Search results for: platform employment

Authors: Atom Mkhitaryan, Astghik Avetisyan

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We analyze the developments of doctoral education in Armenia since 1990 and the management process. Education and training of highly qualified personnel are increasingly seen as a fundamental platform that ensures the development of the state. Reforming the national institute for doctoral studies (aspirantura) is aimed at improving the quality of human resources in science, optimizing research topics in accordance with the priority areas of development of science and technology, increasing publication and innovative activities, bringing national science and research closer to the world level and achieving international recognition. We present a number of defended dissertations in Armenia during the last 30 years, the dynamics and the main trends of the development of the academic degree awarding system. We discuss the possible impact of reforming the system of training and certification of highly qualified personnel on the organization of third–level doctoral education (doctoral schools) and specialized / dissertation councils in Armenia. The results of the SWOT analysis of doctoral education and academic degree awarding processes in Armenia are shown. The article presents the main activities and projects aimed at using the advantages and strong points of the National Academy network in order to improve the quality of doctoral education and training. The paper explores the mechanisms of organizational, methodological and infrastructural support for research and innovation activities of doctoral students and young scientists. There are also suggested approaches to the organization of strong networking between research institutes and foreign universities for training and certification of highly qualified personnel. The authors define the role of ISEC in the management of doctoral studies and the establishment of a competitive third-level education for the sphere of research and development in Armenia.

Keywords: doctoral studies, academic degree, PhD, certification, highly qualified personnel, dissertation, research and development, innovation, networking, management of doctoral school

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Authors: Rosa L. Figueroa, Joselyn A. Hernández

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During the last couple of years, the Ministry of Health have been developing new health policies in order to regulate and improve in benefit of the patient the pharmaceutical system in our country. However, there are still some deficiencies in how medicines have been accessed, distributed, and sold. Therefore, it is necessary to empower the patient by offering new instances to improve access to drug information. This work introduces ‘the bioequivalent’ a medical drug search tool created to increase both diffusion and getting information about the therapeutic equivalence of medicines for the patient. The development of the search tool started with a study on the availability of sources of drug information accessible to the patient where advantages and disadvantages were analyzed. The information obtained was used to feed the functional design of the new tool. The design of the new tool shows an external interface that includes a header, body, sidebar and footer. The header has a menu containing ‘Home,’ ‘Who we are,’ and ‘Mission and vision.’ The Body contains the medical drug search tool, and the Sidebar is for the user logging in. It could be anonym, registered user, as well as, administrator. Anonym user could only use the tool. Registered users could add some information on existing medicines in the database; however, adding information will be restricted and limited to specific items and subject to administrator approval because the information added must be endorsed by the Chilean Public Health Institute. On the other hand, the administrator will have all the privileges, including creating or deleting drugs or information about them. The Bioequivalent was tested on different mobile devices, and no fails have been found. Moreover, a small survey was answered by ten people who tested the tool, and all of them agree that the tool was useful to get information about bioequivalent drugs, and they would recommend the tool to others. Nevertheless, an 80% of people who tested the tool says it was easy to use, and a 70% indicates that additional help is not required. These results are evidence that ‘the Bioequivalent’ may contribute to the knowledge about the therapeutic bioequivalence and bioequivalent drugs existing in Chile. As future work, the tool will be developed to make it available to the public for a first testing stage in a more massive scenario.

Keywords: collaborative database, bioequivalent drugs, search tool, web platform

Procedia PDF Downloads 222

Authors: Susan Ka Yee Chow

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The Coronavirus disease (COVID-19) reached Hong Kong in 2019 resulting in epidemic in late January 2020. Considering the epidemic development, tertiary institutions made announcements that all on-campus classes were suspended since 01/29/2020. In Tung Wah College, e-learning was adopted in all courses for all programmes. For the undergraduate nursing students, the contact hours and curriculum are bounded by the Nursing Council of Hong Kong to ensure core competence after graduation. Unlike the usual e-learning where students are allowed having flexibility of time and place in their learning, real time learning mode using Blackboard was used to mimic the actual classroom learning environment. Students were required to attend classes according to the timetable using online platform. For lectures, voice over PowerPoint file was the initial step for mass lecturing. Real time lecture was then adopted to improve interactions between teacher and students. Post-lecture quizzes were developed to monitor the effectiveness of lecture delivery. The seminars and tutorials were conducted using real time mode where students were separated into small groups with interactive discussions with teacher within the group. Live time demonstrations were conducted during laboratory sessions. All teaching sessions were audio/video recorded for students’ referral. The assessments including seminar presentation and debate were retained. The learning mode creates an atmosphere for students to display the visual, audio and written works in a non-threatening atmosphere. Other students could comment using text or direct voice as they desired. Real time online learning is the pedagogy to replace classroom contacts in the emergent and unforeseeable circumstances. The learning pace and interaction between students and students with teacher are maintained. The learning mode has the advantage of creating an effective and beneficial learning experience.

Keywords: e-learning, nursing curriculum, real time mode, teaching and learning

Procedia PDF Downloads 106

Authors: Emir Alaca, Hasbi Apaydin, Rohullah Rahmatullah, Necibe Fusun Oyman Serteller

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In recent years, Permanent Magnet Synchronous Motors (PMSMs) have found extensive applications in various industrial sectors, including electric vehicles, wind turbines, and robotics, due to their high performance and low losses. Accurate mathematical modeling of PMSMs is crucial for advanced studies in electric machines. To enhance the effectiveness of graduate-level education, incorporating virtual or real experiments becomes essential to reinforce acquired knowledge. Virtual laboratories have gained popularity as cost-effective alternatives to physical testing, mitigating the risks associated with electrical machine experiments. This study presents a MATLAB-based Graphical User Interface (GUI) for PMSMs. The GUI offers a visual interface that allows users to observe variations in motor outputs corresponding to different input parameters. It enables users to explore healthy motor conditions and the effects of short-circuit faults in the one-phase winding. Additionally, the interface includes menus through which users can access equivalent circuits related to the motor and gain hands-on experience with the mathematical equations used in synchronous motor calculations. The primary objective of this paper is to enhance the learning experience of graduate and doctoral students by providing a GUI-based approach in laboratory studies. This interactive platform empowers students to examine and analyze motor outputs by manipulating input parameters, facilitating a deeper understanding of PMSM operation and control.

Keywords: magnet synchronous motor, mathematical modelling, education tools, winding inter-turn fault

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Authors: Mustafa Tevfik Hebebci, Ismail Sahin, Sirin Kucuk, Ismail Celik, Ahmet Oguz Akturk

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ADDIE is an instructional design model which has the five core elements: analyze, design, develop, implement, and evaluate. The ADDIE approach provides a systematic process for the analysis of instructional needs, the design and development of instructional programs and materials, implementation of a program, and the evaluation of the effectiveness of an instruction. The case-based study is an instructional design model that is a variant of project-oriented learning. Collecting and analyzing stories can be used in two primary ways -perform task analysis and as a learning support during instruction- by instructional designers. Besides, teachers use technology to develop students’ thinking, enriching the learning environment and providing permanent learning. The purpose of this paper is to introduce an interactive online case-study library website developed in a national project. The design goal of the website is to provide interactive, enhanced, case-based and online educational resource for educators through the purpose and within the scope of a national project. The ADDIE instructional design model was used in the development of the website for the interactive case-based library. This web-based library contains the navigation menus as the follows: “Homepage”, "Registration", "Branches", "Aim of The Research", "About TPACK", "National Project", "Contact Us", etc. This library is developed on a web-based platform, which is important in terms of manageability, accessibility, and updateability of data. Users are able to sort the displayed case-studies by their titles, dates, ratings, view counts, etc. In addition, they encouraged to rate and comment on the case-studies. The usability test is used and the expert opinion is taken for the evaluation of the website. This website is a tool to integrate technology in education. It is believed that this website will be beneficial for pre-service and in-service teachers in terms of their professional developments.

