Identification of pharmaceutical tablets by Raman spectroscopy and chemometrics

Raman spectroscopy has become an attractive tool for the analysis of pharmaceutical solid dosage forms. In the present study it is used to ensure the identity of tablets. The two main applications of this method are release of final products in quality control and detection of counterfeits. Twenty-five product families of tablets have been included in the spectral library and a non-linear classification method, the Support Vector Machines (SVMs), has been employed. Two calibrations have been developed in cascade: the first one identifies the product family while the second one specifies the formulation. A product family comprises different formulations that have the same active pharmaceutical ingredient (API) but in a different amount. Once the tablets have been classified by the SVM model, API peaks detection and correlation are applied in order to have a specific method for the identification and allow in the future to discriminate counterfeits from genuine products. This calibration strategy enables the identification of 25 product families without error and in the absence of prior information about the sample. Raman spectroscopy coupled with chemometrics is therefore a fast and accurate tool for the identification of pharmaceutical tablets.

Atypical EPO profiles in anti-doping analyses

Résumé : Erythropoietin (EPO) is a glycoprotein hormone endogenously produced by the kidney, whose main physiological role is the stimulation of erythropoiesis. Since the beginning of the nineties, recombinant human EPO (rhEPO), a potent anti-anaemia treatment drug, has been manufactured by pharmaceutical industries. However, the erythropoiesis stimulating power of rhEPO was rapidly misused by unscrupulous athletes in order to improve their performances in endurance sports. Endogenous EPO has the same amino-acid backbone as most of recombinant forms; the molecules however differ through their respective glycosylation patterns. This difference constitutes the basis of the usual EPO screening test (IEF) developed in 2000 and still currently used in all anti-doping laboratories of the world. Nowadays, 3 EPO generations have been commercialized. The fight against EPO abuse is a continuous challenge for anti-doping laboratories. The diversity of recombinant EPO forms and the continuous development of new ones considerably confuse the identification of EPO doping. Several facets of this fight were investigated in this work. One of the limiting aspects of doping agents screening is the availability of positive samples. Therefore, 2nd and 3rd generation EPOS, namely NESP and C.E.R.A., were injected to healthy subjects in the frame of pilot clinical studies. These latter allowed to review the current EPO identification criteria defined by the World Anti-Doping Agency (WADA) in the case of NESP and to validate and implement a new assay targeting C.E.R.A. in human serum. Both studies resulted in the determination of the respective detection windows of NESP and C.E.R.A. in biological fluids. Following that, Dynepo, a 1st generation EPO presenting similarities with the endogenous form, was also in the centre of a similar clinical study. Our work aimed to overcome the actual identification criteria, which are not adapted to Dynpeo, and to propose an alternative pattern classification method based on the discriminant analysis of IEF EPO profiles. This method might be validated for other EPO forms in the future. The detection window of this molecule was also determined. Under particular conditions, confounding effects can complicate the identification of EPO in biological matrices. For example, athletes having performed a strenuous physical effort can excrete modified isoforms of endogenous EPO, making it very similar to some recombinant forms. Such phenomena, called effort urines, were reproduced under controlled conditions and, after characterization of effort EPO, an urinary biochemical marker was proposed to unequivocally identify effort urines. It also happens that EPO analyses fail to detect endogenous levels of EPO. Such profiles were thoroughly investigated and potential causes identified. Natural reasons relying on urine properties and test specificity were underlined, but the possible addition of adulterant agents in urine samples was also considered. Therefore, a simple biochemical assay targeting the suspected substances was set up. Our work was based on the characterization of atypical EPO profiles from different origins. Therefore, 3 EPO molecules representing the 3 generations of the drug and 2 confounding effects confusing the results interpretation were studied. These studies resulted in tangible applications for the laboratory, the best example of which being the C.E.R.A. assay, but also in scientific findings allowing to improve our comprehension of EPO doping in sport.

Smooth muscle differentiation identifies two classes of poorly differentiated pleomorphic sarcomas with distinct outcome.

