Search

Abstract Heterojunctions play a crucial role in improving the absorption of visible light and performance of photocatalysts for organic contaminants degradation in water. In this work, a novel type-II–II Ag2CO3/Bi2WO6 (AB) heterojunction was synthesized by hydrothermal reaction and in situ-precipitation methods. The mechanisms of charge transfer and carrier separation at the interface of heterojunctions and the influence on the photocatalytic activity were investigated. The degradation of levofloxacin (LEV) under visible light irradiation was employed to evaluate the photocatalytic performance of AB. The results showed that 85.4% LEV was degraded by AB, which was 1.38 and 1.39 times higher than that of Bi2WO6 and Ag2CO3, respectively. The work functions of the different crystal planes in the AB heterojunction, which was calculated by density functional theory, are a significant difference. The Fermi energy (E f) of Ag2CO3 (− 6.005 eV) is lower than Bi2WO6 (− 3.659 eV), but the conduction band (CB) is higher. Therefore, using AB heterojunctions as an example, the research explored the mechanism of type-II–II which CB and E f of one semiconductor cannot simultaneously surpass those of another material, based on the built-in electric field theory. Through this analysis, a deeper understanding of type-II heterojunctions was achieved, and providing valuable insights into the behavior of this specific heterojunction system.

Abstract Data clustering has attracted the interest of scholars in many fields. In recent years, using heuristic algorithms to solve data clustering problems has gradually become a tendency. The black hole algorithm (BHA) is one of the popular heuristic algorithms among researchers because of its simplicity and effectiveness. In this paper, an improved self-adaptive logarithmic spiral path black hole algorithm (SLBHA) is proposed. SLBHA innovatively introduces a logarithmic spiral path and random vector path to BHA. At the same time, a parameter is used to control the randomness, which enhances the local exploitation ability of the algorithm. Besides, SLBHA designs a replacement mechanism to improve the global exploration ability. Finally, a self-adaptive parameter is introduced to control the replacement mechanism and maintain the balance between exploration and exploitation of the algorithm. To verify the effectiveness of the proposed algorithm, comparison experiments are conducted on 13 datasets creatively using the evaluation criteria including the Jaccard coefficient as well as the Folkes and Mallows index. The proposed methods are compared with the selected algorithms such as the whale optimization algorithm (WOA), compound intensified exploration firefly algorithm (CIEFA), improved black hole algorithm (IBH), etc. The experimental results demonstrate that the proposed algorithm outperforms the compared algorithms on both external criteria and quantization error of the clustering problem.

Although three-dimensional visual training (3DVT) has been used for myopia intervention, its neural mechanisms remain largely unknown. In this study, visual function was examined before and after 3DVT, while resting-state EEG-fNIRS signals were recorded from 38 myopic participants. A graph theoretical analysis was applied to compute the neurovascular properties, including static brain networks (SBNs), dynamic brain networks (DBNs), and dynamic neurovascular coupling (DNC). Correlations between the changes in neurovascular properties and the changes in visual functions were calculated. After 3DVT, the local efficiency and node efficiency in the frontal lobes increased in the SBNs constructed from EEG $\delta $ -band; the global efficiency and node efficiency in the frontal-parietal lobes decreased in the DBNs variability constructed from EEG $\delta $ -band. For the DNC constructed with EEG $\alpha $ -band and oxyhemoglobin (HbO), the local efficiency decreased, for EEG $\alpha $ -band and deoxyhemoglobin (HbR), the node efficiency in the frontal-occipital lobes decreased. For the SBNs constructed from HbO, the functional connectivity (FC) between the frontal-occipital lobes increased. The DNC constructed between the FC of the frontal-parietal lobes from EEG $\beta $ -band and the FC of the frontal-occipital lobes from HbO increased, and between the FC of the frontal-occipital lobes from EEG $\beta $ -band and the FC of the inter-frontal lobes from HbR increased. The neurovascular properties were significantly correlated with the amplitude of accommodation and accommodative facility. The result indicated the positive effects of 3DVT on myopic participants, including improved efficiency of brain networks, increased FC of SBNs and DNC, and enhanced binocular accommodation functions.

