bluuebunny/crossref_metadata_2025_split huggingface dataset:
Designing Expert-Augmented Clinical Decision Support Systems to Predict Mortality Risk in ICUs
Authors: Chen Johannes , Lowin Maximilian , Kellner Domenic , Hinz Oliver , Adam Elisabeth Hannah , Ippolito Angelo , Wenger-Alakmeh Katharina 
Published: August 2023

AbstractOne of the most critical infrastructures during the COVID-19 pandemic are intensive care units (ICU). ICU’s crucial task is to preserve the lives of patients and mitigate the pandemic’s impact on the population. However, most ICUs plan only one day ahead. This short-term planning becomes an obstacle during disaster situations since physicians need to decide efficiently and ensure the timely treatment of high-risk patients. Integrating machine learning (ML) systems for clinical decision support could improve this process by predicting the mortality risk of critically ill patients. Several ML approaches tackling this problem have already shown promising results. However, these systems mostly neglect the integration of explicit domain knowledge, which is crucial to ensure prediction quality and adaptability. Otherwise, black-box systems might base their decision on confounding variables and improper relationships. Following design science research, we utilize a unique dataset of patients diagnosed with SARS-CoV-2 in ICU care to design a clinical decision support system by combining ML and expert knowledge in the form of a severity score. We show that by augmenting the system with expert knowledge, its overall performance improves compared to the baseline approach.
Chitosan-coated nanostructured lipid carriers for effective brain delivery of Tanshinone IIA in Parkinson’s disease: interplay between nuclear factor-kappa β and cathepsin B
Authors: Hassan Donia M. , El-Kamel Amal H. , Allam Eman A. , Bakr Basant A. , Ashour Asmaa A. 
Published: August 2023

AbstractParkinson’s disease (PD) is the second most common progressive neurodegenerative disorder associated with increased oxidative stress, the underlying vital process contributing to cell death. Tanshinone IIA (TAN) is a phytomedicine with a documented activity in treating many CNS disorders, particularly PD owing to its unique anti-inflammatory and antioxidant effect. However, its clinical utility is limited by its poor aqueous solubility, short half-life, and hence low concentration reaching targeted cells. This work aimed to develop a biocompatible chitosan-coated nanostructured lipid carriers (CS-NLCs) for effective brain delivery of TAN for PD management. The proposed nanosystem was successfully prepared using a simple melt-emulsification ultra-sonication method, optimized and characterized both in vitro and in vivo in a rotenone-induced PD rat model. The developed TAN-loaded CS-NLCs (CS-TAN-NLCs) showed good colloidal properties (size ≤ 200 nm, PDI ≤ 0.2, and ζ-potential + 20 mV) and high drug entrapment efficiency (> 97%) with sustained release profile for 24 h. Following intranasal administration, CS-TAN-NLCs succeeded to achieve a remarkable antiparkinsonian and antidepressant effect in diseased animals compared to both the uncoated TAN-NLCs and free TAN suspension as evidenced by the conducted behavioral tests and improved histopathological findings. Furthermore, biochemical evaluation of oxidative stress along with inflammatory markers, nuclear factor-kabba β (NF-Kβ) and cathepsin B further confirmed the potential of the CS-TAN-NLCs in enhancing brain delivery and hence the therapeutic effect of TAN of treatment of PD. Accordingly, CS-TAN-NLCs could be addressed as a promising nano-platform for the effective management of PD.
Graphical abstract
Empirical model to assess leaching of pesticides in soil under a steady-state flow and tropical conditions
Authors: Mosquera-Vivas C. S. , Celis-Ossa R. E. , González-Murillo C. A. , Obregón-Neira N. , Martínez-Cordón M. J. , Guerrero-Dallos J. A. , García-Santos G. 
Published: August 2023

Abstract
An empirical model of leaching of pesticides was developed to simulate the concentration of fungicides throughout unsaturated soil. The model was based on chemical reactions and the travel time of a conservative tracer to represent the travel time required for water to flow between soil layers. The model’s performance was then tested using experimental data from dimethomorph and pyrimethanil applied to the soil under field and laboratory conditions. The empirical model simulated fungicide concentration on soil solids and in soil solution at different depths over time (mean square error between 2.9 mg2 kg−2 and 61mg2 kg−2) using sorption percentages and degradation rates under laboratory conditions. The sorption process was affected by the organic carbon, clay, and the effective cation exchange capacity of the soil. The degradation rate values of dimethomorph (0.039 d−1–0.009 d−1) and pyrimethanil (0.053 d−1–0.004 d−1) decreased from 0 to 40 cm and then remained constant in deeper soil layers (60–80 cm). Fungicide degradation was a critical input in the model at subsurface layers. The model was determined to be a reliable mathematical tool to estimate the leachability of pesticides in tropical soil under a steady-state flow. It may be extended to other substances and soils for environmental risk assessment projects.

