Disaster prone II in Mt. Slamet, Indonesia presents the highest risk for human settlement. To live in this natural disaster-prone area, specific household characteristics are essential. Household capitals and transformation in process and structure were supported by the disaster management framework. However, households in disaster prone II area had limited assets and were required to identify factors influencing disaster management. To study the factors influencing household disaster management capacities, this research, using the sample measurement of Becker and Hursh-Cesar, collected data of 538 households spread across five villages in the disaster prone II area of Mt. Slamet. Sequential mixed methodology combining both qualitative and quantitative research methods were used: samples in the Rukun-Warga-level area were collected by a two-stage stratified random sampling, and to choose the sample of households systematic random sampling was employed. Path analysis through Stata was carried out to analyse the direct and indirect factors supporting disaster management capacity, and multicollinearity was tested before path analysis. This research found direct and indirect effects of household characteristics and household capitals on disaster management. This could be influenced by the transformation in process and the structure of the local government. The quantitative result has been confirmed by the result of the qualitative methodology. Social capital owned by households in disaster-prone area supports disaster management practices. The household relationship and networking access has been strongly supported by disaster management capacities. Disaster management capacities of households in disaster prone II areas could be improved by both internal and external factors. Internal factors include supporting the household members’ health and increasing the size of land and vehicle owning. Meanwhile, external factors has been applied by the policy published by government as to improve the social and cultural belief of households. Household is the proper unit analysis applied in each of the sustainability livelihood approaches. Based on the literature review, the concept could be applied to support vulnerable households in areas prone to high risk of disasters.It is essential for households in disaster-prone areas to have disaster management capacities to ensure their safety and survival when faced with hazardous events  in Java Island, with more than 50 eruptions recorded since 1988. Mt. Slamet borders five districts in Central Java province, namely, Brebes, Banyumas, Purbalingga, Tegal and Pemalang. From March 2014 to January 2015, Mt. Slamet started to have unpredictable fluctuation in seismic activity. Huge explosions occurred in March, August and September 2014, which were the biggest explosions compared to the previous ones in the 20th century. The Indonesian government has identified three disaster-prone areas based on the length of the mountain peak . Disaster is defined as a serious disturbance to the functioning of a society that influences loss of human life, materials and environment, which impacts the capability of the society to cope using its own resources UN . To analThe development of disaster management cognition is described in Hyogo Framework Action was formulated in 2005–2015, which focussed on reducing the risk of vulnerable population from many disaster scenarios. The framework explained the cycle of the disaster event before, during and after the occurrence of the disaster as stated in the mitigation, preparedness, response and recovery phase. Disaster management is defined as comprehensive and integrated activities to cope with the cycle of disaster events. This research is aimed at analysing the disaster management capacities that are linked to the integrated activities on mitigation, preparedness, response and recovery phase. However, there are factors that influence the disaster management, such as household characteristics, household capitals and transformation on process and structures.Based on literature review and development of concept, this research define the definition of term for disaster management and livelihoods as follow:disaster management as a household plan, practice and action for those who live on the border of the disaster prone II area to reduce the risk and recover from the impact of volcanic disaster through integrated activities on mitigation, preparedness, response and the recovery phaselivelihoods as household capitals that influence the transforming structure and process to have access to livelihood resources.Transforming structure and process as an institution and policy interaction supported by the local culture and belief practices. The definition of terms brought three hypotheses that need to be examined in this study:Hypothesis 1: Households that lived in disaster prone II areas having more specific characteristics on occupation, dependency ratio, labour force, healthy house members, migration, size of land, amount of machine goods and vehicles influenced disaster management.Hypothesis 2: Household capitals of those who lived in disaster prone II areas, which consist of certain human capital, social capital, natural capital, physical capital and financial capital, influenced disaster management.Hypothesis 3: Transformation on process and structure, which consists of land-use management, spiritual practices and cultural implementation for households that lived in the disaster prone II areas, influenced disaster management.Through the hypotheses, a semi-structured guideline was developed and factors influencing disaster management practices were described. Qualitative approach was used to further describe how each of the factors in SLA supports disaster management practices. This research aimed to describe the factors influencing the livelihoods of the households that lived on the border of the disaster prone II area of Mt. Slamet, Indonesia.This study used sequential mixed methods, which start with quantitative methods, and had the household as the unit of analysis. As the study area was in the disaster prone II area, the population was spread across five subdistricts of 4268 households. To select the study area, a two-stage stratified sampling was used to choose three districts based on the most impacted areas during previous eruptions. Villages in each district were chosen based on their location in the disaster prone II area of Mt. Slamet. The samples were measured by Backstrom and Hursh-Cesar  formula β (unstandardised beta coefficient) and interpretation. Multicollinearity could be used in three ways: (1) examination of the correlation matrix, (2) variance inflation factor (VIF) and (3) eigen-system analysis of correlation  with multivariate analysis using the Stata version 14 programme. Content validity and measurement of reliability were performed, with Cronbach’s alpha at 0.908, to check the quality of the data. Content validity was performed by sending the questionnaire to an expert in environmental studies and disaster management to make improvements to the questionnaire. The experts were selected based on their expertise: two experts from the field of natural resource management and one from statistics. As this study employed multivariate analysis on path analysis, multicollinearity diagnostic was employed to examine the correlation between IVs. This could cause several problems with the estimation of on Joshi . This stThe second phase of the study was carried out using qualitative methods. These methods used focus group discussions for three different groups: head of the village, rescue team and head of the household. Each group represented five villages that were selected by previous approach, that is, quantitative methods. It was carried out separately in each group to answer the further description of factors relating to disaster management practices.Ethical approval to conduct the study was obtained from Khon Kaen University (registration number: HE 583022).The results of this study described the factors influencing disaster management in three dimensions: household characteristics, capitals of households and transformation of process and structure. Before the path analysis, this study used the conceptual framework model as depicted in χ²), (2) determining the degrees of freedom of the statistics, (3) considering the desired level of confidence of the result of the test, (4) comparing χ² to the critical value from the chi-squared distribution with df (degree of freedom) and adjusted confidence level and (5) determining whether the null hypothesis is accepted or rejected (H0 = no differences between distribution). Through this identification, the whole of the χ² of the 26 variables exceeded the statistical value, which resulted in the rejection of the null hypothesis, or stated that there is a difference between observed data and the expected value.The conceptual framework has been arranged by theoretical reviews and field study in the disaster prone II area of Mt. Slamet. Before the path analysis, the variables need to be analysed for correlation between them. This study used a multicollinearity test to measure the correlation matrix and VIF. The aim of the multicollinearity test is to decrease the exact relationship between predictor variables. To identify the goodness of fit of the model, the study used the Pearson chi-square analysis. This analysis indicates the ‘badness of fit’ of the model and whether the outcome frequencies follow a specified distribution. It is applied in both categorical data and unpaired data from large samples. The computational procedures comprised five steps: (1) calculating the chi-squared test statistics (R squared as 33.44% and is described in This path model has p-level of significance at 0.05). It was further found from the data that most household members who migrate were men, the heads of the household and/or married sons, men who had moved out for education or those who were working in another province. Ho et al. (There were seven IVs having indirect effect (IE) on disaster management through transformation of process and structure as the mediator: labour force, migration (household