bluuebunny/crossref_metadata_2025_split huggingface dataset:
Six Decades of Thermal Change in a Pristine Lake Situated North of the Arctic Circle
Authors: Noori Roohollah , Woolway R. Iestyn , Saari Markus , Pulkkanen Merja , Kløve Bjørn 
Published: September 2022

AbstractThe majority of lake temperature studies have investigated climate‐induced changes occurring at the lake surface, primarily by analyzing detailed satellite images of surface water temperature. Whilst essential to observe long‐term change, satellite images do not provide information on the thermal environment at depth, thus limiting our understanding of lake thermal responses to a warming world. Long‐term in situ observational data can fill some of the information gap, with depth‐resolved field measurements providing a detailed view of thermal change throughout the water column. However, many previous studies that have investigated multi‐decadal changes in lake temperature, both at the surface and at depth, have typically focused on north temperate lakes. Relatively few studies have investigated temperature variations in lakes situated north of the Arctic Circle, which is one of the most rapidly warming regions on Earth. Here, using a 60‐year (1961–2020) observational data set of summer water temperature (July–September) from Lake Inari (Finland), we investigate changes in the thermal environment of this pristine lake. Our analysis suggests a statistically significant summer warming trend at the lake surface (+0.25°C decade−1, p‐value <0.1), whilst deepwater temperatures remain largely unchanged. This contrasting thermal response of surface and bottom water temperature to climatic warming has likewise resulted in a strengthening of summer stratification in this high latitude lake. Implications of the observed change in both temperature and stratification on the lake ecosystem will likely be extensive, including impacts on aquatic organisms which this lake supports. Our work builds on the ever‐growing literature regarding lake thermal responses to climate change.
Bedload Fluxes in a Glacier‐Fed River at Multiple Temporal Scales
Authors: Coviello Velio , Vignoli Gianluca , Simoni Silvia , Bertoldi Walter , Engel Michael , Buter Anuschka , Marchetti Giulia , Andreoli Andrea , Savi Sara , Comiti Francesco 
Published: September 2022

AbstractIn mountain rivers, long‐term observations of water and sediment fluxes are crucial for understanding the dynamics of bedload fluctuations. We analyze 7 years of continuous data gathered from eight geophone plates at a monitoring station in the glacier‐fed Sulden/Solda River (South Tyrol, Italy) to estimate the bedload flux at 1‐min scale. Sixty‐five bedload samples were used to derive the calibration equations adopted to quantify the transported bedload mass. The signal power is proposed as a more effective metric than threshold‐based impulses for calculating bedload masses. Results show (a) a remarkable variability of bedload rates for the same value of flow discharge, (b) the joint effect of storm‐driven flood events and seasonal changes in sediment supply on bedload rates, and (c) the strong impact of climatic factors (i.e., temperature and snow cover) on bedload fluxes. Moderate bedload rates occurring in late spring/early summer are likely related to the mobilization of riverbed sediments, while sustained bedload transport during melt flows in July–August—corresponding to the effective bedload discharge range—is associated with the activation of glacial and proglacial sediment sources. The data set shows a complex climatic control on bedload transport at the basin scale, where precipitation, air temperature, and snow cover determine flow and glacier melting dynamics. These findings suggest how the effects of climate change in the Alps likely will lead to an increase in peak bedload rates in a context of declining annual bedload yields as melt flows will progressively reduce in the next decades.
GMA: An Improved Framework of Radar Extrapolation Based on Spatiotemporal Sequence Neural Network
Authors: Wang Shengchun , Jiang Kefei , Huang Jingui , Huang Long 
Published: September 2022

