Search results for: future of CI as a cochlear delivery channel
8442 Nanoliposomes in Photothermal Therapy: Advancements and Applications
Authors: Mehrnaz Mostafavi
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Nanoliposomes, minute lipid-based vesicles at the nano-scale, show promise in the realm of photothermal therapy (PTT). This study presents an extensive overview of nanoliposomes in PTT, exploring their distinct attributes and the significant progress in this therapeutic methodology. The research delves into the fundamental traits of nanoliposomes, emphasizing their adaptability, compatibility with biological systems, and their capacity to encapsulate diverse therapeutic substances. Specifically, it examines the integration of light-absorbing materials, like gold nanoparticles or organic dyes, into nanoliposomal formulations, enabling their efficacy as proficient agents for photothermal treatment Additionally, this paper elucidates the mechanisms involved in nanoliposome-mediated PTT, highlighting their capability to convert light energy into localized heat, facilitating the precise targeting of diseased cells or tissues. This precise regulation of light absorption and heat generation by nanoliposomes presents a non-invasive and precisely focused therapeutic approach, particularly in conditions like cancer. The study explores advancements in nanoliposomal formulations aimed at optimizing PTT outcomes. These advancements include strategies for improved stability, enhanced drug loading, and the targeted delivery of therapeutic agents to specific cells or tissues. Furthermore, the paper discusses multifunctional nanoliposomal systems, integrating imaging components or targeting elements for real-time monitoring and improved accuracy in PTT. Moreover, the review highlights recent preclinical and clinical trials showcasing the effectiveness and safety of nanoliposome-based PTT across various disease models. It also addresses challenges in clinical implementation, such as scalability, regulatory considerations, and long-term safety assessments. In conclusion, this paper underscores the substantial potential of nanoliposomes in advancing PTT as a promising therapeutic approach. Their distinctive characteristics, combined with their precise ability to convert light into heat, offer a tailored and efficient method for treating targeted diseases. The encouraging outcomes from preclinical studies pave the way for further exploration and potential clinical applications of nanoliposome-based PTT.Keywords: nanoliposomes, photothermal therapy, light absorption, heat conversion, therapeutic agents, targeted delivery, cancer therapy
Procedia PDF Downloads 1128441 Robust Control of Cyber-Physical System under Cyber Attacks Based on Invariant Tubes
Authors: Bruno Vilić Belina, Jadranko Matuško
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The rapid development of cyber-physical systems significantly influences modern control systems introducing a whole new range of applications of control systems but also putting them under new challenges to ensure their resiliency to possible cyber attacks, either in the form of data integrity attacks or deception attacks. This paper presents a model predictive approach to the control of cyber-physical systems robust to cyber attacks. We assume that a cyber attack can be modelled as an additive disturbance that acts in the measuring channel. For such a system, we designed a tube-based predictive controller based. The performance of the designed controller has been verified in Matlab/Simulink environment.Keywords: control systems, cyber attacks, resiliency, robustness, tube based model predictive control
Procedia PDF Downloads 688440 The Image of Egypt in CNN, BBC and Al Jazeera News Channels in Terms of Democracy, Economic Status and Stability
Authors: Sarah El Mokadem
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Egypt has been the focus of international media since 2011 revolution and its repercussions. By the end of 2017, President Abdel Fattah El Sisi will have finished his first term of presidency. With an upcoming presidential election, all eyes are returning back to Egypt as there are speculations about whether the current regime will uphold or change points in the constitution determining the years of presidency term and the allowed number or reelections. In this paper, the researcher examines the reports related to Egypt in three international news channels with different ideologies. The research aims to identify the frames used to portray major issues in Egypt like the economic struggle, democracy levels and stability and safety of the country. All available reports from these three channels in 2017 on YouTube were analyzed which is the year before the presidential elections.Keywords: content analysis, Egypt, image building, news channel ideology
Procedia PDF Downloads 2178439 Bibliometric Analysis of the Research Progress on Graphene Inks from 2008 to 2018
Authors: Jean C. A. Sousa, Julio Cesar Maciel Santos, Andressa J. Rubio, Edneia A. S. Paccola, Natália U. Yamaguchi
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A bibliometric analysis in the Web of Science database was used to identify overall scientific results of graphene inks to date (2008 to 2018). The objective of this study was to evaluate the evolutionary tendency of graphene inks research and to identify its aspects, aiming to provide data that can guide future work. The contributions of different researches, languages, thematic categories, periodicals, place of publication, institutes, funding agencies, articles cited and applications were analyzed. The results revealed a growing number of annual publications, of 258 papers found, 107 were included because they met the inclusion criteria. Three main applications were identified: synthesis and characterization, electronics and surfaces. The most relevant research on graphene inks has been summarized in this article, and graphene inks for electronic devices presented the most incident theme according to the research trends during the studied period. It is estimated that this theme will remain in evidence and will contribute to the direction of future research in this area.Keywords: bibliometric, coating, nanomaterials, scientometrics
