Accelerated Pure Shift NMR Spectroscopy with Deep Learning.

Pure shift nuclear magnetic resonance (NMR) spectroscopy presents a promising solution to provide sufficient spectral resolution and has been increasingly applied in various branches of chemistry, but the optimal resolution is generally accompanied by long experimental times. We present a proof of concept of deep learning for fast, high-quality, and reliable pure shift NMR reconstruction. The deep learning (DL) protocol allows one to eliminate undersampling artifacts, distinguish peaks with close chemical shifts, and reconstruct high-resolution pure shift NMR spectroscopy along with accelerated acquisition. More meaningfully, the lightweight neural network delivers satisfactory reconstruction performance on personal computers by several hundred simulated data learning, which somewhat lifts the prohibiting demand for a large volume of real training samples and advanced computing hardware generally required in DL projects. Additionally, an M-to-S strategy applicable to common DL cases is further exploited to boost the network generalization capability. As a result, this study takes a meaningful step toward deep learning protocols for broad chemical applications.

Identifying ADHD-Related Abnormal Functional Connectivity with a Graph Convolutional Neural Network.

Attention deficit hyperactivity disorder (ADHD) is a common neurodevelopmental disorder that is characterized by inattention, hyperactivity, and impulsivity. The neural mechanisms underlying ADHD remain inadequately understood, and current approaches do not well link neural networks and attention networks within brain networks. Our objective is to investigate the neural mechanisms related to attention and explore neuroimaging biological tags that can be generalized within the attention networks. In this paper, we utilized resting-state functional magnetic resonance imaging data to examine the differential functional connectivity network between ADHD and typically developing individuals. We employed a graph convolutional neural network model to identify individuals with ADHD. After classification, we visualized brain regions with significant contributions to the classification results. Our results suggest that the frontal, temporal, parietal, and cerebellar regions are likely the primary areas of dysfunction in individuals with ADHD. We also explored the relationship between regions of interest and attention networks, as well as the connection between crucial nodes and the distribution of positively and negatively correlated connections. This analysis allowed us to pinpoint the most discriminative brain regions, including the right orbitofrontal gyrus, the left rectus gyrus and bilateral insula, the right inferior temporal gyrus and bilateral transverse temporal gyrus in the temporal region, and the lingual gyrus of the occipital lobe, multiple regions of the basal ganglia and the upper cerebellum. These regions are primarily involved in the attention executive control network and the attention orientation network. Dysfunction in the functional connectivity of these regions may contribute to the underlying causes of ADHD.

Quantifying the Impact of Environment Loads on Displacements in a Suspension Bridge with a Data-Driven Approach.

Long-span bridges are susceptible to damage, aging, and deformation in harsh environments for a long time. Therefore, structural health monitoring (SHM) systems need to be used for reasonable monitoring and maintenance. Among various indicators, bridge displacement is a crucial parameter reflecting the bridge's health condition. Due to the simultaneous bearing of multiple environmental loads on suspension bridges, determining the impact of different loads on displacement is beneficial for the better understanding of the health conditions of the bridges. Considering the fact that extreme gradient boosting (XGBoost) has higher prediction performance and robustness, the authors of this paper have developed a data-driven approach based on the XGBoost model to quantify the impact between different environmental loads and the displacement of a suspension bridge. Simultaneously, this study combined wavelet threshold (WT) denoising and the variational mode decomposition (VMD) method to conduct a modal decomposition of three-dimensional (3D) displacement, further investigating the interrelationships between different loads and bridge displacements. This model links wind speed, temperature, air pressure, and humidity with the 3D displacement response of the span using the bridge monitoring data provided by the GNSS and Earth Observation for Structural Health Monitoring (GeoSHM) system of the Forth Road Bridge (FRB) in the United Kingdom (UK), thus eliminating the temperature time-lag effect on displacement data. The effects of the different loads on the displacement are quantified individually with partial dependence plots (PDPs). Employing testing, it was found that the XGBoost model has a high predictive effect on the target variable of displacement. The analysis of quantification and correlation reveals that lateral displacement is primarily affected by same-direction wind, showing a clear positive correlation, and vertical displacement is mainly influenced by temperature and exhibits a negative correlation. Longitudinal displacement is jointly influenced by various environmental loads, showing a positive correlation with atmospheric pressure, temperature, and vertical wind and a negative correlation with longitudinal wind, lateral wind, and humidity. The results can guide bridge structural health monitoring in extreme weather to avoid accidents.

