Learning-based Single-step Quantitative Susceptibility Mapping Reconstruction Without Brain Extraction

Quantitative susceptibility mapping (QSM) estimates the underlying tissue magnetic susceptibility from MRI gradient-echo phase signal and typically requires several processing steps. These steps involve phase unwrapping, brain volume extraction, background phase removal and solving an ill-posed inverse problem. The resulting susceptibility map is known to suffer from inaccuracy near the edges of the brain tissues, in part due to imperfect brain extraction, edge erosion of the brain tissue and the lack of phase measurement outside the brain. This inaccuracy has thus hindered the application of QSM for measuring the susceptibility of tissues near the brain edges, e.g., quantifying cortical layers and generating superficial venography. To address these challenges, we propose a learning-based QSM reconstruction method that directly estimates the magnetic susceptibility from total phase images without the need for brain extraction and background phase removal, referred to as autoQSM. The neural network has a modified U-net structure and is trained using QSM maps computed by a two-step QSM method. 209 healthy subjects with ages ranging from 11 to 82 years were employed for patch-wise network training. The network was validated on data dissimilar to the training data, e.g. in vivo mouse brain data and brains with lesions, which suggests that the network has generalized and learned the underlying mathematical relationship between magnetic field perturbation and magnetic susceptibility. AutoQSM was able to recover magnetic susceptibility of anatomical structures near the edges of the brain including the veins covering the cortical surface, spinal cord and nerve tracts near the mouse brain boundaries. The advantages of high-quality maps, no need for brain volume extraction and high reconstruction speed demonstrate its potential for future applications.Comment: 26 page

Distances and classification of amino acids for different protein secondary structures

Window profiles of amino acids in protein sequences are taken as a description of the amino acid environment. The relative entropy or Kullback-Leibler distance derived from profiles is used as a measure of dissimilarity for comparison of amino acids and secondary structure conformations. Distance matrices of amino acid pairs at different conformations are obtained, which display a non-negligible dependence of amino acid similarity on conformations. Based on the conformation specific distances clustering analysis for amino acids is conducted.Comment: 15 pages, 8 figure

An energy planning oriented method for analyzing spatial-temporal characteristics of electric loads for heating/cooling in district buildings with a case study of one university campus

Highlights A method to analyze spatial-temporal characteristics of district loads was developed. PCA was used to identify the buildings greatly affecting district load management. The features of electric loads of heating on a university campus were analyzed. Building type and operation mode greatly affect the load level and volatility. Abstract Accurate grasp of district power demand is of great significance to both sizing of district power supply and its operation optimization. In this study, an index system has been established and visualized through a Geographic Information System, for revealing both temporal and spatial characteristics of district power loads caused by heating/cooling systems, including load level and fluctuation characteristics, spatial distribution of electric loads, and load coupling relationships between individual buildings and the district. Principal component analysis was applied to identify the buildings with significant impact on district load management. Using this method, the spatial-temporal characteristics of electric loads caused by heating in one university campus in China were analyzed. The results showed that building type and the operation modes had great effects on the level and volatility of the district electric load caused by heating. Buildings with high load levels and strong coupling with the peak district electric load, such as academic buildings, often had a major impact on the power demand of the district. Therefore, they were considered as key targets for energy-saving renovation and operation optimization. Buildings with large load fluctuation, such as teaching buildings, could contribute to the peak load shaving by adjusting the heating systems’ operation

Chinese provincial multi-regional input-output database for 2012, 2015, and 2017

Global production fragmentation generates indirect socioeconomic and environmental impacts throughout its expanded supply chains. The multi-regional input-output model (MRIO) is a tool commonly used to trace the supply chain and understand spillover effects across regions, but often cannot be applied due to data unavailability, especially at the sub-national level. Here, we present MRIO tables for 2012, 2015, and 2017 for 31 provinces of mainland China in 42 economic sectors. We employ hybrid methods to construct the MRIO tables according to the available data for each year. The dataset is the consistent China MRIO table collection to reveal the evolution of regional supply chains in China’s recent economic transition. The dataset illustrates the consistent evolution of China’s regional supply chain and its economic structure before the 2018 US-Sino trade war. The dataset can be further applied as a benchmark in a wide range of in-depth studies of production and consumption structures across industries and regions

Five tips for China to realize its co-targets of climate mitigation and Sustainable Development Goals (SDGs)

In 2018, a total of US$166 billion global economic losses and a new high of 55.3 Gt of CO2 equivalent emission were generated by 831 climate-related extreme events. As the world's largest CO2 emitter, we reported China's recent progresses and pitfalls in climate actions to achieve climate mitigation targets (i.e., limit warming to 1.5–2°C above the pre-industrial level). We first summarized China's integrated actions (2015 onwards) that benefit both climate change mitigation and Sustainable Development Goals (SDGs). These projects include re-structuring organizations, establishing working goals and actions, amending laws and regulations at national level, as well as increasing social awareness at community level. We then pointed out the shortcomings in different regions and sectors. Based on these analyses, we proposed five recommendations to help China improving its climate policy strategies, which include: 1) restructuring the economy to balance short-term and long-term conflicts; 2) developing circular economy with recycling mechanism and infrastructure; 3) building up unified national standards and more accurate indicators; 4) completing market mechanism for green economy and encouraging green consumption; and 5) enhancing technology innovations and local incentives via bottom-up actions

Interprovincial reliance for improving air quality in China:A case study on black carbon aerosol

Black carbon (BC) is of global concern because of its adverse effects on climate and human health. It can travel long distances via atmospheric movement and can be geographically relocated through trade. Here, we explored the integrated patterns of BC transport within 30 provinces in China from the perspective of meteorology and interprovincial trade using the Weather Research and Forecasting with Chemistry (WRF/Chem) model and multiregional input-output analysis. In general, cross-border BC transport, which accounts for more than 30% of the surface concentration, occurs mainly between neighboring provinces. Specifically, Hebei contributes 1.2 μg·m(-3) BC concentration in Tianjin. By contrast, trade typically drives virtual BC flows from developed provinces to heavily industrial provinces, with the largest net flow from Beijing to Hebei (4.2 Gg). Shanghai is most vulnerable to domestic consumption with an average interprovincial consumption influence efficiency of 1.5 × 10(-4) (μg·m(-3))/(billion Yuan·yr(-1)). High efficiencies (∼8 × 10(-5) (μg·m(-3))/(billion Yuan·yr(-1))) are also found from regions including Beijing, Jiangsu, and Shanghai to regions including Hebei, Shandong, and Henan. The above source-receptor relationship indicates two control zones: Huabei and Huadong. Both mitigating end-of-pipe emissions and rationalizing the demand for pollution-intense products are important within the two control zones to reduce BC and other pollutants

Critical Rare-Earth Elements Mismatch Global Wind-Power Ambitions

Wind power needs to be expanded rapidly across the world to stabilize our climate. However, there are increasing concerns about conflicts between the supply of rare-earth elements (REs) (mainly neodymium, praseodymium, and dysprosium) and the global expansion of wind power. Here, we provide a dynamic, technology-rich, and regional-specific approach to exploring such conflicts among ten world regions through 2050 under four widely recognized climate scenarios. We find that the significant increase in RE demand driven by the ambitious 2050 global wind-power targets cannot be achieved without 11- to 26-fold expansion in the RE production. Material recycling and efficiency, production expansion, and technical innovation are promising for alleviating RE supply shortages in the long term. However, the existing global RE supply structure, along with the intensifying geopolitical and environmental constraints, could inhibit the rapid expansion of wind power, which calls for global cooperation to foster a sustainable and responsible RE supply chain