bluuebunny/crossref_metadata_2025 huggingface dataset:
Rheology of dense suspensions of ideally conductive particles in an electric field
Authors: Mirfendereski Siamak , Park Jae Sung
Published: December 2023

The rheological behaviour of dense suspensions of ideally conductive particles in the presence of both electric field and shear flow is studied using large-scale numerical simulations. Under the action of an electric field, these particles are known to undergo dipolophoresis (DIP), which is the combination of two nonlinear electrokinetic phenomena: induced-charge electrophoresis (ICEP) and dielectrophoresis (DEP). For ideally conductive particles, ICEP is predominant over DEP, resulting in transient pairing dynamics. The shear viscosity and first and second normal stress differences

$N_1$

and

$N_2$

of such suspensions are examined over a range of volume fractions

$15\,\% \leq \phi \leq 50\,\%$

as a function of Mason number

$Mn$

, which measures the relative importance of viscous shear stress over electrokinetic-driven stress. For

$Mn < 1$

or low shear rates, the DIP is shown to dominate the dynamics, resulting in a relatively low-viscosity state. The positive

$N_1$

and negative

$N_2$

are observed at

$\phi < 30\,\%$

, which is similar to Brownian suspensions, while their signs are reversed at

$\phi \ge 30\,\%$

. For

$Mn \ge 1$

, the shear thickening starts to arise at

$\phi \ge 30\,\%$

, and an almost five-fold increase in viscosity occurs at

$\phi = 50\,\%$

. Both

$N_1$

and

$N_2$

are negative for

$Mn \gg 1$

at all volume fractions considered. We illuminate the transition in rheological behaviours from DIP to shear dominance around

$Mn = 1$

in connection to suspension microstructure and dynamics. Lastly, our findings reveal the potential use of nonlinear electrokinetics as a means of active rheology control for such suspensions.
Blood meal sources of mosquitoes (Diptera: Culicidae) in domestic and open green environments from two urbanisations of temperate Argentina
Authors: Melgarejo-Colmenares Karelly , Vezzani Darío , Gallego Alejandra , Cardo María V
Published: December 2023

Understanding the blood-feeding patterns of mosquitoes is essential for evaluating their potential as disease vectors, especially in urban areas where mosquitoes coexist with humans, domestic animals and wildlife. This study aimed to bridge a substantial gap in regional knowledge by identifying the blood meal sources of field-collected mosquitoes in domestic and open green environments from two urbanisations of temperate Argentina, the Área Metropolitana de Buenos Aires (AMBA) and Tandil, using molecular techniques. Female mosquitoes were collected from November 2019 to March 2020 and April–May 2021. A bipartite network analysis was performed for each environment and urbanisation. A total of 103 blood meals from Aedes (2 species) and Culex (7 species) were identified. Among these, five mammal and 18 bird species were recognised as hosts. Aedes mosquitoes exclusively fed on mammals, while Culex mosquitoes exhibited a broader host range including both birds and mammals. In AMBA, the open green environments were composed by more mosquito species than the domestic environments, while both presented similar numbers of vertebrate species. In contrast, in open green environments from Tandil only blood-fed Aedes albifasciatus were collected. For open green environments of AMBA and domestic environments of Tandil, results suggested some degree of host selection. For the three main vectors of diseases in the region, Aedes aegypti, Ae. albifasciatus and Culex pipiens molestus, we present the first molecular evidence of human blood meals in South America. Epidemiological significance of the present findings is discussed.
Consistency of the Troposphere Wet Delay From Water Vapor Radiometer and Co‐Located GPS Station
Authors: Jiang Jun , Song Shuli , Zhou Weili , Liu Qinghui , Chen Houcai , Jiang Yongchen , Zhou Tianyu , Ali Tarig A. , Li Wei
Published: December 2023

The tropospheric delay acquired by the Global Navigation Position System (GPS) Precise Point Positioning (PPP) is continuous and steady, less affected by rainfall. The Water Vapor Radiometer (WVR) can provide real‐time meteorological parameters but is more sensitive to high‐frequency information in troposphere. To explore the use of WVR‐retrieved tropospheric delay and assist other geodetic techniques for atmospheric correction, the tropospheric delay from WVR and co‐located GPS at Shanghai, Beijing, Kunming, and Urumqi stations in China are compared. For the inconsistent values of WVR‐PPP zenith wet delay, the variations of the tropospheric delay from WVR and GPS before and after the rainfall were statistically analyzed. The results suggest that, for the rain rate ranging from 0.1 to 50 mm/hr, the impact of rainfall on WVR could last from 10 min before to 30 min after the rainfall. With filtering WVR data based on meteorological parameters and rain rate, the zenith wet delay between WVR and PPP at Shanghai shows good consistency, the root mean square (RMS) is 6.11 mm, correlation is 0.997, and the RMS in the other three stations ranges from 16.35 to 25.16 mm (correlation ranges in 0.794–0.951). The analysis indicates that the tropospheric delay of WVR is reliable to be applied to space geodetic techniques correction in real‐time with filtering to reduce the effect of rainfall, water vapor, and liquid water variability.
High‐Resolution Maps of Near‐Surface Permafrost for Three Watersheds on the Seward Peninsula, Alaska Derived From Machine Learning
Authors: Thaler E. A. , Uhleman S. , Rowland J. C. , Schwenk J. , Wang C. , Dafflon B. , Bennett K. E.
Published: December 2023

