Search results for: estimation of properties of the model

Authors: Youn Young Shim, Ji Hye Kim, Jae Youl Cho, Martin JT Reaney

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Flaxseed (Linumusitatissimum L.) is gaining popularity in the food industry as a superfood due to its health-promoting properties. Linusorbs (LOs, a.k.a. Cyclolinopeptide) are bioactive compounds present in flaxseed exhibiting potential health effects. The study focused on the effects of processing and storage on the stability of flaxseed-derived LOs added to various bakery products. The flaxseed meal fortified gluten-free (GF) bakery bread was prepared, and the changes of LOs during the bread-making process (meal, fortified flour, dough, and bread) and storage (0, 1, 2, and 4 weeks) at different temperatures (−18 °C, 4 °C, and 22−23 °C) were analyzed by high-performance liquid chromatography-diode array detection. The total oxidative LOs and LO1OB2 were almost kept stable in flaxseed meals at storage temperatures of 22−23 °C, −18 °C, and 4 °C for up to four weeks. Processing steps during GF-bread production resulted in the oxidation of LOs. Interestingly, no LOs were detected in the dough sample; however, LOs appeared when the dough was stored at −18 °C for one week, suggesting that freezing destroyed the sticky structure of the dough and resulted in the release of LOs. The final product, flaxseed meal fortified bread, could be stored for up to four weeks at −18 °C and 4 °C, and for one week at 22−23 °C. All these results suggested that LOs may change during processing and storage and that flaxseed flour-fortified bread should be stored at low temperatures to preserve effective LOs components.

Keywords: linum usitatissimum L., flaxseed, linusorb, stability, gluten-free, peptides, cyclolinopeptide

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Authors: Mohammad Hossein Modarressi, Mozhgan Mondeali, Khabat Barkhordari, Ali Etemadi

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The COVID-19 pandemic, caused by SARS-CoV-2, has led to significant concerns worldwide due to its catastrophic effects on public health. The SARS-CoV-2 infection is initiated with the binding of the receptor-binding domain (RBD) in its spike protein to the ACE2 receptor in the host cell membrane. Due to the error-prone entity of the viral RNA-dependent polymerase complex, the virus genome, including the coding region for the RBD, acquires new mutations, leading to the appearance of multiple variants. These variants can potentially impact transmission, virulence, antigenicity and evasive immune properties. S477N mutation located in the RBD has been observed in the SARS-CoV-2 omicron (B.1.1. 529) variant. In this study, we investigated the consequences of S477N mutation at the molecular level using computational approaches such as molecular dynamics simulation, protein-protein interaction analysis, immunoinformatics and free energy computation. We showed that displacement of Ser with Asn increases the stability of the spike protein and its affinity to ACE2 and thus increases the transmission potential of the virus. This mutation changes the folding and secondary structure of the spike protein. Also, it reduces antibody neutralization, raising concern about re-infection, vaccine breakthrough and therapeutic values.

Keywords: S477N, COVID-19, molecular dynamic, SARS-COV2 mutations

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Authors: Busari Moshood Olanyi

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Good governance remains the expectation of every political party in power, especially in this democratic dispensation of the Nigerian Nation. The need to ensure that the citizenry enjoys the dividends of democracy as often promised during various electioneering campaigns is envisioned to be the motif for different agendas and political slogans by different administrations. Unfortunately, different political agendas towards the security of lives and properties, halting the pillage of the economy by corrupt public officials and creation of employment opportunities for the youths, have a record of setback in the history of political leadership and governance in Nigeria. Therefore, the paper examined the principles of Islamic theocracy in its advocacy for a paradigm shift in the Nigerian political system, with a view to engendering good governance. Islamic political terms such as Shūrā (mutual consultation), ‘Adālah (equality and justice), Khilāfah (succession and stewardship) Majlis ash-Shūrā (consultative forum) and Muḥāsabah (accountability) were espoused as sacrosanct to implementing Islamic theocracy as an alternative system of government in Nigeria. The paper concluded by being flexible on the nomenclature of the suggested political system, considering the multi-religious nature of the country as a political entity. Among other recommendations, infusion of politics into our moral/religious system and not the other way round was considered a good step in the direction of a political paradigm shift for ensuring good governance and guaranteeing its sustainability in Nigeria.

Keywords: Nigerian nation, democracy, good governance, Islamic theocracy, paradigm shift

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Authors: A. Siva, K. Bala Subramanian, Kinson Prabu

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Concrete is widely used construction materials all over the world. Now a day’s fibers are used in this construction due to its advantages like increase in stiffness, energy absorption, ductility and load carrying capacity. The fiber used in the concrete to increases the structural integrity of the member. It is one of the emerging techniques used in the construction industry. In this paper, the effective utilization of high-performance fiber reinforced concrete (HPFRC) beams has been experimental investigated. The experimental investigation has been conducted on different steel fibers (Hooked, Crimpled, and Hybrid) under cyclic loading. The behaviour of HPFRC beams is compared with the conventional beams. Totally four numbers of specimens were cast with different content of fiber concrete and compared conventional concrete. The fibers are added to the concrete by base volume replacement of concrete. The silica fume and superplasticizers were used to modify the properties of concrete. Single point loading was carried out for all the specimens, and the beam specimens were subjected to cyclic loading. The load-deflection behaviour of fibers is compared with the conventional concrete. The ultimate load carrying capacity, energy absorption and ductility of hybrid fiber reinforced concrete is higher than the conventional concrete by 5% to 10%.

