Search results for: learning benefits

Authors: Tam Viet Hoang

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With a plethora of new mobility services and payment systems found in our cities and across modern public transportation systems, several cities globally have turned to common ticketing systems to help navigate this complexity. Helping to create time and space-differentiated fare structures and tariff schemes, common ticketing systems can optimize transport utilization rates, achieve cost efficiencies, and provide key incentives to specific target groups. However, not all cities and transportation systems have enjoyed a smooth journey towards the adoption, roll-out, and servicing of common ticketing systems, with both the experiences of success and failure being attributed to a wide variety of critical factors. Using case study research as a methodology and cities as the main unit of analysis, this research will seek to address the fundamental question of “what are the critical factors for the success and failure of common ticketing systems?” Using rail/train systems as the entry point for this study will start by providing a background to the evolution of transport ticketing and justify the improvements in operational efficiency that can be achieved through common ticketing systems. Examining the socio-economic benefits of common ticketing, the research will also help to articulate the value derived for different key identified stakeholder groups. By reviewing case studies of the implementation of common ticketing systems in different cities, the research will explore lessons learned from cities with the aim to elicit factors to ensure seamless connectivity integrated e-ticketing platforms. In an increasingly digital age and where cities are now coming online, this paper seeks to unpack these critical factors, undertaking case study research drawing from literature and lived experiences. Offering us a better understanding of the enabling environment and ideal mixture of ingredients to facilitate the successful roll-out of a common ticketing system, interviews will be conducted with transport operators from several selected cities to better appreciate the challenges and strategies employed to overcome those challenges in relation to common ticketing systems. Meanwhile, as we begin to see the introduction of new mobile applications and user interfaces to facilitate ticketing and payment as part of the transport journey, we take stock of numerous policy challenges ahead and implications on city-wide and system-wide urban planning. It is hoped that this study will help to identify the critical factors for the success and failure of common ticketing systems for cities set to embark on their implementation while serving to fine-tune processes in those cities where common ticketing systems are already in place. Outcomes from the study will help to facilitate an improved understanding of common pitfalls and essential milestones towards the roll-out of a common ticketing system for railway systems, especially for emerging countries where mass rapid transit transport systems are being considered or in the process of construction.

Keywords: common ticketing, public transport, urban strategies, Bangkok, Fukuoka, Sydney

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Authors: Rida Akzar, Risti Permani, Wahida , Wendy Umberger

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Adoption of farm innovations may increase farm productivity, and therefore improve market access and farm incomes. However, most studies that look at the level and drivers of innovation adoption only focus on a specific type of innovation. Farmers may consider multiple innovation options, and constraints such as budget, environment, scarcity of labour supply, and the cost of learning. There have been some studies proposing different methods to combine a broad variety of innovations into a single measurable index. However, little has been done to compare these methods and assess whether they provide similar information about farmer segmentation by their ‘innovativeness’. Using data from a recent survey of 220 dairy farm households in West Java, Indonesia, this study compares and considers different methods of deriving an innovation index, including expert-weighted innovation index; an index derived from the total number of adopted technologies; and an index of the extent of adoption of innovation taking into account both adoption and disadoption of multiple innovations. Second, it examines the distribution of different farming systems taking into account their innovativeness and farm characteristics. Results from this study will inform policy makers and stakeholders in the dairy industry on how to better design, target and deliver programs to improve and encourage farm innovation, and therefore improve farm productivity and the performance of the dairy industry in Indonesia.

Keywords: adoption, dairy, household survey, innovation index, Indonesia, multiple innovations dairy, West Java

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Authors: Annika Freudenberger, Sin Sokhong

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In just a few years, the Face-to-Face Victory Gardens Project (F2F) in Cambodia has developed a high-impact project that has provided immediate and tangible benefits to local families. This has been accomplished with a relatively hands-off approach that relies on households’ own motivation and personal investments of time and resources -which is both unique and impressive in the landscape of NGO and government initiatives in the area. Households have been growing food both for their own consumption and to sell or exchange. Not all targeted beneficiaries are equally motivated and maximizing their involvement, but there is a clear subset of households -particularly those who serve as facilitators- whose circumstances have been transformed as a result of F2F. A number of household factors and contextual economic factors affect families’ income generation opportunities. All the households we spoke with became involved with F2F with the goal of selling some proportion of their produce (i.e., not exclusively for their own consumption). For some, this income is marginal and supplemental to their core household income; for others, it is substantial and transformative. Some engage directly with customers/buyers in their immediate community, while others sell in larger nearby markets, and others link up with intermediary vendors. All struggle, to a certain extent, to compete in a local economy flooded with cheap produce imported from large-scale growers in neighboring provinces, Thailand, and Vietnam, although households who grow and sell herbs and greens popular in Khmer cuisine have found a stronger local market. Some are content with the scale of their garden, the income they make, and the current level of effort required to maintain it; others would like to expand but are faced with land constraints and water management challenges. Households making a substantial income from selling their products have achieved success in different ways, making it difficult to pinpoint a clear “model” for replication. Within our small sample size of interviewees, it seems as though the families with a clear passion for their gardens and high motivation to work hard to bring their products to market have succeeded in doing so. Khmer greens and herbs have been the most successful; they are not high-value crops, but they are fairly easy to grow, and there is a constant demand. These crops are also not imported as much, so prices are more stable than those of crops such as long beans. Although we talked to a limited number of individuals, it also appears as though successful families either restricted their crops to those that would grow well in drought or flood conditions (depending on which they are affected by most); or benefit already from water management infrastructure such as water tanks which helps them diversify their crops and helps them build their resilience.

