Light Weight Location Verification Algorithm in Wireless Sensors for Checking the Reliability of Data

Wireless sensors can be deployed in any environment, even if that is hazardous and they send back the data gathered to the verification center which is placed at some safe location. Since the data collected by these are very vital so any compromisation may lead to undesirable results. Sensors can be easily compromised by changing its actual position to some false position so there is need for some algorithm to verify the position and ensure that the data is unblemished. Since in previous scheme, heavy and expensive equipments were used along with the deployment knowledge required, it becomes inefficient for all cost range. Therefore, we have proposed a verification system which utilizes the concept of on-spot and in-region location verification. In on-spot verification, we calculate the distance of the wireless sensor from its actual deployed position. In-region verification depends upon neighbouring sensors. Along with that, once a sensors gets out of its tolerable region, even for once, its data gets discarded. Putting the sensors back to its original position after the discarding of the data won’t make it trusted and the sensor will still be considered compromised. This additional feature ensures that the data received in the verification center is from a trusted device and is true. DOI: 10.17762/ijritcc2321-8169.150512

Smooth Pycnophylactic Interpolation Produced by Density-Equalising Map Projections

Velika količina kvantitativnih geoprostornih podataka prikuplja se i spaja u diskretne popisne jedinice (npr. zemlje ili države). Glatka piknofilaktička interpolacija ima za cilj pronaći glatku, nenegativnu funkciju tako da je integral površine nad svakom popisnom jedinicom jednak agregiranim podacima. Konvencionalno, glatka piknofilaktička interpolacija dobiva se algoritmom staničnog automata koji pretvara po dijelovima konstantnu funkciju u približno glatku funkciju definiranu na mreži koordinata na karti u ekvivalentnoj projekciji. Alternativni pristup, kojeg je predložio Tobler (1976), je konstruirati kartografsku projekciju s ujednačavanjem gustoće u kojoj su područja popisnih jedinica proporcionalna agregiranim podacima. Piknofilaktička interpolacija može se dobiti iz Jakobijana te projekcije. U ovom radu opisujemo primjenu softvera za tu metodu. Iako rješenja nisu nužno optimalna u smislu unaprijed definiranih kvantitativnih mjera glatkoće, naša metoda je računski učinkovita i potencijalno se može koristiti zajedno s drugim metodama da bi se ubrzala konvergencija prema optimalnom rješenju.A large amount of quantitative geospatial data is collected and aggregated in discrete enumeration units (e.g. countries or states). Smooth pycnophylactic interpolation aims to find a smooth, nonnegative function such that the area integral over each enumeration unit is equal to the aggregated data. Conventionally, smooth pycnophylactic interpolation is achieved by a cellular automaton algorithm that converts a piecewise constant function into an approximately smooth function defined on a grid of coordinates on an equal-area map. An alternative approach, proposed by Tobler in 1976, is to construct a density-equalising map projection in which areas of enumeration units are proportional to the aggregated data. A pycnophylactic interpolation can be obtained from the Jacobian of this projection. Here, we describe a software implementation of this method. Although solutions are not necessarily optimal in terms of predefined quantitative measures of smoothness, our method is computationally efficient and can potentially be used in tandem with other methods to accelerate convergence towards an optimal solution

Gender-dependent differences in plasma matrix metalloproteinase-8 elevated in pulmonary tuberculosis.

Tuberculosis (TB) remains a global health pandemic and greater understanding of underlying pathogenesis is required to develop novel therapeutic and diagnostic approaches. Matrix metalloproteinases (MMPs) are emerging as key effectors of tissue destruction in TB but have not been comprehensively studied in plasma, nor have gender differences been investigated. We measured the plasma concentrations of MMPs in a carefully characterised, prospectively recruited clinical cohort of 380 individuals. The collagenases, MMP-1 and MMP-8, were elevated in plasma of patients with pulmonary TB relative to healthy controls, and MMP-7 (matrilysin) and MMP-9 (gelatinase B) were also increased. MMP-8 was TB-specific (p<0.001), not being elevated in symptomatic controls (symptoms suspicious of TB but active disease excluded). Plasma MMP-8 concentrations inversely correlated with body mass index. Plasma MMP-8 concentration was 1.51-fold higher in males than females with TB (p<0.05) and this difference was not due to greater disease severity in men. Gender-specific analysis of MMPs demonstrated consistent increase in MMP-1 and -8 in TB, but MMP-8 was a better discriminator for TB in men. Plasma collagenases are elevated in pulmonary TB and differ between men and women. Gender must be considered in investigation of TB immunopathology and development of novel diagnostic markers

Analysis of temporal transcription expression profiles reveal links between protein function and developmental stages of Drosophila melanogaster

Accurate gene or protein function prediction is a key challenge in the post-genome era. Most current methods perform well on molecular function prediction, but struggle to provide useful annotations relating to biological process functions due to the limited power of sequence-based features in that functional domain. In this work, we systematically evaluate the predictive power of temporal transcription expression profiles for protein function prediction in Drosophila melanogaster. Our results show significantly better performance on predicting protein function when transcription expression profile-based features are integrated with sequence-derived features, compared with the sequence-derived features alone. We also observe that the combination of expression-based and sequence-based features leads to further improvement of accuracy on predicting all three domains of gene function. Based on the optimal feature combinations, we then propose a novel multi-classifier-based function prediction method for Drosophila melanogaster proteins, FFPred-fly+. Interpreting our machine learning models also allows us to identify some of the underlying links between biological processes and developmental stages of Drosophila melanogaster