Keywords: cyclic loading, ductility, high performance fiber reinforced concrete, structural integrity

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Authors: Safdar Muhammad Usman, Youji Kohda, Katsuhiro Umemoto

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Electronic market place plays an important intermediary role for connecting dealers and retail customers. The main aim of this paper is to design a value co-creation model in used-car auctions. More specifically, the study has been designed in order to describe the process of value co-creation in used-car auctions, to explore the co-created values in used-car auctions, and finally conclude the paper indicating the future research directions. Our analysis shows that economic values as well as non-economic values are co-created in used-car auctions. In addition, this paper contributes to the academic society broadening the view of value co-creation in service science.

Keywords: value co-creation, used-car auctions, non-financial values, service science

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Authors: Hamed Sadeghi, Pouya A. Panahi, Hamed Nasiri, Mohammad Sadeghi

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Collapsible soils like loess comprise an important category of problematic soils for construction purposes and sustainable development. As a result, research on both geological and geotechnical aspects of this type of soil have been in progress for decades. However, considerable natural variability in physical properties of in-situ loess strata even in a single block sample challenges the fundamental laboratory investigations. The reason behind this is that it is somehow impossible to remove the effect of a specific factor like void ratio from fair comparisons to come with a reliable conclusion. In order to cope with this limitation, two types of artificially made dispersive and calcareous loess are introduced which can be easily reproduced in any soil mechanics laboratory provided that all its compositions are known and controlled. The collapse potential is explored for a variety of soil water salinity and lime content and comparisons are made against the natural soil behavior. Trends are reported for the influence of pore water salinity on collapse potential under different osmotic flow conditions. The most important advantage of artificial loess is the ease of controlling cementing agent content like calcite or dispersive potential for studying their influence on mechanical soil behavior.

Keywords: artificial loess, unsaturated soils, collapse potential, dispersive clays, laboratory tests

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Authors: Ho-Won Jung, Donghun Lee, Hyung-Jin Kim

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Predictive analytics (data analysis) uses a subset of measurements (the features, predictor, or independent variable) to predict another measurement (the outcome, target, or dependent variable) on a single person or unit. It applies empirical methods in statistics, operations research, and machine learning to predict the future, or otherwise unknown events or outcome on a single or person or unit, based on patterns in data. Most analyses of metabolic syndrome are not predictive analytics but statistical explanatory studies that build a proposed model (theory building) and then validate metabolic syndrome predictors hypothesized (theory testing). A proposed theoretical model forms with causal hypotheses that specify how and why certain empirical phenomena occur. Predictive analytics and explanatory modeling have their own territories in analysis. However, predictive analytics can perform vital roles in explanatory studies, i.e., scientific activities such as theory building, theory testing, and relevance assessment. In the context, this study is to demonstrate how to use our predictive analytics to support theory building (i.e., hypothesis generation). For the purpose, this study utilized a big data predictive analytics platform TM based on a co-occurrence graph. The co-occurrence graph is depicted with nodes (e.g., items in a basket) and arcs (direct connections between two nodes), where items in a basket are fully connected. A cluster is a collection of fully connected items, where the specific group of items has co-occurred in several rows in a data set. Clusters can be ranked using importance metrics, such as node size (number of items), frequency, surprise (observed frequency vs. expected), among others. The size of a graph can be represented by the numbers of nodes and arcs. Since the size of a co-occurrence graph does not depend directly on the number of observations (transactions), huge amounts of transactions can be represented and processed efficiently. For a demonstration, a total of 13,254 metabolic syndrome training data is plugged into the analytics platform to generate rules (potential hypotheses). Each observation includes 31 predictors, for example, associated with sociodemographic, habits, and activities. Some are intentionally included to get predictive analytics insights on variable selection such as cancer examination, house type, and vaccination. The platform automatically generates plausible hypotheses (rules) without statistical modeling. Then the rules are validated with an external testing dataset including 4,090 observations. Results as a kind of inductive reasoning show potential hypotheses extracted as a set of association rules. Most statistical models generate just one estimated equation. On the other hand, a set of rules (many estimated equations from a statistical perspective) in this study may imply heterogeneity in a population (i.e., different subpopulations with unique features are aggregated). Next step of theory development, i.e., theory testing, statistically tests whether a proposed theoretical model is a plausible explanation of a phenomenon interested in. If hypotheses generated are tested statistically with several thousand observations, most of the variables will become significant as the p-values approach zero. Thus, theory validation needs statistical methods utilizing a part of observations such as bootstrap resampling with an appropriate sample size.

Keywords: explanatory modeling, metabolic syndrome, predictive analytics, theory building

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Authors: Man-Yun Liu, Emily Chia-Yu Su