The clinical relevance of accurately diagnosing pleomorphic sarcomas has been shown, especially in cases of undifferentiated pleomorphic sarcomas with myogenic differentiation, which appear significantly more aggressive. To establish a new smooth muscle differentiation classification and to test its prognostic value, 412 sarcomas with complex genetics were examined by immunohistochemistry using four smooth muscle markers (calponin, h-caldesmon, transgelin and smooth muscle actin). Two tumor categories were first defined: tumors with positivity for all four markers and tumors with no or incomplete phenotypes. Multivariate analysis demonstrated that this classification method exhibited the strongest prognostic value compared with other prognostic factors, including histological classification. Secondly, incomplete or absent smooth muscle phenotype tumor group was then divided into subgroups by summing for each tumor the labeling intensities of all four markers for each tumors. A subgroup of tumors with an incomplete but strong smooth muscle differentiation phenotype presenting an intermediate metastatic risk was thus identified. Collectively, our results show that the smooth muscle differentiation classification method may be a useful diagnostic tool as well as a relevant prognostic tool for undifferentiated pleomorphic sarcomas.

Estimating soybean crop areas using spectral-temporal surfaces derived from MODIS images in Mato Grosso, Brazil

The objective of this work was to evaluate the application of the spectral-temporal response surface (STRS) classification method on Moderate Resolution Imaging Spectroradiometer (MODIS, 250 m) sensor images in order to estimate soybean areas in Mato Grosso state, Brazil. The classification was carried out using the maximum likelihood algorithm (MLA) adapted to the STRS method. Thirty segments of 30x30 km were chosen along the main agricultural regions of Mato Grosso state, using data from the summer season of 2005/2006 (from October to March), and were mapped based on fieldwork data, TM/Landsat-5 and CCD/CBERS-2 images. Five thematic classes were considered: Soybean, Forest, Cerrado, Pasture and Bare Soil. The classification by the STRS method was done over an area intersected with a subset of 30x30-km segments. In regions with soybean predominance, STRS classification overestimated in 21.31% of the reference values. In regions where soybean fields were less prevalent, the classifier overestimated 132.37% in the acreage of the reference. The overall classification accuracy was 80%. MODIS sensor images and the STRS algorithm showed to be promising for the classification of soybean areas in regions with the predominance of large farms. However, the results for fragmented areas and smaller farms were less efficient, overestimating soybean areas.

Detection and chemical profiling of medicine counterfeits by Raman spectroscopy and chemometrics

Raman spectroscopy combined with chemometrics has recently become a widespread technique for the analysis of pharmaceutical solid forms. The application presented in this paper is the investigation of counterfeit medicines. This increasingly serious issue involves networks that are an integral part of industrialized organized crime. Efficient analytical tools are consequently required to fight against it. Quick and reliable authentication means are needed to allow the deployment of measures from the company and the authorities. For this purpose a method in two steps has been implemented here. The first step enables the identification of pharmaceutical tablets and capsules and the detection of their counterfeits. A nonlinear classification method, the Support Vector Machines (SVM), is computed together with a correlation with the database and the detection of Active Pharmaceutical Ingredient (API) peaks in the suspect product. If a counterfeit is detected, the second step allows its chemical profiling among former counterfeits in a forensic intelligence perspective. For this second step a classification based on Principal Component Analysis (PCA) and correlation distance measurements is applied to the Raman spectra of the counterfeits.

On the Condition Monitoring of Induction machines

The research of condition monitoring of electric motors has been wide for several decades. The research and development at universities and in industry has provided means for the predictive condition monitoring. Many different devices and systems are developed and are widely used in industry, transportation and in civil engineering. In addition, many methods are developed and reported in scientific arenas in order to improve existing methods for the automatic analysis of faults. The methods, however, are not widely used as a part of condition monitoring systems. The main reasons are, firstly, that many methods are presented in scientific papers but their performance in different conditions is not evaluated, secondly, the methods include parameters that are so case specific that the implementation of a systemusing such methods would be far from straightforward. In this thesis, some of these methods are evaluated theoretically and tested with simulations and with a drive in a laboratory. A new automatic analysis method for the bearing fault detection is introduced. In the first part of this work the generation of the bearing fault originating signal is explained and its influence into the stator current is concerned with qualitative and quantitative estimation. The verification of the feasibility of the stator current measurement as a bearing fault indicatoris experimentally tested with the running 15 kW induction motor. The second part of this work concentrates on the bearing fault analysis using the vibration measurement signal. The performance of the micromachined silicon accelerometer chip in conjunction with the envelope spectrum analysis of the cyclic bearing faultis experimentally tested. Furthermore, different methods for the creation of feature extractors for the bearing fault classification are researched and an automatic fault classifier using multivariate statistical discrimination and fuzzy logic is introduced. It is often important that the on-line condition monitoring system is integrated with the industrial communications infrastructure. Two types of a sensor solutions are tested in the thesis: the first one is a sensor withcalculation capacity for example for the production of the envelope spectra; the other one can collect the measurement data in memory and another device can read the data via field bus. The data communications requirements highly depend onthe type of the sensor solution selected. If the data is already analysed in the sensor the data communications are needed only for the results but in the other case, all measurement data need to be transferred. The complexity of the classification method can be great if the data is analysed at the management level computer, but if the analysis is made in sensor itself, the analyses must be simple due to the restricted calculation and memory capacity.