Permafrost soils are a critical component of the global carbon cycle and are locally important because they regulate the hydrologic flux from uplands to rivers. Furthermore, degradation of permafrost soils causes land surface subsidence, damaging infrastructure that is crucial for local communities. Regional and hemispherical maps of permafrost are too coarse to resolve distributions at a scale relevant to assessments of infrastructure stability or to illuminate geomorphic impacts of permafrost thaw. Here we train machine learning models to generate meter‐scale maps of near‐surface permafrost for three watersheds in the discontinuous permafrost region. The models were trained using ground truth determinations of near‐surface permafrost presence from measurements of soil temperature and electrical resistivity. We trained three classifiers: extremely randomized trees (ERTr), support vector machines (SVM), and an artificial neural network (ANN). Model uncertainty was determined using k‐fold cross validation, and the modeled extents of near‐surface permafrost were compared to the observed extents at each site. At‐a‐site near‐surface permafrost distributions predicted by the ERTr produced the highest accuracy (70%–90%). However, the transferability of the ERTr to the sites outside of the training data set was poor, with accuracies ranging from 50% to 77%. The SVM and ANN models had lower accuracies for at‐a‐site prediction (70%–83%), yet they had greater accuracy when transferred to the non‐training site (62%–78%). These models demonstrate the potential for integrating high‐resolution spatial data and machine learning models to develop maps of near‐surface permafrost extent at resolutions fine enough to assess infrastructure vulnerability and landscape morphology influenced by permafrost thaw.
Participatory Modeling for Analyzing Interactions Between High‐Priority Sustainable Development Goals to Promote Local Sustainability
Authors: Bandari Reihaneh , Moallemi Enayat A. , Szetey Katrina , Flanagan‐Smith Claire , Hadjikakou Michalis , Marcos‐Martinez Raymundo , Kharrazi Ali , Trogrlić Robert Šakić , Bryan Brett A.
Published: December 2023

Achieving the Sustainable Development Goals (SDGs) is challenging given the complex interactions between different SDGs and their spillover effects. We developed a system dynamics model—the Local Environmental and Socio‐Economic Model (LESEM)—to analyze and quantify context‐based SDG interactions at the local scale using a participatory model co‐design process with local stakeholders. The LESEM was developed for the Goulburn‐Murray Irrigation District in Victoria, Australia, to assist policymakers in analyzing local issues with a more integrated and holistic approach to sustainable development at the local scale. The process of participatory systems dynamics modeling facilitates integrated and strategic decision‐making and can help local policymakers identify and quantify potential trade‐offs and synergies that benefit multiple SDGs, which eventually leads local communities toward sustainability. We present an illustrative application of the model that quantifies SDG interactions across four high‐priority SDGs, namely clean water and sanitation (SDG 6), zero hunger (SDG 2), economic growth (SDG 8), and life on land (SDG 15). We illustrate the use of the model in assessing key SDG indicator trajectories under a business‐as‐usual (BAU) scenario from 2010 to 2050. Under the BAU, agri‐food production increased despite a decline in water resource availability, with gains driven by intensification and increased agricultural productivity. This boosted local prosperity and reduced the amount of agricultural land required to meet future agri‐food demand, thereby reducing pressures on terrestrial ecosystems and creating the space for ecological restoration and carbon storage in soils and biomass. However, agricultural intensification impacted water quality through increases in algal blooms and river salinity.
Automated Seafloor Massive Sulfide Detection Through Integrated Image Segmentation and Geophysical Data Analysis: Revisiting the TAG Hydrothermal Field
Authors: Haroon Amir , Paasche Hendrik , Graber Sebastian , Petersen Sven , Attias Eric , Jegen Marion , Gehrmann Romina , Hölz Sebastian , Klischies Meike
Published: December 2023

Accessible seafloor minerals located near mid‐ocean ridges are noticed to mitigate the projected metal demands of the net‐zero energy transition, promoting growing interest in quantifying the global distributions of seafloor massive sulfides (SMS). Mineral potentials are commonly estimated using geophysical and geological data that lastly rely on additional confirmation studies using sparsely available, locally limited, seafloor imagery, grab samples, and coring data. This raises the challenge of linking in situ confirmation data to geophysical data acquired at disparate spatial scales to obtain quantitative mineral predictions. Although multivariate data sets for marine mineral research are incessantly acquired, robust, integrative data analysis requires cumbersome workflows and experienced interpreters. We introduce an automated two‐step machine learning approach that integrates the mound detection through image segmentation with geophysical data. SMS predictors are subsequently clustered into distinct classes to infer marine mineral potentials that help guide future exploration. The automated workflow employs a U‐Net convolutional neural network to identify mound structures in bathymetry data and distinguishes different mound classes through the classification of mound architectures and magnetic signatures. Finally, controlled source electromagnetic data are utilized together with in situ sampling data to reassess predictions of potential SMS volumes. Our study focuses on the Trans‐Atlantic Geotraverse area, which is among the most explored SMS areas worldwide and includes 15 known SMS sites. The automated workflow classifies 14 of the 15 known mounds as exploration targets of either high or medium priority. This reduces the exploration area to less than 7% of the original survey area from 49 to 3.1 km2.
Six Consecutive Seasons of High‐Resolution Mountain Snow Depth Maps From Satellite Stereo Imagery
Authors: Hu J. Michelle , Shean David , Bhushan Shashank
Published: December 2023

