Skeletal, Dental and Soft Tissue Cephalometric Changes after Orthodontic Treatment of Dental Class II Malocclusion with Maxillary First Molar or First Premolar Extractions.

The aim of the present retrospective study was evaluating skeletal, dental and soft tissue changes of two groups of Class II patients orthodontically treated with extractions of upper first premolars (U4 group) and upper first molars (U6 group). In total, 21 patient records (9M and 12F; mean age 12.5 ± 1.2 years) were selected for the U4 group, and 38 patient records (17M and 21F; mean age 13.2 ± 1.3 years) were recruited for the U6 group. Twenty cephalometric variables were analysed on standardised lateral cephalograms at baseline (T0) and at the end of orthodontic treatment (T1). Means and standard deviations (SDs) were calculated for both groups and increments were calculated. After revealing the normal distribution of data with the Shapiro-Wilk test, Student's t-test was used to compare variables at T0 between groups. A paired t-test was used to analyse changes between time points within each group, and Student's t-test to compare differences between groups at T1. Both groups showed a significant increase in the distance among upper second molars and the vertical pterygoid line (PTV-maxillary second molar centroid U6 group: 6.66 ± 5.00 mm; U4 group: 3.66 ± 2.20 mm). Moreover, the distance of upper incisors to the palatal plane significantly increased (PP-maxillary incisor tip U6 group: 1.09 ± 1.52 mm; U4 group: 0.20 ± 2.00 mm; p = 0.061). Significant changes were found for overjet (U6 group: -4.86 ± 1.62 mm; U4 group: -3.27 ± 1.90 mm; p = 0.001). The distance between upper lip and esthetic plane showed a significantly reduction in both groups (ULip-E Plane U6 group: -2.98 ± 1.65 mm; U4 group: -1.93 ± 1.57 mm). No statistically significant changes were found in sagittal or vertical skeletal values. The significantly larger reduction of upper lip protrusion and overjet in the U6 group compared to the U4 group suggests preferring molar extraction treatment for severe Class II with protrusive soft tissues' profile and increased overjet. Since no differences on vertical values were found, an increased SN^GoGn angle should not be considered a discriminating factor for choosing molar extraction treatment

Class II Division 1 malocclusion treatment with extraction of maxillary first molars:Evaluation of treatment and post-treatment changes by the PAR Index

OBJECTIVE To investigate occlusal result and post-treatment changes after orthodontic extraction of maxillary first permanent molars in patients with a Class II division 1 malocclusion. SETTING AND SAMPLE Retrospective longitudinal study in a private practice, with outcome evaluation by an independent academic hospital. Ninety-six patients (53 males, 43 females) consecutively treated by one orthodontist with maxillary first permanent molar extraction were studied, divided into three facial types, based on pre-treatment cephalometric values: hypodivergent (n = 18), normodivergent (n = 21) and hyperdivergent (n = 57). METHODS Occlusal outcome was scored on dental casts at T1 (pre-treatment), T2 (post-treatment) and T3 (mean follow-up 2.5 ± 0.9 years) using the weighted Peer Assessment Rating (PAR) Index. The paired sample t test and one-way ANOVA followed by Tukey's post hoc test were used for statistical analysis. RESULTS PAR was reduced by 95.7% and 89.9% at T2 and T3, respectively, compared with the start of treatment. The largest post-treatment changes were found for overjet and buccal occlusion. Linear regression analysis did not reveal a clear effect (R-Square 0.074) of age, sex, PAR score at T1, incremental PAR score T2-T1, overjet and overbite at T1, and facial type on the changes after treatment (incremental PAR score T3-T2). CONCLUSIONS The occlusal outcome achieved after Class II division 1 treatment with maxillary first permanent molar extractions was maintained to a large extent over a mean post-treatment follow-up of 2.5 years. Limited changes after treatment were found, for which no risk factors could be discerned

Nearshore wave forecasting and hindcasting by dynamical and statistical downscaling

A high-resolution nested WAM/SWAN wave model suite aimed at rapidly establishing nearshore wave forecasts as well as a climatology and return values of the local wave conditions with Rapid Enviromental Assessment (REA) in mind is described. The system is targeted at regions where local wave growth and partial exposure to complex open-ocean wave conditions makes diagnostic wave modelling difficult. SWAN is set up on 500 m resolution and is nested in a 10 km version of WAM. A model integration of more than one year is carried out to map the spatial distribution of the wave field. The model correlates well with wave buoy observations (0.96) but overestimates the wave height somewhat (18%, bias 0.29 m). To estimate wave height return values a much longer time series is required and running SWAN for such a period is unrealistic in a REA setting. Instead we establish a direction-dependent transfer function between an already existing coarse open-ocean hindcast dataset and the high-resolution nested SWAN model. Return values are estimated using ensemble estimates of two different extreme-value distributions based on the full 52 years of statistically downscaled hindcast data. We find good agreement between downscaled wave height and wave buoy observations. The cost of generating the statistically downscaled hindcast time series is negligible and can be redone for arbitrary locations within the SWAN domain, although the sectors must be carefully chosen for each new location. The method is found to be well suited to rapidly providing detailed wave forecasts as well as hindcasts and return values estimates of partly sheltered coastal regions.Comment: 20 pages, 7 figures and 2 tables, MREA07 special issue on Marine rapid environmental assessmen

