BOOT: Data-free Distillation of Denoising Diffusion Models with Bootstrapping

Diffusion models have demonstrated excellent potential for generating diverse images. However, their performance often suffers from slow generation due to iterative denoising. Knowledge distillation has been recently proposed as a remedy that can reduce the number of inference steps to one or a few without significant quality degradation. However, existing distillation methods either require significant amounts of offline computation for generating synthetic training data from the teacher model or need to perform expensive online learning with the help of real data. In this work, we present a novel technique called BOOT, that overcomes these limitations with an efficient data-free distillation algorithm. The core idea is to learn a time-conditioned model that predicts the output of a pre-trained diffusion model teacher given any time step. Such a model can be efficiently trained based on bootstrapping from two consecutive sampled steps. Furthermore, our method can be easily adapted to large-scale text-to-image diffusion models, which are challenging for conventional methods given the fact that the training sets are often large and difficult to access. We demonstrate the effectiveness of our approach on several benchmark datasets in the DDIM setting, achieving comparable generation quality while being orders of magnitude faster than the diffusion teacher. The text-to-image results show that the proposed approach is able to handle highly complex distributions, shedding light on more efficient generative modeling.Comment: In progres

Enriching the endophytic bacterial microbiota of Ginkgo roots

Bacterial endophytes of Ginkgo roots take part in the secondary metabolic processes of the fossil tree and contribute to plant growth, nutrient uptake, and systemic resistance. However, the diversity of bacterial endophytes in Ginkgo roots is highly underestimated due to the lack of successful isolates and enrichment collections. The resulting culture collection contains 455 unique bacterial isolates representing 8 classes, 20 orders, 42 families, and 67 genera from five phyla: Actinobacteria, Bacteroidetes, Firmicutes, Proteobacteria, and Deinococcus-Thermus, using simply modified media (a mixed medium without any additional carbon sources [MM)] and two other mixed media with separately added starch [GM] and supplemented glucose [MSM]). A series of plant growth-promoting endophytes had multiple representatives within the culture collection. Moreover, we investigated the impact of refilling carbon sources on enrichment outcomes. Approximately 77% of the natural community of root-associated endophytes were predicted to have successfully cultivated the possibility based on a comparison of the 16S rRNA gene sequences between the enrichment collections and the Ginkgo root endophyte community. The rare or recalcitrant taxa in the root endosphere were mainly associated with Actinobacteria, Alphaproteobacteria, Blastocatellia, and Ktedonobacteria. By contrast, more operational taxonomic units (OTUs) (0.6% in the root endosphere) became significantly enriched in MM than in GM and MSM. We further found that the bacterial taxa of the root endosphere had strong metabolisms with the representative of aerobic chemoheterotrophy, while the functions of the enrichment collections were represented by the sulfur metabolism. In addition, the co-occurrence network analysis suggested that the substrate supplement could significantly impact bacterial interactions within the enrichment collections. Our results support the fact that it is better to use the enrichment to assess the cultivable potential and the interspecies interaction as well as to increase the detection/isolation of certain bacterial taxa. Taken together, this study will deepen our knowledge of the indoor endophytic culture and provide important insights into the substrate-driven enrichment

Learning Controllable 3D Diffusion Models from Single-view Images

Diffusion models have recently become the de-facto approach for generative modeling in the 2D domain. However, extending diffusion models to 3D is challenging due to the difficulties in acquiring 3D ground truth data for training. On the other hand, 3D GANs that integrate implicit 3D representations into GANs have shown remarkable 3D-aware generation when trained only on single-view image datasets. However, 3D GANs do not provide straightforward ways to precisely control image synthesis. To address these challenges, We present Control3Diff, a 3D diffusion model that combines the strengths of diffusion models and 3D GANs for versatile, controllable 3D-aware image synthesis for single-view datasets. Control3Diff explicitly models the underlying latent distribution (optionally conditioned on external inputs), thus enabling direct control during the diffusion process. Moreover, our approach is general and applicable to any type of controlling input, allowing us to train it with the same diffusion objective without any auxiliary supervision. We validate the efficacy of Control3Diff on standard image generation benchmarks, including FFHQ, AFHQ, and ShapeNet, using various conditioning inputs such as images, sketches, and text prompts. Please see the project website (\url{https://jiataogu.me/control3diff}) for video comparisons.Comment: work in progres

