FPTN: Fast Pure Transformer Network for Traffic Flow Forecasting

Traffic flow forecasting is challenging due to the intricate spatio-temporal correlations in traffic flow data. Existing Transformer-based methods usually treat traffic flow forecasting as multivariate time series (MTS) forecasting. However, too many sensors can cause a vector with a dimension greater than 800, which is difficult to process without information loss. In addition, these methods design complex mechanisms to capture spatial dependencies in MTS, resulting in slow forecasting speed. To solve the abovementioned problems, we propose a Fast Pure Transformer Network (FPTN) in this paper. First, the traffic flow data are divided into sequences along the sensor dimension instead of the time dimension. Then, to adequately represent complex spatio-temporal correlations, Three types of embeddings are proposed for projecting these vectors into a suitable vector space. After that, to capture the complex spatio-temporal correlations simultaneously in these vectors, we utilize Transformer encoder and stack it with several layers. Extensive experiments are conducted with 4 real-world datasets and 13 baselines, which demonstrate that FPTN outperforms the state-of-the-art on two metrics. Meanwhile, the computational time of FPTN spent is less than a quarter of other state-of-the-art Transformer-based models spent, and the requirements for computing resources are significantly reduced

A Novel Immune Classification for Predicting Immunotherapy Responsiveness in Patients With Adamantinomatous Craniopharyngioma

Adamantinomatous craniopharyngioma (ACP) is the most common tumor of the sellar region in children. The aggressive behavior of ACP challenges the treatment for it. However, immunotherapy is rarely studied in ACP. In this research, we performed unsupervised cluster analysis on the 725 immune-related genes and arrays of 39 patients with ACP patients in GSE60815 and GSE94349 databases. Two novel immune subtypes were identified, namely immune resistance (IR) subtype and immunogenic (IG) subtype. Interestingly, we found that the ACPs with IG subtype (34.78%, 8/23) were more likely to respond to immunotherapy than the ACPs with IR subtype (6.25%, 1/16) via tumor immune dysfunction and exclusion (TIDE) method. Simultaneously, the enrichment analysis indicated that the differentially expressed genes (DEGs) (p < 0.01, FDR < 0.01) of the IG subtype were chiefly involved in inflammatory and immune responses. However, the DEGs of the IR subtype were mainly involved in RNA processing. Next, immune infiltration analysis revealed a higher proportion of M2 macrophage in the IG subtype than that in the IR subtype. Compared with the IR subtype, the expression levels of immune checkpoint molecules (PD1, PDL1, PDL2, TIM3, CTLA4, Galectin9, LAG3, and CD86) were significantly upregulated in the IG subtype. The ssGSEA results demonstrated that the biofunction of carcinogenesis in the IG subtype was significantly enriched, such as lymphocyte infiltration, mesenchymal phenotype, stemness maintenance, and tumorigenic cytokines, compared with the IR subtype. Finally, a WDR89 (the DEG between IG and IR subtype)-based nomogram model was constructed to predict the immune classification of ACPs with excellent performance. This predictive model provided a reliable classification assessment tool for clinicians and aids treatment decision-making in the clinic

Defending against the Advanced Persistent Threat: An Optimal Control Approach

The new cyberattack pattern of advanced persistent threat (APT) has posed a serious threat to modern society. This paper addresses the APT defense problem, that is, the problem of how to effectively defend against an APT campaign. Based on a novel APT attack-defense model, the effectiveness of an APT defense strategy is quantified. Thereby, the APT defense problem is modeled as an optimal control problem, in which an optimal control stands for a most effective APT defense strategy. The existence of an optimal control is proved, and an optimality system is derived. Consequently, an optimal control can be figured out by solving the optimality system. Some examples of the optimal control are given. Finally, the influence of some factors on the effectiveness of an optimal control is examined through computer experiments. These findings help organizations to work out policies of defending against APTs

Comparative effects of two in situ hybridization methods for the pinewood nematode (Bursaphelenchus xylophilus)

The gene localization technique of Bursaphelenchus xylophilus (pinewood nematode, PWN) is used for study gene expression in PWNs. Two in situ hybridization methods, namely, whole-mount in situ hybridization and the cut-off method are used widely. To compare the effects of these two in situ hybridization methods, the present study investigated the patterns of two functional genes expression in PWNs. The Bx-vap-2 gene (GenBank accession number: OR228482), related to pathogenicity, and the fem-2 gene (GenBank accession number: OR228481), related to sex determination, were selected to map related genes in the whole-mount and amputated PWNs at different ages using these in situ hybridization methods. Based on the overall statistical comparison, we found that compared to the cut-off method, the whole-mount method exhibited higher staining rates and correct staining rates for the fem-2 gene and Bx-vap-2 gene. However, considering the correct staining aspect, the cut-off method yielded better staining effects on pinewood nematode sections than the whole-mount method, with clearer hybridization signal locations and less non-specific staining. In other words, the cut-off method demonstrated more precise gene localization. Both methods are applicable for gene localization, but considering the overall staining pattern, analysis of experimental results, and comprehensive experimental operations, we believe that the whole-mount method is more suitable for gene localization and expression analysis of development-related genes in pinewood nematodes. This is because intact pinewood nematodes are better suited for showcasing the continuous developmental process of development-related genes. On the other hand, considering the experimental time, accuracy of staining site, and the amount of non-specific staining, the cut-off method is more suitable for disease-related genes. Additionally, to achieve better performance, the cut-off method can be selectively applied to samples during the experimental process