Search results for: enhancing effectiveness

Authors: Momita Das, Sofia Banu, Jibon Kotoky

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Environmental contamination of natural resources with persistent organic pollutants is of great world-wide apprehension. Polycyclic aromatic hydrocarbons (PAHs) are among the organic pollutants, released due to various anthropogenic activities. Due to their toxic, carcinogenic and mutagenic properties, PAHs are of environmental and human concern. Presently, bioremediation has evolved as the most promising biotechnology for cleanup of such contaminants because of its economical and less cost effectiveness. In the present study, distribution of 16 USEPA priority PAHs was determined in the soil samples collected from fifteen different sites of Guwahati City, the Gateway of the North East Region of India. The total concentrations of 16 PAHs (Σ16 PAHs) ranged from 42.7-742.3 µg/g. Higher concentration of total PAHs was found more in the Industrial areas compared to all the sites (742.3 µg/g and 628 µg/g). It is noted that among all the PAHs, Naphthalene, Acenaphthylene, Anthracene, Fluoranthene, Chrysene and Benzo(a)Pyrene were the most available and contain the higher concentration of all the PAHs. Since microbial activity has been deemed the most influential and significant cause of PAH removal; further, twenty-three bacteria were isolated from the most contaminated sites using the enrichment process. These strains were acclimatized to utilize naphthalene and anthracene, each at 100 µg/g concentration as sole carbon source. Among them, one Gram-positive strain (JMG-01) was selected, and biodegradation ability and initial catabolic genes of PAHs degradation were investigated. Based on 16S rDNA analysis, the isolate was identified as Bacillus cereus strain JMG-01. Topographic images obtained using Scanning Electron Microscope (SEM) and Atomic Force Microscope (AFM) at scheduled time intervals of 7, 14 and 21 days, determined the variation in cell morphology during the period of degradation. AFM and SEM micrograph of biomass showed high filamentous growth leading to aggregation of cells in the form of biofilm with reference to the incubation period. The percentage degradation analysis using gas chromatography and mass analyses (GC-MS) suggested that more than 95% of the PAHs degraded when the concentration was at 500 µg/g. Naphthalene, naphthalene-2-methy, benzaldehyde-4-propyl, 1, 2, benzene di-carboxylic acid and benzene acetic acid were the major metabolites produced after degradation. Moreover, PCR experiments with specific primers for catabolic genes, ndo B and Cat A suggested that JMG-01 possess genes for PAHs degradation. Thus, the study concludes that Bacillus cereus strain JMG-01 has efficient biodegrading ability and can trigger the clean-up of PAHs contaminated soil.

Keywords: AFM, Bacillus cereus strain JMG-01, degradation, polycyclic aromatic hydrocarbon, SEM

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Authors: Michael Huber, Maximilian J. Poller, Jens Tochtermann, Wolfgang Korth, Andreas Jess, Jakob Albert

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Aside from the desulfurisation, the denitrogenation of fuels is of great importance to minimize the environmental impact of transport emissions. The oxidative reaction pathway of organic nitrogen in the catalytic oxidative denitrogenation could be successfully elucidated. This is the first time such a pathway could be traced in detail in non-microbial systems. It was found that the organic nitrogen is first oxidized to nitrate, which is subsequently reduced to molecular nitrogen via nitrous oxide. Hereby, the organic substrate serves as a reducing agent. The discovery of this pathway is an important milestone for the further development of fuel denitrogenation technologies. The United Nations aims to counteract global warming with Net Zero Emissions (NZE) commitments; however, it is not yet foreseeable when crude oil-based fuels will become obsolete. In 2021, more than 50 million barrels per day (mb/d) were consumed for the transport sector alone. Above all, heteroatoms such as sulfur or nitrogen produce SO₂ and NOx during combustion in the engines, which is not only harmful to the climate but also to health. Therefore, in refineries, these heteroatoms are removed by hy-drotreating to produce clean fuels. However, this catalytic reaction is inhibited by the basic, nitrogenous reactants (e.g., quinoline) as well as by NH3. The ion pair of the nitrogen atom forms strong pi-bonds to the active sites of the hydrotreating catalyst, which dimin-ishes its activity. To maximize the desulfurization and denitrogenation effectiveness in comparison to just extraction and adsorption, selective oxidation is typically combined with either extraction or selective adsorption. The selective oxidation produces more polar compounds that can be removed from the non-polar oil in a separate step. The extraction step can also be carried out in parallel to the oxidation reaction, as a result of in situ separation of the oxidation products (ECODS; extractive catalytic oxidative desulfurization). In this process, H8PV5Mo7O40 (HPA-5) is employed as a homogeneous polyoxometalate (POM) catalyst in an aqueous phase, whereas the sulfur containing fuel components are oxidized after diffusion from the organic fuel phase into the aqueous catalyst phase, to form highly polar products such as H₂SO₄ and carboxylic acids, which are thereby extracted from the organic fuel phase and accumulate in the aqueous phase. In contrast to the inhibiting properties of the basic nitrogen compounds in hydrotreating, the oxidative desulfurization improves with simultaneous denitrification in this system (ECODN; extractive catalytic oxidative denitrogenation). The reaction pathway of ECODS has already been well studied. In contrast, the oxidation of nitrogen compounds in ECODN is not yet well understood and requires more detailed investigations.

Keywords: oxidative reaction pathway, denitrogenation of fuels, molecular catalysis, polyoxometalate

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Authors: Jasmine Renner, Alice Njuguna

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The booming technological revolution is driving a change in the mode of delivery systems especially for e-learning and distance learning in higher education. The report and findings of the study; an assessment of digital platforms, student online learning, teaching pedagogies, research and training at Kenya College of Accounting University (hereinafter 'KCA') was undertaken as a joint collaboration project between the Carnegie African Diaspora Fellowship and input from the staff, students and faculty at KCA University. The participants in this assessment/research met for selected days during a six-week period during which, one-one consultations, surveys, questionnaires, foci groups, training, and seminars were conducted to ascertain 'online learning and teaching, curriculum development, research and training at KCA.' The project was organized into an eight-week project workflow with each week culminating in project activities designed to assess digital online teaching and learning at KCA. The project also included the training of distance learning instructors at KCA and the evaluation of KCA’s distance platforms and programs. Additionally, through a curriculum audit and redesign, the project sought to enhance the curriculum development activities related to of distance learning at KCA. The findings of this assessment/research represent the systematic deliberate process of gathering, analyzing and using data collected from DL students, DL staff and lecturers and a librarian personnel in charge of online learning resources and access at KCA. We engaged in one-on-one interviews and discussions with staff, students, and faculty and collated the findings to inform practices that are effective in the ongoing design and development of eLearning earning at KCA University. Overall findings of the project led to the following recommendations. First, there is a need to address infrastructural challenges that led to poor internet connectivity for online learning, training needs and content development for faculty and staff. Second, there is a need to manage cultural impediments within KCA; for example fears of vital change from one platform to another for effectiveness and Institutional goodwill as a vital promise of effective online learning. Third, at a practical and short-term level, the following recommendations based on systematic findings of the research conducted were as follows: there is a need for the following to be adopted at KCA University to promote the effective adoption of online learning: a) an eLearning compatible faculty lab, b) revision of policy to include an eLearn strategy or strategic management, c) faculty and staff recognitions engaged in the process of training for the adoption and implementation of eLearning and d) adequate website resources on eLearning. The report and findings represent a comprehensive approach to a systematic assessment of online teaching and learning, research and training at KCA.

Keywords: e-learning, digital platforms, student online learning, online teaching pedagogies

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Authors: Emily Schulz

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The ancient Vedic culture from India had traditions that supported all aspects of health, including psychological health, and are relevant in the current era. These traditions have been compiled by Professor Dr. Purna, a rare Himalayan Master, into the Purna Health Management System (PHMS). The PHMS is a unique, holistic, and integrated approach to health management. It is comprised of four key factors: Health, Fitness, and Nutrition (HF&N), Life Balance (Stress Management) (LB-SM), Spiritual Growth and Development (SG&D); and Living in Harmony with the Natural Environment (LHWNE). The purpose of the PHMS is to give people the tools to take responsibility for managing their own holistic health and wellbeing. A study using a cross-sectional mixed-methods anonymous online survey was conducted during 2017-2018. Adult students of Professor Dr. Purna were invited to participate through announcements made at various events He held throughout the globe. Follow-up emails were sent with consenting language for interested parties and provided them with a link to the survey. Participation in the study was completely voluntary and no incentives were given to respond to the survey. The overall aim of the study was to investigate the effectiveness of implementation of the PHMS on practitioners' emotional balance. However, given the holistic nature of the PHMS, survey questions also inquired about participants’ physical health, stress level, ability to manage stress, and wellbeing using Likert scales. The survey also included some open-ended questions to gain an understanding of the participants’ experiences with the PHMS relative to their emotional balance. In total, 52 people out of 253 potential respondents participated in the study. Data were analyzed using nonparametric Spearman’s Rho correlation coefficient (rs) since the data were not on a normal distribution. Statistical significance was set at p < .05. Results of the study suggested that there are moderate to strong statistically significant relationships (p < .001) between participants' frequent implementation of each of the four key factors of the PHMS and self-reported mental/emotional health (HF&N rs = 0.42; LB-SM rs = 0.54; SG&D rs = 0.49; LHWNE rs = 0.45) Results also demonstrated statistically significant relationships (p < .001) between participants' frequent implementation of each of the four key factors of the PHMS and their self-reported ability to manage stress (HF&N rs = 0.44; LB-SM rs = 0.55; SG&D rs = 0.39; LHWNE rs = 0.55). Additionally, those who reported experiencing better physical health also reported better mental/emotional health (rs = 0.49, p < .001) and better ability to manage stress (rs = 0.46, p < .001). The findings of this study suggest that wisdom from the ancient Vedic culture may be useful for those working in the field of psychology and related fields who would like to assist clients in calming their mind and emotions and managing their stress levels.