Metabolic Engineering to Improve Docosahexaenoic Acid Production in Marine Protist Aurantiochytrium sp. by Disrupting 2,4-Dienoyl-CoA Reductase

Docosahexaenoic acid (DHA) has attracted attention from researchers because of its pharmacological and nutritional importance. Currently, DHA production costs are high due to fermentation inefficiency; however, improving DHA yield by metabolic engineering in thraustochytrids is one approach to reduce these costs. In this study, a high-yielding (53.97% of total fatty acids) DHA production strain was constructed by disrupting polyunsaturated fatty acid beta-oxidation via knockout of the 2,4-dienyl-CoA reductase (DECR) gene (KO strain) in Aurantiochytrium sp. Slight differences in cell growth was observed in the wild-type and transformants (OE and KO), with cell concentrations in stationary of 2.65×106, 2.36×106 and 2.56×106 cells mL-1 respectively. Impressively, the KO strain yielded 21.62% more neutral lipids and 57.34% greater DHA production; moreover, the opposite was observed when overexpressing DECR (OE strain), with significant decreases of 30.49% and 64.61%, respectively. Furthermore, the KO strain showed a prolonged DHA production period with a sustainable increase from 63 to 90 h (170.03 to 203.27 mg g−1 DCW), while that of the wildtype strain decreased significantly from 150.58 to 140.10 mg g−1 DCW. This new approach provides an advanced proxy for the construction of sustainable DHA production strains for industrial purposes and deepens our understanding of the metabolic pathways of Aurantiochytrium sp

Defining Global Gene Expression Changes of the Hypothalamic-Pituitary-Gonadal Axis in Female sGnRH-Antisense Transgenic Common Carp (Cyprinus carpio)

BACKGROUND: The hypothalamic-pituitary-gonadal (HPG) axis is critical in the development and regulation of reproduction in fish. The inhibition of neuropeptide gonadotropin-releasing hormone (GnRH) expression may diminish or severely hamper gonadal development due to it being the key regulator of the axis, and then provide a model for the comprehensive study of the expression patterns of genes with respect to the fish reproductive system. METHODOLOGY/PRINCIPAL FINDINGS: In a previous study we injected 342 fertilized eggs from the common carp (Cyprinus carpio) with a gene construct that expressed antisense sGnRH. Four years later, we found a total of 38 transgenic fish with abnormal or missing gonads. From this group we selected the 12 sterile females with abnormal ovaries in which we combined suppression subtractive hybridization (SSH) and cDNA microarray analysis to define changes in gene expression of the HPG axis in the present study. As a result, nine, 28, and 212 genes were separately identified as being differentially expressed in hypothalamus, pituitary, and ovary, of which 87 genes were novel. The number of down- and up-regulated genes was five and four (hypothalamus), 16 and 12 (pituitary), 119 and 93 (ovary), respectively. Functional analyses showed that these genes involved in several biological processes, such as biosynthesis, organogenesis, metabolism pathways, immune systems, transport links, and apoptosis. Within these categories, significant genes for neuropeptides, gonadotropins, metabolic, oogenesis and inflammatory factors were identified. CONCLUSIONS/SIGNIFICANCE: This study indicated the progressive scaling-up effect of hypothalamic sGnRH antisense on the pituitary and ovary receptors of female carp and provided comprehensive data with respect to global changes in gene expression throughout the HPG signaling pathway, contributing towards improving our understanding of the molecular mechanisms and regulative pathways in the reproductive system of teleost fish

Unloading Mechanics and Energy Characteristics of Sandstone under Different Intermediate Principal Stress Conditions

The TRW-3000 true triaxial rock testing machine was used to conduct loading and unloading tests of sandstone under different σ2, and the true triaxial lateral unloading mechanics and energy characteristics of sandstone under different σ2 were studied. The experimental results show the following: (1) compared with the results of the loading test, the peak strength of the sandstone under the unloading σ3 path is reduced, the unloading direction has obvious expansion and deformation, and the amount of expansion increases significantly with the increase of σ2; sudden brittle failure occurs at the end of unloading. E gradually decreases with the increase of H, and it performs well to use the cubic polynomial to fit the curve of E-H. (2) The Mogi–Coulomb strength criterion can accurately describe the true triaxial strength characteristics of sandstone under loading and unloading conditions. Compared with the results of the loading test, the values of c and φ obtained based on this criterion under the unloading σ3 path are reduced. (3) Under the condition of unloading σ3, U,Ue, and Ud, when the specimen is broken, are all linearly positively correlated with σ2. Ud increases nonlinearly with the increase of H, and as σ2 increases, the slope of the Ud-H curve becomes larger, and the specimen consumes more energy under the same unloading amount. Most of the energy absorbed by the specimen under the unloading σ3 path is converted into Ue, but as σ2 increases, Ud /U increases, and the energy consumed when the specimen is broken is greater

