Cost Efficiency of Anycast-Based Forwarding in Duty-Cycled WSNs with Lossy Channel

Anycasting has been proposed recently as an efficient communication method for asynchronous duty-cycled wireless sensor networks. However, the interdependencies between end-toend communication cost and the anycasting design parameters have not been systematically studied. In this paper, a statistical endtoend cost model is presented to capture the end-to-end latency and energy consumption of anycasting operation under a realistic wireless channel model. By exploring the relationship between the end-to-end cost efficiency and the forwarding decision dependent anycasting design parameters, two anycasting forwarding metrics are proposed for fully distributed forwarding decision. By exploring the relationship among the preamble length, the size of the forwarding set and the achievable end-to-end cost efficiency, a series of preamble length control guidelines are proposed for low and extremely low duty-cycled WSNs. According to our analytical results and simulation validation, the proposed forwarding metrics help reduce the end-toend latency and energy consumption by about 55% for anycasting with moderate preamble length, compared with the existing heuristic forwarding metrics. The proposed preamble length control guidelines help reduce, by more than half, the end-to-end energy and latency costs in low and extremely-low duty-cycled WSNs

Transcriptomic changes induced by acute ozone in resistant and sensitive Medicago truncatula accessions

Background: Tropospheric ozone, the most abundant air pollutant is detrimental to plant and animal health including humans. In sensitive plant species even a few hours of exposure to this potent oxidant (200-300 nL. L-1) leads to severe oxidative stress that manifests as visible cell death. In resistant plants usually no visible symptoms are observed on exposure to similar ozone concentrations. Naturally occurring variability to acute ozone in plants provides a valuable resource for examining molecular basis of the differences in responses to ozone. From our earlier study in Medicago truncatula, we have identified cultivar Jemalong is ozone sensitive and PI 464815 (JE154) is an ozone-resistant accession. Analyses of transcriptome changes in ozone-sensitive and resistant accession will provide important clues for understanding the molecular changes governing the plant responses to ozone.Results: Acute ozone treatment (300 nL L-1 for six hours) led to a reactive oxygen species (ROS) burst in sensitive Jemalong six hours post-fumigation. In resistant JE154 increase in ROS levels was much reduced compared to Jemalong. Based on the results of ROS profiling, time points for microarray analysis were one hour into the ozone treatment, end of treatment and onset of an ozone-induced ROS burst at 12 hours. Replicated temporal transcriptome analysis in these two accessions using 17 K oligonucleotide arrays revealed more than 2000 genes were differentially expressed. Significantly enriched gene ontologies (GOs) were identified using the Cluster Enrichment analysis program. A striking finding was the alacrity of JE154 in altering its gene expression patterns in response to ozone, in stark contrast to delayed transcriptional response of Jemalong. GOs involved in signaling, hormonal pathways, antioxidants and secondary metabolism were altered in both accessions. However, the repertoire of genes responding in each of these categories was different between the two accessions. Real-time PCR analysis confirmed the differential expression patterns of a subset of these genes.Conclusion: This study provided a cogent view of the unique and shared transcriptional responses in an ozone-resistant and sensitive accession that exemplifies the complexity of oxidative signaling in plants. Based on this study, and supporting literature in Arabidopsis we speculate that plants sensitive to acute ozone are impaired in perception of the initial signals generated by the action of this oxidant. This in turn leads to a delayed transcriptional response in the ozone sensitive plants. In resistant plants rapid and sustained activation of several signaling pathways enables the deployment of multiple mechanisms for minimizing the toxicity effect of this reactive molecule.Peer reviewedBiochemistry and Molecular Biolog

