Search results for: Kohat university of science and technology

Authors: Akaash Tawade, Manan Khattar, Lucas Spangher, Costas J. Spanos

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Many grids are increasing the share of renewable energy in their generation mix, which is causing the energy generation to become less controllable. Buildings, which consume nearly 33% of all energy, are a key target for demand response: i.e., mechanisms for demand to meet supply. Understanding the behavior of office workers is a start towards developing demand response for one sector of building technology. The literature notes that dynamic computational modeling can be predictive of individual action, especially given that occupant behavior is traditionally abstracted from demand forecasting. Recent work founded on Social Cognitive Theory (SCT) has provided a promising conceptual basis for modeling behavior, personal states, and environment using control theoretic principles. Here, an adapted linear dynamical system of latent states and exogenous inputs is proposed to simulate energy demand amongst office workers engaged in a social energy shifting game. The energy shifting competition is implemented in an office in Singapore that is connected to a minigrid of buildings with a consistent 'price signal.' This signal is translated into a 'points signal' by a reinforcement learning (RL) algorithm to influence participant energy use. The dynamic model functions at the intersection of the points signals, baseline energy consumption trends, and SCT behavioral inputs to simulate future outcomes. This study endeavors to analyze how the dynamic model trains an RL agent and, subsequently, the degree of accuracy to which load deferability can be simulated. The results offer a generalizable behavioral model for energy competitions that provides the framework for further research on transfer learning for RL, and more broadly— transactive control.

Keywords: energy demand forecasting, social cognitive behavioral modeling, social game, transfer learning

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Authors: Chung Danbi, Linton Oliver, Whang Yoon-Jae

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Supermodularity, or complementarity, is a popular concept in economics which can characterize many objective functions such as utility, social welfare, and production functions. Further, supermodular dominance captures a preference for greater interdependence among inputs of those functions, and it can be applied to examine which input set would produce higher expected utility, social welfare, or production. Therefore, we propose and justify a consistent testing for a useful implication of supermodular dominance. We also conduct Monte Carlo simulations to explore the finite sample performance of our test, with critical values obtained from the recentered bootstrap method, with and without the selective recentering, and the subsampling method. Under various parameter settings, we confirmed that our test has reasonably good size and power performance. Finally, we apply our test to compare the geographic and distant knowledge spillover in terms of their effects on social welfare using the National Bureau of Economic Research (NBER) patent data. We expect localized citing to supermodularly dominate distant citing if the geographic knowledge spillover engenders greater social welfare than distant knowledge spillover. Taking subgroups based on firm and patent characteristics, we found that there is industry-wise and patent subclass-wise difference in the pattern of supermodular dominance between localized and distant citing. We also compare the results from analyzing different time periods to see if the development of Internet and communication technology has changed the pattern of the dominance. In addition, to appropriately deal with the sparse nature of the data, we apply high-dimensional methods to efficiently select relevant data.

Keywords: supermodularity, supermodular dominance, stochastic dominance, Monte Carlo simulation, bootstrap, subsampling

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Authors: Manish Khanra, Shashank Prabhu

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The decarbonization of hard-to-abate sectors is currently high on the agenda in the EU and its member states, as these sectors have substantial shares in overall GHG emissions while it is facing serious challenges to decarbonize. In particular, the aviation sector accounts for 2.8% of global anthropogenic CO₂ emissions. These emissions are anticipated to grow dramatically unless immediate mitigating efforts are implemented. Hydrogen and its derivatives based on renewable electricity can have a key role in the transition towards CO₂-neutral flights. The substantial shares of energy carriers in the form of drop-in fuel, direct combustion and Hydrogen-to-Electric are promising in most scenarios towards 2050. For creating appropriate policies to ramp up the production and utilisation of hydrogen commodities in the German aviation sector, a detailed analysis of the spatial distribution of supply-demand sites is essential. The objective of this research work is to assess the demand for hydrogen-based alternative fuels in the German aviation sector to achieve the perceived goal of the ‘Net Zero’ scenario by 2050. Here, the analysis of the technological pathways for the production and utilisation of these fuels in various aircraft options is conducted for reaching mitigation targets. Our method is based on data-driven bottom-up assessment, considering production and demand sites and their spatial distribution. The resulting energy demand and its spatial distribution with consideration of technology diffusion lead to a possible transition pathway of the aviation sector to meet short-term and long-term mitigation targets. Additionally, to achieve mitigation targets in this sector, costs and policy aspects are discussed, which would support decision-makers from airline industries, policymakers and the producers of energy commodities.

Keywords: the aviation sector, hard-to-abate sectors, hydrogen demand, alternative fuels, technological pathways, data-driven approach

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Authors: Muhammad Minhaj Khan, Jaemin Lee, Suhong Lee, Jinyoung Chung, Johoo Whang

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The Republic of Korea has been facing strong storage crisis from nuclear waste generation as At Reactor (AR) temporary storage sites are about to reach saturation. Since the country is densely populated with a rate of 491.78 persons per square kilometer, Construction of High-level waste repository will not be a feasible option. In order to tackle the storage waste generation problem which is increasing at a rate of 350 tHM/Yr. and 380 tHM/Yr. in case of 20 PWRs and 4 PHWRs respectively, the study strongly focuses on the advancement of current nuclear power plants to GEN-IV sustainable and ecological nuclear systems by burning TRUs (Pu, MAs). First, Calculations has made to estimate the generation of SNF including Pu and MA from PWR and PHWR NPPS by using the IAEA code Nuclear Fuel Cycle Simulation System (NFCSS) for the period of 2016, 2030 (including the saturation period of each site from 2024~2028), 2089 and 2109 as the number of NPPS will increase due to high import cost of non-nuclear energy sources. 2ndly, in order to produce environmentally sustainable nuclear energy systems, 4 scenarios to burnout the Plutonium and MAs are analyzed with the concentration on burning of MA only, MA and Pu together by utilizing SFR, LFR and KALIMER-600 burner reactor after recycling the spent oxide fuel from PWR through pyro processing technology developed by Korea Atomic Energy Research Institute (KAERI) which shows promising and sustainable future benefits by minimizing the HLW generation with regard to waste amount, decay heat, and activity. Finally, With the concentration on front and back end fuel cycles for open and closed fuel cycles of PWR and Pyro-SFR respectively, an overall assessment has been made which evaluates the quantitative as well as economical combativeness of SFR metallic fuel against PWR once through nuclear fuel cycle.

