bluuebunny/crossref_metadata_2025_split huggingface dataset:
Differential cortical layer engagement during seizure initiation and spread in humans
Authors: Bourdillon Pierre , Ren Liankun , Halgren Mila , Paulk Angelique C. , Salami Pariya , Ulbert István , Fabó Dániel , King Jean-Rémi , Sjoberg Kane M. , Eskandar Emad N. , Madsen Joseph R. , Halgren Eric , Cash Sydney S. 
Published: June 2024

AbstractDespite decades of research, we still do not understand how spontaneous human seizures start and spread – especially at the level of neuronal microcircuits. In this study, we used laminar arrays of micro-electrodes to simultaneously record the local field potentials and multi-unit neural activities across the six layers of the neocortex during focal seizures in humans. We found that, within the ictal onset zone, the discharges generated during a seizure consisted of current sinks and sources only within the infra-granular and granular layers. Outside of the seizure onset zone, ictal discharges reflected current flow in the supra-granular layers. Interestingly, these patterns of current flow evolved during the course of the seizure – especially outside the seizure onset zone where superficial sinks and sources extended into the deeper layers. Based on these observations, a framework describing cortical-cortical dynamics of seizures is proposed with implications for seizure localization, surgical targeting, and neuromodulation techniques to block the generation and propagation of seizures.
Conceptualizing soil fauna effects on labile and stabilized soil organic matter
Authors: Angst Gerrit , Potapov Anton , Joly François-Xavier , Angst Šárka , Frouz Jan , Ganault Pierre , Eisenhauer Nico 
Published: June 2024

AbstractFauna is highly abundant and diverse in soils worldwide, but surprisingly little is known about how it affects soil organic matter stabilization. Here, we review how the ecological strategies of a multitude of soil faunal taxa can affect the formation and persistence of labile (particulate organic matter, POM) and stabilized soil organic matter (mineral-associated organic matter, MAOM). We propose three major mechanisms - transformation, translocation, and grazing on microorganisms - by which soil fauna alters factors deemed essential in the formation of POM and MAOM, including the quantity and decomposability of organic matter, soil mineralogy, and the abundance, location, and composition of the microbial community. Determining the relevance of these mechanisms to POM and MAOM formation in cross-disciplinary studies that cover individual taxa and more complex faunal communities, and employ physical fractionation, isotopic, and microbiological approaches is essential to advance concepts, models, and policies focused on soil organic matter and effectively manage soils as carbon sinks, nutrient stores, and providers of food.
Highly accurate carbohydrate-binding site prediction with DeepGlycanSite
Authors: He Xinheng , Zhao Lifen , Tian Yinping , Li Rui , Chu Qinyu , Gu Zhiyong , Zheng Mingyue , Wang Yusong , Li Shaoning , Jiang Hualiang , Jiang Yi , Wen Liuqing , Wang Dingyan , Cheng Xi 
Published: June 2024

AbstractAs the most abundant organic substances in nature, carbohydrates are essential for life. Understanding how carbohydrates regulate proteins in the physiological and pathological processes presents opportunities to address crucial biological problems and develop new therapeutics. However, the diversity and complexity of carbohydrates pose a challenge in experimentally identifying the sites where carbohydrates bind to and act on proteins. Here, we introduce a deep learning model, DeepGlycanSite, capable of accurately predicting carbohydrate-binding sites on a given protein structure. Incorporating geometric and evolutionary features of proteins into a deep equivariant graph neural network with the transformer architecture, DeepGlycanSite remarkably outperforms previous state-of-the-art methods and effectively predicts binding sites for diverse carbohydrates. Integrating with a mutagenesis study, DeepGlycanSite reveals the guanosine-5’-diphosphate-sugar-recognition site of an important G-protein coupled receptor. These findings demonstrate DeepGlycanSite is invaluable for carbohydrate-binding site prediction and could provide insights into molecular mechanisms underlying carbohydrate-regulation of therapeutically important proteins.
Embodied CO2 emissions of equity portfolios for Chinese asset managers
Authors: Wang Jinglei , Zhang Zengkai , Chen Danbo , Guan Dabo 
Published: June 2024