Keywords: food security, Victory Gardens, nutrition, Cambodia

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Authors: Fharia Tilat Loba

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Studies show that there is a certain group of students who are more vulnerable to bullying due to their physical appearance, disability, sexual preference, race, and lack of social and behavioral skills. Students with autism spectrum disorders (ASD) are one of the most vulnerable groups among these at-risk groups. Researchers suggest that focusing on vulnerable groups of students who can be the target of bullying helps to understand the causes and patterns of aggression, which ultimately helps in structuring intervention programs to reduce bullying. Since Australia ratified the United Nations Convention on the Rights of Persons with Disabilities in 2006, it has been committed to providing an inclusive, safe, and effective learning environment for all children. In addition, the 2005 Disability Standards for Education seeks to ensure that students with disabilities can access and participate in education on the same basis as other students, covering all aspects of education, including harassment and victimization. However, bullying hinders students’ ability to fully participate in schooling. The proposed study aims to synthesize the notions of traditional bullying and cyberbullying and attempts to understand the experiences of students with ASD who are experiencing bullying in their schools. The proposed study will primarily focus on identifying the gaps between policy and practice related to bullying, and it will also attempt to understand the experiences of parents of students with ASD and professionals who have experience dealing with bullying at the school level in Australia. This study is expected to contribute to the theoretical knowledge of the bullying phenomenon and provide a reference for advocacy at the school, organization, and government levels.

Keywords: education policy, bullying, Australia, neurodiversity

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Authors: Gina Aurora Necula

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From its transformation into a taboo and its hiding under the so-called “Moldovan language” or under the euphemistic expression “state language” to its regained status recognition as an official language, the Romanian language spoken in the Republic of Moldova has undergone impressive reforms in the last 60 years. Meant to erase the awareness of citizens’ ethnic identity and turn a majority language into a minority one, all the laws and regulations issued on the field succeeded into setting numerous barriers for speakers of Romanian. Either manifested as social constraints or materialized into assumed rejection of mother tongue usage, all these laws have demonstrated their usefulness and major impact on the Romanian-speaking population. This article is the result of our research carried out over 10 years with the support of students, and Moldovan citizens, from the master's degree program "Romanian language - identity and cultural awareness." We present here a retrospective insight of the reforms, laws, and regulations that contributed to the shifted status of the Romanian language from the official language, seen as the language of common use both in the public and private spheres, in the minority language that surrendered its privileged place to the Russian language, firstly in the public sphere, and then, slowly but surely, in the private sphere. Our main goal here is to identify and make speakers understand what the barriers to learning Romanian language are nowadays when the social pressure on using Russian no longer exists.

Keywords: linguistic barriers, lingua franca, private sphere, public sphere, reformation

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Authors: Fabienne Vozy, Anick Lepage

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Insects are displaying high nutritional value, low greenhouse gas emissions, low land use requirements and high food conversion efficiency. They can contribute to the food chain and be one of many solutions to protein shortages. Currently, in North America, nutritional entomology is under-developed and the needs to better understand its benefits remain to convince large-scale producers and consumers (both for human and agricultural needs). As such, large-scale production of mealworms offers a promising alternative to replacing traditional sources of protein and fatty acids. To proceed orderly, it is required to collect more data on the nutritional values of insects such as, a) Evaluate the diets of insects to improve their dietary value; b) Test the breeding conditions to optimize yields; c) Evaluate the use of by-products and organic residues as sources of food. Among the featured technical parameters, relative humidity (RH) percentage and temperature, optimal substrates and hydration sources are critical elements, thus establishing potential benchmarks for to optimize conversion rates of protein and fatty acids. This research is to establish the combination of the most influential rearing parameters with local food residues, to correlate the findings with the nutritional value of the larvae harvested. 125 same-monthly old adults/replica are randomly selected in the mealworm breeding pool then placed to oviposit in growth chambers preset at 26°C and 65% RH. Adults are removed after 7 days. Larvae are harvested upon the apparition of the first nymphosis signs and batches, are analyzed for their nutritional values using wet chemistry analysis. The first samples analyses include total weight of both fresh and dried larvae, residual humidity, crude proteins (CP%), and crude fats (CF%). Further analyses are scheduled to include soluble proteins and fatty acids. Although they are consistent with previous published data, the preliminary results show no significant differences between treatments for any type of analysis. Nutritional properties of each substrate combination have yet allowed to discriminate the most effective residue recipe. Technical issues such as the particles’ size of the various substrate combinations and larvae screen compatibility are to be investigated since it induced a variable percentage of lost larvae upon harvesting. To address those methodological issues are key to develop a standardized efficient procedure. The aim is to provide producers with easily reproducible conditions, without incurring additional excessive expenditure on their part in terms of equipment and workforce.

Keywords: entomophagy, nutritional value, rearing parameters optimization, Tenebrio molitor

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Authors: Junior George Martin

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The purpose of this study was to explore college instructors’ integration of technology in their content area curriculum. The instructors indicated that they were in need of additional training to successfully integrate technology in their subject areas. The findings point to the implementation of a proposed the Technological, Pedagogical, and Content Knowledge (TPACK) model professional development workshop to satisfactorily address the weaknesses of the instructors in technology integration. The professional development workshop is proposed as a rational solution to adequately address the instructors’ inability to the successful integration of technology in their subject area in an effort to improve their pedagogy. The intense workshop would last for 5 days and will be designed to provide instructors with training in areas such as a use of technology applications and tools, and using modern methodologies to improve technology integration. Exposing the instructors to the specific areas identified will address the weaknesses they demonstrated during the study. Professional development is deemed the most appropriate intervention based on the opportunities it provides the instructors to access hands-on training to overcome their weaknesses. The purpose of the TPACK professional development workshop will be to improve the competence of the instructors so that they are adequately prepared to integrate technology successfully in their curricula. At the end of the period training, the instructors are expected to adopt strategies that will have a positive impact on the learning experiences of the students.

Keywords: higher education, modern technology tools, professional development, technology integration

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Authors: P. Panwalkar, K. Veravalli, M. Tofighi, A. Mofidi

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Introduction: Anterior femoral perforation or distal anterior nail position is a known complication of femoral nailing specifically in pertrochantric fractures fixed with cephalomedullary nail. This has been attributed to wrong entry point for the femoral nail, nail with large radius of curvature or malreduced fracture. Left alone anterior perforation of femur or abutment of nail on anterior femur will result in pain and risk stress riser at distal femur and periprosthetic fracture. There have been multiple techniques described to avert or correct this problem ranging from using different nail, entry point change, poller screw to deflect the nail position, use of shorter nail or use of curved guidewire or change of nail to ensure a nail with large radius of curvature Methods: We present this technique which we have used in order to centralise the femoral nail either when the nail has been put anteriorly or when the guide wire has been inserted too anteriorly prior to the insertion of the nail. This technique requires the use of femoral reduction spool from the nailing set. This technique was used by eight trainees of different level of experience under supervision. Results: This technique was easily reproducible without any learning curve without a need for opening of fracture site or change in the entry point with three different femoral nailing sets in twenty-five cases. The process took less than 10 minutes even when revising a malpositioned femoral nail. Conclusion: Our technique of using femoral reduction spool is easily reproducible and repeatable technique for avoidance of non-centralised femoral nail insertion and distal anterior perforation of femoral nail.

