cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.6084/m9.figshare.20326188.v1
title: Game_Data_full.xlsx

description: <strong>Data for:</strong> Sargent, R., Rakotonarivo, O.S., Rushton, S.P., Cascio, B., Grau, A., Bell, A.R., Bunnefeld, N., Dickman, A. & Pfeifer, M. (2022) An experimental game to examine pastoralists' preferences for human-lion coexistence strategies. <em>People and Nature.</em> Data includes all game and questionnaire response and column descriptions. <br> <strong>Abstract</strong> 1. Reconciling conflicts between wildlife conservation and other human activities is a pervasive, multifaceted issue. Large carnivores, such as the African lion (<em>Panthera leo</em>) are often the focus of such conflicts as they have significant ecological and cultural value but impose severe social and financial costs on the communities that live alongside them. 2. To effectively manage human-lion conflict, it is vital to understand stakeholder decision-making and preferences regarding mitigation techniques and coexistence strategies. 3. We used a novel experimental game framed around lions and livestock protection, played across eight villages in Tanzania, to examine stakeholder behaviour in response to three incentive structures: support for non-lethal scaring, and individual- and community-level subsidies for provision of wildlife habitat. 4. We found that non-lethal deterrent methods were the preferred mitigation strategy and that individual subsidies most increased the provision of wildlife habitat. Subsidies that were conditional on other community members’ decisions were less effective at increasing habitat choices. Player characteristics and attitudes appeared to have little influence on game behaviour. However, there was some evidence that gender, wealth, perceptions of respect, and the behaviour of other players affected decision-making. 5. Achieving success in managing conservation conflicts requires genuine stakeholder participation leading to mutually beneficial results. Our findings suggest that, while incentive-based instruments can promote pro-conservation behaviour, these may be more effective when targeted at individuals rather than groups. We demonstrate how experimental games offer a practical and engaging approach that can be used to explore preferences and encourage discussion of conflict management.
DOI: 10.34740/kaggle/dsv/3953177
title: YouTube Trending Video Dataset (updated daily)
DOI: 10.5281/zenodo.5498348
title: Dataset for "Comparative Analysis of Machine Learning Models to Forecast Flaring Capability of Solar Active Regions: A Parameter Based Approach"

description: This CSV file contains the values of 14 selected magnetic features along with the active region class for all the regions used in our study. As discussed in the paper, these 14 magnetic features characterize the properties of active regions. All these magnetic features are obtained from the HMI SHARP data series which provides open-sourced vector magnetic field information of solar active regions. the column named 'AR_class' carries information about the class of active regions i.e., 1 for flaring regions and 0 for non-flaring regions.
DOI: 10.5281/zenodo.5498347
title: Dataset for "Comparative Analysis of Machine Learning Models to Forecast Flaring Capability of Solar Active Regions: A Parameter Based Approach"

description: This CSV file contains the values of 14 selected magnetic features along with the active region class for all the regions used in our study. As discussed in the paper, these 14 magnetic features characterize the properties of active regions. All these magnetic features are obtained from the HMI SHARP data series which provides open-sourced vector magnetic field information of solar active regions. the column named 'AR_class' carries information about the class of active regions i.e., 1 for flaring regions and 0 for non-flaring regions.
DOI: 10.5281/zenodo.6850001
title: Training Data for Decision Tree Practical in reading-ml-chemistry repo

description: This is a dataset that can be used to train a decision tree to predict the band gap of a material. The data is associated with a notebook for running the practical and it can be found at https://github.com/keeeto/reading-ml-chemistry. The data originally comes from the Materials Project. A new muon spectroscopy dataset is added. It is from - Machine learning approach to muon spectroscopy analysis - https://iopscience.iop.org/article/10.1088/1361-648X/abe39e/meta
DOI: 10.5281/zenodo.4450206
title: Training Data for Decision Tree Practical in reading-ml-chemistry repo

description: This is a dataset that can be used to train a decision tree to predict the band gap of a material. The data is associated with a notebook for running the practical and it can be found at https://github.com/keeeto/reading-ml-chemistry. The data originally comes from the Materials Project. A new muon spectroscopy dataset is added. It is from - Machine learning approach to muon spectroscopy analysis - https://iopscience.iop.org/article/10.1088/1361-648X/abe39e/meta
DOI: 10.34740/kaggle/dsv/3953196
title: 2021 World Population (updated daily)
DOI: 10.5281/zenodo.6850010
title: paramphy/SCAPS1D-material_database: Initial release

