dataesr/scientific-paragraphs-categorization huggingface dataset:
The main motivation behind the development of the DK-model HIP was that end users, who plan for and implement adaptation measures, needed a more detailed national dataset for shallow groundwater levels, soil moisture, and streamflow, with easy access to results and boundary conditions from the national model for screening, planning, and local submodels. The previous 500 m national DK-model based on the MIKE SHE/MIKE HYDRO model code did not provide sufficient spatial resolution and accuracy for the shallow groundwater. Finally, an enhancement of the deliverables with more detailed monthly, seasonal, and extreme event results of climate change impacts for the future climate was demanded by end users  [26, 27]. some urban and peri-urban areas, but at the same time, drought frequency is projected to increase  [23, 24].
The consequences especially challenge water security, which is critical in Denmark with a 100% groundwater-based drinking water supply. Consequences of increasing shallow groundwater level  [25]  can be mobilized pollutants, increased leaching of nutrients, water in cellars, damages to buildings and infrastructure, and consequences for human or environmental health (Figure  1 ). The main motivation behind the development of the DK-model HIP was that end users, who plan for and implement adaptation measures, needed a more detailed national dataset for shallow groundwater levels, soil moisture, and streamflow, with easy access to results and boundary conditions from the national model for screening, planning, and local submodels. The previous 500 m national DK-model based on the MIKE SHE/MIKE HYDRO model code did not provide sufficient spatial resolution and accuracy for the shallow groundwater.
The DK-model is run as a transient model with daily climate forcing and a maximum time step of 24 h. The model is calibrated against a large dataset of river stream flow (305 stations) and groundwater level records (29,000 wells). For further details on model construction and calibration, please refer to  [26, 32, 33]. The physical-based DK-model HIP simulates the entire terrestrial hydrological cycle in an integrated manner at a national scale for Denmark. The model is a numerical gridded model based on the MIKE SHE software and is used to simulate coupled 3D subsurface flow, 2D overland flow, rootzone and evapotranspiration processes, and 1D kinematic routing of streamflow. The DK-model is run as a transient model with daily climate forcing and a maximum time step of 24 h. The model is calibrated against a large dataset of river stream flow (305 stations) and groundwater level records (29,000 wells).
Throughout the construction of the DK-model, the model code MIKE SHE-MIKE Hydro from DHI was the applied software for the modeling. All model results from the 500 m and 100 m models have been delivered (5 TB of data) to the HIP portal to be freely accessible for climate change adaptation planning (CCA), water management, and disaster risk reduction (DRR). In addition to model results for various seasons, months, and daily time series, various hydrological observations are displayed on the HIP portal. As part of the HIP portal project, data from five Danish regions for groundwater levels have been transferred to the JUPITER database, and groundwater levels from JUPITER are displayed on HIP, updated in real time. Observations and estimates of daily discharge and water level data and extreme value estimates have been delivered by the Danish EPA and DCE.
Discharge data are updated every year. Climate data and sea level scenarios are available from DMI's database (Klimaatlas). GEUS used bias-corrected and downscaled results from 22 regional climate models based on distribution-based scaling  [36]. For the calibration of the model (see details in the HIP documentation report), a total of 667,568 groundwater level observations were used, of which 40,103 intakes (27%) are observing shallow groundwater, as well as time series of discharge from about 300 stations. Additionally, water levels from 20,470 small lakes were used as a proxy of the uppermost groundwater table. The model is parameterized with nationwide parameter sets to enhance spatial consistency. Initial, full calibration was conducted for the 500 m version, with a subsequent transfer of parameters and partial recalibration of the 100 m version based on ten 100 m submodels, each of a size of 500-1000 km 2 (see Figure  3 ).
