Search

Granger causality-based effective brain connectivity provides a powerful tool to probe the neural mechanism for information processing and the potential features for brain computer interfaces. However, in real applications, traditional Granger causality is prone to the influence of outliers, such as inevitable ocular artifacts, resulting in unreasonable brain linkages and the failure to decipher inherent cognition states. In this work, motivated by constructing the sparse causality brain networks under the strong physiological outlier noise conditions, we proposed a dual Laplacian Granger causality analysis (DLap-GCA) by imposing Laplacian distributions on both model parameters and residuals. In essence, the first Laplacian assumption on residuals will resist the influence of outliers in electroencephalogram (EEG) on causality inference, and the second Laplacian assumption on model parameters will sparsely characterize the intrinsic interactions among multiple brain regions. Through simulation study, we quantitatively verified its effectiveness in suppressing the influence of complex outliers, the stable capacity for model estimation, and sparse network inference. The application to motor-imagery (MI) EEG further reveals that our method can effectively capture the inherent hemispheric lateralization of MI tasks with sparse patterns even under strong noise conditions. The MI classification based on the network features derived from the proposed approach shows higher accuracy than other existing traditional approaches, which is attributed to the discriminative network structures being captured in a timely manner by DLap-GCA even under the single-trial online condition. Basically, these results consistently show its robustness to the influence of complex outliers and the capability of characterizing representative brain networks for cognition information processing, which has the potential to offer reliable network structures for both cognitive studies and future brain–computer interface (BCI) realization.

Multichannel electroencephalogram (EEG) is an array signal that represents brain neural networks and can be applied to characterize information propagation patterns for different emotional states. To reveal these inherent spatial graph features and increase the stability of emotion recognition, we propose an effective emotion recognition model that performs multicategory emotion recognition with multiple emotion-related spatial network topology patterns (MESNPs) by learning discriminative graph topologies in EEG brain networks. To evaluate the performance of our proposed MESNP model, we conducted single-subject and multisubject four-class classification experiments on two public datasets, MAHNOB-HCI and DEAP. Compared with existing feature extraction methods, the MESNP model significantly enhances the multiclass emotional classification performance in the single-subject and multisubject conditions. To evaluate the online version of the proposed MESNP model, we designed an online emotion monitoring system. We recruited 14 participants to conduct the online emotion decoding experiments. The average online experimental accuracy of the 14 participants was 84.56%, indicating that our model can be applied in affective brain–computer interface (aBCI) systems. The offline and online experimental results demonstrate that the proposed MESNP model effectively captures discriminative graph topology patterns and significantly improves emotion classification performance. Moreover, the proposed MESNP model provides a new scheme for extracting features from strongly coupled array signals.

Despite the varied decision responses are revealed between adolescents with emotional stability and instability (ES and EI), the possible association underlying decision making and resting-state activity remains unknown. The study explored the potential relationship between the resting-state electroencephalogram network and decision responses when adolescents with different emotional stabilities participated in the ultimatum game (UG). A significant relationship between the resting-state activation of the two frequency bands (i.e., delta and alpha) and the UG acceptance rate. Furthermore, the ES adolescents mainly activated the frontal cortex in the delta band compared to the EI adolescents, whereas the EI adolescents exhibited stronger frontal-occipital linkages in the alpha band than the ES group. During decision making, the delta oscillation played a positive role in the cognitive process, while the alpha activity decreased. Finally, emotional stability could be predicted by a multivariable linear prediction model based on the resting-state metrics while adolescents made decisions in the UG task. The distinct resting-state electrophysiological evidence may deepen our knowledge of decision making in individuals with different emotional traits, which may further facilitate the prediction of individual decision behaviors.

