Sustainable agriculture in the digital era: Past, present, and future trends by bibliometric analysis.

The digital era is reshaping agricultural practices, opening new avenues for sustainable growth, and proving indispensable in global challenges like food security and environmental conservation. However, a comprehensive understanding of this evolving landscape remains paramount. This research evaluates 344 papers from the Web of Science database to delve into sustainable agriculture's historical and current patterns in the digital era through bibliometric analysis and project future domains. Specifically, citation analysis identified influential papers, journals, institutions, and countries, while co-authorship analysis verified the interactions between authors, affiliations, and countries. Co-citation analysis found four hotspot clusters: prosperity and challenges in agricultural sustainability, digital information and agricultural development, innovations for sustainable agriculture, and geospatial analysis in environmental studies. The co-occurrence of keywords analysis revealed four main clusters for future studies: smart agriculture and biodiversity conservation, digitalization and sustainable agriculture, technologies and agricultural challenge management, and digital intelligence and farmer adoption. The study pioneers the use of bibliometric analysis to explore sustainable agriculture in the digital era. It presents invaluable insights into the evolving landscape of this field, summarizing its hotspots and suggesting future trajectories.

Thermogenic Fat as a New Obesity Management Tool: From Pharmaceutical Reagents to Cell Therapies.

Obesity is a complex medical condition caused by a positive imbalance between calorie intake and calorie consumption. Brown adipose tissue (BAT), along with the newly discovered "brown-like" adipocytes (called beige cells), functions as a promising therapeutic tool to ameliorate obesity and metabolic disorders by burning out extra nutrients in the form of heat. Many studies in animal models and humans have proved the feasibility of this concept. In this review, we aim to summarize the endeavors over the last decade to achieve a higher number/activity of these heat-generating adipocytes. In particular, pharmacological compounds, especially agonists to the ß3 adrenergic receptor (ß3-AR), are reviewed in terms of their feasibility and efficacy in elevating BAT function and improving metabolic parameters in human subjects. Alternatively, allograft transplantation of BAT and the transplantation of functional brown or beige adipocytes from mesenchymal stromal cells or human induced pluripotent stem cells (hiPSCs) make it possible to increase the number of these beneficial adipocytes in patients. However, practical and ethical issues still need to be considered before the therapy can eventually be applied in the clinical setting. This review provides insights and guidance on brown- and beige-cell-based strategies for the management of obesity and its associated metabolic comorbidities.

The use of peripheral CD3+γδ+Vδ2+ T lymphocyte cells in combination with the ALBI score to predict immunotherapy response in patients with advanced hepatocellular carcinoma: a retrospective study.

BACKGROUND: Currently, there is a lack of effective indicators for predicting the efficacy of immunotherapy in patients with advanced hepatocellular carcinoma (HCC). This study aimed to investigate the expression and prognostic value of peripheral T lymphocyte subsets in advanced HCC. METHODS: Patients with advanced HCC who were treated with immune checkpoint inhibitors (ICIs) from December 2021 to December 2023 were included in the study. Flow cytometry was used to detect lymphocyte subsets before treatment. The patients were divided into disease control (DC) and nondisease control (nDC) groups based on treatment efficacy. Relationships between the clinical characteristics/peripheral T lymphocytes and immunotherapy efficacy were analyzed. The effectiveness of peripheral T lymphocyte subsets in predicting immunotherapy efficacy for patients with advanced HCC was analyzed using receiver operating characteristic (ROC) curves. RESULTS: A total of 40 eligible patients were included in this study. Non-DC was significantly associated with higher albumin-bilirubin (ALBI) scores. The percentages of γδ+Vδ2+PD1+ T cells and γδ+Vδ2+Tim3+ T cells were greater in the nDC group than in the DC group. Multivariable regression analysis revealed that the ALBI score and T lymphocytes expressing γδ+Vδ2+PD1+ and γδ+Vδ2+Tim3+ were founded to be independent influencing factors. The area under the ROC curve (AUC) values for these combinations was 0.944 (95% CI, 0.882 ~ 1.000). CONCLUSIONS: The calculation of the ALBI score and determination of the percentages CD3+γδ+Vδ2+PD1+ T lymphocytes and CD3+γδ+Vδ2+Tim3+ T lymphocytes in the peripheral blood of patients with advanced HCC are helpful for predicting the patients' responses to ICIs, helping to screen patients who may clinically benefit from immunotherapy. RETROSPECTIVELY REGISTERED: number: ChiCTR2400080409, date of registration: 2024-01-29.

