Direct Melt-Calendaring of Highly Textured (Bi,Sb)2Te3 Thick Films: Superior Thermoelectric and Mechanical Performance via Strain Engineering.

The evolutions of chip thermal management and micro energy harvesting put forward urgent need for micro thermoelectric devices. Nevertheless, low-performance thermoelectric thick films as well as the complicated precision cutting process for hundred-micron thermoelectric legs still remain the bottleneck hindering the advancement of micro thermoelectric devices. In this work, an innovative direct melt-calendaring manufacturing technology is first proposed with specially designed and assembled equipment, that enables direct, rapid, and cost-effective continuous manufacturing of Bi2Te3-based films with thickness of hundred microns. Based on the strain engineering with external glass coating confinement and controlled calendaring deformation degree, enhanced thermoelectric performance has been achieved for (Bi,Sb)2Te3 thick films with highly textured nanocrystals, which can promote carrier mobility over 182.6 cm2 V-1 s-1 and bring out a record-high zT value of 0.96 and 1.16 for n-type and p-type (Bi,Sb)2Te3 thick films, respectively. The nanoscale interfaces also further improve the mechanical strength with excellent elastic modules (over 42.0 GPa) and hardness (over 1.7 GPa), even superior to the commercial zone-melting ingots and comparable to the hot-extrusion (Bi,Sb)2Te3 alloys. This new fabrication strategy is versatile to a wide range of inorganic thermoelectric thick films, which lays a solid foundation for the development of micro thermoelectric devices.

PRRSV GP5 inhibits the antivirus effects of chaperone-mediated autophagy by targeting LAMP2A.

Autophagy is an important biological process in host defense against viral infection. However, many viruses have evolved various strategies to disrupt the host antiviral system. Porcine reproductive and respiratory syndrome virus (PRRSV) is a typical immunosuppressive virus with a large economic impact on the swine industry. At present, studies on the escape mechanism of PRRSV in the autophagy process, especially through chaperone-mediated autophagy (CMA), are limited. This study confirmed that PRRSV glycoprotein 5 (GP5) could disrupt the formation of the GFAP-LAMP2A complex by inhibiting the MTORC2/PHLPP1/GFAP pathway, promoting the dissociation of the pGFAP-EF1α complex, and blocking the K63-linked polyubiquitination of LAMP2A to inhibit the activity of CMA. Further research demonstrated that CMA plays an anti-PRRSV role by antagonizing nonstructural protein 11 (NSP11)-mediated inhibition of type I interferon (IFN-I) signaling. Taken together, these results indicate that PRRSV GP5 inhibits the antiviral effect of CMA by targeting LAMP2A. This research provides new insight into the escape mechanism of immunosuppressive viruses in CMA. IMPORTANCE: Viruses have evolved sophisticated mechanisms to manipulate autophagy to evade degradation and immune responses. Porcine reproductive and respiratory syndrome virus (PRRSV) is a typical immunosuppressive virus that causes enormous economic losses in the swine industry. However, the mechanism by which PRRSV manipulates autophagy to defend against host antiviral effects remains unclear. In this study, we found that PRRSV GP5 interacts with LAMP2A and disrupts the formation of the GFAP-LAMP2A complex, thus inhibiting the activity of CMA and subsequently enhancing the inhibitory effect of the NSP11-mediated IFN-I signaling pathway, ultimately facilitating PRRSV replication. Our study revealed a novel mechanism by which PRRSV escapes host antiviral effects through CMA, providing a potential host target, LAMP2A, for developing antiviral drugs and contributing to understanding the escape mechanism of immunosuppressive viruses.

Shikonin blocks CAF-induced TNBC metastasis by suppressing mitochondrial biogenesis through GSK-3ß/NEDD4-1 mediated phosphorylation-dependent degradation of PGC-1α.

