cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.6084/m9.figshare.3084055.v1
title: Information, how to get it precious?

description: In our Age of Information the term Information is one of the most used words. Some Information Scientists tried to find a common definition. PLOCHBERGER Franz (2012) tried to fix it in his “Information scientific Axioms”. He used terms of Wolfgang HOFKIRCHNER or Raphael CAPURRO.<br>The author started a new research impact: „IT-Orientation towards Human Being“. The aim of this research is to find out significant terms and to evaluate a scientifically usable paradigm under this surrounding topic. The orientation on human needs is necessary, because we have to make a difference between human cognitive information evolution (technological) and human biological evolution as species, which is much more slowly.<br>In chapter 4 human abilities to manage Information will be showed. In the chapters 5 and 6 the author tries to find topics and permanent valid Information scientific terms for the usage of Information in a precious way for human beings in future (e.g. in a rising amount of Data (Big Data) or moving Data with electronically speed on worldwide spread networks).<br>Information Science is not a narrow science; it touches Philosophy, Mathematics, Physics, Psychology, Sociology, Economy and System Sciences. These sciences contain all interesting theories.<br>The actual trend is that the changing’s of new Information-instruments (Desktop, Laptop, Smartphone or Mobile Touch Screens) seem to fascinate and stimulate customers. If we don't try to find scientific backgrounds we get in dependence of some worldwide single IT-companies with commercial interests only.<br>We have to ask: Do we know already the most important values in Information Science for future? Is it sure that IT-Orientation towards Human Being is able to surround the most precious parts of Information Science and to set definitive orientation points towards the human being? The orientation towards human being has borders – by human being. But no restrictions are definable in complexity towards the machine side.<br>
DOI: 10.6084/m9.figshare.3083971
title: Kin recognition in a butterfly: inferences about its heritability

description: Some animal species are able to recognise their relatives, cannibalising mostly non-kin individuals, as happens with the caterpillars of the butterfly <i>Heliconius erato phyllis</i>. Here, we established a breeding programme where adults had different coefficients of relatedness (r = 0 and r = 0.5; offspring, respectively with F = 0 and F = 0.25). The caterpillars cannibalised or did not cannibalise sibling eggs, which was used to make inferences on the kin recognition inheritance of non-cannibals, and to estimate its heritability. The parents had both cannibal and non-cannibal phenotypes; crosses were done for all combinations of these phenotypes, which were divided into outbred and inbred. Caterpillars were grown in the laboratory until the adult stage, and were classified as cannibal or non-cannibal after a test with three sibling eggs. The results showed that the mean number of non-cannibal siblings, those that recognise their kin, is larger in inbreds, above 60%, regardless of their parents’ behaviour. Among non-inbred individuals the mean frequency of non-cannibal siblings was around 38%; these differences were statistically significant. The heritability was estimated by four methods. For F = 0 it was around 0.24 ± 0.11, and for F = 0.25 it was around 0.20 ± 0.17. These results, taken together, were discussed in terms of a threshold character: above this threshold the expression of the non-cannibal phenotype is allowed. As for the low values for heritabilities, they were discussed in terms of the theory of traits relevant to both fitness and the resource allocation priority hypothesis.
DOI: 10.6084/m9.figshare.3083980
title: alldata.csv

description: Preliminary experiments on human sensitivity to rhythmic structure in a grammar with recursive self-similarity<br>
DOI: 10.6084/m9.figshare.3083998
title: Cloning of the growth hormone receptor and its muscle-specific mRNA expression in black Muscovy duck (<i>Cairina moschata</i>)