Keywords: GEN IV nuclear fuel cycle, nuclear waste, waste sustainability, transmutation

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Authors: Giovanna Grosso, Martien A. Hulsen, Arash Sarhangi Fard, Andrew Overend, Patrick. D. Anderson

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In many industrial applications and, in particular in polymer industry, the quality of mixing between different materials is fundamental to guarantee the desired properties of finished products. However, properly modelling and understanding polymer mixing often presents noticeable difficulties, because of the variety and complexity of the physical phenomena involved. This is the case of the Cavity Transfer Mixer (CTM), for which a clear understanding of mixing mechanisms is still missing, as well as clear guidelines for the system optimization. This device, invented and patented by Gale at Rapra Technology Limited, is an add-on to be mounted downstream of existing extruders, in order to improve distributive mixing. It consists of two concentric cylinders, the rotor and stator, both provided with staggered rows of hemispherical cavities. The inner cylinder (rotor) rotates, while the outer (stator) remains still. At the same time, the pressure load imposed upstream, pushes the fluid through the CTM. Mixing processes are driven by the flow field generated by the complex interaction between the moving geometry, the imposed pressure load and the rheology of the fluid. In such a context, the present work proposes a complete and accurate three dimensional modelling of the CTM and results of a broad range of simulations assessing the impact on mixing of several geometrical and functioning parameters. Among them, we find: the number of cavities per row, the number of rows, the size of the mixer, the rheology of the fluid and the ratio between the rotation speed and the fluid throughput. The model is composed of a flow part and a mixing part: a finite element solver computes the transient velocity field, which is used in the mapping method implementation in order to simulate the concentration field evolution. Results of simulations are summarized in guidelines for the device optimization.

Keywords: Mixing, non-Newtonian fluids, polymers, rheology.

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Authors: F. S. Al-Anzi, M. Sarfraz, A. Elmi, A. R. Khan

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Researchers are responding to the environmental challenges of Kuwait in localized, innovative, effective and economic ways. One of the vital and significant examples of the natural challenges is lack or water and desertification. In this research, the project team focuses on redesigning a prototype, using Value Engineering Methodology, which would provide similar functionalities to the well-known technology of Waterboxx kits while reducing the capital and operational costs and simplifying the process of manufacturing and usability by regular farmers. The design employs used tires and recycled plastic sheets as raw materials. Hence, this approach is going to help not just fighting desertification but also helping in getting rid of ever growing huge tire dumpsters in Kuwait, as well as helping in avoiding hazards of tire fires yielding in a safer and friendlier environment. Several alternatives for implementing the prototype have been considered. The best alternative in terms of value has been selected after thorough Function Analysis System Technique (FAST) exercise has been developed. A prototype has been fabricated and tested in a controlled simulated lab environment that is being followed by real environment field testing. Water and soil analysis conducted on the site of the experiment to cross compare between the composition of the soil before and after the experiment to insure that the prototype being tested is actually going to be environment safe. Experimentation shows that the design was equally as effective as, and may exceed, the original design with significant savings in cost. An estimated total cost reduction using the VE approach of 43.84% over the original design. This cost reduction does not consider the intangible costs of environmental issue of waste recycling which many further intensify the total savings of using the alternative VE design. This case study shows that Value Engineering Methodology can be an important tool in innovating new designs for reducing costs.

Keywords: desertification, functional analysis, scrap tires, value engineering, waste recycling, water irrigation rationing

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Authors: A. Degale Desta, Tamirat Kebamo

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Background: Recent advances in computer vision and pattern recognition have significantly improved activity recognition through video analysis, particularly with the application of Deep Convolutional Neural Networks (CNNs). One-stage detectors now enable efficient video-based recognition by simultaneously predicting object categories and locations. Such advancements are highly relevant in educational settings where CCTV surveillance could automatically monitor academic activities, enhancing security and classroom management. However, current datasets and recognition systems lack the specific focus on campus environments necessary for practical application in these settings.Objective: This study aims to address this gap by developing a dataset and testing an automated activity recognition system specifically tailored for educational campuses. The EthioCAD dataset was created to capture various classroom activities and teacher-student interactions, facilitating reliable recognition of academic activities using deep learning models. Method: EthioCAD, a novel video-based dataset, was created with a design science research approach to encompass teacher-student interactions across three domains and 18 distinct classroom activities. Using the Roboflow AI framework, the data was processed, with 4.224 KB of frames and 33.485 MB of images managed for frame extraction, labeling, and organization. The Ultralytics YOLOv8 model was then implemented within Google Colab to evaluate the dataset’s effectiveness, achieving high mean Average Precision (mAP) scores. Results: The YOLOv8 model demonstrated robust activity recognition within campus-like settings, achieving an mAP50 of 90.2% and an mAP50-95 of 78.6%. These results highlight the potential of EthioCAD, combined with YOLOv8, to provide reliable detection and classification of classroom activities, supporting automated surveillance needs on educational campuses. Discussion: The high performance of YOLOv8 on the EthioCAD dataset suggests that automated activity recognition for surveillance is feasible within educational environments. This system addresses current limitations in campus-specific data and tools, offering a tailored solution for academic monitoring that could enhance the effectiveness of CCTV systems in these settings. Conclusion: The EthioCAD dataset, alongside the YOLOv8 model, provides a promising framework for automated campus activity recognition. This approach lays the groundwork for future advancements in CCTV-based educational surveillance systems, enabling more refined and reliable monitoring of classroom activities.

Keywords: deep CNN, EthioCAD, deep learning, YOLOv8, activity recognition

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Authors: Sulemana Saibu, Moses Ikpeme

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Background: The severity of the COVID-19 pandemic, brought on by the SARS-CoV-2 coronavirus, has been unprecedented since the 1918 influenza pandemic. SARS-CoV-2 cases of CNS and peripheral nervous system disease, including neurodegenerative disorders and chronic immune-mediated diseases, may be anticipated based on knowledge of past coronaviruses, particularly those that caused the severe acute respiratory syndrome and Middle East respiratory syndrome outbreaks. Although respiratory symptoms are the most common clinical presentation, neurological symptoms are becoming increasingly recognized, raising concerns about their potential role in causing Parkinson's disease, Multiple sclerosis, and Narcolepsy. This systematic review aims to summarize the current evidence by exploring the association between COVID-19 infection and how it may overlap with etiological mechanisms resulting in Narcolepsy, Parkinson's disease, and Multiple sclerosis. Methods: A systematic search was conducted using electronic databases ((PubMed/MedLine, Embase, PsycINFO, ScieLO, Web of Science, ProQuest (Biotechnology, Virology, and AIDS), Scopus, and CINAHL)) to identify studies published between January 2020 and December 2022 that investigated the association between COVID-19 and Parkinson's disease, multiple sclerosis, and Narcolepsy. Per the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines, the review was performed and reported. Study quality was assessed using the Critical Appraisal Skills Programme Checklist and the Joanna Briggs Institute Critical appraisal tools. Results: A total of 21 studies out of 1025 met the inclusion criteria, including 8 studies reporting Parkinson's disease, 11 on multiple sclerosis, and 2 on Narcolepsy. In COVID-19 individuals compared to the general population, Narcolepsy, Parkinson's disease, and multiple sclerosis were shown to have a higher incidence. The findings imply that COVID-19 may worsen the signs or induce multiple sclerosis and Parkinson's disease and may raise the risk of developing Narcolepsy. Further research is required to confirm these connections because the available data is insufficient. Conclusion: According to the existing data, COVID-19 may raise the risk of Narcolepsy and have a causative relationship with Parkinson's disease, multiple sclerosis, and other diseases. More study is required to confirm these correlations and pinpoint probable mechanisms behind these interactions. Clinicians should be aware of how COVID-19 may affect various neurological illnesses and should treat patients who are affected accordingly.

