Design and Development of Fiber Optic Sensors for Trace Detection of Certain Environmental Pollutants

In recent years,photonics has emerged as an essential technology related to such diverse fields like laser technology,fiber optics,communication,optical signal processing,computing,entertainment,consumer electronics etc.Availabilities of semiconductor lasers and low loss fibers have also revolutionized the field of sensor technology including telemetry. There exist fiber optic sensors which are sensitive,reliable.light weight and accurate devices which find applications in wide range of areas like biomedicine,aviation,surgery,pollution monitoring etc.,apart from areas in basic sciences.The present thesis deals with the design,fabrication and characterization of a variety of cost effective and sensitive fiber optic sensors for the trace detetction of certain environment pollutants in air and water.The sensor design is carried out using the techniques like evanescent waves,micro bending and long period gratings.

Design and development of an LED based fiber optic evanescent wave sensor for simultaneous detection of chromium and nitrite traces in water

The design and development of a cost-effective, simple, sensitive and portable LED based fiber optic evanescent wave sensor for simultaneously detecting trace amounts of chromium and nitrite in water are presented. In order to obtain the desired performance, the middle portions of two multimode plastic clad silica fibers are unclad and are used as the sensing elements in the two arms of the sensor. Each of the sensor arms is sourced by separate super bright green LEDs, which are modulated in a time-sharing manner and a single photo detector is employed for detecting these light signals. The performance and characteristics of this system clearly establish the usefulness of the technique for detecting very low concentrations of the dissolved contaminants.

Feature Point Detection and Curve Approximation for Early Processing of Freehand Sketches

Freehand sketching is both a natural and crucial part of design, yet is unsupported by current design automation software. We are working to combine the flexibility and ease of use of paper and pencil with the processing power of a computer to produce a design environment that feels as natural as paper, yet is considerably smarter. One of the most basic steps in accomplishing this is converting the original digitized pen strokes in the sketch into the intended geometric objects using feature point detection and approximation. We demonstrate how multiple sources of information can be combined for feature detection in strokes and apply this technique using two approaches to signal processing, one using simple average based thresholding and a second using scale space.

What are the priorities for prevention and control of non-communicable diseases and injuries in sub-Saharan Africa and South East Asia?

Last year’s UN high level meeting sought to galvanise the international community into scaling up its response to the escalating global burden of non-communicable diseases. With resources tight, D Chisholm and colleagues examine which interventions should be given priority for action and investment

Neighborhood characteristics and the spatial concentration of crime: Evidence for Bogotá

Using a unique neighborhood crime dataset for Bogotá in 2011, this study uses a spatial econometric approach and examines the role of socioeconomic and agglomeration variables in explaining the variance of crime. It uses two different types of crime, violent crime represented in homicides and property crime represented in residential burglaries. These two types of crime are then measured in non-standard crime statistics that are created as the area incidence for each crime in the neighborhood. The existence of crime hotspots in Bogotá has been shown in most of the literature, and using these non-standard crime statistics at this neighborhood level some hotspots arise again, thus validating the use of a spatial approach for these new crime statistics. The final specification includes socioeconomic, agglomeration, land-use and visual aspect variables that are then included in a SARAR model an estimated by the procedure devised by Kelejian and Prucha (2009). The resulting coefficients and marginal effects show the relevance of these crime hotspots which is similar with most previous studies. However, socioeconomic variables are significant and show the importance of age, and education. Agglomeration variables are significant and thus more densely populated areas are correlated with more crime. Interestingly, both types of crimes do not have the same significant covariates. Education and young male population have a different sign for homicide and residential burglaries. Inequality matters for homicides while higher real estate valuation matters for residential burglaries. Finally, density impacts positively both crimes.

