On the growth and velocity effects of money

We show that a one-sector AK model of endogenous growth with the most generalized cash-in-advance constraint is able to account for (i) the observed long-run negative relationship between the nominal growth rate of money and the income velocity of money, (ii) the empirically ambiguous effect of changing inflation on the economy's output growth, and (iii) the divergent growth experience of countries that start with similar macroeconomic conditions.

TempEE: Temporal-Spatial Parallel Transformer for Radar Echo Extrapolation Beyond Auto-Regression

Meteorological radar reflectivity data (i.e. radar echo) significantly influences precipitation prediction. It can facilitate accurate and expeditious forecasting of short-term heavy rainfall bypassing the need for complex Numerical Weather Prediction (NWP) models. In comparison to conventional models, Deep Learning (DL)-based radar echo extrapolation algorithms exhibit higher effectiveness and efficiency. Nevertheless, the development of reliable and generalized echo extrapolation algorithm is impeded by three primary challenges: cumulative error spreading, imprecise representation of sparsely distributed echoes, and inaccurate description of non-stationary motion processes. To tackle these challenges, this paper proposes a novel radar echo extrapolation algorithm called Temporal-Spatial Parallel Transformer, referred to as TempEE. TempEE avoids using auto-regression and instead employs a one-step forward strategy to prevent cumulative error spreading during the extrapolation process. Additionally, we propose the incorporation of a Multi-level Temporal-Spatial Attention mechanism to improve the algorithm's capability of capturing both global and local information while emphasizing task-related regions, including sparse echo representations, in an efficient manner. Furthermore, the algorithm extracts spatio-temporal representations from continuous echo images using a parallel encoder to model the non-stationary motion process for echo extrapolation. The superiority of our TempEE has been demonstrated in the context of the classic radar echo extrapolation task, utilizing a real-world dataset. Extensive experiments have further validated the efficacy and indispensability of various components within TempEE.Comment: Have been accepted by IEEE Transactions on Geoscience and Remote Sensing, see https://ieeexplore.ieee.org/document/1023874

MASK-CNN-Transformer For Real-Time Multi-Label Weather Recognition

Weather recognition is an essential support for many practical life applications, including traffic safety, environment, and meteorology. However, many existing related works cannot comprehensively describe weather conditions due to their complex co-occurrence dependencies. This paper proposes a novel multi-label weather recognition model considering these dependencies. The proposed model called MASK-Convolutional Neural Network-Transformer (MASK-CT) is based on the Transformer, the convolutional process, and the MASK mechanism. The model employs multiple convolutional layers to extract features from weather images and a Transformer encoder to calculate the probability of each weather condition based on the extracted features. To improve the generalization ability of MASK-CT, a MASK mechanism is used during the training phase. The effect of the MASK mechanism is explored and discussed. The Mask mechanism randomly withholds some information from one-pair training instances (one image and its corresponding label). There are two types of MASK methods. Specifically, MASK-I is designed and deployed on the image before feeding it into the weather feature extractor and MASK-II is applied to the image label. The Transformer encoder is then utilized on the randomly masked image features and labels. The experimental results from various real-world weather recognition datasets demonstrate that the proposed MASK-CT model outperforms state-of-the-art methods. Furthermore, the high-speed dynamic real-time weather recognition capability of the MASK-CT is evaluated.Comment: Under Revie

The functions and clinical applications of tumor-derived exosomes

Exosomes are extracellular vesicles with diameters ranging from 30 to 150 nm. They can be secreted by all cell types and transfer information in the form of their contents, which include proteins, lipids and nucleic acids, to other cells throughout the body. They have roles in normal physiological processes as well as in disease development. Here, we review recent findings regarding tumor-derived exosomes, including methods for their extraction and preservation. We also describe the actions of exosomes in tumorigenesis. The exosomal antigen-presenting effect during antitumor immune responses and its suppressive function in immune tolerance are discussed. Finally, we describe the potential application of exosomes to cancer therapy and liquid biopsy

Female media use behavior and agreement with publicly promoted agenda-specific health messages.

