bluuebunny/crossref_metadata_2025 huggingface dataset:
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

This 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

This 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

In 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

While 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.
Occupational Silica Exposure as a Potential Risk for Microscopic Polyangiitis
Authors: Alp Alper , Ersoy Melike , Meteoğlu İbrahim , Kahraman Çetin Nesibe , Akdam Hakan , Yeniçerioğlu Yavuz
Published: August 2023

Microscopic polyangiitis is an important and common component of cytoplasmic antibody–associated vasculitides that can lead to serious morbidity and even death. A clear causative etiology has not been identified. Although silica is well known to produce lung damage, the negative renal effects of silica exposure should not be overlooked. We present a case of renal dysfunction associated with silica exposure, its diagnosis by renal biopsy, and the treatment method used. Environmental or occupational silica exposure can cause microscopic polyangiitis. Working in occupations with increased risk of silica exposure may result in serious medical problems.
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

The 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

Shifting 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

Here, 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

Scalar 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

Forest 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

Despite 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

TOI‐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.
Evaluation of Spectral Wave Models Physics as Applied to a 100‐Year Southern Hemisphere Extra‐Tropical Cyclone Sea State
Authors: Meucci Alberto , Young Ian R. , Pepler Acacia , Rudeva Irina , Ribal Agustinus , Bidlot Jean‐Raymond , Babanin Alexander V.
Published: August 2023

Extreme significant wave height estimates, and their probability of exceedance, are fundamental offshore and coastal engineering design parameters. These estimates are characterized by uncertainty due to an incomplete understanding of the atmosphere‐ocean energy and momentum exchanges during intense storms. This particularly affects extreme wave statistics of ocean regions exposed to large and frequent synoptic disturbances such as Extra‐Tropical Cyclones (ETCs). In this work, we assessed the performance of global phase‐averaged spectral wave models in representing the 1 in 100‐year sea state generated by a Southern Ocean ETC in April 2021. We collected in situ and remote sensing observations, from the storm generation region to its decaying phase and the impact on South‐East Australian coastlines. We compared the observations with a suite of reanalysis and hindcast global wave model data sets. While comparing well for wind speed up to 20 m/s, the models presented differences in solving the air‐sea momentum exchange between the atmosphere and the ocean for wind speed velocities between 20 and 35 m/s, which are a distinctive characteristic of ETCs. Despite marked differences in the storm generation region, the models converged to a similar representation of the swell systems impacting the South‐East Australian coastlines, as demonstrated by a comparison with deep‐water buoy observations close to the coastlines. Furthermore, we found that the energy of the ERA5 reanalysis, which assimilates satellite wave height measurements is quickly dispersed and, as such, of little advantage in representing the 9.9 m significant wave heights that impacted the South‐East Australian coastlines on 10 April 2021.
Estimating the Maximum Safe Pumping Rate in Sloping Unconfined Coastal Aquifers
Authors: Sun Jiazhi , Wu Huiqiang , Yin Jina , Lu Chunhui
Published: August 2023

Unconfined coastal aquifers with a sloping aquifer bed are ubiquitous. However, most analytical solutions previously developed to estimate pumping‐induced seawater intrusion considered a horizontal aquifer bed. In this study, we first developed a steady‐state analytical solution to quantify the maximum safe pumping rate in sloping unconfined coastal aquifers with a fixed‐flux inland boundary condition, using the single potential approach. The analytical solution corrected by an empirical factor is validated against the numerical simulation, which reproduces the corresponding numerical results well. It is found that coastal aquifers with a higher aquifer bed toward inland (i.e., a positive sloping angle) yield a higher maximum safe pumping rate than that of coastal aquifers with a horizontal aquifer base, since the elevated freshwater head prevents seawater intrusion and enhances groundwater pumping. Specifically, for the aquifer bases with the sloping angle of 0.01 and −0.01, the maximum safe pumping rate is increased by 42.6% and decreased by 48.4%, respectively, in comparison to the case of a horizontal aquifer base, suggesting that neglecting the aquifer base slop can result in a significant error in estimating the maximum safe pumping rate. Moreover, the sensitivity analysis reveals that the maximum safe pumping rate increases with a lower hydraulic conductivity and a larger dispersivity. Our results provide valuable insights into the effect of the aquifer base slope on the maximum safe pumping in coastal aquifers, and analytical solutions developed can serve as a powerful tool for quick assessment of pumping‐induced seawater intrusion in sloping unconfined coastal aquifers.
Hydraulic Tomography Estimates Improved by Zonal Information From the Clustering of Geophysical Survey Data
Authors: Wang Chenxi , Illman Walter A.
Published: August 2023