Targeting Neuronal GPR65 With Delayed BTB09089 Treatment Improves Neurorehabilitation Following Ischemic Stroke.

BACKGROUND: GPR65 (G protein-coupled receptor 65) can sense extracellular acidic environment to regulate pathophysiological processes. Pretreatment with the GPR65 agonist BTB09089 has been proven to produce neuroprotection in acute ischemic stroke. However, whether delayed BTB09089 treatment and neuronal GPR65 activation promote neurorestoration remains unknown. METHODS: Ischemic stroke was induced in wild-type (WT) or GPR65 knockout (GPR65-/-) mice by photothrombotic ischemia. Male mice were injected intraperitoneally with BTB09089 every other day at days 3, 7, or 14 poststroke. AAV-Syn-GPR65 (adenoassociated virus-synapsin-GPR65) was utilized to overexpress GPR65 in the peri-infarct cortical neurons of GPR65-/- and WT mice. Motor function was monitored by grid-walk and cylinder tests. The neurorestorative effects of BTB09089 were observed by immunohistochemistry, Golgi-Cox staining, and Western blotting. RESULTS: BTB09089 significantly promoted motor outcomes in WT but not in GPR65-/- mice, even when BTB09089 was delayed for 3 to 7 days. BTB09089 inhibited the activation of microglia and glial scar progression in WT but not in GPR65-/- mice. Meanwhile, BTB09089 reduced the decrease in neuronal density in WT mice, but this benefit was abolished in GPR65-/- mice and reemerged by overexpressing GPR65 in peri-infarct cortical neurons. Furthermore, BTB09089 increased the GAP43 (growth-associated protein-43) and synaptophysin puncta density, dendritic spine density, dendritic branch length, and dendritic complexity by overexpressing GPR65 in the peri-infarct cortical neurons of GPR65-/- mice, which was accompanied by increased levels of p-CREB (phosphorylated cAMP-responsive element-binding protein). In addition, the therapeutic window of BTB09089 was extended to day 14 by overexpressing GPR65 in the peri-infarct cortical neurons of WT mice. CONCLUSIONS: Our findings indicated that delayed BTB09089 treatment improved neurological functional recovery and brain tissue repair poststroke through activating neuronal GRP65. GPR65 overexpression may be a potential strategy to expand the therapeutic time window of GPR65 agonists for neurorehabilitation after ischemic stroke.

Targeting astrocytic TDAG8 with delayed CO2 postconditioning improves functional outcomes after controlled cortical impact injury in mice.

T-cell death-associated gene 8 (TDAG8), a G-protein-coupled receptor sensing physiological or weak acids, regulates inflammatory responses. However, its role in traumatic brain injury (TBI) remains unknown. Our recent study showed that delayed CO2 postconditioning (DCPC) has neuroreparative effects after TBI. We hypothesized that activating astrocytic TDAG8 is a key mechanism for DCPC. WT and TDAG8-/- mice received DCPC daily by transiently inhaling 10% CO2 after controlled cortical impact (CCI). HBAAV2/9-GFAP-m-TDAG8-3xflag-EGFP was used to overexpress TDAG8 in astrocytes. The beam walking test, mNSS, immunofluorescence and Golgi-Cox staining were used to evaluate motor function, glial activation and dendritic plasticity. DCPC significantly improved motor function; increased total dendritic length, neuronal complexity and spine density; inhibited overactivation of astrocytes and microglia; and promoted the expression of astrocytic brain-derived neurotrophic factor in WT but not TDAG8-/- mice. Overexpressing TDAG8 in astrocytes surrounding the lesion in TDAG8-/- mice restored the beneficial effects of DCPC. Although the effects of DCPC on Days 14-28 were much weaker than those of DCPC on Days 3-28 in WT mice, these effects were further enhanced by overexpressing astrocytic TDAG8. Astrocytic TDAG8 is a key target of DCPC for TBI rehabilitation. Its overexpression is a strategy that broadens the therapeutic window and enhances the effects of DCPC.