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Alzheimer's disease (AD) is the public health crisis of the 21st century. AD is a degenerative brain disease and the most common cause of dementia, a costly disease on the healthcare system. Unfortunately, the cause of AD is poorly understood, furthermore; the treatments of AD so far can only alleviate symptoms rather cure or stop the progress of the disease. Currently, there are several ways to diagnose AD; medical imaging can be used to distinguish between AD, other dementias, and early onset AD, and cerebrospinal fluid (CSF). Compared with other diagnostic tools, blood (plasma) test has advantages as an approach to population-based disease screening because it is simpler, less invasive also cost effective. In our study, we used blood biomarkers dataset of The Alzheimer’s disease Neuroimaging Initiative (ADNI) which was funded by National Institutes of Health (NIH) to do data analysis and develop a prediction model. We used independent analysis of datasets to identify plasma protein biomarkers predicting early onset AD. Firstly, to compare the basic demographic statistics between the cohorts, we used SAS Enterprise Guide to do data preprocessing and statistical analysis. Secondly, we used logistic regression, neural network, decision tree to validate biomarkers by SAS Enterprise Miner. This study generated data from ADNI, contained 146 blood biomarkers from 566 participants. Participants include cognitive normal (healthy), mild cognitive impairment (MCI), and patient suffered Alzheimer’s disease (AD). Participants’ samples were separated into two groups, healthy and MCI, healthy and AD, respectively. We used the two groups to compare important biomarkers of AD and MCI. In preprocessing, we used a t-test to filter 41/47 features between the two groups (healthy and AD, healthy and MCI) before using machine learning algorithms. Then we have built model with 4 machine learning methods, the best AUC of two groups separately are 0.991/0.709. We want to stress the importance that the simple, less invasive, common blood (plasma) test may also early diagnose AD. As our opinion, the result will provide evidence that blood-based biomarkers might be an alternative diagnostics tool before further examination with CSF and medical imaging. A comprehensive study on the differences in blood-based biomarkers between AD patients and healthy subjects is warranted. Early detection of AD progression will allow physicians the opportunity for early intervention and treatment.

Keywords: Alzheimer's disease, blood-based biomarkers, diagnostics, early detection, machine learning

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Authors: Mona Mahmoud Abou Samra, Alaa Hamed Salama, Ghada Awad, Soheir Said Mansy

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Proniosomes are well documented for topical drug delivery and preferred over other vesicular systems because they are biodegradable, biocompatible, non-toxic, possess skin penetration ability and prolong the release of drugs by acting as depot in deeper layers of skin. Proniosome drug delivery was preferred due to improved stability of the system than niosomes. The present investigation aimed at formulation development and performance evaluation of proniosomal gel as a vesicular drug carrier system for antifungal drug tolnaftate. Proniosomes was developed using different nonionic surfactants such as span 60 and span 65 with cholesterol in different molar ratios by the Coacervation phase separation method in presence or absence of either lecithin or phospholipon 80 H. Proniosomal gel formulations of tolnaftate were characterized for vesicular shape & size, entrapment efficiency, rheological properties and release study. The effect of surfactants and additives on the entrapment efficiency, particle size and percent of drug released was studied. The selected proniosomal formulations for topical delivery of tolnaftate was subjected to a microbiological study in male rats infected with Trichophyton rubrum; the main cause of Tinea Pedis compared to the free drug and a market product and the results was recorded.

Keywords: fungal infection, proniosome, tolnaftate, trichophyton rubrum

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Authors: Feleke Tsegaye

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The work in this thesis mainly focuses on trajectory tracking of fixed wing unmanned aerial vehicle (FWUAV) by using fuzzy based sliding mode controller(FSMC) for surveillance applications. Unmanned Aerial Vehicles (UAVs) are general-purpose aircraft built to fly autonomously. This technology is applied in a variety of sectors, including the military, to improve defense, surveillance, and logistics. The model of FWUAV is complex due to its high non-linearity and coupling effect. In this thesis, input decoupling is done through extracting the dominant inputs during the design of the controller and considering the remaining inputs as uncertainty. The proper and steady flight maneuvering of UAVs under uncertain and unstable circumstances is the most critical problem for researchers studying UAVs. A FSMC technique was suggested to tackle the complexity of FWUAV systems. The trajectory tracking control algorithm primarily uses the sliding-mode (SM) variable structure control method to address the system’s control issue. In the SM control, a fuzzy logic control(FLC) algorithm is utilized in place of the discontinuous phase of the SM controller to reduce the chattering impact. In the reaching and sliding stages of SM control, Lyapunov theory is used to assure finite-time convergence. A comparison between the conventional SM controller and the suggested controller is done in relation to the chattering effect as well as tracking performance. It is evident that the chattering is effectively reduced, the suggested controller provides a quick response with a minimum steady-state error, and the controller is robust in the face of unknown disturbances. The designed control strategy is simulated with the nonlinear model of FWUAV using the MATLAB® / Simulink® environments. The simulation result shows the suggested controller operates effectively, maintains an aircraft’s stability, and will hold the aircraft’s targeted flight path despite the presence of uncertainty and disturbances.

Keywords: fixed-wing UAVs, sliding mode controller, fuzzy logic controller, chattering, coupling effect, surveillance, finite-time convergence, Lyapunov theory, flight path

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Authors: Babak Forouraghi

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A genetic circuit is a collection of interacting genes and proteins that enable individual cells to implement and perform vital biological functions such as cell division, growth, death, and signaling. In cell engineering, synthetic gene circuits are engineered networks of genes specifically designed to implement functionalities that are not evolved by nature. These engineered networks enable scientists to tackle complex problems such as engineering cells to produce therapeutics within the patient's body, altering T cells to target cancer-related antigens for treatment, improving antibody production using engineered cells, tissue engineering, and production of genetically modified plants and livestock. Construction of computational models to realize genetic circuits is an especially challenging task since it requires the discovery of the flow of genetic information in complex biological systems. Building synthetic biological models is also a time-consuming process with relatively low prediction accuracy for highly complex genetic circuits. The primary goal of this study was to investigate the utility of a pre-trained bidirectional encoder transformer that can accurately predict gene expressions in genetic circuit designs. The main reason behind using transformers is their innate ability (attention mechanism) to take account of the semantic context present in long DNA chains that are heavily dependent on the spatial representation of their constituent genes. Previous approaches to gene circuit design, such as CNN and RNN architectures, are unable to capture semantic dependencies in long contexts, as required in most real-world applications of synthetic biology. For instance, RNN models (LSTM, GRU), although able to learn long-term dependencies, greatly suffer from vanishing gradient and low-efficiency problem when they sequentially process past states and compresses contextual information into a bottleneck with long input sequences. In other words, these architectures are not equipped with the necessary attention mechanisms to follow a long chain of genes with thousands of tokens. To address the above-mentioned limitations, a transformer model was built in this work as a variation to the existing DNA Bidirectional Encoder Representations from Transformers (DNABERT) model. It is shown that the proposed transformer is capable of capturing contextual information from long input sequences with an attention mechanism. In previous works on genetic circuit design, the traditional approaches to classification and regression, such as Random Forrest, Support Vector Machine, and Artificial Neural Networks, were able to achieve reasonably high R2 accuracy levels of 0.95 to 0.97. However, the transformer model utilized in this work, with its attention-based mechanism, was able to achieve a perfect accuracy level of 100%. Further, it is demonstrated that the efficiency of the transformer-based gene expression classifier is not dependent on the presence of large amounts of training examples, which may be difficult to compile in many real-world gene circuit designs.

