Search results for: IVF techniques evolution

Authors: Rithika Sriram, Kiran M. Bhojwani

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Introduction : Tuberculosis of the head and neck has proved to be a diagnostic challenge for otorhinolarynologists around the world. These lesions are often misdiagnosed as cancer. So in order to contribute to a better understanding of these lesions, we have conducted our study among patients affected by TB in the head and neck region with the objective of assessing the various manifestations, presentations, diagnostic techniques, risk factors such as smoking and alcohol consumption, coexisting illnesses and treatment modalities. Materials and Methods: This was a retrospective study conducted over a three year period (2012-2014) in 2 hospitals affliated to Kasturba Medical College in Mangalore, South India. A semi structured proforma was used to capture information from the medical records pertaining to the various objectives of the study such as clinical features and history of smoking. Data was analysed using SPSS version 16.0 and results obtained were depicted as percentages. Chi square test was used to find association between the variables and p<0.05 was considered statistically significant. Results: 104 patients were found to have TB of the head and neck and among them,the most common manifestation was found to be Tubercular Lymphadenitis (86.53%), followed by laryngeal TB (4.8%), submandibular gland TB (3.8%), deep neck space abscess(3.8%) and adenotonsillar TB. FNAC was found to be the gold standard for the diagnosis of TB disease of the lymph node.26% of the patients had coexisting HIV infection and 16.3% of the patients had associated pulmonary TB. More than 20% of the patients were smokers. Most patients were treated using ATT. Conclusion: Tuberculosis affecting regions of head and neck is no longer uncommon. Sufficient knowledge and appropriate diagnostic means is required while dealing with these lesions and must be included in the differential diagnosis of pathological lesions of head and neck.

Keywords: FNAC, Mangalore, smoking, tuberculosis

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Authors: Hadjer Didouh, Izzaddine Sameut Bouhaik, Mohammed Hadj Meliani

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This research delves into the intricate dynamics of biofilm adhesion on surfaces, particularly focusing on the widely employed X52 surface in oil and gas industry pipelines. Biofilms, characterized by microorganisms within a self-produced matrix, pose significant challenges due to their detrimental impact on surfaces. Our study integrates advanced molecular techniques and cutting-edge microscopy, such as scanning electron microscopy (SEM), to identify microbial communities and visually assess biofilm adhesion. Simultaneously, we concentrate on the X52 surface, utilizing impedance spectroscopy and potentiodynamic polarization to gather electrochemical responses under various conditions. In conjunction with the broader investigation, we propose a novel approach to mitigate biofilm-induced corrosion challenges. This involves environmentally friendly inhibitors derived from plants, offering a sustainable alternative to conventional chemical treatments. Our inquiry screens and selects inhibitors based on their efficacy in hindering biofilm formation and reducing corrosion rates on the X52 surface. This study contributes valuable insights into the interplay between electrochemical processes and biofilm attachment on the X52 surface. Furthermore, the outcomes of this research have broader implications for the oil and gas industry, where biofilm-related corrosion is a persistent concern. The exploration of eco-friendly inhibitors not only holds promise for corrosion control but also aligns with environmental considerations and sustainability goals. The comprehensive nature of this research aims to enhance our understanding of biofilm dynamics, provide effective strategies for corrosion mitigation, and contribute to sustainable practices in pipeline management within the oil and gas sector.

Keywords: bio-corrosion, biofilm, attachment, X52, metal/bacteria interface

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Authors: Muhammad Adeel Arshad, Faiz-Ul Hassan, Yanfen Cheng

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According to FAO, enteric methane (CH4) production is about 44% of all greenhouse gas emissions from the livestock sector. Ruminants produce CH4 as a result of fermentation of feed in the rumen especially from roughages which yield more CH4 per unit of biomass ingested as compared to concentrates. Efficient ruminal fermentation is not possible without abating CO2 and CH4. Methane abatement strategies are required to curb the predicted rise in emissions associated with greater ruminant production in future to meet ever increasing animal protein requirements. Ecology of ruminal methanogenesis and avenues for its mitigation can be identified through various genomic and transcriptomic techniques. Programs such as Hungate1000 and the Global Rumen Census have been launched to enhance our understanding about global ruminal microbial communities. Through Hungate1000 project, a comprehensive reference set of rumen microbial genome sequences has been developed from cultivated rumen bacteria and methanogenic archaea along with representative rumen anaerobic fungi and ciliate protozoa cultures. But still many species of rumen microbes are underrepresented especially uncultivable microbes. Lack of sequence information specific to the rumen's microbial community has inhibited efforts to use genomic data to identify specific set of species and their target genes involved in methanogenesis. Metagenomic and metatranscriptomic study of entire microbial rumen populations offer new perspectives to understand interaction of methanogens with other rumen microbes and their potential association with total gas and methane production. Deep understanding of methanogenic pathway will help to devise potentially effective strategies to abate methane production while increasing feed efficiency in ruminants.

Keywords: Genome sequences, Hungate1000, methanogens, ruminal fermentation

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Authors: Hadas Sopher, Davide Schaumann, Yehuda E. Kalay

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This paper addresses the shortcomings of architectural computation tools in representing human behavior in built environments, prior to construction and occupancy of those environments. Evaluating whether a design fits the needs of its future users is currently done solely post construction, or is based on the knowledge and intuition of the designer. This issue is of high importance when designing complex buildings such as hospitals, where the quality of treatment as well as patient and staff satisfaction are of major concern. Existing computational pre-occupancy human behavior evaluation methods are geared mainly to test ergonomic issues, such as wheelchair accessibility, emergency egress, etc. As such, they rely on Agent Based Modeling (ABM) techniques, which emphasize the individual user. Yet we know that most human activities are social, and involve a number of actors working together, which ABM methods cannot handle. Therefore, we present an event-based model that manages the interaction between multiple Actors, Spaces, and Activities, to describe dynamically how people use spaces. This approach requires expanding the computational representation of Actors beyond their physical description, to include psychological, social, cultural, and other parameters. The model presented in this paper includes cognitive abilities and rules that describe the response of actors to their physical and social surroundings, based on the actors’ internal status. The model has been applied in a simulation of hospital wards, and showed adaptability to a wide variety of situated behaviors and interactions.

