Where can managers effectively resist climate-driven ecological transformation in pinyon-juniper woodlands of the US Southwest?

Pinyon-juniper (PJ) woodlands are an important component of dryland ecosystems across the US West and are potentially susceptible to ecological transformation. However, predicting woodland futures is complicated by species-specific strategies for persisting and reproducing under drought conditions, uncertainty in future climate, and limitations to inferring demographic rates from forest inventory data. Here, we leverage new demographic models to quantify how climate change is expected to alter population demographics in five PJ tree species in the US West and place our results in the context of a climate adaptation framework to resist, accept, or direct ecological transformation. Two of five study species, Pinus edulis and Juniperus monosperma, are projected to experience population declines, driven by both rising mortality and decreasing recruitment rates. These declines are reasonably consistent across various climate futures, and the magnitude of uncertainty in population growth due to future climate is less than uncertainty due to how demographic rates will respond to changing climate. We assess the effectiveness of management to reduce tree density and mitigate competition, and use the results to classify southwest woodlands into areas where transformation is (a) unlikely and can be passively resisted, (b) likely but may be resisted by active management, and (c) likely unavoidable, requiring managers to accept or direct the trajectory. Population declines are projected to promote ecological transformation in the warmer and drier PJ communities of the southwest, encompassing 37.1%-81.1% of our sites, depending on future climate scenarios. Less than 20% of sites expected to transform away from PJ have potential to retain existing tree composition by density reduction. Our results inform where this adaptation strategy could successfully resist ecological transformation in coming decades and allow for a portfolio design approach across the geographic range of PJ woodlands.

Applications of liquid crystals in biosensing.

Liquid crystals (LCs), as a promising branch of highly-sensitive, quick-response, and low-cost materials, are widely applied to the detection of weak external stimuli and have attracted significant attention. Over the past decade, many research groups have been devoted to developing LC-based biosensors due to their self-assembly potential and functional diversity. In this paper, recent investigations on the design and application of LC-based biosensors are reviewed, based on the phenomenon that the orientation of LCs can be directly influenced by the interactions between biomolecules and LC molecules. The sensing principle of LC-based biosensors, as well as their signal detection by probing interfacial interactions, is described to convert, amplify, and quantify the information from targets into optical and electrical parameters. Furthermore, commonly-used LC biosensing targets are introduced, including glucose, proteins, enzymes, nucleic acids, cells, microorganisms, ions, and other micromolecules that are critical to human health. Due to their self-assembly potential, chemical diversity, and high sensitivity, it has been reported that tunable stimuli-responsive LC biosensors show bright perspectives and high superiorities in biological applications. Finally, challenges and future prospects are discussed for the fabrication and application of LC biosensors to both enhance their performance and to realize their promise in the biosensing industry.

A Novel A Priori Simulation Algorithm for Absorbing Receivers in Diffusion-Based Molecular Communication Systems.

A novel a priori Monte Carlo (APMC) algorithm is proposed to accurately simulate the molecules absorbed at spherical receiver(s) with low-computational complexity in diffusion-based molecular communication (MC) systems. It is demonstrated that the APMC algorithm achieves high-simulation efficiency since by using this algorithm, the fraction of molecules absorbed for a relatively large time step length precisely matches the analytical result. Therefore, the APMC algorithm overcomes the shortcoming of the existing refined Monte Carlo (RMC) algorithm, which enables accurate simulation for a relatively small time step length only. Moreover, for the RMC algorithm, an expression is proposed to quickly predict the simulation accuracy as a function of the time step length and system parameters, which facilitates the choice of simulation time step for a given system. Furthermore, a likelihood threshold is proposed for both the RMC and APMC algorithms to significantly save computational complexity while causing an extremely small loss in accuracy.

Algorithm for Mesoscopic Advection-Diffusion.

