bluuebunny/crossref_metadata_2025_split huggingface dataset:
Comparative Metatranscriptomics of Rhizosphere Microbiomes in Survived and Dead Cocoa Plants Under Drought Condition
Authors: Tamchek Norasekin , Lee Ping-Chin 
Published: August 2024

AbstractPlant rhizosphere is an important ecological niche in which complex plant–microbe interactions occur. The rhizosphere microbial community has high genetic diversity, acting as an important regulator of plant productivity and growth, especially under stress conditions. This study reports the investigation of the rhizosphere community and their interactions under drought conditions in Theobroma cacao (cocoa), an important cash crop and commodity worldwide. We compared the active microbial community of the dead and survived cocoa plants under drought conditions using a metatranscriptomic approach. The metatranscriptome of four rhizosphere samples (two from drought plants and two from dead plants) was analysed. Based on mRNA annotation, the dominant taxa in the rhizosphere revealed Proteobacteria as the major phyla in all rhizosphere samples. The order of the top abundant phyla in rhizosphere of the surviving cocoa plant was Proteobacteria (42–49%), Firmicutes (0.4–2%), Actinobacteria (0.8–1.3%) and Acidobacteria (0.3–0.4%) whereas the rhizosphere of the dead plant revealed Proteobacteria (38–46%), Firmicutes (0.1–1.5%), Acidobacteria (0.7–0.9%) and Thaumarchaeota (0.3–0.5%). The microbial profiles of both rhizosphere samples were similar at the phylum level. Further analysis at the genus level revealed 1712 classified genera in the rhizosphere samples, at which all rhizosphere samples shared 739 genera. The most dominant genus identified was Pseudomonas, followed by Bacillus and Thiocapsa in rhizospheres of the surviving cocoa plants and Pseudomonas, followed by Aeromonas and Klebsiella in rhizospheres of the dead cocoa plants, respectively. Our results suggested changes in the microbial composition and structure in the rhizosphere of the cocoa plant, which might play important roles in the plant’s survival due to drought.
Rapid particle generation from an STL file and related issues in the application of material point methods to complex objects
Authors: Zhang Duan Z. , Perez Kyle A. , Barclay Paul L. , Waters Jiajia 
Published: August 2024

AbstractIn this paper, we focus on three issues related to applications of material point methods (MPMs) to objects with complex geometries. They are material point generation, compatibility of material points with a mesh, and sensitivity to mesh orientation. An efficient method of generating material points from a stereolithography (STL) file is introduced. This material point generation method is independent of the mesh used in MPM calculations. The compatibility between the material points and the mesh is then studied. We also show that the original MPM and the dual domain material point (DDMP) method are sensitive to mesh orientation. These issues are related to the calculation of the internal force and are concerns of the MPMs. They become more prominent when MPMs are applied to complex geometries. Our numerical results show that the recently developed local stress difference (LSD) algorithm (Perez et al. in J Comp Phys 498:112681, 2024) can be used to effectively address them.
Creep deformation characteristics and control technology in deep mine soft rock roadway
Authors: Yan Lianghuan , Chang Jucai , Shi Wenbao , Wang Tuo , Qiao Longquan , Guo Yijun , Wang Hongda 
Published: August 2024

AbstractIn order to control the strong ageing creep and large deformation of deep soft rock roadway effectively, with the 61–71 track on the uphill of the mining area in Suzhou, Anhui as the research background, the triaxial creep test of mudstone was conducted using the TYJ-1500 M rock mechanics testing system. The creep deformation and failure characteristics of mudstone were analyzed. Additionally, the creep deformation characteristics of deep soft rock roadways were obtained through FLAC3D numerical simulation experiment, and the control techniques for deep soft rock roadway was proposed. The results showed that the axial strain and lateral strain of the specimen were mainly instantaneous strain and creep strain under triaxial stress conditions, and the both confining pressure and the axial pressure have a significant impact on the deformation and creep failure strength of the specimen. Under the condition of high ground stress and complex geological structure, the high stress concentration of roadway roof and floor and two bottom angles is the main cause of creep failure of soft rock roadway, and the large degree of surrounding rock fragmentation and unreasonable support mode reduce the bearing capacity of surrounding rock and aggravate the creep failure of roadway. The 'anchor net cable shotcrete + floor and two corners in floor bolt-grouting + deep and shallow hole grouting + secondary reinforcement support' combined support method was proposed and industrially tested, with average deformation of the roof, floor, and two sidewalls being 111.9 and 62.5 mm, respectively, representing 13.2 and 10.3% of the deformation under the original support scheme.
QUBO Models for the FIFO Stack-Up Problem and Experimental Evaluation on a Quantum Annealer
Authors: Gebler Colin , Rethmann Jochen , Ueberholz Peer 
Published: August 2024

