FluidHarmony is an algorithmic method for defining a hierarchical harmonic lexicon in equal temperaments. It utilizes an enharmonic weighted Fourier transform space to represent pitch class set (pcsets) relations. The method ranks pcsets based on user-defined constraints: the importance of interval classes (ICs) and a reference pcset. Evaluation of 5,184 Western musical pieces from the 16th to 20th centuries shows FluidHarmony captures 8% of the corpus's harmony in its top pcsets. This highlights the role of ICs and a reference pcset in regulating harmony in Western tonal music while enabling systematic approaches to define hierarchies and establish metrics beyond 12-TET.

This digital GIS dataset and accompanying nonspatial files synthesize the model outputs from a regional-scale volumetric 3-D geologic model that portrays the generalized subsurface geology of western South Dakota from a wide variety of input data sources.The study area includes all of western South Dakota from west of the Missouri River to the Black Hills uplift and Wyoming border. The model data released here consist of the stratigraphic contact elevation of major Phanerozoic sedimentary units that broadly define the geometry of the subsurface, the elevation of Tertiary intrusive and Precambrian basement rocks, and point data representing the three-dimensional geometry of fault surfaces. the presence of folds and unconformities are implied by the 3D geometry of the stratigraphic units, but these are not included as discrete features in this data release. The 3D geologic model was constructed from a wide variety of publicly available surface and subsurface geologic data; none of these input data are part of this Data Release, but data sources are thoroughly documented such that a user could obtain these data from other sources if desired. This model was created as part of the U.S. Geological Survey’s (USGS) National Geologic Synthesis (NGS) project—a part of the National Cooperative Geologic Mapping Program (NCGMP). The WSouthDakota3D geodatabase contains twenty-five (25) subsurface horizons in raster format that represent the tops of modeled subsurface units, and a feature dataset “GeologicModel”. The GeologicModel feature dataset contains a feature class of thirty-five (35) faults served in elevation grid format (FaultPoints). The feature class “ModelBoundary” describes the footprint of the geologic model, and was included to meet the NCGMP’s GeMS data schema. Nonspatial tables define the data sources used (DataSources), define terms used in the dataset (Glossary), and provide a description of the modeled surfaces (DescriptionOfModelUnits). Separate file folders contain the vector data in shapefile format, the raster data in ASCII format, and the nonspatial tables as comma-separated values. In addition, a tabular data dictionary describes the entity and attribute information for all attributes of the geospatial data and the accompanying nonspatial tables (EntityAndAttributes). An included READ_ME file documents the process of manipulating and interpreting publicly available surface and subsurface geologic data to create the model. It additionally contains critical information about model units, and uncertainty regarding their ability to predict true ground conditions. Accompanying this data release is the “WSouthDakotaInputSummaryTable.csv”, which tabulates the global settings for each fault block, the stratigraphic horizons modeled in each fault block, the types and quantity of data inputs for each stratigraphic horizon, and then the settings associated with each data input.

This digital GIS dataset and accompanying nonspatial files synthesize model outputs from a regional-scale volumetric 3-D geologic model that portrays the generalized subsurface geology of the Powder River Basin and Williston Basin regions from a wide variety of input data sources. The study area includes the Hartville Uplift, Laramie Range, Bighorn Mountains, Powder River Basin, and Williston Basin. The model data released here consist of the stratigraphic contact elevation of major Phanerozoic sedimentary units that broadly define the geometry of the subsurface, the elevation of Tertiary intrusive and Precambrian basement rocks, and point data that illustrate an estimation of the three-dimensional geometry of fault surfaces. The presence of folds and unconformities are implied by the 3D geometry of the stratigraphic units, but these are not included as discrete features in this data release. The 3D geologic model was constructed from a wide variety of publicly available surface and subsurface geologic data; none of these input data are part of this Data Release, but data sources are thoroughly documented such that a user could obtain these data from other sources if desired. The PowderRiverWilliston3D geodatabase contains 40 subsurface horizons in raster format that represent the tops of modeled subsurface units, and a feature dataset “GeologicModel”. The GeologicModel feature dataset contains a feature class of 30 estimated faults served in elevation grid format (FaultPoints), a feature class illustrating the spatial extent of 22 fault blocks (FaultBlockFootprints), and a feature class containing a polygon delineating the study areas (ModelBoundary). Nonspatial tables define the data sources used (DataSources), define terms used in the dataset (Glossary), and provide a description of the modeled surfaces (DescriptionOfModelUnits). Separate file folders contain the vector data in shapefile format, the raster data in ASCII format, and the tables as comma-separated values. In addition, a tabular data dictionary describes the entity and attribute information for all attributes of the geospatial data and the accompanying nonspatial tables (EntityAndAttributes). An included READ_ME file documents the process of manipulating and interpreting publicly available surface and subsurface geologic data to create the model. It additionally contains critical information about model units, and uncertainty regarding their ability to predict true ground conditions. Accompanying this data release is the “PowderRiverWillistonInputSummaryTable.csv”, which tabulates the global settings for each fault block, the stratigraphic horizons modeled in each fault block, the types and quantity of data inputs for each stratigraphic horizon, and then the settings associated with each data input.