characteristics), livelihood changing , household networking to others , chemical fertiliser , access to transportation or road  and income . Migration and livelihood changing were found to be unstandardised coefficients with values of -0.0965* and -0.0970*, respectively Local government appointed by the villagers took the lead role in introducing disaster maps. Therefore, several areas are aware of both the likely dangers in their place of habitation and the evacuation area or meeting point during an eruption. On the contrary, one of the key informants from Guci explained that the evacuation signs were missing because of the vested interests of another faction in the government who fear that revenue from tourism will decrease. As stated by the participant:… everytime we saw from TNI ABRI (Indonesian soldier) put evacuation sign and meeting point sign; in the next day it will automatically be missing. Someone takes it out and we do not know who and why they take it. You can see Guci does not have the signs now…. When Mt. Slamet indicates higher seismic activities, the preparedness phase begins. During this phase, the households need to be aware of and prepare the survival kit as the next phase could occur anytime. To recognise the warning alarm or warning system owned by each local area is the most important capacity of each household member. Networking with other households living in non-risk areas is needed to encourage households that live in disaster prone II areas. Improving the physical capital, such as road access, plays an important role in the preparedness phase before the actual eruption or response to an eruption. However, one of the places closest to the peak of Mt. Slamet has a limitation with the quality of infrastructure, mainly concerning the road for evacuation. Statement by participant:… local government has agreed but the making of the road took long time. We are running out of our patience, so we keep it that way. The most important road is the evacuation road; it is the road that made us die during evacuation because we could not pass using car or motorcycle, but only bare foot. How can we do the evacuation during Mt. Slamet eruption …. Limitations with regard to physical capital resulted in less disaster management practices. Transformation in process and structure is addressed related to land-use management, spiritual implementation and cultural practices. Land-use management is the practice of cutting lesser number of trees and retaining the trees to strike an environmental balance with nature. In this area, most of the households were Muslim and followed the practices of Islam. Cultural practices have been described as the traditional and customary practices of a cultural group, for example, the Ruwat Bumi event. Households from Guci described Ruwat Bumi as an annual event that is celebrated in collaboration with the local government for Mt. Slamet, and most of the households invite tourists to their area and thus increase their income.p-value of 0.05  labour force, (2) number of healthy household members, (3) migration, (4) amount of vehicles and (5) size of land. These were the specific household characteristics which could influence the disaster management for households that lived in the disaster prone II area of Mt. Slamet. The result of this hypothesis is in line with the concept of Onuma, Shin and Managi , who desThe second hypothesis is in line with the core concept of the research by Lewis  and WisnThe third hypothesis described three parts that were explained as land-use management, spiritual implementation and cultural practices. However, the variable of transformation of process and structure had a positive influence on disaster management and played a role to bridge the gap between some variables of household characteristics and the capitals of households. In line with this hypothesis, the researcher has proven that the transformation of process and structure has a positive influence on disaster management as the outcome activities for households that lived in the disaster prone II area of Mt. Slamet. It is supported by DFID  and Scoo


The implementation of innovative eLearning platforms offers numerous benefits, but it is important to understand individual acceptance and use of new technological systems in the educational setting. This study adopts a modified version of the Technology Acceptance Model (TAM), including three service quality constructs as external variables, to assess students’ acceptance of PerLE, a Moodle-based eLearning platform developed at the University of Calabria . A six-section questionnaire, which was based on previous studies, was administered to 293 undergraduate students. Results show that the quality of online courses is the main construct that affects students’ acceptance of PerLE. We found also that the PerLE user interface was a critical issue, requiring improvements to facilitate ease of use. In addition, the study underlines the important influence of Technical Support as an antecedent to the two main constructs of the TAM: PerLE Usefulness and PerLE Ease of Use. When used in educational contexts, eLearning environments have numerous aspects that require constant evaluation . EvaluatBlended learning which focuses on learner-centeredness is a significant component of current university educational approaches ,5. FurthAlthough formal instruction is still predominant in the classroom, the diffusion of web-based and related technologies extends the range of application of instructional design practices with the support of numerous software solutions. These both facilitate the learning process and motivate students to use them autonomously .The current educational trend is to design not only more advanced eLearning environments but also to apply consolidated theoretical models to evaluate both the levels of users’ interaction and their acceptance of the system . A recenTo investigate the acceptance factors for the PerLE platform for students enrolled on blended learning courses;To examine the profile of students involved in blended learning teaching modalities;To evaluate the importance of the role of technical support, user interface, and course materials in influencing user response to the platform.We resolved to adapt the Technology Acceptance Model (TAM), which was originally proposed by Davis , who sugThe paper has seven sections: the present introduction, the theoretical background for the study, the research hypotheses, method, results, discussion, and the conclusion.The TAM constitutes a valid approach in explaining and predicting both acceptance and usage behaviour of information technologies . It mainIncreasingly, international researchers in education have adopted the TAM to explore the extent of learner acceptance of eLearning systems as new learning environments ,13,14,15One study applied the TAM to evaluate methodological and technological improvements deriving from the introduction of a Moodle-based eLearning system in an online Italian university. It considered all system users and made use of additional information related to the system in the evaluation. Results confirmed the validity of extending the component criteria of the TAM to embrace other factors identifiable as defining characteristics of a given system . In thisPerLE is an open-source digital learning platform and environment whose architecture offers students the opportunity to develop digital skills, to collaborate on community-based activities, and to display their work as well as personal and group initiatives. It also provides the institutional function of housing courses, materials, and project activities, making use of the different approaches available in Blended Learning models. The formal study component is Moodle-based and employs a modularity-based approach, which is understood as the freedom to integrate useful learning objects, software tools, and media, favouring responsiveness to user needs. The interactive icon shown in Encourage self-directed activity management.Promote collaborative learning/community of practice.Develop digital competence and literacy.Integrate use of tools and social media.This enables experimentation with blended learning initiatives aimed at stimulating students to develop digital skills and competencies ,18. The Provision of support materials for study on particular degree courses on the rotation model;Projects for the completion of activities using presentation formats familiar in MOOCs (flipped classroom approach);Projects managed according to a lab rotation model with class/lab time monitoring and support of student activity in the digital environment.In the PerLE platform, didactic materials include:The designers of PerLE believe that the fostering of learning collaboration in an environment open to a range of integrated components is sustainable if the digital environment satisfies expectations related to the use and acceptance of the eLearning proposal. Therefore, access to the platform, navigation to specific course content, and use of functions and tools must be efficient and responsive. These factors promote a positive perception of platform use as well as the provided service, which responds to needs ranging from paced performance on coursework to varied forms of communication, exploration, sharing, and collaboration. To facilitate ease of access to options and menus, PerLE offers support for problems of access, accreditation, and general platform use through tutor support and a help service. Our concept of Blended Learning in PerLE is a response to user requirements and is to be adapted and varied according to perceived needs. This involves gauging the acceptance, motivation, ease of use and perception of efficacy of a potential user, a process that is concomitant with other forms of evaluation carried out by course managers.Results from recent research highlight the TAM as one of the most important information systems theories in eLearning acceptance ,20,21. TThe first construct, Technical Support (TS), consists of intervention by technical staff to assist students in using the platform effectively; it also includes support functions such as telephone, internal messaging, email, and personal tutoring. Quality