Hydraulic tomography (HT) has been demonstrated as a robust approach to characterize subsurface heterogeneity through the inverse modeling of multiple pumping data. However, smooth or even erroneous tomograms can result when insufficient observations are involved in the inversion. In this study, the feasibility of integrating geophysical survey data into HT analysis is investigated. First, k‐means clustering is utilized to extract zonal information from borehole geophysical logs, and a new type of spatial constraints containing geological knowledge is proposed to obtain improved hydrostratigraphic boundaries along boreholes. Next, zonation models are constructed by applying clustering‐based zone geometry and populating zonal estimates of hydraulic conductivity (K) from analyzing pumping data. Afterwards, zonation models are treated as the initial guess of spatial variability in the geostatistical inversion of HT analysis. Additionally, local K measurements can be utilized to further improve HT estimates. Comparative cases of HT analyses are designed for a numerical sandbox experiment to highlight the HT performance integrated with geophysical surveys, in which the geostatistical inversion is initialized with: (a) a homogeneous K field; (b) zonation models built by the clustering of disparate geophysical surveys with/without spatial constraints; and (c) zonation improved by incorporating local K measurements. Based on ln K field comparisons and validation through predictions of drawdowns and tracer plume migration from independent tests not used in the calibration effort, we find that integration of geophysical surveys into HT analysis by clustering with spatial constraints is demonstrated as an effective approach, and local K measurements can further improve HT estimates.
Predicting 3D Physical Properties From a Single 2D Slice Based on Convolutional Neural Networks: 2D‐Slice‐To‐3D‐Properties for Porous Rocks
Authors: Chen Xiaojun , Yang Junwei , Ma Lin , Rabbani Arash , Babaei Masoud
Published: August 2023

The 3D physical properties of porous rocks directly determine the subsurface flow and modeling. However, predicting a wide range of 3D physical rocks remains a formidable challenge and requires a large amount of input. Reliable microstructure‐property correlations can accurately predict 3D physical properties, avoiding time‐consuming experimental testing. Here, we propose a new dimensionless convolutional neural network (CNN)‐based method to find inherent correlations for accurately predicting 3D properties of porous rocks using only a single 2D slice or a series of 2D slices. Training and testing were conducted on 9 properties of 16,409 semi‐realistic 3D porous rocks. Eight properties, except for the formation factor, were predicted with an acceptable correlation coefficient of 0.92. Furthermore, the modeling results indicate that the network architecture of the model has a significant impact on its performance. The classical CNN Model 4 achieved an average validating loss of 1.0 × 10−3. Interval 2D slice sampling can significantly reduce the computational cost in training model. The developed model was verified and tested by five independent porous samples. Additionally, the proposed method accurately predicted permeability in different directions using only 2D slices trained in one direction, for porous rocks where anisotropy is not significant. This work demonstrates the ability to predict various 3D properties rapidly and accurately using only a single 2D slice from semi‐realistic 3D volumes. It provides insights into the conversion of 2D slices to 3D properties for porous media in a wide range of applications, including property estimation from 2D images without structural construction and simulation in 3D.
Exploiting the fibroblast growth factor receptor-1 vulnerability to therapeutically restrict the MYC-EZH2-CDKN1C axis-driven proliferation in Mantle cell lymphoma
Authors: Sircar Anuvrat , Singh Satishkumar , Xu-Monette Zijun Y. , Coyle Krysta Mila , Hilton Laura K. , Chavdoula Evangelia , Ranganathan Parvathi , Jain Neeraj , Hanel Walter , Tsichlis Philip , Alinari Lapo , Peterson Blake R. , Tao Jianguo , Muthusamy Natarajan , Baiocchi Robert , Epperla Narendranath , Young Ken H. , Morin Ryan , Sehgal Lalit
Published: August 2023