Keywords: balanced emotions, balanced mind, stress management, Vedic philosophy

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Authors: Aziza Al-Sawafi

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Introduction: The evidence of family interventions in schizophrenia is robust primarily in high-income settings. However, they have been adapted to other settings and cultures to improve effectiveness and acceptability. In Oman, there is limited integration of psychosocial interventions in the treatment of schizophrenia. Therefore, the adaptation of family intervention to the Omani culture may facilitate its uptake. Most service users in Oman live with their families outside the healthcare system, and nothing is known about their experience, needs, or resources. Furthermore, understanding caregivers' and mental health professionals' preferences, perceptions, and experience is a fundamental element in the process of intervention development. Therefore, this study aims to develop a culturally sensitive, feasible, and acceptable family intervention for relatives living with schizophrenia in Oman. Method: The Medical Research Council's framework for the evaluation of complex health care interventions provided the conceptual structure for the study. The development phase was carried out, which involved three stages: 1) systematically reviewing the available literature regarding culturally adapted family interventions in the Arab world 2) In-depth interviews with caregivers to explore their experience and perceived needs and preferences regarding intervention 3) A focus group study involving health professionals to explore the acceptability and feasibility of delivering the family intervention in the Omani context. Data synthesis determined the design of the proposed intervention according to the findings obtained from the previous stages. Results: Stage one: The systematic review found limited evidence of culturally-adapted family interventions in the Arab region. However, the cultural adaptation process was comprehensive, and the implementation was reported to be feasible and acceptable. Stage two: The experience of family caregivers illuminated four main themes: burden, stigma, violence, and family needs. Burdens of care included objective and subjective burdens, positive feelings, and coping mechanisms. Caregivers gave their opinion about the content and preference of the intervention from their personal experiences. Stage three: mental health professionals discussed the delivery system of the intervention from a clinical standpoint concerning issues and barriers to implementation. They recommended modifications to the components of the intervention to ensure its acceptability and feasibility in the local setting. Data synthesis was carried out, and the intervention was designed. Conclusion: This study provides evidence of the potential applicability and acceptability of a culturally sensitive family intervention for families of individuals with schizophrenia in Oman. However, more work needs to be done to test the feasibility of the study and overcome the practical challenges.

Keywords: cultural-adaptation, family intervention, Oman, schizophrenia

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Authors: Teruya Goto, Hokuto Chiba, Tatsuhiro Takahashi

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Carbon fiber reinforced thermoplastic resin using short carbon fiber has been produced by melt mixing and the improvement of mechanical properties has been frequently reported up to now. One of the most frequently reported enhancement has been seen in carbon fiber / polypropylene (PP) composites by adding small amount of maleic anhydride grafted polypropylene (MA-g-PP) into PP matrix. However, the further enhancement of tensile strength and tensile modules has been expected for lightning the composite more. Our present research aims to improve the mechanical property by using a highly reactive monolayer polymer, which can react with both COOH of carbon fiber surface and maleic anhydride of MA-g-PP in the matrix, on carbon fiber for PP/CF composite. It has been known that oxazoline has much higher reactivity with COOH without catalysts, compared with amine group and alcohol OH group. However, oxazoline group has not been used for the interface. To achieve the purpose, poly-2-vinyl-2-oxazoline (Pvozo), having highly reactivity with COOH and maleic anhydride, has been originally synthesized through radical polymerization using 2-vinyl-2-oxazoline as a monomer, resulting in the Mw around 140,000. Monolayer Pvozo chemically reacted on CF was prepared in 1-methoxy-2-propanol solution of Pvozo by heating at 100oC for 3 hours. After this solution treatment, unreacted Pvozo was completely washed out by methanol, resulting the uniform formation of the monolayer Pvozo on CF. Monolayer Pvozo coated CF was melt mixed by with PP and a small amount of MA-g-PP for the preparation of the composite samples using a batch type melt mixer. With performing the tensile strength tests of the composites, the tensile strength of CF/MA-g-PP/PP showed 40% increase, compared to that of CF/PP. While, that of Pvozo coated CF/MA-g-PP/PP exhibited 80% increase, compared to that of CF/PP. To get deeper insight of the dramatic increase, the weight percentage of chemically grafted polymer based on CF was evaluated by dissolving and removing the matrix polymer by xylene using by thermos gravimetric analysis (TGA). The chemically grafted remained polymer was found to be 0.69wt% in CF/PP, 0.98wt% in CF/MA-g-PP/PP, 1.51wt% in Pvozo coated CF/MA-g-PP/PP, suggesting that monolayer Pvozo contributed to the increase of the grafted polymer amount. In addition, the very strong adhesion by Pvozo was confirmed by observing the fractured cross-sectional surface of the composite by scanning electron micrograph (SEM). As a conclusion, the effectiveness of a highly reactive monolayer Pvozo on CF for the enhancement of the mechanical properties of CF/PP composite was demonstrated, which can be interpreted by the clear evidence of the increase of the grafting polymer on CF.

Keywords: CFRTP, interface, oxazoline, polymer graft, mechanical property

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Authors: Ahmed Borg, Elsa Aristodemou, Attia Attia

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Well control involves managing the circulating drilling fluid within the wells and avoiding kicks and blowouts as these can lead to losses in human life and drilling facilities. Current practices for good control incorporate predictions of pressure losses through computational models. Developing a realistic hydraulic model for a good control problem is a very complicated process due to the existence of a complex multiphase region, which usually contains a non-Newtonian drilling fluid and the miscibility of formation gas in drilling fluid. The current approaches assume an inaccurate flow fluid model within the well, which leads to incorrect pressure loss calculations. To overcome this problem, researchers have been considering the more complex two-phase fluid flow models. However, even these more sophisticated two-phase models are unsuitable for applications where pressure dynamics are important, such as in managed pressure drilling. This study aims to develop and implement new fluid flow models that take into consideration the miscibility of fluids as well as their non-Newtonian properties for enabling realistic kick treatment. furthermore, a corresponding numerical solution method is built with an enriched data bank. The research work considers and implements models that take into consideration the effect of two phases in kick treatment for well control in conventional drilling. In this work, a corresponding numerical solution method is built with an enriched data bank. Software STARCCM+ for the computational studies to study the important parameters to describe wellbore multiphase flow, the mass flow rate, volumetric fraction, and velocity of each phase. Results showed that based on the analysis of these simulation studies, a coarser full-scale model of the wellbore, including chemical modeling established. The focus of the investigations was put on the near drill bit section. This inflow area shows certain characteristics that are dominated by the inflow conditions of the gas as well as by the configuration of the mud stream entering the annulus. Without considering the gas solubility effect, the bottom hole pressure could be underestimated by 4.2%, while the bottom hole temperature is overestimated by 3.2%. and without considering the heat transfer effect, the bottom hole pressure could be overestimated by 11.4% under steady flow conditions. Besides, larger reservoir pressure leads to a larger gas fraction in the wellbore. However, reservoir pressure has a minor effect on the steady wellbore temperature. Also as choke pressure increases, less gas will exist in the annulus in the form of free gas.

Keywords: multiphase flow, well- control, STARCCM+, petroleum engineering and gas technology, computational fluid dynamic

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Authors: Praskovya Britskaya, Fatima Shaizadina, Alua Omarova, Nessipkul Alysheva

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Planned preventive vaccination, which is carried out in the Republic of Kazakhstan, promoted permanent decrease in the incidence of measles and viral hepatitis B. In the structure of VHB patients prevail people of young, working age. Monitoring of infectious incidence, monitoring of coverage of immunization of the population, random serological control over the immunity enable well-timed identification of distribution of the activator, effectiveness of the taken measures and forecasting. The serological blood analysis was conducted in indicator groups of the population of Central Kazakhstan for the purpose of identification of antibody titre for vaccine preventable infections (measles, viral hepatitis B). Measles antibodies were defined by method of enzyme-linked assay (ELA) with test-systems "VektoKor" – Ig G ('Vektor-Best' JSC). Antibodies for HBs-antigen of hepatitis B virus in blood serum was identified by method of enzyme-linked assay (ELA) with VektoHBsAg test systems – antibodies ('Vektor-Best' JSC). The result of the analysis is positive, the concentration of IgG to measles virus in the studied sample is equal to 0.18 IU/ml or more. Protective level of concentration of anti-HBsAg makes 10 mIU/ml. The results of the study of postvaccinal measles immunity showed that the share of seropositive people made 87.7% of total number of surveyed. The level of postvaccinal immunity to measles in age groups differs. So, among people older than 56 the percentage of seropositive made 95.2%. Among people aged 15-25 were registered 87.0% seropositive, at the age of 36-45 – 86.6%. In age groups of 25-35 and 36-45 the share of seropositive people was approximately at the same level – 88.5% and 88.8% respectively. The share of people seronegative to a measles virus made 12.3%. The biggest share of seronegative people was found among people aged 36-45 – 13.4% and 15-25 – 13.0%. The analysis of results of the examined people for the existence of postvaccinal immunity to viral hepatitis B showed that from all surveyed only 33.5% have the protective level of concentration of anti-HBsAg of 10 mIU/ml and more. The biggest share of people protected from VHB virus is observed in the age group of 36-45 and makes 60%. In the indicator group – above 56 – seropositive people made 4.8%. The high percentage of seronegative people has been observed in all studied age groups from 40.0% to 95.2%. The group of people which is least protected from getting VHB is people above 56 (95.2%). The probability to get VHB is also high among young people aged 25-35, the percentage of seronegative people made 80%. Thus, the results of the conducted research testify to the need for carrying out serological monitoring of postvaccinal immunity for the purpose of operational assessment of the epidemiological situation, early identification of its changes and prediction of the approaching danger.