description: A collection of material files for SCAPS1D simulation.
DOI: 10.5281/zenodo.6850009
title: paramphy/SCAPS1D-material_database: Initial release

description: A collection of material files for SCAPS1D simulation.
DOI: 10.34740/kaggle/dsv/3953223
title: TimeSeries
DOI: 10.5281/zenodo.6850066
title: Mapping Study Document

description: Document for the mapping study
DOI: 10.34740/kaggle/dsv/3953184
title: Natural gas prices with Twitter sentiment scores
DOI: 10.5281/zenodo.6849988
title: Animal Recognition Using Methods Of Fine-Grained Visual Analysis - Kashtanka Pets (All Dev and Test Images, Single Folder)

description: Kashtanka Pets images, with all Dev and Test images (total 66639 images). In a single folder, with filenames indicating path of file in original dataset distribution.
description: {"references": ["kashtanka.pet"]}
DOI: 10.5281/zenodo.6849987
title: Animal Recognition Using Methods Of Fine-Grained Visual Analysis - Kashtanka Pets (All Dev and Test Images, Single Folder)

description: Kashtanka Pets images, with all Dev and Test images (total 66639 images). In a single folder, with filenames indicating path of file in original dataset distribution.
description: {"references": ["kashtanka.pet"]}
DOI: 10.5281/zenodo.6849958
title: Animal Recognition Using Methods Of Fine-Grained Visual Analysis - YOLOv5 Breed Classification Dataset (Tsinghua Dogs)

description: Tsinghua Dogs Dataset with ground truth labels for breeds in YOLOv5 format.
description: {"references": ["Zou, DN., Zhang, SH., Mu, TJ.\u00a0et al.\u00a0A new dataset of dog breed images and a benchmark for finegrained classification.\u00a0Comp. Visual Media\u00a06,\u00a0477\u2013487 (2020). https://doi.org/10.1007/s41095-020-0184-6"]}
DOI: 10.5281/zenodo.6849957
title: Animal Recognition Using Methods Of Fine-Grained Visual Analysis - YOLOv5 Breed Classification Dataset (Tsinghua Dogs)

description: Tsinghua Dogs Dataset with ground truth labels for breeds in YOLOv5 format.
description: {"references": ["Zou, DN., Zhang, SH., Mu, TJ.\u00a0et al.\u00a0A new dataset of dog breed images and a benchmark for finegrained classification.\u00a0Comp. Visual Media\u00a06,\u00a0477\u2013487 (2020). https://doi.org/10.1007/s41095-020-0184-6"]}
DOI: 10.5281/zenodo.6850085
title: Mapping Study Document

description: Document for the mapping study
DOI: 10.5281/zenodo.6849931
title: Animal Recognition Using Methods Of Fine-Grained Visual Analysis - YOLOv5 Breed Classification Dataset (Oxford-IIIT Pet)

description: Oxford-IIIT Pet Dataset with ground truth labels for breeds (from https://public.roboflow.com/object-detection/oxford-pets).
description: {"references": ["https://public.roboflow.com/object-detection/oxford-pets"]}
DOI: 10.5281/zenodo.6849930
title: Animal Recognition Using Methods Of Fine-Grained Visual Analysis - YOLOv5 Breed Classification Dataset (Oxford-IIIT Pet)

description: Oxford-IIIT Pet Dataset with ground truth labels for breeds (from https://public.roboflow.com/object-detection/oxford-pets).
description: {"references": ["https://public.roboflow.com/object-detection/oxford-pets"]}
DOI: 10.5281/zenodo.6849907
title: Animal Recognition Using Methods Of Fine-Grained Visual Analysis - Kashtanka Pets (200 Hand-labelled Images, Cats and Dogs, Separate Folders)

description: 400 images (200 cats, 200 dogs) hand-labelled by Maria E. with head and body bounding box labels in YOLOv5 format. Images for cats, for dogs are in a separate folders.
description: {"references": ["kashtanka.pet"]}
DOI: 10.5281/zenodo.6849906
title: Animal Recognition Using Methods Of Fine-Grained Visual Analysis - Kashtanka Pets (200 Hand-labelled Images, Cats and Dogs, Separate Folders)

