cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.20372/eiar-rdm/7ssjzu
title: Evaluation of Bradyrhizobium Strain Rates for Growth, Nodulation and Yield of Soybean (Glycine Max L.) at Seka District, Jimma Zone, Southwestern Ethiopia

description: To determine biological strain rates on nodulation and yield of soybean in 2019 cropping season
DOI: 10.20372/eiar-rdm/z0pgum/miyavk
title: Jimma and bora soybean inoculation trial field data sheet.tab

description: :unav
DOI: 10.20372/eiar-rdm/z0pgum
title: Soybean rhizobia inoculation trial

description: Data collected from field trial conducted to evaluate the response of soybean to rhizobia inoculation
DOI: 10.20372/eiar-rdm/iso6f2/lzqdkx
title: 6.pdf

description: :unav
DOI: 10.20372/eiar-rdm/iso6f2
title: Effect of Sulfur and Bradyrhizobium Inoculation on Nodulation and Yield of Soybean (Glycine max L.) on Nitisols of Southwestern Ethiopia

description: To evaluate the integrated effect of Sulfur and biological strains on nodulation and yield of soybean at Jimma zone in 2019 cropping season
DOI: 10.20372/eiar-rdm/vlra18/odflx1
title: BOF journals.pdf

description: :unav
DOI: 10.20372/eiar-rdm/vlra18
title: Grain Yield and Economic Importance of Bio Fertilizer Rates of Soybean at Begi and Asossa Districts Western Ethiopia

description: A field experiment was conducted on Nitisols of Asossa Agricultural Research Centre during 2017/18 to 2018/2019 cropping season toinvestigate the response of yieldpartial budget analysis to biofertilizer rates.The N fertilizer treatments considered in the study consisted of six levels (rates) of biofertilizer, one nationally recommended inorganic N and negative control of N.The treatments consists of: 125 g ha-1 (T1), 250 g ha-1 (T2), 500 g ha-1(T3), 625 g ha-1(T4), 750 g ha-1(T5), 900 g ha-1 (T6), negative control (T7) and 18kg N ha-1. The treatments were laid out as a Randomized Complete Block Design with three replications.The analysis of variance revealed that bio-fertilizer rates significantly (P &lt; 0.01) affected grain yield at Begi district, while non-siginificant (p&lt;0.05) at Asossa district. The maximum (3483.7 kg ha-1and 1750.9 kg ha-1 ) grain yield was recorded from 500 g ha-1bio-fertilizer at Begi and Asossa districtrespectively. The application of 500 g ha- 1biofertilizer had the highest net-benefit of 20850.8 ETB, followed by 125 g ha -1biofertilizer which also had a total of 20196.8 ETB net benefit at Asossa district, while the application of 500 g ha- 1biofertilizerhad the highest net-benefit of 41644.4 ETB, followed by 125 g ha-1biofertilizer which also had a total of 38315.6 ETB net benefit at Begi district. The application of 500 g ha-1 bio-fertilizerha-1 had highest net benefit. Therefore, we recommended the treatment 500 g ha-1 since it produced high marginal rate of return, high net benefit and relatively small total cost of production, for soybean production in Begi and Asossa area.
DOI: 10.20372/eiar-rdm/bqjyte/j219mb
title: Jimma and bora soybean inoculation trial field data sheet.tab

description: data collected from soybean rhizobia inoculation trial at Jimma and Bora
DOI: 10.20372/eiar-rdm/bqjyte
title: Soybean rhizobia inoculation trial

description: Data collected from field trial conducted to evaluate the response of soybean to rhizobia inoculation
DOI: 10.20372/eiar-rdm/et7w3r/axnvcn
title: Wheat Varieties.tab

description: :unav
DOI: 10.20372/eiar-rdm/et7w3r
title: Evaluation of Wheat Varieties/Lines for Salt Tolerance at Different Growth Stages

description: raw data collected to select salt tolerant wheat varieties
DOI: 10.20372/eiar-rdm/6r0qik/4eigjb
title: ISFM_Tithonia_P.tab

