How to Measure Carbon Equity: Carbon Gini Index Based on Historical Cumulative Emission Per Capita

This paper uses Lorenz Curve and Gini Index with adjustment to per capita historical cumulative emission and constructs Carbon Gini Index to measure inequality in climate change area. The analysis using Carbon Gini Index shows that 70% of carbon space in the atmosphere has been used for unequal distribution, which is almost the same as that of income in the country with the biggest gap between rich and poor in the world. The carbon equity should be an urgency and priority in the climate agenda. Carbon Gini Index established in this paper can be used to measure inequality in the distribution of carbon space and provide a quantified indicator for measurement of carbon equity among different proposals.Climate Change, Carbon Equity, Long-term Mitigation Goal, Cumulative Emission Per Capita, Carbon Gini Index

The Monkeytyping Solution to the YouTube-8M Video Understanding Challenge

This article describes the final solution of team monkeytyping, who finished in second place in the YouTube-8M video understanding challenge. The dataset used in this challenge is a large-scale benchmark for multi-label video classification. We extend the work in [1] and propose several improvements for frame sequence modeling. We propose a network structure called Chaining that can better capture the interactions between labels. Also, we report our approaches in dealing with multi-scale information and attention pooling. In addition, We find that using the output of model ensemble as a side target in training can boost single model performance. We report our experiments in bagging, boosting, cascade, and stacking, and propose a stacking algorithm called attention weighted stacking. Our final submission is an ensemble that consists of 74 sub models, all of which are listed in the appendix.Comment: Submitted to the CVPR 2017 Workshop on YouTube-8M Large-Scale Video Understandin

Mapping the Alzheimer’s Brain with Connectomics

Alzheimer’s disease (AD) is the most common form of dementia. As an incurable, progressive, and neurodegenerative disease, it causes cognitive and memory deficits. However, the biological mechanisms underlying the disease are not thoroughly understood. In recent years, non-invasive neuroimaging and neurophysiological techniques [e.g., structural magnetic resonance imaging (MRI), diffusion MRI, functional MRI, and EEG/MEG] and graph theory based network analysis have provided a new perspective on structural and functional connectivity patterns of the human brain (i.e., the human connectome) in health and disease. Using these powerful approaches, several recent studies of patients with AD exhibited abnormal topological organization in both global and regional properties of neuronal networks, indicating that AD not only affects specific brain regions, but also alters the structural and functional associations between distinct brain regions. Specifically, disruptive organization in the whole-brain networks in AD is involved in the loss of small-world characters and the re-organization of hub distributions. These aberrant neuronal connectivity patterns were associated with cognitive deficits in patients with AD, even with genetic factors in healthy aging. These studies provide empirical evidence to support the existence of an aberrant connectome of AD. In this review we will summarize recent advances discovered in large-scale brain network studies of AD, mainly focusing on graph theoretical analysis of brain connectivity abnormalities. These studies provide novel insights into the pathophysiological mechanisms of AD and could be helpful in developing imaging biomarkers for disease diagnosis and monitoring

Unifying ultrafast demagnetization and intrinsic Gilbert damping in Co/Ni bilayers with electronic relaxation near the Fermi surface

The ability to controllably manipulate the laser-induced ultrafast magnetic dynamics is a prerequisite for future high speed spintronic devices. The optimization of devices requires the controllability of the ultrafast demagnetization time, , and intrinsic Gilbert damping, . In previous attempts to establish the relationship between and , the rare-earth doping of a permalloy film with two different demagnetization mechanism is not a suitable candidate. Here, we choose Co/Ni bilayers to investigate the relations between and by means of time-resolved magneto-optical Kerr effect (TRMOKE) via adjusting the thickness of the Ni layers, and obtain an approximately proportional relation between these two parameters. The remarkable agreement between TRMOKE experiment and the prediction of breathing Fermi-surface model confirms that a large Elliott-Yafet spin-mixing parameter is relevant to the strong spin-orbital coupling at the Co/Ni interface. More importantly, a proportional relation between and in such metallic films or heterostructures with electronic relaxation near Fermi surface suggests the local spin-flip scattering domains the mechanism of ultrafast demagnetization, otherwise the spin-current mechanism domains. It is an effective method to distinguish the dominant contributions to ultrafast magnetic quenching in metallic heterostructures by investigating both the ultrafast demagnetization time and Gilbert damping simultaneously. Our work can open a novel avenue to manipulate the magnitude and efficiency of Terahertz emission in metallic heterostructures such as the perpendicular magnetic anisotropic Ta/Pt/Co/Ni/Pt/Ta multilayers, and then it has an immediate implication of the design of high frequency spintronic devices

Using Baidu Index to Understand the Public Concern of Children's Mental Health in Mainland China in the Context of COVID-19 Epidemic

This study aims to understand the temporal and spatial characteristics of public concern for "children's mental health" in China in the context of the COVID-19 epidemic. Baidu Index is a research tool to collect and analyze massive data on Chinese netizens' behaviors. Using Baidu Index as the research tool, this paper analyzes the trend and distribution of Chinese netizens' attention to "children's mental health" from December 1st, 2019 to March 20th, 2022 from three aspects of trend research, demand map, and crowd portrait. The study found that since the outbreak of COVID- 19, the search trend of "children's mental health" has shown a cyclical change, peaking in May and valley around the Spring Festival and National Day, and stable in other periods. "Mental health", "handwritten newspaper on mental health" and "youth mental health" are the most popular buzzwords among the public. The groups concerned with "children's mental health" is mainly distributed in Guangdong, Jiangsu, Beijing, and the majority are women between 30 and 39 years old. Meanwhile, search trends for "mental health" are like that for "children's mental health." The factors influencing the search volume change of "children's mental health" include Chinese traditional holidays, Spring Festival, National Day, Chinese Mental Health Day, and policies and instructions on children's mental health issued by the PRC Ministry of Education. The public would like to know about "mental health", "handwritten newspaper on mental health" and "adolescent mental health"

Polymorphisms of the _ENPP1_ gene are not associated with type 2 diabetes or obesity in the Chinese Han population

*Objective:* Type 2 Diabetes mellitus is a metabolic disorder characterized by chronic hyperglycemia and with a major feature of insulin resistance. Genetic association studies have suggested that _ENPP1_ might play a potential role in susceptibility to type 2 diabetes and obesity. Our study aimed to examine the association between _ENPP1_ and type 2 diabetes and obesity.

*Design:* Association study between two SNPs, rs1044498 (K121Q) and rs7754561 of ENPP1 and diabetes and obesity in the Chinese Han population.

*Subjects:* 1912 unrelated patients (785 male and 1127 female with a mean age 63.8 ± 9 years), 236 IFG/IGT subjects (83 male and 153 female with a mean age 64 ± 9 years) and 2041 controls (635 male and 1406 female with a mean age 58 ± 9 years).
 
*Measurements:* Subjects were genotyped for two SNPs using TaqMan technology on an ABI7900 system and tested by regression analysis.

*Results:* By logistic regression analysis, rs1044498 (K121Q) and rs7754561 showed no statistical association with type 2 diabetes, obesity under additive, dominant and recessive models either before or after adjusting for sex and age. Haplotype analysis found a marginal association of haplotype C-G (p=0.05) which was reported in the previous study.

*Conclusion:* Our investigation did not replicated the positive association found previously and suggested that the polymorphisms of _ENPP1_ might not play a major role in the susceptibility to type 2 diabetes or obesity in the Chinese Han population