Keywords: agent based modeling, architectural design evaluation, event modeling, human behavior simulation, spatial cognition

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Authors: Habte Tadesse Likassa, Bacha Edosa

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Customer’s satisfaction was very important thing that is required for the existence of banks to be more productive and success in any organization and business area. The main goal of the study is assessing and identifying factors that influence customer’s satisfaction in West Shoa Zone of Commercial Bank of Ethiopia (Holeta, Ginchi, Ambo, Gedo and Bako). Stratified random sampling procedure was used in the study and by using simple random sampling (lottery method) 520 customers were drawn from the target population. By using Probability Proportional Size Techniques sample size for each branch of banks were allocated. Both descriptive and inferential statistics methods were used in the study. A binary logistic regression model was fitted to see the significance of factors affecting customer’s satisfaction in this study. SPSS statistical package was used for data analysis. The result of the study reveals that the overall level of customer’s satisfaction in the study area is low (38.85%) as compared those who were not satisfied (61.15%). The result of study showed that all most all factors included in the study were significantly associated with customer’s satisfaction. Therefore, it can be concluded that based on the comparison of branches on their customers satisfaction by using odd ratio customers who were using Ambo and Bako are less satisfied as compared to customers who were in Holeta branch. Additionally, customers who were in Ginchi and Gedo were more satisfied than that of customers who were in Holeta. Since the level of customers satisfaction was low in the study area, it is more advisable and recommended for concerned body works cooperatively more in maximizing satisfaction of their customers.

Keywords: customers, satisfaction, binary logistic, complain handling process, waiting time

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Authors: Sandeep Kaushal

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Tetracycline (TC) is a widespread antibiotic that is utilised in a multitude of countries, particularly China, India, and the United States of America, due to its low cost and potency in boosting livestock production. Unfortunately, certain antibiotics can be hazardous to living beings due to metal complexation and aggregation, which can lead to teratogenicity and carcinogenicity. Heterojunction photocatalysts are promising for the effective removal of pollutants like antibiotics. Herein, a simple, economical, and pollution-less hydrothermal technique was used to construct SnO₂/MnV₂O₆heterojunction with varying amounts of tin dioxide (SO₂). Various sophisticated techniques like XRD, FTIR, XPS, FESEM, HRTEM, and PLand Raman spectroscopy demonstrated the successful synthesis of SnO₂/MnV₂O₆ heterojunction photocatalysts.BET surface area analysis revealed that the as-synthesized heterojunction has a favorable surface area and surface properties for efficacious degradation of tetracycline. Under the direct sunlight exposure, the SnO₂/MnV₂O₆ heterojunction possessed superior photodegradation activity toward TC than the pristine SnO₂ and MnV2O6owing to their excellent adsorption abilities suitable band positions, large surface areas along with the effective charge-transfer ability of the heterojunction. The SnO₂/MnV₂O₆ heterojunction possessed extraordinary efficiency for the photocatalytic degradation of TC antibiotic (98% in 60 min) with an apparent rate constant of 0.092 min–1. In the degradation experiments, photocatalytic activities of as-synthesized heterojunction were studied by varying different factors such as time contact, catalyst dose, and solution pH. The role of reactive species in antibiotics was validated by radical scavenging studies, which indicated that.OH, radical has a critical role in photocatalytic degradation. Moreover, liquid chromatography-mass spectrometry (LC-MS) investigations were employed to anticipate a plausible mechanism for TC degradation.

Keywords: photocatalytic degradation, tetracycline, heterojunction, LC-MS

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Authors: Vinh Duy Cao, Shima Pilehvar, Anna M. Szczotok, Anna-Lena Kjøniksen

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The total energy consumption is dramatically increasing on over the world, especially for building energy consumption where a significant proportion of energy is used for heating and cooling purposes. One of the solutions to reduce the energy consumption for the building is to improve construction techniques and enhance material technology. Recently, microcapsulated phase change materials (MPCM) with high energy storage capacity within the phase transition temperature of the materials is a potential method to conserve and save energy. A new composite materials with high energy storage capacity by mixing MPCM into concrete for passive building technology is the promising candidate to reduce the energy consumption. One of the most untilized building materials for mixing with MPCM is Portland cement concrete. However, the emission of carbon dioxide (CO2) due to producing cement which plays the important role in the global warming is the main drawback of PCC. Accordingly, an environmentally friendly building material, geopolymer, which is synthesized by the reaction between the industrial waste material (aluminosilicate) and a strong alkali activator, is a potential materials to mixing with MPCM. Especially, the effect of MPCM on the thermal and mechanical properties of geopolymer concrete (GPC) is very limited. In this study, high thermal energy storage capacity materials were fabricated by mixing MPCM into geopolymer concrete. This article would investigate the effect of MPCM concentration on thermal and mechanical properties of GPC. The target is to balance the effect of MPCM on improving the thermal performance and maintaining the compressive strength of the geopolymer concrete at an acceptable level for building application.

Keywords: microencapsulated phase change materials, geopolymer concrete, energy storage capacity, thermal performance

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Authors: Lavanya Annadi, Fahimeh Jafari

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Transportation brings immense benefits to society, but it also has its costs. Costs include such as the cost of infrastructure, personnel and equipment, but also the loss of life and property in traffic accidents on the road, delays in travel due to traffic congestion and various indirect costs in terms of air transport. More research has been done to identify the various factors that affect road accidents, such as road infrastructure, traffic, sociodemographic characteristics, land use, and the environment. The aim of this research is to predict the probabilistic crash prediction of vehicles using machine learning due to natural and structural reasons by excluding spontaneous reasons like overspeeding etc., in the United States. These factors range from weather factors, like weather conditions, precipitation, visibility, wind speed, wind direction, temperature, pressure, and humidity to human made structures like road structure factors like bump, roundabout, no exit, turning loop, give away, etc. Probabilities are dissected into ten different classes. All the predictions are based on multiclass classification techniques, which are supervised learning. This study considers all crashes that happened in all states collected by the US government. To calculate the probability, multinomial expected value was used and assigned a classification label as the crash probability. We applied three different classification models, including multiclass Logistic Regression, Random Forest and XGBoost. The numerical results show that XGBoost achieved a 75.2% accuracy rate which indicates the part that is being played by natural and structural reasons for the crash. The paper has provided in-deep insights through exploratory data analysis.