Based on the principles of biomimicry, evolutionary algorithms (EAs) have been widely applied across diverse domains to tackle practical challenges. However, the inherent limitations of these algorithms call for further refinement to strike a delicate balance between global exploration and local exploitation. Thus, this paper introduces a novel multi-strategy enhanced hybrid algorithm called MHWACO, which integrates a Whale Optimization Algorithm (WOA) and Ant Colony Optimization (ACO). Initially, MHWACO employs Gaussian perturbation optimization for individual initialization. Subsequently, individuals selectively undertake either localized exploration based on the refined WOA or global prospecting anchored in the Golden Sine Algorithm (Golden-SA), determined by transition probabilities. Inspired by the collaborative behavior of ant colonies, a Flight Ant (FA) strategy is proposed to guide unoptimized individuals toward potential global optimal solutions. Finally, the Gaussian scatter search (GSS) strategy is activated during low population activity, striking a balance between global exploration and local exploitation capabilities. Moreover, the efficacy of Support Vector Regression (SVR) and random forest (RF) as regression models heavily depends on parameter selection. In response, we have devised the MHWACO-SVM and MHWACO-RF models to refine the selection of parameters, applying them to various real-world problems such as stock prediction, housing estimation, disease forecasting, fire prediction, and air quality monitoring. Experimental comparisons against 9 newly proposed intelligent optimization algorithms and 9 enhanced algorithms across 34 benchmark test functions and the CEC2022 benchmark suite, highlight the notable superiority and efficacy of MSWOA in addressing global optimization problems. Finally, the proposed MHWACO-SVM and MHWACO-RF models outperform other regression models across key metrics such as the Mean Bias Error (MBE), Coefficient of Determination (R2), Mean Absolute Error (MAE), Explained Variance Score (EVS), and Median Absolute Error (MEAE).

Abstract Conflict monitoring and processing are crucial components of the human cognitive system, with significant implications for daily life and the diagnosis of cognitive disorders. The Stroop task, combined with brain function detection technology, has been widely employed as a classical paradigm for investigating conflict processing. However, there remains a lack of public datasets that integrate Electroencephalogram (EEG) and functional Near-infrared Spectroscopy (fNIRS) to simultaneously record brain activity during a Stroop task. We introduce a dual-modality Stroop task dataset incorporating 34-channel EEG (sampling frequency is 1000 Hz) and 20-channel high temporal resolution fNIRS (sampling frequency is 100 Hz) measurements covering the whole frontal cerebral cortex from 21 participants (9 females/12 males, aged 23.0 ± 2.3 years). Event-related potential analysis of EEG recordings and activation analysis of fNIRS recordings were performed to show the significant Stroop effect. We expected that the data provided would be utilized to investigate multimodal data processing algorithms during cognitive processing.

In recent years, biomedical optics technology has developed rapidly. The current widespread use of biomedical optics was made possible by the invention of optical instruments. The advantages of being non-invasive, portable, effective, low cost, and less susceptible to system noise have led to the rapid development of functional near-infrared spectroscopy (fNIRS) technology for hemodynamics detection, especially in the field of functional brain imaging. At the same time, laboratories and companies have developed various fNIRS-based systems. The safety, stability, and efficacy of fNIRS systems are key performance indicators. However, there is still a lack of comprehensive and systematic evaluation methods for fNIRS instruments. This study uses the fNIRS system developed in our laboratory as the test object. The test method established in this study includes system validation and performance testing to comprehensively assess fNIRS systems' reliability. These methods feature low cost and high practicality. Based on this study, existing or newly developed systems can be comprehensively and easily evaluated in the laboratory or workspace.

