cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.6084/m9.figshare.24923937
title: Data and code for "Responses of plant biomass and biomass allocation to experimental drought: a global phylogenetic meta-analysis"

description: Divergent responses of plant biomass to drought were found across hundreds of manipulative experiments. While many researchers have explored the influences of plant functional types (PFTs) and climatic conditions, few studies focus on the importance of evolutionary history to biomass responses to drought. Here we compiled a global dataset of the responses of plant biomass and biomass allocation to the experimental drought from 281 studies conducted on 329 wild species and conducted both traditional and phylogenetic meta-analyses to explore the potential role of phylogenetic information (the proxy of evolutionary history) in affecting the differences among PFTs and the regulation effect of environmental conditions. We found that there were no consistent differences in biomass responses to drought between gymnosperm and angiosperm woody plants when the traditional meta-analysis was applied. Taking the phylogenetic information into account by applying the phylogenetic meta-analysis consistently resulted in more sensitive responses in gymnosperms than angiosperms. These differences between gymnosperms and angiosperms were large but with high uncertainty, probably due to the high hydraulic diversity in both groups. Within gymnosperms, the observed higher drought sensitivity in evergreen species than deciduous ones was mainly derived from the phylogenetic relatedness among species. Similarly, weaker biomass response to drought in C4 than C3 herbs was also largely due to the phylogenetic relatedness as most C4 plants clustered in a clade called PACMAD (Panicoideae, Aristidoideae, Chloridoideae, Micrairoideae, Arundinoideae, and Danthonioideae) in Poaceae family. The influences of drought intensity were prevalent in both traditional and phylogenetic meta-analyses. Overall, our results highlight the vital role of plant evolutionary history played in affecting plant responses to drought. Given the potentially complicated interactive effects of climatic change and evolutionary history on plant responses, we call for experiments that aim to investigate the role of phylogenetic relatedness on plant and ecosystem functions in future studies.
DOI: 10.14278/rodare.2623
title: Data publication: Characterization of Magnetic and Mineralogical Properties of Slag Particles from WEEE Processing

description: This dataset includes the modal mineralogy and the SQUID-VSM measurements. The latter were conducted at the HZDR.
DOI: 10.14278/rodare.2624
title: Data publication: Characterization of Magnetic and Mineralogical Properties of Slag Particles from WEEE Processing

description: This dataset includes the modal mineralogy and the SQUID-VSM measurements. The latter were conducted at the HZDR.
DOI: 10.14278/rodare.2625
title: Data publication: Revealing Non-equilibrium and Relaxation in Warm Dense Matter

description: All data as needed to generate the figures in the manuscript.
DOI: 10.14278/rodare.2626
title: Data publication: Revealing Non-equilibrium and Relaxation in Warm Dense Matter

description: All data as needed to generate the figures in the manuscript.
DOI: 10.6084/m9.figshare.18273137.v2
title: On distribution selection under ranked set sampling schemes

description: Distribution selection plays a key role in parametric statistics. Choosing one from a set of candidate distributions that best fits the sample data is a recurring task in a large number of statistical analysis. The choice of a misspecified and/or poor fitted distribution can lead to unreliable results and conclusions. Although distribution selection has been widely studied regarding goodness of fit procedures, less attention has been given on how the sampling design impacts the chance of choosing the most suitable distribution. In this work we address the performance of ranked set sampling (RSS), extreme ranked set sampling (ERSS), and mixture ranked set sampling (MRSS) in distribution selection. In particular, we focus on count data, an important and very usual class of random variables. A comprehensive simulation study was carried out, accounting for five distributions: Poisson, negative binomial, geometric, zero-inflated Poisson, and zero-inflated negative binomial. Results show that RSS and extensions performed better than simple random sampling (SRS) under perfect ranking. When ranking errors are present, better efficiency depends on how accurate is the ranking criterion, and the different RSS-based designs also differ in terms of their robustness. Findings are reinforced by additional simulation based on two real data sets.
DOI: 10.6084/m9.figshare.18273137
title: On distribution selection under ranked set sampling schemes