Keywords: COVID-19, parkinson’s disease, multiple sclerosis, narcolepsy, neurological disorders, sars-cov-2, neurodegenerative disorders, chronic immune-mediated diseases

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Authors: Chi-Ying Yu

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In real life, the occurrence of disasters is always dreadful and heartbreaking, yet paradoxically, disaster film is a genre that has been popular at periodic intervals in motion picture history. This study attempts to compare the disaster film cycles of the 1970s, 1990s, and the early 21st century. Two research questions are addressed: First, how this genre has responded to the existing conditions of society in different periods in terms of the disaster proposition? Second, how this genre reflects a certain eternal substance of the human mind in light of its lasting appeal? Through cinematic textual analysis and literature review, this study finds that the emergence of disaster films in the 1970s reflected the turmoil in international relations and domestic politics situation in contemporary American society, and cinema screens showed such disaster stories as shipwrecks, air accidents, and skyscraper blazes due to human negligence. The 1990s saw the fervor of millennial apocalypse legends, and the awakening of environmental consciousness, which, together with the rapid advances in digital technology, once again gave rise to a frenzy of disaster films, with natural disasters and threats from aliens as the major themes of disasters. Since the beginning of the 21st century, the 911 Incident and natural disasters around the world have generated a consciousness of imminent crisis. Cinematic images simulated actual disasters, while aesthetic techniques focused on creating a kind of ‘empathetic’ experience in their exploration of the essence of the disaster experience. At the same time, post-apocalypse films that focus on post-disaster reconstruction have become an even more popular theme. Taking the approach of Jungian/post-Jungian film study, this study also reviews and interprets the commonly exhibited subliminal feelings in the disaster films of the three different periods. The imagination of disaster seems to serve as an underlying state of the human mind.

Keywords: disaster film, Jungian/post-Jungian film studies, stimulation, sublime

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Authors: Zachary Blanks, Solomon Sonya

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Poaching presents a serious threat to endangered animal species, environment conservations, and human life. Additionally, some poaching activity has even been linked to supplying funds to support terrorist networks elsewhere around the world. Consequently, agencies dedicated to protecting wildlife habitats have a near intractable task of adequately patrolling an entire area (spanning several thousand kilometers) given limited resources, funds, and personnel at their disposal. Thus, agencies need predictive tools that are both high-performing and easily implementable by the user to help in learning how the significant features (e.g. animal population densities, topography, behavior patterns of the criminals within the area, etc) interact with each other in hopes of abating poaching. This research develops a classification model using machine learning algorithms to aid in forecasting future attacks that is both easy to train and performs well when compared to other models. In this research, we demonstrate how data imputation methods (specifically predictive mean matching, gradient boosting, and random forest multiple imputation) can be applied to analyze data and create significant predictions across a varied data set. Specifically, we apply these methods to improve the accuracy of adopted prediction models (Logistic Regression, Support Vector Machine, etc). Finally, we assess the performance of the model and the accuracy of our data imputation methods by learning on a real-world data set constituting four years of imputed data and testing on one year of non-imputed data. This paper provides three main contributions. First, we extend work done by the Teamcore and CREATE (Center for Risk and Economic Analysis of Terrorism Events) research group at the University of Southern California (USC) working in conjunction with the Department of Homeland Security to apply game theory and machine learning algorithms to develop more efficient ways of reducing poaching. This research introduces ensemble methods (Random Forests and Stochastic Gradient Boosting) and applies it to real-world poaching data gathered from the Ugandan rain forest park rangers. Next, we consider the effect of data imputation on both the performance of various algorithms and the general accuracy of the method itself when applied to a dependent variable where a large number of observations are missing. Third, we provide an alternate approach to predict the probability of observing poaching both by season and by month. The results from this research are very promising. We conclude that by using Stochastic Gradient Boosting to predict observations for non-commercial poaching by season, we are able to produce statistically equivalent results while being orders of magnitude faster in computation time and complexity. Additionally, when predicting potential poaching incidents by individual month vice entire seasons, boosting techniques produce a mean area under the curve increase of approximately 3% relative to previous prediction schedules by entire seasons.

Keywords: ensemble methods, imputation, machine learning, random forests, statistical analysis, stochastic gradient boosting, wildlife protection

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Authors: Mehrnoosh Abouzari, Shahrokh Sahraei

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Arrival of artificial intelligence or smart robots in the modern world put them in charge on pericise and at risk. So acting human activities with robots makes criminal or civil responsibilities for their acts or behavior. The practical usage of smart robots has entered them in to a unique situation when naturalization happens and smart robots are identifies as members of society. There would be some legal situation by adopting these new smart citizens. The first situation is about legal responsibility of robots. Recognizing the naturalization of robot involves some basic right , so humans have the rights of employment, property, housing, using energy and other human rights may be employed for robots. So how would be the practice of these rights in the society and if some problems happens with these rights, how would the civil responsibility and punishment? May we consider them as population and count on the social programs? The second episode is about the criminal responsibility of robots in important activity instead of human that is the aim of inventing robots with handling works in AI technology , but the problem arises when some accidents are happened by robots who are in charge of important activities like army, surgery, transporting, judgement and so on. Moreover, recognizing independent identification for robots in the legal world by register ID cards, naturalization and civilian rights makes and prepare the same rights and obligations of human. So, the civil responsibility is not avoidable and if the robot commit a crime it would have criminal responsibility and have to be punished. The basic component of criminal responsibility may changes in so situation. For example, if designation for criminal responsibility bounds to human by sane, maturity, voluntariness, it would be for robots by being intelligent, good programming, not being hacked and so on. So it is irrational to punish robots by prisoning , execution and other human punishments for body. We may determine to make digital punishments like changing or repairing programs, exchanging some parts of its body or wreck it down completely. Finally the responsibility of the smart robot creators, programmers, the boss in chief, the organization who employed robot, the government which permitted to use robot in important bases and activities , will be analyzing and investigating in their article.

Keywords: robot, artificial intelligence, personality, responsibility

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Authors: Doddy T. P. Enggarsyah, Soebowo Musa

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Covid-19 pandemic has changed business environments and has spread economic contagion rapidly, as the stringent lockdowns and social distancing, which were initially intended to cut off the spread, have instead cut off the flow of economies. With no existing experience or playbook to deal with such a crisis, the prolonged pandemic can lead to bankruptcies, despite the fact that there are cases of companies that are not only able to survive but also to increase sales and create more jobs amid the economic crisis. This quantitative research study clarifies conflicting findings on organizational inertia whether it is a better strategy to implement during a disruptive environment. 316 respondents who worked in diverse firms operating in various industry types in Indonesia have completed the survey with a response rate of 63.2%. Further, this study clarifies the roles and relationships between organizational inertia, organizational creativity, organizational agility, and organizational resilience that potentially have determinants factors on firm performance in a disruptive environment. The findings of the study confirm that the organizational inertia of the firm will set up strong protection on the organization's fundamental orientation, which eventually will confine organizations to build adequate creative and adaptability responses—such fundamental orientation built from path dependency along with past success and prolonged firm performance. Organizational inertia acts like a control mechanism to ensure the adequacy of the given responses. The term adequate is important, as being overly creative during a disruptive environment may have a contradictory result since it can burden the firm performance. During a disruptive environment, organizations will limit creativity by focusing more on creativity that supports the resilience and new technology adoption will be limited since the cost of learning and implementation are perceived as greater than the potential gains. The optimal path towards firm performance is gained through organizational resilience, as in a disruptive environment, the survival of the organization takes precedence over firm performance.