Systemic delivery of E6/7 siRNA using novel lipidic particles and its application with cisplatin in cervical cancer mouse models

Small interfering RNA (siRNA) shows great promise in cancer therapy, but its effectiveness in vivo still remains a crucial issue for its transition into the clinics. Although the successful use of polyethylene glycol (PEG)ylated lipidic delivery systems have already been reported, most of the formulation procedures used are labour intensive and also result in unstable end products. We have previously developed a simple yet efficient hydration-of-freeze-dried- matrix (HFDM) method to entrap siRNA within lipid particles, in which the products exhibited superior stability. Here, we show that these HFDM-formulated particles are stable in the presence of serum and can deliver siRNA efficiently to tumours after intravenous administration. Using these particles, around 50% knockdown of the target gene expression was observed in tumours. With the use of siRNA targeting the E6/7 oncogenes expressed in cervical cancer, we showed a 50% reduction in tumour size. This level of tumour growth suppression was comparable to that achieved from cisplatin at the clinically used dose. Overall, our results demonstrate the feasibility of using HFDM-formulated particles to systematically administer E6/7-targeted siRNA for cervical cancer treatment. The simplicity of preparation procedure along with superior product stability obtained from our method offers an innovative approach for the in vivo delivery of siRNA

Solid-state fermentation of oil palm frond petiole for lignin peroxidase and xylanase-rich cocktail production

In current practice, oil palm frond leaflets and stems are re-used for soil nutrient recycling, while the petioles are typically burned. Frond petioles have high commercialization value, attributed to high lignocellulose fiber content and abundant of juice containing free reducing sugars. Pressed petiole fiber is the subject of interest in this study for the production of lignocellulolytic enzyme. The initial characterization showed the combination of 0.125 mm frond particle size and 60% moisture content provided a surface area of 42.3 m2/g, porosity of 12.8%, and density of 1.2 g/cm3, which facilitated fungal solid-state fermentation. Among the several species of Aspergillus and Trichoderma tested, Aspergillus awamori MMS4 yielded the highest xylanase (109 IU/g) and cellulase (12 IU/g), while Trichoderma virens UKM1 yielded the highest lignin peroxidase (222 IU/g). Crude enzyme cocktail also contained various sugar residues, mainly glucose and xylose (0.1–0.4 g/L), from the hydrolysis of cellulose and hemicellulose. FT-IR analysis of the fermented petioles observed reduction in cellulose crystallinity (I900/1098), cellulose–lignin (I900/1511), and lignin–hemicellulose (I1511/1738) linkages. The study demonstrated successful bioconversion of chemically untreated frond petioles into lignin peroxidase and xylanase-rich enzyme cocktail under SSF condition

Epithelial IL-6 trans-signaling defines a new asthma phenotype with increased airway inflammation

Background: Although several studies link high levels of IL-6 and soluble IL-6 receptor (sIL-6R) to asthma severity and decreased lung function, the role of IL-6 trans-signaling (IL-6TS) in asthmatic patients is unclear. Objective: We sought to explore the association between epithelial IL-6TS pathway activation and molecular and clinical phenotypes in asthmatic patients. Methods: An IL-6TS gene signature obtained from air-liquid interface cultures of human bronchial epithelial cells stimulated with IL-6 and sIL-6R was used to stratify lung epithelial transcriptomic data (Unbiased Biomarkers in Prediction of Respiratory Disease Outcomes [U-BIOPRED] cohorts) by means of hierarchical clustering. IL-6TS-specific protein markers were used to stratify sputum biomarker data (Wessex cohort). Molecular phenotyping was based on transcriptional profiling of epithelial brushings, pathway analysis, and immunohistochemical analysis of bronchial biopsy specimens. Results: Activation of IL-6TS in air-liquid interface cultures reduced epithelial integrity and induced a specific gene signature enriched in genes associated with airway remodeling. The IL-6TS signature identified a subset of patients with IL-6TS-high asthma with increased epithelial expression of IL-6TS-inducible genes in the absence of systemic inflammation. The IL-6TS-high subset had an overrepresentation of frequent exacerbators, blood eosinophilia, and submucosal infiltration of T cells and macrophages. In bronchial brushings Toll-like receptor pathway genes were upregulated, whereas expression of cell junction genes was reduced. Sputum sIL-6R and IL-6 levels correlated with sputum markers of remodeling and innate immune activation, in particular YKL-40, matrix metalloproteinase 3, macrophage inflammatory protein 1 beta, IL-8, and IL-1 beta. Conclusions: Local lung epithelial IL-6TS activation in the absence of type 2 airway inflammation defines a novel subset of asthmatic patients and might drive airway inflammation and epithelial dysfunction in these patients.Peer reviewe