description: Distribution selection plays a key role in parametric statistics. Choosing one from a set of candidate distributions that best fits the sample data is a recurring task in a large number of statistical analysis. The choice of a misspecified and/or poor fitted distribution can lead to unreliable results and conclusions. Although distribution selection has been widely studied regarding goodness of fit procedures, less attention has been given on how the sampling design impacts the chance of choosing the most suitable distribution. In this work we address the performance of ranked set sampling (RSS), extreme ranked set sampling (ERSS), and mixture ranked set sampling (MRSS) in distribution selection. In particular, we focus on count data, an important and very usual class of random variables. A comprehensive simulation study was carried out, accounting for five distributions: Poisson, negative binomial, geometric, zero-inflated Poisson, and zero-inflated negative binomial. Results show that RSS and extensions performed better than simple random sampling (SRS) under perfect ranking. When ranking errors are present, better efficiency depends on how accurate is the ranking criterion, and the different RSS-based designs also differ in terms of their robustness. Findings are reinforced by additional simulation based on two real data sets.
DOI: 10.6084/m9.figshare.18273137.v1
title: On distribution selection under ranked set sampling schemes

description: Distribution selection plays a key role in parametric statistics. Choosing one from a set of candidate distributions that best fits the sample data is a recurring task in a large number of statistical analysis. The choice of a misspecified and/or poor fitted distribution can lead to unreliable results and conclusions. Although distribution selection has been widely studied regarding goodness of fit procedures, less attention has been given on how the sampling design impacts the chance of choosing the most suitable distribution. In this work we address the performance of ranked set sampling (RSS), extreme ranked set sampling (ERSS), and mixture ranked set sampling (MRSS) in distribution selection. In particular, we focus on count data, an important and very usual class of random variables. A comprehensive simulation study was carried out, accounting for five distributions: Poisson, negative binomial, geometric, zero-inflated Poisson, and zero-inflated negative binomial. Results show that RSS and extensions performed better than simple random sampling (SRS) under perfect ranking. When ranking errors are present, better efficiency depends on how accurate is the ranking criterion, and the different RSS-based designs also differ in terms of their robustness. Findings are reinforced by additional simulation based on two real data sets.
DOI: 10.6084/m9.figshare.24873588
title: data.xlsx

description: this is the data of my paper.
DOI: 10.6084/m9.figshare.24873588.v1
title: data.xlsx

description: this is the data of my paper.
DOI: 10.5281/zenodo.10448259
title: The dataset of Synoptic Analysis of the Regional Daily Extreme Precipitation in the Yangtze River Delta during 1979-2021 Summer

description: The dataset contains the SOM results, the onset and latest ending dates of the Meiyu period, and the number of extreme precipitation stations over the YRD region per day during the 1979-2021 summer.
DOI: 10.5281/zenodo.10448260
title: The dataset of Synoptic Analysis of the Regional Daily Extreme Precipitation in the Yangtze River Delta during 1979-2021 Summer

description: The dataset contains the SOM results, the onset and latest ending dates of the Meiyu period, and the number of extreme precipitation stations over the YRD region per day during the 1979-2021 summer.
DOI: 10.6084/m9.figshare.13264793
title: BioSR: a biological image dataset for super-resolution microscopy

description: BioSR is a biological image dataset for super-resolution microscopy, currently including more than 2200 pairs of low-and-high resolution images covering four biology structures (CCPs, ER, MTs, F-actin), nine signal levels (15-600 average photon count), and two upscaling-factors (linear SIM and non-linear SIM). BioSR is now freely available, aiming to provide a high-quality dataset for the community of single bio-image super-resolution algorithm and advanced SIM reconstruction algorithm developers. For more information about BioSR, please see our Nature Methods manuscript, "Evaluation and development of deep neural networks for image super-resolution in optical microscopy" (DOI: 10.1038/s41592-020-01048-5).
Update 2022.10.04
Add <em>DataSet of rDL-SRM (Zenodo Link).xlsx</em> file, which includes descriptions and Zenodo links of BioSR+ (data extension of BioSR) and other data used in our Nature Biotechnology paper "Rationalized deep learning super-resolution microscopy for sustained live imaging of rapid subcellular processes" (DOI: 10.1038/s41587-022-01471-3 ).<br>
DOI: 10.6084/m9.figshare.24923919
title: Data for IJLRA Manuscript-2023.xlsx

