South China University of Technology

To understand the impact of gut microbes on human health and well-being it is crucial to assess their genetic potential. Here we describe the Illumina-based metagenomic sequencing, assembly and characterization of 3.3 million non-redundant microbial genes, derived from 576.7 gigabases of sequence, from faecal samples of 124 European individuals. The gene set, ∼150 times larger than the human gene complement, contains an overwhelming majority of the prevalent (more frequent) microbial genes of the cohort and probably includes a large proportion of the prevalent human intestinal microbial genes. The genes are largely shared among individuals of the cohort. Over 99% of the genes are bacterial, indicating that the entire cohort harbours between 1,000 and 1,150 prevalent bacterial species and each individual at least 160 such species, which are also largely shared. We define and describe the minimal gut metagenome and the minimal gut bacterial genome in terms of functions present in all individuals and most bacteria, respectively. The human body plays host to an estimated 100 trillion microbial cells, most of them in the gut where they have a profound influence on human physiology and nutrition — and are now regarded as crucial for human life. Gut microbes contribute to the energy harvest from food, and changes of gut microbiome may be associated with bowel diseases or obesity. Now the international MetaHIT (Metagenomics of the Human Intestinal Tract) project has published a gene catalogue of the human gut microbiome derived from 124 healthy, overweight and obese human adults, as well as inflammatory disease patients, from Denmark and Spain. The resulting data provide the first insights into this gene set — which is over 150 times larger than the human gene complement — and show that the genes are largely shared among individuals. Based on the variety of functions encoded by the gene set, it is possible to define both a minimal gut metagenome and a minimal gut bacterial genome. Deep metagenomic sequencing and characterization of the human gut microbiome from healthy and obese individuals, as well as those suffering from inflammatory bowel disease, provide the first insights into this gene set and how much of it is shared among individuals. The minimal gut metagenome as well as the minimal gut bacterial genome is also described.

Aggregation-induced emission (AIE) is another photophysical phenomenon associated with chromophore aggregation. The concept of AIE has been introduced by a group of researchers in 2001. In the AIE process, non-emissive luminogens are induced to emit by the aggregate formation. The luminogens exhibiting AIE attributes are termed AIEgens, by analogue with the term of 'mesogens' for the molecules showing mesomorphism under suitable conditions.

BACKGROUND: There is a rapidly increasing amount of de novo genome assembly using next-generation sequencing (NGS) short reads; however, several big challenges remain to be overcome in order for this to be efficient and accurate. SOAPdenovo has been successfully applied to assemble many published genomes, but it still needs improvement in continuity, accuracy and coverage, especially in repeat regions. FINDINGS: To overcome these challenges, we have developed its successor, SOAPdenovo2, which has the advantage of a new algorithm design that reduces memory consumption in graph construction, resolves more repeat regions in contig assembly, increases coverage and length in scaffold construction, improves gap closing, and optimizes for large genome. CONCLUSIONS: Benchmark using the Assemblathon1 and GAGE datasets showed that SOAPdenovo2 greatly surpasses its predecessor SOAPdenovo and is competitive to other assemblers on both assembly length and accuracy. We also provide an updated assembly version of the 2008 Asian (YH) genome using SOAPdenovo2. Here, the contig and scaffold N50 of the YH genome were ~20.9 kbp and ~22 Mbp, respectively, which is 3-fold and 50-fold longer than the first published version. The genome coverage increased from 81.16% to 93.91%, and memory consumption was ~2/3 lower during the point of largest memory consumption.

High-resolution representations are essential for position-sensitive vision problems, such as human pose estimation, semantic segmentation, and object detection. Existing state-of-the-art frameworks first encode the input image as a low-resolution representation through a subnetwork that is formed by connecting high-to-low resolution convolutions in series (e.g., ResNet, VGGNet), and then recover the high-resolution representation from the encoded low-resolution representation. Instead, our proposed network, named as High-Resolution Network (HRNet), maintains high-resolution representations through the whole process. There are two key characteristics: (i) Connect the high-to-low resolution convolution streams in parallel and (ii) repeatedly exchange the information across resolutions. The benefit is that the resulting representation is semantically richer and spatially more precise. We show the superiority of the proposed HRNet in a wide range of applications, including human pose estimation, semantic segmentation, and object detection, suggesting that the HRNet is a stronger backbone for computer vision problems. All the codes are available at https://github.com/HRNet.

