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A new method is presented to efficiently estimate daily groundwater level time series at unmonitored sites by linking groundwater dynamics to local hydrogeological system controls. The proposed approach is based on the concept of comparative regional analysis, an approach widely used in surface water hydrology, but uncommon in hydrogeology. Using physiographic and climatic site descriptors, the method utilizes regression analysis to estimate cumulative frequency distributions of groundwater levels (groundwater head duration curves, HDC) at unmonitored locations. The HDC is then used to construct a groundwater hydrograph using time series from distance‐weighted neighboring monitored (donor) locations. For estimating times series at unmonitored sites, in essence, spatio‐temporal interpolation, stepwise multiple linear regression (MLR), extreme gradient boosting (XGB), and nearest neighbors are compared. The methods were applied to 10‐year daily groundwater level time series at 157 sites in unconfined alluvial aquifers in Southern Germany. Models of HDCs were physically plausible and showed that physiographic and climatic controls on groundwater level fluctuations are nonlinear and dynamic, varying in significance from "wet" to "dry" aquifer conditions. XGB yielded a significantly higher predictive skill than nearest neighbor and MLR. However, donor site selection is of key importance. The study presents a novel approach for regionalization and infilling of groundwater level time series that also aids conceptual understanding of controls on groundwater dynamics, both central tasks for water resources managers. Key Points: Daily groundwater levels at unmonitored sites are estimated through transfer of head duration curves based on the similarity of site characteristics at monitored sitesNonlinearity of controls on groundwater levels favors using of Machine Learning (e.g., regression trees) over multiple linear regression for predictionThe dynamic nature of controls on groundwater levels can be disentangled, which is central for studies of recharge seasonality, droughts, and floods [ABSTRACT FROM AUTHOR]

Objectives: ST-elevation myocardial infarction (STEMI) is an Acute Myocardial Infarction (AMI) with the greatest risk of death and disability. Getting diagnosed patients rapid definitive treatment at the correct facility is crucial in improving their outcome. Using a Question-and-Answer algorithm (Mobile Priority Dispatch System (MPDS ® )), trained Emergency Medical Dispatchers (EMDs) can help identifying STEMI at the time of dispatch. This can assist Emergency Medical Services (EMS) pre-planning transport to potential STEMI-receiving hospitals. The study aimed to determine whether hospital-confirmed STEMI cases transported by ambulance are associated with certain dispatch determinant codes and identify the treatments performed., Methods: The retrospective study analyzed deidentified dispatch and hospital data of STEMI patients who were transported by Qatar's Ambulance Service between January 2018 and May 2021. Data analysis compared patient demographics with dispatch measures, considering chief complaint and determinant codes, and Percutaneous Coronary Intervention (PCI) treatment received., Results: A total of 3,724 STEMI cases with MPDS ® dispatch codes were retrieved. After excluding patient transfer and pandemic-related cases, a final sample of 2,607 cases was analyzed. Most STEMI patients (86.0%) were classified as high priority levels at dispatch, had chest pain as chief complaint (62.9%), and were male (90.8%). Approximately, 99.0% of the STEMI patients received PCI treatment. Distributions of STEMI cases and PCI treatment did not significantly differ by patient demographics and dispatch measures., Conclusions: Qatar's STEMI patients are more likely to be male and to receive adequate acute care irrespective of any demographic factor and despite potential language issues. This study highlights that the chief complaint may be described or interpreted differently when the questioning language is not their mother tongue, or when there is a language barrier between the caller, call taker, or when using the MPDS ® protocols language or when self-translating questions instantly in another language. Therefore, EMDs should be made aware of the language differences and be encouraged to further clarify the chief complaint when appropriate. There may be a need for potential refinements of the MPDS ® questioning algorithm and EMD training with AMI symptoms reinforcement. This could help improve their early identification of STEMI cases with non-classic chest pain symptoms.

