Review: Groundwater recharge estimation in northern China karst regions

Reliable estimates of groundwater recharge are crucial for the groundwater resources evaluating and sustainable utilization plans formulating. To protect the precious karst groundwater resources, this paper critically reviewed the previous studies on karst groundwater recharge in northern China karst regions from the perspective of diffuse recharge and focused recharge, and took Niangziguan Spring catchment as a case study. It is concluded that for the 119 karst groundwater systems, 52% occur diffuse recharge through precipitation infiltration, 48% occur both diffuse recharge through precipitation infiltration and focused recharge through surface water leakage. The mean annual precipitation, diffuse recharge and infiltration coefficient (IC, as percentage of precipitation) are 560 mm, 136 mm and 23.1%, respectively. A high correlation was observed between annual precipitation and annual diffuse recharge with a nonlinear relationship. The IC can vary substantially even with the same annual precipitation between 9.3 and 38.0%, with an evidently increasing trend eastward. This reflects a significant difference in the degree of karstification for the northern karst regions. The most commonly applied for recharge assessment in northern China karst regions is equal volume spring flow method, the chloride mass balance method is highly recommended for groundwater recharge estimation of the regions based on the case study. This work provides reference for recharge estimation, assessment and management of karst groundwater resources in northern China

Matching-CNN Meets KNN: Quasi-Parametric Human Parsing

Both parametric and non-parametric approaches have demonstrated encouraging performances in the human parsing task, namely segmenting a human image into several semantic regions (e.g., hat, bag, left arm, face). In this work, we aim to develop a new solution with the advantages of both methodologies, namely supervision from annotated data and the flexibility to use newly annotated (possibly uncommon) images, and present a quasi-parametric human parsing model. Under the classic K Nearest Neighbor (KNN)-based nonparametric framework, the parametric Matching Convolutional Neural Network (M-CNN) is proposed to predict the matching confidence and displacements of the best matched region in the testing image for a particular semantic region in one KNN image. Given a testing image, we first retrieve its KNN images from the annotated/manually-parsed human image corpus. Then each semantic region in each KNN image is matched with confidence to the testing image using M-CNN, and the matched regions from all KNN images are further fused, followed by a superpixel smoothing procedure to obtain the ultimate human parsing result. The M-CNN differs from the classic CNN in that the tailored cross image matching filters are introduced to characterize the matching between the testing image and the semantic region of a KNN image. The cross image matching filters are defined at different convolutional layers, each aiming to capture a particular range of displacements. Comprehensive evaluations over a large dataset with 7,700 annotated human images well demonstrate the significant performance gain from the quasi-parametric model over the state-of-the-arts, for the human parsing task.Comment: This manuscript is the accepted version for CVPR 201

Multistaged discharge constructing heterostructure with enhanced solid-solution behavior for long-life lithium-oxygen batteries.

Inferior charge transport in insulating and bulk discharge products is one of the main factors resulting in poor cycling stability of lithium-oxygen batteries with high overpotential and large capacity decay. Here we report a two-step oxygen reduction approach by pre-depositing a potassium carbonate layer on the cathode surface in a potassium-oxygen battery to direct the growth of defective film-like discharge products in the successive cycling of lithium-oxygen batteries. The formation of defective film with improved charge transport and large contact area with a catalyst plays a critical role in the facile decomposition of discharge products and the sustained stability of the battery. Multistaged discharge constructing lithium peroxide-based heterostructure with band discontinuities and a relatively low lithium diffusion barrier may be responsible for the growth of defective film-like discharge products. This strategy offers a promising route for future development of cathode catalysts that can be used to extend the cycling life of lithium-oxygen batteries