Procedia PDF Downloads 1698438 Comparison of Due Date Assignment Rules in a Dynamic Job Shop
Authors: Mumtaz Ipek, Burak Erkayman
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Due date is assigned as an input for scheduling problems. At the same time, due date is selected as a decision variable for real time scheduling applications. Correct determination of due dates increases shop floor performance and number of jobs completed on time. This subject has been mentioned widely in the literature. Moreover rules for due date determination have been developed from analytical analysis. When a job arrives to the shop floor, a due date is assigned for delivery. Various due date determination methods are used in the literature. In this study six different due date methods are implemented for a hypothetical dynamic job shop and the performances of the due date methods are compared.Keywords: scheduling, dynamic job shop, due date assignment, management engineering
Procedia PDF Downloads 5538437 Understanding Work-Related Values of Generation Z: The Lessons for Employers
Authors: Nebojša Janićijević
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The paper presents the results of a study on work-related values of Generation Z, comprised of young people born between the late 1990s and 2010. Following Millennials, Generation Z is the first generation of digital natives. This is the reason, along with some other circumstances that accompanied them during their growing up, why Generation Z has somewhat different work-related values than previous generations. Since they are just beginning to enter the labor market and will be the majority of the workforce in the next decade or two, it is very important and useful for their employers to understand what Generation Z values when it comes to work. The study was conducted by surveying the students of the Faculty of Economics, University of Belgrade, Serbia, during 2022 and 2023. The research results show that Generation Z values safety, achievement, and status the most in the workplace. From the individual perspective, future employees consider it most important that their job provides good working conditions, recognition for the work performed, and the possibility of achievement. It is noticeable that Generation Z students, to a significant extent, expect to be protected and safe at work in the future, both in terms of the job itself and in terms of social relations. According to the research findings, Generation Z is relatively homogeneous, and no significant differences in work-related values were found among them, except by gender.Keywords: generation Z, work related values, students, Serbia
Procedia PDF Downloads 258436 Innovative Preparation Techniques: Boosting Oral Bioavailability of Phenylbutyric Acid Through Choline Salt-Based API-Ionic Liquids and Therapeutic Deep Eutectic Systems
Authors: Lin Po-Hsi, Sheu Ming-Thau
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Urea cycle disorders (UCD) are rare genetic metabolic disorders that compromise the body's urea cycle. Sodium phenylbutyrate (SPB) is a medication commonly administered in tablet or powder form to lower ammonia levels. Nonetheless, its high sodium content poses risks to sodium-sensitive UCD patients. This necessitates the creation of an alternative drug formulation to mitigate sodium load and optimize drug delivery for UCD patients. This study focused on crafting a novel oral drug formulation for UCD, leveraging choline bicarbonate and phenylbutyric acid. The active pharmaceutical ingredient-ionic liquids (API-ILs) and therapeutic deep eutectic systems (THEDES) were formed by combining these with choline chloride. These systems display characteristics like maintaining a liquid state at room temperature and exhibiting enhanced solubility. This in turn amplifies drug dissolution rate, permeability, and ultimately oral bioavailability. Incorporating choline-based phenylbutyric acid as a substitute for traditional SPB can effectively curtail the sodium load in UCD patients. Our in vitro dissolution experiments revealed that the ILs and DESs, synthesized using choline bicarbonate and choline chloride with phenylbutyric acid, surpassed commercial tablets in dissolution speed. Pharmacokinetic evaluations in SD rats indicated a notable uptick in the oral bioavailability of phenylbutyric acid, underscoring the efficacy of choline salt ILs in augmenting its bioavailability. Additional in vitro intestinal permeability tests on SD rats authenticated that the ILs, formulated with choline bicarbonate and phenylbutyric acid, demonstrate superior permeability compared to their sodium and acid counterparts. To conclude, choline salt ILs developed from choline bicarbonate and phenylbutyric acid present a promising avenue for UCD treatment, with the added benefit of reduced sodium load. They also hold merit in formulation engineering. The sustained-release capabilities of DESs position them favorably for drug delivery, while the low toxicity and cost-effectiveness of choline chloride signal potential in formulation engineering. Overall, this drug formulation heralds a prospective therapeutic avenue for UCD patients.Keywords: phenylbutyric acid, sodium phenylbutyrate, choline salt, ionic liquids, deep eutectic systems, oral bioavailability
Procedia PDF Downloads 1168435 Forecasting Cancers Cases in Algeria Using Double Exponential Smoothing Method
Authors: Messis A., Adjebli A., Ayeche R., Talbi M., Tighilet K., Louardiane M.
