Prevalence of hypertension in schoolchildren based on repeated measurements and association with overweight.

OBJECTIVE: Most studies assess the prevalence of hypertension in pediatric populations based on blood pressure (BP) readings taken on a single visit. We determined the prevalence of hypertension measured on up to three visits in a Swiss pediatric population and examined the association between hypertension and overweight and selected other factors. METHODS: Anthropometric data and BP were measured in all children of the sixth school grade of the Vaud canton (Switzerland) in 2005-2006. 'Elevated BP' was defined according to sex-specific, age-specific and height-specific US reference data. BP was measured on up to two additional visits in children with elevated BP. 'Hypertension' was defined as 'elevated BP' on all three visits. RESULTS: Out of 6873 children, 5207 (76%) participated [2621 boys, 2586 girls; mean (SD) age, 12.3 (0.5) years]. The prevalence of elevated BP was 11.4, 3.8 and 2.2% on first, second and thirds visits, respectively; hence 2.2% had hypertension. Among hypertensive children, 81% had isolated systolic hypertension. Hypertension was associated with excess body weight, elevated heart rate and parents' history of hypertension. Of the children, 16.1% of boys and 12.4% of girls were overweight or obese (CDC criteria, body mass index >or= 85th percentile). Thirty-seven percent of cases of hypertension could be attributed to overweight or obesity. CONCLUSIONS: The proportion of children with elevated BP based on one visit was five times higher than based on three measurements taken at few-week intervals. Our data re-emphasize the need for prevention and control of overweight in children to curb the global hypertension burden.

Ambient intelligence application based on environmental measurements performed with an assistant mobile robot

This paper proposes the use of an autonomous assistant mobile robot in order to monitor the environmental conditions of a large indoor area and develop an ambient intelligence application. The mobile robot uses single high performance embedded sensors in order to collect and geo-reference environmental information such as ambient temperature, air velocity and orientation and gas concentration. The data collected with the assistant mobile robot is analyzed in order to detect unusual measurements or discrepancies and develop focused corrective ambient actions. This paper shows an example of the measurements performed in a research facility which have enabled the detection and location of an uncomfortable temperature profile inside an office of the research facility. The ambient intelligent application has been developed by performing some localized ambient measurements that have been analyzed in order to propose some ambient actuations to correct the uncomfortable temperature profile.

Ympäristövaikutusten velvoitetarkkailun tulosten epävarmuuden arviointi

Tämä diplomityö tehtiin Neste Oil Oyj:n Kehittäminen ja Laboratoriot yksikön HSE-palveluille. Työn tavoitteena oli arvioida Neste Oilin ympäristövaikutusten velvoitetarkkailujen mittaustulosten epävarmuutta. Tarkastelu koski ilmanlaadun SO2-, NO2-, TRS- sekä O3-mittauksia, ympäristömelumittauksia sekä pohjavesinäytteenottoa. Ympäristönsuojelulaki (86/2000) velvoittaa tuotantolaitoksia selvittämään toimintansa ympäristövaikutukset. Myös esimerkiksi akkreditoitaessa menetelmiä mittausepävarmuus on tunnettava. On arvioitu, että tulevaisuudessa direktiivit tulevat tiukentamaan päästöraja-arvoja ja mittausepävarmuuden käsite tulee käyttöön kaikilla ympäristösektoreilla.Tässä työssä ilmanlaadun mittausepävarmuus arvioitiin vertaamalla Neste Oilin mittaustuloksia Ilmatieteenlaitoksen vertailumittausten ja kalibrointien tuloksiin. Ympäristömelun mittausepävarmuus arvioitiin Ympäristöministeriön ympäristömelunmittausohjeen (1/1995)mukai-sesti. Pohjavesinäytteenoton mittausepävarmuus arvioitiin laskemalla haitta-aineiden ajallisen vaihtelun, näytteenottomenetelmien, näytteiden kuljetuksenja säilytyksen aiheuttaman kontaminaation sekä analyysivaiheen epävarmuustekijöiden yhdistetty mittausepävarmuus. Tarkastelussa todettiin, että ilmanlaadunmittaustulokset eivät poikenneet merkittävästi vertai-lumittausten ja kalibrointien tuloksista. Menetelmien laajennetuksi mittausepävarmuudeksi saatiin 6-8 %. Ympäristömelun mittausepävarmuus vastasi ympäristömelunmittausohjeessa esitettyjä arvoja ja vaihtelivat 2-10 dB:n välillä, riippuen mittausetäisyydestä ja mittauskertojen lukumäärästä. Pohjavesinäytteenoton mittausepävarmuudelle ei ole asetettu laatutavoitteita. Tässä tarkastelussa pohjavesinäytteenoton mittausepävarmuudeksi saatiin 33 %.

