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Background: The threat of a disaster or potential for a disaster is something that may be experienced by individuals globally. Schools are places of daily mass gatherings which make them an ideal target for mass casualty, natural disasters, and biological incidents. Methods: An integrative review using Whittemore and Knafl's model was conducted to explore peer-reviewed publications about K-12 schools and natural disasters and pandemic preparedness and planning. Results: Themes identified from the systematic review of 12 articles reflected determinants and level of school preparedness, disaster plan components, compliance with government requirements, emergency equipment, supplies, drills, and training, collaboration with outside agencies, and perceptions of school preparedness. Preparedness for disasters and biological events among schools varies and multiple factors contribute to the level of preparedness. Perceptions of school preparedness differ among school community members. Schools perceive more preparedness for disasters than their actual level. Conclusions: Our nation's schools are not adequately prepared for disasters. There is a need for further research in schools to identify and understand preparedness for disasters.

Abstract The need to develop and provide integrated observation systems to better understand and manage global and regional environmental change is one of the major challenges facing Earth system science today. In 2008, the German Helmholtz Association took up this challenge and launched the German research infrastructure TERrestrial ENvironmental Observatories (TERENO). The aim of TERENO is the establishment and maintenance of a network of observatories as a basis for an interdisciplinary and long‐term research program to investigate the effects of global environmental change on terrestrial ecosystems and their socio‐economic consequences. State‐of‐the‐art methods from the field of environmental monitoring, geophysics, remote sensing, and modeling are used to record and analyze states and fluxes in different environmental disciplines from groundwater through the vadose zone, surface water, and biosphere, up to the lower atmosphere. Over the past 15 years we have collectively gained experience in operating a long‐term observing network, thereby overcoming unexpected operational and institutional challenges, exceeding expectations, and facilitating new research. Today, the TERENO network is a key pillar for environmental modeling and forecasting in Germany, an information hub for practitioners and policy stakeholders in agriculture, forestry, and water management at regional to national levels, a nucleus for international collaboration, academic training and scientific outreach, an important anchor for large‐scale experiments, and a trigger for methodological innovation and technological progress. This article describes TERENO's key services and functions, presents the main lessons learned from this 15‐year effort, and emphasizes the need to continue long‐term integrated environmental monitoring programmes in the future.

In his comment (Kowalski 2023) on our recent publication (Heiskanen et al. 2022) where we present the Integrated Carbon Observation System (ICOS) research infrastructure, Andrew Kowalski introduces three important and, [...]

PurposeThe significance of atraumatic electrode array (EA) insertion in cochlear implant (CI) surgery is widely acknowledged, with consensus that forces due to EA insertion are directly correlated with insertion trauma. Unfortunately, the manual perception of these forces through haptic feedback is inherently limited, and techniques for in vivo force measurements to monitor the insertion are not yet available. Addressing this gap, we developed of a force-sensitive insertion tool capable of capturing real-time insertion forces during standard CI surgery.MethodsThis paper describes the tool and its pioneering application in a clinical setting and reports initial findings from an ongoing clinical study. Data and experiences from five patients have been evaluated so far, including force profiles of four patients.ResultsThe initial intraoperative experiences are promising, with successful integration into the conventional workflow. Feasibility of in vivo insertion force measurement and practicability of the tool’s intraoperative use could be demonstrated. The recorded in vivo insertion forces show the expected rise with increasing insertion depth. Forces at the end of insertion range from 17.2 mN to 43.6 mN, while maximal peak forces were observed in the range from 44.8 mN to 102.4 mN.ConclusionWe hypothesize that this novel method holds the potential to assist surgeons in monitoring the insertion forces and, thus, minimizing insertion trauma and ensuring better preservation of residual hearing. Future data recording with this tool can form the basis of ongoing research into the causes of insertion trauma, paving the way for new and improved prevention strategies.

In research on cochlear implants, preclinical testing of newly developed electrode arrays and surgical tools is an essential procedure, which requires the availability of a suitable testing environment. For this purpose, human temporal bone specimens are most realistic, but their availability is limited and additional parameters such as insertion forces are hardly measurable. Therefore, the aim of this study was to develop a temporal bone phantom with realistic anatomical structures for intracochlear force measurement. The temporal bone was segmented from CBCT data of a human cadaver head. The segmented model was 3D printed with an additional artificial skin layer to enable the simulated use of surgical instruments such as a self-retaining retractor. A mechanically decoupled artificial cochlear model was realistically positioned within the temporal bone and was furthermore attached to a force sensor. The usability of the phantom was evaluated by performing automated EA insertions using an automated hydraulic insertion device. The experiments showed that the insertion forces within the cochlea could be measured without interferences from surrounding structures. Moreover, the artificial skin provided a rigid interface for the insertion tool. The new phantom is a realistic testing and training platform for cochlear implant electrode insertions with the advantage of measureable insertion forces.

Introduction: In cochlear implant surgery, the insertion of the electrode array (EA) into the cochlea is critical as its implementation can influence the preservation of residual hearing. Insertion tests are the primary method for basic research on parameters influencing the insertion and help to further improve the design of EAs and surgical techniques. With automated insertion devices close to clinical application, a consensus on optimal insertion parameters is needed, which requires reliable testing methods. Moreover, the limited availability of EAs needs to be considered. We propose a test setup that provides high repeatability and flexibility for various research questions. Methods: Design requirements for multiple types of experiments such as variability of insertion speed or trajectory as well as cochlear geometry guided the computer aided design of the test bench. Moreover, repeated insertions with the same EA were supposed to be possible. To evaluate its functionality, insertion tests into a 3D printed cochlea model were performed and recorded. Results: The central components of the test bench are a linear actuator driving the EA and a goniometer changing the orientation of the target - a cochlea model or a specimen. A force sensor can be mounted below the target to measure forces in its frame of reference. The experimental results show high reproducibility of insertion forces for recurring trajectories with a single EA. Conclusion: The test bench enables reproducible insertion tests with a high number of repetitions and reduced EA usage. This allows a more detailed investigation of broadly discussed influences on the insertion such as the insertion speed or trajectory as well as cochlear geometry and can thereby drive future EA development.

