Search results for: dynamic selection

Authors: Inês N. Peça , A. Bicho, Rui Gardner, M. Margarida Cardoso

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Inorganic/organic nanocomplexes offer tremendous scope for future biomedical applications, including imaging, disease diagnosis and drug delivery. The combination of Fe3O4 with biocompatible polymers to produce smart drug delivery systems for use in pharmaceutical formulation present a powerful tool to target anti-cancer drugs to specific tumor sites through the application of an external magnetic field. In the present study, we focused on the evaluation of the effect of the magnetic field application time on the rate of drug release from iron oxide polymeric nanoparticles. Doxorubicin, an anticancer drug, was selected as the model drug loaded into the nanoparticles. Nanoparticles composed of poly(d-lactide-co-glycolide (PLGA), a biocompatible polymer already approved by FDA, containing iron oxide nanoparticles (MNP) for magnetic targeting and doxorubicin (DOX) were synthesized by the o/w solvent extraction/evaporation method and characterized by scanning electron microscopy (SEM), by dynamic light scattering (DLS), by inductively coupled plasma-atomic emission spectrometry and by Fourier transformed infrared spectroscopy. The produced particles yielded smooth surfaces and spherical shapes exhibiting a size between 400 and 600 nm. The effect of the magnetic doxorubicin loaded PLGA nanoparticles produced on cell viability was investigated in mammalian CHO cell cultures. The results showed that unloaded magnetic PLGA nanoparticles were nontoxic while the magnetic particles without polymeric coating show a high level of toxicity. Concerning the therapeutic activity doxorubicin loaded magnetic particles cause a remarkable enhancement of the cell inhibition rates compared to their non-magnetic counterpart. In vitro drug release studies performed under a non-permanent magnetic field show that the application time and the on/off cycle duration have a great influence with respect to the final amount and to the rate of drug release. In order to determine the mechanism of drug release, the data obtained from the release curves were fitted to the semi-empirical equation of the the Korsmeyer-Peppas model that may be used to describe the Fickian and non-Fickian release behaviour. Doxorubicin release mechanism has shown to be governed mainly by Fickian diffusion. The results obtained show that the rate of drug release from the produced magnetic nanoparticles can be modulated through the magnetic field time application.

Keywords: drug delivery, magnetic nanoparticles, PLGA nanoparticles, controlled release rate

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Authors: Ahmed Alghurabi, Mysara Mohyaldinn, Shiferaw Jufar, Obai Younis, Abdullah Abduljabbar

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Erosion modeling equations were typically acquired from regulated experimental trials for solid particles entrained in single-phase or multi-phase flows. Evidently, those equations were later employed to predict the erosion damage caused by the continuous impacts of solid particles entrained in streamflow. It is also well-known that the particle impact angle and velocity do not change drastically in gas-sand flow erosion prediction; hence an accurate prediction of erosion can be projected. On the contrary, high-density fluid flows, such as water flow, through complex geometries, such as sand screens, greatly affect the sand particles’ trajectories/tracks and consequently impact the erosion rate predictions. Particle tracking models and erosion equations are frequently applied simultaneously as a method to improve erosion visualization and estimation. In the present work, computational fluid dynamic (CFD)-based erosion modeling was performed using a commercially available software; ANSYS Fluent. The continuous phase (water flow) behavior was simulated using the realizable K-epsilon model, and the secondary phase (solid particles), having a 5% flow concentration, was tracked with the help of the discrete phase model (DPM). To accomplish a successful erosion modeling, three erosion equations from the literature were utilized and introduced to the ANSYS Fluent software to predict the screen wire-slot velocity surge and estimate the maximum erosion rates on the screen surface. Results of turbulent kinetic energy, turbulence intensity, dissipation rate, the total pressure on the screen, screen wall shear stress, and flow velocity vectors were presented and discussed. Moreover, the particle tracks and path-lines were also demonstrated based on their residence time, velocity magnitude, and flow turbulence. On one hand, results from the utilized erosion equations have shown similarities in screen erosion patterns, locations, and DPM concentrations. On the other hand, the model equations estimated slightly different values of maximum erosion rates of the wire-wrapped screen. This is solely based on the fact that the utilized erosion equations were developed with some assumptions that are controlled by the experimental lab conditions.

Keywords: CFD simulation, erosion rate prediction, material loss due to erosion, water-sand flow

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Authors: Hazel James P. Agngarayngay, Arnold R. Elepaño

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Mango is the third most important export fruit in the Philippines. Despite the expanding mango trade in world market, problems on postharvest losses caused by pests and diseases are still prevalent. Many disease control and pest disinfestation methods have been studied and adopted. Heat treatment is necessary to eliminate pests and diseases to be able to pass the quarantine requirements of importing countries. During heat treatments, temperature and time are critical because fruits can easily be damaged by over-exposure to heat. Modeling the process enables researchers and engineers to study the behaviour of temperature distribution within the fruit over time. Understanding physical processes through modeling and simulation also saves time and resources because of reduced experimentation. This research aimed to simulate the heat transfer mechanism and predict the temperature distribution in ‘Carabao' mangoes during hot water treatment (HWT) and extended hot water treatment (EHWT). The simulation was performed in ANSYS CFD Software, using ANSYS CFX Solver. The simulation process involved model creation, mesh generation, defining the physics of the model, solving the problem, and visualizing the results. Boundary conditions consisted of the convective heat transfer coefficient and a constant free stream temperature. The three-dimensional energy equation for transient conditions was numerically solved to obtain heat flux and transient temperature values. The solver utilized finite volume method of discretization. To validate the simulation, actual data were obtained through experiment. The goodness of fit was evaluated using mean temperature difference (MTD). Also, t-test was used to detect significant differences between the data sets. Results showed that the simulations were able to estimate temperatures accurately with MTD of 0.50 and 0.69 °C for the HWT and EHWT, respectively. This indicates good agreement between the simulated and actual temperature values. The data included in the analysis were taken at different locations of probe punctures within the fruit. Moreover, t-tests showed no significant differences between the two data sets. Maximum heat fluxes obtained at the beginning of the treatments were 394.15 and 262.77 J.s-1 for HWT and EHWT, respectively. These values decreased abruptly at the first 10 seconds and gradual decrease was observed thereafter. Data on heat flux is necessary in the design of heaters. If underestimated, the heating component of a certain machine will not be able to provide enough heat required by certain operations. Otherwise, over-estimation will result in wasting of energy and resources. This study demonstrated that the simulation was able to estimate temperatures accurately. Thus, it can be used to evaluate the influence of various treatment conditions on the temperature-time history in mangoes. When combined with information on insect mortality and quality degradation kinetics, it could predict the efficacy of a particular treatment and guide appropriate selection of treatment conditions. The effect of various parameters on heat transfer rates, such as the boundary and initial conditions as well as the thermal properties of the material, can be systematically studied without performing experiments. Furthermore, the use of ANSYS software in modeling and simulation can be explored in modeling various systems and processes.

Keywords: heat transfer, heat treatment, mango, modeling and simulation

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Authors: Tahzeeb Mahreen

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Distance education refers to giving instruction in which students are remote from the institution and once in a while go to formal demonstration classes, and teaching sessions. Segments of media, for example, radio, TV, PC and Internet and so on are the assets and method for correspondence being utilized as a part of learning material by many open and distance learning institutions. Media has a great part in maximizing the learning opportunities thus enabling distance education, a mode of increased literacy rate of the country. This study goes for analyzing how media had affected distance education through its different mediums. The objectives of the study were (i) to determine the direct impact of media on distance education? (ii) To know how media effects distance education pedagogy (iii) To find out how media works to increase student’s achievement. Literature-based methodology was used, and books, peer-reviewed articles, press reports and internet-based materials were studied as a result. By using descriptive qualitative research analysis, the researcher has interpreted that distance education programs are progressively utilizing mixes of media to convey training that has a positive impact on learning along with a few challenges. In addition, the perception of the researcher varied depending on the programs of distance learning but generally believed that electronic media were moderately more supportive in enhancing the overall performance of the learners. It was concluded that the intellectual style, identity qualities, and self-expectations are the three primary enhanced areas in a student’s educational life in distance education programs. It was portrayed that a comprehension of how individual learners approach learning may make it workable for the distance educator to see an example of learning styles and arrange or modify course presentations through media. Moreover, it is noticed that teaching in distance education address the developing role of the instructor, the requirement for diminishing resistance as conventional teachers utilize remove conveyance frameworks lastly, staff state of mind toward the utilization of innovation. Furthermore, the results showed that media had assumed its part to make distance learning educators more dynamic, capable and concerned about their individual works. The study also indicated a high positive relationship between the media available at study centers and media used by the distance education. The challenge pointed out by the researcher was the clash of distance and time with communication as the life situations of every learner are varied. Recommendations included the realization of the duty of distance learning instructor to help students understand the effective use of media for their study lessons and also to develop online learning communities to be in instant connection with the students.