A Discussion of Building a Smart SHM Platform for Long-Span Bridge Monitoring.

This paper explores the development of a smart Structural Health Monitoring (SHM) platform tailored for long-span bridge monitoring, using the Forth Road Bridge (FRB) as a case study. It discusses the selection of smart sensors available for real-time monitoring, the formulation of an effective data strategy encompassing the collection, processing, management, analysis, and visualization of monitoring data sets to support decision-making, and the establishment of a cost-effective and intelligent sensor network aligned with the objectives set through comprehensive communication with asset owners. Due to the high data rates and dense sensor installations, conventional processing techniques are inadequate for fulfilling monitoring functionalities and ensuring security. Cloud-computing emerges as a widely adopted solution for processing and storing vast monitoring data sets. Drawing from the authors' experience in implementing long-span bridge monitoring systems in the UK and China, this paper compares the advantages and limitations of employing cloud- computing for long-span bridge monitoring. Furthermore, it explores strategies for developing a robust data strategy and leveraging artificial intelligence (AI) and digital twin (DT) technologies to extract relevant information or patterns regarding asset health conditions. This information is then visualized through the interaction between physical and virtual worlds, facilitating timely and informed decision-making in managing critical road transport infrastructure.

Application of Response Surface-Corrected Finite Element Model and Bayesian Neural Networks to Predict the Dynamic Response of Forth Road Bridges under Strong Winds.

With the rapid development of big data, the Internet of Things (IoT), and other technological advancements, digital twin (DT) technology is increasingly being applied to the field of bridge structural health monitoring. Achieving the precise implementation of DT relies significantly on a dual-drive approach, combining the influence of both physical model-driven and data-driven methodologies. In this paper, two methods are proposed to predict the displacement and dynamic response of structures under strong winds, namely, a Bayesian Neural Network (BNN) model based on Bayesian inference and a finite element model (FEM) method modified based on genetic algorithms (GAs) and multi-objective optimization (MOO) using response surface methodology (RSM). The characteristics of these approaches in predicting the dynamic response of large-span bridges are explored, and a comparative analysis is conducted to evaluate their differences in computational accuracy, efficiency, model complexity, interpretability, and comprehensiveness. The characteristics of the two methods were evaluated using data collected on the Forth Road Bridge (FRB) as an example under unusual weather conditions with strong wind action. This work proposes a dual-driven approach, integrating machine learning and FEM with GNSS and Earth Observation for Structural Health Monitoring (GeoSHM), to bridge the gap in the limited application of dual-driven methods primarily applied for small- and medium-sized bridges to large-span bridge structures. The research results show that the BNN model achieved higher R2 values for predicting the Y and Z displacements (0.9073 and 0.7969, respectively) compared to the FEM model (0.6167 and 0.6283). The BNN model exhibited significantly faster computation, taking only 20 s, while the FEM model required 5 h. However, the physical model provided higher interpretability and the ability to predict the dynamic response of the entire structure. These findings help to promote the further integration of these two approaches to obtain an accurate and comprehensive dual-driven approach for predicting the structural dynamic response of large-span bridge structures affected by strong wind loading.

A 5.5-kb LTR-retrotransposon insertion inside phytochrome B gene (CsPHYB) results in long hypocotyl and early flowering in cucumber (Cucumis sativus L.).