Graphical abstract
Adaptive optimal sliding-mode fault-tolerant control for nonlinear systems with disturbances and estimation errors
Authors: Du Yanbin , Jiang Bin , Ma Yajie 
Published: August 2023

AbstractThis paper gives a fault-tolerant control scheme concerning with the optimal and near-optimal system performance for a class of nonlinear systems with time-varying actuator faults, time-varying disturbances, and identification errors of the neural network-based identifier. In this paper, the adaptive dynamic programming method is directly used to design the optimal sliding surface, so that the designer can design the target dynamics of the sliding mode in advance. In addition, the barrier function-based sliding-mode control is used to cope with the bounded but boundary-unknown estimation errors of the identifier, and the method ensures that the sliding-mode variable converges to the designer’s predefined neighborhood of zero in finite time and the control gain is not overestimated. Specifically, first, by adaptive dynamic programming, near-optimal sliding surface is designed in the sense of the quadratic optimal criterion. Second, a neural network identifier is designed to model the lumped uncertainties including actuator faults and disturbances. Third, a barrier function-based adaptive sliding-mode control is used to cope with the identification errors of the neural network identifier and has no control gain overestimation, which can guarantee to confine the sliding variable to a predefined vicinity of the proposed sliding surface. For this system with faults and disturbances, it is shown that near-optimal property is achieved by this scheme, the chattering phenomenon is effectively suppressed, and the reconstruction error of the neural network identifier with unknown boundary is effectively handled by the adaptive sliding-mode control based on the barrier function. The proof of stability is given by Lyapunov’s direct method and the effectiveness of this control scheme is verified by applying it to the spacecraft attitude system.
Development of in vitro cardiovascular tissue models within capillary circuit microfluidic devices fabricated with 3D stereolithography printing
Authors: Esparza Aibhlin , Jimenez Nicole , Joddar Binata , Natividad-Diaz Sylvia 
Published: August 2023

AbstractThis study presents the development and morphology analysis of bioinspired 3D cardiovascular tissue models cultured within a dynamic capillary circuit microfluidic device. This study is significant because our in vitro 3D cardiovascular tissue models retained within a capillary circuit microfluidic device provide a less expensive, more controlled, and reproducible platform for more physiologically-relevant evaluation of cellular response to microenvironmental stimuli. The overall aim of our study is to demonstrate our cardiovascular tissue model (CTM) and vascular tissue model (VTM) actively changed their cellular morphology and exhibited structural reorganization in response to biophysical stimuli provided by microposts within the device tissue culture chambers during a 5-day period. The microfluidic device in this study was designed with the Young–Laplace and Navier–Stokes principles of capillary driven fluid flow and fabricated with 3D stereolithography (SLA) printing. The cardiac tissue model and vascular tissue model presented in this study were developed by encapsulating AC16 cardiomyocytes (CTM) and Human umbilical vein endothelial cells (VTM) in a fibrin hydrogel which were subsequently loaded into a capillary circuit microfluidic device. The cardiovascular tissue models were analyzed with fluorescent microscopy for morphological differences, average tube length, and cell orientation. We determined the VTM displayed capillary-like tube formation and the cells within both cardiovascular tissue models continued to elongate around microposts by day-5 which indicates the microfluidic system provided biophysical cues to guide cell structure and direction-specific organization.
Study on the effects of drying–wetting cycles on the dynamic elasticity modulus of weathered red sandstone soil
Authors: Deng Yunye 
Published: August 2023

