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This data repository includes the features and the trained backbone parameters used in the ICLR 2022 Paper "On the Importance of Firth Bias Reduction in Few-Shot Classification". The code accompanying this data is open-source and available at https://github.com/ehsansaleh/firth_bias_reduction The code and the data have three modules: 1. The "code_firth" module (10 files) relates to the basic ResNet backbones and logistic classifiers (e.g., Figures 2 and 3 in the main paper). 2. The "code_s2m2rf" module (2 files) relates to the S2M2R feature backbones and cosine classifiers (e.g., Figure 4 in the main paper). 3. The "code_dcf" module (3 files) relates to the few-shot Distribution Calibration (DC) method (e.g., Table 1 in the main paper). The relevant files for each module have the module name as a prefix in their name. 1. For instance, the "code_dcf_features.tar" file should be placed at the "features" directory of the "code_dcf" module. 2. As another example, "code_firth_features_cifarfs_novel.tar" should be placed in the "features" directory of the "code_firth" module, and it includes the features extracted from the novel split of mini-ImageNet dataset. Each tar-ball should be extracted in its relevant directory, and the md5 check-sums of the extracted files are also provided in the open-source code repository for verification. Please note that the actual datasets of images are not included here (since we do not own those datasets). However, helper scripts for automatically downloading the original datasets are also provided in the every module and sub-directory of the GitHub code repository.

This dataset contains model output from the Community Earth System Model, Version 2 (CESM2; Danabasoglu et al. 2020). These data were used for analysis in Impacts of Large-Scale Soil Moisture Anomalies in Southeastern South America, published in the Journal of Hydrometeorology (DOI: 10.1175/JHM-D-20-0116.1). See this publication for details of the model simulations that created these data. Four NetCDF (.nc) files are included in this dataset. Two files correspond to the control simulation (FHIST_SP_control) and two files correspond to a simulation with a dry soil moisture anomaly imposed in southeastern South America (FHIST_SP_dry; see the publication mentioned in the preceding paragraph for details on the spatial extent of the imposed anomaly). For each simulation, one file corresponds to output from the atmospheric model (file names with "cam") of CESM2 and the other to the land model (file names with "clm2"). These files are raw CESM output concatenated into a single file for each simulation. All files include data from 1979-01-02 to 2003-12-31 at a daily resolution. The spatial resolution of all files is about 1 degree longitude x 1 degree latitude. Variables included in these files are listed or linked below. Variables in atmosphere model output: Vertical velocity (omega) Convective precipitation Large-scale precipitation Surface pressure Specific humidity Temperature (atmospheric profile) Reference temperature (temp. at reference height, 2 meters in this case) Zonal wind Meridional wind Geopotential height Variables in land model output: See https://www.cesm.ucar.edu/models/cesm1.2/clm/models/lnd/clm/doc/UsersGuide/history_fields_table_40.xhtml Note that not all of the variables listed at the above link are included in the land model output files in this dataset. This material is based upon work supported by the National Science Foundation under Grant No. 1454089. We acknowledge high-performance computing support from Cheyenne (doi:10.5065/D6RX99HX) provided by NCAR's Computational and Information Systems Laboratory, sponsored by the National Science Foundation. The CESM project is supported primarily by the National Science Foundation. We thank all the scientists, software engineers, and administrators who contributed to the development of CESM2. References Danabasoglu, G., and Coauthors, 2020: The Community Earth System Model Version 2 (CESM2). Journal of Advances in Modeling Earth Systems, 12, e2019MS001916, https://doi.org/10.1029/2019MS001916.

Microbial fermentation provides a sustainable method of producing valuable chemicals. Adding dynamic control to fermentations can significantly improve titers, but most systems rely on transcriptional controls of metabolic enzymes, leaving existing intracellular enzymes unregulated. This limits the ability of transcriptional controls to switch off metabolic pathways, especially when metabolic enzymes have long half-lives. We developed a two-layer transcriptional/post-translational control system for yeast fermentations. Specifically, the system uses blue light to transcriptionally activate the major pyruvate decarboxylase PDC1, required for cell growth and concomitant ethanol production. Switching to darkness transcriptionally inactivates PDC1 and instead activates the anti-Pdc1p nanobody, NbJRI, to act as a genetically encoded inhibitor of Pdc1p accumulated during the growth phase. This dual transcriptional/post-translational control improves the production of 2,3-BDO and citramalate by up to 100 and 92% compared to using transcriptional controls alone in dynamic two-phase fermentations. This study establishes the NbJRI nanobody as an effective genetically encoded inhibitor of Pdc1p that can enhance the production of pyruvate-derived chemicals.