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Cancers are the second cause of death worldwide. Prevalence and incidence of cancers is getting increased by aging and population growth. This study aims to predict and modeling the evolution of breast, Colorectal, Lung, Bladder and Prostate cancers over the period of 2014-2019. In this study, data were analyzed using time series analysis with double exponential smoothing method to forecast the future pattern. To describe and fit the appropriate models, Minitab statistical software version 17 was used. Between 2014 and 2019, the overall trend in the raw number of new cancer cases registered has been increasing over time; the change in observations over time has been increasing. Our forecast model is validated since we have good prediction for the period 2020 and data not available for 2021 and 2022. Time series analysis showed that the double exponential smoothing is an efficient tool to model the future data on the raw number of new cancer cases.Keywords: cancer, time series, prediction, double exponential smoothing
Procedia PDF Downloads 898434 Study of the Prevalence, Associated Factors and Impact of Maternal Perinatal Depression in Women Alexandria 2022
Authors: Nermeen Saad Elbeltagy, Hoda Ghareeb, Hesham Adel Elsheshtawy, Nadim Hamed, Amany Ibrahim Mostafa, Sara Hazem Hassan
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Introduction: Depression is one of the most common mental health problems occurring in women during their child bearing years. Perinatal depression refers to major and minor depressive episodes that occur either during pregnancy or aer delivery. Although perinatal depression is common in developing countries, it is under-recognized in low and middle income countries making a substantial contribution to maternal and infant morbidity and mortality. About 12.5 - 42% of pregnant women and, 12 - 50% of post natal mothers in low and middle income countries such as Ethiopia had depression AIM OF THE WORK: To study prevalence, associated factors and impact of maternal perinatal depression in Alexandria. Patients and method: This study was conducted on 300 mothers at the postnatal ward in ElShatby Maternity Hospital from April 2022 unl October 2022. Females with past history of depression before pregnancy or females who receive medications inducing depression were excluded. The participants were asked to complete the questionnaire that includes the Edinburgh Postnatal Depression Scale (EPDS) as a screening test to obtain information concerning the current frame of mind at antepartum, partum and postpartum periods Results: The prevalence of perinatal depression was 22.3%. It was found that there is a significant negave moderate correlation between socioeconomic status and perinatal depression(r=-0.42). The present study revealed that about two thirds (60.7%) of postpartum women had low socioeconomic level. Also, less than one fourth (20%) of parents had high education and only one fourth (25.3%) of postpartum women were working. There was a statically significance difference between the number of previous abortions and perinatal depression (p=0.04). There was a significant moderate correlation between the amount of blood lost during delivery and an increased risk of developing postpartum depression. The prevalence of perinatal depression was high in cases of female neonates more than male ones. Conclusion: the prevalence of perinatal depression among the studied women was 22.3% of studied group. The significant factors identified in this study can be targeted to reduce the occurrence of perinatal depression among pregnant women in Alexandria through appropriate health interventions which includes perinatal depression screening, counseling, and the provision of support for pregnant women during antenatal care as well as lifestyle modification.Keywords: mental health, depression in pregnancy, mental disorders, psychology in pregnancy
Procedia PDF Downloads 748433 New Types of Fitness Equipment for Seniors-Based on Beginning Movement Load Training
Authors: Chia-Chi Chen, Tai-Sheng Huang
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Ageing society has been spread around the world. The global population is not only ageing but also declining. The structure of population has changed, which has a significant impact on both the economies and industries. Thus, how to be a healthy senior citizen to relieve the burden to the family and society will be a popular issue. Although fitness equipment manufacturing industry has been mature, the ageing population is still increasing. Therefore, this study aims to design an innovative style of fitness equipment for senior citizens, based on BMLT presented by Dr. Koyama Hirofumi. The analysis of current fitness equipment on the market and the future trend will be applied in the study. With the coming of information age, senior citizens in the future are the users of information product for sure, and the new style of fitness equipment will be combined with information technology as well. Through this study, it is believed to design an innovative style of fitness equipment for seniors and help them live heartier and happier lives.Keywords: aging society, BMLT (Beginning Movement Load Training), seniors, new style of fitness equipment
Procedia PDF Downloads 2168432 Predicting Costs in Construction Projects with Machine Learning: A Detailed Study Based on Activity-Level Data
Authors: Soheila Sadeghi
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Construction projects are complex and often subject to significant cost overruns due to the multifaceted nature of the activities involved. Accurate cost estimation is crucial for effective budget planning and resource allocation. Traditional methods for predicting overruns often rely on expert judgment or analysis of historical data, which can be time-consuming, subjective, and may fail to consider important factors. However, with the increasing availability of data from construction projects, machine learning techniques can be leveraged to improve the accuracy of overrun predictions. This study applied machine learning algorithms to enhance the prediction of cost overruns in a case study of a construction project. The methodology involved the development and evaluation of two machine learning models: Random Forest and Neural Networks. Random Forest can handle high-dimensional data, capture complex relationships, and provide feature importance estimates. Neural Networks, particularly Deep Neural Networks (DNNs), are capable of automatically learning and