AbstractIn this paper, the effect of drying–wetting cycles on the dynamic elasticity modulus of weathered red sandstone soil was studied based on a series of unconsolidated undrained dynamic triaxial tests under different confining pressures and with the help of the Hardin–Drnevich model. The main results from this work as follows: (1) Hardin–Drnevich model can well express the hyperbolic behaviors of dynamic backbone curves of the weathered red sandstone soil exposed to drying–wetting cycles. (2) Both the maximum dynamic elasticity modulus and the dynamic elastic modulus of the weathered red sandstone soil decreased linearly with numbers of drying–wetting cycles under a certain confining pressure. The dynamic elasticity modulus decreased non-linearly with the increase of dynamic strain. (3) The maximum dynamic elastic modulus of the weathered red sandstone soil decreased by 19.62% to 70.91%, 21.16% to 71.07%, and 29.53% to 77.36%, respectively after 3 to 12 drying–wetting cycles under confining pressures of 100, 200, and 300 kPa. The rate at which the maximum dynamic elastic modulus decreases is basically the same under different confining pressures.
Mind the Gap: Uneven and Unequal Experiences of Youth Citizenship
Authors: Wood Bronwyn E. 
Published: August 2023

AbstractWhile the field of youth citizenship has grown in recent years, many ‘gaps’ still exist. This commentary paper takes a critical look at three of these gaps in youth citizenship studies, namely (i) the Global North/Global South gap in understandings about youth citizenship, (ii) the citizenship status and empowerment gap, and (iii) the citizenship opportunity and participation gap. The paper argues that unless these gaps are attended to, we have a distortion in what we know about youth citizenship as the understandings and young people profiled (predominantly the Global North, elite, White and well resourced) represent only a small subsection of the whole, thus ignoring the experiences, knowledge, stories and voices of many diverse young citizens.
Estimation of Soil Surface Roughness Parameters Under Simulated Rainfall Using Spectral Reflectance in Optical Domain
Authors: Herodowicz‐Mleczak Karolina , Piekarczyk Jan , Ratajkiewicz Henryk , Nowosad Jakub , Śledź Szymon , Kaźmierowski Cezary , Królewicz Sławomir , Kierzek Roman 
Published: August 2023

AbstractThe purpose of the study was to evaluate the possibility of parameterizing the state of soil surface roughness (SSR) based on proximal measurements of spectral reflectance in the VIS‐NIR range, which is important for the needs of monitoring the state of soil surfaces. SSR should be constantly monitored as it provides an insight into a range of hydrological and erosive soil processes and improves the interpretation of remote sensing data. SSR and the spectral reflectance of three texturally different soils were measured under simulated rainfall in laboratory condition. The relationship between the SSR parameters and soil spectra was determined using regression random forest models. Various spectral data processing methods were tested and the best wavelengths for SSR description after rainfall were found. Two roughness indices were used to describe the SSR: Height Standard Deviation (HSD) and T3D (Tortuosity index). Although both shared a significant correlation with SSR, the T3D index demonstrated a more pronounced rainfall effect and a closer correlation with spectral data than HSD. The best determination of T3D was obtained with the raw spectra (RAW) (R2 = 0.71), as well as with spectra transformed with the baseline alignment first derivative (BA1d) method (R2 = 0.71) or the Savitzky‐Golay (SG) method (R2 = 0.69). Different wavelengths were the best SSR predictors depending on the spectral transformation method (VIPs ‐ Variable Importance in Projection). For both roughness indices, the NIR wavelengths (725–820 nm) yielded the highest VIP Score in models based on RAW spectra, while those in the VIS region (450–772 nm) were most important in models based on transformed spectra.
Predicting Hydrological Change in an Alpine Glacierized Basin and Its Sensitivity to Landscape Evolution and Meteorological Forcings
Authors: Aubry‐Wake Caroline , Pomeroy John W. 
Published: August 2023