Keywords: design, ADDIE, case based library, technology integration

Procedia PDF Downloads 463

Authors: Shahzad A. Mughal, Ameer A. P. Ghaloo, Faisal Laghari, Mohsin A. Mirza

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Job satisfaction and level of job stressors among employees of a university are considered as essential factors responsible for institutional success. Job satisfaction is usually believed as a single baseline variable for the evaluation of a university human resource area. The objectives of this study were to assess the level of job satisfaction and influence of job stressors among university teachers and their association with long term physical health of the employees in government sector universities in Pakistan. A cross-sectional study was conducted on university employees including faculty members and administrative staff of three government sector universities in Sindh province of Pakistan who have completed at least ten years of their job. The study period was six months. All the employees were randomly selected. The job satisfaction scale Questionnaire with yes and no options, together with questions regarding demographic factors, job stress or other working factors and physical health issues were administered in questionnaires. These questionnaires were handed out to 100 faculty members of both genders with permanent job and 50 non faculty staff of grade 17 and above with permanent employment status. Students’ T test and one way ANOVA was applied to categorical variables and Pearson’s correlation analysis was performed to evaluate the correlations between study variables. 121 successful responses were obtained (effective respondent rate 80.6%). The average score of overall job satisfaction was 65.6%. Statistical analysis revealed that the job satisfaction and work related stressors had negative impact on overall health status of the employees with resultant less efficacy and mental stress. The positive relation was perceived by employees for organizational support and high income with job satisfaction. Demographic features such as age and female gender were also linked to the level of job satisfaction and health related issues. The total variation among all responses regarding correlation between job satisfaction job stressors and health related issues was 55%. A study was conducted on University employees of government sector Universities in Pakistan, regarding association of job satisfaction and job stressors with long term physical health of the employees. Study revealed a moderate level of job satisfaction among the employees of all universities included in this study. Attitude and personal relations with heads of the departments and institution along with salary packages were considered as biggest job stressors related correlated directly with physical health. Demographic features and gender were associated factors for job satisfaction. Organizational support was the strongest factor for job satisfaction and results pointed out that by improving support level from University may improve the quality of job satisfaction and overall health of employees.

Keywords: job satisfaction, organizational support, physical health, university employees

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Authors: Daniele Calvi, Loris Franchi, Sabrina Corpino

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Thanks to the latest Mars mission, the planetary exploration has made enormous strides over the past ten years increasing the interest of the scientific community and beyond. These missions aim to fulfill many complex operations which are of paramount importance to mission success. Among these, a special mention goes to the Entry, Descent and Landing (EDL) functions which require a dedicated system to overcome all the obstacles of these critical phases. The general objective of the system is to safely bring the spacecraft from orbital conditions to rest on the planet surface, following the designed mission profile. For this reason, this work aims to develop a simulation tool integrating the re-entry trajectory algorithm in order to support the EDL design during the preliminary phase of the mission. This tool was used on a reference unmanned mission, whose objective is finding bio-evidence and bio-hazards on Martian (sub)surface in order to support the future manned mission. Regarding the concept of operations (CONOPS) of the mission, it concerns the use of Space Penetrator Systems (SPS) that will descend on Mars surface following a ballistic fall and will penetrate the ground after the impact with the surface (around 50 and 300 cm of depth). Each SPS shall contain all the instrumentation required to sample and make the required analyses. Respecting the low-cost and low-mass requirements, as result of the tool, an Entry Descent and Impact (EDI) system based on inflatable structure has been designed. Hence, a solution could be the one chosen by Finnish Meteorological Institute in the Mars Met-Net mission, using an inflatable Thermal Protection System (TPS) called Inflatable Braking Unit (IBU) and an additional inflatable decelerator. Consequently, there are three configurations during the EDI: at altitude of 125 km the IBU is inflated at speed 5.5 km/s; at altitude of 16 km the IBU is jettisoned and an Additional Inflatable Braking Unit (AIBU) is inflated; Lastly at about 13 km, the SPS is ejected from AIBU and it impacts on the Martian surface. Since all parameters are evaluated, it is possible to confirm that the chosen EDI system and strategy verify the requirements of the mission.

Keywords: EDL, Mars, mission, SPS, TPS

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Authors: Thierry Sammour Sawaya, Heikki Deschacht

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In commercial aircraft operations, almost half of the accidents happen during approach or landing phases. Automatic guidance and automatic landings have proven to bring significant safety value added for this challenging landing phase. This is why Airbus and ScioTeq have decided to work together to explore the capability of image-based landing solutions as additional landing aids to further expand the possibility to perform automatic approach and landing to runways where the current guiding systems are either not fitted or not optimum. Current systems for automated landing often depend on radio signals provided by airport ground infrastructure on the airport or satellite coverage. In addition, these radio signals may not always be available with the integrity and performance required for safe automatic landing. Being independent from these radio signals would widen the operations possibilities and increase the number of automated landings. Airbus and ScioTeq are joining their expertise in the field of Computer Vision in the European Program called Clean Sky 2 Large Passenger Aircraft, in which they are leading the IMBALS (IMage BAsed Landing Solutions) project. The ultimate goal of this project is to demonstrate, develop, validate and verify a certifiable automatic landing system guiding an airplane during the approach and landing phases based on an onboard camera system capturing images, enabling automatic landing independent from radio signals and without precision instrument for landing. In the frame of this project, ScioTeq is responsible for the development of the Image Processing Platform (IPP), while Airbus is responsible for defining the functional and system requirements as well as the testing and integration of the developed equipment in a Large Passenger Aircraft representative environment. The aim of this paper will be to describe the system as well as the associated methods and tools developed for validation and verification.

Keywords: aircraft landing system, aircraft safety, autoland, avionic system, computer vision, image processing

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Authors: Sufian Abdo Jilo

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Veterinary services conserve and maintain animal life and improve the living conditions of human beings through improving rural livelihoods and feeding; veterinary services also address global health crises by preventing risks such as emerging pandemic diseases, antimicrobial resistance, contamination of foods, and environmental health problems at their origin. The purpose of this policy brief is to analyze the way veterinary organizations provide services and to propose an optimal organization for veterinary services in developing countries. The current situation of veterinary institutions in developing countries can't counter the challenge related to animal health and productivity. As a result, reorganization, amalgamation, merging, and consolidation of veterinary health services (veterinary clinics, slaughterhouses, quarantine, and veterinary markets) together with the construction of closer veterinary service facilities and the construction of common areas will help institutions to strengthen cooperation among different veterinarians, which is the first steps for the implementation of a One Health platform and multidisciplinary activities. The improvement and reorganization of the veterinary services institutions will also help the veterinary clinics easily obtain various medical chemicals such as blood and rumen from abattoirs, enhance the surveillance of livestock diseases, enable the community to buy healthy animals from the animal market, and help to reduce economic waste. The services can be performed by a small number of veterinarians through a model of specific areas common to all veterinary services. This model improves the skills and knowledge of veterinarians in all aspects of veterinary medicine and saves students and researchers time. Communities or customers can save time by getting all veterinary services at once. It saves the budget on purchasing medical equipment and medicines at each location and avoids expiration dates on medicines. This model is the latest solution to the global health crisis and should be implemented in the near future to combat the emergence and reemergence of new pathogenic microorganisms.