modeling complex, non-linear relationships between input features and the target variable. These models can adapt to new data, reduce human bias, and uncover hidden patterns in the dataset. The findings of this study demonstrate that both Random Forest and Neural Networks can significantly improve the accuracy of cost overrun predictions compared to traditional methods. The Random Forest model also identified key cost drivers and risk factors, such as changes in the scope of work and delays in material delivery, which can inform better project risk management. However, the study acknowledges several limitations. First, the findings are based on a single construction project, which may limit the generalizability of the results to other projects or contexts. Second, the dataset, although comprehensive, may not capture all relevant factors influencing cost overruns, such as external economic conditions or political factors. Third, the study focuses primarily on cost overruns, while schedule overruns are not explicitly addressed. Future research should explore the application of machine learning techniques to a broader range of projects, incorporate additional data sources, and investigate the prediction of both cost and schedule overruns simultaneously.Keywords: cost prediction, machine learning, project management, random forest, neural networks
Procedia PDF Downloads 568431 Hardware-In-The-Loop Relative Motion Control: Theory, Simulation and Experimentation
Authors: O. B. Iskender, K. V. Ling, V. Dubanchet, L. Simonini
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This paper presents a Guidance and Control (G&C) strategy to address spacecraft maneuvering problem for future Rendezvous and Docking (RVD) missions. The proposed strategy allows safe and propellant efficient trajectories for space servicing missions including tasks such as approaching, inspecting and capturing. This work provides the validation test results of the G&C laws using a Hardware-In-the-Loop (HIL) setup with two robotic mockups representing the chaser and the target spacecraft. Through this paper, the challenges of the relative motion control in space are first summarized, and in particular, the constraints imposed by the mission, spacecraft and, onboard processing capabilities. Second, the proposed algorithm is introduced by presenting the formulation of constrained Model Predictive Control (MPC) to optimize the fuel consumption and explicitly handle the physical and geometric constraints in the system, e.g. thruster or Line-Of-Sight (LOS) constraints. Additionally, the coupling between translational motion and rotational motion is addressed via dual quaternion based kinematic description and accordingly explained. The resulting convex optimization problem allows real-time implementation capability based on a detailed discussion on the computational time requirements and the obtained results with respect to the onboard computer and future trends of space processors capabilities. Finally, the performance of the algorithm is presented in the scope of a potential future mission and of the available equipment. The results also cover a comparison between the proposed algorithms with Linear–quadratic regulator (LQR) based control law to highlight the clear advantages of the MPC formulation.Keywords: autonomous vehicles, embedded optimization, real-time experiment, rendezvous and docking, space robotics
Procedia PDF Downloads 1248430 Hotel Customers’ Attitudes towards Service Marketing Mix, Service Behavior, and Perceived Brand Value
Authors: Trikhun Rotkasem
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This research paper aimed to investigate hotel customers’ attitudes towards the service marketing, service behavior and perceived brand value. The focus of the study was on the Suan Sunandha Rajabhat University’s hotel. It is a small hotel which aims to provide service to mainly university’s guests. A simple random sampling technique was conducted to obtain a sample group that included 200 respondents. The research question was established as follows: What are customers’ attitudes towards the service marketing mix of hotel customers? The findings revealed the respondents’ attitudes towards the service marketing mix indicated high level in the area of product, place or distribution channel, people, and physical evidence, whereas, the respondents’ attitude towards the service marketing mix indicated medium level in the area of price, promotion, and process.Keywords: marketing mix, perceived brand value, service behavior, hotel customers
Procedia PDF Downloads 4428429 A Machine Learning Approach for Efficient Resource Management in Construction Projects
Authors: Soheila Sadeghi
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Construction projects are complex and often subject to significant cost overruns due to the multifaceted nature of the activities involved. Accurate cost estimation is crucial for effective budget planning and resource allocation. Traditional methods for predicting overruns often rely on expert judgment or analysis of historical data, which can be time-consuming, subjective, and may fail to consider important factors. However, with the increasing availability of data from construction projects, machine learning techniques can be leveraged to improve the accuracy of overrun predictions. This study applied machine learning algorithms to enhance the prediction of cost overruns in a case study of a construction project. The methodology involved the development and evaluation of two machine learning models: Random Forest and Neural Networks. Random Forest can handle high-dimensional data, capture complex relationships, and provide feature importance estimates. Neural Networks, particularly Deep Neural Networks (DNNs), are capable of automatically learning and modeling complex, non-linear relationships between input features and the target variable. These models can adapt to new data, reduce human bias, and uncover hidden patterns in the dataset. The findings of this study demonstrate that both Random Forest and Neural Networks can significantly improve the accuracy of cost overrun predictions compared to traditional methods. The Random Forest model also identified key cost drivers and risk factors, such as changes in the scope of work and delays in material delivery, which can inform better project risk management. However, the study acknowledges several limitations. First, the findings are based on a single construction project, which may limit the generalizability of the results to other projects or contexts. Second, the dataset, although comprehensive, may not capture all relevant factors influencing cost overruns, such as external economic conditions or political factors. Third, the study focuses primarily on cost overruns, while schedule overruns are not explicitly addressed. Future research should explore the application of machine learning techniques to a broader range of projects, incorporate additional data sources, and investigate the prediction of both cost and schedule overruns simultaneously.Keywords: resource allocation, machine learning, optimization, data-driven decision-making, project management