In this paper, an algorithm is presented to calculate the transition rates between adjacent mesoscopic subvolumes in the presence of flow and diffusion. These rates can be integrated in stochastic simulations of reaction-diffusion systems that follow a mesoscopic approach, i.e., that partition the environment into homogeneous subvolumes and apply the spatial stochastic simulation algorithm (spatial SSA). The rates are derived by integrating Fick's second law over a single subvolume in 1D and are also shown to apply in 3D. The proposed algorithm corrects the derived rates to ensure that they are physically meaningful and it is implemented in the AcCoRD Simulator (Actor-based Communication via Reaction-Diffusion). Simulations using the proposed method are compared with a naive mesoscopic approach, microscopic simulations that track every molecule, and analytical results that are exact in 1D and an approximation in 3D. By choosing subvolumes that are sufficiently small, such that the Péclet number associated with a subvolume is sufficiently less than two, the accuracy of the proposed method is comparable with microscopic method, thus enabling the simulation of advection-reaction-diffusion systems with the spatial SSA.

Distortion Distribution of Neural Spike Train Sequence Matching With Optogenetics.

OBJECTIVE: This paper uses a simple optogenetic model to compare the timing distortion between a randomly-generated target spike sequence and an externally-stimulated neuron spike sequence. Optogenetics is an emerging field of neuroscience where neurons are genetically modified to express light-sensitive receptors that enable external control when the neurons fire. METHODS: Two different measures are studied to determine the timing distortion. The first measure is the delay in externally-stimulated spikes. The second measure is the root-mean-square-error between the filtered outputs of the target and stimulated spike sequences. RESULTS: The mean and the distribution of the distortion are derived in closed form when the target sequence generation rate is sufficiently low. The derived results are verified with simulations. CONCLUSION: The proposed model and distortion measures can be used to measure the deviation between neuron spike sequences that are prescribed and what can be achieved via external stimulation. SIGNIFICANCE: Given the prominence of neuronal signaling within the brain and throughout the body, optogenetics has significant potential to improve the understanding of the nervous system and to develop treatments for neurological diseases. This work is a step towards an analytical model to predict whether different spike trains were observed from the same external stimulus, and the broader goal of understanding the quantity and reliability of information that can be carried by neurons.

The Effect of Two Receivers on Broadcast Molecular Communication Systems.

Molecular communication is a paradigm that utilizes molecules to exchange information between nano-machines. When considering such systems where multiple receivers are present, prior work has assumed for simplicity that they do not interfere with each other. This paper aims to address this issue and shows to what extent an interfering receiver, [Formula: see text], will have an impact on the target receiver, [Formula: see text], with respect to Bit Error Rate (BER) and capacity. Furthermore, approximations of the Binomial distribution are applied to reduce the complexity of calculations. Results show the sensitivity in communication performance due to the relative location of the interfering receiver. Critically, placing [Formula: see text] between the transmitter [Formula: see text] and [Formula: see text] causes a significant increase in BER or decrease in capacity.

Optimal receiver design for diffusive molecular communication with flow and additive noise.

In this paper, we perform receiver design for a diffusive molecular communication environment. Our model includes flow in any direction, sources of information molecules in addition to the transmitter, and enzymes in the propagation environment to mitigate intersymbol interference. We characterize the mutual information between receiver observations to show how often independent observations can be made. We derive the maximum likelihood sequence detector to provide a lower bound on the bit error probability. We propose the family of weighted sum detectors for more practical implementation and derive their expected bit error probability. Under certain conditions, the performance of the optimal weighted sum detector is shown to be equivalent to a matched filter. Receiver simulation results show the tradeoff in detector complexity versus achievable bit error probability, and that a slow flow in any direction can improve the performance of a weighted sum detector.

Improving receiver performance of diffusive molecular communication with enzymes.

This paper studies the mitigation of intersymbol interference in a diffusive molecular communication system using enzymes that freely diffuse in the propagation environment. The enzymes form reaction intermediates with information molecules and then degrade them so that they cannot interfere with future transmissions. A lower bound expression on the expected number of molecules measured at the receiver is derived. A simple binary receiver detection scheme is proposed where the number of observed molecules is sampled at the time when the maximum number of molecules is expected. Insight is also provided into the selection of an appropriate bit interval. The expected bit error probability is derived as a function of the current and all previously transmitted bits. Simulation results show the accuracy of the bit error probability expression and the improvement in communication performance by having active enzymes present.