1,721,085 research outputs found
Where Visual Speech Meets Language: VSP-LLM Framework for Efficient and Context-Aware Visual Speech Processing
No full textHarnessing Large Language Models to Collect and Analyze Metal-Organic Framework Property Data Set
No full textThis research focused on the efficient collection of experimental metal-organic framework (MOF) data from scientific literature to address the challenges of accessing hard-to-find data and improving the quality of information available for machine learning studies in materials science. Utilizing a chain of advanced large language models (LLMs), we developed a systematic approach to extract and organize MOF data into a structured format. Our methodology successfully compiled information from more than 40,000 research articles, creating a comprehensive and ready-to-use data set. Specifically, data regarding MOF synthesis conditions and properties were extracted from both tables and text and then analyzed. Subsequently, we utilized the curated database to analyze the relationships between synthesis conditions, properties, and structure. Through machine learning, we identified the existence of a gap between simulation data and experimental data, and further analysis revealed the factors contributing to this discrepancy. Additionally, we leveraged the extracted synthesis condition data to develop a synthesis condition recommender system. This system suggests optimal synthesis conditions based on the provided precursors, offering a practical tool to refine synthesis strategies. This underscores the importance of experimental datasets in advancing MOF research.
Physicochemical Profiling of Macrophage Heterogeneity Using Deep Learning Integrated Nanosensor Cytometry
No full textLabel-free single-cell analytics have been developed for understanding the collective immune response mechanism of immune cells. However, it remains difficult to analyze the physicochemical properties of a single cell in high spatiotemporal resolution for an immune cell having dynamic morphological changes and significant molecular heterogeneities. It is deemed due to the absence of a sensitive molecular sensing construct and single-cell imaging analytic program. In this study, we developed a deep learning integrated nanosensor chemical cytometry (DI-NCC) platform, which combines a fluorescent nano sensor array in microfluidics and a deep learning model for cell feature analysis. The DI-NCC platform possesses the capability to collect rich, multivariate data sets for each individual immune cell (e.g., macrophage) within the population. We obtained LPS+ (n = 25) and LPS- (n = 61) near-infrared images and analyzed 250 cells/ mm2 in 1 mu m spatial resolution and 0 to 1.0 confidence level even with overlapped or adhered cell configurations. This enables automatic quantification of the activation and nonactivation levels of a single macrophage upon instantaneous immune stimulations. Furthermore, we support the activation level quantified by deep learning with heterogeneities analysis of both biophysical (cell size) and biochemical (nitric oxide efflux) properties. The DI-NCC platform can be promising for activation profiling of dynamic heterogeneity variations of cell populations.
Super Proton Conductivity Through Control of Hydrogen‐Bonding Networks in Flexible Metal–Organic Frameworks
No full textMetal-organic frameworks (MOFs) have received much attention as a solid-state electrolyte in proton exchange membrane fuel cells. The introduction of proton carriers and functional groups into MOFs can improve the proton conductivity attributed to the formation of hydrogen-bonding networks, while the underlying synergistic mechanism is still unclear. Here, a series of flexible MOFs (MIL-88B, [Fe3O(OH)(H2O)(2)(O2C-C6H4-CO2)(3)] with imidazole) is designed to modify the hydrogen-bonding networks and investigate the resulting proton-conducting characteristics by controlling the breathing behaviors. The breathing behavior is tuned by varying the amount of adsorbed imidazole into pore (small breathing (SB) and large breathing (LB)) and introducing functional groups onto ligands (-NH2, -SO3H), resulting in four kinds of imidazole-loaded MOFs-Im@MIL-88B-SB, Im@MIL-88B-LB, Im@MIL-88B-NH2, and Im@MIL-88B-SO3H. Im@MIL-88B-LB without functional groups exhibits the highest proton conductivity of 8.93 x 10(-2) S cm(-1) at 60 degrees C and 95% relative humidity among imidazole-loaded proton conductors despite the mild condition, indicating that functional groups may not be always required to enhance proton conductivity. The elaborately controlled pore size and host-guest interaction in flexible MOFs through imidazole-dependent structural transformation are translated into the high proton concentration without the limitation of proton mobility, contributing to the formation of effective hydrogen-bonding networks in imidazole conducting media.