description: :unav
DOI: 10.20372/eiar-rdm/6r0qik
title: ISFM using P fertilizer and Tithonia biomass

description: Yield response of maize to Integrated application of Tithonia biomass and P fertilizer
DOI: 10.20372/eiar-rdm/fiy0gj/l5ea2d
title: phosphorus calibration Chickpea.tab

description: :unav
DOI: 10.20372/eiar-rdm/fiy0gj
title: Soil Test-Based Phosphorus Calibration Study for Chickpea (Cicer arietinum) on Vertisol of Dendi District Under Balanced Soil Fertilization in Central Ethiopia

description: P calibration data for chickpea on vertisol of Dendi district
DOI: 10.20372/eiar-rdm/tkbvyo/o3e3y7
title: Data of wheat.tab

description: :unav
DOI: 10.20372/eiar-rdm/tkbvyo
title: Wheat response to Urea stable

description: Raw data
DOI: 10.20372/eiar-rdm/8xm8vn/dhtli1
title: WELMERA WOREDA MPN TAG.docx

description: MPN file
DOI: 10.20372/eiar-rdm/8xm8vn
title: Welmera woreda MPN Files

description: Welmera woreda MPN Files
DOI: 10.20372/eiar-rdm/qobuej/ngpoxn
title: Effect of seed priming on germination of lentil.tab

description: :unav
DOI: 10.20372/eiar-rdm/qobuej
title: Effect of seed priming on germination of lentil

description: Seed germination of lentil as affected by seed priming
DOI: 10.20372/eiar-rdm/uygmjt/me1wyo
title: data sheet.xls

description: Tomato Crop yield data
DOI: 10.20372/eiar-rdm/uygmjt
title: Mela organics Liquid fertilizer testing result

description: New fertilizer testing field evaluation
DOI: 10.20372/eiar-rdm/pgwjmx/ka2yxw
title: MARC Sorghum OPHRA2014.xlsx

description: :unav
DOI: 10.20372/eiar-rdm/pgwjmx
title: MARC Sorghum OPRA 2014

description: Sorghum Measso data
DOI: 10.20372/eiar-rdm/ditfqk/fo6shp
title: P calibration_EIAR_Fitih.tab

description: Data collected for P calibration from 2012 to 2017 main growing season
DOI: 10.20372/eiar-rdm/ditfqk
title: Phosphorous calibration experiment data for the CRV areas of Ethiopia

description: The data was collected for a P calibration study in the CRV Andosol soil type of Ethiopia for the 2012 and 2017 growing season
DOI: 10.20372/eiar-rdm/54ttpm/xtdnym
title: climate data.tab

description: :unav
DOI: 10.20372/eiar-rdm/54ttpm/q23ein
title: climate data-1.tab

description: :unav
DOI: 10.20372/eiar-rdm/54ttpm
title: Climate data

description: Climatic data for Welmera district from 2013 to 2018
DOI: 10.5281/zenodo.7293726
title: VISEM-Tracking

description: <strong>Pre-print and citation:</strong> [Pre-print](https://arxiv.org/abs/2212.02842) <pre><code>@article{thambawita2023visem, title={VISEM-Tracking, a human spermatozoa tracking dataset}, author={Thambawita, Vajira and Hicks, Steven A and Stor{\aa}s, Andrea M and Nguyen, Thu and Andersen, Jorunn M and Witczak, Oliwia and Haugen, Trine B and Hammer, Hugo L and Halvorsen, P{\aa}l and Riegler, Michael A}, journal={Scientific Data}, volume={10}, number={1}, pages={1--8}, year={2023}, publisher={Nature Publishing Group} }</code></pre> <strong>Motivation and background</strong> Manual evaluation of a sperm sample using a microscope is time-consuming and requires costly experts who have extensive training. In addition, the validity of manual sperm analysis becomes unreliable due to limited reproducibility and high inter-personnel variations due to the complexity of tracking, identifying, and counting sperms in fresh samples. The existing computer-aided sperm analyzer systems are not working well enough for application in a real clinical setting due to unreliability caused by the consistency of the semen sample. Therefore, we need to research new methods for automated sperm analysis. <strong>Target group</strong> The task is of interest to researchers in the areas of machine learning (classification and detection), visual content analysis, and multimodal fusion. Overall, this task is intended to encourage the multimedia community to help improve the health care system through the application of their knowledge and methods to reach the next level of computer and multimedia-assisted diagnosis, detection, and interpretation. <strong>Class Label Mapping</strong><br> <em>sperm: 0<br> cluster: 1<br> small or pinhead: 2</em>
DOI: 10.5281/zenodo.7293725
title: VISEM-Tracking