description: The cDNA sequence of the growth hormone receptor (GHR) from the black Muscovy duck was obtained and compared to the mRNA expression of growth hormone (GH) in the breast and leg muscles during 2–13 weeks of age using quantitative RT-PCR.The cDNA sequence of the Muscovy duck GHR gene is 1903 bp in length, with an 1830 bp coding region that encodes 609 amino acids. It exhibits &gt; 92.9% homology with the poultry GHR cDNA and amino acid sequences.Overall, GHR mRNA expression was the highest at 2 weeks and the lowest at 13 weeks of age, exhibiting different profiles in different muscles. In the breast muscles, the GHR mRNA level declined sharply at 2–4 weeks, maintained at a plateau at 4–10 weeks and decreased slightly at 10–13 weeks. In the leg muscles, a gradual and slow decrease was observed during the whole period of 2–13 weeks.Robust extra-pituitary GH mRNA expression was detected in the muscles and the expression profile was highly correlated with that of GHR mRNA, in contrast to the inverse correlation between the pituitary GH and tissue GHR levels shown previously.These data suggest that the locally synthesised GH in the muscles, rather than the pituitary GH, is more closely associated with GHR and may be more critical for the regulation of muscle growth and contribute to the tissue-specific effects of GH. The cDNA sequence of the growth hormone receptor (GHR) from the black Muscovy duck was obtained and compared to the mRNA expression of growth hormone (GH) in the breast and leg muscles during 2–13 weeks of age using quantitative RT-PCR. The cDNA sequence of the Muscovy duck GHR gene is 1903 bp in length, with an 1830 bp coding region that encodes 609 amino acids. It exhibits &gt; 92.9% homology with the poultry GHR cDNA and amino acid sequences. Overall, GHR mRNA expression was the highest at 2 weeks and the lowest at 13 weeks of age, exhibiting different profiles in different muscles. In the breast muscles, the GHR mRNA level declined sharply at 2–4 weeks, maintained at a plateau at 4–10 weeks and decreased slightly at 10–13 weeks. In the leg muscles, a gradual and slow decrease was observed during the whole period of 2–13 weeks. Robust extra-pituitary GH mRNA expression was detected in the muscles and the expression profile was highly correlated with that of GHR mRNA, in contrast to the inverse correlation between the pituitary GH and tissue GHR levels shown previously. These data suggest that the locally synthesised GH in the muscles, rather than the pituitary GH, is more closely associated with GHR and may be more critical for the regulation of muscle growth and contribute to the tissue-specific effects of GH.
DOI: 10.6084/m9.figshare.3083971.v1
title: Kin recognition in a butterfly: inferences about its heritability

description: Some animal species are able to recognise their relatives, cannibalising mostly non-kin individuals, as happens with the caterpillars of the butterfly <i>Heliconius erato phyllis</i>. Here, we established a breeding programme where adults had different coefficients of relatedness (r = 0 and r = 0.5; offspring, respectively with F = 0 and F = 0.25). The caterpillars cannibalised or did not cannibalise sibling eggs, which was used to make inferences on the kin recognition inheritance of non-cannibals, and to estimate its heritability. The parents had both cannibal and non-cannibal phenotypes; crosses were done for all combinations of these phenotypes, which were divided into outbred and inbred. Caterpillars were grown in the laboratory until the adult stage, and were classified as cannibal or non-cannibal after a test with three sibling eggs. The results showed that the mean number of non-cannibal siblings, those that recognise their kin, is larger in inbreds, above 60%, regardless of their parents’ behaviour. Among non-inbred individuals the mean frequency of non-cannibal siblings was around 38%; these differences were statistically significant. The heritability was estimated by four methods. For F = 0 it was around 0.24 ± 0.11, and for F = 0.25 it was around 0.20 ± 0.17. These results, taken together, were discussed in terms of a threshold character: above this threshold the expression of the non-cannibal phenotype is allowed. As for the low values for heritabilities, they were discussed in terms of the theory of traits relevant to both fitness and the resource allocation priority hypothesis.
DOI: 10.6084/m9.figshare.3083965
title: Data in 2012-2014 .xlsx

description: Data of Study on light interception and biomass production of different cotton cultivar.
DOI: 10.6084/m9.figshare.3083980.v1
title: alldata.csv

description: Preliminary experiments on human sensitivity to rhythmic structure in a grammar with recursive self-similarity<br>
DOI: 10.6084/m9.figshare.3083998.v2
title: Cloning of the growth hormone receptor and its muscle-specific mRNA expression in black Muscovy duck (<i>Cairina moschata</i>)