Detrital zircons from Late Paleozoic Ice Age sequences in Victoria Land (Antarctica): New constraints on the glaciation of southern Gondwana
No full textThe Lower Permian tillites of the Beacon Supergroup, cropping out in Victoria Land (Antarctica), record climatic history during one of the Earth’s coldest periods: the Late Paleozoic Ice Age. Reconstruction of ice-extent and paleo-flow directions, as well as geochronological and petrographic data, are poorly constrained in this sector of Gondwana. Here, we provide the first detrital zircon U-Pb age analyses of both the Metschel Tillite in southern Victoria Land and some tillites correlatable with the Lanterman Formation in northern Victoria Land to identify the source regions of these glaciogenic deposits. Six-hundred detrital zircon grains from four diamictite samples were analyzed using laser ablation−inductively coupled plasma−mass spectrometry. Geochronological and petrographic compositional data of the Metschel Tillite indicate a widespread reworking of older Devonian Beacon Supergroup sedimentary strata, with minor contribution from Cambro-Ordovician granitoids and meta-sedimentary units as well as Neoproterozoic metamorphic rocks. Euhedral to subhedral Carboniferous−Devonian zircon grains match coeval magmatic units of northern Victoria Land and Marie Byrd Land. This implies, in accordance with published paleo-ice directions, a provenance from the east-southeast sectors. In contrast, the two samples from northern Victoria Land tillite reflect the local basement provenance; their geochronological age and petrographic composition indicates a restricted catchment area with multiple ice centers. This shows that numerous ice centers were present in southern Gondwana during the Late Paleozoic Ice Age. While northern Victoria Land hosted discrete glaciers closely linked with the northern Victoria Land-Tasmania ice cap, the west-northwestward flowing southern Victoria Land ice cap contributed most of the sediments comprising the Metschel Tillite
Going Beyond Counting First Authors in Author Co-citation Analysis
Full text linkThe present study examines one of the fundamental aspects of author co-citation analysis (ACA) - the way co-citation
counts are defined. Co-citation counting provides the data on which all subsequent statistical analyses and mappings
are based, and we compare ACA results based on two different types of co-citation counting - the traditional type that
only counts the first one among a cited work's authors on the one hand and a non-traditional type that takes into
account the first 5 authors of a cited work on the other hand. Results indicate that the picture produced through this non-traditional author co-citation counting contains more coherent author groups and is therefore considerably clearer. However, this picture represents fewer specialties in the research field being studied than that produced through the traditional first-author co-citation counting when the same number of top-ranked authors is selected and analyzed. Reasons for these effects are discussed
Preliminary Evaluation of Path-aware Crossover Operators for Search-Based Test Data Generation for Autonomous Driving
No full textAs autonomous driving gains attraction, testing of autonomous vehicles has become an important issue. However, testing in the real world is not only dangerous but also expensive. Consequently, a virtual test method has emerged as an alternative. Recently, a novel testing technique based on Procedural Content Generation (PCG) and Genetic Algorithm (GA), As-Fault, has been proposed to test the lane-keeping functionality of autonomous vehicles. This paper proposes new crossover operators for AsFault that can better preserve the coupling between genotype (representations of road segments) and phenotype (occurrences of interesting self-driving behaviour). We explain our design intentions and present a preliminary evaluation of the proposed operators using the Simulink autonomous driving simulator. We report promising early results: The proposed operators can lead not only to Out of Bound Episodes (OBEs) but also causes more vision errors in the simulation when compared to the original. © 2021 IEEE
Variations on the Author
Full text link“Variations on the Author” discusses two of Eduardo Coutinho’s recent films (Um Dia na Vida, from 2010, and Últimas Conversas, posthumously released in 2015) and their contribution to the general question of documentary authorship. The director’s filmography is characterized by a consistent yet self-effacing form of authorial self-inscription: Coutinho often features as an interviewer that rather than express opinions propels discourses; an interviewer that is good at listening. This mode of self-inscription characterizes him as an author who is not expressive but who is nonetheless markedly present on the screen. In Um Dia na Vida, however, Coutinho is completely absent form the image, while Últimas Conversas, on the contrary, includes a confessional prologue that moves the director from the margins to the center of his films. This article examines the ways in which these works stand out in the filmography of a director who offers new insights into the notion of cinematic authorship
Effect of groundwater ions (Ca2+, Na+, and HCO3-) on removal of hexavalent chromium by Fe(II)-phosphate mineral
No full textA systematic study was conducted to investigate the effect of major groundwater ions (i.e., Ca2+, Na+, and HCO3-) on removal of hexavalent chromium (Cr(VI)) by an Fe(II)-phosphate mineral (i.e., vivianite). The batch experiments revealed that the second-order rate constant for Cr(VI) removal by vivianite with Ca2+ + CO32-(0.076-1.90 mM) and Na++ HCO3- (0.26-6.50 mM) was 1.5-5.2 times lower than that without these ions. The removal kinetics of Cr(VI) by vivianite was abruptly slowed down with the increased ion concentration, which showed their inhibitory effect on the reaction. The results of the geochemical modeling and density functional theory calculations showed that the presence of Ca2+ + HCO3 (-) and Na+ + HCO3- can form less favorable Cr (VI) species (i.e., CaCrO4(aq) and NaCrO4-) on the Fe-B site of vivianite surface, leading to the inhibitory effect observed in this study. Finally, the X-ray absorption spectroscopy results showed that reductive immobilization of Cr(VI) to Cr(III) occurred by structural Fe(II) oxidation of vivianite to amorphous mixed-valence Fe-phosphate via an inner-sphere complexation. The results suggest that the presence of Ca2+, Na+, and HCO3- in phosphorous-enriched iron-reducing environments may lower the remedial efficiency of Cr(VI) removal.
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