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How can one visually characterize photographs of people over time? In this work, we describe theFaces Through Timedataset, which contains over a thousand portrait images per decade from the 1880s to the present day. Using our new dataset, we devise a framework for resynthesizing portrait images across time, imagining how a portrait taken during a particular decade might have looked like had it been taken in other decades. Our framework optimizes a family of per‐decade generators that reveal subtle changes that differentiate decades—such as different hairstyles or makeup—while maintaining the identity of the input portrait. Experiments show that our method can more effectively resynthesizing portraits across time compared to state‐of‐the‐art image‐to‐image translation methods, as well as attribute‐based and language‐guided portrait editing models. Our code and data will be available at facesthroughtime.github.io.

 

Beneficial relationships between animals and microbial organisms (symbionts) are ubiquitous in nature. In the ocean, microbial symbionts are typically acquired from the environment and their composition across geographic locations is often shaped by adaptation to local habitat conditions. However, it is currently unknown how generalizable these patterns are across symbiotic systems that have contrasting ecological characteristics. To address this question, we compared symbiont population structure between deep-sea hydrothermal vent mussels and co-occurring but ecologically distinct snail species. Our analyses show that mussel symbiont populations are less partitioned by geography and do not demonstrate evidence for environmental adaptation. We posit that the mussel's mixotrophic feeding mode may lower its need to affiliate with locally adapted symbiont strains, while microhabitat stability and symbiont genomic mixing likely favors persistence of symbiont strains across geographic locations. Altogether, these findings further our understanding of the mechanisms shaping symbiont population structure in marine environmentally transmitted symbioses. 

Collaboration between public administration organizations and various stakeholders is often prescribed as a potential solution to the current complex problems of governance, such as climate change. According to the Advocacy Coalition Framework, shared beliefs are one of the most important drivers of collaboration. However, studies investigating the role of beliefs in collaboration show mixed results. Some argue that similarity of general normative and empirical policy beliefs elicits collaboration, while others focus on beliefs concerning policy instruments. Proposing a new divisive beliefs hypothesis, we suggest that agreeing on those beliefs over which there is substantial disagreement in the policy subsystem is what matters for collaboration. Testing our hypotheses using policy network analysis and data on climate policy subsystems in 11 countries (Australia, Brazil, the Czech Republic, Germany, Finland, Ireland, Japan, Korea, Portugal, Sweden, and Taiwan), we find belief similarity to be a stronger predictor of collaboration when the focus is divisive beliefs rather than normative and empirical policy beliefs or beliefs concerning policy instruments. This knowledge can be useful for managing collaborative governance networks because it helps to identify potential competing coalitions and to broker compromises between them.

 

Choosing the optimum assembly approach is essential to achieving a high-quality genome assembly suitable for comparative and evolutionary genomic investigations. Significant recent progress in long-read sequencing technologies such as PacBio and Oxford Nanopore Technologies (ONT) has also brought about a large variety of assemblers. Although these have been extensively tested on model species such as Homo sapiens and Drosophila melanogaster , such benchmarking has not been done in Mollusca, which lacks widely adopted model species. Molluscan genomes are notoriously rich in repeats and are often highly heterozygous, making their assembly challenging. Here, we benchmarked 10 assemblers based on ONT raw reads from two published molluscan genomes of differing properties, the gastropod Chrysomallon squamiferum (356.6 Mb, 1.59% heterozygosity) and the bivalve Mytilus coruscus (1593 Mb, 1.94% heterozygosity). By optimizing the assembly pipeline, we greatly improved both genomes from previously published versions. Our results suggested that 40–50X of ONT reads are sufficient for high-quality genomes, with Flye being the recommended assembler for compact and less heterozygous genomes exemplified by C. squamiferum , while NextDenovo excelled for more repetitive and heterozygous molluscan genomes exemplified by M. coruscus . A phylogenomic analysis using the two updated genomes with 32 other published high-quality lophotrochozoan genomes resulted in maximum support across all nodes, and we show that improved genome quality also leads to more complete matrices for phylogenomic inferences. Our benchmarking will ensure efficiency in future assemblies for molluscs and perhaps also for other marine phyla with few genomes available. This article is part of the Theo Murphy meeting issue ‘Molluscan genomics: broad insights and future directions for a neglected phylum’. 

Abstract Nanosensors have proven to be powerful tools to monitor single cells, achieving spatiotemporal precision even at molecular level. However, there has not been way of extending this approach to statistically relevant numbers of living cells. Herein, we design and fabricate nanosensor array in microfluidics that addresses this limitation, creating a Nanosensor Chemical Cytometry (NCC). nIR fluorescent carbon nanotube array is integrated along microfluidic channel through which flowing cells is guided. We can utilize the flowing cell itself as highly informative Gaussian lenses projecting nIR profiles and extract rich information. This unique biophotonic waveguide allows for quantified cross-correlation of biomolecular information with various physical properties and creates label-free chemical cytometer for cellular heterogeneity measurement. As an example, the NCC can profile the immune heterogeneities of human monocyte populations at attomolar sensitivity in completely non-destructive and real-time manner with rate of ~600 cells/hr, highest range demonstrated to date for state-of-the-art chemical cytometry. 

Explaining collaboration between actors involved in policy processes is crucial for understanding these processes and their outcomes. The policy science literature has advanced several hypotheses explicating what enables or hinders collaboration. However, only a handful of studies compare these factors across different policy contexts. This paper investigates the role of beliefs and influence in shaping collaboration under conditions of high and low conflict by estimating Exponential Random Graph Models using network survey data on the climate policy domains in four countries. Results show that both beliefs and influence are associated with the formation of collaboration ties in the high conflict contexts of South Korea and the United States, whereas neither are significant in the low conflict contexts of Sweden and Switzerland. By considering the level of conflict, our findings provide a more nuanced understanding of when beliefs and influence shape collaboration patterns.