Keywords: abattoir, developing countries, reform, service, veterinary

Procedia PDF Downloads 70

Authors: Kajal Attri

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Introduction: Transgender people are considered third gender in India, although they still face identification issues and alienated from society. Furthermore, they face several challenges, including discrimination in employment, resources, education, and property as a result, most transgender people make a living through begging at traffic lights, trains, and buses; attending auspicious occasions such as childbirth and weddings; and engaging in sex work, which includes both home-based and street-based sex work. During COVID-19, maintaining social distance exacerbates transgender people's circumstances and prevents them from accessing health care services, sexual reassignment surgery, identity-based resources, government security, and financial stability. Nonetheless, the pandemic raised unfavorable attitudes about transgender persons, such as unsupportive family members and trouble forming emotional relationships. This study focuses on how we missed transgender people during COVID-19 to provide better facilities to cope with this situation when they are already the most vulnerable segment of the society. Methodology: The research was conducted using secondary data from published publications and grey literature obtained from four databases: Pubmed, Psychinfo, Science direct, and Google scholar. The literature included total 25 articles that met the inclusion criteria for a review. Result and Discussion: Transgender people, who are considered the most vulnerable sector of society, have already faced several obstacles as a result of the outbreak. The analysis underscores the difficulties that transgender persons faced during COVID-19, such as, They had trouble accessing the government's social security programmes during the lockdown, which provide rations and pensions since they lack the necessary identifying cards. The impact of COVID-19 leaves transgender people at heightened risk of poverty and ill health because they exist on the margins of society, those livelihood base on sex work, begging, and participation on auspicious occasions. They had a significant risk of contracting SARS-CoV2 because they lived in congested areas or did not have permanent shelter, and they were predominantly infected with HIV, cancer, and other non-communicable illnesses. The pandemic raised unfavorable attitudes about transgender persons, such as unsupportive family members and trouble forming emotional relationships. Conclusion: The study comes forward with useful suggestions based on content analysis and information to reduce the existing woes of transgenders during any pandemic like COVID-19.

Keywords: COVID-19, transgender, lockdown, transwomen, stigmatization

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Authors: M. Ntšolo, D. Kalumba, N. Lefu, G. Letlatsa

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Rock mass damage due to shear tectonic activity has been investigated largely in geoscience where fluid transport is of major interest. However, little has been studied on the effect of shear zones on rock mass behavior and its impact on stability of rock slopes. At Letšeng Diamonds open pit mine in Lesotho, the shear zone composed of sheared kimberlite material, calcite and altered basalt is forming part of the haul ramp into the main pit cut 3. The alarming rate at which the shear zone is deteriorating has triggered concerns about both local and global stability of pit the walls. This study presents the numerical modelling of the open pit slope affected by shear zone at Letšeng Diamond Mine (LDM). Analysis of the slope involved development of the slope model by using a two-dimensional finite element code RS2. Interfaces between shear zone and host rock were represented by special joint elements incorporated in the finite element code. The analysis of structural geological mapping data provided a good platform to understand the joint network. Major joints including shear zone were incorporated into the model for simulation. This approach proved successful by demonstrating that continuum modelling can be used to evaluate evolution of stresses, strain, plastic yielding and failure mechanisms that are consistent with field observations. Structural control due to geological shear zone structure proved to be important in its location, size and orientation. Furthermore, the model analyzed slope deformation and sliding possibility along shear zone interfaces. This type of approach can predict shear zone deformation and failure mechanism, hence mitigation strategies can be deployed for safety of human lives and property within mine pits.

Keywords: numerical modeling, open pit mine, shear zone, slope stability

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Authors: P. Bauer, K. Mougin, V. Vignal, A. Buch, P. Ponthiaux, D. Faye

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Nowadays, noble metallic nanostructures with unique morphology are widely used as new sensors due to their fascinating optical, electronic and catalytic properties. Among various shapes, dendritic nanostructures have attracted much attention because of their large surface-to-volume ratio, high sensitivity and special texture with sharp tips and nanoscale junctions. Several methods have been developed to fabricate those specific structures such as electrodeposition, photochemical way, seed-mediated growth or wet chemical method. The present study deals with a novel approach for a controlled growth pattern-directed organisation of Au flower-like crystals (NFs) deposited onto stainless steel plates to achieve large-scale functional surfaces. This technique consists in the deposition of a soft nanoporous template on which Au NFs are grown by electroplating and seed-mediated method. Size, morphology, and interstructure distance have been controlled by a site selective nucleation process. Dendritic Au nanostructures have appeared as excellent Raman-active candidates due to the presence of very sharp tips of multi-branched Au nanoparticles that leads to a large local field enhancement and a good SERS sensitivity. In addition, these structures have also been used as electrochemical sensors to detect traces of molecules present in a solution. A correlation of the number of active sites on the surface and the current charge by both colorimetric method and cyclic voltammetry of gold structures have allowed a calibration of the system. This device represents a first step for the fabrication of MEMs platform that could ultimately be integrated into a lab-on-chip system. It also opens pathways to several technologically large-scale nanomaterials fabrication such as hierarchically ordered crystal architectures for sensor applications.

Keywords: dendritic, electroplating, gold, template

Procedia PDF Downloads 178

Authors: Fizza Saghir

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Rohingyas are an ethnic minority of predominantly Buddhist-Myanmar. Living in ghettos in Rakhine, one of the poorest states of Myanmar, for decades, they have been marginalized, discriminated, deprived of the basic amenities and have faced ghastly violations of their rights- politically, socially, economically and culturally. In 2012, in violence that, erupted between ethnic Rakhine Buddhists and Rohingya Muslims, hundreds of Rohingyas were slayed and many more displaced. The state does not recognize them as ‘citizens’ and the military and police have constantly persecuted and pushed them to either migrate to other countries like India, Bangladesh or else die of deprivation. Amidst the deadly violence, Rohingya women are the most vulnerable. Many of them have faced sexual abuse and gender-based violence. Minimalistic to insignificant studies have been done on the plight of Rohingya women refugees in context of India. Thus, this paper focuses on psycho-social status of Rohingya women refugees settled in Delhi, India. The research study used both quantitative and qualitative methods. It was explorative in nature and used non-probability sampling, purposive sampling, in particular. A sample size of 30 Rohingya women refugees was interviewed out of the universe of 45 Rohingya refugee families living in Kalindi Kunj Refugee Camp of Delhi. Case studies were developed. The paper explores the psychological and social status of the respondents along with a deep understanding of their issues and concerns. Moreover, it assesses the impact of violence and migration on respondents. It was found that Rohingya women refugees are deeply and severely affected by a violent past, an insecure present and an uncertain future. Major problems they face in Delhi, India are finding employment, lack of identity cards to avail government services, language barrier, lack of health and education facilities. All they desire is peace and shelter in India. Besides, recommendations and suggestions have been given to various stakeholders of the forced mass migration of Rohingya refugees which includes, Government of Myanmar, Government of India, other bordering nations of Myanmar, international NGOs and media and the Rohingya community, itself. Only an immediate, peaceful and continuous dialogue process can help resolve the issue of exodus of Rohingyas. Countries, including India, must come together to help the Rohingyas who are in need of urgent humanitarian aid and assistance.

