75 research outputs found

    An Image-Based Real-Time Georeferencing Scheme for a UAV Based on a New Angular Parametrization

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    Simultaneous localization and mapping (SLAM) of a monocular projective camera installed on an unmanned aerial vehicle (UAV) is a challenging task in photogrammetry, computer vision, and robotics. This paper presents a novel real-time monocular SLAM solution for UAV applications. It is based on two steps: consecutive construction of the UAV path, and adjacent strip connection. Consecutive construction rapidly estimates the UAV path by sequentially connecting incoming images to a network of connected images. A multilevel pyramid matching is proposed for this step that contains a sub-window matching using high-resolution images. The sub-window matching increases the frequency of tie points by propagating locations of matched sub-windows that leads to a list of high-frequency tie points while keeping the execution time relatively low. A sparse bundle block adjustment (BBA) is employed to optimize the initial path by considering nuisance parameters. System calibration parameters with respect to global navigation satellite system (GNSS) and inertial navigation system (INS) are optionally considered in the BBA model for direct georeferencing. Ground control points and checkpoints are optionally included in the model for georeferencing and quality control. Adjacent strip connection is enabled by an overlap analysis to further improve connectivity of local networks. A novel angular parametrization based on spherical rotation coordinate system is presented to address the gimbal lock singularity of BBA. Our results suggest that the proposed scheme is a precise real-time monocular SLAM solution for a UAV.Peer reviewe

    The reproduction of gender differences in early career choices and professional identity of young dentist in Finland

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    Introduction For over the last 20 years, approximately 70% of working dentists in Finland have been women. However, there is internal division of the profession along gender lines. Female dentists work more often in the public sector and male dentists in the private sector. The aim of this study was to investigate the gender differences in young dentists' early career choices, specialization plans, values and perceptions of professional identity. Materials and methods The data were taken from a national e-mail questionnaire study called "Young Dentist," which was sent to 458 dentists who had received their licence to practise dentistry in 2014-2016 from all four universities with dental curricula in Finland. A total of 52% young dentists (n = 238) answered the questionnaire. Results and discussion The results indicated that whereas female dentists were more likely to perceive themselves as comforters, social workers and health promoters, male dentists tended to perceive themselves as technicians. These professional identities were interrelated with early-stage career choices in which female dentists worked more often in the public than in the private sector when compared to male dentists. There were also clear gender differences in the importance of values and the specialization plans of the young dentists. Conclusion Young dentists in Finland make career choices and develop professional identity in accordance with the attributes traditionally associated with cultural ideals related to femininity and masculinity.Peer reviewe

    Direct reflectance transformation methodology for drone-based hyperspectral imaging

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    Multi- and hyperspectral cameras on drones can be valuable tools in environmental monitoring. A significant shortcoming complicating their usage in quantitative remote sensing applications is insufficient robust radiometric calibration methods. In a direct reflectance transformation method, the drone is equipped with a camera and an irradiance sensor, allowing transformation of image pixel values to reflectance factors without ground reference data. This method requires the sensors to be calibrated with higher accuracy than what is usually required by the empirical line method (ELM), but consequently it offers benefits in robustness, ease of operation, and ability to be used on Beyond-Visual Line of Sight flights. The objective of this study was to develop and assess a drone-based workflow for direct reflectance transformation and implement it on our hyperspectral remote sensing system. A novel atmospheric correction method is also introduced, using two reference panels, but, unlike in the ELM, the correction is not directly affected by changes in the illumination. The sensor system consists of a hyperspectral camera (Rikola HSI, by Senop) and an onboard irradiance spectrometer (FGI AIRS), which were both given thorough radiometric calibrations. In laboratory tests and in a flight experiment, the FGI AIRS tilt-corrected irradiances had accuracy better than 1.9% at solar zenith angles up to 70◦. The system’s lowaltitude reflectance factor accuracy was assessed in a flight experiment using reflectance reference panels, where the normalized root mean square errors (NRMSE) were less than ±2% for the light panels (25% and 50%) and less than ±4% for the dark panels (5% and 10%). In the high-altitude images, taken at 100–150 m altitude, the NRMSEs without atmospheric correction were within 1.4%–8.7% for VIS bands and 2.0%–18.5% for NIR bands. Significant atmospheric effects appeared already at 50 m flight altitude. The proposed atmospheric correction was found to be practical and it decreased the high-altitude NRMSEs to 1.3%–2.6% for VIS bands and to 2.3%– 5.3% for NIR bands. Overall, the workflow was found to be efficient and to provide similar accuracies as the ELM, but providing operational advantages in such challenging scenarios as in forest monitoring, large-scale autonomous mapping tasks, and real-time applications. Tests in varying illumination conditions showed that the reflectance factors of the gravel and vegetation targets varied up to 8% between sunny and cloudy conditions due to reflectance anisotropy effects, while the direct reflectance workflow had better accuracy. This suggests that the varying illumination conditions have to be further accounted for in drone-based in quantitative remote sensing applications

