Distributional effects of vehicle tax in the framework of transportation externalities

Figure S2.The relationship between perivascular CD4 infiltration and 12 months follow-up DLCO (p = 0.134, r = −0.205). (PPT 43 kb

OphGLM: Training an Ophthalmology Large Language-and-Vision Assistant based on Instructions and Dialogue

Large multimodal language models (LMMs) have achieved significant success in general domains. However, due to the significant differences between medical images and text and general web content, the performance of LMMs in medical scenarios is limited. In ophthalmology, clinical diagnosis relies on multiple modalities of medical images, but unfortunately, multimodal ophthalmic large language models have not been explored to date. In this paper, we study and construct an ophthalmic large multimodal model. Firstly, we use fundus images as an entry point to build a disease assessment and diagnosis pipeline to achieve common ophthalmic disease diagnosis and lesion segmentation. Then, we establish a new ophthalmic multimodal instruction-following and dialogue fine-tuning dataset based on disease-related knowledge data and publicly available real-world medical dialogue. We introduce visual ability into the large language model to complete the ophthalmic large language and vision assistant (OphGLM). Our experimental results demonstrate that the OphGLM model performs exceptionally well, and it has the potential to revolutionize clinical applications in ophthalmology. The dataset, code, and models will be made publicly available at https://github.com/ML-AILab/OphGLM.Comment: OphGLM:The first ophthalmology large language-and-vision assistant based on instructions and dialogu

Global 30 meters spatiotemporal 3D urban expansion dataset from 1990 to 2010

Abstract Understanding the spatiotemporal dynamics of global 3D urban expansion over time is becoming increasingly crucial for achieving long-term development goals. In this study, we generated a global dataset of annual urban 3D expansion (1990–2010) using World Settlement Footprint 2015 data, GAIA data, and ALOS AW3D30 data with a three-step technical framework: (1) extracting the global constructed land to generate the research area, (2) neighborhood analysis to calculate the original normalized DSM and slope height of each pixel in the study area, and (3) slope correction for areas with a slope greater than 10° to improve the accuracy of estimated building heights. The cross-validation results indicate that our dataset is reliable in the United States(R2 = 0.821), Europe(R2 = 0.863), China(R2 = 0.796), and across the world(R2 = 0.811). As we know, this is the first 30-meter 3D urban expansion dataset across the globe, which can give unique information to understand and address the implications of urbanization on food security, biodiversity, climate change, and public well-being and health

A Novel De-Noising Method for Improving the Performance of Full-Waveform LiDAR Using Differential Optical Path

A novel de-noising method for improving the performance of full-waveform light detection and ranging (LiDAR) based on differential optical path is proposed, and the mathematical models of this method are developed and verified. Backscattered full-waveform signal (BFWS) is detected by two avalanche photodiodes placed before and after the focus of the focusing lens. On the basis of the proposed method, some simulations are carried out and conclusions are achieved. (1) Background noise can be suppressed effectively and peak points of the BFWS are transformed into negative-going zero-crossing points as stop timing moments. (2) The relative increment percentage of the signal-to-noise ratio based on the proposed method first dramatically increases with the increase of the distance, and then the improvement gets smaller by increasing the distance. (3) The differential Gaussian fitting with the Levenberg-Marquardt algorithm is applied, and the results show that it can decompose the BFWS with high accuracy. (4) The differential distance should not be larger than c/2 × τrmin, and two variable gain amplifiers can eliminate the inconsistency of two differential beams. The results are beneficial for designing a better performance full-waveform LiDAR

Association between haplotypes of RET tagSNPs and susceptibility to thyroid cancer.

<p>Association between haplotypes of RET tagSNPs and susceptibility to thyroid cancer.</p

Functional prediction of seven tagSNPs of the RET gene.

<p>Functional prediction of seven tagSNPs of the RET gene.</p

Association between RET tagSNP and clinicopathological features of thyroid cancer.

<p>Association between RET tagSNP and clinicopathological features of thyroid cancer.</p