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Tha dataset contains ballistocardiography signals together with ECG. We studied changes in the signals related with breath holding. The BCG sensor dataset is obtained from twenty tested individuals. The schedule of measuring was in two types (V1 and V2) described in description. Every breath-holding was done for the time of the approximatelly 30 seconds. For measurement a force plate in the form of bed was used. The force plate had four tensometers embedded in its four legs. Each tensometer could measure the force in three orthogonal directions with a precision of up to 0.1 N. Therefore, 12 force signals were obtained. The ECG signal was measured simultaneously with the force measurement. All the signals were registered using a 24-bit AD converter with a sampling rate of 1 kHz. Measurement took place in laboratory at Faculty of Science, University of Hradec Králové, Czech republic.
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in-situ observation data at the Mt. Waliguan and Shangri-La
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the study is to compare the effect of dynamic stretching on vertical jump performance in recreational athletes and normal collegiate students
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Julia code used to simulate the data presented in "Surface Temperature Estimation in Determined Multi-Wavelength Pyrometry Systems"
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This datasets contains the model output at 8 assimilation cycles, only mean background or mean analysis in both assimilation Experiments (Exp_all, Exp_b) are uploaded. Exp_all/analysis: the mean analysis of Exp_all Exp_all/background: the mean background of Exp_all Exp_b/analysis: the mean analysis of Exp_b Exp_b/background: the mean background of Exp_b
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All the tables and figures
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There is a detailed Readme.pdf in the files for the informations about the dataset. The main purpose is providing a dataset for the vibration behavior of a robot manipulator system under the control input of model-associative vibration control (MAVC) prodecure. Velocity profile is shown as [∗,𝑡𝑐𝑜𝑛,𝑡𝑑𝑒𝑐,𝑡𝑚] in study. In the case studies for both simulations and experiments, the parameters are varied as follows; 𝑡𝑐𝑜𝑛 can be valued as 0, 𝑡1ℎ or 2𝑡1ℎ, 𝑡𝑑𝑒𝑐 can be valued as 𝑡1ℎ,2𝑡1ℎ,3𝑡1ℎ,4𝑡1ℎ or 5𝑡1ℎ and 𝑡𝑚 can be valued as 1 or 1.5 seconds for corresponded 90 or 135 angular displacements. Thus thirty different velocity profiles are produced with aim to performed on system. Cases are invastigated with and without performing the MAVC procedure. Than the robot manipulator is examined for both unloaded and loaded cases, therefore total one hundred twenty cases are occured. More details can be found in related study.
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RNA sequencing data to Identify DEGs in control EBs and EBs irradiated at 630 nm. RNA-seq raw data 1. Control EBs - read1 & read2 (fq.gz) 2. EBs irradiated at 630 nm - read1 & read2 (fq.gz) RNA-seq raw data of this study are available at other drive (https://drive.google.com/open?id=1JJP4eRvW0r4ZviSvGQJOJKD2eb4_J6os).
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Hypothesis: Does dogs exhibit different protein profile of seminal plasma and spermatozoa among breeds? What data shows: These data show the proteomic profile and its respectively gene ontology of seminal plasma and sperm cells of four purebred dogs (Golden Retriever n = 3, Bernese Mountain Dog n = 4, Great Dane n = 3, Maremmano-Abruzzese Sheepdog n = 3), with mean ages and standard deviation of 4,0 ± 1,0 years (Golden Retriever), 2,0 ± 1,0 years (Bernese Mountain Dog), 1,4 ± 0,5 years (Great Dane) and 4,0 ± 0,7 years (Maremmano-Abruzzese Sheepdog), kenneled at Sao Paulo State, Brazil. Besides How it was gathered: Entire second fraction and a portion of the third semen fraction were collected into a silicone funnel attached to a graduated plastic tube by manual stimulation of the penis in the presence of a teaser bitch, when possible. The semen was subjectively evaluated at the kennel, and only ejaculate within normal seminal parameters considered for dogs, according to Kustritz et al. (2007), were used in this study. Spermatozoa and seminal plasma were separated by centrifugation and prepared individually for proteomic analysis by ESI Q-Tof mass spectrometer. The gene ontology annotation of the proteins found within the samples was obtained using the UniprotKB website (www.uniprot.org), and considered the molecular function, biological process and cellular component categories. How the data can be interpreted: There are two folders dataset. The "Seminal plasma and sperm cell proteins" folder contain two folders, one with all seminal plasma proteins, and other folder with all sperm cell proteins, which have individual files named by breed for each dog (n=13). The “Gene ontology of seminal plasma and sperm cell proteins” contain three files: Table S1, Table S2, and Table S3. The file Table S1 contain all proteins found in seminal plasma of evaluated dogs and their respective gene ontology. The file Table S2 contain all proteins found in spermatozoa of all dogs evaluated and their respective gene ontology. The file Table S3 contain all common proteins found in seminal plasma and spermatozoa of evaluated dogs and their respective gene ontology. References: Kustritz R. The value of canine semen evaluation for practitioners. Theriogenology 2007;68(3):329-37.
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This data set presents supplementary material to Monroy, Oscar; Saucedo, Gerardo; Espinosa, Ruben (2020) Composting a digestate from the organic fraction of urban solid wastes (OFUSW), Revista Mexicana de Ingeniería Química. An interesting design approach to prepare a balanced composting mass is proposed based on the carbon to nitrogen ratio (C/N) and the minimum required inert material to promote aeration. By using Scheffe’s simplex centroid method to design an optimum mixture of three components (digestate, fresh OFUSW and sawdust), using two regression equations for two process variables (C/N and volatile solids), a solution is obtained for a compost with the adequate C/N for a biosolid and the highest organic matter degradation efficiency. This data set contains the diagrams (figures S1 and S2) of the experimental rigs (lab scale and bench scales compost reactors), describing air circulation, mixing and heating devices. Table S1 shows the elemental analysis (C, N and H; O is reported as the difference from the total) and the C/N of the initial compost components. Ten mixtures were prepared to yield a C/N between 25 and 35 and set to compost. The resulting C/N and volatile solids loss due to the composting process are shown in Table S2. From these results, two regression equations were obtained using PASW Statistics 18 software, which generated table S3 and the contour levels of the tricomponents plot (figure S3). Three of these initial mixtures tried in a 95 L bench scale compost batch reactor. The resulting compost was tested for toxicity with the germination index. The results of three different reactor runs were tried by triplicate with ten seeds each are shown in table S4.
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