5G Fieldlab Rural Drenthe : duurzame en autonome onkruidbestrijding

Boeren kijken al een aantal jaren met een schuin oog naar robots om de saaie, herhaaldelijke en soms zware taken van hen over te nemen. Aardappelopslagbestrijding, een relatief simpele maar saaie taak, is één van de taken die boeren graag aan een autonome robot zouden overdragen. Robots om deze taak uit te voeren moesten telkens opgeven omdat het detecteren van aardappelopslagplanten in een suikerbietengewas voor de computer erg lastig bleek. Door state-of-the-art deep learning technologieën toe te passen is WUR er nu wel in geslaagd een robuust detectiealgoritme te bouwen. Vanuit een demo op de kleine Husky robot is gewerkt naar een 3 meter brede, autonome toepassing op de Robotti robot. De rekenintensieve operatie van het herkennen van aardappelopslag- en suikerbietenplanten werd hierbij in de cloud uitgevoerd, waarbij state-of-art 5G verbindingstechnieken gebruikt werden om de te analyseren data snel genoeg in de cloud en terug te kunnen krijgen om tijdig een actuatie te kunnen uitvoeren op de robot. Door nauwe samenwerking tussen KPN en WUR is een herkenningsalgoritme voor aardappel- en suikerbietenplanten ontwikkeld dat in een KPN-cloud omgeving kan draaien. Terwijl de robot met 4km/u over het veld reed werden de foto’s via 5G naar deze cloud gestuurd en werden de analyse-resultaten teruggestuurd naar de robot binnen 0.25 seconde. De spuit-unit met spuitdoppen om de 0.1 m werd daarop door de computer geïnstrueerd welke spuitdop wanneer geactiveerd moest worden om de gedetecteerde aardappelopslagplant te bespuiten. Tijdens toepassing van het algoritme in augustus werden 96% van de aardappelopslagplanten en 3% van de suikerbietenplanten geraakt. Hoewel deze getallen het systeem al zeer dicht richting praktijkintroductie brengen zal het aantal geraakte suikerbieten nog om laag moeten om boeren massaal te overtuigen van de toepasbaarheid van het systeem. Daar waar 5G genoemd wordt in dit verslag betekent dit het gebruik van pré 5G technologie met 5G capaciteit en performance

Gene x dietary pattern interactions in obesity : analysis of up to 68 317 adults of European ancestry

Obesity is highly heritable. Genetic variants showing robust associationswith obesity traits have been identified through genome wide association studies. We investigated whether a composite score representing healthy diet modifies associations of these variants with obesity traits. Totally, 32 body mass index (BMI)- and 14 waist-hip ratio (WHR)-associated single nucleotide polymorphismswere genotyped, and genetic risk scores (GRS) were calculated in 18 cohorts of European ancestry (n = 68 317). Diet score was calculated based on self-reported intakes of whole grains, fish, fruits, vegetables, nuts/seeds (favorable) and red/processed meats, sweets, sugar-sweetened beverages and fried potatoes (unfavorable). Multivariable adjusted, linear regression within each cohort followed by inverse variance-weighted, fixed-effects meta-analysis was used to characterize: (a) associations of each GRS with BMI and BMI-adjustedWHR and (b) diet score modification of genetic associations with BMI and BMI-adjusted WHR. Nominally significant interactions (P = 0.006-0.04) were observed between the diet score and WHR-GRS (but not BMI-GRS), two WHR loci (GRB14 rs10195252; LYPLAL1 rs4846567) and two BMI loci (LRRN6C rs10968576; MTIF3 rs4771122), for the respective BMI-adjustedWHR or BMI outcomes. Although the magnitudes of these select interactions were small, our data indicated that associations between genetic predisposition and obesity traits were stronger with a healthier diet. Our findings generate interesting hypotheses; however, experimental and functional studies are needed to determine their clinical relevance.Peer reviewe

Predicting the large-scale consequences of offshore wind turbine array development on a North Sea ecosystem