Mantle cell lymphoma (MCL) is a lethal hematological malignancy with a median survival of 4 years. Its lethality is mainly attributed to a limited understanding of clinical tumor progression and resistance to current therapeutic regimes. Intrinsic, prolonged drug treatment and tumor-microenvironment (TME) facilitated factors impart pro-tumorigenic and drug-insensitivity properties to MCL cells. Hence, elucidating neoteric pharmacotherapeutic molecular targets involved in MCL progression utilizing a global “unified” analysis for improved disease prevention is an earnest need. Using integrated transcriptomic analyses in MCL patients, we identified a Fibroblast Growth Factor Receptor-1 (FGFR1), and analyses of MCL patient samples showed that high FGFR1 expression was associated with shorter overall survival in MCL patient cohorts. Functional studies using pharmacological intervention and loss of function identify a novel MYC-EZH2-CDKN1C axis-driven proliferation in MCL. Further, pharmacological targeting with erdafitinib, a selective small molecule targeting FGFRs, induced cell-cycle arrest and cell death in-vitro, inhibited tumor progression, and improved overall survival in-vivo. We performed extensive pre-clinical assessments in multiple in-vivo model systems to confirm the therapeutic potential of erdafitinib in MCL and demonstrated FGFR1 as a viable therapeutic target in MCL.
Brain-cognition relationships in late-life depression: a systematic review of structural magnetic resonance imaging studies
Authors: Marawi Tulip , Ainsworth Nicholas J. , Zhukovsky Peter , Rashidi-Ranjbar Neda , Rajji Tarek K. , Tartaglia Maria Carmela , Voineskos Aristotle N. , Mulsant Benoit H.
Published: August 2023

Background

Most patients with late-life depression (LLD) have cognitive impairment, and at least one-third meet diagnostic criteria for mild cognitive impairment (MCI), a prodrome to Alzheimer’s dementia (AD) and other neurodegenerative diseases. However, the mechanisms linking LLD and MCI, and brain alterations underlying impaired cognition in LLD and LLD + MCI remain poorly understood.

Methods

To address this knowledge gap, we conducted a systematic review of studies of brain-cognition relationships in LLD or LLD + MCI to identify circuits underlying impaired cognition in LLD or LLD + MCI. We searched MEDLINE, PsycINFO, EMBASE, and Web of Science databases from inception through February 13, 2023. We included studies that assessed cognition in patients with LLD or LLD + MCI and acquired: (1) T1-weighted imaging (T1) measuring gray matter volumes or thickness; or (2) diffusion-weighted imaging (DWI) assessing white matter integrity. Due to the heterogeneity in studies, we only conducted a descriptive synthesis.

Results

Our search identified 51 articles, resulting in 33 T1 studies, 17 DWI studies, and 1 study analyzing both T1 and DWI. Despite limitations, reviewed studies suggest that lower thickness or volume in the frontal and temporal regions and widespread lower white matter integrity are associated with impaired cognition in LLD. Lower white matter integrity in the posterior cingulate region (precuneus and corpus callosum sub-regions) was more associated with impairment executive function and processing speed than with memory.