This is the dataset used in the Journal of Ecology publication of the same name. It is a site by species matrix of species relative abundances. The file BH.veg.data.csv contains a site by species matrix of species relative abundance (percent cover across all sampling quadrats within site). Data under the heading Year refers to sampling periods. Year 1 refers to the first set of samples taken between 1997 and 2000, Year 2 refers to the second set taken between 2002 and 2005, Year 3 refers to the third set taken between 2007 and 2010, and Year 4 refers to the fourth set taken between 2012 and 2015. All sites met Critical Trends Assessment Program (CTAP) size criteria of being at least 2 ha in size with a minimum of 500 m2 of suitable sampling area. The data in file BH.site.location.csv contains Public Land Survey System ranges and townships in which specific sites were located. All sites were located within the U.S. state of Illinois. More information about this dataset: Interested parties can request data from the Critical Trends Assessment Program, which was the source for the data on the wetlands in this study. More information on the program and data requests can be obtained by visiting the program webpage. Critical Trends Assessment Program, Illinois Natural History Survey. http://wwx.inhs.illinois.edu/research/ctap/

This repository includes scripts and datasets for Chapter 6 of my PhD dissertation, " Supertree-like methods for genome-scale species tree estimation," that had not been published previously. This chapter is based on the article: Molloy, E.K. and Warnow, T. "FastMulRFS: Fast and accurate species tree estimation under generic gene duplication and loss models." Bioinformatics, In press. https://doi.org/10.1093/bioinformatics/btaa444. The results presented in my PhD dissertation differ from those in the Bioinformatics article, because I re-estimated species trees using FastMulRF and MulRF on the same datasets in the original repository (https://doi.org/10.13012/B2IDB-5721322_V1). To re-estimate species trees, (1) a seed was specified when running MulRF, and (2) a different script (specifically preprocess_multrees_v3.py from https://github.com/ekmolloy/fastmulrfs/releases/tag/v1.2.0) was used for preprocessing gene trees (which were then given as input to MulRF and FastMulRFS). Note that this preprocessing script is a re-implementation of the original algorithm for improved speed (a bug fix also was implemented). Finally, it was brought to my attention that the simulation in the Bioinformatics article differs from prior studies, because I scaled the species tree by 10 generations per year (instead of 0.9 years per generation, which is ~1.1 generations per year). I re-simulated datasets (true-trees-with-one-gen-per-year-psize-10000000.tar.gz and true-trees-with-one-gen-per-year-psize-50000000.tar.gz) using 0.9 years per generation to quantify the impact of this parameter change (see my PhD dissertation or the supplementary materials of Bioinformatics article for discussion).

Models and predictions for submission to TRAC - 2020 Second Workshop on Trolling, Aggression and Cyberbullying Our approach is described in our paper titled: Mishra, Sudhanshu, Shivangi Prasad, and Shubhanshu Mishra. 2020. “Multilingual Joint Fine-Tuning of Transformer Models for Identifying Trolling, Aggression and Cyberbullying at TRAC 2020.” In Proceedings of the Second Workshop on Trolling, Aggression and Cyberbullying (TRAC-2020). The source code for training this model and more details can be found on our code repository: https://github.com/socialmediaie/TRAC2020 NOTE: These models are retrained for uploading here after our submission so the evaluation measures may be slightly different from the ones reported in the paper.