description: The cDNA sequence of the growth hormone receptor (GHR) from the black Muscovy duck was obtained and compared to the mRNA expression of growth hormone (GH) in the breast and leg muscles during 2–13 weeks of age using quantitative RT-PCR.The cDNA sequence of the Muscovy duck GHR gene is 1903 bp in length, with an 1830 bp coding region that encodes 609 amino acids. It exhibits &gt; 92.9% homology with the poultry GHR cDNA and amino acid sequences.Overall, GHR mRNA expression was the highest at 2 weeks and the lowest at 13 weeks of age, exhibiting different profiles in different muscles. In the breast muscles, the GHR mRNA level declined sharply at 2–4 weeks, maintained at a plateau at 4–10 weeks and decreased slightly at 10–13 weeks. In the leg muscles, a gradual and slow decrease was observed during the whole period of 2–13 weeks.Robust extra-pituitary GH mRNA expression was detected in the muscles and the expression profile was highly correlated with that of GHR mRNA, in contrast to the inverse correlation between the pituitary GH and tissue GHR levels shown previously.These data suggest that the locally synthesised GH in the muscles, rather than the pituitary GH, is more closely associated with GHR and may be more critical for the regulation of muscle growth and contribute to the tissue-specific effects of GH. The cDNA sequence of the growth hormone receptor (GHR) from the black Muscovy duck was obtained and compared to the mRNA expression of growth hormone (GH) in the breast and leg muscles during 2–13 weeks of age using quantitative RT-PCR. The cDNA sequence of the Muscovy duck GHR gene is 1903 bp in length, with an 1830 bp coding region that encodes 609 amino acids. It exhibits &gt; 92.9% homology with the poultry GHR cDNA and amino acid sequences. Overall, GHR mRNA expression was the highest at 2 weeks and the lowest at 13 weeks of age, exhibiting different profiles in different muscles. In the breast muscles, the GHR mRNA level declined sharply at 2–4 weeks, maintained at a plateau at 4–10 weeks and decreased slightly at 10–13 weeks. In the leg muscles, a gradual and slow decrease was observed during the whole period of 2–13 weeks. Robust extra-pituitary GH mRNA expression was detected in the muscles and the expression profile was highly correlated with that of GHR mRNA, in contrast to the inverse correlation between the pituitary GH and tissue GHR levels shown previously. These data suggest that the locally synthesised GH in the muscles, rather than the pituitary GH, is more closely associated with GHR and may be more critical for the regulation of muscle growth and contribute to the tissue-specific effects of GH.
DOI: 10.6084/m9.figshare.3084319.v4
title: IJEE Educational Data Mining

description: Histograms and results of k-means and Ward's clustering for IJEE special issue<br><br>The fileset contains information from three sources:<br><br>1. Histograms (two files):<br>* Lexical_histogram.png (histogram of lexical errors ratios)<br>* Grammatical_histogram.png (histogram of grammatical erros ratios)<br><br>2. K-means clustering (eight files):<br>* elbow-lex.png (clustering by lexical aspects: error curves obtained for applying elbow method to determinate the optimal number of clusters)<br>* cube-lex.png (clustering by lexical aspects: a three-dimensional representation of clusters obtained after applying k-means method)<br>* Lexical_clusters (table).xls (clustering by lexical aspects: centroids, standard deviations and number of instances assigned to each cluster)<br>* elbow-gram.png (clustering by grammatical aspects: error curves obtained for applying elbow method to determinate the optimal number of clusters)<br>* cube-gramm.png (clustering by grammatical aspects: a three-dimensional representation of clusters obtained after applying k-means method)<br>* Grammatical_clusters (table).xls (clustering by grammatical aspects: centroids, standard deviations and number of instances assigned to each cluster)<br>* elbow-lexgram.png (clustering by lexical and grammatical aspects: error curves obtained for applying elbow method to determinate the optimal number of clusters)<br>* Lexical_Grammatical_clusters (table).xls (clustering by lexical and grammatical aspects: centroids, standard deviations and number of instances assigned to each cluster)<br><br>3. Ward’s Agglomerative Hierarchical Clustering (three files):<br>* Lexical_Cluster_Dendrogram_ward.png (clustering by lexical aspects: dendrogram obtained after applying Ward's clustering method).<br>* Grammatical_Cluster_Dendrogram_ward.png (clustering by grammatical aspects: dendrogram obtained after applying Ward's clustering method)<br>* Lexical_Grammatical_Cluster_Dendrogram_ward.png (clustering by lexical and grammatical aspects: dendrogram obtained after applying Ward's clustering method)<br>* Lexical_Grammatical_clusters (table).xls: Centroids (from column 2 to 7) and cluster sizes (last column) obtained by applying Ward's agglomerative hierarchical clustering to lexical and grammatical error ratios.<br>* Grammatical_clusters (table).xls: Centroids (from column 2 to 4) and cluster sizes (last column) obtained by applying Ward's agglomerative hierarchical clustering to grammatical error ratios.<br>* Lexical_clusters (table).xls: Centroids (from column 2 to 4) and cluster sizes (last column) obtained by applying Ward's agglomerative hierarchical clustering to lexical error ratios.<br><br>
DOI: 10.6084/m9.figshare.3083962
title: Interactive search for action and motion planning with dynamics

