Adult onset lung disease following transient disruption of fetal stretch-induced differentiation

One of the mechanisms by which adult disease can arise from a fetal origin is by in utero disruption of organogenesis. These studies were designed to examine respiratory function changes in aging rats following transient disruption of lung growth at 16 days gestation. Fetuses were treated in utero with a replication deficient adenovirus containing the cystic fibrosis conductance transmembrane regulator (CFTR) gene fragment cloned in the anti-sense direction. The in utero-treated rats demonstrated abnormal lung function beginning as early as 30 days of age and the pathology progressed as the animals aged. The pulmonary function abnormalities included decreased static compliance as well as increased conducting airway resistance, tissue damping, and elastance. Pressure volume (PV) curves demonstrated a slower early rise to volume and air trapping at end-expiration. The alterations of pulmonary function correlated with lung structural changes determined by morphometric analysis. These studies demonstrate how transient disruption of lung organogensis by single gene interference can result in progressive change in lung function and structure. They illustrate how an adult onset disease can arise from subtle changes in gene expression during fetal development

Characterizing forest succession with lidar data: An evaluation for the Inland Northwest, USA

Quantifying forest structure is important for sustainable forest management, as it relates to a wide variety of ecosystem processes and services. Lidar data have proven particularly useful for measuring or estimating a suite of forest structural attributes such as canopy height, basal area, and LAI. However, the potential of this technology to characterize forest succession remains largely untested. The objective of this study was to evaluate the use of lidar data for characterizing forest successional stages across a structurally diverse, mixed-species forest in Northern Idaho. We used a variety of lidar-derived metrics in conjunction with an algorithmic modeling procedure (Random Forests) to classify six stages of three-dimensional forest development and achieved an overall accuracy \u3e95%. The algorithmic model presented herein developed ecologically meaningful classifications based upon lidar metrics quantifying mean vegetation height and canopy cover, among others. This study highlights the utility of lidar data for accurately classifying forest succession in complex, mixed coniferous forests; but further research should be conducted to classify forest successional stages across different forests types. The techniques presented herein can be easily applied to other areas. Furthermore, the final classification map represents a significant advancement for forest succession modeling and wildlife habitat assessment

Characterizing forest succession with lidar data: An evaluation for the Inland Northwest, USA

Quantifying forest structure is important for sustainable forest management, as it relates to a wide variety of ecosystem processes and services. Lidar data have proven particularly useful for measuring or estimating a suite of forest structural attributes such as canopy height, basal area, and LAI. However, the potential of this technology to characterize forest succession remains largely untested. The objective of this study was to evaluate the use of lidar data for characterizing forest successional stages across a structurally diverse, mixed-species forest in Northern Idaho. We used a variety of lidar-derived metrics in conjunction with an algorithmic modeling procedure (Random Forests) to classify six stages of three-dimensional forest development and achieved an overall accuracy \u3e95%. The algorithmic model presented herein developed ecologically meaningful classifications based upon lidar metrics quantifying mean vegetation height and canopy cover, among others. This study highlights the utility of lidar data for accurately classifying forest succession in complex, mixed coniferous forests; but further research should be conducted to classify forest successional stages across different forests types. The techniques presented herein can be easily applied to other areas. Furthermore, the final classification map represents a significant advancement for forest succession modeling and wildlife habitat assessment

Investigating the influence of LiDAR ground surface errors on the utility of derived forest inventories

Light detection and ranging, or LiDAR, effectively produces products spatially characterizing both terrain and vegetation structure; however, development and use of those products has outpaced our understanding of the errors within them. LiDAR’s ability to capture three-dimensional structure has led to interest in conducting or augmenting forest inventories with LiDAR data. Prior to applying LiDAR in operational management, it is necessary to understand the errors in Li- DAR-derived estimates of forest inventory metrics (i.e., tree height). Most LiDAR-based forest inventory metrics require creation of digital elevation models (DEM), and because metrics are calculated relative to the DEM surface, errors within the DEMs propagate into delivered metrics. This study combines LiDAR DEMs and 54 ground survey plots to investigate how surface morphology and vegetation structure influence DEM errors. The study further compared two LiDAR classification algorithms and found no significant difference in their performance. Vegetation structure was found to have no influence, whereas increased variability in the vertical error was observed on slopes exceeding 30°, illustrating that these algorithms are not limited by high-biomass western coniferous forests, but that slope and sensor accuracy both play important roles. The observed vertical DEM error translated into ±1%–3% error range in derived timber volumes, highlighting the potential of LiDAR-derived inventories in forest management

Head butting sheep: Kink Collisions in the Presence of False Vacua

We investigate numerically kink collisions in a 1+1 dimensional scalar field theory with multiple vacua. The domain wall model we are interested in involves two scalar fields and a potential term built from an asymmetric double well and (double) sine-Gordon potential together with an interaction term. Depending on the initial kink setup and impact velocities, the model allows for a wide range of scattering behaviours. Kinks can repel each other, annihilate, form true or false domain walls and reflect off each other

Extracting ecological and biophysical information from AVHRR optical data: An integrated algorithm based on inverse modeling

Satellite remote sensing provides the only means of directly observing the entire surface of the Earth at regular spatial and temporal intervals

Extracting ecological and biophysical information from AVHRR optical data: An integrated algorithm based on inverse modeling

Satellite remote sensing provides the only means of directly observing the entire surface of the Earth at regular spatial and temporal intervals

Interaction Properties of the Periodic and Step-like Solutions of the Double-Sine-Gordon Equation

The periodic and step-like solutions of the double-Sine-Gordon equation are investigated, with different initial conditions and for various values of the potential parameter $\epsilon$. We plot energy and force diagrams, as functions of the inter-soliton distance for such solutions. This allows us to consider our system as an interacting many-body system in 1+1 dimension. We therefore plot state diagrams (pressure vs. average density) for step-like as well as periodic solutions. Step-like solutions are shown to behave similarly to their counterparts in the Sine-Gordon system. However, periodic solutions show a fundamentally different behavior as the parameter $\epsilon$ is increased. We show that two distinct phases of periodic solutions exist which exhibit manifestly different behavior. Response functions for these phases are shown to behave differently, joining at an apparent phase transition point.Comment: 17pages, 15 figure

Teaching functional patterns through robotic applications

We present our approach to teaching functional programming to First Year Computer Science stu- dents at Middlesex University through projects in robotics. A holistic approach is taken to the cur- riculum, emphasising the connections between different subject areas. A key part of the students’ learning is through practical projects that draw upon and integrate the taught material. To support these, we developed the Middlesex Robotic plaTfOrm (MIRTO), an open-source platform built using Raspberry Pi, Arduino, HUB-ee wheels and running Racket (a LISP dialect). In this paper we present the motivations for our choices and explain how a number of concepts of functional programming may be employed when programming robotic applications. We present some students’ work with robotics projects: we consider the use of robotics projects to have been a success, both for their value in reinforcing students’ understanding of programming concepts and for their value in motivating the students