Laatupoikkeamienkäsittelyn tehostaminen Olkiluoto 3 -projektissa

Diplomityössä tutustaan Olkiluoto 3-laitoksen suunnittelu- ja rakennusvaiheen aikaisiin laatupoikkeamiin ja niiden käsittelyyn. Työn tavoitteena on paikantaa poikkeamakäsittelyn pahimmat ongelmakohdat, ja kehittää menetelmiä ongelmien ratkaisemiseksi. Diplomityön tutkimusmenetelmänä käytettiin toimintatutkimusta. Tutkimus toteutettiin kevään 2007 aikana havainnoimalla Olkiluoto 3-projektin laadunhallinnan toimintaa ja analysoimalla projektissa syntyneitä poikkeamia. Työn toteuttamisessa tutustuttiin kansallisin ja kansainvälisiin laadunhallinnan standardeihin sekä erityisesti ydinvoima-alaa koskeviin laadunhallinnan ohjeistuksiin. Diplomityön tuloksena kehitettiin menetelmä OL 3-projektin toiminnallisten poikkeamien luokittelemiseksi. Jatkossa luokittelumenetelmää voidaan hyödyntää aiempaa tarkemman poikkeamatiedon analysoinnissa, sisäisessä päätöksenteossa sekä OL 3-projektin tiedotuksessa.

Inhimillisten virheiden tarkastelu ydinvoimalaitosten käyttökokemusten hyödyntämisessä

Tässä työssä on kuvattu ydinvoimalaitosten käyttökokemusten tutkimusta keskittyen erityisesti inhimillisten toimintojen tarkasteluun. Työssä on kerrottu kansainvälisistä vaatimuksista ja järjestöistä sekä yleisesti käyttökokemusten tutkimuksessa käytössä olevista menetelmistä keskittyen perussyyanalyysimenetelmiin. Suomen osalta työssä on käsitelty lainsäädännön asettamia velvoitteita ja muita vaatimuksia, jotka ydinvoima-alalla koostuvat lähinnä Säteilyturvakeskuksen YVL-ohjeista. Viranomaisena toimivan Säteilyturvakeskuksen, alan tutkimusta suorittavan Valtion teknillisen tutkimuskeskuksen ja Teollisuuden Voima Oy:n käyttökokemusten tutkimiseen liittyvät organisaatiot ja menettelytavat on esitelty. Fortum Power and Heat Oy:n omistaman ja käyttämän Loviisan ydinvoimalaitoksen käyttökokemusten hyödyntäminen on käsitelty tarkemmin. Loviisan voimalaitoksen organisaatio ja käyttökokemusten sekä inhimillisten virheiden käsittelymenetelmiä on esitelty ja analysoitu. Työn alkuvaiheessa Loviisan voimalaitoksella inhimillisistä virheistä kerätystä tiedosta koottu tietokanta järjesteltiin kuntoon. Järjestelyn jälkeen tietoa analysoitiin ja analysoinnin tulokset on esitetty tässä työssä. Sekä järjestelyn että analysoinnin aikana havaitut kehityskohteet kirjattiin muistiin. Pienet toimenpiteet suoritettiin heti ja suuremmat kirjattiin tämän työn toimenpide-ehdotuksiin. Kehittämiskeinoja on ehdotettu virheiden luokittelumenetelmään ja käyttökokemusten käsittelymenetelmiin.

