cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.17614/q4tt4g574
title: 7-hydroxy-8-oxo-12,13-epoxytrichothec-9-ene-3,15-diyl diacetate
DOI: 10.17614/q4vm43875
title: ethyl (2s)-2-hydroxy-4-methylpentanoate
DOI: 10.17614/q4vm43b0p
title: (1r,3s,5z)-5-[(2e)-2-{(1r,3as,7ar)-1-[(2r,3e)-9-hydroxy-9-methyl-3-decen-2-yl]-7a-methyloctahydro-4h-inden-4-ylidene}ethylidene]-4-methylene-1,3-cyclohexanediol
DOI: 10.17614/q4vm43b6k
title: mallotojaponin c
DOI: 10.17614/q4vx06h36
title: n-(9,10-dioxo-9,10-dihydro-2-anthracenyl)benzamide
DOI: 10.17614/q4wm14779
title: methyl 5-benzyl-2-hydroxy-11-methylene-6-oxo-5h-benzo(b)carbazole-1-carboxylate
DOI: 10.17614/q4wp9tk9r
title: indophenol
DOI: 10.17614/q4x34n50h
title: 3-nitroso-1,3-oxazolidine
DOI: 10.17614/q4xk85324
title: chlorobenzilate
DOI: 10.17614/q4z02zq1d
title: 5,9-dimethyl-2h-furo[2,3-h]chromen-2-one
DOI: 10.17614/q4zc7s873
title: s-[(z)-(hydroxyimino)(4-methylphenyl)methyl] (diethylamino)ethanethioate
DOI: 10.17614/q4zg6gk8j
title: 2,5-dichlorophenol
DOI: 10.17614/q40v89w4f
title: 4-amino-4,6-dideoxy-beta-d-glucopyranose
DOI: 10.17614/q41c1tt6j
title: 1-[2-(benzhydryloxy)ethyl]-4-(3-phenylpropyl)piperazine
DOI: 10.17614/q41r6nf67
title: (3s)-n-[2-(benzylamino)-2-oxoethyl]-2-(2,6-dimethyl-l-tyrosyl)-1,2,3,4-tetrahydro-3-isoquinolinecarboxamide
DOI: 10.17614/q4251g12d
title: isoamyl valerate
DOI: 10.17614/q42f7k52g
title: n-[(e)-2-(2,5-dihydroxyphenyl)vinyl]formamide
DOI: 10.17614/q4348gt87
title: 1-[(4as,5r,7s,8ar)-5-{[(1r,2s,5s,9s,11r,13s,17r)-2-hydroxy-11,14-dimethyl-6,14-diazatetracyclo[7.6.2.0~2,7~.0~13,17~]heptadec-6-en-5-yl]methyl}-7-methyloctahydro-1(2h)-quinolinyl]ethanone
DOI: 10.17614/q4348gw7n
title: (2s,3s,4r,5r)-2-(4-aminophenyl)-5-(hydroxymethyl)-3,4-pyrrolidinediol
DOI: 10.17614/q4377678z
title: estradiol 17.beta.-valerate
DOI: 10.17614/q44m91p8k
title: 4-amino-4,6-dideoxy-alpha-d-glucopyranose
DOI: 10.17614/q4513v79b
title: (3beta,6alpha,12beta)-3,12,20-trihydroxydammar-24-en-6-yl beta-d-glucopyranoside
DOI: 10.17614/q45h7c800
title: 2-(3,4-dichlorophenyl)-n-[(1r,2r)-5-methoxy-2-(1-pyrrolidinyl)-1,2,3,4-tetrahydro-1-naphthalenyl]-n-methylacetamide
DOI: 10.17614/q45x25s4d
title: 22beta-hydroxycholesterol
DOI: 10.17614/q45x25t79
title: 8-oxoguanine
DOI: 10.17632/ntmjhxbnwr.1
title: Arduino Code for: Low Cost-tech and no Tech Solutions for Assessing Likelihood of Impact for Tree Risk Assessment

