Search

Crowdsourced platforms provide huge amounts of street-view images that contain valuable building information. This work addresses the challenges in applying Scene Text Recognition (STR) in crowdsourced street-view images for building attribute mapping. We use Flickr images, particularly examining texts on building facades. A Berlin Flickr dataset is created, and pre-trained STR models are used for text detection and recognition. Manual checking on a subset of STR-recognized images demonstrates high accuracy. We examined the correlation between STR results and building functions, and analysed instances where texts were recognized on residential buildings but not on commercial ones. Further investigation revealed significant challenges associated with this task, including small text regions in street-view images, the absence of ground truth labels, and mismatches in buildings in Flickr images and building footprints in OpenStreetMap (OSM). To develop city-wide mapping beyond urban hotspot locations, we suggest differentiating the scenarios where STR proves effective while developing appropriate algorithms or bringing in additional data for handling other cases. Furthermore, interdisciplinary collaboration should be undertaken to understand the motivation behind building photography and labeling. The STR-on-Flickr results are publicly available at https://github.com/ya0-sun/STR-Berlin.

Highly accurate reference vehicle trajectories are required in the automotive domain e. g. for testing mobile GNSS devices. Common methods used to determine reference trajectories are based on the same working principles as the device under test and suffer from the same underlying error problems. In this paper, a new method to generate reference vehicle trajectories in real-world situations using simultaneously acquired aerial imagery from a helicopter is presented. This method requires independent height information which is coming from a LIDAR DTM and the relative height of the GNSS device. The reference trajectory is then derived by forward intersection of the vehicle position in each image with the DTM. In this context, the influence of all relevant error sources were analysed, like the error from the LIDAR DTM, from the sensor latency, from the semi-automatic matching of the vehicle marking, and from the image orientation. Results show that the presented method provides a tool for creating reference trajectories that is independent of the GNSS reception at the vehicle. Moreover, it can be demonstrated that the proposed method reaches an accuracy level of 10 cm, which is defined as necessary for certification and validation of automotive GNSS devices.

To allow for a robust and automatic exploitation of Sentinel-2 data, Analysis Ready Data (ARD) products are requested by most users. The processors of ARD products take care of the common burdens necessary for most applications, that include precise orthorectification, cloud detection and atmospheric correction steps, as well as the generation of periodic syntheses of cloud free surface reflectances. The French Theia land data center, and the German Earth Observation Center (EOC) started delivering Sentinel-2 surface reflectance products to users in 2016 in France and 2019 in Germany respectively. Both centers produce and distribute these data sets in near real time, over large regions requested by French users such as Western Europe, Maghreb, Sahel, Madagascar… Theia’s and EOC products include an instantaneous surface reflectance product (Level-2A), and a monthly cloud free synthesis of surface reflectance (Level-3A). This article shortly describes the methods used to generate the Level-2A products with the MAJA processor, and the Level-3A products with theWASP processor. The MAJA processor is based on multi-temporal methods, that use the slow variation of surface reflectance to detect clouds and estimate aerosol depth, while WASP, thanks to the quality of MAJA cloud mask, calculates a weighted average of all the cloud free observations over 45 days, every month. The article also provides validation results for Level-2A and Level-3A products, resulting from comparison with in-situ data and with other methods. A last section gives first insights from the monitoring of user uptake of the distributed products.

Undocumented buildings are buildings which were built years ago, but were never recorded in official digital cadastral maps. Detection of undocumented buildings is of great importance for urban planning and monitoring. The state of Bavaria, Germany, pursues this task based on high resolution optical data and digital surface models, using semi-automatic detection methods, which suffer from a high false alarm rate. In order to study the influence of sampling strategies on the performance of building detection, we have firstly designed a transferability analysis experiment, which has not been adequately addressed in the current literature. In this experiment, we test whether the trained model from a district contains valuable information for building detection in a different district. It was found that the large-scale building detection results can be considerably improved when training samples are collected from different districts. Based on the building detection results, we propose a novel framework for the detection of undocumented buildings using Convolutional Neural Network (CNN) and official geodata. More specifically, buildings are identified as undocumented, when their pixels in the output of the CNN are predicted as “building”, whereas they belong to the “non-building” in the Digital Cadastral Map (DFK). The detected undocumented building pixels are subsequently divided into the class of old or new undocumented building with the aid of a Temporal Digital Surface Model (tDSM) in the stage of decision fusion. By doing so, a seamless map of undocumented buildings is generated for 1/4th of the state of Bavaria, Germany at a spatial resolution of 0.4 m, which has demonstrated the use of CNN for the robust detection of undocumented buildings at large-scale.