Conclusion

Future studies should analyze larger samples of participants with various degrees of cognitive impairment and go beyond univariate statistical models to assess reliable brain-cognition relationships in LLD.
Challenges in developing Geroscience trials
Authors: Rolland Yves , Sierra Felipe , Ferrucci Luigi , Barzilai Nir , De Cabo Rafael , Mannick Joan , Oliva Anthony , Evans William , Angioni Davide , De Souto Barreto Philipe , Raffin Jeremy , Vellas Bruno , Kirkland James L. ,   the G.C.T-TF group, Andrieu Sandrine , Bacqueville Daniel , Bischoff-Ferrari Heike , Blivet Guillaume , Cash Timothy , Cuervo Ana-Maria , Davezac Noelie , Dimet-Wiley Andrea , Fleming Alexander , Gérard Friedlander , Gonzales Mitzi , Guyonnet Sophie , Hare Joshua , Hendrix Suzanne , Jorgensen Christian , Kaeberlein Matt , Khan Mehmood , Kritchevsky Stephen , Labokha Aksana , Lairez Olivier , Lederman Stephanie , Mariani Jean , Middleton Lefkos , Newman John , Parini Angelo , Peschin Susan , Prunotto Marco , Sagol Sami , Tomlinson Suzanne , Terstappen Georg , Touchon Jacques , Tourette Cendrine , Van Maanen Rob , Verdin Eric , Watowich Stan , Zhang Lei , Zhavoronkov Alex
Published: August 2023

Geroscience is becoming a major hope for preventing age-related diseases and loss of function by targeting biological mechanisms of aging. This unprecedented paradigm shift requires optimizing the design of future clinical studies related to aging in humans. Researchers will face a number of challenges, including ideal populations to study, which lifestyle and Gerotherapeutic interventions to test initially, selecting key primary and secondary outcomes of such clinical trials, and which age-related biomarkers are most valuable for both selecting interventions and predicting or monitoring clinical responses (“Gerodiagnostics”). This article reports the main results of a Task Force of experts in Geroscience.
APOGEE 2: multi-layer machine-learning model for the interpretable prediction of mitochondrial missense variants
Authors: Bianco Salvatore Daniele , Parca Luca , Petrizzelli Francesco , Biagini Tommaso , Giovannetti Agnese , Liorni Niccolò , Napoli Alessandro , Carella Massimo , Procaccio Vincent , Lott Marie T. , Zhang Shiping , Vescovi Angelo Luigi , Wallace Douglas C. , Caputo Viviana , Mazza Tommaso
Published: August 2023

Mitochondrial dysfunction has pleiotropic effects and is frequently caused by mitochondrial DNA mutations. However, factors such as significant variability in clinical manifestations make interpreting the pathogenicity of variants in the mitochondrial genome challenging. Here, we present APOGEE 2, a mitochondrially-centered ensemble method designed to improve the accuracy of pathogenicity predictions for interpreting missense mitochondrial variants. Built on the joint consensus recommendations by the American College of Medical Genetics and Genomics/Association for Molecular Pathology, APOGEE 2 features an improved machine learning method and a curated training set for enhanced performance metrics. It offers region-wise assessments of genome fragility and mechanistic analyses of specific amino acids that cause perceptible long-range effects on protein structure. With clinical and research use in mind, APOGEE 2 scores and pathogenicity probabilities are precompiled and available in MitImpact. APOGEE 2’s ability to address challenges in interpreting mitochondrial missense variants makes it an essential tool in the field of mitochondrial genetics.
Numerical analysis for tangent-hyperbolic micropolar nanofluid flow over an extending layer through a permeable medium
Authors: Moatimid Galal M. , Mohamed Mona A. A. , Gaber Ahmed A. , Mostafa Doaa M.
Published: August 2023