KEY MESSAGE: The novel spontaneous long hypocotyl and early flowering (lhef) mutation in cucumber is due to a 5551-bp LTR-retrotransposon insertion in CsPHYB gene encoding PHYTOCHROME B, which plays a major role in regulating photomorphogenic hypocotyl growth and flowering. Hypocotyl length and flowering time are important for establishing high-quality seedlings in modern cucumber production, but little is known for the underlying molecular mechanisms of these two traits. In this study, a spontaneous cucumber long hypocotyl and early flowering mutant was identified and characterized. Based on multiple lines of evidence, we show that cucumber phytochrome B (CsPHYB) is the candidate gene for this mutation, and a 5551-bp LTR-retrotransposon insertion in the first exon of CsPHYB was responsible for the mutant phenotypes. Uniqueness of the mutant allele at CsPHYB was verified in 114 natural cucumber lines. Ectopic expression of the CsPHYB in Arabidopsis phyB mutant rescued the long hypocotyl and early flowering phenotype of phyB-9 mutant. The wild-type CsPHYB protein was localized on the membrane and cytoplasm under white light condition, whereas in the nucleus under red light, it is consistent with its roles as a red-light photoreceptor in Arabidopsis. However, the mutant csphyb protein was localized on the membrane and cytoplasm under both white and red-light conditions. Expression dynamics of CsPHYB and several cell elongation-related genes were positively correlated with hypocotyl elongation; the transcription levels of key positive and negative regulators for flowering time were also consistent with the anthesis dates in the mutant and wild-type plants. Yeast two hybrid and bimolecular fluorescence complementation assays identified physical interactions between CsPHYB and phytochrome interacting factor 3/4 (CsPIF3/4). These findings will provide new insights into the roles of the CsPHYB in cucumber hypocotyl growth and flowering time.

A mutation in CsHY2 encoding a phytochromobilin (PΦB) synthase leads to an elongated hypocotyl 1(elh1) phenotype in cucumber (Cucumis sativus L.).

KEY MESSAGE: The elongated hypocotyl1 (elh1) mutant in cucumber is due to a mutation in CsHY2, which is a homolog of the Arabidopsis HY2 encoding the phytochromobilin (PΦB) synthase for phytochrome biosynthesis Hypocotyl length is a critical determinant in establishing high quality seedlings for successful cucumber production, but knowledge on the molecular regulation of hypocotyl growth in cucumber is very limited. Here, we reported identification and characterization of a cucumber elongated hypocotyl 1 (elh1) mutant. We found that the longer hypocotyl in elh1 was due to longitudinal growth of hypocotyl cells. With fine mapping, the elh1 locus was delimited to a 20.9-kb region containing three annotated genes; only one polymorphism was identified in this region between two parental lines, which was a non-synonymous SNP (G28153633A) in the third exon of CsHY2 (CsGy1G030000) that encodes a phytochromobilin (PΦB) synthase. Uniqueness of the mutant allele at CsHY2 was verified in natural cucumber populations. Ectopic expression of CsHY2 in Arabidopsis hy2-1 long-hypocotyl mutant led to reduced hypocotyl length. The PΦB protein was targeted to the chloroplast. The expression levels of CsHY2 and five phytochrome genes CsPHYA1, CsPHYA2, CsPHYB, CsPHYC and CsPHYE were all significantly down-regulated while several cell elongation related genes were up-regulated in elh1 mutant compared to wild-type cucumber, which are correlated with dynamic hypocotyl elongation in the mutant. RNA-seq analysis in the WT and mutant revealed differentially expressed genes involved in porphyrin and chlorophyll metabolisms, cell elongation and plant hormone signal transduction pathways. This is the first report to characterize and clone the CsHY2 gene in cucumber. This work reveals the important of CsHY2 in regulating hypocotyl length and extends our understanding of the roles of CsHY2 in cucumber.

Preservation of the genetic diversity of a local common carp in the agricultural heritage rice-fish system.

We examined how traditional farmers preserve the genetic diversity of a local common carp (Cyprinus carpio), which is locally referred to as "paddy field carp" (PF-carp), in a "globally important agricultural heritage system" (GIAHS), i.e., the 1,200-y-old rice-fish coculture system in Zhejiang Province, China. Our molecular and morphological analysis showed that the PF-carp has changed into a distinct local population with higher genetic diversity and diverse color types. Within this GIAHS region, PF-carps exist as a continuous metapopulation, although three genetic groups could be identified by microsatellite markers. Thousands of small farmer households interdependently obtained fry and parental carps for their own rice-fish production, resulting in a high gene flow and large numbers of parent carps distributing in a mosaic pattern in the region. Landscape genetic analysis indicated that farmers' connectivity was one of the major factors that shaped this genetic pattern. Population viability analysis further revealed that the numbers of these interconnected small farmer households and their connection intensity affect the carps' inherent genetic diversity. The practice of mixed culturing of carps with diverse color types helped to preserve a wide range of genetic resources in the paddy field. This widespread traditional practice increases fish yield and resource use, which, in return, encourages famers to continue their practice of selecting and conserving diverse color types of PF-carp. Our results suggested that traditional farmers secure the genetic diversity of PF-carp and its viability over generations in this region through interdependently incubating and mixed-culturing practices within the rice-fish system.

