AURPO Guidance - the safe use of lasers in research and education

AURPO Guidance - The safe use of lasers in research and education - Guidance note no.7, 2012 Edition

Laser Safety

Documents, Guidance, Video information relating to Laser Safety in the University

Evaluación a largo plazo en mujeres tratadas con laser para depilación facial en uniláser medica

El vello facial no deseado es un problema común en las mujeres, los tratamientos láser han mostrado efectividad para su manejo. Objetivo: Evaluar los resultados de la depilación láser en cara de las pacientes tratadas a largo plazo (20 sesiones o más ) luego de un seguimiento de 6 meses durante los años 1997 y 2012. Metodología: 55 mujeres que con tipo de piel II a V recibieron 20 o más sesiones de láser con seguimiento mayor a 6 meses posterior al la última sesión. Resultados: la edad promedio fue (32 ± 9,3 años), el 18,2 % presentaban SOP o Hiperandrogenismo el número de sesiones en cara fue de (30,84 ± 12,132), un promedio de disparos de (6,330 ± 7,804), los Kilojulios acumulados tuvieron un promedio de (126,5 ± 161,4) la fluencia promedio fue (18,5 ± 3,2 Julios/cm2), el láser de Alexandrita fue utilizado en el 98% de las pacientes. Se encontró cambios significativos entre el conteo inicial y el final de vello facial (484,9 ± 568.9 (med=300) vs. 103,33± 138,63 (med=60), p<0.001, Test de Wilcoxon). El 32.7% mostraron reducción > 90% (5,5% reducción del 100%). Conclusión : El tratamiento con de depilación con láser mostro una reducción significativa del vello facial, en mujeres mayores de 14 años con un tratamiento a largo plazo (20 sesiones o más), con una tasa de reducción mayor del 90% en 32.7% de las pacientes y un promedio de reducción del grupo de 79,36 ±15,51 %, similar a lo reportado en los diferentes estudios (77%).

La inclusión social y laboral de las personas con discapacidad intelectual mediante los programas de empleo con apoyo : un reto para la Orientación. 'Social and labour inclusion of people with intellectual disability through supported employment programs : a challenge for guidance'.

Resumen tomado de la publicación. Con el apoyo económico del departamento MIDE de la UNED

Higher Education Quality and Guidance : efficacy of a career celf-management seminar for undergraduates

Monogr??fico con el t??tulo: "Calidad en la Educaci??n Superior: una visi??n en perspectiva"

Using problem-based learning for introducing producer theory and market structure in intermediate microeconomics

This paper shows how instructors can use the problem‐based learning method to introduce producer theory and market structure in intermediate microeconomics courses. The paper proposes a framework where different decision problems are presented to students, who are asked to imagine that they are the managers of a firm who need to solve a problem in a particular business setting. In this setting, the instructors’ role is to provide both guidance to facilitate student learning and content knowledge on a just‐in‐time basis

Use of fused airborne scanning laser altimetry and digital map data for urban flood modelling

Flood modelling of urban areas is still at an early stage, partly because until recently topographic data of sufficiently high resolution and accuracy have been lacking in urban areas. However, Digital Surface Models (DSMs) generated from airborne scanning laser altimetry (LiDAR) having sub-metre spatial resolution have now become available, and these are able to represent the complexities of urban topography. The paper describes the development of a LiDAR post-processor for urban flood modelling based on the fusion of LiDAR and digital map data. The map data are used in conjunction with LiDAR data to identify different object types in urban areas, though pattern recognition techniques are also employed. Post-processing produces a Digital Terrain Model (DTM) for use as model bathymetry, and also a friction parameter map for use in estimating spatially-distributed friction coefficients. In vegetated areas, friction is estimated from LiDAR-derived vegetation height, and (unlike most vegetation removal software) the method copes with short vegetation less than ~1m high, which may occupy a substantial fraction of even an urban floodplain. The DTM and friction parameter map may also be used to help to generate an unstructured mesh of a vegetated urban floodplain for use by a 2D finite element model. The mesh is decomposed to reflect floodplain features having different frictional properties to their surroundings, including urban features such as buildings and roads as well as taller vegetation features such as trees and hedges. This allows a more accurate estimation of local friction. The method produces a substantial node density due to the small dimensions of many urban features.

