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Alzheimer’s disease and depressive disorder are frequent in old age. Both may be associated with depressed mood and cognitive impairment. Therefore, finding a strategy to clarify the diagnosis underlying subjective complaints of impaired cognition and depressed mood in older persons is of utmost interest. We conducted a cross-sectional retrospective observational clinical cohort study using patient records from 2014 to 2018. From 3758 patients, we included patients aged 60 years and older with a Mini-Mental-Status Examination score of 24 and above. Final analysis included all patients in whom Alzheimer’s disease biomarker analysis was performed (cerebrospinal fluid markers of Alzheimer’s disease or positron emission tomography imaging; n = 179) and patients with depressive disorder in whom Alzheimer’s disease was ruled out by analysis of biomarkers suggestive of Alzheimer’s disease (n = 70). With case–control matching for age, education and gender, performance of patients with Alzheimer’s disease was worse in acquisition, consolidation and recall of verbal information and false-positive answers. None of the results, however, sufficed to differentially diagnose individual patients with Alzheimer’s disease or depressive disorder. With more severe symptoms of depression, patients with biomarker-verified Alzheimer’s disease performed worse in executive testing but were not additionally impaired in verbal episodic memory performance. We conclude that distinguishing between Alzheimer’s disease and depressive disorder is unreliable on clinical grounds and behavioural testing alone. Diagnosing the cause of subjective complaints about deteriorating cognitive function or depressed mood requires additional biomarker assessment, whereas cognitive assessment is needed to define appropriate targets of symptomatic treatment in patients with Alzheimer’s disease and depressive disorder., Both Alzheimer’s disease and depressive disorder may be associated with depressed mood and cognitive impairment. Distinguishing between the two conditions on clinical and behavioural grounds alone is unreliable. Diagnosing the cause of subjective complaints about deteriorating cognitive function or depressed mood requires additional biomarker assessment., Graphical Abstract

ObjectivesDepressive symptoms and cognitive impairment often concur in older persons. Differentiating the cause of cognitive impairment in older persons with Depressive Disorder (DD) from other diseases such as Alzheimer's Disease (AD) is challenging. The goal of this study was to characterize cognitive impairment in older persons with DD.DesignCross-sectional retrospective observational clinical cohort study using patient records from 2014 to 2018.SettingGerontopsychiatric services of Ulm University at Bezirkskrankenhaus Günzburg serving as primary psychiatric care institution and tertiary referral center for psychiatric care for older persons.PartcipantsDD was diagnosed according to ICD-10 criteria. When indicated by the medical history or neuropsychological assessment further diagnostic procedures were initiated. Cerebrospinal fluid (CSF) tap was routinely the first additional procedure. If patients did not consent to CSF tap or contraindications were present, 18F-fluordesoxyglucose-PET (FDG-PET) or Amyloid-PET (Am-PET) were performed.Materials and methodsExtensive neuropsychological test battery to assess cognitive profile.Results457 subjects were diagnosed with DD (DD-all; age 50-94; 159 males, 298 females). Biomarkers were assessed in 176 persons; in 90 of these subjects AD-biomarkers were negative (DD-BM-; age 54-89; 40 males, 50 females), and in 86 subjects at least one biomarker was compatible with AD (DD-BM+; age 60-90; 31 males, 55 females). Cognitive performance was below healthy controls (HC; n = 56; age 50-80; 30 males, 26 females) for all groups of patients with DD. With case-control matching of HC and DD-BM- we find that executive functions are impaired in about one out of three and delayed recall in about two out of three patients with DD.ConclusionCognitive impairment is frequent in older persons with DD. Cognitive profile in older patients with DD without and with biomarkers of AD is not distinguishable. Therefore, cognitive impairment due to DD should be diagnosed after exclusion of comorbid AD.

The increasing electrification of powertrain systems is driven by the idea of using electric power as an alternative energy source. Fuel cells combined with electric traction are one example. Batteries will have a sufficient energy density for a maximum mileage of 200 km, sufficient for driving even in the largest of conurbations. In urban surroundings, a market for fuel cells as a range extender may develop. For mobility with distances of more than 400 km, there is no real alternative to the internal combustion engine powered by liquid hydrocarbons, as Volkswagen engineers predict.

Due to changing economic, technical and social environments and resulting customer demands, future vehicle drive systems will be required to have lower pollutant emissions and greater efficiency, leading to a CO2 reduction. Combining the advantages of the petrol and diesel combustion processes is a way of achieving these objectives. In the Group Research — Drive Systems of Volkswagen AG, this implementation is referred to as the Combined Combustion System CCS.

Given an image sequence recorded by a hand-held camera we examine the computation of a light field without any further input data. Using structure-from-motion algorithms and optimization techniques camera motion and a 3-D reconstruction of the scene are established. The light field is completed by computing local depth information for each input image. During experimental evaluation a special focus is set on the effects of falsely estimated intrinsic parameters as well as different depth representations on the quality of the resulting light fields.

Image-based rendering techniques require capturing an object or scene from many viewpoints. Often, depth maps are used in addition to the original images for rendering new iews for novel viewpoints not coinciding with one of the original camera positions. Due to the high amount of data, efficient compression is necessary. When the data is stored or transmitted, it is not only desirable to compress the image data but also the depth information. In this paper, the case of sequences recorded with a single, hand-held camera is investigated. These sequences are used for unstructured lumigraph rendering. In addition, the case of multi-view video sequences is analyzed. For both cases, depth maps are compressed using H.264/AVC, and the achievable data rates are studied. For the case of unstructured lumigraph rendering, the effect of depth map compression on the quality of rendered images is analyzed in a second step.

A common approach to 3-D reconstruction from image sequences is to track point features through the images, followed by an estimation of camera parameters and scene geometry. For long sequences, the latter is done by applying a factorization method followed by an image-by-image calibration. In this contribution we propose to integrate the tracking and calibration steps and to feed back already known camera parameters to both tracking and calibration. For loop-like camera motion, reconstruction can thus be optimized by using loop-closing algorithms known from robot navigation.

We describe an Augmented Reality system using the corners of a color cube for camera calibration. In the augmented image the cube is replaced by a computer generated virtual object. The cube is localized in an image by the CSC color segmentation algorithm. The camera projection matrix is estimated with a linear method that is followed by a nonlinear refinement step. Because of possible missclassifications of the segmented color regions and the minimum number of point correspondences used for calibration, the estimated pose of the cube may be very erroneous for some frames; therefore we perform outlier detection and treatment for rendering the virtual object in an acceptable manner.