IntroductionConflict monitoring and processing is an important part of the human cognitive system, it plays a key role in many studies of cognitive disorders.MethodsBased on a Chinese word-color match Stroop task, which included incongruent and neutral stimuli, the Electroencephalogram (EEG) and functional Near-infrared Spectroscopy (fNIRS) signals were recorded simultaneously. The Pearson correlation coefficient matrix was calculated to analyze brain connectivity based on EEG signals. Granger Causality (GC) method was employed to analyze the effective connectivity of bilateral frontal lobes. Wavelet Transform Coherence (WTC) was used to analyze the functional connectivity of the bilateral hemisphere and ipsilateral hemisphere.ResultsResults indicated that brain connectivity analysis on EEG signals did not show any significant lateralization, while fNIRS analysis results showed the frontal lobes especially the left frontal lobe play the leading role in dealing with conflict tasks. The human brain shows leftward lateralization while processing the more complicated incongruent stimuli. This is demonstrated by the higher functional connectivity in the left frontal lobe and the information flow from the left frontal lobe to the right frontal lobe.DiscussionOur findings in brain connectivity during cognitive conflict processing demonstrated that the dual modality method combining EEG and fNIRS is a valuable tool to excavate more information through cognitive and physiological studies.

In this submission, we report a maximum 638-W fiberized chirped-pulse-amplification (CPA) laser system with a bulk reflection grating compressor. The system is able to emit 338-W compressed pulses of 624 fs centered at 1 µm, corresponding to a pulse energy of 1.3 µJ at a pulse repetition rate of 258 MHz. The output beam quality factor M2 is measured to be

Abstract Formation flight of unmanned aerial vehicles (UAVs) utilizes reconfiguration procedures to handle a variety of emergencies, such as collision avoidance, malfunctions, fuel savings, and member replacement. As UAVs have limited computing power and energy resources, it is necessary to optimize the control inputs to reduce the distance travelled by UAVs while reducing the computing costs during formation reconfiguration. In this paper, the problem of multi-UAV reconfiguration is decoupled into two stages: task assignment and control input optimization of UAVs. For a solution to the above problem, we propose an adaptive hybrid particle swarm optimization and differential evolution algorithm (AHPSODE) to optimize minimize the distance of the total movement and reduce the computing cost of formation reconfiguration. Based on the idea of receding horizon control (RHC) and the nonlinear model of multi-UAV formation reconfiguration, an RHC controller using AHPSODE is designed to optimize the control input of the UAV group to obtain the shortest movement distance, and this method can reduce the computation time. We use the CEC 2017 test suit to test the performance of our proposed AHPSODE algorithm, and simulate the AHPSODE-based RHC controller to manage formation reconfiguration. The results show that our proposed AHPSODE performed well in convergence and accuracy and the RHC controller is effective.

IntroductionHuman language allows us to generate an infinite number of linguistic expressions. It’s proposed that this competence is based on a binary syntactic operation, Merge, combining two elements to form a new constituent. An increasing number of recent studies have shifted from complex syntactic structures to two-word constructions to investigate the neural representation of this operation at the most basic level.MethodsThis fMRI study aimed to develop a highly flexible artificial grammar paradigm for testing the neurobiology of human syntax at a basic level. During scanning, participants had to apply abstract syntactic rules to assess whether a given two-word artificial phrase could be further merged with a third word. To control for lower-level template-matching and working memory strategies, an additional non-mergeable word-list task was set up.ResultsBehavioral data indicated that participants complied with the experiment. Whole brain and region of interest (ROI) analyses were performed under the contrast of “structure > word-list.” Whole brain analysis confirmed significant involvement of the posterior inferior frontal gyrus [pIFG, corresponding to Brodmann area (BA) 44]. Furthermore, both the signal intensity in Broca’s area and the behavioral performance showed significant correlations with natural language performance in the same participants. ROI analysis within the language atlas and anatomically defined Broca’s area revealed that only the pIFG was reliably activated.DiscussionTaken together, these results support the notion that Broca’s area, particularly BA 44, works as a combinatorial engine where words are merged together according to syntactic information. Furthermore, this study suggests that the present artificial grammar may serve as promising material for investigating the neurobiological basis of syntax, fostering future cross-species studies.