BACKGROUND: Triple-negative breast cancer (TNBC) is characterized by its high metastatic potential, which results in poor patient survival. Cancer-associated fibroblasts (CAFs) are crucial in facilitating TNBC metastasis via induction of mitochondrial biogenesis. However, how to inhibit CAF-conferred mitochondrial biogenesis is still needed to explore. METHODS: We investigated metastasis using wound healing and cell invasion assays, 3D-culture, anoikis detection, and NOD/SCID mice. Mitochondrial biogenesis was detected by MitoTracker green FM staining, quantification of mitochondrial DNA levels, and blue-native polyacrylamide gel electrophoresis. The expression, transcription, and phosphorylation of peroxisome-proliferator activated receptor coactivator 1α (PGC-1α) were detected by western blotting, chromatin immunoprecipitation, dual-luciferase reporter assay, quantitative polymerase chain reaction, immunoprecipitation, and liquid chromatography-tandem mass spectrometry. The prognostic role of PGC-1α in TNBC was evaluated using the Kaplan-Meier plotter database and clinical breast cancer tissue samples. RESULTS: We demonstrated that PGC-1α indicated lymph node metastasis, tumor thrombus formation, and poor survival in TNBC patients, and it was induced by CAFs, which functioned as an inducer of mitochondrial biogenesis and metastasis in TNBC. Shikonin impeded the CAF-induced PGC-1α expression, nuclear localization, and interaction with estrogen-related receptor alpha (ERRα), thereby inhibiting PGC-1α/ERRα-targeted mitochondrial genes. Mechanistically, the downregulation of PGC-1α was mediated by synthase kinase 3ß-induced phosphorylation of PGC-1α at Thr295, which associated with neural precursor cell expressed developmentally downregulated 4e1 recognition and subsequent degradation by ubiquitin proteolysis. Mutation of PGC-1α at Thr295 negated the suppressive effects of shikonin on CAF-stimulated TNBC mitochondrial biogenesis and metastasis in vitro and in vivo. CONCLUSIONS: Our findings indicate that PGC-1α is a viable target for blocking TNBC metastasis by disrupting mitochondrial biogenesis, and that shikonin merits potential for treatment of TNBC metastasis as an inhibitor of mitochondrial biogenesis through targeting PGC-1α.

M6A demethylase FTO-stabilized exosomal circBRCA1 alleviates oxidative stress-induced granulosa cell damage via the miR-642a-5p/FOXO1 axis.

BACKGROUND: Premature ovarian insufficiency (POI) is an important cause of female infertility and seriously impacts the physical and psychological health of patients. Human umbilical cord mesenchymal stem cell-derived exosomes (HucMSCs-Exs, H-Exs) have exhibited protective effects on ovarian function with unclear mechanisms. METHODS: A comprehensive analysis of the Gene Expression Omnibus (GEO) database were used to identify POI-associated circRNAs and miRNAs. The relationship between HucMSC-derived exosomal circBRCA1/miR-642a-5p/FOXO1 axis and POI was examined by RT-qPCR, Western blotting, reactive oxygen species (ROS) staining, senescence-associated ß-gal (SA-ß-gal) staining, JC-1 staining, TEM, oxygen consumption rate (OCR) measurements and ATP assay in vivo and in vitro. RT-qPCR detected the expression of circBRCA1 in GCs and serum of patients with normal ovarian reserve function (n = 50) and patients with POI (n = 50); then, the correlation of circBRCA1 with ovarian reserve function indexes was analyzed. RESULTS: Herein, we found that circBRCA1 was decreased in the serum and ovarian granulosa cells (GCs) of patients with POI and was associated with decreased ovarian reserve. H-Exs improved the disorder of the estrous cycles and reproductive hormone levels, reduced the number of atretic follicles, and alleviated the apoptosis and senescence of GCs in rats with POI. Moreover, H-Exs mitigated mitochondrial damage and reversed the reduced circBRCA1 expression induced by oxidative stress in GCs. Mechanistically, FTO served as an eraser to increase the stability and expression of circBRCA1 by mediating the m6A demethylation of circBRCA1, and exosomal circBRCA1 sponged miR-642a-5p to block its interaction with FOXO1. CircBRCA1 insufficiency aggravated mitochondrial dysfunction, mimicking FTO or FOXO1 depletion effects, which was counteracted by miR-642a-5p inhibition. CONCLUSION: H-Exs secreted circBRCA1 regulated by m6A modification, directly sponged miR-642a-5p to upregulate FOXO1, resisted oxidative stress injuries in GCs and protected ovarian function in rats with POI. Exosomal circBRCA1 supplementation may be a general prospect for the prevention and treatment of POI.