AbstractMost previous current spatiotemporal sequence neural networks used for radar extrapolation have difficulties in learning long‐term spatiotemporal memories. This is because the spatiotemporal sequential neural networks only use the information from the previous time step node to update the prediction state, and the networks tend to rely on the convolution layers to capture the spatiotemporal features, which are local and inefficient. In order to capture the long‐term temporal characteristics and local abrupt spatial characteristics of radar echo sequence, we propose a new framework, Global Memory Attention (GMA), which has two contributions. The first is that we establish a global information flow between calculation units, extract the key historical memory from the global information flow, calculate the correlation between the historical key memory and the current time frame prediction state, and determine how much historical memory participates in the prediction state update. It alleviates the current network's difficulty in learning the long‐term spatial and temporal characteristics of radar echo sequences and the problem of short‐term dependence, and reduces the interference of image noise in the process of radar extrapolation prediction. The second is that the GMA module is a flexible additional module that can be applied to most radar extrapolation algorithms based on timing networks. GMA has reached the highest level on radar extrapolation tasks, and we have provided ablation studies to verify the effectiveness of GMA.
Three‐Dimensional Fourier Analysis of Atmospheric Gravity Waves and Medium‐Scale Traveling Ionospheric Disturbances Observed in Airglow Images in Hawaii Over Three Years
Authors: Naito Hideto , Shiokawa Kazuo , Otsuka Yuichi , Fujinami Hatsuki , Tsuboi Takuma , Sakanoi Takeshi , Saito Akinori , Nakamura Takuji 
Published: September 2022

AbstractThree‐dimensional Fourier spectral analysis of airglow images is a useful technique to provide propagation characteristics of atmospheric gravity waves (AGWs) in the mesopause region and medium‐scale traveling ionospheric disturbances (MSTIDs) in the thermosphere observed at emission wavelengths of 557.7 nm (altitudes: 90–100 km for AGWs) and 630.0 nm (200–300 km for MSTIDs). However, a statistical study of spectral analysis of airglow images over years has not been done yet at Hawaii. Here, we report the first spectral analysis of AGWs and MSTIDs using airglow images obtained at Haleakala (20.71°N, 203.74°E), Hawaii, during the three years from 2013 to 2016. The power spectral density (PSD) of AGWs tends to be larger toward north to northeast in summer and from north to west and southward in winter. The eastward (summer) and westward (winter) preferences are consistent with a wind‐filtering mechanism of AGWs by a mesospheric jet. Some correspondence is found between the locations of tropospheric convection activities and AGW propagation directions, suggesting that these mesospheric AGWs are originated from the troposphere. The PSDs of MSTIDs are larger in solstice than in equinox. This PSD enhancement in solstice is consistent with a sporadic‐E (Es) layer occurrence in either northern or southern hemisphere, suggesting that the MSTIDs over Hawaii could be caused by a coupling process between the Perkins and Es layer instabilities. A small correlation was found between the PSDs of AGWs in the mesopause region and the PSDs of MSTIDs, suggesting that the MSTIDs are partly caused by AGWs from the mesopause region.
Climatology of the CO Vertical Distribution on Mars Based on ACS TGO Measurements
Authors: Fedorova Anna , Trokhimovskiy Alexander , Lefèvre Franck , Olsen Kevin S. , Korablev Oleg , Montmessin Franck , Ignatiev Nikolay , Lomakin Alexander , Forget Francois , Belyaev Denis , Alday Juan , Luginin Mikhail , Smith Michael , Patrakeev Andrey , Shakun Alexey , Grigoriev Alexey 
Published: September 2022

AbstractCarbon monoxide is a non‐condensable gas in the Martian atmosphere produced by the photolysis of CO2. Its abundance responds to the condensation and sublimation of CO2 from the polar caps, resulting in seasonal variations of the CO mixing ratio. ACS onboard the ExoMars Trace Gas Orbiter have measured CO in infrared bands by solar occultation. Here we provide the first long‐term monitoring of the CO vertical distribution at the altitude range from 0 to 80 km for 1.5 Martian years from Ls = 163° of MY34 to the end of MY35. We obtained a mean CO mixing ratio of ∼960 ppmv at latitudes from 45°S to 45°N and altitudes below 40 km, mostly consistent with previous observations. We found a strong enrichment of CO near the surface at Ls = 100–200° in high southern latitudes with a layer of 3,000–4,000 ppmv, corresponding to local depletion of CO2. At equinoxes we found an increase of the CO mixing ratio above 50 km to 3,000–4,000 ppmv at high latitudes of both hemispheres explained by the downwelling flux of the Hadley circulation on Mars, which drags the CO enriched air. General circulation models tend to overestimate the intensity of this process, bringing too much CO. The observed minimum of CO in the high and mid‐latitudes southern summer atmosphere amounts to 700–750 ppmv, agreeing with nadir measurements. During the global dust storm of MY34, when the H2O abundance peaks, we see less CO than during the calm MY35, suggesting an impact of HOx chemistry on the CO abundance.
Upscaling Hydrodynamic Dispersion in Non‐Newtonian Fluid Flow Through Porous Media
Authors: An Senyou , Sahimi Muhammad , Niasar Vahid 
Published: September 2022