The principal purpose of the current investigation is to indicate the behavior of the tangent-hyperbolic micropolar nanofluid border sheet across an extending layer through a permeable medium. The model is influenced by a normal uniform magnetic field. Temperature and nanoparticle mass transmission is considered. Ohmic dissipation, heat resource, thermal radiation, and chemical impacts are also included. The results of the current work have applicable importance regarding boundary layers and stretching sheet issues like rotating metals, rubber sheets, glass fibers, and extruding polymer sheets. The innovation of the current work arises from merging the tangent-hyperbolic and micropolar fluids with nanoparticle dispersal which adds a new trend to those applications. Applying appropriate similarity transformations, the fundamental partial differential equations concerning speed, microrotation, heat, and nanoparticle concentration distributions are converted into ordinary differential equations, depending on several non-dimensional physical parameters. The fundamental equations are analyzed by using the Rung-Kutta with the Shooting technique, where the findings are represented in graphic and tabular forms. It is noticed that heat transmission improves through most parameters that appear in this work, except for the Prandtl number and the stretching parameter which play opposite dual roles in tin heat diffusion. Such an outcome can be useful in many applications that require simultaneous improvement of heat within the flow. A comparison of some values of friction with previous scientific studies is developed to validate the current mathematical model.
A fast imaging method for the interpretation of self-potential data with application to geothermal systems and mineral investigation
Authors: Mehanee Salah A. , Essa Khalid S. , Soliman Khaled S. , Diab Zein E.
Published: August 2023

We describe a rapid imaging approach for the interpretation of self-potential data collected along profile by some geometrically simple model of cylinders and spheres. The approach calculates the correlation coefficient between the analytic signal (AS) of the observed self-potential measurements and the AS of the self-potential signature of the idealized model. The depth, electric dipole moment, polarization angle, and center are the inverse parameters we aim to extract from the imaging approach for the interpretative model, and they pertain to the highest value of the correlation coefficient. The approach is demonstrated on noise-free numerical experiments, and reproduced the true model parameters. The accuracy and stability of the proposed approach are examined on numerical experiments contaminated with realistic noise levels and regional fields prior to the interpretation of real data. Following that, five real field examples from geothermal systems and mineral exploration have been successfully analyzed. The results agree well with the published research.
Assessing the relationship between energy-related methane emissions and the burden of cardiovascular diseases: a cross-sectional study of 73 countries
Authors: Mendoza-Cano Oliver , Trujillo Xóchitl , Huerta Miguel , Ríos-Silva Mónica , Lugo-Radillo Agustin , Bricio-Barrios Jaime Alberto , Rueda-Abad José Clemente , Pérez-Rodríguez Rebeca Yasmín , Quintanilla-Montoya Ana Luz , Uribe-Ramos Juan Manuel , Mendoza-Olivo Valeria Argentina , Murillo-Zamora Efrén
Published: August 2023

The energy industry significantly contributes to anthropogenic methane emissions, which add to global warming and have been linked to an increased risk of cardiovascular diseases (CVD). This study aims to evaluate the relationship between energy-related methane emissions and the burden of CVD, measured in disability-adjusted life years (DALYs), in 2019. We conducted a cross-sectional analysis of datasets from 73 countries across all continents. The analyzed datasets included information from 2019 on environmental energy-related methane emissions, burden of DALYs due to CVD. The age-standardized prevalence of obesity in adults and life expectancy at birth were retrieved. The relationship between the variables of interest was evaluated using multiple linear regression models. In the multiple model, we observed a positive linear association between methane emissions and the log-transformed count of DALYs related to CVD. Specifically, for each unit increase in energy-related methane emissions, the burden of CVD increased by 0.06% (95% CI 0.03–0.09%, p < 0.001). The study suggests that reducing methane emissions from the energy industry could improve public health for those at risk of CVD. Policymakers can use these findings to develop strategies to reduce methane emissions and protect public health.
A comparative study using response surface methodology and artificial neural network towards optimized production of melanin by Aureobasidium pullulans AKW
Authors: Saber WesamEldin I. A. , Ghoniem Abeer A. , Al-Otibi Fatimah O. , El-Hersh Mohammed S. , Eldadamony Noha M. , Menaa Farid , Elattar Khaled M.
Published: August 2023