description: 400 images (200 cats, 200 dogs) hand-labelled by Maria E. with head and body bounding box labels in YOLOv5 format. Images for cats, for dogs are in a separate folders.
description: {"references": ["kashtanka.pet"]}
DOI: 10.5281/zenodo.6848816
title: Animal Recognition Using Methods Of Fine-Grained Visual Analysis - YOLOv5 Object Detection Dataset (Oxford-IIIT Pet)

description: Preprocessed dataset for Oxford-IIIT Pet in YOLOv5 format.. Ground truth labels for head bounding boxes, body bounding boxes (derived from segmentation mask).
description: {"references": ["Parkhi, Omkar M., et al. \"Cats and dogs.\" 2012 IEEE conference on computer vision and pattern recognition. IEEE, 2012."]}
DOI: 10.5281/zenodo.6848815
title: Animal Recognition Using Methods Of Fine-Grained Visual Analysis - YOLOv5 Object Detection Dataset (Oxford-IIIT Pet)

description: Preprocessed dataset for Oxford-IIIT Pet in YOLOv5 format.. Ground truth labels for head bounding boxes, body bounding boxes (derived from segmentation mask).
description: {"references": ["Parkhi, Omkar M., et al. \"Cats and dogs.\" 2012 IEEE conference on computer vision and pattern recognition. IEEE, 2012."]}
DOI: 10.5281/zenodo.6848854
title: Animal Recognition Using Methods Of Fine-Grained Visual Analysis - YOLOv5 Object Detection Dataset (Tsinghua Dogs)

description: Preprocessed dataset for Tsinghua Dogs in YOLOv5 format.. Ground truth labels for head bounding boxes, body bounding boxes
description: {"references": ["Zou, DN., Zhang, SH., Mu, TJ.\u00a0et al.\u00a0A new dataset of dog breed images and a benchmark for finegrained classification.\u00a0Comp. Visual Media\u00a06,\u00a0477\u2013487 (2020). https://doi.org/10.1007/s41095-020-0184-6"]}
DOI: 10.5281/zenodo.6848853
title: Animal Recognition Using Methods Of Fine-Grained Visual Analysis - YOLOv5 Object Detection Dataset (Tsinghua Dogs)

description: Preprocessed dataset for Tsinghua Dogs in YOLOv5 format.. Ground truth labels for head bounding boxes, body bounding boxes
description: {"references": ["Zou, DN., Zhang, SH., Mu, TJ.\u00a0et al.\u00a0A new dataset of dog breed images and a benchmark for finegrained classification.\u00a0Comp. Visual Media\u00a06,\u00a0477\u2013487 (2020). https://doi.org/10.1007/s41095-020-0184-6"]}
DOI: 10.5281/zenodo.6849903
title: Animal Recognition Using Methods Of Fine-Grained Visual Analysis - Kashtanka Pets (400 Hand-labelled Images - Cats & Dogs, Single Folder)

description: 400 images (200 cats, 200 dogs) hand-labelled by Maria E. with head and body bounding box labels in YOLOv5 format. Images are in a single folder, no separate folders for cats and dogs.
description: {"references": ["kashtanka.pet"]}
DOI: 10.5281/zenodo.6849902
title: Animal Recognition Using Methods Of Fine-Grained Visual Analysis - Kashtanka Pets (400 Hand-labelled Images - Cats & Dogs, Single Folder)

description: 400 images (200 cats, 200 dogs) hand-labelled by Maria E. with head and body bounding box labels in YOLOv5 format. Images are in a single folder, no separate folders for cats and dogs.
description: {"references": ["kashtanka.pet"]}
DOI: 10.34740/kaggle/dsv/3953309
title: COVID Vaccination in World (updated daily)
DOI: 10.18112/openneuro.ds004208.v1.0.0
title: An fMRI Dataset for Concept Representation with semantic feature annotations
DOI: 10.5281/zenodo.5433974
title: Linear-time Temporal Logic guided Greybox Fuzzing