Association between plant-based dietary index and gallstone disease: A cross sectional study from NHANES.

BACKGROUND: The relationship between plant-based diets and gallstone disease has been debated. This study aimed to shed light on the association between plant-based dietary index and the risk of developing gallstone disease. METHODS: Eligible participants were selected from National Health and Nutrition Examination Survey (NHANES) 2017-2020. Three plant-based diet indexes (PDI, healthy PDI, unhealthy PDI) were calculated using data from two NHANES 24-h dietary recall interviews. Restricted Cubic Spline and multivariate logistic regression were used to analyze the associations. Subgroup analysis was adopted to make the results more robust. RESULTS: A total of 5673 eligible participants were analyzed. After adjusting for various confounding variables, uPDI was positively associated with gallstone disease (OR = 1.53, 95%CI: 1.02-2.29). No association was found between PDI/hPDI and gallstone disease (p > 0.05). The results of subgroup analysis did not show any positive association between uPDI and gallstones in specific groups. CONCLUSION: Our study shows that the elevated uPDI are linked to a higher risk of gallstone disease.

Maize residue retention shapes soil microbial communities and co-occurrence networks upon freeze-thawing cycles.

Maize residue retention is an effective agricultural practice for improving soil fertility in black soil region, where suffered from long freezing-thawing periods and intense freeze-thawing (FT) cycles. However, very few studies have examined the influence of maize residue retention on soil microbial communities under FT cycles. We investigated the response of soil microbial communities and co-occurrence networks to maize residue retention at different FT intensities over 12 cycles using a microcosm experiment conditioned in a temperature incubator. Our results indicated that maize residue retention induced dramatic shifts in soil archaeal, bacterial and fungal communities towards copiotroph-dominated communities. Maize residue retention consistently reduced soil fungal richness across all cycles, but this effect was weaker for archaea and bacteria. Normalized stochastic ratio analysis revealed that maize residue retention significantly enhanced the deterministic process of archaeal, bacterial and fungal communities. Although FT intensity significantly impacted soil respiration, it did not induce profound changes in soil microbial diversity and community composition. Co-occurrence network analysis revealed that maize residue retention simplified prokaryotic network, while did not impact fungal network complexity. The network robustness index suggested that maize residue retention enhanced the fungal network stability, but reduced prokaryotic network stability. Moreover, the fungal network in severe FT treatment harbored the most abundant keystone taxa, mainly being cold-adapted fungi. By identifying modules in networks, we observed that prokaryotic Module #1 and fungal Module #3 were enhanced by maize residue retention and contributed greatly to soil quality. Together, our results showed that maize residue retention exerted stronger influence on soil microbial communities and co-occurrence network patterns than FT intensity and highlighted the potential of microbial interactions in improving soil functionality.

An Efficient Graph Learning System for Emotion Recognition Inspired by the Cognitive Prior Graph of EEG Brain Network.