Keywords: distance education, education, media, teaching and learning

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Authors: Pampita Chakraborty, Sukumar Mukherjee

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This study was done to determine the bacteriological profile and antibiotic resistance of the isolates and to find out the potential risk factors for infection with multidrug-resistant organisms. Diabetic foot ulcer is a major medical, social, economic problem and a leading cause of morbidity and mortality, especially in the developing countries like India. 25 percent of all diabetic patients develop a foot ulcer at some point in their lives which is highly susceptible to infections and that spreads rapidly, leading to overwhelming tissue destruction and subsequent amputation. Infection with multidrug resistant organisms (MDRO) may increase the cost of management and may cause additional morbidity and mortality. Proper management of these infections requires appropriate antibiotic selection based on culture and antimicrobial susceptibility testing. Early diagnosis of microbial infections is aimed to institute the appropriate antibacterial therapy initiative to avoid further complications. A total of 200 Type 2 Diabetic Mellitus patients with infection were admitted at GD Hospital and Diabetes Institute, Kolkata. 60 of them who developed ulcer during the year 2013 were included in this study. A detailed clinical history and physical examination were carried out for every subject. Specimens for microbiological studies were obtained from ulcer region. Gram-negative bacilli were tested for extended spectrum Beta-lactamase (ESBL) production by double disc diffusion method. Staphylococcal isolates were tested for susceptibility to oxacillin by screen agar method and disc diffusion. Potential risk factors for MDRO-positive samples were explored. Gram-negative aerobes were most frequently isolated, followed by gram-positive aerobes. Males were predominant in the study and majority of the patients were in the age group of 41-60 years. The presence of neuropathy was observed in 80% cases followed by peripheral vascular disease (73%). Proteus spp. (22) was the most common pathogen isolated, followed by E.coli (17). Staphylococcus aureus was predominant amongst the gram-positive isolates. S.aureus showed a high rate of resistance to antibiotic tested (63.6%). Other gram-positive isolates were found to be highly resistant to erythromycin, tetracycline and ciprofloxacin, 40% each. All isolates were found to be sensitive to Vancomycin and Linezolid. ESBL production was noted in Proteus spp and E.coli. Approximately 70 % of the patients were positive for MDRO. MDRO-infected patients had poor glycemic control (HbA1c 11± 2). Infection with MDROs is common in diabetic foot ulcers and is associated with risk factors like inadequate glycemic control, the presence of neuropathy, osteomyelitis, ulcer size and increased the requirement for surgical treatment. There is a need for continuous surveillance of resistant bacteria to provide the basis for empirical therapy and reduce the risk of complications.

Keywords: diabetic foot ulcer, bacterial infection, multidrug-resistant organism, extended spectrum beta-lactamase

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Authors: Priyanka Bharti

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Decades ago designs were based on common sense and tradition, but after an enhancement in visualization technology and research, we are now able to comprehend the cognitive ability involved in the decoding of the visual information. However, many fields in visuals need intense research to deliver an efficient explanation for the events. Visuals are an information representation mode through images, symbols and graphics. It plays an impactful role in decision making by facilitating quick recognition, comprehension, and analysis of a situation. They enhance problem-solving capabilities by enabling the processing of more data without overloading the decision maker. As research proves that, visuals offer an improved learning environment by a factor of 400 compared to textual information. Visual information engages learners at a cognitive level and triggers the imagination, which enables the user to process the information faster (visuals are processed 60,000 times faster in the brain than text). Appropriate information, visualization, and its presentation are known to aid and intensify the decision-making process for the users. However, most literature discusses the role of visual aids in comprehension and decision making during normal conditions alone. Unlike emergencies, in a normal situation (e.g. our day to day life) users are neither exposed to stringent time constraints nor face the anxiety of survival and have sufficient time to evaluate various alternatives before making any decision. An emergency is an unexpected probably fatal real-life situation which may inflict serious ramifications on both human life and material possessions unless corrective measures are taken instantly. The situation demands the exposed user to negotiate in a dynamic and unstable scenario in the absence or lack of any preparation, but still, take swift and appropriate decisions to save life/lives or possessions. But the resulting stress and anxiety restricts cue sampling, decreases vigilance, reduces the capacity of working memory, causes premature closure in evaluating alternative options, and results in task shedding. Limited time, uncertainty, high stakes and vague goals negatively affect cognitive abilities to take appropriate decisions. More so, theory of natural decision making by experts has been understood with far more depth than that of an ordinary user. Therefore, in this study, the author aims to understand the role of visual aids in supporting rapid comprehension to take appropriate decisions during an emergency situation.

Keywords: cognition, visual, decision making, graphics, recognition

Procedia PDF Downloads 243

Authors: Heather Mroz

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Geothermal fluids can provide a nearly unlimited source of renewable energy but are often highly corrosive due to dissolved carbon dioxide (CO2), hydrogen sulphide (H2S), Ammonia (NH3) and chloride ions. The corrosive environment drives material selection for many components, including piping, heat exchangers and pressure vessels, to higher alloys of stainless steel, nickel-based alloys and titanium. The use of these alloys is cost-prohibitive and does not offer the pressure rating of carbon steel. One solution, explosion cladding, has been proven to reduce the capital cost of the geothermal equipment while retaining the mechanical and corrosion properties of both the base metal and the cladded surface metal. Explosion cladding is a solid-state welding process that uses precision explosions to bond two dissimilar metals while retaining the mechanical, electrical and corrosion properties. The process is commonly used to clad steel with a thin layer of corrosion-resistant alloy metal, such as stainless steel, brass, nickel, silver, titanium, or zirconium. Additionally, explosion welding can join a wider array of compatible and non-compatible metals with more than 260 metal combinations possible. The explosion weld is achieved in milliseconds; therefore, no bulk heating occurs, and the metals experience no dilution. By adhering to a strict set of manufacturing requirements, both the shear strength and tensile strength of the bond will exceed the strength of the weaker metal, ensuring the reliability of the bond. For over 50 years, explosion cladding has been used in the oil and gas and chemical processing industries and has provided significant economic benefit in reduced maintenance and lower capital costs over solid construction. The focus of this paper will be on the many benefits of the use of explosion clad in process equipment instead of more expensive solid alloy construction. The method of clad-plate production with explosion welding as well as the methods employed to ensure sound bonding of the metals. It will also include the origins of explosion cladding as well as recent technological developments. Traditionally explosion clad plate was formed into vessels, tube sheets and heads but recent advances include explosion welded piping. The final portion of the paper will give examples of the use of explosion-clad metals in geothermal energy recovery. The classes of materials used for geothermal brine will be discussed, including stainless steels, nickel alloys and titanium. These examples will include heat exchangers (tube sheets), high pressure and horizontal separators, standard pressure crystallizers, piping and well casings. It is important to educate engineers and designers on material options as they develop equipment for geothermal resources. Explosion cladding is a niche technology that can be successful in many situations, like geothermal energy recovery, where high temperature, high pressure and corrosive environments are typical. Applications for explosion clad metals include vessel and heat exchanger components as well as piping.

Keywords: clad metal, explosion welding, separator material, well casing material, piping material

Procedia PDF Downloads 137

Authors: Jonathan Kissi, Baozhen Dai, Wisdom W. K. Pomegbe, Abdul-Basit Kassim

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Protecting patient’s digital information is a growing concern for healthcare institutions as people nowadays perpetually live their lives through telemedicine services. These telemedicine services have been confronted with several determinants that hinder their successful implementations, especially in developing countries. Identifying such determinants that influence the acceptance of telemedicine services is also a problem for healthcare professionals. Despite the tremendous increase in telemedicine services, its adoption, and use has been quite slow in some healthcare settings. Generally, it is accepted in today’s globalizing world that the success of telemedicine services relies on users’ satisfaction. Satisfying health professionals and patients are one of the crucial objectives of telemedicine success. This study seeks to investigate the determinants that influence health professionals’ intention to utilize telemedicine services in clinical activities in a sub-Saharan African country in West Africa (Ghana). A hybridized model comprising of health adoption models, including technology acceptance theory, diffusion of innovation theory, and protection of motivation theory, were used to investigate these quandaries. The study was carried out in four government health institutions that apply and regulate telemedicine services in their clinical activities. A structured questionnaire was developed and used for data collection. Purposive and convenience sampling methods were used in the selection of healthcare professionals from different medical fields for the study. The collected data were analyzed based on structural equation modeling (SEM) approach. All selected constructs showed a significant relationship with health professional’s behavioral intention in the direction expected from prior literature including perceived usefulness, perceived ease of use, management strategies, financial sustainability, communication channels, patients security threat, patients privacy risk, self efficacy, actual service use, user satisfaction, and telemedicine services systems securities threat. Surprisingly, user characteristics and response efficacy of health professionals were not significant in the hybridized model. The findings and insights from this research show that health professionals are pragmatic when making choices for technology applications and also their willingness to use telemedicine services. They are, however, anxious about its threats and coping appraisals. The identified significant constructs in the study may help to increase efficiency, quality of services, quality patient care delivery, and satisfactory user satisfaction among healthcare professionals. The implantation and effective utilization of telemedicine services in the selected hospitals will aid as a strategy to eradicate hardships in healthcare services delivery. The service will help attain universal health access coverage to all populace. This study contributes to empirical knowledge by identifying the vital factors influencing health professionals’ behavioral intentions to adopt telemedicine services. The study will also help stakeholders of healthcare to formulate better policies towards telemedicine service usage.