description: The LTL-Fuzzer tool, built on top of the AFL fuzzer, is found to be effective in detecting bugs in well-known protocol implementations, such as OpenSSL and Telnet. We use LTL-Fuzzer to reproduce known vulnerabilities (CVEs), to find new or zero-day bugs by checking properties extracted from RFCs (for which CVEs have been assigned), and to find violations of both safety as well as liveness properties in real-world protocol implementations. This package contains the LTL-Fuzzer tool and data-set in our experiments.
DOI: 10.5281/zenodo.5370735
title: Linear-time Temporal Logic guided Greybox Fuzzing

description: The LTL-Fuzzer tool, built on top of the AFL fuzzer, is found to be effective in detecting bugs in well-known protocol implementations, such as OpenSSL and Telnet. We use LTL-Fuzzer to reproduce known vulnerabilities (CVEs), to find new or zero-day bugs by checking properties extracted from RFCs (for which CVEs have been assigned), and to find violations of both safety as well as liveness properties in real-world protocol implementations. This package contains the LTL-Fuzzer tool and data-set in our experiments.
DOI: 10.6084/m9.figshare.20326380
title: Dataset of drought-rewatering experiment on five subtropical tree species

description: Dataset for the manuscript <em>Embolism resistance explains mortality and recovery of five subtropical evergreen broadleaf trees to persistent drought</em>
DOI: 10.6084/m9.figshare.20326377
title: A thundercloud rader results during the experiment

description: This dataset contains a series of results from a Doppler weather radar. There are eleven datas with 8 sets of datetime (local time) at different longitude and latitude, as shown in “Latitude_data.csv”, 'Longitude_data.csv'' and “DWR_date.csv”.
DOI: 10.6084/m9.figshare.20326377.v1
title: A thundercloud rader results during the experiment

description: This dataset contains a series of results from a Doppler weather radar. There are eleven datas with 8 sets of datetime (local time) at different longitude and latitude, as shown in “Latitude_data.csv”, 'Longitude_data.csv'' and “DWR_date.csv”.
DOI: 10.6084/m9.figshare.20324556
title: vcf files for SNPs and INDELs

description: vcf files for SNPs and INDELs
DOI: 10.34740/kaggle/dsv/3953690
title: Mahanagar Yatayat Dataset
DOI: 10.21223/7qy6ku/hb9c7z
title: Data_SIF.tab

description: :unav
DOI: 10.21223/7qy6ku/wyfvnw
title: Data_Dictionary.xlsx

description: :unav
DOI: 10.21223/7qy6ku/eugylg
title: Data_Temp.tab

description: :unav
DOI: 10.21223/7qy6ku/tabcry
title: 02_Data_Temp-Control.tab

description: :unav
DOI: 10.21223/7qy6ku/lsyvd8
title: 03_Data_SIF.tab

description: :unav
DOI: 10.21223/7qy6ku/w8t75x
title: 01_Data_Fs_250717.tab

description: :unav
DOI: 10.21223/7qy6ku/dgxsms
title: 01_Data_Fs_240717.tab

description: :unav
DOI: 10.21223/7qy6ku/j2vvuh
title: 02_Data_Temp_Stress.tab

description: :unav
DOI: 10.21223/7qy6ku/fxvkw0
title: 01_Data_Fs_160717.tab

description: :unav
DOI: 10.21223/7qy6ku/1nakff
title: 04_Data_Dictionary.tab

description: :unav
DOI: 10.21223/7qy6ku
title: Dataset for: Active in situ and passive airborne fluorescence measurements for water stress detection on a fescue field

description: It was a water stress experiment conducted during summer in a Mediterranean area (Barrax - Spain). It was composed of two treatments: control and water stress. We used Ledflex, a fluorimeter adapted to measure chlorophyll fluorescence at canopy level. It has been fully described in Moya et al. (2019), Photosynthesis Research. DOI: 10.1007/s11120-019-00642-9. This instrument was placed in the stress trial and It allowed to determine the effect of water stress on fluorescence of a fescue field under extreme conditions of temperature and light. In addition to the fluorescence data, surface temperature was also measured in both treatments using infrared radiometers. Last but not least "Airflex", described by Daumard et al., (2015), IEEE Transactions on Geoscience and Remote Sensing. DOI: 10.1109/TGRS.2015.2418992, a passive fluorimeter measuring the filling-in of the atmospheric oxygen absorption band at 760 nm was installed in an ultralight plane and flown during the most critical days of the campaign over the control and water stress treatments.
DOI: 10.5517/ccdc.csd.cc1n3ddk
title: CCDC 1522608: Experimental Crystal Structure Determination