Keywords: dialogue process, ethnic minority, forced mass migration, impact of violence and migration, psycho-social status, Rohingya women refugees, sexual abuse

Procedia PDF Downloads 167

Authors: Noor Hasmini Abd Ghani

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Brand resonance is among of new focused strategy that getting more attention in nowadays by larger companies for their long-term market survival. The brand resonance emphasizing of two main characteristics that are intensity and activity able to generate psychology bond and enduring relationship between a brand and consumer. This strong attachment relationship has represented brand resonance with the concept of consumer brand relationship (CBR) that exhibit competitive advantage for long-term market survival. The main consideration toward this brand resonance approach is not only in the context of larger companies but also can be adapted in Small and Medium Enterprises (SMEs) as well. The SMEs have been recognized as vital pillar to the world economy in both developed and emergence countries are undeniable due to their economic growth contributions, such as opportunity for employment, wealth creation, and poverty reduction. In particular, the facts that SMEs in Malaysia are pivotal to the well-being of the Malaysian economy and society are clearly justified, where the SMEs competent in provided jobs to 66% of the workforce and contributed 40% to the GDP. As regards to it several sectors, the SMEs service category that covers the Food & Beverage (F&B) sector is one of the high-potential industries in Malaysia. For that reasons, SMEs strong brand or brand equity is vital to be developed for their long-term market survival. However, there’s still less appropriate strategies in develop their brand equity. The difficulties have never been so evident until Covid-19 swept across the globe from 2020. Since the pandemic began, more than 150,000 SMEs in Malaysia have shut down, leaving more than 1.2 million people jobless. Otherwise, as the SMEs are the pillar of any economy for the countries in the world, and with negative effect of COVID-19 toward their economic growth, thus, their protection has become important more than ever. Therefore, focusing on strategy that able to develop SMEs strong brand is compulsory. Hence, this is where the strategy of brand resonance is introduced in this study. Mainly, this study aims to investigate the impact of CBR as a predictor and mediator in the context of social media marketing (SMM) activities toward SMEs e-brand equity (or strong brand) building. The study employed the quantitative research design concerning on electronic survey method with the valid response rate of 300 respondents. Interestingly, the result revealed the importance role of CBR either as predictor or mediator in the context of SMEs SMM as well as brand equity development. Further, the study provided several theoretical and practical implications that can benefit the SMEs in enhancing their strategic marketing decision.

Keywords: SME brand equity, SME social media marketing, SME consumer brand relationship, SME brand resonance

Procedia PDF Downloads 53

Authors: Richard Ren

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Air pollution is a serious danger to international well-being and economies - it will kill an estimated 7 million people every year, costing world economies $2.6 trillion by 2060 due to sick days, healthcare costs, and reduced productivity. In the United States alone, 60,000 premature deaths are caused by poor air quality. For this reason, there is a crucial need to develop effective methods to forecast air quality, which can mitigate air pollution’s detrimental public health effects and associated costs by helping people plan ahead and avoid exposure. The goal of this study is to propose an artificial intelligence framework for predicting future air quality based on timing variables (i.e. season, weekday/weekend), future weather forecasts, as well as past pollutant and air quality measurements. The proposed framework utilizes multiple machine learning algorithms (logistic regression, random forest, neural network) with different specifications and averages the results of the three top-performing models to eliminate inaccuracies, weaknesses, and biases from any one individual model. Over time, the proposed framework uses new data to self-adjust model parameters and increase prediction accuracy. To demonstrate its applicability, a prototype of this framework was created to forecast air quality in Los Angeles, California using datasets from the RP4 weather data repository and EPA pollutant measurement data. The results showed good agreement between the framework’s predictions and real-life observations, with an overall 92% model accuracy. The combined model is able to predict more accurately than any of the individual models, and it is able to reliably forecast season-based variations in air quality levels. Top air quality predictor variables were identified through the measurement of mean decrease in accuracy. This study proposed and demonstrated the efficacy of a comprehensive air quality prediction framework leveraging multiple machine learning algorithms to overcome individual algorithm shortcomings. Future enhancements should focus on expanding and testing a greater variety of modeling techniques within the proposed framework, testing the framework in different locations, and developing a platform to automatically publish future predictions in the form of a web or mobile application. Accurate predictions from this artificial intelligence framework can in turn be used to save and improve lives by allowing individuals to protect their health and allowing governments to implement effective pollution control measures.Air pollution is a serious danger to international wellbeing and economies - it will kill an estimated 7 million people every year, costing world economies $2.6 trillion by 2060 due to sick days, healthcare costs, and reduced productivity. In the United States alone, 60,000 premature deaths are caused by poor air quality. For this reason, there is a crucial need to develop effective methods to forecast air quality, which can mitigate air pollution’s detrimental public health effects and associated costs by helping people plan ahead and avoid exposure. The goal of this study is to propose an artificial intelligence framework for predicting future air quality based on timing variables (i.e. season, weekday/weekend), future weather forecasts, as well as past pollutant and air quality measurements. The proposed framework utilizes multiple machine learning algorithms (logistic regression, random forest, neural network) with different specifications and averages the results of the three top-performing models to eliminate inaccuracies, weaknesses, and biases from any one individual model. Over time, the proposed framework uses new data to self-adjust model parameters and increase prediction accuracy. To demonstrate its applicability, a prototype of this framework was created to forecast air quality in Los Angeles, California using datasets from the RP4 weather data repository and EPA pollutant measurement data. The results showed good agreement between the framework’s predictions and real-life observations, with an overall 92% model accuracy. The combined model is able to predict more accurately than any of the individual models, and it is able to reliably forecast season-based variations in air quality levels. Top air quality predictor variables were identified through the measurement of mean decrease in accuracy. This study proposed and demonstrated the efficacy of a comprehensive air quality prediction framework leveraging multiple machine learning algorithms to overcome individual algorithm shortcomings. Future enhancements should focus on expanding and testing a greater variety of modeling techniques within the proposed framework, testing the framework in different locations, and developing a platform to automatically publish future predictions in the form of a web or mobile application. Accurate predictions from this artificial intelligence framework can in turn be used to save and improve lives by allowing individuals to protect their health and allowing governments to implement effective pollution control measures.Air pollution is a serious danger to international wellbeing and economies - it will kill an estimated 7 million people every year, costing world economies $2.6 trillion by 2060 due to sick days, healthcare costs, and reduced productivity. In the United States alone, 60,000 premature deaths are caused by poor air quality. For this reason, there is a crucial need to develop effective methods to forecast air quality, which can mitigate air pollution’s detrimental public health effects and associated costs by helping people plan ahead and avoid exposure. The goal of this study is to propose an artificial intelligence framework for predicting future air quality based on timing variables (i.e. season, weekday/weekend), future weather forecasts, as well as past pollutant and air quality measurements. The proposed framework utilizes multiple machine learning algorithms (logistic regression, random forest, neural network) with different specifications and averages the results of the three top-performing models to eliminate inaccuracies, weaknesses, and biases from any one individual model. Over time, the proposed framework uses new data to self-adjust model parameters and increase prediction accuracy. To demonstrate its applicability, a prototype of this framework was created to forecast air quality in Los Angeles, California using datasets from the RP4 weather data repository and EPA pollutant measurement data. The results showed good agreement between the framework’s predictions and real-life observations, with an overall 92% model accuracy. The combined model is able to predict more accurately than any of the individual models, and it is able to reliably forecast season-based variations in air quality levels. Top air quality predictor variables were identified through the measurement of mean decrease in accuracy. This study proposed and demonstrated the efficacy of a comprehensive air quality prediction framework leveraging multiple machine learning algorithms to overcome individual algorithm shortcomings. Future enhancements should focus on expanding and testing a greater variety of modeling techniques within the proposed framework, testing the framework in different locations, and developing a platform to automatically publish future predictions in the form of a web or mobile application. Accurate predictions from this artificial intelligence framework can in turn be used to save and improve lives by allowing individuals to protect their health and allowing governments to implement effective pollution control measures.