DLRAD – a new vision and mapping benchmark dataset for autonomous driving is under development for the validation of intelligent driving algorithms. Stationary, mobile, and airborne sensors monitored simultaneously the environment around a reference vehicle, which was driving on urban, suburb and rural roads in and around the city of Braunschweig/Germany. Airborne images were acquired with the DLR 4k sensor system mounted on a helicopter. The DLR research car FASCarE is equipped with the latest sensor technology like front/rear radar, ultrasound and laser sensors, optical single and stereo cameras, and GNSS/IMU. Additionally, stationary terrestrial sensors like induction loops, optical mono and stereo cameras, radar and laser scanners monitor defined sections of the path from the ground. Simultaneously, the helicopter with the 4k sensor systems follows the reference car by keeping it all the time in the central nadir view. A next crucial step in the construction of the DLRAD benchmark dataset is the annotation of all objects in the reference dataset.The DLRAD benchmark dataset enables a huge variety of validation capabilities and opens a wide field of possibilities for the development, training and validation of machine learning algorithms in the context of autonomous driving. In this paper, we will present details of the sensor configurations and the acquisition campaign, which had taken place between the 18th July and 20th July 2017 in Braunschweig/Germany. Also, we show a first analysis of the data including the completeness and geometrical quality. The dataset will be published as soon as the coregistration and annotations are complete.

In this paper, we present a work-flow to investigate the joint visibility between very-high-resolution SAR and optical images of urban scenes. For this task, we extend the simulation framework SimGeoI to enable a simulation of individual pixels rather than complete images. Using the extended SimGeoI simulator, we carry out a case study using a TerraSAR-X staring spotlight image and a Worldview-2 panchromatic image acquired over the city of Munich, Germany. The results of this study indicate that about 55 % of the scene are visible in both images and are thus suitable for matching and data fusion endeavours, while about 25 % of the scene are affected by either radar shadow or optical occlusion. Taking the image acquisition parameters into account, our findings can provide support regarding the definition of upper bounds for image fusion tasks, as well as help to improve acquisition planning with respect to different application goals.

GeoRaySAR, an automated SAR simulator developed at DLR, identifies buildings in high resolution SAR data by utilizing geometric knowledge extracted from digital surface models (DSMs). Hitherto, the simulator has utilized DSMs generated from LiDAR data from airborne sensors with pre-filtered vegetation. Discarding the need for pre-optimized model input, DSMs generated from high resolution optical data (acquired with WorldView-2) are used for the extraction of building-related SAR image parts in this work. An automatic preprocessing of the DSMs has been developed for separating buildings from elevated vegetation (trees, bushes) and reducing the noise level. Based on that, automated simulations are triggered considering the properties of real SAR images. Locations in three cities, Munich, London and Istanbul, were chosen as study areas to determine advantages and limitations related to WorldView-2 DSMs as input for GeoRaySAR. Beyond, the impact of the quality of the DSM in terms of building extraction is evaluated as well as evaluation of building DSM, a DSM only containing buildings. The results indicate that building extents can be detected with DSMs from optical satellite data with various success, dependent on the quality of the DSM as well as on the SAR imaging perspective.

The assignment of phase center positions (in 2D or 3D) derived from SAR data to physical object is challenging for many man-made structures such as buildings or bridges. In contrast, light poles and traffic signs are promising targets for tasks based on 3-D geolocation as they often show a prominent and spatially isolated appearance. For a detailed understanding of the nature of both targets, this paper presents results of a dedicated simulation case study, which is based on ray tracing methods (simulator RaySAR). For the first time, the appearance of the targets is analyzed in 2D (image plane) and 3D space (world coordinates of scene model) and reflecting surfaces are identified for related dominant image pixels. The case studies confirms the crucial impact of spatial resolution in the context of light poles and traffic signs and the appropriateness of light poles as target for 3-D geolocation in case of horizontal ground surfaces beneath.