of technical support influences students’ interest in the acceptance of the technology because as it is related to overall satisfaction . A recenH1. Technical Support has a positive effect on PerLE Usefulness.H2. Technical Support has a positive effect on PerLE Ease of Use.The second construct, PerLE User Interface (PUI), is defined as the extent to which students find the system interface easy to understand by promoting and facilitating the interaction between students and the educational tool. The quality of the User Interface is critical to the design and development of technological applications and it should satisfy the usability criteria ,26. ThusH3. PerLE User Interface will positively affect PerLE Usefulness.H4. PerLE User Interface will positively affect PerLE Ease of Use.Lastly, the third construct, Online Course Lesson (OCL), defines the extent to which educational learning contents are developed to fit students’ needs. This function denotes all educational materials that the teachers create and publish in their own dedicated course areas. It is a repository where students can download or initiate interactive didactic contents on specific topics. Currently, there are several types of course content available, ranging from course-specific materials to guided projects on specific subjects.The quality of online educational materials is another central factor in the success of an eLearning platform . StudentH5. Online Course Lesson has a positive effect on PerLE Usefulness.H6. Online Course Lesson has a positive effect on PerLE Ease of Use.In accordance with the TAM model, two belief variables, PerLE usefulness and PerLE ease of use, were included and represent the determinant variables that influence user acceptance of the technological system. Perceived usefulness of PerLE can be defined as the “degree to which an individual believes that using a particular system will enhance his or her performance” . For itsH7. PerLE Ease of use affects PerLE Usefulness.H8. PerLE usefulness has a positive effect on PerLE System Usage.H9. PerLE Ease of Use has a positive effect on PerLE System Usage.The dependent variable is PerLE System Usage (PSU), which defines students’ use of the system and their behaviour. We excluded the Intention to Use variable because, as previous studies indicate, even if a student’s attitude towards web-based learning is positive, they may have no intention to use one unless their lecturers consider this necessary ,29.The following sections provide a detailed description of how the study was conducted in terms of participants, data collection, instrument design; it also includes the procedure for statistical analysis.Our study involved 293 undergraduates who used PerLE during course-related activities. Only students who had accounts and had used PerLE for nearly a year prior to the study completed the questionnaire. These parameters were set to test the effective learning potentialities of PerLE in terms of acceptance. An email was sent to all second-year students  on all courses available in PerLE, inviting them to participate. The response rate within the specified time was 36.6%. The data were collected from November 2016 to February 2017 using the open source software, LimeSurvey. The language used was Italian. The first page of the questionnaire emphasized the voluntary nature of participation and the possibility to interrupt questionnaire completion at any time. Anonymity was guaranteed and participants were informed that the data would be used only for research. Other information collected included self-perception of personal competences in the use of information technologies, with 63.6% of the respondents reporting a basic level, 73.7% intermediate, and 54.6% advanced, with time spent using PerLe per week . The study procedures were in compliance with the Helsinki Declaration of 1975 and the Code of Ethics of the Italian Psychology Association (AIP).During the development of the questionnaire, the items of the TAM constructs were adapted, with minor language modifications, from previously validated questionnaires used in the context of eLearning frameworks . The queThe last part of the questionnaire included items with different categories of answers, which related to the demographic profile of the students and other relevant information about eLearning and the use of PerLE.The Statistical Package for the Social Sciences (SPSS ver. 24) was used to perform descriptive, reliability, and other statistical analyses. Participants who did not respond to one or more items, with the exception of the profile section, were excluded. Convergent and discriminant validity were computed to assess the construct reliability. Convergent validity tests whether the items of a construct that are expected to be related are highly correlated . Composi2) [2/df), where values of less than 3.0 were considered to reflect a good model fit [A Structural Equation Modeling (SEM) was produced to test the proposed TAM aimed at examining the acceptance of PerLE. Data were analyzed by using Mplus . Taking2) , an adju2) ,34. To todel fit . Resultsodel fit ; the Rooodel fit .Potential model adjustments were based on modification indices, as provided in the Mplus output. Following the advice of Byrne , we consThe results of the CFA showed a good measurement fit to the data . The prop > 0.05), rejecting both hypothesis 1 and PerLE Ease of Use  as well as hypothesis 2.We found no significant relationship between Technical Support and PerLE Usefulness . Hypothesis 4, which involved PerLE User Interface and PerLE Ease of Use , was accepted. Hypothesis 5 supported the relationship between Online Course Lessons and PerLE Usefulness . Online Course Lesson was also positively related to PerLE Ease of Use , confirming hypothesis 6. A positive and significant relationship was found between PerLE Ease of Use and PerLE Usefulness , confirming hypothesis 7. PerLE System Usage was related positively and significantly both to PerLE Usefulness , supporting hypothesis 8 and to PerLE Ease of Use , confirming hypothesis 9. Lastly, we found a positive and significant relationship between Technical Support and PerLE System Usage . The R-Square results indicate that the predictor variables  explained the 70% for PerLE Usefulness and the 61% for PerLE Ease of Use. In turn, PerLE Usefulness and PerLE Ease of Use explained the 61% for PerLE System Usage. The cause of the other remaining variance of the aforementioned predictors is unknown.Hypothesis 3, which was rejected, explored the relationship between PerLE User Interface and PerLE Usefulness . On the basis of previous studies, we decided to select these because this research is the first attempt to evaluate the PerLE platform. We then investigated the students’ technological acceptance, gathering information on technical support, user interface, and course lessons. Future studies should consider the inclusion of other external variables to further extend the TAM, for example, computer self-efficacy , subjectSecond, this study focused only on university students and did not explore the perceptions of teachers on PerLE usage. Future research should address the perceptions of students and teachers and analyse the differences between them to identify their respective requirements. The number of teachers adopting eLearning is on the increase but not in adequate proportion to the numbers of students doing so.Third, we have limited our evaluation to the assessment of the functionalities of the system; the nature of the results suggests the utility of investigating the implications of the positive and negative responses to engagement with applications that are both internal and external to PerLE.Finally, the results of this study may be generalized to other research by considering the Moodle-based nature of the PerLE platform. On the other hand, as a result of the homogeneous nature of the sample, the current results cannot be generalized to other studies. Further investigations should be conducted to verify the validity of the present findings.This study supports the importance of testing students’ acceptance of eLearning platforms, and, in particular, suggests that the quality of online courses is the main construct affecting student acceptance of the PerLE platform. Considering this result, it is essential to the success of an eLearning environment that priority be accorded to constructive course content design. Highly pertinent in this regard is an understanding of student expectations regarding educational materials, didactic resources and tools used for eLearning purposes.The participants involved in the present study were satisfied by the current PerLe user interface. However, we found that participants disliked the Usefulness of the PerLe User Interface, indicating that it required some improvements, especially for enhancing the ease of interaction with the external educational software provided by the platform.In addition, the weak relationship between PerLE Ease of Use and PerLE System Usage demonstrates that developers should ensure the interface be user friendly, supporting students in the course of their interactions. In general, the results of this study contribute to the literature by providing evidence on the students’ acceptance of PerLE, a Moodle-based platform in use for blended learning, by gathering information from undergraduates. The TAM constitutes a helpful theoretical approach to predicting and understanding student acceptance of use of PerLE. It also confirms that to motivate students to use an eLearning system, teachers should make learning more interesting for users with the support of PerLE; this can be achieved by integrating quality materials through stimulating use of the tools available via the platform. Further, teachers need support in designing more user-oriented eLearning content, to minimize difficulties for students in a productive use of the platform. The study underlines the influence of Technical Support as an antecedent of PerLE Usefulness and PerLE Ease of Use. The results of the study provide practitioners  with insights on the use of PerLE in terms of design and the delivery of educational contents as well as on student interaction.