Keywords: air quality prediction, air pollution, artificial intelligence, machine learning algorithms

Procedia PDF Downloads 110

Authors: Priyanka Dargode, Suhas Gore, Manju Sharma, Arvind Lali

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Anaerobic digestion has been widely used for production of methane from different biowastes. However, the complexity of microbial communities involved in the process is poorly understood. The performance of biogas production process concerning the process productivity is closely coupled to its microbial community structure and syntrophic interactions amongst the community members. The present study aims at understanding taxonomic variations occurring in any starter inoculum when acclimatised to different lignocellulosic biomass (LBM) feedstocks relating to time of digestion. The work underlines use of high throughput Next Generation Sequencing (NGS) for validating the changes in taxonomic patterns of microbial communities. Biomethane Potential (BMP) batches were set up with different pretreated and non-pretreated LBM residues using the same microbial consortium and samples were withdrawn for studying the changes in microbial community in terms of its structure and predominance with respect to changes in metabolic profile of the process. DNA of samples withdrawn at different time intervals with reference to performance changes of the digestion process, was extracted followed by its 16S rRNA amplicon sequencing analysis using Illumina Platform. Biomethane potential and substrate consumption was monitored using Gas Chromatography(GC) and reduction in COD (Chemical Oxygen Demand) respectively. Taxonomic analysis by QIIME server data revealed that microbial community structure changes with different substrates as well as at different time intervals. It was observed that biomethane potential of each substrate was relatively similar but, the time required for substrate utilization and its conversion to biomethane was different for different substrates. This could be attributed to the nature of substrate and consequently the discrepancy between the dominance of microbial communities with regards to different substrate and at different phases of anaerobic digestion process. Knowledge of microbial communities involved would allow a rational substrate specific consortium design which will help to reduce consortium adaptation period and enhance the substrate utilisation resulting in improved efficacy of biogas process.

Keywords: amplicon sequencing, biomethane potential, community predominance, taxonomic analysis

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Authors: S. N. Susenburger, D. Boecker

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In the age of Volatility, Uncertainty, Complexity, and Ambiguity (VUCA), where digital transformation is challenging long standing traditional hardware and manufacturing companies, innovation needs a different methodology, strategy, mindset, and culture. What used to be a mindset of scaling per quantity is now shifting to orchestrating ecosystems, platform business models and service bundles. While large corporations are trying to mimic the nimbleness and versatile mindset of startups in the core of their digital strategies, they’re at the frontier of facing one of the largest organizational and cultural changes in history. This paper elaborates on how a manufacturing giant transformed its Corporate Information Technology (IT) to enable digital and Internet of Things (IoT) business while establishing the mindset and the approaches of the Innovation Inside-Out/Outside-In Strategy. It gives insights into the core elements of an innovation culture and the tactics and methodologies leveraged to support the cultural shift and transformation into an IoT company. This paper also outlines the core elements for an innovation culture and how the persona 'Connected Engineer' thrives in the digital innovation environment. Further, it explores how tapping domain-focused ecosystems in vibrant innovative cities can be used as a part of the strategy to facilitate partner co-innovation. Therefore, findings from several use cases, observations and surveys led to conclusion for the strategy tandem of Innovation Inside-Out/Outside-In. The findings indicate that it's crucial in which phases and maturity level the Innovation Inside-Out/Outside-In Strategy is activated: cultural aspects of the business and the regional ecosystem need to be considered, as well as cultural readiness from management and active contributors. The 'not invented here syndrome' is a barrier of large corporations that need to be addressed and managed to successfully drive partnerships, as well as embracing co-innovation and a mindset shifting away from physical products toward new business models, services, and IoT platforms. This paper elaborates on various methodologies and approaches tested in different countries and cultures, including the U.S., Brazil, Mexico, and Germany.

Keywords: innovation management, innovation culture, innovation methodologies, digital transformation

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Authors: Ankita Tiwari, Jyoti Saini, Subhasis Ghosh

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For many years, researchers have been fascinated by the subject of how properties evolve as dimensionality is lowered. Early on, it was shown that the presence of a significant magnetic anisotropy might compensate for the lack of long-range (LR) magnetic order in a low-dimensional system (d < 3) with continuous symmetry, as proposed by Hohenberg-Mermin and Wagner (HMW). Strong magnetic anisotropy allows an LR magnetic order to stabilize in two dimensions (2D) even in the presence of stronger thermal fluctuations which is responsible for the absence of Heisenberg ferromagnetism in 2D. Van der Waals (vdW) ferromagnets, including CrI₃, CrTe₂, Cr₂X₂Te₆ (X = Si and Ge) and Fe₃GeTe₂, offer a nearly ideal platform for studying ferromagnetism in 2D. Fe₃GeTe₂ is the subject of extensive investigation due to its tunable magnetic properties, high Curie temperature (Tc ~ 220K), and perpendicular magnetic anisotropy. Many applications in the field of spintronics device development have been quite active due to these appealing features of Fe₃GeTe₂. Although it is known that LR-driven ferromagnetism is necessary to get around the HMW theorem in 2D experimental realization, Heisenberg 2D ferromagnetism remains elusive in condensed matter systems. Here, we show that Fe₃GeTe₂ hosts both localized and delocalized spins, resulting in itinerant and local-moment ferromagnetism. The presence of LR itinerant interaction facilitates to stabilize Heisenberg ferromagnet in 2D. With the help of Rhodes-Wohlfarth (RW) and generalized RW-based analysis, Fe₃GeTe₂ has been shown to be a 2D ferromagnet with itinerant magnetism that can be modulated by an external magnetic field. Hence, the presence of both local moment and itinerant magnetism has made this system interesting in terms of research in low dimensions. We have also rigorously performed critical analysis using an improvised method. We show that the variable critical exponents are typical signatures of 2D ferromagnetism in Fe₃GeTe₂. The spontaneous magnetization exponent β changes the universality class from mean-field to 2D Heisenberg with field. We have also confirmed the range of interaction via the renormalization group (RG) theory. According to RG theory, Fe₃GeTe₂ is a 2D ferromagnet with LR interactions.

