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 dataset describes streamflow and precipitation event statistics for four watersheds located in Clarksburg, Maryland, USA. Streamflow and precipitation events were identified from fourteen years of sub-daily (5- and 15-minute) monitoring data spanning October 1, 2004 through September 30, 2018. A 6-hour inter-event window was used to define discrete streamflow and precipitation events. The following streamflow metrics were calculated for each event area normalized peak streamflow, runoff yield, runoff ratio, streamflow duration, time to peak, and rise rate. Precipitation event metrics include total precipitation depth and precipitation event duration.

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.

Integrated Site Assessments are carried out by Natural England staff to assess the condition of notified features on Sites of Special Scientific Interest, and Indicators of Success on Higher Level Stewardship agri-environment schemes. The ISA process integrates surveys for both purposes, so where they co-occur they are usually recorded together. Individual surveys include the recording of a variety of species within SSSI Units and/or Rural Land Register Parcels, as well as other non-biotic measurements such as vegetation structure, which together are used in the assessment of SSSI feature condition, Indicators of Success, or both. Species records are associated with the SSSI units and/or RLR Parcels containing the list of features which are the subject of each part of the ISA survey, so survey 'feature lists' are used to define discrete geographic areas within which the species were recorded. Precise BNG grid references, or eastings and northings, are not recorded for individual species, and the precise extent of the features (usually semi-natual habitats) within the SSSI units and/or RLR parcels is unknown. Each species record is provided with additional attribute information including the list of features assessed, the variable and summary value. Species recorded are mostly vascular plants, often because they are used within ISAs to indicate good or poor habitat condition. Only species that were actually seen are included - there are no 'absence' records. Attribution statement: © Natural England copyright. Contains Ordnance Survey data © Crown copyright and database right [year].

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

PLEASE NOTE: This is a large dataset. The dataset is only currently downloadable from our Open Data Geoportal in Spreadsheet, Shapefile and File Geodatabase formats.Integrated Site Assessments are carried out by Natural England staff to assess the condition of notified features on Sites of Special Scientific Interest, and Indicators of Success on Higher Level Stewardship agri-environment schemes. The ISA process integrates surveys for both purposes, so where they co-occur they are usually recorded together. Individual surveys include the recording of a variety of species within SSSI Units and/or Rural Land Register Parcels, as well as other non-biotic measurements such as vegetation structure, which together are used in the assessment of SSSI feature condition, Indicators of Success, or both. Species records are associated with the SSSI units and/or RLR Parcels containing the list of features which are the subject of each part of the ISA survey, so survey 'feature lists' are used to define discrete geographic areas within which the species were recorded. Precise BNG grid references, or eastings and northings, are not recorded for individual species, and the precise extent of the features (usually semi-natual habitats) within the SSSI units and/or RLR parcels is unknown.Full metadata can be viewed on data.gov.uk.

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.

Demographic data (n = 30).

This digital GIS dataset and accompanying nonspatial files synthesize model outputs from a regional-scale volumetric 3D geologic model that portrays the generalized subsurface geology of the Michigan Basin region of Michigan, Wisconsin, Illinois, Indiana, and Ohio. The intent of this product is to rapidly and efficiently synthesize large quantities of geologic data from a wide variety of sources into a multi-use geologic framework model applicable to natural resource exploration and management. Major geographic features within the study area include Lake Michigan and the Lower Peninsula of Michigan, and portions of the Upper Peninsula of Michigan, Lake Huron, Lake Saint Clair, and Lake Erie. Geologically, the study area incorporates major structures such as the Kankakee Arch, Findlay Arch, Wisconsin Arch, Algonquin Arch, Lake Superior Syncline, and the broader Michigan sedimentary basin from the Precambrian basement to the Earth's surface. Data released here consists of stratigraphic horizon grids of major Phanerozoic sedimentary units that broadly define the geometry of the subsurface, a stratigraphic horizon grid of the uppermost Precambrian basement rocks, and line data that estimate the two-dimensional geometry of fault planes that intersect stratigraphic horizon grids. 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 private and public 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 MichiganBasin3D geodatabase contains 41 subsurface stratigraphic horizons in raster format, representing the tops of modeled subsurface units, as well as a feature dataset titled "GeologicModel." This feature dataset includes a line feature class of 180 fault segments that delineate faults with probable post-Precambrian offset extending into the Phanerozoic sedimentary layers (PrecambrianLevelFaults_Throughgoing). It also features a line class of 170 fault segments representing throughgoing faults at the level of the top Trenton Group (TrentonLevelFaults), along with a polygon feature class delineating the study area (ModelBoundary). Nonspatial tables provide definitions of data sources (DataSources), terminology used in the dataset (Glossary), and descriptions of the modeled surfaces (DescriptionOfModelUnits). Additional file folders contain vector data in shapefile format, raster data in ASCII format, and tables in comma-separated values format. A comprehensive data dictionary outlines the entity and attribute information for all geospatial data and accompanying nonspatial tables (EntityAndAttributes). Accompanying this data release is a workbook “MichiganBasinInputSummaryTable.csv”, which tabulates the stratigraphic horizons modeled in each fault block, and the types and quantity of data inputs for each stratigraphic horizon. Key references associated with each data input are found in the "MichiganBasinInputReferences" so any user could replicate this work if they desired. An associated USGS report: “A three-dimensional geologic framework model of the Michigan Basin region, Illinois, Indiana, Michigan, Ohio, and Wisconsin, USA” documents the process of manipulating and interpreting 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.