Keywords: disruptive environment, organizational agility, organizational creativity, organizational inertia, organizational resilience

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Authors: M. Qamarul Islam, Ergun Dogan, Mehmet Yazici

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There is a growing body of evidence that non-normal data is more prevalent in nature than the normal one. Examples can be quoted from, but not restricted to, the areas of Economics, Finance and Actuarial Science. The non-normality considered here is expressed in terms of fat-tailedness and asymmetry of the relevant distribution. In this study a skew t distribution that can be used to model a data that exhibit inherent non-normal behavior is considered. This distribution has tails fatter than a normal distribution and it also exhibits skewness. Although maximum likelihood estimates can be obtained by solving iteratively the likelihood equations that are non-linear in form, this can be problematic in terms of convergence and in many other respects as well. Therefore, it is preferred to use the method of modified maximum likelihood in which the likelihood estimates are derived by expressing the intractable non-linear likelihood equations in terms of standardized ordered variates and replacing the intractable terms by their linear approximations obtained from the first two terms of a Taylor series expansion about the quantiles of the distribution. These estimates, called modified maximum likelihood estimates, are obtained in closed form. Hence, they are easy to compute and to manipulate analytically. In fact the modified maximum likelihood estimates are equivalent to maximum likelihood estimates, asymptotically. Even in small samples the modified maximum likelihood estimates are found to be approximately the same as maximum likelihood estimates that are obtained iteratively. It is shown in this study that the modified maximum likelihood estimates are not only unbiased but substantially more efficient than the commonly used moment estimates or the least square estimates that are known to be biased and inefficient in such cases. Furthermore, in conventional regression analysis, it is assumed that the error terms are distributed normally and, hence, the well-known least square method is considered to be a suitable and preferred method for making the relevant statistical inferences. However, a number of empirical researches have shown that non-normal errors are more prevalent. Even transforming and/or filtering techniques may not produce normally distributed residuals. Here, a study is done for multiple linear regression models with random error having non-normal pattern. Through an extensive simulation it is shown that the modified maximum likelihood estimates of regression parameters are plausibly robust to the distributional assumptions and to various data anomalies as compared to the widely used least square estimates. Relevant tests of hypothesis are developed and are explored for desirable properties in terms of their size and power. The tests based upon modified maximum likelihood estimates are found to be substantially more powerful than the tests based upon least square estimates. Several examples are provided from the areas of Economics and Finance where such distributions are interpretable in terms of efficient market hypothesis with respect to asset pricing, portfolio selection, risk measurement and capital allocation, etc.

Keywords: least square estimates, linear regression, maximum likelihood estimates, modified maximum likelihood method, non-normality, robustness

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Authors: Omuvwie R. Ewien

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Palm oil production in Delta State, Nigeria, is a significant economic activity. However, ensuring its sustainability is crucial to mitigate environmental impacts, promote social equity, and maintain long-term economic viability. This abstract provides an overview of palm oil production sustainability in Delta State, focusing on environmental, social, and economic aspects. In terms of environmental sustainability, the impact of palm oil plantations on deforestation and biodiversity loss is explored. The adoption of sustainable land use practices and measures to reduce greenhouse gas emissions, such as conserving high conservation value areas and utilizing methane capture systems, are highlighted. Social sustainability considerations encompass the inclusion and empowerment of smallholders, ensuring fair labor practices and community engagement. Supporting small-scale farmers, promoting fair working conditions, and investing in local infrastructure and services are identified as key strategies. Economic sustainability is emphasized through yield improvement, efficiency, and value addition. Enhancing productivity and profitability for farmers, promoting downstream processing and market diversification, and building economic resilience is crucial for long-term sustainability. Government policies, including regulatory frameworks and public-private collaborations, play a pivotal role in promoting sustainable palm oil production. Enabling policies and partnerships with industry stakeholders and NGOs facilitates the adoption of sustainable practices. Challenges such as illegal activities, the need to balance economic development with environmental conservation, and leveraging technology for sustainability are discussed. The abstract concludes by emphasizing the importance of stakeholders' commitment to prioritize sustainable palm oil production in Delta State, Nigeria, for a sustainable future.

Keywords: palm oil production, environmental sustainability, community development, yield improvement, future outlook

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Authors: Ka Ho Yau, Jan Frederick Engels, Kwok Kei Lai, Reinhard Renneberg

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Lateral flow test is a prevalent technology in various sectors such as food, pharmacology and biomedical sciences. Colloidal gold (CG) is widely used as the signalling molecule because of the ease of synthesis, bimolecular conjugation and its red colour due to intrinsic SPRE. However, the production of colloidal gold is costly and requires vigorous conditions. The stability of colloidal gold are easily affected by environmental factors such as pH, high salt content etc. Silica nanoparticles are well known for its ease of production and stability over a wide range of solvents. Using reverse micro-emulsion (w/o), silica nanoparticles with different sizes can be produced precisely by controlling the amount of water. By incorporating different water-soluble dyes, a rainbow colour of the silica nanoparticles could be produced. Conjugation with biomolecules such as antibodies can be achieved after surface modification of the silica nanoparticles with organosilane. The optimum amount of the antibodies to be labelled was determined by Bradford Assay. In this work, we have demonstrated the ability of the dye-doped silica nanoparticles as a signalling molecule in lateral flow test, which showed a semi-quantitative measurement of the analyte. The image was further analysed for the LOD=10 ng of the analyte. The working range and the linear range of the test were from 0 to 2.15μg/mL and from 0 to 1.07 μg/mL (R2=0.988) respectively. The performance of the tests was comparable to those using colloidal gold with the advantages of lower cost, enhanced stability and having a wide spectrum of colours. The positives lines can be imaged by naked eye or by using a mobile phone camera for a better quantification. Further research has been carried out in multicolour detection of different biomarkers simultaneously. The preliminary results were promising as there was little cross-reactivity being observed for an optimized system. This approach provides a platform for multicolour detection for a set of biomarkers that enhances the accuracy of diseases diagnostics.

Keywords: colorimetric detection, immunosensor, paper-based biosensor, silica

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Authors: Kayum Fokoue Carole

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This paper aims at verifying the effectiveness of reaching target populations while paying attention to their cultural background when communicating new knowledge, ideas or technology in a multicultural world. Our case study is an experiment on the communication of knowledge on breast cancer in three sub-Saharan countries (Ghana, Tchad, and Cameroon health). The methodology consisted of submitting a semi-structured questionnaire to local populations in some localities in these target countries in order to determine the cultural barriers hindering the effective communication of knowledge on breast cancer. Once this done, sensitization documents on breast cancer were translated into Ewe (Ghana), Mbaye (Tchad), Ghomala’, Ewondo, and Fufulde (Cameroon). In each locality, a sensitization programme was organised for two groups. For one group, the cultural barriers discovered were taken into consideration while communicating during the programme whereas in the other group, they were not. Another questionnaire was disseminated after three months to verify the level of appropriation of those who attended the campaign based on Chumbow’s appropriation theory. This paper, therefore, discusses some spiritual beliefs, representations and practices in the target African communities hindering effective communication of issues on breast cancer in the target localities. Findings reveal that only 38% of respondents in the group of those for whom cultural barriers were not taken into account during the programme had a high level of appropriation while for the other group, 86% had a high level of appropriation. This is evidence that the communication of issues on breast cancer can be more effective by reaching different populations in a language they best master while paying attention to their culture. Therefore, international communication of new knowledge should be culturally contextualised. Suggestions at the end of the paper are directed towards the achievement of these goals. The present work promotes international partnership in addressing and resolving global health preoccupations since research findings from one community/country can be mutualized in partnership with other communities and countries.