Keywords: femoral fracture, nailing, malposition, surgery

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Authors: Kishore Kumar R., Kaustav Sengupta, Shalini Sood Sehgal, Poornima Santhanam

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Fashion is a human expression that is constantly changing. One of the prime factors that consistently influences fashion is the change in colour preferences. The role of colour in our everyday lives is very significant. It subconsciously explains a lot about one’s mindset and mood. Analyzing the colours by extracting them from the outfit images is a critical study to examine the individual’s/consumer behaviour. Several research works have been carried out on extracting colours from images, but to the best of our knowledge, there were no studies that extract colours to specific apparel and identify colour patterns geographically. This paper proposes a framework for accurately extracting colours from T-shirt images and predicting dominant colours geographically. The proposed method consists of two stages: first, a U-Net deep learning model is adopted to segment the T-shirts from the images. Second, the colours are extracted only from the T-shirt segments. The proposed method employs the iMaterialist (Fashion) 2019 dataset for the semantic segmentation task. The proposed framework also includes a mechanism for gathering data and analyzing India’s general colour preferences. From this research, it was observed that black and grey are the dominant colour in different regions of India. The proposed method can be adapted to study fashion’s evolving colour preferences.

Keywords: colour analysis in t-shirts, convolutional neural network, encoder-decoder, k-means clustering, semantic segmentation, U-Net model

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Authors: Rajesh Kumar, Puneet Aggarwal

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In context of understanding problems faced by undergraduate students while carrying out laboratory experiments dealing with high voltages, it was found that most of the students are hesitant to work directly on machine. The reason is that error in the circuitry might lead to deterioration of machine and laboratory instruments. So, it has become inevitable to include modern pedagogic techniques for undergraduate students, which would help them to first carry out experiment in virtual system and then to work on live circuit. Further advantages include that students can try out their intuitive ideas and perform in virtual environment, hence leading to new research and innovations. In this paper, virtual environment used is of MATLAB/Simulink for three-phase induction machines. The performance analysis of three-phase induction machine is carried out using virtual environment which includes Direct Current (DC) Test, No-Load Test, and Block Rotor Test along with speed torque characteristics for different rotor resistances and input voltage, respectively. Further, this paper carries out computer aided teaching of basic Voltage Source Inverter (VSI) drive circuitry. Hence, this paper gave undergraduates a clearer view of experiments performed on virtual machine (No-Load test, Block Rotor test and DC test, respectively). After successful implementation of basic tests, VSI circuitry is implemented, and related harmonic distortion (THD) and Fast Fourier Transform (FFT) of current and voltage waveform are studied.

Keywords: block rotor test, DC test, no load test, virtual environment, voltage source inverter

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Authors: Louise Ödlund, Danica Djuric Ilic

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Sustainable development includes many challenges related to energy use, such as (1) developing flexibility on the demand side of the electricity systems due to an increased share of intermittent electricity sources (e.g., wind and solar power), (2) overcoming economic challenges related to an increased share of renewable energy in the transport sector, (3) increasing efficiency of the biomass use, (4) increasing utilization of industrial excess heat (e.g., approximately two thirds of the energy currently used in EU is lost in the form of excess and waste heat). The European Commission has been recognized DH technology as of essential importance to reach sustainability. Flexibility in the fuel mix, and possibilities of industrial waste heat utilization, combined heat, and power (CHP) production and energy recovery through waste incineration, are only some of the benefits which characterize DH technology. The aim of this study is to provide an overview of the possible business strategies which would enable DH to have an important role in future sustainable energy systems. The methodology used in this study is a systematic literature review. The study includes a systematic approach where DH is seen as a part of an integrated system that consists of transport , industrial-, and electricity sectors as well. The DH technology can play a decisive role in overcoming the sustainability challenges related to our energy use. The introduction of biofuels in the transport sector can be facilitated by integrating biofuel and DH production in local DH systems. This would enable the development of local biofuel supply chains and reduce biofuel production costs. In this way, DH can also promote the development of biofuel production technologies that are not yet developed. Converting energy for running the industrial processes from fossil fuels and electricity to DH (above all biomass and waste-based DH) and delivering excess heat from industrial processes to the local DH systems would make the industry less dependent on fossil fuels and fossil fuel-based electricity, as well as the increasing energy efficiency of the industrial sector and reduce production costs. The electricity sector would also benefit from these measures. Reducing the electricity use in the industry sector while at the same time increasing the CHP production in the local DH systems would (1) replace fossil-based electricity production with electricity in biomass- or waste-fueled CHP plants and reduce the capacity requirements from the national electricity grid (i.e., it would reduce the pressure on the bottlenecks in the grid). Furthermore, by operating their central controlled heat pumps and CHP plants depending on the intermittent electricity production variation, the DH companies may enable an increased share of intermittent electricity production in the national electricity grid.