Earthquakes present severe hazards for people and economies and can be primary drivers of landscape change yet their impact to river-channel networks remains poorly known. Here we show evidence for an abrupt earthquake-triggered avulsion of the Ganges River at ~2.5 ka leading to relocation of the mainstem channel belt in the Bengal delta. This is recorded in freshly discovered sedimentary archives of an immense relict channel and a paleo-earthquake of sufficient magnitude to cause major liquefaction and generate large, decimeter-scale sand dikes >180 km from the nearest seismogenic source region. Precise luminescence ages of channel sand, channel fill, and breached and partially liquefied floodplain deposits support coeval timing of the avulsion and earthquake. Evidence for reorganization of the river-channel network in the world's largest delta broadens the risk posed by seismic events in the region and their recognition as geomorphic agents in this and other tectonically active lowlands. The recurrence of comparable earthquake-triggered ground liquefaction and a channel avulsion would be catastrophic for any of the heavily populated, large river basins and deltas along the Himalayan arc (e.g., Indus, Ganges, Brahmaputra, Ayeyarwady). The compounding effects of climate change and human impacts heighten and extend the vulnerability of many lowlands worldwide to such cascading hazards., (© 2024. The Author(s).)

Neurotoxic compounds can interfere with active gill ventilation in fish, which might lead to premature death in adult fish, but not in skin-breathing embryos of zebrafish, since these exclusively rely on passive diffusion across the skin. Regarding lethality, this respiratory failure syndrome (RFS) has been discussed as one of the main reasons for the higher sensitivity of adult fish in the acute fish toxicity test (AFT), if compared to embryos in the fish embryo toxicity test (FET). To further elucidate the relationship between the onset of gill respiration and death by a neurotoxic mode of action, a comparative study into oxygen consumption (MO 2 ), breathing frequency (f v ) and amplitude (f ampl ) was performed with 4 d old skin-breathing and 12 d old early gill-breathing zebrafish. Neurotoxic model substances with an LC 50 FET/AFT ratio of > 10 were used: chlorpyrifos, permethrin, aldicarb, ziram, and fluoxetine. Exposure to hypoxia served as a positive control, whereas aniline was tested as an example of a narcotic substance interfering non-specifically with gill membranes. In 12 d old larvae, all substances caused an increase in MO 2 , f v and partly f ampl , whereas effects were minor in 4 d old embryos. An increase of f v in 4 d old embryos following exposure to chlorpyrifos, aldicarb and hypoxia could not be correlated with an increased MO 2 and might be attributed either to (1) to the successfully postponed decrease of arterial partial pressure of oxygen (PO 2 ) through support of skin respiration by increased f v , (2) to an unspecific stimulation of the sphincter muscles at the base of the gill filaments, or (3) to the establishment of oxygen sensing for later stages. In gill-breathing 12 d old zebrafish, a concentration-dependent increase of f v was detected for aniline and chlorpyrifos, whereas for aldicarb, fluoxetine and permethrin, a decline of f v at higher substance concentrations was measured, most likely due to the onset of paralysis and/or fatigue of the gill filament sphincter muscles. Since alterations of f v serve to postpone the decrease in arterial PO 2 and MO 2 increased with decreasing f v , the respiratory failure syndrome could clearly be demonstrated in 12 d old zebrafish larvae. Passive respiration across the skin in zebrafish embryos could thus be confirmed as a probable reason for the lower sensitivity of early life-stages to neurotoxicants. Integration of respiratory markers into existing testing protocols with non-protected developmental stages such as embryos might help to not underestimate the toxicity of early life-stages of fish., Competing Interests: Declaration of competing interest The authors declare the following financial interests/personal relationships which may be considered as potential competing interests. Dr. Thomas Braunbeck reports financial support was provided by German Federal Ministry of Education and Research (BMBF). 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. Published by Elsevier B.V.)

Quantum magnonics investigates the quantum-mechanical properties of magnons, such as quantum coherence or entanglement for solid-state quantum information technologies at the nanoscale. The most promising material for quantum magnonics is the ferrimagnetic yttrium iron garnet (YIG), which hosts magnons with the longest lifetimes. YIG films of the highest quality are grown on a paramagnetic gadolinium gallium garnet (GGG) substrate. The literature has reported that ferromagnetic resonance (FMR) frequencies of YIG/GGG decrease at temperatures below 50 K despite the increase in YIG magnetization. We investigated a 97 nm-thick YIG film grown on 500 μm-thick GGG substrate through a series of experiments conducted at temperatures as low as 30 mK, and using both analytical and numerical methods. Our findings suggest that the primary factor contributing to the FMR frequency shift is the stray magnetic field created by the partially magnetized GGG substrate. This stray field is antiparallel to the applied external field and is highly inhomogeneous, reaching up to 40 mT in the center of the sample. At temperatures below 500 mK, the GGG field exhibits a saturation that cannot be described by the standard Brillouin function for a paramagnet. Including the calculated GGG field in the analysis of the FMR frequency versus temperature dependence allowed the determination of the cubic and uniaxial anisotropies. We find that the total crystallographic anisotropy increases more than three times with the decrease in temperature down to 2 K. Our findings enable accurate predictions of the YIG/GGG magnetic systems behavior at low and ultralow millikelvin temperatures, crucial for developing quantum magnonic devices., Competing Interests: Competing interestsThe authors declare no competing interests., (© The Author(s) 2024.)