Keywords: road safety, crash prediction, exploratory analysis, machine learning

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Authors: Andy Zhang, Awnik Roy, Trevor B. Chen, Bibik Oleksandar, Subodh Adhikari, Paul S. Hsu

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The durability of a combustor in gas-turbine engines is a strong function of its component temperatures and requires good control of these temperatures. Since the temperature of combustion gases frequently exceeds the melting point of the combustion liner walls, an efficient air-cooling system with optimized flow rates of cooling air is significantly important to elongate the lifetime of liner walls. To determine the effectiveness of the air-cooling system, accurate two-dimensional (2D) surface temperature measurement of combustor liner walls is crucial for advanced engine development. Traditional diagnostic techniques for temperature measurement in this application include the rmocouples, thermal wall paints, pyrometry, and phosphors. They have shown some disadvantages, including being intrusive and affecting local flame/flow dynamics, potential flame quenching, and physical damages to instrumentation due to harsh environments inside the combustor and strong optical interference from strong combustion emission in UV-Mid IR wavelength. To overcome these drawbacks, a compact and small borescope long-wave-infrared (LWIR) sensor is developed to achieve 2D high-spatial resolution, high-fidelity thermal imaging of 2D surface temperature in gas-turbine engines, providing the desired engine component temperature distribution. The compactLWIRborescope sensor makes it feasible to promote the durability of a combustor in gas-turbine engines and, furthermore, to develop more advanced gas-turbine engines.

Keywords: borescope, engine, low-wave-infrared, sensor

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Authors: Madikeri Rohit

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As energy efficiency is the key concern in many aircraft manufacturing companies regenerative braking is a technique using which energy lost due to friction while braking can be regained. In the operation of an aircraft, significant energy is lost during deceleration or braking which occurs during its landing phase. This problem can be overcome using Regenerative Breaking System (RBS) in landing gear. The major problem faced is regarding the batteries and the overall efficiency gained in competence with the added weight. As the amount of energy required to store is huge we need batteries with high capacity for storage. Another obstacle by using high capacity batteries is the added weight which undermines the efficiency obtained using RBS. An approach to this problem is to either use the obtained energy immediately without storage or to store in other forms such as mechanical, pneumatic and hydraulic. Problem faced with mechanical systems is the weight of the flywheel needed to obtain required efficiency. Pneumatic and hydraulic systems are a better option at present. Using hydraulic systems for storing energy is efficient as it integrates into the overall hydraulic system present in the aircraft. Another obstacle is faced with the redundancy of this system. Conventional braking must be used along with RBS in order to provide redundancy. Major benefits obtained using RBS is with the help of the energy obtained during landing which can be used of engine less taxing. This reduces fuel consumption as well as noise and air pollution. Another added benefit of using RBS is to provide electrical supply to lighting systems, cabin pressurization system and can be used for emergency power supply in case of electric failure. This paper discusses about using RBS in landing gear, problems, prospects and new techniques being pursued to improve RBS.

Keywords: regenerative braking, types of energy conversion, landing gear, energy storage

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Authors: Young Nam Chun, Mun Sup Lim, Byeo Ri Jeong

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Sewage sludge is regarded as the residue produced by the waste water treatment process, during which liquids and solids are being separated. Thermal treatments are interesting techniques to stabilize the sewage sludge for disposal. Among the thermal treatments, pyrolysis and/or gasification has been being applied to the sewage sludge. The final goal of our NRF research is to develop a microwave In-line Drying-Pyrolysis-Gasification (IDPG) technology for the dewatered sewage sludge for the bio-waste to energy conversion. As a first step, the pyrolysis characteristics in a bench scale electric furnace was investigated at 800℃ for the dewatered sludge and dried sludge samples of which moisture contents are almost 80% and 0%, respectively. Main components of producer gas are hydrogen and carbon dioxide. Particularly, higher hydrogen for the dewatered sludge is shown as 75%. The hydrogen production for the dewatered sludge and dried sludge are 56% and 32%, respectively. However, the pyrolysis for the dried sludge produces higher carbon dioxide and other gases, while higher methane and carbon dioxide are given to 74% and 53%, respectively. Tar also generates during the pyrolysis process, showing lower value for case of the dewatered sludge. Gravimetric tar is 195 g/m3, and selected light tar like benzene, naphthalene, anthracene, pyrene are 9.4 g/m3, 2.1 g/m3, 0.5 g/m3, 0.3 g/m3, respectively. After the pyrolysis process, residual char for the dewatered sludge and dried sludge remain 1g and 1.3g, showing weight reduction rate of 93% and 57%, respectively. Through the results, this could be known that the dewatered sludge can be used to produce a clean hydrogen-rich gas fuel without the drying process. Therefore, the IDPG technology can be applied effectively to the energy conversion for dewater sludge waste without a drying pretreatment. Acknowledgment: This work was supported by the National Research Foundation of Korea(NRF) grant funded by the Korea government(MSIP) (No. 2015R1A2A2A03003044).

Keywords: pyrolysis, gasification, sewage sludge, tar generation, producer gas, sludge char, biomass energy

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Authors: Hamdi Beji, Toufik Kanit, Tanguy Messager

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This study aims to construct a predictive model proficient in foreseeing the linear elastic and thermal characteristics of composite materials, drawing on a multitude of influencing parameters. These parameters encompass the shape of inclusions (circular, elliptical, square, triangle), their spatial coordinates within the matrix, orientation, volume fraction (ranging from 0.05 to 0.4), and variations in contrast (spanning from 10 to 200). A variety of machine learning techniques are deployed, including decision trees, random forests, support vector machines, k-nearest neighbors, and an artificial neural network (ANN), to facilitate this predictive model. Moreover, this research goes beyond the predictive aspect by delving into an inverse analysis using genetic algorithms. The intent is to unveil the intrinsic characteristics of composite materials by evaluating their thermomechanical responses. The foundation of this research lies in the establishment of a comprehensive database that accounts for the array of input parameters mentioned earlier. This database, enriched with this diversity of input variables, serves as a bedrock for the creation of machine learning and genetic algorithm-based models. These models are meticulously trained to not only predict but also elucidate the mechanical and thermal conduct of composite materials. Remarkably, the coupling of machine learning and genetic algorithms has proven highly effective, yielding predictions with remarkable accuracy, boasting scores ranging between 0.97 and 0.99. This achievement marks a significant breakthrough, demonstrating the potential of this innovative approach in the field of materials engineering.

