Decision process in large-scale crisis management

International audienceThis paper deals with the decision-aiding process in large-scale crisis such as natural disasters. It consists in four phases: decision context characterization, system modelling, aggregation and integration. The elements of the context, such as crisis level, risk situation, decision-maker problem issue are defined through the characterization phase. At the feared event occurrence, these elements will interact on a target system. Through the model on this system, the consequences to stakes could be assessed or estimated. The presented aggregation approaches will allow taking the right decisions. The architecture of a Decision Support System is presented in the integration phase

Revisiting the Hetero-Fertilization Phenomenon in Maize

Development of a seed DNA-based genotyping system for marker-assisted selection (MAS) has provided a novel opportunity for understanding aberrant reproductive phenomena such as hetero-fertilization (HF) by observing the mismatch of endosperm and leaf genotypes in monocot species. In contrast to conventional approaches using specific morphological markers, this approach can be used for any population derived from diverse parental genotypes. A large-scale experiment was implemented using seven F2 populations and four three-way cross populations, each with 534 to 1024 individuals. The frequency of HF within these populations ranged from 0.14% to 3.12%, with an average of 1.46%. The highest frequency of HF in both types of population was contributed by the pollen gametes. Using three-way crosses allowed, for the first time, detection of the HF contributed by maternal gametes, albeit at very low frequency (0.14%–0.65%). Four HF events identified from each of two F2 populations were tested and confirmed using 1032 single nucleotide polymorphic markers. This analysis indicated that only 50% of polymorphic markers can detect a known HF event, and thus the real HF frequency can be inferred by doubling the estimate obtained from using only one polymorphic marker. As expected, 99% of the HF events can be detected by using seven independent markers in combination. Although seed DNA-based analysis may wrongly predict plant genotypes due to the mismatch of endosperm and leaf DNA caused by HF, the relatively low HF frequencies revealed with diverse germplasm in this study indicates that the effect on the accuracy of MAS is limited. In addition, comparative endosperm and leaf DNA analysis of specific genetic stocks could be useful for revealing the relationships among various aberrant fertilization phenomena including haploidy and apomixis

Designing a Process Mining-Enabled Decision Support System for Business Process Standardization in ERP Implementation Projects

Process standardization allows to optimize ERP systems and is a nec-essary step prior to ERP implementation projects. Traditional approaches to standardizing business processes are based on manually created "de-jure" process models, which are distorted, error-prone, simplistic, and often deviating from process reality. Theoretically embedded in the organizational contingency theory as kernel theory, this paper employs a design science approach to design a process mining-enabled decision support system (DSS) which combines bottom-up process mining models with manually added top-down standardization infor-mation to recommend a suitable standard process specification from a repository. Extended process models of the as-is process are matched against a repository of best-practice standard process model using an attributebased process similarity matching algorithm. Thus, the DSS aims to reduce the overall costs of process standardization, to optimize the degree of fit between the organization and the implemented processes, and to minimize the degree of organizational change re-quired in standardization and ERP implementation projects. This paper imple-ments a working prototype instantiation in the open-source process analytics platform Apromore based on a real-life event log and standardization attributes for the Purchase-to-Pay and Order-to-Cash processes from three SAP R/3 ERP systems at the industry partner

Combining Computational Prediction of Cis-Regulatory Elements with a New Enhancer Assay to Efficiently Label Neuronal Structures in the Medaka Fish

The developing vertebrate nervous system contains a remarkable array of neural cells organized into complex, evolutionarily conserved structures. The labeling of living cells in these structures is key for the understanding of brain development and function, yet the generation of stable lines expressing reporter genes in specific spatio-temporal patterns remains a limiting step. In this study we present a fast and reliable pipeline to efficiently generate a set of stable lines expressing a reporter gene in multiple neuronal structures in the developing nervous system in medaka. The pipeline combines both the accurate computational genome-wide prediction of neuronal specific cis-regulatory modules (CRMs) and a newly developed experimental setup to rapidly obtain transgenic lines in a cost-effective and highly reproducible manner. 95% of the CRMs tested in our experimental setup show enhancer activity in various and numerous neuronal structures belonging to all major brain subdivisions. This pipeline represents a significant step towards the dissection of embryonic neuronal development in vertebrates

Synergistic study of a Danshen (Salvia Miltiorrhizae Radix et Rhizoma) and Sanqi (Notoginseng Radix et Rhizoma) combination on cell survival in EA.hy926 cells

Background: This study investigated the protective effects of the Danshen (DS) and Sanqi (SQ) herb pair on cell survival in the human cardiovascular endothelial (EA.hy926) cell line exposed to injury. Methods: Nine combination ratios of Danshen-Sanqi extracts (DS-SQ) were screened for their protective effects in the EA.hy926 cell line against two different cellular impairments induced by DL-homocysteine (Hcy) – adenosine (Ado) – tumour necrosis factors (TNF) and oxidative stress (H2O2), respectively. The type of interaction (synergistic, antagonistic, additive) between DS and SQ was analysed using a combination index (CI) model. The effects of key bioactive compounds from DS and SQ were tested using the same models. The compound from each herb that demonstrated the most potent activity in cell viability was combined to evaluate their synergistic/antagonistic interaction using CI. Results: DS-SQ ratios of 6:4 (50–300 μg/mL) produced synergistic effects (CI < 1) in restoring cell viability, reducing lactate dehydrogenase (LDH) leakage and caspase-3 expressions against Hcy-Ado-TNF. Additionally, DS-SQ 6:4 (50–150 μg/mL) was found to synergistically protect endothelial cells from impaired cellular injury induced by oxidative damage (H2O2) by restoring reduced cell viability and inhibiting excessive expression of reactive oxygen species (ROS). In particular, the combination of salvianolic acid A (SA) and ginsenoside Rb1 (Rb1) at 4:6 (1–150 μM) showed synergistic effects in preventing cytotoxic effects caused by Hcy-Ado-TNF (CI < 1). This simplified combination also demonstrated synergistic effects on H2O2-induced oxidative damage on EA.hy926 cells. Conclusions: This study provides scientific evidence to support the traditional use of the DS-SQ combination on protecting endothelial cells through their synergistic interactions