AbstractQuantum annealing has been applied to combinatorial optimization problems in recent years. In this paper we study the possibility to use quantum annealing for solving the combinatorial FIFO Stack-Up problem, where bins have to be stacked-up from a conveyor belt onto pallets. The problem is NP-hard and can be solved using linear programming approaches. We developed two QUBO (quadratic unconstrained binary optimization) objective functions based on a bin stack-up solution and a pallet stack-up solution for this problem suitable for a quantum annealer. The number of variables was minimized to increase the performance and their dependence on the number of bins and pallets was discussed. The performances of both methods were studied for various small problem sizes on a D-Wave quantum annealer. We found that only tiny instances could be solved and looked at the terms of the QUBO-formulations, which cause the quantum annealer to fail for larger problem sizes. Furthermore we compare the results to the performance of a classic computer using the same QUBO-formulations.
Forecasting Daily Fire Radiative Energy Using Data Driven Methods and Machine Learning Techniques
Authors: Thapa Laura H. , Saide Pablo E. , Bortnik Jacob , Berman Melinda T. , da Silva Arlindo , Peterson David A. , Li Fangjun , Kondragunta Shobha , Ahmadov Ravan , James Eric , Romero‐Alvarez Johana , Ye Xinxin , Soja Amber , Wiggins Elizabeth , Gargulinski Emily 
Published: August 2024

AbstractIncreasing impacts of wildfires on Western US air quality highlights the need for forecasts of smoke emissions based on dynamic modeled wildfires. This work utilizes knowledge of weather, fuels, topography, and firefighting, combined with machine learning and other statistical methods, to generate 1‐ and 2‐day forecasts of fire radiative energy (FRE). The models are trained on data covering 2019 and 2021 and evaluated on data for 2020. For the 1‐day (2‐day) forecasts, the random forest model shows the most skill, explaining 48% (25%) of the variance in observed daily FRE when trained on all available predictors compared to the 2% (<0%) of variance explained by persistence for the extreme fire year of 2020. The random forest model also shows improved skill in forecasting day‐to‐day increases and decreases in FRE, with 28% (39%) of observed increase (decrease) days predicted, and increase (decrease) days are identified with 62% (60%) accuracy. Error in the random forest increases with FRE, and the random forest tends toward persistence under severe fire weather. Sensitivity analysis shows that near‐surface weather and the latest observed FRE contribute the most to the skill of the model. When the random forest model was trained on subsets of the training data produced by agencies (e.g., the Canadian or US Forest Services), comparable if not better performance was achieved (1‐day R2 = 0.39–0.48, 2‐day R2 = 0.13–0.34). FRE is used to compute emissions, so these results demonstrate potential for improved fire emissions forecasts for air quality models.
Fluid‐Driven Shear Instabilities in the Subducted Oceanic Mantle at Intermediate Depths: Insights From Western Alps Meta‐Ophiolites
Authors: Muñoz‐Montecinos J. , Angiboust S. , Minnaert C. , Ceccato A. , Morales L. , Gasc J. , Behr W. 
Published: August 2024