"United we stand, divided we fall."--Aesop. Aggregation-induced emission (AIE) refers to a photophysical phenomenon shown by a group of luminogenic materials that are non-emissive when they are dissolved in good solvents as molecules but become highly luminescent when they are clustered in poor solvents or solid state as aggregates. In this Review we summarize the recent progresses made in the area of AIE research. We conduct mechanistic analyses of the AIE processes, unify the restriction of intramolecular motions (RIM) as the main cause for the AIE effects, and derive RIM-based molecular engineering strategies for the design of new AIE luminogens (AIEgens). Typical examples of the newly developed AIEgens and their high-tech applications as optoelectronic materials, chemical sensors and biomedical probes are presented and discussed.

Single image haze removal is a challenging ill-posed problem. Existing methods use various constraints/priors to get plausible dehazing solutions. The key to achieve haze removal is to estimate a medium transmission map for an input hazy image. In this paper, we propose a trainable end-to-end system called DehazeNet, for medium transmission estimation. DehazeNet takes a hazy image as input, and outputs its medium transmission map that is subsequently used to recover a haze-free image via atmospheric scattering model. DehazeNet adopts convolutional neural network-based deep architecture, whose layers are specially designed to embody the established assumptions/priors in image dehazing. Specifically, the layers of Maxout units are used for feature extraction, which can generate almost all haze-relevant features. We also propose a novel nonlinear activation function in DehazeNet, called bilateral rectified linear unit, which is able to improve the quality of recovered haze-free image. We establish connections between the components of the proposed DehazeNet and those used in existing methods. Experiments on benchmark images show that DehazeNet achieves superior performance over existing methods, yet keeps efficient and easy to use.

autophagic responses. Here, we critically discuss current methods of assessing autophagy and the information they can, or cannot, provide. Our ultimate goal is to encourage intellectual and technical innovation in the field.

Although organic photovoltaic (OPV) cells have many advantages, their performance still lags far behind that of other photovoltaic platforms. A fundamental reason for their low performance is the low charge mobility of organic materials, leading to a limit on the active-layer thickness and efficient light absorption. In this work, guided by a semi-empirical model analysis and using the tandem cell strategy to overcome such issues, and taking advantage of the high diversity and easily tunable band structure of organic materials, a record and certified 17.29% power conversion efficiency for a two-terminal monolithic solution-processed tandem OPV is achieved.

Simultaneous enhancement of open-circuit voltage, short-circuit current density, and fill factor in highly efficient polymer solar cells by incorporating an alcohol/water-soluble conjugated polymer as cathode interlayer is domonstrated. When combined with a low-bandgap polymer PTB7 as the electron donor material, the power efficiency of the devices is improved to certified 8.370%. Due to drastic improvement in efficiency and easy utilization, this method opens new opportunities for PSCs from various material systems to improve towards 10% efficiency. Detailed facts of importance to specialist readers are published as ”Supporting Information”. Such documents are peer-reviewed, but not copy-edited or typeset. They are made available as submitted by the authors. Please note: The publisher is not responsible for the content or functionality of any supporting information supplied by the authors. Any queries (other than missing content) should be directed to the corresponding author for the article.

Sensing from the ultraviolet-visible to the infrared is critical for a variety of industrial and scientific applications. Today, gallium nitride-, silicon-, and indium gallium arsenide--based detectors are used for different sub-bands within the ultraviolet to near-infrared wavelength range. We demonstrate polymer photodetectors with broad spectral response (300 to 1450 nanometers) fabricated by using a small-band-gap semiconducting polymer blended with a fullerene derivative. Operating at room temperature, the polymer photodetectors exhibit detectivities greater than 10(12) cm Hz(1/2)/W and a linear dynamic range over 100 decibels. The self-assembled nanomorphology and device architecture result in high photodetectivity over this wide spectral range and reduce the dark current (and noise) to values well below dark currents obtained in narrow-band photodetectors made with inorganic semiconductors.

Image Super-Resolution (SR) is an important class of image processing techniqueso enhance the resolution of images and videos in computer vision. Recent years have witnessed remarkable progress of image super-resolution using deep learning techniques. This article aims to provide a comprehensive survey on recent advances of image super-resolution using deep learning approaches. In general, we can roughly group the existing studies of SR techniques into three major categories: supervised SR, unsupervised SR, and domain-specific SR. In addition, we also cover some other important issues, such as publicly available benchmark datasets and performance evaluation metrics. Finally, we conclude this survey by highlighting several future directions and open issues which should be further addressed by the community in the future.

Recent progress and strategies toward solar water splitting over heterogeneous semiconductors are reviewed and the challenges and future perspectives are suggested.

