Extend Wave Function Collapse to Large-Scale Content Generation

Wave Function Collapse (WFC) is a widely used tile-based algorithm in procedural content generation, including textures, objects, and scenes. However, the current WFC algorithm and related research lack the ability to generate commercialized large-scale or infinite content due to constraint conflict and time complexity costs. This paper proposes a Nested WFC (N-WFC) algorithm framework to reduce time complexity. To avoid conflict and backtracking problems, we offer a complete and sub-complete tileset preparation strategy, which requires only a small number of tiles to generate aperiodic and deterministic infinite content. We also introduce the weight-brush system that combines N-WFC and sub-complete tileset, proving its suitability for game design. Our contribution addresses WFC's challenge in massive content generation and provides a theoretical basis for implementing concrete games.Comment: This paper is accepted by IEEE Conference on Games 2023 (nomination of the Best Paper Award

Temporal-spatial Correlation Attention Network for Clinical Data Analysis in Intensive Care Unit

In recent years, medical information technology has made it possible for electronic health record (EHR) to store fairly complete clinical data. This has brought health care into the era of "big data". However, medical data are often sparse and strongly correlated, which means that medical problems cannot be solved effectively. With the rapid development of deep learning in recent years, it has provided opportunities for the use of big data in healthcare. In this paper, we propose a temporal-saptial correlation attention network (TSCAN) to handle some clinical characteristic prediction problems, such as predicting death, predicting length of stay, detecting physiologic decline, and classifying phenotypes. Based on the design of the attention mechanism model, our approach can effectively remove irrelevant items in clinical data and irrelevant nodes in time according to different tasks, so as to obtain more accurate prediction results. Our method can also find key clinical indicators of important outcomes that can be used to improve treatment options. Our experiments use information from the Medical Information Mart for Intensive Care (MIMIC-IV) database, which is open to the public. Finally, we have achieved significant performance benefits of 2.0\% (metric) compared to other SOTA prediction methods. We achieved a staggering 90.7\% on mortality rate, 45.1\% on length of stay. The source code can be find: \url{https://github.com/yuyuheintju/TSCAN}

Cloning and expression analysis of potassium channel gene NKT3 from Nicotiana tabacum

Potassium (K+) is the predominant inorganic ion of plant cells. K+ channels in higher plant cells play an important role in regulating the influx and efflux of K+ from cells, and activity of these channels might be involved in plant stress resistance. A completely new K+ channel gene of Nicotiana tabacum was obtained through homologous cloning strategy. The complete cDNA sequence was submitted to the National Center for Biotechnology Information (NCBI) GenBank, designated as NKT3 and the accession number is FJ230956. The phylogenetic analysis indicated that NKT3 is located at the branch of weak-inwardly rectifying K+ channels and might be a member of the Shaker family. The spatial and temporal expression of the gene was also investigated. NKT3 is expressed abundantly in the roots, while little in the leaves of N. tabacum. It might be involved in the process of K+ acquirement and release in tobacco roots.Keywords: Potassium channel gene, NKT3, RACE, Nicotiana tabacu

Analytical modeling of gas production rate in tight channel sand formation and optimization of artificial fracture

Permeability variation in tight channel sand formation makes an important role in gas production. Based on the features of channel sand formation, a mathematical model has been established considering anisotropy of permeability. The analytical solutions were derived for productivity of both vertical wells and vertically fractured wells. Simulation results show that, gas production rate of anisotropic channel sand formation is less than that of isotropic formation. For vertically fractured well, artificial fracture direction, drainage radius, permeability ratio and fracture half-length have considerable influence on production rate. The optimum fracture direction should be deviated less than π/8 from the maximum permeability direction (or the channel direction). In addition, the analytical model was verified by in situ measured data. The research provides theoretical basis for the development of tight channel sand gas reservoirs