Motivated by the distinct appearance of facades in high resolution SAR images with respect to signal incidence angles and polarizations, this paper introduces a way to fuse SAR imagery and 3D GIS (geoinformation system) data (format: CityGML) based on SAR simulation methods. To this end, the known building geometry is used to simulate the extent of building layover for identifying the related image parts in high resolution TerraSAR-X images. The simulated SAR images are generated and geocoded by an automated processing chain which is initialized by the automated parsing of the CityGML dataset and the TerraSAR-X orbit file. Confirming the functionality of the developed interface between simulation and CityGML, first results are presented for an urban scene in the Munich city center in order to discuss future opportunities in the context of change detection applications.

Thanks to the high resolution of modern SAR satellites many persistent scatterers (PS) appear at single buildings, approximately half of them representing building facades. These groups of points often show regular patterns in the SAR images that can be related to repeating structure elements on the facades. Hence, individual buildings can now be monitored over time, either based on amplitude (for change detection) and phase information (using interferometric methods). However, patterns of point signatures are often disrupted or disappear when the imaging geometry is slightly changed. The investigation at hand provides a detailed analysis of PS patterns based on reference data obtained from a photogrammetric survey. The processing of the optical images allows to create a detailed 3D model of the respective facade, which represents the geometrical object information for SAR simulation. From the simulation results the appearance of the point patterns of natural PS in high resolution SAR data can be better understood. The approach and findings for a case study in Munich is described in detail in this paper.

In Drosophila, Notch and EGFR signalling pathways are closely intertwined. Their relationship is mostly antagonistic, and may in part be based on the phosphorylation of the Notch signal transducer Suppressor of Hairless [Su(H)] by MAPK. Su(H) is a transcription factor that together with several cofactors regulates the expression of Notch target genes. Here we address the consequences of a local induction of three Su(H) variants on Notch target gene expression. To this end, wild-type Su(H), a phospho-deficient Su(H)MAPK-ko and a phospho-mimetic Su(H)MAPK-ac isoform were overexpressed in the central domain of the wing anlagen. The expression of the Notch target genes cut, wingless, E(spl)m8-HLH and vestigial, was monitored. For the latter two, reporter genes were used (E(spl)m8-lacZ, vgBE-lacZ). In general, Su(H)MAPK-ko induced a stronger response than wild-type Su(H), whereas the response to Su(H)MAPK-ac was very weak. Notch target genes cut, wingless and vgBE-lacZ were ectopically activated, whereas E(spl)m8-lacZ was repressed by overexpression of Su(H) proteins. In addition, in epistasis experiments an activated form of the EGF-receptor (DERact) or the MAPK (rlSEM) and individual Su(H) variants were co-overexpressed locally, to compare the resultant phenotypes in adult flies (thorax, wings and eyes) as well as to assay the response of the Notch target gene cut in cell clones.

Freshwater crayfish are amongst the largest macroinvertebrates and play a keystone role in the ecosystems they occupy. Understanding the global distribution of these animals is often hindered due to a paucity of distributional data. Additionally, non-native crayfish introductions are becoming more frequent, which can cause severe environmental and economic impacts. Management decisions related to crayfish and their habitats require accurate, up-to-date distribution data and mapping tools. Such data are currently patchily distributed with limited accessibility and are rarely up-to-date. To address these challenges, we developed a versatile e -portal to host distributional data of freshwater crayfish and their pathogens (using Aphanomyces astaci , the causative agent of the crayfish plague, as the most prominent example). Populated with expert data and operating in near real-time, World of Crayfish ™ is a living, publicly available database providing worldwide distributional data sourced by experts in the field. The database offers open access to the data through specialized standard geospatial services (Web Map Service, Web Feature Service) enabling users to view, embed, and download customizable outputs for various applications. The platform is designed to support technical enhancements in the future, with the potential to eventually incorporate various additional features. This tool serves as a step forward towards a modern era of conservation planning and management of freshwater biodiversity., Competing Interests: The authors declare there are no competing interests., (©2024 Ion et al.)