description: Most tree risk assessment methods task the assessor with the evaluation of a trees’ likelihood of impact (i.e., the likelihood a target will be present if a tree fails) when determining the probability that an adverse event will occur. While this is generally accomplished in a qualitative manner based on visual cues, site occupancy, a key component of likelihood of impact, can often be directly measured with traffic counters. The use of traffic counters could potentially reduce risk assessment bias and increase reproducibility, though commercially-available devices may be cost-prohibitive. This work addresses one potential barrier to traffic counter adoption through the creation of a low-cost vehicle and pedestrian counting system. In this study, we compare the accuracy and consistency of a low-cost, homemade traffic counting system to estimates derived from a commercially available system, as well as, actual vehicle and pedestrian counts tallied by a hand clicker.
DOI: 10.17632/2c3kzy4v93.3
title: Drains, Sanitation and Health in Uttarakhand, India

description: Primary survey data of 1530 households from the state of Uttarakhand, India on individual health (specifically water-borne disease), household and village attributes, and sanitation quality (including drain quality, toilets, open-defecation). Survey date, November 2004 - January 2005.
DOI: 10.17632/3s5yzcy2mc.1
title: Urbanization Favourability Mapping

description: Matlab code
DOI: 10.17632/8y55zscjd3.1
title: MFC: An open-source high-order multi-component, multi-phase, and multi-scale compressible flow solver

description: MFC is an open-source tool for solving multi-component, multi-phase, and bubbly compressible flows. It is capable of efficiently solving a wide range of flows, including droplet atomization, shock–bubble interaction, and bubble dynamics. We present the 5- and 6-equation thermodynamically-consistent diffuse-interface models we use to handle such flows, which are coupled to high-order interface-capturing methods, HLL-type Riemann solvers, and TVD time-integration schemes that are capable of simulating unsteady flows with strong shocks. The numerical methods are implemented in a flexible, modular framework that is amenable to future development. The methods we employ are validated via comparisons to experimental results for shock–bubble, shock–droplet, and shock–water-cylinder interaction problems and verified to be free of spurious oscillations for material-interface advection and gas–liquid Riemann problems. For smooth solutions, such as the advection of an isentropic vortex, the methods are verified to be high-order accurate. Illustrative examples involving shock–bubble-vessel-wall and acoustic–bubble-net interactions are used to demonstrate the full capabilities of MFC.
DOI: 10.17632/wswkrcydmd.1
title: HWC behavior in China

description: A questionnaire survey using a sample of 604 residents from urban and rural areas.
DOI: 10.17632/sysyspmjdz.1
title: Reducción del churn a través de modelos predictivos

description: Código separado en 5 archivos .py Resultados del código para cada planteamiento recogidos en 2 archivos .xlsx El código de ejecución de las estrategias se denomina: Ensamble_Submuestras.py y Oversampling_SMOTE.py Dicho código necesita de los archivos f_analisis.py que contiene funciones y clases creadas para desempeñar de forma más rápida el análisis de datos, f_ESubmuestras.py que contiene las funciones y clases creadas para el desarrollo de la estrategia del Ensamble de Submuestras , y f_O_SMOTE.py,que contiene las funciones y clases creadas para el desarrollo de la estrategia del Oversampling con SMOTE. Resultados de ensamble de estimadores para cada planteamiento: Ensamble_Submuestras -&gt; ES_21_Resultado_Abanico.xlsx Oversampling_SMOTE -&gt; SMOTE_TR_Resultado_Abanico.xlsx
DOI: 10.17632/vptywz7dpr.9
title: Data for: Effect of dexmedetomidine sedation on the swallowing reflex: A pilot study

description: Effect of dexmedetomidine sedation on the swallowing reflex
DOI: 10.17632/mz484h884h.1
title: Strand specific RNA sequencing of L.monocytogenes 10403S under UV irradiation conditions in comparison to bacteria grown in BHI 2

description: Part 2. Bacteria were grown in BHI medium (with UV irradiation) and harvested at 1,2,3 and 4 hours post UV irradiation for ssRNA-Seq analysis.
DOI: 10.17632/5zmkg9xb4m.1
title: Data sets of water chemistry in Shiyang river basin