The data provided herein is accelerometer and strain data taken from free vibration response of pre-tensioned, partially submerged steel beam specimens (modulus of elasticity assumed = 29,000 ksi). The specimens were subjected to various levels of pre-tension, and various levels of submersion in water. The purpose of the testing was to quantify the effects of partial submersion on the vibrating frequencies of pretensioned beams. Three specimens were tested, each with different cross section (but identical cross-sectional area). The different cross sections allow investigation of the effects of specimen width as the specimen vibrates through water. The testing procedure was as follows: 1) Apply a specified level of tension in the beam. Measure tension via 3 strain gages. 2) Submerge the specimens to a specified depth of water 3) Excite the beams with either a hammer impact or a pull-and-release method (physically pull the middle of the bar and quickly release) 4) Measure the free vibration of the beam with 2 accelerometers. Schematic drawings of the test setup and the test specimens are provided, as is a picture of the test setup.

Bioenergy with carbon capture and storage (BECCS) sits at the nexus of the climate and energy security. We evaluated trade-offs between scenarios that support climate stabilization (negative emissions and net climate benefit) or energy security (ethanol production). Our spatially explicit model indicates that the foregone climate benefit from abandoned cropland (opportunity cost) increased carbon emissions per unit of energy produced by 14–36%, making geologic carbon capture and storage necessary to achieve negative emissions from any given energy crop. The toll of opportunity costs on the climate benefit of BECCS from set-aside land was offset through the spatial allocation of crops based on their individual biophysical constraints. Dedicated energy crops consistently outperformed mixed grasslands. We estimate that BECCS allocation to land enrolled in the Conservation Reserve Program (CRP) could capture up to 9 Tg C year–1 from the atmosphere, deliver up to 16 Tg CE year–1 in emissions savings, and meet up to 10% of the US energy statutory targets, but contributions varied substantially as the priority shifted from climate stabilization to energy provision. Our results indicate a significant potential to integrate energy security targets into sustainable pathways to climate stabilization but underpin the trade-offs of divergent policy-driven agendas.

These data were collected for an experiment examining effects of neonicotinoid (clothianidin) presence on hover fly (Diptera: Syrphidae) behavior. Hover flies of two species (Eristalis arbustorum and Toxomerus marginatus) were offered a choice to feed on artificial flowers laced with sucrose solution that was either contaminated (CLO) or not contaminated (CON) with clothianidin. Two different concentrations of clothianidin in 0.5 M sucrose solution were tested: 2.5 ppb and 150 ppb. We conducted four sets of 10 trials, each trial set examining a different combination of species and clothianidin dose. Across 6 hours of video for each trial we recorded 1) number of visits to each flower that resulted in feeding, and 2) amount of time spent feeding during each visit. We found that while neither species fed significantly longer on either of the solutions, E. arbustorum appeared to avoid flowers with clothianidin particularly at high rates. In the paper, we attribute this avoidance response, partially, to hover fly-visible spectral differences between the two flower choices and discuss potential implications for field and lab-based studies. In the enclosed zip file we have included all data for this project and code scripts from R. * Note: Data folder contains 4 files (instead of 6 as mentioned in Readme): e.tenax_photoreceptors.csv; hoverfly_data_UPDATE.csv; number_visits_UPDATE.csv; and Original 2018 hover fly choice test data_Clem2020.xlsx

This dataset includes five files developed using the procedures described in the article 'Developing County-level Data of Nitrogen Fertilizer and Manure Inputs for Corn Production in the United States' and Supplemental Information published in the Journal of Cleaner Production in 2021. Citation: Xia, Yushu, Hoyoung Kwon, and Michelle Wander. "Developing county-level data of nitrogen fertilizer and manure inputs for corn production in the United States." Journal of Cleaner Production 309 (2021): e126957. Brief method: The fertilizer and manure inputs for corn were generated with a top-down approach by assigning county-level total N inputs reported by USGS to different crops using state- and county-level survey data. The corn N needs were estimated using empirical extension-based equations coupled with soil and environmental covariates. The estimates of fertilizer N inputs were further refined for corn grain and silage production at the county level and gap-filling (using state-level averages) was carried out to generate final files for U.S. county-level N inputs. The dataset is provided in an alternative format in Google Earth Engine: https://code.earthengine.google.com/13a0078e7ee727bc001e045ad0e8c6fc

This dataset contains Raman spectra, each acquired from an individual, living, cell entrapped within a soft or stiff gelatin methacrylate hydrogel or from a cell-free region of the hydrogel sample. Spectra were acquired from the following cell types: Madin-Darby Canine Kidney cell (MDCK); Chinese hamster ovary cell (CHO-K1); transfected CHO-K1 cell that expressed the SNAP-tag and HaloTag reporter proteins fused to an organelle-specific protein (CHO-T); human monocyte-like cell (THP-1); inactive macrophage-like (M0-like); active anti-inflammatory macrophage-like (M2-like), pro/anti-inflammatory macrophage-like (M1/M2-like). These spectra are useful for identifying whether the hydrogel matrix obscures the Raman spectral signatures that are characteristic of each of these cell types.