description: This data was collected via a survey.
DOI: 10.6084/m9.figshare.24923919.v1
title: Data for IJLRA Manuscript-2023.xlsx

description: This data was collected via a survey.
DOI: 10.5281/zenodo.10449882
title: [Data] Optimizing In-situ Monitoring for Laser Powder Bed Fusion Process: Deciphering Acoustic Emission and Sensor Sensitivity with Explainable Machine Learning

description: Intentional variations in Metal-Laser Powder Bed Process (L-PBF) spaces were introduced by employing two distinct distributions of 316L stainless steel powder, characterized by particle sizes both greater than 45 μm and less than 45 μm. These powders underwent processing with two different sets of laser parameters, resulting in the generation of four datasets (D1, D2, D3, D4). These datasets encapsulate airborne Acoustic Emissions (AE) arising from diverse build qualities, including Lack of Fusion (LoF) pores, conduction mode, and keyhole formations. The experiments were conducted utilizing a Sisma MYSINT 100 commercial LPBF printer and an airborne Acoustic Emission (AE) sensor system boasting a flat frequency response ranging from 0 to 150 kHz. Validation of the ground truths for the three laser regimes across the four datasets, representing distinct process spaces, was accomplished through the confirmation of cross-sectional images. In the fabrication of a cube using a powder bed and laser, data acquisition from an AE sensor commenced when the optical intensity reached a threshold of 0.5 V for each scan length. The photodiode trigger gain was adjusted to saturate at 5 V, and the subsequent continuous-time window, where the optical signal remained at 5 V for 12.5 ms, was calculated and segmented to generate the dataset. Irrespective of the specific regime (Lack of Fusion, Conduction, and Keyhole) or the cube being fabricated (with two powder distributions), the signals obtained during this process were segmented into a 12.5 ms window comprising 5000 data points. Each dataset is accompanied by two files – one for raw data and the other for ground truth labels. To mitigate noise, an offline low-pass Butterworth filter with a 150 kHz cut-off frequency was applied, aligning with the frequency response specification of the AE sensor. The total number of AE windows per dataset is approximately 7500 raw AE signals.
DOI: 10.5281/zenodo.10449883
title: [Data] Optimizing In-situ Monitoring for Laser Powder Bed Fusion Process: Deciphering Acoustic Emission and Sensor Sensitivity with Explainable Machine Learning

description: Intentional variations in Metal-Laser Powder Bed Process (L-PBF) spaces were introduced by employing two distinct distributions of 316L stainless steel powder, characterized by particle sizes both greater than 45 μm and less than 45 μm. These powders underwent processing with two different sets of laser parameters, resulting in the generation of four datasets (D1, D2, D3, D4). These datasets encapsulate airborne Acoustic Emissions (AE) arising from diverse build qualities, including Lack of Fusion (LoF) pores, conduction mode, and keyhole formations. The experiments were conducted utilizing a Sisma MYSINT 100 commercial LPBF printer and an airborne Acoustic Emission (AE) sensor system boasting a flat frequency response ranging from 0 to 150 kHz. Validation of the ground truths for the three laser regimes across the four datasets, representing distinct process spaces, was accomplished through the confirmation of cross-sectional images. In the fabrication of a cube using a powder bed and laser, data acquisition from an AE sensor commenced when the optical intensity reached a threshold of 0.5 V for each scan length. The photodiode trigger gain was adjusted to saturate at 5 V, and the subsequent continuous-time window, where the optical signal remained at 5 V for 12.5 ms, was calculated and segmented to generate the dataset. Irrespective of the specific regime (Lack of Fusion, Conduction, and Keyhole) or the cube being fabricated (with two powder distributions), the signals obtained during this process were segmented into a 12.5 ms window comprising 5000 data points. Each dataset is accompanied by two files – one for raw data and the other for ground truth labels. To mitigate noise, an offline low-pass Butterworth filter with a 150 kHz cut-off frequency was applied, aligning with the frequency response specification of the AE sensor. The total number of AE windows per dataset is approximately 7500 raw AE signals.
DOI: 10.6084/m9.figshare.24720558
title: Different doses of imeglimin for management of type 2 diabetes mellitus: a systematic review, meta-analysis, and meta-regression of randomized clinical trials