Structural Correspondence Learning for Cross-Lingual Sentiment Classification with One-to-Many Mappings

Structural correspondence learning (SCL) is an effective method for cross-lingual sentiment classification. This approach uses unlabeled documents along with a word translation oracle to automatically induce task specific, cross-lingual correspondences. It transfers knowledge through identifying important features, i.e., pivot features. For simplicity, however, it assumes that the word translation oracle maps each pivot feature in source language to exactly only one word in target language. This one-to-one mapping between words in different languages is too strict. Also the context is not considered at all. In this paper, we propose a cross-lingual SCL based on distributed representation of words; it can learn meaningful one-to-many mappings for pivot words using large amounts of monolingual data and a small dictionary. We conduct experiments on NLP&CC 2013 cross-lingual sentiment analysis dataset, employing English as source language, and Chinese as target language. Our method does not rely on the parallel corpora and the experimental results show that our approach is more competitive than the state-of-the-art methods in cross-lingual sentiment classification

Enhanced Electrochemical Characteristics of the Glucose Oxidase Bioelectrode Constructed by Carboxyl-Functionalized Mesoporous Carbon

This research revealed the effect of carboxyl-functionalization on the mesoporous carbon (MC)-fixed glucose oxidase (GOx) for promoting the properties of bioelectrodes. It showed that the oxidation time, temperature and concentration, can significantly affect MC carboxylation. The condition of 2 M ammonium persulfate, 50 °C and 24 h was applied in the study for the successful addition of carboxyl groups to MC, analyzed by FTIR. The nitrogen adsorption isotherms, and X-ray diffraction analysis showed that the carboxylation process slightly changed the physical properties of MC and that the specific surface area and pore size were all well-maintained in MC-COOH. Electrochemical characteristics analysis showed that Nafion/GOx/MC-COOH presented better electrocatalytic activity with greater peak current intensity (1.13-fold of oxidation peak current and 4.98-fold of reduction peak current) compared to Nafion/GOx/MC. Anodic charge-transfer coefficients (α) of GOx/MC-COOH increased to 0.77, implying the favored anodic reaction. Furthermore, the GOx immobilization and enzyme activity in MC-COOH increased 140.72% and 252.74%, leading to the enhanced electroactive GOx surface coverage of Nafion/GOx/MC-COOH electrode (22.92% higher, 1.29 × 10−8 mol cm−2) than the control electrode. Results showed that carboxyl functionalization could increase the amount and activity of immobilized GOx, thereby improving the electrode properties

Influence of biochar incorporation on the collector surface properties and the transport of silver nanoparticles in porous media

Biochar is widely used as a soil amendment due to its environmental friendliness and convenient availability. It is believed that the presence of biochar in porous media can influence the transport of colloidal and solute contaminants. In this study, different mass ratios of biochar were added to packed sand with a rough or smooth surface to determine the significance of biochar on the retention and release of silver nanoparticles (AgNPs). The results showed that biochar reduced the transport of AgNPs in rough and smooth sands under different solution conditions. A small amount of biochar (0.1–1% in mass percentage) can significantly enhance the retention of AgNPs due to the alteration in collector surface roughness and chemical heterogeneity that potentially reduce the energy barrier for retention. Furthermore, the retention of AgNPs in rough sand was always higher than that in smooth sand under the same experimental conditions. The presence of biochar also produced nonmonotonic retention of AgNPs mainly due to the changes in collector surface roughness. Additionally, the AgNPs retention associated with biochar tended to be irreversible due to the charge heterogeneity, while the reversible retention could mainly occur on a rough sand surface via shallow primary minima. This work highlights the significance of collector surface roughness that needs to be considered in the process of biochar amendment for practical applications to effectively immobilize colloidal contaminants in soil or groundwater