A Human Situation Awareness Support System to Avoid Technological Disasters

In many complex technological systems, accidents have primarily been attributed to human error. In the majority of these accidents the human operators were striving against significant challenges. They have to face data overload, the challenge of working with a complex system and the stressful task of understanding what is going on in the situation. Therefore, to design and implement complex technological systems where the information flow is quite high, and poor decisions may lead to serious consequences, Situation Awareness (SA) should be appropriately considered. A level 1 SA is highly supported in these systems through the various heterogeneous sensors and signal-processing methods but, for levels 2 and 3 there is still a need for concepts and methods. This work develops a system called the Human Situation Awareness Support System (HSASS) that supports the safety operators in an ever increasing amount of available risky status and alert information. The proposed system includes a new dynamic situation assessment method based on risk, which has the ability to support the operators understanding of the current state of the system, predict the near future, and suggest appropriate actions. The proposed system does not control the course of action and allows the human to act at his/her discretion in specific contexts

The effect of educational interventions based on synectics and 5E patterns on students' academic performance in geometry

Background and Objectives: Educating creative people is one of the important goals of educational systems. Undoubtedly, using educational models appropriate to educational content provides a suitable platform for achieving this goal. Innovative and 5 E patterns lead to increasing student creativity. In the innovation model, the student tries to look at the problem with a new perspective and turn it into a familiar problem by analogy and simile. In the 5E inclusive model, the student discovers relationships, solutions, and concepts through participation in a variety of activities. The aim of the present study was to investigate the effect of educational interventions based on innovation and 5E patterns on the academic performance of 9th grade students’ geometry. Methods: The research method was quasi-experimental in which pre-test, post-test design with control group was used. From the statistical population of 9th grade female students of Tehran public high schools, 3 classes, each class included 30 students as a sample, were selected by convenience sampling method. Then two classes were randomly selected as experimental groups of innovation and 5E and one class as control group. Data collection instruments included researcher-made performance tests tailored to innovation models and 5E, while the reliability and validity of these tests were assessed only for group 5E and the results were generalized for innovation groups and 5E. In order to collect the data, at the first phase, performance pre-tests based on the basic geometric concepts were administrated for innovation, 5E and control groups. Then, the content based on innovation and 5E patterns and the traditional method for innovation, 5E and control groups were implemented by the researcher in 8 sessions for 60 minutes in five consecutive weeks. Finally, the researcher-made post-test based on the geometric concepts was run for innovation, 5E and control groups. To analyze the data descriptive statistics (including mean and standard deviation) and inferential statistics containing Kolmogrov Smirnov (to check the normality of the data) and the ANOVA were used by SPSS statistical software. Findings: The results of the research in the descriptive statistics section showed that the mean difference between the pretest tests of the performance tests of the innovation groups with 2.73 and 5E with 3.16 compared to the control group with 0.42 showed significant differences. Also in the inferential statistics section, the results of the ANOVA test for pretests of the innovation, 5E and control groups indicated that the academic level of the students of innovation, 5E and control groups was the same. (0.05 <0.963). The results of the ANOVA test for post-tests of innovation, 5E, and control groups showed that 5E and innovation had a positive effect on the performance of 9th grade students in geometry. (0.00 <0.05). Conclusion: The use of innovation models and 5E led to students’ performance, so the educational system should emphasize the use of the methods that aim to increase interaction and cooperation between students. Therefore, it is suggested that the necessary training should be introduced in the curriculum of teacher training in order to get acquainted with and apply active teaching methods such as Baybi. Also, the content of textbooks should be organized based on active teaching methods, so that these methods can be taught and implemented in teaching materials. This research has been accompanied by limitations that may affect the generalizability of the research findings. Because it is not possible for the researcher to control disturbing variables such as intelligence and gender, these variables have some effect on the results. Also, due to time and space constraints and the issue of necessary permissions, this study was conducted only among 9th grade female students. Naturally, increasing the sample will lead to more accurate results.   ===================================================================================== COPYRIGHTS  ©2020 The author(s). This is an open access article distributed under the terms of the Creative Commons Attribution (CC BY 4.0), which permits unrestricted use, distribution, and reproduction in any medium, as long as the original authors and source are cited. No permission is required from the authors or the publishers.  ====================================================================================

Formal Safety Assessment of a Marine Seismic Survey Vessel Operation, Incorporating Risk Matrix and Fault Tree Analysis

In maritime safety research, risk is assessed usually within the framework of formal safety assessment (FSA), which provides a formal and systematic methodology to improve the safety of lives, assets, and the environment. A bespoke application of FSA to mitigate accidents in marine seismic surveying is put forward in this paper, with the aim of improving the safety of seismic vessel operations, within the context of developing an economically viable strategy. The work herein takes a close look at the hazards in North Sea offshore seismic surveying, in order to identify critical risk factors, leading to marine seismic survey accidents. The risk factors leading to undesirable events are analysed both qualitatively and quantitatively. A risk matrix is introduced to screen the identified undesirable events. Further to the screening, Fault Tree Analysis (FTA) is presented to investigate and analyse the most critical risks of seismic survey operation, taking into account the lack of historical data. The obtained results show that man overboard (MOB) event is a major risk factor in marine seismic survey operation; lack of training on safe work practice, slippery deck as a result of rain, snow or water splash, sea state affecting human judgement, and poor communication are identified as the critical risk contributors to the MOB event. Consequently, the risk control options are focused on the critical risk contributors for decision-making. Lastly, suggestions for the introduction and development of the FSA methodology are highlighted for safer marine and offshore operations in general

