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  • Understanding the physico-chemical interactions on outdoor artificial aquaponics pond is the fundamental for effective nutrient dynamics in cultivating fishes and vegetable crops. The current trend of water quality monitoring is through time consuming laboratory experiments or deployment of expensive chemical sensors. This dataset contains water temperature, pH and electrical conductivity sensor-acquired data from temperature perturbed aquaponic pond water samples collected from 5 zones in a 250 cubic meter pond in Morong, Rizal, Philippines, and the corresponding dissolved organic compound namely nitrate, phosphate, and potassium absorbances and concentrations through spectrophotometry in the UV-Vis-NIR spectrum. Codes for principal component analysis in selecting the characteristic activated water bands resembling nutrient biomarkers detection, and the codes for regression based decision tree, recurrent neural network and multigene symbolic regression genetic programming for nutrient prediction were provided.
    Data Types:
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    • Software/Code
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  • Serra dos Órgãos National Park offers a unique opportunity in Brazil to study human-place relationship with wilderness areas. In this study, we explore the complexity of the meanings attached to wilderness areas and visitors’ opinions about a change in access regulations. We conducted two focus groups with wilderness visitors and used content analysis and a qualitative data analysis software, IRAMUTEQ, to analyze data. Results indicate that place meanings were created from a combination of social, environmental and experiential aspects. The threats to access and to the wilderness character led to protective attitudes and opinions, forming one of the pillars of place meaning. Concepts related to the participants' identities also shaped meanings, motivations and assessments of quality and satisfaction with the visit. Place meanings promoted a sense of the continuity of the past with the present, besides being relevant for developing and honoring social relationships. This study enables land managers to better understand the interests, needs, values and symbolism related to wilderness recreation, which can contribute to decision making about recreation policies. Data here include raw data (texts, corpus, images), coding process examples and IRAMUTEQ analysis, including statistics, word clouds, and similitude graphs. Data is in Portuguese.
    Data Types:
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    • Software/Code
    • Image
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    • Document
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  • This data set contains responses of 234 farmers regarding soil conservation intention. The survey to this data was conducted in 2019 Feb-Mar
    Data Types:
    • Software/Code
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  • Data for each figure. Plotting programs are also included.
    Data Types:
    • Software/Code
    • Dataset
  • Matlab codes developed to calculate vehicle and bridge responses (displacement, velocity, and acceleration) for a theoretical vehicle bridge interaction (VBI) system (simply supported boundary condition) reestablished to consider both the vehicle and bridge damping effects and multiple bridge vibration modes. Hypothesis: Multiple bridge dynamic information may be extracted from the vehicle that travels on it. Assumption: 1. The magnitude of the vehicle acceleration signal (gravitational direction) is negligible compared to the gravitational acceleration constant (g), say 20%; 2. Uniformly distributed bridge property (mass, damping, section stiffness); 3. Vehicle traveling speed is constant. Limit: 1. The bridge is considered as the Bernoulli-Euler beam, flexure effects caused by shear forces, rotary inertial forces, and axial forces are not considered; 2. For zero initial conditions of bridge and vehicle only; 3. Other flaws may also apply.
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  • The investigation related to these data aimed to track sources, molecular composition, and structural information of sedimentary fulvic (FA) and humic (HA) acids across a subtropical reservoir. This data set includes results from 13C nuclear magnetic resonance (13C NMR, raw spectra files), Fourier-transform ion cyclotron resonance mass spectrometry (FT-ICR-MS), organic carbon distribution (from fractionation using ultrafiltration), fluorescence and UV/VIS spectrometry. These techniques were used to investigate the origin and characteristics of FA and HA extracted from surface sediments from seven sampling sites (P1-P7) in Itupararanga Reservoir (Brazil). The results showed that samples from the upstream part of the reservoir (P1-P2) have more aromatic, oxygen-poor (O/C ratio 0.5) and partly more unsaturated compounds for FA as well as oxygen-poor and saturated compounds with H/C > 1.1 for HA. Many oxygen-poor molecules were present in HA samples but in none of the FA samples.