Fine‐scale seasonal snow depth observations can improve estimates of snow water equivalent at critical times of year. Airborne lidar is the current gold standard for snow depth measurement, but it involves high costs and relatively limited coverage. Using very‐high‐resolution satellite stereo images from WorldView‐2, WorldView‐3, and Pléiades‐HR 1A/1B, we produced a six‐year time series (2017–2022) of spatially continuous digital elevation models for an 874 km2 study area over Grand Mesa, Colorado. We generated high‐resolution stereo snow depth maps that capture intra‐ and interannual variability and span multiple anomalous years (58%–158% of median peak SNOTEL snow depth). Comparisons with near‐contemporaneous airborne lidar snow depth measurements showed good agreement, with median offset of −0.13 m, precision of 0.19 m and accuracy of 0.31 m. Our results suggest that satellite stereo can provide snow depth observations with the spatiotemporal coverage needed to improve operational forecast models and inform adaptive management strategies.
An Extended Triple Collocation Method With Maximized Correlation for Near Global‐Land Precipitation Fusion
Authors: Wei Linyong , Jiang Shanhu , Ren Liliang , Yuan Shanshui , Liu Yi , Yang Xiaoli , Wang Menghao , Zhang Linqi , Yu Huafei , Duan Zheng
Published: December 2023

An Extended Triple Collocation for maximized Correlation (ETCC) method was proposed with a unique correlation function, the purpose of which is to maximize the correlation between the merged product and unknown truth. The method was tested over quasi‐global land by combining three independent precipitation products. The performance of the ETCC‐merged product was then evaluated against three reference data sets and compared with the existing Triple Collocation (TC) merging. The merged product was found to be generally superior to each contributor. Moreover, the ETCC method is better able to improve the correlation of merged product compared with the TC approach. Other improvements are also shown in the absolute difference of the ETCC‐merged product, such as regional validation for central North America and mainland China. These demonstrate the effectiveness of the ETCC method, and accordingly, it can provide a promising solution for maximizing the correlation of merged product without the truth.
Modeling the Effects of Drift Orbit Bifurcation on the Magnetopause Shadowing Loss of Radiation Belt Electrons
Authors: Huang Jinbei , Lyu Xingzhi , Tu Weichao , Albert Jay M. , Lee Sang‐Yun
Published: December 2023

Last closed drift shell (LCDS) has been identified as a crucial parameter for investigating the magnetopause shadowing loss of radiation belt electrons. However, drift orbit bifurcation (DOB) effects have not been physically incorporated into the LCDS calculation. Here we calculate event‐specific LCDS using different approaches to dealing with the DOB effects, that is, tracing field lines ignoring DOB, tracing test particles rejecting field lines with DOB, and tracing particles including field lines with DOB, and then incorporate them into a radial diffusion model to simulate the fast electron dropout observed by Van Allen Probes in May 2017. The model effectively captures the fast dropout at high L* and exhibits the best agreement with data when LCDS is calculated by tracing test particles with DOB more physically included. This study represents the first quantitative modeling of the DOB effects on radiation belt magnetopause shadowing loss via a more physical specification of LCDS.
Evaluation of Leftward Biased Cold Wakes Induced by Tropical Cyclones in the North Hemisphere
Authors: Ye Hexin , Ma Zhanhong , Fei Jianfang , Duan Yihong
Published: December 2023

The cold wake features are one of the most significant characteristics left behind by tropical cyclones (TCs) over the warm ocean. In the past several decades, the cold wakes have been widely conceived to be rightward biased (in the Northern Hemisphere). This basic cognition is examined in this study based on satellite sea surface temperature (SST) data with the high‐resolution of ∼0.09° between 2002 and 2021. Statistical results reveal that roughly one third (∼30.58%) of TC cold wakes are actually leftward biased in real world. On average, the maximum cooling of leftward cold wakes is approximately −0.7°C, appearing at ∼60 km to the left of the storm track. The proportion of leftward cases decreases steadily with increasing TC intensity, while shows little relation with the translation speed. The leftward biased phenomena are found to be independent from meso‐scale oceanic features and mainly attributed to inhomogeneous large‐scale background oceanic environment. The generally deeper (shallower) pre‐storm mixed layer and weaker (stronger) stratification found in the right (left) of track can effectively suppress rightward (enhance leftward) surface cooling and synchronously deform the normal spatial patterns of cold wakes. These effects cooperate with leftward‐biased surface enthalpy flux resulted from asymmetric pre‐storm SST, and eventually contributes to the left‐shifted feature. A series of three‐dimensional simulations using the three‐dimensional Price‐Weller‐Pinkel (3DPWP) model consolidate these physical explanations. Further observations suggest that distributions of cold wakes could significantly affect the asymmetric precipitation of TCs, confirming the importance of leftward cases to the TCs structure.
Enhanced Turbulent Diapycnal Mixing in the Northern Sargasso Sea Inferred From a Finescale Parameterization
Authors: Li Zhuoran , Jing Zhao , Wu Lixin , Johnson Rodney J. , Yang Zhibin , Song Zhuo , Chen Zhaohui , Gan Bolan , Ma Xiaohui
Published: December 2023