The effect of three independent variables (i.e., tyrosine, sucrose, and incubation time) on melanin production by Aureobasidium pullulans AKW was unraveled by two distinctive approaches: response surface methodology (i.e. Box Behnken design (BBD)) and artificial neural network (ANN) in this study for the first time ever using a simple medium. Regarding BBD, sucrose and incubation intervals did impose a significant influence on the output (melanin levels), however, tyrosine did not. The validation process exhibited a high consistency of BBD and ANN paradigms with the experimental melanin production. Concerning ANN, the predicted values of melanin were highly comparable to the experimental values, with minor errors competing with BBD. Highly comparable experimental values of melanin were achieved upon using BBD (9.295 ± 0.556 g/L) and ANN (10.192 ± 0.782 g/L). ANN accurately predicted melanin production and showed more improvement in melanin production by about 9.7% higher than BBD. The purified melanin structure was verified by scanning electron microscopy (SEM), energy-dispersive X-ray spectroscopy (EDX), X-ray diffraction pattern (XRD), and thermogravimetric analysis (TGA). The results verified the hierarchical architecture of the particles as small compasses by SEM analysis, inter-layer spacing in the XRD analysis, maximal atomic % for carbon, and oxygen atoms in the EDX analysis, and the great thermal stability in the TGA analysis of the purified melanin. Interestingly, the current novel endophytic strain was tyrosine-independent, and the uniquely applied ANN paradigm was more efficient in modeling the melanin production with appreciate amount on a simple medium in a relatively short time (168 h), suggesting additional optimization studies for further maximization of melanin production.
Spectrofluorometric determination of orphenadrine, dimenhydrinate, and cinnarizine using direct and synchronous techniques with greenness assessment
Authors: Ghonim Rana , Tolba Manar M. , Ibrahim Fawzia , El-Awady Mohamed I.
Published: August 2023

Orphenadrine (ORP), dimenhydrinate (DMN), and cinnarizine (CNN) were investigated using green-sensitive spectrofluorometric methods. Method, I used for determination of DMN in 0.1 M hydrochloric acid (HCl) and 1.0% sodium dodecyl sulphate (SDS) at 286 nm after λex 222 nm, while for determination of ORP in 1.0% w/v SDS involves measuring the fluorescence at 285 nm after λex 220 nm. For DMN and ORP, the detection and quantitation limits were 2.99 and 4.71 and 9.08 and 14.29 ng/mL, respectively. The ranges of DMN and ORP were 0.10–1.0 and 0.04–0.5 µg/mL, respectively, in micellar aqueous solution. Method II, the derivative intensities of DMN and CNN were measured at a fixed of different wavelength between the excitation and the emission wavelengths (Δλ) = 60 nm at 282 and 322 nm, at the zero crossing of each other, respectively. The detection and quantitation limits for DMN and CNN were 1.77 and 0.88 ng/mL and 5.36 and 2.65 ng/mL, correspondingly, through the entire range of 0.1–1.0 µg/mL for DMN and CNN. The linearity was perfectly determined through the higher values of the correlation coefficient ranging from 0.9997 to 0.9999 for both direct and synchronous methods. The precision of the proposed methods was also confirmed via the lower values of the standard deviation which ranged from 0.39 to 1.11. The technique was expanded to analyze this mixture in combined tablets and laboratory-prepared mixtures. The method validation was done depending on the international conference on harmonization (ICH) recommendations. An analysis of the statistical data revealed a high agreement between the proposed data and the comparison methodology. Three different assessment methods demonstrated the greenness of the technique.
Land use and land cover (LULC) performance modeling using machine learning algorithms: a case study of the city of Melbourne, Australia
Authors: Aryal Jagannath , Sitaula Chiranjibi , Frery Alejandro C.
Published: August 2023