Keywords: energy system, district heating, sustainable business strategies, sustainable development

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Authors: Rishi Pal Singh

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In Indian Scenario, Organic agriculture is growing by the conscious efforts of inspired people who are able to create the best promising relationship between the earth and men. Nowadays, the major challenge is its entry into the policy-making framework, its entry into the global market and weak sensitization among the farmers. But, during the last two decades, the contamination in environment and food which is linked with the bad agricultural potential/techniques has diverted the mind set of farmers towards the organic farming. In the view of above concept, a small-scale project has been installed to promote the 20 farmers from the Kunjura and surrounding villages for organic farming. This project is working since from the last 3 crops (starting from October, 2016) and found that it can meet both demands and complete development of rural areas. Farmers of this concept are working on the principles such that the nature never demands unreasonable quantities of water, mining and to destroy the microbes and other organisms. As per details of Organic Monitor estimates, global sales reached in billion in the present analysis. In this initiative, firstly, wheat and rice were considered for farming and observed that the production of crop has grown almost 10-15% per year from the last crop production. This is not linked only with the profit or loss but also emphasized on the concept of health, ecology, fairness and care of soil enrichment. Several techniques were used like use of biological fertilizers instead of chemicals, multiple cropping, temperature management, rain water harvesting, development of own seed, vermicompost and integration of animals. In the first year, to increase the fertility of the land, legumes (moong, cow pea and red gram) were grown in strips for the 60, 90 and 120 days. Simultaneously, the mixture of compost and vermicompost in the proportion of 2:1 was applied at the rate of 2.0 ton per acre which was enriched with 5 kg Azotobacter and 5 kg Rhizobium biofertilizer. To complete the amount of phosphorus, 250 kg rock phosphate was used. After the one month, jivamrut can be used with the irrigation water or during the rainy days. In next season, compost-vermicompost mixture @ 2.5 ton/ha was used for all type of crops. After the completion of this treatment, now the soil is ready for high value ordinary/horticultural crops. The amount of above stated biofertilizers, compost-vermicompost and rock phosphate may be increased for the high alternative fertilizers. The significance of the projects is that now the farmers believe in cultural alternative (use of disease-free their own seed, organic pest management), maintenance of biodiversity, crop rotation practices and health benefits of organic farming. This type of organic farming projects should be installed at the level of gram/block/district administration.

Keywords: organic farming, Kunjpura, compost, bio-fertilizers

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Authors: A. Shoiynbek, K. Kozhakhmet, P. Menezes, D. Kuanyshbay, D. Bayazitov

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Speech emotion recognition has received increasing research interest all through current years. There was used emotional speech that was collected under controlled conditions in most research work. Actors imitating and artificially producing emotions in front of a microphone noted those records. There are four issues related to that approach, namely, (1) emotions are not natural, and it means that machines are learning to recognize fake emotions. (2) Emotions are very limited by quantity and poor in their variety of speaking. (3) There is language dependency on SER. (4) Consequently, each time when researchers want to start work with SER, they need to find a good emotional database on their language. In this paper, we propose the approach to create an automatic tool for speech emotion extraction based on facial emotion recognition and describe the sequence of actions of the proposed approach. One of the first objectives of the sequence of actions is a speech detection issue. The paper gives a detailed description of the speech detection model based on a fully connected deep neural network for Kazakh and Russian languages. Despite the high results in speech detection for Kazakh and Russian, the described process is suitable for any language. To illustrate the working capacity of the developed model, we have performed an analysis of speech detection and extraction from real tasks.

Keywords: deep neural networks, speech detection, speech emotion recognition, Mel-frequency cepstrum coefficients, collecting speech emotion corpus, collecting speech emotion dataset, Kazakh speech dataset

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Authors: Jennifer K. Bowerman, Rhonda L. Reich

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The purpose of this paper is to explore the concepts ACDC (Amore, Consciousness, Discipline, and Commitment) which the authors first discovered as a philosophy and framework for recruitment and organizational development in a successful start-up tech company in Brazil. This paper represents an exploration of these concepts as a potential pedagogical foundation for undergraduate business education in the classroom. It explores whether their application has potential to build emotional and practical resilience in the face of constant organizational and societal change. Derived from Holonomy this paper explains the concepts and develops a narrative around how change influences the operation of organizations. Using examples from leading edge organizational theorists, it explains why a different educational approach grounded in ACDC concepts may not only have relevance for the working world, but also for undergraduates about to enter that world. The authors propose that in the global context of constant change, it makes sense to develop an approach to education, particularly business education, beyond cognitive knowledge, models and tools, in such a way that emotional and practical resilience and creative thinking may be developed. Using the classroom as an opportunity to explore these concepts, and aligning personal passion with the necessary discipline and commitment, may provide students with a greater sense of their own worth and potential as they venture into their ever-changing futures.

Keywords: ACDC, holonomic thinking, organizational learning, organizational change, business pedagogy

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Authors: Abhishek Sharma, Arnab Banerjee

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The research is intended to study the solar electric propulsion (SEP) technology for planetary missions. The main benefits of using solar electric propulsion for such missions are shorter flight times, more frequent target accessibility and the use of a smaller launch vehicle than that required by a comparable chemical propulsion mission. Energized by electric power from on-board solar arrays, the electrically propelled system uses 10 times less propellant than conventional chemical propulsion system, yet the reduced fuel mass can provide vigorous power which is capable of propelling robotic and crewed missions beyond the Lower Earth Orbit (LEO). The various thrusters used in the SEP are gridded ion thrusters and the Hall Effect thrusters. The research is solely aimed to study the ion thrusters and investigate the complications related to it and what can be done to overcome the glitches. The ion thrusters are used because they are found to have a total lower propellant requirement and have substantially longer time. In the ion thrusters, the anode pushes or directs the incoming electrons from the cathode. But the anode is not maintained at a very high potential which leads to divergence. Divergence leads to the charges interacting against the surface of the thruster. Just as the charges ionize the xenon gases, they are capable of ionizing the surfaces and over time destroy the surface and hence contaminate it. Hence the lifetime of thruster gets limited. So a solution to this problem is using substances which are not easy to ionize as the surface material. Another approach can be to increase the potential of anode so that the electrons don’t deviate much or reduce the length of thruster such that the positive anode is more effective. The aim is to work on these aspects as to how constriction of the deviation of charges can be done by keeping the input power constant and hence increase the lifetime of the thruster. Predominantly ring cusp magnets are used in the ion thrusters. However, the study is also intended to observe the effect of using solenoid for producing micro-solenoidal magnetic field apart from using the ring cusp magnetic field which are used in the discharge chamber for prevention of interaction of electrons with the ionization walls. Another foremost area of interest is what are the ways by which power can be provided to the Solar Electric Propulsion Vehicle for lowering and boosting the orbit of the spacecraft and also provide substantial amount of power to the solenoid for producing stronger magnetic fields. This can be successfully achieved by using the concept of Electro-dynamic tether which will serve as a power source for powering both the vehicle and the solenoids in the ion thruster and hence eliminating the need for carrying extra propellant on the spacecraft which will reduce the weight and hence reduce the cost of space propulsion.