Procedia PDF Downloads 408428 Morphotectonic Analysis of Burkh Anticline, North of Bastak, Zagros
Authors: A. Afroogh, R. Ramazani omali, N. Hafezi Moghaddas, A. Nohegar
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The Burkh anticline with a length of 50 km and a width of 9 km is located 40 km to the north of Bastak in internal Fars zone in folded-trusted belt of Zagros. In order to assess the active tectonics in the area of study, morphometrical indexes such as V indexes (V), ratio of valley floor to valley width (Vf), the stream length-gradient ratio (Sl), channel sinuosity indexes (S), mountain front faceting indexes (F%) and mountain front sinuosity(Smf) have been studied. These investigations show that the activity is not equal in various sections of the length of Burkh anticline. The central part of this anticline is the most active one.Keywords: anticline, internal fars zone, tectonic, morohometrical indexes, folded-trusted belt
Procedia PDF Downloads 2518427 A Two Phase VNS Algorithm for the Combined Production Routing Problem
Authors: Nejah Ben Mabrouk, Bassem Jarboui, Habib Chabchoub
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Production and distribution planning is the most important part in supply chain management. In this paper, a NP-hard production-distribution problem for one product over a multi-period horizon is investigated. The aim is to minimize the sum of costs of three items: production setups, inventories and distribution, while determining, for each period, the amount produced, the inventory levels and the delivery trips. To solve this difficult problem, we propose a bi-phase approach based on a Variable Neighbourhood Search (VNS). This heuristic is tested on 90 randomly generated instances from the literature, with 20 periods and 50, 100, 200 customers. Computational results show that our approach outperforms existing solution procedures available in the literatureKeywords: logistic, production, distribution, variable neighbourhood search
Procedia PDF Downloads 3378426 Developing API Economy: Associating Value to APIs and Microservices in an Enterprise
Authors: Mujahid Sultan
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The IT industry has seen many transformations in the Software Development Life Cycle (SDLC) methodologies and development approaches. SDLCs range from waterfall to agile, and the development approaches from monolith to microservices. Management, orchestration, and monetization of microservices have created an API economy in the modern enterprise. There are two approaches to API design, code first and design first. Design first is gaining popularity in the industry as this allows capturing the API needs from the stakeholders rather than the development teams guesstimating the needs and associating a monetary value with the APIs and microservices. In this publication, we describe an approach to organizing and creating stakeholder needs and requirements for designing microservices and APIs.Keywords: requirements engineering, enterprise architecture, APIs, microservices, DevOps, continuous delivery, continuous integration, stakeholder viewpoints
Procedia PDF Downloads 1918425 The Relationship Between Exposure to Traumatic Events in the Delivery Room, Post-Traumatic Stress Symptoms, Personal Resilience, Organizational Commitment, and Professional Quality of Life Among Midwives
Authors: Kinneret Segal
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Background: The work of a midwife is emotionally challenging, both positively and negatively. Midwives share moments of joy when a baby is welcomed into the world and also attend difficult events of loss and trauma. The relationship that develops with the maternity is the essence of the midwife's care, and it is a fundamental source of motivation and professional satisfaction. This close relationship with the maternity may be used as a double-edged sword in cases of exposure to traumatic events at birth. Birth problems, exposure to emergencies and traumatic events, and loss can affect the professional quality of life and the Compassion satisfaction of the midwife. It seems that the issue of traumatic experiences in the work of midwives has not been sufficiently explored. Aim: The present study examined the associations between exposure to traumatic events, personal resilience and post-traumatic symptoms, professional quality of life, and organizational commitment among midwifery nurses in Israeli hospitals. Methods: 131 midwives from three hospitals in the country's center in Israel participated in this study. The data were collected during 2021 using a self-report questionnaire that examined sociodemographic characteristics, the degree of exposure to traumatic events in the delivery room, personal resilience, post-traumatic symptoms, professional quality of life, and organizational commitment. Results: The three most difficult traumatic events for the midwives were death or fear of death of a newborn, death or fear of the death of a mother, and a quiet birth. The higher the frequency of exposure to traumatic events, the more numerous and intense the onset of post-trauma symptoms. The more numerous and powerful the post-trauma symptoms, the higher the level of professional burnout and/or compassion fatigue, and the lower the level of compassion satisfaction. High levels of compassion satisfaction and/or low professional burnout were expressed in a heightened sense of organizational commitment. Personal resilience, country of birth, traumatic symptoms, and organizational commitment predicted satisfaction from compassion. Conclusions: Midwives are exposed to traumatic events associated with dissatisfaction and impairment of the professional quality of life that accompanies burnout and compassion fatigue. Exposure to traumatic events leads to the appearance of traumatic symptoms, a decrease in organizational commitment, and psychological and mental well-being. The issue needs to be addressed by implementing training programs, organizational support, and policies to improving well-being and quality of care among midwives.Keywords: organizational commitment, traumatic experiences, personal resilience, quality of life
