Balanced Quantization: An Effective and Efficient Approach to Quantized Neural Networks

Quantized Neural Networks (QNNs), which use low bitwidth numbers for representing parameters and performing computations, have been proposed to reduce the computation complexity, storage size and memory usage. In QNNs, parameters and activations are uniformly quantized, such that the multiplications and additions can be accelerated by bitwise operations. However, distributions of parameters in Neural Networks are often imbalanced, such that the uniform quantization determined from extremal values may under utilize available bitwidth. In this paper, we propose a novel quantization method that can ensure the balance of distributions of quantized values. Our method first recursively partitions the parameters by percentiles into balanced bins, and then applies uniform quantization. We also introduce computationally cheaper approximations of percentiles to reduce the computation overhead introduced. Overall, our method improves the prediction accuracies of QNNs without introducing extra computation during inference, has negligible impact on training speed, and is applicable to both Convolutional Neural Networks and Recurrent Neural Networks. Experiments on standard datasets including ImageNet and Penn Treebank confirm the effectiveness of our method. On ImageNet, the top-5 error rate of our 4-bit quantized GoogLeNet model is 12.7\%, which is superior to the state-of-the-arts of QNNs

STGC-GNNs: A GNN-based traffic prediction framework with a spatial-temporal Granger causality graph

The key to traffic prediction is to accurately depict the temporal dynamics of traffic flow traveling in a road network, so it is important to model the spatial dependence of the road network. The essence of spatial dependence is to accurately describe how traffic information transmission is affected by other nodes in the road network, and the GNN-based traffic prediction model, as a benchmark for traffic prediction, has become the most common method for the ability to model spatial dependence by transmitting traffic information with the message passing mechanism. However, existing methods model a local and static spatial dependence, which cannot transmit the global-dynamic traffic information (GDTi) required for long-term prediction. The challenge is the difficulty of detecting the precise transmission of GDTi due to the uncertainty of individual transport, especially for long-term transmission. In this paper, we propose a new hypothesis\: GDTi behaves macroscopically as a transmitting causal relationship (TCR) underlying traffic flow, which remains stable under dynamic changing traffic flow. We further propose spatial-temporal Granger causality (STGC) to express TCR, which models global and dynamic spatial dependence. To model global transmission, we model the causal order and causal lag of TCRs global transmission by a spatial-temporal alignment algorithm. To capture dynamic spatial dependence, we approximate the stable TCR underlying dynamic traffic flow by a Granger causality test. The experimental results on three backbone models show that using STGC to model the spatial dependence has better results than the original model for 45 min and 1 h long-term prediction.Comment: 14 pages, 16 figures, 4 table

Correlations between negative life events and suicidal ideation among Chinese adolescents: a meta-analysis

BackgroundSuicide ideation (SI) has become a serious social issue worldwide, and research has found a certain correlation between negative life events (NLE) and SI. Nevertheless, this relationship is still not clear among Chinese adolescents, a special population. Hence, this investigation performed a meta-analysis of observational research on the correlation between NLE and SI among adolescents in China, to further clarify the association.MethodsWe performed an extensive search on seven electronic databases starting from their establishment until March 10, 2023. The research mainly focused on cross-sectional studies conducted on samples of Chinese adolescents. To examine the association between NLE and SI, a meta-analysis model using random effects was utilized. To investigate moderating factors such as age, region, assessment tools for SI, and year of publication, subgroup and meta-regression analyses were performed. The AHRQ evaluated the quality of the study. The synthesis of data was conducted utilizing STATA software (version 16).ResultsUltimately, a total of 30 cross-sectional studies were selected for this analysis, including 39,602 individuals in the participant sample. The results showed that NLE was moderately positively correlated with SI among Chinese adolescents (r = 0.29, 95% CI: 0.26, 0.32). In addition, this relationship was moderated by regional differences and the measurement tool used for SI. Studies conducted in Western China showed a higher correlation coefficient than those conducted in Eastern and Central China. Moreover, research conducted with the SSIOSS demonstrated a stronger correlation coefficient compared to studies utilizing the BSI-CV or other assessment instruments.ConclusionThis meta-analysis indicates that NLE is linked to SI in Chinese teenagers, especially those residing in Western regions of China. Identifying and intervening in NLE and associated risk factors are crucial to prevent suicide within this demographic

Genome-wide analysis of the TCP gene family and their expression pattern in Cymbidium goeringii