Impact on sexual function of plasma button transurethral vapour enucleation versus plasmakinetic resection of the large prostate >90 ml: Results of a prospective, randomized trial.

To compare the impact of plasma button transurethral vapour enucleation of the prostate (PVEP) and plasmakinetic resection of the prostate (PKRP) on lower urinary tract symptoms and sexual function in patients with benign prostatic enlargement (BPE) >90 ml. Between July 2017 and August 2018, 101 patients with symptomatic BPE were randomly, prospectively assigned to either PKRP or PVEP in our department. The clinical characteristics and sexual function were evaluated before and after surgery. Post-void residual volume, IPSS and QoL were all significantly decreased compared with baseline data in each group, while Qmax was significantly increased. The IIEF-5 score showed a slight but nonsignificant increase in both groups at 3 and 6 months after surgery, and there was no significant difference between the two groups. The post-operative rate of reduced ejaculate volume was significantly higher than the pre-operative rate in PKRP group, while there was no significant difference in PVEP group. PVEP had an attenuated effect on no ejaculate compared with PRKP, and they both had a significantly negative effect on no ejaculate. PVEP is an effective and minimally invasive procedure for large prostate. Compared with PKRP, PVEP has no effect on erectile dysfunction and has a lower negative impact on ejaculation.

The maintenance of stable yield and high genetic diversity in the agricultural heritage torreya tree system.

BACKGROUND: Understanding how traditional agriculture systems have been maintained would help design sustainable agriculture. In this study, we examined how farmers have used two types of local trees (Torreya grandis) for stable yield and maintaining genetic diversity in the "globally important agricultural heritage torreya tree system". The two type of torreya trees are grafted torreya (GT) tree and non-grafted-torreya (NGT) tree. The GT tree has only female and was used to produced seed yields. The NGT tree has both male and female and was used to support GT tree by providing pollens and rootstocks. We first tested the ratio of GT tree to NGT tree, their age groups, ratio of female trees (including GT and NGT trees) to male, and the flowering period of GT and NGT trees. We then tested seed yields and genetic diversity of GT and NGT trees. We further tested gene flow among NGT trees, and the relationship of gene flow with exchange rates of pollens and seeds. RESULTS: GT and NGT trees (male and female) were planted in a mosaic pattern with a ratio of 4:1 (GT:NGT). In this planting pattern, one NGT male trees provided pollen for 20 female trees of GT and NGT. The trees were classified into four age groups (I = 100-400 years old; II = 400-700 years old; III = 700-1000 years old; and IV = 1000-1300 years old) based on basal diameter. The entire flowering period was longer for NGT trees than for GT trees that ensured GT trees (which lack of males) being exposed to pollens. GT tree had high and stable seed yield that increased with age groups. High genetic diversity has been maintained in both rootstocks of the GT trees and NGT trees. There was a strong gene flow among NGT trees, which positive correlated with the exchange rates of pollens and seeds. CONCLUSIONS: Our results suggest that farmers obtain stable seed yields, and maintain high genetic diversity by ingeniously using the local GT tree as yield producer and NGT tree as supporter. These GT and NGT trees together ensure sustainable torreya production.

Probucol improves erectile function via Activation of Nrf2 and coordinates the HO-1 / DDAH / PPAR-γ/ eNOS pathways in streptozotocin-induced diabetic rats.