description: A new medication for type 2 diabetes mellitus (T2DM) called imeglimin can target all three organs involved in the pathogenesis of DM, namely the liver, skeletal muscles, and pancreas. This research seeks to examine the most efficacious and safe dose of imeglimin for the management of T2DM. Using particular keywords, we searched the CENTRAL, Medline, Scopus, and ClinicalTrials.gov databases for pertinent literature. The results of continuous variables were pooled into the mean difference (MD) and dichotomous variables into odds ratio (OR) along with their 95% confidence intervals (95% CI) using fixed-effect models. Our pooled analysis revealed that imeglimin 1000 mg twice daily [MD −0.90% <i>p</i> &lt; 0.00001] and 1500 mg twice daily [MD −0.84% <i>p</i> = 0.0003] as monotherapy was associated with a higher reduction in the HbA<sub>1c</sub> compared to placebo. This superiority was still maintained when given as combination therapy. Regrettably, there was an observed escalation in gastrointestinal AEs as the dosage of imeglimin was raised, despite the absence of a corresponding improvement in its efficacy in decreasing HbA<sub>1c</sub> levels. Our study suggests that imeglimin 1000 mg twice daily may offer the most optimum therapeutic effects for glycemic control without compromising its safety profiles.
DOI: 10.6084/m9.figshare.24720558.v1
title: Different doses of imeglimin for management of type 2 diabetes mellitus: a systematic review, meta-analysis, and meta-regression of randomized clinical trials

description: A new medication for type 2 diabetes mellitus (T2DM) called imeglimin can target all three organs involved in the pathogenesis of DM, namely the liver, skeletal muscles, and pancreas. This research seeks to examine the most efficacious and safe dose of imeglimin for the management of T2DM. Using particular keywords, we searched the CENTRAL, Medline, Scopus, and ClinicalTrials.gov databases for pertinent literature. The results of continuous variables were pooled into the mean difference (MD) and dichotomous variables into odds ratio (OR) along with their 95% confidence intervals (95% CI) using fixed-effect models. Our pooled analysis revealed that imeglimin 1000 mg twice daily [MD −0.90% <i>p</i> &lt; 0.00001] and 1500 mg twice daily [MD −0.84% <i>p</i> = 0.0003] as monotherapy was associated with a higher reduction in the HbA<sub>1c</sub> compared to placebo. This superiority was still maintained when given as combination therapy. Regrettably, there was an observed escalation in gastrointestinal AEs as the dosage of imeglimin was raised, despite the absence of a corresponding improvement in its efficacy in decreasing HbA<sub>1c</sub> levels. Our study suggests that imeglimin 1000 mg twice daily may offer the most optimum therapeutic effects for glycemic control without compromising its safety profiles.
DOI: 10.3886/e192865v1-144481
title: Code for: The (Lack of) Anticipatory Effects of the Social Safety Net on Human Capital Investment

description: How does the expectation that a child will receive government benefits in adulthood
affect parental investments in the child’s human capital? Most parents whose children
receive Supplemental Security Income (SSI) benefits overestimate the likelihood that
their child will receive SSI benefits in adulthood. We present randomly-selected families
with the predicted likelihood that their child will receive SSI benefits in adulthood.
Reducing parents’ expectations that children will receive benefits in adulthood does
not increase investments in children’s human capital. This zero effect is precisely
estimated. Likely explanations include parents working more themselves, non-financial
goals influencing investment, and families facing investment constraints.
description: Random subset of households with a child receiving SSI.
DOI: 10.57841/casdc.0003321
title: 呼包鄂地区高时空分辨率空气质量模拟数据集
DOI: 10.57841/casdc.0003322
title: 鄂尔多斯高时空分辨率温室气体模拟数据
DOI: 10.57841/casdc.0003323
title: 鄂尔多斯格点化城市碳排放清单
DOI: 10.6084/m9.figshare.24924282
title: Data for Physics-Informed Convolutional Decoder (PICD)

description: This dataset is the supporting data for the manuscript " <b>Physics-Informed Convolutional Decoder (PICD): A novel approach for direct inversion of heterogeneous subsurface flow</b>".
DOI: 10.5281/zenodo.10450180
title: Radio-frequency WLAN data frame recordings from a common off-the-shelf laptop

description: This dataset contains IQ-baseband recordings of data frames transmitted from a Lenovo Thinkpad T470s. A program called Scapy was used to force the WLAN chip (Intel 8265NGW) of the laptop to send a data frame with a fixed bit payload on repeat. The measurements were conducted in the anechoic chamber located at the Tampere University's Hervanta campus.