Keywords: cultural barriers, communication, health, breast cancer

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Authors: Samantha Ramachandra, Avanthi Rupasinghe

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Demographic transition from lower to higher percentage of elderly population eventually coupled with epidemiological transition from communicable to non-communicable diseases (NCD). Higher percentage of NCD overload the health system as NCD survivors claims continuous health care. The demands are challenging to a resource constrained setting but reorganizing the system may find solutions. The study focused on the facilities available and their utilization at outpatient department (OPD) setting of the public hospitals of Sri Lanka for continuous medical care. This will help in identifying steps of reorganizing the system to provide better care with the maximum utilization of available facilities. The study was conducted as a situation analysis with secondary data at hospital planning units. Variable were identified according to the world health organization (WHO) recommendation on continuous health care for elders in “age-friendly primary health care toolkit”. Data were collected from secondary and tertiary care hospitals of Sri Lanka where most of the continuous care services are available. Out of 58 secondary and tertiary care hospitals, 16 were included in the study to represent each hospital categories. Average number of patient attending for episodic treatment at OPD and Clinical follow-up of chronic conditions shows vast disparity according to the category of the hospital ranging from 3750 – 800 per day at OPD and 1250 – 200 per clinic session. Average time spent per person at OPD session is low, range from 1.54 - 2.28 minutes, the time was increasing as the hospital category goes down. 93.7% hospitals had special arrangements for providing acute care on chronic conditions such as catheter, feeding tube and wound care. 25% hospitals had special clinics for elders, 81.2% hospitals had healthy lifestyle clinics (HLC), 75% hospitals had physical rehabilitation facilities and 68.8% hospitals had facilities for counselling. Elderly clinics and HLC were mostly available at lower grade hospitals where as rehabilitation and counselling facilities were mostly available at bigger hospitals. HLC are providing health education for both patients and their family members, refer patients for screening of complication but not provide medical examinations, investigations or treatments even though they operate in the hospital setting. Physical rehabilitation is basically offered for patients with rheumatological conditions but utilization of centers for injury rehabilitation and rehabilitation of survivors following major illness such as myocardial infarctions, stroke, cancer is not satisfactory (12.5%). Human Resource distribution within hospital shows vast disparity and there are 103 physiotherapists in the biggest hospital where only 36 physiotherapists available at the next level hospital. Counselling facilities also provided mainly for the patient with psychological conditions (100%) but they were not providing counselling for newly diagnosed patients with major illnesses (0%). According to results, most of the public-sector hospitals in Sri Lanka have basic facilities required in providing continuous care but the utilization of services need more focus. Hospital administration or the government need to have initial steps in proper utilization of them in improving continuous health care incorporating team approach of rehabilitation. The author wishes to acknowledge that this paper was made possible by the support and guidance given by the “Australia Awards Fellowships Program for Sri Lanka – 2017,” which was funded by the Department of Foreign Affairs and Trade, Australia, and co-hosted by Monash University, Australia and the Sri Lanka Institute of Development Administration.

Keywords: continuous care, outpatient department, non communicable diseases, rehabilitation

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Authors: Popoola I. Olayinka, Alamu E. Oladeji, B. Maziya-Dixon

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Cassava, an indigenous crop grown locally by subsistence farmers in Nigeria has potential to bring economic benefits to the country. Consumption of bread and other confectionaries has been on the rise due to lifestyle changes of Nigerian consumers. However, wheat, being the major ingredient for bread and confectionery production does not thrive well under Nigerian climate hence the huge spending on wheat importation. To reduce spending on wheat importation, the Federal Government of Nigeria intends passing into law mandatory inclusion of 20% high-quality cassava flour (HQCF) in wheat flour. While the proposed policy may reduce post harvest loss of cassava, and also increase food security and domestic agricultural productivity, there are downsides to the policy which include reduction in nutritional quality and low sensory appeal of cassava-wheat bread, reluctance of flour millers to use HQCF, technology and processing challenges among others. The policy thus presents an ethical dilemma which must be resolved for its successful implementation. While inclusion of HQCF to wheat flour in bread and confectionery is a topic that may have been well addressed, resolving the ethical dilemma resulting from the act has not received much attention. This paper attempts to resolve this dilemma using various approaches in food ethics (cost benefits, utilitarianism, deontological and deliberative). The Cost-benefit approach did not provide adequate resolution of the dilemma as all the costs and benefits of the policy could not be stated in the quantitative term. The utilitarianism approach suggests that the policy delivers greatest good to the greatest number while the deontological approach suggests that the act (inclusion of HQCF to wheat flour) is right hence the policy is not utterly wrong. The deliberative approach suggests a win-win situation through deliberation with the parties involved.

Keywords: HQCF, ethical dilemma, food security, composite flour, cassava bread

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Authors: Maryam Mohammadi, Mohammadjavad Mahdavinejad, Mojtaba Ansari

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The main driving force for increasing movement towards the design of High-Performance Buildings (HPB) are building codes and rating systems that address the various components of the building and their impact on the environment and energy conservation through various methods like prescriptive methods or simulation-based approaches. The methods and tools developed to meet these needs, which are often based on building performance simulation tools (BPST), have limitations in terms of compatibility with the integrated design process (IDP) and HPB design, as well as use by architects in the early stages of design (when the most important decisions are made). To overcome these limitations in recent years, efforts have been made to develop Design Decision Support Systems, which are often based on artificial intelligence. Numerous needs and steps for designing and developing a Decision Support System (DSS), which complies with the early stages of energy-efficient architecture design -consisting of combinations of different methods in an integrated package- have been listed in the literature. While various review studies have been conducted in connection with each of these techniques (such as optimizations, sensitivity and uncertainty analysis, etc.) and their integration of them with specific targets; this article is a critical and holistic review of the researches which leads to the development of applicable systems or introduction of a comprehensive framework for developing models complies with the IDP. Information resources such as Science Direct and Google Scholar are searched using specific keywords and the results are divided into two main categories: Simulation-based DSSs and Meta-simulation-based DSSs. The strengths and limitations of different models are highlighted, two general conceptual models are introduced for each category and the degree of compliance of these models with the IDP Framework is discussed. The research shows movement towards Multi-Level of Development (MOD) models, well combined with early stages of integrated design (schematic design stage and design development stage), which are heuristic, hybrid and Meta-simulation-based, relies on Big-real Data (like Building Energy Management Systems Data or Web data). Obtaining, using and combining of these data with simulation data to create models with higher uncertainty, more dynamic and more sensitive to context and culture models, as well as models that can generate economy-energy-efficient design scenarios using local data (to be more harmonized with circular economy principles), are important research areas in this field. The results of this study are a roadmap for researchers and developers of these tools.