Keywords: antibodies, blood serum, immunity, immunoglobulin

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Authors: Aya Tanaka, Mariko Era, Manami Masuda, Yui Okuno, Takayoshi Kawahara, Takahide Kanyama, Hiroshi Morita

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Objectives— Fungi and bacteria are present in a wide range of natural environments. They are breed in the foods such as vegetables and fruit, causing corruption and deterioration of these foods in some cases. Furthermore, some species of fungi and bacteria are known to cause food intoxication or allergic reactions in some individuals. To prevent fungal and bacterial contamination, various fungicides and bactericidal have been developed that inhibit fungal and bacterial growth. Fungicides and bactericides must show high antifungal and antibacterial activity, sustainable activity, and a high degree of safety. Therefore, we focused on the fatty acid salt which is the main component of soap. We focused on especially C10K and C12K. This study aimed to find the effectiveness of the fatty acid salt as antimicrobial agents for food safety. Materials and Methods— Cladosporium cladosporioides NBRC 30314, Penicillium pinophilum NBRC 6345, Aspergillus oryzae (Akita Konno store), Rhizopus oryzae NBRC 4716, Fusarium oxysporum NBRC 31631, Escherichia coli NBRC 3972, Bacillus subtilis NBRC 3335, Staphylococcus aureus NBRC 12732, Pseudomonas aenuginosa NBRC 13275 and Serratia marcescens NBRC 102204 were chosen as tested fungi and bacteria. Hartmannella vermiformis NBRC 50599 and Acanthamoeba castellanii NBRC 30010 were chosen as tested amoeba. Nine fatty acid salts including potassium caprate (C10K) and laurate (C12K) at 350 mM and pH 10.5 were used as antifungal activity. The spore suspension of each fungus (3.0×10⁴ spores/mL) or the bacterial suspension (3.0×10⁵ or 3.0×10⁶ or 3.0×10⁷ CFU/mL) was mixed with each of the fatty acid salts (final concentration of 175 mM). Samples were counted at 0, 10, 60, and 180 min by plating (100 µL) on potato dextrose agar or nutrient agar. Fungal and bacterial colonies were counted after incubation for 1 or 2 days at 30 °C. Results— C10K was antifungal activity of 4 log-unit incubated time for 10 min against fungi other than A. oryzae. C12K was antifungal activity of 4 log-unit incubated time for 10 min against fungi other than P. pinophilum and A. oryzae. C10K and C12K did not show high anti-yeast activity. C10K was antibacterial activity of 6 or 7 log-unit incubated time for 10 min against bacteria other than B. subtilis. C12K was antibacterial activity of 5 to 7 log-unit incubated time for 10 min against bacteria other than S. marcescens. C12K was anti-amoeba activity of 4 log-unit incubated time for 10 min against H. vermiformis. These results suggest C10K and C12K have potential in the field of food safety.

Keywords: food safety, microbes, antimicrobial, fatty acid salts

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Authors: Nayer Mofidtabatabaei

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Advancements in artificial intelligence (AI) have transformed various fields, including psychology and behavioral sciences. This paper explores the diverse ways in which AI is applied to enhance research, diagnosis, therapy, and understanding of human behavior and mental health. We discuss the potential benefits and challenges associated with AI in these fields, emphasizing the ethical considerations and the need for collaboration between AI researchers and psychological and behavioral science experts. Artificial Intelligence (AI) has gained prominence in recent years, revolutionizing multiple industries, including healthcare, finance, and entertainment. One area where AI holds significant promise is the field of psychology and behavioral sciences. AI applications in this domain range from improving the accuracy of diagnosis and treatment to understanding complex human behavior patterns. This paper aims to provide an overview of the various AI applications in psychological and behavioral sciences, highlighting their potential impact, challenges, and ethical considerations. Mental Health Diagnosis AI-driven tools, such as natural language processing and sentiment analysis, can analyze large datasets of text and speech to detect signs of mental health issues. For example, chatbots and virtual therapists can provide initial assessments and support to individuals suffering from anxiety or depression. Autism Spectrum Disorder (ASD) Diagnosis AI algorithms can assist in early ASD diagnosis by analyzing video and audio recordings of children's behavior. These tools help identify subtle behavioral markers, enabling earlier intervention and treatment. Personalized Therapy AI-based therapy platforms use personalized algorithms to adapt therapeutic interventions based on an individual's progress and needs. These platforms can provide continuous support and resources for patients, making therapy more accessible and effective. Virtual Reality Therapy Virtual reality (VR) combined with AI can create immersive therapeutic environments for treating phobias, PTSD, and social anxiety. AI algorithms can adapt VR scenarios in real-time to suit the patient's progress and comfort level. Data Analysis AI aids researchers in processing vast amounts of data, including survey responses, brain imaging, and genetic information. Privacy Concerns Collecting and analyzing personal data for AI applications in psychology and behavioral sciences raise significant privacy concerns. Researchers must ensure the ethical use and protection of sensitive information. Bias and Fairness AI algorithms can inherit biases present in training data, potentially leading to biased assessments or recommendations. Efforts to mitigate bias and ensure fairness in AI applications are crucial. Transparency and Accountability AI-driven decisions in psychology and behavioral sciences should be transparent and subject to accountability. Patients and practitioners should understand how AI algorithms operate and make decisions. AI applications in psychological and behavioral sciences have the potential to transform the field by enhancing diagnosis, therapy, and research. However, these advancements come with ethical challenges that require careful consideration. Collaboration between AI researchers and psychological and behavioral science experts is essential to harness AI's full potential while upholding ethical standards and privacy protections. The future of AI in psychology and behavioral sciences holds great promise, but it must be navigated with caution and responsibility.

Keywords: artificial intelligence, psychological sciences, behavioral sciences, diagnosis and therapy, ethical considerations

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Authors: Mardianto

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Education and learning are now grown rapidly. Synergy of techonology especially instructional technology in the learning activities are very big influence on the effectiveness of learning and creativity to achieve optimal results. But on the other hand there is a education value that is difficult to be articulated through character-forming technology such as honesty, discipline, hard work, heroism, and so forth. Learning strategy and storytelling from the past until today is still an option for teachers to convey the message of character values. With the material was loaded from the local culture (stories folklore), the combination of learning objectives (build character child) strategy, and traditional methods (storytelling and story), and the preservation of local culture (dig tale folklore) is critical to maintaining the nation's culture. In the context of maintaining the nation's culture, then since the age of the child at the level of government elementary school a necessity. Globalization, the internet and technology sometimes feel can displace the role of the teacher in the learning activities. To the oral tradition is a mainstay of storytelling should be maintained and preserved. This research was conducted at the elementary school in the city of Medan, North Sumatra Indonesia, with a random sampling technique, the 27 class teachers were respondents who were randomly assigned to the Madrasah Ibtdaiyah (Islamic Elementary School) both public and private. Research conducted at the beginning of 2014 refers to a curriculum that is being transformed in the environment ministry Republic Religion Indonesia. The results of this study indicate that; the declining skills of teachers to develop storytelling this can be seen from; 74.07% of teachers have never attended a special training storytelling, 85.19% no longer nasakah new stories, only 22.22% are teachers who incorporate methods of stories in the learning plan. Most teachers are no longer concerned with storytelling, among those experiencing difficulty in developing methods because the story; 66.67% of children are more interested in children's cartoons like Bobo boy, Angrybirds and others, 59.26 children prefer other activities than listening to a story. The teachers hope, folklore books should be preserved, storytelling training should be provided by the government through the ministry of religion, race or competition of storytelling should be scheduled, writing a new script-based populist storytelling should be provided immediately. The teachers’ hope certainly not excessive, by realizing the story method becomes articulation as the efforts of child character development based populist, therefore the local knowledge can be a strong fortress facing society in the era of progress as at present, and future.