Keywords: electro-dynamic tether, ion thruster, lifetime of thruster, solar electric propulsion vehicle

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Authors: Dasom Kim, Chen Liu, Myungsu Lim, Su-Hyeon Jeon, ByeoungKug Jeon, Kee-Young Kwahk, Namgyu Kim

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Recently, numerous documents including unstructured data and text have been created due to the rapid increase in the usage of social media and the Internet. Each document is usually provided with a specific category for the convenience of the users. In the past, the categorization was performed manually. However, in the case of manual categorization, not only can the accuracy of the categorization be not guaranteed but the categorization also requires a large amount of time and huge costs. Many studies have been conducted towards the automatic creation of categories to solve the limitations of manual categorization. Unfortunately, most of these methods cannot be applied to categorizing complex documents with multiple topics because the methods work by assuming that one document can be categorized into one category only. In order to overcome this limitation, some studies have attempted to categorize each document into multiple categories. However, they are also limited in that their learning process involves training using a multi-categorized document set. These methods therefore cannot be applied to multi-categorization of most documents unless multi-categorized training sets are provided. To overcome the limitation of the requirement of a multi-categorized training set by traditional multi-categorization algorithms, we previously proposed a new methodology that can extend a category of a single-categorized document to multiple categorizes by analyzing relationships among categories, topics, and documents. In this paper, we design a survey-based verification scenario for estimating the accuracy of our automatic categorization methodology.

Keywords: big data analysis, document classification, multi-category, text mining, topic analysis

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Authors: James Jr. Mashiyane, Risuna Nkolele, Stephanie J. Müller, Gciniwe S. Dlamini, Rebone L. Meraba, Darlington S. Mapiye

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When performing language tasks in natural language processing (NLP), the dimensionality of word embeddings is chosen either ad-hoc or is calculated by optimizing the Pairwise Inner Product (PIP) loss. The PIP loss is a metric that measures the dissimilarity between word embeddings, and it is obtained through matrix perturbation theory by utilizing the unitary invariance of word embeddings. Unlike in natural language, in genomics, especially in genome sequence processing, unlike in natural language processing, there is no notion of a “word,” but rather, there are sequence substrings of length k called k-mers. K-mers sizes matter, and they vary depending on the goal of the task at hand. The dimensionality of word embeddings in NLP has been studied using the matrix perturbation theory and the PIP loss. In this paper, the sufficiency and reliability of applying word-embedding algorithms to various genomic sequence datasets are investigated to understand the relationship between the k-mer size and their embedding dimension. This is completed by studying the scaling capability of three embedding algorithms, namely Latent Semantic analysis (LSA), Word2Vec, and Global Vectors (GloVe), with respect to the k-mer size. Utilising the PIP loss as a metric to train embeddings on different datasets, we also show that Word2Vec outperforms LSA and GloVe in accurate computing embeddings as both the k-mer size and vocabulary increase. Finally, the shortcomings of natural language processing embedding algorithms in performing genomic tasks are discussed.

Keywords: word embeddings, k-mer embedding, dimensionality reduction

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Authors: Michael W. Markowitz, Jeffrey Gingerich

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The landscape of higher education in the United States has undergone significant changes in the last 25 years. What was once a domain of competition among prospective students for a limited number of college and university seats has become a marketplace in which institutions vie for the enrollment of educational consumers. A central figure in this paradigm shift has been the Chief Academic Officer (CAO), whose institutional role has also evolved beyond academics to include such disparate responsibilities as strategic planning, fiscal oversight, student recruitment, fundraising and personnel management. This paper explores the scope and impact of this transition by, first, explaining its context: the intersection of key social, economic and political factors in neo-conservative, late 20th Century America that redefined the value and accountability of institutions of higher learning. This context, in turn, is shown to have redefined the role and function of the CAO from a traditional academic leader to one centered on the successful application of corporate principles of organizational and fiscal management. Information gathered from a number of sitting Provosts, Vice-Presidents of Academic Affairs and Deans of Faculty is presented to illustrate the parameters of this change, as well as the extent to which today’s academic officers feel prepared and equipped to fulfill this broader institutional role. The paper concludes with a discussion of the impact of this transition on the American academy and whether it serves as a portend of change to come in higher education systems around the globe.

Keywords: academic administration, higher education, leadership, organizational management

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Authors: Leonard D. Agana, Wendell Ace Dela Cruz, Arjan C. Lingaya, Bonifacio T. Doma Jr.

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The purpose of this paper is to study the predict the fuel performance parameters, which include drivability index (DI), vapor lock index (VLI), and vapor lock potential using distillation curve and Reid vapor pressure (RVP) of dual alcohol-gasoline fuel blends. Distillation curve and Reid vapor pressure were predicted using artificial neural networks (ANN) with macroscopic properties such as boiling points, RVP, and molecular weights as the input layers. The ANN consists of 5 hidden layers and was trained using Bayesian regularization. The training mean square error (MSE) and R-value for the ANN of RVP are 91.4113 and 0.9151, respectively, while the training MSE and R-value for the distillation curve are 33.4867 and 0.9927. Fuel performance analysis of the dual alcohol–gasoline blends indicated that highly volatile gasoline blended with dual alcohols results in non-compliant fuel blends with D4814 standard. Mixtures of low-volatile gasoline and 10% methanol or 10% ethanol can still be blended with up to 10% C3 and C4 alcohols. Intermediate volatile gasoline containing 10% methanol or 10% ethanol can still be blended with C3 and C4 alcohols that have low RVPs, such as 1-propanol, 1-butanol, 2-butanol, and i-butanol. Biography: Graduate School of Chemical, Biological, and Materials Engineering and Sciences, Mapua University, Muralla St., Intramuros, Manila, 1002, Philippines

Keywords: dual alcohol-gasoline blends, distillation curve, machine learning, reid vapor pressure

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Authors: Shreyansh Singh, Afroz Ahmed