The Sargasso Sea, accommodating marine species and mode water, is highly productive relative to other oligotrophic subtropical regions with intense air‐sea carbon and heat exchanges. Turbulent diapycnal mixing regulates these processes and is generally thought to be weakened in a more stratified ocean under anthropogenic forcing. However, by applying a finescale parameterization to long‐term hydrographic profiles collected during the Bermuda Atlantic Time‐Series Study (BATS), we show that its intensity has become stronger from 1994 to 2019 in the permanent thermocline. The enhanced turbulent diapycnal mixing is mainly attributed to the increase of wind power on internal waves along the Gulf Stream extension. Numerical simulations suggest that stronger internal waves excited along the Gulf Stream extension radiate downward and equatorward, causing enhanced turbulent diapycnal mixing in the northern Sargasso Sea including the BATS station. The findings have important implications for understanding responses of mode water and ecosystem in the Sargasso Sea to anthropogenic forcing.
Scale‐Awareness in an Eddy Energy Constrained Mesoscale Eddy Parameterization
Authors: Mak J. , Maddison J. R. , Marshall D. P. , Ruan X. , Wang Y. , Yeow L.
Published: December 2023

There is an increasing interest in mesoscale eddy parameterizations that are scale‐aware, normally interpreted to mean that a parameterization does not require parameter recalibration as the model resolution changes. Here we examine whether Gent–McWilliams (GM) based version of GEOMETRIC, a mesoscale eddy parameterization that is constrained by a parameterized eddy energy budget, is scale‐aware in its energetics. It is generally known that GM‐based schemes severely damp out explicit eddies, so the parameterized component would be expected to dominate across resolutions, and we might expect a negative answer to the question of energetic scale‐awareness. A consideration of why GM‐based schemes damp out explicit eddies leads a suggestion for what we term a splitting procedure: a definition of a “large‐scale” field is sought, and the eddy‐induced velocity from the GM‐scheme is computed from and acts only on the large‐scale field, allowing explicit and parameterized components to co‐exist. Within the context of an idealized re‐entrant channel model of the Southern Ocean, evidence is provided that the GM‐based version of GEOMETRIC is scale‐aware in the energetics as long as we employ a splitting procedure. The splitting procedure also leads to an improved representation of mean states without detrimental effects on the explicit eddy motions.
Modeling Pipe to Soil Potentials From Geomagnetic Storms in Gas Pipelines in New Zealand
Authors: Divett Tim , Ingham Malcolm , Richardson Gemma , Sigley Mark , Rodger Craig J.
Published: December 2023

Gas pipelines can experience elevated pipe to soil potentials (PSPs) during geomagnetic disturbances due to the induced geoelectric field. Gas pipeline operators use cathodic protection to keep PSPs between −0.85 and −1.2 V to prevent corrosion of the steel pipes and disbondment of the protective coating from the pipes. We have developed a model of the gas pipelines in the North Island of New Zealand to identify whether a hazard exists to these pipelines and how big this hazard is. We used a transmission line representation to model the pipelines and a nodal admittance matrix method to calculate the PSPs at nodes up to 5 km apart along the pipelines. We used this model to calculate PSPs resulting from an idealized 100 mVkm−1 electric field, initially to the north and east. The calculated PSPs are highest are at the ends of the pipelines in the direction of the applied electric field vector. The calculated PSP follows a characteristic curve along the length of the pipelines that matches theory, with deviations due to branchlines and changes in pipeline direction. The modeling shows that the PSP magnitudes are sensitive to the branchline coating conductance with higher coating conductances decreasing the PSPs at most locations. Enhanced PSPs produce the highest risk of disbondment and corrosion occurring, and hence this modeling provides insights into the network locations most at risk.
Contrasting Land and Atmospheric Controls on the Generalized Complementary Relationship of Evaporation Over Grasslands and Forests
Authors: Han Songjun , Yan Jianwei , Liu Yaping , Tian Fuqiang , Zhang Baozhong , Wang Xiaochun , Shao Changliang , Wang Liming
Published: December 2023

The generalized complementary relationship (CR) rooted on land–atmosphere coupling has been widely used to study evaporation over various ecosystems. Evaporation estimation models based on CR usually contain two parameters. The first one controls the shape of CR, and the second one is related to potential evaporation (Epo). Previous studies have found substantial variations in these parameters, but how they are affected by land surface and/or the atmosphere under conditions with varying land–atmosphere coupling remains unclear. In this study, the land and atmospheric controls for the generalized CR were comparatively investigated focusing on the two parameters of the sigmoid type function by using the data of 24 grassland and 19 forest flux sites and by considering the contrasting land–atmosphere coupling strength. The strong coupling to the outer atmosphere at the forest sites resulted in a large variation in the Epo‐related parameter and its significant correlation with the mean relative humidity. The shape parameter had a large variation at the grassland sites due to the weak coupling with the outer atmosphere and was significantly correlated with the mean soil water content. The simple parameterizations for the two parameters based on the correlations improved the predictions of monthly actual evaporation compared with the parameterizations for the fixed parameters corresponding to ecosystem types. The effects of land surface wetness and local advections on the generalized CR over grasslands and forests were also discussed respectively.
Development and validation of a machine learning model using electronic health records to predict trauma- and stressor-related psychiatric disorders after hospitalization with sepsis
Authors: Papini Santiago , Iturralde Esti , Lu Yun , Greene John D. , Barreda Fernando , Sterling Stacy A. , Liu Vincent X.
Published: December 2023