Benefiting from the high-temporal resolution of electroencephalogram (EEG), EEG-based emotion recognition has become one of the hotspots of affective computing. For EEG-based emotion recognition systems, it is crucial to utilize state-of-the-art learning strategies to automatically learn emotion-related brain cognitive patterns from emotional EEG signals, and the learned stable cognitive patterns effectively ensure the robustness of the emotion recognition system. In this work, to realize the efficient decoding of emotional EEG, we propose a graph learning system Graph Convolutional Network framework with Brain network initial inspiration and Fused attention mechanism (BF-GCN) inspired by the brain cognitive mechanism to automatically learn graph patterns from emotional EEG and improve the performance of EEG emotion recognition. In the proposed BF-GCN, three graph branches, i.e., cognition-inspired functional graph branch, data-driven graph branch, and fused common graph branch, are first elaborately designed to automatically learn emotional cognitive graph patterns from emotional EEG signals. And then, the attention mechanism is adopted to further capture the brain activation graph patterns that are related to emotion cognition to achieve an efficient representation of emotional EEG signals. Essentially, the proposed BF-CGN model is a cognition-inspired graph learning neural network model, which utilizes the spectral graph filtering theory in the automatic learning and extracting of emotional EEG graph patterns. To evaluate the performance of the BF-GCN graph learning system, we conducted subject-dependent and subject-independent experiments on two public datasets, i.e., SEED and SEED-IV. The proposed BF-GCN graph learning system has achieved 97.44% (SEED) and 89.55% (SEED-IV) in subject-dependent experiments, and the results in subject-independent experiments have achieved 92.72% (SEED) and 82.03% (SEED-IV), respectively. The state-of-the-art performance indicates that the proposed BF-GCN graph learning system has a robust performance in EEG-based emotion recognition, which provides a promising direction for affective computing.

Sleep stages classification by fusing the time-related synchronization analysis and brain activations.

Sleep staging plays an important role in the diagnosis and treatment of clinical sleep disorders. The sleep staging standard defines every 30 seconds as a sleep period, which may mean that there exist similar brain activity patterns during the same sleep period. Thus, in this work, we propose a novel time-related synchronization analysis framework named time-related multimodal sleep scoring model (TRMSC) to explore the potential time-related patterns of sleeping. In the proposed TRMSC, the time-related synchronization analysis is first conducted on the single channel electrophysiological signal, i.e., Electroencephalogram (EEG) and Electrooculogram (EOG), to explore the time-related patterns, and the spectral activation features are also extracted by spectrum analysis to obtain the multimodal features. With the extracted multimodal features, the feature fusion and selection strategy is utilized to obtain the optimal feature set and achieve robust sleep staging. To verify the effectiveness of the proposed TRMSC, sleep staging experiments were conducted on the Sleep-EDF dataset, and the experimental results indicate that the proposed TRMSC has achieved better performance than other existing strategies, which proves that the time-related synchronization features can make up for the shortcomings of traditional spectrum-based strategies and achieve a higher classification accuracy. The proposed TRMSC model may be helpful for portable sleep analyzers and provide a new analytical method for clinical sleeping research.

Arene-, Chlorido-, and Imido-Uranium Bis- and Tris(boryloxide) Complexes.

We introduce the boryloxide ligand {(HCNDipp)2BO}- (NBODipp, Dipp = 2,6-di-isopropylphenyl) to actinide chemistry. Protonolysis of [U{N(SiMe3)2}3] with 3 equiv of NBODippH produced the uranium(III) tris(boryloxide) complex [U(NBODipp)3] (1). In contrast, treatment of UCl4 with 3 equiv of NBODippK in THF at room temperature or reflux conditions produced only [U(NBODipp)2(Cl)2(THF)2] (2) with 1 equiv of NBODippK remaining unreacted. However, refluxing the mixture of 2 and unreacted NBODippK in toluene instead of THF afforded the target complex [U(NBODipp)3(Cl)(THF)] (3). Two-electron oxidation of 1 with AdN3 (Ad = 1-adamantyl) afforded the uranium(V)-imido complex [U(NBODipp)3(NAd)] (4). The solid-state structure of 1 reveals a uranium-arene bonding motif, and structural, spectroscopic, and DFT calculations all suggest modest uranium-arene δ-back-bonding with approximately equal donation into the arene π4 and π5 δ-symmetry π* molecular orbitals. Complex 4 exhibits a short uranium(V)-imido distance, and computational modeling enabled its electronic structure to be compared to related uranium-imido and uranium-oxo complexes, revealing a substantial 5f-orbital crystal field splitting and extensive mixing of 5f |ml,ms⟩ states and mj projections. Complexes 1-4 have been variously characterized by single-crystal X-ray diffraction, 1H NMR, IR, UV/vis/NIR, and EPR spectroscopies, SQUID magnetometry, elemental analysis, and CONDON, F-shell, DFT, NLMO, and QTAIM crystal field and quantum chemical calculations.