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Sentiment Analysis intends to naturally reveal the hidden mentality that we hold towards an entity. The total of this assumption over a populace addresses sentiment surveying and has various applications. Current text-based sentiment analysis depends on the development of word embeddings and Machine Learning models that take in conclusion from enormous text corpora. Sentiment Analysis from text is presently generally utilized for consumer loyalty appraisal and brand insight investigation. With the expansion of online media, multimodal assessment investigation is set to carry new freedoms with the appearance of integral information streams for improving and going past text-based feeling examination using the new transforms methods. Since supposition can be distinguished through compelling follows it leaves, like facial and vocal presentations, multimodal opinion investigation offers good roads for examining facial and vocal articulations notwithstanding the record or printed content. These methodologies use the Recurrent Neural Networks (RNNs) with the LSTM modes to increase their performance. In this study, we characterize feeling and the issue of multimodal assessment investigation and audit ongoing advancements in multimodal notion examination in various spaces, including spoken surveys, pictures, video websites, human-machine, and human-human connections. Difficulties and chances of this arising field are additionally examined, promoting our theory that multimodal feeling investigation holds critical undiscovered potential.

Keywords: sentiment analysis, RNN, LSTM, word embeddings

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Authors: Elaine Wong

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Introduction: The Singapore Physical Activity and Nutrition Study (SPANS) aimed to assess the effects of a community-based intervention on physical activity (PA) and nutrition behaviours as well as chronic disease risk factors for Singaporean women aged above 50 years. This article examines the participation, dose, fidelity, reach, satisfaction and reasons for completion and non-completion of the SPANS. Methods: The SPANS program integrated constructs of Social Cognitive Theory (SCT) and is composed of PA activities; nutrition workshops; dietary counselling coupled with motivational interviewing (MI) through phone calls; and text messages promoting healthy behaviours. Printed educational resources and health incentives were provided to participants. Data were collected via a mixed-method design strategy from a sample of 295 intervention participants. Quantitative data were collected using self-completed survey (n = 209); qualitative data were collected via research assistants’ notes, post feedback sessions and exit interviews with program completers (n = 13) and non-completers (n = 12). Results: Majority of participants reported high ‘satisfactory to excellent’ ratings for the program pace, suitability of interest and overall program (96.2-99.5%). Likewise, similar ratings for clarity of presentation; presentation skills, approachability, knowledge; and overall rating of trainers and program ambassadors were achieved (98.6-100%). Phone dietary counselling had the highest level of participation (72%) at less than or equal to 75% attendance rate followed by nutrition workshops (65%) and PA classes (60%). Attrition rate of the program was 19%; major reasons for withdrawal were personal commitments, relocation and health issues. All participants found the program resources to be colourful, informative and practical for their own reference. Reasons for program completion and maintenance were: desired health benefits; social bonding opportunities and to learn more about PA and nutrition. Conclusions: Process evaluation serves as an appropriate tool to identify recruitment challenges, effective intervention strategies and to ensure program fidelity. Program participants were satisfied with the educational resources, program components and delivery strategies implemented by the trainers and program ambassadors. The combination of printed materials and intervention components, when guided by the SCT and MI, were supportive in encouraging and reinforcing lifestyle behavioural changes. Mixed method evaluation approaches are integral processes to pinpoint barriers, motivators, improvements and effective program components in optimising the health status of Singaporean women.

Keywords: process evaluation, Singapore, older adults, lifestyle changes, program challenges

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Authors: Stephen Osei Akyiaw, Divine Kwabena Atta Kyere-Owusu

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Malaria has been a worldwide menace of a health condition to human beings for several decades with majority of people on the African continent with most causalities where Ghana is no exception. Therefore, this study employed the use of animation to enhance awareness creation on the spread and prevention of Malaria in Effutu Communities in the Central Region of Ghana. Working with the interpretivist paradigm, this study adopted Art-Based Research, where the AIDA Model and Cognitive Theory of Multimedia Learning (CTML) served as the theories underpinning the study. Purposive and convenience sampling techniques were employed in selecting sample for the study. The data collection instruments included document review and interviews. Besides, the study developed an animation using the local language of the people as the voice over to foster proper understanding by the rural community folks. Also, indigenous characters were used for the animation for the purpose of familiarization with the local folks. The animation was publicized at Health Town Halls within the communities. The outcomes of the study demonstrated that the use of animation was effective in enhancing the awareness creation for preventing and controlling malaria disease in rural communities in Effutu Communities in the Central Region of Ghana. Health officers and community folks expressed interest and desire to practice the preventive measures outlined in the animation to help reduce the spread of Malaria in their communities. The study, therefore, recommended that animation could be used to curtail the spread and enhanced the prevention of Malaria.

Keywords: malaria, animation, prevention, communities

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Authors: Chidozie C. Nwobi-Okoye, Basil Q. Ochieze, Stanley Okiy

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This research reports on the modeling of age hardening process using adaptive neuro-fuzzy inference system (ANFIS). The age hardening output (Hardness) was predicted using ANFIS. The input parameters were ageing time, temperature and percentage composition of cow horn particles (CHp%). The results show the correlation coefficient (R) of the predicted hardness values versus the measured values was of 0.9985. Subsequently, values outside the experimental data points were predicted. When the temperature was kept constant, and other input parameters were varied, the average relative error of the predicted values was 0.0931%. When the temperature was varied, and other input parameters kept constant, the average relative error of the hardness values predictions was 80%. The results show that ANFIS with coarse experimental data points for learning is not very effective in predicting process outputs in the age hardening operation of A356 alloy/CHp particulate composite. The fine experimental data requirements by ANFIS make it more expensive in modeling and optimization of age hardening operations of A356 alloy/CHp particulate composite.

