Life-cycle GHG emission Factors of Final Energy in China

AbstractIn this manuscript, a model for the estimation of the life-cycle GHG emission factors of final energy and an empirical study of China is presented. A linear programming method is utilized to solve the problem that several forms of final energy are utilized in the life-cycle of one certain type of final energy. Nine types of final energy are considered, including raw coal, crude oil, raw natural gas, treated coal, diesel, gasoline, fuel oil, treated natural gas, and electricity. The results indicate that the life-cycle GHG emission factors of final energy in China slightly decreased in recent years

Instance Segmentation in the Dark

Existing instance segmentation techniques are primarily tailored for high-visibility inputs, but their performance significantly deteriorates in extremely low-light environments. In this work, we take a deep look at instance segmentation in the dark and introduce several techniques that substantially boost the low-light inference accuracy. The proposed method is motivated by the observation that noise in low-light images introduces high-frequency disturbances to the feature maps of neural networks, thereby significantly degrading performance. To suppress this ``feature noise", we propose a novel learning method that relies on an adaptive weighted downsampling layer, a smooth-oriented convolutional block, and disturbance suppression learning. These components effectively reduce feature noise during downsampling and convolution operations, enabling the model to learn disturbance-invariant features. Furthermore, we discover that high-bit-depth RAW images can better preserve richer scene information in low-light conditions compared to typical camera sRGB outputs, thus supporting the use of RAW-input algorithms. Our analysis indicates that high bit-depth can be critical for low-light instance segmentation. To mitigate the scarcity of annotated RAW datasets, we leverage a low-light RAW synthetic pipeline to generate realistic low-light data. In addition, to facilitate further research in this direction, we capture a real-world low-light instance segmentation dataset comprising over two thousand paired low/normal-light images with instance-level pixel-wise annotations. Remarkably, without any image preprocessing, we achieve satisfactory performance on instance segmentation in very low light (4~\% AP higher than state-of-the-art competitors), meanwhile opening new opportunities for future research.Comment: Accepted by International Journal of Computer Vision (IJCV) 202

V2HDM-Mono: A Framework of Building a Marking-Level HD Map with One or More Monocular Cameras

Marking-level high-definition maps (HD maps) are of great significance for autonomous vehicles, especially in large-scale, appearance-changing scenarios where autonomous vehicles rely on markings for localization and lanes for safe driving. In this paper, we propose a highly feasible framework for automatically building a marking-level HD map using a simple sensor setup (one or more monocular cameras). We optimize the position of the marking corners to fit the result of marking segmentation and simultaneously optimize the inverse perspective mapping (IPM) matrix of the corresponding camera to obtain an accurate transformation from the front view image to the bird's-eye view (BEV). In the quantitative evaluation, the built HD map almost attains centimeter-level accuracy. The accuracy of the optimized IPM matrix is similar to that of the manual calibration. The method can also be generalized to build HD maps in a broader sense by increasing the types of recognizable markings

High drug-loaded microspheres enabled by controlled in-droplet precipitation promote functional recovery after spinal cord injury

High drug loading improves therapeutic efficacy and reduces side effects in drug delivery. Here, the authors use controlled diffusion of solvents to precipitate drug nanoparticles in polymer particles while the polymer is solidifying and demonstrate the particles for drug delivery in a spinal cord injury model. Drug delivery systems with high content of drug can minimize excipients administration, reduce side effects, improve therapeutic efficacy and/or promote patient compliance. However, engineering such systems is extremely challenging, as their loading capacity is inherently limited by the compatibility between drug molecules and carrier materials. To mitigate the drug-carrier compatibility limitation towards therapeutics encapsulation, we developed a sequential solidification strategy. In this strategy, the precisely controlled diffusion of solvents from droplets ensures the fast in-droplet precipitation of drug molecules prior to the solidification of polymer materials. After polymer solidification, a mass of drug nanoparticles is embedded in the polymer matrix, forming a nano-in-micro structured microsphere. All the obtained microspheres exhibit long-term storage stability, controlled release of drug molecules, and most importantly, high mass fraction of therapeutics (21.8-63.1 wt%). Benefiting from their high drug loading degree, the nano-in-micro structured acetalated dextran microspheres deliver a high dose of methylprednisolone (400 mu g) within the limited administration volume (10 mu L) by one single intrathecal injection. The amount of acetalated dextran used was 1/433 of that of low drug-loaded microspheres. Moreover, the controlled release of methylprednisolone from high drug-loaded microspheres contributes to improved therapeutic efficacy and reduced side effects than low drug-loaded microspheres and free drug in spinal cord injury therapy.Peer reviewe

Coal Use, Stove Improvement, and Adult Pneumonia Mortality in Xuanwei, China: A Retrospective Cohort Study

Background: In Xuanwei County, China, unvented indoor coal burning is strongly associated with increased risk of lung cancer and chronic obstructive pulmonary disease. However, the impact of coal burning and stove improvement on risk of pneumonia is not clear. Methods: We conducted a retrospective cohort study among all farmers born 1917 through 1951 and living in Xuanwei as of 1 January 1976. The analysis included a total of 42,422 cohort members. Follow-up identified all deaths in the cohort from 1976 through 1996. Ages at entry into and at exit from follow-up ranged from 24 to 59 years and from 25 to 80 years, respectively. The record search detected 225 deaths from pneumonia, and 32,332 (76%) were alive as of 31 December 1996. We constructed multivariable Cox models (time variable = age) to estimate hazard ratios (HRs) and 95% confidence intervals (CIs). Results: Use of coal, especially smokeless coal, was positively associated with pneumonia mortality. Annual tonnage and lifetime duration of smoky and smokeless coal use were positively associated with pneumonia mortality. Stove improvement was associated with a 50% reduction in pneumonia deaths (smoky coal users: HR, 0.521; 95% CI, 0.340-0.798; smokeless coal users: HR, 0.449; 95% CI, 0.215-0.937). Conclusions: Our analysis is the first to suggest that indoor air pollution from unvented coal burning is an important risk factor for pneumonia death in adults and that improving ventilation by installing a chimney is an effective measure to decrease it.published_or_final_versio

Search for dark matter in events with a leptoquark and missing transverse momentum in proton-proton collisions at 13 TeV

A search is presented for dark matter in proton-proton collisions at a center-of-mass energy of root s= 13 TeV using events with at least one high transverse momentum (p(T)) muon, at least one high-p(T) jet, and large missing transverse momentum. The data were collected with the CMS detector at the CERN LHC in 2016 and 2017, and correspond to an integrated luminosity of 77.4 fb(-1). In the examined scenario, a pair of scalar leptoquarks is assumed to be produced. One leptoquark decays to a muon and a jet while the other decays to dark matter and low-p(T) standard model particles. The signature for signal events would be significant missing transverse momentum from the dark matter in conjunction with a peak at the leptoquark mass in the invariant mass distribution of the highest p(T) muon and jet. The data are observed to be consistent with the background predicted by the standard model. For the first benchmark scenario considered, dark matter masses up to 500 GeV are excluded for leptoquark masses m(LQ) approximate to 1400 GeV, and up to 300 GeV for m(LQ) approximate to 1500 GeV. For the second benchmark scenario, dark matter masses up to 600 GeV are excluded for m(LQ) approximate to 1400 GeV. (C) 2019 The Author(s). Published by Elsevier B.V.Peer reviewe