Rechargeable aqueous Zn/MnO2 battery chemistry in a neutral or mildly acidic electrolyte has attracted extensive attention recently because all the components (anode, cathode, and electrolyte) in a Zn/MnO2 battery are safe, abundant, and sustainable. However, the reaction mechanism of the MnO2 cathode remains a topic of discussion. Herein, we design a highly reversible aqueous Zn/MnO2 battery where the binder-free MnO2 cathode was fabricated by in situ electrodeposition of MnO2 on carbon fiber paper in mild acidic ZnSO4+MnSO4 electrolyte. Electrochemical and structural analysis identify that the MnO2 cathode experience a consequent H+ and Zn2+ insertion/extraction process with high reversibility and cycling stability. To our best knowledge, it is the first report on rechargeable aqueous batteries with a consequent ion-insertion reaction mechanism.

Fluorescent bioprobes are powerful tools for analytical sensing and optical imaging, which allow direct visualization of biological analytes at the molecular level and offer useful insights into complex biological structures and processes. The sensing and imaging sensitivity of a bioprobe is determined by the brightness and contrast of its fluorescence before and after analyte binding. Emission from a fluorophore is often quenched at high concentration or in aggregate state, which is notoriously known as concentration quenching or aggregation-caused quenching (ACQ). The ACQ effect limits the label-to-analyte ratio and forces researchers to use very dilute solutions of fluorophores. It compels many probes to operate in a fluorescence "turn-off" mode with a narrow scope of practical applications. The unique aggregation-induced emission (AIE) process offers a straightforward solution to the ACQ problem. Typical AIE fluorogens are characterized by their propeller-shaped rotorlike structures, which undergo low-frequency torsional motions as isolated molecules and emit very weakly in solutions. Their aggregates show strong fluorescence mainly due to the restriction of their intramolecular rotations in the aggregate state. This fascinating attribute of AIE fluorogens provides a new platform for the development of fluorescence light-up molecules and photostable nanoaggregates for specific analyte detection and imaging. In this Account, we review our recent AIE work to highlight the utility of AIE effect in the development of new fluorescent bioprobes, which allows the use of highly concentrated fluorogens for biosensing and imaging. The simple design and fluorescence turn-on feature of the molecular AIE bioprobes offer direct visualization of specific analytes and biological processes in aqueous media with higher sensitivity and better accuracy than traditional fluorescence turn-off probes. The AIE dot-based bioprobes with different formulations and surface functionalities show advanced features over quantum dots and small molecule dyes, such as large absorptivity, high luminosity, excellent biocompatibility, free of random blinking, and strong photobleaching resistance. These features enable cancer cell detection, long term cell tracing, and tumor imaging in a noninvasive and high contrast manner. Recent research has significantly expanded the scope of biological applications of AIE fluorogens and offers new strategies to fluorescent bioprobe design. We anticipate that future development on AIE bioprobes will combine one- or multiphoton fluorescence with other modalities (e.g., magnetic resonance imaging) or functionalities (e.g. therapy) to fully demonstrate their potential as a new generation of theranostic reagent. In parallel, the advances in molecular biology will provide more specific bioreceptors, which will enable the development of next generation AIE bioprobes with high selectivity and sensitivity for molecular sensing and imaging.

The gut microbiota has been linked to cardiovascular diseases. However, the composition and functional capacity of the gut microbiome in relation to cardiovascular diseases have not been systematically examined. Here, we perform a metagenome-wide association study on stools from 218 individuals with atherosclerotic cardiovascular disease (ACVD) and 187 healthy controls. The ACVD gut microbiome deviates from the healthy status by increased abundance of Enterobacteriaceae and Streptococcus spp. and, functionally, in the potential for metabolism or transport of several molecules important for cardiovascular health. Although drug treatment represents a confounding factor, ACVD status, and not current drug use, is the major distinguishing feature in this cohort. We identify common themes by comparison with gut microbiome data associated with other cardiometabolic diseases (obesity and type 2 diabetes), with liver cirrhosis, and rheumatoid arthritis. Our data represent a comprehensive resource for further investigations on the role of the gut microbiome in promoting or preventing ACVD as well as other related diseases.The gut microbiota may play a role in cardiovascular diseases. Here, the authors perform a metagenome-wide association study on stools from individuals with atherosclerotic cardiovascular disease and healthy controls, identifying microbial strains and functions associated with the disease.