Objective: The multivariate autoregression (MVAR) model is an effective model to construct brain causality networks. However, the accuracy of MVAR parameter estimation is considerably affected by outliers such as head movements and eye blinks contained in EEG signals, especially in short time windows. Methods: We proposed a robust MVAR parameter estimation method based on a Bayesian probabilistic framework and Laplace fitting error known as Lap-SBL. With the Bayesian inference framework, we can accurately estimate the MVAR parameters under short time windows. Additionally, to alleviate the influence of outliers, we model the fitting error using the Laplace distribution instead of the typical Gaussian distribution. We employ convex analysis to model the inference task by approximating the Laplace noise prior with a maximum over Gaussian functions with varying scales. The variational inference approach was used to efficiently estimate the MVAR parameters. Results: The numerical results suggest that the proposed method obtains less parameter estimation bias and more consistent linkages than existing benchmark methods, i.e., LS, LASSO, LAPPS and SBL. The motor imagery experimental data analysis shows that Lap-SBL can better describe the lateralization characteristics of brain network. This lateralization is less apparent in a subject with poor MI classification accuracy. Conclusion and significance: Lap-SBL effectively suppresses the influence of outliers and recovers reliable networks in the presence of outliers and short time windows.

Cr3+-doped phosphors are widely used in the near-infrared (NIR) phosphor-converted light-emitting diodes (pc-LEDs) for plant growth lighting in the modern agriculture due to their excellent luminous efficiency and spectral tunability. However, the inevitable energy consumption and heat radiation issues force us to shift our focus to develop a novel plant lighting pattern of energy storage activated by sunlight and NIR afterglow illumination at night. Herein, a series of Zn1-xMgxAl2-2xGa2xO4:Cr3+(ZMAGO:Cr3+) NIR persistent luminescence (PersL) phosphors, achieving a far-red emission at 675–775 nm upon 387 nm or 530 nm excitation is designed. The optimal ZMAGO:Cr3+(x = 0.6) phosphor exhibits a 194-fold initial NIR afterglow intensity and PersL decay time last for more than 6 h. The enhancement of afterglow originates from the introduction of effective electron traps, which can be precisely controlled by changing the Mg2+/Ga3+doping concentration. Meanwhile, by utilizing the photon transmission from SrAl2O4:Eu2+,Dy3+green phosphor to ZMAGO:Cr3+(x = 0.6) NIR phosphor, the prepared NIR coatings obtain 2.5 times enhanced PersL intensity and afterglow far more than 12 h by sunlight excitation, meeting the requirements of non-electrical excitation and round-the-clock plant lighting. The successful development of NIR coatings based on the ZMAGO:Cr3+phosphor is expected to accelerate the exploitation of next generation of intelligent and energy friendly light sources for indoor agriculture.

ABSTRACTBackgroundMen who have sex with men (MSM), a population bearing the greatest HIV burden in many countries, may also be vulnerable to COVID-19. COVID-19 vaccines are essential to containing the pandemic. However, vaccine hesitancy may compromise vaccine coverage. We aimed to understand the uptake of COVID-19 vaccine and factors associated with COVID-19 vaccine hesitancy among HIV-infected MSM in mainland China.MethodsA cross-sectional online survey among HIV-infected MSM was conducted between 13 and 21 February 2021 in mainland China. Variables including demographics, mental health status, HIV characteristics, and knowledge of and attitudes toward COVID-19 pandemic and COVID-19 vaccine were collected. Chi-square tests and multivariable logistic regression were used to analyze factors associated with COVID-19 vaccine hesitancy.ResultsA total of 1295 participants were included. The median age was 29.3 years (interquartile range [IQR] 25.2–34.0 years). The uptake of COVID-19 vaccine was 8.7%. Two main reasons for receiving vaccines were “regarded vaccination as self-health protection” (67.3%) and “trust in domestic medical technology” (67.3%). Among participants who did not initiate vaccination, concern about side effects (46.4%) and disclosure of HIV infection (38.6%) were top two reasons, and 47.2% had higher vaccine hesitancy. Men who had with high antiretroviral therapy (ART) adherence (adjusted odds ratio [aOR] 0.53, 95% confidence interval [CI] 0.35–0.80), often (0.26, 0.17–0.40) or sometimes (0.46, 0.31–0.67) paid attention to information about the COVID-19 vaccine, preferred domestic vaccines (0.37, 0.24–0.59), thought the pandemic had moderate (0.58, 0.38–0.90) and moderately severe or severe impact (0.54, 0.38–0.78) on immunity, who were waiting for vaccination programs organized at workplace (0.60, 0.44–0.81) and who were unaware of where to get COVID-19 vaccine (0.61, 0.45–0.82) had lower degree of COVID-19 vaccine hesitancy. Men who were concerned about the efficacy (1.72, 1.16–2.54) and side effects (2.44, 1.78–3.35) had higher degree of COVID-19 vaccine hesitancy.ConclusionCOVID-19 vaccine uptake among HIV-infected MSM is still suboptimal. Understanding influencing factors of vaccine hesitancy among this group and making tailored measures to alleviate hesitancy would help improve the coverage of COVID-19 vaccination in this population.