This study presents a graphene field-effect transistor (gFET) biosensor with dual detection capabilities for SARS-CoV-2: one RNA detection assay to confirm viral positivity and the other for nucleocapsid (N-)protein detection as a proxy for infectiousness of the patient. This technology can be rapidly adapted to emerging infectious diseases, making an essential tool to contain future pandemics. To detect viral RNA, the highly conserved E-gene of the virus was targeted, allowing for the determination of SARS-CoV-2 presence or absence using nasopharyngeal swab samples. For N-protein detection, specific antibodies were used. Tested on 213 clinical nasopharyngeal samples, the gFET biosensor showed good correlation with RT-PCR cycle threshold values, proving its high sensitivity in detecting SARS-CoV-2 RNA. Specificity was confirmed using 21 pre-pandemic samples positive for other respiratory viruses. The gFET biosensor had a limit of detection (LOD) for N-protein of 0.9 pM, establishing a foundation for the development of a sensitive tool for monitoring active viral infection. Results of gFET based N-protein detection corresponded to the results of virus culture in all 16 available clinical samples and thus it also proved its capability to serve as a proxy for infectivity. Overall, these findings support the potential of the gFET biosensor as a point-of-care device for rapid diagnosis of SARS-CoV-2 infection and indirect assessment of infectiousness in patients, providing additional information for clinical and public health decision-making., Competing Interests: Declaration of competing interest The authors declare the following financial interests/personal relationships which may be considered as potential competing interests: Dr. Robert Strassl reports financial support was provided by Austrian Science Fund. If there are other authors, they declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 The Authors. Published by Elsevier B.V. All rights reserved.)

Background: An array of evidence shows how the presence of implicit bias in clinical encounters can negatively impact provider-patient communication, quality of care and ultimately contribute to health inequities. Reflexive practice has been explored as an approach to identify and address implicit bias in healthcare providers, including medical students. At the Lausanne School of Medicine, a clinically integrated module was introduced in 2019 to raise students' awareness of gender bias in medical practice using a reflexivity and positionality approach. The purpose of this study is to describe the gender bias that were identified by medical students, analysing their types, places and modes of emergence during a clinical encounter. It further explores how positionality supported students' reflection on the way in which social position modulates their relationship to patients., Methods: As part of the teaching activity, medical students individually reflected on gender bias in a specific clinical encounter by answering questions in their electronic portfolio. The questionnaire included a section on positionality. We qualitatively analysed the students' assignments (n=76), applying a thematic analysis framework., Results: Medical students identified and described gender biases occurring at different moments of the clinical encounter (anamnesis (i.e. patient history), physical exam, differential diagnosis, final management). They causally associated these biases with wider social phenomena such as the gendered division of labour or stereotypes around sexuality and gender. Analysing students' reflections on how their position influenced their relationship with patients, we found that the suggested exercise revealed a major contradiction in the process of medical enculturation: the injunction to be neutral and objective erases the social and cultural context of patients and impedes an understanding of gender bias., Conclusion: Gender biases are present in the different steps of a clinical consultation and are rooted in broader gendered social representations. We further conclude that the tension between a quest for objectivity and the reality of social encounters should be made explicit to students, because it is constitutive of medical practice., (© 2024. The Author(s).)

Multiple studies have investigated bibliometric features and uncategorized scholarly documents for the influential scholarly document prediction task. In this paper, we describe our work that attempts to go beyond bibliometric metadata to predict influential scholarly documents. Furthermore, this work also examines the influential scholarly document prediction task over categorized scholarly documents. We also introduce a new approach to enhance the document representation method with a domain-independent knowledge graph to find the influential scholarly document using categorized scholarly content. As the input collection, we use the WHO corpus with scholarly documents on the theme of COVID-19. This study examines different document representation methods for machine learning, including TF-IDF, BOW, and embedding-based language models (BERT). The TF-IDF document representation method works better than others. From various machine learning methods tested, logistic regression outperformed the other for scholarly document category classification, and the random forest algorithm obtained the best results for influential scholarly document prediction, with the help of a domain-independent knowledge graph, specifically DBpedia, to enhance the document representation method for predicting influential scholarly documents with categorical scholarly content. In this case, our study combines state-of-the-art machine learning methods with the BOW document representation method. We also enhance the BOW document representation with the direct type (RDF type) and unqualified relation from DBpedia. From this experiment, we did not find any impact of the enhanced document representation for the scholarly document category classification. We found an effect in the influential scholarly document prediction with categorical data., (© 2023. The Author(s).)