Aging-related yield decline in Miscanthus × giganteus (miscanthus) remains a major constraint to sustainable biomass production. This study evaluated how nitrogen (N) management and soil fertility influence yield-component traits and productivity in aging miscanthus. Trials were conducted at two sites established in 2008 at the University of Illinois Energy Farm, Urbana, IL. (i) The Sun Grant trial received 0, 60, and 120 kg N ha−1 annually until 2015. Starting 2021, half of each plot received 60 or 120 kg N ha−1, resulting in six legacy-contemporary treatments: 0N–0N, 0N–120N, 60N–0N, 60N–60N, 120N–0N, 120N–120N. (ii) The Energy Farm trial remained unfertilized until 2014, when one half of each plot received 56 kg N ha−1, forming two treatments: 0N–0N, 0N–56N. Sun Grant trial results showed N fertilization increased tiller density (tillers m−2) and tiller weight (g tiller−1) in juvenile to early-mature miscanthus (2011–2015). After N withdrawal, both traits declined (20 % and 40 %), though legacy effects persisted in tiller weight in the aging stands (2020–2023). Contemporary N had little effect on tiller density but increased tiller weight by 34 %–77 %, resulting in 23 %–106 % higher machine-harvested biomass yield in 0–120N, 60-60N, and 120-120N plots. At the Energy Farm trial, 0N–56N plots yielded 59 %–108 % more biomass than 0N–0N. Soil total N increased (Sun Grant: 47 % by 2020; Energy Farm: 58 % by 2023), while Mehlich-3 P (42 %–44 %) and K (21 %–46 %) declined. These findings identify tiller weight as a key determinant of biomass yield in aging miscanthus and highlight the need for P and K management for long-term productivity.

This set of scripts accompanies the manuscript describing the R package polyRAD, which uses DNA sequence read depth to estimate allele dosage in diploids and polyploids. Using several high-confidence SNP datasets from various species, allelic read depth from a typical RAD-seq dataset was simulated, then genotypes were estimated with polyRAD and other software and compared to the true genotypes, yielding error estimates.

This is the data set for a publication titled, "Coupling carbon dioxide gas within a bubble curtain enhances its effectiveness to deter fish." The current study sought to quantify whether adding carbon dioxide gas (CO2) to a bubble curtain would enhance its efficacy to block fish. For this, a choice tank was outfitted with bubble curtains infused with either compressed air alone, or with two different concentrations of CO2 [30 or 100 mg/L]. Passage rates and position of common carp (an invasive Cyprinid) and black bullhead (a native Ictalurid) exposed to these treatments were compared. The data set consists of data from each of the experiments performed during the study.

Datasets and R scripts relating to the manuscript "Ecological characteristics and in situ genetic associations for yield-component traits of wild Miscanthus from eastern Russia" published in Annals of Botany, 10.1093/aob/mcw137. Field data, including collection locations, physical and ecological information for each location, and plant phenotypes relating to biomass are included. Genetic data in this repository include single nucleotide polymorphisms (SNPs) derived from restriction site-associated DNA sequencing (RAD-seq), as well as plastid microsatellites. A file is also included listing the DNA sequences of all RAD-seq markers generated to-date by the Sacks lab, including those from this publication.

