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The life cycle of eukaryotic microorganisms involves complex transitions between states such as dormancy, mating, meiosis, and cell division, which are often studied independently from each other. Therefore, most microbial life cycles are theoretical reconstructions from partial observations of cellular states. Here we show that complete microbial life cycles can be directly and continuously studied by combining microfluidic culturing, life cycle stage-specific segmentation of micrographs, and a novel cell tracking algorithm, FIEST, based on deep learning video frame interpolation. As proof of principle, we quantitatively imaged and compared cell growth and the activity state of the cell division kinase, Cdk1, across the life cycle of Saccharomyces cerevisiae for up to three sexually reproducing generations. Our analysis of S. cerevisiae's life cycle provided the following new insights: 1) the accumulation of cell cycle regulators, such as Whi5, is tailored to each life cycle stage; 2) cell growth always preceded exit from nonproliferative states in our conditions; 3) the temporal coordination of meiotic events is the same across sexually reproducing populations when each generation is exposed to same conditions; 4) information such as cell size and morphology resets after each sexual reproduction cycle. Image processing and tracking algorithms are available as the Python package Yeastvision, which could be used study pathogens such as Candida glabrata, Cryptococcus neoformans, Colletotrichum acutatum, and other unicellular systems. 

Globally, winter temperatures are rising, and snowpack is shrinking or disappearing entirely. Despite previous research and published literature reviews, it remains unknown whether biomes across the globe will cross important thresholds in winter temperature and precipitation that will lead to significant ecological changes. Here, we combine the widely used Köppen–Geiger climate classification system with worst-case-scenario projected changes in global monthly temperature and precipitation to illustrate how multiple climatic zones across Earth may experience shifting winter conditions by the end of this century. We then examine how these shifts may affect ecosystems within corresponding biomes. Our analysis demonstrates potential widespread losses of extreme cold (<−20°C) in Arctic, boreal, and cool temperate regions. We also show the possible disappearance of freezing temperatures (<0°C) and large decreases in snowfall in warm temperate and dryland areas. We identify important and potentially irreversible ecological changes associated with crossing these winter climate thresholds. 

Blue phase (BP) liquid crystals represent a fascinating state of soft matter that showcases unique optical and electro-optical properties. Existing between chiral nematic and isotropic phases, BPs are characterized by a three-dimensional cubic lattice structure resulting in selective Bragg reflections of light and consequent vivid structural colors. However, the practical realization of these material systems is hampered by their narrow thermal stability and multi-domain crystalline nature. This feature article provides an overview of the efforts devoted to stabilizing these phases and creating monodomain structures. In particular, it delves into the complex relationship between geometrical confinement, induced curvature, and the structural stability and photonic features of BPs. Understanding the interaction of curved confinement and structural stability of BPs proves crucially important for the integration of these materials into flexible and miniaturized devices. By shedding light on these critical aspects, this feature review aims to highlight the significance of understanding the coupling effects of physical and mechanical forces on the structural stability of these systems, which can pave the way for the development of efficient and practical devices based on BP liquid crystals. 

Condensates have emerged as a new way to understand how cells are orga- nized, and have been invoked to play crucial roles in essentially all cellular processes. In this view, the cell is occupied by numerous assemblies, each composed of member proteins and nucleic acids that preferentially interact with each other. However, available visual represen- tations of condensates fail to communicate the growing body of knowledge about how con- densates form and function. The resulting focus on only a subset of the potential implications of condensates can skew interpretations of results and hinder the generation of new hypoth- eses. Here we summarize the discussion from a workshop that brought together cell biolo- gists, visualization and computation specialists, and other experts who specialize in thinking about space and ways to represent it. We place the recent advances in condensate research in a historical perspective that describes evolving views of the cell; highlight different attri- butes of condensates that are not well-served by current visual conventions; and survey po- tential approaches to overcome these challenges. An important theme of these discussions is that the new understanding on the roles of condensates exposes broader challenges in visual representations that apply to cell biological research more generally. 

