The production and distribution of counterfeit drugs is a critical health problem that plagues nations worldwide. The presence of counterfeit antimalarials has become especially worrying, as these drugs are most often needed by those living in nations whose resources to verify the medicine supply are lacking. Rapid analysis methods used for screening large quantities of poor quality antimalarials are critical in the battle to protect those in less developed regions of the world. Simple, cost effective analysis methods that can be used in the field must be developed so those whose governments cannot afford to maintain medicine regulatory agencies can still have faith in their medicinal supply. A very powerful screening method, Direct Analysis in Real Time Mass Spectrometry (DART-MS) has been used to investigate thousands of poor quality medicines. This method, however, is known to fragment molecules more readily than commonly used, 'softer' ionization methods, such as electrospray ionization. Excess fragmentation in 'harder' ionization sources is due to deposition of additional internal energy to the ionized molecules. This internal energy deposition can be measured, so the analyst can be knowledgeable as to what to expect when examining unknowns using this recently developed ionization source. Quantitation of the active pharmaceutical ingredient (API) in pharmaceuticals is crucial to the determination of what class a poor quality medicine fits into. Because poor quality drugs can be of different types, it is important to accurately classify them, in hopes of improving the supply of medicines available to those in less developed regions of the world. High performance liquid chromatography (HPLC) is most commonly used to quantify the active pharmaceutical ingredient in poor quality medicines, however, this method is time consuming, preventing its use in high throughput settings. During the course of my research, hundreds of poor quality pharmaceuticals were analyzed using DART-MS. The active pharmaceutical ingredient was detected during the rapid screening for many of these drugs, however, a more in depth analysis would often reveal less than the expected quantity of active ingredient. A rapid non-chromatographic quantitation method was developed using a mass spectrometer as the detector. This method allows for both quantitative and qualitative information regarding a specific sample to be obtained simultaneously, saving the analyst time and resources. Utilizing this non- chromatographic mass spectrometric method, degradation products have been identified, thus increasing our ability to classify drugs into their respective divisions.

Thesis (Ph. D.)--University of California, San Diego, 2009. / Title from first page of PDF file (viewed January 19, 2010). Available via ProQuest Digital Dissertations. Vita. Includes bibliographical references (p. 283-295).

Les mesures de télédétection (MT) dépendent de l'interaction du rayonnement avec les paysages terrestres et l'atmosphère ainsi que des configurations instrumentales (bande spectrale, résolution spatiale, champ de vue: FOV,...) et expérimentales (structure et propriétés optiques du paysage et atmosphère,...). L'évolution rapide des techniques de télédétection requiert des outils appropriés pour valider leurs principes et améliorer l'emploi des MT. Les modèles de transfert radiatif (RTM) simulent des quantités (fonctions de distribution de la réflectance (BRDF) et température (BTDF), forme d'onde LiDAR, etc.) plus ou moins proches des MT. Ils constituent l'outil de référence pour simuler les MT, pour diverses applications : préparation et validation des systèmes d'observation, inversion de MT,... DART (Discrete Anisotropic Radiative Transfer) est reconnu comme le RTM le plus complet et efficace. J'ai encore nettement amélioré son réalisme via les travaux de modélisation indiqués ci-dessous. 1. Discrétisation de l'espace des directions de propagation des rayons. DART simule la propagation des rayons dans les paysages terrestres et l'atmosphère selon des directions discrètes. Les méthodes classiques définissent mal le centroïde et forme des angles solides de ces directions, si bien que le principe de conservation de l'énergie n'est pas vérifié et que l'obtention de résultats précis exige un grand nombre de directions. Pour résoudre ce problème, j'ai conçu une méthode originale qui crée des directions discrètes de formes définies. 