AbstractThe 2015 Paris Agreement has set out the climate change target of limiting global warming to 1.5 °C, which poses a serious challenge to countries to reduce emissions. As the world’s largest carbon emitter, promoting the realization of the “dual-carbon” goal is the key to realizing China’s green transformation and high-quality development. Chinese asset managers play active roles in the capital market as an important channel of asset allocation. Currently, the vast majority of Chinese asset managers hold high percentages of high-carbon industries in their portfolios, and lack quantitative data of their carbon footprints embodied in equity investments, which faces huge carbon-related risks. Therefore, it’s an urgent need to comprehensively and scientifically measure financed emissions of Chinese asset managers, which is of great significance for asset managers’ carbon risk management and sustainable investment. This paper develops a detailed inventory of carbon emissions for equity portfolios managed by Chinese asset managers from 2010 to 2020, which stands as a pivotal reference for in-depth analysis of emission characteristics.
An experienced racial-ethnic diversity dataset in the United States using human mobility data
Authors: Xu Wenfei , Wang Zhuojun , Attia Nada , Attia Youssef , Zhang Yucheng , Zong Haotian 
Published: June 2024

AbstractDespite the importance of measuring racial-ethnic segregation and diversity in the United States, current measurements are largely based on the Census and, thus, only reflect segregation and diversity as understood through residential location. This leaves out the social contexts experienced throughout the course of the day during work, leisure, errands, and other activities. The National Experienced Racial-ethnic Diversity (NERD) dataset provides estimates of diversity for the entire United States at the census tract level based on the range of place and times when people have the opportunity to come into contact with one another. Using anonymized and opted-in mobile phone location data to determine co-locations of people and their demographic backgrounds, these measurements of diversity in potential social interactions are estimated at 38.2 m × 19.1 m scale and 15-minute timeframe for a representative year and aggregated to the Census tract level for purposes of data privacy. As well, we detail some of the characteristics and limitations of the data for potential use in national, comparative studies.
Association of intensity and dominance of CEOs’ smiles with corporate performance
Authors: Fujiwara Ken , Plusquellec Pierrich 
Published: June 2024

AbstractThis study investigated whether the facial expressions of chief executive officers (CEOs) are associated with corporate performance. A photograph of the CEO or president of each company that appeared on the Fortune Global 500 list for 2018 was taken from the company’s official website. The smile intensity and action unit activation in each face were calculated using a pre-trained machine learning algorithm, FACET. The results revealed a positive association between smile intensity and company profit, even when controlling for the company’s geographic location (Western culture versus others) and the CEO’s gender. Furthermore, when the type of smile was examined with the activation of each action unit, this significant positive association was identified in the dominant smile but not in the reward and affiliative smiles. Relationships among the leader’s smile intensity, group strategy, and group performance are discussed.
Mechanical evaluation of soil and artisanal bricks for quality masonry product management, Limpopo South Africa
Authors: Akintola George Oluwole , Amponsah-Dacosta Francis , Mhlongo Sphiwe Emmanuel , Matsiketa Khensani Eullen 
Published: June 2024

AbstractThe selection of raw materials to produce quality artisanal bricks is imperative for sustainable building in rural regions. Artisanal brick-making process often employs traditional kiln to fire brick because it is an affordable, and applicable technology in the rural region. However, there are noticeable cracks, increasing among buildings constructed with artisanal bricks from the rural region in South Africa. In response, this study aims to evaluate the soil and artisanal brick specimens to understand the suitability of the raw materials and quality of products in the study area. A total of twenty soil samples and twenty-seven artisanal burnt bricks were collected from three different artisanal brick-making sites designated as Site A, B, and C. In all samples, the geotechnical tests revealed a sandy loam soil type with a predominance of chlorite clay minerals and non-clay minerals. Furthermore, the sand-size particles depict a relatively higher proportion compared to clay-size particles. Besides, Atterberg’s limit test plotted above the A-line of the plasticity chart indicates an inorganic clay of low plasticity with a low to medium compressibility property. Based on the empirical workability and mechanical tests, most of the studied soils are suitable for optimum and acceptable extrusion bricks and suitable for an on-site single-story construction based on SANS 227:2007 standards.
Joint stereo 3D object detection and implicit surface reconstruction
Authors: Li Shichao , Huang Xijie , Liu Zechun , Cheng Kwang-Ting 
Published: June 2024