The relationship between physical activity and mental health, especially depression, is one of the most studied topics in the field of exercise science and kinesiology. Although there is strong consensus that regular physical activity improves mental health and reduces depressive symptoms, some debate the mechanisms involved in this relationship as well as the limitations and definitions used in such studies. Meta-analyses and systematic reviews continue to examine the strength of the association between physical activity and depressive symptoms for the purpose of improving exercise prescription as treatment or combined treatment for depression. This dataset covers 27 review articles (either systematic review, meta-analysis, or both) and 365 primary study articles addressing the relationship between physical activity and depressive symptoms. Primary study articles are manually extracted from the review articles. We used a custom-made workflow (Fu, Yuanxi. (2022). Scopus author info tool (1.0.1) [Python]. <a href="https://github.com/infoqualitylab/Scopus_author_info_collection">https://github.com/infoqualitylab/Scopus_author_info_collection</a> that uses the Scopus API and manual work to extract and disambiguate authorship information for the 392 reports. The author information file (author_list.csv) is the product of this workflow and can be used to compute the co-author network of the 392 articles. This dataset can be used to construct the inclusion network and the co-author network of the 27 review articles and 365 primary study articles. A primary study article is "included" in a review article if it is considered in the review article's evidence synthesis. Each included primary study article is cited in the review article, but not all references cited in a review article are included in the evidence synthesis or primary study articles. The inclusion network is a bipartite network with two types of nodes: one type represents review articles, and the other represents primary study articles. In an inclusion network, if a review article includes a primary study article, there is a directed edge from the review article node to the primary study article node. The attribute file (article_list.csv) includes attributes of the 392 articles, and the edge list file (inclusion_net_edges.csv) contains the edge list of the inclusion network. Collectively, this dataset reflects the evidence production and use patterns within the exercise science and kinesiology scientific community, investigating the relationship between physical activity and depressive symptoms. FILE FORMATS 1. article_list.csv - Unicode CSV 2. author_list.csv - Unicode CSV 3. Chinese_author_name_reference.csv - Unicode CSV 4. inclusion_net_edges.csv - Unicode CSV 5. review_article_details.csv - Unicode CSV 6. supplementary_reference_list.pdf - PDF 7. README.txt - text file 8. systematic_review_inclusion_criteria.csv - Unicode CSV <b>UPDATES IN THIS VERSION COMPARED TO V3</b> (Clarke, Caitlin; Lischwe Mueller, Natalie; Joshi, Manasi Ballal; Fu, Yuanxi; Schneider, Jodi (2023): The Inclusion Network of 27 Review Articles Published between 2013-2018 Investigating the Relationship Between Physical Activity and Depressive Symptoms. University of Illinois at Urbana-Champaign. https://doi.org/10.13012/B2IDB-4614455_V3) - We added a new file systematic_review_inclusion_criteria.csv.

This is the core data for RELIX, a dataset of vascular plant species presence for 353 prairie remnants in the Midwestern United States and associated dataset of prairie remnant metadata. The primary data file contains a list of the vascular plant species observed in the prairie remnants, as well as a metadata table with more information about the prairie remnant in question and the species list itself. The data was compiled from a variety of written sources, private and published, chronicling observations made between the mid-twentieth century and 2021. It also contains a supplementary data table of vascular plant species observed in at least 8 of the prairie remnants in RELIX, as well as a list of acknowledgements for the associated manuscript.

This page contains the data for the manuscript "Vacuolating cytotoxin A interactions with the host cell surface". This manuscript is currently in prep.

Agriculture has substantial socioeconomic and environmental impacts that vary between crops. However, information on how the spatial distribution of specific crops has changed over time across the globe is relatively sparse. We introduce the Probabilistic Cropland Allocation Model (PCAM), a novel algorithm to estimate where specific crops have likely been grown over time. Specifically, PCAM downscales annual and national-scale data on the crop-specific area harvested of 17 major crops to a global 0.5-degree grid from 1961-2014. The resulting database presented here provides annual global gridded likelihood estimates of crop-specific areas. Both mean and standard deviations of grid cell fractions are available for each of the 17 crops. Each netCDF file contains an individual year of data with an additional variable ("crs") that defines the coordinate reference system used. Our results provide new insights into the likely changes in the spatial distribution of major crops over the past half-century. For additional information, please see the related paper by Jackson et al. (2019) in Environmental Research Letters (https://doi.org/10.1088/1748-9326/ab3b93).

