Cleaning of a model food soil from horizontal plates by a moving vertical water jet

The removal of layers of a model food soil (dried Xanthan gum containing fluorescent ZnS particles) by a vertical water jet impinging normally on to the plate, generated by a solid stream nozzle which moves across the plate was reported by Köhler et al. (2014). Their experiments investigated nozzle pressures from 0.5-2.0 barg; nozzle diameters from 0.84-2.66 mm, nozzle-layer separation of 20 mm, and nozzle traverse speeds of 2.1-126 mm s-1. The flow parameters and separation are smaller than those typical of industrial jet cleaning operations. The model developed by Wilson et al. (2014; Chem. Eng. Sci., 109, 183–196) for cleaning of similar layers by a stationary impinging jet was modified to describe the case of moving nozzle. This new model predicted the trends observed in the experiments, and analysis of the data yielded a similar cleaning rate constant to that obtained previously for cleaning of similar layers by stationary jets. The model predicted a non-circular cleaning front which matched that extracted from new experiments in which the flow was interrupted in order to capture this feature. The model allowed the cleaning performance indicators suggested by Köhler et al. (2014) to be expressed quantitatively: these indicated that higher nozzle traverse speeds give increased cleaning time, energy and liquid consumption performance.The work at TU Dresden was funded by the European Union and the Free State of Saxony as part of project SAB 080951793. A short vacation study grant for LC from Fitzwilliam College, Cambridge, is gratefully acknowledged.This is the accepted manuscript. The final version is available from Elsevier at http://www.sciencedirect.com/science/article/pii/S000925091400630

Non-Negative Local Sparse Coding for Subspace Clustering

Subspace sparse coding (SSC) algorithms have proven to be beneficial to clustering problems. They provide an alternative data representation in which the underlying structure of the clusters can be better captured. However, most of the research in this area is mainly focused on enhancing the sparse coding part of the problem. In contrast, we introduce a novel objective term in our proposed SSC framework which focuses on the separability of data points in the coding space. We also provide mathematical insights into how this local-separability term improves the clustering result of the SSC framework. Our proposed non-linear local SSC algorithm (NLSSC) also benefits from the efficient choice of its sparsity terms and constraints. The NLSSC algorithm is also formulated in the kernel-based framework (NLKSSC) which can represent the nonlinear structure of data. In addition, we address the possibility of having redundancies in sparse coding results and its negative effect on graph-based clustering problems. We introduce the link-restore post-processing step to improve the representation graph of non-negative SSC algorithms such as ours. Empirical evaluations on well-known clustering benchmarks show that our proposed NLSSC framework results in better clusterings compared to the state-of-the-art baselines and demonstrate the effectiveness of the link-restore post-processing in improving the clustering accuracy via correcting the broken links of the representation graph.Comment: 15 pages, IDA 2018 conferenc

Environmental change and atmospheric contamination across China as indicated by lake sediments (Joint Project Q741)

In China, anthropogenic impact from changes in water quality, land-use and atmospheric deposition vary both spatially and temporally. There is a gradient across the country from the populous lowlands in the east, where considerable long-term impact on water bodies has resulted from centuries of agricultural and aquacultural practices superimposed by more recent, rapid industrial growth; to the mountainous west where many areas remain minimally impacted and any anthropogenic impact is restricted to long-range transport of atmospheric pollutants and change in climate. Currently, however, there is little information on temporal trends in atmospheric deposition. The importance of water resources in China cannot be overestimated and therefore determining the extent, rate and direction of change in water quality is a national priority. In the absence of long-term monitoring programmes, lake sediments remain the only way whereby this information can be retrospectively determined at the necessary temporal scale to ascertain whether the causes of any detriment in quality are as a result of natural changes, or due to agricultural or industrial impacts. Therefore, the aim of this research programme is to use lake sediments from three regions of China to detennine the extent to which impacts to lakes have changed through time and the causes of these changes. The project focuses on an east - west transect along the Yangtse River. The Middle and Lower Reaches of the Yangtse are undergoing exceptionally rapid economic and industrial development and this region is receiving a great deal of attention as the Three Gorges Dam undergoes construction. The three areas in which lakes are to be studied in this proposal are: l. Jiangsu Province in east China north of Shanghai. Lowland sites. Lakes in this area are likely to have been impacted by long-term agriculture and may therefore may have become eutrophic. Atmospheric deposition may also be significant from local and regional industrial sources. 2. The upper reaches of the Yangtse River, in Sichuan and Yunnan Provinces. Lakes at l-2000m. Lakes in this area may have been impacted by agriculture, but where possible sites will be selected where direct impact is minimal. Lakes may therefore be mesotrophic but sources of atmospherically derived industrial pollutants are likely to be remote. 3. The Tibetan Plateau. Lakes at 4 - 5000m. 'Control' sites in a pristine area with minimal human influence. Sediment cores from these sites will be used to detem1ine background levels of atmospherically deposited contaminants. Oligotrophic (low nutrient) sites on sensitive geology (low acid neutralising capacity e.g. granites) will be selected where possible. By including earlier collaborative work between the participating institutes (funded by the Royal Society and the Chinese Academy of Sciences) on the lake sediment records on the Jianghan Plain and research currently being undertaken on lakes in the Shennonggjia region in western Hubei (NNFSC funded), this study will produce a transect of lakes from five regions providing a unique database on the historical impact of human activity on the freshwater environment