The biogeography-based optimization (BBO) algorithm is known for its simplicity and low computational overhead, but it often struggles with falling into local optima and slow convergence speed. Against this background, this work presents a multi-strategy enhanced BBO variant, named MSBBO. Firstly, the example chasing strategy is proposed to eliminate the destruction of the inferior solutions to superior solutions. Secondly, the heuristic crossover strategy is designed to enhance the search ability of the population. Finally, the prey search–attack strategy is used to balance the exploration and exploitation. To verify the performance of MSBBO, we compare it with standard BBO, seven BBO variants (PRBBO, BBOSB, HGBBO, FABBO, BLEHO, MPBBO and BBOIMAM) and seven meta-heuristic algorithms (GWO, WOA, SSA, ChOA, MPA, GJO and BWO) on multiple dimensions of 24 benchmark functions. It concludes that MSBBO significantly outperforms all competitors both on convergence accuracy, speed and stability, and MSBBO basically converges to the same results on 10,000 dimensions as on 1000 dimensions. Further, MSBBO is applied to six real-world engineering design problems. The experimental results show that our work is still more competitive than other latest optimization techniques (COA, EDO, OMA, SHO and SCSO) on constrained optimization problems.

IntroductionEarly monolingual versus bilingual experience affects linguistic and cognitive processes during the first months of life, as well as functional activation patterns. The previous study explored the influence of a bilingual environment in the first months of life on resting-state functional connectivity and reported no significant difference between language groups.MethodsTo further explore the influence of a bilingual environment on brain development function, we used the resting-state functional near-infrared spectroscopy public dataset of the 4-month-old infant group in the sleep state (30 Spanish; 33 Basque; 36 bilingual). Wavelet Transform Coherence, graph theory, and Granger causality methods were performed on the functional connectivity of the frontal lobes.ResultsThe results showed that functional connectivity strength was significantly higher in the left hemisphere than that in the right hemisphere in both monolingual and bilingual groups. The graph theoretic analysis showed that the characteristic path length was significantly higher in the left hemisphere than in the right hemisphere for the bilingual infant group. Contrary to the monolingual infant group, the left-to-right direction of information flow was found in the frontal regions of the bilingual infant group in the effective connectivity analysis.DiscussionThe results suggested that the left hemispheric lateralization of functional connectivity in frontal regions is more pronounced in the bilingual group compared to the monolingual group. Furthermore, effective connectivity analysis may be a useful method to investigate the resting-state brain networks of infants.

Background. The poor survival rates of transplanted mesenchymal stem cells (MSCs) in harsh microenvironments impair the efficacy of MSCs transplantation in myocardial infarction (MI). Extrinsic apoptosis pathways play an important role in the apoptosis of transplanted MSCs, and Fas apoptosis inhibitory molecule (FAIM) is involved in regulation of the extrinsic apoptosis pathway. Thus, we aimed to explore whether FAIM augmentation protects MSCs against stress-induced apoptosis and thereby improves the therapeutic efficacy of MSCs. Methods. We ligated the left anterior descending coronary artery (LAD) in the mouse heart to generate an MI model and then injected FAIM-overexpressing MSCs (MSCsFAIM) into the peri-infarction area in vivo. Moreover, FAIM-overexpressing MSCs were challenged with oxygen, serum, and glucose deprivation (OGD) in vitro, which mimicked the harsh microenvironment that occurs in cardiac infarction. Results. FAIM was markedly downregulated under OGD conditions, and FAIM overexpression protected MSCs against OGD-induced apoptosis. MSCsFAIM transplantation improved cell retention, strengthened angiogenesis, and ameliorated heart function. The antiapoptotic effect of FAIM was mediated by cellular-FLICE inhibitory protein (c-FLIP), and FAIM augmentation improved the protein expression of c-FLIP by reducing ubiquitin–proteasome-dependent c-FLIP degradation. Furthermore, FAIM inhibited the activation of JNK, and treatment with the JNK inhibitor SP600125 abrogated the reduction in c-FLIP protein expression caused by FAIM silencing. Conclusions. Overall, these results indicated that FAIM curbed the JNK-mediated, ubiquitination–proteasome-dependent degradation of c-FLIP, thereby improving the survival of transplanted MSCs and enhancing their efficacy in MI. This study may provide a novel approach to strengthen the therapeutic effect of MSC-based therapy.

