Revisiting the Temporal Modeling in Spatio-Temporal Predictive Learning under A Unified View

Spatio-temporal predictive learning plays a crucial role in self-supervised learning, with wide-ranging applications across a diverse range of fields. Previous approaches for temporal modeling fall into two categories: recurrent-based and recurrent-free methods. The former, while meticulously processing frames one by one, neglect short-term spatio-temporal information redundancies, leading to inefficiencies. The latter naively stack frames sequentially, overlooking the inherent temporal dependencies. In this paper, we re-examine the two dominant temporal modeling approaches within the realm of spatio-temporal predictive learning, offering a unified perspective. Building upon this analysis, we introduce USTEP (Unified Spatio-TEmporal Predictive learning), an innovative framework that reconciles the recurrent-based and recurrent-free methods by integrating both micro-temporal and macro-temporal scales. Extensive experiments on a wide range of spatio-temporal predictive learning demonstrate that USTEP achieves significant improvements over existing temporal modeling approaches, thereby establishing it as a robust solution for a wide range of spatio-temporal applications.Comment: Under revie

A Quantitative Analysis of Open Source Software Code Quality: Insights from Metric Distributions

Code quality is a crucial construct in open-source software (OSS) with three dimensions: maintainability, reliability, and functionality. To accurately measure them, we divide 20 distinct metrics into two types: 1) threshold-type metrics that influence code quality in a monotonic manner; 2) non-threshold-type metrics that lack a monotonic relationship to evaluate. We propose a distribution-based method to provide scores for metrics, which demonstrates great explainability on OSS adoption. Our empirical analysis includes more than 36,460 OSS projects and their raw metrics from SonarQube and CK. Our work contributes to the understanding of the multi-dimensional construct of code quality and its metric measurements

Omni-Line-of-Sight Imaging for Holistic Shape Reconstruction

We introduce Omni-LOS, a neural computational imaging method for conducting holistic shape reconstruction (HSR) of complex objects utilizing a Single-Photon Avalanche Diode (SPAD)-based time-of-flight sensor. As illustrated in Fig. 1, our method enables new capabilities to reconstruct near-$360^\circ$ surrounding geometry of an object from a single scan spot. In such a scenario, traditional line-of-sight (LOS) imaging methods only see the front part of the object and typically fail to recover the occluded back regions. Inspired by recent advances of non-line-of-sight (NLOS) imaging techniques which have demonstrated great power to reconstruct occluded objects, Omni-LOS marries LOS and NLOS together, leveraging their complementary advantages to jointly recover the holistic shape of the object from a single scan position. The core of our method is to put the object nearby diffuse walls and augment the LOS scan in the front view with the NLOS scans from the surrounding walls, which serve as virtual ``mirrors'' to trap lights toward the object. Instead of separately recovering the LOS and NLOS signals, we adopt an implicit neural network to represent the object, analogous to NeRF and NeTF. While transients are measured along straight rays in LOS but over the spherical wavefronts in NLOS, we derive differentiable ray propagation models to simultaneously model both types of transient measurements so that the NLOS reconstruction also takes into account the direct LOS measurements and vice versa. We further develop a proof-of-concept Omni-LOS hardware prototype for real-world validation. Comprehensive experiments on various wall settings demonstrate that Omni-LOS successfully resolves shape ambiguities caused by occlusions, achieves high-fidelity 3D scan quality, and manages to recover objects of various scales and complexity

Emulating Anyonic Fractional Statistical Behavior in a Superconducting Quantum Circuit

Anyons are exotic quasiparticles obeying fractional statistics, whose behavior can be emulated in artificially designed spin systems. Here we present an experimental emulation of creating anyonic excitations in a superconducting circuit that consists of four qubits, achieved by dynamically generating the ground and excited states of the toric code model, i.e., four-qubit Greenberger-Horne-Zeilinger states. The anyonic braiding is implemented via single-qubit rotations: a phase shift of π related to braiding, the hallmark of Abelian 1/2 anyons, has been observed through a Ramsey-type interference measurement

BASP1 is a prognostic biomarker associated with immunotherapeutic response in head and neck squamous cell carcinoma