Keywords: machine learning, classification and regression, gene circuit design, bidirectional transformers

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Authors: Julia Wicker, Alexander Lang

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The shortage of skilled workers is no longer unique to Europe; Australia now faces similar challenges, particularly in the field of project management. Project managers, essential to the success of a wide range of industries, frequently operate under intense stress and, as a result, may choose to leave their positions before the completion of their projects. This trend poses significant risks to project continuity, budget stability, and the long-term success of organizations. Consequently, it is crucial to explore strategies aimed at improving the retention of project managers, with a specific focus on fostering intrinsic motivation -an essential factor for achieving sustained success and commitment within project-based roles. The aim of this paper is to investigate retention strategies from other industries to identify effective practices that could be adapted to the unique challenges faced by project managers. In particular, the paper draws inspiration from the volunteer sector, an industry also heavily reliant on intrinsic motivation to drive commitment and performance. By examining how the volunteer sector sustains retention through a focus on intrinsic motivation, this paper seeks to highlight potential parallels and offer actionable insights for improving the retention of project managers. The paper includes an overview of the current landscape of retention challenges in project management, highlighting key factors that contribute to early departures and their impacts on organizations. This is followed by an analysis of interviews conducted with both active volunteers and those who have left their roles, leading to the development of a model that categorizes different types of volunteers and explores their behaviours. The model identifies specific reasons for volunteer terminating their assignments and proposes strategies to mitigate these issues. The paper then adapts these volunteer retention strategies to address the challenges faced by project managers, concluding with actionable recommendations for fostering an intrinsically motivated and resilient project management workforce. Ultimately, this research aims to contribute to broader efforts in mitigating skilled workforce shortages by offering sustainable retention strategies.

Keywords: skilled workforce shortages, retention challenges in project management, retention strategies in the volunteering sector, retention strategies for project managers

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Authors: Michela Terlizzi, Chiara Colarusso, Aldo Pinto, Rosalinda Sorrentino

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Sphingosine-1-phosphate (S1P) is a membrane-derived bioactive phospholipid exerting a multitude of effects on respiratory cell physiology and pathology through five S1P receptors (S1PR1-5). Higher levels of S1P have been registered in a broad range of respiratory diseases, including inflammatory disorders and cancer, although its exact role is still elusive. Based on our previous study in which we found that S1P/S1PR3 is involved in an inflammatory pattern via the activation of Toll-like Receptor 9 (TLR9), highly expressed on lung cancer cells, the main goal of the current study was to better understand the involvement of S1P/S1PR3 pathway/signaling during lung carcinogenesis, taking advantage of a mouse model of first-hand smoke exposure and of carcinogen-induced lung cancer. We used human samples of Non-Small Cell Lung Cancer (NSCLC), a mouse model of first-hand smoking, and of Benzo(a)pyrene (BaP)-induced tumor-bearing mice and A549 lung adenocarcinoma cells. We found that the intranuclear, but not the membrane, localization of S1PR3 was associated to the proliferation of lung adenocarcinoma cells, the mechanism that was correlated to human and mouse samples of smoke-exposure and carcinogen-induced lung cancer, which were characterized by higher utilization of S1P. Indeed, the inhibition of the membrane S1PR3 did not alter tumor cell proliferation after TLR9 activation. Instead, according to the nuclear localization of sphingosine kinase (SPHK) II, the enzyme responsible for the catalysis of the S1P last step synthesis, the inhibition of the kinase completely blocked the endogenous S1P-induced tumor cell proliferation. These results prove that the endogenous TLR9-induced S1P can on one side favor pro-inflammatory mechanisms in the tumor microenvironment via the activation of cell surface receptors, but on the other tumor progression via the nuclear S1PR3/SPHK II axis, highlighting a novel molecular mechanism that identifies S1P as one of the crucial mediators for lung carcinogenesis-associated inflammatory processes and that could provide differential therapeutic approaches especially in non-responsive lung cancer patients.