AbstractHydrodynamic dispersion in flow through porous media is an essential phenomenon in many geosystems. While dispersion in flow of Newtonian fluids is relatively well‐understood, many subsurface applications, such as groundwater remediation, use the flooding system with non‐Newtonian fluids, such as polymer oxidants. Despite its significance, however, very limited studies have been carried out focusing on hydrodynamic dispersion in flow of non‐Newtonian fluids. The present study addresses a fundamental question regarding how solute transport in flow of non‐Newtonian fluids in porous media differs from the Newtonian limit. We report on the results of an extensive pore‐scale study of the upscaling of advection‐diffusion in flow of a non‐Newtonian, shear thinning fluid through disordered and spatially‐correlated porous media, using an advanced GPU‐based pore‐scale simulator in order to delineate the effects of the fluid's rheology, dynamics of fluid flow, and pore‐scale spatial correlations on hydrodynamic dispersion. The simulations indicate a surprising non‐monotonic relation between the injection rate (or injection velocity) and the dispersivity. While dispersivity in Newtonian fluid flow in porous media is constant in the flow regime that we study, we find, however, that the dispersivity in flow of non‐Newtonian fluids is shear‐dependent. This highlights the gap in the existing theories of transport through porous materials for non‐Newtonian fluids, which can lead to erroneous estimates of dispersion coefficients in porous materials when the fluid's rheology cannot be represented by Newtonian mechanics.
Differentiable, Learnable, Regionalized Process‐Based Models With Multiphysical Outputs can Approach State‐Of‐The‐Art Hydrologic Prediction Accuracy
Authors: Feng Dapeng , Liu Jiangtao , Lawson Kathryn , Shen Chaopeng 
Published: September 2022

AbstractPredictions of hydrologic variables across the entire water cycle have significant value for water resources management as well as downstream applications such as ecosystem and water quality modeling. Recently, purely data‐driven deep learning models like long short‐term memory (LSTM) showed seemingly insurmountable performance in modeling rainfall runoff and other geoscientific variables, yet they cannot predict untrained physical variables and remain challenging to interpret. Here, we show that differentiable, learnable, process‐based models (called δ models here) can approach the performance level of LSTM for the intensively observed variable (streamflow) with regionalized parameterization. We use a simple hydrologic model HBV as the backbone and use embedded neural networks, which can only be trained in a differentiable programming framework, to parameterize, enhance, or replace the process‐based model's modules. Without using an ensemble or post‐processor, δ models can obtain a median Nash‐Sutcliffe efficiency of 0.732 for 671 basins across the USA for the Daymet forcing data set, compared to 0.748 from a state‐of‐the‐art LSTM model with the same setup. For another forcing data set, the difference is even smaller: 0.715 versus 0.722. Meanwhile, the resulting learnable process‐based models can output a full set of untrained variables, for example, soil and groundwater storage, snowpack, evapotranspiration, and baseflow, and can later be constrained by their observations. Both simulated evapotranspiration and fraction of discharge from baseflow agreed decently with alternative estimates. The general framework can work with models with various process complexity and opens up the path for learning physics from big data.
Microbial carbon, sulfur, iron, and nitrogen cycling linked to the potential remediation of a meromictic acidic pit lake
Authors: Ayala-Muñoz Diana , Macalady Jennifer L , Sánchez-España Javier , Falagán Carmen , Couradeau Estelle , Burgos William D 
Published: September 2022