Procedia PDF Downloads 1128424 Enhanced Performance of an All-Vanadium Redox Flow Battery Employing Graphene Modified Carbon Paper Electrodes
Authors: Barun Chakrabarti, Dan Nir, Vladimir Yufit, P. V. Aravind, Nigel Brandon
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Fuel cell grade gas-diffusion layer carbon paper (CP) electrodes are subjected to electrophoresis in N,N’-dimethylformamide (DMF) consisting of reduced graphene oxide (rGO). The rGO modified electrodes are compared with CP in a single asymmetric all-vanadium redox battery system (employing a double serpentine flow channel for each half-cell). Peak power densities improved by 4% when the rGO deposits were facing the ion-exchange membrane (cell performance was poorer when the rGO was facing the flow field). Cycling of the cells showed least degradation of the CP electrodes that were coated with rGO in comparison to pristine samples.Keywords: all-vanadium redox flow batteries, carbon paper electrodes, electrophoretic deposition, reduced graphene oxide
Procedia PDF Downloads 2288423 PM10 Prediction and Forecasting Using CART: A Case Study for Pleven, Bulgaria
Authors: Snezhana G. Gocheva-Ilieva, Maya P. Stoimenova
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Ambient air pollution with fine particulate matter (PM10) is a systematic permanent problem in many countries around the world. The accumulation of a large number of measurements of both the PM10 concentrations and the accompanying atmospheric factors allow for their statistical modeling to detect dependencies and forecast future pollution. This study applies the classification and regression trees (CART) method for building and analyzing PM10 models. In the empirical study, average daily air data for the city of Pleven, Bulgaria for a period of 5 years are used. Predictors in the models are seven meteorological variables, time variables, as well as lagged PM10 variables and some lagged meteorological variables, delayed by 1 or 2 days with respect to the initial time series, respectively. The degree of influence of the predictors in the models is determined. The selected best CART models are used to forecast future PM10 concentrations for two days ahead after the last date in the modeling procedure and show very accurate results.Keywords: cross-validation, decision tree, lagged variables, short-term forecasting
Procedia PDF Downloads 1948422 Clean Sky 2 – Project PALACE: Aeration’s Experimental Sound Velocity Investigations for High-Speed Gerotor Simulations
Authors: Benoît Mary, Thibaut Gras, Gaëtan Fagot, Yvon Goth, Ilyes Mnassri-Cetim
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A Gerotor pump is composed of an external and internal gear with conjugate cycloidal profiles. From suction to delivery ports, the fluid is transported inside cavities formed by teeth and driven by the shaft. From a geometric and conceptional side it is worth to note that the internal gear has one tooth less than the external one. Simcenter Amesim v.16 includes a new submodel for modelling the hydraulic Gerotor pumps behavior (THCDGP0). This submodel considers leakages between teeth tips using Poiseuille and Couette flows contributions. From the 3D CAD model of the studied pump, the “CAD import” tool takes out the main geometrical characteristics and the submodel THCDGP0 computes the evolution of each cavity volume and their relative position according to the suction or delivery areas. This module, based on international publications, presents robust results up to 6 000 rpm for pressure greater than atmospheric level. For higher rotational speeds or lower pressures, oil aeration and cavitation effects are significant and highly drop the pump’s performance. The liquid used in hydraulic systems always contains some gas, which is dissolved in the liquid at high pressure and tends to be released in a free form (i.e. undissolved as bubbles) when pressure drops. In addition to gas release and dissolution, the liquid itself may vaporize due to cavitation. To model the relative density of the equivalent fluid, modified Henry’s law is applied in Simcenter Amesim v.16 to predict the fraction of undissolved gas or vapor. Three parietal pressure sensors have been set up upstream from the pump to estimate the sound speed in the oil. Analytical models have been compared with the experimental sound speed to estimate the occluded gas content. Simcenter Amesim v.16 model was supplied by these previous analyses marks which have successfully improved the simulations results up to 14 000 rpm. This work provides a sound foundation for designing the next Gerotor pump generation reaching high rotation range more than 25 000 rpm. This improved module results will be compared to tests on this new pump demonstrator.Keywords: gerotor pump, high speed, numerical simulations, aeronautic, aeration, cavitation
Procedia PDF Downloads 1348421 Effect of Span 60, Labrasol, and Cholesterol on Labisia pumila Loaded Niosomes Quality
Authors: H. Binti Ya’akob, C. Siew Chin, A. Abd Aziz, I. Ware, M. Fauzi Abd Jalil, N. Rashidah Ahmed, R. Sabtu
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Labisia pumila (LP) plant extract has the potential to be applied in cosmeceutical products due to its anti-photoaging properties. The main purpose of this study was to improve transdermal delivery of LP by encapsulating LP in niosomes. Niosomes loaded LPs were prepared by coacervation phase separation method using non-ionic surfactant (Span 60), labrasol, and cholesterol. The optimum formula obtained were Span 60, labrasol and cholesterol at the mole ratio of 6:1:4. At the optimum formulation, the niosome obtained significantly improved the quality of transdermal penetration of LP compared to free LP.Keywords: Labisia pumila, niosomes, transdermal, quality
Procedia PDF Downloads 3158420 Exploring Problem-Based Learning and University-Industry Collaborations for Fostering Students’ Entrepreneurial Skills: A Qualitative Study in a German Urban Setting
Authors: Eylem Tas