Keywords: telemedicine service, perceived usefulness, perceived ease of use, management strategies, security threats

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Authors: Raphael M. Rettig, Tessa C. Flatten

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This empirical study answer calls for research on Absorptive Capacity and Process Innovation. Due to the fourth industrial revolution, manufacturing companies face the biggest disruption of their production processes since the rise of advanced manufacturing technologies in the last century. Therefore, process innovation will become a critical task to master in the future for many manufacturing firms around the world. The general ability of organizations to acquire, assimilate, transform, and exploit external knowledge, known as Absorptive Capacity, was proven to positively influence product innovation and is already conceptually associated with process innovation. The presented research provides empirical evidence for this influence. The findings are based on an empirical analysis of 732 companies from seven leading and emerging countries: Brazil, China, France, Germany, India, Japan, and the United States of America. The answers to the survey were collected in February and March 2018 and addressed senior- and top-level management with a focus on operations departments. The statistical analysis reveals the positive influence of potential and Realized Absorptive Capacity on successful process innovation taking the implementation of new digital manufacturing processes as an example. Potential Absorptive Capacity covering the acquisition and assimilation capabilities of an organization showed a significant positive influence (β = .304, p < .05) on digital manufacturing implementation success and therefore on process innovation. Realized Absorptive Capacity proved to have significant positive influence on process innovation as well (β = .461, p < .01). The presented study builds on prior conceptual work in the field of Absorptive Capacity and process innovation and contributes theoretically to ongoing research in two dimensions. First, the already conceptually associated influence of Absorptive Capacity on process innovation is backed by empirical evidence in a broad international context. Second, since Absorptive Capacity was measured with a focus on new product development, prior empirical research on Absorptive Capacity was tailored to the research and development departments of organizations. The results of this study highlight the importance of Absorptive Capacity as a capability in mechanical engineering and operations departments of organizations. The findings give managers an indication of the importance of implementing new innovative processes into their production system and fostering the right mindset of employees to identify new external knowledge. Through the ability to transform and exploit external knowledge, own production processes can be innovated successfully and therefore have a positive influence on firm performance and the competitive position of their organizations.

Keywords: absorptive capacity, digital manufacturing, dynamic capabilities, process innovation

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Authors: Shenghong Huang, Weirong Wang, Xisheng Luo, Xinzhu Li, Xinwen Zhao

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Understanding of material mixing induced by Richtmyer-Meshkov instability (RMI) at extreme shock compressing conditions (high energy density environment: P >> 100GPa, T >> 10000k) is of great significance in engineering and science, such as inertial confinement fusion(ICF), supersonic combustion, etc. Turbulent mixing induced by RMI is a kind of complex fluid dynamics, which is closely related with hydrodynamic conditions, thermodynamic states, material physical properties such as compressibility, strength, surface tension and viscosity, etc. as well as initial perturbation on interface. For phenomena in ordinary thermodynamic conditions (low energy density environment), many investigations have been conducted and many progresses have been reported, while for mixing in extreme thermodynamic conditions, the evolution may be very different due to ionization as well as large difference of material physical properties, which is full of scientific problems and academic interests. In this investigation, the first principle based molecular dynamic method is applied to study metal Lithium and gas Hydrogen (Li-H2) interface mixing in micro/meso scale regime at different shock compressing loading speed ranging from 3 km/s to 30 km/s. It's found that, 1) Different from low-speed shock compressing cases, in high-speed shock compresing (>9km/s) cases, a strong acceleration of metal/gas interface after strong shock compression is observed numerically, leading to a strong phase inverse and spike growing with a relative larger linear rate. And more specially, the spike growing rate is observed to be increased with shock loading speed, presenting large discrepancy with available empirical RMI models; 2) Ionization is happened in shock font zone at high-speed loading cases(>9km/s). An additional local electric field induced by the inhomogeneous diffusion of electrons and nuclei after shock font is observed to occur near the metal/gas interface, leading to a large acceleration of nuclei in this zone; 3) In conclusion, the work of additional electric field contributes to a mechanism of RMI in micro/meso scale regime at extreme shock compressing conditions, i.e., a Rayleigh-Taylor instability(RTI) is induced by additional electric field during RMI mixing process and thus a larger linear growing rate of interface spike.

Keywords: ionization, micro/meso scale, material mixing, shock

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Authors: Xingyu Gao, Qiang Wu, Yuanyuan Liu, Yue Yang

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In the era of the knowledge economy, the relationship between scientific knowledge and patents has garnered significant attention. Understanding the intricate interplay between the foundations of science and technological innovation has emerged as a pivotal challenge for both researchers and policymakers. This study establishes a coupled network of artificial intelligence patents based on co-cited scientific papers. Leveraging centrality metrics from network analysis offers a fresh perspective on understanding the influence of information flow and knowledge sharing within the network on patent impact. The study initially obtained patent numbers for 446,890 granted US AI patents from the United States Patent and Trademark Office’s artificial intelligence patent database for the years 2002-2020. Subsequently, specific information regarding these patents was acquired using the Lens patent retrieval platform. Additionally, a search and deduplication process was performed on scientific non-patent references (SNPRs) using the Web of Science database, resulting in the selection of 184,603 patents that cited 37,467 unique SNPRs. Finally, this study constructs a coupled network comprising 59,379 artificial intelligence patents by utilizing scientific papers co-cited in patent backward citations. In this network, nodes represent patents, and if patents reference the same scientific papers, connections are established between them, serving as edges within the network. Nodes and edges collectively constitute the patent coupling network. Structural characteristics such as node degree centrality, betweenness centrality, and closeness centrality are employed to assess the scientific connections between patents, while citation count is utilized as a quantitative metric for patent influence. Finally, a negative binomial model is employed to test the nonlinear relationship between these network structural features and patent influence. The research findings indicate that network structural features such as node degree centrality, betweenness centrality, and closeness centrality exhibit inverted U-shaped relationships with patent influence. Specifically, as these centrality metrics increase, patent influence initially shows an upward trend, but once these features reach a certain threshold, patent influence starts to decline. This discovery suggests that moderate network centrality is beneficial for enhancing patent influence, while excessively high centrality may have a detrimental effect on patent influence. This finding offers crucial insights for policymakers, emphasizing the importance of encouraging moderate knowledge flow and sharing to promote innovation when formulating technology policies. It suggests that in certain situations, data sharing and integration can contribute to innovation. Consequently, policymakers can take measures to promote data-sharing policies, such as open data initiatives, to facilitate the flow of knowledge and the generation of innovation. Additionally, governments and relevant agencies can achieve broader knowledge dissemination by supporting collaborative research projects, adjusting intellectual property policies to enhance flexibility, or nurturing technology entrepreneurship ecosystems.

Keywords: centrality, patent coupling network, patent influence, social network analysis

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Authors: Michio Kurosu

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Alterations in glycosylation not only directly impact cell growth and survival but also facilitate tumor-induced immunomodulation and eventual metastasis. Identification of cell type-specific glycoconjugates (tumor markers) has led to the discovery of new assay systems for certain cancers via immunodetection reagents. N- and O-linked glycans are the most abundant forms of glycoproteins. Recent studies of cancer immunotherapy are based on the immunogenicity of truncated O-glycan chains (e.g., Tn, sTn, T, and sLea/x). The prevalence of N-linked glycan changes in the development of tumor cells is known; however, therapeutic antibodies against N-glycans have not yet been developed. This is due to the lack of specificity of N-linked glycans between normal/healthy and cancer cells. Abnormal branching of N-linked glycans has been observed, particularly in solid cancer cells. While the discovery of drug-like glycosyltransferase inhibitors that block the biosynthesis of specific branching has a very low likelihood of success, altered glycosylation levels can be exploited by suppressing N-glycan biosynthesis through the inhibition of dolichyl-phosphate N-acetylglucosaminephosphotransferase1 (DPAGT1) activity. Inhibition of DPAGT1 function leads to changes of O-glycosylation on proteins associated with mitochondria and zinc finger binding proteins (indirect effects). On the basis of dynamic crosstalk between DPAGT1 and Snail/Slung/ZEB1 (a family of transcription factors that promote the repression of the adhesion molecules), we have developed pharmacologically acceptable selective DPAGT1 inhibitors. Tunicamycin kills a wide range of cancer and healthy cells in a non-selective manner. In sharp contrast, our DPAGT1 inhibitors display strong cytostatic effects against 16 solid cancers, which require the overexpression of DPAGT1 in their progression but do not affect the cell viability of healthy cells. The identified DPAGT1 inhibitors possess impressive anti-metastatic ability in various solid cancer cell lines and induce their mitochondrial structural changes, resulting in apoptosis. A prototype DPAGT1 inhibitor, APPB has already been proven to shrink solid tumors (e.g., pancreatic cancers, triple-negative breast cancers) in vivo while suppressing metastases and has strong synergistic effects when combined with current cytotoxic drugs (e.g., paclitaxel). At this conference, our discovery of selective DPAGT1 inhibitors with drug-like properties and proof-of-pharmaceutical concept studies of a novel DPAGT1 inhibitor are presented.