AbstractSerpentinites are major carriers of volatiles in deep subduction zones, releasing most fluids in the 500–650°C range. Despite fundamental implications for mass transfer and intermediate‐depth seismicity, the mechanical role of these fluids is unclear. To characterize the mechanical role of fluids at (ultra)high‐pressure conditions, we perform a petro‐structural analysis on olivine‐rich veins from the Western Alps meta‐ophiolite. Some veins formed through dilational and mixed dilational‐shear fracturing without significant shear‐related deformation. However, field and microstructural observations indicate transient shearing and dilational fracturing at high pore fluid pressures. These include: (a) foliated sheared veins; (b) newly formed olivine and Ti‐clinohumite within mineral lineations coating sheared veins and shear bands; (c) Olivine and Ti‐clinohumite mineral fibers sealing porphyroclasts; (d) mutual crosscutting relationships among dilational and shear features. Dilational veins prevail in low‐strain areas, while sheared veins and shear bands dominate within high‐strain zones toward the ultramafic sliver boundaries. These strain variations underscore the role of local stress regimes during serpentinite dehydration. Consequently, areas experiencing stronger shear stresses around large‐scale blocks or mechanical weakening during fluid circulation are prone to draining overpressurized fluids. These interface‐parallel and fracture‐controlled pathways thus facilitate fluid escape from the dehydrating downgoing slab. Transient events of dilational fracturing and brittle‐ductile shearing, along with strain localization in highly comminuted olivine‐bearing sheared veins, may have resulted from strain rate bursts potentially related to (sub)seismic deformation. These observations are in line with geophysical data indicating high pore fluid pressures within the intermediate‐depth seismicity region.
Reconciling Rapid Glacial Erosion and Steady Basin Accumulation Rates in the Late Cenozoic Through the Effect of Glacial Sediment on Fluvial Erosion
Authors: Schanz Sarah A. , Yanites Brian J. 
Published: August 2024

AbstractThe onset of glaciation in the late Cenozoic caused rapid bedrock erosion above the snowline; however, whether the influx of eroded sediment is recorded in continental weathering and basin accumulation rates is an ongoing debate. We propose that the transport of glacially eroded bedrock through the fluvial system damps the signal of rapid headwater erosion and results in steady basin‐integrated sediment flux. Using a numerical model with integrated glacial and fluvial erosion, we find that headwater bedrock erosion rates increase rapidly at the onset of glaciation and continue to fluctuate with climatic oscillation. However, bedrock erosion rates decrease in the downstream fluvial system because larger grain sizes from glaciers result in an increase in sediment cover effect. When erosion and sediment flux rates are averaged, long‐term sediment flux is similar to nonglacial flux values, while localized bedrock erosion rates in the glaciated landscape are elevated 2–4 times compared to nonglacial values. Our simulated values are consistent with field measurements of headwater bedrock erosion, and the pattern of sediment flux and fluvial erosion matches paraglacial theory and terrace aggradation records. Thus, we emphasize that the bedload produced from glacial erosion provides a missing link to reconcile late Cenozoic erosion records.
AGATNet: An Adaptive Graph Attention Network for Bias Correction of CMAQ‐Forecasted PM2.5 Concentrations Over South Korea
Authors: Dimri Rijul , Choi Yunsoo , Salman Ahmed Khan , Park Jincheol , Singh Deveshwar 
Published: August 2024

AbstractAccurate forecasting of surface PM2.5 concentrations is essential for enhancing air quality insights and enabling informed decision‐making in a timely manner. Traditional numerical models often exhibit biases originating from uncertainties in input parameters and oversimplified parameterization. This study introduces AGATNet, a graph‐based neural network aimed at correcting such biases by adaptively learning the spatial connections between air quality monitoring stations and associated temporal dependency of input features, leveraging masked self‐attentional layers and causal dilated 1D convolution. Trained with PM2.5‐contributing input features provided for the past 24 hr and future 72 hr during the years from 2016 to 2019, AGATNet effectively corrected CMAQ's 72‐hr advance forecasts of surface PM2.5 concentrations in South Korea for 2021. Across 183 monitoring stations, the application of AGATNet resulted in a substantial improvement in forecast accuracy, with index of agreement increased from 0.67 to 0.96 on +1 hr and root mean square error decreased by 51.56% on average throughout 2021, outperforming other machine learning models such as PM2.5‐GNN, multi‐layer perceptron, and long short‐term memory network. Notably, AGATNet demonstrated the most reliable hit rates for both the highly‐polluted episodes as well as relatively pristine conditions across South Korea, the distributions and occurrences of which were spatially and temporally more closely aligned to the observed values. AGATNet's success across diverse terrains and pollution scenarios in South Korea underscores its robust adaptability as well as the utility of graph neural networks in capturing spatial and temporal variabilities in input features more effectively.
Prevalence and correlates of irritability among U.S. adults
Authors: Perlis Roy H. , Uslu Ata , Schulman Jonathan , Himelfarb Aliayah , Gunning Faith M. , Solomonov Nili , Santillana Mauricio , Baum Matthew A. , Druckman James N. , Ognyanova Katherine , Lazer David 
Published: August 2024