Extraction of tidal channel networks from aerial photographs alone and combined with laser altimetry

Tidal channel networks play an important role in the intertidal zone, exerting substantial control over the hydrodynamics and sediment transport of the region and hence over the evolution of the salt marshes and tidal flats. The study of the morphodynamics of tidal channels is currently an active area of research, and a number of theories have been proposed which require for their validation measurement of channels over extensive areas. Remotely sensed data provide a suitable means for such channel mapping. The paper describes a technique that may be adapted to extract tidal channels from either aerial photographs or LiDAR data separately, or from both types of data used together in a fusion approach. Application of the technique to channel extraction from LiDAR data has been described previously. However, aerial photographs of intertidal zones are much more commonly available than LiDAR data, and most LiDAR flights now involve acquisition of multispectral images to complement the LiDAR data. In view of this, the paper investigates the use of multispectral data for semiautomatic identification of tidal channels, firstly from only aerial photographs or linescanner data, and secondly from fused linescanner and LiDAR data sets. A multi-level, knowledge-based approach is employed. The algorithm based on aerial photography can achieve a useful channel extraction, though may fail to detect some of the smaller channels, partly because the spectral response of parts of the non-channel areas may be similar to that of the channels. The algorithm for channel extraction from fused LiDAR and spectral data gives an increased accuracy, though only slightly higher than that obtained using LiDAR data alone. The results illustrate the difficulty of developing a fully automated method, and justify the semi-automatic approach adopted.

Extraction of tidal channel networks from airborne scanning laser altimetry and aerial photography

The study of the morphodynamics of tidal channel networks is important because of their role in tidal propagation and the evolution of salt-marshes and tidal flats. Channel dimensions range from tens of metres wide and metres deep near the low water mark to only 20-30cm wide and 20cm deep for the smallest channels on the marshes. The conventional method of measuring the networks is cumbersome, involving manual digitising of aerial photographs. This paper describes a semi-automatic knowledge-based network extraction method that is being implemented to work using airborne scanning laser altimetry (and later aerial photography). The channels exhibit a width variation of several orders of magnitude, making an approach based on multi-scale line detection difficult. The processing therefore uses multi-scale edge detection to detect channel edges, then associates adjacent anti-parallel edges together to form channels using a distance-with-destination transform. Breaks in the networks are repaired by extending channel ends in the direction of their ends to join with nearby channels, using domain knowledge that flow paths should proceed downhill and that any network fragment should be joined to a nearby fragment so as to connect eventually to the open sea.

Uses of airborne scanning laser altimetry for river flood modelling and coastal geomorphology

Two ongoing projects at ESSC that involve the development of new techniques for extracting information from airborne LiDAR data and combining this information with environmental models will be discussed. The first project in conjunction with Bristol University is aiming to improve 2-D river flood flow models by using remote sensing to provide distributed data for model calibration and validation. Airborne LiDAR can provide such models with a dense and accurate floodplain topography together with vegetation heights for parameterisation of model friction. The vegetation height data can be used to specify a friction factor at each node of a model’s finite element mesh. A LiDAR range image segmenter has been developed which converts a LiDAR image into separate raster maps of surface topography and vegetation height for use in the model. Satellite and airborne SAR data have been used to measure flood extent remotely in order to validate the modelled flood extent. Methods have also been developed for improving the models by decomposing the model’s finite element mesh to reflect floodplain features such as hedges and trees having different frictional properties to their surroundings. Originally developed for rural floodplains, the segmenter is currently being extended to provide DEMs and friction parameter maps for urban floods, by fusing the LiDAR data with digital map data. The second project is concerned with the extraction of tidal channel networks from LiDAR. These networks are important features of the inter-tidal zone, and play a key role in tidal propagation and in the evolution of salt-marshes and tidal flats. The study of their morphology is currently an active area of research, and a number of theories related to networks have been developed which require validation using dense and extensive observations of network forms and cross-sections. The conventional method of measuring networks is cumbersome and subjective, involving manual digitisation of aerial photographs in conjunction with field measurement of channel depths and widths for selected parts of the network. A semi-automatic technique has been developed to extract networks from LiDAR data of the inter-tidal zone. A multi-level knowledge-based approach has been implemented, whereby low level algorithms first extract channel fragments based mainly on image properties then a high level processing stage improves the network using domain knowledge. The approach adopted at low level uses multi-scale edge detection to detect channel edges, then associates adjacent anti-parallel edges together to form channels. The higher level processing includes a channel repair mechanism.

High resolution photoacoustic overtone spectroscopy of monofluoroacetylene, HCCF, with a titanium:sapphire ring laser

Intracavity photoacoustic overtone spectrum of monofluoroacetylene, HCCF, has been recorded in the wave number region 10 750–14 500 cm−1 with a titanium:sapphire ring laser. The spectrum contains many dense vibration–rotation band systems which can be resolved with Doppler limited resolution. Altogether 58 individual overtone bands have been analyzed rotationally. Many of the observed bands show perturbations of which some have been attributed to anharmonic resonance interactions. A Fermi resonance model based on conventional rectilinear normal coordinate theory has been used to assign vibrationally bands from this work and from earlier studies. Many of the observed vibrational term values and rotational constants can be reproduced well with this model. The results show the importance of the Fermi resonance interactions at the high overtone excitations.