    Autonomous robotic drone system for mapping forest interiors

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    During the last decade, the use of drones in forest monitoring and remote sensing has become highly popular. While most of the monitoring tasks take place in high altitudes and open air, in the last few years drones have also gained interest in under-canopy data collection. However, flying under the forest canopy is a complex task since the drone can not use Global Navigation Satellite Systems (GNSS) for positioning and it has to continually avoid obstacles, such as trees, branches, and rocks, on its path. For that reason, drone-based data collection under the forest canopy is still mainly based on manual control by human pilots. Autonomous flying in GNSS-denied obstacle-rich environment has been an actively researched topic in the field of robotics during the last years and various open-sourced methods have been published in the literature. However, most of the research is done purely from the point-of-view of robotics and only a few studies have been published in the boundary of forest sciences and robotics aiming to take steps towards autonomous forest data collection. In this study, a prototype of an autonomous under-canopy drone is developed and implemented utilizing state-of-the-art open-source methods. The prototype is utilizing the EGO-Planner-v2 trajectory planner for autonomous obstacle avoidance and VINS-Fusion for Visual-inertial-odometry based GNSS-free pose estimation. The flying performance of the prototype is evaluated by performing multiple test flights with real hardware in two different boreal forest test plots with medium and difficult densities. Furthermore, the first results of the forest data collecting performance are obtained by post-processing the data collected with a low-cost stereo camera during one test flight to a 3D point cloud and by performing diameter breast at height (DBH) estimation. In the medium-density forest, all seven test flights were successful, but in the difficult test forest, one of eight test flights failed. The RMSE of the DBH estimation was 3.86 cm (12.98 %)

    APOE ε4 gene dose effect on imaging and blood biomarkers of neuroinflammation and beta-amyloid in cognitively unimpaired elderly

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    BACKGROUND: Neuroinflammation, characterized by increased reactivity of microglia and astrocytes in the brain, is known to be present at various stages of the Alzheimer's disease (AD) continuum. However, its presence and relationship with amyloid pathology in cognitively normal at-risk individuals is less clear. Here, we used positron emission tomography (PET) and blood biomarker measurements to examine differences in neuroinflammation and beta-amyloid (Aβ) and their association in cognitively unimpaired homozygotes, heterozygotes, or non-carriers of the APOE ε4 allele, the strongest genetic risk for sporadic AD. METHODS: Sixty 60-75-year-old APOE ε4 homozygotes (n = 19), heterozygotes (n = 21), and non-carriers (n = 20) were recruited in collaboration with the local Auria biobank. The participants underwent 11C-PK11195 PET (targeting 18-kDa translocator protein, TSPO), 11C-PiB PET (targeting Aβ), brain MRI, and neuropsychological testing including a preclinical cognitive composite (APCC). 11C-PK11195 distribution volume ratios and 11C-PiB standardized uptake value ratios (SUVRs) were calculated for regions typical for early Aβ accumulation in AD. Blood samples were drawn for measuring plasma glial fibrillary acidic protein (GFAP) and plasma Aβ1-42/1.40. RESULTS: In our cognitively unimpaired sample, cortical 11C-PiB-binding increased according to APOE ε4 gene dose (median composite SUVR 1.47 (range 1.38-1.66) in non-carriers, 1.55 (1.43-2.02) in heterozygotes, and 2.13 (1.61-2.83) in homozygotes, P = 0.002). In contrast, cortical composite 11C-PK11195-binding did not differ between the APOE ε4 gene doses (P = 0.27) or between Aβ-positive and Aβ-negative individuals (P = 0.81) and associated with higher Aβ burden only in APOE ε4 homozygotes (Rho = 0.47, P = 0.043). Plasma GFAP concentration correlated with cortical 11C-PiB (Rho = 0.35, P = 0.040), but not 11C-PK11195-binding (Rho = 0.13, P = 0.47) in Aβ-positive individuals. In the total cognitively unimpaired population, both higher composite 11C-PK11195-binding and plasma GFAP were associated with lower hippocampal volume, whereas elevated 11C-PiB-binding was associated with lower APCC scores. CONCLUSIONS: Only Aβ burden measured by PET, but not markers of neuroinflammation, differed among cognitively unimpaired elderly with different APOE ε4 gene dose. However, APOE ε4 gene dose seemed to modulate the association between neuroinflammation and Aβ