Keywords: DPAGT1 inhibitors, anti-metastatic drugs, natural product based drug designs, cytostatic effects

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Authors: Deepak Loura

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Production and productivity of several crops in the country continue to be adversely affected by biotic (e.g., Insect-pests and diseases) and abiotic (e.g., water temperature and salinity) stresses. Over-dependence on pesticides and other chemicals is economically non-viable for the resource-poor farmers of our country. Further, pesticides can potentially affect human and environmental safety. While traditional breeding techniques and proper- management strategies continue to play a vital role in crop improvement, we need to judiciously use biotechnology approaches for the development of genetically modified crops addressing critical problems in the improvement of crop plants for sustainable agriculture. Modern biotechnology can help to increase crop production, reduce farming costs, and improve food quality and the safety of the environment. Genetic engineering is a new technology which allows plant breeders to produce plants with new gene combinations by genetic transformation of crop plants for improvement of agronomic traits. Advances in recombinant DNA technology have made it possible to have genes between widely divergent species to develop genetically modified or genetically engineered plants. Plant genetic engineering provides the strength to harness useful genes and alleles from indigenous microorganisms to enrich the gene pool for developing genetically modified (GM) crops that will have inbuilt (inherent) resistance to insect pests, diseases, and abiotic stresses. Plant biotechnology has made significant contributions in the past 20 years in the development of genetically engineered or genetically modified crops with multiple benefits. A variety of traits have been introduced in genetically engineered crops which include (i) herbicide resistance. (ii) pest resistance, (iii) viral resistance, (iv) slow ripening of fruits and vegetables, (v) fungal and bacterial resistance, (vi) abiotic stress tolerance (drought, salinity, temperature, flooding, etc.). (vii) quality improvement (starch, protein, and oil), (viii) value addition (vitamins, micro, and macro elements), (ix) pharmaceutical and therapeutic proteins, and (x) edible vaccines, etc. Multiple genes in transgenic crops can be useful in developing durable disease resistance and a broad insect-control spectrum and could lead to potential cost-saving advantages for farmers. The development of transgenic to produce high-value pharmaceuticals and the edible vaccine is also under progress, which requires much more research and development work before commercially viable products will be available. In addition, molecular-aided selection (MAS) is now routinely used to enhance the speed and precision of plant breeding. Newer technologies need to be developed and deployed for enhancing and sustaining agricultural productivity. There is a need to optimize the use of biotechnology in conjunction with conventional technologies to achieve higher productivity with fewer resources. Therefore, genetic modification/ engineering of crop plants assumes greater importance, which demands the development and adoption of newer technology for the genetic improvement of crops for increasing crop productivity.

Keywords: biotechnology, plant genetic engineering, genetically modified, biotic, abiotic, disease resistance

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Authors: Jing Nan

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The air breakdown voltage in compact circuit breakers is a critical factor in the design and reliability of electrical distribution systems. This voltage determines the threshold at which the air insulation between conductors will fail or 'break down,' leading to an arc. This phenomenon is highly sensitive to the conditions within the breaker, such as the temperature and the distance between electrodes. Typically, air breakdown voltage models have been reliable for predicting failure under standard operational temperatures. However, in conditions post-arcing, where temperatures can soar above 2000K, these models face challenges due to the complex physics of ionization and electron behaviour at such high-energy states. Building upon the foundational understanding that the breakdown mechanism is initiated by free electrons and propelled by electric fields, which lead to ionization and, potentially, to avalanche or streamer formation, we acknowledge the complexity introduced by high-temperature environments. Recognizing the limitations of existing experimental data, a notable research gap exists in the accurate prediction of breakdown voltage at elevated temperatures, typically observed post-arcing, where temperatures exceed 2000K.To bridge this knowledge gap, we present a method that integrates gap distance and high-temperature effects into air breakdown voltage assessment. The proposed model is grounded in the physics of ionization, accounting for the dynamic behaviour of free electrons which, under intense electric fields at elevated temperatures, lead to thermal ionization and potentially reach the threshold for streamer formation as Meek's criterion. Employing the Saha equation, our model calculates equilibrium electron densities, adapting to the atmospheric pressure and the hot temperature regions indicative of post-arc temperature conditions. Our model is rigorously validated against established experimental data, demonstrating substantial improvements in predicting air breakdown voltage in the high-temperature regime. This work significantly improves the predictive power for air breakdown voltage under conditions that closely mimic operational stressors in compact circuit breakers. Looking ahead, the proposed methods are poised for further exploration in alternative insulating media, like SF6, enhancing the model's utility for a broader range of insulation technologies and contributing to the future of high-temperature electrical insulation research.

Keywords: air breakdown voltage, high-temperature insulation, compact circuit breakers, electrical discharge, saha equation

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Authors: Ashok Kumar, Parveen Parveen

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India is bestowed with an extremely high population of plant species with medicinal value and even has two biodiversity hotspots. Indian systems of medicine including Ayurveda, Siddha and Unani have historically been serving humankind across the world since time immemorial. About 1500 plant species have well been documented in Ayurvedic Nighantus as official medicinal plants. Additionally, several hundred species of plants are being routinely used as medicines by local people especially tribes living in and around forests. The natural resources for medicinal plants have unscientifically been over-exploited forcing rapid depletion in their genetic diversity. Moreover, renewed global interest in herbal medicines may even lead to additional depletion of medicinal plant wealth of the country, as about 95% collection of medicinal plants for pharmaceutical preparation is being carried out from natural forests. On the other hand, huge export market of medicinal and aromatic plants needs to be seriously tapped for enhancing inflow of foreign currency. Asparagus racemosus Willd., a member of family Liliaceae, is one of thirty-two plant species that have been identified as priority species for cultivation and conservation by the National Medicinal Plant Board (NMPB), Government of India. Though attention is being focused on standardization of agro-techniques and extraction methods, little has been designed on genetic improvement and selection of desired types with higher root production and saponin content, a basic ingredient of medicinal value. The saponin not only improves defense mechanisms and controls diabetes but the roots of this species promote secretion of breast milk, improved lost body weight and considered as an aphrodisiac. There is ample scope for genetic improvement of this species for enhancing productivity substantially, qualitatively and quantitatively. It is emphasized to select desired genotypes with sufficient genetic diversity for important economic traits. Hybridization between two genetically divergent genotypes could result in the synthesis of new F1 hybrids consisting of useful traits of both the parents. The evaluation of twenty seed sources of Asparagus racemosus assembled different geographical locations of India revelled high degree of variability for traits of economic importance. The maximum genotypic and phenotypic variance was observed for shoot height among shoot related traits and for root length among root related traits. The shoot height, genotypic variance, phenotypic variance, genotypic coefficient of variance, the phenotypic coefficient of variance was recorded to be 231.80, 3924.80, 61.26 and 1037.32, respectively, where those of the root length were 9.55, 16.80, 23.46 and 41.27, respectively. The maximum genetic advance and genetic gain were obtained for shoot height among shoot-related traits and root length among root-related traits. Index values were developed for all seed sources based on the four most important traits, and Panthnagar (Uttrakhand), Jodhpur (Rajasthan), Dehradun (Uttarakhand), Chandigarh (Punjab), Jammu (Jammu & Kashmir) and Solan (Himachal Pradesh) were found to be promising seed sources.