description: This paper proposes an interactive search approach, termed INTERACT, which couples sampling-based motion planning with action planning in order to effectively solve the combined task and motion planning problem. INTERACT is geared towards scenarios involving a mobile robot operating in a fully known environment consisting of static and movable objects. INTERACT makes it possible to specify a task in the planning domain definition language (PDDL) and automatically computes a collision-free and dynamically feasible trajectory that enables the robot to accomplish the task. The coupling of sampling-based motion planning with action planning is made possible by expanding a tree of feasible motions and partitioning it into equivalence classes based on the task predicates. Action plans provide guidance as to which a equivalence class should be further expanded. Information gathered during the motion tree expansion is used to adjust the action costs in order to effectively guide the expansion towards the goal. This interactive process of selecting an equivalence class, expanding the motion tree to implement its action plan and updating the action costs and plans to reflect the progress made is repeated until a solution is found. Experimental validation is provided in simulation using a robotic vehicle to accomplish sophisticated pick-and-place tasks. Comparisons to previous work show significant improvements.
DOI: 10.6084/m9.figshare.3083965.v1
title: Data in 2012-2014 .xlsx

description: Data of Study on light interception and biomass production of different cotton cultivar.
DOI: 10.6084/m9.figshare.3083962.v1
title: Interactive search for action and motion planning with dynamics

description: This paper proposes an interactive search approach, termed INTERACT, which couples sampling-based motion planning with action planning in order to effectively solve the combined task and motion planning problem. INTERACT is geared towards scenarios involving a mobile robot operating in a fully known environment consisting of static and movable objects. INTERACT makes it possible to specify a task in the planning domain definition language (PDDL) and automatically computes a collision-free and dynamically feasible trajectory that enables the robot to accomplish the task. The coupling of sampling-based motion planning with action planning is made possible by expanding a tree of feasible motions and partitioning it into equivalence classes based on the task predicates. Action plans provide guidance as to which a equivalence class should be further expanded. Information gathered during the motion tree expansion is used to adjust the action costs in order to effectively guide the expansion towards the goal. This interactive process of selecting an equivalence class, expanding the motion tree to implement its action plan and updating the action costs and plans to reflect the progress made is repeated until a solution is found. Experimental validation is provided in simulation using a robotic vehicle to accomplish sophisticated pick-and-place tasks. Comparisons to previous work show significant improvements.
DOI: 10.6084/m9.figshare.3084319.v5
title: IJEE Educational Data Mining

description: Histograms and results of k-means and Ward's clustering for IJEE special issue<br><br>The fileset contains information from three sources:<br><br>1. Histograms (two files):<br>* Lexical_histogram.png (histogram of lexical errors ratios)<br>* Grammatical_histogram.png (histogram of grammatical erros ratios)<br><br>2. K-means clustering (eight files):<br>* elbow-lex.png (clustering by lexical aspects: error curves obtained for applying elbow method to determinate the optimal number of clusters)<br>* cube-lex.png (clustering by lexical aspects: a three-dimensional representation of clusters obtained after applying k-means method)<br>* Lexical_clusters (table).xls (clustering by lexical aspects: centroids, standard deviations and number of instances assigned to each cluster)<br>* elbow-gram.png (clustering by grammatical aspects: error curves obtained for applying elbow method to determinate the optimal number of clusters)<br>* cube-gramm.png (clustering by grammatical aspects: a three-dimensional representation of clusters obtained after applying k-means method)<br>* Grammatical_clusters (table).xls (clustering by grammatical aspects: centroids, standard deviations and number of instances assigned to each cluster)<br>* elbow-lexgram.png (clustering by lexical and grammatical aspects: error curves obtained for applying elbow method to determinate the optimal number of clusters)<br>* Lexical_Grammatical_clusters (table).xls (clustering by lexical and grammatical aspects: centroids, standard deviations and number of instances assigned to each cluster)<br><br>3. Ward’s Agglomerative Hierarchical Clustering (three files):<br>* Lexical_Cluster_Dendrogram_ward.png (clustering by lexical aspects: dendrogram obtained after applying Ward's clustering method).<br>* Grammatical_Cluster_Dendrogram_ward.png (clustering by grammatical aspects: dendrogram obtained after applying Ward's clustering method)<br>* Lexical_Grammatical_Cluster_Dendrogram_ward.png (clustering by lexical and grammatical aspects: dendrogram obtained after applying Ward's clustering method)<br>* Lexical_Grammatical_clusters (table).xls: Centroids (from column 2 to 7) and cluster sizes (last column) obtained by applying Ward's agglomerative hierarchical clustering to lexical and grammatical error ratios.<br>* Grammatical_clusters (table).xls: Centroids (from column 2 to 4) and cluster sizes (last column) obtained by applying Ward's agglomerative hierarchical clustering to grammatical error ratios.<br>* Lexical_clusters (table).xls: Centroids (from column 2 to 4) and cluster sizes (last column) obtained by applying Ward's agglomerative hierarchical clustering to lexical error ratios.<br><br>
DOI: 10.6084/m9.figshare.3083830
title: ELIXIR in a Business Model Canvas

