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We present 97 new high-quality strong lensing candidates found in the final $\sim 350\,\rm deg^2$, that completed the full $\sim 1350\,\rm deg^2$ area of the Kilo-Degree Survey (KiDS). Together with our previous findings, the final list of high-quality candidates from KiDS sums up to 268 systems. The new sample is assembled using a new Convolutional Neural Network (CNN) classifier applied to $r$-band (best seeing) and $g,~r,~i$ color-composited images separately. This optimizes the complementarity of the morphology and color information on the identification of strong lensing candidates. We apply the new classifiers to a sample of luminous red galaxies (LRGs) and a sample of bright galaxies (BGs) and select candidates that received a high probability to be a lens from the CNN ($P_{\rm CNN}$). In particular, setting $P_{\rm CNN}>0.8$ for the LRGs, the $1$-band CNN predicts 1213 candidates, while the $3$-band classifier yields 1299 candidates, with only $\sim$30\% overlap. For the BGs, in order to minimize the false positives, we adopt a more conservative threshold, $P_{\rm CNN} >0.9$, for both CNN classifiers. This results in 3740 newly selected objects. The candidates from the two samples are visually inspected by 7 co-authors to finally select 97 "high-quality" lens candidates which received mean scores larger than 6 (on a scale from 0 to 10). We finally discuss the effect of the seeing on the accuracy of CNN classification and possible avenues to increase the efficiency of multi-band classifiers, in preparation of next-generation surveys from ground and space., Comment: Published by APJ

© 2020 IOP Publishing Ltd. This bioprinting roadmap features salient advances in selected applications of the technique and highlights the status of current developments and challenges, as well as envisioned advances in science and technology, to address the challenges to the young and evolving technique. The topics covered in this roadmap encompass the broad spectrum of bioprinting; from cell expansion and novel bioink development to cell/stem cell printing, from organoid-based tissue organization to bioprinting of human-scale tissue structures, and from building cell/tissue/organ-on-a-chip to biomanufacturing of multicellular engineered living systems. The emerging application of printing-in-space and an overview of bioprinting technologies are also included in this roadmap. Due to the rapid pace of methodological advancements in bioprinting techniques and wide-ranging applications, the direction in which the field should advance is not immediately clear. This bioprinting roadmap addresses this unmet need by providing a comprehensive summary and recommendations useful to experienced researchers and newcomers to the field.

Plant pathogens are increasingly considered as important agents in promoting plant coexistence, while plant symbionts like ectomycorrhizal fungi (EMF) can facilitate plant dominance by helping conspecific individuals to defend against plant pathogens. However, we know little about their relationships with plants at large scales. Here, using soil fungal data collected from 28 forest reserves across China, we explored the latitudinal diversity gradients of overall fungi and different fungal functional guilds, including putative plant pathogens, EMF, and saprotrophic fungi. We further linked the spatial patterns of alpha diversities of putative plant pathogens and EMF to the variation of plant species richness. We found that the relationships between latitude and alpha diversities of putative plant pathogens and EMF were region-dependent with sharp diversity shifts around the mid-latitude (~35°N), which differed from the unimodal diversity distributions of the overall and saprotrophic fungi. The variations in the diversities of putative plant pathogens and EMF were largely explained by the spatial regions (south vs. north/subtropical zone vs. temperate zone). Additionally, the alpha diversities of these two fungal guilds exhibited opposing trends across latitude. EMF could alter the relationship between diversities of putative plant pathogens and plants in the south/subtropical region, but not vice versa. We also found that the ratio of their alpha diversities (EMF to putative plant pathogens) was negatively related to plant species richness across the spatial regions (north to south), and explained ~10% of the variation of plant species richness. Overall, our findings suggest that plant-microbe interactions not only shape the local plant diversity but also may have non-negligible contributions to the large-scale patterns of plant diversity in forest ecosystems.