2. Simulation d'images de spectroradiomètre avec FOV fini (caméra, pushbroom,...). Les RTMs sont de type "pixel" ou "image". Un modèle "pixel" calcule une quantité unique (BRDF, BTDF) de toute la scène simulée via sa description globale (indice foliaire, fraction d'ombre,...). Un modèle "image" donne une distribution spatiale de quantités (BRDF,...) par projection orthographique des rayons sur un plan image. Tous les RTMs supposent une acquisition monodirectionnelle (FOV nul), ce qui peut être très imprécis. Pour pouvoir simuler des capteurs à FOV fini (caméra, pushbroom,...), j'ai conçu un modèle original de suivi de rayons convergents avec projection perspective. 3. Simulation de données LiDAR. Beaucoup de RTMs simulent le signal LiDAR de manière rapide mais imprécise (paysage très simplifié, pas de diffusions multiples,...) ou de manière précis mais avec de très grands temps de calcul (e.g., modèles Monte-Carlo: MC). DART emploie une méthode "quasi-MC" originale, à la fois précise et rapide, adaptée à toute configuration instrumentale (altitude de la plateforme, attitude du LiDAR, taille de l'empreinte,...). Les acquisitions multi-impulsions LiDAR (satellite, avion, terrestre) sont simulées pour toute configuration (position du LiDAR, trajectoire de la plateforme,...). Elles sont converties dans un format industriel pour être traitées par des logiciels dédiés. Un post-traitement convertit les formes d'onde LiDAR simulées en données LiDAR de comptage de photons. 4. Bruit solaire et fusion de données LiDAR et d'images de spectroradiomètre. DART peut combiner des simulations de LiDAR multi-impulsions et d'image de spectro-radiomètre (capteur hyperspectral,...). C'est une configuration à 2 sources (soleil, laser LiDAR) et 1 capteur (télescope du LiDAR). Les régions mesurées par le LiDAR, dans le plan image du sol, sont segmentées dans l'image du spectro-radiomètre, elle aussi projetée sur le plan image du sol. Deux applications sont présentées : bruit solaire dans le signal LiDAR, et fusion de données LiDAR et d'images de spectro-radiomètre. Des configurations d'acquisition (trajectoire de plateforme, angle de vue par pixel du spectro-radiomètre et par impulsion LiDAR) peuvent être importées pour encore améliorer le réalisme des MT simulées, De plus, j'ai introduit la parallélisation multi-thread, ce qui accélère beaucoup les calculs / Remote Sensing (RS) data depend on radiation interaction in Earth landscapes and atmosphere, and also on instrumental (spectral band, spatial resolution, field of view (FOV),...) and experimental (landscape/atmosphere architecture and optical properties,...) conditions. Fast developments in RS techniques require appropriate tools for validating their working principles and improving RS operational use. Radiative Transfer Models (RTM) simulate quantities (bidirectional reflectance; BRDF, directional brightness temperature: BTDF, LiDAR waveform...) that aim to approximate actual RS data. Hence, they are celebrated tools to simulate RS data for many applications: preparation and validation of RS systems, inversion of RS data... Discrete Anisotropic Radiative Transfer (DART) model is recognized as the most complete and efficient RTM. During my PhD work, I further improved its modeling in terms of accuracy and functionalities through the modeling work mentioned below. 1. Discretizing the space of radiation propagation directions.DART simulates radiation propagation along a finite number of directions in Earth/atmosphere scenes. Classical methods do not define accurately the solid angle centroids and geometric shapes of these directions, which results in non-conservative energy or imprecise modeling if few directions are used. I solved this problem by developing a novel method that creates discrete directions with well-defined shapes. 2. Simulating images of spectroradiometers with finite FOV.Existing RTMs are pixel- or image-level models. Pixel-level models use abstract landscape (scene) description (leaf area index, overall fraction of shadows,...) to calculate quantities (BRDF, BTDF,...) for the whole scene. Image-level models generate scene radiance, BRDF or BTDF images, with orthographic projection of rays that exit the scene onto an image plane. All models neglect the multi-directional acquisition in the sensor finite FOV, which is unrealistic. Hence, I implemented a sensor-level model, called converging tracking and perspective projection (CTPP), to simulate camera and cross-track sensor images, by coupling DART with classical perspective and parallel-perspective projection. 