AbstractWe present a new learning-based framework S-3D-RCNN that can recover accurate object orientation in SO(3) and simultaneously predict implicit rigid shapes from stereo RGB images. For orientation estimation, in contrast to previous studies that map local appearance to observation angles, we propose a progressive approach by extracting meaningful Intermediate Geometrical Representations (IGRs). This approach features a deep model that transforms perceived intensities from one or two views to object part coordinates to achieve direct egocentric object orientation estimation in the camera coordinate system. To further achieve finer description inside 3D bounding boxes, we investigate the implicit shape estimation problem from stereo images. We model visible object surfaces by designing a point-based representation, augmenting IGRs to explicitly address the unseen surface hallucination problem. Extensive experiments validate the effectiveness of the proposed IGRs, and S-3D-RCNN achieves superior 3D scene understanding performance. We also designed new metrics on the KITTI benchmark for our evaluation of implicit shape estimation.
Enhancing soil amendment for salt stress using pretreated rice straw and cellulolytic fungi
Authors: Ma Yen Nhi , Mongkolthanaruk Wiyada , Riddech Nuntavun 
Published: June 2024

AbstractRice straw breakdown is sluggish, which makes agricultural waste management difficult, however pretreatment procedures and cellulolytic fungi can address this issue. Through ITS sequencing, Chaetomium globosum C1, Aspergillus sp. F2, and Ascomycota sp. SM2 were identified from diverse sources. Ascomycota sp. SM2 exhibited the highest carboxymethyl cellulase (CMCase) activity (0.86 IU/mL) and filter-paper cellulase (FPase) activity (1.054 FPU/mL), while Aspergillus sp. F2 showed the highest CMCase activity (0.185 IU/mL) after various pretreatments of rice straw. These fungi thrived across a wide pH range, with Ascomycota sp. SM2 from pH 4 to 9, Aspergillus sp. F2, and Chaetomium globosum C1 thriving in alkaline conditions (pH 9). FTIR spectroscopy revealed significant structural changes in rice straw after enzymatic hydrolysis and solid-state fermentation, indicating lignin, cellulose, and hemicellulose degradation. Soil amendments with pretreated rice straw, cow manure, biochar, and these fungi increased root growth and soil nutrient availability, even under severe salt stress (up to 9.3 dS/m). The study emphasizes the need for a better understanding of Ascomycota sp. degradation capabilities and proposes that using cellulolytic fungus and pretreatment rice straw into soil amendments could mitigate salt-related difficulties and improve nutrient availability in salty soils.
The associations of leukocyte telomere length and intermediary cardiovascular phenotype with adverse cardiovascular outcomes in the white population
Authors: Chung Ho-Gi , Yang Pil-Sung , Cho Seunghoon , Jang Eunsun , Kim Daehoon , Yu Hee Tae , Kim Tae-Hoon , Uhm Jae-Sun , Sung Jung-Hoon , Pak Hui-Nam , Lee Moon-Hyoung , Joung Boyoung 
Published: June 2024

AbstractThe evidence about the associations of leukocyte telomere length (LTL) and intermediary cardiovascular phenotypes with adverse cardiovascular outcomes is inconclusive. This study assessed these relationships with cardiovascular imaging, electrocardiography, and the risks of sudden cardiac death (SCD), coronary events, and heart failure (HF) admission. We conducted a cross-sectional analysis of UK Biobank participants enrolled between 2006 and 2010. LTL was measured using quantitative polymerase chain reactions. Electronic health records were used to determine the incidence of SCD, coronary events, and HF admission. Cardiovascular measurements were made using cardiovascular magnetic resonance imaging and machine learning. The associations of LTL with SCD, coronary events, and HF admission and cardiac magnetic resonance imaging, electrocardiogram parameters of 33,043 and 19,554 participants were evaluated by multivariate regression. The median (interquartile range) follow-up period was 11.9 (11.2–12.6) years. Data was analyzed from January to May 2023. Among the 403,382 white participants without coronary artery disease or HF, 181,637 (45.0%) were male with a mean age of 57.1 years old. LTL was independently negatively associated with a risk of SCD (LTL third quartile vs first quartile: hazard ratio [HR]: 0.81, 95% confidence interval [CI]: 0.72–0.92), coronary events (LTL third quartile vs first quartile: HR: 0.88, 95% CI: 0.84–0.92), and HF admission (LTL fourth quartile vs first quartile: HR: 0.84, 95% CI: 0.74–0.95). LTL was also independently positively associated with cardiac remodeling, specifically left ventricular mass index, left-ventricular-end systolic and diastolic volumes, mean left ventricular myocardial wall thickness, left ventricular stroke volume, and with electrocardiogram changes along the negative degree of T-axis. Cross-sectional study results showed that LTL was positively associated with heart size and cardiac function in middle age, but electrocardiography results did not show these associations, which could explain the negative association between LTL and risk of SCD, coronary events, and HF admission in UK Biobank participants.
CO2 rock physics modeling for reliable monitoring of geologic carbon storage
Authors: Creasy Neala , Huang Lianjie , Gasperikova Erika , Harbert William , Bratton Tom , Zhou Quanlin 
Published: June 2024