Keywords: machine learning, composite materials, genetic algorithms, mechanical and thermal proprieties

Procedia PDF Downloads 44

Authors: Shady S. Hassan, Brijesh K. Tiwari, Gwilym A. Williams, Amit K. Jaiswal

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EU is known as the destination with the highest rate of the coffee consumption per capita in the world. Spent coffee grounds (SCG) are the main by-product of coffee brewing. SCG is either disposed as a solid waste or employed as compost, although the polysaccharides from such lignocellulosic biomass might be used as feedstock for fermentation processes. However, SCG as a lignocellulose have a complex structure and pretreatment process is required to facilitate an efficient enzymatic hydrolysis of carbohydrates. However, commonly used pretreatment methods, such as chemical, physico-chemical and biological techniques are still insufficient to meet optimal industrial production requirements in a sustainable way. Ultrasound is a promising candidate as a sustainable green pretreatment solution for lignocellulosic biomass utilization in a large scale biorefinery. Thus, ultrasound pretreatment of SCG without adding harsh chemicals investigated as a green technology to enhance enzyme hydrolysis. In the present work, ultrasound pretreatment experiments were conducted on SCG using different ultrasound frequencies (25, 35, 45, 130, and 950 kHz) for 60 min. Regardless of ultrasound power, low ultrasound frequency is more effective than high ultrasound frequency in pretreatment of biomass. Ultrasound pretreatment of SCG (at ultrasound frequency of 25 kHz for 60 min) followed by enzymatic hydrolysis resulted in total reducing sugars of 56.1 ± 2.8 mg/g of biomass. Fourier transform Infrared Spectroscopy (FTIR) was employed to investigate changes in functional groups of biomass after pretreatment, while high-performance liquid chromatography (HPLC) was employed for determination of glucose. Pretreatment of lignocellulose by low frequency ultrasound in water only was found to be an effective green approach for SCG to improve saccharification and glucose yield compared to native biomass. Pretreatment conditions will be optimized, and the enzyme hydrolysate will be used as media component substitute for the production of ethanol.

Keywords: lignocellulose, ultrasound, pretreatment, spent coffee grounds

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Authors: Reine Suci Wulandari, Rosa Suryantini

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Albizia (Paraserianthes falcataria) is a woody plant species that has a high economic value and multifunctional. Albizia is important timber, medicinal plants and can also be used as a plant to rehabilitate critical lands. The demand value of Albizia is increased so that the large quantities and high quality of seeds are required. In vitro propagation techniques are seed propagation that can produce more seeds and quality in a short time. In vitro cultures require growth regulators that can be obtained from biological agents such as endophytic fungi. Endophytic fungi are micro fungi that colonize live plant tissue without producing symptoms or other negative effects on host plants and increase plant growth. The purposes of this research were to isolate and identify endophytic fungi isolated from the root of Albizia and to study the effect of endophytic fungus on the growth of Albizia in vitro. The methods were root isolation, endophytic fungal identification, and inoculation of endophytic fungi to Albizia plants in vitro. Endophytic fungus isolates were grown on PDA media before being inoculated with Albizia sprouts. Incubation is done for 4 (four) weeks. The observed growth parameters were live explant percentage, percentage of explant shoot, and percentage of explant rooted. The results of the research showed that 6 (six) endophytic fungal isolates obtained from the root of Albizia, namely Aspergillus sp., Verticillium sp, Penicillium sp., Trichoderma sp., Fusarium sp., and Acremonium sp. Statistical analysis found that Trichoderma sp. and Fusarium sp. affect in vitro growth of Albizia. Endophytic fungi from the results of this research were potential as plant growth promoting. It can be applied to increase productivity either through increased plant growth and increased endurance of Albizia seedlings to pests and diseases.

Keywords: Albizia, endophytic fungi, propagation, in vitro

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Authors: A. A. Sadia, A. Emdad, E. Hossain

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The increasing importance of mushrooms as a source of nutrition, health benefits, and even potential cancer treatment has raised awareness of the impact of climate-sensitive variables on their cultivation. Factors like temperature, relative humidity, air quality, and substrate composition play pivotal roles in shaping mushroom growth, especially in Bangladesh. Oyster mushrooms, a commonly cultivated variety in this region, are particularly vulnerable to climate fluctuations. This research explores the climatic dynamics affecting oyster mushroom cultivation and, presents an approach to address these challenges and provides tangible solutions to fortify the agro-economy, ensure food security, and promote the sustainability of this crucial food source. Using climate and production data, this study evaluates the performance of three clustering algorithms -KMeans, OPTICS, and BIRCH- based on various quality metrics. While each algorithm demonstrates specific strengths, the findings provide insights into their effectiveness for this specific dataset. The results yield essential information, pinpointing the optimal temperature range of 13°C-22°C, the unfavorable temperature threshold of 28°C and above, and the ideal relative humidity range of 75-85% with the suitable production regions in three different seasons: Kharif-1, 2, and Robi. Additionally, a user-friendly web application is developed to support mushroom farmers in making well-informed decisions about their cultivation practices. This platform offers valuable insights into the most advantageous periods for oyster mushroom farming, with the overarching goal of enhancing the efficiency and profitability of mushroom farming.