Background: Various rescue techniques are used for the prehospital transport of trauma patients. This study compares different techniques in terms of immobilization of the cervical spine and the rescue time., Methods: A wireless motion capture system (Xsens Technologies, Enschede, The Netherlands) was used to record motion in three-dimensional space and the rescue time in a standardized environment. Immobilization was performed by applying different techniques through different teams of trained paramedics and physicians. All tests were performed on the set course, starting with the test person lying on the floor and ending with the test person lying on an ambulance cot ready to be loaded into an ambulance. Six different settings for rescue techniques were examined: rescue sheet with/without rigid cervical collar (P1S1, P1S0), vacuum mattress and scoop stretcher with/without rigid cervical collar (P2S1, P2S0), and long spinal board with/without rigid cervical collar (P3S1, P3S0). Four time intervals were defined: the time interval in which the rigid cervical collar is applied (T0), the time interval in which the test person is positioned on rescue sheet, vacuum mattress and scoop stretcher, or long spinal board (T1), the time interval in which the test person is carried to the ambulance cot (T2), and the time interval in which the ambulance cot is rolled to the ambulance (T3). An ANOVA was performed to compare the different techniques., Results: During the simulated extrication procedures, a rigid cervical collar provided biomechanical stability at all angles with hardly any loss of time (mean angle ranges during T1: axial rotation P1S0 vs P1S1 p<0.0001, P2S0 vs P2S1 p<0.0001, P3S0 vs P3S1 p<0.0001; lateral bending P1S0 vs P1S1 p = 0.0263, P2S0 vs P2S1 p<0.0001, P3S0 vs P3S1 p<0.0001; flexion/extension P1S0 vs P1S1 p = 0.0023, P2S0 vs P2S1 p<0.0001). Of the three techniques examined, the scoop stretcher and vacuum mattress were best for reducing lateral bending in the frontal plane (mean angle ranges during T1: P2S1 vs P3S1 p = 0.0333; P2S0 vs P3S0 p = 0.0123) as well as flexion and extension in the sagittal plane (mean angle ranges during T2: P1S1 vs P2S1 p<0.0001; P1S0 vs P2S0 p<0.0001). On the other hand, the rescue sheet was clearly superior in terms of time (total duration P1S0 vs P2S0 p<0.001, P1S1 vs P2S1 p<0.001, P1S0 vs P3S0 p<0.001, P1S1 vs P3S1 p<0.001) but was always associated with significantly larger angular ranges of the cervical spine during the procedure. Therefore, the choice of technique depends on various factors such as the rescue time, the available personnel, as well as the severity of the suspected instability., Competing Interests: Martin Kieninger serves as academic editor for PLOS ONE. This does not alter our adherence to PLOS ONE policies on sharing data and materials., (Copyright: © 2023 Morag et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.)

Reproducible research and open science practices have the potential to accelerate scientific progress by allowing others to reuse research outputs, and by promoting rigorous research that is more likely to yield trustworthy results. However, these practices are uncommon in many fields, so there is a clear need for training that helps and encourages researchers to integrate reproducible research and open science practices into their daily work. Here, we outline eleven strategies for making training in these practices the norm at research institutions. The strategies, which emerged from a virtual brainstorming event organized in collaboration with the German Reproducibility Network, are concentrated in three areas: (i) adapting research assessment criteria and program requirements; (ii) training; (iii) building communities. We provide a brief overview of each strategy, offer tips for implementation, and provide links to resources. We also highlight the importance of allocating resources and monitoring impact. Our goal is to encourage researchers - in their roles as scientists, supervisors, mentors, instructors, and members of curriculum, hiring or evaluation committees - to think creatively about the many ways they can promote reproducible research and open science practices in their institutions., Competing Interests: FK, SA, AB, SF, TH, VH, CH, FA, RB, AB, NB, BC, LC, AE, KE, MF, CF, MF, AG, KG, DG, LH, MH, MI, SI, LK, MK, LK, AK, FL, DM, CM, AM, CN, HN, FP, AP, CP, RR, JR, JR, AS, SS, ES, LS, VS, MW, CW, JZ, DZ, PZ, TW No competing interests declared, (© 2023, Kohrs et al.)