Antibodies serve as biomarkers of infection, but if sustained can confer long-term immunity. Yet, for most clinically approved vaccines, binding antibody titers only serve as a surrogate of protection. Instead, the ability of vaccine induced antibodies to neutralize or mediate Fc-effector functions is mechanistically linked to protection. While evidence has begun to point to persisting antibody responses among SARS-CoV-2 infected individuals, cases of re-infection have begun to emerge, calling the protective nature of humoral immunity against this highly infectious pathogen into question. Using a community-based surveillance study, we aimed to define the relationship between titers and functional antibody activity to SARS-CoV-2 over time. Here we report significant heterogeneity, but limited decay, across antibody titers amongst 120 identified seroconverters, most of whom had asymptomatic infection. Notably, neutralization, Fc-function, and SARS-CoV-2 specific T cell responses were only observed in subjects that elicited RBD-specific antibody titers above a threshold. The findings point to a switch-like relationship between observed antibody titer and function, where a distinct threshold of activity—defined by the level of antibodies—is required to elicit vigorous humoral and cellular response. This response activity level may be essential for durable protection, potentially explaining why re-infections occur with SARS-CoV-2 and other common coronaviruses.

Discrete jet forcing is a method to delay or suppress flow separation that is associated with a decrease in lift as well as an increase in drag. Although this method is used in both wind tunnel testing and flight experiments, the underlying mechanisms and scaling laws are not fully understood. Understanding these laws enables an optimized application of active flow control (AFC) to increase the efficacy, while reducing the input requirements. Only if the benefits of separation control significantly outweigh the associated costs does an application on an airplane become feasible. Both steady and sweeping jets are employed in the current work to investigate the effect of the sweeping motion on separation control authority. The associated flow fields are investigated for a variety of input parameters and actuator spacings. All actuator designs are tested on the NASA hump geometry that provides a platform with fixed boundary conditions for the comparison of various actuator designs. It is found that steady jets are able to effectively control the flow only at small spacings. Due to their favorable energy requirements, separation control at small spacings is the preferred application for steady jets. Fluidic oscillators are able to control the flow at both small and large spacings. Various actuator designs are tested to investigate the effect of the sweeping angle on the control authority. The results indicate that actuator designs with large sweeping angles are more suitable for controlling the flow at larger spacings, significantly outperforming steady jets, which yield a smaller jet spreading angle. The underlying mechanism for the superior performance of fluidic oscillators is an increased entrainment of high momentum fluid to wall-near regions with counter-rotating vortex pairs (CRVP) created along the span. The coherence in space and time of these CRVP is found to correlate with the control authority. If fluidic oscillators are tightly spaced, the flow field is less organized and no CRVP are formed. Here, the fluidic oscillators do not operate to their full potential and the additional energy requirements due to their internal feedback-mechanism may make them an inferior choice compared to steady jets. In the present work, a scaling law for freestream Reynolds number and actuator size is suggested. A properly defined momentum coefficient governs both the scaling of freestream Reynolds number and actuator size. To properly define this momentum coefficient, the throat conditions either have to be measured directly or accurately determined from measurements at the plenum. This scaling law allows for accurate scaling of an AFC design and its associated performance in the wind tunnel to flight conditions. This means, if the momentum coefficient is maintained between wind tunnel experiments and flight tests, the same performance is to be expected, excluding potential freestream Mach number effects. A quantitative relationship between actuator spacing and performance is yet to be determined. The present work provides a guideline for future work by suggesting circulation coefficients that quantify the vorticity and its organization introduced by discrete jet forcing at various spacings. The circulation data allow to distinguish boundary layer control and circulation control and reveal that the vorticity introduction in the boundary layer control region is a function of mass flow rate per jet and independent of spacing. Furthermore, the optimal spacing of a fluidic oscillator design can be determined by quantifying its flow field organization.