The modulation of AMPA receptor (AMPAR) content at synapses is thought to be an underlying molecular mechanism of memory and learning. AMPAR content at synapses is highly plastic and is regulated by numerous AMPAR accessory transmembrane proteins such as TARPs, cornichons, and CKAMPs. SynDIG (synapse differentiation-induced gene) defines a family of four genes (SynDIG1-4) expressed in distinct and overlapping patterns in the brain. SynDIG1 was previously identified as a novel transmembrane AMPAR-associated protein that regulates synaptic strength. The related protein SynDIG4 [also known as Prrt1 (proline-rich transmembrane protein 1)] has recently been identified as a component of AMPAR complexes. In this study, we show that SynDIG1 and SynDIG4 have distinct yet overlapping patterns of expression in the central nervous system, with SynDIG4 having especially prominent expression in the hippocampus and particularly within CA1. In contrast to SynDIG1 and other traditional AMPAR auxiliary subunits, SynDIG4 is de-enriched at the postsynaptic density and colocalizes with extrasynaptic GluA1 puncta in primary dissociated neuron culture. These results indicate that, although SynDIG4 shares sequence similarity with SynDIG1, it might act through a unique mechanism as an auxiliary factor for extrasynaptic GluA1-containing AMPARs. J. Comp. Neurol. 524:2266-2280, 2016. © 2015 Wiley Periodicals, Inc.

Cadmium (Cd) is one of the most toxic and widely distributed pollutants in the environment. Cadmium contamination of soils has posed a serious threat to safe food production in many parts of the world. The authors present a comprehensive review of present status of phytoextraction technology for cleaning up Cd-contaminated soils, based primarily on the data resulting from both laboratory and field-scale studies that have been conducted to assess or improve the Cd phytoextraction potential of various plant species in the past decade. The encouraging results of field-scale studies have provided a fundamental basis to usher phytoextraction technology into practical use to remediate slightly to moderately Cd-contaminated soils in Europe and Asia, although this technology is not yet ready for widespread application. Chelators and microorganisms tested so far seem not to contribute to the applicability of Cd phytoextraction. The major challenges for the large-scale application of Cd phytoextraction are (a) how to further improve the efficiency of Cd phytoextraction, (b) how to cut the overall costs of Cd phytoextraction, and (c) how to get greater stakeholders' acceptance of Cd phytoextraction as a reliable option.

This paper proposes a new approach to extracting natural strokes from the skeletons of loosely-constrained, off-line handwritten Chinese characters. It admits the output substrokes from a previously proposed fuzzy substroke extractor as its inputs. By identifying a number of expected ambiguities, which include mutual similarities, unstable touches and joint/cross distortions, fuzzy stroke models are constructed and a "hit-all" fuzzy stroke matching strategy is pursued. Fuzzy partitioning technique is used to generate a ranked list of consistent stroke sets from the set of fuzzy strokes being identified. With this approach, a maximum of 20 distinct natural stroke classes can be extracted from each input character, together with an estimate on the actual count of strokes, which compose the character. Our system offers a number of performance tuning capabilities such as the computation of the fuzzy scores of each extracted stroke, the adjustment on the fuzzy stroke model parameters, and the potential of incorporating one's personal writing styles into our methodology.

Scheduling DAGs to multiprocessors is one of the key issues in high-performance computing. Most realistic scheduling algorithms are heuristic and heuristic algorithms often have room for improvement. The quality of a scheduling algorithm can be effectively improved by a local search. In this paper, we present a fast local search algorithm based on topological ordering. This is a compaction algorithm that can effectively reduce the schedule length produced by any DAG scheduling algorithm. Thus, it can improve the quality of existing DAG scheduling algorithms. This algorithm can quickly determine the optimal search direction. Thus, it is of low complexity and extremely fast.

It has been shown by earlier studies on the formation of the Los Angeles smog aerosol, that a significant fraction of the particulate matter in the visible size range is made by secondary gas-particle conversion processes, and that it consists mainly of liquid matter. In this study the volatility was studied quantitatively by heating the smog aerosol up to 250°C and simultaneously measuring the scattering coefficient using a nephelometer and the change of size distribution by an optical counter. The thermal analyses revealed that 50–80% of the submicron aerosol mass is volatile at 220°C. Inspection of the shapes of thermo-nephelograms (bscat vs temperature) also revealed that photochemically formed aerosols have distinctly different thermo-nephelograms than those obtained on humid “hazy” days. Thus it is suggested that thermal analyses may at least in some instances provide the means of on-line monitoring the origin of the ambient aerosol.