Keywords: Van der Waal ferromagnet, 2D ferromagnetism, phase transition, itinerant ferromagnetism, long range order

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Authors: Florence Ibeh, David Oyewmi Oyekunle, David Boohene

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The continuous advancement of information technology has completely transformed how businesses and organizations operate on a global scale. The widespread availability of virtual communication tools enables individuals to opt for remote work. While remote employment offers various benefits, such as facilitating corporate growth and enhancing customer support, it also presents distinct challenges. Therefore, investigating the intricacies of virtual team morale is crucial for ensuring the achievement of project objectives. For this study, content analysis of pre-existing secondary data was employed to examine the phenomenon. Essential elements vital for improving the success of projects within virtual teams were identified. These factors include technology adoption, creating a distraction-free work environment, effective leadership, trust-building, clear communication channels, well-defined task allocation, active team participation, and motivation. Furthermore, the study established a substantial correlation between morale levels and the participation and productivity of virtual team members. Higher levels of morale were associated with optimal performance among virtual teams. The study determined that the key factors for enhancing project performance in virtual teams are the adoption of technology, a focused environment, effective leadership, trust, communication, well-defined tasks, collaborative teamwork, and motivation. Additionally, the study discovered that modifying the optimal strategies employed by in-office teams can enhance the diminished morale prevalent in remote teams to sustain a high level of team morale for virtual teams. The findings of this study are highly significant in the dynamic field of project management. Currently, there is limited information regarding strategies that address challenges arising from external factors in virtual teams, such as ambient noise and disruptions caused by family members. The findings underscore the significance of selecting appropriate communication technologies, delineating distinct roles and responsibilities for virtual team members, and nurturing a culture of accountability and trust. Promoting seamless collaboration and instilling motivation among virtual team members are deemed highly effective in augmenting employee engagement and performance within virtual team setting.

Keywords: virtual teams, morale, project performance, distract-free environment, technology adaptation

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Authors: Koko Iwan Agus Kurniawan, Dwi Purnomo, Anas Bunyamin, Arif Rahman Jaya

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Fruters model is a concept of technopreneurship-based on empowerment, in which technology research results were designed to create high value-added products and implemented as a locomotive of collaborative empowerment; thereby, the impact was widely spread. This model still needs to be inventoried and validated concerning the influenced variables in the business growth process. Model validation accompanied by mapping was required to be applicable to Small Medium Enterprises (SMEs) agro-industry based on sustainable social business and existing real cases. This research explained the empowerment model of Yourgood, an SME, which emphasized on empowering the farmers/ breeders in farmers in rural areas, Cipageran, Cimahi, to housewives in urban areas, Bandung, West Java, Indonesia. This research reviewed some works of literature discussing the agro-industrial development associated with the empowerment and social business process and gained a unique business model picture with the social business platform as well. Through the mapped business model, there were several advantages such as technology acquisition, independence, capital generation, good investment growth, strengthening of collaboration, and improvement of social impacts that can be replicated on other businesses. This research used analytical-descriptive research method consisting of qualitative analysis with design thinking approach and that of quantitative with the AHP (Analytical Hierarchy Process). Based on the results, the development of the enterprise’s process was highly affected by supplying farmers with the score of 0.248 out of 1, being the most valuable for the existence of the enterprise. It was followed by university (0.178), supplying farmers (0.153), business actors (0.128), government (0.100), distributor (0.092), techno-preneurship laboratory (0.069), banking (0.033), and Non-Government Organization (NGO) (0.031).

Keywords: agro-industry, small medium enterprises, empowerment, design thinking, AHP, business model canvas, social business

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Authors: Temmuz Gönç Şavran

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Migration is a multidimensional and health-related concept that has important consequences for both migrants and the host society. Due to past conflicts and poor living conditions that lead to migration, the dangerous and difficult journey, and the problems they face upon arrival in the destination country, migrants are at higher risk for poor health. Health is a human right, and all societies and communities, including migrant groups, must receive adequate health care. In addition, the health of migrants must be improved to protect the health of the host society and ensure social integration. The main determinants of health are employment, income, education, good housing, and adequate nutrition. It can be said that migrants are among the most vulnerable groups in society in these respects, and migrant health is negatively affected by this situation. Rigid immigration policies or financial constraints in destination countries, the complexity and bureaucracy of health systems, the low health literacy of migrant groups, and the inadequate provision of translation services in health facilities are among the other main factors affecting migrant health. Migrants are also at risk of stigma, exclusion, detection, and deportation when seeking medical care. Based on data from a qualitative study with a descriptive case study design, this paper aims to highlight and sociologically assess the health-related problems of international migrants in Eskisehir, Turkey. The sample consists of 30 international migrants living in Eskisehir, two-thirds of whom are from Syria, Iraq, Afghanistan, and Pakistan. Those who are citizens of the Republic of Turkey are excluded from the study; otherwise, the legal status of the participants is not considered in the selection of the sample. This makes it possible to distinguish the different needs and problems of subgroups and to consider migrant health as a comprehensive concept. The research is supported by Anadolu University in Eskisehir, and data will be collected through semi-structured interviews between November 2022 and February 2023. With holistic sociology of health approach, this study considers migrant health as a comprehensive sociological concept. It aims to reveal the health-related resources and needs of the international migrant groups living in the center of Eskisehir, the problems they encounter in meeting these needs, and the strategies they use to solve these problems. The results are expected to show that the health of migrants is not only influenced by legislation but is shaped by many processes, from housing conditions to cultural habits. It is expected that the results will also raise awareness of discrimination, exclusion, marginalization, and hate speech in migrants’ access to health services.

Keywords: migrant health, sociology of health, sociology of migration, Turkey, refugees

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Authors: Kharisma Utomo Mulyodinoto, Suwarno, Ahmed Abu-Siada

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Transformer insulating oil is a key component that can be utilized to detect incipient faults within operating transformers without taking them out of service. Dissolved gas-in-oil analysis has been widely accepted as a powerful technique to detect such incipient faults. While the measurement of dissolved gases within transformer oil samples has been standardized over the past two decades, analysis of the results is not always straightforward as it depends on personnel expertise more than mathematical formulas. In analyzing such data, the generation rate of each dissolved gas is of more concern than the absolute value of the gas. As such, history of dissolved gases within a particular transformer should be archived for future comparison. Lack of such history may lead to misinterpretation of the obtained results. IEEE C57.104-2008 standards have classified the health condition of the transformer based on the absolute value of individual dissolved gases along with the total dissolved combustible gas (TDCG) within transformer oil into 4 conditions. While the technique is easy to implement, it is considered as a very conservative technique and is not widely accepted as a reliable interpretation tool. Moreover, measured gases for the same oil sample can be within various conditions limits and hence, misinterpretation of the data is expected. To overcome this limitation, this paper introduces a fuzzy logic approach to predict the health condition of the transformer oil based on IEEE C57.104-2008 standards along with Roger ratio and IEC ratio-based methods. DGA results of 31 chosen oil samples from 469 transformer oil samples of normal transformers and pre-known fault-type transformers that were collected from Indonesia Electrical Utility Company, PT. PLN (Persero), from different voltage rating: 500/150 kV, 150/20 kV, and 70/20 kV; different capacity: 500 MVA, 60 MVA, 50 MVA, 30 MVA, 20 MVA, 15 MVA, and 10 MVA; and different lifespan, are used to test and establish the fuzzy logic model. Results show that the proposed approach is of good accuracy and can be considered as a platform toward the standardization of the dissolved gas interpretation process.