Neosporosis is caused by Neospora caninum (N. caninum), which mainly infects cattle and goats and severely threatens the animal industry. In this study, the inhibitory effects of polyclonal antiserum anti-NcSRS17, NcSRS2 and NcSRS52 were explored. Cytokines in mice or goat serum were detected after immunization. After infection, the survival of mice was recorded. The pathological changes and parasite loads were observed and detected in tissues. The results showed that anti-NcSRS2, NcSRS17 and NcSRS52 antibodies all inhibit the invasion and proliferation of N. caninum. The IFN-γ level in the NcSRS17 group was higher than that in the NcSRS2 and NcSRS52 groups, and higher in the NcSRS2-mIL-18 group than in the NcSRS2 group. The survival rates of mice were 16% in the positive control group, 67% in the SRS52 group, 83% in the SRS2 and mIL-18 groups and 100% in the SRS17 and SRS2-mIL-18 groups. Goats immunized with NcSRS17-gIL-18 developed high levels of IL-4, IL-12 and IFN-γ compared with those immunized with NcSRS-17. Parasite loads in the brains of animals in the NcSRS17 and NcSRS17-gIL-18 groups were significantly reduced, and were significantly lower in the NcSRS17-gIL-18 group (p ≤ 0.01). This study indicates that SRS17 may be an antigen candidate for vaccine development against neosporosis, and IL-18 can enhance the immune protective efficiency of antigen candidates.

Background: Optic neuritis (ON) is an important clinical manifestation of neuromyelitis optic spectrum disease (NMOSD). Myelin oligodendrocyte glycoprotein (MOG) antibody-related and aquaporin 4 (AQP4) antibody-related ON show different disease patterns. The aim of this study was to explore the differences in structure and function of the visual pathway in patients with ON associated with MOG and AQP4 antibodies.Methods: In this prospective study, we recruited 52 subjects at Beijing Tiantan Hospital, including 11 with MOG Ig+ ON (MOG-ON), 13 with AQP4 Ig+ ON (AQP4-ON), and 28 healthy controls (HCs). Fractional anisotropy (FA), mean diffusivity (MD), axial diffusivity (AD), and radial diffusivity (RD) of optic radiation (OR), primary visual cortex volume (V1), brain volume, and visual acuity (VA) were compared among groups. A multiple linear regression was used to explore associations between VA and predicted factors. In addition, we used optical coherence tomography (OCT) to examine thickness of the peripapillary retinal nerve fiber layer (pRNFL) and retinal ganglion cell complex (GCC) in a separate cohort consisting of 15 patients with ON (8 MOG-ON and 7 AQP4-ON) and 28 HCs.Results: Diffusion tensor imaging showed that the FA of OR was lower than controls in patients with AQP4-ON (p = 0.001) but not those with MOG-ON (p = 0.329) and was significantly different between the latter two groups (p = 0.005), while V1 was similar in patients with MOG-ON and AQP4-ON (p = 0.122), but was lower than controls in AQP4-ON (p = 0.002) but not those with MOG-ON (p = 0.210). The VA outcomes were better in MOG-ON than AQP4-ON, and linear regression analysis revealed that VA in MOG-ON and AQP4-ON was both predicted by the FA of OR (standard β = −0.467 and −0.521, p = 0.036 and 0.034). Both patients of MOG-ON and AQP4-ON showed neuroaxonal damage in the form of pRNFL and GCC thinning but showed no statistically significant difference (p = 0.556, 0.817).Conclusion: The structural integrity of OR in patients with MOG-ON, which is different from the imaging manifestations of AQP4-ON, may be a reason for the better visual outcomes of patients with MOG-ON.

The dictionary learning algorithm has been successfully applied to electronic noses because of its high recognition rate. However, most dictionary learning algorithms use l0-norm or l1-norm to regularize the sparse coefficients, which means that the electronic nose takes a long time to test samples and results in the inefficiency of the system. Aiming at accelerating the recognition speed of the electronic nose system, an efficient dictionary learning algorithm is proposed in this paper where the algorithm performs a multi-column atomic update. Meanwhile, to solve the problem that the singular value decomposition of the k-means (K-SVD) dictionary has little discriminative power, a novel classification model is proposed, a coefficient matrix is achieved by a linear projection to the training sample, and a constraint is imposed where the coefficients in the same category should keep a large coefficient and be closer to their class centers while coefficients in the different categories should keep sparsity. The algorithm was evaluated and analyzed based on the comparisons of several traditional classification algorithms. When the dimension of the sample was larger than 10, the average recognition rate of the algorithm was maintained above 92%, and the average training time was controlled within 4 s. The experimental results show that the improved algorithm is an effective method for the development of an electronic nose.

