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Abstract We propose and unify classes of different models for information propagation over graphs. In a first class, propagation is modelled as a wave, which emanates from a set ofknownnodes at an initial time, to all otherunknownnodes at later times with an ordering determined by the arrival time of the information wave front. A second class of models is based on the notion of a travel time along paths between nodes. The time of information propagation from an initialknownset of nodes to a node is defined as the minimum of a generalised travel time over subsets of all admissible paths. A final class is given by imposing a local equation of an eikonal form at eachunknownnode, with boundary conditions at theknownnodes. The solution value of the local equation at a node is coupled to those of neighbouring nodes with lower values. We provide precise formulations of the model classes and prove equivalences between them. Finally, we apply the front propagation models on graphs to semi-supervised learning via label propagation and information propagation on trust networks. 

Abstract BackgroundThe increasing size, severity, and frequency of wildfires is one of the most rapid ways climate warming could alter the structure and function of high-latitude ecosystems. Historically, boreal forests in western North America had fire return intervals (FRI) of 70–130 years, but shortened FRIs are becoming increasingly common under extreme weather conditions. Here, we quantified pre-fire and post-fire C pools and C losses and assessed post-fire seedling regeneration in long (> 70 years), intermediate (30–70 years), and short (< 30 years) FRIs, and triple (three fires in < 70 years) burns. As boreal forests store a significant portion of the global terrestrial carbon (C) pool, understanding the impacts of shortened FRIs on these ecosystems is critical for predicting the global C balance and feedbacks to climate. ResultsUsing a spatially extensive dataset of 555 plots from 31 separate fires in Interior Alaska, our study demonstrates that shortened FRIs decrease the C storage capacity of boreal forests through loss of legacy C and regeneration failure. Total wildfire C emissions were similar among FRI classes, ranging from 2.5 to 3.5 kg C m⁻². However, shortened FRIs lost proportionally more of their pre-fire C pools, resulting in substantially lower post-fire C pools than long FRIs. Shortened FRIs also resulted in the combustion of legacy C, defined as C that escaped combustion in one or more previous fires. We found that post-fire successional trajectories were impacted by FRI, with ~ 65% of short FRIs and triple burns experiencing regeneration failure. ConclusionsOur study highlights the structural and functional vulnerability of boreal forests to increasing fire frequency. Shortened FRIs and the combustion of legacy C can shift boreal ecosystems from a net C sink or neutral to a net C source to the atmosphere and increase the risk of transitions to non-forested states. These changes could have profound implications for the boreal C-climate feedback and underscore the need for adaptive management strategies that prioritize the structural and functional resilience of boreal forest ecosystems to expected increases in fire frequency. 

Networks with controlled ratios of neutral and ionic dynamic crosslinks were prepared and demonstrate multiple damping modes. 

Abstract Bursty star formation—a key prediction for high-redshift galaxies from cosmological simulations explicitly resolving stellar feedback in the interstellar medium—has recently been observed to prevail among galaxies at redshiftz≳ 6. Line intensity mapping (LIM) of the 158μm [Cii] line as a star formation rate (SFR) indicator offers unique opportunities to tomographically constrain cosmic star formation at high redshift, in a way complementary to observations of individually detected galaxies. To understand the effects of bursty star formation on [Cii] LIM, which have remained unexplored in previous studies, we present an analytic modeling framework for high-zgalaxy formation and [Cii] LIM signals that accounts for bursty star formation histories induced by delayed supernova feedback. We use it to explore and characterize how bursty star formation can impact and thus complicate the interpretation of the [Cii] luminosity function and power spectrum. Our simple analytic model indicates that bursty star formation mainly affects low-mass galaxies by boosting their average SFR and [Cii] luminosity, and in the [Cii] power spectrum it can create a substantial excess in the large-scale clustering term. This distortion results in a power spectrum shape that cannot be explained by invoking a mass-independent logarithmic scatter. We conclude that burstiness must be accounted for when modeling and analyzing [Cii] data sets from the early Universe, and that in the extreme, the signature of burstiness may be detectable with first-generation experiments such as TIME, CONCERTO, and CCAT-DSS. 