Keywords: adaptive neuro-fuzzy inference system (ANFIS), age hardening, aluminum alloy, metal matrix composite

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Authors: Emma Groenewald

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In 1994, numerous policies of a democratic dispensation envisage social justice and the transformation of the South Africa society. The drive for transformation and social justice resulted in an increasing number of university students from diverse backgrounds, which in turn, lead to the establishment of Sol Plaatje University (SPU) in 2014. A re-curriculated B. Ed. programme at SPU aims to equip students with knowledge and skills to realise the aim of social justice and to enhance the transformation of the South African society. The aim of this study is to explore the experiences and perceptions of students at a diverse university campus on a curriculum that aims to promote social justice. Four education modules, with the assumption that it reflects social justice content, were selected. Four students, representative of different ethnic and language groupings found at the SPU, were chosen as participants. Data were generated by the participants through four reflective exercises on each of the modules, spread over a period of four years. The module aims, linked with the narratives of the participants' perceptions and experiences of each module, provided an overview of the enacted curriculum. A qualitative research design with an interpretivist approach informed by Vygotsky's theory of learning was used. The participants' experiences of the four modules were analysed, and their views were interpreted. The students' narratives shed light on the strengths and weaknesses of how the B.Ed. Curriculum works towards social justice and revealed student's perceptions of otherness. From the narratives it became apparent that module did promote a social justice orientation in prospective teachers trained at a university.

Keywords: student diversity, social justice, transformation, teacher education

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Authors: A. M. John-Otumu, M. M. Rahman, M. C. Onuoha, E. P. Ojonugwa

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A Convolutional Neural Network (CNN) model for predicting Lassa fever was built using Python 3.8.0 programming language, alongside Keras 2.2.4 and TensorFlow 2.6.1 libraries as the development environment in order to reduce the current high risk of Lassa fever in West Africa, particularly in Nigeria. The study was prompted by some major flaws in existing conventional laboratory equipment for diagnosing Lassa fever (RT-PCR), as well as flaws in AI-based techniques that have been used for probing and prognosis of Lassa fever based on literature. There were 15,679 blood smear microscopic image datasets collected in total. The proposed model was trained on 70% of the dataset and tested on 30% of the microscopic images in avoid overfitting. A 3x3x3 convolution filter was also used in the proposed system to extract features from microscopic images. The proposed CNN-based model had a recall value of 96%, a precision value of 93%, an F1 score of 95%, and an accuracy of 94% in predicting and accurately classifying the images into clean or infected samples. Based on empirical evidence from the results of the literature consulted, the proposed model outperformed other existing AI-based techniques evaluated. If properly deployed, the model will assist physicians, medical laboratory scientists, and patients in making accurate diagnoses for Lassa fever cases, allowing the mortality rate due to the Lassa fever virus to be reduced through sound decision-making.

Keywords: artificial intelligence, ANN, blood smear, CNN, deep learning, Lassa fever

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Authors: Noor Ayuni Che Zakaria, Takashi Komeda, Cheng Yee Low, Kaoru Inoue, Fazah Akhtar Hanapiah

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Previous studies have shown that there are arguments regarding the reliability and validity of the Ashworth and Modified Ashworth Scale towards evaluating patients diagnosed with upper limb disorders. These evaluations depended on the raters’ experiences. This initiated us to develop an upper limb disorder part-task trainer that is able to simulate consistent upper limb disorders, such as spasticity and rigidity signs, based on the Modified Ashworth Scale to improve the variability occurring between raters and intra-raters themselves. By providing consistent signs, novice therapists would be able to increase training frequency and exposure towards various levels of signs. A total of 22 physiotherapists and occupational therapists participated in the study. The majority of the therapists agreed that with current therapy education, they still face problems with inter-raters and intra-raters variability (strongly agree 54%; n = 12/22, agree 27%; n = 6/22) in evaluating patients’ conditions. The therapists strongly agreed (72%; n = 16/22) that therapy trainees needed to increase their frequency of training; therefore believe that our initiative to develop an upper limb disorder training tool will help in improving the clinical education field (strongly agree and agree 63%; n = 14/22).

Keywords: upper limb disorder, clinical education tool, inter/intra-raters variability, spasticity, modified Ashworth scale

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Authors: Astrid Bagireanu, Julio Bros-Williamson, Mila Duncheva, John Currie

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Digital Twins (DTs) have entered the built environment from more established industries like aviation and manufacturing, although there has never been a common goal for utilising DTs at scale. Defined as the cyber-physical integration of data between an asset and its virtual counterpart, DT has been identified in literature from an operational standpoint – in addition to monitoring the performance of a built asset. However, this has never been translated into how DTs should be implemented into a project and what responsibilities each project stakeholder holds in the realisation of a DT. What is needed is an approach to translate these requirements into actionable DT dimensions. This paper presents a foundation for an overarching framework specific to the built environment. For the purposes of this research, the UK widely used the Royal Institute of British Architects (RIBA) Plan of Work from 2020 is used as a basis for itemising project stages. The RIBA Plan of Work consists of eight stages designed to inform on the definition, briefing, design, coordination, construction, handover, and use of a built asset. Similar project stages are utilised in other countries; therefore, the recommendations from the interviews presented in this paper are applicable internationally. Simultaneously, there is not a single mainstream software resource that leverages DT abilities. This ambiguity meets an unparalleled ambition from governments and industries worldwide to achieve a national grid of interconnected DTs. For the construction industry to access these benefits, it necessitates a defined starting point. This research aims to provide a comprehensive understanding of the potential applications and ramifications of DT in the context of the built environment. This paper is an integral part of a larger research aimed at developing a conceptual framework for the Architecture, Engineering, and Construction (AEC) sector following a conventional project timeline. Therefore, this paper plays a pivotal role in providing practical insights and a tangible foundation for developing a stage-by-stage approach to assimilate the potential of DT within the built environment. First, the research focuses on a review of relevant literature, albeit acknowledging the inherent constraint of limited sources available. Secondly, a qualitative study compiling the views of 14 DT experts is presented, concluding with an inductive analysis of the interview findings - ultimately highlighting the barriers and strengths of DT in the context of framework development. As parallel developments aim to progress net-zero-centred design and improve project efficiencies across the built environment, the limited resources available to support DTs should be leveraged to propel the industry to reach its digitalisation era, in which AEC stakeholders have a fundamental role in understanding this, from the earliest stages of a project.