BackgroundPoor cell survival after transplantation restricts the therapeutic potential of mesenchymal stem cell (MSC) transplantation into infarcted hearts, particularly in older individuals. TPP1, a component of the shelterin complex that is involved in telomere protection, is highly expressed in young MSCs but declines in aged ones. Here, we explore whether TPP1 overexpression in aged mouse MSCs improves cell viability in vivo and in vitro.MethodsAged mouse MSCs overexpressing TPP1 were injected into the peri-infarct area of the mouse heart after left anterior descending coronary artery ligation. In parallel, to evaluate cellular-level effects, H2O2 was applied to MSCs in vitro to mimic the microenvironment of myocardial injury.ResultsIn vivo, the transplantation of aged MSCs overexpressing TPP1 resulted in improved cell survival, enhanced cardiac function, and reduced fibrosis compared to unmodified aged MSCs. In vitro, TPP1 overexpression protected aged MSCs from H2O2-induced apoptosis and enhanced DNA double-strand break (DSB) repair. In addition, the phosphorylation of AKT and the key DSB repair protein MRE11 were both significantly upregulated in aged MSCs that overexpressed TPP1.ConclusionsOur results reveal that TPP1 can enhance DNA repair through the AKT/MRE11 pathway, thereby improving the therapeutic effects of aged MSC transplantation and offering significant potential for the clinical application of autologous transplantation in aged patients.

Many bacterial pathogens secret effectors into host cells to disable host defenses and thus promote infection. The exocyst complex functions in the transport and secretion of defense molecules, and loss of function of the EXO70B1 subunit leads to autoimmunity by activation of a truncated Toll/interleukin-1 receptor–nucleotide-binding sequence protein (TIR-NBS2; herein referred to as TN2). Here, we show that EXO70B1 is required for pathogen-associated molecular pattern-triggered immune responses in Arabidopsis thaliana. The effector AvrPtoB, an E3 ligase from Pseudomonas syringae pv. tomato (Pto) strain DC3000, associates with EXO70B1. AvrPtoB ubiquitinates EXO70B1 and mediates EXO70B1 degradation via the host’s 26S proteasome in a manner requiring E3 ligase activity. AvrPtoB enhances Pto DC3000 virulence by overcoming EXO70B1-mediated resistance. Moreover, overexpression of AvrPtoB in Arabidopsis leads to autoimmunity, which is partially dependent on TN2. Expression of TN2 in tobacco (Nicotiana tabacum and Nicotiana benthamiana) triggers strong and rapid cell death, which is suppressed by co-expression with EXO70B1 but reoccurs when co-expressed with AvrPtoB. Taken together, our data highlight that AvrPtoB targets the Arabidopsis thaliana EXO70 protein family member EXO70B1 to manipulate the defense molecule secretion machinery or immunity.

Functional near-infrared spectroscopy (fNIRS), as a new optical functional neuroimaging method, has been widely used in neuroscience research. In some research fields with NIRS, heartrate (HR) (or heartbeat) is needed as useful information to evaluate its influence, or to know the state of subject, or to remove its artifact. If HR (or heartbeat) can be detected with high accuracy from the optical intensity, this will undoubtedly benefit a lot to many NIRS studies. Previous studies have used the moving time window method or mathematical morphology method (MMM) to detect heartbeats in the optical intensity. However, there are some disadvantages in these methods. In this study, we proposed a method combining the periodic information of heartbeats and the operator of mathematical morphology to automatically detect heartbeats in the optical intensity. First the optical intensity is smoothed using a moving average filter. Then, the opening operator of mathematical morphology extracts peaks in the smoothed optical intensity. Finally, one peak is identified as a heartbeat peak if this peak is the maximum in a predefined point range. Through validation on experimental data, our method can overcome the disadvantages of previous methods, and detect heartbeats in the optical signal of fNIRS with nearly 100% accuracy.