Population structure of Taenioides sp. (Gobiiformes, Gobiidae) reveals their invasion history to inland waters of China based on mitochondrial DNA control region.

Taenioides sp. is a small temperate fish originally known to inhabit muddy bottoms of brackish waters in coastal areas of China. However, it began to invade multiple inland freshwaters and caused severe damage to Chinese aquatic ecosystems in recent years. To investigate the sources and invasive history of this species, we examined the population structure of 141 individuals collected from seven locations based on partial mitochondrial D-loop regions. The results revealed that the genetic diversity gradually decreased from south to north, with the Yangtze River Estuary and Taihu Lake populations possessing the highest haplotype diversity (Hd), average number of differences (k), and nucleotide diversity (π) values, suggesting that they may be the sources of Taenioides sp. invasions. Isolation-by-distance analysis revealed a non-significant correlation (p = 0.166) between genetic and geographic distances among seven populations, indicating that dispersal mediated through the regional hydraulic projects may have played an essential role in Taenioides sp. invasions. The population genetic structure analysis revealed two diverged clades among seven populations, with clade 2 only detected in source populations, suggesting a possible difference in the invasion ability of the two clades. Our results provide insights into how native estuary fish become invasive through hydraulic projects and may provide critical information for the future control of this invasive species.

Downregulation of lysine-specific histone demethylase 1A (KDM1A/LSD1) in medial prefrontal cortex facilitates chronic stress-induced pain and emotional dysfunction in female mice.

Chronic primary pain, characterized by overlapping symptoms of chronic pain, anxiety, and depression, is strongly associated with stress and is particularly prevalent among females. Recent research has convincingly linked epigenetic modifications in the medial prefrontal cortex (mPFC) to chronic pain and chronic stress. However, our understanding of the role of histone demethylation in the mPFC in chronic stress-induced pain remains limited. In this study, we investigated the function of lysine-specific histone demethylase 1A (KDM1A/LSD1) in the context of chronic overlapping pain comorbid with anxiety and depression in female mice. We employed a chronic variable stress model to induce pain hypersensitivity in the face and hindpaws, as well as anxiety-like and depression-like behaviors, in female mice. Our findings revealed that chronic stress led to a downregulation of KDM1A mRNA and protein expression in the mPFC. Notably, overexpressing KDM1A in the mPFC alleviated the pain hypersensitivity, anxiety-like behaviors, and depression-like behaviors in female mice, without affecting basal pain responses or inducing emotional distress. Conversely, conditional knockout of KDM1A in the mPFC exacerbated pain sensitivity and emotional distress specifically in females. In summary, this study highlights the crucial role of KDM1A in the mPFC in modulating chronic stress-induced overlapping pain, anxiety, and depression in females. Our findings suggest that KDM1A may serve as a potential therapeutic target for treating chronic stress-related overlap pain and associated negative emotional disorders.

A deep reinforcement learning algorithm framework for solving multi-objective traveling salesman problem based on feature transformation.