Developing bifunctional nanoplatforms integrating advanced biological imaging with high-performance therapeutic functions is interesting for nanoscience and biomedicine. Herein, thin-layered FePS3nanosheets modified with amine polyethylene glycol (FePS3-PEG) are synthesized by ultrasonicated exfoliation of bulk FePS3single crystals under Ar atmosphere and in situchemical functionalization with amine PEG. The prepared FePS3-PEG nanosheets give a photothermal conversion efficiency of 22.1% under 808-nm laser and evident T1relaxation (r1= 2.69 (mmol L−1)−1S−1) in external magnetic fields. Biologically experimental results in vitroand in vivodemonstrate that FePS3-PEG nanosheets have good biocompatibility and exhibit excellent photothermal therapy (PTT) effect under clear T1weighted magnetic resonance imaging (MRI). The characteristics of FePS3-PEG nanosheets enable them to be a promising nanomedicine for T1-weighted MRI-guided near-infrared PTT of cancers.

BackgroundMen who have sex with men (MSM) are disproportionately affected by HIV and other STIs worldwide. Rectal douching, which is commonly used by MSM in preparation for anal sex, may increase the risk of HIV and other STIs by injuring the rectal mucosa. Results from individual studies reporting associations between rectal douching and HIV and other STIs among MSM are inconsistent. We performed a systematic review and meta-analysis to estimate the association between rectal douching and HIV and other STIs among MSM.MethodsWe searched PubMed, Embase, Scopus and Web of Science for studies published from January 1970 to November 2018. Studies that reported ORs and 95% CIs of associations between rectal douching and infection with HIV/STIs, or reported enough data to calculate these estimates, were included. We assessed risk of bias using the Newcastle-Ottawa Scale. ORs were pooled using a random effects model.ResultsTwenty-eight eligible studies were identified in our review, of which 24 (20 398 participants) were included in the meta-analysis. Rectal douching was associated with increased odds of infection with HIV (OR 2.80, 95% CI 2.32 to 3.39), and any STI other than HIV (including hepatitis B virus (HBV), hepatitis C virus (HCV), chlamydia, gonorrhoea, syphilis and human papillomavirus) (OR 2.46, 95% CI 1.95 to 3.11) among MSM. For specific STIs, douching was associated with increased odds of viral hepatitis (HBV, HCV) (OR 3.29, 95% CI 2.79 to 3.87), and chlamydia or gonorrhoea (OR 3.25, 95% CI 2.02 to 5.23). These associations remained significant in studies that adjusted for potential confounders.ConclusionRectal douching may put MSM at increased risk for infection with HIV and other STIs. Longitudinal studies are needed to clarify this association, and health education materials should inform men of the potential for increased risk of infection with rectal douching.