Keywords: story telling, local wisdom, education, technology development

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Authors: Béla Kovács, Éva Bódi, Farzaneh Garousi, Szilvia Várallyay, Áron Soós, Xénia Vágó, Dávid Andrási

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In agriculture for analysis of elements in different food and food raw materials, moreover environmental samples generally flame atomic absorption spectrometers (FAAS), graphite furnace atomic absorption spectrometers (GF-AAS), inductively coupled plasma optical emission spectrometers (ICP-OES) and inductively coupled plasma mass spectrometers (ICP-MS) are routinely applied. An inductively coupled plasma mass spectrometer (ICP-MS) is capable for analysis of 70-80 elements in multielemental mode, from 1-5 cm3 volume of a sample, moreover the detection limits of elements are in µg/kg-ng/kg (ppb-ppt) concentration range. All the analytical instruments have different physical and chemical interfering effects analysing the above types of samples. The smaller the concentration of an analyte and the larger the concentration of the matrix the larger the interfering effects. Nowadays there is very important to analyse growingly smaller concentrations of elements. From the above analytical instruments generally the inductively coupled plasma mass spectrometer is capable of analysing the smallest concentration of elements. The applied ICP-MS instrument has Collision Cell Technology (CCT) also. Using CCT mode certain elements have better (smaller) detection limits with 1-3 magnitudes comparing to a normal ICP-MS analytical method. The CCT mode has better detection limits mainly for analysis of selenium, arsenic, germanium, vanadium and chromium. To elaborate an analytical method for trace elements with an inductively coupled plasma mass spectrometer the most important interfering effects (problems) were evaluated: 1) Physical interferences; 2) Spectral interferences (elemental and molecular isobaric); 3) Effect of easily ionisable elements; 4) Memory interferences. Analysing food and food raw materials, moreover environmental samples an other (new) interfering effect emerged in ICP-MS, namely the effect of various matrixes having different evaporation and nebulization effectiveness, moreover having different quantity of carbon content of food and food raw materials, moreover environmental samples. In our research work the effect of different water-soluble compounds furthermore the effect of various quantity of carbon content (as sample matrix) were examined on changes of intensity of the applied elements. So finally we could find “opportunities” to decrease or eliminate the error of the analyses of applied elements (Cr, Co, Ni, Cu, Zn, Ge, As, Se, Mo, Cd, Sn, Sb, Te, Hg, Pb, Bi). To analyse these elements in the above samples, the most appropriate inductively coupled plasma mass spectrometer is a quadrupole instrument applying a collision cell technique (CCT). The extent of interfering effect of carbon content depends on the type of compounds. The carbon content significantly affects the measured concentration (intensities) of the above elements, which can be corrected using different internal standards.

Keywords: elements, environmental and food samples, ICP-MS, interference effects

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Authors: Ezinne K. Okoro, Takahiko Katoh, Yoko Kawamura, Stanley C. Meribe

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HIV infection in children is largely as a result of vertical transmission (mother to child transmission [MTCT]). Thus, elimination of mother to child transmission of HIV/AIDS is critical in eliminating HIV infection in children. In Nigeria, drawbacks such as; limited pediatric screening, limited human capital, insufficient advocacy and poor understanding of ART guidelines, have impacted efforts at combating the disease, even as treatment services are free. Prevention of Mother to Child Transmission (PMTCT) program relies on health workers who not only counsel pregnant women on first contact but can competently provide HIV-positive pregnant women with accurate information about the PMTCT program such as feeding techniques and drug adherence. In developing regions like Nigeria where health care delivery faces a lot of drawbacks, it becomes paramount to address these issues of poor PMTCT coverage by conducting a baseline assessment of the knowledge, practices and perceptions related to HIV prevention amongst healthcare workers in Nigeria. A descriptive cross-sectional study was conducted amongst 250 health workers currently employed in health facilities in Abuja, Nigeria where PMTCT services were offered with the capacity to carry out early infant diagnosis testing (EID). Data was collected using a self-administered, pretested, structured questionnaire. This study showed that the knowledge of PMTCT of HIV was poor (30%) among healthcare workers who offer this service day-to-day to pregnant women. When PMTCT practices were analyzed in keeping with National PMTCT guidelines, over 61% of the respondents reported observing standard practices and the majority (58%) had good attitudes towards caring for patients with HIV/AIDS. Although 61% of the respondents reported being satisfied with the quality of service being rendered, 63% reported not being satisfied with their level of knowledge. Predictors of good knowledge were job designation and level of educational attainment. Health workers who were more satisfied with their working conditions and those who had worked for a longer time in the PMTCT service were more likely to observe standard PMTCT practices. With over 62% of the healthcare workers suggesting that more training would improve the quality of service being rendered, this is a strong pointer to stakeholders to consider a ‘healthcare worker-oriented approach’ when planning and conducting PMTCT training for healthcare workers. This in turn will increase pediatric ARV coverage, the knowledge and effectiveness of the healthcare workers in carrying out appropriate PMTCT interventions and culminating in the reduction/elimination of HIV transmission to newborns.

Keywords: attitudes, HIV/AIDS, healthcare workers, knowledge, mother to child transmission, Nigeria, perceptions

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Authors: Tauqir A. Moughal, Fusheng Yu, Abeer Mazher

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Land-cover and land-use change information are important because of their practical uses in various applications, including deforestation, damage assessment, disasters monitoring, urban expansion, planning, and land management. Therefore, developing change detection methods for remote sensing images is an important ongoing research agenda. However, detection of change through optical remote sensing images is not a trivial task due to many factors including the vagueness between the boundaries of changed and unchanged regions and spatial dependence of the pixels to its neighborhood. In this paper, we propose a binary change detection technique for bi-temporal optical remote sensing images. As in most of the optical remote sensing images, the transition between the two clusters (change and no change) is overlapping and the existing methods are incapable of providing the accurate cluster boundaries. In this regard, a methodology has been proposed which uses the fuzzy c-means clustering to tackle the problem of vagueness in the changed and unchanged class by formulating the soft boundaries between them. Furthermore, in order to exploit the neighborhood information of the pixels, the input patterns are generated corresponding to each pixel from bi-temporal images using 3×3, 5×5 and 7×7 window. The between images and within image spatial dependence of the pixels to its neighborhood is quantified by using Pearson product moment correlation and Moran’s I statistics, respectively. The proposed technique consists of two phases. At first, between images and within image spatial correlation is calculated to utilize the information that the pixels at different locations may not be independent. Second, fuzzy c-means technique is used to produce two clusters from input feature by not only taking care of vagueness between the changed and unchanged class but also by exploiting the spatial correlation of the pixels. To show the effectiveness of the proposed technique, experiments are conducted on multispectral and bi-temporal remote sensing images. A subset (2100×1212 pixels) of a pan-sharpened, bi-temporal Landsat 5 thematic mapper optical image of Los Angeles, California, is used in this study which shows a long period of the forest fire continued from July until October 2009. Early forest fire and later forest fire optical remote sensing images were acquired on July 5, 2009 and October 25, 2009, respectively. The proposed technique is used to detect the fire (which causes change on earth’s surface) and compared with the existing K-means clustering technique. Experimental results showed that proposed technique performs better than the already existing technique. The proposed technique can be easily extendable for optical hyperspectral images and is suitable for many practical applications.

Keywords: burned area, change detection, correlation, fuzzy clustering, optical remote sensing

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Authors: Joseph Ippolito, David Megenhardt

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In the United States, displaced workers, the unemployed and those seeking to build additional work skills are provided employment training and job placement services through a system of One-Stop Career Centers that are sponsored by the country’s 593 local Workforce Boards. During the period 2010-2015, these centers served roughly 8 million individuals each year. The quality of services provided at these centers rests upon professional employment specialists who work closely with clients to identify their job interests, to connect them to appropriate training opportunities, to match them with needed supportive social services and to guide them to eventual employment. Despite the crucial role these Employment Specialists play, currently there are no broadly accepted standards that establish what these individuals are expected to do in the workplace, nor are there indicators to assess how well an individual performs these responsibilities. Education Development Center (EDC) and the United Labor Agency (ULA) have partnered to create a foundation upon which curriculum can be developed that addresses the skills, knowledge and behaviors that Employment Specialists must master in order to serve their clients effectively. EDC is a non-profit, education research and development organization that designs, implements, and evaluates programs to improve education, health and economic opportunity worldwide. ULA is the social action arm of organized labor in Greater Cleveland, Ohio. ULA currently operates One-Stop Career Centers in both Cleveland and Pittsburgh, Pennsylvania. This case study outlines efforts taken to create standards that define the work of Employment Specialists and to establish indicators that can guide assessment of work performance. The methodology involved in the study has engaged a panel of expert Employment Specialists in rigorous, structured dialogues that analyze and identify the characteristics that enable them to be effective in their jobs. It has also drawn upon and integrated reviews of the panel’s work by more than 100 other Employment Specialists across the country. The results of this process are two documents that provide resources for developing training curriculum for future Employment Specialists, namely: an occupational profile of an Employment Specialist that offers a detailed articulation of the skills, knowledge and behaviors that enable individuals to be successful at this job, and; a collection of performance based indicators, aligned to the profile, which illustrate what the work responsibilities of an Employment Specialist 'look like' a four levels of effectiveness ranging from novice to expert. The method of occupational analysis used by the study has application across a broad number of fields.