Extract of FIA data ("COND" files). A condition is a discrete combination of landscape attributes that define the condition (a condition will have the same land class, reserved status, owner group, forest type, stand-size class, regeneration status, and stand density). Conditions are assigned to plots.

Titanium (Ti), aluminum (Al), and boron (B) reactive mixed-metal nanopowders (Ti–Al–B RMNPs) represent attractive additives to hydrocarbon fuels such as exo-tetrahydrodicyclopentadiene (C10H16; JP-10) enhancing the limited volumetric energy densities of traditional hydrocarbons, but fundamental mechanisms and combustion stages in the oxidation have been obscure. This understanding is of vital significance in the development of next-generation propulsion systems and energy-generation technologies. Here, we expose distinct oxidation stages of single droplets of JP-10 doped with Ti–Al–B–RMNP exploiting innovative ultrasonic levitator technology coupled with time-resolved spectroscopic (UV–vis) and imaging diagnostics (optical and infrared). Two spatially and temporally distinct stages of combustion define a glow flame stage in which JP-10 and nanoparticles combust via a homogeneous gas phase (Al) and heterogeneous gas-surface oxidation (Ti, B) and a slower diffusion flame stage associated with the oxidation of JP-10. These findings enable the development of next-generation RMNP fuel additives with superior payload delivery capabilities.

In daily life, two common algorithms are used for collecting medical disease data: data integration of medical institutions and questionnaires. However, these statistical methods require collecting data from the entire research area, which consumes a significant amount of manpower and material resources. Additionally, data integration is difficult and poses privacy protection challenges, resulting in a large number of missing data in the dataset. The presence of incomplete data significantly reduces the quality of the published data, hindering the timely analysis of data and the generation of reliable knowledge by epidemiologists, public health authorities, and researchers. Consequently, this affects the downstream tasks that rely on this data. To address the issue of discrete missing data in cardiac disease, this paper proposes the AGAN (Attribute Generative Adversarial Nets) architecture for missing data filling, based on generative adversarial networks. This algorithm takes advantage of the strong learning ability of generative adversarial networks. Given the ambiguous meaning of filling data in other network structures, the attribute matrix is designed to directly convert it into the corresponding data type, making the actual meaning of the filling data more evident. Furthermore, the distribution deviation between the generated data and the real data is integrated into the loss function of the generative adversarial networks, improving their training stability and ensuring consistency between the generated data and the real data distribution. This approach establishes the missing data filling mechanism based on the generative adversarial networks, which ensures the rationality of the data distribution while filling the missing data samples. The experimental results demonstrate that compared to other filling algorithms, the data matrix filled by the proposed algorithm in this paper has more evident practical significance, fewer errors, and higher accuracy in downstream classification prediction.

Extract of Vermont FIA data ("COND" file). A condition is a discrete combination of landscape attributes that define the condition (a condition will have the same land class, reserved status, owner group, forest type, stand-size class, regeneration status, and stand density). Conditions are assigned to plots

Demographic data (n = 30).

RMSE value of missing data filling algorithms on different datasets (mean ± std).

The DCE data collected and analysed for this study. (DTA)

Extract of New York FIA data ("COND" file). A condition is a discrete combination of landscape attributes that define the condition (a condition will have the same land class, reserved status, owner group, forest type, stand-size class, regeneration status, and stand density). Conditions are assigned to plots