3. Simulating LiDAR data.Many RTMs simulate LiDAR waveform, but results are inaccurate (abstract scene description, account of first-order scattering only...) or require tremendous computation time for obtaining accurate results (e.g., Monte-Carlo (MC) models). With a novel quasi-MC method, DART can provide accurate results with fast processing speed, for any instrumental configuration (platform altitude, LiDAR orientation, footprint size...). It simulates satellite, airborne and terrestrial multi-pulse laser data for realistic configurations (LiDAR position, platform trajectory, scan angle range...). These data can be converted into industrial LiDAR format for being processed by LiDAR processing software. A post-processing method converts LiDAR waveform into photon counting LiDAR data, through modeling single photon detector acquisition. 4. In-flight Fusion of LiDAR and imaging spectroscopy.DART can combine multi-pulse LiDAR and cross-track imaging spectroscopy (hyperspectral sensor...). It is a 2 sources (sun, LiDAR laser) and 1 sensor (LiDAR telescope) system. First, a LiDAR multi-pulse acquisition and a sun-induced spectro-radiometer radiance image are simulated. Then, the LiDAR FOV regions projected onto the ground image plane are segmented in the spectro-radiometer image, which is also projected on the ground image plane. I applied it to simulate solar noise in LiDAR signal, and to the fusion of LiDAR data and spectro-radiometer images. To further improve accuracy when simulating actual LiDAR and spectro-radiometer, DART can also import actual acquisition configuration (platform trajectory, view angle per spectro-radiometer pixel / LiDAR pulse). Moreover, I introduced multi-thread parallelization, which greatly accelerates DART simulations

Orientador: Marcos Antonio Machado / Resumo: Phytophthora nicotianae Breda de Haan (Phytophthora parasitica Dastur) e Phytophthora citrophthora (Smith & Smith), agentes causadores da gomose e podridão radicular, têm trazido graves danos em viveiros e pomares de citros no mundo inteiro. O Centro de Citricultura Sylvio Moreira/IAC vem realizando um amplo programa de melhoramento genético de citros via cruzamentos dirigidos com relação ao patossistema Phytophthora-citros, em que já foram verificadas diferenças no nível de resistência na progênie do cruzamento entre tangerina Sunki (Citrus sunki) e trifoliata Rubidoux (Poncirus trifoliata), a partir da detecção de genes diferencialmente expressos utilizando microarranjos, identificando transcritos envolvidos na resistência à Phytophthora, e do mapeamento genético. Este trabalho teve como objetivo principal mapear nos grupos de ligação dos mapas de P. trifoliata e C. sunki as regiões genômicas associadas à resistência à Phytophthora parasitica por meio de análise fenotípica (QTLs) e de expressão (eQTLs). Uma população de 110 híbridos, seus genitores e dois porta-enxertos de referência para a citricultura (limão Cravo e citrumelo Swingle), foi enxertada em limão Cravo e estabelecida em casa de vegetação. Cada híbrido foi conduzido com uma única haste e a inoculação foi realizada pelo método do disco a partir do meio de cultura contendo o micélio de P. parasitica, a 10 cm e 15 cm acima da região da enxertia, totalizando duas inoculações por genótipo. As plantas foram mantidas ... (Resumo completo, clicar acesso eletrônico abaixo) / Mestre

Bildgruppen på enheten för dokument och informationsteknik hos SKL har ett behov av att kunna förbättra bilder med extremt låg upplösning. Detta bildmaterial kan komma från diverse övervakningskameror där det intressanta objektet endast utgör en väldigt liten del, i detta fall registreringsskyltar på förbipasserande bilar. Att skapa en högupplöst bild av en registreringsskylt utav ett fåtal lågupplösta bilder är ett välkänt problem med ett flertal förslag på metoder och lösningar. I denna rapport kommer vi att undersöka vilka metoder som passar bäst vid bildförbättring av registreringsskyltar. Vi kommer även att skapa ett användargränssnitt där man kan läsa in en bild och välja mellan att automatiskt hitta registreringsskylten i bilden eller att manuellt klippa ut den. Efter att man erhållit en bild innehållandes endast registreringsskylten ska de olika implementerade bildförbättringsmetoderna kunna användas. Slutligen diskuteras vilka för- och nackdelar de respektive metoderna har. Förslag på eventuella förbättringar och hur man kan utveckla dessa metoder vidare presenteras därtill.