Keywords: assessment, employability, job standards, workforce development

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Authors: Y. Roumila, D. Meziani, R. Bagtache, K. Abdmeziem, M. Trari

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Heterogeneous photocatalysis over semiconductors has proved its effectiveness in the treatment of wastewaters since it works under soft conditions. It has emerged as a promising technique, giving rise to less toxic effluents and offering the opportunity of using sunlight as a sustainable and renewable source of energy. Many compounds have been used as photocatalysts. Though synthesized ones are intensively used, they remain expensive, and their synthesis involves special conditions. We thus thought of implementing a natural material, a phosphate ore, due to its low cost and great availability. Our work is devoted to the removal of hazardous organic pollutants, which cause several environmental problems and health risks. Among them, dye pollutants occupy a large place. This work relates to the study of the photodegradation of methyl violet (MV) and rhodamine B (RhB), in single and binary systems, under UV light and sunlight irradiation. Methyl violet is a triarylmethane dye, while RhB is a heteropolyaromatic dye belonging to the Xanthene family. In the first part of this work, the natural compound was characterized using several physicochemical and photo-electrochemical (PEC) techniques: X-Ray diffraction, chemical, and thermal analyses scanning electron microscopy, UV-Vis diffuse reflectance measurements, and FTIR spectroscopy. The electrochemical and photoelectrochemical studies were performed with a Voltalab PGZ 301 potentiostat/galvanostat at room temperature. The structure of the phosphate material was well characterized. The photo-electrochemical (PEC) properties are crucial for drawing the energy band diagram, in order to suggest the formation of radicals and the reactions involved in the dyes photo-oxidation mechanism. The PEC characterization of the natural phosphate was investigated in neutral solution (Na₂SO₄, 0.5 M). The study revealed the semiconducting behavior of the phosphate rock. Indeed, the thermal evolution of the electrical conductivity was well fitted by an exponential type law, and the electrical conductivity increases with raising the temperature. The Mott–Schottky plot and current-potential J(V) curves recorded in the dark and under illumination clearly indicate n-type behavior. From the results of photocatalysis, in single solutions, the changes in MV and RhB absorbance in the function of time show that practically all of the MV was removed after 240 mn irradiation. For RhB, the complete degradation was achieved after 330 mn. This is due to its complex and resistant structure. In binary systems, it is only after 120 mn that RhB begins to be slowly removed, while about 60% of MV is already degraded. Once nearly all of the content of MV in the solution has disappeared (after about 250 mn), the remaining RhB is degraded rapidly. This behaviour is different from that observed in single solutions where both dyes are degraded since the first minutes of irradiation.

Keywords: environment, organic pollutant, phosphate ore, photodegradation

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Authors: Jing-Yang Chung, Chi-Wei Liao, Jing Li, Bor Kae Chang, Cheng-Yu Wang

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Chemical hydride ammonia borane (AB, NH3BH3) draws attentions to hydrogen energy researches for its high theoretical gravimetrical capacity (19.6 wt%). Nevertheless, the elevated AB decomposition temperatures (Td) and unwanted byproducts are main hurdles in practical application. It was reported that the byproducts and Td can be reduced with nanoconfinement technique, in which AB molecules are confined in porous materials, such as porous carbon, zeolite, metal-organic frameworks (MOFs), etc. Although nanoconfinement empirically shows effectiveness on hydrogen generation temperature reduction in AB, the theoretical mechanism is debatable. Low Td was reported in AB@IRMOF-1 (Zn4O(BDC)3, BDC = benzenedicarboxylate), where Zn atoms form closed metal clusters secondary building unit (SBU) with no exposed active sites. Other than nanosized hydride, it was also observed that catalyst addition facilitates AB decomposition in the composite of Li-catalyzed carbon CMK-3, MOF JUC-32-Y with exposed Y3+, etc. It is believed that nanosized AB is critical for lowering Td, while active sites eliminate byproducts. Nonetheless, some researchers claimed that it is the catalytic sites that are the critical factor to reduce Td, instead of the hydride size. The group physically ground AB with ZIF-8 (zeolitic imidazolate frameworks, (Zn(2-methylimidazolate)2)), and found similar reduced Td phenomenon, even though AB molecules were not ‘confined’ or forming nanoparticles by physical hand grinding. It shows the catalytic reaction, not nanoconfinement, leads to AB dehydrogenation promotion. In this research, we explored the possible criteria of hydrogen production temperature from nanoconfined AB in MOFs with different pore sizes and active sites. MOFs with metal SBU such as Zn (IRMOF), Zr (UiO), and Al (MIL-53), accompanying with various organic ligands (BDC and BPDC; BPDC = biphenyldicarboxylate) were modified with AB. Excess MOFs were used for AB size constrained in micropores estimated by revisiting Horvath-Kawazoe model. AB dissolved in methanol was added to MOFs crystalline with MOF pore volume to AB ratio 4:1, and the slurry was dried under vacuum to collect AB@MOF powders. With TPD-MS (temperature programmed desorption with mass spectroscopy), we observed Td was reduced with smaller MOF pores. For example, it was reduced from 100°C to 64°C when MOF micropore ~1 nm, while ~90°C with pore size up to 5 nm. The behavior of Td as a function of AB crystalline radius obeys thermodynamics when the Gibbs free energy of AB decomposition is zero, and no obvious correlation with metal type was observed. In conclusion, we discovered Td of AB is proportional to the reciprocal of MOF pore size, possibly stronger than the effect of active sites.

Keywords: ammonia borane, chemical hydride, metal-organic framework, nanoconfinement

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Authors: T. Thein, S. Kalyar Myo

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Human uses visual information for understanding the speech contents in noisy conditions or in situations where the audio signal is not available. The primary advantage of visual information is that it is not affected by the acoustic noise and cross talk among speakers. Using visual information from the lip movements can improve the accuracy and robustness of automatic speech recognition. However, a major challenge with most automatic lip reading system is to find a robust and efficient method for extracting the linguistically relevant speech information from a lip image sequence. This is a difficult task due to variation caused by different speakers, illumination, camera setting and the inherent low luminance and chrominance contrast between lip and non-lip region. Several researchers have been developing methods to overcome these problems; the one is lip reading. Moreover, it is well known that visual information about speech through lip reading is very useful for human speech recognition system. Lip reading is the technique of a comprehensive understanding of underlying speech by processing on the movement of lips. Therefore, lip reading system is one of the different supportive technologies for hearing impaired or elderly people, and it is an active research area. The need for lip reading system is ever increasing for every language. This research aims to develop a visual teaching method system for the hearing impaired persons in Myanmar, how to pronounce words precisely by identifying the features of lip movement. The proposed research will work a lip reading system for Myanmar Consonants, one syllable consonants (င (Nga)၊ ည (Nya)၊ မ (Ma)၊ လ (La)၊ ၀ (Wa)၊ သ (Tha)၊ ဟ (Ha)၊ အ (Ah) ) and two syllable consonants ( က(Ka Gyi)၊ ခ (Kha Gway)၊ ဂ (Ga Nge)၊ ဃ (Ga Gyi)၊ စ (Sa Lone)၊ ဆ (Sa Lain)၊ ဇ (Za Gwe) ၊ ဒ (Da Dway)၊ ဏ (Na Gyi)၊ န (Na Nge)၊ ပ (Pa Saug)၊ ဘ (Ba Gone)၊ ရ (Ya Gaug)၊ ဠ (La Gyi) ). In the proposed system, there are three subsystems, the first one is the lip localization system, which localizes the lips in the digital inputs. The next one is the feature extraction system, which extracts features of lip movement suitable for visual speech recognition. And the final one is the classification system. In the proposed research, Two Dimensional Discrete Cosine Transform (2D-DCT) and Linear Discriminant Analysis (LDA) with Active Contour Model (ACM) will be used for lip movement features extraction. Support Vector Machine (SVM) classifier is used for finding class parameter and class number in training set and testing set. Then, experiments will be carried out for the recognition accuracy of Myanmar consonants using the only visual information on lip movements which are useful for visual speech of Myanmar languages. The result will show the effectiveness of the lip movement recognition for Myanmar Consonants. This system will help the hearing impaired persons to use as the language learning application. This system can also be useful for normal hearing persons in noisy environments or conditions where they can find out what was said by other people without hearing voice.

Keywords: feature extraction, lip reading, lip localization, Active Contour Model (ACM), Linear Discriminant Analysis (LDA), Support Vector Machine (SVM), Two Dimensional Discrete Cosine Transform (2D-DCT)

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Authors: Alice Civera, Mattia Cattaneo, Michele Meoli, Stefano Paleari

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Despite the fact that more equal access to higher education has been an objective public policy for several decades, little is known about the effectiveness of alternative means for achieving such goal. Indeed, nowadays, high level of graduate population can be observed both in countries with the high and low level of fees, or high and low level of public expenditure in higher education. This paper surveys the extant literature providing some background on the economic concepts of the higher education market, and reviews key determinants of demand and supply. A theoretical model of aggregate demand and supply of higher education is derived, with the aim to facilitate the understanding of the challenges in today’s higher education systems, as well as the opportunities for development. The model is validated on some exemplary case studies describing the different relationship between the level of public investment and levels of graduate population and helps to derive general implications. In addition, using a two-stage least squares model, we build a macroeconomic model of supply and demand for European higher education. The model allows interpreting policies shifting either the supply or the demand for higher education, and allows taking into consideration contextual conditions with the aim of comparing divergent policies under a common framework. Results show that the same policy objective (i.e., increasing graduate population) can be obtained by shifting either the demand function (i.e., by strengthening student aid) or the supply function (i.e., by directly supporting higher education institutions). Under this theoretical perspective, the level of tuition fees is irrelevant, and empirically we can observe high levels of graduate population in both countries with high (i.e., the UK) or low (i.e., Germany) levels of tuition fees. In practice, this model provides a conceptual framework to help better understanding what are the external conditions that need to be considered, when planning a policy for increasing graduate population. Extrapolating a policy from results in different countries, under this perspective, is a poor solution when contingent factors are not addressed. The second implication of this conceptual framework is that policies addressing the supply or the demand function needs to address different contingencies. In other words, a government aiming at increasing graduate population needs to implement complementary policies, designing them according to the side of the market that is interested. For example, a ‘supply-driven’ intervention, through the direct financial support of higher education institutions, needs to address the issue of institutions’ moral hazard, by creating incentives to supply higher education services in efficient conditions. By contrast, a ‘demand-driven’ policy, providing student aids, need to tackle the students’ moral hazard, by creating an incentive to responsible behavior.