Development of molecular-based techniques for the detection, identification and quantification of food-borne pathogens

La presencia de microorganismos patógenos en alimentos es uno de los problemas esenciales en salud pública, y las enfermedades producidas por los mismos es una de las causas más importantes de enfermedad. Por tanto, la aplicación de controles microbiológicos dentro de los programas de aseguramiento de la calidad es una premisa para minimizar el riesgo de infección de los consumidores. Los métodos microbiológicos clásicos requieren, en general, el uso de pre-enriquecimientos no-selectivos, enriquecimientos selectivos, aislamiento en medios selectivos y la confirmación posterior usando pruebas basadas en la morfología, bioquímica y serología propias de cada uno de los microorganismos objeto de estudio. Por lo tanto, estos métodos son laboriosos, requieren un largo proceso para obtener resultados definitivos y, además, no siempre pueden realizarse. Para solucionar estos inconvenientes se han desarrollado diversas metodologías alternativas para la detección identificación y cuantificación de microorganismos patógenos de origen alimentario, entre las que destacan los métodos inmunológicos y moleculares. En esta última categoría, la técnica basada en la reacción en cadena de la polimerasa (PCR) se ha convertido en la técnica diagnóstica más popular en microbiología, y recientemente, la introducción de una mejora de ésta, la PCR a tiempo real, ha producido una segunda revolución en la metodología diagnóstica molecular, como pude observarse por el número creciente de publicaciones científicas y la aparición continua de nuevos kits comerciales. La PCR a tiempo real es una técnica altamente sensible -detección de hasta una molécula- que permite la cuantificación exacta de secuencias de ADN específicas de microorganismos patógenos de origen alimentario. Además, otras ventajas que favorecen su implantación potencial en laboratorios de análisis de alimentos son su rapidez, sencillez y el formato en tubo cerrado que puede evitar contaminaciones post-PCR y favorece la automatización y un alto rendimiento. En este trabajo se han desarrollado técnicas moleculares (PCR y NASBA) sensibles y fiables para la detección, identificación y cuantificación de bacterias patogénicas de origen alimentario (Listeria spp., Mycobacterium avium subsp. paratuberculosis y Salmonella spp.). En concreto, se han diseñado y optimizado métodos basados en la técnica de PCR a tiempo real para cada uno de estos agentes: L. monocytogenes, L. innocua, Listeria spp. M. avium subsp. paratuberculosis, y también se ha optimizado y evaluado en diferentes centros un método previamente desarrollado para Salmonella spp. Además, se ha diseñado y optimizado un método basado en la técnica NASBA para la detección específica de M. avium subsp. paratuberculosis. También se evaluó la aplicación potencial de la técnica NASBA para la detección específica de formas viables de este microorganismo. Todos los métodos presentaron una especificidad del 100 % con una sensibilidad adecuada para su aplicación potencial a muestras reales de alimentos. Además, se han desarrollado y evaluado procedimientos de preparación de las muestras en productos cárnicos, productos pesqueros, leche y agua. De esta manera se han desarrollado métodos basados en la PCR a tiempo real totalmente específicos y altamente sensibles para la determinación cuantitativa de L. monocytogenes en productos cárnicos y en salmón y productos derivados como el salmón ahumado y de M. avium subsp. paratuberculosis en muestras de agua y leche. Además este último método ha sido también aplicado para evaluar la presencia de este microorganismo en el intestino de pacientes con la enfermedad de Crohn's, a partir de biopsias obtenidas de colonoscopia de voluntarios afectados. En conclusión, este estudio presenta ensayos moleculares selectivos y sensibles para la detección de patógenos en alimentos (Listeria spp., Mycobacterium avium subsp. paratuberculosis) y para una rápida e inambigua identificación de Salmonella spp. La exactitud relativa de los ensayos ha sido excelente, si se comparan con los métodos microbiológicos de referencia y pueden serusados para la cuantificación de tanto ADN genómico como de suspensiones celulares. Por otro lado, la combinación con tratamientos de preamplificación ha resultado ser de gran eficiencia para el análisis de las bacterias objeto de estudio. Por tanto, pueden constituir una estrategia útil para la detección rápida y sensible de patógenos en alimentos y deberían ser una herramienta adicional al rango de herramientas diagnósticas disponibles para el estudio de patógenos de origen alimentario.

