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This data includes all the input data for the test instances used in the experiments. The input data consists of three sets of benchmarks including OR-Lib set (40 graphs), TSP-Lib set (20 graphs) and University of Florida Sparse Matrix Collection (3 graphs) .
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These files contained lab notes on the preparation of hot-pressed plant-based biopolymers and, raw, filtered and analyzed data on bending properties, thermal and structural analysis.
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The Indeterminate Domain (IDD) proteins are a plant specific subclass of C2H2 Zinc Finger transcription factors. Some of these transcription factors play roles in diverse aspects of plant metabolism and development; however the function of most of IDDs is unknown and its molecular evolution has not been explored. Here, Prochetto and Reinheimer reconstructed the evolution of IDDs during plant land conquest. They found that IDDs arose from the common ancestor of Streptophyta. Once in land, IDDs experienced a rapid radiation that accompanied key morphological, physiological and biochemical transitions required in plant terrestrialization. The authors present a solid phylogenetic framework of annotated IDD genes which links genetic and functional knowledge from model to non-model species.
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  • Sequencing Data
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The procreative statistical framework of musical note structures produces a crucial role in multimedia music classification and reconstruction strategies. Another most significant thing for harmonious music composition is the rhythmic structures that provide musical performance in a harmonic form. This paper has illustrated computational music theory and allied factors to regulate what human beings can acquire, remember, and reconstruct music for sustaining intangible cultural heritage. The music strings or symbols are also imperative factors that assist the musicians as performance guidelines. To afford a syntactic outline of musical note arrangements, a stochastic model along with probabilistic context-free music grammar has been illustrated in this paper. The state transition analysis has also been incorporated in terms of transition table and diagram to demonstrate which state can move to the other one within a finite automaton depending on the behaviors of the current state and associated transition rule. Petri net has been used for modeling and simulating the projected complex music composition framework to analyze system performances. The Petri net simulation-based reachability and system efficiency have been evaluated for analyzing the effectiveness of the proposed event-driven architecture. For incorporating real data into the projected framework, the music composition and reconstruction tool has also been demonstrated. The system performance evaluation metric has shown that around 92% efficiency level has been achieved by analyzing the projected music composition model.
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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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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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Homer Legacy software is a well-known software for simulation of small hybrid energy systems that can be used for both design and research. This dataset is a set of files generated by Homer Legacy bringing the simulation results of hybrid energy systems over the last seven years, as a consequence of the research work led by Dr. Alexandre Beluco, Federal University of Rio Grande do Sul, in southern Brazil. This dataset is being published in conjunction with a paper in Data Science Journal, which presents further explanations about the hybrid energy systems that were simulated and the papers that publish and discuss the results. The readme.pdf file included in this dataset and the associated article provide more details. These files are made available both for their educational nature, as case studies, and for the possibilities of research that can always be opened from the dissemination of research data. The next steps of this research point to the study of the influence of energetic complementarity on the performance of hybrid systems and to the study of hybrid systems equipped with hybrid storage,
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This dataset contains the time series of axial peak tibial acceleration. We recruited 10 runners with high axial peak tibial acceleration. The participants performed a gait retraining session whilst running overground at 3.2 ± 0.2 m/s in self-selected footwear. Real-time auditory biofeedback on axial peak tibial acceleration was provided. The axial peak tibial acceleration was detected before and during the biofeedback-based intervention using a backpack system connected to a very lightweight accelerometer. We refer to the full paper for details on how the data were collected and processed. Data are from an experimental protocol approved by the Ethics Committee of Ghent University (bimetra identification number 2015/0864). The present dataset has been used to determine when runners change their level of peak tibial acceleration during over-ground running using an auditory biofeedback system. The folder 'Change-Point" contains the .cpa-files to be opened in the Change-Point Analyzer v2.3 software. The values of axial peak tibial acceleration are also stored in an Excel-compatible file 'change point analysis_data' . The spreadsheet comprising of 10 columns. Each column represents a participant. A column contains the values of axial peak tibial acceleration of the no-biofeedback condition (1.5 min. of baseline), followed by the biofeedback condition (2x10 min.). The total number of trials detected per participant equals 1853 ± 88 (mean ± SD).
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Presented data includes output files corresponding to structure optimisation of the systems dealt in the article. Refer the articles to understand the nomenclature and configuration.
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