Keywords: sphingosine-1-phosphate (S1P), S1P Receptor 3 (S1PR3), smoking-mice, lung inflammation, lung cancer

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Authors: Changyong Liu, Junda Tong, Feng Xu, Ninggui Huang

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In the injection molding process, the performance of cooling channels is crucial to the part quality. Through the application of conformal cooling channels fabricated via metal additive manufacturing, part distortion, warpage can be greatly reduced and cycle time can be greatly shortened. However, the properties of additively manufactured conformal cooling channels are quite different from conventional drilling processes such as the poorer dimensional accuracy and larger surface roughness. These features have significant influences on its cooling performance. In this study, test molds with the cooling channel diameters of φ2 mm, φ3 mm and φ4 mm were fabricated via selective laser melting and conventional drilling process respectively. A test system was designed and manufactured to measure the pressure difference between the channel inlet and outlet, the coolant flow rate and the temperature variation during the heating process. It was found that the cooling performance of SLM-fabricated channels was poorer than drilled cooling channels due to the smaller sectional area of cooling channels resulted from the low dimensional accuracy and the unmolten particles adhered to the channel surface. Theoretical models were established to determine the friction factor and heat transfer coefficient of SLM-fabricated cooling channels. These findings may provide guidance to the design of conformal cooling channels.

Keywords: conformal cooling channels, selective laser melting, cooling performance, injection molding

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Authors: P. C. Ihenacho, M. Burby, G. G. Nasr, G. C. Enyi

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Formulation of a low oil-water ratio drilling mud with vegetable oil continuous phase without adversely affecting the mud rheology and stability has been a major challenge. A low oil-water ratio is beneficial in producing low fluid loss which is essential for wellbore stability. This study examined the possibility of 50/50 oil-water ratio invert emulsion drilling mud using a vegetable oil continuous phase. Jatropha oil was used as continuous phase. 12 ml of egg yolk which was separated from the albumen was added as the primary emulsifier additive. The rheological, stability and filtration properties were examined. The plastic viscosity and yield point were found to be 36cp and 17 Ib/100 ft2 respectively. The electrical stability at 48.9ºC was 353v and the 30 minutes fluid loss was 6ml. The results compared favourably with a similar formulation using 70/30 oil - water ratio giving plastic viscosity of 31cp, yield point of 17 Ib/100 ft2, electrical stability value of 480v and 12ml for the 30 minutes fluid loss. This study indicates that with a good mud composition using guided empiricism, 50/50 oil-water ratio invert emulsion drilling mud is feasible with a vegetable oil continuous phase. The choice of egg yolk as emulsifier additive is for compatibility with the vegetable oil and environmental concern. The high water content with no fluid loss additive will also minimise the cost of mud formulation.

Keywords: environmental compatibility, low cost of mud formulation, low fluid loss, wellbore stability

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Authors: Dorra Gherib

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This article explores in depth the technological innovations by the Top Managements of banks in the Tunisian banking sector. The framework of this research is based on an amalgamation of four theories related to the decision of adopting technological innovations: The Theory of Reasoned Action (TRA), the Theory of Planned Behaviour (TPB), Technology Acceptance Model (TAM), and Diffusion of Innovation (DI). The result of our qualitative study highlights four variables which influence the attitude of the Top Managements towards the adoption of internet banking: Relative advantage, Perceived Ease of Use, compatibility and Perceived risk.

Keywords: top management, attitude, internet banking, TRA, TAM, TPB, DI

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Authors: Mladen Jankovic, Biljana Djuric, Djurdja Oljaca, Vladimir Damjanovic, Radislav Filipovic, Zoran Obrenovic

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One of the key characteristics of zeolites with ZSM-5 crystalline form is the possibility of synthesis in a wide range of molar ratios, from the relatively low ratio of about 20 to highly silicate forms with a Si/Al ratio over 1000. For industrial production and commercial use of this type of zeolite, it is very important to know the influence of the molar Si/Al ratio on the characteristics of zeolite powders. In this paper, the influence of the Si/Al ratio on the characteristics of H-ZSM-5 zeolites synthesized in the presence of tetrapropylammonium bromide is questioned, including the possibility of conversion to the H-form using different acids. The quality of the samples is characterized in terms of crystallinity, chemical composition, morphology, granulometry, specific surface area (BET), pore size and acidity. XRD, FT-IR, EDX, ICP, SEM and TPD instrumental techniques were used to characterize the samples. In most of the performed syntheses, zeolite has been obtained with very good properties. It was shown that the examined conditions have a significant influence on the characteristics of the synthesized powders. The different chemical composition of the starting mixture, ie. the Si/Al ratio, has a very significant influence on the crystal structure of the synthesized powders, and thus on the other tested characteristics. It has been observed that optimal ion exchange results for powders of different Si/Al ratios are achieved by using different acids. Also, the dependence of the specific surface on the concentration of H+ or Na+ ions was confirmed.

Keywords: Characterisation, H-ZSM-5, molar ratio, synthesis, tetrapropylammonium bromide

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Authors: Abdullah Alnutayfat, Alexander Sutin, Dong Liu

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Wind turbine has become one of the most popular energy productions. However, failure of blades and maintenance costs evolve into significant issues in the wind power industry, so it is essential to detect the initial blade defects to avoid the collapse of the blades and structure. This paper aims to apply modulation of high-frequency blade vibrations by low-frequency blade rotation, which is close to the known Vibro-Acoustic Modulation (VAM) method. The high-frequency wideband blade vibration is produced by the interaction of the surface blades with the environment air turbulence, and the low-frequency modulation is produced by alternating bending stress due to gravity. The low-frequency load of rotational wind turbine blades ranges between 0.2-0.4 Hz and can reach up to 2 Hz for strong wind. The main difference between this study and previous ones on VAM methods is the use of a wideband vibration signal from the blade's natural vibrations. Different features of the vibroacoustic modulation are considered using a simple model of breathing crack. This model considers the simple mechanical oscillator, where the parameters of the oscillator are varied due to low-frequency blade rotation. During the blade's operation, the internal stress caused by the weight of the blade modifies the crack's elasticity and damping. The laboratory experiment using steel samples demonstrates the possibility of VAM using a probe wideband noise signal. A cycle load with a small amplitude was used as a pump wave to damage the tested sample, and a small transducer generated a wideband probe wave. The received signal demodulation was conducted using the Detecting of Envelope Modulation on Noise (DEMON) approach. In addition, the experimental results were compared with the modulation index (MI) technique regarding the harmonic pump wave. The wideband and traditional VAM methods demonstrated similar sensitivity for earlier detection of invisible cracks. Importantly, employing a wideband probe signal with the DEMON approach speeds up and simplifies testing since it eliminates the need to conduct tests repeatedly for various harmonic probe frequencies and to adjust the probe frequency.