Keywords: dissolved gas analysis, fuzzy logic, health index, IEEE C57.104-2008, IEC ratio method, Roger ratio method

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Authors: Keiko Yamauchi, Motoyuki Nakao, Yoko Ishihara

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The increase in the number of women with breast cancer in Japan has required hospitals to provide a higher quality of medicine so that patients are satisfied with the treatment they receive. However, patients’ satisfaction following breast cancer treatment has not been sufficiently studied. Hence, we investigated the factors influencing patient satisfaction following breast cancer treatment among Japanese women. These women underwent either breast-conserving surgery (BCS) (n = 380) or total mastectomy (TM) (n = 247). In March 2016, we conducted a cross-sectional internet survey of Japanese women with breast cancer in Japan. We assessed the following factors: socioeconomic status, cancer-related information, the role of medical decision-making, the degree of satisfaction regarding the treatments received, and the regret arising from the medical decision-making processes. We performed logistic regression analyses with the following dependent variables: extreme satisfaction with the treatments received, and regret regarding the medical decision-making process. For both types of surgery, the odds ratio (OR) of being extremely satisfied with the cancer treatment was significantly higher among patients who did not have any regrets compared to patients who had. Also, the OR tended to be higher among patients who chose to play a wanted role in the medical decision-making process, compared with patients who did not. In the BCS group, the OR of being extremely satisfied with the treatment was higher if, at diagnosis, the patient’s youngest child was older than 19 years, compared with patients with no children. The OR was also higher if patient considered the stage and characteristics of their cancer significant. The OR of being extremely satisfied with the treatments was lower among patients who were not employed on full-time basis, and among patients who considered the second medical opinions and medical expenses to be significant. These associations were not observed in the TM group. The OR of having regrets regarding the medical decision-making process was higher among patients who chose to play a role in the decision-making process as they preferred, and was also higher in patients who were employed on either a part-time or contractual basis. For both types of surgery, the OR was higher among patients who considered a second medical opinion to be significant. Regardless of surgical type, regret regarding the medical decision-making process decreases treatment satisfaction. Patients who received breast-conserving surgery were more likely to have regrets concerning the medical decision-making process if they could not play a role in the process as they preferred. In addition, factors associated with the satisfaction with treatment in BCS group but not TM group included the second medical opinion, medical expenses, employment status, and age of the youngest child at diagnosis.

Keywords: medical decision making, breast-conserving surgery, total mastectomy, Japanese

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Authors: Wissal Ben Arfi, Lubica Hikkerova, Jean-Michel Sahut

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This study examines interfirm networks in the digital transformation era, and in particular, how tacit knowledge codification affects innovation success within digital platforms. Hence, one of the most important features of digital transformation and innovation process outcomes is the emergence of digital platforms, as an interfirm network, at the heart of open innovation. This research aims to illuminate how digital platforms influence inter-organizational innovation through virtual team interactions and knowledge sharing practices within an interfirm network. Consequently, it contributes to the respective strategic management literature on new product development (NPD), open innovation, industrial management, and its emerging interfirm networks’ management. The empirical findings show, on the one hand, that knowledge conversion may be enhanced, especially by the socialization which seems to be the most important phase as it has played a crucial role to hold the virtual team members together. On the other hand, in the process of socialization, the tacit knowledge codification is crucial because it provides the structure needed for the interfirm network actors to interact and act to reach common goals which favor the emergence of open innovation. Finally, our results offer several conditions necessary, but not always sufficient, for interfirm managers involved in NPD and innovation concerning strategies to increasingly shape interconnected and borderless markets and business collaborations. In the digital transformation era, the need for adaptive and innovative business models as well as new and flexible network forms is becoming more significant than ever. Supported by technological advancements and digital platforms, companies could benefit from increased market opportunities and creating new markets for their innovations through alliances and collaborative strategies, as a mode of reducing or eliminating uncertainty environments or entry barriers. Consequently, an efficient and well-structured interfirm network is essential to create network capabilities, to ensure tacit knowledge sharing, to enhance organizational learning and to foster open innovation success within digital platforms.

Keywords: interfirm networks, digital platform, virtual teams, open innovation, knowledge sharing

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Authors: Mathieu Audet, Monica Soliman, Emilie Eve Gravel, Rebecca Friesdorf

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Access to higher education is critical for reducing social inequalities. The Canada Learning Bond (CLB) is a government savings incentive aimed at increasing higher education access for children of low income families by providing money toward a Registered Education Savings Plan. To better understand the educational and financial decision-making of low income families, Employment Social Development Canada conducted qualitative fieldwork with eligible parents and children, teachers, and community organizations promoting the Bond. Insights from this fieldwork were then used to develop letters to better target the needs and experiences of eligible families. In the present study, we conducted a randomized controlled trial with children ages 12 to 13, the oldest cohort of eligible children, to test the effectiveness of the new letters. Parents or caregivers of 150,088 eligible children were assigned to one of five letter conditions promoting the Bond or to a control condition that did not receive a letter. The letter conditions were: (a) the standard letter from past outreach, (b) a letter presenting the exact amount the child was eligible to receive, enhancing the salience of benefits, (c) a letter with a social norm, (d) a letter with an image emphasizing the feasibility of higher education by presenting the diversity of options (i.e., college, trade schools, apprenticeships) – many participants interviewed viewed that university was unfeasible, and (e) a letter minimizing references to 'saving' (i.e., not framing the Bond explicitly as a savings incentive) – a concept that did not resonate with low income families who felt they could not afford to save. The exact amount was also presented in letters (c) through (e). The letter minimizing references to 'saving' and presenting the exact amount had the highest net take-up rate at 6.6%, compared to 3.5% for the standard letter group. Furthermore, this trial’s BI-informed letters showed the largest impact on take-up so far, with a net take-up of 5.7% compared to 3.0% and 3.9% in the first two trials. This research highlights the value of mixed-method approaches combining qualitative and behavioural insights methods for developing context-sensitive interventions for social programs. By gaining a deeper understanding of the needs and experiences of program users through qualitative fieldwork, and then integrating these insights into behaviourally informed communications, we were able to increase take-up of an education savings program, which may ultimately improve access to higher education in children of low income families.

Keywords: access to higher education, behavioral insights, government, innovation, mixed-methods, social programs

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Authors: Nicholas C. Rose, Christopher D. Spicer

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The regeneration of damaged or diseased tissues would provide an invaluable therapeutic tool in biological research and medicine. Cells must be provided with a number of different biochemical signals in order to form mature tissue through complex signaling networks that are difficult to recreate in synthetic materials. The ability to attach and detach bioactive proteins from material in an iterative and dynamic manner would therefore present a powerful way to mimic natural biochemical signaling cascades for tissue growth. We propose to reversibly attach these bioactive proteins using ortho-boronoimine (oBI) linkages and related derivatives formed by the reaction of an ortho-boronobenzaldehyde with a nucleophilic amine derivative. To enable the use of oBIs for biomaterial modification, we have studied binding and cleavage processes with precise detail in the context of small molecule models. A panel of oBI complexes has been synthesized and screened using a novel Förster resonance energy transfer (FRET) assay, using a cyanine dye FRET pair (Cy3 and Cy5), to identify the most reactive boron-aldehyde/amine nucleophile pairs. Upon conjugation of the dyes, FRET occurs under Cy3 excitation and the resultant ratio of Cy3:Cy5 emission directly correlates to conversion. Reaction kinetics and equilibria can be accurately quantified for reactive pairs, with dissociation constants of oBI derivatives in water (KD) found to span 9-orders of magnitude (10⁻²-10⁻¹¹ M). These studies have provided us with a better understanding of oBI linkages that we hope to exploit to reversibly attach bioconjugates to materials. The long-term aim of the project is to develop a modular biomaterial platform that can be used to help combat chronic diseases such as osteoarthritis, heart disease, and chronic wounds by providing cells with potent biological stimuli for tissue engineering.