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This empirical study aims to explore the development of students' entrepreneurial skills through problem-based learning within the context of university-industry collaborations (UICs) in curriculum co-design and co-delivery (CDD). The research question guiding this study is: "How do problem-based learning and university-industry collaborations influence the development of students' entrepreneurial skills in the context of curriculum co-design and co-delivery?” To address this question, the study was conducted in a big city in Germany and involved interviews with stakeholders from various industries, including the private sector, government agencies (govt), and non-governmental organizations (NGOs). These stakeholders had established collaborative partnerships with the targeted university for projects encompassing entrepreneurial development aspects in CDD. The study sought to gain insights into the intricacies and subtleties of UIC dynamics and their impact on fostering entrepreneurial skills. Qualitative content analysis, based on Mayring's guidelines, was employed to analyze the interview transcriptions. Through an iterative process of manual coding, 442 codes were generated, resulting in two main sections: "the role of problem-based learning and UIC in fostering entrepreneurship" and "challenges and requirements of problem-based learning within UIC for systematical entrepreneurship development.” The chosen experimental approach of semi-structured interviews was justified by its capacity to provide in-depth perspectives and rich data from stakeholders with firsthand experience in UICs in CDD. By enlisting participants with diverse backgrounds, industries, and company sizes, the study ensured a comprehensive and heterogeneous sample, enhancing the credibility of the findings. The first section of the analysis delved into problem-based learning and entrepreneurial self-confidence to gain a deeper understanding of UIC dynamics from an industry standpoint. It explored factors influencing problem-based learning, alignment of students' learning styles and preferences with the experiential learning approach, specific activities and strategies, and the role of mentorship from industry professionals in fostering entrepreneurial self-confidence. The second section focused on various interactions within UICs, including communication, knowledge exchange, and collaboration. It identified key elements, patterns, and dynamics of interaction, highlighting challenges and limitations. Additionally, the section emphasized success stories and notable outcomes related to UICs' positive impact on students' entrepreneurial journeys. Overall, this research contributes valuable insights into the dynamics of UICs and their role in fostering students' entrepreneurial skills. UICs face challenges in communication and establishing a common language. Transparency, adaptability, and regular communication are vital for successful collaboration. Realistic expectation management and clearly defined frameworks are crucial. Responsible data handling requires data assurance and confidentiality agreements, emphasizing the importance of trust-based relationships when dealing with data sharing and handling issues. The identified key factors and challenges provide a foundation for universities and industrial partners to develop more effective UIC strategies for enhancing students' entrepreneurial capabilities and preparing them for success in today's digital age labor market. The study underscores the significance of collaborative learning and transparent communication in UICs for entrepreneurial development in CDD.Keywords: collaborative learning, curriculum co-design and co-delivery, entrepreneurial skills, problem-based learning, university-industry collaborations
Procedia PDF Downloads 608419 Adaptive Data Approximations Codec (ADAC) for AI/ML-based Cyber-Physical Systems
Authors: Yong-Kyu Jung
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The fast growth in information technology has led to de-mands to access/process data. CPSs heavily depend on the time of hardware/software operations and communication over the network (i.e., real-time/parallel operations in CPSs (e.g., autonomous vehicles). Since data processing is an im-portant means to overcome the issue confronting data management, reducing the gap between the technological-growth and the data-complexity and channel-bandwidth. An adaptive perpetual data approximation method is intro-duced to manage the actual entropy of the digital spectrum. An ADAC implemented as an accelerator and/or apps for servers/smart-connected devices adaptively rescales digital contents (avg.62.8%), data processing/access time/energy, encryption/decryption overheads in AI/ML applications (facial ID/recognition).Keywords: adaptive codec, AI, ML, HPC, cyber-physical, cybersecurity
Procedia PDF Downloads 798418 A Pilot Randomized Controlled Trial of a Physical Activity Intervention in a Low Socioeconomic Population: Focus on Mental Contrasting with Implementation Intentions
Authors: Shaun G. Abbott, Rebecca C. Reynolds, John B. F. de Wit
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Low physical activity (PA) levels are a major public health concern in Australia. There is some evidence that PA interventions can increase PA levels via various methods, including online delivery. Low Socioeconomic Status (SES) people participate in less PA than the rest of the population, partly due to poor self-regulation behaviors associated with socioeconomic characteristics. Interventions that involve a particular method of self-regulation, Mental Contrasting with Implementation Intentions (MCII), has regularly achieved healthy behavior change, but few studies focus on PA behavior outcomes and no studies examining the effect of MCII on the PA behaviors of low SES people has been done. In this study, a pilot randomized controlled trial (RCT) will deliver MCII for PA behavior change to individuals of relative disadvantage for the first time. The current pilot study will predict sample size for a future full RCT and test the hypothesis that sedentary participants from areas of relative socioeconomic disadvantage of Sydney, who learn the MCII technique will be more physically active, have improved anthropometry and psychological indicators at the completion of a 12-week intervention compared to baseline and control. Eligible participants of relative socioeconomic disadvantage will be randomly assigned to either the ‘PA Information Plus MCII Intervention Group’ or a ‘PA Information-Only Control Group’. Both groups will attend a baseline and 12-week face-to-face consultation; where PA, anthropometric and psychological data will be gathered. The intervention group will be guided through an MCII session at the baseline appointment to establish a PA goal to aim to achieve over 12 weeks. Other than these baseline and 12-week consultations, all participant interaction will occur online. All participants will receive a ‘Fitbit’ accelerometer to record objectively. PA as a daily step count, along with a PA diary for the duration of the study. PA data will be recorded on a personalized online spreadsheet. Both groups will receive a standard PA information email at weeks 2, 4, and 8. The intervention group will also receive scripted follow-up online appointments to discuss goal progress. The current pilot study is in recruitment stage with findings to be presented at the conference in December if selected.Keywords: implementation intentions, mental contrasting, motivation, pedometer, physical activity, socioeconomic