Keywords: integrated design process, design decision support system, meta-simulation based, early stage, big data, energy efficiency

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Authors: Rachid Dris, Robin Treilles, Max Beaurepaire, Minh Trang Nguyen, Sam Azimi, Vincent Rocher, Johnny Gasperi, Bruno Tassin

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Microplastic sources and fluxes in urban catchments are only poorly studied. Most often, the approaches taken focus on a single source and only carry out a description of the contamination levels and type (shape, size, polymers). In order to gain an improved knowledge of microplastic inputs at urban scales, estimating and comparing various fluxes is necessary. The Laboratoire Eau, Environnement et Systèmes Urbains (LEESU), the Laboratoire Eau Environnement (LEE) and the SIAAP (Service public de l’assainissement francilien) initiated several projects to investigate different urban sources and flows of microplastics. A systemic approach is undertaken at the scale of Paris Megacity, and several compartments are considered, including atmospheric fallout, wastewater treatments plants, runoff and combined sewer overflows. These investigations are carried out within the Limnoplast and OPUR projects. Atmospheric fallout was sampled during consecutive periods ranging from 2 to 3 weeks with a stainless-steel funnel. Both wet and dry periods were considered. Different treatment steps were sampled in 2 wastewater treatment plants (Seine-Amont for activated sludge and Seine-Centre for biofiltration) of the SIAAP, including sludge samples. Microplastics were also investigated in combined sewer overflows as well as in stormwater at the outlet suburban catchment (Sucy-en-Brie, France) during four rain events. Samples are treated using hydroperoxide digestion (H₂O₂ 30 %) in order to reduce organic material. Microplastics are then extracted from the samples with a density separation step using NaI (d=1.6 g.cm⁻³). Samples are filtered on metallic filters with a porosity of 14 µm between steps to separate them from the solutions (H₂O₂ and NaI). The last filtration was carried out on alumina filters. Infrared mapping analysis (using a micro-FTIR with an MCT detector) is performed on each alumina filter. The resulting maps are analyzed using a microplastic analysis software simple, developed by Aalborg University, Denmark and Alfred Wegener Institute, Germany. Blanks were systematically carried out to consider sample contamination. This presentation aims at synthesizing the data found in the various projects. In order to carry out a systemic approach and compare the various inputs, all the data were converted into annual microplastic fluxes (number of microplastics per year), and extrapolated to the Parisian agglomeration. PP, PE and alkyd are the most prevalent polymers found in storm water samples. Rain intensity and microplastic concentrations did not show any clear correlation. Considering the runoff volumes and the impervious surface area of the studied catchment, a flux of 4*107–9*107 MPs.yr⁻¹.ha⁻¹ was estimated. Samples of wastewater treatment plants and atmospheric fallout are currently being analyzed in order to finalize this assessment. The representativeness of such samplings and uncertainties related to the extrapolations will be discussed and gaps in knowledge will be identified. The data provided by such an approach will help to prioritize future research as well as policy efforts.

Keywords: microplastics, atmosphere, wastewater, urban runoff, Paris megacity, urban waters

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Authors: Daniela Rivera-Tobar Mario Perez-Won, Roberto Lemus-Mondaca, Gipsy Tabilo-Munizaga

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Different dietary trends worldwide seek to consume foods with anti-inflammatory properties, rich in antioxidants, proteins, and unsaturated fatty acids that lead to better metabolic, intestinal, mental, and cardiac health. In this sense, food matrices with high protein content based on macro and microalgae are an excellent alternative to meet the new needs of consumers. An emerging and environmentally friendly technology for producing protein matrices is ultrasonic agglomeration. It consists of the formation of permanent bonds between particles, improving the agglomeration of the matrix compared to conventionally agglomerated products (compression). Among the advantages of this process are the reduction of nutrient loss and the avoidance of binding agents. The objective of this research was to optimize the ultrasonic agglomeration process in matrices composed of Spirulina (Arthrospira platensis) powder and Cochayuyo (Durvillae Antartica) flour, by means of the response variable (Young's modulus) and the independent variables were the process conditions (percentage of ultrasonic amplitude: 70, 80 and 90; ultrasonic agglomeration times and cycles: 20, 25 and 30 seconds, and 3, 4 and 5). It was evaluated using a central composite design and analyzed using response surface methodology. In addition, the effects of agglomeration on thermophysical and microstructural properties were evaluated. It was determined that ultrasonic compression with 80 and 90% amplitude caused conformational changes according to Fourier infrared spectroscopy (FTIR) analysis, the best condition with respect to observed microstructure images (SEM) and differential scanning calorimetry (DSC) analysis, was the condition of 90% amplitude 25 and 30 seconds with 3 and 4 cycles of ultrasound. In conclusion, the agglomerated matrices present good macro and microstructural properties which would allow the design of food systems with better nutritional and functional properties.

Keywords: ultrasonic agglomeration, physical properties of food, protein matrices, macro and microalgae

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Authors: George Cudjoe Agbemabiese, John Paul Kosiba, Michael Boadi Nyamekye, Vanessa Narkie Tetteh, Caleb Nunoo, Mohammed Muniru Husseini

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The smartphone industry continues to experience massive growth, evidenced by expanding markets and an increasing number of brands, models and manufacturers. As technology advances rapidly, manufacturers of smartphones are consistently introducing new innovations to keep up with the latest evolving industry trends and customer demand for more modern devices. This study aimed to assess the influence of artificial intelligence (AI) voice assistant (VA) on improving customer experience, resulting in the continuous use of mobile brands. Specifically, this article assesses the role of hedonic, utilitarian, and social benefits provided by AIVA on customer experience and the continuance intention to use mobile phone brands. Using a primary data collection instrument, the quantitative approach was adopted to examine the study's variables. Data from 348 valid responses were used for the analysis based on structural equation modeling (SEM) with AMOS version 23. Three main factors were identified to influence customer experience, which results in continuous usage of mobile phone brands. These factors are social benefits, hedonic benefits, and utilitarian benefits. In conclusion, a significant and positive relationship exists between the factors influencing customer experience for continuous usage of mobile phone brands. The study concludes that mobile brands that invest in delivering positive user experiences are in a better position to improve usage and increase preference for their brands. The study recommends that mobile brands consider and research their prospects' and customers' social, hedonic, and utilitarian needs to provide them with desired products and experiences.