The dynamic nature of technological developments invites us to rethink the learning spaces. In this context, science education can be enriched by the contribution of new computational resources, making the educational process more up-to-date, challenging, and attractive. Bioinformatics is a key interdisciplinary field, contributing to the understanding of biological processes that is often underrated in secondary schools. As a useful resource in learning activities, bioinformatics could help in engaging students to integrate multiple fields of knowledge  and generate an enriched and long-lasting learning environment. Here, we report our recent project in which high school students learned basic concepts of programming applied to solving biological problems. The students were taught the Python syntax, and they coded simple tools to answer biological questions using resources at hand. Notably, these were built mostly on the students’ own smartphones, which proved to be capable, readily available, and relevant complementary tools for teaching. This project resulted in an empowering and inclusive experience that challenged differences in social background and technological accessibility. http://ufq.unq.edu.ar/sbg/education/index.html). The choice of computational tools, with a major role of smartphone applications, made the teaching–learning process easier, dynamic, and accessible. This experience allowed us to build bridges with the participating schools and develop a great commitment toward expanding the project in the near future. The great interest shown by educational communities and the positive responses of students reinforce the idea of bioinformatics as a plausible tool for the learning–teaching of biology.Bioinformatics is an interdisciplinary activity that complements and connects several fields with biology and can also be used as an educational tool for science. During 2017, the Structural Bioinformatics Group at National University of Quilmes in Buenos Aires, Argentina, worked together with public and private schools to promote the usage of bioinformatics towards a better understanding of biology. We performed short biology-oriented programming workshops using Python, aimed at students in different schools, who were later invited to participate in a specially organized and challenging bioinformatics contest ( There have been many difficulties in the last years for the incorporation of information and communication technologies (ICTs) as a strategy for teaching and learning biology in the classroom . In the The usage of integrated technologies in basic education represents a challenge for teachers, who must transform their daily practices in order to inspire real intellectual curiosity in students  12]. Bu. Bu12]. In countries like Argentina, for example, in which new technologies are often accessible to students  were also presented in order to show additional ways to use the language. Internet was only requested for the first meeting for Python installation. Overall, more than 90% of the students completed the practical exercises on their smartphones whereas the rest used netbooks or notebooks.Biology-oriented programming workshops using Python for students and teachers were performed in one private and two public schools from La Plata, the capital city of the province of Buenos Aires, Argentina. These schools were selected on the basis of their willingness to take part in the project and the possibility to accommodate the instructors’ schedule in their weekly activities. Participation of the students in the workshops was voluntary in all cases, although framed in the context of a particular science course like biology or genetics. Although representing schools with different educational goals and infrastructures, the three groups of students that took part comprised similar demographic profiles, with mixed socioeconomic backgrounds and a balanced gender ratio. The workshops were delivered as three weekly 90-minute-long face-to-face classes offered during consecutive weeks, with one teacher or teaching assistant per ten students. They took place in the schools with the technological resources available at each of them, using installed versions of Python 2.7 and/or 3.6 on PCs and students’ smartphones. Online Python terminals . In particular, the different activities proposed during the workshops require basic operations in mathematics, understanding of logical operators, and knowledge of the classical perspective on the molecular basis of information flow from DNA to proteins. Because these contents are included in the shared nucleus of all orientations, students from both years in each school joined a unique, integrated class for the workshop. The contents covered in each class are shown in The workshops were aimed at students of the last years of their secondary school  due to the science background needed to face the biological problems presented during the course. In spite of the public or private nature of the school, the curriculum design in the province of Buenos Aires establishes a common core in natural sciences and mathematics. Apart from this shared nucleus, the students can follow different orientations with additional workload in distinctive subjects  available for the different operating systems (OSs), which may be more or less useful for working in the classroom, depending on the type of tools to create. When developing simple tools that could be run from the interactive interpreter or by loading single scripts, and that only require standard libraries, distributions that offer a Python terminal are sufficient and recommended. There are many Python apps available for Android and iOS, both free and paid, but fewer options can be used in Windows smartphones and are generally not optimal for running external scripts. In https://repl.it/) can perform somewhere between PC and mobile phones, although permanent access to the internet should be provided.For a preliminary evaluation of different standard smartphone platforms, we tested several Python apps using a simple script and recording its calculation times. The script we implemented see  is a “TrIt is also possible to see in A total of 100 students aged between 16 and 19 years old were part of the project, all of them owning a smartphone; 92.9% of the students didn’t have previous programming knowledge, and most of them (87.5%) did not know about bioinformatics. More than half (53.57%) of the participant students were from the natural sciences orientation. Students enrolled in the social sciences (35.71%) and economy (10.72%) orientations also took part in the workshop, showing that the proposal of learning a programming language was transversal and attractive for the students in general.The tools chosen for the workshops  made the teaching–learning process, as well as the exchange of knowledge among students, engaging and effective. As derived from student’s feedback, the exchange of ideas was fluid and the immediacy provided by these technological devices allowed students and teachers to explore different variants for the proposed exercises, generally derived from questions raised in the classroom, making it possible to evaluate several possible paths toward a solution. The biological questions proposed and solved in the workshops see  triggereOur results show that the use of smartphones could help to surmount the limitations related with the availability of computers in high schools. The easy setup of this kind of workshop, based almost entirely in smartphones and thus independent of the available equipment in schools, triggered a great interest of the educational community and generated enthusiastic responses in students. Although it is yet not possible to collect enough evidence to address the impact of our workshops, this novel approach should let students deepen their knowledge and interest in the field by revisiting biological concepts under a new light. The workshop should have also helped students to realize the potential of acquiring programming skills, giving them a tool not only for understanding and experiencing science, but also for developing strategies to help solve different challenges of their future professional life. Altogether, we think that these practices reinforce the notion that bioinformatics provides a suitable framework to improve the learning-teaching experience of biology and programming.S1 FileGuide given to the students for learning Python programming oriented to biology.(DOCX)Click here for additional data file.S2 FileContest questionnaire and examples of final scripts built by the students answering the required contest questions.(DOCX)Click here for additional data file.S3 FileThis script was used for testing different platforms—multiple combinations of smartphones models or PCs, with different OSs and Python versions, or online tools. OS, operating system.(PDF)Click here for additional data file.


The automatic traffic sign detection and recognition (TSDR) system is very important research in the development of advanced driver assistance systems (ADAS). Investigations on vision-based TSDR have received substantial interest in the research community, which is mainly motivated by three factors, which are detection, tracking and classification. During the last decade, a substantial number of techniques have been reported for TSDR. This paper provides a comprehensive survey on traffic sign detection, tracking and classification. The details of algorithms, methods and their specifications on detection, tracking and classification are investigated and summarized in the tables along with the corresponding key references. A comparative study on each section has been provided to evaluate the TSDR data, performance metrics and their availability. Current issues and challenges of the existing technologies are illustrated with brief suggestions and a discussion on the progress of driver assistance system research in the future. This review will hopefully lead to increasing efforts towards the development of future vision-based TSDR system. In all countries of the world, the important information about the road limitation and condition is presented to drivers as visual signals, such as traffic signs and traffic lanes. Traffic signs are an important part of road infrastructure to provide information about the current state of the road, restrictions, prohibitions, warnings, and other helpful information for navigation ,2. This This paper provides a comprehensive survey on traffic sign detection, tracking and classification. The details of algorithms, methods and their specifications on detection, tracking and classification are investigated and summarized in the tables along with the corresponding key references. A comparative study on each section has been provided to evaluate the TSDR methods, performance metrics and their availability. Current issues and challenges of the existing technologies are illustrated with brief suggestions and a discussion on the progress of driver assistance system research in the future. The rest of this paper is organized as follows: In Aiming at standardizing traffic signs across different countries, an international treaty, commonly known as the Vienna Convention on Road Signs and Signals , was agrDespite the well-defined laws in the Vienna Treaty, variations in traffic sign designs still exist among the countries’ signatories to the treaty, and in some cases considerable variation within traffic sign designs can exist within the nation itself. These variations are easier to be detected by humans, nevertheless, they may pose a major challenge to an automatic detection system. As an example, different designs of stop signs in different countries are shown in In terms of research, recently there has been a growing interest in developing efficient and reliable TSDR systems. To show the current state of scientific research regarding this development, a simple search of the term “traffic sign detection and recognition” in the Scopus database has been carried out, with the aim of locating articles published in journals indexed in this database. To focus on the recent and most relevant research, the search has been restricted to the past decade (2009–2018) and only in the subjects of computer science and engineering. In this way, a set of 674 articles and 5414 citations were obtained. The publication and citation trends are shown in A traffic sign database is an essential requirement in developing any TSDR system. It is used for training and testing the detection and recognition techniques. A traffic sign database contains a large number of traffic sign scenes and images representing samples of all available types of traffic signs: Guide, regulatory, temporary and warning signs. During the past few years, a number of research groups have worked on creating traffic sign datasets for the task of detection, recognition and tracking. Some of these datasets are publicly available for use by the research community. The detailed information regarding the publicly available databases are summarized As aforementioned, a TSDR is a driver supportive system that can be used to notify and warn the driver in adverse conditions. This system is a vision-based system that usually has the capability to detect and recognize all traffic signs, even those signs that may be partially occluded or somewhat distorted . Its maiTracking is used by some research in order to improve the recognition performance . The thrThe initial stage in any TSDR system is locating potential sign image regions from a natural scene image input. This initial stage is called the detection stage, in which a ROI-containing traffic sign ise actually localized ,23,24. TColor-based methods take advantage of the fact that traffic signs are designed to be easily distinguished from their surroundings, often colored in highly visible contrasting colors . These cIn color-based approaches, the captured images are partitioned into subsets of connected pixels that share similar color