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A bstract We study spinning particle/defect geometries in the context of AdS 3 /CFT 2 . These solutions lie below the BTZ threshold, and can be obtained from identifications of AdS 3 . We construct the Feynman propagator by solving the bulk equation of motion in the spinning particle geometry, summing over the modes of the fields and passing to the boundary. The quantization of the scalar fields becomes challenging when confined to the regions that are causally well-behaved. If the region containing closed timelike curves (CTCs) is included, the normalization of the scalar fields enjoys an analytical simplification and the propagator can be expressed as an infinite sum over image geodesics. In the dual CFT 2 , the propagator can be recast as the HHLL four-point function, where by taking into account the PSL(2, ℤ ) modular images, we recover the bulk computation. We comment on the casual behavior of bulk geometries associated with single-trace operators of spin scaling with the central charge below the BTZ threshold.

In the analysis of high-throughput data from complex samples, cell composition is an important factor that needs to be accounted for. Except for a limited number of tissues with known pure cell type profiles, a majority of genomics and epigenetics data relies on the “reference-free deconvolution” methods to estimate cell composition. We develop a novel computational method to improve reference-free deconvolution, which iteratively searches for cell type-specific features and performs composition estimation. Simulation studies and applications to six real datasets including both DNA methylation and gene expression data demonstrate favorable performance of the proposed method. TOAST is available at https://bioconductor.org/packages/TOAST .

Single-cell RNA sequencing (scRNA-seq) is a versatile tool for discovering and annotating cell types and states, but the determination and annotation of cell subtypes is often subjective and arbitrary. Often, it is not even clear whether a given cluster is uniform. Here we present an entropy-based statistic, ROGUE, to accurately quantify the purity of identified cell clusters. We demonstrate that our ROGUE metric is broadly applicable, and enables accurate, sensitive and robust assessment of cluster purity on a wide range of simulated and real datasets. Applying this metric to fibroblast, B cell and brain data, we identify additional subtypes and demonstrate the application of ROGUE-guided analyses to detect precise signals in specific subpopulations. ROGUE can be applied to all tested scRNA-seq datasets, and has important implications for evaluating the quality of putative clusters, discovering pure cell subtypes and constructing comprehensive, detailed and standardized single cell atlas. Single cell RNA-seq is a powerful method to assign cell identity, but the purity of cell clusters arising from this data is not clear. Here the authors present an entropy-based statistic called ROGUE to quantify the purity of cell clusters, and identify subtypes within clusters.

Emotion recognition based on physiological signals has been a hot topic and applied in many areas such as safe driving, health care and social security. In this paper, we present a comprehensive review on physiological signal-based emotion recognition, including emotion models, emotion elicitation methods, the published emotional physiological datasets, features, classifiers, and the whole framework for emotion recognition based on the physiological signals. A summary and comparation among the recent studies has been conducted, which reveals the current existing problems and the future work has been discussed.

The fast-advancing single cell RNA sequencing (scRNA-seq) technology enables researchers to study the transcriptome of heterogeneous tissues at a single cell level. The initial important step of analyzing scRNA-seq data is usually to accurately annotate cells. The traditional approach of annotating cell types based on unsupervised clustering and marker genes is time-consuming and laborious. Taking advantage of the numerous existing scRNA-seq databases, many supervised label assignment methods have been developed. One feature that many label assignment methods shares is to label cells with low confidence as “unassigned.” These unassigned cells can be the result of assignment difficulties due to highly similar cell types or caused by the presence of unknown cell types. However, when unknown cell types are not expected, existing methods still label a considerable number of cells as unassigned, which is not desirable. In this work, we develop a neural network-based cell annotation method called NeuCA (Neural network-based Cell Annotation) for scRNA-seq data obtained from well-studied tissues. NeuCA can utilize the hierarchical structure information of the cell types to improve the annotation accuracy, which is especially helpful when data contain closely correlated cell types. We show that NeuCA can achieve more accurate cell annotation results compared with existing methods. Additionally, the applications on eight real datasets show that NeuCA has stable performance for intra- and inter-study annotation, as well as cross-condition annotation. NeuCA is freely available as an R/Bioconductor package at https://bioconductor.org/packages/NeuCA .

In an increasingly competitive business environment, marketing strategy plays a very important role, providing the basis for marketing plans and indicating future courses of action. A systematic marketing strategy includes the organization’s goals, policies, and actions to conduct business effectively. With the passage of time and the improvement of the transportation system, the tourism B&B industry in Huangshan City has made great progress and has played a vital role in enhancing the image of tourism in Huangshan. Tourism is one of the fastest growing and oldest industries; the marketing of available hotel services is critical at all levels and destinations. The new crown epidemic in recent years will also promote the role of innovative ideas that help to enhance the hospitality industry is developed and effective decision making strategies are followed and implemented by the industry in general and prominent hotel groups in particular to attract potential travelers. This paper highlights the challenges faced by the Huangshan hotel B&B industry in the post-epidemic period in terms of hardware facilities and services and future strategies to address these challenges through literature analysis and a study of the current situation of small and medium-sized hotels and B&Bs in Huangshan. It also proposes measures to improve operational efficiency to make this prestigious industry practical and feasible.