A significant minority of individuals develop trauma- and stressor-related disorders (TSRD) after surviving sepsis, a life-threatening immune response to infections. Accurate prediction of risk for TSRD can facilitate targeted early intervention strategies, but many existing models rely on research measures that are impractical to incorporate to standard emergency department workflows. To increase the feasibility of implementation, we developed models that predict TSRD in the year after survival from sepsis using only electronic health records from the hospitalization (n = 217,122 hospitalizations from 2012-2015). The optimal model was evaluated in a temporally independent prospective test sample (n = 128,783 hospitalizations from 2016-2017), where patients in the highest-risk decile accounted for nearly one-third of TSRD cases. Our approach demonstrates that risk for TSRD after sepsis can be stratified without additional assessment burden on clinicians and patients, which increases the likelihood of model implementation in hospital settings.
Position-sensitive non-destructive detection of charged-particle bunches in low-energy beamlines
Authors: Ringleb Stefan , Kiffer Markus , Ballentin Jonas K. C. , Stöhlker Thomas , Vogel Manuel
Published: December 2023

We have developed and operated an electronic detection system for the non-destructive single-pass detection of bunches of charged particles in a beamline that allows for a measurement of their lateral position with respect to the central beamline axis on a shot-to-shot basis. It provides all features of our related development reported in Kiffer et al. (Rev Sci Instrum 90:113301, 2019), namely single-pass measurement of bunch length, kinetic energy and absolute charge, and is additionally designed to provide the lateral position of bunches with sub-mm accuracy. We show the setup, associated methods and provide characterizing measurements with bunches of highly charged ions in the keV regime of kinetic energy that demonstrate the capabilities and show a typical application.
Association of adiponectin gene expression with atrial fibrillation in a Pakistani populace
Authors: Rafaqat Saira , Sharif Saima , Majeed Mona , Naz Shagufta , Saqib Muhammad , Manzoor Farkhanda
Published: December 2023

Adiponectin, an adipocytokine produced and secreted by adipose tissue, has anti-diabetic, anti-atherogenic, and anti-inflammatory properties. This case-control study was aimed to assess the expression and serum levels of adiponectin in subject suffereing from atrial fibrillation (AF). The study's subjects (n = 690) were enrolled from the Punjab Institute of Cardiology, Lahore and were grouped into control, AF without Metabolic syndrome (MetS), and AF with MetS groups. Along with the collection of demographic data, an analysis of adiponectin and biochemical parameters were performed. A highly significant difference in serum levels of adiponectin was observed among the control, AF without MetS, and AF with MetS groups (61.61 ± 45.30 ng/ml, 37.20 ± 19.46 ng/ml, 63.78 ± 61.69 ng/ml). The expression analysis of adiponectin was decreased (n-fold = ̴ 0.30) in AF without MetS group as compared to control group (n-fold =  ~ 1.16) but increased in AF with MetS group (n-fold = ̴ 6.26). The correlation analysis revealed a highly significant positive relationship between the expression of the adiponectin gene with waist-to-hip ratio (WHR) in AF without MetS group. Whereas, serum adiponectin was negatively related to serum triglycerides (TG) in AF with MetS group. In multiple regression analysis using adiponectin expression as the dependent variable, WHR was a determinant in AF without MetS. Whereas, when serum adiponectin was used as the dependent variable, serum TG was the determinant in group AF with MetS. The present study implicates that decreased expression and serum levels of adiponectin were associated with the development of AF in which WHR and serum TG also contributed towards the onset of atrial fibrillation.
Global trends in antimicrobial resistance on organic and conventional farms
Authors: Ager Eldon O. , Carvalho Tamilie , Silva Erin M. , Ricke Steven C. , Hite Jessica L.
Published: December 2023

The important hypothesis that organic livestock management reduces the prevalence of antimicrobial resistance is either fiercely supported or bitterly contested. Yet, empirical evidence supporting this view remains fragmentary, in part because relationships between antimicrobial use and drug resistance vary dramatically across contexts, hosts, pathogens, and country-specific regulations. Here, we synthesize global policies and definitions of ‘organic’ and ask if organic farming results in notable reductions in the prevalence of antimicrobial resistance when directly examined alongside conventional analogs. We synthesized the results of 72 studies, spanning 22 countries and five pathogens. Our results highlight substantial variations in country-specific policies on drug use and definitions of ‘organic’ that hinder broad-scale and generalizable patterns. Overall, conventional farms had slightly higher levels of antimicrobial resistance (28%) relative to organic counterparts (18%), although we found significant context-dependent variation in this pattern. Notably, environmental samples from organic and conventional farms often exhibited high levels of resistance to medically important drugs, underscoring the need for more stringent and consistent policies to control antimicrobial contaminants in the soil (particularly on organic farms, where the application of conventional manure could faciliate the spread antimicrobial resistance). Taken together, these results emphasize the challenges inherent in understanding links between drug use and drug resistance, the critical need for global standards governing organic policies, and greater investment in viable alternatives for managing disease in livestock.
Flow-induced oscillations of vocal-fold replicas with tuned extensibility and material properties
Authors: Luizard Paul , Bailly Lucie , Yousefi-Mashouf Hamid , Girault Raphaël , Orgéas Laurent , Henrich Bernardoni Nathalie
Published: December 2023