Knowledge graphs have gained increasing popularity in the last decade in science and technology. However, knowledge graphs are currently relatively simple to moderate semantic structures that are mainly a collection of factual statements. Question answering (QA) benchmarks and systems were so far mainly geared towards encyclopedic knowledge graphs such as DBpedia and Wikidata. We present SciQA a scientific QA benchmark for scholarly knowledge. The benchmark leverages the Open Research Knowledge Graph (ORKG) which includes almost 170,000 resources describing research contributions of almost 15,000 scholarly articles from 709 research fields. Following a bottom-up methodology, we first manually developed a set of 100 complex questions that can be answered using this knowledge graph. Furthermore, we devised eight question templates with which we automatically generated further 2465 questions, that can also be answered with the ORKG. The questions cover a range of research fields and question types and are translated into corresponding SPARQL queries over the ORKG. Based on two preliminary evaluations, we show that the resulting SciQA benchmark represents a challenging task for next-generation QA systems. This task is part of the open competitions at the 22nd International Semantic Web Conference 2023 as the Scholarly Question Answering over Linked Data (QALD) Challenge., (© 2023. The Author(s).)

Scholarly knowledge graphs provide researchers with a novel modality of information retrieval, and their wider use in academia is beneficial for the digitalization of published works and the development of scholarly communication. To increase the acceptance of scholarly knowledge graphs, we present a dashboard, which visualizes the research contributions on an educational science topic in the frame of the Open Research Knowledge Graph (ORKG). As dashboards are created at the intersection of computer science, graphic design, and human-technology interaction, we used these three perspectives to develop a multi-relational visualization tool aimed at improving the user experience. According to preliminary results of the user evaluation survey, the dashboard was perceived as more appealing than the baseline ORKG-powered interface. Our findings can be used for the development of scholarly knowledge graph-powered dashboards in different domains, thus facilitating acceptance of these novel instruments by research communities and increasing versatility in scholarly communication., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2022 Lezhnina, Kismihók, Prinz, Stocker and Auer.)

Chronic psychosocial stress participates prominently in the etiology of various psychiatric conditions and comorbid somatic pathologies; however, suitable pharmacotherapy of these disorders is still of high medical need. During the last few decades, research on mGlu receptors advanced remarkably and much attention was given to the mGlu7 subtype. Here, genetic mGlu7 ablation, short-term pharmacological mGlu7 blockade, as well as siRNA-mediated knockdown of mGlu7 were shown to result in an acute anti-stress, antidepressant- and anxiolytic-like phenotype in mice. Moreover, we recently revealed a prominent stress-protective effect of genetic mGlu7 ablation also with respect to chronic psychosocial stress. In addition, we are able to demonstrate in the present study that the chronic pharmacological blockade of mGlu7 interferes with various chronic stress-induced alterations. For this, we used the chronic subordinate colony housing (CSC), a mouse model of chronic male subordination, in combination with chronic treatment with the mGlu7-selective orthosteric-like antagonist XAP044 (7-hydroxy-3-(4-iodophenoxy)-4H-chromen-4-one). Interestingly, XAP044 dose-dependently ameliorates hypothalamic-pituitary-adrenal axis dysfunctions, thymus atrophy, as well as the CSC-induced increase in innate anxiety. Taken together, our findings provide further evidence for the role of mGlu7 in chronic psychosocial stress-induced alterations and suggests the pharmacological blockade of mGlu7 as a promising therapeutic approach for the treatment of chronic stress-related pathologies in men.

In 2021, during the COVID-19 response, the Council of State and Territorial Epidemiologists (CSTE) conducted its seventh periodic Epidemiology Capacity Assessment (ECA), a national assessment that evaluates trends in applied epidemiology workforce size, funding, and epidemiology capacity at state health departments.* A standardized web-based questionnaire was sent to state epidemiologists in 50 states and the District of Columbia (DC). The questionnaire assessed the number of current and optimal epidemiologist positions; sources of epidemiology activity and personnel funding; and each health department's self-perceived capacity to lead activities, provide subject matter expertise, and obtain and manage resources for the three essential public health services (EPHS) most closely linked to epidemiology. † CSTE enumerated 4,136 epidemiology positions across the United States, with an additional 2,196 positions needed to provide basic public health services. From 2017 to 2021, the number of epidemiologists in state health departments increased 23%, an increase primarily accounted for by the number of those supporting the COVID-19 response § . The number of staff members decreased in program areas of infectious diseases, chronic diseases, and maternal and child health (MCH). Federal funding supports most epidemiology activities (85%) and epidemiology personnel (83%). Overall capacity to deliver the EPHS has declined, and epidemiology workforce and capacity needs remain unmet. More epidemiologists and sustainable funding are needed to consistently and effectively deliver EPHS. Additional resources (e.g., funding for competitive compensation and pathways for career advancement) are essential for recruitment and retention of epidemiologists to support public health activities across all program areas., Competing Interests: All authors have completed and submitted the International Committee of Medical Journal Editors form for disclosure of potential conflicts of interest. No potential conflicts of interest were disclosed.