Abstract
Cueva de la Mora is a permanently stratified acidic pit lake and a model system for extreme acid mine drainage (AMD) studies. Using a combination of amplicon sequencing, metagenomics and metatranscriptomics we performed a taxonomically resolved analysis of microbial contributions to carbon, sulfur, iron, and nitrogen cycling. We found that active green alga Coccomyxa onubensis dominated the upper layer and chemocline. The chemocline had activity for iron(II) oxidation carried out by populations of Ca. Acidulodesulfobacterium, Ferrovum, Leptospirillium, and Armatimonadetes. Predicted activity for iron(III) reduction was only detected in the deep layer affiliated with Proteobacteria. Activity for dissimilatory nitrogen cycling including nitrogen fixation and nitrate reduction was primarily predicted in the chemocline. Heterotrophic archaeal populations with predicted activity for sulfide oxidation related to uncultured Thermoplasmatales dominated in the deep layer. Abundant sulfate-reducing Desulfomonile and Ca. Acidulodesulfobacterium populations were active in the chemocline. In the deep layer, uncultured populations from the bacterial phyla Actinobacteria, Chloroflexi, and Nitrospirae contributed to both sulfate reduction and sulfide oxidation. Based on this information we evaluated the potential for sulfide mineral precipitation in the deep layer as a tool for remediation. We argue that sulfide precipitation is not limited by microbial genetic potential but rather by the quantity and quality of organic carbon reaching the deep layer as well as by oxygen additions to the groundwater enabling sulfur oxidation. Addition of organic carbon and elemental sulfur should stimulate sulfate reduction and limit reoxidation of sulfide minerals.
An update regarding the role of WNK kinases in cancer
Authors: Xiu Mengxi , Li Li , Li Yandong , Gao Yong 
Published: September 2022

AbstractMammalian WNK kinases (WNKs) are serine/threonine kinases that contain four members, WNK1–4. They function to maintain ion homeostasis and regulate blood pressure in mammals. Recent studies have revealed that the dysregulation of WNKs contributes to tumor growth, metastasis, and angiogenesis through complex mechanisms, especially through phosphorylating kinase substrates SPS1-related proline/alanine-rich kinase (SPAK) and oxidative stress-responsive kinase 1 (OSR1). Here, we review and discuss the relationships between WNKs and several key factors/biological processes in cancer, including ion channels, cation chloride cotransporters, sodium bicarbonate cotransporters, signaling pathways, angiogenesis, autophagy, and non-coding RNAs. In addition, the potential drugs for targeting WNK-SPAK/OSR1 signaling have also been discussed. This review summarizes and discusses knowledge of the roles of WNKs in cancer, which provides a comprehensive reference for future studies.
Structural characterization of a soil viral auxiliary metabolic gene product – a functional chitosanase
Authors: Wu Ruonan , Smith Clyde A. , Buchko Garry W. , Blaby Ian K. , Paez-Espino David , Kyrpides Nikos C. , Yoshikuni Yasuo , McDermott Jason E. , Hofmockel Kirsten S. , Cort John R. , Jansson Janet K. 
Published: September 2022

AbstractMetagenomics is unearthing the previously hidden world of soil viruses. Many soil viral sequences in metagenomes contain putative auxiliary metabolic genes (AMGs) that are not associated with viral replication. Here, we establish that AMGs on soil viruses actually produce functional, active proteins. We focus on AMGs that potentially encode chitosanase enzymes that metabolize chitin – a common carbon polymer. We express and functionally screen several chitosanase genes identified from environmental metagenomes. One expressed protein showing endo-chitosanase activity (V-Csn) is crystalized and structurally characterized at ultra-high resolution, thus representing the structure of a soil viral AMG product. This structure provides details about the active site, and together with structure models determined using AlphaFold, facilitates understanding of substrate specificity and enzyme mechanism. Our findings support the hypothesis that soil viruses contribute auxiliary functions to their hosts.
ARID1A mutations confer intrinsic and acquired resistance to cetuximab treatment in colorectal cancer
Authors: Johnson Radia M. , Qu Xueping , Lin Chu-Fang , Huw Ling-Yuh , Venkatanarayan Avinashnarayan , Sokol Ethan , Ou Fang-Shu , Ihuegbu Nnamdi , Zill Oliver A. , Kabbarah Omar , Wang Lisa , Bourgon Richard , de Sousa e Melo Felipe , Bolen Chris , Daemen Anneleen , Venook Alan P. , Innocenti Federico , Lenz Heinz-Josef , Bais Carlos 
Published: September 2022