description: From May 2014 to Oct 2018, representative reservoirs were selected for monitoring in the mountainous area (NY Reservoir), the oasis (HYS Reservoir), and desert (QTH reservoir)(Table 1) Five reservoir water sampling points were established in each reservoir to collect reservoir water, and the sampling points were distributed at reservoir inlets, reservoirs, and reservoir outlets. To ensure the representative of the samples and avoid the influence of extreme climate eventspecial weather, the sampling was always carried out under sunny and windless conditions. Once a month, aAt least three water samples were collected from each reservoir once a month. A total of 513 valid samples were obtained (Three of the sampling points are close to the dam, one sampling point is in the center of the lake, and the sample is taken 10cm below the water surface).
DOI: 10.5281/zenodo.3611097
title: Genotypes for GWAS study on feed efficiency traits in rabbits

description: Dataset with genotypes on rabbits
DOI: 10.5281/zenodo.3611096
title: Genotypes for GWAS study on feed efficiency traits in rabbits

description: Dataset with genotypes on rabbits
DOI: 10.5519/qd.9m1vwjuw
title: Query on the Natural History Museum Data Portal (data.nhm.ac.uk) (1 records)
DOI: 10.5519/qd.f9yytj74
title: Query on the Natural History Museum Data Portal (data.nhm.ac.uk) (1 records)
DOI: 10.17632/mz484h884h.2
title: Strand specific RNA sequencing of L.monocytogenes 10403S under UV irradiation conditions in comparison to bacteria grown in BHI 2

description: Part 2. Bacteria were grown in BHI medium (with UV irradiation) and harvested at 1,2,3 and 4 hours post UV irradiation for ssRNA-Seq analysis.
DOI: 10.17632/rhgkb8wfxj.1
title: Sound strength parameter G determined from uncalibrated room impulse responses measurements of concert halls using a set of window functions and lengths

description: The sound strength factor G computed using sixty three time windows in six frequency bands from two hundred and seventy seven uncalibrated room impulse responses (RIRs) corresponding to seven concert halls is reported. The RIRs were collected from the website of the Concert Hall Research Group of the Acoustical Society of America. The raw, processed, and compared data are provided as coma delimited, mat files and figures as well as the codes implementing the method. The maximum error across halls for mid frequencies using a Blackman-Harris time window of 23 ms was 1 dB. Figures p1, p2, p3 and p4 show the summary of the data for the 1/1 octave band centerd at 125 Hz, the low frequencies, the mid frequencies, and the high frequencies, repectively. The summary data are the mean error, maximum error and correlation across halls for the average G of each hall using seven time window functions and nine time window lengths. The whole data can be acessed in the folder DAT_files. The data is divided in 6 groups. In the first group, the strength factor G is estimated for the six 1/1 octave frequency bands from 125 Hz to 4 kHz. Each file contains a table of six columns corresponding to the frequency bands and a number of rows corresponding to the source-receiver combinations. Each file is labelled G_R_W_L.dat replacing R, W and L for the following codes. R codes the concert hall as follows: BM: Baltimore. Joseph Meyerhoff Symphony Hall (30 RIRs) BS: Boston. Symphony Hall (42 RIRs) BK: Buffalo. Kleinhans Music Hall (72 RIRs) PA: Philadelphia. Academy Of Music (36 RIRs) WM: Worcester. Massachusetts. The Grand Hall. Mechanics Hall (25 RIRs) CS: Cleveland. Severance Hall (36 RIRs) WK: Washington. D.C. JFK center. Concert hall (36 RIRs) W codes the window function as follows: TW: Taylor FT: Flattop RW: Rectangular HN: Hann HM: Hamming BW: Blackman BH: Blackman Harris L is the window length in ms with zero padding so as to complete three digits. The codes are the following: 001 003 006 012 023 046 093 186 372. A group (b) of sixty three files contains the average G for each of the seven halls in each row. This second group is coded as G_b_W_L.dat. A group (c) comprises the average for low, mid , and high frequencies coded as G_c_low.dat, G_c_mid.dat, and G_c_hig.dat. The columns of each file correspond to the halls and the rows to the windows. Each row correspond to a window length and each consecutive group of nine rows correspond to a window function. (e.g. the first nine correspond to a Taylor window of 1 ms, 3 ms, 6 ms, 12 ms, 23 ms, 46 ms, 93 ms, 186 ms, and 372 ms length, respectively). Groups (d), (e), and (f), are the data reported in figures p1-p4 obtained by comparison with results of G reported in the literature. All this data can be generated using the Matlab code result_figures.m and the Mat files. In turn, the mat files can be generated using the code calculate_Num_Den.m and the other auxiliary codes provided in the Matlab_code folder.
DOI: 10.17632/k3msdp67cn.1
title: Mussel acclimatization to high, variable temperatures is lost slowly upon transfer to benign conditions