Keywords: graduates, higher education, higher education policies, tuition fees

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Authors: Martin Pellon Consunji

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Due to the rise in popularity of Bitcoin and other crypto assets as a store of wealth and speculative investment, there is an ever-growing demand for automated trading tools, such as bots, in order to gain an advantage over the market. Traditionally, trading in the stock market was done by professionals with years of training who understood patterns and exploited market opportunities in order to gain a profit. However, nowadays a larger portion of market participants are at minimum aided by market-data processing bots, which can generally generate more stable signals than the average human trader. The rise in trading bot usage can be accredited to the inherent advantages that bots have over humans in terms of processing large amounts of data, lack of emotions of fear or greed, and predicting market prices using past data and artificial intelligence, hence a growing number of approaches have been brought forward to tackle this task. However, the general limitation of these approaches can still be broken down to the fact that limited historical data doesn’t always determine the future, and that a lot of market participants are still human emotion-driven traders. Moreover, developing markets such as those of the cryptocurrency space have even less historical data to interpret than most other well-established markets. Due to this, some human traders have gone back to the tried-and-tested traditional technical analysis tools for exploiting market patterns and simplifying the broader spectrum of data that is involved in making market predictions. This paper proposes a method which uses neuro evolution techniques on both sentimental data and, the more traditionally human-consumed, technical analysis data in order to gain a more accurate forecast of future market behavior and account for the way both automated bots and human traders affect the market prices of Bitcoin and other cryptocurrencies. This study’s approach uses evolutionary algorithms to automatically develop increasingly improved populations of bots which, by using the latest inflows of market analysis and sentimental data, evolve to efficiently predict future market price movements. The effectiveness of the approach is validated by testing the system in a simulated historical trading scenario, a real Bitcoin market live trading scenario, and testing its robustness in other cryptocurrency and stock market scenarios. Experimental results during a 30-day period show that this method outperformed the buy and hold strategy by over 260% in terms of net profits, even when taking into consideration standard trading fees.

Keywords: neuro-evolution, Bitcoin, trading bots, artificial neural networks, technical analysis, evolutionary algorithms

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Authors: Ipsita Pujari, Abitha Thomas, Vidhu S. Babu, K. Satyamoorthy

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Orchids are esteemed as celebrities in cut flower industry globally, due to their long-lasting fragrance and freshness. Apart from splendor, the unique metabolites endowed with pharmaceutical potency have made them one of the most hunted in plant kingdom. This had led to their trafficking, resulting in habitat loss, subsequently making them occupiers of IUCN red list as RET species. Many of the orchids especially wild varieties still remain undiscovered. In view to protect and conserve the wild germplasm, researchers have been inventing novel micropropagation protocols; thereby conserving Orchids. India is overflowing with exclusive wild cultivars of Orchids, whose pharmaceutical properties remain untapped and are not marketed owing to relatively small flowers. However, their germplasm is quite pertinent to be preserved for making unusual hybrids. Dendrobium genus is the second largest among Orchids exists in India and has highest demand attributable to enduring cut flowers and significant therapeutic uses in traditional medicinal system. Though the genus is quite endemic in Western Ghat regions of the country, many species are still anonymous with their unknown curative properties. A standard breeding cycle in Orchids usually takes five to seven years (Dendrobium hybrids taking a long juvenile phase of two to five years reaching maturity and flowering stage) and this extensive life cycle has always hindered the development of Dendrobium breeding. Dendrobium is reported with essential therapeutic plant bio-chemicals and ‘Moscatilin’ is one, found exclusive to this famous Dendrobium genus. Moscatilin is reported to have anti-mutagenic and anti-cancer properties, whose positive action has very recently been demonstrated against a range of cancers. Our preliminary study here established a simple and economic small-scale propagation protocol of Dendrobium ovatum describing in vitro production of Moscatilin. Subsequently for enhancing the content of Moscatilin, an efficient experimental related to the organization of transgenic (hairy) D. ovatum root cultures through infection of Agrobacterium rhizogenes 2364 strain on MS basal medium is being reported in the present study. Hairy roots generated on almost half of the explants used (spherules, in vitro plantlets and calli) maintained through suspension cultures, after 8 weeks of co-cultivation with Agrobacterium rhizogenes. GFP assay performed with isolated hairy roots has confirmed the integrative transformation which was further positively confirmed by PCR using rolB gene specific primers. Reverse phase-high performance liquid chromatography and mass spectrometry techniques were used for quantification and accurate identification of Moscatilin respectively from transgenic systems. A noticeable ~3 fold increase in contents were observed in transformed D. ovatum root cultures as compared to the simple in vitro culture, callus culture and callus regeneration plantlets. Role of elicitors e.g., Methyl jasmonate, Salicylic acid, Yeast extract and Chitosan were tested for elevating the Moscatilin content to obtain a comprehensive optimized protocol facilitating the in vitro production of valuable Moscatilin with larger yield. This study would provide evidence towards the in vitro assembly of Moscatilin within a short time-period through not a so-expensive technology for the first time. It also serves as an appropriate basis for bioreactor scale-up resulting in commercial bioproduction of Moscatilin.

Keywords: bioproduction, Dendrobium ovatum, hairy root culture, moscatilin

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Authors: Juliette MacDonald, Jun Li, Wenji Xiang, Mingwei Zhao

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Shanghai International College of Fashion and Innovation (SCF) was created as a result of a collaborative partnership agreement between the University of Edinburgh and Donghua University. The College provides two programmes: Fashion Innovation and Fashion Interior Design and the overarching curriculum has the intention of developing innovation and creativity within an international learning, teaching, knowledge exchange and research context. The research problem presented here focuses on the multi-national/cultural faculty in the team, the challenges arising from difficulties in communication and the associated limitations of management frameworks. The teaching faculty at SCF are drawn from China, Finland, Korea, Singapore and the UK with input from Flying Faculty from Fashion and Interior Design, Edinburgh College of Art (ECA), for 5 weeks each semester. Rather than fully replicating the administrative and pedagogical style of one or other of the institutions within this joint partnership the aim from the outset was to create a third way which acknowledges the quality assurance requirements of both Donghua and Edinburgh, the academic and technical needs of the students and provides relevant development and support for all the SCF-based staff and Flying Academics. It has been well acknowledged by those who are involved in teaching across cultures that there is often a culture shock associated with transnational education but that the experience of being involved in the delivery of a curriculum at a Joint Institution can also be very rewarding for staff and students. It became clear at SCF that if a third way might be achieved which encourages innovative approaches to fashion education whilst balancing the expectations of Chinese and western concepts of education and the aims of two institutions, then it was going to be necessary to construct a framework which developed close working relationships for the entire teaching team, so not only between academics and students but also between technicians and administrators at ECA and SCF. The attempts at co-construction and integration are built on the sharing of cultural and educational experiences and knowledge as well as provision of opportunities for reflection on the pedagogical purpose of the curriculum and its delivery. Methods on evaluating the effectiveness of these aims include a series of surveys and interviews and analysis of data drawn from teaching projects delivered to the students along with graduate successes from the last five years, since SCF first opened its doors. This paper will provide examples of best practice developed by SCF which have helped guide the faculty and embed common core values and aims of co-construction regulations and management, whilst building a pro-active TNE (Trans-National Education) team which enhances the learning experience for staff and students alike.

Keywords: cultural co-construction, educational team management, multi-cultural challenges, TNE integration for teaching teams

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Authors: Anup Anand Deshmukh, Catherine Soladie, Renaud Seguier

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Emotion plays a key role in many applications like healthcare, to gather patients’ emotional behavior. Unlike typical ASR (Automated Speech Recognition) problems which focus on 'what was said', it is equally important to understand 'how it was said.' There are certain emotions which are given more importance due to their effectiveness in understanding human feelings. In this paper, we propose an approach that models human stress from audio signals. The research challenge in speech emotion detection is finding the appropriate set of acoustic features corresponding to an emotion. Another difficulty lies in defining the very meaning of emotion and being able to categorize it in a precise manner. Supervised Machine Learning models, including state of the art Deep Learning classification methods, rely on the availability of clean and labelled data. One of the problems in affective computation is the limited amount of annotated data. The existing labelled emotions datasets are highly subjective to the perception of the annotator. We address the first issue of feature selection by exploiting the use of traditional MFCC (Mel-Frequency Cepstral Coefficients) features in Convolutional Neural Network. Our proposed Emo-CNN (Emotion-CNN) architecture treats speech representations in a manner similar to how CNN’s treat images in a vision problem. Our experiments show that Emo-CNN consistently and significantly outperforms the popular existing methods over multiple datasets. It achieves 90.2% categorical accuracy on the Emo-DB dataset. We claim that Emo-CNN is robust to speaker variations and environmental distortions. The proposed approach achieves 85.5% speaker-dependant categorical accuracy for SAVEE (Surrey Audio-Visual Expressed Emotion) dataset, beating the existing CNN based approach by 10.2%. To tackle the second problem of subjectivity in stress labels, we use Lovheim’s cube, which is a 3-dimensional projection of emotions. Monoamine neurotransmitters are a type of chemical messengers in the brain that transmits signals on perceiving emotions. The cube aims at explaining the relationship between these neurotransmitters and the positions of emotions in 3D space. The learnt emotion representations from the Emo-CNN are mapped to the cube using three component PCA (Principal Component Analysis) which is then used to model human stress. This proposed approach not only circumvents the need for labelled stress data but also complies with the psychological theory of emotions given by Lovheim’s cube. We believe that this work is the first step towards creating a connection between Artificial Intelligence and the chemistry of human emotions.