BACKGROUND: Diabetic erectile dysfunction (DMED) is mainly attributed to oxidative stress, and Nrf2 plays an important role in cellular antioxidation and regulates NO production in the vascular endothelium. Probucol maintains endothelial function through its antioxidant activity. This study investigated the efficacy and mechanism of probucol in improving erectile function in streptozotocin-induced diabetic rats. METHODS: In our study, thirty 12-week-old Sprague-Dawley male rats were fasted for 12 h. All rats received a 1-time injection of intraperitoneal streptozotocin(60 mg/kg) or vehicle. After 72 h, STZ-treated rats (with random blood glucose concentrations consistently greater than 16.7 mmol/L) were considered diabetic. The diabetic rats were randomly assigned into 2 groups and treated with daily gavage feedings of probucol at doses of 0 and 500 mg/kg for 12 weeks. A positive control group underwent intraperitoneal injection of normal saline followed by daily gavage of saline solution. Erectile function was assessed by electrical stimulation of the cavernous nerves with real-time intracavernous pressure measurement. After euthanasia, penile tissue was investigated using immunohistochemistry, Western blot, and ELISA to assess the proteins of Nrf2/HO-1/DDAH/PPAR-γ/eNOS pathways. RESULTS: After treatment, the rats in the probucol group presented significantly improved erectile function (P < 0.05) than that of the diabetic group without probucol treatment (DM). Also, protein expression of Nrf2, DDAH, PPAR-γ, HO-1 and eNOS was significantly higher than that of the DM group (P < 0.05). CGMP concentrations and SOD concentrations of probucol-treated rats were higher than those of DM group (P < 0.05). The MDA levels and ADMA levels were significantly lower than those of DM group rats (P < 0.05). CONCLUSION: Probucol can improve erectile function via activation of Nrf2, which coordinates the HO-1/DDAH/PPAR-γ/eNOS pathways in streptozotocin-induced diabetic rats.

Mutations in CsPID encoding a Ser/Thr protein kinase are responsible for round leaf shape in cucumber (Cucumis sativus L.).

KEY MESSAGE: Two round-leaf mutants, rl-1 and rl-2, were identified from EMS-induced mutagenesis. High throughput sequencing and map-based cloning suggested CsPID encoding a Ser/Thr protein kinase as the most possible candidate for rl-1. Rl-2 was allelic to Rl-1. Leaf shape is an important plant architecture trait that is affected by plant hormones, especially auxin. In Arabidopsis, PINOID (PID), a regulator for the auxin polar transporter PIN (PIN-FORMED) affects leaf shape formation, but this function of PID in crop plants has not been well studied. From an EMS mutagenesis population, we identified two round-leaf (rl) mutants, C356 and C949. Segregation analysis suggested that both mutations were controlled by single recessive genes, rl-1 and rl-2, respectively. With map-based cloning, we show that CsPID as the candidate gene of rl-1; a non-synonymous SNP in the second exon of CsPID resulted in an amino acid substitution and the round leaf phenotype. As compared in the wild type plant, CsPID had significantly lower expression in the root, leaf and female flowers in C356, which may result in the less developed roots, round leaves and abnormal female flowers, respectively in the rl-1 mutant. Among the three copies of PID genes, CsPID, CsPID2 and CSPID2L (CsPID2-like) in the cucumber genome, CsPID was the only one with significantly differential expression in adult leaves between WT and C356 suggesting CsPID plays a main role in leaf shape formation. The rl-2 mutation in C949 was also cloned, which was due to another SNP in a nearby location of rl-1 in the same CsPID gene. The two round leaf mutants and the work presented herein provide a good foundation for understanding the molecular mechanisms of CsPID in cucumber leaf development.

De novo transcriptomic analysis of cowpea (Vigna unguiculata L. Walp.) for genic SSR marker development.