description: Climate change is increasing the temperature variability animals face, and thermal acclimatization allows animals to adjust adaptively to this variability. Although the rate of heat acclimatization has received some study, little is known about how long these adaptive changes remain without continuing exposure to heat stress. This study explored the rate at which field acclimatization states are lost when temperature variability is minimized during constant submersion. California mussels (Mytilus californianus) with different acclimatization states were collected from high- and low-zone sites (∼12 versus ∼5°C daily temperature ranges, respectively) and then kept submerged at 15°C for 8 weeks. Each week, the cardiac thermal performance of mussels was measured as a metric of acclimatization state; critical (Tcrit) and flatline (Tflat) temperatures were recorded. Over 8 weeks of constant submersion, the mean Tcrit of high-zone mussels decreased by 1.07°C from baseline, but low-zone mussel mean Tcrit was unchanged. High- and low-zone mussels mean maximum heart rate (HR) and resting HR decreased ∼12 and 35%, respectively. Tflat was unchanged in both groups. These data suggest that Tcrit and HR are more physiologically plastic in response to the narrowing of an animal’s daily temperature range than Tflat is, and that an animal’s prior acclimatization state (high versus low) influences the acclimatory capacity of Tcrit. Approximately 2 months were required for the cardiac thermal performance of the high-zone mussels to reach that of the low-zone mussels, suggesting that acclimatization to high and variable temperatures may persist long enough to enable these animals to cope with intermittent bouts of heat stress.
DOI: 10.17632/5xtgndzw4g.2
title: Data for: Un-riped fruit pods of Prosopis cineraria (L.) Druce ameliorates Cisplatin therapy induced partial testicular atrophy in male wistar rats

description: The .zip file contains IAEC certificate (confidential details removed) obtained for the project in 2015, Plant authentication certificate (obtained from Dr. Jayaraman, Botanist), together with all statistical calculations done on Sigmaplot®14. The PDF files generated as a result of statistical calculations performed in 2016 via. Sigmaplot® 14 compares G1 vs. G2, G3, G4, and G5. These were performed back in 2018 during the first manuscript submission. However, after comments from the reviewers, we had rerun the statistical evaluations via. Sigmaplo®14 in May 2020 during the revision and submission of the R1 version of the manuscript. These evaluations were performed as G2 vs. G1, G3, G4, and G5.
DOI: 10.17632/gkgrk7d8hg.1
title: Source Data repository "Human GBP1 differentially targets Salmonella and Toxoplasma to license recognition of microbial ligands and caspase-mediated death"

description: Quantification data for "Human GBP1 differentially targets Salmonella and Toxoplasma to license recognition of microbial ligands and caspase-mediated death" organised by Figure
DOI: 10.17632/m5k4rp8g4z.1
title: Anosmia and Ageusia in COVID-19 patients

description: objecitve olfactory and gustatory testing, MRI settings
DOI: 10.17632/92mkcf9knn.1
title: Supplemental Materials