This dataset is associated with the manuscript "Residual tau-fluvalinate, a beehive acaricide, disrupts growth and metabolism in the greater wax moth, Galleria mellonella" This dataset includes 2 Excel files: 1) raw_data_bioassay.xlsx: this file contains the raw data for waxworm bioassay. There are 2 worksheets within this file: - LC50: raw data for measuring the LC50 of Galleria mellonella (greater wax moth) in laboratory and field strains exposed to tau-fluvalinate. - RGR: Relative Growth Rate, raw data for measuring body weight of field strain of Galleria mellonella exposed to tau-fluvalinate. 2) raw-data_RT-qPCR.xlsx: this file contains raw data (Ct value) of RT-qPCR.

Data characterize zooplankton in Shelbyville Reservoir, Illinois, United States of America. Zooplankton were sampled with a conical zooplankton net (0.5m diameter mouth) when water was deeper than 2 m and by grab sample when water was shallower. Zooplankton samples were concentrated and subsampled with a Hensen-Stempel pipette following protocols described in Detmer et al. (2019). Zooplankton were identified to the lowest feasible taxonomic unit according to Pennak (1989) and Thorp and Covich (2001) and were enumerated in a 1 mL Sedgewick-Rafter cell. Subsamples were analyzed until at least 200 individuals were enumerated from each site.were counted across for each of the three main taxonomic groups (cladocerans, copepods, and rotifers). Given the variation in zooplankton concentrations at each site, this process often lead to far more than 200 individuals being counted (x̄ = 269, min = 200, max = 487). A summary of the sample size from each site can be found in Supplementary Table S2. Abundances were corrected for volume of water filtered. For rare taxa (< 20 individuals per sample), all individuals were measured for length. For abundant taxa, length measurements were collected on the first 20 organisms of each abundant taxon encountered in a subsample. Dry mass was calculated from equations for microcrustaceans, rotifers, and Chaoborus sp. (Rosen ,1981; Botrell et al., 1976; Dumont and Balvay, 1979).

A dataset of acoustic impulse responses for microphones worn on the body. Microphones were placed at 80 positions on the body of a human subject and a plastic mannequin. The impulse responses can be used to study the acoustic effects of the body and can be convolved with sound sources to simulate wearable audio devices and microphone arrays. The dataset also includes measurements with different articles of clothing covering some of the microphones and with microphones placed on different hats and accessories. The measurements were performed from 24 angles of arrival in an acoustically treated laboratory. Related Paper: Ryan M. Corey, Naoki Tsuda, and Andrew C. Singer. "Acoustic Impulse Responses for Wearable Audio Devices," IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP), Brighton, UK, May 2019. All impulse responses are sampled at 48 kHz and truncated to 500 ms. The impulse response data is provided in WAVE audio and MATLAB data file formats. The microphone locations are provided in tab-separated-value files for each experiment and are also depicted graphically in the documentation. The file wearable_mic_dataset_full.zip contains both WAVE- and MATLAB-format impulse responses. The file wearable_mic_dataset_matlab.zip contains only MATLAB-format impulse responses. The file wearable_mic_dataset_wave.zip contains only WAVE-format impulse responses.

This upload includes the 16S.B.ALL in 100-HF condition (referred to as 16S.B.ALL-100-HF) used in Experiment 3 of the WITCH paper (currently accepted in principle by the Journal of Computational Biology). 100-HF condition refers to making sequences fragmentary with an average length of 100 bp and a standard deviation of 60 bp. Additionally, we enforced that all fragmentary sequences to have lengths > 50 bp. Thus, the final average length of the fragments is slightly higher than 100 bp (~120 bp). In this case (i.e., 16S.B.ALL-100-HF), 1,000 sequences with lengths 25% around the median length are retained as "backbone sequences", while the remaining sequences are considered "query sequences" and made fragmentary using the "100-HF" procedure. Backbone sequences are aligned using MAGUS (or we extract their reference alignment). Then, the fragmentary versions of the query sequences are added back to the backbone alignment using either MAGUS+UPP or WITCH. More details of the tar.gz file are described in README.txt.

This dataset is derived from the raw dataset (https://doi.org/10.13012/B2IDB-4950847_V1) and collects entity mentions that were manually determined to be noisy, non-species entities.