This article describes the design and evaluation of a virtual field trip on the topic of radioactive waste management research for university education. We created an interactive virtual tour through the Mont Terri underground research laboratory by enhancing the virtual experiment information system, designed for domain experts, with background information, illustrations, tasks, tests, and an improved user interface. To put the tour's content into context, a conventional introductory presentation on the final disposal of radioactive waste was added. A user study with 22 participants proved a good perceived usability of the virtual tour and the virtual field trip's ability to transfer knowledge. These results suggest a benefit of employing virtual field trips in geoscientific university courses. In addition, it is conceivable to use the virtual field trip as a tool for science communication in the context of participatory processes during nuclear waste disposal site selection processes.

The conduit flow process (CFP) for MODFLOW's groundwater flow model is an advanced approach for investigating complex groundwater systems, such as karst, with coupled discrete-continuum models. CFP represents laminar and turbulent flow in a discrete pipe network coupled to a matrix continuum. However, the preprocessing demand is comparatively high to generate the conduit network and is usually performed with graphical user interfaces. To overcome this limitation and allow a scalable, reproducible, and comprehensive workflow, existing and new routines were aggregated to a Python package named CFPy, to allow script-based modeling that harmonizes well with the available and widely used FloPy package. CFPy allows information about the location and geometry of the conduit network to be considered by user-specific approaches or by sophisticated methods such as stochastic conduit network generators. The latter allows the automatic generation of many model variants with differing conduit networks for advanced investigations like multi-model approaches in combination with automatic parameter estimation. Additional postprocessing routines provide powerful control and valuable insights for CFP applications. In this methods note, a general technical description of the approach is complemented with two examples that guide users and demonstrate the main capabilities of CFPy., (© 2023 The Authors. Groundwater published by Wiley Periodicals LLC on behalf of National Ground Water Association.)

Stress responses of fish to disruption of oxygen homeostasis include adjusted oxygen consumption rate (MO 2 ) as well as the hyperventilation consisting of changes in breathing frequency (f v ) and amplitude (f ampl ). However, studying the HVR in very small organisms such as zebrafish (Danio rerio) embryos and larvae is challenging, and breathing movements (i.e., f v ) are usually manually counted, which is time- and human resource-intense, error-prone and does not provide information on the amplitude of breathing movements of the response, the breathing amplitude (f ampl ). Hence, in the present study, a new automated method was developed to simultaneously measure f v and f ampl in small zebrafish embryos and larvae with the computer software DanioScope™. To compare HVR strategies at different life-stages of zebrafish and the physiologically linked MO 2 , hatched 4 d old embryos and early gill-breathing 12 d old larvae were treated with the HVR-inducing neurotoxic compound lindane (γ-hexachlorocyclohexane; γ-HCH) as a model substance. Comparison of manually counted f v with f v data measured by DanioScope™ at both life-stages showed high to moderate agreement between the two methods with respect to f v in control fish and in fish treated with lower lindane concentrations (3 - 18% deviation at 25 µg/L γ-HCH). With increasing lindane concentrations (100 and 400 µg/L γ-HCH), however, manual counts showed an average underestimation of f v by up to 30%, mainly due to very fast, rapidly successive, and indistinct movements of the fish, which cannot be properly detected by manual counts. Automated measurement thus proved significantly more sensitive, although several pre- and post-processing steps are needed. The improved automated detection of f v and the first reliable estimation of f ampl in small fish embryos and larvae, as well as the inclusion of MO 2 , may provide new insights into different respiratory strategies and may, thus, represent a tool to lower the detection limit for reactions of different life-stages of fish to environmental stressors. In the present study, this became evident, as early gill-breathing 12 d old zebrafish larvae showed symptoms of respiratory failure (i.e., increase in f v , f ampl and MO 2 , followed by subsequent lethargy) after exposure to lindane, whereas skin-breathing in 4 d old embryos proved mainly insensitive to the paralytic effects of lindane., Competing Interests: Declaration of Competing Interest The authors 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 © 2023 Elsevier B.V. All rights reserved.)