Keywords: vibro-acoustic modulation, detecting of envelope modulation on noise, damage, turbine blades

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Authors: Fazli Idris, Jihad Mohammad

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The study aims to determine the impact of technology and service operations flexibility, which is divided into external flexibility and internal robustness, on operations costs. A mediation model is proposed that links technology to operations costs via operation flexibility. Drawing on a sample of 475 of operations managers of various service sectors in Malaysia and South Africa, Structural Equation Modeling (SEM) was employed to test the relationship using Smart-PLS procedures. It was found that a significant relationship was established between technologies to operations costs via both operations flexibility dimensions. Theoretical and managerial implications are offered to explain the results.

Keywords: Operations flexibility, technology, costs, mediation

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Authors: Matheus Nunes, Rafael Mendes, Taygoara Felamingo Oliveira, Antonio Brasil Junior

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Wind tunnel experiments of horizontal axis propeller hydrokinetic turbines model were carried out, in order to determine the performance behavior for different configurations and operational range. The present experiments introduce the use of two different geometries of rear diffusers to enhance the performance of the free flow machine. The present paper reports an increase of the power coefficient about 50%-80%. It represents an important feature that has to be taken into account in the design of this kind of machine.

Keywords: diffuser-enhanced turbines, hydrokinetic turbine, wind tunnel experiments, micro hydro

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Authors: Nadjette Belhamra, Abdelouahed Chala, Ibrahim Guasmi

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Titanium nitride coatings have been extensively used in industry, such as in cutting tools. TiN coating were deposited by chemical vapour deposition (CVD) on carbide insert at a temperature between 850°C and 1100°C, which often exceeds the hardening treatment temperature of the metals. The objective of this work is to realize, to characterize of TiN coating and to apply it in the turning of steel 42CrMo4 under lubrification. Various experimental techniques were employed for the microstructural characterization of the coatings, e. g., X-ray diffraction (XRD), scanning electron microscope (SEM) model JOEL JSM-5900 LV, equipped with energy dispersive X-ray (EDX). The results show that TiN-coated demonstrate a good wear resistance.

Keywords: hard coating TiN, carbide inserts, machining, turning, wear

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Authors: Tariq Bashir, Muhammad Waseem Tahir, Ulf Stigh, Behnaz Baghaie, Mikael Skrifvars

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Absorption of moisture may cause many problems in a composite material, such as delamination, degradation of the strength and increase in the weight. For small coupons, the increase in weight may be negligible, however, for large structures increase in weight due to moisture absorption may be quite significant. Polyamides (PA6, PA66) absorb more moisture as compared to other thermoplastics. There are many parameters which affect the moisture absorption of the composite material for example temperature, pressure, type of matrix and fibers, thickness of the material and relative humidity (RH) etc. So, it is utmost important to investigate the impact of moisture on PA66 based composites which can be done by characterizing the mechanical properties of composite materials both for dry and wet conditions. In this study, laminates of C/PA66 composite are manufactured by first heating the commingled material in conventional oven at a temperature of 220 °C followed by pressing in a manual hot press for 20 minutes with preheated platen at 220 °C. To observe the moisture absorption of the composite, coupons of the material were placed in a climate chamber at five different conditions 0, 25, 50, 75 and 100% RH for 24 hours. Five specimens were used for each condition. These coupons were weighed before placing in the climate chamber and just after removing from the chamber to observe the moisture absorption of the material. The mechanical characterization such as tensile strength, flexural modulus, impact strength and DMTA of C/PA66 material are performed at 0, 50 and 100 % RH. The work is going on for the testing of the material and results will be presented in full paper.

Keywords: Carbon/Polyamide 66 composites, structural composites, mechanical characterizations, wet and dry conditions

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Authors: S. Teimouri, S. Abbasi

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Milk-fruit juice mixture is a type of soft drinks, which can be produced by mixing milk with pieces of fruits, fruit juices, or fruit juices concentrates. The major problem of these products, mainly the acidic ones, is phase separation which occurs during formulation and storage due to the aggregation of caseins at low pH Short-chain inulin (CLR), long-chain inulin (TEX), native inulin (IQ) and Long-chain inulin (TEX) and short-chain inulin (CLR) combined in different proportions (2o:80, 50:50, and 80:20) were added (2-10 %) to sourcherry juice-milk mixture and their stabilization mechanisms were studied with using rheological and microstructural observations. Stevioside as a bio-sweetener and sugar-replacer was added at last step. Finally, sensory analyses were taken place on stabilized samples. According to the findings, TEX stabilized the mixture at concentration of 8%. MIX and IQ reduced phase separation at high concentration but had not complete effect on stabilization. CLR did not effect on stabilization. Rheological changes and inulin aggregates formation were not observed in CLR samples during the one month storage period. However TEX, MIX and IQ samples formed inulin aggregates and became more thixotropic, elastic and increased the viscosity of mixture. The rate of the inulin aggregates formation and viscosity increasing was in the following order TEX > MIX > IQ. Consequently the mixture which stabilized with inulin and sweetened with stevioside had the prebiotic properties which may suggest to diabetic patients and children.