Hydrological Information and Prediction System (the HIP Portal) The HIP portal is an open geodata tool that visualizes and provides access to large, free-of-charge national datasets about hydrological conditions and how they are expected to change with a warmer and wetter climate in the future. Data on depth to the groundwater table (phreatic depth), soil moisture, and discharge are available (daily simulations for 1990-2019). Furthermore, it is possible to download a wide range of boundary conditions (groundwater infiltration, recharge to aquifers, etc. ). Downstream services (Figure  2 ) can access data from the HIP portal through an API. This is used, for example, by the KAMP portal, which is a screening tool that compares selected national data, calculations, and projections and is aimed, in particular, at supporting planning and environmental tasks in local governments.
KAMP shows areas where possible climate change impacts may require attention. KAMP can also be used to determine how many buildings and kilometers of road potentially can be affected by flooding, and it can estimate the value of the buildings and constructions at risk for damages. The tool also contains an option that allows downloading of QGIS files, allowing further work on the same dataset and map sections in the user's system. KAMP was developed in collaboration between the Danish Natural Environment Portal and the Danish EPA in consultation with the national association of municipalities, KL, the Danish Business Authority, Central Region Denmark, and several selected municipalities. KAMP is available at https://en. klimatilpasning. dk/ ("URL(accessed on 1 December 2022)"). For the moment, a beta version of the real-time model is being tested (DK-model HIP 100 m real-time).
Within the near future, all of Denmark will be run operationally with daily updates. A database API will be developed and indices for soil moisture, depth to shallow groundwater, deep groundwater, and streamflow will be added, and data transfer and file formats developed to transfer data between the Danish Meteorological Institute (DMI), Geological Survey of Denmark and Greenland (GEUS) and Agency for Data Supply and Infrastructure (SDFI). SDFI will take care of making the real-time data publicly available on the HIP portal, and facilitating the stakeholder engagement process as part of the design of the portal. Figure  6  shows the monthly time series of wetness and drought anomalies for soil moisture, shallow and deep groundwater level, and streamflow for 2010-2019. The HIP portal is an open geodata tool that visualizes and provides access to large, free-of-charge national datasets about hydrological conditions and how they are expected to change with a warmer and wetter climate in the future.
Data on depth to the groundwater table (phreatic depth), soil moisture, and discharge are available (daily simulations for 1990-2019). Furthermore, it is possible to download a wide range of boundary conditions (groundwater infiltration, recharge to aquifers, etc. ). Downstream services (Figure  2 ) can access data from the HIP portal through an API. Supply and Infrastructure (SDFI). SDFI will take care of making the real-time data publicly available on the HIP portal, and facilitating the stakeholder engagement process as part of the design of the portal. Figure  6  shows the monthly time series of wetness and drought anomalies for soil moisture, shallow and deep groundwater level, and streamflow for 2010-2019. Figure  7  shows the spatial distribution of the indices for Denmark for the summer of 2018.
e. , land surface temperature or crop types, are added to the model. The regional water table is added from the DK-model HIP at 100 m resolution to inform the peatland plug-in ML model. Prescriptive quality: The HIP model is a physically based model; hence, we assume that it somewhat reasonably represents the different fluxes (many of which we cannot directly quantify, but still are interested in, such as drainage flow, etc. ). It also runs with demand-driven irrigation, and actual extraction amounts. Prescriptive quality, in the sense of the model being as simple and consistent as a reference model, is strived for. Prescriptive quality is also a matter of transparency of the model, which we believe is high since observed discharge and groundwater level data and performance results at calibration locations are shown on the HIP portal.
Who Are the Users of the Hydrological Services in Denmark (HIP Portal & DT)? Municipal and climate adaptation planners will use (and already are using) data on the entire hydrological cycle to better assess opportunities for storing excess water, which often happens in close cooperation with water utilities. There is a need for calculated extreme events for depth to groundwater table and streamflow discharge, in addition to precipitation. Water utilities also express this need for good access to data about the entire hydrological cycle in order to avoid wrong investments and choose the most appropriate means of action, as well as use boundary conditions to develop their own local models, e. g. , for watercourses. Municipal planners will typically use model calculations of the depth to shallow groundwater to avoid inappropriate urban planning and improve the database for case processing, for example, to assess where it is possible to build, or whether there is a need for drainage or terrain raising in relation to new build construction.