Keywords: artificial intelligence, continuance usage, customer experience, smartphone industry

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Authors: Matej Buzgo, Erico Himawan, Ksenija JašIna, Aiva Simaite

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Electrospinning is a versatile and efficient technology for producing nanofibers for biomedical applications. One of the most common polymers used for the preparation of nanofibers for regenerative medicine and drug delivery applications is polycaprolactone (PCL). PCL is a biocompatible and bioabsorbable material that can be used to stimulate the regeneration of various tissues. It is also a common material used for the development of drug delivery systems by blending the polymer with small active molecules. However, for many drug delivery applications, e.g. cancer immunotherapy, PCL biodegradation rate that may exceed 9 months is too long, and faster nanofiber dissolution is needed. In this paper, we investigate the dissolution and small molecule release rates of PCL blends with two hydrophilic polymers: polyethylene oxide (PEO) or polyvinylpyrrolidone (PVP). We show that adding hydrophilic polymer to the PCL reduces the water contact angle, increases the dissolution rate, and strengthens the interactions between the hydrophilic drug and polymer matrix that further sustain its release. Finally using this method, we were also able to increase the nanofiber degradation rate when PCL-PEO and PCL-PVP were used as a shell in the electrospun core-shell nanofibers and spread up the release of active proteins from their core. Electrospinning can be used for the preparation of the core-shell nanofibers, where active ingredients are encapsulated in the core and their release rate is regulated by the shell. However, such fibers are usually prepared by coaxial electrospinning that is an extremely low-throughput technique. An alternative is emulsion electrospinning that could be upscaled using needleless blades. In this work, we investigate the possibility of using emulsion electrospinning for encapsulation and sustained release of the growth factors for the development of the organotypic skin models. The core-shell nanofibers were prepared using the optimized formulation and the release rate of proteins from the fibers was investigated for 2 weeks – typical cell culture conditions.

Keywords: electrospinning, polycaprolactone (PCL), polyethylene oxide (PEO), polyvinylpyrrolidone (PVP)

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Authors: Guillaume Craveur

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This study shows the opportunity to use numerical tools dedicated to Fire Safety Engineering for the Rolling Stock. Indeed, some lawful requirements can now be demonstrated by using numerical tools. The first part of this study presents the use of modelling evacuation tool to satisfy the criteria of evacuation time for the rolling stock. The buildingEXODUS software is used to model and simulate the evacuation of rolling stock. Firstly, in order to demonstrate the reliability of this tool to calculate the complete evacuation time, a comparative study was achieved between a real test and simulations done with buildingEXODUS. Multiple simulations are performed to capture the stochastic variations in egress times. Then, a new study is done to calculate the complete evacuation time of a train with the same geometry but with a different interior architecture. The second part of this study shows some applications of Computational Fluid Dynamics. This work presents the approach of a multi scales validation of numerical simulations of standardized tests with Fire Dynamics Simulations software developed by the National Institute of Standards and Technology (NIST). This work highlights in first the cone calorimeter test, described in the standard ISO 5660, in order to characterize the fire reaction of materials. The aim of this process is to readjust measurement results from the cone calorimeter test in order to create a data set usable at the seat scale. In the second step, the modelisation concerns the fire seat test described in the standard EN 45545-2. The data set obtained thanks to the validation of the cone calorimeter test was set up in the fire seat test. To conclude with the third step, after controlled the data obtained for the seat from the cone calorimeter test, a larger scale simulation with a real part of train is achieved.

Keywords: fire safety engineering, numerical tools, rolling stock, multi-scales validation

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Authors: Jiwon Lee, Yeong-Ju Go, Jong-Soo Choi

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Drones were first developed for military use and were used in World War 1. But recently drones have been used in a variety of fields. Several companies actively utilize drone technology to strengthen their services, and in agriculture, drones are used for crop monitoring and sowing. Other people use drones for hobby activities such as photography. However, as the range of use of drones expands rapidly, problems caused by drones such as improperly flying, privacy and terrorism are also increasing. As the need for monitoring and tracking of drones increases, researches are progressing accordingly. The drone detection system estimates the position of the drone using the physical phenomena that occur when the drones fly. The drone detection system measures being developed utilize many approaches, such as radar, infrared camera, and acoustic detection systems. Among the various drone detection system, the acoustic detection system is advantageous in that the microphone array system is small, inexpensive, and easy to operate than other systems. In this paper, the acoustic signal is acquired by using minimum microphone when drone is flying, and direction of drone is estimated. When estimating the Direction of Arrival(DOA), there is a method of calculating the DOA based on the Time Difference of Arrival(TDOA) and a method of calculating the DOA based on the beamforming. The TDOA technique requires less number of microphones than the beamforming technique, but is weak in noisy environments and can only estimate the DOA of a single source. The beamforming technique requires more microphones than the TDOA technique. However, it is strong against the noisy environment and it is possible to simultaneously estimate the DOA of several drones. When estimating the DOA using acoustic signals emitted from the drone, it is impossible to measure the position of the drone, and only the direction can be estimated. To overcome this problem, in this work we show how to estimate the position of drones by arranging multiple microphone arrays. The microphone array used in the experiments was four tetrahedral microphones. We simulated the performance of each DOA algorithm and demonstrated the simulation results through experiments.

Keywords: acoustic sensing, direction of arrival, drone detection, microphone array

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Authors: Cliff Shunsheng Han

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Identifying the direct allergy cause that can be easily mitigated is the foundation to stop the allergy epidemic that has been started in the seventies. It has confirmed that the personal and social hygiene practices are associated with the allergy prevalence. But direct causes have been found, and proposed translational measures have not been effective. This study, assisted by a particular case of allergies, has seen the direct cause of allergies, developed a valid test resulted in lasting relief for allergies, and constructed theory describing general relationship between microbiota and host immune system. Saliva samples were collected from a subject for three years during which time the person experienced yearlong allergy, seasonal allergy, and remission of allergy symptoms. Bacterial DNA was extracted and 16S rRNA genes were profiled with Illumina sequencing technology. The analyzing results indicate that the possible direct cause of allergy is the lacking probiotic bacteria in the oral cavity, such as genera Streptococcus and Veilonella, that can produce metabolites to pacify immune system. Targeted promotion of those bacteria with a compound designed for them, has led to lasting remissions of allergic rhinitis. During the development of the translational measure, the subject's oral biofilm was completely destructed by a moderate fever due to an unrelated respiratory infection. The incident not only facilitated the development of the heat based microbiota reseeding procedure but also indicated a possible natural switch that subsequently increases the efficacy of the immune system previously restrained by metabolites from microbiota. These results lead to the proposal of a Theory of Negative Trigger (TNT) to describe the relationship between oral probiotics and immune system, in which probiotics are the negative trigger that will release the power of immune system when removed by fever or modern lifestyles. This study could open doors leading to further understanding of how the immune system functions under the influence of microbiota as well as validate simple traditional practices for healthy living.

Keywords: oral microbiome, allergy, immune system, infection

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Authors: D. Berg, N. Hartley, L. Nasr

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This paper presents a conceptual model of human-robot interaction within service encounters and the effect on the well-being of both consumers and service providers. In this paper, service providers are those employees who work alongside frontline service robots. The significance of this paper lies in the knowledge created which outlines how frontline service robots can be effectively utilized in service encounters for the benefit of organizations and society as a whole. As this paper is conceptual in nature, the main methodologies employed are theoretical, namely problematization and theory building. The significance of this paper is underpinned by the shift of service robots from manufacturing plants and factory floors to consumer-facing service environments. This service environment places robots in direct contact with frontline employees and consumers creating a hybrid workplace where humans work alongside service robots. This change from back-end to front-end roles may have implications not only on the physical environment, servicescape, design, and strategy of service offerings and encounters but also on the human parties of the service encounter itself. Questions such as ‘how are frontline service robots impacting and changing the service encounter?’ and ‘what effect are such changes having on the well-being of the human actors in a service encounter?’ spring to mind. These questions form the research question of this paper. To truly understand social service robots, an interdisciplinary perspective is required. Besides understanding the function, system, design or mechanics of a service robot, it is also necessary to understand human-robot interaction. However not simply human-robot interaction, but particularly what happens when such robots are placed in commercial settings and when human-robot interaction becomes consumer-robot interaction and employee-robot interaction? A service robot in this paper is characterized by two main factors; its social characteristics and the consumer-facing environment within which it operates. The conceptual framework presented in this paper contributes to interdisciplinary discussions surrounding social robotics, service, and technology’s impact on consumer and service provider well-being, and hopes that such knowledge will help improve services, as well as the prosperity and well-being of society.