description: <strong>Pre-print and citation:</strong> [Pre-print](https://arxiv.org/abs/2212.02842) <pre><code>@article{thambawita2023visem, title={VISEM-Tracking, a human spermatozoa tracking dataset}, author={Thambawita, Vajira and Hicks, Steven A and Stor{\aa}s, Andrea M and Nguyen, Thu and Andersen, Jorunn M and Witczak, Oliwia and Haugen, Trine B and Hammer, Hugo L and Halvorsen, P{\aa}l and Riegler, Michael A}, journal={Scientific Data}, volume={10}, number={1}, pages={1--8}, year={2023}, publisher={Nature Publishing Group} }</code></pre> <strong>Motivation and background</strong> Manual evaluation of a sperm sample using a microscope is time-consuming and requires costly experts who have extensive training. In addition, the validity of manual sperm analysis becomes unreliable due to limited reproducibility and high inter-personnel variations due to the complexity of tracking, identifying, and counting sperms in fresh samples. The existing computer-aided sperm analyzer systems are not working well enough for application in a real clinical setting due to unreliability caused by the consistency of the semen sample. Therefore, we need to research new methods for automated sperm analysis. <strong>Target group</strong> The task is of interest to researchers in the areas of machine learning (classification and detection), visual content analysis, and multimodal fusion. Overall, this task is intended to encourage the multimedia community to help improve the health care system through the application of their knowledge and methods to reach the next level of computer and multimedia-assisted diagnosis, detection, and interpretation. <strong>Class Label Mapping</strong><br> <em>sperm: 0<br> cluster: 1<br> small or pinhead: 2</em>
DOI: 10.15151/esrf-es-1265820306
title: samples from collaborators

description: measuring ex situ samples for users + a coin cell in operando remainng from previous experiment (MA5656 - Vostrov)
DOI: 10.15151/esrf-es-1117959526
title: Structural Biology at EMBL Grenoble, IBS-CIBB and IAB

description: This proposal clusters crystallography projects at the EMBL Grenoble, IBS and IAB working on different topics with a focus on nucleic acid-protein complexes and host-pathogen interactions. The proposers have long-standing experience in the use, as well as the development of beam lines for macromolecular crystallography and have participated in successive BAG applications over the years, mostly at the ESRF but also at other synchrotrons (i.e. Soleil, Petra II, Diamond, SLS)
DOI: 10.15151/esrf-es-1119945183
title: Synchrotron Serial Crystallography (SSX) BAG

description: The aim of this BAG is the development of new methods, hardware and software for different applications in SSX. The new EBS machine is in the privileged position of exploiting flux density previously unmatched at synchrotron beamlines. The increase in photon flux density at the sample position will interest most of the MX beamlines and it is going to be particularly effective for microfocus beamline such as ID23-2 and ID30A3. We plan to further develop different SSX data collection methods and sample delivery devices in the attempt to profit of the characteristic of the new beam and to extend the implementation of automated procedures to simplify the access to SSX methods for the MX community. The methods developed will be eventually applied to the new ID29 ESRF beamline and similar projects under development at other European sources.
DOI: 10.15151/esrf-es-1160644552
title: The Israeli BAG