Human vocal folds are highly deformable non-linear oscillators. During phonation, they stretch up to 50% under the complex action of laryngeal muscles. Exploring the fluid/structure/acoustic interactions on a human-scale replica to study the role of the laryngeal muscles remains a challenge. For that purpose, we designed a novel in vitro testbed to control vocal-folds pre-phonatory deformation. The testbed was used to study the vibration and the sound production of vocal-fold replicas made of (i) silicone elastomers commonly used in voice research and (ii) a gelatin-based hydrogel we recently optimized to approximate the mechanics of vocal folds during finite strains under tension, compression and shear loadings. The geometrical and mechanical parameters measured during the experiments emphasized the effect of the vocal-fold material and pre-stretch on the vibration patterns and sounds. In particular, increasing the material stiffness increases glottal flow resistance, subglottal pressure required to sustain oscillations and vibratory fundamental frequency. In addition, although the hydrogel vocal folds only oscillate at low frequencies (close to 60 Hz), the subglottal pressure they require for that purpose is realistic (within the range 0.5–2 kPa), as well as their glottal opening and contact during a vibration cycle. The results also evidence the effect of adhesion forces on vibration and sound production.
Upregulated LAMA3 modulates proliferation, adhesion, migration and epithelial‑to‑mesenchymal transition of cholangiocarcinoma cells
Authors: Islam Kittiya , Balasubramanian Brinda , Venkatraman Simran , Thummarati Parichut , Tunganuntarat Janpen , Phueakphud Nut , Kanjanasirirat Phongthon , Khumpanied Tanawadee , Kongpracha Pornparn , Kittirat Yingpinyapat , Tohtong Rutaiwan , Janvilisri Tavan , Wongtrakoongate Patompon , Borwornpinyo Suparerk , Namwat Nisana , Suthiphongchai Tuangporn
Published: December 2023

A poor outcome for cholangiocarcinoma (CCA) patients is still a clinical challenge. CCA is typically recognized by the desmoplastic nature, which accounts for its malignancy. Among various extracellular matrix proteins, laminin is the most potent inducer for CCA migration. Herein, we accessed the expression profiles of laminin gene family and explored the significance of the key laminin subunit on CCA aggressiveness. Of all 11 laminin genes, LAMA3, LAMA5, LAMB3 and LAMC2 were concordantly upregulated based on the analysis of multiple public transcriptomic datasets and also overexpressed in Thai CCA cell lines and patient tissues in which LAMA3A upregulated in the highest frequency (97%) of the cases. Differential expression genes (DEGs) analysis of low and high laminin signature groups revealed LAMA3 as the sole common DEG in all investigated datasets. Restratifying CCA samples according to LAMA3 expression indicated the association of LAMA3 in the focal adhesion pathway. Silencing LAMA3 revealed that it plays important roles in CCA cell proliferation, adhesion, migration and epithelial-to-mesenchymal transition. Taken together, this research signifies the roles of dysregulated ECM homeostasis in CCA malignancy and highlights, for the first time, the potential usage of LAMA3 as the diagnostic biomarker and the therapeutic target to tackle the CCA stromal.
Task-evoked pulse wave amplitude tracks cognitive load
Authors: Pavlov Yuri G. , Gashkova Anastasia S. , Kasanov Dauren , Kosachenko Alexandra I. , Kotyusov Alexander I. , Kotchoubey Boris
Published: December 2023

Cognitive load is a crucial factor in mentally demanding activities and holds significance across various research fields. This study aimed to investigate the effectiveness of pulse wave amplitude (PWA) as a measure for tracking cognitive load and associated mental effort in comparison to heart rate (HR) during a digit span task. The data from 78 participants were included in the analyses. Participants performed a memory task in which they were asked to memorize sequences of 5, 9, or 13 digits, and a control task where they passively listened to the sequences. PWA and HR were quantified from photoplethysmography (PPG) and electrocardiography (ECG), respectively. Pupil dilation was also assessed as a measure of cognitive load. We found that PWA showed a strong suppression with increasing memory load, indicating sensitivity to cognitive load. In contrast, HR did not show significant changes with task difficulty. Moreover, when memory load exceeded the capacity of working memory, a reversal of the PWA pattern was observed, indicating cognitive overload. In this respect, changes in PWA in response to cognitive load correlated with the dynamics of pupil dilation, suggesting a potential shared underlying mechanism. Additionally, both HR and PWA demonstrated a relationship with behavioral performance, with higher task-evoked HR and lower PWA associated with better memory performance. Our findings suggest that PWA is a more sensitive measure than HR for tracking cognitive load and overload. PWA, measured through PPG, holds significant potential for practical applications in assessing cognitive load due to its ease of use and sensitivity to cognitive overload. The findings contribute to the understanding of psychophysiological indicators of cognitive load and offer insights into the use of PWA as a non-invasive measure in various contexts.
Multitechnique characterization of secondary minerals near HI-SEAS, Hawaii, as Martian subsurface analogues
Authors: Mulder Sebastian J. , van Ruitenbeek Frank J. A. , Foing Bernard H. , Sánchez-Román Mónica
Published: December 2023