The new high-resolution shallow groundwater depth maps in a 10-100 m grid will be used as a screening basis to identify areas in the local plan where prevention measures must be specified, demands can be made for seepage of surface water, or solutions for local drainage of rainwater (SUDS) can be developed  [43, 46]. Information about inundation along watercourses will also be used to make agreements with landowners about compensation schemes, and this will be able to reduce case-processing time. Municipal planners also expect that consultant hours can be saved on some tasks, and that it will be possible to set up local models with a significantly smaller grid size at a cheaper price if boundary conditions from HIP are used. User stories from consulting engineers also express the expectation that modeling tasks will be delivered with lower costs due to the better access to data and boundary conditions.
The Protection Agency or an upstream municipality will use model calculations and data from HIP to assess the need for regulation, weed cutting, and retention of water to delay downstream water flow, as well as the preparation of long-term watercourse regulations using model-calculated future scenarios for water flow, e. g. , using drought and flood scenarios for the future. The wastewater officer will use all ground-level hydrological data, but especially stream data, to assess the consequences of discharge permits. Groundwater workers will use near-surface groundwater maps to assess possible consequences of setting up and decommissioning extraction wells, as well as consequences for nature and the environment. The watercourse employee will use both measurements and model calculations of water flow and water level, as well as model-calculated effects of climate change, preferably converted to water level (water level calculations are not supplied with the HIP project, but there is an option to download model-calculated water flow and model uncertainties, which can be converted to water level).
The high density of model calculation points in HIP (approximately every 0. 5 km) (compared to 300 to 600 measuring stations in streams) can be used as boundary conditions together with available local measurements. Water supply and utility employees express a great need for data and model calculations of shallow groundwater to plan the installation of basins, pumps, buildings, etc. , as well as to be able to assess the effects of closing a well or sealing a sewer, which could cause groundwater flooding. It is expected that a more targeted effort can be made against infiltrating groundwater in sewer systems (sewer renovation and renovation prioritization), which will also provide a better function of treatment plants and could reduce the substance load in Danish water bodies. The design of the drainage system and other construction projects are generally expected to be optimized technically, economically, and functionally.
It will be avoided that plants are destroyed, and operating costs will be reduced. It is expected that better sewerage investments will provide more robust (fewer floods), attractive, and safe cities. There is a need for screening maps for shallow groundwater levels in the present and future, as well as historical data and model calculations for streamflow and water levels in streams and the sea for the preparation of flood maps for the municipality. The purpose is generally to obtain an overview of potential challenges related to project planning (including urban planning) and choose the most appropriate means of meeting these challenges. Data and model calculations for streams will also be used to assess the capacity and robustness of streams in relation to discharges and storage of water near streams (instead of the establishment of basins) while at the same time avoiding backflow from streams to the sewage systems.
Seepage basins will be established, taking into account recipient impact (nature and environment). Outfalls will be planned to be future-proofed, and pipes and basins will be designed in appropriate sizes for efficient water diversion and storage, also for the future. The supply worker wants access to both dynamic and statistical calculations for water flow, and needs to know the maximum level of the water table in 10, 20, 50, and 100 years, including the effect of coupled events (ocean-stream), as well as the uncertainty of model calculations. The water supply worker sees it as a great advantage that easy and unified access to stream data from different data owners is created in HIP. There is also a strong desire for joint access to water level data for both streams and the sea (coastal zones) in HIP.
Model-calculated effects of climate change will be used in the transport sector to identify intervention areas that may be affected by flooding in the future, either from rising groundwater or rainwater. Better access to ground-level bearing data and water flow data will also be used for more efficient groundwater mapping throughout the country, and more water level data in a common database will be used to make better calculations of water flow that will be used by municipalities and advisors. Agriculture will benefit from the model-calculated depth to groundwater close to the ground in the short and long term, so that it is possible to distribute effort and prioritization of the fields differently, so that land that is not thought to be suitable for cultivation can, for example, be used for storing water.