Keywords: prebiotic, inulin, casein, stabilization, stevioside

Procedia PDF Downloads 277

Authors: Brennan Lodge

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Amidst a complex regulatory landscape, Retrieval Augmented Generation (RAG) emerges as a transformative tool for Governance Risk and Compliance (GRC) officers. This paper details the application of RAG in synthesizing Large Language Models (LLMs) with external knowledge bases, offering GRC professionals an advanced means to adapt to rapid changes in compliance requirements. While the development for standalone LLM’s (Large Language Models) is exciting, such models do have their downsides. LLM’s cannot easily expand or revise their memory, and they can’t straightforwardly provide insight into their predictions, and may produce “hallucinations.” Leveraging a pre-trained seq2seq transformer and a dense vector index of domain-specific data, this approach integrates real-time data retrieval into the generative process, enabling gap analysis and the dynamic generation of compliance and risk management content. We delve into the mechanics of RAG, focusing on its dual structure that pairs parametric knowledge contained within the transformer model with non-parametric data extracted from an updatable corpus. This hybrid model enhances decision-making through context-rich insights, drawing from the most current and relevant information, thereby enabling GRC officers to maintain a proactive compliance stance. Our methodology aligns with the latest advances in neural network fine-tuning, providing a granular, token-level application of retrieved information to inform and generate compliance narratives. By employing RAG, we exhibit a scalable solution that can adapt to novel regulatory challenges and cybersecurity threats, offering GRC officers a robust, predictive tool that augments their expertise. The granular application of RAG’s dual structure not only improves compliance and risk management protocols but also informs the development of compliance narratives with pinpoint accuracy. It underscores AI’s emerging role in strategic risk mitigation and proactive policy formation, positioning GRC officers to anticipate and navigate the complexities of regulatory evolution confidently.

Keywords: cybersecurity, gen AI, retrieval augmented generation, cybersecurity defense strategies

Procedia PDF Downloads 101

Authors: R. Horchani

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Optical pumping technique with laser fields combined with photo-association of ultra-cold atoms leads to control on demand the vibrational and/or the rotational population of molecules. Here, we review the basic concepts and main steps should be followed, including the excitation schemes and detection techniques we use to achieve the ro-vibrational cooling of Cs2 molecules. We also discuss the extension of this technique to other molecules. In addition, we present a theoretical model used to support the experiment. These simulations can be widely used for the preparation of various experiments since they allow the optimization of several important experimental parameters.

Keywords: cold molecule, photo-association, optical pumping, vibrational and rotational cooling

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Authors: Saeedeh Bakhtiari, Johannes Depessemier, Stijn Hertelé, Wim De Waele

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High cycle fatigue comprising up to 10⁷ load cycles has been the subject of many studies, and the behavior of many materials was recorded adequately in this regime. However, many applications involve larger numbers of load cycles during the lifetime of machine components. In this ultra-high cycle regime, other failure mechanisms play, and the concept of a fatigue endurance limit (assumed for materials such as steel) is often an oversimplification of reality. When machine component design demands a high geometrical complexity, cast iron grades become interesting candidate materials. Grey cast iron is known for its low cost, high compressive strength, and good damping properties. However, the ultra-high cycle fatigue behavior of cast iron is poorly documented. The current work focuses on the ultra-high cycle fatigue behavior of EN-GJL-250 (GG25) grey cast iron by developing an ultrasonic (20 kHz) fatigue testing system. Moreover, the testing machine is instrumented to measure the temperature and the displacement of  the specimen, and to control the temperature. The high resonance frequency allowed to assess the  behavior of the cast iron of interest within a matter of days for ultra-high numbers of cycles, and repeat the tests to quantify the natural scatter in fatigue resistance.

Keywords: GG25, cast iron, ultra-high cycle fatigue, ultrasonic test

Procedia PDF Downloads 182

Authors: Sanja O. Podunavac-Kuzmanović, Lidija R. Jevrić, Strahinja Z. Kovačević

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In last decade, metal-organic complexes have captured intensive attention because of their wide range of biological activities such as antibacterial, antifungal, anticancerous, antimicrobial and antiHIV. Therefore, it is of great importance for the development of coordination chemistry to explore the assembly of functional organic ligands with metal ion and to investigate the relationship between the structure and property. In view of our studies, we reasoned that benzimidazoles complexed to metal ions could act as a potent antibacterial agents. Thus, we have bioassayed the inhibitory potency of benzimidazoles and their metal salts (Co or Ni) against Gram negative bacteria Escherichia coli. In order to validate our in vitro study, we performed in silico studies using molecular docking software’s. The investigated compounds and their metal complexes (Co, Ni) showed good antibacterial activity against Escherichia coli. In silico docking studies of the synthesized compounds suggested that complexed benzimidazoles have a greater binding affinity and enhanced antibacterial activity in comparison with noncomplexed ligands. In view of their enhanced inhibitory properties we propose that the studied complexes can be used as potential pharmaceuticals. This study is financially supported by COST action CM1306 and the project No. 114-451-347/2015-02, financially supported by the Provincial Secretariat for Science and Technological Development of Vojvodina.