Abstract This study evaluates a popular density current propagation speed equation using a large, novel set of radiosonde and dropsonde observations. Data from pairs of sondes launched inside and outside of cold pools along with the theoretical density current propagation speed equation are used to calculate sonde-based propagation speeds. Radar-/satellite-based propagation speeds, assumed to be the truth, are calculated by manually tracking the propagation of cold pools and correcting for advection due to the background wind. Several results arise from the comparisons of the theoretical sonde-based speeds with the radar-/satellite-based speeds. First, sonde-based and radar-based propagation speeds are strongly correlated for U.S. High Plains cold pools, suggesting the density current propagation speed equation is appropriate for use in midlatitude continental environments. Second, cold pool Froude numbers found in this study are in agreement with previous studies. Third, sonde-based propagation speeds are insensitive to how cold pool depth is defined since the preponderance of negative buoyancy is near the surface in cold pools. Fourth, assuming an infinite channel depth and assuming an incompressible atmosphere when deriving the density current propagation speed equation can increase sonde-based propagation speeds by up to 20% and 11%, respectively. Finally, sonde-based propagation speeds can vary by ∼300% based on where and when the sondes were launched, suggesting submesoscale variability could be a major influence on cold pool propagation. 

Sensitive, accurate, and early detection of biomarkers is essential for prompt response to medical decisions for saving lives. Some infectious diseases are deadly even in small quantities and require early detection for patients and public health. The scarcity of these biomarkers necessitates signal amplification before diagnosis. Recently, we demonstrated single-molecule-level detection of tuberculosis biomarker, lipoarabinomannan, from patient urine using silver plasmonic gratings with thin plasma-activated alumina. While powerful, biomarker binding density was limited by the surface density of plasma-activated carbonyl groups, that degraded quickly, resulting in immediate use requirement after plasma activation. Therefore, development of stable high density binding surfaces such as high binding polystyrene is essential to improving shelf-life, reducing binding protocol complexity, and expanding to a wider range of applications. However, any layers topping the plasmonic grating must be ultra-thin (<10 nm) for the plasmonic enhancement of adjacent signals. Furthermore, fabricating thin polystyrene layers over alumina is nontrivial because of poor adhesion between polystyrene and alumina. Herein, we present the development of a stable, ultra-thin polystyrene layer on the gratings, which demonstrated 63.8 times brighter fluorescence compared to commercial polystyrene wellplates. Spike protein was examined for COVID-19 demonstrating the single-molecule counting capability of the hybrid polystyrene-plasmonic gratings. 

Capillary suspensions are three-phase mixtures containing a solid particulate phase, a continuous liquid phase, and a second immiscible liquid forming capillary bridges between particles. Capillary suspensions are encountered in a wide array of applications including 3D printing, porous materials, and food formulations, but despite recent progress, the micromechanics of particle clusters in flow is not fully understood. In this work, we study the dynamics of meniscus-bound particle clusters in planar extensional flow using a Stokes trap, which is an automated flow control technique that allows for precise manipulation of freely suspended particles or particle clusters in flow. Focusing on the case of a two-particle doublet, we use a combination of experiments and analytical modeling to understand how particle clusters rearrange, deform, and ultimately break up in extensional flow. The time required for cluster breakup is quantified as a function of capillary number Ca and meniscus volume V. Importantly, a critical capillary number Cacrit for cluster breakup is determined using a combination of experiments and modeling. Cluster relaxation experiments are also performed by deforming particle clusters in flow, followed by flow cessation prior to breakup and observing cluster relaxation dynamics under zero-flow conditions. In all cases, experiments are complemented by an analytical model that accounts for capillary forces, lubrication forces, hydrodynamic drag forces, and hydrodynamic interactions acting on the particles. Results from the analytical models are found to be in good agreement with experiments. Overall, this work provides a new quantitative understanding of the deformation dynamics of capillary clusters in extensional flow.