The Integration of Observations and Model Results in HIP DT Visualization Planning and climate change adaptation tools/portals such as the HIP DT are unique since they build upon an integrated groundwater-surface water dynamical model which hereby provides a system model that is absolutely necessary when evaluating climate change impacts for shallow and deep groundwater, interactions with surface water, and changes in precipitation, temperature, and evapotranspiration. One of the key strengths of the national HIP DT is the possibility to compare time series of shallow and deep groundwater levels from the model with observations available in the JUPITER national database. The transparency of model performance is supported by the visualization of daily time series from model and observations, with calculated statistics making it easy to compare statistics on an annual basis, and for wet and dry extreme values.
Not only are shallow groundwater levels available with daily values for the 30-year period, but, in addition, various percentiles and return values are available for each 100 m grid and each of more than 50,000 streamflow points. In some cases, the model will be wrong or uncertain; in other cases, observations are biased or wrong. By integrating both datasets and displaying and visualizing data on the HIP portal, the basic idea of the digital twin gains momentum, and users, area for area, can evaluate where the model has a good enough performance at a screening level, or where observations indicate that there can be something missing in the model structure, the process description, or the input data, and, eventually, the boundary conditions  [23]. Another major feature and strength of HIP DT is the possibility of utilizing the highresolution 10 m national map, obtained with machine learning.
The HIP DT and KAMP are mainly for screening purposes. KAMP focuses on spatial planners in municipalities and a wide set of areal data, and HIP DT provides data, useful for the professional user, consultants, and employees at municipalities, regions, and state agencies. Besides these users, researchers can also dive into the huge dataset on shallow groundwater. Citizens, with some help from more experienced users, can search for valuable information from the HIP DT, KAMP, JUPITER, or other tools available from the national climate change adaptation portal: www. klimatilpasning. dk "URL(accessed on 1 December 2022)"). Nature-based solutions (recommended by the EU commission) only provide a few adaptation measures against high groundwater levels (there are many more NBSs for too-low groundwater levels).
The EIF4E-ALDH1B1 complex facilitates ferroptosis In addition to EIF4G1, EIF4E also binds to other proteins under certain conditions  45, 46. Using immunoprecipitation in combination with mass spectrometry, we examined the interactome of EIF4E during RSL3induced ferroptosis (Supplementary Data 3). We compared our data with 130 known EIF4E-binding proteins reported in the protein-protein interaction database STRING (search tool for the retrieval of interacting genes/proteins)  47. Regardless of the sample, 46 known EIF4E-binding proteins in the STRING database were confirmed in HT-1080 and Calu-1 cells (Supplementary Data 3). We further identified seven upregulated EIF4E-binding proteins that were at least twofold (including copine 3 [CPNE3], prostaglandin E synthase 2 [PTGES2], isoleucyl-tRNA synthetase 1 [IARS], ALDH1B1, glutathione S-transferase omega 1 [GSTO1], hydroxysteroid 17-beta dehydrogenase 4 [HSD17B4], and choline/ethanolamine phosphotransferase 1 [CEPT1]) in both HT-1080 and Calu-1 cells following RSL3 treatment (Fig.
Lipid peroxidation assay Cells were seeded at 1 × 10 5 cells per well into 12-well plates and incubated with the indicated treatments in 5% CO 2 at 37 °C. During the last 30 min of incubation, 1 μg/ml of Hoechst 33342 (Thermo Fisher Scientific, 62249) and 10 μM BODIPY 581/591 C11 (Thermo Fisher Scientific, D3861) dyes were added. After the cells were washed with PBS, they were imaged using an EVOS imaging system (Thermo Fisher Scientific). Image analysis was conducted with Image J software (version 1. 52 v) based on 8-10 random fields. The relative lipid peroxidation was quantified by using the ratio of green fluorescence intensity (BODIPY 581/591 C11-oxidized) to red fluorescence intensity (BODIPY 581/591 C11-reduced)  26.