Abstract Transparency is essential for public awareness of government activity and in holding officials accountable for their behavior and decisions. However, executives understandably have a desire to maintain autonomy over the flow of information outside of the executive branch, which can sometimes lead to a clash between government openness and executive control over information. This article investigates executive branch transparency along two specific dimensions: threats to the preservation of government information, and the judicial monitoring of executive branch transparency. Federal law directs executive branch actors to preserve government information. Statutes and regulations detail governing policies as well as guidelines that apply to every presidential administration. However, we consider each rule and recommendation through the lens of the Trump administration to gain greater clarity and precision. The Trump administration proves a useful focus for our empirical analysis because of its recency as well as multiple reports of its improper handling and preservation of records. We lay out and develop a typology of threats to record preservation. Preservation conflicts have emerged across multiple presidential administrations and have become increasingly common and visible. Judicial monitoring of executive branch transparency has become a crucial tool to address the withholding of records. We show that federal judges can play a vital role in defining the boundaries of government transparency through their decisions in Freedom of Information Act (FOIA) litigation. The U.S. Department of Justice oversees and often leads the government's defense against FOIA actions. We find that federal judges are most likely to require executive branch responsiveness and disclosure when the judges' underlying policy preferences are most distant from that of the administration. Our findings should inform reforms to protect government transparency. 

Innovation in ecological restoration is necessary to achieve the ambitious targets established in United Nations conventions and other global restoration initiatives. Innovation is also crucial for navigating uncertainties in repairing and restoring ecosystems, and thus practitioners often develop innovations at project design and implementation stages. However, innovation in ecological restoration can be hindered by many factors (e.g., time and budget constraints, and project complexity). Theory and research on innovation has been formally applied in many fields, yet explicit study of innovation in ecological restoration remains nascent. To assess the use of innovation in restoration projects, including its drivers and inhibitors, we conducted a social survey of restoration practitioners in the United States. Specifically, we assessed relationships between project-based innovation and traits of the individual practitioner (including, for example, age, gender, experience); company (including, for example, company size and company’s inclusion of social goals); project (including, for example, complexity and uncertainty); and project outcomes (such as completing the project on time/on budget and personal satisfaction with the work). We found positive relationships between project-based innovation and practitioner traits (age, gender, experience, engagement with research scientists), one company trait (company’s inclusion of social goals in their portfolio), and project traits (project complexity and length). In contrast, two practitioner traits, risk aversion and the use of industry-specific information, were negatively related to project-based innovation. Satisfaction with project outcomes was positively correlated with project-based innovation. Collectively, the results provide insights into the drivers and inhibitors of innovation in restoration and suggest opportunities for research and application. 

As lithographic techniques advance in their capabilities of shrinking microelectronics devices, the need for improved resist materials, especially for extreme ultraviolet (EUV), has become increasingly pressing. In this work, we study the molecular layer deposition (MLD) of an Al-based hybrid thin film resist, known as “alucone,” extending our previous research that tested the Hf-based hybrid thin film “hafnicone” as an EUV resist. Alucone is grown at 100 ºC using the metal precursor trimethylaluminum and the organic precursor ethylene glycol. Like hafnicone, alucone behaves as a negative tone resist that can resolve 50-nm line widths, though preliminary data suggest that alucone’s line patterns are more sharply defined than those of hafnicone. Whereas hafnicone’s sensitivity is 400 μC/cm2 using 3 M HCl as the developer, alucone’s sensitivity is not yet as good (4800 μC/cm2 using 0.125 M HCl). Our study of alucone offers new insight into structural features of an MLD film that can lead to desired EUV-responsive behavior. This insight may accelerate the development of vapor-deposited inorganic resists for use in electron-beam and EUV lithography. 

Emulators of ice flow models have shown promise for speeding up simulations of glaciers and ice sheets. Existing ice flow emulators have relied primarily on convolutional neural networks (CNN’s), which assume that model inputs and outputs are discretized on a uniform computational grid. However, many existing finite element-based ice sheet models such as the Ice-Sheet and Sea-level System model (ISSM) benefit from their ability to use unstructured computational meshes. Unstructured meshes allow for greater flexibility and computational efficiency in many modeling scenarios. In this work, we present an emulator of a higher order, finite element ice flow model based on a graph neural network (GNN) architecture. In this architecture, an unstructured finite element mesh is represented as a graph, with inputs and outputs of the ice flow model represented as variables on graph nodes and edges. An advantage of this approach is that the ice flow emulator can interface directly with a standard finite element –based ice sheet model by mapping between the finite element mesh and a graph suitable for the GNN emulator. We test the ability of the GNN to predict velocity fields on complex mountain glacier geometries and show how the emulated velocity can be used to solve for mass continuity using a standard finite element approach.