The dataset contains 10 repeat recordings with MCS indices 3,5,6 and 8. The WLAN bandwidth was 20 MHz on channel 12, corresponding to center frequency of 2.467 GHz. The recordings were made with a vector signal transceiver PXIe-5840 by National Instruments. The sampling frequency in all recordings was 200 MHz with a recording length of 20e6 samples, corresponding to a recording period of 100 ms.

All recordings are provided in a binary format. More specifically, the data is interleaved (I1 Q1 I2 Q2 I3 Q3 ...) in little-endian 64-bit floating point format. A matlab function is provided for converting the binary data in a file to a complex float vector. Additionally, a simple Matlab example script is provided to showcase how the data can be used to plot a spectrogram.
DOI: 10.5281/zenodo.10450181
title: Radio-frequency WLAN data frame recordings from a common off-the-shelf laptop

description: This dataset contains IQ-baseband recordings of data frames transmitted from a Lenovo Thinkpad T470s. A program called Scapy was used to force the WLAN chip (Intel 8265NGW) of the laptop to send a data frame with a fixed bit payload on repeat. The measurements were conducted in the anechoic chamber located at the Tampere University's Hervanta campus.

The dataset contains 10 repeat recordings with MCS indices 3,5,6 and 8. The WLAN bandwidth was 20 MHz on channel 12, corresponding to center frequency of 2.467 GHz. The recordings were made with a vector signal transceiver PXIe-5840 by National Instruments. The sampling frequency in all recordings was 200 MHz with a recording length of 20e6 samples, corresponding to a recording period of 100 ms.

All recordings are provided in a binary format. More specifically, the data is interleaved (I1 Q1 I2 Q2 I3 Q3 ...) in little-endian 64-bit floating point format. A matlab function is provided for converting the binary data in a file to a complex float vector. Additionally, a simple Matlab example script is provided to showcase how the data can be used to plot a spectrogram.
DOI: 10.5517/ccdc.csd.cc2hz7pf
title: CCDC 2322975: Experimental Crystal Structure Determination

description: Related Article: Suma Dilipkumar|2024|CSD Communication|||
description: An entry from the Cambridge Structural Database, the world’s repository for small molecule crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the CCDC and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures.
DOI: 10.11588/data/dytw8a
title: Adsorption Structures Affecting the Electronic Properties and Photoinduced Charge Transfer at Perylene-Based Molecular Interfaces [Data]

description: Underlying data for figures in the paper "Adsorption Structures Affecting the Electronic Properties and Photoinduced Charge Transfer at Perylene-Based Molecular Interfaces"
DOI: 10.34740/kaggle/dsv/7322340
title: Egypt Gold Prices | Daily Updated
DOI: 10.5281/zenodo.10055760
title: E3SM output for tracking mesoscale convection systems in the US

description: E3SMv1 output for tracking mesoscale convection systems in the US.
DOI: 10.5281/zenodo.8227942
title: A dataset of land cover samples over the Tibetan Plateau

description: A dataset consists of 10,242 land cover samples over the Tibetan Plateau with 12 vegetation types and 3 non-vegetation types created through manual interpretation and field trips.
DOI: 10.17632/zvsdkyhn2m.3
title: Raw data on the deformation of granitic mylonite in a Paterson gas-medium apparatus

description: This data set is about the raw data on deformation of 15 granitic mylonite samples at a confining pressure of 300 MPa and temperatures of 800-1000 °C in a Paterson gas-medium apparatus. This data set can be used to inverstigate the effect of foliation and lineation on the deformation of granitic mylonite under high temperature. Results show that the maximum strength is not perpendicular to the foliation as previously expected or reported but parallel to the lineation direction.
DOI: 10.5281/zenodo.8382289
title: Data for "Statistical characteristics of thunderstorm activity in the middle reaches of the Yangtze River Basin based on a five-year cloud-to-ground lighting dataset"

description: Data for "Statistical characteristics of thunderstorm activity in the middle reaches of the Yangtze River Basin based on a five-year"