AbstractShifting precipitation patterns, a warming climate, changing snow dynamics and retreating glaciers are occurring simultaneously in glacierized mountain headwaters. To predict future hydrological behavior in an exemplar glacierized basin, a spatially distributed, physically based cold regions process hydrological model including on and off‐glacier process representations was applied to the Peyto Glacier Research Basin in the Canadian Rockies. The model was forced with bias‐corrected outputs from a high‐resolution Weather and Research Forecasting (WRF‐PGW) atmospheric simulation for 2000–2015, and under pseudo‐global warming for 2085–2100 under a business‐as‐usual climate change scenario. The simulations show that the end‐of‐century increase in precipitation nearly compensates for the decreased ice melt associated with almost complete deglaciation, resulting in a decrease in annual streamflow of 7%. However, the timing of streamflow advances drastically, with peak flow shifting from July to June, and August streamflow dropping by 68%. To examine the sensitivity of future hydrology to possible future drainage basin biophysical attributes, the end‐of‐century simulations were run under a range of initial conditions and parameters and showed the highest sensitivity to initial ice volume and surface water storage capacity. This comprehensive examination suggests that hydrological compensation between declining icemelt and increasing rainfall and snowmelt runoff as well as between deglaciation and increasing basin depressional storage capacity play important roles in determining future streamflow in a rapidly deglaciating high‐mountain environment. Conversely, afforestation and soil development had relatively smaller impacts on future hydrology.
Large‐Scale Groundwater Monitoring in Brazil Assisted With Satellite‐Based Artificial Intelligence Techniques
Authors: Renna Camacho Clyvihk , Getirana Augusto , Rotunno Filho Otto Corrêa , Mourão Maria Antonieta A. 
Published: August 2023

AbstractHere, we develop and test an artificial intelligence (AI)‐based approach to monitor major Brazilian aquifers. The approach combines Gravity Recovery and Climate Experiment (GRACE) data and ground‐based hydrogeological measurements from Brazil's Integrated Groundwater Monitoring Network at hundreds of wells distributed in 12 aquifers across the country. We tested model ensembles based on three AI approaches: Extreme Gradient Boost, Light Gradient Boosting Model and CatBoost, followed by a Linear Regression step. The approach is further boosted with wavelet and seasonal decomposition processes applied to GRACE data. To determine the AI‐based model's sensitivity to data availability, we propose four experiments combining hydrogeological measurements from different aquifers. Groundwater storage (GWS) estimates from the Global Land Data Assimilation System (GLDAS) are used as benchmark. A sensitivity analysis shows that the LR‐based model ensemble is the best suited and to reproduce GWS change in all studied Brazilian aquifers. Results show that the proposed approach outperforms GLDAS in all experiments, with an root mean square error (RMSE) value of 2.68 cm for the experiment that covers all monitored wells in Brazil. GLDAS resulted in RMSE = 6.76 cm. Using our AI model outputs, we quantified the GWS change of two major aquifers, Urucuia and Bauru‐Caiuá, over the past two decades: −31 and −6 km3, respectively. Water loss is driven by a prolonged drought across most of the country and intensification of groundwater pumping for irrigation. This study demonstrates that combining satellite data and AI can be a cost‐effective alternative to monitor poorly equipped aquifers at the continental scale, with possible global replicability.
Effects of Submerged Flexible Vegetation on Scalar Transport in an Open‐Channel Flow
Authors: Wang Jianyu , He Guojian , Huang Lei , Dey Subhasish , Fang Hongwei 
Published: August 2023

AbstractScalar transport in vegetated flow plays an important role in natural river ecology. In this study, a scalar transport model for the flow with flexible submerged vegetation is developed. The turbulent structure and scalar transport characteristics in the flow without vegetation, and with rigid and flexible vegetation are compared. The results show that the scalar diffusion in the flow is mainly governed by the turbulent diffusion outside the diffusion boundary layer. The wake flow downstream of rigid vegetation and the small‐scale Kelvin–Helmholtz (KH) vortices near the top of the canopy are the main reasons to enhance the turbulence intensity in the flow and to significantly increase the turbulence diffusion of scalars. However, the flexible vegetation movement induces the large‐scale KH vortices near the top of the canopy. It also causes to increase the turbulence intensity in the flow, to redistribute the scalar concentration in a wide range, to increase the scalar concentration across the flow depth, and to increase the scalar turbulence diffusion intensity. In the flow with rigid vegetation, the values of the turbulent Schmidt number vary from 0.72 to 1.93 below the top of the canopy, while in the flow with flexible vegetation, they vary from 0.58 to 1.99 only near the top of the canopy. Above the top of the canopy, the Schmidt number ranges from 0.48 to 0.84. The results are useful for the parameterization of scalar transport in natural vegetated rivers.
Forest Soil Carbon Efflux Evaluation Across China: A New Estimate With Machine Learning
Authors: Sun Hongru , Bond‐Lamberty Ben , Hu Tianyu , Li Juan , Jian Jinshi , Xu Zhenzhu , Jia Bingrui 
Published: August 2023