AbstractThis study aimed to characterize the prevalence of irritability among U.S. adults, and the extent to which it co-occurs with major depressive and anxious symptoms. A non-probability internet survey of individuals 18 and older in 50 U.S. states and the District of Columbia was conducted between November 2, 2023, and January 8, 2024. Regression models with survey weighting were used to examine associations between the Brief Irritability Test (BITe5) and sociodemographic and clinical features. The survey cohort included 42,739 individuals, mean age 46.0 (SD 17.0) years; 25,001 (58.5%) identified as women, 17,281 (40.4%) as men, and 457 (1.1%) as nonbinary. A total of 1218(2.8%) identified as Asian American, 5971 (14.0%) as Black, 5348 (12.5%) as Hispanic, 1775 (4.2%) as another race, and 28,427 (66.5%) as white. Mean irritability score was 13.6 (SD 5.6) on a scale from 5 to 30. In linear regression models, irritability was greater among respondents who were female, younger, had lower levels of education, and lower household income. Greater irritability was associated with likelihood of thoughts of suicide in logistic regression models adjusted for sociodemographic features (OR 1.23, 95% CI 1.22–1.24). Among 1979 individuals without thoughts of suicide on the initial survey assessed for such thoughts on a subsequent survey, greater irritability was also associated with greater likelihood of thoughts of suicide being present (adjusted OR 1.17, 95% CI 1.12–1.23). The prevalence of irritability and its association with thoughts of suicide suggests the need to better understand its implications among adults outside of acute mood episodes.
Emotion perception through the nose: how olfactory emotional cues modulate the perception of neutral facial expressions in affective disorders
Authors: Dal Bò Elisa , Cecchetto Cinzia , Callara Alejandro Luis , Greco Alberto , Mura Francesca , Vanello Nicola , Di Francesco Fabio , Scilingo Enzo Pasquale , Gentili Claudio 
Published: August 2024

AbstractHumans can decode emotional states from the body odors of the conspecifics and this type of emotional communication is particularly relevant in conditions in which social interactions are impaired, as in depression and social anxiety. The present study aimed to explore how body odors collected in happiness and fearful conditions modulate the subjective ratings, the psychophysiological response and the neural processing of neutral faces in individuals with depressive symptoms, social anxiety symptoms, and healthy controls (N = 22 per group). To this aim, electrocardiogram (ECG) and HD-EEG were recorded continuously. Heart Rate Variability (HRV) was extracted from the ECG as a measure of vagal tone, event-related potentials (ERPs) and event-related spectral perturbations (ERPSs) were extracted from the EEG. The results revealed that the HRV increased during the fear and happiness body odors conditions compared to clean air, but no group differences emerged. For ERPs data, repeated measure ANOVA did not show any significant effects. However, the ERPSs analyses revealed a late increase in delta power and a reduced beta power both at an early and a late stage of stimulus processing in response to the neutral faces presented with the emotional body odors, regardless of the presence of depressive or social anxiety symptoms. The current research offers new insights, demonstrating that emotional chemosignals serve as potent environmental cues. This represents a substantial advancement in comprehending the impact of emotional chemosignals in both individuals with and without affective disorders.
IMPRESS: Improved methylation profiling using restriction enzymes and smMIP sequencing, combined with a new biomarker panel, creating a multi-cancer detection assay
Authors: Vandenhoeck Janah , Neefs Isabelle , Vanpoucke Thomas , Ibrahim Joe , Suls Arvid , Peeters Dieter , Schepers Anne , Hoischen Alexander , Fransen Erik , Peeters Marc , Van Camp Guy , Op de Beeck Ken 
Published: August 2024

Abstract
Background
Despite the worldwide progress in cancer diagnostics, more sensitive diagnostic biomarkers are needed. The methylome has been extensively investigated in the last decades, but a low-cost, bisulfite-free detection method for multiplex analysis is still lacking.