description: The Israeli BAG encompass most MX groups in Israel and is highly diverse and versatile in its scientific interests and convictions. In the last year some groups which are not regarded as genuine MX have been joining our BAG as users of the bioSAXS BM29 station adding to the diversity of the BAG. It is not straightforward to set descriptive summary that covers all the topics. A central theme in several BAG members could be regarded is molecular virology such as, the molecular basis for cell entry of viruses, from the Arenaviridae family of viruses, design of Vaccines against HVC by targeting HCV E2 envelope (Env) glycoprotein for neutralizing antibodies (nanobodies). The group of Rouvunski focuses on studying arthropod borne viruses (dengue, West Nile, Zika, Israel Turkey Meningoencephalitis) and recently coronaviruses (SARS-CoV-2, MERS, OC43) and their envelope proteins. On another approach we attempt to discover therapeutics against Chikungunya Virus by targeting the Clk1.
DOI: 10.15151/esrf-es-1253274560
title: EXAFS study of Li-ion battery NMC cathodes with CeOx protective layers

description: NMC cathodes with CeOx protective layers whow imporved performance compared to non-protected cathodes. Here we study the local environment of different cathode materials with or without CeOx protection in order to understand the effects of the protective layer.
DOI: 10.4121/980484ec-5187-4f73-9e57-2e0dcd1330cc
title: Code and Data for "U-Space Utilisation of Airspace under Various Layer Function Assignments and Allocations"

description: This contains the code and output logs to run the BlueSky simulator for "U-Space Utilisation of Airspace under Various Layer Function Assignments and Allocations". The code provided here is a modified version of the main fork of BlueSky (https://github.com/TUDelft-CNS-ATM/bluesky).<br>The first step is to install the correct environment. Refer to `condaenv.txt` for the list of packages needed to run the simulator.<br>After setting up the environment, we then need to save all of the potential paths of drones in `bluesky/plugins/streets/path_plan_dills`. Note that this takes about 180GB of storage so make sure to have enough available. The paths can be downloaded from https://surfdrive.surf.nl/files/index.php/s/EcPGLvaBu7cZfTA. There are some example paths saved in this dataset but it will not be possible to run all of the experiment without downloading the paths.<br>The scenarios for sub-experiment 1 are saved in `bluesky/scenario/subexperiment1`.<br>The scenarios for sub-experiment 2 are saved in `bluesky/scenario/subexperiment2`.<br>To run the scenarios we first need to start a bluesky server by running the following code inside `bluesky`:<br>`python BlueSky.py --headless`<br>In another terminal we can start a bluesky client by running:<br>`python BlueSky.py --client`<br>In the bluesky console we can now run each batch scenario by typing and entering:<br>`batch batch_subexperiment_1.scn` or`batch batch_subexperiment_2.scn`<br>The logs of the scenarios are saved in `bluesky/output`.<br>Without the paths, it will not possible to run the simulations. However, this code currently has some paths so that it is possible to run some example scenarios. The zeroth repetition for the low imposed traffic demand case can be run without all of the paths. For example, `bluesky/scenario/subexperiment1/Flight_intention_low_40_0_1to1.scn` and `bluesky/scenario/subexperiment2/Flight_intention_low_40_0_baseline.scn` can be run directly with this dataset.<br>First start bluesky by running:<br>`python BlueSky.py`<br>In the console, type.<br>`ic subexperiment2/Flight_intention_low_40_0_baseline.scn`<br>Please do not hesistate to contact me with any questions.<br>-Andres<br><br>
DOI: 10.4121/980484ec-5187-4f73-9e57-2e0dcd1330cc.v3
title: Code and Data for "U-Space Utilisation of Airspace under Various Layer Function Assignments and Allocations"