    ASIC-E4: Interplay of Beta-Amyloid, Synaptic Density and Neuroinflammation in Cognitively Normal Volunteers With Three Levels of Genetic Risk for Late-Onset Alzheimer's Disease – Study Protocol and Baseline Characteristics

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    Background: Detailed characterization of early pathophysiological changes in preclinical Alzheimer's disease (AD) is necessary to enable development of correctly targeted and timed disease-modifying treatments. ASIC-E4 study (“Beta-Amyloid, Synaptic loss, Inflammation and Cognition in healthy APOE ε4 carriers”) combines state-of-the-art neuroimaging and fluid-based biomarker measurements to study the early interplay of three key pathological features of AD, i.e., beta-amyloid (Aβ) deposition, neuroinflammation and synaptic dysfunction and loss in cognitively normal volunteers with three different levels of genetic (APOE-related) risk for late-onset AD. Objective: Here, our objective is to describe the study design, used protocols and baseline demographics of the ASIC-E4 study. Methods/Design: ASIC-E4 is a prospective observational multimodal imaging study performed in Turku PET Centre in collaboration with University of Gothenburg. Cognitively normal 60–75-year-old-individuals with known APOE ε4/ε4 genotype were recruited via local Auria Biobank (Turku, Finland). Recruitment of the project has been completed in July 2020 and 63 individuals were enrolled to three study groups (Group 1: APOE ε4/ε4, N = 19; Group 2: APOE ε4/ε3, N = 22; Group 3: APOE ε3/ε3, N = 22). At baseline, all participants will undergo positron emission tomography imaging with tracers targeted against Aβ deposition (11C-PIB), activated glia (11C-PK11195) and synaptic vesicle glycoprotein 2A (11C-UCB-J), two brain magnetic resonance imaging scans, and extensive cognitive testing. In addition, blood samples are collected for various laboratory measurements and blood biomarker analysis and cerebrospinal fluid samples are collected from a subset of participants based on additional voluntary informed consent. To evaluate the predictive value of the early neuroimaging findings, neuropsychological evaluation and blood biomarker measurements will be repeated after a 4-year follow-up period. Discussion: Results of the ASIC-E4 project will bridge the gap related to limited knowledge of the synaptic and inflammatory changes and their association with each other and Aβ in “at-risk” individuals. Thorough in vivo characterization of the biomarker profiles in this population will produce valuable information for diagnostic purposes and future drug development, where the field has already started to look beyond Aβ

    Exercise training decreases pancreatic fat content and improves beta cell function regardless of baseline glucose tolerance: a randomised controlled trial