This paper was accepted for publication in the journal Continental Shelf Research and the definitive published version is available at http://dx.doi.org/10.1016/j.csr.2014.05.018.Three models were applied to obtaina first assessment of some of the potential impacts of large-scale operational wind turbine arrays on the marine ecosystem in a well-mixed area in a shelf sea: a biogeochemical model,a wave propagation model and an a coustic energy flux model.The results of the models are discussed separately and together to elucidate the combined effects. Overall,all three models suggested relatively weak environmental changes for the mechanisms included in this study, however these are only a subset of all the potential impacts,and a number of assumptions had to be made. Further work is required to address these assumptions and additional mechanisms. All three models suggested most of the changes with in the wind turbine array,and small changes up to several tens of km outside the array. Within the array, the acoustic model indicated the most concentrated, spatially repetitive changes to the environment,followed by the SWAN wave model,and the biogeochemical model being the most diffuse. Because of the different spatial scales of the response of the three models,the combined results suggested a spectrum of combinations of environmental changes with in the wind turbine array that marine organism smight respond to. The SWAN wave model and the acoustic model suggested a reduction in changes with increasing distance between turbines. The SWAN wave model suggested that the biogeochemical model, because of the in ability of its simple wave model to simulate wave propagation,over-estimated the biogeochemical changes by a factor of 2 or more. The biogeochemical model suggested that the benthic system was more sensitive to the environmental changes than the pelagic system

Analysis of metadata standards for the exchange of image datasets and algorithms in the agricultural domain : A metadata-oriented approach to identify minimum interoperability mechanisms for image data and deep learning algorithms that is used for vision-based applications in agriculture. Sprint Robotics Project PL4.0 WP7

This report discusses the importance of precision agriculture in achieving sustainability goals and the need for a basis that considers different perspectives of a data space such as interoperability, scalability, security, transparency, and data ownership. The Towards Precision Agriculture 4.0 project aims to address these perspectives to provide better-informed management decisions for farmers and the ecosystem. The current study focuses on determining minimum interoperability mechanisms concerning the standardization of image data and deep learning algorithms for vision-based applications in weed management by robots. The study adopts a metadata-oriented approach to make data and algorithms semantically interoperable and reuses existing knowledge from the Reference Model Agro (rmAgro). The results indicate the need for a balance between established standardization and agile standardization for supporting semantic interoperability, and the interoperability of preferred standards like Robot Operating System (ROS) and Open Neural Network Exchange (ONNX) is insufficient. The study results are useful for professionals and academia who work in the design and development of software for the farming business

Long-term evaluation of Class II subdivision treatment with unilateral maxillary first molar extraction

OBJECTIVE To evaluate the long-term effects of asymmetrical maxillary first molar (M1) extraction in Class II subdivision treatment. MATERIALS AND METHODS Records of 20 Class II subdivision whites (7 boys, 13 girls; mean age, 13.0 years; SD, 1.7 years) consecutively treated with the Begg technique and M1 extraction, and 15 untreated asymmetrical Class II adolescents (4 boys, 11 girls; mean age, 12.2 years; SD, 1.3 years) were examined in this study. Cephalometric analysis and PAR assessment were carried out before treatment (T1), after treatment (T2), and on average 2.5 years posttreatment (T3) for the treatment group, and at similar time points and average follow-up of 1.8 years for the controls. RESULTS The adjusted analysis indicated that the maxillary incisors were 2.3 mm more retracted in relation to A-Pog between T1 and T3 (β  =  2.31; 95% CI; 0.76, 3.87), whereas the mandibular incisors were 1.3 mm more protracted (β  =  1.34; 95% CI; 0.09, 2.59), and 5.9° more proclined to the mandibular plane (β  =  5.92; 95% CI; 1.43, 10.41) compared with controls. The lower lip appeared 1.4 mm more protrusive relative to the subnasale-soft tissue-Pog line throughout the observation period in the treated adolescents (β  =  1.43; 95% CI; 0.18, 2.67). There was a significant PAR score reduction over the entire follow-up period in the molar extraction group (β  =  -6.73; 95% CI; -10.7, -2.7). At T2, 65% of the subjects had maxillary midlines perfectly aligned with the face. CONCLUSIONS Unilateral M1 extraction in asymmetrical Class II cases may lead to favorable occlusal outcomes in the long term without harming the midline esthetics and soft tissue profile

Autonome aanpak aardappelopslag : Resultaten activiteiten 2019-2020

Het beheersen van aardappelopslag in landbouwgewassen is van groot belang voor de bodemgezondheid en verspreiding van aardappelziekten. De relatief hoge kosten voor handmatige bestrijding maken inzet van high tech oplossingen interessant. In dit project is een Deep Learning herkenningsalgoritme voor aardappelplanten in een tweetal akkerbouwgewassen ontwikkeld. Tevens is het algoritme getest met een prototype van een spotsprayer, een apparaat dat kleine hoeveelheden middel precies op gedetecteerde planten kan spuiten. Dit rapport beschrijft de behaalde resultaten en de verbeterstappen die nodig zijn om de gewenste kwaliteit in de praktijk te realiseren