BACKGROUND: Cowpea [Vigna unguiculata (L.) Walp.] is one of the most important legumes in tropical and semi-arid regions. However, there is relatively little genomic information available for genetic research on and breeding of cowpea. The objectives of this study were to analyse the cowpea transcriptome and develop genic molecular markers for future genetic studies of this genus. RESULTS: Approximately 54 million high-quality cDNA sequence reads were obtained from cowpea based on Illumina paired-end sequencing technology and were de novo assembled to generate 47,899 unigenes with an N50 length of 1534 bp. Sequence similarity analysis revealed 36,289 unigenes (75.8%) with significant similarity to known proteins in the non-redundant (Nr) protein database, 23,471 unigenes (49.0%) with BLAST hits in the Swiss-Prot database, and 20,654 unigenes (43.1%) with high similarity in the Kyoto Encyclopedia of Genes and Genomes (KEGG) database. Further analysis identified 5560 simple sequence repeats (SSRs) as potential genic molecular markers. Validating a random set of 500 SSR markers yielded 54 polymorphic markers among 32 cowpea accessions. CONCLUSIONS: This transcriptomic analysis of cowpea provided a valuable set of genomic data for characterizing genes with important agronomic traits in Vigna unguiculata and a new set of genic SSR markers for further genetic studies and breeding in cowpea and related Vigna species.

The chlorophyll-deficient golden leaf mutation in cucumber is due to a single nucleotide substitution in CsChlI for magnesium chelatase I subunit.

KEY MESSAGE: The cucumber chlorophyll-deficient golden leaf mutation is due to a single nucleotide substitution in the CsChlI gene for magnesium chelatase I subunit which plays important roles in the chlorophyll biosynthesis pathway. The Mg-chelatase catalyzes the insertion of Mg(2+) into the protoporphyrin IX in the chlorophyll biosynthesis pathway, which is a protein complex encompassing three subunits CHLI, CHLD, and CHLH. Chlorophyll-deficient mutations in genes encoding the three subunits have played important roles in understanding the structure, function and regulation of this important enzyme. In an EMS mutagenesis population, we identified a chlorophyll-deficient mutant C528 with golden leaf color throughout its development which was viable and able to set fruits and seeds. Segregation analysis in multiple populations indicated that this leaf color mutation was recessively inherited and the green color showed complete dominance over golden color. Map-based cloning identified CsChlI as the candidate gene for this mutation which encoded the CHLI subunit of cucumber Mg-chelatase. The 1757-bp CsChlI gene had three exons and a single nucleotide change (G to A) in its third exon resulted in an amino acid substitution (G269R) and the golden leaf color in C528. This mutation occurred in the highly conserved nucleotide-binding domain of the CHLI protein in which chlorophyll-deficient mutations have been frequently identified. The mutant phenotype, CsChlI expression pattern and the mutated residue in the CHLI protein suggested the mutant allele in C528 is unique among mutations identified so far in different species. This golden leaf mutant not only has its potential in cucumber breeding, but also provides a useful tool in understanding the CHLI function and its regulation in the chlorophyll biosynthesis pathway as well as chloroplast development.

Deviation from niche optima affects the nature of plant-plant interactions along a soil acidity gradient.

There is increasing recognition of the importance of niche optima in the shift of plant-plant interactions along environmental stress gradients. Here, we investigate whether deviation from niche optima would affect the outcome of plant-plant interactions along a soil acidity gradient (pH = 3.1, 4.1, 5.5 and 6.1) in a pot experiment. We used the acid-tolerant species Lespedeza formosa Koehne as the neighbouring plant and the acid-tolerant species Indigofera pseudotinctoria Mats. or acid-sensitive species Medicago sativa L. as the target plants. Biomass was used to determine the optimal pH and to calculate the relative interaction index (RII). We found that the relationships between RII and the deviation of soil pH from the target's optimal pH were linear for both target species. Both targets were increasingly promoted by the neighbour as pH values deviated from their optima; neighbours benefitted target plants by promoting soil symbiotic arbuscular mycorrhizal fungi, increasing soil organic matter or reducing soil exchangeable aluminium. Our results suggest that the shape of the curve describing the relationship between soil pH and facilitation/competition depends on the soil pH optima of the particular species.

Ecological mechanisms underlying the sustainability of the agricultural heritage rice-fish coculture system.