TCP gene family are specific transcription factors for plant, and considered to play an important role in development and growth. However, few related studies investigated the TCP gene trait and how it plays a role in growth and development of Orchidaceae. In this study, we obtained 14 TCP genes (CgTCPs) from the Spring Orchid Cymbidium goeringii genome. The classification results showed that 14 CgTCPs were mainly divided into two clades as follows: four PCF genes (Class I), nine CIN genes and one CYC gene (Class II). The sequence analysis showed that the TCP proteins of C. goeringii contain four conserved regions (basic Helix-Loop-Helix) in the TCP domain. The exon−intron structure varied in the clade according to a comparative investigation of the gene structure, and some genes had no introns. There are fewer CgTCP homologous gene pairs compared with Dendrobium catenatum and Phalaenopsis equestris, suggesting that the TCP genes in C. goeringii suffered more loss events. The majority of the cis-elements revealed to be enriched in the function of light responsiveness, followed by MeJA and ABA responsiveness, demonstrating their functions in regulating by light and phytohormones. The collinearity study revealed that the TCPs in D. catenatum, P. equestris and C. goeringii almost 1:1. The transcriptomic data and real-time reverse transcription-quantitative PCR (RT−qPCR) expression profiles showed that the flower-specific expression of the TCP class II genes (CgCIN2, CgCIN5 and CgCIN6) may be related to the regulation of florescence. Altogether, this study provides a comprehensive analysis uncovering the underlying function of TCP genes in Orchidaceae

Self-Supervised Spatiotemporal Masking Strategy-Based Models for Traffic Flow Forecasting

Traffic flow forecasting is an important function of intelligent transportation systems. With the rise of deep learning, building traffic flow prediction models based on deep neural networks has become a current research hotspot. Most of the current traffic flow prediction methods are designed from the perspective of model architectures, using only the traffic features of future moments as supervision signals to guide the models to learn the spatiotemporal dependence in traffic flow. However, traffic flow data themselves contain rich spatiotemporal features, and it is feasible to obtain additional self-supervised signals from the data to assist the model to further explore the underlying spatiotemporal dependence. Therefore, we propose a self-supervised traffic flow prediction method based on a spatiotemporal masking strategy. A framework consisting of symmetric backbone models with asymmetric task heads were applied to learn both prediction and spatiotemporal context features. Specifically, a spatiotemporal context mask reconstruction task was designed to force the model to reconstruct the masked features via spatiotemporal context information, so as to assist the model to better understand the spatiotemporal contextual associations in the data. In order to avoid the model simply making inferences based on the local smoothness in the data without truly learning the spatiotemporal dependence, we performed a temporal shift operation on the features to be reconstructed. The experimental results showed that the model based on the spatiotemporal context masking strategy achieved an average prediction performance improvement of 1.56% and a maximum of 7.72% for longer prediction horizons of more than 30 min compared with the backbone models

Whole-Genome Analysis of ZF-HD Genes among Three <i>Dendrobium</i> Species and Expression Patterns in <i>Dendrobium chrysotoxum</i>

ZF-HD transcription factors, which are unique to land plants, are involved in the regulation of abiotic stress response and related signaling pathways, and play a crucial role in plant growth and development. Dendrobium is one of the largest genera of orchids, with a high ornamental and ecological value. However, the specific functions of the ZF-HDs in Dendrobium remain unknown. In this study, we identified a total of 53 ZF-HDs from D. chrysotoxum (17), D. catenatum (23), and D. huoshanense (13), and analyzed their physicochemical properties, phylogenetic relationships, chromosomal locations, protein structures, conserved motifs, and expression patterns. The phylogenetic relationships revealed that 53 ZF-HDs were classified into six subfamilies (ZHDI–V and MIF), and all ZF-HD proteins contained motif 1 and motif 4 conserved domains, while a minority of these proteins had exons. The analysis of cis-elements in the promoters of ZF-HDs from three Dendrobium species showed that growth- and development-related elements were the most prevalent, followed by hormone response and abiotic stress response elements. Through collinearity analysis, 14 DchZF-HDs were found to be collinear with DhuZF-HDs, and 12 DchZF-HDs were found to be collinear with DcaZF-HDs. Furthermore, RT-qPCR analysis revealed that DchZF-HDs play a regulatory role in the development of lateral organs during the flowering process. The results indicated that DchZHD2 plays a role in the unpigmented bud stage, while DchMIF8 and DchZHD16 play significant roles during the pigmented bud and initial bloom stages. Hence, this study provides a crucial basis for further exploring ZF-HDs functions in regulating the floral organs of orchids

Genome-Based Identification of the Dof Gene Family in Three <i>Cymbidium</i> Species and Their Responses to Heat Stress in <i>Cymbidium goeringii</i>