Keywords: asparagus, genetic, genotypes, variance

Procedia PDF Downloads 108

Authors: Javier E. García-Gallo, Nelson J. Fonseca-Ruiz, John F. Duitama-Munoz

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Sepsis is a syndrome that occurs with physiological and biochemical abnormalities induced by severe infection and carries a high mortality and morbidity, therefore the severity of its condition must be interpreted quickly. After patient admission in an intensive care unit (ICU), it is necessary to synthesize the large volume of information that is collected from patients in a value that represents the severity of their condition. Traditional severity of illness scores seeks to be applicable to all patient populations, and usually assess in-hospital mortality. However, the use of machine learning techniques and the data of a population that shares a common characteristic could lead to the development of customized mortality prediction scores with better performance. This study presents the development of a score for the one-year mortality prediction of the patients that are admitted to an ICU with a sepsis diagnosis. 5650 ICU admissions extracted from the MIMICIII database were evaluated, divided into two groups: 70% to develop the score and 30% to validate it. Comorbidities, demographics and clinical information of the first 24 hours after the ICU admission were used to develop a mortality prediction score. LASSO (least absolute shrinkage and selection operator) and SGB (Stochastic Gradient Boosting) variable importance methodologies were used to select the set of variables that make up the developed score; each of this variables was dichotomized and a cut-off point that divides the population into two groups with different mean mortalities was found; if the patient is in the group that presents a higher mortality a one is assigned to the particular variable, otherwise a zero is assigned. These binary variables are used in a logistic regression (LR) model, and its coefficients were rounded to the nearest integer. The resulting integers are the point values that make up the score when multiplied with each binary variables and summed. The one-year mortality probability was estimated using the score as the only variable in a LR model. Predictive power of the score, was evaluated using the 1695 admissions of the validation subset obtaining an area under the receiver operating characteristic curve of 0.7528, which outperforms the results obtained with Sequential Organ Failure Assessment (SOFA), Oxford Acute Severity of Illness Score (OASIS) and Simplified Acute Physiology Score II (SAPSII) scores on the same validation subset. Observed and predicted mortality rates within estimated probabilities deciles were compared graphically and found to be similar, indicating that the risk estimate obtained with the score is close to the observed mortality, it is also observed that the number of events (deaths) is indeed increasing as the outcome go from the decile with the lowest probabilities to the decile with the highest probabilities. Sepsis is a syndrome that carries a high mortality, 43.3% for the patients included in this study; therefore, tools that help clinicians to quickly and accurately predict a worse prognosis are needed. This work demonstrates the importance of customization of mortality prediction scores since the developed score provides better performance than traditional scoring systems.

Keywords: intensive care, logistic regression model, mortality prediction, sepsis, severity of illness, stochastic gradient boosting

Procedia PDF Downloads 187

Authors: Nodar Kekelidze, David Kekelidze, Elza Khutsishvili, Bela Kvirkvelia

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The semiconductor devices are irreplaceable elements for investigations in Space (artificial Earth satellite, interplanetary space craft, probes, rockets) and for investigation of elementary particles on accelerators, for atomic power stations, nuclear reactors, robots operating on heavily radiation contaminated territories (Chernobyl, Fukushima). Unfortunately, the most important parameters of semiconductors dramatically worsen under irradiation. So creation of radiation-resistant semiconductor materials for opto and microelectronic devices is actual problem, as well as investigation of complicated processes developed in irradiated solid states. Homogeneous single crystals of InP-InAs solid solutions were grown with zone melting method. There has been studied the dependence of the optical absorption coefficient vs photon energy near fundamental absorption edge. This dependence changes dramatically with irradiation. The experiments were performed on InP, InAs and InP-InAs solid solutions before and after irradiation with electrons and fast neutrons. The investigations of optical properties were carried out on infrared spectrophotometer in temperature range of 10K-300K and 1mkm-50mkm spectral area. Radiation fluencies of fast neutrons was equal to 2·1018neutron/cm2 and electrons with 3MeV, 50MeV up to fluxes of 6·1017electron/cm2. Under irradiation, there has been revealed the exponential type of the dependence of the optical absorption coefficient vs photon energy with energy deficiency. The indicated phenomenon takes place at high and low temperatures as well at impurity different concentration and practically in all cases of irradiation by various energy electrons and fast neutrons. We have developed the common mechanism of this phenomenon for unirradiated materials and implemented the quantitative calculations of distinctive parameter; this is in a satisfactory agreement with experimental data. For the irradiated crystals picture get complicated. In the work, the corresponding analysis is carried out. It has been shown, that in the case of InP, irradiated with electrons (Ф=1·1017el/cm2), the curve of optical absorption is shifted to lower energies. This is caused by appearance of the tails of density of states in forbidden band due to local fluctuations of ionized impurity (defect) concentration. Situation is more complicated in the case of InAs and for solid solutions with composition near to InAs when besides noticeable phenomenon there takes place Burstein effect caused by increase of electrons concentration as a result of irradiation. We have shown, that in certain conditions it is possible the prevalence of Burstein effect. This causes the opposite effect: the shift of the optical absorption edge to higher energies. So in given solid solutions there take place two different opposite directed processes. By selection of solid solutions composition and doping impurity we obtained such InP-InAs, solid solution in which under radiation mutual compensation of optical absorption curves displacement occurs. Obtained result let create on the base of InP-InAs, solid solution radiation-resistant optical materials. Conclusion: It was established the nature of optical absorption near fundamental edge in semiconductor materials and it was created radiation-resistant optical material.

Keywords: InAs-InP, electrons concentration, irradiation, solid solutions

Procedia PDF Downloads 169

Authors: J. S. M. Yang, G. E. T. Chua

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Diploma in Optometry (OPT) course is a three-year program offered by Ngee Ann Polytechnic (NP) to train students to provide primary eye care. Students are equipped with foundational conceptual knowledge and practical skills in the first three semesters before clinical modules in fourth to six semesters. In the clinical modules, students typically have difficulties in integrating the acquired knowledge and skills from the past semesters to perform general eye examinations on public patients at NP Optometry Centre (NPOC). To help the students overcome the challenge, a web-based game Virtual Optometrist (VO) was developed to help students apply their skills and knowledge through scenario-based learning. It consisted of two interfaces, Optical Practice Counter (OPC) and Optometric Consultation Room (OCR), to provide two simulated settings for authentic learning experiences. In OPC, students would recommend and provide appropriate frame and lens selection based on virtual patient’s case history. In OCR, students would diagnose and manage virtual patients with common ocular conditions. Simulated scenarios provided real-world clinical situations that required contextual application of integrated knowledge from relevant modules. The stages in OPC and OCR are of increasing complexity to align to expected students’ clinical competency as they progress to more senior semesters. This prevented gameplay fatigue as VO was used over the semesters to achieve different learning outcomes. Numerous feedback opportunities were provided to students based on their decisions to allow individualized learning to take place. The game-based learning element in VO was achieved through the scoreboard and leader board to enhance students' motivation to perform. Scores were based on the speed and accuracy of students’ responses to the questions posed in the simulated scenarios, preparing the students to perform accurately and effectively under time pressure in a realistic optometric environment. Learning analytics was generated in VO’s backend office based on students’ responses, offering real-time data on distinctive and observable learners’ behavior to monitor students’ engagement and learning progress. The backend office allowed versatility to add, edit, and delete scenarios for different intended learning outcomes. Likert Scale was used to measure students’ learning experience with VO for OPT Year 2 and 3 students. The survey results highlighted the learning benefits of implementing VO in the different modules, such as enhancing recall and reinforcement of clinical knowledge for contextual application to develop higher-order thinking skills, increasing efficiency in clinical decision-making, facilitating learning through immediate feedback and second attempts, providing exposure to common and significant ocular conditions, and training effective communication skills. The results showed that VO has been useful in reinforcing optometry students’ learning and supporting the development of higher-order thinking, increasing efficiency in clinical decision-making, and allowing students to learn from their mistakes with immediate feedback and second attempts. VO also exposed the students to diverse ocular conditions through simulated real-world clinical scenarios, which may otherwise not be encountered in NPOC, and promoted effective communication skills.

Keywords: authentic learning, game-based learning, scenario-based learning, simulated clinical scenarios

Procedia PDF Downloads 92

Authors: Andreas Schweiger, Matthias Gnigler, Elisabeth Wieder, Michael Grobbauer

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Especially in the alpine region, available areas for new residential development are limited. One possible solution is to exploit the potential of existing settlements. Urban redensification, especially the addition of floors to existing buildings, requires efficient, lightweight constructions with short construction times. This topic is being addressed in the five-year Alpine Building Centre. The focus of this cooperation between Salzburg University of Applied Sciences and RSA GH Studio iSPACE is on transdisciplinary research in the fields of building and energy technology, building envelopes and geoinformation, as well as the transfer of research results to industry. One development objective is a system of wood panel system construction with a high degree of prefabrication to optimize the construction quality, the construction time and the applicability for small and medium-sized enterprises. The system serves as a reliable working basis for mastering the complex building task of redensification. The technical solution is the development of an open system in timber frame and solid wood construction, which is suitable for a maximum two-story addition of residential buildings. The applicability of the system is mainly influenced by the existing building stock. Therefore, timber frame and solid timber construction are combined where necessary to bridge large spans of the existing structure while keeping the dead weight as low as possible. Escape routes are usually constructed in reinforced concrete and are located outside the system boundary. Thus, within the framework of the legal and normative requirements of timber construction, a hybrid construction method for redensification created. Component structure, load-bearing structure and detail constructions are developed in accordance with the relevant requirements. The results are directly applicable in individual cases, with the exception of the required verifications. In order to verify the practical suitability of the developed system, stakeholder workshops are held on the one hand, and the system is applied in the planning of a two-storey extension on the other hand. A company-independent construction standard offers the possibility of cooperation and bundling of capacities in order to be able to handle larger construction volumes in collaboration with several companies. Numerous further developments can take place on the basis of the system, which is under open license. The construction system will support planners and contractors from design to execution. In this context, open means publicly published and freely usable and modifiable for own use as long as the authorship and deviations are mentioned. The companies are provided with a system manual, which contains the system description and an application manual. This manual will facilitate the selection of the correct component cross-sections for the specific construction projects by means of all component and detail specifications. This presentation highlights the initial situation, the motivation, the approach, but especially the technical solution as well as the possibilities for the application. After an explanation of the objectives and working methods, the component and detail specifications are presented as work results and their application.