description: Related Article: Yahia Nasser Mabkhot Gabr, Jamal Mohammed Ali Khaled, Mujeeb Abdullah Saeed Sultan, Salim S. Al-Showiman, Naiyf Sultan Helial Alaloi Alharbi, Hazem Ahmed Ghabbour|2018|U.S.Patents|||
description: Related Article: Yahia N. Mabkhot, Jamal M.A. Khaled, Mujeeb A.S. Sultan, Naiyf S.H.A. Alharbi, Salim S. Al-Showiman, Hazem A. Ghabbour, Abdulrahman Alsayari, Abdullatif Bin Muhsinah, H. Algarni|2019|Bioorg.Chem.|91|103157|doi:10.1016/j.bioorg.2019.103157
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: 10.5281/zenodo.6850537
title: Corydoras paleatus decontaminated gx

description: .
DOI: 10.5281/zenodo.6850536
title: Corydoras paleatus decontaminated gx

description: .
DOI: 10.5281/zenodo.6850557
title: Gallinago stenura decontaminated gx

description: .
DOI: 10.5281/zenodo.6850556
title: Gallinago stenura decontaminated gx

description: .
DOI: 10.21223/5rl85w/ktmsaa
title: Data_Dictionary_ChlF.xlsx

description: :unav
DOI: 10.21223/5rl85w/qrcbeq
title: 01_Data_SIF_LIF_56DAP.tab

description: :unav
DOI: 10.21223/5rl85w/m6w9ua
title: 01_Data_SIF_LIF_73DAP.tab

description: :unav
DOI: 10.21223/5rl85w/vojdkh
title: 01_Data_SIF_LIF_57DAP.tab

description: :unav
DOI: 10.21223/5rl85w/hoeqcz
title: 01_Data_SIF_LIF_74DAP.tab

description: :unav
DOI: 10.21223/5rl85w/kdr8fg
title: 01_Data_SIF_LIF_53DAP.tab

description: :unav
DOI: 10.21223/5rl85w/76pw8u
title: 01_Data_SIF_LIF_52DAP.tab

description: :unav
DOI: 10.21223/5rl85w/eb7cam
title: 01_Data_SIF_LIF_82DAP.tab

description: :unav
DOI: 10.21223/5rl85w/mayx6x
title: 01_Data_SIF_LIF_64DAP.tab

description: :unav
DOI: 10.21223/5rl85w/ymh49a
title: 01_Data_SIF_LIF_51DAP.tab

description: :unav
DOI: 10.21223/5rl85w/mj8pcv
title: 01_Data_SIF_LIF_80DAP.tab

description: :unav
DOI: 10.21223/5rl85w/xtduts
title: 01_Data_SIF_LIF_48DAP.tab

description: :unav
DOI: 10.21223/5rl85w/si94zq
title: 01_Data_SIF_LIF_81DAP.tab

description: :unav
DOI: 10.21223/5rl85w/qpg7xd
title: 02_Data_Dictionary.tab

description: :unav
DOI: 10.5281/zenodo.6850563
title: Hippopotamyrus pictus decontaminated gx

description: .
DOI: 10.5281/zenodo.6850562
title: Hippopotamyrus pictus decontaminated gx

description: .
DOI: 10.5281/zenodo.6827865
title: Dynamic regimes of the Greenland Ice Sheet emerging from interacting melt-elevation and glacial isostatic adjustment feedbacks - Dataset

description: Research data for the publication "Dynamic regimes of the Greenland Ice Sheet emerging from interacting melt-elevation and glacial isostatic adjustment feedbacks" by Maria Zeitz, Jan M. Haacker, Jonathan F. Donges, Torsten Albrecht, and Ricarda Winkelmann, accepted for Earth System Dynamics in 2022. Find the output of the simulations with the Parallel Ice Sheet Model PISM in the pism_out* archives, the binary, the run scripts, the input data and the analysis scripts in the "other" archive.
DOI: 10.5281/zenodo.6827864
title: Dynamic regimes of the Greenland Ice Sheet emerging from interacting melt-elevation and glacial isostatic adjustment feedbacks - Dataset