Keywords: benzimidazoles, complexes, antibacterial, Escherichia coli, metal

Procedia PDF Downloads 322

Authors: Weikang Peng

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The innovation corridor is an important spatial carrier to promote regional collaborative innovation, and its development process is the spatial re-organization process of regional innovation resources. This paper takes the Nanjing-Zhenjiang G312 Industrial Innovation Corridor, which involves seven municipal districts in Jiangsu Province, as empirical evidence. Based on multi-source spatial big data in 2010, 2016, and 2022, this paper applies triangulated irregular network (TIN), head/tail breaks, regional innovation ecosystem (RIE) niche fitness evaluation model, and social network analysis to carry out empirical research on the spatial organization and functional structural evolution characteristics of innovation corridors and their correlation with the structural evolution of collaborative innovation network. The results show, first, the development of innovation patches in the corridor has fractal characteristics in time and space and tends to be multi-center and cluster layout along the Nanjing Bypass Highway and National Highway G312. Second, there are large differences in the spatial distribution pattern of niche fitness in the corridor in various dimensions, and the niche fitness of innovation patches along the highway has increased significantly. Third, the scale of the collaborative innovation network in the corridor is expanding fast. The core of the network is shifting from the main urban area to the periphery of the city along the highway, with small-world and hierarchical levels, and the core-edge network structure is highlighted. With the development of the Innovation Corridor, the main collaborative mode in the corridor is changing from collaboration within innovation patches to collaboration between innovation patches, and innovation patches with high ecological suitability tend to be the active areas of collaborative innovation. Overall, polycentric spatial layout, graded functional structure, diversified innovation clusters, and differentiated environmental support play an important role in effectively constructing collaborative innovation linkages and the stable expansion of the scale of collaborative innovation within the innovation corridor.

Keywords: innovation corridor development, spatial structure, niche fitness evaluation model, head/tail breaks, innovation network

Procedia PDF Downloads 26

Authors: Nihal Kartaltepe Behram, Göksel Ataman, Dila Okçu

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With the development of foreign direct investments, the social, cultural, political and economic interactions between countries and institutions have become visible and they have become determining factors for the strategic structuring and market goals. In this context the purpose of this study is to investigate the effects of cultural distance and institutions on foreign direct investment choices in terms of location and investment model. For international establishments, the concept of culture, as well as the concept of cultural distance, is taken specifically into consideration, especially in the selection of methods for entering the market. In the researches and empirical studies conducted, a direct relationship between cultural distance and foreign direct investments is set and institutions and effective variable factors are examined at the level of defining the investment types. When the detailed calculation strategies and empirical researches and studies are taken into consideration, the most common methods for determining the direct investment model, considering the cultural distances, are full-ownership enterprises and joint ventures. Also, when all of the factors affecting the investments are taken into consideration, it was seen that the effect of institutions such as Government Intervention, Intellectual Property Rights, Corruption and Contract Enforcements is very important. Furthermore agglomeration is more intense and effective on the investment, compared to other factors. China has been selected as the target country, due to its effectiveness in world economy and its contributions to developing countries, which has commercial relationships with. Qualitative research methods are used for this study conducted, to measure the effects of determinative variable factors in the hypotheses of study, on the direct foreign investors and to evaluate the findings. In this study in-depth interview is used as a data collection method and the data analysis is made through descriptive analysis. Foreign Direct Investments are so reactive to institutions and cultural distance is identified by all interviews and analysis. On the other hand, agglomeration is the most strong determiner factor on foreign direct investors in Chinese Market. The reason of this factors, which comprise the sectorial aggregate, are not the strongest factors as agglomeration that the most important finding. We expect that this study became a beneficial guideline for developed and developing countries and local and national institutions’ strategic plans.

Keywords: China, cultural distance, Foreign Direct Investments, institutions

Procedia PDF Downloads 422

Authors: Mir Ahmad Lashteh Neshaei, Hamed Afsoos Biria, Ata Ghabraei, Mir Abdolhamid Mehrdad

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Awareness of effective land using issues in coastal area including protection of natural ecosystems and coastal environment due to the increasing of human life along the coast is of great importance. There are numerous valuable structures and heritages which are located in defence sites and waterfront area. Marine structures such as groins, sea walls and detached breakwaters are constructed in coast to improve the coast stability against bed erosion due to changing wave and climate pattern. Marine mechanisms and interaction with the shore protection structures need to be intensively studied. Groins are one of the most prominent structures that are used in shore protection to create a safe environment for coastal area by maintaining the land against progressive coastal erosion. The main structural function of a groin is to control the long shore current and littoral sediment transport. This structure can be submerged and provide the necessary beach protection without negative environmental impact. However, for submerged structures adopted for beach protection, the shoreline response to these structures is not well understood at present. Nowadays, modelling and computer simulation are used to assess beach morphology in the vicinity of marine structures to reduce their environmental impact. The objective of this study is to predict the beach morphology in the vicinity of submerged groins and comparison with non-submerged groins with focus on a part of the coast located in Dahane sar Sefidrood, Guilan province, Iran where serious coast erosion has occurred recently. The simulations were obtained using a one-line model which can be used as a first approximation of shoreline prediction in the vicinity of groins. The results of the proposed model are compared with field measurements to determine the shape of the coast. Finally, the results of the present study show that using submerged groins can have a good efficiency to control the beach erosion without causing severe environmental impact to the coast. The important outcome from this study can be employed in optimum designing of defence sites in the coastal cities to improve their efficiency in terms of re-using the heritage lands.

Keywords: submerged structures, groin, shore protective structures, coastal cities

Procedia PDF Downloads 320