Use of field measurements in fatigue analysis of forestry cranes

Tässä työssä on esitetty väsyttävän kuormituksen mittaamiseen ja mittausdatan jälkikäsittelyyn sekä väsymismitoitukseen liittyviä menetelmiä. Menetelmien sovelluskohteena oli metsäkoneen kuormain, joka on väsyttävästi kuormitettu hitsattu rakenne. Teoriaosassa on kuvattu väsymisilmiötä ja väsymismitoitusmenetelmiä sekä kuormitusten tunnistamiseen ja mittausten jälkikäsittelyyn liittyviä menetelmiä. Yleisimmin käytettyjen väsymismitoitusmenetelmien rinnalle on esitetty luotettavuuteen perustuvaa väsymismitoitusmenetelmää. Kuormainten suunnittelussa on keveys- j a kestoikävaatimusten takia erityisen suuri merkitys väsymisen huomioimisella. Rakenteille on ominaista tietyt toiminnan kannalta välttämättömät hitsatut yksityiskohdat, jotka usein määräävät koko rakenteen kestoiän. Koska nämä ongelmakohdat pystytään useimmiten tunnistamaan jo suunnitteluvaiheessa, voidaan yksityiskohtien muotoilulla usein parantaa huomattavasti koko rakenteen kestoikää. Näiden yksityiskohtien optimointi on osittain mahdollista toteuttaa ilman kuormituskertymätietoa, mutta useimmiten kuormitusten tunnistaminen on edellytys parhaan ratkaisun löytymiselle. Tällöin toistaiseksi paras keino todellisen väsyttävän kuormituksen tunnistamiseksi on pitkäaikaiset kenttämittaukset. Kenttämittauksilla selvitetään rakenteeseen kohdistuvat kuormitukset venymäliuskojen avulla. Kuormitusten tunnistamisella on erityisen suuri merkitys kun halutaan määrittää rakenteen kestoikä. Väsyminen ja väsyttävä kuormitus ovat kuitenkin tilastollisia muuttujia j a yksittäiselle rakenteelle ei ole mahdollista määrittää tarkkaa k estoikää. Tilastollisia menetelmiä käyttäen on kuitenkin mahdollista määrittää rakenteen vaurioitumisriski. Laskettaessa vaurioitumisriskiä suurelle määrälle yksittäisiä rakenteita voidaan muodostaa tarkkojakin ennusteita mahdollisten vaurioiden lukumäärästä. Tällöin kuormituskertymätiedosta voi olla tavanomaisen suunnittelun lisäksi laajempaa hyötyä esimerkiksi takuukäsittelyssä. Tässä työssä on sovellettu esitettyjä teorioita käytännössä metsäkoneen harvesterin puomiston väsymistarkasteluun. Kyseisen rakenteen kuormituksia mitattiin kahden viikon aikana yhteensä 35 tuntia, jonka perusteella laskettiin väsyttävän kuormituksen tilastollinen jakauma esimerkkitapaukselle. Mittauksen perusteella ei voitu tehdä kuitenkaan johtopäätöksiä tuotteen koko elinkaaren kuormituksista eikä muiden samanlaisten tuotteiden kuormituksista, koska mitattu otos oli suhteellisen lyhyt ja rajoittui vain yhteen käyttäjään ja muutamaan käyttökohteeseen. Menetelmien testaamiseksi kyseinen otos oli kuitenkin riittävä. Kuormituskertymätietoa käytettiin hyväksi myös laatumääritysten muodostamisessaesimerkkitapaukselle. Murtumismekaniikkaan perustuvalla menetelmällä arvioitiinharvesteripilarin valun mahdollisten valuvirheiden suurin sallittu koko. Luotettavuuteen pohjautuvan mitoitusmenettelyn tarve näyttää olevanlisääntymässä, joten pitkäaikaisten kenttämittausten tehokas hyödyntäminen tulee olemaan keskeinen osa väsymismitoitusta lähitulevaisuudessa. Menetelmiä olisi mahdollista tehostaa yhdistämällä kuormituskertymään erilaisia kuormitusten suhteen riippuvia tunnettuja suureita kuten käsiteltävän puun halkaisija. Todellisettuotekohtaiset tilastolliset jakaumat kuormituksista voitaisiin muodostaa mahdollisesti tehokkaammin, jos esimerkiksi kuormitusten riippuvuus metsätyypistä pystyttäisiin ensin määrittämään.