properties . Then thColor thresholding segmentation is one of the earliest techniques used to segment digital images . General(x)). In , Vazquez(x)). In ,43,44,45(x)). In , a simplRegion growing is another simple and popular technique used for detection in TSDR systems. Region growing is a pixel-based image segmentation method that starts by selecting a starting point or seed pixel. Then, the region develops by adding neighboring pixels that are uniform, according to a certain match criterion, increasing step-by-step the size of the region . This meI and M, each containing n bins, the histogram intersections are defined as [The color indexing method is another simple method that identifies objects entirely on the basis of color . It was fined as :(2)∑j=1nThe match value is then,The advantage of using color histograms is their robustness with respect to geometric changes of projected objects . Howeverk is the normalization parameter and seedS is the seed pixel saturation. The main advantage of this approach is hue instability reduction. However, it fails to reduce other segmentation-based problems, such as fading and illumination. This method was tested in [Another approach to color segmentation is called a dynamic pixel aggregation . In thisested in  on theirThe International Commission on Illumination 1997 Interim Color Appearance Model (CIECAM97) appearance model is another method has been used to detect and extract color information and to segment and classify traffic signs. Generally, color appearance models are capable of predicting color appearance under a variety of viewing conditions, including different light sources, luminance levels, surrounds, and lightness of backgrounds . This moThe Green (Y), Blue (Cb), Red (Cr) (YCbCr) color space has been considered in recent approaches. Different from the most common color space RGB, which represents color as red, green and blue, YCbCr represents color as brightness and two-color difference signals. It was used for detection in , showingJust as traffic signs have specific colors, they also have very well-defined shapes that can be searched for. Shape-based methods ignore the color in favor of the characteristic shape of signs . DetectiThe most common shape-based approach is the Hough transformation. The Hough transformation usually isolates features of a particular shape within a given frame/images . It was Another shape-based detection method is the similarity detection. In this method the detection is performed by computing a similarity factor between a segmented region and set of binary image samples representing each road sign shape . This meDistance transform matching (DTM) is also another type of shape-based detection method. In this method, the distance transform of the image is formed by assigning each non-edge pixel a value that is a measure of distance to the nearest edge pixel. It was used by Gavrila  to captu Gavrila  used DTMAnother popular two colorless traffic sign detection methods are edge detection features and Haar-like features. Edge detection refers to the process of identifying and locating sharp discontinuities in an image . By usinAs previously discussed, both color-based and shape-based methods have some advantages and disadvantages. Therefore, researchers recently have tried to improve the efficiency of the TSDR system using a combination of color- and shape-based features. In the hybrid methods, either color-based approaches take shape into account after having looked at colors, or shape detection is used as the main method but integrate some color aspects as well. In color-based approaches a two-stage strategy is usually employed. First, segmentation is done to narrow the search space. Subsequently, shape detection is implemented and is applied only to the segmented regions . Color aFor robust detection and in order to increase the accuracy of the information used in identifying traffic signs, the signs are tracked using a simple motion model and temporal information propagation. This tracking process is very important for real-time applications, by which the TSDR system verifies correctness of the traffic sign and keeps tracking the sign to avoid handling the same detected sign more than once ,83. The After the localization of ROIs, classification techniques are employed to determine the content of the detected traffic signs . UnderstTemplate matching is a common method in image processing and pattern recognition. It is a low-level approach which uses pre-defined templates to search the whole image pixel by pixel or to perform the small window matching . It was Another common classification method is the random forest. It is a machine learning method that operates by constructing a multitude of decision trees during the training time and outputting the class that is the mode of the output of the class of individual trees. This method was compared in ,93 with Genetic algorithm is another classification method. It is based on a natural selection process that mimics biological evolution, which was used early in this century. This method was used for traffic sign recognition by Aoyagi et al.  and EccaThe other most common method for classification is using an artificial neural network (ANN). This method has gained an increasing popularity in recent years due to the advancement in general-purpose computing on graphics processing units (GPGPU) technologies . In addiAnother increasingly popular method in vision-based object recognition is the deep learning method. This method has acquired general interest in recent years owing to its high performance of classification and the power of representational learning from raw data ,110. DeeAdaptive boosting or AdaBoost is a combination of multiple learning algorithms that can be utilized for regression or classification . It is aSupport vector machine (SVM) is another classification method that contracts an N-dimensional hyper plane that optimally separates the data into two categories. More precisely, SVM is a binary classifier that separates two different classes by a subset of data samples called support vectors. It was implemented as a classifier for traffic sign recognition in ,135,136.In addition to these conventional methods, researchers have used other methods for recognition. In , the SIFTSDR is the essential part of the ADAS. It is mainly designed to operate in a real-time environment for enhancing driver safety through the fast acquisition and interpretation of traffic signs. However, there are a number of external non-technical challenges that may face this system in the real environment degrading its performance significantly. Among the many issues that needed to be addressed while developing a TSDR system are the following issues outlined in Variable lighting condition: Variable lighting condition is one of the key issues to be considered during TSDR system development. As aforementioned, one of the main distinguishing features of traffic sign is its unique colors which discriminate it from the background information, thus facilitating its detection. However, in outdoor environments illumination changes greatly affects the color of traffic sign, making the color information become completely unreliable as a main feature for traffic sign detection. To cope with such challenge, a method based on adaptive color threshold segmentation and high efficient shape symmetry algorithms has been recently proposed by Xu et al. . This meFading and blurring effect: Another important difficulty for a TSDR system is the fading and blurring of traffic signs caused by illumination through rain or snow. These conditions can lead to increase in false detections and reduce the effectiveness of a TSDR system. Using a hybrid shape-based detection and recognition method in such conditions can be very useful and may give more superior performance .Affected visibility: Light emitted by the headlamps of the incoming vehicles, shadows, and other weather-related factors such as rains, clouds, snow and fog can lead to poor visibility. Recognizing traffic signs from a road image taken in such cases is a challenging task, and a simple detector may fail to detect these traffic signs. To resolve this problem, it is necessary to enhance the quality of taken images and make them clear by using an image pre-processing technique. A pre-processing makes image filtration and converts input information into usable format for further analysis and detection .Multiple appearances of sign: While detecting traffic signs mainly in city areas, which are more crowded by signs, multiple traffic sign appearing at a time and similar shape man-made objects can cause overlapping of signs and lead to a false detection. The detection process can also be affected by rotation, translation, scaling and partial occlusion. Li et al. in , used HSMotion artifacts: In the ADAS application, the images are captured from a moving vehicle and sometimes using a low resolution camera, thus, these images usually appear blurry. Recognition of blurred images is a challenging task and may lead to false results. In this respect, a TSDR system that integrates color, shape, and motion information could be a possible solution. In such a system, the robustness of recognition is improved through incorporating the detection and classification with tracking using temporal information fusion . The detDamaged or partially obscured sign: The other distinctive feature of traffic sign is its unique shape. However, traffic signs could appear in various conditions including damaged, partly occluded and/or clustered. These conditions can be very problematic for the detection systems, particularly shape-based detection systems. In order to overcome these problems, hybrid color segmentation and shape analysis based methods are recommended .Unavailability of public database: A database is a crucial requirement for developing any TSDR system. It is used for training and testing the detection and recognition methods. One of the obstacles facing this research area is the lack of large, properly organized, and free available public image databases. According to , for exaReal-time application: The detection and recognition of traffic signs are caught up with the performance of a system in real-time. Accuracy and speed are surely the two main requirements in practical applications. Achieving these requirements requires a system with efficient algorithms and powerful hardware. A good choice is convolutional neural networks-based learning methods with GPGPU technologies .In brief, although lots of relevant approaches have been presented in the literature, no one can solve the traffic sign recognition problem very well in conditions of different illumination, motion blur, occlusion and so on. Therefore, more effective and more robust approaches need to be developed .The major objective of the paper was to analyze the main direction of the research in the field of automatic TSDR and to categorize the main approaches into particular sections to make the topics easy to understand and to visualize the overall research for future directions. Unlike most of the available review papers, the scope of this paper has been broadened to cover all recognition phases: Detection, tracking and classification. In addition, this paper has tried to discuss as many studies as possible, in an attempt to provide a comprehensive review of the various alternative methods available for traffic sign detection and recognition; including along with methods categorization, current trends and research challenges associated with TSDR systems. The overall summary is presented in The conducted review reveals that research in traffic sign detection and recognition has grown rapidly, where the number of papers published during the last three years was approximately 280 papers, which represents about 41.69% of the total number of papers published during the last decade as a whole. With regard to the methods used, it was observed that the subject of traffic sign detection and recognition incorporates three main steps: Detection, tracking and classification; and in each step, many methods and algorithms were applied, each has its own merits and demerits. In general, the methods applied in detection and recognition consider either color or shape information of the traffic sign. However, it is well known that the image quality in real-world traffic scenarios is usually poor; due to low resolution, weather condition, varying lighting, motion blur, occlusion, scale and rotation and so on. In addition, traffic signs are usually in a variety of appearances, with high inter-class similarity, and complicated backgrounds. Thus, proper integration of color and shape information in both detection and classification phases is a very promising and exciting task that is in need of much more attention. For tracking, the Kalman filter and its variations are the most common methods. For classification, artificial neural network and support vector machine-based methods were found to be the most popular methods, with a high detection rate, high flexibility and easy adoptability. Despite the recent improvements in the overall performance of TSDR systems, more research is still needed to achieve a rigorous, robust and reliable TSDR system. It is believed that TSDR system performance can be enhanced by merging the detection and classification tasks into one step rather than performing them separately. By doing so, classification can improve detection and vice versa. Another idea for further improvement of TSDR is by using standard, sufficient and large databases for learning, testing and evaluation of the proposed algorithms. In this way, the TSDR system will be able to recognize the eight different categories of the traffic signs in the real environment with different conditions. This paper will be a useful reference for researchers looking for an understanding of the current status of research in the field of TSDR and finding the related research problems in need of solutions.