Dynamic risk assessment using failure assessment and Bayesian theory

To ensure the safety of a process system, engineers use different methods to identify the potential hazards that may cause severe consequences. One of the most popular methods used is quantitative risk assessment (QRA) which quantifies the risk associated with a particular process activity. One of QRA's major disadvantages is its inability to update risk during the life of a process. As the process operates, abnormal events will result in incidents and near misses. These events are often called accident precursors. A conventional QRA process is unable to use the accident precursor information to revise the risk profile. To overcome this, a methodology has been proposed based on the work of Meel and Seider (2006). Similar to Meel and Seider (2006) work, this methodology uses Bayesian theory to update the likelihood of the event occurrence and also failure probability of the safety system. In this paper the proposed methodology is outlined and its application is demonstrated using a simple case study. First, potential accident scenarios are identified and represented in terms of an event tree, next, using the event tree and available failure data end-state probabilities are estimated. Subsequently, using the available accident precursor data, safety system failure likelihood and event tree end-state probabilities are revised. The methodology has been simulated using deterministic (point value) as well as probabilistic approach. This Methodology is applied to a case study demonstrating a storage tank containing highly hazardous chemicals. The comparison between conventional QRA and the results from dynamic failure assessment approach shows the significant deviation in system failure frequency throughout the life time of the process unit

Modelling the neuroimmune system in Alzheimer's and Parkinson’s diseases

Parkinson's disease (PD) and Alzheimer's disease (AD) are neurodegenerative disorders caused by the interaction of genetic, environmental, and familial factors. These diseases have distinct pathologies and symptoms that are linked to specific cell populations in the brain. Notably, the immune system has been implicated in both diseases, with a particular focus on the dysfunction of microglia, the brain's resident immune cells, contributing to neuronal loss and exacerbating symptoms. Researchers use models of the neuroimmune system to gain a deeper understanding of the physiological and biological aspects of these neurodegenerative diseases and how they progress. Several in vitro and in vivo models, including 2D cultures and animal models, have been utilized. Recently, advancements have been made in optimizing these existing models and developing 3D models and organ-on-a-chip systems, holding tremendous promise in accurately mimicking the intricate intracellular environment. As a result, these models represent a crucial breakthrough in the transformation of current treatments for PD and AD by offering potential for conducting long-term disease-based modelling for therapeutic testing, reducing reliance on animal models, and significantly improving cell viability compared to conventional 2D models. The application of 3D and organ-on-a-chip models in neurodegenerative disease research marks a prosperous step forward, providing a more realistic representation of the complex interactions within the neuro-immune system. Ultimately, these refined models of the neuro-immune system aim to aid in the quest to combat and mitigate the impact of debilitating neuro-immune diseases on patients and their families

Modeling the neuroimmune system in Alzheimer's and Parkinson's diseases.

Acknowledgements: This collaboration was supported by the Stem Cell Network and the Medical Research Council through the “MRC-SCN UK–Canada Regenerative Medicine Exchange Program Awards” (MR/X503125/1). We also thank Nottingham Trent University and the University of Victoria for hosting the research exchange.Parkinson's disease (PD) and Alzheimer's disease (AD) are neurodegenerative disorders caused by the interaction of genetic, environmental, and familial factors. These diseases have distinct pathologies and symptoms that are linked to specific cell populations in the brain. Notably, the immune system has been implicated in both diseases, with a particular focus on the dysfunction of microglia, the brain's resident immune cells, contributing to neuronal loss and exacerbating symptoms. Researchers use models of the neuroimmune system to gain a deeper understanding of the physiological and biological aspects of these neurodegenerative diseases and how they progress. Several in vitro and in vivo models, including 2D cultures and animal models, have been utilized. Recently, advancements have been made in optimizing these existing models and developing 3D models and organ-on-a-chip systems, holding tremendous promise in accurately mimicking the intricate intracellular environment. As a result, these models represent a crucial breakthrough in the transformation of current treatments for PD and AD by offering potential for conducting long-term disease-based modeling for therapeutic testing, reducing reliance on animal models, and significantly improving cell viability compared to conventional 2D models. The application of 3D and organ-on-a-chip models in neurodegenerative disease research marks a prosperous step forward, providing a more realistic representation of the complex interactions within the neuroimmune system. Ultimately, these refined models of the neuroimmune system aim to aid in the quest to combat and mitigate the impact of debilitating neuroimmune diseases on patients and their families