Evaluation and comparison of current fetal ultrasound image segmentation methods for biometric measurements: a grand challenge.

This paper presents the evaluation results of the methods submitted to Challenge US: Biometric Measurements from Fetal Ultrasound Images, a segmentation challenge held at the IEEE International Symposium on Biomedical Imaging 2012. The challenge was set to compare and evaluate current fetal ultrasound image segmentation methods. It consisted of automatically segmenting fetal anatomical structures to measure standard obstetric biometric parameters, from 2D fetal ultrasound images taken on fetuses at different gestational ages (21 weeks, 28 weeks, and 33 weeks) and with varying image quality to reflect data encountered in real clinical environments. Four independent sub-challenges were proposed, according to the objects of interest measured in clinical practice: abdomen, head, femur, and whole fetus. Five teams participated in the head sub-challenge and two teams in the femur sub-challenge, including one team who tackled both. Nobody attempted the abdomen and whole fetus sub-challenges. The challenge goals were two-fold and the participants were asked to submit the segmentation results as well as the measurements derived from the segmented objects. Extensive quantitative (region-based, distance-based, and Bland-Altman measurements) and qualitative evaluation was performed to compare the results from a representative selection of current methods submitted to the challenge. Several experts (three for the head sub-challenge and two for the femur sub-challenge), with different degrees of expertise, manually delineated the objects of interest to define the ground truth used within the evaluation framework. For the head sub-challenge, several groups produced results that could be potentially used in clinical settings, with comparable performance to manual delineations. The femur sub-challenge had inferior performance to the head sub-challenge due to the fact that it is a harder segmentation problem and that the techniques presented relied more on the femur's appearance.

Development of the Acoustic Emission Based Diagnostics Concept for the Rotary Lime Kiln

Reaaliaikainen, ennakoiva kunnonvalvonta on erittäin tärkeä osa modernin tehtaan tai tuotantolinjan toimintaa. Diplomityön teettäjä haluaa edelleen kehittää akustiseen emissioon perustuvaa kunnonvalvonta järjestelmäänsä, jotta siitä olisi enemmän hyötyä asiakkaalle. Diplomityö sisältää johdannonakustiseen emissioon ja akustisiin emissio sensoreihin. Työn tavoitteena oli kehittää päätöksentekojärjestelmä, jota käytettäisiin työn teettäjän valmistamien sensoreiden antaman tiedon automatisoituun analysointiin. Työssä on vertailtu kolmea eri ohjelmistotoimittajaa ja heidän ohjelmiaan, ja tehty ehdotus hankittavasta ohjelmistosta. Lisäksi työssä on kehitetty ohjeita, joiden avulla ohjelmisto ohjelmoidaan tuottamaan reaaliaikaista tietoa ja huolto-ohjeita sen käyttäjille. Lisäksi työssä annetaan ehdotuksia kunnonvalvonta- ja päätöksentekojärjestelmän edelleen kehittämiseen.

Deep-hole drilling process, monitoring system and sensors modifications

 In the drilling processes and especially deep-hole drilling process, the monitoring system and having control on mechanical parameters (e.g. Force, Torque,Vibration and Acoustic emission) are essential. The main focus of this thesis work is to study the characteristics of deep-hole drilling process, and optimize the monitoring system for controlling the process. The vibration is considered as a major defect area of the deep-hole drilling process which often leads to breakage of the drill, therefore by vibration analysis and optimizing the workpiecefixture, this area is studied by finite element method and the suggestions are explained. By study on a present monitoring system, and searching on the new sensor products, the modifications and recommendations are suggested for optimize the present monitoring system for excellent performance in deep-hole drilling process research and measurements.