The analysis of functional data calls for a bivariate functional covariance function σ(s, t) that may be evaluated at any discrete set of points to define a variance-covariance matrix Σ. This article uses finite element methodology to construct a representation of a functional Choleski factor λ(w, s) to define σ(s, t) = ∫λ(w, s)λ(w, t) dw. An estimate of Σ-1 is especially important for applications and, where the eigenstructure of the covariance permits, this is readily available since the resulting Σ is almost always positive definite. A simulation study compares the performance of estimates of Σ and Σ-1 to those from the classic covariance matrix estimate and an estimate using glasso package in R. The method’s capability of constraining estimates of Σ-1 to be strongly band-structured resulted in superior estimates. The real data application is to the smoothing of the Fels female growth data where σ(s, t) estimates the residual covariance structure in the presence of sampling points varying from one case to another. Supplementary materials are available online.

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

Scientific writing, particularly quantitative writing, is difficult to master. To help undergraduate students write more clearly about data, we sought to deconstruct writing into discrete, specific elements. We focused on statements typically used to describe data found in the results sections of research articles (quantitative comparative statements, QC). In this paper, we define the essential components of a QC statement and the rules that govern those components. Clearly defined rules allowed us to quantify writing quality of QC statements (4C scoring). Using 4C scoring, we measured student writing gains in a post-test at the end of the term compared to a pre-test (37% improvement). In addition to overall score, 4C scoring provided insight into common writing mistakes by measuring presence/absence of each essential component. Student writing quality in lab reports improved when they practiced writing isolated QC statements. Although we observed a significant increase in writing quality in lab reports describing a simple experiment, we noted a decrease in writing quality when the complexity of the experimental system increased. Our data suggest a negative correlation of writing quality with complexity. We discuss how our data aligns with existing cognitive theories of writing and how science instructors might improve the scientific writing of their students.

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

Although South Africa is the global epicenter of the HIV epidemic, the uptake of HIV testing and treatment among young people remains low. Concerns about confidentiality impede the utilization of HIV prevention services, which signals the need for discrete HIV prevention measures that leverage youth-friendly platforms. This paper describes the process of developing a youth-friendly internet-enabled HIV risk calculator in collaboration with young people, including young key populations aged between 18 and 24 years old. Using qualitative research, we conducted an exploratory study with 40 young people including young key population (lesbian, gay, bisexual, transgender (LGBT) individuals, men who have sex with men (MSM), and female sex workers). Eligible participants were young people aged between 18–24 years old and living in Soweto. Data was collected through two peer group discussions with young people aged 18–24 years, a once-off group discussion with the [Name of clinic removed for confidentiality] adolescent community advisory board members and once off face-to-face in-depth interviews with young key population groups: LGBT individuals, MSM, and female sex workers. LGBT individuals are identified as key populations because they face increased vulnerability to HIV/AIDS and other health risks due to societal stigma, discrimination, and obstacles in accessing healthcare and support services. The measures used to collect data included a socio-demographic questionnaire, a questionnaire on mobile phone usage, an HIV and STI risk assessment questionnaire, and a semi-structured interview guide. Framework analysis was used to analyse qualitative data through a qualitative data analysis software called NVivo. Descriptive statistics were summarized using SPSS for participant socio-demographics and mobile phone usage. Of the 40 enrolled participants, 58% were male, the median age was 20 (interquartile range 19–22.75), and 86% had access to the internet. Participants’ recommendations were considered in developing the HIV risk calculator. They indicated a preference for an easy-to-use, interactive, real-time assessment offering discrete and private means to self-assess HIV risk. In addition to providing feedback on the language and wording of the risk assessment tool, participants recommended creating a colorful, interactive and informational app. A collaborative and user-driven process is crucial for designing and developing HIV prevention tools for targeted groups. Participants emphasized that privacy, confidentiality, and ease of use contribute to the acceptability and willingness to use internet-enabled HIV prevention methods.