AbstractForest soil respiration (Rs) plays an important role in the carbon balance of terrestrial ecosystems. China's forest occupies a large part of the world's forest. However, due to the lack of integrated observation data and appropriate upscaling methodologies, substantial uncertainties exist in the Rs evaluation, which limits our understanding of the carbon balance. Here, we re‐evaluated the total soil carbon effluxes across China by combining field observations from 634 published annual Rs with a machine learning technique (i.e., Random Forest (RF)). Our results revealed that the combination of systematic measurements with the RF model allowed a definite estimate. The average annual Rs was 773.6 g C m−2 yr−1, ranging from 404.6 to 1,772.3 g C m−2 yr−1. Total forest soil carbon effluxes amounted to 1.17 Pg C yr−1 in China. Geographically, annual Rs showed a clear spatially increasing trend from northeast to southwest. Forest type is an important factor in determining the soil respiration rate. Bamboo and Evergreen broadleaf forests were higher than other types of forests. These results provide a unique insight into the magnitudes and mechanisms of soil CO2 emissions in China's forest ecosystems.
Fire Characteristics and Hydrologic Connectivity Influence Short‐Term Responses of North Temperate Lakes to Wildfire
Authors: McCullough Ian M. , Brentrup Jennifer A. , Wagner Tyler , Lapierre Jean‐Francois , Henneck Jerald , Paul Andrea M. , Belair Mathilde , Moritz Max. A. , Filstrup Christopher T. 
Published: August 2023

AbstractDespite increasing wildfires, few studies have investigated seasonal water quality responses to wildfire characteristics (e.g., burn severity) across a large number of lakes. We monitored 30 total lakes (15 burned, 15 control) monthly following the Greenwood Fire in Minnesota, USA, a lake‐rich region with historically prevalent wildfire. We found increases in median concentrations of total nitrogen (68%), total phosphorus (70%), dissolved organic carbon (127%), total suspended solids (71%), and reduced water clarity (48%) and pH (0.45) in burned lakes. Post‐wildfire responses in drainage lakes were often persistent or cumulative throughout the open‐water season, compared to isolated lakes. Total phosphorus (TP) increased linearly with watershed high‐severity burns, and shoreline high‐severity burns explained more variation in TP than lake morphometry and watershed variables. Post‐wildfire chlorophyll‐a responses were nonsignificant and inconsistent, possibly due to light limitation. Our results suggest that increasing wildfires have significant potential to affect water quality of inland lakes.
Study of Atmospheric Ion Escape From Exoplanet TOI‐700 d: Venus Analogs
Authors: Nishioka T. , Seki K. , Sakata R. , Yamamoto K. , Terada N. , Sakai S. , Shinagawa H. , Nakayama A. 
Published: August 2023

AbstractTOI‐700 d is the first Earth‐sized planet in the habitable zone (HZ) discovered by the Transiting Exoplanet Survey Satellite. Here, we assess whether a Venus‐like exoplanet at the TOI‐700 d location could retain an atmosphere for a time comparable to the age of the host star based on multispecies magnetohydrodynamics simulations. We investigate the effects of X‐ray and EUV (XUV) radiation from the host star, the interplanetary magnetic field (IMF) orientation, and the planetary intrinsic magnetic field. In unmagnetized cases, major ion loss is caused by O+ escape through a ring‐shaped region by the mass loading process after the ionization of the extended oxygen corona. As the IMF Parker spiral angle increases, the escape flux in the magnetotail shows stronger enhancement around the meridional current sheet, and the escape rate of molecular ions ( and ) increases by an order of magnitude due to acceleration in the ionosphere by magnetic tension forces. In magnetized cases, the intrinsic magnetic field suppresses ion pickup loss from the neutral oxygen corona by deflecting the stellar wind and preventing ion pickup while promoting cusp‐origin escape from the lower ionosphere. These results suggest that the unmagnetized exoplanet would have difficulty retaining its atmosphere over a few billion years under extreme conditions where XUV is 30 times stronger than at the current Earth. However, the dipole intrinsic magnetic field of 1,000 nT at the equatorial surface reduces the escape rate and would help the exoplanet to retain its atmosphere even under strong XUV conditions.