As a special type of multi-objective combinatorial optimization problems (MOCOPs), the multi-objective traveling salesman problem (MOTSP) plays an important role in practical fields such as transportation and robot control. However, due to the complexity of its solution space and the conflicts between different objectives, it is difficult to obtain satisfactory solutions in a short time. This paper proposes an end-to-end algorithm framework for solving MOTSP based on deep reinforcement learning (DRL). By decomposing strategies, solving MOTSP is transformed into solving multiple single-objective optimization subproblems. Through linear transformation, the features of the MOTSP are combined with the weights of the objective function. Subsequently, a modified graph pointer network (GPN) model is used to solve the decomposed subproblems. Compared with the previous DRL model, the proposed algorithm can solve all the subproblems using only one model without adding weight information as input features. Furthermore, our algorithm can output a corresponding solution for each weight, which increases the diversity of solutions. In order to verify the performance of our proposed algorithm, it is compared with four classical evolutionary algorithms and two DRL algorithms on several MOTSP instances. The comparison shows that our proposed algorithm outperforms the compared algorithms both in terms of training time and the quality of the resulting solutions.

General strategy for developing thick-film micro-thermoelectric coolers from material fabrication to device integration.

Micro-thermoelectric coolers are emerging as a promising solution for high-density cooling applications in confined spaces. Unlike thin-film micro-thermoelectric coolers with high cooling flux at the expense of cooling temperature difference due to very short thermoelectric legs, thick-film micro-thermoelectric coolers can achieve better comprehensive cooling performance. However, they still face significant challenges in both material preparation and device integration. Herein, we propose a design strategy which combines Bi2Te3-based thick film prepared by powder direct molding with micro-thermoelectric cooler integrated via phase-change batch transfer. Accurate thickness control and relatively high thermoelectric performance can be achieved for the thick film, and the high-density-integrated thick-film micro-thermoelectric cooler exhibits excellent performance with maximum cooling temperature difference of 40.6 K and maximum cooling flux of 56.5 W·cm-2 at room temperature. The micro-thermoelectric cooler also shows high temperature control accuracy (0.01 K) and reliability (over 30000 cooling cycles). Moreover, the device demonstrates remarkable capacity in power generation with normalized power density up to 214.0 µW · cm-2 · K-2. This study provides a general and scalable route for developing high-performance thick-film micro-thermoelectric cooler, benefiting widespread applications in thermal management of microsystems.

Exosomal YB-1 facilitates ovarian restoration by MALAT1/miR-211-5p/FOXO3 axis.

Premature ovarian failure (POF) affects many adult women less than 40 years of age and leads to infertility. Mesenchymal stem cells-derived small extracellular vesicles (MSCs-sEVs) are attractive candidates for ovarian function restoration and folliculogenesis for POF due to their safety and efficacy, however, the key mediator in MSCs-sEVs that modulates this response and underlying mechanisms remains elusive. Herein, we reported that YB-1 protein was markedly downregulated in vitro and in vivo models of POF induced with H2O2 and CTX respectively, accompanied by granulosa cells (GCs) senescence phenotype. Notably, BMSCs-sEVs transplantation upregulated YB-1, attenuated oxidative damage-induced cellular senescence in GCs, and significantly improved the ovarian function of POF rats, but that was reversed by YB-1 depletion. Moreover, YB-1 showed an obvious decline in serum and GCs in POF patients. Mechanistically, YB-1 as an RNA-binding protein (RBP) physically interacted with a long non-coding RNA, MALAT1, and increased its stability, further, MALAT1 acted as a competing endogenous RNA (ceRNA) to elevate FOXO3 levels by sequestering miR-211-5p to prevent its degradation, leading to repair of ovarian function. In summary, we demonstrated that BMSCs-sEVs improve ovarian function by releasing YB-1, which mediates MALAT1/miR-211-5p/FOXO3 axis regulation, providing a possible therapeutic target for patients with POF.

Inhibition of MFN1 restores tamoxifen-induced apoptosis in resistant cells by disrupting aberrant mitochondrial fusion dynamics.