Open and reproducible research practices increase the reusability and impact of scientific research. The reproducibility of research results is influenced by many factors, most of which can be addressed by improved education and training. Here we describe how workshops developed by the Reproducibility for Everyone (R4E) initiative can be customized to provide researchers at all career stages and across most disciplines with education and training in reproducible research practices. The R4E initiative, which is led by volunteers, has reached more than 3000 researchers worldwide to date, and all workshop materials, including accompanying resources, are available under a CC-BY 4.0 license at https://www.repro4everyone.org/., Competing Interests: SA, NH, TW, JE, DS, MJ, MG, BS, NJ No competing interests declared, (© 2021, Auer et al.)

Scientists routinely use images to display data. Readers often examine figures first; therefore, it is important that figures are accessible to a broad audience. Many resources discuss fraudulent image manipulation and technical specifications for image acquisition; however, data on the legibility and interpretability of images are scarce. We systematically examined these factors in non-blot images published in the top 15 journals in 3 fields; plant sciences, cell biology, and physiology (n = 580 papers). Common problems included missing scale bars, misplaced or poorly marked insets, images or labels that were not accessible to colorblind readers, and insufficient explanations of colors, labels, annotations, or the species and tissue or object depicted in the image. Papers that met all good practice criteria examined for all image-based figures were uncommon (physiology 16%, cell biology 12%, plant sciences 2%). We present detailed descriptions and visual examples to help scientists avoid common pitfalls when publishing images. Our recommendations address image magnification, scale information, insets, annotation, and color and may encourage discussion about quality standards for bioimage publishing., Competing Interests: The authors have declared that no competing interests exist.

Background: There is growing evidence that the cost for dementia care will increase rapidly in the coming years. Therefore, the objective of this paper was to determine the economic impact of treating clients with dementia in outpatient Dementia Service Centres (DSCs) and simulate the cost progression with real clinical and cost data., Methods: To estimate the cost for dementia care, real administrative and clinical data from 1341 clients of the DSCs were used to approximate the total cost of non-pharmaceutical treatment and simulate the cost progression with a discrete-time Markov chain (DTMC) model. The economic simulation model takes severity and progression of dementia into account to display the cost development over a period of up to ten years., Results: Based on the administrative data, the total cost for treating these 1341 clients of the DSCs came to 67,294,910 EUR in the first year. From these costs, 74% occurred as indirect costs. Within a five-year period, these costs will increase by 7.1-fold (16.2-fold over 10 years). Further, the DTMC shows that the greatest share of the cost increase derives from the sharp increase of people with severe dementia and that the cost of severe dementia prevails the cost in later periods., Conclusion: The DTMC model has shown that the cost increase of dementia care is mostly driven by the indirect cost and the increase of severity of dementia within any given year. The DTMC reveals also that the cost for mild dementia will decrease steadily over the time period of the simulation, whereas the cost for severe dementia increases sharply after running the simulation for 3 years.

Background: Dementia is a particularly severe societal challenge in several countries of the Danube Region due to higher-than-average increment in population longevity, disproportionate increase of the old-age dependency ratio, and selective outward migration of health care professionals. A survey was conducted among dementia experts to obtain a deeper understanding of the dementia care structures and services in this geographical area, and to identify the educational needs of health care professionals, and the availability of assistive technology., Subjects and Methods: A standardized questionnaire was sent out to 15 leading dementia experts/clinicians in 10 Danube Region countries inquiring about professional groups involved in dementia care, availability and reimbursement of services, inclusion of dementia in professional education and training, acceptability of Internet-based education, and availability of assistive technology. The authors are the survey respondents., Results: The majority of individuals with dementia receive care in the community rather than in institutions. The roles of medical specialties are disparate. General practitioners usually identify dementia symptoms while specialists contribute most to clinical diagnosis and treatment. Health care professionals, particularly those who work closely with patients and carers, have limited access to dementia-specific education and training. The greatest need for dementia-specific education is seen for general practitioners and nurses. An Internet-based education and skill-building program is considered to be equivalent to traditional face-to-face but offer advantages in terms of convenience of access. Assistive technology is available in countries of the Danube Region but is significantly underused., Conclusion: Dementia care in the Danube Region can be improved by an educational and skill-building program for health care professionals who work in the frontline of dementia care. Such a program should also attempt to enhance interdisciplinary and intersectorial collaboration, to intensify the interaction between primary care and specialists, and to promote the implementation of assistive technology., Competing Interests: The authors report that they are the survey respondents that this paper is based on. The authors report no other conflicts of interest in this work.