Gasoline is a substance commonly encountered in forensic settings. Unfortunately, gasoline is an easily obtainable ignitable liquid that arsonists commonly use to initiate or expedite the spread of an intentionally set fire. Fires claim the lives of many people each year in addition to causing widespread property damage. Many fire scene investigations result in charges of arson, which has the legal connotation of a committed crime. For this reason, extensive analysis and investigation must be undertaken before any suspected arson scene is deemed an actual case of arson. Although ignitable liquids, including gasoline, may be present at the scene of a fire, it does not necessarily mean they were intentionally used as accelerants. An accelerant is a fuel used to initiate a fire. These realities, in addition to several other factors, demonstrate why a rapid, reliable, gasoline analysis method is crucial to forensic applications. In this thesis, direct analysis in real time – mass spectrometry (DART-MS) is evaluated as a potential method that could better identify, distinguish and classify gasoline brands from one another. Techniques such as DART-MS could enable forensic laboratories to better identify questioned gasoline samples. Many ignitable liquids share similar chemical properties, and forensically relevant evidence is often obtained from a crime scene in less than favorable conditions. Fire debris can encompass various materials, including burnt carpet, flooring, items of furniture and clothing, among others. If gasoline was used as an accelerant, it may be present in trace amounts after the termination of the fire. Materials submitted for laboratory analysis may be substrates with compositions that have components similar to those found in some ignitable liquids. These are just a few of the potential obstacles that could be encountered with analyzing fire debris in a forensic setting. Traditionally, gas chromatography – mass spectrometry (GC-MS) methods are utilized for gasoline analysis in the criminal laboratory setting. While traditional GC-MS methods are sensitive and able to classify samples as gasoline, they are time consuming in terms of both sample preparation and analysis. Additionally, they do not generate differential mass spectral data based on the brand of gasoline. Conversely, gasoline analysis in this research, utilizing the DART-MS method, demonstrated that five different brands of gasoline could be distinguished from one another both by visual examination of mass spectra and with methods of chemometric analysis. Advantageously, the DART-MS method, an ambient ionization technique, requires little sample preparation and a rapid sample analysis time, which could drastically increase the throughput of standard sample analysis with further method development. The goals and objectives of this research were to optimize the DART-MS parameters for gasoline analysis, determine if DART-MS analysis could distinguish gasoline by brand, develop chemometric models to appropriately classify gasoline samples, and finally lay groundwork for future studies that could further develop a more efficient and discriminating DART-MS gasoline analysis method for forensic casework. Each brand of gasoline was observed to have a chemical attribute signature (CAS) consisting of not only low-mass ions, but also a variety of high-mass ions not usually observed with gasoline samples analyzed by GC-MS. Although variables including season, storage time, dilution and age of the gasoline were observed to contribute to the resulting mass spectral data, once the mass spectra are better understood, they could offer even more discriminating power between samples than simple analysis of the gasoline brand. In this research, DART-MS parameters were first optimized for gasoline analysis. Subsequently, the five acquired brands of gasoline: Shell, Sunoco, Irving, Cumberland Farms and Gulf, were analyzed both undiluted (or neat) and diluted utilizing the DART-MS analysis method. GC-MS data was generated and analyzed to show comparisons. After analyzing the data generated by both approaches, it was apparent that the DART-MS method could generate CASs based on the gasoline brand and offer a degree of differentiation that traditional GC-MS does not. Additional chemometric analyses utilizing principle component analysis (PCA) and the construction of models with Analyze IQ Lab software verified that the gasoline brands were distinguishable when samples were analyzed with this ambient ionization method. PCA plots of the neat gasoline demonstrated clustering based on brand. Additionally, models constructed from training samples generated from DART-MS analysis of the various brands were able to accurately classify gasoline samples as "yes" or "no" when a test set of gasoline was compared to all five brands. The lowest associated testing error rate for some of these models was 0%. However, additional analysis with greater sample sizes needs to be further carried out to more accurately evaluate this method of gasoline analysis and classification.