Keywords: climate variability, mushroom cultivation, clustering techniques, food security, sustainability, web-application

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Authors: Aliyu Damri

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In every educational institution, students of mass communication receive training to report events and issues accurately and objectively in accordance with official controls. However, the complex nature of society today made it possible to use WhatsApp platform that revolutionizes the means of sharing information, ideas, and experiences. This paper examined how students in the Department of Mass Communication, Abdu Gusau Polytechnic, Talata Mafara used WhatsApp platform in spreading fake news. It used in depth interview techniques and focus group discussion with students as well as the use of published materials to gather related and relevant data. Also, the paper used procedures involved to analyze long interview content. This procedure includes observation of a useful utterance, development of expanded observation, examination of interconnection of observed comments, collective scrutiny of observation for patterns and themes, and review and analysis of the themes across all interviews for development of thesis. The result indicated that inadequate and absent of official controls guiding the conduct of online information sharing, inaccuracies and poor source verification, lack of gate keeping procedures to ensure ethical and legal provisions, bringing users into the process, sharing all information, availability of misinformation, disinformation and rumor and problem of conversation strongly encouraged the emergence of fake news. Surprisingly, the idea of information as a commodity has increased, and transparency of a source as new ethics emerged.

Keywords: disinformation, fake news, group, mass communication, misinformation, WhatsApp

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Authors: Vânia Graça, Paula Quadros-Flores, Altina Ramos

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The use of Digital Technologies in teaching and learning processes is currently a reality, namely in initial teacher training. This study aims at knowing the digital reality of students in initial teacher training in order to improve training in the educational use of ICT and to promote digital technology integration strategies in an educational context. It is part of the IFITIC Project "Innovate with ICT in Initial Teacher Training to Promote Methodological Renewal in Pre-school Education and in the 1st and 2nd Basic Education Cycle" which involves the School of Education, Polytechnic of Porto and Institute of Education, University of Minho. The Project aims at rethinking educational practice with ICT in the initial training of future teachers in order to promote methodological innovation in Pre-school Education and in the 1st and 2nd Cycles of Basic Education. A qualitative methodology was used, in which a questionnaire survey was applied to teachers in initial training. For data analysis, the techniques of content analysis with the support of NVivo software were used. The results point to the following aspects: a) future teachers recognize that they have more technical knowledge about ICT than pedagogical knowledge. This result makes sense if we consider the objective of Basic Education, so that the gaps can be filled in the Master's Course by students who wish to follow the teaching; b) the respondents are aware that the integration of digital resources contributes positively to students' learning and to the life of children and young people, which also promotes preparation in life; c) to be a teacher in the digital age there is a need for the development of digital literacy, lifelong learning and the adoption of new ways of teaching how to learn. Thus, this study aims to contribute to a reflection on the teaching profession in the digital age.

Keywords: digital technologies, initial teacher training, pedagogical use of ICT, skills

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Authors: S. I. Usenko, V. N. Golubeva, I. A. Konopkina, I. V. Astakhova, O. V. Vakhnina, A. A. Korableva, A. A. Kalinina, K. B. Zhogova

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Gold can be determined in natural objects and manufactured articles of different origin. The up-to-date status of research and problems of high gold level determination in alloys and manufactured articles are described in detail in the literature. No less important is the task of this metal determination in minerals, process products and waste pieces. The latters, as objects of gold content chemical analysis, are most hard-to-study for two reasons: Because of high requirements to accuracy of analysis results and because of difference in chemical and phase composition. As a rule, such objects are characterized by compound, variable and very often unknown matrix composition that leads to unpredictable and uncontrolled effect on accuracy and other analytical characteristics of analysis technique. In this paper, the methods for the determination of gold are described, using flame atomic-absorption spectrophotometry and gravimetric analysis technique. The techniques are aimed at gold determination in a solution for gold etching (KJ+J2), in the technological mixture formed after cleaning stainless steel members of vacuum-deposit installation with concentrated nitric and hydrochloric acids as well as in gold-containing powder resulted from liquid wastes reprocessing. Optimal conditions for sample preparation and analysis of liquid and solid waste specimens of compound and variable matrix composition were chosen. The boundaries of relative resultant error were determined for the methods within the range of gold mass concentration from 0.1 to 30g/dm3 in the specimens of liquid wastes and mass fractions from 3 to 80% in the specimens of solid wastes.

Keywords: microelectronics waste pieces, gold, sample preparation, atomic-absorption spectrophotometry, gravimetric analysis technique

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Authors: Nompumelelo P. Mathebula, Roger A. Sheldon, Daniel P. Pienaar, Moira L. Bode

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The preparation of enantiopure Morita-Baylis-Hillman (MBH) adducts remains a challenge in organic chemistry. MBH adducts are highly functionalised compounds which act as key intermediates in the preparation of compounds of medicinal importance. MBH adducts are prepared in racemic form by reacting various aldehydes and activated alkenes in the presence of DABCO. Enantiopure MBH adducts can be obtained by employing Enzymatic kinetic resolution (EKR). This technique has been successfully demonstrated in our group, amongst others, using lipases in either hydrolysis or transesterification reactions. As these methods only allow 50% of each enantiomer to be obtained, our interest grew in exploring other enzymatic methods for the synthesis of enantiopure MBH adducts where, theoretically, 100% of the desired enantiomer could be obtained.Dehydrogenase enzymes can be employed on prochiral substrates to obtain optically pure compounds by reducing carbon-carbon double bonds or carbonyl groups of ketones. Ketoreductases have been used historically to obtain enantiopure secondary alcohols on an industrial scale. Ketoreductases are NAD(P)H-dependent enzymes and thus require nicotinamide as a cofactor. This project focuses on employing ketoreductase enzymes to selectively reduce ketones derived from Morita-Baylis-Hillman (MBH) adducts in order to obtain these adducts in enantiopure form.Results obtained from this study will be reported. Good enantioselectivity was observed using a range of different ketoreductases, however, reactions were complicated by the formation of an unexpected by-product, which was characterised employing single crystal x-ray crystallography techniques. Methods to minimise by-product formation are currently being investigated.