Keywords: dynamic, bioconjugation, bornoimine, rapid, physiological

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Authors: P. Kavuma, J. Mukasa, M. Lusunku

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Background and Problem: The widespread poverty in Africa- together with the negative impacts of climate change-are two great global challenges that call for everyone’s involvement including Architects. This in particular places serious challenges on architects to have additional skills in both Entrepreneurship and Environmental Design (SEED). Regrettably, while Architectural Training in most African Universities including those from Uganda lack comprehensive implementation of SEED in their curricula, regulatory bodies have not contributed towards the effective integration of SEED in their professional practice. In response to these challenges, Nkumba University (NU) under Architect Kavuma Paul supported by the Uganda Chambers of Architects– initiated the SEED integration in the undergraduate Architectural curricula to cultivate SEED know-how and examples of best practices. Main activities: Initiated in 2007, going beyond the traditional Architectural degree curriculum, the NU Architect department offers SEED courses including provoking passions for creating desirable positive changes in communities. Learning outcomes are assessed theoretically and practically through field projects. The first set of SEED graduates came out in 2012. As part of the NU post-graduation and alumni survey, in October 2014, the pioneer SEED graduates were contacted through automated reminder emails followed by individual, repeated personal follow-ups via email and phone. Out of the 36 graduates who responded to the survey, 24 have formed four (4) private consortium agencies of 5-7 graduates all of whom have pioneered Ugandan-own-cultivated Architectural social projects that include: fishing farming in shipping containers; solar powered mobile homes in shipping containers, solar powered retail kiosks in rural and fishing communities, and floating homes in the flood-prone areas. Primary outcomes: include being business self –reliant in creating the social change the architects desired in the communities. Examples of the SEED project returns to communities reported by the graduates include; employment creation via fabrication, retail business, marketing, improved diets, safety of life and property, decent shelter in the remote mining and oil exploration areas. Negative outcomes-though not yet evaluated include the disposal of used-up materials. Conclusion: The integration of SEED in Architectural Training has established a baseline benchmark and a replicable model based on best practice projects.

Keywords: architectural training, entrepreneurship, environment, integration

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Authors: Liang-Jen Wang, Sung-Chou Li, Yuan-Ming Yeh, Sheng-Yu Lee, Ho-Chang Kuo, Chia-Yu Yang

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Background: Dysbiosis in the gut microbial community might be involved in the pathophysiology of attention deficit/hyperactivity disorder (ADHD). The fungal component of the gut microbiome, namely the mycobiota, is a hyperdiverse group of multicellular eukaryotes that can influence host intestinal permeability. This study therefore aimed to investigate the impact of fungal mycobiome dysbiosis and intestinal permeability on ADHD. Methods: Faecal samples were collected from 35 children with ADHD and from 35 healthy controls. Total DNA was extracted from the faecal samples, and the internal transcribed spacer (ITS) regions were sequenced using high-throughput next-generation sequencing (NGS). The fungal taxonomic classification was analysed using bioinformatics tools, and the differentially expressed fungal species between the ADHD and healthy control groups were identified. An in vitro permeability assay (Caco-2 cell layer) was used to evaluate the biological effects of fungal dysbiosis on intestinal epithelial barrier function. Results: The β-diversity (the species diversity between two communities), but not α-diversity (the species diversity within a community), reflected the differences in fungal community composition between ADHD and control groups. At the phylum level, the ADHD group displayed a significantly higher abundance of Ascomycota and significantly lower abundance of Basidiomycota than the healthy control group. At the genus level, the abundance of Candida (especially Candida albicans) was significantly increased in ADHD patients compared to the healthy controls. In addition, the in vitro cell assay revealed that C. albicans secretions significantly enhanced the permeability of Caco-2 cells. Conclusions: The current study is the first to explore altered gut mycobiome dysbiosis using the NGS platform in ADHD. The findings from this study indicated that dysbiosis of the fungal mycobiome and intestinal permeability might be associated with susceptibility to ADHD.

Keywords: ADHD, fungus, gut–brain axis, biomarker, child psychiatry

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Authors: Chih-Jer Lin, Jian-Hong Hou

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Industry 4.0 is a vision of integrated industry implemented by artificial intelligent computing, software, and Internet technologies. The main goal of industry 4.0 is to deal with the difficulty owing to competitive pressures in the marketplace. For today’s manufacturing factories, the type of production is changed from mass production (high quantity production with low product variety) to medium quantity-high variety production. To offer flexibility, better quality control, and improved productivity, robot manipulators are used to combine material processing, material handling, and part positioning systems into an integrated manufacturing system. To implement the automated system for sheet metal bending operations, motion planning of a 7-degrees of freedom (DOF) robot is studied in this paper. A virtual reality (VR) environment of a bending cell, which consists of the robot and a bending machine, is established using the virtual robot experimentation platform (V-REP) simulator. For sheet metal bending operations, the robot only needs six DOFs for the pick-and-place or tracking tasks. Therefore, this 7 DOF robot has more DOFs than the required to execute a specified task; it can be called a redundant robot. Therefore, this robot has kinematic redundancies to deal with the task-priority problems. For redundant robots, Pseudo-inverse of the Jacobian is the most popular motion planning method, but the pseudo-inverse methods usually lead to a kind of chaotic motion with unpredictable arm configurations as the Jacobian matrix lose ranks. To overcome the above problem, we proposed a method to formulate the motion planning problems as optimization problem. Moreover, a genetic algorithm (GA) based method is proposed to deal with motion planning of the redundant robot. Simulation results validate the proposed method feasible for motion planning of the redundant robot in an automated sheet-metal bending operations.

Keywords: redundant robot, motion planning, genetic algorithm, obstacle avoidance

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Authors: Cristian Soitu, Alexander Feuerborn, Cyril Deroy, Alfonso Castrejon-Pita, Peter R. Cook, Edmond J. Walsh

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Microfluidics now stands as an academically mature technology after a quarter of a century research activities have delivered a vast array of proof of concepts for many biological workflows. However, translation to industry remains poor, with only a handful of notable exceptions – e.g. digital PCR, DNA sequencing – mainly because of biocompatibility issues, limited range of readouts supported or complex operation required. This technology exploits the domination of interfacial forces over gravitational ones at the microscale, replacing solid walls with fluid ones as building blocks for cell micro-environments. By employing only materials used by biologists for decades, the system is shown to be biocompatible, and easy to manufacture and operate. The method consists in displacing a continuous fluid layer into a pattern of isolated chambers overlaid with an immiscible liquid to prevent evaporation. The resulting fluid arrangements can be arrays of micro-chambers with rectangular footprint, which use the maximum surface area available, or structures with irregular patterns. Pliant, self-healing fluid walls confine volumes as small as 1 nl. Such fluidic structures can be reconfigured during the assays, giving the platform an unprecedented level of flexibility. Common workflows in cell biology are demonstrated – e.g. cell growth and retrieval, cloning, cryopreservation, fixation and immunolabeling, CRISPR-Cas9 gene editing, and proof-of-concept drug tests. This fluid-shaping technology is shown to have potential for high-throughput cell- and organism-based assays. The ability to make and reconfigure on-demand microfluidic circuits on standard Petri dishes should find many applications in biology, and yield more relevant phenotypic and genotypic responses when compared to standard microfluidic assays.

Keywords: fluid walls, micro-chambers, reconfigurable, freestyle

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