Keywords: frontline service robots, human-robot interaction, service encounters, well-being

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Authors: Bauta J., Raynaud C., Vaca-Medina G., Simon V., Roully A., Vandenbossche V.

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Sargassum is a brown algae, originally found in the Sargasso Sea, located in the Caribbean region and the Gulf of Mexico. The flow of Sargassum is becoming a critical environmental problem all over the Caribbean islands particularly. In Guadeloupe alone, around 80,000 tons of seaweed are stranded during the season. Since the appearance of the first waves of Sargassum algae, several measures have been taken to collect them to keep the beaches clean. Nevertheless, 90% of the collected algae are currently stored without recovery. The lack of research initiative demands a more in-depth exploration of Sargassum algae chemistry, targeted towards added value applications and their development. In this context, the aim of the study was to develop a biorefinery process to valorize Sargassum as a source of bioactive natural substances and as raw material to produce biomaterials simultaneously. The technology used was the twin-screw extrusion, which allows to achieve continuously in the same machine different unit fractionation operations. After the identification of the molecules of interest in Sargassum algae, different operating conditions of thermo-mechanical treatment were applied in a twin-screw extruder. The nature of the solvent, the configuration of the extruder, the screw profile, and the temperature profile were studied in order to fractionate the algal biomass and to allow the recovery of a bioactive liquid fraction of interest and a solid residue suitable for the production of biomaterials. Each bioactive liquid fraction was characterized and strategic ways of adding value were proposed. In parallel, the possibility of using the solid residue to produce biomaterials was studied by setting up Dynamic Vapour Sorption (DVS) and basic Pressure-Volume-Temperature (PVT) analyses. The solid residue was molded by compression cooking. The obtained materials were finally characterized mechanically. The results obtained were very comforting and gave some perspectives to find an interesting valorization for the Sargassum algae.

Keywords: seaweeds, twin-screw extrusion, fractionation, bioactive compounds, biomaterials, biomass

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Authors: A. M. Isakhanyan, F. N. Tkhruni, N. N. Yakimovich, Z. I. Kuvaeva, T. V. Khachatryan

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Introduction: At present, the simbiotics based on different genera and species of lactic acid bacteria (LAB) and yeasts are used. One of the basic properties of probiotics is presence of antimicrobial activity and therefore selection of LAB and yeast strains for their co-cultivation with the aim of increasing of the activity is topical. Since probiotic yeast and bacteria have different mechanisms of action, natural synergies between species, higher viability and increasing of antimicrobial activity might be expected from mixing both types of probiotics. Endemic strains of LAB Enterococcus faecium БТK-64, Lactobaccilus plantarum БТK-66, Pediococcus pentosus БТK-28, Lactobacillus rhamnosus БТK-109 and Kluyveromyces lactis БТX-412, Saccharomycopsis sp. БТX- 151 strains of yeast, with probiotic properties and hight antimicrobial activity, were selected. Strains are deposited in "Microbial Depository Center" (MDC) SPC "Armbiotechnology". Methods: LAB and yeast strains were isolated from different dairy products from rural households of Armenia. The genotyping by 16S rRNA sequencing for LAB and 26S RNA sequencing for yeast were used. Combined cultivation of LAB and yeast strains was carried out in the nutrient media on the basis of milk whey, in anaerobic conditions (without shaker, in a thermostat at 37oC, 48 hours). The complex preparations were obtained by purification of cell free culture broth (CFC) broth by the combination of ion-exchange chromatography and gel filtration methods. The spot-on-lawn method was applied for determination of antimicrobial activity and expressed in arbitrary units (AU/ml). Results. The obtained data showed that at the combined growth of bacteria and yeasts, the cultivation conditions (medium composition, time of growth, genera of LAB and yeasts) affected the display of antimicrobial activity. Purification of CFC broth allowed obtaining partially purified antimicrobial complex preparation which contains metabiotics from both bacteria and yeast. The complex preparation inhibited the growth of pathogenic and conditionally pathogenic bacteria, isolated from various internal organs from diseased animals and poultry with greater efficiency than the preparations derived individually alone from yeast and LAB strains. Discussion. Thus, our data shown perspectives of creation of a new class of antimicrobial preparations on the basis of combined cultivation of endemic strains of LAB and yeast. Obtained results suggest the prospect of use of the partially purified complex preparations instead antibiotics in the agriculture and for food safety. Acknowledgments: This work was supported by the RA MES State Committee of Science and Belarus National Foundation for Basic Research in the frames of the joint Armenian - Belarusian joint research project 13РБ-064.

Keywords: co-cultivation, antimicrobial activity, biosafety, metabiotics, lactic acid bacteria, yeast

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Authors: Azzah Alghamdi

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The Interactive White Boards (IWBs) as one of the innovative educational technologies have been extensively investigated in advanced countries such as the UK, US, and Australia. However, there is a significant lack of research studies, which mainly examine the use of IWBs in Saudi Arabia. Therefore, this study aims to investigate the attitudes of primary teachers towards using IWBs in both the teaching and learning processes. Moreover, it aims to investigate if there is any significant difference between male teachers and females regarding their attitudes towards using this technology. This study concentrated on teachers in primary schools, which participated in Tatweer project in the city of Jeddah, in Saudi Arabia. Mixed methods approach was employed in this study using a designed questionnaire, classroom observations, and a semi-structured interview. 587 teachers (286 men and 301 women) from Tatweer primary schools were completed the questionnaire as well as twenty teachers were interviewed including seven female teachers were observed in their classrooms. The findings of this study indicated that approximately 11% of the teachers within the sample (n=587) had negative attitudes towards the use of IWBs in the teaching and learning processes. However, the majority of them nearly 89% agreed about the benefits of using IWBs in their classrooms. Additionally, all the twenty teachers who were interviewed (including the seven observed female teachers) had positive attitudes towards the use of these technologies. Moreover, 87% of male teachers and 91% of female teachers who completed the questionnaire accepted the usefulness of using IWBs in improving their teaching and students' learning. Thus, this indicates that there was no significant difference between male and female teachers in Tatweer primary schools in terms of their views about using these innovative technologies in their lessons. The findings of the current study will help the Ministry of Education to improve the policies of using IWBs in Saudi Arabia. Indeed, examining teachers’ attitudes towards IWBs is a very important issue because they are the main users in classrooms. Hence, their views should be considered to addressing the powers and boundaries of using IWBs. Moreover, students will feel comfortable to use IWBs if their teachers accept and use them well.

Keywords: IWBs, Saudi teachers’ views, Tatweer schools, teachers' gender

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