Clasificación automática de textos y explotación BI

El presente proyecto tiene como objetivo desarrollar una tecnología que permita codificar grandes cantidades de texto de manera automática para posteriormente ser visualizada y analizada mediante una aplicación diseñada en Qlikview. El motor de la investigación e implementación de este proyecto se ha encontrado en la incipiente presencia de tecnologías informáticas en los procesos de codificación para ciencias políticas. De esta manera, el programa creado tiene como objetivo automatizar un proceso que se desarrolla comúnmente de manera manual y, por ende, las ventajas de introducir técnicas informáticas son notablemente valiosas. Estas automatizaciones permiten ahorrar tanto en tiempo de codificación, como en recursos económicos o humanos. Se ha elaborado una revisión teórica y metodológica que han servido como instrumentos de estudio y mejora, con el firme propósito de reducir al máximo el margen de error y ofrecer un instrumento de calidad con salida de mercado real. El método de clasificación utilizado ha sido Bayes, y se ha implementado utilizando Matlab. Los resultados de la clasificación han llegado a índices del 99.2%. En la visualización y análisis mediante Qlikview se pueden modificar los parámetros referentes a partido político, año, categoría o región, con lo que se permite analizar numerosos aspectos relacionados con la distribución de las palabras repartidas entre las diferentes categorías y en el tiempo.

Rakennukset ja rakentajat Raision Ihalassa rautakauden lopulla ja varhaisella keskiajalla

Turun yliopiston arkeologian oppiaine tutki Raision Ihalan historiallisella kylätontilla, ns. Mullin eduspellolla, asuinpaikan, josta löydettiin maamme oloissa harvinaisen hyvin säilyneitä rakennusten puuosien jäännöksiä. Löytö on ainutlaatuinen Suomen oloissa ja sillä on kansainvälistäkin merkitystä, koska hyvin säilyneet myöhemmän rautakauden ja varhaisen keskiajan maaseutuasuinpaikat, joista tavataan puujäännöksiä, ovat harvinaisia erityisesti itäisen Itämeren piirissä. Rakennukset on ennallistettu käyttäen tiukkaa paikallisen analogian (’Tight Local Analogy’) metodia, erityisesti suoraa historiallista analogista lähestymistapaa. Tätä tarkoitusta varten muodostettiin aluksi arkeologinen, historiallinen ja etnografinen lähdemalli. Tämä valittiin maantieteellisesti ja ajallisesti relevantista tutkimusaineistosta pohjoisen Itämeren piiristä. Tiedot lounaisen Suomen rakennuksista ja rakennusteknologiasta katsottiin olevan tärkein osa mallia johtuen historiallisesta ja spatiaalisesta jatkuvuudesta. Lähdemalli yhdistettiin sitten Mullin arkeologiseen aineistoon ja analyysin tuloksena saatiin rakennusten ennallistukset. Mullista on voitu ennallistaa ainakin kuusi eri rakennusta neljässä eri rakennuspaikassa. Rakennusteknologia perustui kattoa kannattaviin horisontaalisiin pitkiin seinähirsiin, jotka oli nurkissa yhdistetty joko salvoksella tai varhopatsaalla. Kaikissa rakennuksissa ulkoseinän pituus oli 5 – 7 metriä. Löydettiin lisäksi savi- ja puulattioita sekä kaksi tulisijaa, savikupoliuuni ja avoin liesi. Runsaan palaneen saven perusteella on mahdollista päätellä, että katto oli mitä todennäköisimmin kaksilappeinen vuoliaiskatto, joka oli katettu puulla ja/tai turpeella. Kaikki rakennukset olivat samaa tyyppiä ja ne käsittivät isomman huoneen ja kapean eteisen. Kaikki analysoitu puu oli mäntyä. Ulkoalueelta tavattiin lisäksi tunkioita, ojia, aitoja ja erilaisia varastokuoppia. Rakennukset on ajoitettu 900-luvun lopulta 1200-luvun lopulle (cal AD). Lopuksi tutkittiin rakennuksia yhteisöllisessä ympäristössään, niiden ajallista asemaa sekä asukkaiden erilaisia spatiaalisia kokemuksia ja yhteyksiä. Raision Ihalaa analysoidaan sosiaalisen identiteetin ja sen materiaalisten ilmenemismuotojen kautta. Nämä sosiaaliset identiteetit muodostuvat kommunikaatioverkostoista eri spatiaalisilla ja yhteisöllisillä ta¬soilla. Näitä eri tasoja ovat: 1) kotitalous arjen toimintoineen, perhe ja sukulaisuussuhteet traditioineen; 2) paikallinen identiteetti, rakennus, rakennuspaikka, asuinpaikan ympäristö ja sen käyttö, (maa)talo ja kylä; 3) Raision Ihalan kylä laajemmassa alueellisessa kontekstissaan pohjoisen Itämeren piirissä: kauppiaiden ja käsityöläisten kontaktiverkostot, uskonnollinen identiteetti ja sen muutokset.