FENIX assay The fluorescence-enabled inhibited autoxidation (FENIX) microplatebased assay was performed according to the previous protocol  85. In brief, egg phosphatidylcholine liposomes (1 mM), STY-BODIPY (1 µM), and the indicated compounds (10 μM) were vortexed in PBS (pH7. 4), then 297 µl aliquots of the mixture were incubated in black 96-well polypropylene plate in a BioTek Synergy H1 plate reader at 37 °C for 10 min. The plate was ejected from the plate reader and the autoxidation was initiated by adding 3 µL aliquots of (2,2-azobis(2-amidinopropane)dihydrochloride (AAPH, 1 mM), followed by a mixing protocol for 5 min. The kinetic data of [STY-BODIPYox] was acquired by excitation of the probes at 488 nm and emission was measured at 518 nm.
qPCR analysis Total RNA was extracted and purified from cultured cells using the RNeasy Plus Mini Kit (QIAGEN, 74136). First-strand cDNA was synthesized from 1 µg of RNA using the iScript cDNA Synthesis Kit (Bio-Rad, 1708890). Briefly, 20-µl reactions were prepared by combining 4 µl of iScript Select reaction mix, 2 µl of gene-specific enhancer solution, 1 µl of reverse transcriptase, 1 µl of gene-specific assay pool (20×, 2 µM), and 12 µl of RNA diluted in ribonuclease-free water. The cDNA from various cell samples was then amplified by real-time qPCR with specific primers using the CFX96 Touch Real-Time PCR Detection System (Bio-Rad) with the CFX Manager Software (Bio-Rad, version 3. 1). The gene expression was calculated via the 2 -ΔΔCt method and normalized to 18SRNA. The relative concentrations of mRNA were expressed in arbitrary units based on the untreated group, which was assigned a value of 1.
Chemiluminescence substrate was applied using the SuperSignal West Pico Chemiluminescent Substrate (Thermo Fisher Scientific, 34080) or the SuperSignal West Femto Maximum Sensitivity Substrate (Thermo Fisher Scientific, 34095), and blots were analyzed using the ChemiDoc Touch Imaging System (Bio-Rad) and Image Lab Software (Bio-Rad, version 6. 1)  77. The information on antibodies is shown in Supplementary Table  1.
Peptide identification by database search MS/MS spectra were searched using the Mascot search engine (version 2. 4. 0, Matrix Science Ltd. ) against the UniProt human proteome database (https://www. uniprot. org/proteomes?facets=superkingdom %3AEukaryota&query = %2A). The modifications used were the following: static modification of cysteine (carboxyamidomethylation, +57. 05 Da), variable modification of methionine (oxidation, +15. 99 Da), and protein N-terminal acetylation. The mass tolerance was set to 1. 4 Da for the precursor ions and 0. 8 Da for the fragment ions. Peptide identifications were filtered using PeptideProphet and ProteinProphet algorithms with a protein threshold cutoff of 99% and a peptide threshold cutoff of 90% implemented in Scaffold (Proteome Software, Portland, OR, USA).
Iron assay The relative Fe 2+ concentration in cells was assessed using an Iron Assay Kit (Sigma-Aldrich, MAK025). Briefly, cells (2 × 10 6 ) were homogenized in 4-10 volumes of iron assay buffer and the samples were centrifuged at 16,000 × g for 10 min to remove insoluble materials to collect the supernatants. To measure ferrous iron, we added 50 μl samples to sample wells in a 96-well plate and brought the volume to 100 μl per well with 5 μl assay buffer. After incubation of the reaction at 37 °C for 30 min, the absorbance at 593 nm was measured using a microplate reader. The sample concentration was counted based on the standard curve.
They also completed the Autism-Spectrum Quotient Test (AQ), a measure of the autism-spectrum traits, sensitive to interindividual differences in the general population, with respect to socially relevant cognitive abilities  ( Baron-Cohen et al. , 2001 ; Ruzich et al. , 2015 ). With caution due to a small sample size for correlational analyses, we used this dataset to begin exploring the test-retest reliability of the 2BIE, and the relationship between the 2BIE and the AQ. We aimed to provide first-pass indication that the way in which individuals process social scenes can capture individual differences in the visuoperceptual foundations of social cognition.