description: Table 1 and full references, for Yoon, et al.
DOI: 10.17632/jy6ww3hmyw.2
title: Multi-Paradigm Modeling for Cyber-Physical Systems literature

description: This dataset includes the set of papers retrieved to perform a systematic mapping review (SMR) on multi-paradigm modelling (MPM) for cyber-physical systems (CPS). Moreover, it includes several tables that map the studies under several perspectives, notably used modelling formalisms and processes, part of the CPS addressed by the research, domain of expertise of paper authors, and relevance of the paper at review date. The set of papers is selected over a period ranging from 2006 to 2017, according to publication dates. The selection of the papers and their mapping has been performed by means of a rigorous process based on precise aspects to be evaluated and peer reviewing. Further, the process has been supported by a web-based survey management application. Both the selection of existing publications and their mappings by means of the included perspectives provide interested readers/researches with interesting data possible re-usable for multiple purposes: analysing the progress of research on modelling of CPS, studying further the papers pertaining to a specific (set of) characteristic(s), performing a follow-up study related to other development technologies, just to mention a few.
DOI: 10.5519/qd.g6vkd9hx
title: Query on the Natural History Museum Data Portal (data.nhm.ac.uk) (4559635 records)
DOI: 10.5281/zenodo.3890984
title: New production channels for light dark matter in hadronic showers

description: This is the companion dataset to the publication "<em>New production channels for light dark matter in hadronic showers</em>" by the same authors. It includes the track-lengths for electrons and positrons for MiniBooNE, SHiP, NOvA and DUNE. An example process card and UFO model files for Maddump are further provided.
description: These track lengths have been obtained from simplified geometries of the experimental setups and are primarily dedicated to the simulation of light new physics production via lepton-induced processes.
DOI: 10.3886/e113143
title: Replication data for: Bias in Cable News: Persuasion and Polarization

description: We measure the persuasive effects of slanted news and tastes for like-minded news, exploiting cable channel positions as exogenous shifters of cable news viewership. Channel positions do not correlate with demographics that predict viewership and voting, nor with local satellite viewership. We estimate that Fox News increases Republican vote shares by 0.3 points among viewers induced into watching 2.5 additional minutes per week by variation in position. We then estimate a model of voters who select into watching slanted news, and whose ideologies evolve as a result. We use the model to assess the growth over time of Fox News influence, to quantitatively assess media-driven polarization, and to simulate alternative ideological slanting of news channels.
DOI: 10.5281/zenodo.3897351
title: Data for "Optimal Mutation Rates for the (1+λ) EA on OneMax"

description: This dataset contains optimal mutation rates for the few variations of the (1+λ) evolutionary algorithm on the OneMax problem. The OneMax problem is a famous benchmark problem which is defined on bit strings, with the maximized function being the number of bits set to 1. The optimal mutation rates depend on the Hamming distance to the optimum (or, put simple, on the current fitness). We study three flavours of the algorithm: the algorithm with the standard bit mutation - where each bit is flipped independently of others with the probability <em>p</em>, which is the sought <em>mutation rate</em> - nicknamed "<strong>sbm</strong>" in the file names; the algorithm with the so-called "shift" bit mutation - which is similar to the one above, except that when none bits were flipped, one randomly chosen bit is forcefully flipped - nicknamed "<strong>shf</strong>" in the file names; the algorithm which always flips <em>k</em> bits, which is the mutation rate for this algorithm - nicknamed "<strong>rls</strong>" in the file names, because it is a generalization of the famous randomized local search (RLS) that always flips one randomly chosen bit. All these variations have one parent individual, produce λ offspring on each iteration and choose the best of both the parent and the offspring to be the parent in the next iteration (hence the (1+λ) in the notation). As a result, λ is often called the <em>popiulation size</em>. We study the values of λ to be powers of two ranging from 2<sup>0</sup>=1 to 2<sup>18</sup>=262144, and the problem sizes <em>n</em>=1000, 2000, 5000. For all the variations and all population sizes, we compute the optimal mutation rates (in the corresponding sense) as functions of the distance to the optimum, where "optimal" mean those which minimize the <strong>expected running time</strong>. For the "rls" variation we also compute the "drift-maximizing" mutation rates, which maximize the <strong>expected fitness increase</strong> (and which is, in fact, different from minimizing the expected running time). The files in the dataset are as follows: <strong>data-expectations-&lt;problem size&gt;.csv</strong>: the summary of the expected running times of all these algorithms for all population sizes, where &lt;problem size&gt; is the value of the problem size. <strong>data-optimal-&lt;algo&gt;-&lt;problem size&gt;.csv</strong>: the mutation rates optimal for the given algorithm and the given problem size for all population sizes. Note that for "<strong>rls</strong>" the mutation rate is an integer from 1 to <em>n</em>, whereas for other algorithms the mutation rate is the probability, so a floating-point number from [0;1]. <strong>data-drift-optimal-rls-&lt;problem size&gt;.csv</strong>: same thing from drift-optimal mutation rates. <strong>img-optimal-&lt;algo&gt;-&lt;problem size&gt;-&lt;population size&gt;.png</strong>: the pictures that display how good each mutation rate is for each distance to the optimum. Please check the exact semantics in the paper, but the overall idea is that yellow is better.
DOI: 10.5281/zenodo.3897350
title: Data for "Optimal Mutation Rates for the (1+λ) EA on OneMax"