Keywords: ketoreductase, morita-baylis-hillman, selective reduction, x-ray crystallography

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Authors: Morné Roman, Robert van Zyl, Nishanth Parus, Nishal Mahatho

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Leakage current monitoring for high voltage transmission line insulators is of interest as a performance indicator. Presently, to the best of our knowledge, there is no commercially available, clamp-on type, non-intrusive device for measuring leakage current on energised high voltage direct current (HVDC) transmission line insulators. The South African power utility, Eskom, is investigating the development of such a hand-held sensor for two important applications; first, for continuous real-time condition monitoring of HVDC line insulators and, second, for use by live line workers to determine if it is safe to work on energised insulators. In this paper, a DC leakage current sensor based on magnetic field sensing techniques is developed. The magnetic field sensor used in the prototype can also detect alternating current up to 5 MHz. The DC leakage current prototype detects the magnetic field associated with the current flowing on the surface of the insulator. Preliminary HVDC leakage current measurements are performed on glass insulators. The results show that the prototype can accurately measure leakage current in the specified current range of 1-200 mA. The influence of external fields from the HVDC line itself on the leakage current measurements is mitigated through a differential magnetometer sensing technique. Thus, the developed sensor can perform measurements on in-service HVDC insulators. The research contributes to the body of knowledge by providing a sensor to measure leakage current on energised HVDC insulators non-intrusively. This sensor can also be used by live line workers to inform them whether or not it is safe to perform maintenance on energized insulators.

Keywords: direct current, insulator, leakage current, live line, magnetic field, sensor, transmission lines

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Authors: Belgherbi Aicha, Bessaid Abdelhafid

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In the recent years a great deal of research work has been devoted to the development of semi-automatic and automatic techniques for the analysis of abdominal CT images. The first and fundamental step in all these studies is the semi-automatic liver and spleen segmentation that is still an open problem. In this paper, a semi-automatic liver and spleen segmentation method by the mathematical morphology based on watershed algorithm has been proposed. Our algorithm is currency in two parts. In the first, we seek to determine the region of interest by applying the morphological to extract the liver and spleen. The second step consists to improve the quality of the image gradient. In this step, we propose a method for improving the image gradient to reduce the over-segmentation problem by applying the spatial filters followed by the morphological filters. Thereafter we proceed to the segmentation of the liver, spleen. The aim of this work is to develop a method for semi-automatic segmentation liver and spleen based on watershed algorithm, improve the accuracy and the robustness of the liver and spleen segmentation and evaluate a new semi-automatic approach with the manual for liver segmentation. To validate the segmentation technique proposed, we have tested it on several images. Our segmentation approach is evaluated by comparing our results with the manual segmentation performed by an expert. The experimental results are described in the last part of this work. The system has been evaluated by computing the sensitivity and specificity between the semi-automatically segmented (liver and spleen) contour and the manually contour traced by radiological experts. Liver segmentation has achieved the sensitivity and specificity; sens Liver=96% and specif Liver=99% respectively. Spleen segmentation achieves similar, promising results sens Spleen=95% and specif Spleen=99%.

Keywords: CT images, liver and spleen segmentation, anisotropic diffusion filter, morphological filters, watershed algorithm

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Authors: Dan Yan, Yunuo Zhang, Yuhan Huang, Weijie Ouyang

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The cornea serves as a vital protective barrier for the eye; however, it is prone to injury and damage that can disrupt corneal epithelium and nerves, triggering inflammation. Therefore, understanding the biological effects and molecular mechanisms involved in corneal wound healing and identifying drugs targeting these pathways is crucial for researchers in this field. This study aimed to investigate the therapeutic potential of progranulin (PGRN) in treating corneal injuries. Our findings demonstrated that PGRN significantly enhanced corneal wound repair by accelerating corneal re-epithelialization and re-innervation. In vitro experiments with cultured epithelial cells and trigeminal ganglion cells further revealed that PGRN stimulated corneal epithelial cell proliferation and promoted axon growth in trigeminal ganglion cells. Through RNA-sequencing (RNA-seq) analysis and other experimental techniques, we discovered that PGRN exerted its healing effects by modulating the Wnt signaling pathway, which played a critical role in repairing epithelial cells and promoting axon regeneration in trigeminal neurons. Importantly, our study highlighted the anti-inflammatory properties of PGRN by inhibiting the NF-κB signaling pathway, leading to decreased infiltration of macrophages. In conclusion, our findings underscored the potential of PGRN in facilitating corneal wound healing by promoting corneal epithelial cell proliferation, trigeminal ganglion cell axon regeneration, and suppressing ocular inflammation. These results suggest that PGRN could potentially expedite the healing process and improve visual outcomes in patients with corneal injuries.

Keywords: cornea, wound healing, progranulin, corneal epithelial cells, trigeminal ganglion cells

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Authors: Henrique Fernandes, Sofia Catalucci, Richard Leach, Kapil Sugand

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Background: Holograms are 3D images formed by the interference of light beams from a laser or other coherent light source. Pepper’s ghost is a form of hologram conceptualised in the 18th century. This Holographic visualisation with metrology measuring techniques by displaying measurements taken in real-time in holographic form can assist in research and education. New structural designs such as the Plexiglass Stand and the Hologram Box can optimise the holographic experience. Method: The equipment used included: (i) Zeiss’s ATOS Core 300 optical coordinate measuring instrument that scanned real-world objects; (ii) Cloud Compare, open-source software used for point cloud processing; and (iii) Hologram Box, designed and manufactured during this research to provide the blackout environment needed to display 3D point clouds in real-time measurements in holographic format, in addition to a portability aspect to holograms. The equipment was tailored to realise the goal of displaying measurements in an innovative technique and to improve on conventional methods. Three test scans were completed before doing a holographic conversion. Results: The outcome was a precise recreation of the original object in the holographic form presented with dense point clouds and surface density features in a colour map. Conclusion: This work establishes a way to visualise data in a point cloud system. To our understanding, this is a work that has never been attempted. This achievement provides an advancement in holographic visualisation. The Hologram Box could be used as a feedback tool for measurement quality control and verification in future smart factories.

