ETSI SmartM2M Technical Report 103714: Study for oneM2M Discovery and Query use cases and requirements

The oneM2M system has implemented basic native discovery capabilities. In order to enhance the semantic capabilities of the oneM2M architecture by providing solid contributions to the oneM2M standards, four Technical Reports have been developed. Each of them is the outcome of a special study phase: requirements, study, simulation and standardization phase. The present document covers the first phase and provides the basis for the other documents.The use cases specified in the present document lead to potential requirements, which extend the existing requirements of the use case documented in oneM2M TR-0001 [i.19], clause 12.9 with a focus on the discovery and query capabilities, introducing a direct relation with the semantic aspects and enabling more sophisticated semantic queries as e.g. a capability in the CSE, that takes routing decisions for forwarding a received Advanced Semantic Discovery Query.oneM2M has currently native discovery capabilities that work properly only if the search is related to specific known sources of information (e.g. searching for the values of a known set of containers) or if the discovery is well scoped and designed (e.g. the lights in a house). When oneM2M is used to discover wide sets of data or unknown sets of data, the functionality is typically integrated by ad hoc applications that are expanding the oneM2M functionality. This means that this core function may be implemented with different flavours and this is not optimal for interworking and interoperability.The objective of the present document [i.1] in conjunction with three other ones [i.2], [i.3] and [i.4] is the study and development of semantic Discovery and Query capabilities for oneM2M and its contribution to the oneM2M standard.The goal is to enable an easy and efficient discovery of information and a proper interworking with external source/consumers of information (e.g. a distributed data base in a smart city or in a firm), or to directly search information in the oneM2M system for big data purposes

ETSI SmartM2M Technical Report 103717; Study for oneM2M; Discovery and Query specification development

The oneM2M system has implemented basic native discovery capabilities. In order to enhance the semantic capabilities of the oneM2M architecture by providing solid contributions to the oneM2M standards, four Technical Reports have been developed. Each of them is the outcome of a special study phase: requirements, study, simulation and standardization phase. The present document covers the second phase and provides the basis for the other documents. It identifies, defines and analyses relevant approaches with respect to the use cases and requirements developed in ETSI TR 103 714 The most appropriate one will be selected.The present document develops the specification for the discovery solution selected in ETSI TR 103 715 [i.2] and which simulation is documented in ETSI TR 103 716 [i.3]. The present document specifies candidate solutions while the corresponding standardization proposals are contributed to oneM2M TS-0001 (Architecture) [i.5], oneM2M TS- 0034 (Semantic support) [i.7], oneM2M TS-0033 (Interworking Framework) [i.18], oneM2M TS-0004 (Protocols) [i.19] (other oneM2M TS may be also impacted) with the help of the supporting companies active in oneM2M

ETSI SmartM2M Technical Report 103716; oneM2M Discovery and Query solution(s) simulation and performance evaluation

oneM2M has currently native discovery capabilities that work properly only if the search is related to specific known sources of information (e.g. searching for the values of a known set of containers) or if the discovery is well scoped and designed (e.g. the lights in a house). When oneM2M is used to discover wide sets of data or unknown sets of data, the functionality is typically integrated by ad hoc applications that are expanding the oneM2M functionality. This means that this core function may be implemented with different flavours and this is not optimal for interworking and interoperability.The objective of the present document [i.3] in conjunction with three other ones ETSI TR 103 714 [i.1], ETSITR 103 715 [i.2] and ETSI TR 103 717 [i.4] is the study and development of semantic Discovery and Query capabilities for oneM2M and its contribution to the oneM2M standard.The goal is to enable an easy and efficient discovery of information and a proper interworking with external source/consumers of information (e.g. a distributed data base in a smart city or in a firm), or to directly search information in the oneM2M system for big data purposes.A simulation phase is conducted in parallel and "circular" feedback with respect to the study phase, with the goal to provide a proof of concept, run suitable scenarios provided by previous phases and a performance evaluation to support the selection/development of the Discovery and Query solution. The simulator and the simulation results are documented in ETSI TR 103 716 [i.3] (the present document). An extract of the simulation results is included ETSI TR 103 715 [i.2] and ETSI TR 103 717 [i.4]. A selection of the use cases includes a set of oneM2M relevant configurations scenarios to be considered for the simulation activity described below