Procedia PDF Downloads 3068417 Aspects of Semiotics in Contemporary Design: A Case Study on Dice Brand
Authors: Laila Zahran Mohammed Alsibani
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The aim of the research is to understand the aspects of semiotics in contemporary designs by redesigning an Omani donut brand with localized cultural identity. To do so, visual identity samples of Dice brand of donuts in Oman has been selected to be a case study. This study conducted based on semiotic theory by using mixed method research tools which are: documentation analysis, interview and survey. The literature review concentrates on key areas of semiotics in visual elements used in the brand designs. Also, it spotlights on the categories of semiotics in visual design. In addition, this research explores the visual cues in brand identity. The objectives of the research are to investigate the aspects of semiotics in providing meaning to visual cues and to identify visual cues for each visual element. It is hoped that this study will have the contribution to a better understanding of the different ways of using semiotics in contemporary designs. Moreover, this research can be a review of further studies in understanding and explaining current and future design trends. Future research can also focus on how brand-related signs are perceived by consumers.Keywords: brands, semiotics, visual arts, visual communication
Procedia PDF Downloads 1608416 The Application of Maintenance Strategy in Energy Power Plant: A Case Study
Authors: Steven Vusmuzi Mashego, Opeyeolu Timothy Laseinde
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This paper presents a case study on applying maintenance strategies observed in a turbo-generator at a coal power plant. Turbo generators are one of the primary and critical components in energy generation. It is essential to apply correct maintenance strategies and apply operational procedures accordingly. The maintenance strategies are implemented to ensure the high reliability of the equipment. The study was carried out at a coal power station which will transit to a cleaner energy source in the nearest future. The study is relevant as lessons learned in this system will support plans and operational models implemented when cleaner energy sources replace coal-powered turbines. This paper first outlines different maintenance strategies executed on the turbo-generator modules. Secondly, the impacts of human factors on a coal power station are discussed, and the findings prompted recommendations for future actions.Keywords: maintenance strategies, turbo generator, operational error, human factor, electricity generation
Procedia PDF Downloads 1128415 Business-to-Business Deals Based on a Co-Utile Collaboration Mechanism: Designing Trust Company of the Future
Authors: Riccardo Bonazzi, Michaël Poli, Abeba Nigussie Turi
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This paper presents an applied research of a new module for the financial administration and management industry, Personalizable and Automated Checklists Integrator, Overseeing Legal Investigations (PACIOLI). It aims at designing the business model of the trust company of the future. By identifying the key stakeholders, we draw a general business process design of the industry. The business model focuses on disintermediating the traditional form of business through the new technological solutions of a software company based in Switzerland and hence creating a new interactive platform. The key stakeholders of this interactive platform are identified as IT experts, legal experts, and the New Edge Trust Company (NATC). The mechanism we design and propose has a great importance in improving the efficiency of the financial business administration and management industry, and it also helps to foster the provision of high value added services in the sector.Keywords: new edge trust company, business model design, automated checklists, financial technology
Procedia PDF Downloads 3728414 Parametric Analysis of Solid Oxide Fuel Cell Using Lattice Boltzmann Method
Authors: Abir Yahya, Hacen Dhahri, Khalifa Slimi
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The present paper deals with a numerical simulation of temperature field inside a solid oxide fuel cell (SOFC) components. The temperature distribution is investigated using a co-flow planar SOFC comprising the air and fuel channel and two-ceramic electrodes, anode and cathode, separated by a dense ceramic electrolyte. The Lattice Boltzmann method (LBM) is used for the numerical simulation of the physical problem. The effects of inlet temperature, anode thermal conductivity and current density on temperature distribution are discussed. It was found that temperature distribution is very sensitive to the inlet temperature and the current density.Keywords: heat sources, Lattice Boltzmann method, solid oxide fuel cell, temperature
Procedia PDF Downloads 3098413 Proposal Evaluation of Critical Success Factors (CSF) in Lean Manufacturing Projects
Authors: Guilherme Gorgulho, Carlos Roberto Camello Lima
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Critical success factors (CSF) are used to design the practice of project management that can lead directly or indirectly to the success of the project. This management includes many elements that have to be synchronized in order to ensure the project on-time delivery, quality and the lowest possible cost. The objective of this work is to develop a proposal for evaluation of the FCS in lean manufacturing projects, and apply the evaluation in a pilot project. The results show that the use of continuous improvement programs in organizations brings benefits as the process cost reduction and improve productivity.Keywords: continuous improvement, critical success factors (csf), lean thinking, project management
Procedia PDF Downloads 364