Chernozems/Phaeozems are important agricultural resources and have been intensively used for millennia. However, their origin and age are still controversial. In Europe, the westernmost widespread Chernozem/Phaeozem area is located in Central Germany. In contrast to other German regions with anthropogenic Chernozems/Phaeozems, their natural origin is suggested in connection with intensive bioturbation. Yet, radiocarbon is unsuitable for decoding Chernozem/Phaeozem formation so this hypothesis remains untested, whereas single-grain luminescence dating allows to discriminate between different soil sub-processes and formation phases. We applied single-grain feldspar luminescence to a Central German Chernozem that was buried during the Bronze Age and subsequently protected from pedogenic processes. For the first time, we could directly determine timing and rate of Chernozem/Phaeozem formation in Central Europe by dating bioturbation as the dominant soil forming process. Accordingly, Chernozem/Phaeozem formation started at the latest in the Early Holocene prior to Neolithic settlement indicating a natural origin of Central German Chernozems/Phaeozems, and Chernozem/Phaeozem formation ceased around 6-5 ka when the regional climate became more humid. Our effective soil reworking rates show that earthworm bioturbation in Chernozems/Phaeozems is more intense than ant-dominated bioturbation, but significantly less intense than bioturbation by lugworms or ploughing. The latter effect allows to identify prehistoric ploughing in paleosols., (© 2023. The Author(s).)

Karst aquifers are important sources of fresh water on a global scale. The hydrological modelling of karst spring discharge, however, still poses a challenge. In this study we apply a transfer function noise (TFN) model in combination with a bucket-type recharge model to simulate karst spring discharge. The application of the noise model for the residual series has the advantage that it is more consistent with assumptions for optimization such as homoscedasticity and independence. In an earlier hydrological modeling study, named Karst Modeling Challenge (KMC; Jeannin et al., J Hydrol 600:126-508, 2021), several modelling approaches were compared for the Milandre Karst System in Switzerland. This serves as a benchmark and we apply the TFN model to KMC data, subsequently comparing the results to other models. Using different data-model-combinations, the most promising data-model-combination is identified in a three-step least-squares calibration. To quantify uncertainty, the Bayesian approach of Markov-chain Monte Carlo (MCMC) sampling is subsequently used with uniform priors for the previously identified best data-model combination. The MCMC maximum likelihood solution is used to simulate spring discharge for a previously unseen testing period, indicating a superior performance compared to all other models in the KMC. It is found that the model gives a physically feasible representation of the system, which is supported by field measurements. While the TFN model simulated rising limbs and flood recession especially well, medium and baseflow conditions were not represented as accurately. The TFN approach poses a well-performing data-driven alternative to other approaches that should be considered in future studies., Competing Interests: Conflict of interestThe authors have no competing interests to declare that are relevant to the content of this article., (© The Author(s) 2023.)

Smart health presents an ever-expanding attack surface due to the continuous adoption of a broad variety of Internet of Medical Things (IoMT) devices and applications. IoMT is a common approach to smart city solutions that deliver long-term benefits to critical infrastructures, such as smart healthcare. Many of the IoMT devices in smart cities use Bluetooth technology for short-range communication due to its flexibility, low resource consumption, and flexibility. As smart healthcare applications rely on distributed control optimization, artificial intelligence (AI) and deep learning (DL) offer effective approaches to mitigate cyber-attacks. This paper presents a decentralized, predictive, DL-based process to autonomously detect and block malicious traffic and provide an end-to-end defense against network attacks in IoMT devices. Furthermore, we provide the BlueTack dataset for Bluetooth-based attacks against IoMT networks. To the best of our knowledge, this is the first intrusion detection dataset for Bluetooth classic and Bluetooth low energy (BLE). Using the BlueTack dataset, we devised a multi-layer intrusion detection method that uses deep-learning techniques. We propose a decentralized architecture for deploying this intrusion detection system on the edge nodes of a smart healthcare system that may be deployed in a smart city. The presented multi-layer intrusion detection models achieve performances in the range of 97-99.5% based on the F1 scores.