ContinuousMultimodal Global Optimization with Differential Evolution-Based Methods

Metaheuristic methods have become increasingly popular approaches in solving global optimization problems. From a practical viewpoint, it is often desirable to perform multimodal optimization which, enables the search of more than one optimal solution to the task at hand. Population-based metaheuristic methods offer a natural basis for multimodal optimization. The topic has received increasing interest especially in the evolutionary computation community. Several niching approaches have been suggested to allow multimodal optimization using evolutionary algorithms. Most global optimization approaches, including metaheuristics, contain global and local search phases. The requirement to locate several optima sets additional requirements for the design of algorithms to be effective in both respects in the context of multimodal optimization. In this thesis, several different multimodal optimization algorithms are studied in regard to how their implementation in the global and local search phases affect their performance in different problems. The study concentrates especially on variations of the Differential Evolution algorithm and their capabilities in multimodal optimization. To separate the global and local search search phases, three multimodal optimization algorithms are proposed, two of which hybridize the Differential Evolution with a local search method. As the theoretical background behind the operation of metaheuristics is not generally thoroughly understood, the research relies heavily on experimental studies in finding out the properties of different approaches. To achieve reliable experimental information, the experimental environment must be carefully chosen to contain appropriate and adequately varying problems. The available selection of multimodal test problems is, however, rather limited, and no general framework exists. As a part of this thesis, such a framework for generating tunable test functions for evaluating different methods of multimodal optimization experimentally is provided and used for testing the algorithms. The results demonstrate that an efficient local phase is essential for creating efficient multimodal optimization algorithms. Adding a suitable global phase has the potential to boost the performance significantly, but the weak local phase may invalidate the advantages gained from the global phase.

Mapping of summer crops in the State of Paraná, Brazil, through the 10-day spot vegetation NDVI composites

The search for low subjectivity area estimates has increased the use of remote sensing for agricultural monitoring and crop yield prediction, leading to more flexibility in data acquisition and lower costs comparing to traditional methods such as census and surveys. Low spatial resolution satellite images with higher frequency in image acquisition have shown to be adequate for cropland mapping and monitoring in large areas. The main goal of this study was to map the Summer crops in the State of Paraná, Brazil, using 10-day composition of NDVI SPOT Vegetation data for 2005/2006, 2006/2007 and 2007/2008 cropping seasons. For this, a supervised digital classification method with Parallelepiped algorithm in multitemporal RGB image composites was used, in order to generate masks of Summer cultures for each 10-day composition. Accuracy assessment was performed using Kappa index, overall accuracy and Willmott's concordance index, resulting in good levels of accuracy. This methodology allowed the accomplishment, with free and low resolution data, of the mapping of Summer cultures at State level.