BackgroundsImmunotherapy is effective in a subset of head and neck squamous cell carcinoma (HNSCC). However, the unfavorable response rate and inadequate biomarkers for stratifying patients have primarily limited its clinical application. Considering transcriptional factors (TFs) play essential roles in regulating immune activity during HNSCC progression, we comprehensively analyzed the expression alterations of TFs and their prognostic values.MethodsGene expression datasets and clinical information of HNSCC were obtained from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) repository. Then, Brain abundant membrane attached signal protein 1 (BASP1) was screened out of differentially expressed TFs by univariate and multivariate survival analysis. Tumor immune dysfunction and exclusion (TIDE) was applied to analyze the response to immunotherapy of BASP1high/low patients. Meanwhile, GO, KEGG and GSEA analyses were used to enrich the pathways between the BASP1high and BASP1low groups. Single-sample gene set enrichment analysis (ssGSEA), CIBERSORT, EPIC and quanTiseq algorithms were applied to explore immune infiltrations. Also, immune cycle analysis was conducted by ssGSEA. Additionally, lipid peroxidation, glutathione and reactive oxygen species were performed to detect the ferroptosis alternations.ResultsBASP1 was upregulated and associated with poor survival in HNSCC patients. BASP1high patients exhibited better response rates to anti-PD-1 immunotherapy and higher expressions of immune checkpoint inhibitors. GO, KEGG and GSEA analyses indicated that the expression of BASP1 was related to several immune-related pathways and immunogenic ferroptosis signature. The infiltration of activated CD8+ T cells was authenticated to be decreased in BASP1high patients. Furthermore, BASP1 was identified to be positively correlated with T cell dysfunction and immune escape. Moreover, silencing BASP1 triggered ferroptosis in HNSCC cells, representing as increased LDH, lipid peroxidation and ROS levels, and reduced glutathione synthesisConclusionsWe demonstrated that BASP1 suppressed immunogenic ferroptosis to induce immunosuppressive tumor microenvironment. BASP1 plays a critical role in immune response, and might be a promising classifier for selecting HNSCC patients who benefit from current immunotherapy

PIK3C2A is a prognostic biomarker that is linked to immune infiltrates in kidney renal clear cell carcinoma

BackgroundPhosphoinositide 3-kinases (PI3Ks) are lipid enzymes that regulate a wide range of intracellular functions. In contrast to Class I and Class III PI3K, which have more detailed descriptions, Class II PI3K has only recently become the focus of functional research. PIK3C2A is a classical member of the PI3Ks class II. However, the role of PIK3C2A in cancer prognosis and progression remains unknown.MethodsThe expression pattern and prognostic significance of PIK3C2A in human malignancies were investigated using multiple datasets and scRNA-seq data. The PIK3C2A expression in renal clear cell carcinoma (KIRC) was then validated utilizing Western blot. The functional role of PIK3C2A in KIRC was assessed using combined function loss experiments with in vitro experiments. Furthermore, the correlation of PIK3C2A expression with tumor immunity was investigated in KIRC. The TCGA database was employed to investigate PIK3C2A functional networks.ResultsSignificant decrease in PIK3C2A expression in KIRC, demonstrated that it potentially influences the prognosis of diverse tumors, particularly KIRC. In addition, PIK3C2A was significantly correlated with the T stage, M stage, pathologic stage, and histologic grade of KIRC. Nomogram models were constructed and used to predict patient survival based on the results of multivariate Cox regression analysis. PIK3C2A knockdown resulted in significantly increased KIRC cell proliferation. Of note, PIK3C2A expression demonstrated a significant correlation with the infiltrating levels of primary immune cells in KIRC.ConclusionThese findings support the hypothesis that PIK3C2A is a novel biomarker for tumor progression and indicates dynamic shifts in immune infiltration in KIRC. Furthermore, aberrant PIK3C2A expression can influence the biological activity of cancer cells

<i>Trans</i>-vaccenic acid reprograms CD8⁺ T cells and anti-tumour immunity

Diet-derived nutrients are inextricably linked to human physiology by providing energy and biosynthetic building blocks and by functioning as regulatory molecules. However, the mechanisms by which circulating nutrients in the human body influence specific physiological processes remain largely unknown. Here we use a blood nutrient compound library-based screening approach to demonstrate that dietary trans-vaccenic acid (TVA) directly promotes effector CD8+ T cell function and anti-tumour immunity in vivo. TVA is the predominant form of trans-fatty acids enriched in human milk, but the human body cannot produce TVA endogenously. Circulating TVA in humans is mainly from ruminant-derived foods including beef, lamb and dairy products such as milk and butter, but only around 19% or 12% of dietary TVA is converted to rumenic acid by humans or mice, respectively. Mechanistically, TVA inactivates the cell-surface receptor GPR43, an immunomodulatory G protein-coupled receptor activated by its short-chain fatty acid ligands. TVA thus antagonizes the short-chain fatty acid agonists of GPR43, leading to activation of the cAMP–PKA–CREB axis for enhanced CD8+ T cell function. These findings reveal that diet-derived TVA represents a mechanism for host-extrinsic reprogramming of CD8+ T cells as opposed to the intrahost gut microbiota-derived short-chain fatty acids. TVA thus has translational potential for the treatment of tumours