Tamoxifen (TAM) resistance presents a major clinical obstacle in the management of estrogen-sensitive breast cancer, highlighting the need to understand the underlying mechanisms and potential therapeutic approaches. We showed that dysregulated mitochondrial dynamics were involved in TAM resistance by protecting against mitochondrial apoptosis. The dysregulated mitochondrial dynamics were associated with increased mitochondrial fusion and decreased fission, thus preventing the release of mitochondrial cytochrome c to the cytoplasm following TAM treatment. Dynamin-related GTPase protein mitofusin 1 (MFN1), which promotes fusion, was upregulated in TAM-resistant cells, and high MFN1 expression indicated a poor prognosis in TAM-treated patients. Mitochondrial translocation of MFN1 and interaction between MFN1 and mitofusin 2 (MFN2) were enhanced to promote mitochondrial outer membrane fusion. The interaction of MFN1 and cristae-shaping protein optic atrophy 1 (OPA1) and OPA1 oligomerization were reduced due to augmented OPA1 proteolytic cleavage, and their apoptosis-promoting function was reduced due to cristae remodeling. Furthermore, the interaction of MFN1 and BAK were increased, which restrained BAK activation following TAM treatment. Knockdown or pharmacological inhibition of MFN1 blocked mitochondrial fusion, restored BAK oligomerization and cytochrome c release, and amplified activation of caspase-3/9, thus sensitizing resistant cells to apoptosis and facilitating the therapeutic effects of TAM both in vivo and in vitro. Conversely, overexpression of MFN1 alleviated TAM-induced mitochondrial apoptosis and promoted TAM resistance in sensitive cells. These results revealed that dysregulated mitochondrial dynamics contributes to the development of TAM resistance, suggesting that targeting MFN1-mediated mitochondrial fusion is a promising strategy to circumvent TAM resistance.

Gut microbiome and metabolome profiling in Framingham heart study reveals cholesterol-metabolizing bacteria.

Accumulating evidence suggests that cardiovascular disease (CVD) is associated with an altered gut microbiome. Our understanding of the underlying mechanisms has been hindered by lack of matched multi-omic data with diagnostic biomarkers. To comprehensively profile gut microbiome contributions to CVD, we generated stool metagenomics and metabolomics from 1,429 Framingham Heart Study participants. We identified blood lipids and cardiovascular health measurements associated with microbiome and metabolome composition. Integrated analysis revealed microbial pathways implicated in CVD, including flavonoid, γ-butyrobetaine, and cholesterol metabolism. Species from the Oscillibacter genus were associated with decreased fecal and plasma cholesterol levels. Using functional prediction and in vitro characterization of multiple representative human gut Oscillibacter isolates, we uncovered conserved cholesterol-metabolizing capabilities, including glycosylation and dehydrogenation. These findings suggest that cholesterol metabolism is a broad property of phylogenetically diverse Oscillibacter spp., with potential benefits for lipid homeostasis and cardiovascular health.

Diverse and asymmetric patterns of single-neuron projectome in regulating interhemispheric connectivity.

The corpus callosum, historically considered primarily for homotopic connections, supports many heterotopic connections, indicating complex interhemispheric connectivity. Understanding this complexity is crucial yet challenging due to diverse cell-specific wiring patterns. Here, we utilized public AAV bulk tracing and single-neuron tracing data to delineate the anatomical connection patterns of mouse brains and conducted wide-field calcium imaging to assess functional connectivity across various brain states in male mice. The single-neuron data uncovered complex and dense interconnected patterns, particularly for interhemispheric-heterotopic connections. We proposed a metric "heterogeneity" to quantify the complexity of the connection patterns. Computational modeling of these patterns suggested that the heterogeneity of upstream projections impacted downstream homotopic functional connectivity. Furthermore, higher heterogeneity observed in interhemispheric-heterotopic projections would cause lower strength but higher stability in functional connectivity than their intrahemispheric counterparts. These findings were corroborated by our wide-field functional imaging data, underscoring the important role of heterotopic-projection heterogeneity in interhemispheric communication.

A Color- and Geometric-Feature-Based Approach for Denoising Three-Dimensional Cultural Relic Point Clouds.