As an important genus in Orchidaceae, Cymbidium has rich ecological diversity and significant economic value. DNA binding with one zinc finger (Dof) proteins are pivotal plant-specific transcription factors that play crucial roles in the growth, development, and stress response of plants. Although the Dof genes have been identified and functionally analyzed in numerous plants, exploration in Orchidaceae remains limited. We conducted a thorough analysis of the Dof gene family in Cymbidium goeringii, C. ensifolium, and C. sinensis. In total, 91 Dof genes (27 CgDofs, 34 CeDofs, 30 CsDofs) were identified, and Dof genes were divided into five groups (I–V) based on phylogenetic analysis. All Dof proteins have motif 1 and motif 2 conserved domains and over half of the genes contained introns. Chromosomal localization and collinearity analysis of Dof genes revealed their evolutionary relationships and potential gene duplication events. Analysis of cis-elements in CgDofs, CeDofs, and CsDofs promoters showed that light-responsive cis-elements were the most common, followed by hormone-responsive elements, plant growth-related elements, and abiotic stress response elements. Dof proteins in three Cymbidium species primarily exhibit a random coil structure, while homology modeling exhibited significant similarity. In addition, RT-qPCR analysis showed that the expression levels of nine CgDofs changed greatly under heat stress. CgDof03, CgDof22, CgDof27, CgDof08, and CgDof23 showed varying degrees of upregulation. Most upregulated genes under heat stress belong to group I, indicating that the Dof genes in group I have great potential for high-temperature resistance. In conclusion, our study systematically demonstrated the molecular characteristics of Dof genes in different Cymbidium species, preliminarily revealed the patterns of heat stress, and provided a reference for further exploration of stress breeding in orchids

Genome-Wide Identification and Expression Analysis of the GRAS Gene Family and Their Responses to Heat Stress in <i>Cymbidium goeringii</i>

The GRAS gene family, responsible for encoding transcription factors, serves pivotal functions in plant development, growth, and responses to stress. The exploration of the GRAS gene family within the Orchidaceae has been comparatively limited, despite its identification and functional description in various plant species. This study aimed to conduct a thorough examination of the GRAS gene family in Cymbidum goeringii, focusing on its physicochemical attributes, phylogenetic associations, gene structure, cis-acting elements, and expression profiles under heat stress. The results show that a total of 54 CgGRASs were pinpointed from the genome repository and categorized into ten subfamilies via phylogenetic associations. Assessment of gene sequence and structure disclosed the prevalent existence of the VHIID domain in most CgGRASs, with around 57.41% (31/54) CgGRASs lacking introns. The Ka/Ks ratios of all CgGRASs were below one, indicating purifying selection across all CgGRASs. Examination of cis-acting elements unveiled the presence of numerous elements linked to light response, plant hormone signaling, and stress responsiveness. Furthermore, CgGRAS5 contained the highest quantity of cis-acting elements linked to stress response. Experimental results from RT-qPCR demonstrated notable variations in the expression levels of eight CgGRASs after heat stress conditions, particularly within the LAS, HAM, and SCL4/7 subfamilies. In conclusion, this study revealed the expression pattern of CgGRASs under heat stress, providing reference for further exploration into the roles of CgGRAS transcription factors in stress adaptation

Genome-Wide Identification and Expression Analysis of the SPL Gene Family in Three Orchids

SPL transcription factors regulate important processes such as plant growth and development, metabolic regulation, and abiotic stress. They play crucial roles in the development of flower organs. However, little is known about the characteristics and functions of the SPLs in the Orchidaceae. In this study, Cymbidium goeringii Rchb. f., Dendrobium chrysotoxum Lindl., and Gastrodia elata BI. were used as research objects. The SPL gene family of these orchids was analyzed on a genome-wide scale, and their physicochemical properties, phylogenetic relationships, gene structures, and expression patterns were studied. Transcriptome and qRT-PCR methods were combined to investigate the regulatory effect of SPLs on the development of flower organs during the flowering process (bud, initial bloom, and full bloom). This study identifies a total of 43 SPLs from C. goeringii (16), D. chrysotoxum (17), and G. elata (10) and divides them into eight subfamilies according to the phylogenetic tree. Most SPL proteins contained conserved SBP domains and complex gene structures; half of the genes had introns longer than 10 kb. The largest number and variety of cis-acting elements associated with light reactions were enriched, accounting for about 45% of the total (444/985); 13/43 SPLs contain response elements of miRNA156. GO enrichment analysis showed that the functions of most SPLs were mainly enriched in the development of plant flower organs and stems. In addition, expression patterns and qRT-PCR analysis suggested the involvement of SPL genes in the regulation of flower organ development in orchids. There was little change in the expression of the CgoSPL in C. goeringii, but DchSPL9 and GelSPL2 showed significant expression during the flowering process of D. chrysotoxum and G. elata, respectively. In summary, this paper provides a reference for exploring the regulation of the SPL gene family in orchids