    Data Types:
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    • Software/Code
    • Image
    • Tabular Data
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    • Document
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  • A deep learning database and network for focusing guided wave defect detection Since the paper is being submitted, the database set will be published after the paper is accepted. Database set information:The defects are classified as three types and specimens with no defect are also included. In the established database set, the defect depth ranges from 10% to 50%, with 10% intervals. In addition, the radius of the pinhole defect ranges from 0.5 mm to 3 mm, and the sizes of the crack defect range from 1×5 mm2 to 2×10 mm2, and the sizes of the corrosion defect range from 5×5 mm2 to 10×10 mm2. Each defect contains 1500 signal data, and the ratio of the training, validation, and test data sets are divided into 6:2:2 in this work. The data storage format and explain the descriptive data (take the pinhole defect signal with a radius of 3 mm and a depth of 10% as an example). The data set has a total of 48,060,000 signal value data and contains detailed information about defects. No. 1 2 3 4 5 6 7 8 9 10 11 12 13 14 ··· Data -1 1 0 0 3 10 0 0 0 -2 0 0 0 0 ··· Title: Development of frequency-mixed point-focusing SH guided wave EMAT for defect inspection using deep neural network Author: Hongyu Sun, Songling Huang, State Key of Power Systems, Department of Electrical Engineering, Tsinghua University, Beijing, 10084, China. Email: sunhy18@mails.tsinghua.edu.cn If you use our code and database set, please cite our paper [however, not published]. NOTICE: Reviewers can obtain the data set password from the end of the paper's Abstract to run the code. Development environment: TensorFlow 2.2 CUDA 10.1 Python 3.7
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    • File Set
  • The data consist of an application, namely PyFEST, written in Python language, and a file with instructions to install and use the application. It can be used to estimate the frequencies of short-time signals with high accuracy. Along with the application, examples with generated signal (single-ton, multi-tone, noisy, damped etc.) and measured signals are delivered for testing purposes. The frequencies of the harmonic components are evaluated one-by-one with high accuracy. Because the actions performed do not imply previous expertise, the results are not influenced by human intervention.
    Data Types:
    • Other
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    • Text
  • Our research conducts a large-scale survey on elementary and secondary school students in China, where has been highly influenced by the disease.
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    • Software/Code
    • Dataset
  • Background. Downs syndrome (DS) is the commonest of the congenital genetic defects. Its incidence has been rising in recent years for unknown reasons. Objective. Investigate the relationship of DS to substance- and cannabinoid- exposure; and causality. Methods. Observational ecological population-based epidemiological study 1986-2016. Analysis performed January 2020. Geotemporospatial and causal inference analysis. Participants: Patients were diagnosed with DS and reported to state based registries; collated nationally. Data source: annual reports of National Birth Defects Prevention Network of Centres for Disease Control. Exposures: Drug exposure was taken from the National Survey of Drug Use and Health (NSDUH) conducted annually by Substance Abuse and Mental Health Services Administration. Nationally representative sample 67,000 participants annually. Drug exposures: cigarette consumption, alcohol abuse, analgesic/opioid abuse, cocaine use and last month cannabis use. Ethnicity and median household income: US Census Bureau. Maternal age of childbearing: CDC births registries. Cannabinoid concentrations: Drug Enforcement Agency seizures. Results. NSDUH report 74.1% mean annual response rate. All other data was population-wide. DS rate (DSR) was noted to be rising over time, cannabis use, and cannabis-use quintile. In the optimal geospatial model lagged to four years terms including Δ9-tetrahydrocannabinol and cannabigerol were significant (from β-est.=4189.96 (95%C.I. 1924.74, 6455.17), P=2.9x10-4). Ethnicity, income, and maternal age covariates were not significant. DSR in states where cannabis was not illegal was higher than elsewhere (β-est.=2.160 (1.5, 2.82), R.R.=1.81 (1.51, 2.16), P=4.7x10-10). In inverse probability-weighted mixed models terms including cannabinoids were significant (from β-estimate=18.82 (16.82, 20.82), P<0.0001). EValues in geospatial models ranged up to infinity. Conclusions. Our data show that the association between DSR and substance- and cannabinoid- exposure is robust to multivariable geotemporospatial adjustment, implicate particularly cannabigerol and Δ9-tetrahydrocannabinol, and fulfil causal crietria. Cannabis legalization was associated with elevated DSR’s. These findings are consistent with those from Hawaii, Colorado, Canada and Australia and concordant with several cellular mechanisms. Given that the cannabis industry is presently in a rapid growth-commercialization phase the present findings linking cannabis use with megabase scale genotoxicity suggest unrecognized DS risk factors, are of public health importance and suggest that re-focussing the cannabis debate on multigenerational and intergenerational health concerns is prudent.
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    • Geospatial Data
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