Keywords: redensification, SME, urban development, wood building system

Procedia PDF Downloads 79

Authors: Kyung Jin Kim, Jiwon Kwak, Jae-Hoon Lee, Soo Suk Lee

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MicroRNAs (miRNA) are a class of endogenous, single-stranded, small, and non-protein coding RNA molecules typically 20-25 nucleotides long. They are thought to regulate the expression of other genes in a broad range by binding to 3’- untranslated regions (3’-UTRs) of specific mRNAs. The detection of miRNAs is very important for understanding of the function of these molecules and in the diagnosis of variety of human diseases. However, detection of miRNAs is very challenging because of their short length and high sequence similarities within miRNA families. So, a simple-to-use, low-cost, and highly sensitive method for the detection of miRNAs is desirable. In this study, we demonstrate a novel bi-directional extension (BDE) assay. In the first step, a specific linear RT primer is hybridized to 6-10 base pairs from the 3’-end of a target miRNA molecule and then reverse transcribed to generate a cDNA strand. After reverse transcription, the cDNA was hybridized to the 3’-end which is BDE sequence; it played role as the PCR template. The PCR template was amplified in an SYBR green-based quantitative real-time PCR. To prove the concept, we used human brain total RNA. It could be detected quantitatively in the range of seven orders of magnitude with excellent linearity and reproducibility. To evaluate the performance of BDE assay, we contrasted sensitivity and specificity of the BDE assay against a commercially available poly (A) tailing method using miRNAs for let-7e extracted from A549 human epithelial lung cancer cells. The BDE assay displayed good performance compared with a poly (A) tailing method in terms of specificity and sensitivity; the CT values differed by 2.5 and the melting curve showed a sharper than poly (A) tailing methods. We have demonstrated an innovative, cost-effective BDE assay that allows improved sensitivity and specificity in detection of miRNAs. Dynamic range of the SYBR green-based RT-qPCR for miR-145 could be represented quantitatively over a range of 7 orders of magnitude from 0.1 pg to 1.0 μg of human brain total RNA. Finally, the BDE assay for detection of miRNA species such as let-7e shows good performance compared with a poly (A) tailing method in terms of specificity and sensitivity. Thus BDE proves a simple, low cost, and highly sensitive assay for various miRNAs and should provide significant contributions in research on miRNA biology and application of disease diagnostics with miRNAs as targets.

Keywords: bi-directional extension (BDE), microRNA (miRNA), poly (A) tailing assay, reverse transcription, RT-qPCR

Procedia PDF Downloads 138

Authors: Kari Björn

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Introduction of games has expanded the application area of computer-aided learning tools to wide variety of age groups of learners. Serious games engage the learners into a real-world -type of simulation and potentially enrich the learning experience. Institutional background of a Bachelor’s level engineering program in Information and Communication Technology is introduced, with detailed focus on one of its majors, Health Technology. As part of a Customer Oriented Software Application thematic semester, one particular course of “eHealth Business and Solutions” is described and reflected in a gamified framework. Learning a consistent view into vast literature of business management, strategies, marketing and finance in a very limited time enforces selection of topics relevant to the industry. Health Technology is a novel and growing industry with a growing sector in consumer wearable devices and homecare applications. The business sector is attracting new entrepreneurs and impatient investor funds. From engineering education point of view the sector is driven by miniaturizing electronics, sensors and wireless applications. However, the market is highly consumer-driven and usability, safety and data integrity requirements are extremely high. When the same technology is used in analysis or treatment of patients, very strict regulatory measures are enforced. The paper introduces a course structure using gamification as a tool to learn the most essential in a new market: customer value proposition design, followed by a market entry game. Students analyze the existing market size and pricing structure of eHealth web-service market and enter the market as a steering group of their company, competing against the legacy players and with each other. The market is growing but has its rules of demand and supply balance. New products can be developed with an R&D-investment, and targeted to market with unique quality- and price-combinations. Product cost structure can be improved by investing to enhanced production capacity. Investments can be funded optionally by foreign capital. Students make management decisions and face the dynamics of the market competition in form of income statement and balance sheet after each decision cycle. The focus of the learning outcome is to understand customer value creation to be the source of cash flow. The benefit of gamification is to enrich the learning experience on structure and meaning of financial statements. The paper describes the gamification approach and discusses outcomes after two course implementations. Along the case description of learning challenges, some unexpected misconceptions are noted. Improvements of the game or the semi-gamified teaching pedagogy are discussed. The case description serves as an additional support to new game coordinator, as well as helps to improve the method. Overall, the gamified approach has helped to engage engineering student to business studies in an energizing way.

Keywords: engineering education, integrated curriculum, learning experience, learning outcomes

Procedia PDF Downloads 222

Authors: Naima Mohammadi

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The present paper critically reports on the emergency of Iranian international students in a large public university in Italy. Although the most sizeable diaspora of Iranians dates back to the 1979 revolution, a huge wave of Iranian female students travelled abroad after the Iranian Green Movement (2009) due to the intensification of gender discrimination and Islamization. To explore the experience of Iranian female students at an Italian public university, two complementary methods were adopted: a focus group and individual interviews. Focus groups yield detailed collective conversations and provide researchers with an opportunity to observe the interaction between participants, rather than between participant and researcher, which generates data. Semi-structured interviews allow participants to share their stories in their own words and speak about personal experiences and opinions. Research participants were invited to participate through a public call in a Telegram group of Iranian students. Theoretical and purposive sampling was applied to select participants. All participants were assured that full anonymity would be ensured and they consented to take part in the research. A two-hour focus group was held in English with participants in the presence and some online. They were asked to share their motivations for studying in Italy and talk about their experiences both within and outside the university context. Each of these interviews lasted from 45 to 60 minutes and was mostly carried out online and in Farsi. The focus group consisted of 8 Iranian female post-graduate students. In analyzing the data a blended approach was adopted, with a combination of deductive and inductive coding. According to research findings, although 9/11 was the beginning of the West’s challenges against Muslims, the nuclear threats of Islamic regimes promoted the toughest international sanctions against Iranians as a nation across the world. Accordingly, carrying an Iranian identity contributes to social, political, and economic exclusion. Research findings show that geopolitical factors such as international sanctions and Islamophobia, and a lack of reciprocity in terms of recognition, have created a sense of stigmatization for veiled and unveiled Iranian female students who are the largest groups of ‘non-European Muslim international students’ enrolled in Italian universities. Participants addressed how their nationality has devalued their public image and negatively impacted their self-confidence and self-realization in academia. They highlighted the experience of an unwelcoming atmosphere by different groups of people and institutes, such as receiving marked students’ badges, rejected bank account requests, failed visa processes, secondary security screening selection, and hyper-visibility of veiled students. This study corroborates the need for institutions to pay attention to geopolitical factors and religious diversity in student recruitment and provide support mechanisms and access to basic rights. Accordingly, it is suggested that Higher Education Institutions (HEIs) have a social and moral responsibility towards the discrimination and both social and academic exclusion of Iranian students.

Keywords: Iranian diaspora, female students, recognition theory, inclusive university

Procedia PDF Downloads 39

Authors: Miroslava Cuperlovic-Culf, Lipu Wang, Ketty Boyle, Nadine Makley, Ian Burton, Anissa Belkaid, Mohamed Touaibia, Marc E. Surrette

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Metabolic changes are one of the major factors in the development of a variety of diseases in various species. Metabolism of agricultural plants is altered the following infection with pathogens sometimes contributing to resistance. At the same time, pathogens use metabolites for infection and progression. In humans, metabolism is a hallmark of cancer development for example. Quantified metabolomics data combined with other omics or clinical data and analyzed using various unsupervised and supervised methods can lead to better diagnosis and prognosis. It can also provide information about resistance as well as contribute knowledge of compounds significant for disease progression or prevention. In this work, different methods for metabolomics quantification and analysis from Nuclear Magnetic Resonance (NMR) measurements that are used for investigation of disease development in wheat and human cells will be presented. One-dimensional 1H NMR spectra are used extensively for metabolic profiling due to their high reliability, wide range of applicability, speed, trivial sample preparation and low cost. This presentation will describe a new method for metabolite quantification from NMR data that combines alignment of spectra of standards to sample spectra followed by multivariate linear regression optimization of spectra of assigned metabolites to samples’ spectra. Several different alignment methods were tested and multivariate linear regression result has been compared with other quantification methods. Quantified metabolomics data can be analyzed in the variety of ways and we will present different clustering methods used for phenotype determination, network analysis providing knowledge about the relationships between metabolites through metabolic network as well as biomarker selection providing novel markers. These analysis methods have been utilized for the investigation of fusarium head blight resistance in wheat cultivars as well as analysis of the effect of estrogen receptor and carbonic anhydrase activation and inhibition on breast cancer cell metabolism. Metabolic changes in spikelet’s of wheat cultivars FL62R1, Stettler, MuchMore and Sumai3 following fusarium graminearum infection were explored. Extensive 1D 1H and 2D NMR measurements provided information for detailed metabolite assignment and quantification leading to possible metabolic markers discriminating resistance level in wheat subtypes. Quantification data is compared to results obtained using other published methods. Fusarium infection induced metabolic changes in different wheat varieties are discussed in the context of metabolic network and resistance. Quantitative metabolomics has been used for the investigation of the effect of targeted enzyme inhibition in cancer. In this work, the effect of 17 β -estradiol and ferulic acid on metabolism of ER+ breast cancer cells has been compared to their effect on ER- control cells. The effect of the inhibitors of carbonic anhydrase on the observed metabolic changes resulting from ER activation has also been determined. Metabolic profiles were studied using 1D and 2D metabolomic NMR experiments, combined with the identification and quantification of metabolites, and the annotation of the results is provided in the context of biochemical pathways.