Research has shown that inadequate access to water, sanitation, and hygiene (WASH) affects women and girls in several ways, including lowering their participation in the labour market and community activities and contributing to psychosocial stress and poor educational outcomes. There is growing awareness that addressing the gender inequalities related to WASH that many women and girls face on a daily basis must go beyond focusing on delivery of infrastructure and facilities alone and include attention to issues of empowerment. Yet there is limited exploration of how the concept of empowerment is defined and applied in the WASH sector and thus limited information on how it could be measured. This study used concept mapping to uncover the meaning and key dimensions of empowerment in WASH among 34 and 24 stakeholders in Asutifi North District, Ghana, and Banfora Commune, Burkina Faso, respectively. The study was part of initial steps toward choosing indicators for developing an Empowerment in WASH Index. In Ghana and Burkina Faso, 42 and 29 items were generated, respectively. These items were thought to empower men and women in WASH at the household and community levels. In both case studies, 7 clusters were generated and named by participants, and themes related to sharing of information, sociocultural norms, participation, and accessibility of WASH services were associated with empowerment. Some themes were unique to each case study site. Participants also showed a multidimensional and multilevel understanding of empowerment. Concept mapping created an effective balance between individual and group contributions and facilitated accessible, rapid, and contextually relevant data collection. The findings can be used to generate domains of empowerment in future quantitative research as well as inform the design of the Empowerment in WASH Index. •Gender empowerment is central to achieving the water-related Sustainable Development Goals.•Participants operationalized empowerment as a multidimensional and multilevel concept.•There were contextual similarities and differences in empowerment dimensions.•Concept mapping provided a structured process for synthesising ideas. BiologiConsidering these challenges, Sustainable Development Goal 6 (SDG 6) focuses on ensuring availability and sustainable management of water and sanitation for all people, with explicit attention to meeting the needs of women and girls. SDG 6 is critical to achieving SDG 5—“to achieve gender equality and empower all women and girls”—and has importation implications for the health and well-being of women. However, despite the importance of gender outcomes for WASH interventions, focus continues to be placed on measuring progress through improvements in WASH infrastructure, such as access to improved water sources and sanitation facilities . Interve1.2Empowerment in the context of gender and development often refers to the ability of women to take control and make choices about their lives and well-being. Several definitions of empowerment are found in development discourse, with similar themes relating to expansion of agency, choices, opportunities, resources, and power . Kabeer Over the past few decades, considerable research has emphasized the importance of empowerment for poverty reduction and development, and empowerment is often considered a major goal of development interventions and outcomes . For exa1.3Access to water and sanitation is thought to be critical for positive gender outcomes in low and middle-income contexts. Research has shown that inadequate access to water and sanitation affect women and girls in several ways, because of social norms that position them as principal household water collectors and managers. These effects, include low participation in the labour market and community activities, adverse biomedical outcomes, psychosocial stress, and poor educational outcomes . For exabari and to socialize with others.” Water fetching thus became one of the best avenues for women to leverage outdoor mobility and participate in conversations about important things in their lives. The introduction of household tube wells, although important for improved water quality, reduced water collection time/distance and opportunities for socialization among women.These limitations have led to growing calls for gender mainstreaming in the water sector, with the explicit aim of addressing differing water and sanitation needs based on sex and social construction of gender,and inequalities in access to, use of, and control over water and sanitation resources at the household level and beyond . HoweverA number of frameworks, including those describing social capital  and capaTo generate better evidence on the relationship between empowerment and WASH and health outcomes, more systematic approaches are needed to track changes, such as those developed in other sectors  . The obj1.4Workshops were conducted in 2 sites to investigate local understanding of empowerment in Ghana and Burkina Faso. In the Asutifi North District and Banfora commune, local authorities and key WASH stakeholders launched WASH master plans in 2018 that contain a broad vision, programmes, and key strategies for implementing a 13-year initiative to achieve universal access to WASH services by 2030. This study was initiated together with IRC WASH, an international WASH nongovernmental organization (NGO) supporting the development of the district and commune master plans. Findings from this study will contribute to the development of better approaches for assessing progress toward the SDG targets for universal access to water and sanitation, with a particular focus on equity and empowerment.Asutifi North District has a projected population of approximately 62,816 people . The DisBanfora commune, in the Cascades region of Burkina Faso, has approximately 162,000 inhabitants and comprises 22 villages and 15 urban sectors. Economic activities include agriculture, livestock husbandry, and industries such as mining, which all require reliable access to water. Surveys conducted in 2017 indicated that only 69% of the population in Banfora had access to basic water services, while 28% had access to basic sanitation services . In the 2We used group concept mapping as a participatory research method to achieve the study objective. Concept mapping is built on ideas drawn from participatory planning, multivariate statistics, program theory, and theory-based judgement . Trochim2.1The preparation often involves participant selection and other preparatory activities such as finalizing the concept mapping process, timeframe, guidelines, and instructions for generating statements, brainstorming, and structuring. A partner NGO in collaboration with the respective local government offices led the participant recruitment process. Participants were purposively selected to represent key stakeholder groups at the district level. In Ghana, participants were selected from the district assembly, queen mothers’ association, chiefs, disabled groups, women groups, youth groups, community water committees, and local government institutions such as the district departments of gender, environment, and social welfare.In Burkina Faso, participants were selected from local government, including Banfora commune and other neighboring communes, NGOs, women's associations and other community groups. In order to maintain diversity, 2 to 4 representatives were recruited from each group. A total of 34  and 23 participants  were recruited in Ghana and Burkina Faso, respectively. The study received ethics clearance from the Health Research Ethics Board at Queen's University at Kingston.2.2what is empowerment? Participants were reminded that the idea is not to build consensus around the definition of empowerment but to exchange ideas on the meaning of empowerment at the household level. Responses to the focal question were written on flip charts visible to all participants. The second major activity involved brainstorming to generate factors that empower men and women in WASH at the household and community levels. Groups were encouraged to list all factors that came up during their discussions. Participants were also encouraged to respect divergent viewpoints and contributions. The list of items generated at the group level was collected by the facilitator after approximately an hour of brainstorming. Individuals were then encouraged to add any item they felt was important that was not included at the group level. This was to accommodate participants who might have been reluctant to publicly present their ideas at the group level. In Ghana, groups generated between 7 and 11 items, with a total of 63 items.The goal of this step was to obtain a list of items related to empowerment in WASH at the household and community levels. In Ghana, stakeholders were divided into 6 groups, comprised of 5–8 members of mixed representation. To start the brainstorming exercise, participants were first asked to respond to the following focus question or prompt: In Burkina Faso, stakeholders were divided into 4 groups made up of 5–7 members. The groups generated between 8 and 14 items, with a total of 32 items. Following the group brainstorming exercise, the research team consolidated all the group items in one final list. Duplicates were removed during the consolidation process and very similar items were grouped into one statement. Groups also examined the final list to clarify local jargons or statements that were not easily understandable to the entire group. After removal of duplicates, 42 items remained in Ghana and 29 items remained in Burkina Faso , Table 32.3Each item from the final list of brainstormed items was written on a set of index cards, with the item on one side and a