Porous composite pressure sensors have the advantage of a wide deformation range owing to their structural characteristics. It is one of the building blocks for wearable intelligent devices and systems. Conductor‐coated porous composites (CCPCs), consisting of a conductive coating and an insulating elastomeric skeleton, exhibit low modulus, high compressibility, and a facile fabrication process. Pressure sensors developed based on CCPCs provide specific intelligent wearable sensor applications, including high‐resolution pressure detection and multimodal sensing under extremely compressing environments. Here, representative works on the fabrication, performance, and applications of CCPC devices are reviewed. The “state‐of‐the‐art” compilation of the most sophisticated design strategy of CCPCs with durable, low hysteresis, high sensitivity, and wide detection range is summarized, which also ensures instructive significance for the design of other pressure devices based on soft matter and rigid conductors. Finally, the intelligent device and system scenarios of CCPC devices are introduced. Porous composite sensors have the advantage of a wide deformation range owing to their structural characteristics. Conductor‐coated porous composites (CCPCs), consisting of a conductive coating and an insulating elastomeric skeleton, exhibit high compressibility and a facile fabrication process. Here, representative works on the fabrication, performance, and applications of CCPC devices are reviewed. The “state‐of‐the‐art” compilation of the most sophisticated design strategy of CCPCs with durable, low hysteresis, high sensitivity, and wide detection range is summarized.

Conductor‐Coated Porous Composites In article number 2200091, Fuwen Shi, Xing Wu, and co‐workers discuss the “state‐of‐the‐art” compilation of the most sophisticated design strategies of conductor‐coated porous composites, which are considered excellent choices for sensitive layers of the next‐generation electronic skin.

Human papillomavirus (HPV) infection and related diseases are common among men who have sex with men (MSM). The most effective prevention is HPV vaccination. In China, however, men are not included in the HPV vaccination plan. We investigated the intention to initiate HPV vaccination and associated factors among MSM in China. Methods We surveyed 563 unvaccinated MSM aged 18 or older from six cities in China. Participants completed an electronic questionnaire about demographics, knowledge of and attitude towards HPV and HPV vaccine, intention to initiate HPV vaccination, willingness to recommend HPV vaccine to peers, feeling about government policy about HPV vaccination. We used the structural equation modeling (SEM) to analyze factors associated with HPV vaccine intention. Results The knowledge of HPV and HPV vaccine among participants was low. The mean score of knowledge about HPV and HPV vaccine was only 1.59 (range 0–11). The intention to initiate HPV vaccination within 6 months among participants was moderate (43.3% in total, 18.1% for ‘very high' and 25.2% for ‘above average').

Indoor formaldehyde (HCHO) is an important air pollutant, while it is very difficult to reduce HCHO to low-level (e.g. <0.08 mg/m3). Catalytic oxidation at ambient temperature has been increasingly recognized as one of the important methods to mitigate HCHO pollution due to its good effectiveness, stability, and recyclability. To further improve the activity of catalytic oxidation, this study develops the integrated MnCeOxcatalysts supported on palygorskite (Pal) and aluminium hydroxide (Al(OH)3). Our results indicate that the synergistic interaction in MnCeOxthrough the oxygen transfer mechanism from the oxygen reservoir CeO2to MnOxsignificantly improves the activity. Pal, Al(OH)3, etc. were applied as the supports with a focus on their dispersion, microstructure, strength, and relative role. MnCeOxcan be anchored on the surface of Al(OH)3with high dispersion. With the integrated catalyst, HCHO decreases from 1.012 to 0.086 mg/m3within 48 h. Higher oxidation activity of MnCeOxpowder may be ascribed to the amount of active components on the surface. The incorporation of ZSM–5 and activated carbon can improve the adsorption of HCHO, and all integrated catalysts exhibit stronger activities, with HCHO being degraded to the level lower than 0.08 mg/m3. Meantime, the samples exhibited good stability and strength (20.2 MPa) without obvious decreasing over five consecutive stability experiments.