Spermidine-Functionalized Injectable Hydrogel Reduces Inflammation and Enhances Healing of Acute and Diabetic Wounds In Situ.

The inflammatory response is a key factor affecting tissue regeneration. Inspired by the immunomodulatory role of spermidine, an injectable double network hydrogel functionalized with spermidine (DN-SPD) is developed, where the first and second networks are formed by dynamic imine bonds and non-dynamic photo-crosslinked bonds respectively. The single network hydrogel before photo-crosslinking exhibits excellent injectability and thus can be printed and photo-crosslinked in situ to form double network hydrogels. DN-SPD hydrogel has demonstrated desirable mechanical properties and tissue adhesion. More importantly, an "operando" comparison of hydrogels loaded with spermidine or diethylenetriamine (DETA), a sham molecule resembling spermidine, has shown similar physical properties, but quite different biological functions. Specifically, the outcomes of 3 sets of in vivo animal experiments demonstrate that DN-SPD hydrogel can not only reduce inflammation caused by implanted exogenous biomaterials and reactive oxygen species but also promote the polarization of macrophages toward regenerative M2 phenotype, in comparison with DN-DETA hydrogel. Moreover, the immunoregulation by spermidine can also translate into faster and more natural healing of both acute wounds and diabetic wounds. Hence, the local administration of spermidine affords a simple but elegant approach to attenuate foreign body reactions induced by exogenous biomaterials to treat chronic refractory wounds.

Biogenesis of Rab14-positive endosome buds at Golgi-endosome contacts by the RhoBTB3-SHIP164-Vps26B complex.

Early endosomes (EEs) are crucial in cargo sorting within vesicular trafficking. While cargoes destined for degradation are retained in EEs and eventually transported to lysosomes, recycled cargoes for the plasma membrane (PM) or the Golgi undergo segregation into specialized membrane structures known as EE buds during cargo sorting. Despite this significance, the molecular basis of the membrane expansion during EE bud formation has been poorly understood. In this study, we identify a protein complex comprising SHIP164, an ATPase RhoBTB3, and a retromer subunit Vps26B, which promotes the formation of EE buds at Golgi-EE contacts. Our findings reveal that Vps26B acts as a novel Rab14 effector, and Rab14 activity regulates the association of SHIP164 with EEs. Depletion of SHIP164 leads to enlarged Rab14+ EEs without buds, a phenotype rescued by wild-type SHIP164 but not the lipid transfer-defective mutants. Suppression of RhoBTB3 or Vps26B mirrors the effects of SHIP164 depletion. Together, we propose a lipid transport-dependent pathway mediated by the RhoBTB3-SHIP164-Vps26B complex at Golgi-EE contacts, which is essential for EE budding.

Research landscape of energy transition and green finance: A bibliometric analysis.

This study utilizes bibliometric analysis to examine historical and present research patterns in the area of energy transition and green finance and to forecast potential future domains. Using the bibliometric method, 328 scholarly articles from the Web of Science database were evaluated. This paper identifies influential publications, maps the research landscape, and forecasts emerging tendencies through co-citation and co-word analyses. Co-citation analysis found three main clusters, while co-word analysis revealed four main clusters. Despite the growing significance of research on energy transition and green finance research, further in-depth investigation is necessary to offer a thorough depiction of the research domain. This research represents a pioneering endeavour in the utilization of bibliometric analysis to investigate the interrelationship between two items. It offers valuable insights into the rapidly expanding field of energy transition and green finance, effectively highlighting its contours and indicating potential future developments.

Large-scale interplant exchange of macromolecules between soybean and dodder under nutrient stresses.

