Hurricane annual cycle controlled by both seeds and genesis probability

Understanding tropical cyclone (TC) climatology is a problem of profound societal significance and deep scientific interest. The annual cycle is the biggest radiatively forced signal in TC variability, presenting a key test of our understanding and modeling of TC activity. TCs over the North Atlantic (NA) basin, which are usually called hurricanes, have a sharp peak in the annual cycle, with more than half concentrated in only 3 mo (August to October), yet existing theories of TC genesis often predict a much smoother cycle. Here we apply a framework originally developed to study TC response to climate change in which TC genesis is determined by both the number of pre-TC synoptic disturbances (TC “seeds”) and the probability of TC genesis from the seeds. The combination of seeds and probability predicts a more consistent hurricane annual cycle, reproducing the compact season, as well as the abrupt increase from July to August in the NA across observations and climate models. The seeds-probability TC genesis framework also successfully captures TC annual cycles in different basins. The concise representation of the climate sensitivity of TCs from the annual cycle to climate change indicates that the framework captures the essential elements of the TC climate connection.

A generalization of t-SNE and UMAP to single-cell multimodal omics

Emerging single-cell technologies profile multiple types of molecules within individual cells. A fundamental step in the analysis of the produced high-dimensional data is their visualization using dimensionality reduction techniques such as t-SNE and UMAP. We introduce j-SNE and j-UMAP as their natural generalizations to the joint visualization of multimodal omics data. Our approach automatically learns the relative contribution of each modality to a concise representation of cellular identity that promotes discriminative features but suppresses noise. On eight datasets, j-SNE and j-UMAP produce unified embeddings that better agree with known cell types and that harmonize RNA and protein velocity landscapes.

Mechanized Theory of Event Structures: A Case of Parallel Register Machine

The true concurrency models, and in particular event structures, have been introduced in the 1980s as an alternative to operational interleaving semantics of concurrency, and nowadays they are regaining popularity. Event structures represent the causal dependency and conflict between the individual atomic actions of the system directly. This property leads to a more compact and concise representation of semantics. In this work-in-progress report, we present a theory of event structures mechanized in the COQ proof assistant and demonstrate how it can be applied to define certified executable semantics of a simple parallel register machine with shared memory.

Simulation tests of selected gas flow parameters through combustion engine valves

The article presents the numerical analysis of a single-cylinder gasoline engine with indirect injection and spark ignition. The goal is to recognize and analyze gas flow through inlet and outlet valves and channels. These data were obtained from the simulation of a four-cycle engine cycle without combustion of the fuel-air mixture. The simulation was carried out in ANSYS, using a dedicated IC Engine module. After the simulation, the result was analyzed on the cross-sectional plane of both the valves and the combustion chamber. This method provided the necessary and concise representation of the flow characteristics. Five separate stages are presented - two describing the different displacement of the valve for each inlet and exhaust stroke and one representing the phenomenon of overlapping. The type of flow, its speed and tendency to create turbulence are described

Foundation of the Analytic Element Method

The Analytic Element Method provides a foundation to solve boundary value problems commonly encountered in engineering and science, where problems are structured around elements to organize mathematical functions and methods. While this text mostly adheres to a ``just in time mathematics'' philosophy, whereby mathematical approaches are introduced when they are first needed, a comprehensive paradigm is presented in Section 2.1 as four steps necessary to achieve solutions. Likewise, Section 2.2 develops general solution methods, and Section 2.3 presents a consistent notation and concise representation to organize analytic elements across the broad range of disciplinary perspectives introduced in Chapter 1.

A Fast-Effective Algorithm on A Concise Representation of Top Rated Utility Mining Datasets

The average of customer ratings on a product, which we call a reputation, is one of the key factors in online purchasing decisions. There is, however, no guarantee of the trustworthiness of a reputation since it can be manipulated rather easily. In this paper, we define false reputation as the problem of a reputation being manipulated by unfair ratings and design a general framework that provides trustworthy reputations. For this purpose, we propose Trust-reputation, an algorithm that iteratively adjusts a reputation based on the confidence of customer ratings. We also show the effectiveness of Trust-reputation through extensive experiments in comparisons to state-of-the-art approaches.

Some Applications of Clifford Algebra in Geometry

In this paper, we provide some enlightening examples of the application of Clifford algebra in geometry, which show the concise representation, simple calculation and profound insight of this algebra. The definition of Clifford algebra implies geometric concepts such as vector, length, angle, area and volume, and unifies the calculus of scalar, spinor, vector and tensor, so that it is able to naturally describe all variables and calculus in geometry and physics. Clifford algebra unifies and generalizes real number, complex, quaternion and vector algebra, converts complicated relations and operations into intuitive matrix algebra independent of coordinate systems. By localizing the basis or frame of space-time and introducing differential and connection operators, Clifford algebra also contains Riemann geometry. Clifford algebra provides a unified, standard, elegant and open language and tools for numerous complicated mathematical and physical theories. Clifford algebra calculus is an arithmetic-like operation that can be well understood by everyone. This feature is very useful for teaching purposes, and popularizing Clifford algebra in high schools and universities will greatly improve the efficiency of students to learn fundamental knowledge of mathematics and physics. So Clifford algebra can be expected to complete a new big synthesis of scientific knowledge.

Capturing User Intent when Brushing In Scatterplots

Being able to capture or predict a user's intent behind a brush in a visualization tool has important implications in two scenarios. First, predicting intents can be used to auto-complete a partial selection in a mixed-initiative approach, with potential benefits to selection speed, correctness, and confidence. Second, capturing the intent of a selection can be used to improve recall, reproducibility, and even re-use. Augmenting provenance logs with semi-automatically captured intents makes it possible to save the reasoning behind selections. In this paper, we introduce a method to infer intent for selections and brushes in scatterplots. We first introduce a taxonomy of types of patterns that users might specify, which we elicited in a formative study conducted with professional data analysts and scientists. Based on this, we identify algorithms that can classify these patterns, and introduce various approaches to score the match of each pattern to an analyst's selection of items. We introduce a system that implements these methods for scatterplots and ranks alternative patterns against each other. Analysts then can use these predictions to auto-complete partial selections, and to conveniently capture their intent and provide annotations, thus making a concise representation of that intent available to be stored as provenance data. We evaluate our approach using interviews with domain experts and in a quantitative crowd-sourced study, in which we show that using auto-complete leads to improved selection accuracy for most types of patterns.

Estórias da História da Matemática

Resumo Se perguntassem a um matemático quais as virtudes e os defeitos da Matemática, ouviriam certamente dizer “poupança de esforço” e “satisfação” versus “ansiedade” e “medo”. Neste trabalho vamos contar algumas Estórias da História da Matemática que, em parte, ilustram as três formas de economia em que assenta a Matemática: a ordem, a generalização e a representação concisa. Palavras-chave: Matemática, Estórias, História. Abstract If one asks a mathematician about the virtues and defects of mathematics, the expressions "effort-saving" and "satisfaction" versus "anxiety" and "fear" would certainly appear. In this work, we will tell some Math History Stories, which, in part, illustrate the three forms of economics on which mathematics is based: order, generalization and concise representation. Keywords: Mathematics, Stories, History.