description: This dataset contains optimal mutation rates for the few variations of the (1+λ) evolutionary algorithm on the OneMax problem. The OneMax problem is a famous benchmark problem which is defined on bit strings, with the maximized function being the number of bits set to 1. The optimal mutation rates depend on the Hamming distance to the optimum (or, put simple, on the current fitness). We study three flavours of the algorithm: the algorithm with the standard bit mutation - where each bit is flipped independently of others with the probability <em>p</em>, which is the sought <em>mutation rate</em> - nicknamed "<strong>sbm</strong>" in the file names; the algorithm with the so-called "shift" bit mutation - which is similar to the one above, except that when none bits were flipped, one randomly chosen bit is forcefully flipped - nicknamed "<strong>shf</strong>" in the file names; the algorithm which always flips <em>k</em> bits, which is the mutation rate for this algorithm - nicknamed "<strong>rls</strong>" in the file names, because it is a generalization of the famous randomized local search (RLS) that always flips one randomly chosen bit. All these variations have one parent individual, produce λ offspring on each iteration and choose the best of both the parent and the offspring to be the parent in the next iteration (hence the (1+λ) in the notation). As a result, λ is often called the <em>popiulation size</em>. We study the values of λ to be powers of two ranging from 2<sup>0</sup>=1 to 2<sup>18</sup>=262144, and the problem sizes <em>n</em>=1000, 2000, 5000. For all the variations and all population sizes, we compute the optimal mutation rates (in the corresponding sense) as functions of the distance to the optimum, where "optimal" mean those which minimize the <strong>expected running time</strong>. For the "rls" variation we also compute the "drift-maximizing" mutation rates, which maximize the <strong>expected fitness increase</strong> (and which is, in fact, different from minimizing the expected running time). The files in the dataset are as follows: <strong>data-expectations-&lt;problem size&gt;.csv</strong>: the summary of the expected running times of all these algorithms for all population sizes, where &lt;problem size&gt; is the value of the problem size. <strong>data-optimal-&lt;algo&gt;-&lt;problem size&gt;.csv</strong>: the mutation rates optimal for the given algorithm and the given problem size for all population sizes. Note that for "<strong>rls</strong>" the mutation rate is an integer from 1 to <em>n</em>, whereas for other algorithms the mutation rate is the probability, so a floating-point number from [0;1]. <strong>data-drift-optimal-rls-&lt;problem size&gt;.csv</strong>: same thing from drift-optimal mutation rates. <strong>img-optimal-&lt;algo&gt;-&lt;problem size&gt;-&lt;population size&gt;.png</strong>: the pictures that display how good each mutation rate is for each distance to the optimum. Please check the exact semantics in the paper, but the overall idea is that yellow is better.