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International audience; This paper presents a workflow for the design of transformation processes using different kinds of expert’s knowledge. It introduces POND (Process and observation ONtology Discovery), a workflow dedicated to answer expert’s questions about processes. It addresses two main issues: (1) how to represent the processes inner complexity, and (2) how to reason about processes taking into account uncertainty and causality. First, we show how to use a semantic model, an ontology, and its associated data to answer some of the expert’s questions concerning the processes, using semantic web languages and technologies. Then, we describe how to learn a predictive model, to discover new knowledge and provide explicative models by integrating the semantic model into a probabilistic relational model. The result is a complete workflow able to extensively analyze transformation processes through all their granularity levels and answer expert’s questions about their domains. An example of this workflow is given on biocomposites manufacturing for food packaging.

The study focused on impact of children’s emotional influencing strategies on parental purchasing decision on children’s food. The justification for the study was that it examined how emotional strategies help children to influence parental purchasing decision on children’s food. The specific objective of the study was to examine the extent which children’s emotional influencing strategies affect parents in purchasing food for their children. Survey research design was used. Out of the 400 respondents, 386(97%) were considered valid and used. Simple percentage was used to analyze responses to structured questionnaire items. Multiple regression technique was used to test hypothesis. Results indicated that children’s emotional influencing strategies have a significant effect on parental purchasing decision on children’s food. A major recommendation was that manufacturers and marketers of children’s food products should constantly study children’s emotional behavior with a view to designing food products and communication campaign capable of meeting children’s needs.

The polymer-free biolimus coated stent (BioFreedom) was shown to be superior to bare metal stents in the LEADERS FREE randomized trial in high bleeding risk (HBR) patients treated with 1-month dual antiplatelet therapy (DAPT). However, there is limited outcome data with this device in an all-comers' population.We conducted a prospective single-arm study of patients undergoing percutaneous coronary intervention with the polymer-free biolimus coated stent in 25 centers in France with wide inclusion criteria including multivessel disease, complex lesions, and acute coronary syndromes. The primary endpoint was the incidence of target lesion failure (TLF), a composite of cardiac death or target-vessel myocardial infarction (MI) or clinically indicated target lesion revascularization (ci-TLR) at 1-year. The patient population was classified according to the presence (or not) of HBR criteria according to the recent ARC-HBR definition.Between April 2019 and April 2020, 1497 patients were enrolled. TLF occurred in 101 (6.9%) patients, including cardiac death in 35 (2.4%), target vessel MI in 20 (1.4%) and ci-TLR in 65 (4.5%) of them. There were 491 HBR patients (32.8%) and 1006 non-HBR patients. The median duration of DAPT was 74 days in the HBR group versus 348 days in the non-HBR group (p 0.0001). TLF occurred in 44 (9.2%) of the HBR group and in 57 (5.8%) of the non-HBR group (relative risk 1.62 [95% confidence interval: 1.10-2.41], p = 0015). Compared to the non-HBR group, HBR patients had higher rates of cardiac death (4.4% vs. 1.4%, p = 0.0005) and target vessel MI (2.9% vs. 0.6%, p = 0.0003), but similar rates of ci-TLR. BARC 3-5 bleeding occurred in 6.2% of the HBR group versus 1.4% of the non-HBR group (p 0.0001).In this multicenter all-comers study, HBR patients treated with a polymer-free biolimus coated stent had, compared to non-HBR patients, an increased risk of cardiac death and MI, and despite a shorter duration of DAPT, continued to have higher rates of BARC 3-5 bleeding.

In this work, the screening and quantification of alkaloids, saponins, tannins and cyanogenic glycosides constituents of raw Piper guineense leaves were undertaken. Also post processing and storage studies with the alkaloids, saponins, tannins and cyanogenic glycosides constituents of the sun dried and grated Piper guineense leaves were investigated. The Piper guineense leaves samples used in this study were obtained from some open markets in Benin City, Edo State. Storage facilities used were the open laboratory wherein samples were kept separately in opened and closed containers, as well as at water activities (aw) of 0.23, 0.52 and 0.97. All storages were carried out at ambient conditions and the storage duration was two months. The presence of alkaloids, saponins, tannins and cyanogenic glycosides in the studied Piper guineense leaves were established by the results of the qualitative tests. Findings showed that in the various solvents extracts used, variations occurred in the levels of the phytochemicals examined. Results for the quantitative investigations carried out using raw Piper guineense leaves indicated that among the phytochemicals examined, alkaloids occurred most with a concentration of 6.73±1.25mg/g. In a decreasing order, the sequence of occurrence of the other phytochemicals examined is tannins (2.32±0.18mg/mg), saponins (1.24±0.51mg/g), and cyanogenic glycosides (0.20±0.05mg/g). Further deducible from results was that processing and storage duration positively affected the values of the phytochemicals examined. The noted positive effects were statistically significant (P

There have been several problems caused by sediments which have never been addressed before now in the water supply chain and have therefore been overlooked as not having sizable consequences; however, they actually do and these problems over a period have demanded the attention of sediment in urban water cycle to be given due scrutiny to understand the connection between sediments and the derivative problems in the water supply chain. This review article examines the problems associated with sediments along the water supply chain from the drainage basin, water bodies, treatment plants, water distribution system and end consumers. More so, this review article proposes policies that can be adopted to reduce the influx of sediment in the various stages of the water supply chain.

ANN models are known to give satisfactory results when it comes to simulation and ultimate prediction of events irrespective of the process as far as there are sufficient historical data which the machine learning technique can simulate. However, the process can be modified such that the ANN model can even give better results than it is giving presently; Genetic Algorithm Technique in WinGAmma software was utilized in analysing the dataset in order to select the most relevant combination of input variables from the dataset which will produce better performance of the ANN model and the output was compared with the normal ANN model which utilized all the input variables in the dataset and the GA-ANN model outperformed the ANN model with all input variables, which goes on the show the GA technique is very reliable and a welcome technique in selecting input variables for the optimal performance of the ANN model in simulation and prediction of events. The event simulated in this work is the Daily suspended sediment load with several input variables ranging from present and antecedent parameters of Discharge, Sediment Discharge and Suspended Sediment load. Although the result of the ANN model with all 7 input variables was satisfactory, but the GA-ANN model gave a much better result with lesser but more relevant input variables as selected by the GA technique.

We present different approaches to construct n-Ary relation instances from scientific articles in experimental domains (i.e. food packaging) driven by a Termino-Ontological Resource dealing with the food packaging domain. Our method starts with the identification of partial n-Ary relations in the document tables and seeks to complete them with argument instances from text of the articles. Our approach is based on a new multi-feature representation (i.e. STaRe - Scientific Table Representation) and the n-Ary relation reconstruction based on text-mining methods.

A review of: - Methodologies, methods and tools used for the construction and evaluation of food ontologies - Integration of food ontologies in real world application to solve real world problems