Secondary minerals in lava tubes on Earth provide valuable insight into subsurface processes and the preservation of biosignatures on Mars. Inside lava tubes near the Hawaii-Space Exploration and Analog Simulation (HI-SEAS) habitat on the northeast flank of Mauna Loa, Hawaii, a variety of secondary deposits with distinct morphologies were observed consisting of mainly sodium sulphate powders, gypsum crystalline crusts, and small coralloid speleothems that comprise opal and calcite layers. These secondary deposits formed as a result of hydrological processes shortly after the formation and cooling of the lava tubes and are preserved over long periods of time in relatively dry conditions. The coralloid speleothem layers are likely related to wet and dry periods in which opal and calcite precipitates in cycles. Potential biosignatures seem to have been preserved in the form of porous stromatolite-like layers within the coralloid speleothems. Similar secondary deposits and lava tubes have been observed abundantly on the Martian surface suggesting similar formation mechanisms compared to this study. The origin of secondary minerals from tholeiitic basalts together with potential evidence for microbial processes make the lava tubes near HI-SEAS a relevant analog for Martian surface and subsurface environments.
LPS and its relationship with subjective–objective discrepancies of sleep onset latency in patients with psychiatric disorders
Authors: Kawai Keita , Iwamoto Kunihiro , Miyata Seiko , Okada Ippei , Ando Motoo , Fujishiro Hiroshige , Ando Masahiko , Noda Akiko , Ozaki Norio
Published: December 2023

Subjective–objective discrepancies in sleep onset latency (SOL), which is often observed among psychiatric patients, is attributed partly to the definition of sleep onset. Recently, instead of SOL, latency to persistent sleep (LPS), which is defined as the duration from turning out the light to the first consecutive minutes of non-wakefulness, has been utilized in pharmacological studies. This study aimed to determine the non-awake time in LPS that is most consistent with subjective sleep onset among patients with psychiatric disorders. We calculated the length of non-awake time in 30-s segments from lights-out to 0.5–60 min. The root mean square error was then calculated to determine the most appropriate length. The analysis of 149 patients with psychiatric disorders showed that the optimal non-awake time in LPS was 12 min. On the other hands, when comorbid with moderate or severe obstructive sleep apnea (OSA), the optimal length was 19.5 min. This study indicates that 12 min should be the best fit for the LPS non-awake time in patients with psychiatric disorders. When there is comorbidity with OSA, however, a longer duration should be considered. Measuring LPS minimizes discrepancies in SOL and provides important clinical information.
KRT13 and UPK1B for differential diagnosis between metastatic lung carcinoma from oral squamous cell carcinoma and lung squamous cell carcinoma
Authors: Goda Hiroyuki , Nakashiro Koh-ichi , Sano Yoshifumi , Adachi Tomoko , Tokuzen Norihiko , Kuribayashi Nobuyuki , Hino Satoshi , Uchida Daisuke
Published: December 2023

Oral squamous cell carcinomas unusually show distant metastasis to the lung after primary treatment, which can be difficult to differentiate from primary squamous cell carcinoma of the lung. While the location and number of tumor nodules is helpful in diagnosing cases, differential diagnosis may be difficult even with histopathological examination. Therefore, we attempted to identify molecules that can facilitate accurate differential diagnosis. First, we performed a comprehensive gene expression analysis using microarray data for OSCC-LM and LSCC, and searched for genes showing significantly different expression levels. We then identified KRT13, UPK1B, and nuclear receptor subfamily 0, group B, member 1 (NR0B1) as genes that were significantly upregulated in LSCC and quantified the expression levels of these genes by real-time quantitative RT-PCR. The expression of KRT13 and UPK1B proteins were then examined by immunohistochemical staining. While OSCC-LM showed no KRT13 and UPK1B expression, some tumor cells of LSCC showed KRT13 and UPK1B expression in 10 of 12 cases (83.3%). All LSCC cases were positive for at least one of these markers. Thus, KRT13 and UPK1B might contribute in differentiating OSCC-LM from LSCC.
3-D breast nodule detection on automated breast ultrasound using faster region-based convolutional neural networks and U-Net
Authors: Oh Kangrok , Lee Si Eun , Kim Eun-Kyung
Published: December 2023

Mammography is currently the most commonly used modality for breast cancer screening. However, its sensitivity is relatively low in women with dense breasts. Dense breast tissues show a relatively high rate of interval cancers and are at high risk for developing breast cancer. As a supplemental screening tool, ultrasonography is a widely adopted imaging modality to standard mammography, especially for dense breasts. Lately, automated breast ultrasound imaging has gained attention due to its advantages over hand-held ultrasound imaging. However, automated breast ultrasound imaging requires considerable time and effort for reading because of the lengthy data. Hence, developing a computer-aided nodule detection system for automated breast ultrasound is invaluable and impactful practically. This study proposes a three-dimensional breast nodule detection system based on a simple two-dimensional deep-learning model exploiting automated breast ultrasound. Additionally, we provide several postprocessing steps to reduce false positives. In our experiments using the in-house automated breast ultrasound datasets, a sensitivity of $$93.65\%$$