Flexible covalent organic frameworks (COFs) have been studied for applications containing sorption, selective separation, and catalysis. How to correlate the microscopic structure with flexibility in COFs is a great challenge. Herein, we visually track the flexible deformation behaviors of single COF-300 and COF-300-AR particles in response to solvent vapour guests with dark-field microscopy (DFM) in an in operando manner. COF-300-AR with freely-rotating C-N single bonds are synthesized by the reduction of imine-based COF-300 consisting of rigid C=N double bonds without changing topological structure and crystallinity. Unexpectedly, we observe that the flexible deformation of COF-300 is extremely higher than that of COF-300-AR despite it bears many C-N single bonds, clearly illustrating the apparent flexibility decrease of COF-300 after reduction. The high spatiotemporal resolution of DFM enables the finding of inter-particle variations of the flexibility among COF-300 crystals. Experimental characterizations by variable-temperature X-ray diffraction and infrared spectroscopy as well as theoretical calculations demonstrate that the flexible deformation of COF-300 is ascribed to the pedal motion around rigid C=N double bonds. These observations provide new insights into COF flexibility. To correlate the microstructure of flexible covalent organic frameworks with their flexibility is challenging. Here, the authors visually track the deformation behaviors of single covalent organic framework particles with dark-field microscopy discovering that their flexibility is dictated by the pedal motion around rigid imine bonds.

Colorectal cancer (CRC) is among the most common malignancies with limited treatments other than surgery. The tumor microenvironment (TME) profiling enables the discovery of potential therapeutic targets. Here, we profile 54,103 cells from tumor and adjacent tissues to characterize cellular composition and elucidate the potential origin and regulation of tumor-enriched cell types in CRC. We demonstrate that the tumor-specific FAP + fibroblasts and SPP1 + macrophages were positively correlated in 14 independent CRC cohorts containing 2550 samples and validate their close localization by immuno-fluorescent staining and spatial transcriptomics. This interaction might be regulated by chemerin, TGF-β, and interleukin-1, which would stimulate the formation of immune-excluded desmoplasic structure and limit the T cell infiltration. Furthermore, we find patients with high FAP or SPP1 expression achieved less therapeutic benefit from an anti-PD-L1 therapy cohort. Our results provide a potential therapeutic strategy by disrupting FAP + fibroblasts and SPP1 + macrophages interaction to improve immunotherapy. Tumour microenvironment profiling during colorectal cancer progression may enable the discovery of therapeutic targets. Here, single cell and spatial RNA sequencing of tumour and adjacent normal tissues reveals an interaction between FAP + fibroblasts and SPP1 + macrophages that could be disrupted as an immunotherapy strategy.

•Dynamic integration of neural information across DM and FP lays the foundation for the incubation effect.•The pathway through which brain network dynamics promotes creative cognition is environmentally flexible. When environment is non-demanding or moderately-demanding, DM-FP integration facilitate creative incubation through DM-mediated associative thinking or FP-mediated controlled thinking, respectively.•We suggested a dynamic balance between associative thinking and controlled thinking serves to help human flexibly navigate to creativity in an “offline state”. Although creative ideas often emerge during distraction activities unrelated to the creative task, empirical research has yet to reveal the underlying neurocognitive mechanism. Using an incubation paradigm, we temporarily disengaged participants from the initial creative ideation task and required them to conduct two different distraction activities (moderately-demanding: 1-back working memory task, non-demanding: 0-back choice reaction time task), then returned them to the previous creative task. On the process of creative ideation, we calculated the representational dissimilarities between the two creative ideation phases before and after incubation period to estimate the neural representational change underlying successful incubation. The results found that, for the 0-back condition, successful incubation was associated with the representational change in precuneus (PCU), whereas for the 1-back condition, it was associated with change in rostrolateral PFC (rlPFC), suggesting the dual processes of the DMN-mediated associative thinking and PFC-mediated controlled thinking for the 0- or the 1-back incubation conditions to prompt creation. On the incubation delay, we found the successful incubation in both conditions was accompanied with network integration between frontoparietal (FP) and default mode (DM) network, further suggesting the coupling of the controlled- and associative-thinking for the incubation to work. Moreover, we found the FP-DM integration during incubation period could respectively predict the representational change in PCU or rlPFC in the creative ideation phase of 0- or 1-back condition. This means both conditions benefits from the coordination of the controlled and of the associative thinking in incubation period, but for the representational change in creative ideation phase, 1-back condition relies more on the controlled thinking, whereas the 0-back on the associative ones. Additionally, we created a neural encoding indicator to assess the degree to which temporal activities in the rlPFC or PCU during incubation delay is related to the after-incubation successful problem-solving, and we found a positive relation between this indicator and dynamic reconfiguration of brain networks. This further indicates that FP-DM integration supports creative incubation through offline processing.