Parasitic plants and their hosts communicate through haustorial connections. Nutrient deficiency is a common stress for plants, yet little is known about whether and how host plants and parasites communicate during adaptation to such nutrient stresses. In this study, we used transcriptomics and proteomics to analyze how soybean (Glycine max) and its parasitizing dodder (Cuscuta australis) respond to nitrate and phosphate deficiency (-N and -P). After -N and -P treatment, the soybean and dodder plants exhibited substantial changes of transcriptome and proteome, although soybean plants showed very few transcriptional responses to -P and dodder did not show any transcriptional changes to either -N or -P. Importantly, large-scale interplant transport of mRNAs and proteins was detected. Although the mobile mRNAs only comprised at most 0.2% of the transcriptomes, the foreign mobile proteins could reach 6.8% of the total proteins, suggesting that proteins may be the major forms of interplant communications. Furthermore, the interplant mobility of macromolecules was specifically affected by the nutrient regimes and the transport of these macromolecules was very likely independently regulated. This study provides new insight into the communication between host plants and parasites under stress conditions.

Core bacteria and fungi in response to residue retention and their contribution to soil multifunctionality in maize agroecosystem.

Core microbiome has been proven to play crucial roles in soil function. However, we still lack knowledge on how core microbiome responds to crop residue retention, and whether they contribute to this process. Consequently, we examined the effect of residue retention on soil core and non-core microbial communities in maize seedling, mature stage and freezing period based on a multi-site field experiment in Sanjiang Plain, Northeast China. Totally, 247 bacterial amplicon sequence variants (ASVs) and 109 fungal ASVs were identified as core microbiota. Both core and non-core bacterial/fungal community composition were significantly influenced by residue retention across all study sites. Especially, the core fungal community shifted towards a saprotroph-dominated community. Normalized stochastic ratio pattern revealed that that deterministic process dominated both core and non-core microbial community assembly processes. Residue retention enhanced the deterministic process of core microbial community assembly, while exhibited opposite effect on non-core microbial community. This study also revealed that soil fungi were more sensitive to residue retention than bacteria, with a larger proportion of core fungi were enriched or depleted by residue retention. In addition, residue retention complicated core bacterial co-occurrence network, while simplified fungal network. Our results pointed out both no reduction in microbial diversity or collapse in microbial network structure after repeated freezing-thawing cycles. The potential function of core microbiome was evaluated through random forest analysis and structural equation model, the results indicated core microbiome contributed more to multifunctionality than non-core microbiome. Overall, this study strengthened our understanding of soil core microbiome in response to residue retention, and highlighted their importance in maintaining soil multifunctionality.

Nitrogen deposition mediates more stochastic processes in structuring plant community than soil microbial community in the Eurasian steppe.

Anthropogenic environmental changes may affect community assembly through mediating both deterministic (e.g., competitive exclusion and environmental filtering) and stochastic processes (e.g., birth/death and dispersal/colonization). It is traditionally thought that environmental changes have a larger mediation effect on stochastic processes in structuring soil microbial community than aboveground plant community; however, this hypothesis remains largely untested. Here we report an unexpected pattern that nitrogen (N) deposition has a larger mediation effect on stochastic processes in structuring plant community than soil microbial community (those <2 mm in diameter, including archaea, bacteria, fungi, and protists) in the Eurasian steppe. We performed a ten-year nitrogen deposition experiment in a semiarid grassland ecosystem in Inner Mongolia, manipulating nine rates (0-50 g N m-2 per year) at two frequencies (nitrogen added twice or 12 times per year) under two grassland management strategies (fencing or mowing). We separated the compositional variation of plant and soil microbial communities caused by each treatment into the deterministic and stochastic components with a recently-developed method. As nitrogen addition rate increased, the relative importance of stochastic component of plant community first increased and then decreased, while that of soil microbial community first decreased and then increased. On the whole, the relative importance of stochastic component was significantly larger in plant community (0.552±0.035; mean±standard error) than in microbial community (0.427±0.035). Consistently, the proportion of compositional variation explained by the deterministic soil and community indices was smaller for plant community (0.172-0.186) than microbial community (0.240-0.767). Meanwhile, as nitrogen addition rate increased, the linkage between plant and microbial community composition first became weaker and then became stronger. The larger stochasticity in plant community relative to microbial community assembly suggested that more stochastic strategies (e.g., seeds addition) should be adopted to maintain above- than below-ground biodiversity under the pressure of nitrogen deposition.