Keywords: deep learning, brain chemistry, emotion perception, Lovheim's cube

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Authors: Roza Dzierzak, Waldemar Wojcik, Piotr Kacejko

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Analysis of the texture of medical images consists of determining the parameters and characteristics of the examined tissue. The main goal is to assign the analyzed area to one of two basic groups: as a healthy tissue or a tissue with pathological changes. The CT images of the thoracic lumbar spine from 15 healthy patients and 15 with confirmed osteoporosis were used for the analysis. As a result, 120 samples with dimensions of 50x50 pixels were obtained. The set of features has been obtained based on the histogram, gradient, run-length matrix, co-occurrence matrix, autoregressive model, and Haar wavelet. As a result of the image analysis, 290 descriptors of textural features were obtained. The dimension of the space of features was reduced by the use of three selection methods: Fisher coefficient (FC), mutual information (MI), minimization of the classification error probability and average correlation coefficients between the chosen features minimization of classification error probability (POE) and average correlation coefficients (ACC). Each of them returned ten features occupying the initial place in the ranking devised according to its own coefficient. As a result of the Fisher coefficient and mutual information selections, the same features arranged in a different order were obtained. In both rankings, the 50% percentile (Perc.50%) was found in the first place. The next selected features come from the co-occurrence matrix. The sets of features selected in the selection process were evaluated using six classification tree methods. These were: decision stump (DS), Hoeffding tree (HT), logistic model trees (LMT), random forest (RF), random tree (RT) and reduced error pruning tree (REPT). In order to assess the accuracy of classifiers, the following parameters were used: overall classification accuracy (ACC), true positive rate (TPR, classification sensitivity), true negative rate (TNR, classification specificity), positive predictive value (PPV) and negative predictive value (NPV). Taking into account the classification results, it should be stated that the best results were obtained for the Hoeffding tree and logistic model trees classifiers, using the set of features selected by the POE + ACC method. In the case of the Hoeffding tree classifier, the highest values of three parameters were obtained: ACC = 90%, TPR = 93.3% and PPV = 93.3%. Additionally, the values of the other two parameters, i.e., TNR = 86.7% and NPV = 86.6% were close to the maximum values obtained for the LMT classifier. In the case of logistic model trees classifier, the same ACC value was obtained ACC=90% and the highest values for TNR=88.3% and NPV= 88.3%. The values of the other two parameters remained at a level close to the highest TPR = 91.7% and PPV = 91.6%. The results obtained in the experiment show that the use of classification trees is an effective method of classification of texture features. This allows identifying the conditions of the spongy tissue for healthy cases and those with the porosis.

Keywords: classification, feature selection, texture analysis, tree algorithms

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Authors: Kaori Nakamura, Shun Su, Yusak Sulio, Daisuke Fukuda

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Active modes of transportation, such as walking and cycling, are crucial in promoting healthy and sustainable urban environments. Encouraging the use of these modes requires a well-designed road environment that ensures safety and comfort. Understanding what constitutes a safe environment for these users is essential. While previous research mainly focuses on subjective safety or the likelihood of collisions, there needs to be more analysis of the real-time experiences of travelers and dynamic transitions of their discomfort perceptions. Post-ride surveys or pre-ride impressions, the typical evaluation methods in past studies, may not accurately capture the immediate reactions and discomforts experienced during their rides. Though past experimental studies may also use physiological and behavioral data to evaluate road designs, they evaluated road design by comparing time-average physiological and behavioral data across different designs. This study aims to investigate the effects of the dynamic riding environmental changes experienced by cyclists during their rides on their dynamic physiological and behavioral responses and then explore how these conditions contribute to cyclists' overall subjective safety and comfort. We conducted an experiment with 24 participants who cycled approximately 500 meters in a virtual reality (VR) environment designed to mimic a typical road environment of Japanese local towns where lanes for cyclists and regular cars are adjacent in limited road spaces. Participants experienced six road designs varying in width, separation type, and bike lane color. We measured their physiological data, such as heart rate and skin conductance, and behavioral data, including steering, acceleration, and coordination of bicycles. Questionnaires for eliciting subjective impressions were conducted before and after each ride. The data analysis results indicate that wider paths (i.e., 1.5m and 2m width) are preferred, enhancing perceived safety and reducing stress, as supported by lower heart rates and skin conductance levels over narrower ones (1m width). Designs with clear divisions from car lanes may enhance perceived safety and reduce stress. The analysis of the physiological data also supports these arguments, showing that lower heart rates and skin conductance levels are found in wider, clearly marked paths. Further, the drift-diffusion decision model was performed to reveal whether different road environment designs may impact dynamic decision-making processes and physiological attributes. Designing a 1.5m wide bike lane with clear divisions from car lanes showed the highest level of clarity and safety in decision-making parameters. In contrast, designs without clear separations from car lanes resulted in less favorable decision-making outcomes. These results coincide with previous primary research indicating a preference for bike lane widths more significant than 1.5m. In conclusion, the analysis using the drift-diffusion decision model showed that decision-making ease slightly differs from subjective safety perceptions, providing a comprehensive understanding of how different road designs impact users. This study offers a solid foundation for assessing the perceptions of active mode users and highlights the importance of considering both real-time physiological and subjective data in designing road environments that encourage active transportation modes.

Keywords: active transport modes, cognitive and decision-making modeling, road environment designs, virtual reality experiment

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Authors: Shayan Mohajer Hamidi

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Federated learning has emerged as a promising approach for distributed model training while preserving data privacy. However, the challenges of communication overhead, limited network resources, and slow convergence hinder its widespread adoption. On the other hand, knowledge distillation has shown great potential in compressing large models into smaller ones without significant loss in performance. In this paper, we propose an innovative framework that combines federated learning and knowledge distillation to address these challenges and enhance the efficiency of distributed learning. Our approach, called Federated Knowledge Distillation (FKD), enables multiple clients in a federated learning setting to collaboratively distill knowledge from a teacher model. By leveraging the collaborative nature of federated learning, FKD aims to improve model compression while maintaining privacy. The proposed framework utilizes a coded teacher model that acts as a reference for distilling knowledge to the client models. To demonstrate the effectiveness of FKD, we conduct extensive experiments on various datasets and models. We compare FKD with baseline federated learning methods and standalone knowledge distillation techniques. The results show that FKD achieves superior model compression, faster convergence, and improved performance compared to traditional federated learning approaches. Furthermore, FKD effectively preserves privacy by ensuring that sensitive data remains on the client devices and only distilled knowledge is shared during the training process. In our experiments, we explore different knowledge transfer methods within the FKD framework, including Fine-Tuning (FT), FitNet, Correlation Congruence (CC), Similarity-Preserving (SP), and Relational Knowledge Distillation (RKD). We analyze the impact of these methods on model compression and convergence speed, shedding light on the trade-offs between size reduction and performance. Moreover, we address the challenges of communication efficiency and network resource utilization in federated learning by leveraging the knowledge distillation process. FKD reduces the amount of data transmitted across the network, minimizing communication overhead and improving resource utilization. This makes FKD particularly suitable for resource-constrained environments such as edge computing and IoT devices. The proposed FKD framework opens up new avenues for collaborative and privacy-preserving distributed learning. By combining the strengths of federated learning and knowledge distillation, it offers an efficient solution for model compression and convergence speed enhancement. Future research can explore further extensions and optimizations of FKD, as well as its applications in domains such as healthcare, finance, and smart cities, where privacy and distributed learning are of paramount importance.

