit voltage V(OC) of 0.73 V, the J(SC) value of 3.98 mA cm(-2), fill factor (FF) value of 0.36, the PCE value of 1.046%. After thermal annealing at 210 degrees C, with the removal of the functional groups and recovery of the pi-conjugated areas, the conductivity of the graphene sheet and the charge carrier-transport mobility increased greatly, the J(SC) value of the 10 wt% SPFGraphene content device increased to 4.2 mA cm(-2), the V(OC) value decreased to 0.59 V, which may be attributed to the altered work-function value of the functionalized graphene and low quasi-Fermi levels for electrons and holes, the FF value was 0.27, and the PCE was 0.669%, which is lower than the former one. The results indicated that annealing at the appropriate temperature can improve the device performance greatly, and the functionalized graphene is expected to be a competitive candidate in organic photovoltaic applications because it is soluble, cheap, easily prepared, stable, and inert against the ambient conditions.
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Graphene oxide (GO) of approximately 1 nm was generated from exfoliated graphitic oxide using a modified Hummers method through ultrasonic treatment in water, and the GO film was reduced under protection of Ar/H2 flow at 800 degrees C. Moreover, the obtained graphene film has a high conductivity of 383 S/cm at 10-20 nm thickness.
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We report the optoelectronic properties occurring in solution-processable functionalized graphene (SPFGraphene)-PCBM/poly(3-octylthiophene) (P3OT) composites. The structural configuration of the devices is ITO/PEDOT:PSS/P3OT:PCBM-SPFGraphene/LiF/Al. The best results were obtained with a P3OT/PCBM (1:1) mixture with 8 wt% of SPFGraphene in an open-circuit voltage (V(OC)) of 0.65 V, a short-circuit current density (J(SC)) of 4.2 mA/cm2, and a fill factor (FF) of 0.35, which led to a power conversion efficiency of 0.95% at illumination at 100 mW/cm2 AM 1.5. In the P3OT:PCBM-SPFGraphene composite, the SPFGraphene acted as exciton dissociation sites and provided the transport pathway of the lowest unoccupied molecular orbital (LUMO)-graphene-Al. Doping SPF-Graphene into P3OT resulted in appropriate energetic distance between the highest occupied molecular orbital (HOMO) and LUMO of the donor/acceptor for a high open circuit voltage and provided higher exciton dissociation volume mobility of carrier transport for a large short-circuit current density.