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    Aims/hypothesis: Pancreatic fat accumulation may contribute to the development of beta cell dysfunction. Exercise training improves whole-body insulin sensitivity, but its effects on pancreatic fat content and beta cell dysfunction are unclear. The aim of this parallel-group randomised controlled trial was to evaluate the effects of exercise training on pancreatic fat and beta cell function in healthy and prediabetic or type 2 diabetic participants and to test whether the responses were similar regardless of baseline glucose tolerance.Methods: Using newspaper announcements, a total of 97 sedentary 40-55-year-old individuals were assessed for eligibility. Prediabetes (impaired fasting glucose and/or impaired glucose tolerance) and type 2 diabetes were defined by ADA criteria. Of the screened candidates, 28 healthy men and 26 prediabetic or type 2 diabetic men and women met the inclusion criteria and were randomised into 2-week-long sprint interval or moderate-intensity continuous training programmes in a 1:1 allocation ratio using random permuted blocks. The primary outcome was pancreatic fat, which was measured by magnetic resonance spectroscopy. As secondary outcomes, beta cell function was studied using variables derived from OGTT, and whole-body insulin sensitivity and pancreatic fatty acid and glucose uptake were measured using positron emission tomography. The measurements were carried out at the Turku PET Centre, Finland. The analyses were based on an intention-to-treat principle. Given the nature of the intervention, blinding was not applicable.Results: At baseline, the group of prediabetic or type 2 diabetic men had a higher pancreatic fat content and impaired beta cell function compared with the healthy men, while glucose and fatty acid uptake into the pancreas was similar. Exercise training decreased pancreatic fat similarly in healthy (from 4.4% [3.0%, 6.1%] to 3.6% [2.4%, 5.2%] [mean, 95% CI]) and prediabetic or type 2 diabetic men (from 8.7% [6.0%, 11.9%] to 6.7% [4.4%, 9.6%]; p = 0.036 for time effect) without any changes in pancreatic substrate uptake (p ae 0.31 for time effect in both insulin-stimulated glucose and fasting state fatty acid uptake). In prediabetic or type 2 diabetic men and women, both exercise modes similarly improved variables describing beta cell function.Conclusions/interpretation: Two weeks of exercise training improves beta cell function in prediabetic or type 2 diabetic individuals and decreases pancreatic fat regardless of baseline glucose tolerance. This study shows that short-term training efficiently reduces ectopic fat within the pancreas, and exercise training may therefore reduce the risk of type 2 diabetes.</p

    Impact of Sarcoplasmic Reticulum Calcium Release on Calcium Dynamics and Action Potential Morphology in Human Atrial Myocytes: A Computational Study

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    Electrophysiological studies of the human heart face the fundamental challenge that experimental data can be acquired only from patients with underlying heart disease. Regarding human atria, there exist sizable gaps in the understanding of the functional role of cellular Ca2+ dynamics, which differ crucially from that of ventricular cells, in the modulation of excitation-contraction coupling. Accordingly, the objective of this study was to develop a mathematical model of the human atrial myocyte that, in addition to the sarcolemmal (SL) ion currents, accounts for the heterogeneity of intracellular Ca2+ dynamics emerging from a structurally detailed sarcoplasmic reticulum (SR). Based on the simulation results, our model convincingly reproduces the principal characteristics of Ca2+ dynamics: 1) the biphasic increment during the upstroke of the Ca2+ transient resulting from the delay between the peripheral and central SR Ca2+ release, and 2) the relative contribution of SL Ca2+ current and SR Ca2+ release to the Ca2+ transient. In line with experimental findings, the model also replicates the strong impact of intracellular Ca2+ dynamics on the shape of the action potential. The simulation results suggest that the peripheral SR Ca2+ release sites define the interface between Ca2+ and AP, whereas the central release sites are important for the fire-diffuse-fire propagation of Ca2+ diffusion. Furthermore, our analysis predicts that the modulation of the action potential duration due to increasing heart rate is largely mediated by changes in the intracellular Na+ concentration. Finally, the results indicate that the SR Ca2+ release is a strong modulator of AP duration and, consequently, myocyte refractoriness/excitability. We conclude that the developed model is robust and reproduces many fundamental aspects of the tight coupling between SL ion currents and intracellular Ca2+ signaling. Thus, the model provides a useful framework for future studies of excitation-contraction coupling in human atrial myocytes
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