description: The Business Model Canvas (BMC) is strategic management tool that is used in handling business models in environments where they need to be created, discussed, challenged and possibly redesigned.<br>The ELIXIR-PT node assembled a team to use this tool in a challenging discussion. The exercise consisted in using perceived information manually extracted from the public websites of the ELIXIR-PT and ELIXIR Hub to populate two improvised BMC. Then, we used group discussions to challenge and refine these models until the majority around the table agreed on the successive modifications.<br>The agreed models represent what is perceived from the websites, if we were to define them as businesses, with terms chosen by the team in an attempt to use a unified language, and to refine the value propositions and the relations with the other elements of the models.<br><br>The ELIXIR-PT Business Model<br>The technique was used to highlight the way in which the identified core values relate with the planned activities, resources and partnerships. <br>Competences in Woody Plants and Elixir Branding emerged as proposed values, while the enhancement of the relations with the Bioengineering and Biomedical communities were identified as important targets for the generation of added value.<br>This model can undergo further refinements, but it can already be used to inform and think strategically about the ongoing building of BIODATA.PT (the major infrastructural support of the node in the scope of the Portuguese Roadmap of Research Infrastructures).<br><br>The ELIXIR Hub Business Model
DOI: 10.6084/m9.figshare.3083842
title: Metabolite BridgeDb ID Mapping Database (20160113)

description: BridgeDb ID mapping database for metabolites, using HMDB 3.6, ChEBI 135, and Wikidata (13 January 2016) as data sources.
DOI: 10.6084/m9.figshare.3083800
title: Hospitalizations in pediatric patients with immune thrombocytopenia in the United States

description: To examine utilization and outcomes in pediatric immune thrombocytopenia (ITP) hospitalizations, we used ICD-9 code 287.31 to identify hospitalizations in patients with ITP in the 2009 HCUP KID, an all-payer sample of pediatric hospitalizations from US community hospitals. Diagnosis and procedure codes were used to estimate rates of ITP-related procedures, comorbidity prevalence, costs, length of stay (LOS), and mortality. In 2009, there were an estimated 4499 hospitalizations in children aged 6 months–17 years with ITP; 43% in children aged 1–5 years; and 47% with emergency department encounters. The mean hospitalization cost was $5398, mean LOS 2.0 days, with 0.3% mortality (<i>n</i> = 13). With any bleeding (15.2%, including gastrointestinal 2.0%, hematuria 1.3%, intracranial hemorrhage [ICH] 0.6%), mean hospitalization cost was $7215, LOS 2.5 days, with 1.5% mortality. For ICH (0.6%, <i>n</i> = 27), mean cost was $40 209, LOS 8.5 days, with 21% mortality. With infections (14%, including upper respiratory 5.2%, viral 4.9%, bacterial 1.9%), the mean cost was $6928, LOS 2.9 days, with 0.9% mortality. Septic shock was reported in 0.3% of discharges. Utilization included immunoglobulin administration (37%) and splenectomies (2.3%). Factors associated with higher costs included age &gt;6 years, ICH, hematuria, transfusion, splenectomy, and bone marrow diagnostics (<i>p</i> &lt; 0.05). In conclusion, of the 4499 hospitalizations with ITP, mortality rates of 1.5%, 21%, and 0.9% were seen with any bleeding, ICH, and infection, respectively. Higher costs were associated with clinically significant bleeding and procedures. Future analyses may reveal effects of the implementation of more recent ITP guidelines and use of additional treatments.