number on the other side. A complete set of cards was given to each group to sort into piles that made sense to them. Participants were guided by the following instructions: 1) each card can belong to only one pile; 2) all cards cannot belong to one pile; and 3) a single card cannot stand alone as a pile. This was to ensure heterogeneity across piles and avoid one-item piles. Each pile was labeled after the sorting exercise.2.4Representation involves analyzing and presenting of the statements pictorially. The statements and piles were entered into R-CMap , a conce2.5The interpretation focused on the cluster maps. The maps were projected on a screen and each group was asked to discuss the statements under each cluster and then suggest a name or phrase to describe the cluster. After the group naming, all the participants brainstormed together to achieve a common name for each cluster. Hybrid names were used in cases in which the participants could not agree on a single name. Each group then gave a presentation on how each domain (cluster) can serve to empower or disempower individuals at the household and community levels.2.6The last task was to allow participants to rate the statements on 2 dimensions: importance and prevalence. Each participant received the final list of statements and was asked to rate them on a Likert-type response scale  based on importance and prevalence. A statement was rated based on how important it was to the participant or the perceived prevalence of the phenomena represented by the statement. Ratings ranged from 1  to 5 . The item and cluster ratings are shown in the supplementary material.3Final lists of 42 and 29 statements were generated by participants in Asutifi North and Banfora, respectively, after removing duplicates and led to maps of 7 clusters. Determination of the final cluster solution in both cases was driven by the subjective judgement of the research team and participants. Several similar clusters emerged in Asutifi North District and Banfora Commune . These iresponsibilisation,” the concept of participation was emphasized. This included 2 clusters focused on roles and participation within a household and on leadership and taking initiative. Discussion of these themes emphasized the participation of beneficiaries, including vulnerable groups, in WASH planning and programming to ensure diverse needs and interests are considered.Less similar themes were also identified. In Banfora, 2 clusters described ownership of WASH services and responsibility of all actors in management and operation of WASH. In Asutifi, rather than the concept of “Additionally, several clusters were unique to the respective cases. In Asutifi North, a cluster corresponding to health services and land tenure regulations emerged, tying WASH services to the broader institutional context. In Banfora, a cluster emphasized citizen rights to WASH and another emphasized the efficient use of WASH-related resources. These clusters in Banfora emphasized the realization of rights, as well as the duties and responsibilities of WASH users.4Some level of association is often assumed to exist between access to WASH facilities and women's empowerment. Yet studies seldom reflect on the pathways through which access leads to empowerment or vice versa. Evidence from the literature on water security has shown that the use of “access” in a generic way obscures important inequities and capacities that provide context for linking access to empowerment or empowerment to access . For insGroup concept mapping has been applied in a range of health contexts, such as patient-centred care and evaluation . In thisautonomisation that was used in the Banfora concept mapping workshop emphasizing autonomy, compared with the concept of access to power that emerged in the Asutifi North workshop conducted in English. Thus, while these factors can lead to (dis)empowerment and influence the outcomes of WASH interventions, how they are manifested and measured might differ in the 2 contexts.Within the household and community, the findings highlight differing conceptualizations of agency, inclusion, and empowerment based on the cultural context, with a greater emphasis on rights and responsibility in Banfora Commune and on participation in Asutifi North District. For instance, at the household level, participants in Asutifi North District emphasized participation and inclusion of all household members in decision making. In Banfora, there was an emphasis on ownership and the responsibilities of all actors to play their parts in management of WASH. This included sharing of work at the household level and carrying out respective responsibilities, while at the community level it involved greater participation in WASH responsibilities, such as greater engagement of women in WASH management. In Asutifi North, the concept of participation at the community level was related to leadership and taking initiative on decisions, as well as a household's access to power. These differences may be linked to the French translation of empowerment to . Similar to the Women Empowerment in Agriculture Index (WAEI), the EWI will be a multidimensional instrument that can be used to measure an individual's empowerment in WASH at several levels and across several domains.The broader social, cultural, and economic contexts also emerged as something that could constrain empowerment and agency to make WASH-related decisions or realize rights. For instance, in Asutifi North District, socioeconomic factors were reported, such as low income, physical disability, time use, and tenancy regulations. These factors have wider impacts on how people access, negotiate, and use WASH services. Although the clusters related to these issues seem outside the domain of the household, they influence women's empowerment in complex ways. For example, prevailing human rights, local governance systems, and economic circumstances affect women's decision-making power or participation in WASH activities. Thus, empowering men and women in WASH requires close attention to interventions targeted at several levels and areas . In addition, sociocultural norms and traditional behaviours and practices emerged as cluster in both cases, as these norms were viewed constrains to empowerment, such as limiting opportunities for women in decision making at the household and community levels. It is important to note that some of the clusters presented here have been identified as domains of empowerment in the broader literature . For exa4.1Existing frameworks for understanding empowerment often utilize a multilevel approach  and offeWe draw on the results of the concept mapping study and on existing theoretical constructs describing empowerment to generate a conceptual framework of empowerment in WASH . We desc4.2This study has some limitations worth acknowledging. Given that empowerment is a complex concept and is less conceptualized in the WASH sector, there were some conceptual challenges in exploring its dimensions through concept mapping. For example, comparison between the study sites was challenging because some of the clusters emerged based on experiences grounded in the local environment. Thus, the clusters must be interpreted in the light of each district's specific context. The difference in the cluster maps suggests a need for caution in assuming that empowerment or dimensions of empowerment can be uniformly defined across contexts or cultures. In addition, the prompt question used in the workshop focused on household and community levels, where many WASH decisions and participation by users take place, but it did not explicitly explore individual conceptualization of empowerment or the broader institutional sphere.Although the concept mapping approach is suitable for capturing and representing the views of a broad group of stakeholders, the results are dependent on the type of group that participates. The study involved adult participants largely drawn from various stakeholder groups in the study sites. It would be important to consider participants outside this category who face unique WASH challenges. In addition, we are unable to present sex disaggregated data and cluster maps because we did not conduct gender-specific group concept mapping. Finally, balancing the time required for concept mapping discussions with the time demands of the various stakeholders was a practical challenge. Further discussions could have led to modification of clusters or in-depth discussions of pathways linking each statement/cluster with empowerment.5Substantial research has focused on the importance of women's empowerment for poverty reduction and development but overlooked how it occurs in the WASH sector. There are strong potential synergies between SDG 6 and SDG 5, as achieving universal access to safe water and sanitation services (6.1 and 6.2) in households, healthcare centres, schools, and workplaces underpins several targets on gender equality and empowerment. However, provision or improvement in water and sanitation services may not automatically guarantee the empowerment of women and girls in all contexts. Likewise, reducing gender inequalities and empowering women and girls is thought to be critical for the success of WASH interventions, but less research has explored these pathways . The limThe study received ethics clearance from the Health Research Ethics Board at Queen's University, Kingston.Oxford, which is itself funded by UK aid from the UK Department for International Development (DFID). Funding was also provided by the Swedish International Development Cooperation Agency to the Stockholm Environment Institute.This work was supported by an accelerated grant provided by the REACH programme led by Authors declare no conflict of interest.