In the acquisition process of 3D cultural relics, it is common to encounter noise. To facilitate the generation of high-quality 3D models, we propose an approach based on graph signal processing that combines color and geometric features to denoise the point cloud. We divide the 3D point cloud into patches based on self-similarity theory and create an appropriate underlying graph with a Markov property. The features of the vertices in the graph are represented using 3D coordinates, normal vectors, and color. We formulate the point cloud denoising problem as a maximum a posteriori (MAP) estimation problem and use a graph Laplacian regularization (GLR) prior to identifying the most probable noise-free point cloud. In the denoising process, we moderately simplify the 3D point to reduce the running time of the denoising algorithm. The experimental results demonstrate that our proposed approach outperforms five competing methods in both subjective and objective assessments. It requires fewer iterations and exhibits strong robustness, effectively removing noise from the surface of cultural relic point clouds while preserving fine-scale 3D features such as texture and ornamentation. This results in more realistic 3D representations of cultural relics.

Task sub-type states decoding via group deep bidirectional recurrent neural network.

Decoding brain states under different cognitive tasks from functional magnetic resonance imaging (fMRI) data has attracted great attention in the neuroimaging filed. However, the well-known temporal dependency in fMRI sequences has not been fully exploited in existing studies, due to the limited temporal-modeling capacity of the backbone machine learning algorithms and rigid training sample organization strategies upon which the brain decoding methods are built. To address these limitations, we propose a novel method for fine-grain brain state decoding, namely, group deep bidirectional recurrent neural network (Group-DBRNN) model. We first propose a training sample organization strategy that consists of a group-task sample generation module and a multiple-scale random fragment strategy (MRFS) module to collect training samples that contain rich task-relevant brain activity contrast (i.e., the comparison of neural activity patterns between different tasks) and maintain the temporal dependency. We then develop a novel decoding model by replacing the unidirectional RNNs that are widely used in existing brain state decoding studies with bidirectional stacked RNNs to better capture the temporal dependency, and by introducing a multi-task interaction layer (MTIL) module to effectively model the task-relevant brain activity contrast. Our experimental results on the Human Connectome Project task fMRI dataset (7 tasks consisting of 23 task sub-type states) show that the proposed model achieves an average decoding accuracy of 94.7% over the 23 fine-grain sub-type states. Meanwhile, our extensive interpretations of the intermediate features learned in the proposed model via visualizations and quantitative assessments of their discriminability and inter-subject alignment evidence that the proposed model can effectively capture the temporal dependency and task-relevant contrast.

Multifunctional cross-sensitive magnetic alginate-chitosan-polyethylene oxide nanofiber sensor for human-machine interaction.

Flexible nanofiber membranes are compelling materials for the development of functional multi-mode sensors; however, their essential features such as high cross-sensitivity, reliable stability and signal discrimination capability have rarely been realized simultaneously in one sensor. Here, a novel multi-mode sensor with a nanofiber membrane structure based on multiple interpenetrating networks of bidisperse magnetic particles, sodium alginate (SA), chitosan (CHI) in conjunction with polyethylene oxide hydrogels was prepared in a controllable electrospinning technology. Specifically, the morphology distributions of nanofibers could be regulated by the crosslinking degree of the interpenetrating networks and the spinning process parameters. The incorporation of SA and CHI endowed the sensor with desirable flexibility, ideal biocompatibility and skin-friendly property. Besides, the assembled sensors not only displayed preferable magnetic sensitivity of 0.34 T-1 and reliable stability, but also exhibited favorable cross-sensitivity, quick response time, and long-term durability for over 5000 cycles under various mechanical stimuli. Importantly, the multi-mode stimuli could be discriminated via producing opposite electrical signals. Furthermore, based on the signal distinguishability of the sensor, a wearable Morse code translation system assisted by the machine learning algorithm was demonstrated, enabling a high recognizing accuracy (>99.1 %) for input letters and numbers information. Due to the excellent multifunctional sensing characteristics, we believe that the sensor will have a high potential in wearable soft electronics and human-machine interactions.

