PromptStyler: Prompt-driven Style Generation for Source-free Domain Generalization

In a joint vision-language space, a text feature (e.g., from "a photo of a dog") could effectively represent its relevant image features (e.g., from dog photos). Inspired by this, we propose PromptStyler which simulates various distribution shifts in the joint space by synthesizing diverse styles via prompts without using any images to deal with source-free domain generalization. Our method learns to generate a variety of style features (from "a S* style of a") via learnable style word vectors for pseudo-words S*. To ensure that learned styles do not distort content information, we force style-content features (from "a S* style of a [class]") to be located nearby their corresponding content features (from "[class]") in the joint vision-language space. After learning style word vectors, we train a linear classifier using synthesized style-content features. PromptStyler achieves the state of the art on PACS, VLCS, OfficeHome and DomainNet, although it does not require any images and takes just ~30 minutes for training using a single GPU.Comment: Accepted to ICCV 2023, Project Page: https://promptstyler.github.io

Measurement of Volatile Compounds for Real-Time Analysis of Soil Microbial Metabolic Response to Simulated Snowmelt

Snowmelt dynamics are a significant determinant of microbial metabolism in soil and regulate global biogeochemical cycles of carbon and nutrients by creating seasonal variations in soil redox and nutrient pools. With an increasing concern that climate change accelerates both snowmelt timing and rate, obtaining an accurate characterization of microbial response to snowmelt is important for understanding biogeochemical cycles intertwined with soil. However, observing microbial metabolism and its dynamics non-destructively remains a major challenge for systems such as soil. Microbial volatile compounds (mVCs) emitted from soil represent information-dense signatures and when assayed non-destructively using state-of-the-art instrumentation such as Proton Transfer Reaction-Time of Flight-Mass Spectrometry (PTR-TOF-MS) provide time resolved insights into the metabolism of active microbiomes. In this study, we used PTR-TOF-MS to investigate the metabolic trajectory of microbiomes from a subalpine forest soil, and their response to a simulated wet-up event akin to snowmelt. Using an information theory approach based on the partitioning of mutual information, we identified mVC metabolite pairs with robust interactions, including those that were non-linear and with time lags. The biological context for these mVC interactions was evaluated by projecting the connections onto the Kyoto Encyclopedia of Genes and Genomes (KEGG) network of known metabolic pathways. Simulated snowmelt resulted in a rapid increase in the production of trimethylamine (TMA) suggesting that anaerobic degradation of quaternary amine osmo/cryoprotectants, such as glycine betaine, may be important contributors to this resource pulse. Unique and synergistic connections between intermediates of methylotrophic pathways such as dimethylamine, formaldehyde and methanol were observed upon wet-up and indicate that the initial pulse of TMA was likely transformed into these intermediates by methylotrophs. Increases in ammonia oxidation signatures (transformation of hydroxylamine to nitrite) were observed in parallel, and while the relative role of nitrifiers or methylotrophs cannot be confirmed, the inferred connection to TMA oxidation suggests either a direct or indirect coupling between these processes. Overall, it appears that such mVC time-series from PTR-TOF-MS combined with causal inference represents an attractive approach to non-destructively observe soil microbial metabolism and its response to environmental perturbation

Switchable Gene Expression in Escherichia coli Using a Miniaturized Photobioreactor

We present a light-switchable gene expression system for both inducible and switchable control of gene expression at a single cell level in Escherichia coli using a previously constructed light-sensing system. The lambda cl repressor gene with an LVA degradation tag was expressed under the control of the ompC promoter on the chromosome. The green fluorescent protein (GFP) gene fused to a lambda repressor-repressible promoter was used as a reporter. This light-switchable system allows rapid and reversible induction or repression of expression of the target gene at any desired time. This system also ensures homogenous expression across the entire cell population. We also report the design of a miniaturized photobioreactor to be used in combination with the light-switchable gene expression system. The miniaturized photobioreactor helps to reduce unintended induction of the light receptor due to environmental disturbances and allows precise control over the duration of induction. This system would be a good tool for switchable, homogenous, strong, and highly regulatable expression of target genes over a wide range of induction times. Hence, it could be applied to study gene function, optimize metabolic pathways, and control biological systems both spatially and temporally.open0

LEAFWISE COHOMOLOGICAL EXPRESSION OF DYNAMICAL ZETA FUNCTIONS ON FOLIATED DYNAMICAL SYSTEMS (Analytic Number Theory and Related Topics)

A Riemmanian foliated dynamical system of 3-dimension (RFDS3)is a closed Riemannian 3-manifold with additional structures: foliation, dynamical system. In the context of arithmetic topology, it is a geometric/analytic analogue of an arithmetic scheme with a conjectural dynamical system suggested by C. Deninger. In this paper, we show leafwise cohomological expression of dynamical zeta function on a Riemannian foliated dynamical system