Accurate spatial information on Land use and land cover (LULC) plays a crucial role in city planning. A widely used method of obtaining accurate LULC maps is a classification of the categories, which is one of the challenging problems. Attempts have been made considering spectral (Sp), statistical (St), and index-based (Ind) features in developing LULC maps for city planning. However, no work has been reported to automate LULC performance modeling for their robustness with machine learning (ML) algorithms. In this paper, we design seven schemes and automate the LULC performance modeling with six ML algorithms-Random Forest, Support Vector Machine with Linear kernel, Support Vector Machine with Radial basis function kernel, Artificial Neural Network, Naïve Bayes, and Generalised Linear Model for the city of Melbourne, Australia on Sentinel-2A images. Experimental results show that the Random Forest outperforms remaining ML algorithms in the classification accuracy (0.99) on all schemes. The robustness and statistical analysis of the ML algorithms (for example, Random Forest imparts over 0.99 F1-score for all five categories andpvalue $$\le$$≤ 0.05 from Wilcoxon ranked test over accuracy measures) against varying training splits demonstrate the effectiveness of the proposed schemes. Thus, providing a robust measure of LULC maps in city planning.
Carbon balance of plywood from a social reforestation program in Indonesia
Authors: Müller Daniel Philipp , Szemkus Nadine , Hiete Michael
Published: August 2023

Social reforestation programs plant trees on degraded, uncultivated land in low-income regions to allow the local population to generate income from selling wood products and—in case of agroforestry systems—to grow food. For fundraising it is of interest to demonstrate not only positive social impacts but also environmental ones. Proving negative greenhouse gas (GHG) emissions would allow the programs to enter the market for carbon offsetting projects and liberate further funding. In a case study, a social reforestation program in Kalimantan, Indonesia, is analyzed. GHG emissions (according to ISO 14067, PAS 2050 and EU ILCD Handbook for LCA) of the main product, laminated veneer lumber plywood, are determined as 622 and 21 kg CO2-e/m3 for short-term and long-term (above 100 years) plywood use, respectively. Switching to lignin-based resins and renewable electricity could reduce emissions down to − 363 kg CO2-e/m3 for long-term use. The analyzed agroforestry system produces almost carbon–neutral plywood today and could be climate positive in the mid-term.
Screening adequacy of unstained thyroid fine needle aspiration samples using a deep learning-based classifier
Authors: Jang Junbong , Kim Young H. , Westgate Brian , Zong Yang , Hallinan Caleb , Akalin Ali , Lee Kwonmoo
Published: August 2023

Fine needle aspiration (FNA) biopsy of thyroid nodules is a safe, cost-effective, and accurate diagnostic method for detecting thyroid cancer. However, about 10% of initial FNA biopsy samples from patients are non-diagnostic and require repeated FNA, which delays the diagnosis and appropriate care. On-site evaluation of the FNA sample can be performed to filter out non-diagnostic FNA samples. Unfortunately, it involves a time-consuming staining process, and a cytopathologist has to be present at the time of FNA. To bypass the staining process and expert interpretation of FNA specimens at the clinics, we developed a deep learning-based ensemble model termed FNA-Net that allows in situ screening of adequacy of unstained thyroid FNA samples smeared on a glass slide which can decrease the non-diagnostic rate in thyroid FNA. FNA-Net combines two deep learning models, a patch-based whole slide image classifier and Faster R-CNN, to detect follicular clusters with high precision. Then, FNA-Net classifies sample slides to be non-diagnostic if the total number of detected follicular clusters is less than a predetermined threshold. With bootstrapped sampling, FNA-Net achieved a 0.81 F1 score and 0.84 AUC in the precision-recall curve for detecting the non-diagnostic slides whose follicular clusters are less than six. We expect that FNA-Net can dramatically reduce the diagnostic cost associated with FNA biopsy and improve the quality of patient care.