Keywords: holography, 3D scans, hologram box, metrology, point cloud

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Authors: Morteza Elsa, Amirhossein Moghanian

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The major aim of this study was to evaluate the effect of CaO content on in vitro hydroxyapatite formation, MC3T3 cells cytotoxicity and proliferation as well as antibacterial efficiency of sol-gel derived SiO₂–CaO–P₂O₅ ternary system. For this purpose, first two grades of bioactive glass (BG); BG-58s (mol%: 60%SiO₂–36%CaO–4%P₂O₅) and BG-68s (mol%: 70%SiO₂–26%CaO–4%P₂O₅)) were synthesized by sol-gel method. Second, the effect of CaO content in their composition on in vitro bioactivity was investigated by soaking the BG-58s and BG-68s powders in simulated body fluid (SBF) for time periods up to 14 days and followed by characterization inductively coupled plasma atomic emission spectrometry (ICP-AES), Fourier transform infrared spectroscopy (FTIR), X-ray diffraction (XRD), and scanning electron microscopy (SEM) techniques. Additionally, live/dead staining, 3-(4,5dimethylthiazol-2-yl)-2,5-diphenyltetrazolium bromide (MTT), and alkaline phosphatase (ALP) activity assays were conducted respectively, as qualitatively and quantitatively assess for cell viability, proliferation and differentiations of MC3T3 cells in presence of 58s and 68s BGs. Results showed that BG-58s with higher CaO content showed higher in vitro bioactivity with respect to BG-68s. Moreover, the dissolution rate was inversely proportional to oxygen density of the BG. Live/dead assay revealed that both 58s and 68s increased the mean number live cells which were in good accordance with MTT assay. Furthermore, BG-58s showed more potential antibacterial activity against methicillin-resistant Staphylococcus aureus (MRSA) bacteria. Taken together, BG-58s with enhanced MC3T3 cells proliferation and ALP activity, acceptable bioactivity and significant high antibacterial effect against MRSA bacteria is suggested as a suitable candidate in order to further functionalizing for delivery of therapeutic ions and growth factors in bone tissue engineering.

Keywords: antibacterial, bioactive glass, hydroxyapatite, proliferation, sol-gel processes

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Authors: Jacob Medupe

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Life as we know it has changed since the global outbreak of Coronavirus Disease 2019 (COVID-19) and business as usual will not continue. The human impact of the COVID-19 crisis is already immeasurable. Moreover, COVID-19 has already negatively impacted economies, livelihoods and disrupted food systems around the world. The disruptive nature of the Corona virus has affected every sphere of life including the culture and teaching and learning. Right now the majority of education research is based around classroom management techniques that are no longer necessary with digital delivery. Instead there is a great need for new data about how to make the best use of the one-on-one attention that is now becoming possible (Diamandis & Kotler, 2014). The COVID-19 pandemic has necessitated an environment where the South African learners are focused to adhere to social distancing in order to minimise the wild spread of the Corona virus. This arrangement forces the student to utilise the online classroom technologies to continue with the lessons. The historical reality is that the country has not made much strides on the closing of the digital divide and this is particularly a common status quo in the deep rural areas. This will prove to be a toll order for most of the learners affected by the Corona Virus to be able to have a seamless access to the online learning facilities. The paper will seek to look deeply into this reality and how the Corona virus has brought us to the reality that South Africa remains a deeply unequal society in every sphere of life. The study will also explore the state of readiness for education system around the online classroom environment.

Keywords: virtual learning, virtual classroom, COVID-19, Corona virus, internet connectivity, blended learning, online learning, distance education, e-learning, self-regulated Learning, pedagogy, digital literacy

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Authors: Xingyu Gao, Qiang Wu

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Patents play a crucial role in protecting innovation and intellectual property. Early prediction of the impact of artificial intelligence (AI) patents helps researchers and companies allocate resources and make better decisions. Understanding the key factors that influence patent impact can assist researchers in gaining a better understanding of the evolution of AI technology and innovation trends. Therefore, identifying highly impactful patents early and providing support for them holds immeasurable value in accelerating technological progress, reducing research and development costs, and mitigating market positioning risks. Despite the extensive research on AI patents, accurately predicting their early impact remains a challenge. Traditional methods often consider only single factors or simple combinations, failing to comprehensively and accurately reflect the actual impact of patents. This paper utilized the artificial intelligence patent database from the United States Patent and Trademark Office and the Len.org patent retrieval platform to obtain specific information on 35,708 AI patents. Using six machine learning models, namely Multiple Linear Regression, Random Forest Regression, XGBoost Regression, LightGBM Regression, Support Vector Machine Regression, and K-Nearest Neighbors Regression, and using early indicators of patents as features, the paper comprehensively predicted the impact of patents from three aspects: technical, social, and economic. These aspects include the technical leadership of patents, the number of citations they receive, and their shared value. The SHAP (Shapley Additive exPlanations) metric was used to explain the predictions of the best model, quantifying the contribution of each feature to the model's predictions. The experimental results on the AI patent dataset indicate that, for all three target variables, LightGBM regression shows the best predictive performance. Specifically, patent novelty has the greatest impact on predicting the technical impact of patents and has a positive effect. Additionally, the number of owners, the number of backward citations, and the number of independent claims are all crucial and have a positive influence on predicting technical impact. In predicting the social impact of patents, the number of applicants is considered the most critical input variable, but it has a negative impact on social impact. At the same time, the number of independent claims, the number of owners, and the number of backward citations are also important predictive factors, and they have a positive effect on social impact. For predicting the economic impact of patents, the number of independent claims is considered the most important factor and has a positive impact on economic impact. The number of owners, the number of sibling countries or regions, and the size of the extended patent family also have a positive influence on economic impact. The study primarily relies on data from the United States Patent and Trademark Office for artificial intelligence patents. Future research could consider more comprehensive data sources, including artificial intelligence patent data, from a global perspective. While the study takes into account various factors, there may still be other important features not considered. In the future, factors such as patent implementation and market applications may be considered as they could have an impact on the influence of patents.