Optimization of the procedure for removing iron deposits on ceramic filter media

In this thesis, cleaning of ceramic filter media was studied. Mechanisms of fouling and dissolution of iron compounds, as well as methods for cleaning ceramic membranes fouled by iron deposits were studied in the literature part. Cleaning agents and different methods were closer examined in the experimental part of the thesis. Pyrite is found in the geologic strata. It is oxidized to form ferrous ions Fe(II) and ferric ions Fe(III). Fe(III) is further oxidized in the hydrolysis to form ferric hydroxide. Hematite and goethite, for instance, are naturally occurring iron oxidesand hydroxides. In contact with filter media, they can cause severe fouling, which common cleaning techniques competent enough to remove. Mechanisms for the dissolution of iron oxides include the ligand-promoted pathway and the proton-promoted pathway. The dissolution can also be reductive or non-reductive. The most efficient mechanism is the ligand-promoted reductive mechanism that comprises two stages: the induction period and the autocatalytic dissolution.Reducing agents(such as hydroquinone and hydroxylamine hydrochloride), chelating agents (such as EDTA) and organic acids are used for the removal of iron compounds. Oxalic acid is the most effective known cleaning agent for iron deposits. Since formulations are often more effective than organic acids, reducing agents or chelating agents alone, the citrate¿bicarbonate¿dithionite system among others is well studied in the literature. The cleaning is also enhanced with ultrasound and backpulsing.In the experimental part, oxalic acid and nitric acid were studied alone andin combinations. Also citric acid and ascorbic acid among other chemicals were tested. Soaking experiments, experiments with ultrasound and experiments for alternative methods to apply the cleaning solution on the filter samples were carried out. Permeability and ISO Brightness measurements were performed to examine the influence of the cleaning methods on the samples. Inductively coupled plasma optical emission spectroscopy (ICP-OES) analysis of the solutions was carried out to determine the dissolved metals.

Self-Organising Maps and Correlation Analysis as a Tool to Explore Patterns in Excitation-Emission Matrix Data Sets and to Discriminate Dissolved Organic Matter Fluorescence Components

Dissolved organic matter (DOM) is a complex mixture of organic compounds, ubiquitous in marine and freshwater systems. Fluorescence spectroscopy, by means of Excitation-Emission Matrices (EEM), has become an indispensable tool to study DOM sources, transport and fate in aquatic ecosystems. However the statistical treatment of large and heterogeneous EEM data sets still represents an important challenge for biogeochemists. Recently, Self-Organising Maps (SOM) has been proposed as a tool to explore patterns in large EEM data sets. SOM is a pattern recognition method which clusterizes and reduces the dimensionality of input EEMs without relying on any assumption about the data structure. In this paper, we show how SOM, coupled with a correlation analysis of the component planes, can be used both to explore patterns among samples, as well as to identify individual fluorescence components. We analysed a large and heterogeneous EEM data set, including samples from a river catchment collected under a range of hydrological conditions, along a 60-km downstream gradient, and under the influence of different degrees of anthropogenic impact. According to our results, chemical industry effluents appeared to have unique and distinctive spectral characteristics. On the other hand, river samples collected under flash flood conditions showed homogeneous EEM shapes. The correlation analysis of the component planes suggested the presence of four fluorescence components, consistent with DOM components previously described in the literature. A remarkable strength of this methodology was that outlier samples appeared naturally integrated in the analysis. We conclude that SOM coupled with a correlation analysis procedure is a promising tool for studying large and heterogeneous EEM data sets.

High-performance liquid chromatography of the renal blood flow marker p-aminohippuric acid (PAH) and its metabolite N-acetyl PAH improves PAH clearance measurements.

