GENHOP: An Image Generation Method Based on Successive Subspace Learning

Being different from deep-learning-based (DL-based) image generation methods, a new image generative model built upon successive subspace learning principle is proposed and named GenHop (an acronym of Generative PixelHop) in this work. GenHop consists of three modules: 1) high-to-low dimension reduction, 2) seed image generation, and 3) low-to-high dimension expansion. In the first module, it builds a sequence of high-to-low dimensional subspaces through a sequence of whitening processes, each of which contains samples of joint-spatial-spectral representation. In the second module, it generates samples in the lowest dimensional subspace. In the third module, it finds a proper high-dimensional sample for a seed image by adding details back via locally linear embedding (LLE) and a sequence of coloring processes. Experiments show that GenHop can generate visually pleasant images whose FID scores are comparable or even better than those of DL-based generative models for MNIST, Fashion-MNIST and CelebA datasets.Comment: 10 pages, 5 figures, accepted by ISCAS 202

Glycerol Carbonate: A Novel Biosolvent with Strong Ionizing and Dissociating Powers

The activity of biocatalysts in nonaqueous solvents is related to the interaction of organic solvents with cells or enzymes. The behavior of proteins is strongly dependent on the protonation state of their ionizable groups, which ionization constants are greatly affected by the solvent. Due to the weak ionizing and dissociating powers of common organic solvents, the charge of the protein will change significantly when the protein is transferred from water to common organic solvents, resulting in protein denaturation. In this work, glycerol carbonate (GC) was synthesized, which ionizing and dissociating abilities were very close to those of water. Transesterification activities of Candida antarctica lipase B (CALB) in GC were comparable to those in water and remained constant during 4-week storage. Bacillus subtilis and Saccharomyecs cerevisiae were cultured in liquid media containing GC with test tubes. In the medium containing low GC concentration, Bacillus subtilis and Saccharomyecs cerevisiae grew well as in a medium containing no organic solvent, but, in the medium containing high GC concentration, the growth of Bacillus subtilis and Saccharomyecs cerevisiae was suppressed. The results suggested that GC is a potential biosolvent, which has great significance to biocatalysis in nonaqueous solvents

DDNet: Dual-path Decoder Network for Occlusion Relationship Reasoning

Occlusion relationship reasoning based on convolution neural networks consists of two subtasks: occlusion boundary extraction and occlusion orientation inference. Due to the essential differences between the two subtasks in the feature expression at the higher and lower stages, it is challenging to carry on them simultaneously in one network. To address this issue, we propose a novel Dual-path Decoder Network, which uniformly extracts occlusion information at higher stages and separates into two paths to recover boundary and occlusion orientation respectively in lower stages. Besides, considering the restriction of occlusion orientation presentation to occlusion orientation learning, we design a new orthogonal representation for occlusion orientation and proposed the Orthogonal Orientation Regression loss which can get rid of the unfitness between occlusion representation and learning and further prompt the occlusion orientation learning. Finally, we apply a multi-scale loss together with our proposed orientation regression loss to guide the boundary and orientation path learning respectively. Experiments demonstrate that our proposed method achieves state-of-the-art results on PIOD and BSDS ownership datasets

Ultra-fast charging in aluminum-ion batteries: electric double layers on active anode

With the rapid iteration of portable electronics and electric vehicles, developing high-capacity batteries with ultra-fast charging capability has become a holy grail. Here we report rechargeable aluminum-ion batteries capable of reaching a high specific capacity of 200 mAh g−1. When liquid metal is further used to lower the energy barrier from the anode, fastest charging rate of 104 C (duration of 0.35 s to reach a full capacity) and 500% more specific capacity under high-rate conditions are achieved. Phase boundaries from the active anode are believed to encourage a high-flux charge transfer through the electric double layers. As a result, cationic layers inside the electric double layers responded with a swift change in molecular conformation, but anionic layers adopted a polymer-like configuration to facilitate the change in composition

Omics-based interpretation of synergism in a soil-derived cellulose-degrading microbial community

Reaching a comprehensive understanding of how nature solves the problem of degrading recalcitrant biomass may eventually allow development of more efficient biorefining processes. Here we interpret genomic and proteomic information generated from a cellulolytic microbial consortium (termed F1RT) enriched from soil. Analyses of reconstructed bacterial draft genomes from all seven uncultured phylotypes in F1RT indicate that its constituent microbes cooperate in both cellulose-degrading and other important metabolic processes. Support for cellulolytic inter-species cooperation came from the discovery of F1RT microbes that encode and express complimentary enzymatic inventories that include both extracellular cellulosomes and secreted free-enzyme systems. Metabolic reconstruction of the seven F1RT phylotypes predicted a wider genomic rationale as to how this particular community functions as well as possible reasons as to why biomass conversion in nature relies on a structured and cooperative microbial community

Assessment of climate change impacts on cork oak in western Mediterranean regions : a comparative analysis of extreme indices

Mediterranean regions have a growing number of extreme weather events due to rapid change of climate. Cork oak, which is located in the western Mediterranean area, has become a very valuable resource within the western Mediterranean forests. Therefore, assessment of the impacts of climate extremes upon cork oak can help us produce better forest management practices for coping with future climate change, and to achieve the purpose of sustainable development of the ecosystems and societies within the Mediterranean area in the future. In order to have a comprehensive understanding of how climate affects cork oak, climate extremes are investigated for western Mediterranean regions, especially Portugal and Northwest Africa. 15 indices of frequency and intensity indicators were derived from daily maximum temperature and daily precipitation data of the period from 1979 to 2009, and used in this investigation. Overview maps of the annual maximum temperature and annual precipitation sum distribution were plotted. Exploratory Factor analysis (EFA) was applied to find out the underlying temporal variance for those indices. And on this basis, 15 indices were simplified into several variables. Correlation analysis is adopted to identify the relationship between those climate variables that generated by EFA and cork production. Burned area was also involved in this analysis as a special case in Portugal. A Regression model was developed to make a prediction of cork production by viewing those climate factors as dependent variables. The results of those analyses show that as annual rainfall and maximum temperature changes, distribution of cork oak stands may have a potential of moving to the northwest. Northwest Africa is the recipient of climate extremes, especially hot and dry extremes, with higher frequency and intensity compared to Portugal. Summer dry extremes rather than rainfall extremes, can have considerable effect upon cork production, while burned area shows no correlation with cork production