Mass Spectrometry-Based Proteomic Analysis of Potential Host Proteins Interacting with GP5 in PRRSV-Infected PAMs.

Porcine reproductive and respiratory syndrome virus (PRRSV) is a typical immunosuppressive virus causing a large economic impact on the swine industry. The structural protein GP5 of PRRSV plays a pivotal role in its pathogenicity and immune evasion. Virus-host interactions play a crucial part in viral replication and immune escape. Therefore, understanding the interactions between GP5 and host proteins are significant for porcine reproductive and respiratory syndrome (PRRS) control. However, the interaction network between GP5 and host proteins in primary porcine alveolar macrophages (PAMs) has not been reported. In this study, 709 GP5-interacting host proteins were identified in primary PAMs by immunoprecipitation coupled with liquid chromatography-tandem mass spectrometry (LC-MS/MS). Bioinformatics analysis revealed that these proteins were involved in multiple cellular processes, such as translation, protein transport, and protein stabilization. Subsequently, immunoprecipitation and immunofluorescence assay confirmed that GP5 could interact with antigen processing and presentation pathways related proteins. Finally, we found that GP5 may be a key protein that inhibits the antigen processing and presentation pathway during PRRSV infection. The novel host proteins identified in this study will be the candidates for studying the biological functions of GP5, which will provide new insights into PRRS prevention and vaccine development.

Mapping dynamic spatial patterns of brain function with spatial-wise attention.

Objective: Using functional magnetic resonance imaging (fMRI) and deep learning to discover the spatial pattern of brain function, or functional brain networks (FBNs) has been attracted many reseachers. Most existing works focus on static FBNs or dynamic functional connectivity among fixed spatial network nodes, but ignore the potential dynamic/time-varying characteristics of the spatial networks themselves. And most of works based on the assumption of linearity and independence, that oversimplify the relationship between blood-oxygen level dependence signal changes and the heterogeneity of neuronal activity within voxels.Approach: To overcome these problems, we proposed a novel spatial-wise attention (SA) based method called Spatial and Channel-wise Attention Autoencoder (SCAAE) to discover the dynamic FBNs without the assumptions of linearity or independence. The core idea of SCAAE is to apply the SA to generate FBNs directly, relying solely on the spatial information present in fMRI volumes. Specifically, we trained the SCAAE in a self-supervised manner, using the autoencoder to guide the SA to focus on the activation regions. Experimental results show that the SA can generate multiple meaningful FBNs at each fMRI time point, which spatial similarity are close to the FBNs derived by known classical methods, such as independent component analysis.Main results: To validate the generalization of the method, we evaluate the approach on HCP-rest, HCP-task and ADHD-200 dataset. The results demonstrate that SA mechanism can be used to discover time-varying FBNs, and the identified dynamic FBNs over time clearly show the process of time-varying spatial patterns fading in and out.Significance: Thus we provide a novel method to understand human brain better. Code is available athttps://github.com/WhatAboutMyStar/SCAAE.

Method for Estimating Road Impulse Ahead of Vehicles in Urban Environment with Microelectromechanical System Three-Dimensional Sensor.

Most automated vehicles (AVs) are equipped with abundant sensors, which enable AVs to improve ride comfort by sensing road elevation, such as speed bumps. This paper proposes a method for estimating the road impulse features ahead of vehicles in urban environments with microelectromechanical system (MEMS) light detection and ranging (LiDAR). The proposed method deploys a real-time estimation of the vehicle pose to solve the problem of sparse sampling of the LiDAR. Considering the LiDAR error model, the proposed method builds the grid height measurement model by maximum likelihood estimation. Moreover, it incorporates height measurements with the LiDAR error model by the Kalman filter and introduces motion uncertainty to form an elevation weight method by confidence eclipse. In addition, a gate strategy based on the Mahalanobis distance is integrated to handle the sharp changes in elevation. The proposed method is tested in the urban environment. The results demonstrate the effectiveness of our method.