PAH (N-(4-aminobenzoyl)glycin) clearance measurements have been used for 50 years in clinical research for the determination of renal plasma flow. The quantitation of PAH in plasma or urine is generally performed by colorimetric method after diazotation reaction but the measurements must be corrected for the unspecific residual response observed in blank plasma. We have developed a HPLC method to specifically determine PAH and its metabolite NAc-PAH using a gradient elution ion-pair reversed-phase chromatography with UV detection at 273 and 265 nm, respectively. The separations were performed at room temperature on a ChromCart (125 mmx4 mm I.D.) Nucleosil 100-5 microm C18AB cartridge column, using a gradient elution of MeOH-buffer pH 3.9 1:99-->15:85 over 15 min. The pH 3.9 buffered aqueous solution consisted in a mixture of 375 ml sodium citrate-citric acid solution (21.01 g citric acid and 8.0 g NaOH per liter), added up with 2.7 ml H3PO4 85%, 1.0 g of sodium heptanesulfonate and completed ad 1000 ml with ultrapure water. The N-acetyltransferase activity does not seem to notably affect PAH clearances, although NAc-PAH represents 10.2+/-2.7% of PAH excreted unchanged in 12 healthy subjects. The performance of the HPLC and the colorimetric method have been compared using urine and plasma samples collected from healthy volunteers. Good correlations (r=0.94 and 0.97, for plasma and urine, respectively) are found between the results obtained with both techniques. However, the colorimetric method gives higher concentrations of PAH in urine and lower concentrations in plasma than those determined by HPLC. Hence, both renal (ClR) and systemic (Cls) clearances are systematically higher (35.1 and 17.8%, respectively) with the colorimetric method. The fraction of PAH excreted by the kidney ClR/ClS calculated from HPLC data (n=143) is, as expected, always <1 (mean=0.73+/-0.11), whereas the colorimetric method gives a mean extraction ratio of 0.87+/-0.13 implying some unphysiological values (>1). In conclusion, HPLC not only enables the simultaneous quantitation of PAH and NAc-PAH, but may also provide more accurate and precise PAH clearance measurements.

Prediction of rabbit meat and bone weight using measurements and sample cuts

Regression equations predicting dissectable muscle weight in rabbits from external measurements were presented. Bone weight and weight of muscle groups were also carcass predicted. Predictive capacity of external measurements, retail cuts and muscle groups on total muscle, percent muscle, total bone and muscle to bone ratio were studied separately. Measurements on dissected retail cuts should be included in ordcr to obtain good equations for prediction of percent muscle in the carcass. Equations for predicting the muscle to bone ratio using external mcasurcments and data from the dissection of one hind leg were suggested. The equations had generally high coefficients of determination. The coefficient of determination for prediction of dissectable muscle was 0.91, and for percent muscle in the carcass 0.79.

Characterisation of the LMS200 laser beam under the influence of blockage surfaces. Influence on 3D scanning of tree orchards

The geometric characterisation of tree orchards is a high-precision activity comprising the accurate measurement and knowledge of the geometry and structure of the trees. Different types of sensors can be used to perform this characterisation. In this work a terrestrial LIDAR sensor (SICK LMS200) whose emission source was a 905-nm pulsed laser diode was used. Given the known dimensions of the laser beam cross-section (with diameters ranging from 12 mm at the point of emission to 47.2 mm at a distance of 8 m), and the known dimensions of the elements that make up the crops under study (flowers, leaves, fruits, branches, trunks), it was anticipated that, for much of the time, the laser beam would only partially hit a foreground target/object, with the consequent problem of mixed pixels or edge effects. Understanding what happens in such situations was the principal objective of this work. With this in mind, a series of tests were set up to determine the geometry of the emitted beam and to determine the response of the sensor to different beam blockage scenarios. The main conclusions that were drawn from the results obtained were: (i) in a partial beam blockage scenario, the distance value given by the sensor depends more on the blocked radiant power than on the blocked surface area; (ii) there is an area that influences the measurements obtained that is dependent on the percentage of blockage and which ranges from 1.5 to 2.5 m with respect to the foreground target/object. If the laser beam impacts on a second target/object located within this range, this will affect the measurement given by the sensor. To interpret the information obtained from the point clouds provided by the LIDAR sensors, such as the volume occupied and the enclosing area, it is necessary to know the resolution and the process for obtaining this mesh of points and also to be aware of the problem associated with mixed pixels.