Online Transfer Learning for RSV Case Detection

Transfer learning has become a pivotal technique in machine learning and has proven to be effective in various real-world applications. However, utilizing this technique for classification tasks with sequential data often faces challenges, primarily attributed to the scarcity of class labels. To address this challenge, we introduce Multi-Source Adaptive Weighting (MSAW), an online multi-source transfer learning method. MSAW integrates a dynamic weighting mechanism into an ensemble framework, enabling automatic adjustment of weights based on the relevance and contribution of each source (representing historical knowledge) and target model (learning from newly acquired data). We demonstrate the effectiveness of MSAW by applying it to detect Respiratory Syncytial Virus cases within Emergency Department visits, utilizing multiple years of electronic health records from the University of Pittsburgh Medical Center. Our method demonstrates performance improvements over many baselines, including refining pre-trained models with online learning as well as three static weighting approaches, showing MSAW's capacity to integrate historical knowledge with progressively accumulated new data. This study indicates the potential of online transfer learning in healthcare, particularly for developing machine learning models that dynamically adapt to evolving situations where new data is incrementally accumulated.Comment: 10 pages, 2 figure

The functional and structural alterations of the striatum in chronic spontaneous urticaria

The brain has long been known to be the regulation center of itch, but the neuropathology of chronic itch, such as chronic spontaneous urticaria (CSU), remains unclear. Thus, we aimed to explore the brain areas involved in the pathophysiology of CSU in hopes that our results may provide valuable insights into the treatment of chronic itch conditions. 40 CSU patients and 40 healthy controls (HCs) were recruited. Urticaria activity scores 7 (UAS7) were collected to evaluate patient’s clinical symptoms. Amplitude of low frequency fluctuations (ALFF), voxel-based morphometry (VBM), and seed-based resting-state functional connectivity (rs-FC) analysis were used to assess brain activity and related plasticity. Compared with HCs, CSU patients exhibited 1) higher ALFF values in the right ventral striatum / putamen, which were positively associated with clinical symptoms as measured by UAS7; 2) gray matter volume (GMV) increase in the right ventral striatum and putamen; and 3) decreased rs-FC between the right ventral striatum and the right occipital cortex and between the right putamen and the left precentral gyrus. Using multiple-modality brain imaging tools, we demonstrated the dysfunction of the striatum in CSU. Our results may provide valuable insights into the neuropathology and development of chronic itch

Ultrasound cavitation and exfoliation dynamics of 2D materials re-vealed in operando by X-ray free electron laser megahertz imaging

Ultrasonic liquid phase exfoliation is a promising method for the production of two-dimensional (2D) layered materials. A large number of studies have been made in investigating the underlying ultrasound exfoliation mechanisms. However, due to the experimental challenges for capturing the highly transient and dynamic phenomena in real-time at sub-microsecond time and micrometer length scales simultaneously, most theories reported to date still remain elusive. Here, using the ultra-short X-ray Free Electron Laser pulses (~25ps) with a unique pulse train structure, we applied MHz X-ray Microscopy and machine-learning technique to reveal unambiguously the full cycles of the ultrasound cavitation and graphite layer exfoliation dynamics with sub-microsecond and micrometer resolution. Cyclic fatigue shock wave impacts produced by ultrasound cloud implosion were identified as the dominant mechanism to deflect and exfoliate graphite layers mechanically. For the graphite flakes, exfoliation rate as high as ~5 angstroms per shock wave impact was observed. For the HOPG graphite, the highest exfoliation rate was ~0.15 angstroms per impact. These new findings are scientifically and technologically important for developing industrial upscaling strategies for ultrasonic exfoliation of 2D materials

An Empirical Analysis of Farmers' Rabbit Breeds Purchase and Its Influencing Factors

In this paper, based on the survey data on farmers in 14 provinces and cities nationwide provided by China Rabbit Research System, we analyze the farmers' rabbit breeds selection, purchase channels and the demand for new varieties of rabbits as well as the problems in the course of rabbit usage. We make an empirical analysis of the factors influencing farmers' rabbit demand, and put forth the recommendations for farmers' rabbit breeds usage and to improve the promotion of new varieties of rabbits