Methods
We developed a methylation detection technique called IMPRESS, which combines methylation-sensitive restriction enzymes and single-molecule Molecular Inversion Probes. We used this technique for the development of a multi-cancer detection assay for eight of the most lethal cancer types worldwide. We selected 1791 CpG sites that can distinguish tumor from normal tissue based on DNA methylation. These sites were analysed with IMPRESS in 35 blood, 111 tumor and 114 normal samples. Finally, a classifier model was built.

Results
We present the successful development of IMPRESS and validated it with ddPCR. The final classifier model discriminating tumor from normal samples was built with 358 CpG target sites and reached a sensitivity of 0.95 and a specificity of 0.91. Moreover, we provide data that highlight IMPRESS’s potential for liquid biopsies.

Conclusions
We successfully created an innovative DNA methylation detection technique. By combining this method with a new multi-cancer biomarker panel, we developed a sensitive and specific multi-cancer assay, with potential use in liquid biopsies.
Gelsolin alleviates rheumatoid arthritis by negatively regulating NLRP3 inflammasome activation
Authors: Lee Jiyeon , Sasaki Fumiyuki , Koike Eri , Cho Minjeong , Lee Yeongun , Dho So Hee , Lee Jina , Lee Eunji , Toyohara Eri , Sunakawa Mika , Ishibashi Mariko , Hung Huynh Hiep , Nishioka Saki , Komine Ritsuko , Okura Chiaki , Shimizu Masumi , Ikawa Masahito , Yoshimura Akihiko , Morita Rimpei , Kim Lark Kyun 
Published: August 2024

AbstractDespite numerous biomarkers being proposed for rheumatoid arthritis (RA), a gap remains in our understanding of their mechanisms of action. In this study, we discovered a novel role for gelsolin (GSN), an actin-binding protein whose levels are notably reduced in the plasma of RA patients. We elucidated that GSN is a key regulator of NLRP3 inflammasome activation in macrophages, providing a plausible explanation for the decreased secretion of GSN in RA patients. We found that GSN interacts with NLRP3 in LPS-primed macrophages, hence modulating the formation of the NLRP3 inflammasome complex. Reducing GSN expression significantly enhanced NLRP3 inflammasome activation. GSN impeded NLRP3 translocation to the mitochondria; it contributed to the maintenance of intracellular calcium equilibrium and mitochondrial stability. This maintenance is crucial for controlling the inflammatory response associated with RA. Furthermore, the exacerbation of arthritic symptoms in GSN-deficient mice indicates the potential of GSN as both a diagnostic biomarker and a therapeutic target. Moreover, not limited to RA models, GSN has demonstrated a protective function in diverse disease models associated with the NLRP3 inflammasome. Myeloid cell-specific GSN-knockout mice exhibited aggravated inflammatory responses in models of MSU-induced peritonitis, folic acid-induced acute tubular necrosis, and LPS-induced sepsis. These findings suggest novel therapeutic approaches that modulate GSN activity, offering promise for more effective management of RA and a broader spectrum of inflammatory conditions.
BaTwa populations from Zambia retain ancestry of past hunter-gatherer groups
Authors: Breton Gwenna , Barham Lawrence , Mudenda George , Soodyall Himla , Schlebusch Carina M. , Jakobsson Mattias 
Published: August 2024

AbstractSub-equatorial Africa is today inhabited predominantly by Bantu-speaking groups of Western African descent who brought agriculture to the Luangwa valley in eastern Zambia ~2000 years ago. Before their arrival the area was inhabited by hunter-gatherers, who in many cases were subsequently replaced, displaced or assimilated. In Zambia, we know little about the genetic affinities of these hunter-gatherers. We examine ancestry of two isolated communities in Zambia, known as BaTwa and possible descendants of recent hunter-gatherers. We genotype over two million genome-wide SNPs from two BaTwa populations (total of 80 individuals) and from three comparative farming populations to: (i) determine if the BaTwa carry genetic links to past hunter-gatherer-groups, and (ii) characterise the genetic affinities of past Zambian hunter-gatherer-groups. The BaTwa populations do harbour a hunter-gatherer-like genetic ancestry and Western African ancestry. The hunter-gatherer component is a unique local signature, intermediate between current-day Khoe-San ancestry from southern Africa and central African rainforest hunter-gatherer ancestry.