For centuries, traditional agricultural systems have contributed to food and livelihood security throughout the world. Recognizing the ecological legacy in the traditional agricultural systems may help us develop novel sustainable agriculture. We examine how rice-fish coculture (RF), which has been designated a "globally important agricultural heritage system," has been maintained for over 1,200 y in south China. A field survey demonstrated that although rice yield and rice-yield stability are similar in RF and rice monoculture (RM), RF requires 68% less pesticide and 24% less chemical fertilizer than RM. A field experiment confirmed this result. We documented that a mutually beneficial relationship between rice and fish develops in RF: Fish reduce rice pests and rice favors fish by moderating the water environment. This positive relationship between rice and fish reduces the need for pesticides in RF. Our results also indicate a complementary use of nitrogen (N) between rice and fish in RF, resulting in low N fertilizer application and low N release into the environment. These findings provide unique insights into how positive interactions and complementary use of resource between species generate emergent ecosystem properties and how modern agricultural systems might be improved by exploiting synergies between species.

Decoding emotion with phase-amplitude fusion features of EEG functional connectivity network.

Decoding emotional neural representations from the electroencephalographic (EEG)-based functional connectivity network (FCN) is of great scientific importance for uncovering emotional cognition mechanisms and developing harmonious human-computer interactions. However, existing methods mainly rely on phase-based FCN measures (e.g., phase locking value [PLV]) to capture dynamic interactions between brain oscillations in emotional states, which fail to reflect the energy fluctuation of cortical oscillations over time. In this study, we initially examined the efficacy of amplitude-based functional networks (e.g., amplitude envelope correlation [AEC]) in representing emotional states. Subsequently, we proposed an efficient phase-amplitude fusion framework (PAF) to fuse PLV and AEC and used common spatial pattern (CSP) to extract fused spatial topological features from PAF for multi-class emotion recognition. We conducted extensive experiments on the DEAP and MAHNOB-HCI datasets. The results showed that: (1) AEC-derived discriminative spatial network topological features possess the ability to characterize emotional states, and the differential network patterns of AEC reflect dynamic interactions in brain regions associated with emotional cognition. (2) The proposed fusion features outperformed other state-of-the-art methods in terms of classification accuracy for both datasets. Moreover, the spatial filter learned from PAF is separable and interpretable, enabling a description of affective activation patterns from both phase and amplitude perspectives.

Music-emotion EEG coupling effects based on representational similarity.

BACKGROUND: Music can evoke intense emotions and music emotion is a complex cognitive process. However, we know little about the cognitive mechanisms underlying these processes, and there are significant individual differences in the emotional responses to the same musical stimuli. NEW METHOD: We used the inter-subject representational similarity analysis (IS-RSA) method to investigate the shared music emotion responses across multiple participants. In addition, we extended IS-RSA to estimate the group cross-frequency coupling effects of music emotion. Based on the cross-frequency coupling IS-RSA, we analyzed the differences in cross-frequency coupling patterns under different music emotions using MI. Comparison of existing methods: most current IS-RSA analyses focus on within-frequency band analysis. However, the cognitive processing of music emotion involves not only activation and brain network connections differences within frequency bands but also information communication between frequency bands. RESULTS: The results of the within-frequency band IS-RSA analysis showed that the theta and gamma frequency bands play important roles in the inter-participant consistency of music emotion. The inter-frequency band IS-RSA analysis showed that the theta-beta coupling pattern exhibited stronger inter-participant consistency compared to the theta-gamma coupling pattern, and the theta-beta coupling had significant consistent representation across various music conditions. Through the significant regions of cross-frequency coupling representation similarity analysis, we performed phase-amplitude coupling analysis on FC4-C6 and FC4-Pz connections. For the theta-beta coupling pattern, we found that the MI of these two connections exhibited different coupling patterns under different music conditions, and they showed a significant decrease compared to the baseline period.

Research progress on plant functional traits in agroecosystems.

Plant functional traits have an essential role in community formation and ecosystem function. Unlike natu-ral ecosystems, agroecosystems are affected by natural conditions and human management. Plant (i.e., crop)functional traits in the agroecosystems are thus shaped by natural and human selection. We reviewed the development of functional trait research, focusing on crop functional traits, research methods of agroecosystems based on traits, and the application of functional traits in agriculture. We then elaborated on the effect of domestication on crop trait trade-offs, the relationship between community functional structure and agroecosystem services, and the application of functional traits in weed management, cover cropping, and intercropping systems. Future research directions of crop functional traits include enriching the types of agroecosystems and crop species in studies, buil-ding up a crop functional trait database, and focusing on agroecosystem multifunctionality.