The terrestrial end-Permian mass extinction in the paleotropics postdates the marine extinction.

The end-Permian mass extinction was the most severe ecological event during the Phanerozoic and has long been presumed contemporaneous across terrestrial and marine realms with global environmental deterioration triggered by the Siberian Traps Large Igneous Province. We present high-precision zircon U-Pb geochronology by the chemical abrasion-isotope dilution-thermal ionization mass spectrometry technique on tuffs from terrestrial to transitional coastal settings in Southwest China, which reveals a protracted collapse of the Cathaysian rainforest beginning after the onset of the end-Permian marine extinction. Integrated with high-resolution geochronology from coeval successions, our results suggest that the terrestrial extinction occurred diachronously with latitude, beginning at high latitudes during the late Changhsingian and progressing to the tropics by the early Induan, spanning a duration of nearly 1 million years. This latitudinal age gradient may have been related to variations in surface warming with more degraded environmental conditions at higher latitudes contributing to higher extinction rates.

EEG based emotion recognition by hierarchical bayesian spectral regression framework.

Spectral regression (SR), a graph-based learning regression model, can be used to extract features from graphs to realize efficient dimensionality reduction. However, due to the SR method remains a regularized least squares problem and being defined in L2-norm space, the effect of artifacts in EEG signals cannot be efficiently resisted. In this work, to further improve the robustness of the graph-based regression models, we propose to utilize the prior distribution estimation in the Bayesian framework and develop a robust hierarchical Bayesian spectral regression framework (named HB-SR), which is designed with the hierarchical Bayesian ensemble strategies. In the proposed HB-SR, the impact of noises can be effectively reduced by the adaptive adjustment approach in model parameters with the data-driven manner. Specifically, in the current work, three different distributions have been elaborately designed to enhance the universality of the proposed HB-SR, i.e., Gaussian distribution, Laplace distribution, and Student-t distribution. To objectively evaluate the performance of the HB-SR framework, we conducted both simulation studies and emotion recognition experiments based on emotional EEG signals. Experimental results have consistently indicated that compared with other existing spectral regression methods, the proposed HB-SR can effectively suppress the influence of noises and achieve robust EEG emotion recognition.

A hybrid graph network model for ASD diagnosis based on resting-state EEG signals.

Autism spectrum disorder (ASD) is a common neurodevelopmental disorder and early diagnosis is crucial for effective treatment. Stable and effective biomarkers are essential for understanding the underlying causes of the disorder and improving diagnostic accuracy. Electroencephalography (EEG) signals have proven to be reliable biomarkers for diagnosing ASD. Extracting stable connectivity patterns from EEG signals helps ensure robustness in ASD diagnostic systems. In this study, we propose a hybrid graph convolutional network framework called Rest-HGCN, which utilizes resting-state EEG signals to capture differential patterns of brain connectivity between normal children and ASD patients using graph learning strategies. The Rest-HGCN combines brain network analysis techniques and data-driven strategies to extract discriminative graph features from resting-state EEG signals. By automatically extracting differential graph patterns from these signals, the Rest-HGCN achieves reliable ASD diagnosis. To evaluate the performance of Rest-HGCN, we conducted ASD diagnosis experiments using k-fold cross-validation on the public ABC-CT resting EEG dataset. The proposed Rest-HGCN model achieved accuracies of 87.12 % and 85.32 % in single-subject and cross-experiment analyses, respectively. The results suggest that Rest-HGCN can effectively capture discriminant graph patterns from resting EEG signals and achieve robust ASD diagnosis. This may provide an effective and convenient tool for clinical ASD diagnosis.