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Abstract 4D printing technology enables the fabrication of constructs capable of shape transformation when exposed to external stimuli. Epoxy‐based shape memory polymers (SMPs) have shown great potential for various 4D printing applications. However, due to their thermocurable nature, the fabrication of 4D constructs using epoxy‐based materials is often limited to a mold casting strategy, limiting design flexibility and often yielding flat structures. In this work, photocurable smart 4D inks are developed by integrating polyethylene glycol diacrylate (PD) into epoxy‐based materials. These inks undergo a two‐step crosslinking process: i) photocuring of the PD network, and ii) thermocuring of the SMP, resulting in an interpenetrating polymer network (IPN). The inclusion of PD in the 4D inks not only enables the formation of complex shapes via the restructuring step but also allows for fine‐tuning of mechanical properties and thermal responsiveness. Additionally, these inks offered greater versatility in employable fabrication techniques, including mold casting, photolithography, and stereolithography (SLA). 

ABSTRACT Harmonizable processes are a class of nonstationary time series, that are characterized by their dependence between different frequencies of a time series. The covariance between two frequencies is the dual frequency spectral density, an object analogous to the spectral density function. Local stationarity is another popular form of nonstationarity, though thus far, little attention has been paid to the dual frequency spectral density of a locally stationary process. The focus of this paper is on the dual frequency spectral density of local stationary time series and locally periodic stationary time series, its natural extension. We show that there are some subtle but important differences between the dual frequency spectral density of an almost periodic stationary process and a locally periodic stationary time series. Estimation of the dual frequency spectral density is typically done by smoothing the dual frequency periodogram. We study the sampling properties of this estimator under the assumption of locally periodic stationarity. In particular, we obtain a Gaussian approximation for the smoothed dual frequency periodogram over a group of frequencies, allowing for the number of frequency lags to grow with sample size. These results are used to test for correlation between different frequency bands in the time series. The variance of the smooth dual frequency periodogram is quite complex. However, by identifying which covariances are the most pertinent we propose a nonparametric method for consistently estimating the variance. This is necessary for constructing confidence intervals or testing aspects of the dual frequency spectral density. Simulations are given to illustrate our results. 

Abstract Climate‐driven ecosystem shifts occur through turnover in the foundation species which structure the landscape. Therefore, to predict the fate of areas undergoing climate‐driven ecosystem shifts, one approach is to characterize ecological and evolutionary responses of foundation species along dynamic environmental gradients. One such gradient is the ecotone between tidal marshes and maritime forests in coastal areas of the US Mid‐Atlantic region where accelerated sea‐level rise and coastal storms of increased frequency and intensity are driving forest dieback and inland marsh migration. Mid‐Atlantic tidal marshes are structured by marsh grasses which act as foundation species, and these grasses exhibit trait variation across their distribution from established marsh interior to their inland migration front. We conducted a reciprocal transplant experiment withSpartina patens, a dominant high marsh grass and foundation species, between established populations in the high marsh and range edge populations in the forest understory at three Mid‐Atlantic sites. We monitored environmental conditions in marsh and forest understory habitats, measured plant traits (above‐ and belowground biomass, specific leaf area, leaf N and C concentrations) in transplanted and reference non‐transplanted individuals, and used microsatellite markers to determine the genetic identity of transplants to quantify clonality between habitats and sites. Individuals transplanted into the forest understory exhibited a plastic shift in resource allocation to aboveground structures associated with light acquisition, with shifts in transplants making them more morphologically similar to reference individuals sampled from the forest habitat. Clonal diversity and genetic distance among transplants were relatively high at two of three sites, but individuals at all sites exhibited trans‐habitat plasticity regardless of clonal diversity or a lack thereof. Individuals grown in the forest understory showed lower vegetative and reproductive fitness. Nevertheless, the trait plasticity exhibited by this species allowed individuals from the forest that were transplanted into the marsh to recoup significant biomass in only a single growing season. We predict high plasticity will facilitate the persistence of colonizingS. patensindividuals under suboptimal forest shade conditions until forest dieback increases light availability, ultimately promoting continued inland migration of this foundation species under sea‐level rise. 

ABSTRACT The cerebral cortex accounts for substantial energy expenditure, primarily driven by the metabolic demands of synaptic signaling. Mitochondria, the organelles responsible for generating cellular energy, play a crucial role in this process. We investigated ultrastructural characteristics of the primary visual cortex in 18 phylogenetically diverse mammals, spanning a broad range of brain sizes from mouse to elephant. Our findings reveal remarkable uniformity in synapse density, postsynaptic density (PSD) length, and mitochondria density, indicating functional and metabolic constraints that maintain these fundamental features. Notably, we observed an average of 1.9 mitochondria per synapse across mammalian species. When considered together with the trend of decreasing neuron density with larger brain size, we find that brain enlargement in mammals is characterized by increasing proportions of synapses and mitochondria per cortical neuron. These results shed light on the adaptive mechanisms and metabolic dynamics that govern cortical ultrastructure across mammals.