Artificial intelligence (AI), big data, and ubiquitous robotic companions —the three most notable technologies of the 4th Industrial Revolution—are receiving renewed attention each day. Technologies that can be experienced in daily life, such as autonomous navigation, real-time translators, and voice recognition services, are already being commercialized in the field of information technology. In the biosciences field in Korea, such technologies have become known to the local public with the introduction of the AI doctor Watson in large number of hospitals. Additionally, AlphaFold, a technology resembling the AI AlphaGo for the game Go, has surpassed the limit on protein folding predictions—the most challenging problems in the field of protein biology. This report discusses the significance of AI technology and big data on the bioscience field. The introduction of automated robots in this field is not just only for the purpose of convenience but a prerequisite for the real sense of AI and the consequent accumulation of basic scientific knowledge. T-test, and probability distribution, were working as a biology professor, a biologist at a brewery, and a biologist at an agricultural test field, respectively. Notably, the famous pea breeding experiment of Gregor Johann Mendel provided crucial data for the development of the statistical theories by Pearson and Fischer. Mendel discovered the Laws of Heredity, by which the genetic factors of pea plants are passed on to the offspring according to a certain set of rules to determine the offspring’s trait. All the studies by Mendel, Pearson, and Fischer are equivalent to statistical models that describe the relationship between the genetic factors and the observed traits. The term “error” in statistical models enables explaining the relationship between the two factors with a simple equation, even when their complex mechanical relationship is unknown. In fact, to build an exact mechanistic model of the hereditary DNA and its effect on the generation of yellow peas was not possible based on the existing knowledge. Every cell holds over millions of proteins and an even larger number of metabolites. Interactions between these molecules determine a trait, such as that in yellow peas. The statistical models studied by Pearson and Fischer involved only simple arithmetic operations among the observed trait probabilities; however, their genetic theories were adequately proven and accepted as general law of hereditary. Thus, a good statistical model focuses on having the least errors rather than explaining the exact mechanical relations of the observed phenomenon, and the ‘error’ in a statistical model is essential for the unknown and complex biological phenomenon.Historically, artificial intelligence (AI), which is represented by deep learning, is closely related to biology. To be more precise, the relationship is between statistics and genetics. The prominent statisticians Karl Pearson, William S. Gosset, and Ronald A. Fisher, who created the most well-known statistical theories, such as correlation coefficient, The fundamental principle of the statistical models applies equally to AI (deep-learning) models. Initiated by Marvin Lee Minsky at the Dartmouth Conference, 1965, AI began to attract significant attention  providedCompared with the image or text datasets, biological data are much more complex and multidimensional, with a high level of noise. Thus, an AI model is more appropriate than a simple statistical model for biological datasets. Generally, the main objective of biological research is to uncover the genetic factors that affect a specific trait. In terms of AI model, phenotype labeled genotype data are required but it is never easy to collect more than hundreds of thousands of labeled genotype data like the case of images or texts. A relatively easier way to collect labeled genotype data is to sequence the DNA of a sample with a definite phenotype, such as a disease. The recent advancement of next-generation sequencing (NGS) technology has allowed the systematic collection of labeled data based on phenotype. The most recent example is the EU project that is collecting genomic data of a million patients with cancer, infectious or rare diseases . FortunaSuch problems were recognized by groups researching advanced synthetic biology in the United States and Europe, who went on to apply automated robots to carry out the repetitive and time-consuming biological experiments and to develop software for the integrated management of the complex biological data. This is one of the revolutionary breakthroughs in the production of biological datasets. Notably, the ways of creating a desired genotype—built using DNA components through technology based on synthetic biology—and testing the resulting phenotype using automated robots have led to the unparalleled rapid production of labeled data. Amyris, an American company that specializes in synthetic biology, applied a method to produce new bacterial strains (with different genotypes) every three minutes and succeeded in commercializing 15 products through the course of seven years. Another synthetic biology startup company, Ginkgo Bioworks, attracted a total of 1 billion US dollars from investors for robot-assisted strain design technology in 2017. In addition, companies such as Zymergen and Counsyl are rapidly producing biological data via automated robots and refining the strains and proteins through deep learning, whereas companies like Transcriptic and Riffyn are developing a platform technology that will allow the rapid production and analysis of large quantities of highly complex biological data through the design of cloud-based synthetic biology software. While such private companies in the United States are rapidly developing innovative tools for biotechnology with plentiful capital and manpower, universities and research institutions in developed countries have been establishing Biofoundries with support from the respective Governments. For instance, a Biofoundry known as the Global Biofoundries Alliance, has been formed from 16 institutions from seven nations, for information sharing and the rapid development of automation-based synthetic biology technology [The two fields, biology and statistics, naturally resemble each other. Most biological phenomena arise from the probability-based interactions among myriads of molecules, which can be explained through the statistical concepts of ‘probability’ and ‘error’. In other words, the procedure of getting a result through statistical inference is similar with that of phenotypic expression of a complex biological system in the point of allowing errors and stochasticity. Nonetheless, one of the reasons why AI models have not yet exerted a significant influence in the bioscience field is the lack of a sufficient scale of labeled data with low-speed data production. However, the developments of automated robots and software have enabled precise and rapid performances in the repetitive and time-consuming processes of biological experiments, implying the potential for large-scale labeled genomic data being established in the future. What seems clear is that, thanks to the development of sequencing technology and automated robots, the speed of biological data production has been reduced from ten or more years to within several days, and the future advancements in information technology will further enhance the speed. The improvement in AI models, in line with the accumulation of large-scale data, implies a preoccupancy of basic knowledge and intellectual property with respect to the field of life science with its complex and massive uncharted territories. The first artificial microorganism created by the J. Craig Venter Institute  and the


OBJECTIVES/SPECIFIC AIMS: Addressing Disparities in Asian Populations through Translation research (ADAPT) is a community-research partnership funded by the Tufts Clinical Translational Sciences Institute (CTSI). Founded in 2011, this collaborative brings together 7 Chinatown-serving community-based organizations and academic researchers with the goal of improving health for the local Chinatown community and beyond. The goal of this research project was to document the best practices, lessons learned, and process through which ADAPT has developed and grown. The aim of this project is to disseminate the model to other CTSAs who are currently engaged in METHODS/STUDY POPULATION: We used a combination of qualitative interviews and content analysis to gather data on the evolution of ADAPT over the last 5 years. Current members from both community organizations and the university/medical center were interviewed about their experiences participating in ADAPT. When possible, interviews were recorded and transcribed verbatim. Deidentified transcripts and administrative documents including meeting minutes, conference summaries, bylaws, and mission statements were coded using Dedoose analytic software. RESULTS/ANTICIPATED RESULTS: Established community-based participatory research (CBPR) principles, including mutual respect, transparency, and commitment, are viewed as necessary, but not sufficient. Patience—both with other members and with the group as a work in progress—is highlighted as being a necessary characteristic of participants. Time and funding are 2 of the most important resources, and the majority of members agree that there is no substitute for “skin in the game.” Attempts at last minute, opportunistic engagement were provided as examples of what had not worked. One ongoing tension is the balance between process and product. Individual members are beholden to organizations to different degrees, and the need to produce something in the form of publications or grant money can limit the amount of time members can commit to the collaborative. At the same time, these products are unlikely to materialize if members are not invested in the process of growing and sustaining the collective. DISCUSSION/SIGNIFICANCE OF IMPACT: Out of the 7 community organizations who currently participate in ADAPT, only 1 is explicitly focused on health in the traditional sense. The others are primary service organizations, but because they understand the impact of the social determinants of health on the local community—including housing, employment, education, nutrition, among other factors—the research collaborative is able to leverage the knowledge and expertise of the academic researchers and the community partners to focus on health topics most salient to the local Chinatown community.