This study set out to explore the relationship between female media use behavior and agreement with agenda-specific publicly promoted health messages. A random digit dial telephone cross-sectional survey was conducted using a nationally representative sample of female residents aged 25 and over. Respondents' agreement with health messages was measured by a six-item Health Information Scale (HIS). Data were analyzed using chi-square tests and multiple logistic regression. This survey achieved a response rate of 86% (n = 1074). In this study the longest duration of daily television news watching (OR = 2.32), high self-efficacy (OR = 1.56), and greater attention to medical and health news (OR = 5.41) were all correlates of greater agreement with the selected health messages. Surprisingly, Internet use was not significant in the final model. Many women that public health interventions need to be targeting are not receptive to health information that can be accessed through Internet searches. However, they may be more readily targeted by television campaigns. Agenda-specific public health campaigns aiming to empower women to serve as nodes of information transmission and achieve efficient trickle down through the family unit might do better to invest more heavily in television promotion

Introduction to the wheelchair training's influence on the rehabilitation of patients

目的  通过轮椅训练提高患者掌握轮椅的技巧，保证患者乘坐轮椅时的安全，提高患者日常生活能力及社会参与能力。方法  通过轮椅基本技术动作练习、轮椅技巧动作训练、轮椅体育项目训练、社会实践检测。结果  患者轮椅训练前后对照，躯干的控制能力较前好转，ADL能力明显提高，社会参与能力增强。结论  轮椅训练可以使残疾人参与康复体育和社会活动的机会明显增加。Objective: Training to improve patient’s master of wheelchair technology to ensure the safety of patients in wheelchairs things to improve patients' daily living skills and social participation skills. Methods: By practicing basic techniques wheelchair, wheelchair technology movement training, wheelchair sports training, social practice test. Results: Wheelchair patients before and after control technology, the ability to control the trunk before it gets better, ADL ability as well as social participation improved significantly. Conclusion: Wheelchair training increased opportunities for people with disabilities to participate in the rehabilitation of sports and social activities.

Existence theorems for a crystal surface model involving the p-Laplace operator

The manufacturing of crystal films lies at the heart of modern nanotechnology. How to accurately predict the motion of a crystal surface is of fundamental importance. Many continuum models have been developed for this purpose, including a number of PDE models, which are often obtained as the continuum limit of a family of kinetic Monte Carlo models of crystal surface relaxation that includes both the solid-on-solid and discrete Gaussian models. In this paper we offer an analytical perspective into some of these models. To be specific, we study the existence of a weak solution to the boundary value problem for the equation - \Delta e^{-\mbox{div}\left(|\nabla u|^{p-2}\nabla u\right)}+au=f, where $p>1, a>0$ are given numbers and $f$ is a given function. This problem is derived from a crystal surface model proposed by J.L.~Marzuola and J.~Weare (2013 Physical Review, E 88, 032403). The mathematical challenge is due to the fact that the principal term in our equation is an exponential function of a p-Laplacian. Existence of a suitably-defined weak solution is established under the assumptions that $p\in(1,2], \ N\leq 4$, and $f\in W^{1,p}$. Our investigations reveal that the key to our existence assertion is how to control the set where -\mbox{div}\left(|\nabla u|^{p-2}\nabla u\right) is $\pm\infty$

Paper-based tuberculosis diagnostic devices with colorimetric gold nanoparticles

A colorimetric sensing strategy employing gold nanoparticles and a paper assay platform has been developed for tuberculosis diagnosis. Unmodified gold nanoparticles and single-stranded detection oligonucleotides are used to achieve rapid diagnosis without complicated and time-consuming thiolated or other surface-modified probe preparation processes. To eliminate the use of sophisticated equipment for data analysis, the color variance for multiple detection results was simultaneously collected and concentrated on cellulose paper with the data readout transmitted for cloud computing via a smartphone. The results show that the 2.6 nM tuberculosis mycobacterium target sequences extracted from patients can easily be detected, and the turnaround time after the human DNA is extracted from clinical samples was approximately 1 h