description: Research data for the publication "Dynamic regimes of the Greenland Ice Sheet emerging from interacting melt-elevation and glacial isostatic adjustment feedbacks" by Maria Zeitz, Jan M. Haacker, Jonathan F. Donges, Torsten Albrecht, and Ricarda Winkelmann, accepted for Earth System Dynamics in 2022. Find the output of the simulations with the Parallel Ice Sheet Model PISM in the pism_out* archives, the binary, the run scripts, the input data and the analysis scripts in the "other" archive.
DOI: 10.5281/zenodo.6850573
title: Parsonsia alboflavescens decontaminated gx

description: .
DOI: 10.5281/zenodo.6850572
title: Parsonsia alboflavescens decontaminated gx

description: .
DOI: 10.5281/zenodo.6850605
title: High-surface-area corundum nanoparticles by PDC process

description: Source data for "High-surface-area corundum nanoparticles by resistive hotspot-induced phase transformation".
DOI: 10.5281/zenodo.6850604
title: High-surface-area corundum nanoparticles by PDC process

description: Source data for "High-surface-area corundum nanoparticles by resistive hotspot-induced phase transformation".
DOI: 10.6084/m9.figshare.20323416
title: surrogate responses and sotrovimab

description: - accessions_metadata_nopatid.tsv contains the accession id, the day and treatment information - counts.tsv contains the tpm (transcripts per million) matrix for the respective accession ids.
DOI: 10.6084/m9.figshare.20323416.v1
title: surrogate responses and sotrovimab

description: - accessions_metadata_nopatid.tsv contains the accession id, the day and treatment information - counts.tsv contains the tpm (transcripts per million) matrix for the respective accession ids.
DOI: 10.5281/zenodo.6850643
title: Deroptyus accipitrinus decontaminated gx

description: .
DOI: 10.5281/zenodo.6850642
title: Deroptyus accipitrinus decontaminated gx

description: .
DOI: 10.5281/zenodo.6850680
title: Poicephalus cryptoxanthus zanfona 1

description: .
DOI: 10.5281/zenodo.6850679
title: Poicephalus cryptoxanthus zanfona 1

description: .
DOI: 10.5281/zenodo.6850713
title: Pyrrhura hoffmanni zanfona 1

description: .
DOI: 10.5281/zenodo.6850712
title: Pyrrhura hoffmanni zanfona 1

description: .
DOI: 10.6084/m9.figshare.19221678.v4
title: Discrete emotions for Croatian: CROWD-5e dataset.xlsx

description: Normative database for 3,022 Croatian words rated on five discrete emotions: happiness, fear, anger, sadness & disgust. <br>Manuscript: CROWD-5e: A 3,022 Croatian words psycholinguistic database covering affective norms for five discrete emotions<br>
DOI: 10.6084/m9.figshare.19221678.v5
title: Discrete emotions for Croatian: CROWD-5e dataset.xlsx

description: Normative database for 3,022 Croatian words rated on five discrete emotions: happiness, fear, anger, sadness & disgust. <br>Manuscript: CROWD-5e: A 3,022 Croatian words psycholinguistic database covering affective norms for five discrete emotions<br>
DOI: 10.34740/kaggle/dsv/3953977
title: ECB speeches etc. 1997 to 2022-07-17
DOI: 10.25919/wmmf-3m51
title: Parkes observations for project P1032 semester 2022APRS_04

description: This project aims to continue to perform rapid measurements of relativistic parameters of southern binary pulsar systems using data from the Parkes Ultra Wideband Low (UWL) receiver and the MeerKAT telescope thereby enabling measurement of their component masses and in some cases, test theories of gravity. We will use the UWL data to obtain significant orbital coverage and timing baseline on these pulsars and obtain important constraints on orbital and temporal DM variations that will help in identifying the nature of the companion star. We will then use MeerKAT data at crucial orbital phases to improve our chances of measuring the relativistic parameters. Increase in the number of measured NS masses has profound implications for NS internal structure and for stellar and binary evolution physics.
DOI: 10.34740/kaggle/dsv/3953984
title: www.haonature.com