Keywords: metabolic biomarkers, metabolic network, metabolomics, multivariate linear regression, NMR quantification, quantified metabolomics, spectral alignment

Procedia PDF Downloads 319

Authors: Sanjay K. Behera, Debasish Saha, Paramesh Gadige, Ranjini Bandyopadhyay

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The zero shear viscosity (η₀) of a suspension of hard sphere colloids characterized by a significant polydispersity (≈10%) increases with increase in volume fraction (ϕ) and shows a dramatic increase at ϕ=ϕg with the system entering a colloidal glassy state. Fragility which is the measure of the rapidity of approach of these suspensions towards the glassy state is sensitive to its size polydispersity and stiffness of the particles. Soft poly(N-isopropylacrylamide) (PNIPAM) particles deform in the presence of neighboring particles at volume fraction above the random close packing volume fraction of undeformed monodisperse spheres. Softness, therefore, enhances the packing efficiency of these particles. In this study PNIPAM particles of a nearly constant swelling ratio and with polydispersities varying over a wide range (7.4%-48.9%) are synthesized to study the effects of polydispersity on the dynamics of suspensions of soft PNIPAM colloidal particles. The size and polydispersity of these particles are characterized using dynamic light scattering (DLS) and scanning electron microscopy (SEM). As these particles are deformable, their packing in aqueous suspensions is quantified in terms of effective volume fraction (ϕeff). The zero shear viscosity (η₀) data of these colloidal suspensions, estimated from rheometric experiments as a function of the effective volume fraction ϕeff of the suspensions, increases with increase in ϕeff and shows a dramatic increase at ϕeff = ϕ₀. The data for η₀ as a function of ϕeff fits well to the Vogel-Fulcher-Tammann equation. It is observed that increasing polydispersity results in increasingly fragile supercooled liquid-like behavior, with the parameter ϕ₀, extracted from the fits to the VFT equation shifting towards higher ϕeff. The observed increase in fragility is attributed to the prevalence of dynamical heterogeneities (DHs) in these polydisperse suspensions, while the simultaneous shift in ϕ₀ is ascribed to the decoupling of the dynamics of the smallest and largest particles. Finally, it is observed that the intrinsic nonlinearity of these suspensions, estimated at the third harmonic near ϕ₀ in Fourier transform oscillatory rheological experiments, increases with increase in polydispersity. These results are in agreement with theoretical predictions and simulation results for polydisperse hard sphere colloidal glasses and clearly demonstrate that jammed suspensions of polydisperse colloidal particles can be effectively fluidized with increasing polydispersity. Suspensions of these particles are therefore excellent candidates for detailed experimental studies of the effects of polydispersity on the dynamics of glass formation.

Keywords: dynamical heterogeneity, effective volume fraction, fragility, intrinsic nonlinearity

Procedia PDF Downloads 141

Authors: Abdul Basit Kiani

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Web development, the art of creating and maintaining websites, has witnessed remarkable advancements. The aim is to provide an overview of some of the cutting-edge developments in the field. Firstly, the rise of responsive web design has revolutionized user experiences across devices. With the increasing prevalence of smartphones and tablets, web developers have adapted to ensure seamless browsing experiences, regardless of screen size. This progress has greatly enhanced accessibility and usability, catering to the diverse needs of users worldwide. Additionally, the evolution of web frameworks and libraries has significantly streamlined the development process. Tools such as React, Angular, and Vue.js have empowered developers to build dynamic and interactive web applications with ease. These frameworks not only enhance efficiency but also bolster scalability, allowing for the creation of complex and feature-rich web solutions. Furthermore, the emergence of progressive web applications (PWAs) has bridged the gap between native mobile apps and web development. PWAs leverage modern web technologies to deliver app-like experiences, including offline functionality, push notifications, and seamless installation. This innovation has transformed the way users interact with websites, blurring the boundaries between traditional web and mobile applications. Moreover, the integration of artificial intelligence (AI) and machine learning (ML) has opened new horizons in web development. Chatbots, intelligent recommendation systems, and personalization algorithms have become integral components of modern websites. These AI-powered features enhance user engagement, provide personalized experiences, and streamline customer support processes, revolutionizing the way businesses interact with their audiences. Lastly, the emphasis on web security and privacy has been a pivotal area of progress. With the increasing incidents of cyber threats, web developers have implemented robust security measures to safeguard user data and ensure secure transactions. Innovations such as HTTPS protocol, two-factor authentication, and advanced encryption techniques have bolstered the overall security of web applications, fostering trust and confidence among users. Hence, recent progress in web development has propelled the industry forward, enabling developers to craft innovative and immersive digital experiences. From responsive design to AI integration and enhanced security, the landscape of web development continues to evolve, promising a future filled with endless possibilities.

Keywords: progressive web applications (PWAs), web security, machine learning (ML), web frameworks, advancement responsive web design

Procedia PDF Downloads 27

Authors: Asmat Nawaz, Ceylan Zafer, Ali K. Erdinc, Kaiying Wang, M. Nadeem Akram

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Hybrid halide Perovskites with the general formula ABX₃, where X = Cl, Br or I, are considered as an ideal candidates for the preparation of photovoltaic devices. The most commonly and successfully used hybrid halide perovskite for photovoltaic applications is CH₃NH₃PbI₃ and its analogue prepared from lead chloride, commonly symbolized as CH₃NH₃PbI₃_ₓClₓ. Some researcher groups are using lead free (Sn replaces Pb) and mixed halide perovskites for the fabrication of the devices. Both mesoporous and planar structures have been developed. By Comparing mesoporous structure in which the perovskite materials infiltrate into mesoporous metal oxide scaffold, the planar architecture is much simpler and easy for device fabrication. In a typical perovskite solar cell, a perovskite absorber layer is sandwiched between the hole and electron transport. Upon the irradiation, carriers are created in the absorber layer that can travel through hole and electron transport layers and the interface in between. We fabricated inverted planar heterojunction structure ITO/PEDOT/ Perovskite/PCBM/Al, based solar cell via two-step spin coating method. This is also called Sequential deposition method. A small amount of cheap additive H₂O was added into PbI₂/DMF to make a homogeneous solution. We prepared four different solution such as (W/O H₂O, 1% H₂O, 2% H₂O, 3% H₂O). After preparing, the whole night stirring at 60℃ is essential for the homogenous precursor solutions. We observed that the solution with 1% H₂O was much more homogenous at room temperature as compared to others. The solution with 3% H₂O was precipitated at once at room temperature. The four different films of PbI₂ were formed on PEDOT substrates by spin coating and after that immediately (before drying the PbI₂) the substrates were immersed in the methyl ammonium iodide solution (prepared in isopropanol) for the completion of the desired perovskite film. After getting desired films, rinse the substrates with isopropanol to remove the excess amount of methyl ammonium iodide and finally dried it on hot plate only for 1-2 minutes. In this study, we added H₂O in the PbI₂/DMF precursor solution. The concept of additive is widely used in the bulk- heterojunction solar cells to manipulate the surface morphology, leading to the enhancement of the photovoltaic performance. There are two most important parameters for the selection of additives. (a) Higher boiling point w.r.t host material (b) good interaction with the precursor materials. We observed that the morphology of the films was improved and we achieved a denser, uniform with less cavities and almost full surface coverage films but only using precursor solution having 1% H₂O. Therefore, we fabricated the complete perovskite solar cell by sequential deposition technique with precursor solution having 1% H₂O. We concluded that with the addition of additives in the precursor solutions one can easily be manipulate the morphology of the perovskite film. In the sequential deposition method, thickness of perovskite film is in µm and the charge diffusion length of PbI₂ is in nm. Therefore, by controlling the thickness using other deposition methods for the fabrication of solar cells, we can achieve the better efficiency.