Neuro-endovascular service in The University of Hong Kong Shenzhen Hospital

Conference Theme: Brain Attack: A New EraOral Poster Presentation I: paper no. FP1-03BACKGROUND: The University Hong Kong Shenzhen Hospital (HKU-SZH) is a newly established hospital and its neuroscience unit is affiliated with Queen Mary Hospital in Hong Kong. Its establishment in 2012 was part of a pilot scheme in healthcare reform in Mainland China. Acute stroke is an emerging healthcare burden in the aging population in China. In the management of acute stroke, endovascular intervention plays an important role; in particular for ...postprin

Exploring the impact of random telegraph noise-induced accuracy loss in Resistive RAM-based deep neural network

For Resistive RAM (RRAM)-based deep neural network, Random telegraph noise (RTN) causes accuracy loss during inference. In this work, we systematically investigated the impact of RTN on the complex deep neural networks (DNNs) with different datasets. By using 8 mainstream DNNs and 4 datasets, we explored the origin that caused the RTN-induced accuracy loss. Based on the understanding, for the first time, we proposed a new method to estimate the accuracy loss without going through time-consuming RTN simulation. The method was verified with other 10 DNN/dataset combinations that were not used for establishing the method. Finally, we discussed its potential adoption for the co-optimization of the DNN architecture and the RRAM technology, paving ways to RTN-induced accuracy loss mitigation for future neuromorphic hardware systems

Time-Dependent Variability in RRAM-based Analog Neuromorphic System for Pattern Recognition

For the first time, this work investigated the time dependent variability (TDV) in RRAMs and its interaction with the RRAM-based analog neuromorphic circuits for pattern recognition. It is found that even the circuits are well trained, the TDV effect can introduce non-negligible recognition accuracy drop during the operating condition. The impact of TDV on the neuromorphic circuits increases when higher resistances are used for the circuit implementation, challenging for the future low power operation. In addition, the impact of TDV cannot be suppressed by either scaling up with more synapses or increasing the response time and thus threatens both real-time and general-purpose applications with high accuracy requirements. Further study on different circuit configurations, operating conditions and training algorithms, provides guidelines for the practical hardware implementation

Topological orbital ladders

We unveil a topological phase of interacting fermions on a two-leg ladder of unequal parity orbitals, derived from the experimentally realized double-well lattices by dimension reduction. $Z_2$ topological invariant originates simply from the staggered phases of $sp$-orbital quantum tunneling, requiring none of the previously known mechanisms such as spin-orbit coupling or artificial gauge field. Another unique feature is that upon crossing over to two dimensions with coupled ladders, the edge modes from each ladder form a parity-protected flat band at zero energy, opening the route to strongly correlated states controlled by interactions. Experimental signatures are found in density correlations and phase transitions to trivial band and Mott insulators.Comment: 12 pages, 5 figures, Revised title, abstract, and the discussion on Majorana numbe

SILAC-based proteomic quantification of chemoattractant-induced cytoskeleton dynamics on a second to minute timescale

Cytoskeletal dynamics during cell behaviours ranging from endocytosis and exocytosis to cell division and movement is controlled by a complex network of signalling pathways, the full details of which are as yet unresolved. Here we show that SILAC-based proteomic methods can be used to characterize the rapid chemoattractant-induced dynamic changes in the actin–myosin cytoskeleton and regulatory elements on a proteome-wide scale with a second to minute timescale resolution. This approach provides novel insights in the ensemble kinetics of key cytoskeletal constituents and association of known and novel identified binding proteins. We validate the proteomic data by detailed microscopy-based analysis of in vivo translocation dynamics for key signalling factors. This rapid large-scale proteomic approach may be applied to other situations where highly dynamic changes in complex cellular compartments are expected to play a key role

Millennial atmospheric CO2 changes linked to ocean ventilation modes over past 150,000 years

Ice core measurements show diverse atmospheric CO2 variations—increasing, decreasing or remaining stable—during millennial-scale North Atlantic cold periods called stadials. The reasons for these contrasting trends remain elusive. Ventilation of carbon-rich deep oceans can profoundly affect atmospheric CO2, but its millennial-scale history is poorly constrained. Here we present a well-dated high-resolution deep Atlantic acidity record over the past 150,000 years, which reveals five hitherto undetected modes of stadial ocean ventilation with different consequences for deep-sea carbon storage and associated atmospheric CO2 changes. Our data provide observational evidence to show that strong and often volumetrically extensive Southern Ocean ventilation released substantial amounts of deep-sea carbon during stadials when atmospheric CO2 rose prominently. By contrast, other stadials were characterized by weak ventilation via both Southern Ocean and North Atlantic, which promoted respired carbon accumulation and thus curtailed or reversed deep-sea carbon losses, resulting in diminished rises or even declines in atmospheric CO2. Our findings demonstrate that millennial-scale changes in deep-sea carbon storage and atmospheric CO2 are modulated by multiple ocean ventilation modes through the interplay of the two polar regions, rather than by the Southern Ocean alone, which is critical for comprehensive understanding of past and future carbon cycle adjustments to climate change