Local Histograms and Image Occlusion Models

The local histogram transform of an image is a data cube that consists of the histograms of the pixel values that lie within a fixed neighborhood of any given pixel location. Such transforms are useful in image processing applications such as classification and segmentation, especially when dealing with textures that can be distinguished by the distributions of their pixel intensities and colors. We, in particular, use them to identify and delineate biological tissues found in histology images obtained via digital microscopy. In this paper, we introduce a mathematical formalism that rigorously justifies the use of local histograms for such purposes. We begin by discussing how local histograms can be computed as systems of convolutions. We then introduce probabilistic image models that can emulate textures one routinely encounters in histology images. These models are rooted in the concept of image occlusion. A simple model may, for example, generate textures by randomly speckling opaque blobs of one color on top of blobs of another. Under certain conditions, we show that, on average, the local histograms of such model-generated-textures are convex combinations of more basic distributions. We further provide several methods for creating models that meet these conditions; the textures generated by some of these models resemble those found in histology images. Taken together, these results suggest that histology textures can be analyzed by decomposing their local histograms into more basic components. We conclude with a proof-of-concept segmentation-and-classification algorithm based on these ideas, supported by numerical experimentation

Fabrication of Hollow Microspheres Using Single Step Electrospraying Process

In this study, a single step method for large scale fabrication of hollow microspheres with a narrow size distribution is presented. PolyBenzoThiadiazole (PolyBT), a conducting polymer, was electrosprayed at high voltage to obtain microspheres. Hollow spheres of size ranging from 4.1 to 7.3 µm were observed through scanning electron microscope images, without any chemical degradation as shown by FTIR studies. In addition, these microspheres demonstrated a change in optical and hydrophobic properties as exhibited by the UV-visible and contact angle measurements. Thus providing interesting opportunities for use in biomedical applications, sensors as well as optoelectronic devices

An indigenous cluster beam apparatus with a reflectron time-of-flight mass spectrometer

The design and fabrication of a Smalley-type cluster source in combination with a reflectron based time-of-flight (TOF) mass spectrometer are reported. The generation of clusters is based on supersonic jet expansion of the sampling plume. Sample cells for both liquid and solid targets developed for this purpose are described. Two pulsed Nd-YAG lasers are used in tandem, one (532 nm) for target vapourization and the other (355 nm) for cluster ionization. Methanol clusters of nuclearity up to 14 (mass 500 amu) were produced from liquid methanol as the test sample. The clusters were detected with a mass resolution of ~2500 in the R-TOF geometry. Carbon clusters up to a nuclearity of 28 were obtained using a polyimide target. The utility of the instrument is demonstrated by carrying out experiments to generate mixed clusters from alcohol mixtures

High‑throughput analysis of leaf physiological and chemical traits with VIS–NIR–SWIR spectroscopy: a case study with a maize diversity panel

Hyperspectral reflectance data in the visible, near infrared and shortwave infrared range (VIS–NIR– SWIR, 400–2500 nm) are commonly used to nondestructively measure plant leaf properties. We investigated the usefulness of VIS–NIR–SWIR as a high-throughput tool to measure six leaf properties of maize plants including chlorophyll content (CHL), leaf water content (LWC), specific leaf area (SLA), nitrogen (N), phosphorus (P), and potassium (K). This assessment was performed using the lines of the maize diversity panel. Data were collected from plants grown in greenhouse condition, as well as in the field under two nitrogen application regimes. Leaf-level hyperspectral data were collected with a VIS–NIR–SWIR spectroradiometer at tasseling. Two multivariate modeling approaches, partial least squares regression (PLSR) and support vector regression (SVR), were employed to estimate the leaf properties from hyperspectral data. Several common vegetation indices (VIs: GNDVI, RENDVI, and NDWI), which were calculated from hyperspectral data, were also assessed to estimate these leaf properties

Evaluating effectiveness of non-water based cleaning mechanisms for PV systems

Paper presented to the 3rd Southern African Solar Energy Conference, South Africa, 11-13 May, 2015.PV systems in tropical regions are gifted with ample sunshine, but also vulnerabilities to high cell temperatures and dust settlement. Dust related degradation is progressive and if left unattended, can severely inhibit by more than 40% the efficiency and output of the system. Current mechanisms of cleaning PV systems adopt large quantities of clean water, making the system unsustainable. The current study thereby investigates the effectiveness of non-water based cleaning mechanisms based on traditional palm-leaf brooms. These brooms were found to be more than 90% effective in comparison to water based cleaning. The reason for this effective cleaning has been further scrutinized based on micro-structure studies and dust adhering propertiesdc201