description: This contains the code and output logs to run the BlueSky simulator for "U-Space Utilisation of Airspace under Various Layer Function Assignments and Allocations". The code provided here is a modified version of the main fork of BlueSky (https://github.com/TUDelft-CNS-ATM/bluesky).<br>The first step is to install the correct environment. Refer to `condaenv.txt` for the list of packages needed to run the simulator.<br>After setting up the environment, we then need to save all of the potential paths of drones in `bluesky/plugins/streets/path_plan_dills`. Note that this takes about 180GB of storage so make sure to have enough available. The paths can be downloaded from https://surfdrive.surf.nl/files/index.php/s/EcPGLvaBu7cZfTA. There are some example paths saved in this dataset but it will not be possible to run all of the experiment without downloading the paths.<br>The scenarios for sub-experiment 1 are saved in `bluesky/scenario/subexperiment1`.<br>The scenarios for sub-experiment 2 are saved in `bluesky/scenario/subexperiment2`.<br>To run the scenarios we first need to start a bluesky server by running the following code inside `bluesky`:<br>`python BlueSky.py --headless`<br>In another terminal we can start a bluesky client by running:<br>`python BlueSky.py --client`<br>In the bluesky console we can now run each batch scenario by typing and entering:<br>`batch batch_subexperiment_1.scn` or`batch batch_subexperiment_2.scn`<br>The logs of the scenarios are saved in `bluesky/output`.<br>Without the paths, it will not possible to run the simulations. However, this code currently has some paths so that it is possible to run some example scenarios. The zeroth repetition for the low imposed traffic demand case can be run without all of the paths. For example, `bluesky/scenario/subexperiment1/Flight_intention_low_40_0_1to1.scn` and `bluesky/scenario/subexperiment2/Flight_intention_low_40_0_baseline.scn` can be run directly with this dataset.<br>First start bluesky by running:<br>`python BlueSky.py`<br>In the console, type.<br>`ic subexperiment2/Flight_intention_low_40_0_baseline.scn`<br>Please do not hesistate to contact me with any questions.<br>-Andres<br><br>
DOI: 10.6084/m9.figshare.23626383
title: Ugt sequence data

description: UGT1A3 Sequence data- 'Influence of UGT1A3 Polymorphism on Sodium Valproate Monotherapy And Clinical Outcome in Pediatric Epileptic Patients: A Cohort study'
DOI: 10.6084/m9.figshare.23626383.v1
title: Ugt sequence data

description: UGT1A3 Sequence data- 'Influence of UGT1A3 Polymorphism on Sodium Valproate Monotherapy And Clinical Outcome in Pediatric Epileptic Patients: A Cohort study'
DOI: 10.5281/zenodo.8115535
title: Relocation of the 8 January 2022 Menyuan (Ms 6.9), China, earthquake sequence: A conjugated type of rupturing event with a seismic gap in the Haiyuan fault in northeast Tibet

description: This file is the relocated data of the 2022 Menyuan Ms 6.9 and 2016 Menyuan Ms 6.4 earthquake using Double-difference algorithm. It is only used for scientific research.
DOI: 10.5281/zenodo.8115485
title: Relocation of the 8 January 2022 Menyuan (Ms 6.9), China, earthquake sequence: A conjugated type of rupturing event with a seismic gap in the Haiyuan fault in northeast Tibet

description: This file is the relocated data of the 2022 Menyuan Ms 6.9 and 2016 Menyuan Ms 6.4 earthquake using Double-difference algorithm. It is only used for scientific research.
DOI: 10.34740/kaggle/dsv/6081479
title: Survey_on_features_of_Mobile_Phone
DOI: 10.17632/8zm7jjzmxv.1
title: The effect of Laurencia caspica algae extract on hematological, immune, antioxidant, and disease resistance of Streptococcus agalactiae in Nile tilapia (Oreochromis niloticus)

description: All data analyzed in the article.
DOI: 10.17632/8zm7jjzmxv.2
title: The effect of Laurencia caspica algae extract on hematological, immune, antioxidant, and disease resistance of Streptococcus agalactiae in Nile tilapia (Oreochromis niloticus)

description: All data analyzed in the article.
DOI: 10.23729/1ce75faa-d52a-43cd-af40-3961b3081f70
title: Fracture smectite preview

description: Fracture smectite samples from Kivetty (KI) and Romuvaara (RO). Studied for and included in: Reijonen, H., Al-Ani, T., Kuva, J., Heikkilä, P., Elminen, T., Muniruzzaman, M., Issukka, K., Lamminmäki, R. 2023. Fracture smectite in bedrock in Kivetty and Romuvaara sites, Finland as natural analogues for nuclear waste repository buffer. Submitted to Applied Clay Science. Preview of PAS-dataset https://doi.org/10.23729/72e51f01-a305-4e29-a988-66e23650c952
DOI: 10.5281/zenodo.8115382
title: A Numerical Study of Tropical Cyclone Responses to a New Air-sea Momentum Flux Scheme

