Ocean University of China

About: Ocean University of China is a education organization based out in Qingdao, China. It is known for research contribution in the topics: Population & Sea surface temperature. The organization has 27604 authors who have published 27886 publications receiving 440181 citations. The organization is also known as: Zhōngguó Hǎiyáng Dàxué & OUC.

Pressure-assisted preparation of graphene oxide quantum dot-incorporated reverse osmosis membranes: antifouling and chlorine resistance potentials

Abstract: Graphene-based nanomaterials have opened a new era in the fabrication of novel membranes with outstanding performance. In this study, we propose a new method of fabricating a graphene oxide quantum dot (GOQD)-incorporated thin-film nanocomposite (TFN) membrane for reverse osmosis (RO) applications. Inspired by free-standing graphene membranes prepared by vacuum filtration, an aqueous suspension of GOQD/m-phenylenediamine (MPD) was first filtered onto a polysulfone (PSf) substrate to obtain a cushion layer. A GOQD-incorporated polyamide (PA) selective layer was then constructed by interfacial polymerization between MPD and trimesoyl chloride (TMC). This method can easily be scaled up owing to its simple preparation procedures. The newly developed TFN membrane exhibited stable high performance with a flux of 37.5 L m−2 h−1 and a NaCl rejection of 98.8% at 16 bar. Remarkably, this represents a 51.8% increase in permeate flux relative to a GOQD-free TFC membrane without compromising the solute rejection. In addition, the GOQD-incorporated TFN membrane displayed long-term durability over 120 h of RO testing. More importantly, the introduction of GOQD into the TFN membrane resulted in improved antifouling and chlorine resistance properties, which are greatly desired in the membrane desalination and water reclamation processes.

Diversity and spatial distribution of sediment ammonia-oxidizing crenarchaeota in response to estuarine and environmental gradients in the Changjiang Estuary and East China Sea.

Abstract: Ammonia-oxidizing archaea (AOA) have recently been found to be potentially important in nitrogen cycling in a variety of environments, such as terrestrial soils, wastewater treatment reactors, marine waters and sediments, and especially in estuaries, where high input of anthropogenic nitrogen is often experienced. The sedimentary AOA diversity, community structure and spatial distribution in the Changjiang Estuary and the adjacent East China Sea were studied. Multivariate statistical analysis indicated that the archaeal amoA genotype communities could be clustered according to sampling transects, and the station located in an estuarine mixing zone harboured a distinct AOA community. The distribution of AOA communities correlated significantly with the gradients of surface-water salinity and sediment sorting coefficient. The spatial distribution of putative soil-related AOA in certain sampling stations indicated a strong impact of the Changjiang freshwater discharge on the marine benthic microbial ecosystem. Besides freshwater, nutrients, organic matter and suspended particles, the Changjiang Diluted Water might also contribute to the transport of terrestrial archaea into the seawater and sediments along its flow path.

Visual-Patch-Attention-Aware Saliency Detection

Abstract: The human visual system (HVS) can reliably perceive salient objects in an image, but, it remains a challenge to computationally model the process of detecting salient objects without prior knowledge of the image contents. This paper proposes a visual-attention-aware model to mimic the HVS for salient-object detection. The informative and directional patches can be seen as visual stimuli, and used as neuronal cues for humans to interpret and detect salient objects. In order to simulate this process, two typical patches are extracted individually and in parallel from the intensity channel and the discriminant color channel, respectively, as the primitives. In our algorithm, an improved wavelet-based salient-patch detector is used to extract the visually informative patches. In addition, as humans are sensitive to orientation features, and as directional patches are reliable cues, we also propose a method for extracting directional patches. These two different types of patches are then combined to form the most important patches, which are called preferential patches and are considered as the visual stimuli applied to the HVS for salient-object detection. Compared with the state-of-the-art methods for salient-object detection, experimental results using publicly available datasets show that our produced algorithm is reliable and effective.