Keywords: methylammonium lead iodide, perovskite solar cell, precursor composition, sequential deposition

Procedia PDF Downloads 217

Authors: Rajkumar Ghosh

Abstract:

Jhakri Thrust (JT) coeval of Sarahan Thrust (ST) was later considered to be part of Chaura Thrust (CT). The Main Central Thrust (MCT) delimits the southern extreme of Higher Himalaya, whereas the northern boundary defines by South Tibetan Detachment System (STDS). STDS is parallel set of north dipping extensional faults. The activation timing of MCT and STDS. MCT activated in two parts (MCT-L during 15- 0.7 Ma, and MCT-U during 25-14 Ma). Similarly, STDS triggered in two parts (STDS-L during 24-12 Ma, and STDS-U during 19-14 Ma). The activation ages for MBT and MFT. Besides, the MBT occurred during 11-9 Ma, and MFT followed as <2.5 Ma. There are two mylonitised zones (zone of S-C fabric) found under the microscope. Dynamic and bulging recrystallization and sub-grain formation was documented under the optical microscope from samples collected from these zones. The varieties of crenulated schistosity are shown in photomicrographs. In a rare and uncommon case, crenulation cleavage and sigmoid Muscovite were found together side-by-side. Recrystallized quartzo-feldspathic grains exist in between crenulation cleavages. These thin-section studies allow three possible hypotheses for such variations in crenulation cleavages. S/SE verging meso- and micro-scale box folds around Chaura might be a manifestation of some structural upliftment. Near Chaura, kink folds are visible. Prominent asymmetric shear sense indicators in augen mylonite are missing in meso-scale but dominantly present under the microscope. The main foliation became steepest (range of dip ~ 65 – 80 º) at this place. The aim of this section is to characterize the box fold and its signature in the regional geology of Himachal Himalaya. Grain Boundary Migration (GBM) associated temperature range (400–750 ºC) from microstructural studies in grain scale along Jhakri-Wangtu transect documented. Oriented samples were collected from the Jhakri-Chaura transect at a regular interval of ~ 1km for strain analysis. The Higher Himalayan Out-of-Sequence Thrust (OOST) in Himachal Pradesh is documented a decade ago. The OOST in other parts of the Himalayas is represented as a line in between MCTL and MCTU. But In Himachal Pradesh area, OOST activated the MCTL as well as in between a zone located south of MCTU. The expectations for strain variation near the OOST are very obvious. But multiple sets of OOSTs may produce a zigzag pattern of strain accumulation for this area and figure out the overprinting structures for multiple sets of OOSTs.

Keywords: Chaura Thrust, out-of-sequence thrust, Main Central Thrust, Sarahan Thrust

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Authors: Zhijie Li, Wenhui Peng, Zelong Yuan, Jianchun Wang

Abstract:

Turbulence is a complex phenomenon that plays a crucial role in various fields, such as engineering, atmospheric science, and fluid dynamics. Predicting and understanding its behavior over long time scales have been challenging tasks. Traditional methods, such as large-eddy simulation (LES), have provided valuable insights but are computationally expensive. In the past few years, machine learning methods have experienced rapid development, leading to significant improvements in computational speed. However, ensuring stable and accurate long-term predictions remains a challenging task for these methods. In this study, we introduce the implicit U-net enhanced Fourier neural operator (IU-FNO) as a solution for stable and efficient long-term predictions of the nonlinear dynamics in three-dimensional (3D) turbulence. The IU-FNO model combines implicit re-current Fourier layers to deepen the network and incorporates the U-Net architecture to accurately capture small-scale flow structures. We evaluate the performance of the IU-FNO model through extensive large-eddy simulations of three types of 3D turbulence: forced homogeneous isotropic turbulence (HIT), temporally evolving turbulent mixing layer, and decaying homogeneous isotropic turbulence. The results demonstrate that the IU-FNO model outperforms other FNO-based models, including vanilla FNO, implicit FNO (IFNO), and U-net enhanced FNO (U-FNO), as well as the dynamic Smagorinsky model (DSM), in predicting various turbulence statistics. Specifically, the IU-FNO model exhibits improved accuracy in predicting the velocity spectrum, probability density functions (PDFs) of vorticity and velocity increments, and instantaneous spatial structures of the flow field. Furthermore, the IU-FNO model addresses the stability issues encountered in long-term predictions, which were limitations of previous FNO models. In addition to its superior performance, the IU-FNO model offers faster computational speed compared to traditional large-eddy simulations using the DSM model. It also demonstrates generalization capabilities to higher Taylor-Reynolds numbers and unseen flow regimes, such as decaying turbulence. Overall, the IU-FNO model presents a promising approach for long-term dynamics prediction in 3D turbulence, providing improved accuracy, stability, and computational efficiency compared to existing methods.

Keywords: data-driven, Fourier neural operator, large eddy simulation, fluid dynamics

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Authors: Guoyu Wang, Meilian Zhang, Chunhui LI, Bing Ren

Abstract:

In recent decades, a variety of floating structures have played a crucial role in ocean and marine engineering, such as ships, offshore platforms, floating breakwaters, fish farms, floating airports, etc. It is common for floating structures to suffer from loadings under waves, and the responses of the structures mounted in marine environments have a significant relation to the wave impacts. The interaction between surface waves and floating structures is one of the important issues in ship or marine structure design to increase performance and efficiency. With the progress of computational fluid dynamics, a number of numerical models based on the NS equations in the time domain have been developed to explore the above problem, such as the finite difference method or the finite volume method. Those traditional numerical simulation techniques for moving bodies are grid-based, which may encounter some difficulties when treating a large free surface deformation and a moving boundary. In these models, the moving structures in a Lagrangian formulation need to be appropriately described in grids, and the special treatment of the moving boundary is inevitable. Nevertheless, in the mesh-based models, the movement of the grid near the structure or the communication between the moving Lagrangian structure and Eulerian meshes will increase the algorithm complexity. Fortunately, these challenges can be avoided by the meshless particle methods. In the present study, a moving particle semi-implicit model is explored for the numerical simulation of fluid–structure interaction with surface flows, especially for coupling of fluid and moving rigid body. The equivalent momentum transfer method is proposed and derived for the coupling of fluid and rigid moving body. The structure is discretized into a group of solid particles, which are assumed as fluid particles involved in solving the NS equation altogether with the surrounding fluid particles. The momentum conservation is ensured by the transfer from those fluid particles to the corresponding solid particles. Then, the position of the solid particles is updated to keep the initial shape of the structure. Using the proposed method, the motions of a free-floating body in regular waves are numerically studied. The wave surface evaluation and the dynamic response of the floating body are presented. There is good agreement when the numerical results, such as the sway, heave, and roll of the floating body, are compared with the experimental and other numerical data. It is demonstrated that the presented MPS model is effective for the numerical simulation of fluid-structure interaction.

Keywords: floating body, fluid structure interaction, MPS, particle method, waves

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Authors: Christian Doppler, Gernot Hirschl, Gerhard Zsiga

Abstract:

Starting from 2020, an EU-wide CO2-limitation of 95g/km is scheduled for the average of an OEMs passenger car fleet. Considering that, further measures of optimization on the diesel cycle will be necessary in order to reduce fuel consumption and emissions while keeping performance values adequate at the least. The present article deals with charge air cooling (CAC) on the basis of a diesel passenger car model in a 0D/1D-working process calculation environment. The considered engine is a 2.4 litre EURO VI diesel engine with variable geometry turbocharger (VGT) and low-pressure exhaust gas recirculation (LP EGR). The object of study was the impact of charge air cooling on the engine working process at constant boundary conditions which could have been conducted with an available and validated engine model in AVL BOOST. Part load was realized with constant power and NOx-emissions, whereas full load was accomplished with a lambda control in order to obtain maximum engine performance. The informative results were used to implement a simulation model in Matlab/Simulink which is further integrated into a full vehicle simulation environment via coupling with ICOS (Independent Co-Simulation Platform). Next, the dynamic engine behavior was validated and modified with load steps taken from the engine test bed. Due to the modular setup in the Co-Simulation, different CAC-models have been simulated quickly with their different influences on the working process. In doing so, a new cooler variation isn’t needed to be reproduced and implemented into the primary simulation model environment, but is implemented quickly and easily as an independent component into the simulation entity. By means of the association of the engine model, longitudinal dynamics vehicle model and different CAC models (air/air & water/air variants) in both steady state and transient operational modes, statements are gained regarding fuel consumption, NOx-emissions and power behavior. The fact that there is no more need of a complex engine model is very advantageous for the overall simulation volume. Beside of the simulation with the mentioned demonstrator engine, there have also been conducted several experimental investigations on the engine test bench. Here the comparison of a standard CAC with an intake-manifold-integrated CAC was executed in particular. Simulative as well as experimental tests showed benefits for the water/air CAC variant (on test bed especially the intake manifold integrated variant). The benefits are illustrated by a reduced pressure loss and a gain in air efficiency and CAC efficiency, those who all lead to minimized emission and fuel consumption for stationary and transient operation.

Keywords: air/water-charge air cooler, co-simulation, diesel working process, EURO VI fuel consumption

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