AbstractMonitoring, verification, and accounting (MVA) are crucial to ensure safe and long-term geologic carbon storage. Seismic monitoring is a key MVA technique that utilizes seismic data to infer elastic properties of CO2-saturated rocks. Reliable accounting of CO2 in subsurface storage reservoirs and potential leakage zones requires an accurate rock physics model. However, the widely used CO2 rock physics model based on the conventional Biot-Gassmann equation can substantially underestimate the influence of CO2 saturation on seismic waves, leading to inaccurate accounting. We develop an accurate CO2 rock physics model by accounting for both effects of the stress dependence of seismic velocities in porous rocks and CO2 weakening on the rock framework. We validate our CO2 rock physics model using the Kimberlina-1.2 model (a previously proposed geologic carbon storage site in California) and create time-lapse elastic property models with our new rock physics method. We compare the results with those obtained using the conventional Biot-Gassmann equation. Our innovative approach produces larger changes in elastic properties than the Biot-Gassmann results. Using our CO2 rock physics model can replicate shear-wave speed reductions observed in the laboratory. Our rock physics model enhances the accuracy of time-lapse elastic-wave modeling and enables reliable CO2 accounting using seismic monitoring.
Retrospective performance analysis of a ground shaking early warning system for the 2023 Turkey–Syria earthquake
Authors: Rea Raffaele , Colombelli Simona , Elia Luca , Zollo Aldo 
Published: June 2024

AbstractRecently developed earthquake early warning systems rely on the idea of combining the measured ground motion and the source parameter estimate to issue an alert based on the ground shaking prediction at sites where high potential damage is expected. Here we apply a P-wave, shaking-forecast method that can track and alert in real-time the area where peak ground motion is expected to exceed a user-set threshold during the earthquake. The system performance in providing a fast and reliable warning during the Mw 7.8, February 6 Turkey–Syria earthquake is investigated by the real-time simulated playback of the near-source hundred accelerograms. With an instrumental intensity threshold$${I}_{{MM}}={IV}$$IMM=IVan alert issued 10–20 s after the event origin, results in 95% of successful warning (positive and negative) and lead-times of 10–60 s within the potential damage zone. Setting a higher intensity threshold requires larger alert times (50–60 s) to achieve 90% of successful warning and overall shorter lead-times. Our simulation shows that the P-wave predicted, strong-shaking zone can be rapidly detected only 20 s after the mainshock nucleation. As the time increases, it well delineates the NE-SW bi-lateral rupture development as inferred by kinematic source models.
Findings of PTSD-specific deficits in default mode network strength following a mild experimental stressor
Authors: Averill Christopher L. , Averill Lynnette A. , Akiki Teddy J. , Fouda Samar , Krystal John H. , Abdallah Chadi G. 
Published: June 2024

AbstractReductions in default mode (DMN) connectivity strength have been reported in posttraumatic stress disorder (PTSD). However, the specificity of DMN connectivity deficits in PTSD compared to major depressive disorder (MDD), and the sensitivity of these alterations to acute stressors are not yet known. 52 participants with a primary diagnosis of PTSD (n = 28) or MDD (n = 24) completed resting-state functional magnetic resonance imaging immediately before and after a mild affective stressor. A 2 × 2 design was conducted to determine the effects of group, stress, and group*stress on DMN connectivity strength. Exploratory analyses were completed to identify the brain region(s) underlying the DMN alterations. There was significant group*stress interaction (p = 0.03), reflecting stress-induced reduction in DMN strength in PTSD (p = 0.02), but not MDD (p = 0.50). Nodal exploration of connectivity strength in the DMN identified regions of the ventromedial prefrontal cortex and the precuneus potentially contributing to DMN connectivity deficits. The findings indicate the possibility of distinct, disease-specific, patterns of connectivity strength reduction in the DMN in PTSD, especially following an experimental stressor. The identified dynamic shift in functional connectivity, which was perhaps induced by the stressor task, underscores the potential utility of the DMN connectivity and raises the question whether these disruptions may be inversely affected by antidepressants known to treat both MDD and PTSD psychopathology.
Probing scaffold size effects on multivalent lectin–glycan binding affinity, thermodynamics and antiviral properties using polyvalent glycan-gold nanoparticles
Authors: Basaran Rahman , Budhadev Darshita , Kempf Amy , Nehlmeier Inga , Hondow Nicole , Pöhlmann Stefan , Guo Yuan , Zhou Dejian 
Published: June 2024