Electrical methods of geophysical survey are known to produce results that are hard to predict at different times of the year, and under differing weather conditions. This is a problem which can lead to misinterpretation of archaeological features under investigation. The dynamic relationship between a ‘natural’ soil matrix and an archaeological feature is a complex one, which greatly affects the success of the feature’s detection when using active electrical methods of geophysical survey. This study has monitored the gradual variation of measured resistivity over a selection of study areas. By targeting difficult to find, and often ‘missing’ electrical anomalies of known archaeological features, this study has increased the understanding of both the detection and interpretation capabilities of such geophysical surveys. A 16 month time-lapse study over 4 archaeological features has taken place to investigate the aforementioned detection problem across different soils and environments. In addition to the commonly used Twin-Probe earth resistance survey, electrical resistivity imaging (ERI) and quadrature electro-magnetic induction (EMI) were also utilised to explore the problem. Statistical analyses have provided a novel interpretation, which has yielded new insights into how the detection of archaeological features is influenced by the relationship between the target feature and the surrounding ‘natural’ soils. The study has highlighted both the complexity and previous misconceptions around the predictability of the electrical methods. The analysis has confirmed that each site provides an individual and nuanced situation, the variation clearly relating to the composition of the soils (particularly pore size) and the local weather history. The wide range of reasons behind survey success at each specific study site has been revealed. The outcomes have shown that a simplistic model of seasonality is not universally applicable to the electrical detection of archaeological features. This has led to the development of a method for quantifying survey success, enabling a deeper understanding of the unique way in which each site is affected by the interaction of local environmental and geological conditions.

Current screening methods for drug analysis with urine samples includes examination of the sample with an immunoassay. These methods are used to determine the concentration of drug metabolites contained within the sample prior to further confirmatory testing. Drug testing plays a crucial role in maintaining safe workplace environments and safety of individuals. However, a positive result can lead to heavy consequences for the employee including suspension or removal from the workplace. Therefore, a majority of individuals add commonly known products into the sample to evade detection by developing a false negative result. Although specimen integrity examinations are performed to identify tampering of the sample, these results are typically biased on the experience of the examiner. The purpose of this study was to develop an analytical screening technique that will detect the drug of interest as well as the presence of any additional products that may be added into the sample via Direct Analysis in Real Time – High Resolution/Mass Spectrometry (DART-HR/MS) which is an ambient ionization source that produces fast mass spectrum results that can provide semi-quantitative information of the target metabolite concentration. Although there are various studies that indicate the ability of the DART to detect drug compounds, there are no known studies that have examined how real-world urine samples are analyzed. Additionally, there are no current studies that take into consideration adulteration of the urine sample using the DART method. The results obtained in the study showed the ability for DART to identify molecular protonated peaks indicative of dextroamphetamine and/or the presence of masking agents. While the other target drugs could not be identified using this method, the identification of dextroamphetamine, adulterant products and the deuterated internal standard show promise in using this as a screening technique prior to confirmatory tests. Future work is currently being conducted to optimize the protocol for the evaluation of THC, cocaine and benzodiazepines.