description: The simulation data output from FIO-AOW for tropical cyclone study
DOI: 10.5281/zenodo.8115853
title: A Numerical Study of Tropical Cyclone Responses to a New Air-sea Momentum Flux Scheme

description: The simulation data output from FIO-AOW for tropical cyclone study
DOI: 10.3886/e184647
title: Supplementary data for: Scarred Consumption

description: We show that prior lifetime experiences can "scar" consumers. Consumers who have lived through times of unemployment exhibit persistent pessimism about their future financial situation and spend significantly less years later, controlling for income, employment, and other life-cycle consumption factors. Due to their experience-induced frugality, scarred consumers build up more wealth. We use a stochastic life-cycle model to show that financial constraints and traditional models of income and unemployment scarring fail to generate the negative relationship between past experiences and consumption, while it is consistent with experience-based learning.
DOI: 10.3886/e184647v1
title: Supplementary data for: Scarred Consumption

description: We show that prior lifetime experiences can "scar" consumers. Consumers who have lived through times of unemployment exhibit persistent pessimism about their future financial situation and spend significantly less years later, controlling for income, employment, and other life-cycle consumption factors. Due to their experience-induced frugality, scarred consumers build up more wealth. We use a stochastic life-cycle model to show that financial constraints and traditional models of income and unemployment scarring fail to generate the negative relationship between past experiences and consumption, while it is consistent with experience-based learning.
DOI: 10.3886/e184647v2
title: Supplementary data for: Scarred Consumption

description: We show that prior lifetime experiences can "scar" consumers. Consumers who have lived through times of unemployment exhibit persistent pessimism about their future financial situation and spend significantly less years later, controlling for income, employment, and other life-cycle consumption factors. Due to their experience-induced frugality, scarred consumers build up more wealth. We use a stochastic life-cycle model to show that financial constraints and traditional models of income and unemployment scarring fail to generate the negative relationship between past experiences and consumption, while it is consistent with experience-based learning.
DOI: 10.5281/zenodo.8112319
title: Data archiving for ecography

description: bird densit from bird radar and the corresponding weather radar reflectivity factor
DOI: 10.5281/zenodo.8112318
title: Data archiving for ecography

description: bird densit from bird radar and the corresponding weather radar reflectivity factor
DOI: 10.57841/casdc.0001600
title: 中国海岛植物数据集
DOI: 10.5281/zenodo.8115394
title: Data and code for gmd-2023-113 "Parameter estimation for ocean background vertical diffusivity coefficients in the Community Earth System Model (v1.2.1) and its impact on ENSO forecast"

description: Data and code for the paper "Parameter estimation for ocean background vertical diffusivity coefficients in the Community Earth System Model (v1.2.1) and its impact on ENSO forecast" includes: The model is Community Earth System Model (v1.2.1) (provided by www.cesm.ucar.edu) Data assimilation code is initially provided by Data Assimilation Research Testbed (DART) (https://dart.ucar.edu/), some modifications are made to enable parameter estimation function of ocean background vertical diffusivity coefficients. And the programs and scripts for deal with OISST and EN4 profiles are also developed. The parameter sensitivity experiment results are saved as sensitive2008-2012.nc and sensitive2008-2012salt.nc for temperature and salinity, respectively. And the python script to draw the results is The state estimation results are provided as Temp_05-17.nc and Salt_05-17.nc for temperature and salinity, respectively. The parameter estimation results are provided as PE_Temp_05-17.nc and PE_Salt_05-17.nc for temperature and salinity, respectively. the estimated paremeter ensemble is saved in parameters.nc the python script for comparing the SE and PE results is plot_analysis.py the nino3.4 indices computed by the forecast experiment is saved in fcst_correlation.nc