Residents of the Tibetan Plateau show heritable adaptations to extreme altitude. We sequenced 50 exomes of ethnic Tibetans, encompassing coding sequences of 92% of human genes, with an average coverage of 18x per individual. Genes showing population-specific allele frequency changes, which represent strong candidates for altitude adaptation, were identified. The strongest signal of natural selection came from endothelial Per-Arnt-Sim (PAS) domain protein 1 (EPAS1), a transcription factor involved in response to hypoxia. One single-nucleotide polymorphism (SNP) at EPAS1 shows a 78% frequency difference between Tibetan and Han samples, representing the fastest allele frequency change observed at any human gene to date. This SNP's association with erythrocyte abundance supports the role of EPAS1 in adaptation to hypoxia. Thus, a population genomic survey has revealed a functionally important locus in genetic adaptation to high altitude.

The bulk-heterojunction blend of an electron donor and an electron acceptor material is the key component in a solution-processed organic photovoltaic device. In the past decades, a p-type conjugated polymer and an n-type fullerene derivative have been the most commonly used electron donor and electron acceptor, respectively. While most advances of the device performance come from the design of new polymer donors, fullerene derivatives have almost been exclusively used as electron acceptors in organic photovoltaics. Recently, nonfullerene acceptor materials, particularly small molecules and oligomers, have emerged as a promising alternative to replace fullerene derivatives. Compared to fullerenes, these new acceptors are generally synthesized from diversified, low-cost routes based on building block materials with extraordinary chemical, thermal, and photostability. The facile functionalization of these molecules affords excellent tunability to their optoelectronic and electrochemical properties. Within the past five years, there have been over 100 nonfullerene acceptor molecules synthesized, and the power conversion efficiency of nonfullerene organic solar cells has increased dramatically, from ∼2% in 2012 to >13% in 2017. This review summarizes this progress, aiming to describe the molecular design strategy, to provide insight into the structure-property relationship, and to highlight the challenges the field is facing, with emphasis placed on most recent nonfullerene acceptors that demonstrated top-of-the-line photovoltaic performances. We also provide perspectives from a device point of view, wherein topics including ternary blend device, multijunction device, device stability, active layer morphology, and device physics are discussed.

In this paper, we present LaSOT, a high-quality benchmark for Large-scale Single Object Tracking. LaSOT consists of 1,400 sequences with more than 3.5M frames in total. Each frame in these sequences is carefully and manually annotated with a bounding box, making LaSOT the largest, to the best of our knowledge, densely annotated tracking benchmark. The average video length of LaSOT is more than 2,500 frames, and each sequence comprises various challenges deriving from the wild where target objects may disappear and re-appear again in the view. By releasing LaSOT, we expect to provide the community with a large-scale dedicated benchmark with high quality for both the training of deep trackers and the veritable evaluation of tracking algorithms. Moreover, considering the close connections of visual appearance and natural language, we enrich LaSOT by providing additional language specification, aiming at encouraging the exploration of natural linguistic feature for tracking. A thorough experimental evaluation of 35 tracking algorithms on LaSOT is presented with detailed analysis, and the results demonstrate that there is still a big room for improvements.

Colorectal cancer, a commonly diagnosed cancer in the elderly, often develops slowly from benign polyps called adenoma. The gut microbiota is believed to be directly involved in colorectal carcinogenesis. The identity and functional capacity of the adenoma- or carcinoma-related gut microbe(s), however, have not been surveyed in a comprehensive manner. Here we perform a metagenome-wide association study (MGWAS) on stools from advanced adenoma and carcinoma patients and from healthy subjects, revealing microbial genes, strains and functions enriched in each group. An analysis of potential risk factors indicates that high intake of red meat relative to fruits and vegetables appears to associate with outgrowth of bacteria that might contribute to a more hostile gut environment. These findings suggest that faecal microbiome-based strategies may be useful for early diagnosis and treatment of colorectal adenoma or carcinoma.

With the application of Internet of Things and services to manufacturing, the fourth stage of industrialization, referred to as Industrie 4.0, is believed to be approaching. For Industrie 4.0 to come true, it is essential to implement the horizontal integration of inter-corporation value network, the end-to-end integration of engineering value chain, and the vertical integration of factory inside. In this paper, we focus on the vertical integration to implement flexible and reconfigurable smart factory. We first propose a brief framework that incorporates industrial wireless networks, cloud, and fixed or mobile terminals with smart artifacts such as machines, products, and conveyors. Then, we elaborate the operational mechanism from the perspective of control engineering, that is, the smart artifacts form a self-organized system which is assisted with the feedback and coordination blocks that are implemented on the cloud and based on the big data analytics. In addition, we outline the main technical features and beneficial outcomes and present a detailed design scheme. We conclude that the smart factory of Industrie 4.0 is achievable by extensively applying the existing enabling technologies while actively coping with the technical challenges.