Objective: To summarise evidence on the preventive effects of continuing education on mild cognitive impairment and Alzheimer's-type dementia in adults 45 years or older., Design: Systematic review and overview of systematic reviews., Data Sources: We systematically searched MEDLINE, PsycINFO, EMBASE, Cochrane Central Register of Controlled Trials, Cumulative Index to Nursing and Allied Health Literature, and Scopus for published studies and grey literature databases for unpublished studies from January 1990 to April 2018., Methods: To assess evidence directly addressing our objectives, we conducted a systematic review. Because we were aware of a dearth of direct evidence, we also performed an overview of systematic reviews on leisure activities that mimic formal continuing education. We a priori established the inclusion and exclusion criteria. Two authors independently assessed inclusion and exclusion at the abstract and full-text level, rated the risk of bias, and determined the certainty of evidence using the Grading of Recommendations Assessment, Development and Evaluation. We resolved all discrepancies by consensus. We synthesised the available evidence narratively., Results: Our searches identified 4933 citations. For the systematic review, only two publications on the same prospective cohort study (Tasmanian Healthy Brain Project) met the inclusion criteria; for the overview of reviews, we included five systematic reviews. Based on 459 participants, preliminary data of the ongoing cohort study indicated that cognitive reserve statistically significantly increased in persons attending university classes compared with the control group (92.5% vs 55.7%, p<0.01). Likewise, language processing capacities statistically significantly improved (p<0.01). Episodic memory, working memory and executive function did not differ significantly between groups. Systematic reviews consistently reported a positive association between participation in cognitively stimulating leisure activities and reduced incidence of dementia and improved cognitive test performance., Conclusion: Available results demonstrate that cognitive reserve increases through continuing education and show a positive association of cognitive leisure activities with both improved cognitive function and lower dementia incidence., Prospero Registration Number: CRD42017063944., Competing Interests: Competing interests: None declared., (© Author(s) (or their employer(s)) 2019. Re-use permitted under CC BY-NC. No commercial re-use. See rights and permissions. Published by BMJ.)

Background: Marinobufagenin (MBG) is an endogenous cardiotonic steroid (CTS) that inhibits the Na+/K+-ATPase. Human MBG is significantly increased in end-stage renal disease and immunization against MBG attenuates cardiovascular fibrosis in a rat model of uremic cardiomyopathy. Mineralocorticoid antagonists (MRA) block MBG binding sites and decrease proteinuria in chronic kidney disease (CKD) patients. We therefore aimed to investigate the association of MBG and albuminuria, as a marker of renal damage, as well as MBG and decline of glomerular filtration rate (GFR)., Methods: The Graz endocrine causes of hypertension (GECOH) study is a single center study of adults routinely referred for screening of endocrine hypertension. Plasma MBG was measured by an enzyme-linked immunoassay, and in a post-hoc analysis, follow-up creatinine levels were obtained. Patients with proteinuria >3.5g/day at baseline were excluded from further evaluation., Results: We measured MBG concentrations in 40 hypertensive subjects and excluded one patient due to pre-existing proteinuria. Plasma MBG was significantly correlated with albuminuria (Spearman ρ = .357; p = .028) and proteinuria (ρ = .336; p = .039). In linear regression analysis, the association remained significant after adjustment for age, sex, and BMI (β = .306; p = .036), and for mean systolic blood pressure (β = .352; p = .034). In follow-up analyses (N = 30), MBG was significantly associated with decline in GFR after adjustment for time-to-follow-up (β = -.374; p = .042)., Conclusion: The findings suggest that MBG plasma concentrations were associated with albuminuria as well as decline in kidney function. Whether MBG predicts hard renal endpoints warrants further investigations., Competing Interests: The authors have declared that no competing interests exist.