Keywords: federated learning, knowledge distillation, knowledge transfer, deep learning

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Authors: M. C. O. Ezeibe, F. I. O. Ezeibe

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Reasons viral diseases (including AI, HIV/AIDS, and COVID-19), tumors (including Cancers and Prostrate enlargement), and antimicrobial-resistant infections (AMR) are difficult to cure are features of the pathogens which normal cells do not have or need (biomedical markers) have not been identified; medicines that can counter the markers have not been invented; strategies and mechanisms for their treatments have not been developed. When cells become abnormal, they acquire negative electrical charges, and viruses are either positively charged or negatively charged, while normal cells remain neutral (without electrical charges). So, opposite charges' electrostatic attraction is a treatment mechanism for viral diseases and tumors. Medicines that have positive electrical charges would mop abnormal (infected and tumor) cells and DNA viruses (negatively charged), while negatively charged medicines would mop RNA viruses (positively charged). Molecules of Aluminum-magnesium silicate [AMS: Al₂Mg₃ (SiO₄)₃], an approved medicine and pharmaceutical stabilizing agent, consist of nanoparticles which have both positive electrically charged ends and negative electrically charged ends. The very small size (0.96 nm) of the nanoparticles allows them to reach all cells in every organ. By stabilizing antimicrobials, AMS reduces the rate at which the body metabolizes them so that they remain at high concentrations for extended periods. When drugs remain at high concentrations for longer periods, their efficacies improve. Again, nanoparticles enhance the delivery of medicines to effect targets. Both remaining at high concentrations for longer periods and better delivery to effect targets improve efficacy and make lower doses achieve desired effects so that side effects of medicines are reduced to allow the immunity of patients to be enhanced. Silicates also enhance the immune responses of treated patients. Improving antimicrobial efficacies and enhancing patients` immunity terminate infections so that none remains that could develop resistance. Some countries do not have natural deposits of AMS, but they may have Aluminum silicate (AS: Al₄ (SiO₄)₃) and Magnesium silicate (MS: Mg₂SiO₄), which are also approved medicines. So, AS and MS were used to formulate an AMS-brand, named Medicinal synthetic AMS {Al₄ (SiO₄)₃ + 3Mg₂SiO₄ → 2Al₂Mg₃ (SiO₄)₃}. To overcome the challenge of AMS, AS, and MS being un-absorbable, Dextrose monohydrate is incorporated in MSAMS-formulations for the simple sugar to convey the electrically charged nanoparticles into blood circulation by the principle of active transport so that MSAMS-antimicrobial formulations function systemically. In vitro, MSAMS reduced (P≤0.05) titers of viruses, including Avian influenza virus and HIV. When used to treat virus-infected animals, it cured Newcastle disease and Infectious bursa disease of chickens, Parvovirus disease of dogs, and Peste des petits ruminants disease of sheep and goats. A number of HIV/AIDS patients treated with it have been reported to become HIV-negative (antibody and antigen). COVID-19 patients are also reported to recover and test virus negative when treated with MSAMS. PSA titers of prostate cancer/enlargement patients normalize (≤4) following treatment with MSAMS. MSAMS has also potentiated ampicillin trihydrate, sulfadimidin, cotrimoxazole, piparazine citrate and chloroquine phosphate to achieve ≥ 95 % infection-load reductions (AMR-prevention). At 75 % of doses of ampicillin, cotrimoxazole, and streptomycin, supporting MSAMS-formulations' treatments with antioxidants led to the termination of even already resistant infections.

Keywords: electrical charges, viruses, abnormal cells, aluminum-magnesium silicate

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Authors: E. V. Fakhrutdinova, K. R. Maksimova, P. B. Chursin

Abstract:

At the present stage of the society progress the health care is an integral part of both the economic system and social, while in the second case the medicine is a major component of a number of basic and necessary social programs. Since the foundation of the health system are highly qualified health professionals, it is logical proposition that increase of doctor`s professionalism improves the effectiveness of the system as a whole. Professionalism of the doctor is a collection of many components, essential role played by such personal-psychological factors as honesty, willingness and desire to help people, and motivation. A number of researchers consider motivation as an expression of basic human needs that have passed through the “filter” which is a worldview and values learned in the process of socialization by the individual, to commit certain actions designed to achieve the expected result. From this point of view a number of researchers propose the following classification of highly skilled employee’s needs: 1. the need for confirmation the competence (setting goals that meet the professionalism and receipt of positive emotions in their decision), 2. The need for independence (the ability to make their own choices in contentious situations arising in the process carry out specialist functions), 3. The need for ownership (in the case of health care workers, to the profession and accordingly, high in the eyes of the public status of the doctor). Nevertheless, it is important to understand that in a market economy a significant motivator for physicians (both legal and natural persons) is to maximize its own profits. In the case of health professionals duality motivational structure creates an additional contrast, as in the public mind the image of the ideal physician; usually a altruistically minded person thinking is not primarily about their own benefit, and to assist others. In this context, the question of the real motivation of health workers deserves special attention. The survey conducted by the American researcher Harrison Terni for the magazine "Med Tech" in 2010 revealed the opinion of more than 200 medical students starting courses, and the primary motivation in a profession choice is "desire to help people", only 15% said that they want become a doctor, "to earn a lot". From the point of view of most of the classical theories of motivation this trend can be called positive, as intangible incentives are more effective. However, it is likely that over time the opinion of the respondents may change in the direction of mercantile motives. Thus, it is logical to assume that well-designed system of motivation of doctor`s labor should be based on motivational foundations laid during training in higher education.

Keywords: motivation, quality of working life, health system, personal-psychological factors, motivational structure

Procedia PDF Downloads 336

Authors: Cao Bin, Yuan Yi, Wang Qiang, Amor Abdelkader, Ali Reza Kamali, Diogo Montalvão

Abstract:

The study of the electrodynamic behavior of non-ferrous particles in time-varying magnetic fields is a promising area of research with wide applications, including recycling of non-ferrous metals, mechanical transmission, and space debris. The key technology for recovering non-ferrous metals is eddy current separation (ECS), which utilizes the eddy current force and torque to separate non-ferrous metals. ECS has several advantages, such as low energy consumption, large processing capacity, and no secondary pollution, making it suitable for processing various mixtures like electronic scrap, auto shredder residue, aluminum scrap, and incineration bottom ash. Improving the separation efficiency of mixtures with different particle sizes in ECS can create significant social and economic benefits. Our previous study investigated the influence of particle size on separation efficiency by combining numerical simulations and separation experiments. Pearson correlation analysis found a strong correlation between the eddy current force in simulations and the repulsion distance in experiments, which confirmed the effectiveness of our simulation model. The interaction effects between particle size and material type, rotational speed, and magnetic pole arrangement were examined. It offer valuable insights for the design and optimization of eddy current separators. The underlying mechanism behind the effect of particle size on separation efficiency was discovered by analyzing eddy current and field gradient. The results showed that the magnitude and distribution heterogeneity of eddy current and magnetic field gradient increased with particle size in eddy current separation. Based on this, we further found that increasing the curvature of magnetic field lines within particles could also increase the eddy current force, providing a optimized method to improving the separation efficiency of fine particles. By combining the results of the studies, a more systematic and comprehensive set of optimization guidelines can be proposed for mixtures with different particle size ranges. The separation efficiency of fine particles could be improved by increasing the rotational speed, curvature of magnetic field lines, and electrical conductivity/density of materials, as well as utilizing the eddy current torque. When designing an ECS, the particle size range of the target mixture should be investigated in advance, and the suitable parameters for separating the mixture can be fixed accordingly. In summary, these results can guide the design and optimization of ECS, and also expand the application areas for ECS.

Keywords: eddy current separation, particle size, numerical simulation, metal recovery

Procedia PDF Downloads 52

Authors: A. N. Kurbanova, G. K. Sugurbekova, N. K. Akhmetov

Abstract:

The asphaltenes are heavy fraction of crude oil. Asphaltenes on oilfield is known for its ability to plug wells, surface equipment and pores of the geologic formations. The present research is devoted to the deasphalting of crude oil as the initial stage refining oil. Solvent deasphalting was conducted by extraction with organic solvents (cyclohexane, carbon tetrachloride, chloroform). Analysis of availability of metals was conducted by ICP-MS and spectral feature at deasphalting was achieved by FTIR. High contents of asphaltenes in crude oil reduce the efficiency of refining processes. Moreover, high distribution heteroatoms (e.g., S, N) were also suggested in asphaltenes cause some problems: environmental pollution, corrosion and poisoning of the catalyst. The main objective of this work is to study the effect of deasphalting process crude oil to improve its properties and improving the efficiency of recycling processes. Experiments of solvent extraction are using organic solvents held in the crude oil JSC “Pavlodar Oil Chemistry Refinery. Experimental results show that deasphalting process also leads to decrease Ni, V in the composition of the oil. One solution to the problem of cleaning oils from metals, hydrogen sulfide and mercaptan is absorption with chemical reagents directly in oil residue and production due to the fact that asphalt and resinous substance degrade operational properties of oils and reduce the effectiveness of selective refining of oils. Deasphalting of crude oil is necessary to separate the light fraction from heavy metallic asphaltenes part of crude oil. For this oil is pretreated deasphalting, because asphaltenes tend to form coke or consume large quantities of hydrogen. Removing asphaltenes leads to partly demetallization, i.e. for removal of asphaltenes V/Ni and organic compounds with heteroatoms. Intramolecular complexes are relatively well researched on the example of porphyinous complex (VO2) and nickel (Ni). As a result of studies of V/Ni by ICP MS method were determined the effect of different solvents-deasphalting – on the process of extracting metals on deasphalting stage and select the best organic solvent. Thus, as the best DAO proved cyclohexane (C6H12), which as a result of ICP MS retrieves V-51.2%, Ni-66.4%? Also in this paper presents the results of a study of physical and chemical properties and spectral characteristics of oil on FTIR with a view to establishing its hydrocarbon composition. Obtained by using IR-spectroscopy method information about the specifics of the whole oil give provisional physical, chemical characteristics. They can be useful in the consideration of issues of origin and geochemical conditions of accumulation of oil, as well as some technological challenges. Systematic analysis carried out in this study; improve our understanding of the stability mechanism of asphaltenes. The role of deasphalted crude oil fractions on the stability asphaltene is described.

Keywords: asphaltenes, deasphalting, extraction, vanadium, nickel, metalloporphyrins, ICP-MS, IR spectroscopy

Procedia PDF Downloads 220