Sekajätteen koostumustutkimusten luokitteluohjeen päivittäminen ja testaaminen

Tässä diplomityössä päivitettiin ja testattiin sekajätteen koostumustutkimuksiin tarkoitettua jätejakeiden luokitteluohjetta. Työn tavoitteena oli selvittää, miten luokitteluohje vastaa jätelainsäädännön muutoksiin ja tavoitteisiin, miten ohje toimii käytännössä sekä miten luokitteluohjetta tulee päivittää, jotta se sekä vastaa jätelainsäädännön ja jätealan toimijoiden tietotarpeisiin sekajätteen koostumuksesta että toimii myös käytännössä. Työssä toteutettiin kyselytutkimus ja kaksi sekajätteen koostumustutkimusta. Jätealan toimijoille lähetetyn kyselyn avulla kartoitettiin luokitteluohjeen kehityskohtia. Kyselytutkimuksen vastaajat kokivat, että luokitteluohjeessa on eniten kehitettävää muovien luokittelussa. Muovien luokittelun lisäksi biojätteen sekä kierrätettävien ja vaarallisten jätteiden luokitteluun liittyvät mahdolliset kehityskohdat muodostettiin kyselyn vastausten perusteella. Sekajätteen koostumustutkimusten avulla testattiin luokitteluohjeen toimivuutta. Koostumustutkimukset toteutettiin ohjeen tarkimman tason mukaisesti. Jätteiden lajittelu osoittautui huomattavasti hitaammaksi kuin etukäteen oli arvioitu. Lisäksi monia materiaaleja sisältävien jätteiden lajittelu oli haasteellista molemmissa tutkimuksissa. Luokitteluohjetta päivitettiin kyselytutkimuksen ja koostumustutkimusten perusteella. Jätteet on luokiteltu päivitetyssä ohjeessa alkuperäisen ohjeen tavoin jätemateriaalien perusteella. Luokitteluohjetta päivitettiin jäteluokkien termistön sekä keittiöjätteen ja kierrätettävien jätteiden luokittelun osalta. Päivitetyn ohjeen avulla koostumustutkimuksen toteuttaja saa enemmän tietoa sekajätteestä biojätteen sekä kierrätettävien jätteiden osalta, mikä on tärkeää jätelainsäädännöllisten tavoitteiden kannalta.

Finding Methods for Recognizing and Classifying Spare Part Criticality – Case Full Deposit Stripping Machines

The aim of this Master’s thesis is to find a method for classifying spare part criticality in the case company. Several approaches exist for criticality classification of spare parts. The practical problem in this thesis is the lack of a generic analysis method for classifying spare parts of proprietary equipment of the case company. In order to find a classification method, a literature review of various analysis methods is required. The requirements of the case company also have to be recognized. This is achieved by consulting professionals in the company. The literature review states that the analytic hierarchy process (AHP) combined with decision tree models is a common method for classifying spare parts in academic literature. Most of the literature discusses spare part criticality in stock holding perspective. This is relevant perspective also for a customer orientated original equipment manufacturer (OEM), as the case company. A decision tree model is developed for classifying spare parts. The decision tree classifies spare parts into five criticality classes according to five criteria. The criteria are: safety risk, availability risk, functional criticality, predictability of failure and probability of failure. The criticality classes describe the level of criticality from non-critical to highly critical. The method is verified for classifying spare parts of a full deposit stripping machine. The classification can be utilized as a generic model for recognizing critical spare parts of other similar equipment, according to which spare part recommendations can be created. Purchase price of an item and equipment criticality were found to have no effect on spare part criticality in this context. Decision tree is recognized as the most suitable method for classifying spare part criticality in the company.

Hyperspectral Mineral Identification using SVM and SOM

Remote sensing techniques involving hyperspectral imagery have applications in a number of sciences that study some aspects of the surface of the planet. The analysis of hyperspectral images is complex because of the large amount of information involved and the noise within that data. Investigating images with regard to identify minerals, rocks, vegetation and other materials is an application of hyperspectral remote sensing in the earth sciences. This thesis evaluates the performance of two classification and clustering techniques on hyperspectral images for mineral identification. Support Vector Machines (SVM) and Self-Organizing Maps (SOM) are applied as classification and clustering techniques, respectively. Principal Component Analysis (PCA) is used to prepare the data to be analyzed. The purpose of using PCA is to reduce the amount of data that needs to be processed by identifying the most important components within the data. A well-studied dataset from Cuprite, Nevada and a dataset of more complex data from Baffin Island were used to assess the performance of these techniques. The main goal of this research study is to evaluate the advantage of training a classifier based on a small amount of data compared to an unsupervised method. Determining the effect of feature extraction on the accuracy of the clustering and classification method is another goal of this research. This thesis concludes that using PCA increases the learning accuracy, and especially so in classification. SVM classifies Cuprite data with a high precision and the SOM challenges SVM on datasets with high level of noise (like Baffin Island).