A Study on the Efficiency of Synbiotics for Prevention and Control of Diarrhoea in 21 Dogs Submitted to Radiotherapy

A synbiotic is a formulation containing both probiotics and prebiotics. This study aims to evaluate the effect of supplementation with a synbiotic containing Enterococcus faecium strain E1707 (NCIMB 10415) in preventing or controlling diarrhoea and other gastrointestinal signs in boarded canine radiotherapy patients. A double-blind, randomized, placebocontrolled clinical trial was carried out in 21 adult dogs undergoing radiotherapy and boarded for a duration period of 2 to 3 weeks to treat their cancers. Dogs were randomly divided between two groups: A and B, the synbiotic and placebo group, respectively. The content of the sachets was added to the food once daily. Faecal score was assessed daily, and dogs were also monitored for the development of diarrhoea and other gastrointestinal signs such as weight loss, reduced appetite and vomiting. The results from descriptive statistics seem to favour group B, however these findings were not validated with inferential statistics due to insufficient statistical sample power. Because of this, it is not possible to make conclusions about the benefits of synbiotic as supportive treatment for dogs undergoing radiotherapy. All results should be considered to be preliminary, until they are elucidated by further animal inclusion.

Detection of transgenic and endogenous plant DNA fragments in the blood, tissues, and digesta of broilers

The aim was to determine the fate of transgenic and endogenous plant DNA fragments in the blood, tissues, and digesta of broilers. Male broiler chicks (n = 24) were allocated at 1 day old to each of four treatment diets designated T1-T4. T1 and T2 contained the near isogenic nongenetically modified (GM) maize grain, whereas T3 and T4 contained GM maize grain [cry1a(b) gene]; T1 and T3 also contained the near isogenic non-GM soybean meal, whereas T2 and T4 contained GM soybean meal (cp4epsps gene). Four days prior to slaughter at 39-42 days old, 50% of the broilers on T2-T4 had the source(s) of GM ingredients replaced by their non-GM counterparts. Detection of specific DNA sequences in feed, tissue, and digesta samples was completed by polymerase chain reaction analysis. Seven primer pairs were used to amplify fragments (similar to 200 bp) from single copy genes (maize high mobility protein, soya lectin, and transgenes in the GM feeds) and multicopy genes (poultry mitochondrial cytochrome b, maize, and soya rubisco). There was no effect of treatment on the measured growth performance parameters. Except for a single detection of lectin (nontransgenic single copy gene; unsubstantiated) in the extracted DNA from one bursa tissue sample, there was no positive detection of any endogenous or transgenic single copy genes in either blood or tissue DNA samples. However, the multicopy rubisco gene was detected in a proportion of samples from all tissue types (23% of total across all tissues studied) and in low numbers in blood. Feed-derived DNA was found to survive complete degradation up to the large intestine. Transgenic DNA was detected in gizzard digesta but not in intestinal digesta 96 h after the last feeding of treatment diets containing a source of GM maize and/or soybean meal.

Detection of transgenic DNA and protein, in rumen fluid, duodenal digesta, milk, blood and faeces of lactating dairy cows

The objective was to determine the presence or absence of transgenic and endogenous plant DNA in ruminal fluid, duodenal digesta, milk, blood, and feces, and if found, to determine fragment size. Six multiparous lactating Holstein cows fitted with ruminal and duodenal cannulas received a total mixed ration. There were two treatments (T). In T1, the concentrate contained genetically modified (GM) soybean meal (cp4epsps gene) and GM corn grain (cry1a[b] gene), whereas T2 contained the near isogenic non-GM counterparts. Polymerase chain reaction analysis was used to determine the presence or absence of DNA sequences. Primers were selected to amplify small fragments from single-copy genes (soy lectin and corn high-mobility protein and cp4epsps and cry1a[b] genes from the GM crops) and multicopy genes (bovine mitochondrial cytochrome b and rubisco). Single-copy genes were only detected in the solid phase of rumen and duodenal digesta. In contrast, fragments of the rubisco gene were detected in the majority of samples analyzed in both the liquid and solid phases of ruminal and duodenal digesta, milk, and feces, but rarely in blood. The size of the rubisco gene fragments detected decreased from 1176 bp in ruminal and duodenal digesta to 351 bp in fecal samples.