ETSI SmartM2M Technical Report 103715; Study for oneM2M; Discovery and Query solutions analysis & selection

The oneM2M system has implemented basic native discovery capabilities. In order to enhance the semantic capabilities of the oneM2M architecture by providing solid contributions to the oneM2M standards, four Technical Reports have been developed. Each of them is the outcome of a special study phase: requirements, study, simulation and standardization phase. The present document covers the second phase and provides the basis for the other documents. It identifies, defines and analyses relevant approaches with respect to the use cases and requirements developed in ETSI TR 103 714 The most appropriate one will be selected

Fulfilling young potential The success of the Wider Horizons Programme

SIGLEAvailable from British Library Document Supply Centre-DSC:m00/14354 / BLDSC - British Library Document Supply CentreGBUnited Kingdo

Calculating the individual probability of successful ocriplasmin treatment in eyes with VMT syndrome: a multivariable prediction model from the EXPORT study

Background/Aims To evaluate predictive factors for the treatment success of ocriplasmin and to use these factors to generate a multivariate model to calculate the individual probability of successful treatment. Methods Data were collected in a retrospective, multicentre cohort study. Patients with vitreomacular traction (VMT) syndrome without a full-thickness macular hole were included if they received an intravitreal injection (IVI) of ocriplasmin. Five factors (age, gender, lens status, presence of epiretinal membrane (ERM) formation and horizontal diameter of VMT) were assessed on their association with VMT resolution. A multivariable logistic regression model was employed to further analyse these factors and calculate the individual probability of successful treatment. Results 167 eyes of 167 patients were included. Univariate analysis revealed a significant correlation to VMT resolution for all analysed factors: age (years) (OR 0.9208; 95% CI 0.8845 to 0.9586; p<0.0001), gender (male) (OR 0.480; 95% CI 0.241 to 0.957; p=0.0371), lens status (phakic) (OR 2.042; 95% CI 1.054 to 3.958; p=0.0344), ERM formation (present) (OR 0.384; 95% CI 0.179 to 0.821; p=0.0136) and horizontal VMT diameter (mu m) (OR 0.99812; 95% CI 0.99684 to 0.99941, p=0.0042). A significant multivariable logistic regression model was established with age and VMT diameter. Conclusion Known predictive factors for VMT resolution after ocriplasmin IVI were confirmed in our study. We were able to combine them into a formula, ultimately allowing the calculation of an individual probability of treatment success with ocriplasmin in patients with VMT syndrome without FTHM

Bioinformatic analysis of identified biomarkers.

<p><b>A.</b> Gene ontology analysis shows proteins involved in fatty acid binding. platelet degranulation. serine protease inhibitor activity and hydrogen peroxide catabolic processes. <b>B</b> Interaction network of identified biomarker candidates involving 18 out of the 19 proteins. Proteins involved in inflammation. acute phase response (including cellular adhesion). signaling via lipid-mediated pathways (including transport) and activation of proteolytic cascades. as well as transcriptional activity are indicated. Red diamonds indicate proteins which are significant after correction for multiple testing. and grey ones are the remainder of the query set. Circles indicate gap-fillers which were added to connect proteins via protein-protein interactions. Direct association between the significant biomarker set are indicated by a bold line. and relate to immune response (immunoglobulin cluster). protease inhibitor activity. and an activation of the peroxisome proliferator-activated receptor signaling pathway/CDC42 signal transduction pathway. as suggested through APOA1 interactions. <b>C.</b> Kyoto encyclopedia of genes and genomes pathway analysis. Statistically relevant biomarker proteins were mapped onto KEGG pathway maps and showed an involvement of fibril formation and inhibition of fibrinolysis in the coagulation cascade and association with arachidonic acid metabolism.</p

Proteins in vitreous humor detected by CE-MS and identified by LC-MS/MS analysis.

<p>*Uniprot accession numbers that can be found on <a href="http://www.uniprot.org" target="_blank">www.uniprot.org</a>; ** Number of peptides observed by CE-MS analysis and sequenced by LC-MS/MS for each identified protein; *** Percentage of peptide coverage of the protein sequence; ****, Number of peptides observed by CE-MS and sequenced by LC-MS/MS in controls or cases.</p