Increasing GNP-glycan's scaffold size impacts very differently for their ability to block DC-SIGN- from DC-SIGNR- promoted viral infection: enhancing only the potency in the former, but enhancing both the potency and cooperativity in the latter.
Kinematics and star formation of hub-filament systems in W49A
Authors: Zhang WenJun , Zhou Jianjun , Esimbek Jarken , Baan Willem , He Yuxin , Tang Xindi , Li Dalei , Ji Weiguang , Wu Gang , Ma Yingxiu , Li Jiasheng , Zhou Dongdong , Tursun Kadirya , Komesh Toktarkhan 
Published: June 2024

Aims. W49A is a prominent giant molecular cloud (GMC) that exhibits strong star formation activities, yet its structural and kinematic properties remain uncertain. Our study aims to investigate the large-scale structure and kinematics of W49A, and elucidate the role of filaments and hub-filament systems (HFSs) in its star formation activity.
Methods. We utilized continuum data from Herschel and the James Clerk Maxwell Telescope (JCMT) as well as the molecular lines 12CO (3–2), 13CO (3–2), and C18O (3–2) to identify filaments and HFSs within W49A. Further analysis focused on the physical properties, kinematics, and mass transport within these structures. Additionally, recombination line emission from the H I/OH/Recombination (THOR) line survey was employed to trace the central H II region and ionized gas.
Results. Our findings reveal that W49A comprises one blue-shifted (B-S) HFS and one red-shifted (R-S) HFS, each with multiple filaments and dense hubs. Notably, significant velocity gradients were detected along these filaments, indicative of material transport toward the hubs. High mass accretion rates along the filaments facilitate the formation of massive stars in the HFSs. Furthermore, the presence of V-shaped structures around clumps in position-velocity diagrams suggests ongoing gravitational collapse and local star formation within the filaments.
Conclusions. Our results indicate that W49A consists of one R-S HFS and one B-S HFS, and that the material transport from filaments to the hub promotes the formation of massive stars in the hub. These findings underscore the significance of HFSs in shaping the star formation history of W49A.
Surface parameterisation and spectral synthesis of rapidly rotating stars
Authors: Montesinos Benjamín 
Published: June 2024

Context. Spectral synthesis is a powerful tool with which to find the fundamental parameters of stars. Models are usually restricted to single values of temperature and gravity, and assume spherical symmetry. This approximation breaks down for rapidly rotating stars.
Aims. This paper presents a joint formalism to allow a computation of the stellar structure – namely, the photospheric radius, R, the effective temperature, Teff, and gravity, geff – as a function of the colatitude, θ, for rapid rotators with radiative envelopes, and a subsequent method to build the corresponding synthetic spectrum.
Methods. The structure of the star is computed using a semi-analytical approach, which is easy to implement from a computational point of view and which reproduces very accurately the results of much more complex codes. Once R(θ), Teff(θ), and geff(θ) are computed, the suite of codes, ATLAS and SYNTHE, by R. Kurucz are used to synthesise spectra for a mesh of cells in which the star is divided. The appropriate limb-darkening coefficients are also computed, and the final output spectrum is built for a given inclination of the rotation axis with respect to the line of sight. All the geometrical transformations required are described in detail.
Results. The combined formalism has been applied to Vega, a rapidly rotating star almost seen pole-on, as a testbed. The structure reproduces the results from interferometric studies and the synthetic spectrum matches the peculiar shape of the spectral lines well.
Conclusions. Contexts where this formalism can be applied are outlined in the final sections.