Detection of transgenic and endogenous plant DNA in rumen fluid, duodenal digesta, milk, blood, and feces of lactating dairy cows

The objective was to determine the presence or absence of transgenic and endogenous plant DNA in ruminal fluid, duodenal digesta, milk, blood, and feces, and if found, to determine fragment size. Six multiparous lactating Holstein cows fitted with ruminal and duodenal cannulas received a total mixed ration. There were two treatments (T). In T1, the concentrate contained genetically modified (GM) soybean meal (cp4epsps gene) and GM corn grain (cry1a[b] gene), whereas T2 contained the near isogenic non-GM counterparts. Polymerase chain reaction analysis was used to determine the presence or absence of DNA sequences. Primers were selected to amplify small fragments from single-copy genes (soy lectin and corn high-mobility protein and cp4epsps and cry1a[b] genes from the GM crops) and multicopy genes (bovine mitochondrial cytochrome b and rubisco). Single-copy genes were only detected in the solid phase of rumen and duodenal digesta. In contrast, fragments of the rubisco gene were detected in the majority of samples analyzed in both the liquid and solid phases of ruminal and duodenal digesta, milk, and feces, but rarely in blood. The size of the rubisco gene fragments detected decreased from 1176 bp in ruminal and duodenal digesta to 351 bp in fecal samples.

Detection of pressed hazelnut oil in virgin olive oil by analysis of polar components: improvement and validation of the method

An improved method for the detection of pressed hazelnut oil in admixtures with virgin olive oil by analysis of polar components is described. The method. which is based on the SPE-based isolation of the polar fraction followed by RP-HPLC analysis with UV detection. is able to detect virgin olive oil adulterated with pressed hazelnut oil at levels as low as 5% with accuracy (90.0 +/- 4.2% recovery of internal standard), good reproducibility (4.7% RSD) and linearity (R-2: 0.9982 over the 5-40% adulteration range). An international ring-test of the developed method highlighted its capability as 80% of the samples were, on average, correctly identified despite the fact that no training samples were provided to the participating laboratories. However, the large variability in marker components among the pressed hazelnut oils examined prevents the use of the method for quantification of the level of adulteration. (C) 2003 Elsevier Ltd. All rights reserved.

The automatic identification and prioritisation of criminal networks from police crime data

The identification of criminal networks is not a routine exploratory process within the current practice of the law enforcement authorities; rather it is triggered by specific evidence of criminal activity being investigated. A network is identified when a criminal comes to notice and any associates who could also be potentially implicated would need to be identified if only to be eliminated from the enquiries as suspects or witnesses as well as to prevent and/or detect crime. However, an identified network may not be the one causing most harm in a given area.. This paper identifies a methodology to identify all of the criminal networks that are present within a Law Enforcement Area, and, prioritises those that are causing most harm to the community. Each crime is allocated a score based on its crime type and how recently the crime was committed; the network score, which can be used as decision support to help prioritise it for law enforcement purposes, is the sum of the individual crime scores.

Design and evaluation of intelligent classifier based intrusion detection system

We have discovered a novel approach of intrusion detection system using an intelligent data classifier based on a self organizing map (SOM). We have surveyed all other unsupervised intrusion detection methods, different alternative SOM based techniques and KDD winner IDS methods. This paper provides a robust designed and implemented intelligent data classifier technique based on a single large size (30x30) self organizing map (SOM) having the capability to detect all types of attacks given in the DARPA Archive 1999 the lowest false positive rate being 0.04 % and higher detection rate being 99.73% tested using full KDD data sets and 89.54% comparable detection rate and 0.18% lowest false positive rate tested using corrected data sets.