AbstractMost colorectal (CRC) tumors are dependent on EGFR/KRAS/BRAF/MAPK signaling activation. ARID1A is an epigenetic regulator mutated in approximately 5% of non-hypermutated CRC tumors. Here we show that anti-EGFR but not anti-VEGF treatment enriches for emerging ARID1A mutations in CRC patients. In addition, we find that patients with ARID1A mutations, at baseline, are associated with worse outcome when treated with cetuximab- but not bevacizumab-containing therapies; thus, this suggests that ARID1A mutations may provide both an acquired and intrinsic mechanism of resistance to anti-EGFR therapies. We find that, ARID1A and EGFR-pathway genetic alterations are mutually exclusive across lung and colorectal cancers, further supporting a functional connection between these pathways. Our results not only suggest that ARID1A could be potentially used as a predictive biomarker for cetuximab treatment decisions but also provide a rationale for exploring therapeutic MAPK inhibition in an unexpected but genetically defined segment of CRC patients.
Causal contribution of optic flow signal in Macaque extrastriate visual cortex for roll perception
Authors: Li Wenhao , Lu Jianyu , Zhu Zikang , Gu Yong 
Published: September 2022

AbstractOptic flow is a powerful cue for inferring self-motion status which is critical for postural control, spatial orientation, locomotion and navigation. In primates, neurons in extrastriate visual cortex (MSTd) are predominantly modulated by high-order optic flow patterns (e.g., spiral), yet a functional link to direct perception is lacking. Here, we applied electrical microstimulation to selectively manipulate population of MSTd neurons while macaques discriminated direction of rotation around line-of-sight (roll) or direction of linear-translation (heading), two tasks which were orthogonal in 3D spiral coordinate using a four-alternative-forced-choice paradigm. Microstimulation frequently biased animal’s roll perception towards coded labeled-lines of the artificial-stimulated neurons in either context with spiral or pure-rotation stimuli. Choice frequency was also altered between roll and translation flow-pattern. Our results provide direct causal-link evidence supporting that roll signals in MSTd, despite often mixed with translation signals, can be extracted by downstream areas for perception of rotation relative to gravity-vertical.
Microstructure segmentation with deep learning encoders pre-trained on a large microscopy dataset
Authors: Stuckner Joshua , Harder Bryan , Smith Timothy M. 
Published: September 2022

AbstractThis study examined the improvement of microscopy segmentation intersection over union accuracy by transfer learning from a large dataset of microscopy images called MicroNet. Many neural network encoder architectures were trained on over 100,000 labeled microscopy images from 54 material classes. These pre-trained encoders were then embedded into multiple segmentation architectures including UNet and DeepLabV3+ to evaluate segmentation performance on created benchmark microscopy datasets. Compared to ImageNet pre-training, models pre-trained on MicroNet generalized better to out-of-distribution micrographs taken under different imaging and sample conditions and were more accurate with less training data. When training with only a single Ni-superalloy image, pre-training on MicroNet produced a 72.2% reduction in relative intersection over union error. These results suggest that transfer learning from large in-domain datasets generate models with learned feature representations that are more useful for downstream tasks and will likely improve any microscopy image analysis technique that can leverage pre-trained encoders.
Pseudomonas putida mediates bacterial killing, biofilm invasion and biocontrol with a type IVB secretion system
Authors: Purtschert-Montenegro Gabriela , Cárcamo-Oyarce Gerardo , Pinto-Carbó Marta , Agnoli Kirsty , Bailly Aurélien , Eberl Leo 
Published: September 2022

AbstractMany bacteria utilize contact-dependent killing machineries to eliminate rivals in their environmental niches. Here we show that the plant root colonizer Pseudomonas putida strain IsoF is able to kill a wide range of soil and plant-associated Gram-negative bacteria with the aid of a type IVB secretion system (T4BSS) that delivers a toxic effector into bacterial competitors in a contact-dependent manner. This extends the range of targets of T4BSSs—so far thought to transfer effectors only into eukaryotic cells—to prokaryotes. Bioinformatic and genetic analyses showed that this killing machine is entirely encoded by the kib gene cluster located within a rare genomic island, which was recently acquired by horizontal gene transfer. P. putida IsoF utilizes this secretion system not only as a defensive weapon to kill bacterial competitors but also as an offensive weapon to invade existing biofilms, allowing the strain to persist in its natural environment. Furthermore, we show that strain IsoF can protect tomato plants against the phytopathogen Ralstonia solanacearum in a T4BSS-dependent manner, suggesting that IsoF can be exploited for pest control and sustainable agriculture.