93.65
%

with 8.6 false positives is achieved on unseen test data at best.
Evaluation of glomerular sirtuin-1 and claudin-1 in the pathophysiology of nondiabetic focal segmental glomerulosclerosis
Authors: Lopes-Gonçalves Guilherme , Costa-Pessoa Juliana Martins , Pimenta Ruan , Tostes Ana Flavia , da Silva Eloisa Martins , Ledesma Felipe Lourenço , Malheiros Denise Maria Avancini Costa , Zatz Roberto , Thieme Karina , Câmara Niels Olsen Saraiva , Oliveira-Souza Maria
Published: December 2023

Focal segmental glomerulosclerosis (FSGS) is the leading cause of nephrotic syndrome, which is characterized by podocyte injury. Given that the pathophysiology of nondiabetic glomerulosclerosis is poorly understood and targeted therapies to prevent glomerular disease are lacking, we decided to investigate the tight junction protein claudin-1 and the histone deacetylase sirtuin-1 (SIRT1), which are known to be involved in podocyte injury. For this purpose, we first examined SIRT1, claudin-1 and podocin expression in kidney biopsies from patients diagnosed with nondiabetic FSGS and found that upregulation of glomerular claudin-1 accompanies a significant reduction in glomerular SIRT1 and podocin levels. From this, we investigated whether a small molecule activator of SIRT1, SRT1720, could delay the onset of FSGS in an animal model of adriamycin (ADR)-induced nephropathy; 14 days of treatment with SRT1720 attenuated glomerulosclerosis progression and albuminuria, prevented transcription factor Wilms tumor 1 (WT1) downregulation and increased glomerular claudin-1 in the ADR + SRT1720 group. Thus, we evaluated the effect of ADR and/or SRT1720 in cultured mouse podocytes. The results showed that ADR [1 µM] triggered an increase in claudin-1 expression after 30 min, and this effect was attenuated by pretreatment of podocytes with SRT1720 [5 µM]. ADR [1 µM] also led to changes in the localization of SIRT1 and claudin-1 in these cells, which could be associated with podocyte injury. Although the use of specific agonists such as SRT1720 presents some benefits in glomerular function, their underlying mechanisms still need to be further explored for therapeutic use. Taken together, our data indicate that SIRT1 and claudin-1 are relevant for the pathophysiology of nondiabetic FSGS.
Dual-level clustering ensemble algorithm with three consensus strategies
Authors: Shan Yunxiao , Li Shu , Li Fuxiang , Cui Yuxin , Chen Minghua
Published: December 2023

Clustering ensemble (CE), renowned for its robust and potent consensus capability, has garnered significant attention from scholars in recent years and has achieved numerous noteworthy breakthroughs. Nevertheless, three key issues persist: (1) the majority of CE selection strategies rely on preset parameters or empirical knowledge as a premise, lacking adaptive selectivity; (2) the construction of co-association matrix is excessively one-sided; (3) the CE method lacks a more macro perspective to reconcile the conflicts among different consensus results. To address these aforementioned problems, a dual-level clustering ensemble algorithm with three consensus strategies is proposed. Firstly, a backward clustering ensemble selection framework is devised, and its built-in selection strategy can adaptively eliminate redundant members. Then, at the base clustering consensus level, taking into account the interplay between actual spatial location information and the co-occurrence frequency, two modified relation matrices are reconstructed, resulting in the development of two consensus methods with different modes. Additionally, at the CE consensus level with a broader perspective, an adjustable Dempster–Shafer evidence theory is developed as the third consensus method in present algorithm to dynamically fuse multiple ensemble results. Experimental results demonstrate that compared to seven other state-of-the-art and typical CE algorithms, the proposed algorithm exhibits exceptional consensus ability and robustness.
Enhancing domain generalization in the AI-based analysis of chest radiographs with federated learning
Authors: Tayebi Arasteh Soroosh , Kuhl Christiane , Saehn Marwin-Jonathan , Isfort Peter , Truhn Daniel , Nebelung Sven
Published: December 2023

Developing robust artificial intelligence (AI) models that generalize well to unseen datasets is challenging and usually requires large and variable datasets, preferably from multiple institutions. In federated learning (FL), a model is trained collaboratively at numerous sites that hold local datasets without exchanging them. So far, the impact of training strategy, i.e., local versus collaborative, on the diagnostic on-domain and off-domain performance of AI models interpreting chest radiographs has not been assessed. Consequently, using 610,000 chest radiographs from five institutions across the globe, we assessed diagnostic performance as a function of training strategy (i.e., local vs. collaborative), network architecture (i.e., convolutional vs. transformer-based), single versus cross-institutional performance (i.e., on-domain vs. off-domain), imaging finding (i.e., cardiomegaly, pleural effusion, pneumonia, atelectasis, consolidation, pneumothorax, and no abnormality), dataset size (i.e., from n = 18,000 to 213,921 radiographs), and dataset diversity. Large datasets not only showed minimal performance gains with FL but, in some instances, even exhibited decreases. In contrast, smaller datasets revealed marked improvements. Thus, on-domain performance was mainly driven by training data size. However, off-domain performance leaned more on training diversity. When trained collaboratively across diverse external institutions, AI models consistently surpassed models trained locally for off-domain tasks, emphasizing FL’s potential in leveraging data diversity. In conclusion, FL can bolster diagnostic privacy, reproducibility, and off-domain reliability of AI models and, potentially, optimize healthcare outcomes.