The need for an efficient dimensionality reduction technique has remained a critical challenge for effective analysis of hyperspectral data for vegetation applications. Discrete wavelet transform (DWT), through multiresolution analysis, offers oppurtunities both to reduce dimension and convey information at multiple spectral scales. In this study, we investigated the utility of the Haar DWT for AVIRIS hyperspectral data analysis in three different applications (1) classification of three pine species (Pinus spp.), (2) estimation of leaf area index (LAI) using an empirically-based model, and (3) estimation of LAI using a physically-based model. For pine species classification, different sets of Haar wavelet features were compared to each other and to calibrated radiance. The Haar coefficients selected by stepwise discriminant analysis provided better classification accuracy (74.2%) than the original radiance (66.7%). For empirically-based LAI estimation, the models using the Haar coefficients explained the most variance in observed LAI for both deciduous plots (cross validation R² (CV-R²) = 0.79 for wavelet features vs. CV-R² = 0.69 for spectral bands) and all plots combined (CV R² = 0.71 for wavelet features vs. CV-R² = 0.50 for spectral bands). For physically-based LAI estimation, a look-up-table (LUT) was constructed by a radiative transfer model, DART, using a three-stage approach developed in this study. The approach involved comparison between preliminary LUT reflectances and image spectra to find the optimal set of parameter combinations and input increments. The LUT-based inversion was performed with three different datasets, the original reflectance bands, the full set of the wavelet extracted features, and the two wavelet subsets containing 99.99% and 99.0% of the cumulative energy of the original signal. The energy subset containing 99.99% of the cumulative signal energy provided better estimates of LAI (RMSE = 0.46, R² = 0.77) than the original spectral bands (RMSE = 0.69, R² = 0.42). This study has demonstrated that the application of the discrete wavelet transform can provide more accurate species discrimination within the same genus than the original hyperspectral bands and can improve the accuracy of LAI estimates from both empirically- and physically-based models. / Ph. D.

Titel: DART- en modell för värdesamskapande - En studie i hur fastighetsmäklare och kunder samskapar värde Nivå: C-uppsats i ämnet företagsekonomi Författare: Lizbet Brittsten och Sanna Pickelner Handledare: Jens Eklinder - Frick och Jonas Molin Datum: 2015 – Maj Syfte: Att kunder intresserar sig för ett värdeskapande tillsammans med företagen och vill delta allt mer i affärsprocesser, framför allt i tjänstesektorn, ligger i tiden. Då vi båda kommer arbeta i en tjänstebransch där det krävs samarbete med kunder, väcktes vårt intresse att fördjupa oss i ämnet. Syftet med den här studien är att utifrån ett företags- och kundperspektiv öka förståelsen för hur delarna dialog, access, riskbedömning och transparens påverkar värdesamskapandet i en säljprocess mellan tjänsteföretag och kunder. Metod: I studien har vi använt oss av en kvalitativ metod. Underlaget till studien samlades in genom semistrukturerade djupintervjuer med både fastighetsmäklare och kunder (säljare). Från intervjuerna har vi tagit ut nyckeltermer och presenterat dem i empirikapitlet. Utifrån ett deduktiv angreppssätt har det empiriska underlaget analyserats mot teorin och respondenternas svar har även jämförts sinsemellan.   Resultat & slutsats: Av de faktorer vi undersökte visade sig dialog och transparens ha ett starkare samband och vara mer framträdande vid värdesamskapande än access. Dessutom låg riskbedömning snarare till grund för de tre andra faktorerna vilket vi anser borde revideras och tydliggöras i modellen. Ett annat resultat från vår studie är att ett värdesamskapande snabbt kan övergå till ett värdeförstörande om det inte hanteras på rätt sätt igenom hela affärsprocessen.   Förslag till fortsatt forskning: Det vore intressant att prova våra två omarbetade DART-modeller i en studie med fler respondenter då vårt urval varit begränsat i storlek. Vi finner det också intressant att se om den befintliga DART-modellen är applicerbar i en studie där  utgångspunkten är en annan tjänstebransch där risktagandet inte är av samma betydelse. Vi föreslår även att utföra studier på området med ett induktivt angreppssätt, då vår studie varit begränsad till en befintlig teoretisk modell.   Uppsatsens bidrag: Ett teoretiskt bidrag från vår studie är att DART-modellen borde omformas. Den visade sig inte applicerbar fullt ut i vår studie. Vi har därför vidareutvecklat två modeller baserat på ursprungsmodellen. Dialog och transparens visade sig vara starkt sammankopplade och viktiga verktyg för mäklarna för att få kundernas förtroende. Det ser vi som ett praktiskt bidrag då vi anser att kombinationen av dialog och transparens är central och kan vara kopplad till förtroendeskapande även i andra tjänstebranscher. Kunders helhetsupplevelse, såväl monetärt som relationsmässigt, har i vår studie visat sig vara avgörande för det upplevda värdet.