Keywords: digital twins, decision-making, design, net-zero, built environment

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Authors: Adelina Castelo

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The increasing number of learners of Portuguese as Foreign Language in China justifies the need to define the phonetic profile of these learners and to design didactic materials that are adjusted to their specific problems in pronunciation. Different aspects of this topic have been studied, but the production of oral vowels still needs to be investigated. This study aims: (i) to identify the problems the Chinese learners of Portuguese experience in the pronunciation of oral vowels; (ii) to discuss the didactic implications drawn from those problems. The participants were eight native speakers of Mandarin Chinese that had been learning Portuguese in College for almost a year. They named pictured objects and their oral productions were recorded and phonetically transcribed. The selection of the objects to name took into account some linguistic variables (e.g. stress pattern, syllable structure, presence of the Portuguese oral vowels in different word positions according to stress location). The results are analysed in two ways: the impact of linguistic variables on the success rate in the vowels' production; the replacement strategies used in the non-target productions. Both analyses show that the Chinese learners of Portuguese (i) have significantly more difficulties with the mid vowels as well as the high central vowel and (ii) do not master the vowel height feature. These findings contribute to define the phonetic profile of these learners in terms of oral vowel production. Besides, they have important didactic implications for the pronunciation teaching to these specific learners. Those implications are discussed and exemplified.

Keywords: Chinese learners, learners’ phonetic profile, linguistic variables, Portuguese as foreign language, production data, pronunciation teaching, oral vowels

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Authors: Sunil P. Lonkar, Vishnu V. Pillai, Saeed Alhassan

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Design and development of highly efficient, inexpensive, and long-term stable earth-abundant electrocatalysts hold tremendous promise for hydrogen evolution reaction (HER) in water electrolysis. The 2D transition metal dichalcogenides, especially molybdenum disulfide attracted a great deal of interests due to its high electrocatalytic activity. However, due to its poor electrical conductivity and limited exposed active sites, the performance of these catalysts is limited. In this context, a facile and scalable synthesis method for fabrication nanostructured electrocatalysts composed 3D graphene porous aerogels supported with MoS₂ and WS₂ is highly desired. Here we developed a highly active and stable electrocatalyst catalyst for the HER by growing it into a 3D porous architecture on conducting graphene. The resulting nanohybrids were thoroughly investigated by means of several characterization techniques to understand structure and properties. Moreover, the HER performance of these 3D catalysts is expected to greatly improve in compared to other, well-known catalysts which mainly benefits from the improved electrical conductivity of the by graphene and porous structures of the support. This technologically scalable process can afford efficient electrocatalysts for hydrogen evolution reactions (HER) and hydrodesulfurization catalysts for sulfur-rich petroleum fuels. Owing to the lower cost and higher performance, the resulting materials holds high potential for various energy and catalysis applications. In typical hydrothermal method, sonicated GO aqueous dispersion (5 mg mL⁻¹) was mixed with ammonium tetrathiomolybdate (ATTM) and tungsten molybdate was treated in a sealed Teflon autoclave at 200 ◦C for 4h. After cooling, a black solid macroporous hydrogel was recovered washed under running de-ionized water to remove any by products and metal ions. The obtained hydrogels were then freeze-dried for 24 h and was further subjected to thermal annealing driven crystallization at 600 ◦C for 2h to ensure complete thermal reduction of RGO into graphene and formation of highly crystalline MoS₂ and WoS₂ phases. The resulting 3D nanohybrids were characterized to understand the structure and properties. The SEM-EDS clearly reveals the formation of highly porous material with a uniform distribution of MoS₂ and WS₂ phases. In conclusion, a novice strategy for fabrication of 3D nanostructured MoS₂-WS₂/graphene is presented. The characterizations revealed that the in-situ formed promoters uniformly dispersed on to few layered MoS₂¬-WS₂ nanosheets that are well-supported on graphene surface. The resulting 3D hybrids hold high promise as potential electrocatalyst and hydrodesulfurization catalyst.

Keywords: electrocatalysts, graphene, transition metal chalcogenide, 3D assembly

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Authors: Sofia Papadimitriou

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INTRODUCTION: The differential diagnosis between acute viral and bacterial infections is an important cost-effectiveness parameter at the stage of the treatment process in order to achieve the maximum benefits in therapeutic intervention by combining the minimum cost to ensure the proper use of antibiotics.The discovery of sensitive and robust molecular diagnostic tests in response to the role of the host in infections has enhanced the accurate diagnosis and differentiation of infections. METHOD: The study used a sample of six independent blood samples (total=756) which are associated with human proteins-proteins, each of which at the transcription stage expresses a different response in the host network between viral and bacterial infections.Τhe individual blood samples are subjected to a sequence of computer filters that identify a gene panel corresponding to an autonomous diagnostic score. The data set and the correspondence of the gene panel to the diagnostic patents a new Bangalore -Viral Bacterial (BL-VB). FINDING: We use a biomarker based on the blood of 10 genes(Panel-VB) that are an important prognostic value for the detection of viruses from bacterial infections with a weighted average AUROC of 0.97(95% CL:0.96-0.99) in eleven independent samples (sets n=898). We discovered a base with a patient score (VB 10 ) according to the table, which is a significant diagnostic value with a weighted average of AUROC 0.94(95% CL: 0.91-0.98) in 2996 patient samples from 56 public sets of data from 19 different countries. We also studied VB 10 in a new cohort of South India (BL-VB,n=56) and found 97% accuracy in confirmed cases of viral and bacterial infections. We found that VB 10 (a)accurately identifies the type of infection even in unspecified cases negative to the culture (b) shows its clinical condition recovery and (c) applies to all age groups, covering a wide range of acute bacterial and viral infectious, including non-specific pathogens. We applied our VB 10 rating to publicly available COVID 19 data and found that our rating diagnosed viral infection in patient samples. RESULTS: Τhe results of the study showed the diagnostic power of the biomarker VB 10 as a diagnostic test for the accurate diagnosis of acute infections in recovery conditions. We look forward to helping you make clinical decisions about prescribing antibiotics and integrating them into your policies management of antibiotic stewardship efforts. CONCLUSIONS: Overall, we are developing a new property of the RNA-based biomarker and a new blood test to differentiate between viral and bacterial infections to assist a physician in designing the optimal treatment regimen to contribute to the proper use of antibiotics and reduce the burden on antimicrobial resistance, AMR.

Keywords: acute infections, antimicrobial resistance, biomarker, blood transcriptome, systems biology, classifier diagnostic score

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