Abstract Both carbon dioxide uptake and albedo of the land surface affect global climate. However, climate change mitigation by increasing carbon uptake can cause a warming trade-off by decreasing albedo, with most research focusing on afforestation and its interaction with snow. Here, we present carbon uptake and albedo observations from 176 globally distributed flux stations. We demonstrate a gradual decline in maximum achievable annual albedo as carbon uptake increases, even within subgroups of non-forest and snow-free ecosystems. Based on a paired-site permutation approach, we quantify the likely impact of land use on carbon uptake and albedo. Shifting to the maximum attainable carbon uptake at each site would likely cause moderate net global warming for the first approximately 20 years, followed by a strong cooling effect. A balanced policy co-optimizing carbon uptake and albedo is possible that avoids warming on any timescale, but results in a weaker long-term cooling effect.

Abstract Forests play a major role in the global carbon cycle, and droughts have been shown to explain much of the interannual variability in the terrestrial carbon sink capacity. The quantification of drought legacy effects on ecosystem carbon fluxes is a challenging task, and research on the ecosystem scale remains sparse. In this study we investigate the delayed response of an extreme drought event on the carbon cycle in the mixed deciduous forest site ’Hohes Holz’ (DE-HoH) located in Central Germany, using the measurements taken between 2015 and 2020. Our analysis demonstrates that the extreme drought and heat event in 2018 had strong legacy effects on the carbon cycle in 2019, but not in 2020. On an annual basis, net ecosystem productivity was $$\sim 16\,\%$$ ∼ 16 % higher in 2018 ( $$\sim 424\,{\hbox {g}_{\text {C}}}\hbox {m}^{-2}$$ ∼ 424 g C m - 2 ) and $$\sim 25\,\%$$ ∼ 25 % lower in 2019 ( $$\sim 274\,{\hbox {g}_{\text {C}}}\hbox {m}^{-2}$$ ∼ 274 g C m - 2 ) compared to pre-drought years ( $$\sim 367\,{\hbox {g}_{\text {C}}}\hbox {m}^{-2}$$ ∼ 367 g C m - 2 ). Using spline regression, we show that while current hydrometeorological conditions can explain forest productivity in 2020, they do not fully explain the decrease in productivity in 2019. Including long-term drought information in the statistical model reduces overestimation error of productivity in 2019 by nearly $$50\,\%$$ 50 % . We also found that short-term drought events have positive impacts on the carbon cycle at the beginning of the vegetation season, but negative impacts in later summer, while long-term drought events have generally negative impacts throughout the growing season. Overall, our findings highlight the importance of considering the diverse and complex impacts of extreme events on ecosystem fluxes, including the timing, temporal scale, and magnitude of the events, and the need to use consistent definitions of drought to clearly convey immediate and delayed responses.

Objectives To aid in selecting the optimal artificial intelligence (AI) solution for clinical application, we directly compared performances of selected representative custom-trained or commercial classification, detection and segmentation models for fracture detection on musculoskeletal radiographs of the distal radius by aligning their outputs.Design and setting This single-centre retrospective study was conducted on a random subset of emergency department radiographs from 2008 to 2018 of the distal radius in Germany.Materials and methods An image set was created to be compatible with training and testing classification and segmentation models by annotating examinations for fractures and overlaying fracture masks, if applicable. Representative classification and segmentation models were trained on 80% of the data. After output binarisation, their derived fracture detection performances as well as that of a standard commercially available solution were compared on the remaining X-rays (20%) using mainly accuracy and area under the receiver operating characteristic (AUROC).Results A total of 2856 examinations with 712 (24.9%) fractures were included in the analysis. Accuracies reached up to 0.97 for the classification model, 0.94 for the segmentation model and 0.95 for BoneView. Cohen’s kappa was at least 0.80 in pairwise comparisons, while Fleiss’ kappa was 0.83 for all models. Fracture predictions were visualised with all three methods at different levels of detail, ranking from downsampled image region for classification over bounding box for detection to single pixel-level delineation for segmentation.Conclusions All three investigated approaches reached high performances for detection of distal radius fractures with simple preprocessing and postprocessing protocols on the custom-trained models. Despite their underlying structural differences, selection of one’s fracture analysis AI tool in the frame of this study reduces to the desired flavour of automation: automated classification, AI-assisted manual fracture reading or minimised false negatives.

Abstract Eddy covariance sites are ideally suited for the study of extreme events on ecosystems as they allow the exchange of trace gases and energy fluxes between ecosystems and the lower atmosphere to be directly measured on a continuous basis. However, standardized definitions of hydroclimatic extremes are needed to render studies of extreme events comparable across sites. This requires longer datasets than are available from on-site measurements in order to capture the full range of climatic variability. We present a dataset of drought indices based on precipitation (Standardized Precipitation Index, SPI), atmospheric water balance (Standardized Precipitation Evapotranspiration Index, SPEI), and soil moisture (Standardized Soil Moisture Index, SSMI) for 101 ecosystem sites from the Integrated Carbon Observation System (ICOS) with daily temporal resolution from 1950 to 2021. Additionally, we provide simulated soil moisture and evapotranspiration for each site from the Mesoscale Hydrological Model (mHM). These could be utilised for gap-filling or long-term research, among other applications. We validate our data set with measurements from ICOS and discuss potential research avenues.