An evaluation of a Bayesian method of dose escalation based on bivariate binary responses

Recently, various approaches have been suggested for dose escalation studies based on observations of both undesirable events and evidence of therapeutic benefit. This article concerns a Bayesian approach to dose escalation that requires the user to make numerous design decisions relating to the number of doses to make available, the choice of the prior distribution, the imposition of safety constraints and stopping rules, and the criteria by which the design is to be optimized. Results are presented of a substantial simulation study conducted to investigate the influence of some of these factors on the safety and the accuracy of the procedure with a view toward providing general guidance for investigators conducting such studies. The Bayesian procedures evaluated use logistic regression to model the two responses, which are both assumed to be binary. The simulation study is based on features of a recently completed study of a compound with potential benefit to patients suffering from inflammatory diseases of the lung.

Liquid ultraviolet matrix-assisted laser desorption/ionization - mass spectrometry for automated proteomic analysis

We have combined several key sample preparation steps for the use of a liquid matrix system to provide high analytical sensitivity in automated ultraviolet -- matrix-assisted laser desorption/ionisation -- mass spectrometry (UV-MALDI-MS). This new sample preparation protocol employs a matrix-mixture which is based on the glycerol matrix-mixture described by Sze et al. The low-femtomole sensitivity that is achievable with this new preparation protocol enables proteomic analysis of protein digests comparable to solid-state matrix systems. For automated data acquisition and analysis, the MALDI performance of this liquid matrix surpasses the conventional solid-state MALDI matrices. Besides the inherent general advantages of liquid samples for automated sample preparation and data acquisition the use of the presented liquid matrix significantly reduces the extent of unspecific ion signals in peptide mass fingerprints compared to typically used solid matrices, such as 2,5-dihydroxybenzoic acid (DHB) or alpha-cyano-hydroxycinnamic acid (CHCA). In particular, matrix and low-mass ion signals and ion signals resulting from cation adduct formation are dramatically reduced. Consequently, the confidence level of protein identification by peptide mass mapping of in-solution and in-gel digests is generally higher.

Liquid ultraviolet matrix-assisted laser desorption/ionization mass spectrometry for automated proteomic analysis

We have combined several key sample preparation steps for the use of a liquid matrix system to provide high analytical sensitivity in automated ultraviolet - matrix-assisted laser desorption/ ionisation - mass spectrometry (UV-MALDI-MS). This new sample preparation protocol employs a matrix-mixture which is based on the glycerol matrix-mixture described by Sze et al. U. Am. Soc. Mass Spectrom. 1998, 9, 166-174). The low-ferntomole sensitivity that is achievable with this new preparation protocol enables proteomic analysis of protein digests comparable to solid-state matrix systems. For automated data acquisition and analysis, the MALDI performance of this liquid matrix surpasses the conventional solid-state MALDI matrices. Besides the inherent general advantages of liquid samples for automated sample preparation and data acquisition the use of the presented liquid matrix significantly reduces the extent of unspecific ion signals in peptide mass fingerprints compared to typically used solid matrices, such as 2,5-dihydrox-ybenzoic acid (DHB) or alpha-cyano-hydroxycinnamic acid (CHCA). In particular, matrix and lowmass ion signals and ion signals resulting from cation adduct formation are dramatically reduced. Consequently, the confidence level of protein identification by peptide mass mapping of in-solution and in-gel digests is generally higher.

Influence of glycosidic linkages and molecular weight on the fermentation of maltose-based oligosaccharides by human gut bacteria

A structure-function study was carried out to increase knowledge of how glycosidic linkages and molecular weights of carbohydrates contribute toward the selectivity of fermentation by gut bacteria. Oligosaccharides with maltose as the common carbohydrate source were used. Potentially prebiotic alternansucrase and dextransucrase maltose acceptor products were synthesized and separated into different molecular weights using a Bio-gel P2 column. These fractions were characterized by matrix-assisted laser desorption/ionization time-of-flight. Nonprebiotic maltooligosaccharides with degrees of polymerization (DP) from three to seven were commercially obtained for comparison. Growth selectivity of fecal bacteria on these oligosaccharides was studied using an anaerobic in vitro fermentation method. In general, carbohydrates of DP3 showed the highest selectivity towards bifidobacteria; however, oligosaccharides with a higher molecular weight (DP6-DP7) also resulted in a selective fermentation. Oligosaccharides with DPs above seven did not promote the growth of "beneficial" bacteria. The knowledge of how specific structures modify the gut microflora could help to find new prebiotic oligosaccharides.