Keywords: patent influence, interpretable machine learning, predictive models, SHAP

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Authors: Z. Jamalzadeh, A. Niaei, H. Erfannia

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Due to developing industries, the emission of pollutants such as NOx, SOx, and CO2 are rapidly increased. Generally, NOx is attributed to the mono nitrogen oxides of NO and NO2 that is one of the most important atmospheric contaminants. Hence, controlling the emission of nitrogen oxides is environmentally urgent. Selective catalytic reduction of NOx is one of the most common techniques for NOx removal in which zeolites have wide application due to their high performance. In zeolitic processes, the catalytic reaction occurs mostly in the pores. Therefore, investigation of the adsorption phenomena of the molecules in order to gain an insight and understand the catalytic cycle is of important. Hence, in current study, benefiting from molecular simulations, the adsorption phenomena in the nanocatalysts of SCR of NOx process was investigated in order to get a good insight of the catalysts’ behavior. The effect of cation addition to the support in the catalysts’ behavior through adsorption step was explored by Mont Carlo (MC) using Materials Studio Package. Simulation time of 1 Ns accompanying 1 fs time step, COMPASS27 Force Field and the cut off radios of 12.5 Ȧ was applied for performed runs. It was observed that the adsorption capacity increases in the presence of cations. The sorption isotherms demonstrated the behavior of type I isotherm categories and sorption capacity diminished with increase in temperature whereas an increase was observed at high pressures. Besides, NO sorption showed higher sorption capacity than NH3 in H–ZSM5. In this respect, the energy distributions signified that the molecules could adsorb in just one sorption site at the catalyst and the sorption energy of NO was stronger than the NH3 in H-ZSM5. Furthermore, the isosteric heat of sorption data showed nearly same values for the molecules; however, it indicated stronger interactions of NO molecules with H-ZSM5 zeolite compared to the isosteric heat of NH3 which was low in value.

Keywords: Monte Carlo simulation, adsorption, NOx, ZSM5

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Authors: Sung-Hyeon Park, Jin-Wook Jang, Hak-Sung Kim

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In recent years, Terahertz (THz) time-domain spectroscopy (TDS) imaging method has been received considerable interest as a promising non-destructive technique for detection of internal defects. In comparison to other non-destructive techniques such as x-ray inspection method, scanning acoustic tomograph (SAT) and microwave inspection method, THz-TDS imaging method has many advantages: First, it can measure the exact thickness and location of defects. Second, it doesn’t require the liquid couplant while it is very crucial to deliver that power of ultrasonic wave in SAT method. Third, it didn’t damage to materials and be harmful to human bodies while x-ray inspection method does. Finally, it exhibits better spatial resolution than microwave inspection method. However, this technology couldn’t be applied to IC package because THz radiation can penetrate through a wide variety of materials including polymers and ceramics except of metals. Therefore, it is difficult to detect the defects in IC package which are composed of not only epoxy and semiconductor materials but also various metals such as copper, aluminum and gold. In this work, we proposed a special method for detecting the void in the IC package using THz-TDS imaging system. The IC package specimens for this study are prepared by Packaging Engineering Team in Samsung Electronics. Our THz-TDS imaging system has a special reflection mode called pitch-catch mode which can change the incidence angle in the reflection mode from 10 o to 70 o while the others have transmission and the normal reflection mode or the reflection mode fixed at certain angle. Therefore, to find the voids in the IC package, we investigated the appropriate angle as changing the incidence angle of THz wave emitter and detector. As the results, the voids in the IC packages were successfully detected using our THz-TDS imaging system.

Keywords: terahertz, non-destructive technique, void, IC package

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Authors: Jackson Simon Lusagalika, Lai Hsin-Chih, Dai Yu-Tung

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Particles with an aerodynamic diameter of 2.5 meters or less are referred to as "fine particulate matter" (PM₂.₅) are easily inhaled and can go deeper into the lungs than other particles in the atmosphere, where it may have detrimental health consequences. In this study, we use a hybrid model that combined CMAQ and AERMOD as well as initial meteorological fields from the Weather Research and Forecasting (WRF) model to study the impact of power plant PM₂.₅ emissions in South Taiwan since it frequently experiences higher PM₂.₅ levels. A specific date of March 3, 2022, was chosen as a result of a power outage that prompted the bulk of power plants to shut down. In some way, it is not conceivable anywhere in the world to turn off the power for the sole purpose of doing research. Therefore, this catastrophe involving a power outage and the shutdown of power plants offers a great occasion to evaluate the impact of air pollution driven by this power sector. As a result, four numerical experiments were conducted in the study using the Continuous Emission Data System (CEMS), assuming that the power plants continued to function normally after the power outage. The hybrid model results revealed that power plants have a minor impact in the study region. However, we examined the accumulation of PM₂.₅ in the study and discovered that once the vortex at 925hPa was established and moved to the north of Taiwan's coast, the study region experienced higher observed PM₂.₅ concentrations influenced by meteorological factors. This study recommends that decision-makers take into account not only control techniques, specifically emission reductions, but also the atmospheric and meteorological implications for future investigations.

Keywords: PM₂.₅ concentration, powerplants, hybrid air quality model, CEMS, Vorticity

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Authors: Said Belaaouad

Abstract:

This study aimed to explore the quantitative structure-activity relationship (QSAR) of 1,2,4-Triazine-3(2H)-one derivative as a potential anticancer agent against breast cancer. The electronic descriptors were obtained using the Density Functional Theory (DFT) method, and a multiple linear regression techniques was employed to construct the QSAR model. The model exhibited favorable statistical parameters, including R2=0.849, R2adj=0.656, MSE=0.056, R2test=0.710, and Q2cv=0.542, indicating its reliability. Among the descriptors analyzed, absolute electronegativity (χ), total energy (TE), number of hydrogen bond donors (NHD), water solubility (LogS), and shape coefficient (I) were identified as influential factors. Furthermore, leveraging the validated QSAR model, new derivatives of 1,2,4-Triazine-3(2H)-one were designed, and their activity and pharmacokinetic properties were estimated. Subsequently, molecular docking (MD) and molecular dynamics (MD) simulations were employed to assess the binding affinity of the designed molecules. The Tubulin colchicine binding site, which plays a crucial role in cancer treatment, was chosen as the target protein. Through the simulation trajectory spanning 100 ns, the binding affinity was calculated using the MMPBSA script. As a result, fourteen novel Tubulin-colchicine inhibitors with promising pharmacokinetic characteristics were identified. Overall, this study provides valuable insights into the QSAR of 1,2,4-Triazine-3(2H)-one derivative as potential anticancer agent, along with the design of new compounds and their assessment through molecular docking and dynamics simulations targeting the Tubulin-colchicine binding site.

Keywords: QSAR, molecular docking, ADMET, 1, 2, 4-triazin-3(2H)-ones, breast cancer, anticancer, molecular dynamic simulations, MMPBSA calculation

Procedia PDF Downloads 74